FACEPA
Farm Accountancy Cost Estimation and
Policy Analysis of European Agriculture
EU farms’ technical efficiency, allocative
efficiency, and productivity change in
1990-2006
FACEPA Deliverable No. D 5.2 – December 2010
Zoltán Bakucs
CUB
Imre Fertő
CUB
József Fogarasi
CUB
Csaba Forgács
CUB
József Tóth
CUB
Eduard Matveev
EMU
Mati Sepp
EMU
Yann Desjeux
INRA
Laure Latruffe
INRA
Luca Cesaro
INEA
Sonia Marongiu
INEA
Agostina Zanoli
INEA
Mark Dolman
LEI
Rafat Soboh
LEI
The research leading to these results has received funding from the European
Community’s Seventh Framework Programme (FP7/2007-2013) under grant
agreement no 212292.
Executive Summary
The purpose of this deliverable is to present and analyse various efficiency indicators for European
Union (EU) countries included in the FACEPA project, Belgium, Estonia, France, Germany, Hungary,
Italy, The Netherlands and Sweden. The availability of long period datasets between 1990 and 2006,
allow us to concentrate on long time trends in technical efficiency especially in Old Member States.
This study is the first which may provide a comprehensive overview on the development in farm level
efficiency across eight European countries.
Two main approaches developed over time for analysing technical efficiency in agriculture are used in
this report. (1) The nonparametric data envelopment analysis (DEA); (2) the parametric stochastic
frontier analysis (SFA). While the vast majority of empirical studies on technical efficiency in the
agricultural sector mostly have utilized only one method to estimate their efficiencies, we apply both
methodological approaches to measure efficiency aiming even higher level of robustness. In addition,
most studies focus on a single country’s agricultural sector, thus the comparative analysis of the
technical efficiency across countries is rather scarce. We take into account the relative importance of
specific subsectors and rationale of compilation more homogeneous sample thus our study focuses on
the field crops and dairy sectors separately. Our study highlights the importance of easier availability
to the farm level data, namely Farm Accountancy Data Network (FADN) data in the EU, which
provides interesting insights for policy makers on farm level technical efficiency and develops more
targeted policy to improve efficiency in European agriculture.
This deliverable presents the estimations of each country for each year for two sectors: specialised
field crop (Type of Farming TF1) and dairy (TF41). The estimations include the following efficiency
indicators (reported in Annexes 4 to 17): Technical Efficiency, Scale Efficiency, Allocative
Efficiency, Technical Efficiency Change, Scale Efficiency Change, Allocative Efficiency Change,
Technological Change and Productivity Change. FADN data from 1990 to 2006 (for Sweden from
1995 to 2006) for Old Member States and 2004 to 2006 for the New Member States were used for the
analysis. Technical and Allocative efficiency estimates were computed using both parametric (SFA)
and non-parametric (DEA) methods, the other efficiency measures were estimated using DEA.
Our main results are the following. Generally, all countries have relatively high levels of mean
technical efficiency ranging from 0.72 to 0.92 for both field crops and dairy farms. Interestingly the
majority of countries have better performance in dairy sectors in terms of higher levels of mean
efficiency than in field crop production. A slightly decreasing trend however may be observed for all
countries. Technical Efficiency estimates are largely in line with those obtained by previous studies.
2
We investigate the issue of how relative performance of farms fluctuates in terms of technical
efficiency over time. We may hypothesise that many poorly performing farms remain inefficient and
some farmers are performing always efficiently. We can identify farms which are usually at the
bottom or top of the efficiency ranking. However, the FADN data has an inherent problem for long
time period analysis arising from its rotated/unbalanced panel nature, namely that not all the farms are
observed for the whole period. So we need to calculate transition matrices in each consecutive year.
Surprisingly stability analysis revealed that in average 60% of farms maintain their efficiency ranking
in two consecutive years, whilst 20% improve and 20% worsen their positions for all countries.
However, these ratios slightly fluctuate around these values for one year to next year. Mobility
analysis ranks countries according to the mobility of SFA scores within the distribution. Farms in New
Member States are more mobile than those in EU15.
The DEA estimation shows a similar declining trend on the development of technical efficiency over
time except for the Swedish dairy sector showing an increasing efficiency trend. Additionally, we
investigate the total productivity changes in two steps. First, we do not find a definite trend in total
factor productivity changes. Second, we address the question whether total factor productivity changes
converge or diverge over time. Using panel unit root tests our estimations reveal a convergence of
productivity across old EU member countries during analysed period.
Finally, we decompose the total factor productivity changes into its main elements. Field crop farm
indicators generally present a significantly higher volatility than dairy farms. Random effect panel
regression of Total Factor Productivity Change on its components shows Technological Change as
being the significant positive driver for crop farms, whilst Technical Efficiency Change followed by
Technological Change are the most important for dairy farms. In addition we do not find significant
impacts of CAP reforms in 1992 and 2000 on total productivity changes.
3
Contents
Executive Summary
2
Contents
4
Figures
5
Tables
6
Introduction
7
Literature review
9
Methodology
Stochastic Frontier Analysis
Data Envelopment Analysis
The Constant Return to Scale (CRS) model
The Variable Return to Scale (VRS) model
Panel Unit Root analysis
Stability Analysis
Software
11
11
13
13
15
16
17
18
Data
19
Results
Technical efficiency analysis
OLS on time trend
Stability Analysis
Total Factor Productivity Analysis
23
23
26
27
34
Conclusions
42
References
45
4
Figures
Figure 1. Technical efficiency scores for crop farms ( SFA/DEA) ....................................................... 25
Figure 2. Technical efficiency scores for dairy farms (SFA/DEA) ....................................................... 25
Figure 3 . Tercile stability analysis for Belgian crop and dairy farms .................................................. 28
Figure 4 . Tercile stability analysis for Estonian crop and dairy farms ................................................. 28
Figure 5. Tercile stability analysis for French crop and dairy farms ..................................................... 29
Figure 6. Tercile stability analysis for German crop and dairy farms ................................................... 29
Figure 7. Tercile stability analysis for Hungarian crop and dairy farms .............................................. 30
Figure 8. Tercile stability analysis for Italian crop and dairy farms..................................................... 30
Figure 9. Tercile stability analysis for Dutch crop and dairy farms ..................................................... 31
Figure 10. Tercile stability analysis for Swedish crop and dairy farms ................................................ 31
Figure 11. TFPC and its components for Belgium crop and dairy farms .............................................. 35
Figure 12. TFPC and its components for Italian crop and dairy farms ................................................. 35
Figure 13. TFPC and its components for French crop and dairy farms ................................................ 36
Figure 14. TFPC and its components for German crop and dairy farms............................................... 36
Figure 15. TFPC and its components for Hungarian crop and dairy farms........................................... 37
Figure 16. TFPC and its components for Estonian crop and dairy farms ............................................. 37
Figure 17. TFPC and its components for Dutch crop and dairy farms .................................................. 38
Figure 18. TFPC and its components for Swedish crop and dairy farms .............................................. 38
5
Tables
Table 1. Overview of empirical studies of technical efficiency in crop and dairy sectors of FACEPA
countries .................................................................................................................................................. 9
Table 2. Descriptive statistics and concentration index of crop farms (UAA)..................................... 21
Table 3. Descriptive statistics and concentration index of dairy farms (UAA)..................................... 21
Table 4. Descriptive statistics and concentration index of dairy farms (livestock units) ...................... 21
Table 5. SFA model specifications for crop farms ................................................................................ 23
Table 6. SFA model specifications for dairy farms ............................................................................... 24
Table 7. OLS regression of efficiency scores on a time trend............................................................... 26
Table 8. Stability analysis, percentage of farms in the same tercile during two consecutive years ...... 27
Table 9. Average change in technical efficiencies for crop farms ........................................................ 32
Table 10. Average change in technical efficiencies for dairy farms ..................................................... 32
Table 11. Means of M1 and M2 mobility indices ................................................................................. 33
Table 12. Coefficient of variation for Total Factor Productivity Changes and its components for crop
products ................................................................................................................................................. 34
Table 13. Coefficient of variation for Total Factor Productivity Changes and its components for dairy
products ................................................................................................................................................. 34
Table 14. OLS TFPC on time trend ...................................................................................................... 39
Table 15. Panel unit root analysis for crop farms .................................................................................. 39
Table 16. Panel unit root analysis for dairy farms................................................................................. 40
Table 17. Panel estimations for total productivity changes for crop products ...................................... 41
Table 18. Panel estimations for total productivity changes for milk products ...................................... 41
6
Introduction
The technical efficiency refers to the situation where it is impossible for a farm to produce more with
given technology. There are two possibilities for farmers. First, produce larger output using the same
inputs, second, produce the same output with less amounts of the overall inputs. In practice, the
research and policy interests are focusing on the relative position in terms of efficiency of particular
farms with respect to others. Consequently, the technical efficiency can be described by the
relationship between observed output and some ideal or potential production. There is wealth of
methodological and empirical literature focusing on the issues in efficiency and productivity (standard
theoretical references Coelli et al., 2005; Kumbhakar and Lovell, 2000; while comprehensive
overview on empirical research Bravo-Ureta et al. 2007). There exist two main approaches developed
over time for analysing technical efficiency in agriculture. (1) The construction of a nonparametric
piecewise frontier using linear programming method known as data envelopment analysis (DEA); (2)
the estimation of a parametric production function using stochastic frontier analysis (SFA). While the
vast majority of empirical studies on technical efficiency in the agricultural sector mostly have utilized
only one method to estimate their efficiencies, we apply both methodological approaches to measure
efficiency. In addition, the most studies focus on the single country’s agricultural sector, thus the
comparative analysis of the technical efficiency is rather scarce (see recent exceptions Barnes et al
2010, and Zhou and Lansink 2010). More importantly, easier availability to the farm level data,
namely FADN data in the EU may provide interesting insights for policy makers on farm level
technical efficiency and develop more targeted policy to improve efficiency in European agriculture.
The purpose of this deliverable is to present and analyse various efficiency indicators for the EU
countries included in the FACEPA project, Belgium, Estonia, France, Germany, Hungary, Italy, The
Netherlands and Sweden. The availability of long period datasets between 1990 and 2006, allow us to
concentrate on the long time trends in technical efficiency especially in Old Member States. This study
is the first which may provide a comprehensive overview on the development in farm level efficiency
across eight European countries.
The rest of this deliverable is organised as follows. Section 2 presents a brief review on the efficiency
literature in analysed countries using FADN dataset. Section 3 describes the efficiency methodology,
followed by the description of the datasets and variables employed in section 4. Section 5 presents the
main results of the analysis in two steps. First we outline the results based on the SFA approach.
Second we show our estimations applying DEA methodology. Detailed outcomes of various efficiency
7
indicator estimations are presented in the Annexes. In the results section of this deliverable we focus
on the possible interpretation of results, each sub-chapter focusing on a main issue:
•
Technical Efficiency results are presented and discussed paying special attention to trend and
stability analysis.
•
The second sub-chapter is dedicated to Total Factor Productivity Analysis. After presenting
Total Factor Productivity Change (TFPC) and its component estimations, unit root tests are
applied to analyse convergence. Then decomposition analysis of TFPC indicators closes the
sub-chapter, looking to determine sources of TFPC.
Finally the last chapter summarizes main results of the deliverable and concludes.
8
Literature review
During the last two decades research on various farm efficiency indicators, most often technical
efficiency, has flourished. This rich research is mostly due to the appearance of software packagessome freely available- and the increased availability of detailed farm survey data. Table 1 presents a
brief overlook of some of the recent efficiency and productivity papers. We focused on field crop and
dairy sectors of countries included in this research, presenting the main methodology, data source and
time-span, and estimated mean technical efficiency.
Table 1. Overview of empirical studies of technical efficiency in field crop and dairy sectors of
FACEPA countries
Paper
Sector
Period
Methodology
Data
Mean TE
-
-
Germany
Kleinhanß et al. (2007)
Brümmer et al.(2002)
Zhu and Oude Lansink
Live-
1999-
stock
2000
Dairy
1991-
parametric (output
specialised dairy farms
1994
distance fct.), translog
in Schleswig-Holstein
1995-
parametric (output
FADN
0.64
2004
distance fct.), Translog
0.89
Crop
(2010)
non-parametric, DEA
FADN
0.95
Netherlands
Brümmer et al. (2002)
Zhu and Oude Lansink
Dairy
Crop
(2010)
1991 -
parametric (output
FADN (highly
1994
distance fct.), translog
specialised dairy farms)
1995-
parametric (output
FADN
0.76
2004
distance fct.), translog
1998-
non-parametric, DEA,
Farm Economic Survey,
0.84 (0.82)
2002
input (output) oriented
Agriwise, Swedish
Sweden
Hansson, H. (2007)
Dairy
Dairy Association
database
Larsen, K. (2010)
Crop
Larsen, K. (2010)
Dairy
Zhu and Oude Lansink
Crop
(2010)
2001-
non-parametric, DEA,
2004
CRS (VRS)
2001-
non-parametric, DEA,
2004
CRS (VRS)
1995-
parametric (output
2004
distance fct.), Translog
FADN
0.52 (0.58)
FADN
0.65 (0.70)
FADN
0.71
FADN
0.47
France
Latruffe and Fogarasi
(2009)
Crop
2001-
non-parametric, DEA
2004
9
Latruffe and Fogarasi
Dairy
2001-
non-parametric, DEA
FADN
0.76
FADN
0.76
FADN
TFPC of 1%
2004
(2009)
Italy
Barnes et al. (2010)
Crop
SFA
Belgium
Coelli et al. (2006)
Crop
1987-
non-parametric, DEA,
2002
Malmquist TFP
p.a.
Hungary
Bakucs et al. (2010)
Latruffe and Fogarasi
All
2001-
parametric, SFA,
farms
2005
translog
Crop
2001-
0.73
non-parametric, DEA
FADN
0.42
non-parametric, DEA
FADN
0.85
FADN
0.74
2004
(2009)
Latruffe and Fogarasi
FADN
Dairy
20012004
(2009)
Estonia
Vasiliev et al. (2008)
Crop
2000-
non-parametric, DEA
2004
Note: TE = technical efficiency; fct = function
Source: authors’ compilation
With the exception of few studies (e.g. Barnes et al. 2010, that also estimates a metafrontier for several
countries), most of the research done in Europe, focuses on a single country – one or several
agricultural sectors. Besides estimating various efficiency indicators, most of these papers focus on
determining the drivers of efficiency, i.e. socio-economic variables that influence farms’ relative
position towards the efficient frontier. The analysis of determinants of efficiency is not an objective of
this deliverable. Therefore, besides presenting a large number of efficiency indicator estimations for
each country and sector, some computed with both parametric and non-parametric methods, here we
analyse the general evolution of technical efficiency and total factor productivity change estimates,
focusing on country wise similarities and differences, stability of farms’ position within technical
efficiency ranking, trend and convergence analysis.
10
Methodology
There are a number of methodological approaches applied in this deliverable. Various efficiency
indicators, as well as changes of these scores were computed using standard parametric and nonparametric productivity analysis methodology. In order to analyse the convergence of selected
indicators in a panel framework, Ordinary Least Squares (OLS) on time trend, panel unit root tests and
dynamic OLS analysis methods were applied. Stability analysis was used to evaluate the percentage of
farms with stable (over a two year period), increasing or decreasing efficiency ranking.
Stochastic Frontier Analysis
Within the parametric approaches, the Stochastic Frontier Analysis, (SFA) is commonly used. Aigner
at al. (1977) and Meeusen and Van den Broeck (1977) have simultaneously yet independently
developed the use of SFA in efficiency analysis.
The main idea is to decompose the error term of the production function into two components, one
pure random term (v i ) accounting for measurement errors and effects that can not be influenced by the
firm such as weather, trade issues, access to materials, and a non-negative one, measuring the
technical inefficiency, i.e. the systematic departures from the frontier (u i ):
Yi = f ( xi ) exp(vi − u i )
or, equivalently:
(1)
ln(Y ) i = βxi + vi − ui )
where Y i is the output of the ith firm, x i a (k+1) vector of inputs used in the production, f(·) the
production function, u i and v i the error terms explained above, and finally, β a (k+1) column vector of
parameters to be estimated. The output orientated technical efficiency, (TE) is actually the ratio
between the observed output of firm i to the frontier, i.e. the maximum possible output using the same
input mix x i .
Arithmetically, technical efficiency is equivalent with:
TEi =
Yi exp( xi β + vi − ui )
=
= exp(−ui ) , 0 ≤ TEi ≤ 1 .
exp( xi β + vi )
Yi*
(2)
Contrary to the non-parametric DEA approach, where all technical efficiency scores are located on, or
below the efficient frontier (see below), in SFA they are allowed to be above the frontier, if the
random error v is larger that the non-negative u.
11
Applying SFA methods requires distributional and functional form assumptions. First, because only
the w i =v i - u i error term can be observed, one needs to have specific assumptions about the
distribution of the composing error terms. The random term v i , is usually assumed to be identically
and independently distributed drawn from the normal distribution, N (0, σ v2 ) , independent of u i .
There are a number of possible assumptions regarding the distribution of the non-negative error term
u i associated with technical inefficiency. However most often it is considered to be identically
distributed as a half normal random variable, N + (0, σ u2 ) or a normal variable truncated from below
zero, N + ( µ , σ u2 ) .
Second, being a parametric approach, we need to specify the underlying functional form of the Data
Generating Process, DGP. There are a number of possible functional form specifications available,
however most studies employ either Cobb-Douglas (CD):
K
f ( xi ) = e β0 ∏ xikβ k
(3)
k =1
or TRANSLOG (TL) specification:
K
ln f ( xi ) = ∑ β k ln xik +
k =1
1 K K
∑∑ β kj ln xik ln x jk .
2 k =1 j =1
(4)
Because the two models are nested, it is possible to test the correct functional form by a Likelihood
Ratio, LR test. The TL is a more flexible functional form, whilst the CD restricts the elasticities of
substitution to 1. The model could be estimated either with Corrected Ordinary Least Squares, COLS
or Maximum Likelihood, ML. With the availability of computer software, the estimation by ML
became less computationally demanding, and the ML estimator was found to be significantly better
than COLS (Coelli et al.,1997).
With panel data, TE can be chosen to be time invariant, or to vary systematically with time. To
incorporate time effects, Battese and Coelli (1992) define the non-negative error term as exponential
function of time:
uit = exp[(−η (t − T )]ui
(5)
where t is the actual period, T the final period, and η a parameter to be estimated. TE either increases
(η>0), decreases (η<0) or it is constant over time, i.e. invariant (η=0). LR tests can be applied to test
the inclusion of time in the model. Since TE is allowed to vary, the question arise what determines the
changes of TE scores. Early studies applied a two-stage estimation procedure, first determining the
inefficiency scores, and then, in a second stage regressing TE scores upon a number of firm specific
variables assumed to explain changes in inefficiency scores. Some authors however showed, that
conflicting assumptions are needed for the two different estimation stages. In the first stage, the error
term representing inefficiency effects, are assumed to be independently and identically distributed,
whilst in the second stage they are assumed to be function of firm specific variables explaining
12
inefficiency, i.e. they are not independently distributed (Curtiss, 2002). Battese and Coelli (1995)
proposed a one stage procedure where firm specific variables are used to explain the predicted
inefficiencies within the SFA model. The explanatory variables are related to the firm specific mean μ
of the non-negative error term u i :
µi = ∑ δ j zij
(6)
j
where μ i is the ith firm-specific mean of the non-negative error term; δ j are parameters to be estimated;
z ij are ith firm-specific explanatory variables.
Using cross-section or panel data may often lead to heteroscedasticity in the residuals. With
heteroscedastic residuals, OLS estimates remain unbiased but no longer efficient. In frontier models
however, the consequences of heteroscedasticity are much more severe, as the frontier changes when
the dispersion increases. Caudill et al. (1995) introduced a model which incorporates
heteroscedasticity into the estimation. That is done by modelling the relationship between the variables
responsible for heteroscedasticity and the distribution parameter σ u :
σ ui = exp(∑ xij ρ j )
(7)
j
where x ij are the jth input of the ith farm, assumed to be responsible for heteroscedasticity, and ρ j a
parameter to be estimated.
Within SFA approach it is possible to test whether any form of stochastic frontier production function
is required or the OLS estimation is appropriate using a LR test. Using the parameterisation of Battese
and Cora (1977), define γ, the share of deviation from the frontier that is due to inefficiency:
γ=
σ u2
σ v2 + σ u2
(8)
where σ2 v is the variance of the v and σ2 u the variance of the u error term.
It should be noted however, that the test statistic has a ‘mixed’ chi square distribution, with critical
values tabulated in Kodde and Palm (1996).
Data Envelopment Analysis
The Constant Return to Scale (CRS) model
In the model presented below Constant Return to Scale (CRS) and input orientation are assumed. This
model yields an objective evaluation of overall technical efficiency (TE) and estimates the amounts of
the identified inefficiencies.
13
The data relate to
inputs and
represented by the vectors
matrix (X) and by
and
outputs on each of
. The data of all
firms. For the i-th firm, these are
firms are represented by
input
output matrix (Y). The purpose of DEA is to construct a non-parametric
envelopment frontier over the data points such that all observed points lie on or below the production
frontier. The frontier is therefore constructed with the best performing farms of the sample.
DEA model involves optimising a scoring function, defined as the ratio of the weighted sum of
outputs and the weighted sum of inputs. This function is optimised subject to the condition that the
value of the objective function achieved can not be greater than one, implying that efficient units will
have a score of one. For each i-th firm, the linear problem is the following:
(9)
where
, is the scoring function (
is an
vector of output weights and
is an
vector of input weights). The goal is to find values for u and v that maximise the efficiency score of
the i-th firm subject to the constraint that all the efficiency measures must be less than or equal to one.
The ratio formulation of the model has infinite number of solutions and to avoid this problem it is
necessary to impose the constraint:
Then, the maximization becomes
(10)
This transformation of
and
in
and
, is identified with multiplier form of the DEA linear
programming problem.
Introducing the duality in linear programming, one can derive an equivalent envelopment form of this
problem:
14
where
is a scalar that represents the minimum level to which the use of inputs can be reduced
without altering the output level. So, the scalar
provides the value of the global technical efficiency
score for the i-th firm. Indeed, as the Farrell’s definition (1957),
will satisfy the condition of less
than or equal to 1: if it is equal to one, the firm is considered technically efficient (it is a point on the
frontier). It means also that the use of all inputs can not be reduced at the same time without altering
technical efficiency, although a variation in the use of one of them may improve efficiency. If the
index is less than one there is some degree of technical inefficiency (firms are below the frontier).
is a
vector of constants that represents the weights to be used as multipliers for the input
levels of a reference production unit to indicate the input levels that an inefficient unit should aim at in
order to achieve efficiency.
It’s important to underline that for each firm we must find a value of
programming problem must be solved
, because the linear
times, one for each firm in the sample.
The Variable Return to Scale (VRS) model
The CRS DEA model is appropriate only when the farm is operating at an optimal scale. The previous
model thus permits to obtain a measure of global technical efficiency that does not allow variations in
returns to scale. The VRS model is an extension of the CRS DEA model, introduced to take into
account some factors such as imperfect competition, constraints, on finance, etc., that may cause the
firm to be not operating at an optimal level in practice. This model distinguishes between pure
technical efficiency (calculated with the VRS model) and scale efficiency (SE), identifying whether
increasing, decreasing or constant returns to scale possibilities are present for further exploitations.
As a consequence, the CRS linear model presented above changes by adding a further convexity
constraint:
(11)
Hence, the envelopment form of the input oriented VRS DEA model is specified as
where
is a
vectors of ones.
15
θ is the input technical efficiency score, having a value 0 < θ ≤ 1. As the previous case, if the θ value
is equal to one, the firm is on the frontier; the vector λ is an
vector of weights which defines
the linear combinations of the peers of the i-th firm.
Because the VRS DEA model is more flexible and envelops the data in a tighter way than the CRS
DEA model, the VRS technical efficiency score is equal to or greater than the CRS score. . This
relationship can be used to measure the scale efficiency of the firms:
(12)
SE = 1 implies scale efficiency or the presence of CRS, while SE < 1 indicates scale inefficiency that
can be due to the existence of either increasing or decreasing returns to scale. This may be determined
by calculating an additional DEA problem with non-increasing returns to scale (NIRS) imposed. The
previous VRS DEA model may be changed replacing the
restriction with
.
IF the NIRS TE score is different to the VRS TE score, it indicates that increasing returns to scale
exist for the firm. If they are equal, then decreasing returns to scale apply.
Panel Unit Root analysis
Panel unit root tests provide an easy way to econometrically test stationarity, and thus convergence or
divergence of total factor productivity change components. Panel unit root tests are similar, but not
identical, to unit root tests run on individual series. Consider equation 13:
yi ,t = ρyi ,t −1 + X i ,tδ i + ε i ,t
(13)
where i = 1,2,…,N are cross-section units and t=1,2,…,T the observed periods, X it possible exogenous
variables, ρ i the autoregressive coefficients, and the errors ε i,t are assumed to be mutually independent
idiosyncratic disturbance terms. If ρ i < 1 , y i is considered stationary, while if ρ i = 1 , the process
contains a unit root. With panel unit root tests, there are two assumptions regarding ρ. First, the
persistence parameters are common across cross-sections, that is to say ρ i = ρ, for all i. Second, ρ i can
freely vary across cross-sections. There are a number of panel unit root tests assuming one of the
above assumptions. Considering the well known low power properties of unit root tests, in this
deliverable we employ a battery of unit root tests: Levin et al. (2002) method (common unit root
process), Im et al. (2003) method (assuming individual unit root processes), ADF-Chi square and PPChi square.
16
Stability Analysis
Efficiency scores as such, do not reveal much about the fluctuation of farms’ relative performance.
From policy point of view however, it is an interesting question whether low performing farms are
always inefficient and vice versa, i.e. farms with higher TE scores are efficient throughout the period.
Policy relevance is given by the fact that chronically lower performing farms may be targeted with
specific measures in order to improve their efficiency scores. With large panel datasets however, due
to sample attrition it is not feasible to follow the TE scores of given farms through longer time periods,
therefore comparisons between consecutive years were done. We follow the stability analysis
methodology outlined by Barnes et al. (2010). Yearly farm TE scores were classified by terciles, then
transition matrices linking two consecutive years were constructed, that indicate whether the
considered farm remained in the same tercile, or its relative position has worsened, or contrary,
improved.
The degree of mobility in patterns of SFA scores can be summarised using indices of mobility. These
formally evaluate the degree of mobility throughout the entire distribution of SFA scores and facilitate
direct cross-country comparisons. The first of these indices (M 1 , following Shorrocks, 1978) evaluates
the trace (tr) of the transition probability matrix. This index thus directly captures the relative
magnitude of diagonal and off-diagonal terms, and can be shown to equal the inverse of the harmonic
mean of the expected duration of remaining in a given cell.
M =
1
K − tr (P)
K −1
(14)
where K is the number of cells, and P is the transition probability matrix.
The second index (M 2 , after Shorrocks, 1978 and Geweke et al., 1986) evaluates the determinant (det)
of the transition probability matrix.
M 2 = 1 − det(P)
.
(15)
In both indices, a higher value indicates greater mobility, with a value of zero indicating perfect
immobility.
17
Software
Stata 11.0 was used for SFA estimations, panel unit root and stability analysis, whilst DEAP (Coelli et
al., 1996) was used for DEA and related efficiency indicator estimations.
18
Data
EU FADN data were used for the deliverable. Two sectors were considered, based on the Type of
Farming (TF) variables A28 (one digit TF) and A29 (two digits TF): field crop farms (TF1) and dairy
farms (TF41). The following variables were used for the empirical analysis (EU FADN database code
in brackets):
TO=Total value of Output in Euros (SE131)
TL=Total labour input in Annual Working Units (AWU, 1 AWU corresponds to 2,200 hours)
(SE010)
UAA= Utilised Agricultural Area (UAA) in hectares (SE025)
IC= Intermediate consumption in Euros (SE275)
FA= Fixed assets in Euros (SE441).
Efficiency was calculated with SFA and DEA with one single output (TO) and four inputs
(TL, UAA, IC, FA).
Allocative efficiency was calculated with input prices. Two prices were calculated with
FADN data:
Land price (LAND_PRICE) in Euros per hectare calculated as rentals paid in euros (SE375)
divided by rented UAA in hectares (SE030) 1
Labour price (LAB_PRICE) in Euros per hired AWU calculated as wages paid in euros
(SE370) divided by non-family labour in AWU (SE010 – SE015).
Land price and labour price are thus specific to each farm each year. For those farms having
no rented land, they were assigned the average of the land prices for the same TF, country and
year. The same procedure was carried out regarding labour price.
By contrast, prices for the two other inputs (intermediate consumption and fixed assets) are
not available in the FADN database. Therefore, yearly price indices were retrieved from
Eurostat:
Intermediate consumption price index (INTCONS_IND)
Capital price index (ASSETS_IND).
These prices are thus not specific per farm, but farms in the same country and the same year have the
same price.
All variables in value were deflated by each country’s consumer price indices.
Data source is the FADN database from 1990 to the latest available year (2006) in case of “old”
Member States and 2004–2006 for “new” Member States. Inconsistent data and outliers were removed
from the initial datasets. Some main information about sample size of each country is presented below.
BELGIUM
There are a total of 6065 farms in the sample, 1627 field crop and 4438 dairy farms. The yearly
sample of field crop farms is between 90 and 107 farms, and the yearly number of dairy farms varies
between 246 and 320 farms.
ESTONIA
1
In the EU FADN database rentals (SE375) include rentals for rented land but also for other rented assets; therefore the land
price considered here does not exactly represent price paid for rented land. However, we assume that the difference does not
crucially affect the efficiency results.
19
The analysed sample consisted of 973 farms: 505 field crop farms and 468 dairy farms. The number of
field crop farms in the sample varied from 165 to 173 and the dairy farms from 152 to 160 over the
years of the study.
FRANCE
The French total sample is 53378 farms, of which there are 32874 field crop and 20504 dairy farms.
Yearly sample for field crop farms ranges between 1820 and 2067, for dairy farms between 966 and
1491.
GERMANY
The analysed sample consisted of 48845 farms: 20052 field crop farms and 28493 dairy farms. The
number of field crop farms in the sample varied from 788 to 1481 and the dairy farms from 1,498 to
1,880 over the years of the study.
HUNGARY
The analysed sample consisted of 3,147 farms: 2,859 field crop farms and 288 dairy farms. The
number of field crop farms in the sample varied from 891 to 1,028 and the dairy farms from 90 to 102
over the years of the study.
ITALY
100226 farms are in the Italian sample, 69021 field crop and 31205 dairy farms. Their yearly number
varies between 3214 and 4544 for field crop and 920 to 2301 for dairy farms.
THE NETHERLANDS
There are a total of 11280 farms in the Dutch sample, 4236 field crop and 7044 dairy farms. Yearly
observations range between 184 and 313 for field crop and 333 and 514 for dairy farms.
SWEDEN
The Swedish sample a total of 7345 observations, composed of 2983 field crop and 4362 dairy farms.
Yearly observation numbers are between 165 and 297 for field crop farms and 312 to 386 for dairy
farms.
MERGED SAMPLE
The merged sample of all participating countries totals 212302 observations, consisting of 122527
field crop and 89775 dairy farms. Yearly frequencies are not relevant since starting period varies
between countries.
Annex 1 contains the quantile distribution of the sample farms’ area. Taking a closer look on the data
a quite clear concentration process can be seen in all countries and in most of the quintiles. This
process was even stronger in the dairy sector. Detailed descriptive statistics of the variables employed
are presented in the annexes 2 and 3. To assess sample farm size changes between the start period
(1990 except Hungary, Estonia and Sweden) and the end period (2006), tables 2., 3., and 4. Compare
the respective means of farms per country, along with the Gini coefficient, measuring the
concentration index. Farm size is measured in Utilised Agricultural Area (UAA) for both field crop
and dairy farms. In addition, size of dairy farms is also assessed using livestock numbers.
20
Table 2. Descriptive statistics and concentration index of field crop farms (UAA)
Field
Utilised Agricultural Area
Crop
start period
end period
mean
Gini coefficient
mean
Gini coefficient
Belgium
54.00
0.2975
73.87
0.3159
Estonia
230.11
0.4754
240.27
0.4824
France
80.89
0.3436
135.88
0.3323
Germany
47.11
0.3501
252.02
0.6358
Hungary
255.45
0.6671
240.05
0.6360
Italy
19.61
0.5081
50.96
0.6503
Netherlands
62.34
0.3220
82.81
0.3684
Sweden
83.61
0.2939
120.19
0.4515
Source: authors’ calculations
Table 3. Descriptive statistics and concentration index of dairy farms (UAA)
Dairy
Utilised Agricultural Area
Starting period
End period
mean
Gini coefficient
mean
Gini coefficient
Belgium
33.97
0.2739
50.95
0.2651
Estonia
204.22
0.5538
211.89
0.5603
France
46.86
0.2616
81.43
0.2786
Germany
38.72
0.2609
113.90
0.5716
Hungary
239.25
0.6981
270.66
0.7247
Italy
20.45
0.5126
43.66
0.5349
Netherlands
32.92
0.2927
51.55
0.3041
Sweden
40.62
0.2728
84.06
0.4076
Source: authors’ calculations
Table 4. Descriptive statistics and concentration index of dairy farms (livestock units)
Milk
Livestock unit
Starting period
End period
mean
Gini coefficient
mean
Gini coefficient
Belgium
83.59
0.2818
95.94
0.2510
Estonia
84.53
0.5913
97.42
0.5976
France
60.55
0.2546
90.32
0.2940
Germany
64.44
0.2740
136.58
0.4993
Hungary
234.69
0.6755
222.83
0.6867
Italy
35.54
0.4623
100.11
0.5491
Netherlands
106.99
0.2967
127.80
0.3216
Sweden
43.86
0.2795
80.22
0.4274
Source: authors’ calculations
21
Tables 2 and 3 show an obvious concentration process happened in all analysed countries during the
period. With the exception of Hungary, sample means of farm size for all countries do increase
regardless of the sector or farm size measurement used. In some countries, average sample mean
increased dramatically (e.g. field crop farm size in Germany increased fivefold, Italian field crop and
dairy farm sizes trebled, Swedish, French field crop farm sizes doubled). In both tables the second
column for both the starting and end period presents the Gini concentration index. The coefficient
measures the inequality of a distribution, its value ranging between 0 (total equality) and 1 (maximum
inequality).
Generally the concentration index also increases between the start and end periods, but by far not as
dramatically as farm size means. In Belgium, despite the increasing sample size mean of dairy farms,
the concentration index actually decreased. The highest sample size means and concentration indices
are reported for the New Member States, Hungary and Estonia. With the exception of these two
countries however, interestingly, a higher sample size mean does not translate into a higher
concentration index.
22
Results
Technical efficiency analysis
With different databases per country and sector, it is practically impossible to run ML efficiency
estimations using a common functional form and distributional assumption for all frontiers when using
SFA. There are two issues that can arise with frontier estimations that necessitate country and sector
specific specifications. First, there is the problem of no-convergence of the ML estimation algorithm,
and second, some models may result in no inefficiency term, meaning that the deviation from the
frontier is only due to the random error ν i (the consequence is that all farms are located on the frontier,
i.e. TE scores close to 1). Therefore a pragmatic, parsimonious to general estimation strategy has been
adopted as follows:
•
Try Cobb-Douglas functional form → then try Translog
•
Try with half-normal distribution →
then try exponential → then try truncated-
normal
•
Try with unscaled variable → then try scaled variables (to help achieve algorithm
convergence).
Table 5 and 6 present the functional forms, distributional assumptions and weather input and output
variables were scaled or not during the SFA estimations.
Table 5. SFA model specifications for field crop farms
Functional form
Distributional assumptions
Scaled
Belgium
Cobb-Douglas
half-normal
unscaled
Estonia
Cobb-Douglas
half-normal
unscaled
France
Cobb-Douglas
half-normal
unscaled
Germany
Cobb-Douglas
half-normal
unscaled
Hungary
Cobb-Douglas
half-normal
unscaled
Italy
Cobb-Douglas
half-normal
unscaled
Netherlands
TRANSLOG
half-normal
scaled
Sweden
TRANSLOG
exponential
scaled
Source: authors’ calculations
Annex 4 presents the estimated TE scores per country, sector and their respective descriptive statistics.
Figures 1 presents the TE scores for field crop farms computed with SFA and DEA methods
respectively. Figures 2 shows technical efficiency scores for dairy farms computed with SFA and
DEA respectively.
23
Table 6. SFA model specifications for dairy farms
Functional form
Distributional assumptions
Scaled
Belgium
Cobb-Douglas
exponential
unscaled
Estonia
Cobb-Douglas
exponential
unscaled
France
Cobb-Douglas
exponential
unscaled
Germany
Cobb-Douglas
half-normal
unscaled
Hungary
Cobb-Douglas
half-normal
unscaled
Italy
Cobb-Douglas
exponential
unscaled
Netherlands
TRANSLOG
half-normal
scaled
Sweden
TRANSLOG
exponential
scaled
Source: authors’ calculations
DEA estimates are generally lower than SFA estimates. Despite the differences between TE scores
estimated with SFA and DEA, the relative position of countries is mostly the same. Notable
exceptions are Italian dairy farms, which are located in the top of SFA estimations (figure 2 left)
whilst being the lowest ranking when DEA was applied (figure 2 right). Results are plausible, when
mean technical efficiency scores are computed they are largely in line with results obtained by
previous studies. Some examples confirm this. Zhu and Oude Lansink (2010) employ the longest timespan in their research (see table 1), and focus on several of the countries represented in this
deliverable, this paper may be used as a benchmark to assess our results. For German crop farms,
average TE score obtained was 0.64, versus 0.48 (DEA) and 0.78 (SFA) computed in this study.
Brümmer et al. (2002) report an average TE score of 0.95 for specialised German (SchleswigHolstein) dairy farms, against 0.84 obtained in this paper, also using parametric methods. For the
Netherlands, Zhu and Oude Lansink (2010) report a mean TE score of 0.76, versus 0.90 (SFA) or 0.62
(DEA) in this research. For Dutch dairy farms, Brümmer et al. (2002) present an average TE score of
0.89, we have obtained 0.88 (SFA). Swedish crop farms average TE score was estimated to be 0.71,
estimations using same method within this deliverable report 0.77. For French dairy sector, average
TE score obtained with DEA in this research was 0.60, Fogarasi and Latruffe (2009) computed 0.76
on a shorter time-span. Barnes et al. (2010) obtained an average TE score of 0.76 using SFA,
comparable with 0.74 estimated in this deliverable with the same method.
24
Figure 1. Technical efficiency scores for field crop farms (SFA/DEA)
0,95
0,9
0,8
0,7
DEA scores
SFA scores
0,9
0,85
0,8
0,6
0,5
0,4
0,3
0,75
0,2
0,7
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
0,1
Belgium
Estonia
France
Germany
Belgium
Estonia
France
Germany
Hungary
Italy
The Netherlands
Sweden
Hungary
Italy
The Netherlands
Sweden
Figure 2. Technical efficiency scores for dairy farms (SFA/DEA)
0,95
0,8
0,75
0,7
DEA scores
0,85
0,65
0,6
0,55
0,5
0,45
0,8
0,4
0,35
0,75
0,3
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
SFA scores
0,9
Belgium
Estonia
France
Germany
Belgium
Estonia
France
Germany
Hungary
Italy
The Netherlands
Sweden
Hungary
Italy
The Netherlands
Sweden
25
OLS on time trend
With simple visual inspection of the efficiency estimation figures, it is difficult to determine whether
on long run average per country efficiency scores increase or decrease. We have therefore analysed
this issue econometrically by regressing with OLS the TE scores for each sector and each country (for
all years pooled together) on a single explanatory variable: the time trend. Table 7 presents the
estimated coefficients of per country regressions of efficiency scores on an intercept and time trend as
explanatory variable.
Table 7. OLS regression of efficiency scores on a time trend; coefficients’ value and significance for
the time trend in each country’s and TF’s regression
DEA
SFA
Field Crop
Dairy
Field Crop
Dairy
Belgium
-0.009***
0.001
-0.003***
-0.002***
France
-0.005
-0.002
-0.007***
-0.004***
Germany
-0.020**
-0.005
-0.005***
-0.003***
Italy
-0.038***
-0.011**
-0.003***
-0.001**
Netherlands
-0.014**
-0.007***
-0.002***
-0.005*
Sweden
-0.001
0.005*
-0.005**
-0.007***
Note: ***, **, * significant on 1, 5 and 10% respectively.
Source: authors’ calculations
Significant coefficients are small and negative across regressions, suggesting a decreasing average
technical efficiency score for each country and sector included in the analysis. For France, when the
dependent variable was computed with DEA, the time trend variable is not significant for either field
crop or dairy farms. With SFA, all time trend coefficients are significantly negative in the six countries
and the two sectors included in the regression. The regressions were not performed for New Member
States since their sample covers only 3 years.
26
Stability Analysis
Following the technique outlined in the methodology section, figures 3 to 10 present the results of the
stability analysis for Belgium, Estonia, France, Germany, Hungary, Italy, The Netherlands and
Sweden respectively. For each country, left hand graphs depict field crop, whilst right hand side
graphs represent dairy farms. Simple visual inspection suggests a surprising stability of results across
countries and sectors. Table 8 presents the mean values of the percentage of farms in consecutive years
that remain in the same tercile, along those increasing or decreasing their respective terciles.
Table 8. Stability analysis results: percentage of farms in the same tercile during two consecutive years
(averages for each country and sector)
Field Crop
increase
remain
Dairy
decrease
increase
remain
decrease
Belgium
0.20
0.61
0.19
0.16
0.66
0.17
Estonia
0.26
0.46
0.28
0.28
0.46
0.26
France
0.19
0.61
0.20
0.20
0.59
0.20
Germany
0.20
0.61
0.19
0.21
0.59
0.20
Hungary
0.26
0.48
0.26
0.26
0.44
0.29
Italy
0.20
0.59
0.21
0.20
0.58
0.22
0.20
0.58
0.21
0.17
0.65
0.18
0.18
0.65
0.17
0.21
0.58
0.21
Netherlands
Sweden
Source: authors’ calculations
As suggested earlier, results are surprisingly stable: about 60% of all farms remain in the same tercile
two consecutive years, whilst about 15-20% of farms decrease and increase their performance moving
down or up a tercile. Results obtained in this section are in line with those of Barnes et al. (2010) for
crop and dairy farming in England, Scotland, Wales and Northern Ireland.
27
Figure 3. Tercile stability analysis for Belgian field crop and dairy farms
Figure 4. Tercile stability analysis for Estonian field crop and dairy farms
28
Figure 5. Tercile stability analysis for French field crop and dairy farms
Figure 6. Tercile stability analysis for German field crop and dairy farms
29
Figure 7. Tercile stability analysis for Hungarian field crop and dairy farms
Figure 8. Tercile stability analysis for Italian field crop and dairy farms
30
Figure 9. Tercile stability analysis for Dutch field crop and dairy farms
Figure 10. Tercile stability analysis for Swedish field crop and dairy farms
31
Table 9. Average change in technical efficiencies for field crop farms depending on their tercile
movement
Belgium
Estonia
France
Germany
tercile 1
0.224
0.150
0.222
0.243
tercile 2
0.174
0.133
0.164
tercile 3
0.208
0.173
0.222
Hungary
Italy
Netherlands
Sweden
0.173
0.211
0.226
0.226
0.169
0.134
0.160
0.155
0.181
0.202
0.171
0.215
0.201
0.240
Farms remaining each year
Farms increasing each year
tercile 2-1
0.081
0.093
0.082
0.083
0.100
0.089
0.084
0.078
tercile 3-1
0.030
0.058
0.022
0.025
0.057
0.031
0.026
0.017
tercile 3-2
0.091
0.115
0.089
0.084
0.103
0.083
0.094
0.083
tercile 1-2
0.076
0.102
0.086
0.088
0.103
0.091
0.087
0.082
tercile 1-3
0.035
0.053
0.023
0.022
0.060
0.031
0.030
0.013
tercile 2-3
0.082
0.124
0.089
0.084
0.099
0.089
0.097
0.081
Farms decreasing each year
Source: authors’ calculations
On average, 15% (Estonia) to 24% (Germany) of field crop farms remained in the top tercile each
year, 13% (Estonia and Hungary) to 17% (Belgium, Germany) in the middle tercile and 17% (Estonia,
Hungary) to 22% (France) in the lower tercile (table 9). It is probably more interesting the percentage
of farms that changed their terciles over the year. An average of 10% (France, Germany) to 15%
(Estonia, Hungary) improved their performance by shifting into a higher (2 to 1 or 3 to 1) tercile,
whilst almost the same, on average 10% (France) to 16% (Hungary) fell from the top or middle tercile
to the lowest.
Table 10. Average change in technical efficiencies for dairy farms depending on their tercile
movement
Belgium
Estonia
France
Germany
tercile 1
0.244
0.161
0.090
0.205
tercile 2
0.179
0.127
0.060
tercile 3
0.240
0.172
0.105
Hungary
Italy
Netherlands
Sweden
0.140
0.221
0.239
0.213
0.159
0.104
0.157
0.178
0.160
0.225
0.201
0.200
0.236
0.209
Farms remaining each year
Farms increasing each year
tercile 2-1
0.072
0.109
0.086
0.086
0.140
0.096
0.074
0.079
tercile 3-1
0.015
0.071
0.027
0.025
0.050
0.028
0.015
0.030
tercile 3-2
0.077
0.105
0.094
0.090
0.073
0.084
0.078
0.096
tercile 1-2
0.077
0.090
0.086
0.092
0.161
0.095
0.081
0.082
tercile 1-3
0.012
0.060
0.026
0.027
0.029
0.033
0.015
0.032
tercile 2-3
0.085
0.105
0.092
0.092
0.102
0.086
0.084
0.099
Farms decreasing each year
Source: authors’ calculations
32
For dairy farm analysis (table 10), an average of 9% (France) to 24% (Belgium) remained in the top,
6% (France) to 18% (Belgium) in the middle and 10% (France) to 24% (Belgium) in the lower tercile
over one year period. As for field crop farms, it is more of an interest to comment the percentage of
farms improving or worsening their positions over the period. On average 9% (Belgium) to 19%
(Estonia, Hungary) improved their technical efficiency scores by moving up one or two terciles, whilst
a similar number, 9% (Belgium) to 19% (Hungary) fell from the middle or highest tercile to the
lowest. It is interesting to note, that for both field crop and dairy farms, New Member States (Estonia
and Hungary) register the highest average percentage of farms either dramatically increasing or
decreasing their terciles, suggesting a highly unstable yearly performance. These countries also
register the lowest percentages of farms that are stable in the same tercile during the year.
The mean of yearly mobility indexes, M1 and M2 (see equations 14 and 15), for the Old Member
States are presented in table 11. For both indices a higher value indicates greater mobility, whilst a
value close to zero indicates perfect immobility.
Table 11. Means of M1 and M2 mobility indices for field crop and dairy farms
Field Crop
Belgium
Estonia
France
Germany
Hungary
Italy
Netherlands
Sweden
Dairy
M1
M2
M1
M2
0.59
0.82
0.50
0.79
0.81
0.99
0.81
0.98
0.59
0.86
0.61
0.89
0.58
0.85
0.62
0.89
0.78
0.97
0.83
0.97
0.62
0.88
0.63
0.89
0.63
0.86
0.52
0.80
0.52
0.81
0.63
0.87
Source: authors’ calculations
Index means are remarkably similar across countries in this research. It is important to notice, that the
M2 index ranks countries in the same way as M1 does, implying consistency of results. M1 ranges
from 0.52 to 0.63 (0.50 to 0.63) for field crop (dairy) farms, and M2 from 0.81 to 0.88 (0.79 to 0.89)
for field crop (dairy) farms indicating a similar degree of mobility for the Old Member States
represented here. M1 and M2 indices are significantly higher for New Member States (Estonia and
Hungary). M2 reaches 0.97 and 0.99 for both sectors in Hungary and Estonia, suggesting higher
mobility of SFA scores throughout the entire distribution. For field crop farming, the lowest mobility
scores are recorded for Sweden, whilst for dairy farms in Belgium and Netherlands.
33
Total Factor Productivity Analysis
Detailed results of Total Factor Productivity Change and its driving components are in the Annexes 9
to 17. Figures 11 to 18 present the evolution of Total Factor Productivity Change (TFPC), Technical
Change (TC), Technical Efficiency Change (TEC), Scale Efficiency Change (SEC) and Allocative
Efficiency Change (AEC) computed with non-parametric methods for field crop and dairy farms.
Except for the increased volatility of indicators, figures presented do not reveal much further
information, or indeed common patterns. To get a picture about the volatility of indicators, tables 12
and 13 present the coefficient of variation for TFPC and its components for the field crop and dairy
farms.
Table 12. Coefficient of variation for Total Factor Productivity Changes and its components for field
crop farms
TFPC
TC
0.593
0.054
0.053
0.044
0.150
0.228
0.228
Belgium
France
Germany
Italy
Netherlands
Sweden
Pooled
TEC
0.236
0.130
0.181
0.267
0.376
0.102
0.102
SEC
0.152
0.104
0.216
0.260
0.196
0.125
0.125
AEC
0.093
0.084
0.154
0.226
0.086
0.083
0.083
0.132
0.294
0.454
0.180
0.298
0.174
0.174
Source: authors’ calculations
Table 13. Coefficient of variation for Total Factor Productivity Changes and its components for dairy
farms
TFPC
Belgium
France
Germany
Italy
Netherlands
Sweden
Pooled
TC
0.044
0.026
0.043
0.025
0.126
0.077
0.093
TEC
0.064
0.068
0.181
0.078
0.079
0.051
0.101
SEC
0.046
0.056
0.175
0.080
0.063
0.083
0.094
AEC
0.034
0.037
0.122
0.045
0.042
0.064
0.064
0.149
0.478
0.221
0.141
0.583
0.131
0.361
Source: authors’ calculations
There is no obvious common trend. The highest volatility is recorded for Belgium field crop farms’
TFPC, lowest for French dairy farms’ TFPC. Field crop farm indicators generally present a
significantly higher volatility than dairy farms. Notable exception is the AEC variable that (a) has
much higher volatility in the case of dairy farms, (b) has the highest volatility of all indicators within
dairy farms.
34
Figure 11. TFPC and its components for Belgium field crop and dairy farms
Figure 12. TFPC and its components for Italian field crop and dairy farms
35
Figure 13. TFPC and its components for French field crop and dairy farms
Figure 14. TFPC and its components for German field crop and dairy farms
36
Figure 15. TFPC and its components for Hungarian field crop and dairy farms
Figure 16. TFPC and its components for Estonian field crop and dairy farms
37
Figure 17. TFPC and its components for Dutch field crop and dairy farms
Figure 18. TFPC and its components for Swedish field crop and dairy farms
38
Graphs 11 to 18 above do not suggest any specific trend of increasing or decreasing TFPC
change over time. Table 14 presents an OLS regression analysis of TFPC scores over an
intercept and time trend for each country and each sector. Results do not help much on the
interpretation of results. With the exception of Italian field crop farms, where a weak
positive trend can be observed, the time coefficient is not significant in any other
regression.
Table 14. Results of OLS regression of TFPC on a time trend
DEA
Field
Dairy
Crop
Belgium
0.009
-0.001
France
0.004
-0.001
Germany
0.002
0.002
Italy
0.004**
0.001
Netherlands
0.002
0.005
Sweden
-0.016
0.001
Note: ** marks 5% significance level
Source: authors’ calculations
As indicated in the methodology section, panel unit root tests may provide information
about whether TFPC and its components have the tendency to converge, or contrary, to
diverge between countries. Table 15 and 16 present the panel unit root analysis results for
field crop and dairy farms respectively.
Table 15. Panel unit root analysis for field crop farms
Exogenous variables: Individual effects
Levin, Lin & Chu t
Im, Pesaran and Shin W-stat
ADF - Fisher Chi-square
PP - Fisher Chi-square
TFPC
TC
TEC
SEC
1.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Exogenous variables: Individual effects, individual linear trends
1.00
0.00
0.00
0.00
Levin, Lin & Chu t
0.00
0.00
0.00
0.00
Im, Pesaran and Shin W-stat
0.00
0.00
0.00
0.00
ADF - Fisher Chi-square
0.00
0.00
0.00
0.00
PP - Fisher Chi-square
Source: authors’ calculations
AEC
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Table 16. Panel unit root analysis for dairy farms
Exogenous variables: Individual effects
TFPC
TC
TEC
SEC
0.00
0.00
0.00
0.00
Levin, Lin & Chu t
0.00
0.00
0.00
0.00
Im, Pesaran and Shin W-stat
0.00
0.00
0.00
0.00
ADF - Fisher Chi-square
0.00
0.00
0.00
0.00
PP - Fisher Chi-square
Exogenous variables: Individual effects, individual linear trends
0.00
0.00
0.00
0.00
Levin, Lin & Chu t
0.00
0.00
0.00
0.00
Im, Pesaran and Shin W-stat
0.00
0.00
0.00
0.00
ADF - Fisher Chi-square
0.00
0.00
0.00
0.00
PP - Fisher Chi-square
AEC
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Source: authors’ calculations
All unit root tests applied here have non-stationarity (i.e. unit root) as their null hypothesis.
With the exception of the Levin, Lin & Chu t-test for TFPC variable for field crop farms,
the panel unit root hypothesis is strongly rejected by all tests for all variables, concluding
stationary processes. It follows, that country estimates of TFPC and its components do not
diverge over time.
To evaluate more formally the possible factors influencing TFPC we apply panel model
estimations for Old EU Member States. We need to exclude Estonia and Hungary from the
sample due to short time span. We regress TFPC on its components: TC, TEC, SEC, AEC
(model 1). In addition, we employ two other variables: time trend (model 2), and a reform
dummy which equal to one in 1992 and 2000, otherwise zero (model 3). We applied both
random and fixed effects models, but the Hausman test always favours the fixed effect
models at 5 per cent.
Our results are not really straightforward for field crop farms (table 17). Except for
technical change, all other variables are insignificant. In line with our a priori expectations,
technical change positively influences the total productivity changes. Interestingly, the
CAP reform dummy variable is not significant.
40
Table 17. Panel estimations for total productivity changes for field crop farms
(1)
(2)
(3)
0.509** 0.626*** 0.657***
TC
0.203
0.518
0.643
TEC
0.260
0.002
-0.130
SEC
-0.112
-0.073
-0.077
AEC
0.007
Time
-0.007
CAP Reform
0.103
-0.186
-0.137
Constant
90
90
90
N
2
0.0735
0.0785
0.0681
R
0.000
0.000
Hausman test (p value) 0.000
Sources: own calculations
Estimations show promising results for the milk farms (Table 18). Technical change,
technical efficiency change and allocative efficiency change have positive impact on the
total productivity change. Similarly to crop farms, additional variables as time trend and
CAP reform are insignificant.
Table 18. Panel estimations for total productivity changes for milk farms
(1)
(2)
(3)
TC
0.678*** 0.683*** 0.648***
TEC
0.984*** 0.967*** 0.950***
SEC
-0.269
-0.246
-0.271
AEC
0.044*** 0.043*** 0.039**
Time
0.001
CAP Reform
0.022
constant
-0.489*
-0.509*
-0.420
N
90
90
90
2
R
0.0508
0.0522
Hausman test (p value) 0.0927
0.0063
0.0049
Sources: own calculations
41
Conclusions
The purpose of this deliverable is to present and analyse various efficiency indicators for
countries included in the FACEPA project, Belgium, Estonia, France, Germany, Hungary,
Italy, The Netherlands and Sweden. The availability of long period datasets between 1990
and 2006, allows us to concentrate on the long time trends in technical efficiency especially
in Old Member States. This study is the first which may provide a comprehensive overview
on the development in farm level efficiency across eight European countries.
Two main approaches developed over time for analysing technical efficiency in agriculture
were used here. (1) The nonparametric data envelopment analysis (DEA); (2) the
parametric stochastic frontier analysis (SFA). While the vast majority of empirical studies
on technical efficiency in the agricultural sector mostly have utilized only one method to
estimate their efficiencies, we apply both methodological approaches to measure
efficiency. In addition, most studies focus on the whole country’s agricultural sector, thus
the comparative analysis of the technical efficiency is rather scarce. We take into account
the relative importance of specific subsectors and rationale of compilation more
homogeneous sample thus our study focuses on the field crops and dairy sector separately.
The bulk of this deliverable presents the yearly country estimations for specialised field
crop (TF1) and dairy (TF41) sectors of the following efficiency indicators reported in
Annexes 4 to 17: Technical Efficiency, Scale Efficiency, Allocative Efficiency, Technical
Efficiency Change, Scale Efficiency Change, Allocative Efficiency Change, Technological
Change and Productivity Change. FADN data from 1990 to 2006 (for Sweden from 1995
to 2006) for Old Member States and 2004 to 2006 for the New Member States were used
for the analysis. Technical and Allocative efficiency estimates were computed with both
parametric (SFA) and non-parametric (DEA) methods, other indicators were calculated
using DEA.
Our main results are following. Generally, all countries have relatively high levels of mean
efficiency ranging from 0.72 to 0.92 for both field crops and dairy farms. Interestingly
majority of countries have better performance in dairy sectors in terms of higher levels of
mean efficiency than in field crop production. This suggests that larger heterogeneity in
terms of agricultural practices apply in crop farming than in dairy farming. This is contrary
42
to the intuition that livestock farming, which requires more human input than crop farming,
would present a larger heterogeneity of human practices (this assumption was for example
put forward by Curtiss 2000). However, an explanation may be that crop farming is more
affected by land quality and climate conditions than livestock farming. Latruffe et al.
(2009) have for example provided evidence of the role of climate conditions on farms’
technical efficiency. Input quality is not taken into account within our analysis, as it is
impossible to find equivalent proxy across all countries. Therefore, lower efficiency in field
crop sector than in dairy sector may in fact be due to different land quality, which may
affect farms’ performance more than labour quality for example. A slightly decreasing
trend of efficiency may be observed for all countries. Technical Efficiency estimates are
largely in line with those obtained by previous studies.
We investigate the issue of how relative performance of farms fluctuates in terms of
technical efficiency over time. We may hypothesise that many poorly performed farms
remaining inefficient and some farmers are performing always very efficiently. We can
identify farms which are usually at the bottom or top of the efficiency ranking. However,
the FADN data has an inherent problem for long time period analysis arising from its
rotated panel nature, namely that not all the farms are observed for the whole period. So we
need to calculate transition matrices in each consecutive year. Surprisingly stability
analysis revealed that in average 60% of farms maintain their efficiency ranking in two
consecutive years, whilst 20% improve and 20% worsen their positions for all countries.
However, these ratios slightly fluctuate around these values for one year to next year.
Mobility analysis ranks countries according to the mobility of SFA scores within the
distribution. Farms in New Member States are more mobile than those in EU15. This may
be due to the unstable economic conditions of farms in these countries, where e.g. inputs
access is not always secured or is costly.
The DEA estimation shows a similar declining trend on the development of technical
efficiency over time except Swedish dairy sector increasing efficiency trend. We
investigate the total productivity changes in two steps. First, we do not find a definite trend
in total factor productivity changes. Second, we address the question whether total factor
productivity changes converge or diverge over time. Using panel unit root tests our
estimations reveals a convergence of productivity across old EU member countries during
analysed period. Panel unit root tests also reject the divergent technical change, technical
43
efficiency change, scale efficiency change and allocative efficiency change null hypothesis
across countries.
Finally, we decompose the total factor productivity changes into its main elements. Total
Factor Productivity Change analysis, is first done graphically, showing rather different
behaviour of TFPC and its components across countries and sectors. Indicators are
represented by high volatility, a trend analysis does not however produce conclusive results
except for Italy. In addition, field crop farm indicators generally present a significantly
higher volatility than dairy farms. Random effect panel regression of Total Factor
Productivity Change on its components shows Technological Change as being the
significant positive driver for crop farms, whilst technical efficiency change followed by
technological change are the most important for dairy farms. In addition we do not find
significant impacts on CAP reform in 1992 and 2000 on total productivity changes.
This deliverable has highlighted the usefulness of FADN data in conducting a comparative
analysis of farms’ performance across EU Member States. The FADN database enables to
use homogenous variables and indicators across countries and over time. A few
shortcomings of the database can also be underlined. Firstly, the rotating nature of the
panel makes it difficult to perform a long term investigation. The samples’ changes imply
that balanced panels over several years are too small to produce robust results. Therefore,
we had to resort to balanced panels over two consecutive years only, limiting the
possibility to follow the performance of the same farms over a long period and assess truly
the effect of shocks such as CAP reforms. Secondly, the FADN database is too poor in
terms of input prices. Regarding rentals, the variable includes both rentals for land and
rentals for other assets (buildings, livestock), and therefore land price is difficult to assess.
As for variable inputs, the absence of prices in the FADN database forces to use yearly
price indices that are similar for all farms in each country, which reduces the information
available in the calculations.
44
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46
Annex 1
Quintile distribution of sample farms according to area in hectares
Crop farms (TF 1)
Mean
Quintiles
Start of the
End of the period
period
BELGIUM
Q1
1.899
3.744
Q2
13.667
22.842
Q3
23.944
40.060
Q4
37.691
59.971
Q5
66.505
106.533
ESTONIA
Q1
25.843
27.179
Q2
64.823
67.462
Q3
113.643
118.739
Q4
206.577
217.458
Q5
613.707
708.010
FRANCE
Q1
11.406
11.795
Q2
29.383
42.563
Q3
44.282
73.860
Q4
65.494
114.953
Q5
125.835
211.322
GERMANY
Q1
10.428
9.935
Q2
23.457
34.784
Q3
32.965
58.442
Q4
44.875
96.461
Q5
74.178
604.002
HUNGARY
Q1
22.478
24.320
Q2
56.547
59.738
Q3
101.165
105.905
Q4
188.587
198.948
Q5
911.343
815.989
ITALY
Q1
2.376
2.273
Q2
5.553
6.522
Q3
9.074
13.281
Q4
15.295
27.954
Q5
50.263
122.099
THE NETHERLANDS
Q1
1.166
1.179
Q2
8.101
5.876
Q3
19.906
19.490
Q4
35.269
41.034
Q5
74.570
98.826
SWEDEN
Q1
19.675
22.634
Q2
33.703
47.414
Q3
45.010
70.443
Q4
60.592
105.279
Q5
112.837
245.062
Source: FADN database
47
Dairy farms (TF 41)
Mean
Start of the
End of the period
period
1.069
37.092
70.630
109.312
261.660
0.000
33.901
73.382
125.362
315.325
0.000
5.878
18.311
41.585
262.883
0.000
5.456
18.814
46.273
330.392
0.000
7.581
31.580
56.888
145.942
0.000
35.892
87.519
253.414
1.287
25.671
46.320
68.903
134.795
0.000
21.674
59.221
121.962
448.259
10.668
29.418
69.776
221.116
842.472
12.810
35.153
62.133
175.177
847.454
0
2.785
10.640
52.827
0
11.450
188.44
0.000
33.844
101.211
312.098
0.000
45.546
135.334
687.946
0.183
15.995
32.743
49.634
97.629
0.629
24.556
48.595
87.945
261.339
Annex 2
Descriptive statistics of variables used – first and last years of sample
Crop farms (TF 1)
Countries
First year of sample
Mean
St. Dev.
Min
BELGIUM
Total Output deflated (TO)
118,172
67,802
20,894
Utilised Agricultural Area (UAA)
54.00
29.39
5.18
Total Labour (TL)
1.47
0.64
0.46
Intermediate consumption deflated (IC)
53,664
30,294
8,570
Fixed Assets deflated (FA)
205,672
156,483
19,107
Land price deflated (PL)
155
40
65
Labour price deflated (PL)
11,422
3,327
2,942
Intermediate consumption price index
100
0
100
(PIC)
Capital price index (PC)
100
0
100
ESTONIA
Total Output deflated (TO)
69,556
71,093
4,329
Utilised Agricultural Area (UAA)
230.11
213.95
9.10
Total Labour (TL)
2.40
1.89
0.27
Intermediate consumption deflated (IC)
52,106
53,263
3,775
Fixed Assets deflated (FA)
159,346
190,892
188
Land price deflated (PL)
8
22
0
Labour price deflated (PL)
3,173
1,348
714
Intermediate consumption price index
100
0
100
(PIC)
Capital price index (PC)
100
0
100
FRANCE
Total Output deflated (TO)
109,611
76,576
8,667
Last year of sample
St. Dev.
Min
Max
Mean
Max
337,157
169.37
4.96
170,436
745, 961
300
25,681
100
114,646
73.87
1.40
55,047
314,747
180
16,199
112
95,258
42.29
0.59
43,568
288,662
89
2,953
0
14,477
17.35
0.40
7,653
2,268
45
5,899
112
527,785
223.96
3.91
229,866
1,605,155
494
31,578
112
100
157
0
157
157
369,571
984.95
12.66
250,006
1,204,610
271
7,645
100
68,604
240.27
2.37
56,194
156,800
9
3,498
109
75,946
235.24
1.90
63,625
167,492
9
1,290
0
2,238
8.20
0.55
2,008
1,061
0
996
109
419,243
1,247.55
12.54
342,887
879,786
67
8,181
109
100
106
0
106
106
765,489
114,639
95,250
2,064
1,235,507
Utilised Agricultural Area (UAA)
80.89
53.77
1.40
435.00
135.88
Total Labour (TL)
1.52
0.82
0.76
12.55
1.84
Intermediate consumption deflated (IC)
53,410
35,812
5,518
345,301
73,920
Fixed Assets deflated (FA)
136,700
106,646
432
1,538,609
150,089
Land price deflated (PL)
110
68
0
1,104
107
Labour price deflated (PL)
14,346
5,713
1,058
53,540
14,154
Intermediate consumption price index
100
0
100
100
124
Capital price index (PC)
100
0
100
100
135
GERMANY
Total Output deflated (TO)
91,084.40 67,661.11 11,366.00
475,584.00 229,618.10
Utilised Agricultural Area (UAA)
47.11
32.04
3.53
267.59
252.02
Total Labour (TL)
1.49
0.70
0.17
6.52
3.37
Intermediate consumption deflated (IC)
50,295.05 36,500.36 7,750.00
239,026.00 155,091.19
Fixed Assets deflated (FA)
300,327.56 282,800.77 2,239.00 3,094,287.00 690,661.40
Land price deflated (PL)
254.40
155.14
14.22
1,898.87
205.58
Labour price deflated (PL)
12,221.86
5,923.79 1,699.33
47,793.15 14,067.40
Intermediate consumption price index
100.00
0.00
100.00
100.00
127.10
(PIC)
Capital price index (PC)
100.00
0.00
100.00
100.00
131.30
HUNGARY
Total Output deflated (TO)
189,179
454,328
2,198
5,426,983
141,741
Utilised Agricultural Area (UAA)
255.45
500.9
5.07
5,078.00
240.05
Total Labour (TL)
4.34
10.18
0.01
97.4
4.05
Intermediate consumption deflated (IC)
122,299
280,757
2,685
3,276,464
100,238
Fixed Assets deflated (FA)
232,577
406,143
397
5,692,597
203,281
Land price deflated (PL)
49
41
0
503
53
Labour price deflated (PL)
4,848
2,322
0
18,919
4,718
Intermediate consumption price index
100
0
100
100
105
(PIC)
49
84.87
1.35
51,121
134,145
96
5,159
0
0
2.17
0.76
3,707
19
0
569
124
135
705.63
21.81
484,101
1,449,649
2,942
96,520
124
135
429,410.25 3,327.00
470.17
3.37
6.33
1.00
297,504.53 7,289.00
719,602.79
368.00
406.67
1.46
6,374.18 2,071.15
0.00
127.10
6,610,749.00
5,196.70
95.50
4,416,859.00
9,250,715.00
14,274.86
47,380.12
127.10
0.00
131.30
131.30
276,075
426.50
9
199,847
299,100
39
1,829
492
3.68
0.01
2,080
225
0
0
2,217,689
3,681.00
100.09
1,657,006
2,973,876
257
15,284
0
105
105
Capital price index (PC)
ITALY
Total Output deflated (TO)
Utilised Agricultural Area (UAA)
Total Labour (TL)
Intermediate consumption deflated (IC)
Fixed Assets deflated (FA)
Land price deflated (PL)
Labour price deflated (PL)
Intermediate consumption price index
(PIC)
Capital price index (PC)
THE NETHERLANDS
Total Output deflated (TO)
Utilised Agricultural Area (UAA)
Total Labour (TL)
Intermediate consumption deflated (IC)
Fixed Assets deflated (FA)
Land price deflated (PL)
Labour price deflated (PL)
Intermediate consumption price index
(PIC)
Capital price index (PC)
SWEDEN
Total Output deflated (TO)
Utilised Agricultural Area (UAA)
Total Labour (TL)
Intermediate consumption deflated (IC)
Fixed Assets deflated (FA)
100
0
100
100
111
0
111
111
35,444
19.61
1.66
13,992
197,325
216
12,063
100
44,944
24.48
1.00
18,733
247,516
163
1,932
0
263
0.24
0.04
417
53
0
2,634
100
570,335
378.00
11.58
211,490
3,086,357
3,942
25,032
100
48,070
50.96
1.74
23,549
440,172
163
10,255
140
117,616
101.26
2.60
62,006
1,462,303
138
1,883
0
325
0.50
0.06
244
12
0
1,206
140
2,467,585
1,846.87
45.76
1,225,770
35,561,353
3,078
26,348
140
100
0
100
100
168
0
168
168
182,102
62.34
1.78
79,091
598,801
399
18,155
100
122,456
38.23
0.96
48,424
542,053
224
5,961
0
22,930
13.37
0.10
15,656
8,452
68
2,402
100
639,138
222.97
7.93
260,114
3,443,725
2,324
34,625
100
238,599
82.81
1.95
110,104
1,330,608
632
19,775
131
202,012
56.68
1.50
83,121
1,079,767
667
10,029
0
10,989
11.20
0.05
7,732
30,458
0
1,127
131
1,124,646
302.45
12.18
493,261
5,728,201
5,145
87,489
131
100
0
100
100
136
0
136
136
64,946
83,61
1,01
43,485
277,539
50,936
46,55
0,52
27,375
219,414
3,055
14,00
0,09
5,547
13,536
307,021
275,60
2,51
213,335
1,249,065
98,799
120,19
1,16
73,111
576,479
126,077
124,52
0,89
83,018
560,391
5,781
16,97
0,11
8,322
2,389
694,016
890,50
5,53
523,867
3,568,796
50
Land price deflated (PL)
Labour price deflated (PL)
Intermediate consumption price index
(PIC)
Capital price index (PC)
133
25,839
100
128
3,651
0
12
2,099
100
1541
37,961
100
166
22,312
128
113
4,180
0
7
1,552
128
941
38,312
128
100
0
100
100
132
0
132
132
Source: authors’ calculations
51
Annex 3
Descriptive statistics of variables used – first and last years of sample
Dairy farms (TF4 1)
Countries
Mean
BELGIUM
Total Output deflated (TO)
98,966
Utilised Agricultural Area (UAA)
33.97
Total Labour (TL)
1.66
Intermediate consumption deflated (IC)
45,953
Fixed Assets deflated (FA)
215,187
First year of sample
St. Dev.
Min
Max
Mean
Last year of sample
St. Dev.
Min
52,406
17.61
0.47
27,422
128,066
21,241
6.20
0.80
10,025
23,337
297,678
107.16
3.78
146,875
642,098
95,979
50.95
1.62
49,269
354,465
43,768
25.66
0.52
24,011
196,105
18,352
10.38
1.00
7,047
50,327
Land price deflated (PL)
Labour price deflated (PL)
Intermediate consumption price index (PIC)
Capital price index (PC)
ESTONIA
Total Output deflated (TO)
127
11,649
100
100
51
2,230
0
0
32
3,074
100
100
306
23,594
100
100
157
16,645
112
157
96
2,702
0
0
26
6,304
112
157
105,273
182,927
9,368
124,488
203,379
6,868
Utilised Agricultural Area (UAA)
Total Labour (TL)
Intermediate consumption deflated (IC)
Fixed Assets deflated (FA)
204.22
5.03
66,748
169,473
271.27
7.52
98,512
366,737
15.25
1.00
5,463
9,051
211.89
5.74
90,266
215,198
277.85
8.58
144,108
363,710
17.47
1.00
5,469
1,164
5
3,414
100
100
8
1,364
0
0
0
776
100
100
1,455,08
5
1,949.06
51.86
629,469
2,873,49
1
67
6,635
100
100
7
4,092
109
106
7
1,507
0
0
0
992
109
106
Land price deflated (PL)
Labour price deflated (PL)
Intermediate consumption price index (PIC)
Capital price index (PC)
52
Max
246,730
158.46
3.98
142,025
1,066,67
5
590
37,132
112
157
1,353,18
2
1,840.70
52.00
909,802
2,955,23
9
45
7,842
109
106
FRANCE
Total Output deflated (TO)
Utilised Agricultural Area (UAA)
Total Labour (TL)
Intermediate consumption deflated (IC)
Fixed Assets deflated (FA)
Land price deflated (PL)
Labour price deflated (PL)
Intermediate consumption price index (PIC)
Capital price index (PC)
GERMANY
Total Output deflated (TO)
Utilised Agricultural Area (UAA)
Total Labour (TL)
Intermediate consumption deflated (IC)
Fixed Assets deflated (FA)
Land price deflated (PL)
Labour price deflated (PL)
Intermediate consumption price index (PIC)
Capital price index (PC)
HUNGARY
Total Output deflated (TO)
Utilised Agricultural Area (UAA)
Total Labour (TL)
Intermediate consumption deflated (IC)
Fixed Assets deflated (FA)
79,205
46.86
1.62
43,307
129,114
151
10,552
42,959
23.54
0.54
24,898
67,838
1,752
5,215
3,397
9.00
0.9
4,731
8,647
0
640
313,545
190.00
4.64
181,621
716,539
65,789
34,532
100
100
93,200
81.43
1.83
61,061
182,706
89
11,123
124
135
54,619
42.25
0.87
34,789
110,699
47
4,699
0
0
7,647
8.15
1.0
9,104
19,955
0
1,789
124
135
100
100
0
0
100
100
86,592
44,248
38.72
1.64
7,440
297,251
187,568
395,986
9,769
18.85
0.55
5.46
0.32
177.66
5.01
113.90
3.08
244.68
7.36
11.38
1.00
47,387
24,750
6,651
205,401
123,123
271,364
7,494
268,619
146,617
23,783
523,228
490,516
10,730
217
10,731
100
100
195
5,679
0
0
14
1,535
100
100
1,374,88
6
3 647
44,463
100
100
200
14,258
127
131
190
6,794
0
0
2
1,775
127
131
5,113,70
8
3,011.62
102.00
3,557,39
2
5,230,29
1
2 851
47,374
127
131
399,165
239.25
11.34
331,305
488,580
610,083
402.78
17.51
521,984
711,646
3,571
0.00
0.10
3,197
6,951
2,582,967
2,138.49
76.30
2,028,763
3,429,804
381,994
270.66
11.34
280,582
432,007
631,126
515.61
19.74
494,461
614,096
4,115
0.00
0.32
2,442
5,105
3,045,291
3,059.36
112.17
2,151,636
3,125,486
53
407,519
322.98
8.18
239,970
821,970
564
33,769
124
135
Land price deflated (PL)
Labour price deflated (PL)
Intermediate consumption price index (PIC)
Capital price index (PC)
ITALY
Total Output deflated (TO)
59
4,777
100
100
97
1,944
0
0
0
2,282
100
100
684
9,100
100
100
306
4,794
105
111
2,309
1,802
0
0
0
2,649
105
111
21,081
10,628
105
111
77,154
87,420
1,970
139,789
189,013
4,627
Utilised Agricultural Area (UAA)
Total Labour (TL)
Intermediate consumption deflated (IC)
20.45
2.09
38,581.36
36.33
0.93
45,991
0.10
0.39
1,975
1,018,51
8
588.00
9.62
591,180
43.66
2.54
75,832
54.16
1.87
114,350
0.59
0.44
1,666
Fixed Assets deflated (FA)
235,991.3
7
154.16
10,864
100
100
217.445
5,924
462,126
687,046
5,628
114
1,928
0
0
0
2,395
100
100
2,332,02
4
1,544
37,908
100
100
169
10,618
140
168
183
1,814
0
0
0
1,649
140
168
1,659,24
9
490.31
21.33
1,384,77
9
7,711,38
7
2,717
23,529
140
168
159,590
32.92
1.69
74,418
616,962
90,748
17.98
0.57
43,438
362,534
28,814
4.93
0.60
10,706
40,049
1,902
6.21
0.66
11,090
69,400
690
6,403
0
0
14
2,611
100
100
166,326
51.55
1.72
90,430
1,554,44
7
525
19,465
131
136
107,554
30.04
0.65
53,675
978,106
364
18,009
100
100
615,757
132.50
4.11
293,802
2,332,10
2
15,105
66,046
100
100
604
8,989
0
0
15
1,400
131
136
Land price deflated (PL)
Labour price deflated (PL)
Intermediate consumption price index (PIC)
Capital price index (PC)
THE NETHERLANDS
Total Output deflated (TO)
Utilised Agricultural Area (UAA)
Total Labour (TL)
Intermediate consumption deflated (IC)
Fixed Assets deflated (FA)
Land price deflated (PL)
Labour price deflated (PL)
Intermediate consumption price index (PIC)
Capital price index (PC)
SWEDEN
54
802,786
221.04
4.54
427,527
6,774,70
8
6,570
90,505
131
136
Total Output deflated (TO)
Utilised Agricultural Area (UAA)
Total Labour (TL)
Intermediate consumption deflated (IC)
Fixed Assets deflated (FA)
Land price deflated (PL)
Labour price deflated (PL)
Intermediate consumption price index (PIC)
Capital price index (PC)
70,759
40.62
1.49
45,897
231,170
39,469
21.46
0.49
23,759
133,405
3,875
9.50
0.38
8,097
12,862
257,642
144.79
3.27
146,268
786,807
131,843
84.06
1.91
105,422
362,104
129,835
80.85
1.06
101,116
377,782
12,274
9.53
0.50
7,971
38,610
78
26,063
100
100
94
3,491
0
0
1
11,553
100
100
1,293
58,856
100
100
88
24,624
128
132
127
4,172
0
0
0
4,469
128
132
Source: authors’ calculations
55
797,823
756.70
9.22
860,600
3,459,39
6
1,426
45,860
128
132
Annex 4
Yearly technical efficiency estimates
Crop farms (TF 1)
Years
SFA
Mean St.
Min
Dev.
BELGIUM
1990
1991
0.909 0.025 0.805
1992
0.906 0.029 0.790
1993
0.898 0.047 0.627
1994
0.907 0.039 0.769
1995
0.910 0.038 0.742
1996
0.890 0.082 0.362
1997
0.884 0.073 0.508
1998
0.896 0.052 0.554
1999
2000
0.877 0.066 0.506
2001
0.883 0.068 0.468
2002
0.875 0.081 0.422
2003
0.866 0.079 0.446
2004
0.896 0.057 0.531
2005
0.870 0.064 0.587
2006
0.855 0.064 0.607
Whole period
0.887 0.061 0.362
ESTONIA
2004
0.826 0.070 0.451
2005
0.844 0.051 0.686
2006
0.811 0.068 0.492
Whole period
0.826 0.064 0.450
FRANCE
1990
0.859 0.059 0.441
1991
0.869 0.049 0.461
1992
0.850 0.064 0.389
1993
0.824 0.070 0.247
1994
0.822 0.073 0.210
1995
0.813 0.072 0.339
1996
0.816 0.066 0.404
1997
0.813 0.071 0.425
1998
0.809 0.067 0.382
1999
0.796 0.077 0.215
2000
0.795 0.073 0.337
2001
0.776 0.085 0.225
2002
0.784 0.076 0.312
2003
0.783 0.086 0.267
2004
0.781 0.081 0.304
2005
0.763 0.086 0.308
2006
0.786 0.086 0.149
DEA
Min
Max
Mean
St.
Dev.
Max
0.948
0.946
0.953
0.951
0.963
0.957
0.948
0.951
0.968
0.964
0.967
0.967
0.971
0.971
0.944
0.971
0.802
0.793
0.736
0.791
0.741
0.707
0.775
0.731
0.621
0.741
0.643
0.732
0.656
0.697
0.730
0.679
0.678
0.720
0.139
0.122
0.145
0.147
0.171
0.174
0.153
0.167
0.220
0.160
0.174
0.177
0.185
0.170
0.169
0.159
0.172
0.173
0.488
0.491
0.362
0.456
0.405
0.179
0.301
0.307
0.190
0.245
0.211
0.202
0.203
0.240
0.358
0.368
0.381
0.179
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.948
0.931
0.936
0.947
0.630
0.642
0.588
0.620
0.208
0.199
0.198
0.203
0.112
0.128
0.228
0.112
1.000
1.000
1.000
1.000
0.955
0.965
0.957
0.952
0.956
0.953
0.957
0.946
0.951
0.955
0.927
0.950
0.948
0.957
0.959
0.967
0.965
0.562
0.555
0.568
0.537
0.431
0.508
0.479
0.533
0.558
0.505
0.534
0.495
0.500
0.565
0.524
0.531
0.424
0.154
0.167
0.155
0.160
0.145
0.148
0.152
0.151
0.144
0.152
0.144
0.161
0.143
0.144
0.151
0.164
0.141
0.127
0.080
0.095
0.062
0.034
0.072
0.083
0.102
0.143
0.046
0.106
0.043
0.105
0.143
0.071
0.048
0.023
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
Whole period
GERMANY
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Whole period
HUNGARY
2004
2005
2006
Whole period
ITALY
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Whole period
THE
NETHERLANDS
1990
1991
1992
0.807
0.079
0.148
0.967
0.518
0.157 0.023 1.000
0.815
0.825
0.819
0.799
0.793
0.779
0.786
0.783
0.770
0.781
0.775
0.781
0.741
0.754
0.774
0.761
0.774
0.779
0.073
0.072
0.083
0.093
0.091
0.094
0.082
0.095
0.103
0.091
0.087
0.089
0.110
0.112
0.093
0.089
0.092
0.094
0.365
0.416
0.367
0.106
0.291
0.160
0.418
0.071
0.072
0.333
0.353
0.221
0.049
0.073
0.245
0.315
0.151
0.048
0.942
0.951
0.956
0.949
0.958
0.934
0.959
0.958
0.946
0.968
0.953
0.941
0.955
0.967
0.967
0.946
0.963
0.968
0.649
0.554
0.592
0.559
0.501
0.530
0.422
0.433
0.443
0.327
0.534
0.476
0.391
0.392
0.500
0.488
0.414
0.472
0.167
0.162
0.170
0.175
0.180
0.156
0.137
0.148
0.147
0.146
0.165
0.145
0.151
0.178
0.171
0.163
0.163
0.177
0.166
0.133
0.167
0.034
0.092
0.068
0.109
0.010
0.011
0.062
0.122
0.092
0.066
0.008
0.087
0.105
0.022
0.008
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.803
0.773
0.783
0.786
0.075
0.082
0.094
0.084
0.335
0.152
0.177
0.151
0.952
0.937
0.968
0.968
0.369
0.466
0.446
0.425
0.163
0.169
0.178
0.175
0.089
0.022
0.024
0.022
1.000
1.000
1.000
1.000
0.763
0.779
0.763
0.763
0.754
0.746
0.736
0.732
0.733
0.737
0.733
0.741
0.739
0.724
0.723
0.739
0.741
0.744
0.082
0.064
0.073
0.075
0.080
0.088
0.089
0.090
0.089
0.089
0.096
0.090
0.098
0.105
0.102
0.100
0.095
0.089
0.128
0.467
0.241
0.216
0.215
0.178
0.056
0.108
0.126
0.226
0.096
0.164
0.061
0.154
0.218
0.145
0.184
0.055
0.931
0.930
0.917
0.939
0.921
0.938
0.953
0.927
0.920
0.926
0.938
0.943
0.954
0.941
0.966
0.969
0.934
0.968
0.318
0.312
0.334
0.298
0.320
0.225
0.263
0.239
0.241
0.296
0.231
0.203
0.239
0.183
0.203
0.142
0.208
0.255
0.149
0.148
0.162
0.160
0.159
0.160
0.168
0.153
0.155
0.166
0.149
0.110
0.153
0.138
0.142
0.134
0.141
0.160
0.010
0.056
0.027
0.024
0.019
0.008
0.002
0.003
0.003
0.024
0.003
0.012
0.001
0,007
0.023
0.003
0.008
0.001
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.921
0.911
0.895
0.001 0.803 0.957 0.658
0.001 0.744 0.950 0.696
0.002 0.488 0.954 0.646
57
0.161 0.282 1.000
0.165 0.344 1.000
0.173 0.200 1.000
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Whole period
SWEDEN
0.906
0.923
0.911
0.902
0.915
0.917
0.889
0.888
0.906
0.890
0.901
0.876
0.893
0.898
0.904
0.002
0.001
0.002
0.002
0.001
0.002
0.003
0.003
0.003
0.003
0.003
0.004
0.003
0.004
0.039
0.749
0.792
0.660
0.752
0.815
0.737
0.561
0.521
0.623
0.658
0.560
0.507
0.726
0.597
0.488
0.953
0.959
0.961
0.954
0.960
0.955
0.953
0.951
0.969
0.964
0.957
0.946
0.949
0.955
1.000
0.673
0.639
0.688
0.715
0.558
0.666
0.683
0.681
0.387
0.555
0.579
0.603
0.574
0.578
0.630
0.170
0.201
0.180
0.168
0.189
0.183
0.190
0.186
0.179
0.198
0.207
0.177
0.166
0.212
0.196
0.335
0.281
0.224
0.249
0.212
0.229
0.179
0.180
0.105
0.192
0.229
0.161
0.236
0.196
0.105
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1995
0.803
1996
0.831
1997
0.809
1998
0.748
1999
0.753
2000
0.754
2001
0.750
2002
0.769
2003
0.774
2004
0.753
2005
0.764
2006
0.757
Whole period
0.769
ALL COUNTRIES
1990
0.788
1991
0.800
1992
0.784
1993
0.778
1994
0.772
1995
0.762
1996
0.757
1997
0.753
1998
0.749
1999
0.749
2000
0.746
2001
0.749
2002
0.744
2003
0.738
2004
0.738
2005
0.737
2006
0.745
Whole period
0.757
Source: authors’ calculations
0.010
0.008
0.008
0.012
0.012
0.010
0.010
0.009
0.009
0.009
0.008
0.009
0.141
0.114
0.342
0.405
0.152
0.211
0.087
0.061
0.178
0.270
0.158
0.286
0.204
0.061
0.941
0.942
0.941
0.938
0.945
0.931
0.938
0.936
0.937
0.929
0.930
0.928
1.000
0.556
0.669
0.549
0.553
0.523
0.556
0.544
0.562
0.549
0.561
0.591
0.572
0.563
0.220
0.206
0.200
0.221
0.219
0.224
0.231
0.216
0.211
0.205
0.208
0.214
0.217
0.044
0.164
0.149
0.095
0.091
0.037
0.026
0.072
0.132
0.075
0.158
0.096
0.026
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.081
0.066
0.077
0.079
0.083
0.089
0.087
0.092
0.093
0.092
0.095
0.094
0.098
0.104
0.096
0.096
0.096
0.091
0.107
0.423
0.216
0.133
0.189
0.154
0.044
0.089
0.088
0.200
0.078
0.130
0.047
0.096
0.197
0.124
0.152
0.044
0.948
0.947
0.936
0.952
0.938
0.953
0.965
0.944
0.940
0.944
0.955
0.957
0.966
0.955
0.975
0.978
0.951
0.977
0.384
0.366
0.393
0.361
0.351
0.308
0.324
0.312
0.298
0.283
0.298
0.206
0.280
0.242
0.207
0.172
0.223
0.293
0.173 0.009 1.000
0.177 0.055 1.000
0.175 0.026 1.000
0.179 0.024 1.000
0.156 0.019 1.000
0.181 0.008 1.000
0.166 0.002 1.000
0.169 0.003 1.000
0.145 0.008 1.000
0.144 0.021 1.000
0.166 0.003 1.000
0.099 0.012 1.000
0.150 0.001 1.000
0.143 0.007 1.000
0.108 0.023 1.000
0.118 0.003 1.000
0.133 0.008 1.000
0.166 0.001 1.000
58
Annex 5
Yearly technical efficiency estimates
Dairy farms (TF 41)
Years
SFA
Mean St.
Min
Dev.
BELGIUM
1990
1991
0.904 0.044 0.638
1992
0.889 0.062 0.352
1993
0.906 0.048 0.601
1994
0.909 0.049 0.660
1995
0.903 0.050 0.464
1996
0.876 0.088 0.029
1997
0.871 0.066 0.584
1998
0.892 0.063 0.534
1999
2000
0.894 0.064 0.514
2001
0.897 0.061 0.530
2002
0.889 0.079 0.368
2003
0.874 0.085 0.424
2004
0.888 0.062 0.515
2005
0.864 0.080 0.321
2006
0.854 0.074 0.410
Whole period
0.884 0.073 0.029
ESTONIA
2004
0.826 0.070 0.451
2005
0.844 0.051 0.686
2006
0.811 0.068 0.492
Whole period
0.915 0.040 0.646
FRANCE
1990
0.912 0.053 0.220
1991
0.903 0.058 0.233
1992
0.910 0.063 0.258
1993
0.913 0.055 0.340
1994
0.915 0.049 0.462
1995
0.909 0.054 0.217
1996
0.895 0.065 0.260
1997
0.894 0.064 0.375
1998
0.904 0.055 0.431
1999
0.899 0.063 0.284
2000
0.899 0.068 0.112
2001
0.891 0.064 0.405
2002
0.889 0.074 0.030
2003
0.878 0.072 0.247
2004
0.869 0.083 0.381
2005
0.870 0.081 0.210
2006
0.848 0.096 0.276
59
DEA
Min
Max
Mean
St.
Dev.
Max
0.964
0.966
0.971
0.965
0.961
0.958
0.954
0.963
0.967
0.962
0.964
0.965
0.965
0.963
0.973
0.973
0.714
0.703
0.720
0.763
0.755
0.754
0.766
0.760
0.764
0.724
0.755
0.749
0.746
0.751
0.730
0.695
0.763
0.742
0.136
0.145
0.139
0.143
0.130
0.148
0.135
0.138
0.137
0.139
0.144
0.161
0.154
0.140
0.147
0.156
0.139
0.145
0.336
0.226
0.367
0.395
0.314
0.019
0.434
0.298
0.422
0.316
0.337
0.289
0.295
0.325
0.264
0.233
0.394
0.019
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.948
0.931
0.936
0.971
0.672
0.747
0.693
0.704
0.152
0.148
0.161
0.157
0.326
0.335
0.291
0.291
1.000
1.000
1.000
1.000
0.975
0.975
0.979
0.978
0.980
0.975
0.972
0.975
0.977
0.974
0.971
0.975
0.976
0.970
0.974
0.970
0.974
0.667
0.683
0.667
0.680
0.705
0.651
0.684
0.661
0.618
0.643
0.711
0.686
0.643
0.595
0.719
0.681
0.635
0.120
0.124
0.131
0.131
0.118
0.116
0.121
0.118
0.120
0.125
0.126
0.123
0.126
0.140
0.132
0.133
0.131
0.142
0.144
0.147
0.176
0.299
0.121
0.166
0.205
0.235
0.156
0.075
0.252
0.016
0.143
0.260
0.146
0.162
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
Whole period
GERMANY
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Whole period
HUNGARY
2004
2005
2006
Whole period
ITALY
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Whole period
THE
NETHERLANDS
1990
1991
1992
0.895
0.067
0.030
0.980
0.667
0.129
0.016 1.000
0.870
0.860
0.874
0.860
0.850
0.842
0.824
0.840
0.854
0.858
0.866
0.851
0.829
0.817
0.824
0.815
0.820
0.843
0.060
0.063
0.055
0.064
0.068
0.073
0.068
0.069
0.073
0.067
0.060
0.071
0.079
0.081
0.079
0.072
0.078
0.072
0.336
0.356
0.532
0.463
0.354
0.399
0.493
0.398
0.152
0.334
0.471
0.375
0.340
0.402
0.279
0.345
0.312
0.152
0.962
0.977
0.970
0.966
0.981
0.965
0.979
0.967
0.975
0.976
0.974
0.963
0.974
0.980
0.965
0.972
0.965
0.981
0.682
0.503
0.644
0.657
0.529
0.573
0.407
0.591
0.532
0.532
0.547
0.607
0.491
0.512
0.581
0.572
0.560
0.558
0.127
0.142
0.126
0.131
0.130
0.121
0.127
0.131
0.135
0.143
0.132
0.129
0.134
0.155
0.124
0.146
0.132
0.148
0.130
0.100
0.234
0.205
0.129
0.173
0.141
0.189
0.082
0.089
0.191
0.156
0.105
0.122
0.109
0.114
0.121
0.082
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.842
0.847
0.865
0.851
0.065
0.062
0.042
0.057
0.544
0.566
0.723
0.544
0.940
0.944
0.953
0.953
0.717
0.703
0.720
0.714
0.189
0.185
0.189
0.187
0.230
0.248
0.362
0.230
1.000
1.000
1.000
1.000
0.920
0.919
0.917
0.919
0.917
0.918
0.916
0.914
0.913
0.914
0.914
0.918
0.918
0.908
0.915
0.916
0.916
0.916
0.029
0.021
0.023
0.024
0.038
0.030
0.027
0.029
0.028
0.028
0.028
0.024
0.023
0.038
0.026
0.025
0.027
0.027
0.144
0.683
0.666
0.462
0.092
0.067
0.513
0.477
0.530
0.568
0.476
0.658
0.555
0.359
0.669
0.688
0.713
0.067
0.962
0.967
0.965
0.966
0.963
0.961
0.967
0.966
0.966
0.963
0.961
0.962
0.975
0.967
0.972
0.963
0.969
0.974
0.502
0.480
0.494
0.464
0.444
0.466
0.439
0.387
0.412
0.419
0.416
0.432
0.334
0.429
0.413
0.440
0.438
0.438
0.150
0.170
0.167
0.157
0.164
0.155
0.175
0.169
0.166
0.161
0.148
0.159
0.145
0.181
0.175
0.172
0.201
0.169
0.026
0.094
0.144
0.085
0.015
0.013
0.105
0.078
0.084
0.088
0.091
0.145
0.051
0.058
0.111
0.114
0.090
0.013
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.925
0.924
0.929
0.002 0.632 0.966 0.770
0.001 0.698 0.966 0.770
0.001 0.722 0.970 0.767
60
0.119 0.388 1.000
0.116 0.392 1.000
0.110 0.399 1.000
1993
0.927
1994
0.923
1995
0.906
1996
0.882
1997
0.908
1998
0.900
1999
0.899
2000
0.903
2001
0.894
2002
0.871
2003
0.874
2004
0.862
2005
0.858
2006
0.848
Whole period
0.899
SWEDEN
1995
0.878
1996
0.866
1997
0.853
1998
0.851
1999
0.832
2000
0.852
2001
0.834
2002
0.833
2003
0.839
2004
0.813
2005
0.811
2006
0.792
Whole period
0.837
ALL COUNTRIES
1990
0.866
1991
0.861
1992
0.864
1993
0.863
1994
0.860
1995
0.852
1996
0.844
1997
0.848
1998
0.848
1999
0.850
2000
0.853
2001
0.850
2002
0.844
2003
0.835
2004
0.835
2005
0.833
2006
0.830
Whole period
0.849
Source: authors’ calculations
0.001
0.002
0.002
0.003
0.002
0.003
0.003
0.003
0.003
0.004
0.004
0.004
0.005
0.005
0.060
0.731
0.768
0.686
0.496
0.345
0.560
0.539
0.585
0.565
0.566
0.452
0.510
0.219
0.078
0.078
0.971
0.970
0.970
0.957
0.968
0.975
0.967
0.968
0.970
0.972
0.969
0.965
0.967
0.959
1.000
0.767
0.729
0.728
0.733
0.738
0.695
0.731
0.751
0.749
0.663
0.678
0.745
0.652
0.708
0.732
0.114
0.114
0.122
0.121
0.126
0.134
0.132
0.126
0.131
0.139
0.127
0.125
0.145
0.143
0.130
0.419
0.424
0.386
0.332
0.208
0.309
0.350
0.359
0.346
0.372
0.309
0.460
0.224
0.081
0.081
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.006
0.006
0.006
0.006
0.007
0.006
0.006
0.006
0.005
0.006
0.006
0.006
0.113
0.193
0.285
0.137
0.285
0.198
0.270
0.315
0.180
0.294
0.342
0.259
0.495
0.137
0.975
0.977
0.971
0.963
0.960
0.956
0.963
0.954
0.957
0.961
0.947
0.947
1.000
0.623
0.683
0.613
0.653
0.658
0.682
0.681
0.687
0.682
0.635
0.693
0.679
0.665
0.169
0.177
0.158
0.150
0.168
0.166
0.165
0.169
0.154
0.164
0.157
0.149
0.164
0.092
0.188
0.094
0.179
0.127
0.162
0.162
0.117
0.180
0.212
0.192
0.360
0.092
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.044
0.045
0.046
0.047
0.051
0.053
0.052
0.054
0.055
0.057
0.054
0.054
0.057
0.060
0.058
0.057
0.059
0.054
0.233
0.445
0.483
0.430
0.188
0.165
0.455
0.303
0.262
0.319
0.309
0.478
0.163
0.388
0.390
0.418
0.251
0.163
0.960
0.966
0.964
0.965
0.964
0.959
0.967
0.964
0.965
0.961
0.959
0.959
0.977
0.967
0.974
0.964
0.971
0.976
0.521
0.470
0.523
0.491
0.465
0.464
0.437
0.429
0.446
0.461
0.447
0.438
0.375
0.410
0.384
0.402
0.382
0.452
0.130
0.146
0.139
0.137
0,143
0.127
0.146
0.147
0.144
0.150
0.136
0.137
0.124
0.130
0.121
0.134
0.138
0.148
0.026
0.087
0.131
0.085
0.014
0.013
0.009
0.044
0.082
0.038
0.046
0.089
0.011
0.053
0.045
0.065
0.024
0.011
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
61
Annex 6
Yearly scale efficiency estimates
Crop farms (TF 1)
Years
BELGIUM
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Whole period
ESTONIA
2004
2005
2006
Whole period
FRANCE
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Dairy farms (TF 41)
Mean
St.
Dev.
Min
DEA
Max
Mean
0.913
0.910
0.921
0.910
0.916
0.900
0.941
0.859
0.745
0.897
0.837
0.895
0.855
0.869
0.886
0.845
0.862
0.879
0.099
0.105
0.087
0.122
0.105
0.134
0.076
0.138
0.216
0.123
0.165
0.164
0.163
0.147
0.135
0.136
0.129
0.143
0.568
0.495
0.488
0.503
0.532
0.211
0.668
0.448
0.252
0.385
0.355
0.285
0.236
0.265
0.362
0.446
0.467
0.211
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.841
0.872
0.796
0.837
0.169
0.143
0.171
0.164
0.302
0.231
0.267
0.231
0.767
0.751
0.806
0.743
0.647
0.732
0.709
0.760
0.758
0.752
0.757
0.731
0.739
0.759
0.757
0.773
0.667
0.182
0.185
0.175
0.182
0.203
0.193
0.203
0.182
0.164
0.201
0.181
0.209
0.195
0.165
0.208
0.222
0.238
0.161
0.080
0.101
0.120
0.050
0.081
0.083
0.102
0.175
0.050
0.141
0.057
0.105
0.175
0.077
0.060
0.024
62
St.
Dev.
Min
Max
0.878
0.864
0.859
0.904
0.931
0.911
0.925
0.931
0.921
0.911
0.912
0.920
0.926
0.917
0.895
0.876
0.907
0.906
0.112
0.121
0.121
0.103
0.096
0.117
0.091
0.092
0.096
0.099
0.115
0.114
0.102
0.099
0.117
0.123
0.112
0.110
0.337
0.328
0.421
0.43
0.329
0.034
0.435
0.324
0.452
0.376
0.449
0.372
0.406
0.345
0.285
0.44
0.456
0.034
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.870
0.923
0.840
0.878
0.135
0.099
0.148
0.878
0.519
0.490
0.395
0.395
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.872
0.890
0.897
0.897
0.878
0.868
0.869
0.867
0.855
0.857
0.899
0.880
0.809
0.784
0.874
0.853
0.814
0.128
0.119
0.121
0.118
0.123
0.133
0.128
0.145
0.144
0.134
0.117
0.142
0.160
0.156
0.160
0.166
0.182
0.145
0.180
0.227
0.379
0.417
0.218
0.176
0.214
0.281
0.180
0.134
0.277
0.017
0.175
0.317
0.146
0.233
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
Whole period
GERMANY
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Whole period
HUNGARY
2004
2005
2006
Whole period
ITALY
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Whole period
THE
NETHERLANDS
1990
1991
1992
0.742
0.198
0.024 1.000 0.864
0.143
0.017 1.000
0.896
0.858
0.845
0.873
0.833
0.767
0.663
0.672
0.680
0.539
0.759
0.714
0.610
0.599
0.712
0.701
0.632
0.711
0.126
0.159
0.148
0.148
0.181
0.213
0.221
0.231
0.220
0.240
0.211
0.225
0.248
0.262
0.253
0.236
0.265
0.242
0.375
0.242
0.284
0.172
0.126
0.101
0.138
0.011
0.028
0.078
0.136
0.092
0.066
0.012
0.087
0.105
0.025
0.011
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.934
0.813
0.902
0.908
0.858
0.824
0.627
0.833
0.779
0.747
0.753
0.810
0.712
0.722
0.812
0.768
0.758
0.795
0.090
0.141
0.109
0.108
0.144
0.169
0.193
0.162
0.182
0.180
0.165
0.152
0.185
0.199
0.167
0.183
0.164
0.179
0.262
0.181
0.368
0.360
0.171
0.249
0.159
0.283
0.082
0.089
0.191
0.156
0.105
0.122
0.109
0.114
0.145
0.082
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.786
0.859
0.846
0.828
0.190
0.154
0.183
0.180
0.136
0.133
0.036
0.036
1.000
1.000
1.000
1.000
0.911
0.924
0.919
0.918
0.124
0.109
0.114
0.116
0.333
0.448
0.362
0.333
1.000
1.000
1.000
1.000
0.719
0.717
0.751
0.763
0.800
0.557
0.668
0.612
0.611
0.666
0.678
0.605
0.633
0.534
0.596
0.459
0.601
0.652
0.217
0.203
0.203
0.212
0.189
0.232
0.238
0.219
0.218
0.217
0.240
0.222
0.238
0.259
0.247
0.273
0.232
0.241
0.014
0.099
0.031
0.056
0.029
0.012
0.007
0.014
0.014
0.041
0.009
0.023
0.001
0.009
0.055
0.004
0.038
0.001
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.846
0.783
0.829
0.867
0.824
0.849
0.794
0.887
0.893
0.924
0.921
0.835
0.724
0.794
0.757
0.813
0.760
0.835
0.150
0.188
0.164
0.148
0.140
0.161
0.187
0.137
0.129
0.098
0.108
0.157
0.201
0.189
0.215
0.189
0.220
0.171
0.091
0.133
0.220
0.187
0.053
0.034
0.152
0.216
0.163
0.281
0.209
0.201
0.158
0.178
0.177
0.187
0.150
0.034
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.894
0.906
0.888
0.128 0.290 1.000 0.908
0.122 0.380 1.000 0.902
0.143 0.359 1.000 0.918
63
0.100 0.441 1.000
0.101 0.409 1.000
0.099 0.439 1.000
1993
0.895
1994
0.885
1995
0.903
1996
0.918
1997
0.849
1998
0.901
1999
0.908
2000
0.911
2001
0.733
2002
0.862
2003
0.864
2004
0.846
2005
0.824
2006
0.836
Whole period
0.876
SWEDEN
1995
0.766
1996
0.888
1997
0.835
1998
0.829
1999
0.792
2000
0.807
2001
0.791
2002
0.798
2003
0.768
2004
0.808
2005
0.836
2006
0.814
Whole period
0.809
ALL COUNTRIES
1990
0.800
1991
0.770
1992
0.823
1993
0.837
1994
0.863
1995
0.715
1996
0.773
1997
0.743
1998
0.822
1999
0.734
2000
0.799
2001
0.746
2002
0.679
2003
0.708
2004
0.739
2005
0.690
2006
0.734
Whole period
0.762
Source: authors’ calculations
0.128
0.145
0.145
0.116
0.174
0.138
0.157
0.155
0.221
0.181
0.167
0.173
0.178
0.198
0.161
0.458
0.304
0.325
0.313
0.290
0.337
0.191
0.192
0.143
0.211
0.250
0.185
0.236
0.202
0.143
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.932
0.897
0.895
0.905
0.908
0.889
0.888
0.901
0.924
0.854
0.870
0.931
0.847
0.872
0.898
0.094
0.110
0.114
0.101
0.110
0.122
0.121
0.109
0.099
0.139
0.121
0.087
0.139
0.131
0.113
0.510
0.438
0.407
0.391
0.259
0.374
0.409
0.398
0.457
0.372
0.424
0.480
0.224
0.081
0.081
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.205
0.163
0.187
0.207
0.224
0.229
0.242
0.221
0.225
0.206
0.183
0.187
0.212
0.078
0.207
0.262
0.111
0.093
0.060
0.030
0.100
0.132
0.119
0.168
0.222
0.030
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.834
0.856
0.803
0.865
0.833
0.860
0.865
0.844
0.849
0.807
0.859
0.859
0.844
0.157
0.166
0.169
0.138
0.170
0.155
0.150
0.160
0.145
0.164
0.134
0.134
0.155
0.149
0.219
0.138
0.372
0.129
0.246
0.192
0.152
0.274
0.212
0.316
0.387
0.129
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.201
0.195
0.190
0.192
0.168
0.253
0.227
0.228
0.179
0.216
0.232
0.227
0.213
0.260
0.227
0.290
0.228
0.127
0.012
0.099
0.029
0.056
0.029
0.012
0.007
0.014
0.033
0.037
0.009
0.001
0.047
0.009
0.055
0.004
0.028
0.001
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.865
0.797
0.878
0.893
0.837
0.867
0.792
0.908
0.909
0.944
0.930
0.858
0.762
0.821
0.891
0.873
0.783
0.859
0.117
0.134
0.126
0.116
0.125
0.146
0.167
0.110
0.109
0.079
0.086
0.151
0.176
0.144
0.127
0.122
0.151
0.142
0.091
0.133
0.236
0.187
0.053
0.034
0.135
0.186
0.082
0.164
0.209
0.099
0.024
0.127
0.163
0.177
0.051
0.024
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
64
Annex 7
Yearly allocative efficiency estimates
Crop farms (TF 1)
Years
SFA
Mean St.
Min
Dev.
BELGIUM
1990
0.924 0.020 0.872
1991
0.925 0.020 0.874
1992
0.927 0.023 0.861
1993
0.912 0.028 0.844
1994
0.898 0.058 0.695
1995
0.924 0.022 0.846
1996
0.933 0.019 0.864
1997
0.919 0.026 0.838
1998
1999
0.921 0.054 0.595
2000
0.920 0.042 0.735
2001
0.923 0.029 0.807
2002
0.922 0.030 0.798
2003
0.895 0.040 0.785
2004
0.927 0.025 0.841
2005
0.921 0.030 0.837
2006
0.927 0.019 0.883
Whole period
0.920 0.034 0.595
ESTONIA
2004
0.884 0.056 0.522
2005
0.883 0.053 0.640
2006
0.880 0.058 0.601
Whole period
0.882 0.055 0.521
FRANCE
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Whole period
GERMANY
65
DEA
Min
Max
Mean
St.
Dev.
Max
0.956
0.956
0.969
0.963
0.957
0.959
0.962
0.951
0.960
0.965
0.966
0.966
0.950
0.965
0.958
0.953
0.969
0.171
0.173
0.184
0.244
0.181
0.259
0.226
0.206
0.307
0.143
0.281
0.208
0.173
0.155
0.147
0.245
0.204
0.168
0.279
0.262
0.289
0.258
0.289
0.293
0.337
0.304
0.388
0.195
0.266
0.285
0.204
0.225
0.220
0.241
0.277
0.266
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.002
0.000
0.000
0.000
0.000
0.002
0.000
0.000
1.000
0.944
1.191
1.231
1.000
1.162
1.148
1.000
1.692
1.000
1.016
1.000
1.000
1.000
1.000
1.000
1.692
0.995
0.952
0.953
0.953
0.953
0.574
0.532
0.732
0.612
0.217
0.162
0.198
0.211
0.117
0.171
0.188
0.117
1.000
1.000
1.000
1.000
-
0.327
0.413
0.339
0.287
0.354
0.389
0.408
0.458
0.491
0.391
0.430
0.338
0.394
0.286
0.248
0.154
0.235
0.352
0.117
0.125
0.150
0.120
0.120
0.152
0.140
0.165
0.169
0.146
0.154
0.134
0.142
0.116
0.109
0.082
0.111
0.159
0.062
0.087
0.069
0.067
0.067
0.038
0.057
0.096
0.135
0.102
0.064
0.079
0.091
0.063
0.042
0.031
0.019
0.019
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Whole period
HUNGARY
2004
2005
2006
Whole period
ITALY
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Whole period
THE
NETHERLANDS
1990
1991
1992
1993
1994
-
-
-
-
0.327
0.238
0.260
0.227
0.116
0.256
0.314
0.222
0.286
0.432
0.195
0.307
0.281
0.144
0.430
0.305
0.317
0.211
0.168
0.140
0.156
0.135
0.082
0.206
0.239
0.154
0.214
0.272
0.139
0.221
0.191
0.101
0.237
0.193
0.176
0.206
0.036
0.030
0.040
0.035
0.012
0.016
0.039
0.026
0.033
0.044
0.021
0.026
0.034
0.012
0.005
0.026
0.024
0.005
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.872
0.870
0.854
0.054
0.057
0.076
0.405
0.451
0.297
0.971
0.959
0.964
0.692
0.454
0.264
0.481
0.239
0.181
0.138
0.261
0.023
0.034
0.033
0.023
1.000
1.000
1.000
1.000
0.120
0.124
0.116
0.104
0.084
0.154
0.149
0.145
0.110
0.078
0.048
0.070
0.116
0.165
0.020
0.020
0.084
0.102
0.114
0.128
0.133
0.105
0.115
0.144
0.154
0.166
0.132
0.112
0.064
0.116
0.165
0.168
0.028
0.024
0.103
0.131
0.012
0.007
0.008
0.007
0.004
0.007
0.005
0.009
0.004
0.003
0.001
0.002
0.003
0.000
0.001
0.001
0.002
0.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.358
0.333
0.372
0.367
0.411
0.209
0.208
0.204
0.196
0.227
0.076
0.031
0.096
0.096
0.093
1.000
1.000
1.000
1.000
1.000
0.794
0.797
0.796
0.795
0.785
0.010
0.007
0.009
0.010
0.020
0.737
0.692
0.459
0.695
0.726
66
0.706
0.726
0.735
0.698
0.682
1995
0.800
1996
0.808
1997
0.809
1998
0.801
1999
0.791
2000
0.802
2001
0.817
2002
0.812
2003
0.820
2004
0.806
2005
0.819
2006
0.827
Whole period
0.803
SWEDEN
1995
0.754
1996
0.781
1997
0.762
1998
0.705
1999
0.710
2000
0.713
2001
0.709
2002
0.728
2003
0.733
2004
0.714
2005
0.725
2006
0.719
Whole period
0.727
ALL COUNTRIES
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Whole period
Source: authors’ calculations
0.005
0.003
0.004
0.004
0.014
0.002
0.012
0.007
0.016
0.002
0.014
0.022
0.029
0.612
0.698
0.757
0.683
0.525
0.491
0.588
0.623
0.531
0.481
0.686
0.567
0.459
0.675
0.732
0.731
0.729
0.724
0.767
0.681
0.700
0.787
0.822
0.823
0.815
0.823
0.309
0.249
0.365
0.329
0.205
0.223
0.331
0.279
0.225
0.184
0.191
0.261
0.301
0.198
0.153
0.166
0.198
0.137
0.147
0.205
0.167
0.163
0.158
0.169
0.174
0.197
0.072
0.057
0.086
0.070
0.027
0.021
0.051
0.059
0.050
0.038
0.029
0.045
0.021
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.025
0.052
0.033
0.024
0.020
0.017
0.020
0.002
0.004
0.015
0.004
0.011
0.131
0.110
0.327
0.387
0.147
0.202
0.084
0.059
0.171
0.260
0.152
0.275
0.196
0.059
0.863
0.866
0.867
0.869
0.873
0.861
0.869
0.869
0.874
0.870
0.869
0.868
1.000
0.382
0.405
0.308
0.373
0.330
0.279
0.240
0.283
0.267
0.244
0.206
0.255
0.288
0.235
0.222
0.196
0.256
0.224
0.202
0.179
0.206
0.197
0.174
0.173
0.222
0.212
0.091
0.137
0.079
0.093
0.055
0.060
0.053
0.071
0.061
0.054
0.037
0.029
0.029
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
-
-
-
0.141
0.148
0.139
0.111
0.123
0.184
0.193
0.183
0.162
0.132
0.065
0.120
0.148
0.199
0.033
0.027
0.127
0.130
0.105
0.124
0.125
0.093
0.113
0.131
0.149
0.148
0.129
0.111
0.055
0.126
0.148
0.158
0.027
0.021
0.110
0.127
0.012
0.007
0.008
0.007
0.004
0.007
0.009
0.010
0.004
0.004
0.001
0.002
0.003
0.000
0.001
0.036
0.002
0.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
67
Annex 8
Yearly allocative efficiency estimates
Dairy farms (TF 41)
Years
SFA
Mean St.
Min
Dev.
BELGIUM
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Whole period
ESTONIA
2004
0.911 0.056 0.536
2005
0.913 0.038 0.708
2006
0.917 0.032 0.780
Whole period
0.913 0.042 0.535
FRANCE
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
-
68
DEA
Min
Max
Mean
St.
Dev.
Max
-
0.383
0.349
0.348
0.382
0.415
0.413
0.323
0.347
0.510
0.442
0.420
0.416
0.445
0.337
0.288
0.266
0.384
0.365
0.344
0.339
0.334
0.338
0.384
0.328
0.297
0.305
0.131
0.367
0.344
0.327
0.364
0.335
0.284
0.258
0.328
0.347
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.170
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
1.319
1.101
1.070
1.072
1.316
1.176
1.000
1.000
1.000
1.091
1.086
1.031
1.100
1.088
1.000
1.000
1.319
1.171
0.962
0.969
0.968
0.968
0.693
0.580
0.729
0.668
0.161
0.128
0.194
0.175
0.203
0.184
0.213
0.184
1.000
1.000
1.000
1.000
-
0.423
0.613
0.335
0.611
0.243
0.367
0.613
0.337
0.599
0.444
0.417
0.293
0.304
0.325
0.226
0.630
0.295
0.118
0.156
0.086
0.140
0.068
0.096
0.138
0.088
0.150
0.109
0.103
0.078
0.086
0.099
0.070
0.153
0.090
0.089
0.181
0.080
0.195
0.081
0.107
0.209
0.128
0.183
0.141
0.127
0.079
0.078
0.092
0.065
0.232
0.091
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
Whole period
GERMANY
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Whole period
HUNGARY
2004
2005
2006
Whole period
ITALY
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Whole period
THE
NETHERLANDS
1990
1991
1992
0.417
0.176
0.065 1.000
0.937
0.942
0.936
0.938
0.939
0.939
0.946
0.941
0.926
0.922
0.926
0.937
0.939
0.940
0.939
0.942
0.939
0.935
0.021
0.017
0.027
0.021
0.021
0.025
0.027
0.023
0.035
0.029
0.035
0.023
0.024
0.023
0.026
0.020
0.021
0.025
0.775
0.808
0.629
0.754
0.775
0.714
0.394
0.756
0.705
0.756
0.470
0.801
0.664
0.768
0.613
0.736
0.778
0.393
0.976
0.973
0.976
0.978
0.975
0.979
0.973
0.974
0.984
0.971
0.972
0.982
0.976
0.979
0.981
0.977
0.983
0.984
0.382
0.551
0.415
0.405
0.491
0.327
0.363
0.222
0.225
0.375
0.412
0.316
0.429
0.380
0.300
0.409
0.460
0.334
0.131
0.186
0.140
0.139
0.117
0.191
0.169
0.125
0.109
0.182
0.201
0.202
0.247
0.178
0.175
0.178
0.212
0.194
0.063
0.102
0.079
0.073
0.104
0.027
0.049
0.027
0.029
0.069
0.066
0.045
0.066
0.093
0.049
0.079
0.071
0.027
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.824
0.863
0.867
0.132
0.116
0.125
0.245
0.298
0.141
0.992
0.989
0.991
0.635
0.327
0.512
0.489
0.180
0.165
0.173
0.212
0.161
0.099
0.095
0.095
1.000
1.000
1.000
1.000
0.786
0.780
0.785
0.788
0.775
0.794
0.807
0.806
0.800
0.785
0.780
0.781
0.777
0.794
0.783
0.758
0.767
0.786
0.073
0.089
0.071
0.079
0.075
0.072
0.085
0.086
0.077
0.090
0.092
0.104
0.097
0.105
0.112
0.110
0.108
0.092
0.545
0.437
0.585
0.547
0.549
0.598
0.525
0.413
0.529
0.428
0.390
0.412
0.185
0.353
0.404
0.428
0.266
0.185
0.911
0.945
0.928
0.941
0.936
0.926
0.952
0.968
0.936
0.963
0.937
0.936
0.923
0.951
0.940
0.918
0.949
0.968
0.351
0.371
0.400
0.365
0.299
0.243
0.467
0.485
0.318
0.311
0.346
0.165
0.287
0.365
0.310
0.181
0.314
0.334
0.167
0.155
0.170
0.170
0.151
0.137
0.153
0.195
0.151
0.164
0.209
0.106
0.168
0.193
0.145
0.100
0.188
0.182
0.043
0.067
0.066
0.051
0.041
0.035
0.084
0.029
0.032
0.032
0.028
0.008
0.033
0.021
0.050
0.013
0.023
0.008
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.825
0.827
0.832
0.009 0.589 0.797 0.349
0.010 0.651 0.797 0.326
0.015 0.675 0.805 0.352
69
0.126 0.127 1.000
0.122 0.133 1.000
0.121 0.142 1.000
1993
0.826
1994
0.824
1995
0.820
1996
0.812
1997
0.829
1998
0.815
1999
0.811
2000
0.823
2001
0.825
2002
0.806
2003
0.811
2004
0.803
2005
0.800
2006
0.797
Whole period
0.818
SWEDEN
1995
0.798
1996
0.795
1997
0.786
1998
0.783
1999
0.766
2000
0.789
2001
0.777
2002
0.777
2003
0.784
2004
0.764
2005
0.763
2006
0.748
Whole period
0.776
ALL COUNTRIES
1990
0.883
1991
0.885
1992
0.879
1993
0.879
1994
0.879
1995
0.888
1996
0.897
1997
0.888
1998
0.878
1999
0.868
2000
0.874
2001
0.881
2002
0.884
2003
0.885
2004
0.881
2005
0.881
2006
0.884
Whole period
0.882
Source: authors’ calculations
0.009
0.007
0.004
0.005
0.012
0.002
0.006
0.006
0.008
0.010
0.006
0.014
0.017
0.020
0.046
0.682
0.716
0.640
0.469
0.327
0.527
0.507
0.549
0.535
0.538
0.431
0.485
0.211
0.076
0.076
0.787
0.794
0.782
0.836
0.824
0.785
0.798
0.820
0.807
0.757
0.787
0.829
0.842
0.876
0.876
0.367
0.486
0.362
0.334
0.338
0.445
0.218
0.645
0.435
0.318
0.344
0.199
0.425
0.410
0.373
0.109
0.148
0.119
0.111
0.123
0.121
0.099
0.133
0.131
0.127
0.099
0.070
0.130
0.109
0.152
0.182
0.236
0.141
0.102
0.099
0.151
0.071
0.303
0.198
0.119
0.164
0.098
0.223
0.204
0.071
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.021
0.018
0.009
0.005
0.011
0.011
0.001
0.001
0.007
0.014
0.014
0.030
0.099
0.185
0.273
0.132
0.273
0.190
0.259
0.301
0.174
0.282
0.328
0.249
0.474
0.132
0.799
0.803
0.826
0.845
0.832
0.856
0.860
0.862
0.871
0.877
0.877
0.878
1.000
0.533
0.428
0.466
0.438
0.407
0.449
0.449
0.474
0.509
0.586
0.484
0.546
0.480
0.156
0.147
0.156
0.160
0.162
0.171
0.171
0.174
0.161
0.173
0.168
0.170
0.172
0.166
0.124
0.117
0.142
0.047
0.136
0.136
0.162
0.188
0.198
0.143
0.193
0.047
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.030
0.033
0.033
0.036
0.034
0.031
0.030
0.034
0.036
0.040
0.038
0.041
0.040
0.039
0.042
0.042
0.040
0.037
0.740
0.644
0.675
0.707
0.690
0.719
0.593
0.646
0.684
0.641
0.608
0.634
0.409
0.576
0.617
0.639
0.482
0.409
0.956
0.964
0.956
0.960
0.955
0.989
0.966
0.974
0.972
0.973
0.983
0.968
0.954
0.964
0.965
0.957
0.969
0.989
0.384
0.445
0.290
0.381
0.225
0.301
0.439
0.306
0.323
0.339
0.395
0.215
0.328
0.348
0.308
0.178
0.342
0.290
0.163
0.176
0.114
0.156
0.095
0.173
0.176
0.139
0.159
0.172
0.217
0.127
0.176
0.180
0.154
0.114
0.198
0.172
0.042
0.064
0.043
0.051
0.025
0.023
0.063
0.016
0.024
0.027
0.026
0.010
0.031
0.018
0.039
0.010
0.023
0.010
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
70
Annex 9
Technical efficiency change
Crop farms (TF 1)
Years
SFA
Mean
St.
Min
Dev.
BELGIUM
1990-1991
-0.002 0.022
-0.078
1991-1992
-0.007 0.038
-0.265
1992-1993
0.004
0.033
-0.120
1993-1994
0.005
0.025
-0.084
1994-1995
-0.011 0.026
-0.069
1995-1996
-0.009 0.044
-0.248
1996-1997
0.010
0.039
-0.090
1997-1998
1998-1999
1999-2000
0.008
0.038
-0.085
2000-2001
-0.009 0.037
-0.125
2001-2002
0.016
0.046
-0.208
2002-2003
0.031
0.053
-0.183
2003-2004
2004-2005
-0.014 0.076
-0.241
2005-2006
0.009
0.061
-0.139
Whole period ESTONIA
2004-2005
0.014
0.063
-0.119
2005-2006
-0.033 0.072
-0.385
Whole period 0.081
0.095
-0.409
FRANCE
1990-1991
0.008
0.047
-0.307
1991-1992
-0.022 0.058
-0.387
1992-1993
-0.028 0.057
-0.314
1993-1994
-0.003 0.056
-0.295
1994-1995
-0.008 0.055
-0.386
1995-1996
0.003
0.055
-0.232
1996-1997
-0.005 0.051
-0.241
1997-1998
-0.003 0.050
-0.220
1998-1999
-0.013 0.052
-0.316
1999-2000
-0.002 0.052
-0.258
2000-2001
-0.022 0.056
-0.324
2001-2002
0.007
0.061
-0.312
2002-2003
-0.002 0.063
-0.408
2003-2004
-0.001 0.063
-0.298
2004-2005
-0.017 0.060
-0.540
2005-2006
0.024
0.060
-0.399
Whole period GERMANY
1990-1991
0.011
0.059
-0.236
1991-1992
-0.006 0.061
-0.421
Max
0.092
0.086
0.121
0.073
0.046
0.091
0.250
71
Mean
St.
Dev.
DEA
Min
Max
0.125
0.053
0.093
0.316
1.005
0.999
0.947
0.846
1.109
1.125
0.939
0.810
1.280
0.893
1.082
0.984
1.334
0.189
0.151
0.190
0.161
0.229
0.266
0.193
0.231
0.404
0.180
0.231
0.235
0.376
0.661
0.531
0.543
0.436
0.648
0.640
0.560
0.313
0.637
0.546
0.420
0.599
0.725
1.954
1.373
1.557
1.259
1.767
2.601
1.796
1.509
2.668
1.607
2.143
1.910
2.758
0.324
0.224
-
0.864
0.908
1.038
0.244
0.266
0.293
0.503
0.549
0.313
1.881
2.026
2.758
0.206
0.199
0.388
1.012
0.926
1.022
0.406
0.307
0.362
0.205
0.250
0.205
3.482
2.226
3.482
0.315
0.283
0.292
0.438
0.252
0.417
0.256
0.226
0.210
0.369
0.230
0.380
0.317
0.403
0.211
0.478
-
0.952
1.060
0.876
0.792
1.159
0.923
1.152
0.908
1.008
1.016
0.964
1.013
1.043
1.056
0.976
0.834
0.979
0.229
0.339
0.206
0.211
0.259
0.207
0.226
0.179
0.210
0.269
0.177
0.261
0.228
0.261
0.191
0.205
0.252
0.241
0.277
0.345
0.254
0.320
0.469
0.427
0.450
0.080
0.395
0.262
0.436
0.255
0.360
0.137
0.175
0.080
2.614
4.694
2.985
4.206
3.200
3.884
2.566
2.143
2.376
8.530
1.995
5.716
3.245
4.971
2.483
4.284
8.530
0.549
0.207
0.853
1.016
0.248
0.244
0.422
0.365
5.210
2.202
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
HUNGARY
2004-2005
2005-2006
Whole period
ITALY
1990-1991
-0.026
0.000
-0.024
0.006
0.003
-0.012
0.014
-0.009
0.008
-0.035
0.017
0.018
-0.012
0.008
-
0.072
0.069
0.073
0.069
0.069
0.081
0.076
0.066
0.066
0.077
0.088
0.086
0.066
0.067
-
-0.334
-0.473
-0.263
-0.246
-0.548
-0.526
-0.355
-0.478
-0.321
-0.545
-0.582
-0.485
-0.285
-0.386
-
0.432
0.379
0.464
0.435
0.328
0.403
0.566
0.300
0.364
0.336
0.624
0.741
0.333
0.364
-
-0.033
0.011
-
0.094
0.095
-
-0.744
-0.564
-
0.365
0.597
-
0.944
1.014
0.840
0.866
1.120
1.047
1.167
1.741
0.983
0.978
0.999
0.973
1.049
0.740
1.072
0.483
0.237
0.253
0.315
0.261
0.302
0.295
0.497
0.214
0.251
0.429
0.525
0.238
0.227
0.412
0.043
0.291
0.423
0.328
0.041
0.092
0.465
0.476
0.455
0.246
0.030
0.185
0.373
0.198
0.030
4.724
2.706
3.888
6.841
2.986
3.493
2.815
5.417
2.923
2.874
8.441
14.675
3.088
2.940
14.675
0.913
0.838
0.876
0.413
0.481
0.449
0.024
0.061
0.024
6.228
11.060
11.060
1.101
1.573
0.084
1.080
0.990
1.121
0.829
1.738
0.348
0.377
0.459
0.329
0.948
0.228
0.098
0.143
0.047
0.241
1.262
0.972
0.031
1.331
0.983
0.312
1.019
0.577
0.113
1.068
1.282
0.395
0.942
0.040
0.194
1.053
1.041
0.498
4.787
0.065
0.248
1.240
1.415
0.125
0.678
1.907
0.526
1.188
0.059
0.160
Whole period
1.142
1.062
0.031
66.30
0
4.088
4.802
7.999
4.992
13.05
1
35.36
7
39.92
1
23.11
1
4.761
38.89
6
6.535
93.47
3
56.78
5
9.204
24.14
3
93.47
3
THE NETHERLANDS
1990-1991
0.112
0.352 -0.575
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
0.013
-0.012
-0.009
-0.009
-0.004
0.070
0.055
0.068
0.066
0.081
-0.279
-0.327
-0.571
-0.470
-0.651
0.593
0.292
0.389
0.451
0.386
-0.012
0.070
-0.376
0.408
1996-1997
-0.005
0.078
-0.707
0.427
1997-1998
-0.003
0.074
-0.374
0.601
0.006
-0.004
0.076
0.073
-0.454
-0.653
0.632
0.345
0.004
0.000
0.076
0.080
-0.407
-0.530
0.645
0.540
-0.001
0.108
-0.324
0.661
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
-0.003
0.012
0.094
0.083
-0.477
-0.367
0.637
0.427
-0.002
0.083
-0.582
0.508
72
2.546
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
SWEDEN
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period ALL COUNTRIES
1990-1991
0.011
0.068
1991-1992
-0.015 0.059
1992-1993
-0.012 0.068
1993-1994
-0.005 0.065
1994-1995
-0.007 0.077
1995-1996
-0.006 0.070
1996-1997
-0.003 0.073
1997-1998
-0.005 0.073
1998-1999
0.001
0.076
1999-2000
-0.004 0.070
2000-2001
0.000
0.073
2001-2002
-0.005 0.077
2002-2003
0.006
0.076
2003-2004
-0.001 0.086
2004-2005
-0.004 0.080
2005-2006
0.005
0.080
Whole period
Source: authors’ calculations
-0.024
0.057
-0.041
0.135
0.067
-0.224
0.253
0.045
0.001
-0.459
0.502
0.089
0.115
-0.006
-0.025
0.047
0.416
-
-
-0.316
-0.353
-0.617
-0.522
-0.698
-0.470
-0.746
-0.497
-0.481
-0.693
-0.421
-0.578
-0.538
-0.535
-0.722
-0.625
-
0.640
0.337
0.442
0.475
0.438
0.634
0.474
0.636
0.672
0.446
0.684
0.594
0.687
0.686
0.474
0.559
-
73
-0.140
0.058
0.048
0.154
0.031
0.058
0.044
0.062
0.060
-0.002
0.070
0.359
0.212
0.200
0.253
0.216
0.177
0.301
0.266
0.061
0.211
0.395
0.277
0.330
0.246
0.280
0.321
-0.678
-0.457
-0.573
-0.526
-0.359
-0.614
-0.448
-0.612
-0.138
-0.767
-0.318
-0.570
-0.541
-0.580
-0.593
-0.767
1.273
0.710
0.585
0.899
1.294
0.398
1.635
1.132
0.276
0.398
2.308
1.906
1.585
0.743
1.189
2.546
1.774 -0.817
21.72
7
0.536
1.271
3.188
5.000
1.543
8.346
2.556
1.476
2.984
1.103
1.000
0.222
0.353
0.512
0.523
0.313
0.637
0.364
0.301
0.336
0.275
0.634
-0.618
-0.790
-0.873
-0.868
-0.729
-0.603
-0.540
-0.611
-0.632
-0.821
-0.873
Annex 10
Technical efficiency change
Dairy farms (TF 41)
Years
SFA
Mean St.
Min
Dev.
BELGIUM
1990-1991
-0.015 0.041 -0.177
1991-1992
0.018 0.053 -0.087
1992-1993
0.001 0.034 -0.221
1993-1994
-0.005 0.040 -0.312
1994-1995
-0.024 0.083 -0.892
1995-1996
-0.009 0.082 -0.168
1996-1997
0.017 0.036 -0.137
1997-1998
1998-1999
1999-2000
-0.001 0.035 -0.142
2000-2001
-0.007 0.049 -0.551
2001-2002
-0.017 0.053 -0.380
2002-2003
0.015 0.051 -0.136
2003-2004
-0.044 0.047 -0.095
2004-2005
-0.009 0.059 -0.182
2005-2006
-0.015 0.068 -0.425
Whole period
ESTONIA
2004-2005
-0.008 0.036 -0.211
2005-2006
-0.011 0.046 -0.226
Whole period
FRANCE
1990-1991
-0.009 0.058 -0.273
1991-1992
0.006 0.068 -0.670
1992-1993
-0.001 0.057 -0.556
1993-1994
0.001 0.046 -0.329
1994-1995
-0.006 0.048 -0.702
1995-1996
-0.016 0.061 -0.681
1996-1997
-0.001 0.058 -0.319
1997-1998
0.009 0.053 -0.279
1998-1999
-0.007 0.053 -0.547
1999-2000
0.001 0.069 -0.821
2000-2001
-0.008 0.068 -0.477
2001-2002
-0.003 0.069 -0.862
2002-2003
-0.012 0.070 -0.591
2003-2004
-0.009 0.057 -0.294
2004-2005
0.007 0.055 -0.229
2005-2006
-0.019 0.074 -0.478
Whole period
-
DEA
Min
Max
Mean
St.
Dev.
0.094
0.441
0.107
0.268
0.130
0.864
0.140
1.027
0.988
1.026
1.034
0.989
0.975
1.026
0.947
1.016
1.046
0.993
0.960
1.022
0.180
0.205
0.151
0.166
0.197
0.168
0.143
0.123
0.130
0.154
0.149
0.144
0.169
0.459
0.544
0.562
0.669
0.032
0.602
0.559
0.604
0.621
0.707
0.335
0.408
0.653
1.577
2.437
1.456
1.826
1.823
1.522
1.542
1.365
1.433
1.998
1.545
1.603
1.645
0.864
1.017
1.008
0.166
0.169
0.166
0.497
0.380
0.032
1.998
1.987
2.437
0.147
0.187
-
1.110
0.966
1.056
0.225
0.186
0.219
0.655
0.546
0.546
1.928
1.525
1.928
0.754
0.311
0.520
0.537
0.312
0.649
0.434
0.482
0.257
0.468
0.767
0.338
0.818
0.263
0.266
0.598
-
1.008
0.950
0.983
1.012
0.930
1.042
0.948
0.891
1.005
1.117
0.987
0.951
1.040
0.987
0.941
0.941
0.984
0.245
0.189
0.161
0.159
0.132
0.203
0.145
0.126
0.148
0.175
0.332
0.155
1.143
0.127
0.136
0.174
0.341
0.257
0.208
0.337
0.520
0.181
0.232
0.498
0.520
0.353
0.111
0.330
0.030
0.340
0.510
0.280
0.355
0.030
6.939
4.198
2.746
2.953
2.105
5.081
2.328
2.004
1.936
2.372
7.626
2.175
35.522
1.707
1.758
3.504
35.552
0.258
0.213
0.701
0.952
0.158
0.151
0.202
0.361
2.027
1.664
0.268
0.095
0.316
0.256
0.039
0.396
0.347
-
Max
GERMANY
1990-1991
1991-1992
-0.013
0.010
0.050
0.047
-0.409
-0.180
74
1992-1993
-0.016
1993-1994
-0.012
1994-1995
-0.012
1995-1996
-0.021
1996-1997
0.017
1997-1998
0.010
1998-1999
-0.005
1999-2000
0.004
2000-2001
-0.012
2001-2002
-0.017
2002-2003
-0.013
2003-2004
0.006
2004-2005
-0.011
2005-2006
0.004
Whole period
HUNGARY
2004-2005
0.008
2005-2006
0.017
Whole period
ITALY
1990-1991
0.000
1991-1992
-0.001
1992-1993
0.001
1993-1994
-0.001
1994-1995
0.000
1995-1996
-0.001
1996-1997
-0.002
1997-1998
0.000
1998-1999
0.000
1999-2000
0.001
2000-2001
0.003
2001-2002
-0.002
2002-2003
-0.013
2003-2004
-0.001
2004-2005
0.001
2005-2006
0.002
Whole period
THE NETHERLANDS
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
0.003
0.004
0.002
0.004
0.018
0.050
0.056
0.064
0.061
0.058
0.066
0.062
0.051
0.053
0.060
0.062
0.062
0.057
0.056
-
-0.288
-0.449
-0.397
-0.385
-0.292
-0.770
-0.382
-0.361
-0.295
-0.434
-0.392
-0.462
-0.334
-0.431
-
0.170
0.313
0.252
0.360
0.349
0.332
0.528
0.324
0.187
0.383
0.435
0.384
0.366
0.301
-
1.030
0.770
1.052
0.670
1.298
0.860
0.910
0.846
1.050
0.980
1.017
1.190
0.957
1.109
0.997
0.148
0.155
0.269
0.196
0.252
0.165
0.187
0.162
0.167
0.153
0.468
0.510
0.347
0.255
0.323
0.405
0.216
0.386
0.228
0.684
0.106
0.295
0.375
0.559
0.570
0.233
0.144
0.217
0.277
0.106
1.643
1.941
3.003
1.643
3.483
2.431
2.237
2.074
2.157
1.862
5.758
5.973
2.885
3.696
5.973
0.063
0.052
-
-0.175
-0.092
-
0.241
0.199
-
0.997
1.018
1.008
0.265
0.226
0.244
0.519
0.579
0.519
2.242
1.691
2.242
0.028
0.022
0.024
0.043
0.040
0.034
0.030
0.030
0.027
0.029
0.025
0.022
0.044
0.030
0.026
0.021
-
-0.098
-0.242
-0.433
-0.849
-0.868
-0.329
-0.460
-0.311
-0.353
-0.387
-0.133
-0.353
-0.550
-0.203
-0.194
-0.143
-
0.791
0.159
0.255
0.240
0.825
0.834
0.359
0.383
0.301
0.353
0.424
0.106
0.095
0.288
0.254
0.213
-
1.021
0.898
0.925
0.871
1.120
0.875
0.905
1.068
1.021
0.998
0.955
0.857
0.963
0.910
1.013
1.016
0.960
0.506
0.216
0.247
0.249
0.838
0.931
0.244
0.325
0.252
0.300
0.569
0.216
0.286
0.282
0.287
0.239
0.445
0.406
0.225
0.282
0.023
0.030
0.227
0.183
0.349
0.230
0.303
0.257
0.226
0.195
0.244
0.361
0.370
0.023
18.265
2.801
3.229
3.281
30.314
27.720
3.163
6.868
3.296
4.026
4.938
2.805
3.470
2.729
5.034
2.735
30.314
0.034
0.250
0.109
0.151
0.127
0.176
0.433
0.003
0.002
0.002
0.100
0.633
0.048
0.006
0.080
0.490
0.279
0.302
0.246
0.369
0.019
0.026
0.022
0.032
75
0.083
0.226
0.124
0.076
0.082
0.083
0.097
0.332
0.397
0.163
0.360
1995-1996
0.027
0.028
0.043
0.010
0.005
0.001
0.039
0.014
0.026
0.004
0.055
0.010
0.001
0.016
0.006
0.072
SWEDEN
1995-1996
0.014
0.274
1996-1997
0.004
0.226
1997-1998
0.030
0.416
1998-1999
0.005
0.072
0.259
0.231
2001-2002
0.010
0.026
2002-2003
0.050
0.324
2003-2004
0.011
0.019
0.249
0.002
0.018
0.253
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
1999-2000
2000-2001
2004-2005
2005-2006
Whole period
0.049
0.037
0.012
0.066
0.071
0.067
0.086
0.050
0.378
0.255
0.202
0.287
0.308
0.555
0.246
0.141
0.052
0.359
0.356
0.280
0.169
0.383
0.645
0.645
0.124
0.010
0.105
0.258
0.005
0.111
0.196
0.122
0.312
0.053
0.051
0.101
0.029
0.060
0.213
0.128
0.490
0.014
0.118
0.035
0.741
0.114
0.146
0.324
0.117
0.092
0.142
0.835
0.001
0.131
0.580
0.838
0.687
0.769
0.654
0.647
0.754
0.665
0.543
0.685
0.400
-
3.300
0.122
0.295
1.699
0.129
0.126
0.197
0.199
3.415
0.003
0.038
1.788
0.055
0.447
1.601
0.107
0.456
3.402
0.008
0.162
2.046
0.081
0.120
0.153
0.012
0.033
0.135
76
0.418
0.835
5.867
1.339
0.989
2.486
1.000
0.129
0.134
0.172
0.178
0.478
0.208
0.194
0.303
0.343
0.634
0.466
0.350
0.128
0.407
0.583
0.428
0.268
0.570
0.640
0.640
0.391
0.560
0.752
0.491
0.708
0.582
0.747
0.833
0.726
0.615
0.542
0.402
-
1.728
0.450
0.298
0.466
0.309
0.748
0.277
0.936
1.025
0.471
1.428
1.428
0.921
6.702
0.690
1.461
3.741
2.741
0.553
0.382
0.962
0.615
1.000
0.838
ALL COUNTRIES
1990-1991
-0.005
1991-1992
0.003
1992-1993
-0.002
1993-1994
-0.003
1994-1995
-0.006
1995-1996
-0.008
1996-1997
0.003
1997-1998
0.002
1998-1999
-0.003
1999-2000
0.002
2000-2001
-0.003
2001-2002
-0.007
2002-2003
-0.007
2003-2004
-0.002
2004-2005
-0.003
2005-2006
-0.002
Whole period
Source: authors’ calculations
0.039
0.040
0.038
0.044
0.045
0.046
0.044
0.046
0.045
0.043
0.043
0.044
0.046
0.045
0.041
0.041
-
-0.302
-0.395
-0.354
-0.726
-0.735
-0.402
-0.456
-0.636
-0.383
-0.573
-0.381
-0.690
-0.449
-0.389
-0.267
-0.354
-
77
0.833
0.657
0.271
0.331
0.304
0.655
0.732
0.301
0.538
0.398
0.381
0.509
0.335
0.668
0.355
0.335
0.368
-
Annex 11
Scale efficiency change
Crop farms (TF 1)
Years
Mean
BELGIUM
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
1.002
1.020
St. Dev.
0.085
0.087
Dairy farms (TF 41)
DEA
Max
Mean
Min
0.673
0.788
1.264
1.305
0.980
1.003
St. Dev.
0.137
0.160
Min
0.414
0.637
Max
1.998
2.188
0.948
0.990
1.096
1.061
0.901
0.858
1.193
0.931
1.006
1.008
1.160
0.114
0.100
0.148
0.125
0.113
0.170
0.308
0.100
0.150
0.148
0.291
0.589
0.634
0.827
0.640
0.560
0.313
0.706
0.575
0.483
0.682
0.726
1.432
1.256
1.597
1.535
1.118
1.423
2.470
1.313
1.428
1.662
2.469
1.014
1.012
0.962
0.999
0.999
0.971
0.984
1.029
0.992
0.947
1.028
0.114
0.099
0.121
0.096
0.083
0.080
0.091
0.118
0.107
0.101
0.126
0.561
0.785
0.030
0.602
0.768
0.655
0.623
0.666
0.335
0.526
0.705
1.456
1.660
1.359
1.465
1.346
1.254
1.282
1.921
1.414
1.519
1.663
0.920
0.965
0.129
0.166
0.516
0.607
1.355
1.732
0.901
1.007
0.140
0.154
0.452
0.472
1.569
1.896
1.016
0.190
0.313
2.470
0.995
0.120
0.030
2.188
ESTONIA
2004-2005
2005-2006
Whole period
FRANCE
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
1.026
0.249
0.294
2.788
1.061
0.125
0.869
1.514
0.948
1.005
0.155
0.212
0.377
0.294
1.512
2.788
0.975
1.023
0.105
0.123
0.691
0.691
1.525
1.525
0.952
1.078
0.886
0.840
1.121
0.947
1.098
0.935
1.042
0.993
0.969
1.015
1.037
1.052
0.993
0.858
0.986
0.179
0.288
0.152
0.185
0.222
0.162
0.174
0.132
0.158
0.181
0.130
0.201
0.184
0.226
0.148
0.176
0.201
0.235
0.308
0.356
0.250
0.272
0.510
0.443
0.481
0.107
0.437
0.262
0.344
0.256
0.374
0.156
0.175
0.107
2.720
4.694
2.364
4.199
3.174
3.040
2.675
1.754
2.060
5.609
1.869
2.742
2.906
5.002
2.451
4.064
5.609
1.010
0.991
1.009
1.007
0.976
1.018
0.999
0.966
0.992
1.076
0.979
0.939
1.075
0.989
0.966
0.959
0.997
0.215
0.157
0.128
0.117
0.093
0.157
0.111
0.104
0.100
0.141
0.221
0.123
0.299
0.103
0.109
0.155
0.355
0.292
0.252
0.444
0.535
0.226
0.344
0.494
0.547
0.309
0.165
0.351
0.028
0.030
0.482
0.280
0.434
0.028
6.770
4,464
2.838
2.341
1.706
4.347
1.790
2.351
1.668
2.372
6.144
1.991
40.722
1.467
1.574
3.504
40.722
0.961
1.079
0.118
0.186
0.502
0.419
2.628
2.024
0.851
0.965
0.109
0.077
0.222
0.538
1.422
1.381
GERMANY
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1.027
1.003
0.874
0.320
0.124
0.202
0.186
0.250
0.370
78
3.159
2.262
3.044
1.020
0.908
1.020
0.076
0.106
0.209
0.501
0.254
0.463
1.372
1.323
2.562
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
0.902
1.082
1.024
1.126
1.523
0.991
0.978
0.976
0.973
1.021
0.792
1.055
0.393
0.240
0.251
0.243
0.532
0.170
0.191
0.444
0.282
0.219
0.234
0.340
0.390
0.045
0.111
0.474
0.613
0.501
0.246
0.019
0.185
0.304
0.256
9.546
2.254
2.859
2.568
4.466
2.286
2.613
11.044
4.685
3.385
3.294
0.019 11.044
0.725
1.202
0.907
0.936
0.871
1.033
0.992
1.021
1.170
0.927
1.092
1.008
0.195
0.216
0.146
0.141
0.133
0.124
0.118
0.470
0.569
0.381
0.212
0.295
0.160
0.579
0.084
0.302
0.366
0.446
0.598
0.136
0.123
0.145
0.277
0.084
2.088
2.358
2.032
1.834
1.884
1.660
1.756
4.172
7.230
4.240
3.696
7.230
HUNGARY
2004-2005
2005-2006
Whole period
0.970
0.955
0.963
0.167
0.246
0.209
0.135
0.138
0.135
2.268
6.131
6.131
0.996
0.978
0.987
0.131
0.083
0.108
0.768
0.579
0.579
1.875
1.198
1.875
ITALY
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
1.036
1.013
1.035
1.051
0.895
1.649
1.198
1.401
0.948
1.085
1.089
1.033
1.037
1.248
0.671
1.635
0.971
0.238
0.243
0.256
0.205
0.868
0.746
1.071
0.456
0.284
0.682
0.382
4.742
1.965
0.341
0.887
1.104
0.968
THE NETHERLANDS
1990-1991
0.046
0.277
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
0.003
0.015
-0.005
0.059
0.030
-0.082
0.081
-0.008
0.004
-0.225
0.205
0.035
-0.015
0.251
0.103
0.094
0.121
0.130
0.115
0.183
0.120
0.035
0.190
0.240
0.140
0.172
0.152 28.954
0.232 4.523
0.116
0.232
0.106
0.238
0.036
0.409
0.151
0.041
0.261
0.064
0.397
0.197
0.035
0.288
3.622
4.852
3.269
12.641
27.320
49.912
21.746
4.248
28.327
9.447
93.506
90.593
6.239
12.718
0.035 93.506
0.520
0.564
-0.309
-0.382
-0.432
-0.412
-0.495
-0.425
-0.582
-0.138
-0.772
-0.256
-0.303
-0.559
79
1.013
0.963
1.017
0.946
1.103
1.000
0.964
1.025
1.023
1.007
1.041
0.921
0.956
0.959
1.032
1.017
0.291
0.144
0.164
0.152
0.598
1.108
0.176
0.142
0.148
0.137
0.393
0.136
0.157
0.163
0.211
0.180
0.458 10.986
0.455 2.339
0.455
0.057
0.045
0.220
0.328
0.431
0.400
0.479
0.290
0.258
0.332
0.334
0.487
0.388
2.238
2.013
22.038
36.351
2.780
2.157
2.310
2.574
4.593
1.808
1.925
2.299
4.427
2.571
0.999
0.368
0.045 36.351
2.448
-0.012
0.058
1.216
0.016
0.055
0.468
0.171
0.419
0.388
0.603
0.852
0.123
1.506
0.698
0.165
0.103
1.366
0.991
1.632
0.019
-0.038
-0.011
0.009
-0.002
-0.026
-0.005
0.018
0.006
-0.082
0.020
0.083
0.055
0.056
0.057
0.061
0.065
0.068
0.078
0.049
0.079
0.096
0.108
0.104
-0.216
-0.254
-0.291
-0.199
-0.596
-0.410
-0.350
-0.110
-0.407
-0.425
-0.267
-0.100
0.310
0.332
0.379
0.148
0.216
0.263
0.292
0.230
0.316
0.309
0.336
0.133
0.502
0.652
2004-2005
2005-2006
Whole period
-0.014
-0.005
0.125
0.155
-0.377
-0.487
0.618
0.877
-0.091
0.030
0.108
0.123
-0.638
-0.640
0.082
1.272
0.013
0.181
0.772
2.448
-0.004
0.086
0.640
1.272
1995-1996
0.266
0.983
0.027
0.188
-0.022
0.117
-0.110
0.158
0.557
0.810
1.826
1996-1997
- 11.821
0.640
- 0.505
0.355
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
0.006
0.002
0.085
-0.005
-0.024
-0.017
0.059
0.015
-0.031
SWEDEN
0.206
0.338
0.446
0.194
0.269
0.193
0.219
0.162
0.159
0.026
0.366
-0.814
-0.871
-0.851
-0.704
-0.502
-0.604
-0.551
-0.774
-0.641
0.871
ALL COUNTRIES
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Whole period
Source: authors’ calculations
80
0.698
3.188
5.000
1.003
2.257
1.402
1.395
1.093
0.720
1.000
0.137
0.003
0.028
-0.007
-0.018
0.013
-0.063
0.071
-0.010
0.006
0.399
0.322
0.135
0.116
0.138
0.115
0.104
0.134
0.081
0.197
-0.626
-0.822
-0.597
-0.710
-0.775
-0.644
-0.617
-0.517
-0.322
0.822
0.652
3.674
1.659
0.669
0.882
1.080
0.653
0.269
0.822
0.264
1
Annex 12
Allocative efficiency change
Crop farms (TF 1)
Years
SFA
Mean
St.
Min
Dev.
BELGIUM
1990-1991
0.002
0.018
-0.047
1991-1992
0.001
0.016
-0.030
1992-1993
-0.011
0.023
-0.087
1993-1994
-0.021
0.052
-0.204
1994-1995
0.024
0.056
-0.051
1995-1996
0.006
0.021
-0.037
1996-1997
-0.009
0.014
-0.046
1997-1998
1998-1999
1999-2000
-0.013
0.041
-0.170
2000-2001
0.004
0.025
-0.033
2001-2002
0.002
0.020
-0.028
2002-2003
-0.025
0.040
-0.135
2003-2004
2004-2005
-0.003
0.025
-0.056
2005-2006
0.006
0.022
-0.029
Whole period ESTONIA
2004-2005
0.002
0.074
-0.290
2005-2006
-0.007
0.063
-0.164
Whole period FRANCE
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period GERMANY
1990-1991
1991-1992
-
81
Max
0.059
0.032
0.033
0.037
0.224
0.075
0.026
0.032
0.072
0.054
0.090
0.028
0.050
0.335
0.313
-
Mean
0.690
1.127
0.844
1.082
0.943
1.026
0.838
1.291
1.052
0.985
0.862
0.945
0.877
0.902
1.034
0.948
0.950
1.371
1.141
St.
Dev.
DEA
Min
1.510
2.693
5.548
3.238
3.767
5.378
1.791
5.226
4.131
2.698
1.999
3.511
2.826
4.355
12.619
4.863
0.239
0.204
0.302
0.032
0.076
0.058
0.025
0.062
0.100
0.045
0.146
0.097
0.027
0.026
0.107
0.020
0.046
0.050
0.020
0.413
0.592
0.413
Max
7.984
14.533
50.471
23.278
31.083
45.294
10.417
40.455
32.055
14.441
13.750
23.333
18.875
24.233
113.833
113.833
1.986
2.298
2.298
0.812
0.223
0.238
3.610
0.781
0.266
0.199
4.212
0.736
0.193
0.130
3.156
1.485
0.332
0.379
5.611
0.964
0.211
0.256
4.234
1.080
0.215
0.287
2.945
0.985
0.244
0.323
4.587
1.002
0.207
0.237
4.250
0.846
0.199
0.232
3.348
1.022
0.209
0.230
3.620
1.212
0.235
0.307
4.600
0.937
0.242
-2.265
1.740
0.647
0.159
0.160
2.623
0.887
0.217
0.255
3.836
0.636
0.161
0.154
3.044
1.721
1.084
0.060
15.152
0.986
0.443
-2.265
15.152
2.480
1.195
1.011
0.367
0.548
0.097
12.190
5.744
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period HUNGARY
2004-2005
0.002
2005-2006
-0.014
Whole period ITALY
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period THE NETHERLANDS
1990-1991
0.004
1991-1992
-0.003
1992-1993
-0.001
1993-1994
-0.010
1994-1995
0.020
1995-1996
0.013
1996-1997
0.001
1997-1998
-0.010
1998-1999
-0.010
1999-2000
0.014
2000-2001
0.023
-
-
-
0.058
0.061
-
-0.278
-0.438
-
0.317
0.294
-
-
-
-
0.017
0.036
0.027
0.036
0.042
0.040
0.027
0.027
0.044
0.015
0.071
-0.077
-0.431
-0.139
-0.147
-0.226
-0.123
-0.104
-0.149
-0.323
-0.065
-0.190
0.126
0.094
0.096
0.167
0.196
0.333
0.155
0.116
0.174
0.129
0.431
82
0.825
0.730
0.761
1.213
0.654
1.200
0.917
0.660
1.411
0.648
0.493
1.217
1.001
1.254
0.960
0.823
1.040
0.922
1.014
0.996
1.061
0.670
1.098
0.983
0.928
0.973
0.973
0.982
1.030
0.986
1.615
1.033
0.948
1.014
0.982
0.204
0.635
0.022
0.150
-0.238
-0.135
0.595
-0.137
-0.371
0.095
0.509
0.145
0.283
0.561
0.734
0.154
0.358
0.655
0.238
0.345
0.283
0.123
0.388
0.288
0.376
0.632
0.886
0.237
0.663
7.076
2.353
0.413
0.326
0.538
0.379
0.592
0.524
0.906
0.720
0.894
1.012
3.753
0.665
0.663
0.577
2.187
1.077
2.044
0.219
0.164
0.125
0.149
0.266
0.329
0.148
0.077
0.398
0.151
0.031
0.089
0.238
0.201
0.148
0.137
0.110
0.222
0.098
0.034
0.133
0.108
0.142
0.031
0.236
0.247
0.236
0.007
0.019
0.053
0.056
0.056
0.084
0.058
0.051
0.040
0.030
0.074
0.055
0.031
0.043
0.098
0.029
0.007
-0.857
-0.874
-0.555
-0.603
-0.592
-0.734
-0.388
-0.750
-0.814
-0.396
-0.774
1.606
5.618
6.280
10.674
2.539
9.338
7.928
5.148
8.123
5.424
1.899
7.731
5.977
3.838
12.190
26.191
4.035
26.191
96.500
38.720
7.698
7.213
11.286
8.500
17.188
16.000
35.200
17.750
24.813
37.529
61.063
14.190
19.000
19.250
96.500
8.479
26.613
1.879
0.813
0.219
0.350
1.652
3.639
0.804
0.224
1.555
2001-2002
-0.006
0.067
2002-2003
0.011
0.063
2003-2004
-0.015
0.076
2004-2005
0.014
0.059
2005-2006
0.012
0.063
Whole period 0.003
0.046
SWEDEN
1995-1996
0.088
0.573
1996-1997
0.001
0.115
1997-1998
-0.062
0.179
1998-1999
0.062
0.304
1999-2000
0.049
0.293
2000-2001
0.029
0.210
2001-2002
0.033
0.316
2002-2003
0.037
0.205
2003-2004
-0.015
0.166
2004-2005
0.002
0.170
2005-2006
0.001
0.159
Whole period 0.021
0.269
ALL COUNTRIES
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period Source: authors’ calculations
-0.250
-0.361
-0.429
-0.166
-0.319
-0.431
0.411
0.355
0.566
0.305
0.245
0.566
-0.164
-0.184
-0.162
0.119
0.559
0.089
0.170
0.411
0.248
0.494
0.348
0.750
-0.801
-0.701
-0.804
-0.912
-0.720
-0.912
0.385
4.023
1.433
5.289
2.503
26.613
-0.610
-0.404
-0.726
-0.755
-0.856
-0.719
-0.471
-0.460
-0.625
-0.605
-0.631
-0.856
6.763
0.531
0.538
2.259
2.528
1.297
2.843
1.519
0.928
1.378
0.869
1.000
0.166
-0.284
0.184
-0.059
-0.109
-0.141
0.175
-0.004
-0.092
-0.156
0.243
-0.007
0.475
0.209
0.221
0.285
0.256
0.200
0.333
0.231
0.206
0.219
0.268
0.314
-0.628
-0.776
-0.476
-0.789
-0.798
-0.659
-0.350
-0.812
-0.879
-0.652
-0.885
-0.885
2.941
1.366
0.761
1.616
1.446
0.791
3.766
2.086
1.410
1.175
1.495
1.000
-
-
83
Annex 13
Allocative efficiency change
Dairy farms (TF 41)
Years
SFA
Mean
St.
Min
Dev.
BELGIUM
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
ESTONIA
2004-2005
2005-2006
Whole period
FRANCE
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
GERMANY
1990-1991
Max
Mean
St.
Dev.
DEA
Min
Max
-
0.690
1.127
0.844
1.082
0.943
1.026
0.838
1.291
1.052
0.985
0.862
0.945
0.877
1.510
2.693
5.548
3.238
3.767
5.378
1.791
5.226
4.131
2.698
1.999
3.511
2.826
0.032
0.076
0.058
0.025
0.062
0.100
0.045
0.146
0.097
0.027
0.026
0.107
0.020
7.984
14.533
50.471
23.278
31.083
45.294
10.417
40.455
32.055
14.441
13.750
23.333
18.875
0.902
0.046
24.233
-
-
-
-
0.948
4.355
12.61
9
4.863
0.003
0.005
-
0.071
0.041
-
-0.242
-0.129
-
0.396
0.188
-
1.005
1.020
1.013
0.157
0.146
0.152
0.669
0.530
0.530
1.564
1.449
1.564
-
-
-
-
1.056
0.563
0.945
0.413
0.621
0.896
0.556
1.885
0.928
0.710
0.536
0.497
0.842
0.452
1.076
0.450
0.769
0.135
0.078
0.099
0.086
0.094
0.115
0.083
0.696
0.130
0.088
0.067
0.083
0.167
0.059
0.123
0.066
0.398
0.538
0.295
0.473
0.238
0.277
0.372
0.309
0.383
0.342
0.342
0.147
0.111
0.292
0.211
0.568
0.211
0.111
2.040
1.285
1.917
2.577
1.850
1.787
2.000
6.869
1.873
1.332
1.147
1.765
3.257
1.279
1.501
1.279
6.869
0.004
0.019
-0.082
0.128
1.476
0.314
0.251
3.691
84
1.034
0.050 113.833
0.020 113.833
1991-1992
-0.005
1992-1993
0.002
1993-1994
0.002
1994-1995
0.000
1995-1996
0.007
1996-1997
-0.005
1997-1998
-0.013
1998-1999
-0.003
1999-2000
0.005
2000-2001
0.011
2001-2002
0.000
2002-2003
0.003
2003-2004
-0.001
2004-2005
0.004
2005-2006
-0.004
Whole period HUNGARY
2004-2005
0.042
2005-2006
0.006
Whole period ITALY
1990-1991
0.000
1991-1992
0.000
1992-1993
-0.005
1993-1994
-0.011
1994-1995
0.005
1995-1996
0.006
1996-1997
-0.002
1997-1998
-0.018
1998-1999
-0.018
1999-2000
0.003
2000-2001
0.000
2001-2002
0.001
2002-2003
0.026
2003-2004
0.003
2004-2005
-0.038
2005-2006
-0.002
Whole period THE NETHERLANDS
1990-1991
0.001
1991-1992
0.004
1992-1993
-0.007
1993-1994
-0.002
1994-1995
-0.004
1995-1996
-0.012
1996-1997
0.020
1997-1998
-0.017
1998-1999
-0.009
0.027
0.028
0.020
0.019
0.030
0.016
0.026
0.030
0.034
0.032
0.018
0.017
0.023
0.023
0.020
-
-0.308
-0.081
-0.098
-0.099
-0.533
-0.103
-0.220
-0.210
-0.472
-0.077
-0.098
-0.055
-0.265
-0.237
-0.089
-
0.073
0.313
0.179
0.093
0.166
0.115
0.188
0.107
0.102
0.484
0.064
0.104
0.169
0.230
0.233
-
1.153
0.939
1.360
0.551
1.449
0.993
1.086
1.120
1.282
0.874
1.027
0.947
0.952
1.070
0.891
1.046
0.204
0.132
0.263
0.241
0.380
0.216
0.171
0.341
0.321
0.173
0.243
0.218
0.231
0.269
0.206
0.341
0.104
0.327
0.290
0.167
0.346
0.176
0.164
0.225
0.260
0.215
0.349
0.203
0.258
0.323
0.197
0.104
3.285
2.501
3.118
2.639
3.546
4.762
3.041
4.627
5.129
3.681
5.806
4.368
3.580
3.469
3.402
5.806
0.132
0.109
-
-0.403
-0.581
-
0.577
0.606
-
0.929
0.913
0.920
0.232
0.169
0.199
0.525
0.460
0.460
2.257
1.392
2.257
0.094
0.086
0.069
0.068
0.069
0.072
0.063
0.074
0.082
0.086
0.085
0.096
0.085
0.108
0.099
0.082
-
-0.335
-0.280
-0.169
-0.192
-0.215
-0.306
-0.213
-0.321
-0.359
-0.283
-0.359
-0.318
-0.332
-0.353
-0.381
-0.168
-
0.204
0.284
0.178
0.260
0.211
0.156
0.157
0.319
0.207
0.347
0.199
0.398
0.280
0.306
0.423
0.319
-
0.989
1.002
1.014
0.743
1.103
0.969
0.984
0.908
0.986
1.100
1.037
1.013
1.464
1.035
0.952
1.005
0.998
0.214
0.224
0.226
0.179
0.209
0.185
0.159
0.219
0.284
0.375
1.314
0.208
0.588
0.307
0.307
0.233
0.431
0.301
0.333
0.274
0.292
0.220
0.184
0.468
0.187
0.276
0.150
0.084
0.273
0.463
0.269
0.179
0.285
0.084
4.087
6.748
3.886
2.187
3.167
3.385
3.309
4.000
8.542
10.243
13.754
2.780
4.549
3.780
5.794
3.157
13.754
-0.051
0.093
0.069
0.307
-0.251
-0.080
0.010
0.366
-0.519
0.105
0.125
0.131
0.122
0.081
0.107
0.127
0.179
0.074
-0.433
-0.686
-0.503
-0.184
-0.592
-0.456
-0.456
-0.335
-0.755
0.412
1.257
0.682
1.094
0.546
0.336
1.090
0.932
-0.188
0.027
0.015
0.022
0.018
0.028
0.041
0.045
0.033
0.032
-0.187
-0.095
-0.139
-0.115
-0.161
-0.286
-0.540
-0.240
-0.134
85
0.372
0.064
0.203
0.109
0.076
0.112
0.226
0.172
0.293
1999-2000
0.013 0.011
2000-2001
-0.001 0.051
2001-2002
-0.024 0.061
2002-2003
0.006 0.064
2003-2004
-0.007 0.067
2004-2005
-0.001 0.063
2005-2006
-0.007 0.083
Whole period
-0.003 0.045
SWEDEN
1995-1996
0.020 0.257
1996-1997
0.005 0.214
1997-1998
0.025 0.385
1998-1999
-0.007 0.243
1999-2000
0.074 0.360
2000-2001
-0.006 0.220
2001-2002
0.025 0.243
2002-2003
0.049 0.310
2003-2004
-0.007 0.239
2004-2005
0.019 0.195
2005-2006
0.000 0.244
Whole period
0.019 0.273
ALL COUNTRIES
1990-1991
0.003
0.026
1991-1992
-0.006 0.027
1992-1993
0.000
0.026
1993-1994
0.001
0.024
1994-1995
0.004
0.025
1995-1996
0.009
0.027
1996-1997
-0.007 0.022
1997-1998
-0.013 0.027
1998-1999
-0.006 0.031
1999-2000
0.007
0.031
2000-2001
0.007
0.032
2001-2002
0.002
0.032
2002-2003
0.003
0.026
2003-2004
0.001
0.028
2004-2005
0.000
0.033
2005-2006
0.002
0.030
Whole period Source: authors’ calculations
-0.042
-0.338
-0.341
-0.268
-0.158
-0.374
-0.642
-0.642
0.103
0.172
0.391
0.439
0.694
0.284
0.811
0.811
2.173
-0.328
-0.289
0.137
-0.424
1.168
-0.016
0.171
0.551
0.091
0.111
0.204
0.075
0.309
0.143
0.685
-0.061
-0.756
-0.659
-0.601
-0.796
0.242
-0.495
-0.796
4.056
-0.035
0.627
1.981
-0.092
2.555
0.531
4.056
-0.563
-0.831
-0.674
-0.760
-0.638
-0.635
-0.747
-0.654
-0.532
-0.675
-0.386
-0.831
3.125
1.629
5.433
1.292
3.310
1.710
1.535
3.282
1.975
0.962
2.404
1.000
-0.194
0.058
-0.052
-0.024
0.106
0.120
0.201
0.116
0.165
-0.182
0.148
0.048
0.134
0.155
0.165
0.148
0.194
0.644
0.637
0.167
0.162
0.133
0.200
0.344
-0.544
-0.406
-0.472
-0.874
-0.746
-0.741
-0.763
-0.466
-0.420
-0.716
-0.384
-0.874
0.366
0.865
0.819
0.376
2.014
4.192
2.968
1.378
1.416
0.685
1.994
1.000
-0.183
-0.181
-0.099
-0.168
-0.115
-0.287
-0.122
-0.178
-0.194
-0.260
-0.195
-0.191
-0.198
-0.242
-0.224
-0.120
-
86
0.116
0.187
0.196
0.157
0.163
0.109
0.102
0.152
0.121
0.228
0.276
0.216
0.166
0.178
0.223
0.190
-
Annex 14
Technological change
Crop farms (TF 1)
Years
Mean
St.
Dev.
SFA
Min
Max
BELGIUM
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
ESTONIA
2004-2005
2005-2006
Whole period
FRANCE
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
GERMANY
1990-1991
1991-1992
87
Mean
St.
Dev.
DEA
Min
Max
0.969
0.980
1.080
1.252
0.836
0.867
1.091
1.275
0.695
1.147
0.917
0.945
0.875
0.090
0.064
0.155
0.138
0.141
0.122
0.097
0.134
0.097
0.162
0.124
0.099
0.448
0.456
0.703
0.782
0.681
0.711
0.571
0.756
0.736
0.563
0.903
0.545
0.754
0.619
1.214
1.178
2.223
1.471
1.880
1.400
1.607
1.624
1.096
1.666
1.491
1.534
5.096
0.403
1.224
1.023
0.152
0.207
0.237
0.000
0.737
0.000
1.244
1.647
5.096
1.064
0.909
0.994
0.166
0.076
0.153
0.820
0.441
0.441
1.811
1.096
1.811
1.090
0.845
0.996
1.254
0.849
1.116
0.862
1.087
0.950
0.983
0.971
0.994
0.952
0.949
0.976
1.306
1.003
0.355
0.196
0.207
0.125
0.140
0.115
0.175
0.085
0.098
0.071
0.043
0.076
0.070
0.099
0.094
0.323
0.257
0.861
0.418
0.788
0.727
0.661
0.802
0.702
0.696
0.669
0.465
0.777
0.696
0.715
0.702
0.875
0.749
0.418
8.677
4.305
22.963
1.778
3.824
3.120
7.053
1.800
1.728
1.422
1.406
1.725
1.641
1.775
1.963
7.086
22.963
1.210
0.946
0.095
0.104
0.979
0.641
2.304
1.410
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
HUNGARY
2004-2005
2005-2006
Whole period
ITALY
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
THE NETHERLANDS
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
88
0.954
0.986
1.107
1.185
0.900
0.916
0.895
0.560
1.051
0.914
1.055
1.080
0.922
1.396
1.020
0.056
0.103
0.117
0.062
0.082
0.094
0.096
0.140
0.089
0.100
0.183
0.103
0.086
0.323
0.221
0.788
0.800
0.885
0.802
0.770
0.605
0.737
0.322
0.754
0.720
0.636
0.679
0.564
0.756
0.229
1.499
2.883
2.049
1.364
1.654
1.342
1.670
1.243
2.744
1.930
1.793
1.904
1.914
2.587
4.950
0.955
1.221
1.077
0.108
0.114
0.172
0.648
0.764
0.648
1.524
1.637
1.637
0.947
0.844
0.921
0.815
1.175
0.552
0.789
0.723
1.003
0.922
0.797
0.949
0.973
0.799
1.543
0.516
0.858
0.156
0.088
0.115
0.141
0.152
0.184
0.186
0.114
0.097
0.094
0.111
0.186
0.111
0.201
0.317
0.163
0.271
0.043
0.417
0.166
0.578
0.460
0.335
0.259
0.494
0.712
0.657
0.387
0.576
0.525
0.510
0.360
0.253
0.043
1.311
1.242
1.337
2.082
1.501
1.941
1.742
1.443
2.040
2.455
1.481
2.741
1.375
2.547
2.407
1.985
2.741
0.734
0.976
1.048
1.284
0.805
0.852
1.457
0.852
0.791
1.000
0.393
0.084
0.108
0.095
0.082
0.070
0.170
0.104
0.062
0.040
0.000
0.743
0.593
0.959
0.662
0.684
0.794
0.710
0.698
0.905
1.451
1.325
1.630
1.726
1.225
1.095
1.799
1.165
1.002
1.115
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
SWEDEN
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
ALL COUNTRIES
…
…
Whole period
Source: authors’ calculations
89
2.280
0.597
1.059
0.781
1.162
1.121
0.988
0.291
0.081
0.098
0.087
0.092
0.108
0.108
1.354
0.420
0.874
0.655
0.988
0.688
0.000
2.891
0.935
1.608
1.155
1.436
1.265
2.891
0.924
1.138
0.854
1.206
0.929
1.021
1.009
1.037
0.926
0.953
1.034
0.908
0.103
0.141
0.077
0.699
0.119
0.062
0.059
0.050
0.083
0.043
0.087
0.367
0.790
0.717
0.649
0.966
0.139
0.913
0.795
0.801
0.734
0.770
0.845
0.139
1.560
1.401
1.053
8.652
1.012
1.249
1.254
1.123
1.164
1.055
1.248
1.000
Annex 15
Technological change
Dairy farms (TF 41)
Years
Mean
St.
Dev.
SFA
Min
Max
BELGIUM
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
ESTONIA
2004-2005
2005-2006
Whole period
FRANCE
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
GERMANY
1990-1991
1991-1992
90
Mean
St.
Dev.
DEA
Min
Max
0.934
1.075
1.009
0.935
0.930
0.972
1.014
1.082
0.944
0.944
1.012
0.971
1.013
0.066
0.077
0.101
0.064
0.060
0.078
0.056
0.075
0.051
0.053
0.155
0.049
0.102
0.783
0.713
0.883
0.487
0.612
0.827
0.514
0.924
0.485
0.714
0.909
0.760
0.837
1.210
1.273
2.118
1.080
1.073
1.717
1.174
1.631
1.040
1.228
2.856
1.139
2.145
1.141
0.952
0.999
0.254
0.068
0.120
0.949
0.140
0.140
4.652
1.125
4.652
0.861
0.974
0.922
0.073
0.079
0.095
0.686
0.793
0.686
1.164
1.253
1.253
0.949
1.090
1.011
0.999
1.050
0.907
1.052
1.153
0.975
0.898
0.995
1.041
0.927
0.994
1.073
1.016
1.004
0.055
0.838
1.275
0.087
0.928
2.658
0.048
0.843
1.208
0.612
0.861 17.164
0.211
0.867
6.842
0.071
0.000
1.162
0.189
0.855
6.254
0.061
0.687
1.331
0.051
0.758
1.103
0.049
0.779
1.267
0.300
0.835 10.486
0.130
0.905
4.956
0.368
0.775
8.929
0.149
0.827
5.265
0.053
0.899
1.180
0.094
0.891
2.672
0.229 0.000
17.164
1.358
1.085
0.201
0.093
0.802
0.847
1.761
1.445
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
HUNGARY
2004-2005
2005-2006
Whole period
ITALY
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
THE NETHERLANDS
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
91
0.921
1.261
0.846
1.405
0.802
1.200
1.092
1.209
0.924
0.968
0.946
0.848
1.068
0.876
1.057
0.043
0.173
0.154
0.277
0.089
0.078
0.107
0.105
0.048
0.040
0.094
0.174
0.151
0.130
0.235
0.721
0.865
0.517
0.779
0.611
0.872
0.803
0.860
0.724
0.693
0.712
0.545
0.269
0.606
0.269
1.179
2.244
1.543
1.896
1.064
1.447
1.559
1.480
1.243
1.095
1.439
5.710
1.556
1.204
5.710
1.022
1.003
1.012
0.061
0.123
0.098
0.945
0.617
0.617
1.298
1.249
1.298
0.962
1.098
1.072
1.114
0.886
1.138
1.078
0.899
0.974
1.031
1.114
1.135
1.021
1.093
0.987
0.980
1.034
0.088
0.086
0.106
0.082
0.086
0.105
0.124
0.054
0.058
0.130
0.124
0.108
0.149
0.130
0.106
0.079
0.130
0.667
0.828
0.646
0.627
0.733
0.689
0.763
0.719
0.737
0.641
0.470
0.355
0.565
0.764
0.681
0.731
0.355
1.356
1.465
1.337
1.389
1.308
1.570
1.426
1.443
1.222
1.638
1.642
1.458
1.852
1.608
1.726
1.238
1.852
0.994
1.032
0.983
1.036
0.945
0.921
1.086
1.025
0.918
0.877
0.029
0.042
0.035
0.036
0.035
0.079
0.083
0.107
0.092
0.116
0.892
0.919
0.824
0.895
0.854
0.745
0.903
0.800
0.745
0.379
1.134
1.193
1.067
1.157
1.136
1.109
1.285
1.247
1.387
1.043
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
SWEDEN
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
ALL COUNTRIES
…
…
Whole period
Source: authors’ calculations
92
1.023
1.069
0.972
0.882
1.155
0.914
0.931
0.077
0.092
0.091
0.068
0.123
0.080
0.253
0.926
0.619
0.742
0.759
0.881
0.752
0.379
1.717
1.294
1.238
1.300
1.404
1.090
1.717
0.920
1.085
0.956
0.976
1.002
0.965
0.978
1.018
1.026
0.904
0.979
0.891
0.105
0.098
0.126
0.076
0.091
0.048
0.043
0.049
0.044
0.043
0.045
0.297
0.711
0.738
0.794
0.861
0.087
0.683
0.887
0.862
0.851
0.823
0.748
0.087
1.373
1.572
1.573
1.437
1.108
1.086
1.318
1.360
1.115
1.012
1.137
1.000
Annex 16
Productivity change
Crop farms (TF 1)
Years
Mean
SFA
St. Dev. Min
Max
BELGIUM
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
Mean
DEA
St. Dev. Min
0.973
0.979
1.023
1.059
0.927
0.976
1.024
1.032
0.889
1.024
0.992
0.930
1.167
0.188
0.153
0.308
0.218
0.216
0.240
0.267
0.312
0.272
0.243
0.234
0.216
0.747
0.381
0.468
0.606
0.391
0.507
0.431
0.514
0.338
0.361
0.564
0.412
0.526
0.577
1.874
1.345
2.975
1.738
1.880
2.285
2.886
2.045
1.904
2.054
2.108
1.737
8.257
0.348
3.424
1.034
0.283 0.000
0.271 0.677
0.324 0.000
2.233
1.946
8.257
1.076
0.842
1.017
0.433 0.183
0.297 0.216
0.392 0.183
3.220
2.134
3.220
1.038
0.895
0.872
0.992
0.985
1.030
0.993
0.987
0.957
0.999
0.936
1.008
0.993
1.002
0.953
1.089
0.982
0.743
0.265
0.117
0.233
0.315
0.265
0.379
0.184
0.179
0.268
0.172
0.307
0.220
0.238
0.201
0.590
0.425
0.398
0.181
0.357
0.307
0.322
0.461
0.311
0.486
0.080
0.329
0.253
0.369
0.253
0.427
0.141
0.229
0.080
19.031
5.142
40.490
4.530
8.765
5.920
13.368
2.703
2.868
8.677
2.029
9.860
3.528
4.539
4.547
15.071
40.490
1.032
0.961
0.901
1.000
0.336
0.199
0.464
0.289
0.524
0.371
0.040
0.253
7.486
1.965
4.506
5.797
Max
2003-2004
2004-2005
2005-2006
Whole period
ESTONIA
2004-2005
2005-2006
Whole period
FRANCE
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
GERMANY
1990-1991
1991-1992
1992-1993
1993-1994
93
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
HUNGARY
2004-2005
2005-2006
Whole period
ITALY
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
THE NETHERLANDS
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
94
0.930
1.027
1.007
0.960
1.045
0.975
1.033
0.893
1.054
1.051
0.968
1.033
1.030
0.289
0.342
0.226
0.245
0.264
0.195
0.222
0.230
0.410
0.631
0.221
0.254
0.331
0.464 4.186
0.422 7.228
0.041 2.601
0.084 2.998
0.375 2.740
0.269 2.291
0.452 2.910
0.245 2.570
0.041 8.216
0.206 18.093
0.338 2.945
0.278 4.335
0.040 18.093
0.873
1.023
0.943
0.343
0.576
0.479
0.025
0.069
0.025
4.610
13.454
13.454
1.043
0.911
0.911
0.913
0.974
0.959
0.996
0.962
1.022
0.984
1.022
0.999
1.013
0.991
1.046
0.985
0.980
0.856
0.266
0.331
0.375
0.359
0.423
0.523
0.635
0.583
0.359
0.686
0.496
4.554
0.991
0.656
0.508
0.770
0.016
0.151
0.086
0.122
0.041
0.114
0.021
0.187
0.115
0.032
0.130
0.093
0.283
0.124
0.085
0.067
0.016
19.544
3.621
4.775
8.264
4.879
7.120
13.180
24.952
23.972
4.079
27.413
10.497
89.436
37.845
11.888
9.281
89.436
0.734
0.768
0.958
1.021
0.720
0.726
0.873
0.899
0.709
1.000
0.623
0.774
0.393
0.400
0.425
0.522
0.408
0.405
0.501
0.437
0.354
0.064
0.686
0.345
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.832
0.000
0.000
1.000
3.000
2.000
2.000
2.000
2.000
2.000
2.000
2.000
1.000
4.000
2.000
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
SWEDEN
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
ALL COUNTRIES
…
…
Whole period
Source: authors’ calculations
95
0.953
0.704
0.860
0.959
0.829
0.518
0.404
0.554
0.440
0.461
0.000
0.000
0.000
0.000
0.000
4.000
2.000
2.000
3.000
4.000
1.274
0.798
0.602
1.335
0.952
0.937
0.837
0.945
0.868
0.824
0.812
0.908
1.586
0.430
0.480
1.884
0.600
0.436
0.694
0.492
0.389
0.488
0.487
0.821
0.000 20.412
0.000 1.640
0.000 1.876
0.000 22.590
0.000 5.845
0.000 2.861
0.000 8.864
0.000 3.733
0.000 2.269
0.000 3.985
0.000 1.996
0.000 22.590
Annex 17
Productivity change
Dairy farms (TF 41)
Years
Mean
SFA
St. Dev. Min
Max
BELGIUM
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
Mean
DEA
St. Dev. Min
0.959
1.062
1.035
0.966
0.919
0.948
1.040
1.024
0.960
0.988
1.005
0.933
1.035
0.179
0.225
0.190
0.159
0.176
0.206
0.154
0.129
0.118
0.141
0.206
0.139
0.197
0.424
0.536
0.602
0.355
0.029
0.559
0.416
0.702
0.485
0.557
0.329
0.343
0.644
1.821
2.638
2.696
1.694
1.519
2.568
1.545
1.631
1.269
1.668
2.856
1.564
2.617
0.986
0.968
1.003
0.357 0.598
0.170 0.127
0.193 0.029
5.487
1.940
5.487
0.956
0.940
0.965
0.189 0.530
0.177 0.594
0.183 0.530
1.776
1.582
1.776
0.957
1.035
0.994
1.011
0.977
0.945
0.998
1.028
0.981
1.002
0.982
0.990
0.964
0.981
1.009
0.957
0.988
0.284
0.216
0.158
0.837
0.291
0.170
0.228
0.138
0.134
0.150
0.552
0.245
1.075
0.236
0.135
0.189
0.416
0.220
0.220
0.340
0.525
0.201
0.000
0.533
0.611
0.361
0.097
0.335
0.031
0.327
0.515
0.290
0.395
0.000
8.845
4.635
2.831
24.236
7.924
4.220
6.254
2.365
1.761
2.329
15.182
7.006
28.963
7.017
1.837
3.607
28.963
0,952
1,032
0,949
0,971
0,148
0,149
0,132
0,161
0,310
0,448
0,358
0,297
2,727
2,008
1,577
2,593
Max
2003-2004
2004-2005
2005-2006
Whole period
ESTONIA
2004-2005
2005-2006
Whole period
FRANCE
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
GERMANY
1990-1991
1991-1992
1992-1993
1993-1994
96
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
HUNGARY
2004-2005
2005-2006
Whole period
ITALY
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
THE NETHERLANDS
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
97
0,890
0,942
1,040
1,032
0,994
1,023
0,970
0,949
0,962
1,009
1,022
0,972
1,009
0,191
0,176
0,178
0,191
0,184
0,171
0,147
0,144
0,454
0,491
0,365
0,145
0,258
0,280 2,201
0,389 2,534
0,446 3,375
0,123 3,116
0,338 2,592
0,453 2,323
0,476 2,111
0,559 1,813
0,256 6,283
0,107 12,653
0,199 3,096
0,231 2,531
0,107 12,653
1.019
1.020
1.020
0.281
0.251
0.264
0.565
0.576
0.565
2.162
1.911
2.162
0.982
0.986
0.992
0.970
0.992
0.996
0.976
0.961
0.995
1.029
1.064
0.973
0.984
0.994
1.000
0.996
0.993
0.527
0.236
0.227
0.269
0.719
1.030
0.243
0.284
0.233
0.273
0.654
0.231
0.301
0.280
0.270
0.231
0.445
0.431
0.244
0.282
0.028
0.024
0.236
0.241
0.300
0.238
0.355
0.177
0.187
0.187
0.264
0.362
0.361
0.024
19.322
3.359
2.846
3.555
26.182
30.801
3.583
5.933
3.268
3.775
6.868
2.912
3.427
2.881
4.832
2.544
30.801
0.800
0.855
0.771
0.778
0.799
0.726
0.919
0.842
0.830
0.888
0.504
0.856
0.401
0.394
0.412
0.408
0.345
0.388
0.407
0.331
0.333
0.148
0.519
0.293
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
2.000
1.000
1.000
1.000
1.000
1.000
2.000
1.000
1.000
1.000
2.000
2.000
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
SWEDEN
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
Whole period
ALL COUNTRIES
…
…
Whole period
Source: authors’ calculations
98
0.939
0.822
0.901
0.912
0.818
0.267
0.378
0.332
0.294
0.379
0.000
0.000
0.000
0.000
0.000
2.000
2.000
2.000
2.000
2.000
0.982
0.767
0.817
0.866
0.967
0.847
0.940
0.927
0.821
0.905
0.858
0.883
0.339
0.418
0.602
0.361
0.341
0.330
0.339
0.338
0.346
0.348
0.330
0.384
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
3.000
2.000
8.000
2.000
3.000
2.000
3.000
2.000
1.000
2.000
2.000
8.000
Farm Accountancy Cost Estimation and
Policy Analysis of European Agriculture
www.ekon.slu.se/facepa
99