Land Markets and Agricultural Efficiency in Albania
Klaus Deininger, Sara Savastano, and Gero Carletto♣
The World Bank, and University of Rome “Tor Vergata”
Abstract
We use the 2005 Albania Living Standard Measurement Survey to investigate factors affecting productivity of land
use and land market development. A stochastic frontier estimate points towards gaps in productivity but does not
support the notion that fragmentation is one of he underlying factor. We also find that rental markets help to transfer
land to more efficient producers and -contrary to what is observed in sales markets- help consolidate operational
holdings.
Keywords: Agriculture efficiency, Land markets development, Market constraints.
JEL Codes: Q120 - Q150 – Q240- O120
1. Introduction
During the past decade the countries of Central and Eastern Europe (CEE) and the Commonwealth of
Independent States (CIS) have undergone important land policy reforms. Large-scale collective and state
farms that used to be the building block of the former socialist agriculture have been replaced by new
forms of farm organizations. The process of privatization aimed at transferring land to private owners,
and at increasing effectiveness of land use by eliminating the hereditary inefficiency of the socialist largescale farming organizations.
Contrary to most of the Central and Eastern European countries (CEE), and the Commonwealth of
Independent State (CIS) of the Former Soviet Union, Albania followed a radical form of land
privatization, namely physical distribution of land among rural population and to workers of agriculture
production cooperatives and state farms. The rational for this choice was the highly concentration land
into few households prior the first agrarian reform of 1945. Albanian land privatization of 1991 was
driven more by social equity and efficiency purposes than by historical justice reasons (Cungu and
Swinnen 1999). The fear to recreate a feudal system pre-1945 with less than 3% of the population owning
land, has led to the implementation of physical distribution of land to rural population, and not restitution,
which happened in a second stage of the privatization process.
Although scholars generally acknowledge that this land distribution helped the country to avoid major
drops in output as experienced by other CEE’s, agricultural growth rates remained much below those in
The authors would like to thank The Governor of the Bank of Albania, Dr. Ardian Fullani, and Prof. Adrian Civici - from the Agricultural
University of Tirana -, for helpful advices and references, as well as to Andrew Dabalen and Carlo Azzarri for insightful comments and
suggestions. The findings, interpretations, and conclusions expressed are entirely those of the authors, and they do not necessarily represent the
views of the World Bank and its member countries..
1
China or Vietnam (Lin 1992).There is also concern that a highly fragmented land ownership has become
a drag on the rural economy and that, despite ample scope, land markets are ill-suited to help consolidate
land holdings or prompt households to move out of the agricultural sector, possibly through migration,
and foster non-agricultural development. As a result, it is often held, nearly 15 years after the start of its
land reform, Albania remains one of the poorest countries in Eastern Europe with a per capita income of
some 2,500 USD, in 2005.
To assess whether the current production structure is in line with the imperative of increasing productivity
and whether land markets help to improve land access by productive producers, we use a model of
producers who differ in endowments and skills and who face imperfect labor markets and transaction
costs -further increased by policy-induced restrictions- in the land market (Deininger et al. 2006) We
want to know whether land fragmentation reduces productive efficiency; whether operation of land rental
markets allows productive producers to increase their operational size while at the same time providing an
opportunity for those with outside opportunities with an option to exit the sector; and the extent to which
functioning of land sales markets is different from that of rental markets, possibly due to imperfections in
other markets, notably those for credit and insurance
The structure of paper is as follows: The next section reviews the evolution of land relations in Albania,
from the pre-privatization situation to the land reform process. Regional comparisons and reaming issues
in land sale and rental market are also discussed. Section three reviews the relevant literature and derives
the conceptual framework underpinning the empirical work in the paper. This is followed by descriptions
of the data and the statistics for rural household involved in agriculture activities and specific information
on rental and sale market. A subsequent section outlines the results for the determinants of land use,
efficiency and land market participation. The last section provides conclusions and policy implications.
2. Land relations in Albania: Evolution and analytical issues
Based on a description of the evolution of Albania’s farm sector, this section sets out the key questions
for subsequent analysis. Compared to other Eastern European countries, Albania’s reforms are radical,
avoided restitution, and have led to a rapid supply response. Concerns about negative long-term effects,
largely due to land market imperfections have thus far not been addressed analytically.
2.1 Collectivization and its reform
Prior to independence from the Ottoman Empire in 1912, land property was organized in çiflik et timar
where land was given under inheritable usufruct to local overlords. They could give some plots (çiflik) to
farmers under non-inheritable usufruct rights (Civici 2001). As a result, the first Albanian state inherited a
system based on latifundia where land ownership was restricted to few families. The 1945 Agrarian Law
2
started the first land reform in the country whereby private property was eliminated and land use rights
were given to landless or small farmers. Farmers were subsequently organized in agricultural production
cooperatives, followed by formation of state farms.
Under the collectivized regime which started around 1970, the large majority of agricultural land was
either in cooperatives or state farms. Private property even to house plots was eliminated with the
nationalization of all land in 1976 (Cungu and Swinnen 1999). Agricultural policy focused on achieving
self sufficiency. A large decline of productivity, food shortages, and a severe drop in welfare ensued and
in the 1980s and 90s, a number of reforms were introduced. Albania’s “New Economic Mechanism” of
the 1980s was modeled on Hungary’s model, centering on three areas, namely (i) distribution of small
house plots and under (insecure) private ownership; (ii) a decentralization and liberalization of enterprise
management; and (iii) establishment of private marketing for most agricultural produce.
Despite these measures, food production in the early 1990s dropped to levels that resulted in Albania
becoming dependent on food aid. This led to a contraction of the economy, collapse of the industrial
sector, political instability, and social disorder. These prompted, in 1991, radical economic changes
including the adoption of private property rights.1 Land privatization initially entailed distribution of
ownership certificates (tapi) to workers of former production cooperatives and state farms under the
guidance of district and village land commissions. Compared to other Eastern European countries reforms
were radical not only in the fact that farms were physically broken up and land distributed rather than just
allocating paper shares as, e.g., in Russia, and that that ownership claims predating collectivization were
declared null and void (Csaki et al. 2004).23 Reforms were implemented very rapidly and irregularities
were limited; by the end of 1992 all cooperatives had been dismantled and their land and assets
1
Law 7512, on Sanctioning and Defending Private Property, Free Enterprise, Private Independent Activities, and Privatization from August, 1991
states that “All sectors of the economy are opened to private activity including state-owned institutions and other units, with all of the following
fields of activity being converted to private property; industry, handicraft, agriculture, building, transportation, banking services…etc.”
2
Albania and Romania chose land distribution to former farm workers and farmers, and therefore private farmers are the dominant form of farm
organization that resulted after the reform (Mathijs et al. 2000, Deininger and Sarris 2002). In other countries such as Bulgaria, Czech Republic
and Hungary where land was restituted to former land owners, a consistent part of farm land is operated by former cooperatives and restructured
state enterprises. In most cases, this has resulted in a separation of land ownership from use, and a high proportion of rented land. I will be
interesting to verify in the following years how the new land law No. 9235, dated 29.07.2004 adopted by the Parliament of Albania on February
6th, 2007 with some amendments will affect the operation of land markets in the future. The existence of several conflicts over land from former
owners prior the first agrarian reform has led to the adoption of this new law. The objective of the Albanian governemnt is the ives of the
government is the acceleration of the process of property restitution and compensation. Other than the restitution of property and replying to the
conflicts of the expropriated subject entities, the State Committee for Property Restitution and Compensation will compile the Property Value
Map (PVM) for all the Republic. PVM is important in that it represents the final and decisive step for the possibility of resolving ownershiprelated problems. This map will assist the Albanian government in the creation of ideas and funds that will be needed for the compensation of
expropriated subject entities.
3
The Russian Law on Peasant Farms (December 1990) legalized private farming in order to favor the process of creation of an independent
peasant farm outside the collectivist framework. Collective land was distributed to members in the form of paper shares, and members had the
option to withdraw land plots. However, paper shares certified the entitlement of household to a certain amount of land, without specifying a
concrete physical plot. The "share conversion" process that allocates physical plots to shareholders took place in a second stage of the Reform, in
2003, with of law on land trasactions (Lerman, 2005).
3
distributed.4 Land transfers through rental were allowed and land sales to Albanians (but not to
foreigners) which had originally been prohibited, were first allowed in 1995 and regulated in 1998.
Agricultural production has increased considerably, at an annual rate of 10% throughout the 1990s, one of
the highest rates of growth during this period among the countries of Central and Eastern Europe.
Although land distribution is complete and all state farms and cooperatives have been transformed in
individual farms, the process of land titling was slower and not fully realized. Individual farming has
resulted in an important problem of plot fragmentation of land use. More than 95% of agriculture land is
used by close to half a million individual private farms with 1.9 million parcels, i.e., 3.3 plots per
household with an average farm size of 1 ha (Cungu and Swinnen 1999).
2.2 Analytical issues
While most observers concede that this strategy helped Albania avoid starvation and crisis in the short
term, there was concern about this leading to a highly inefficient and fragmented structure production in
the agricultural sector (Childress 2003). Although the number of plots per production unit in Albania
remains low compared to other countries such as China or Vietnam (Deininger and Jin 2005, Deininger
and Jin 2008), there has been concern that Albania’s land ownership structure may be too fragmented
(Lusho and Dhimiter 1998). Below, we explore empirically whether fragmentation reduced productive
efficiency and whether markets for rental or sale help transfer land to more efficient users. Before doing
so, it will be useful to identify the main channels through which fragmentation may affect productivity.
Disadvantages of fragmentation include the need for higher physical inputs due to increased labor time,
transportation costs, and limitations on access; operational problems such as an inability to use certain
equipment, greater difficulty with pest control and supervision; and social externalities associated with the
need for extensive road networks and associated land loss (Simons 1987). At low levels of mechanization,
this can be offset by advantages of a large number of plots in terms of risk diversification (McCloskey 1975)
or an ability to smooth out seasonal labor requirements (Fenoaltea 1976). Studies quantifying losses from
fragmentation in developing countries such as India (Heston and Kumar 1983) and Ghana and Rwanda
(Blarel 1992) generally estimate associated losses to be modest. More recent evidence from China is
ambiguous; different studies find a negative (Wan and Cheng 2001), insignificant (Wu et al. 2005), or
inverted U-shaped (Chen et al. 2006) relationship between fragmentation and productivity. This is consistent
with the notion that normally fragmentation will become a serious constraint requiring intervention once it
impedes the ability to use machinery on a large scale in areas with a rapidly decreasing agricultural
population (Bentley 1987).
4
In addition to that the restructuring process was lacking monitoring and resulted into inequitably distribution of cooperative’s assets: machinery,
fruit trees, farm equipment were either simply grabbed or were sold at very low prices (Civici and Lerin 2001).
4
Rural areas have been the most affected by internal and international migration. Earlier study using our
same data estimate that 30% of rural household have at least one member living overseas (in Italy or
Greece), and more than 60% of them are reported to remit (Miluka et al. 2007). Migration affects almost
all household both directly and indirectly, through the migration of relatives. Almost 90% of the
household have at least a relative that have migrated (Carletto et al. 2005), therefore creating the basis for
network relation and increasing flow of migration. The relation between migration and agriculture
development is bidirectional. On the one hand, income from remittance may be used to embark in riskier
but more profitable off-farm activities, reducing labor mobility cost, and increasing education and skills.
On the other hand, it may serve as an investment incentive for land improvement and input use, therefore
increasing agriculture productivity.
Rental markets, which have traditionally helped to bring about increased agricultural productivity in many
countries beyond Eastern Europe (Deininger 2003), have recently emerged as a major factor in Eastern
Europe as well (Vranken and Swinnen 2006). Having land markets transfer land to more productive
producers can help to improve not only efficiency but, giving land owners better rents for the land they
own, also equity (Deininger et al. 2004). Still, in an environment where land ownership is highly
fragmented, reliance on short-term rental will require coordination among a large number of landowners at
any given point in time, thus involving significant transaction costs (Csaki et al. 2002).
Land sales transactions, which could deal with the issue once and for all, may be affected negatively by
credit market imperfections and therefore unlikely to help tackle excessive land fragmentation head on to
bring about an ‘optimal’ farm size. This has traditionally provided the justification for compulsory
government intervention to address high levels of fragmentation. Such efforts, which often included a range
of developmental initiatives, have been argued to be associated with high economic returns, e.g., some 40
percent in France (Simons 1987). At the same time, experimental evidence from Vietnam suggests that the
performance of voluntary programs of land consolidation as implemented in many European countries
during the 1960s and 70s may still be sub-optimal (Tanaka 2007).
3. Conceptual framework and econometric approach
Against the backdrop we are interested whether land markets can help overcome possible productivityreducing effects of fragmentation providing more productive farmers with access to larger amounts of
land while at the same time allowing those with higher non-agricultural skills to move out of agriculture.
The latter could facilitate movement of labor out of the sector and growth of the non-agricultural
economy.
3.1 Determinants of technical efficiency
5
To identify how different factors, including fragmentation, affect efficiency of agricultural production, we
first need to generate a measure of farmers’ ability. As we have only a cross-section of farmers available,
we do so by estimating a stochastic frontier production function. Let farm households be indexed by i and
assume that production follows a Cobb-Douglas production function
ln( yi ) = β ln( xi ) + vi − u i
i = 1,2,...N
(1)
where ln( y i ) is the logarithm of output, x i is a (K+1)-row vector of inputs with ‘1’ as its first element,
β = ( β 0 , β1 ,..., β K )' is vector of parameters to be estimated, vi is a two-sided error term representing
white noise that is assumed to be normally distributed with mean 0 and variance
σ v 2 and u is a one-sided
i
non-negative error term that proxies for technical (in)efficiency. In line with the literature, we assume that
u follows a half-normal distribution with unknown mean and variance
(u ~ N [mi , σ u2 ])
that can be
interpreted as farmers’ agricultural ability. The technical inefficiency parameters (ui) are assumed to be a
function of a set of explanatory variables zi and an unknown coefficient vector δ (Coelli 1998, Coelli
2004) where the zi include the stock of perennials, the number of plots owned, the main tenure status,
household size, the head’s age, the highest level of education, and dummies for access to extension and
irrigation. Although we lack information on individual credit access, community-level distance to the
nearest bank, the mean interest rate charged, and the share of households in the community with credit
access are used as proxies for credit supply.
3.2 Rental market participation
Let household i be endowed with fixed amounts of labor ( Li ) and land ( Ai ), and an exogenously given
level of agricultural ability ( α i ). Assuming that agricultural production follows a production function
f(αi,,li,a,Ai) with standard properties, i.e. f’>0, f’’<0 with respect to all arguments and f’’lA>0.5 In an
environment of relative land scarcity, together with the cost of supervising labor (Frisvold 1994) wagelabor-based cultivation will not occur in equilibrium (Binswanger et al. 1995), implying that households
allocate their labor endowment between farming their own land (li,a) and off-farm employment (li,o) at an
exogenous wage ( wi ). We also assume that the need to obtain information on market conditions, the
negotiation and enforcement of payments, and the implicit or explicit restrictions on transferability for
certain contract types that need to be overcome imply that renting of land incurs transaction costs TCin for
5
Note that, f(αi,,li,a,Ai) is subject to constant return to scale. For example, in the Cobb-Douglass case, f (α i , li , a Ai ) = α i
1− β1 − β 2 β1
i,a
β1
is not tradable, f (li , a Ai ) = li , a Ai
β2
is subject to decreasing return to scale in land and labor (Conning and Robinson 2005).
6
l Ai
β2
. As ability
renting-in and TCout for renting-out. These transaction costs, which are expected to be reduced if a
household has a formal title, are assumed to be proportional to the size of land transferred. We also
assume that households can to structure rental contracts in a way that allows those lacking liquidity to
enter into arrangements to allow them to defer rental payments until after the harvest. With this,
household i’s decision problem is to choose Ai, li,a and li,o to solve
Max
li , a , li ,o , Ai
s.t.
pf (α i , li ,a , Ai ) + wli ,o − I in [( Ai − Ai )(r + TC in )] + I out [( A − Ai )(r − TC out )]
(2)
li,a+li,o≤ L
(2a)
li,a, li,o, Ai ≥ 0
(2b)
where p is the price of agricultural goods, r is the rental rate, Ai is the operational land size, I in is a
indicator variable for rent-in (=1 for rent-in, 0 otherwise), I out is an indicator for rent-out (=1 for rentout, and 0 otherwise), TCin and TCout are transaction costs, and all other variables are as defined above.
Assuming that the restrictions in (2a) hold with equality, the optimal choices of li,a*, li,o* and Ai* will solve
the first order conditions (FOC) of problem (2), i.e.
pf li ,a (α i , l i ,a , Ai ) = w
(3)
and for households who rent in (A* > Ai ),
pf Ai (α i , li , a , Ai ) = r + TC in
(4)
and for households who rent out (A* < Ai ),
pf Ai (α i , li ,a , Ai ) = r − TC out
(5)
and for autarkic households (A* = Ai ), r − TC out < pf Ai (α i , l i , a , Ai ) < r + TC in
(6)
Derivation and solution of the first order conditions allows us to derive demand functions for labor and
land and provides a basis for three main propositions (Deininger et al. 2007). First, the amount of land
rented in (out) will be strictly increasing (decreasing) in households’ ability, αi, and strictly decreasing
(increasing) in the land endowment Ai . This leads to the well-known factor equalization effect of land
rental whereby rental markets will transfer land to efficient but land-poor producers, thereby contributing
to higher levels of productivity and better factor use in the economy. Second, presence of transaction
costs defines two critical ability levels αl(TCout, ..) and αu(TCin, ..) such that households with ability
αi ∈ [αl, αu] will remain in autarky. Any increase in transaction costs will expand the autarky range, thus
reducing the number of producers participating in rental markets and the number of efficiency-enhancing
land transactions. Compared to a situation with no transaction cost, this will decrease productivity and
social welfare. Finally increases of the exogenously given wage for off-farm employment will imply that
7
higher amounts of land are transacted in rental markets as households with low agricultural ability who
join the off-farm labor market will supply more land.
To empirically test these predictions, we use an ordered probit model with upper and lower thresholds
that includes variables to represent transaction costs. Equations (3) to (6) imply that producers’ decision
to enter land rental markets depends on their marginal productivity in autarky, MP( A ) as compared to
the rental rate to be paid rin(T) or received rout(T) which again is a function of transaction costs. Formally,
the three regimes are defined by
I. Rent - out regime (A *i > A i ) :
II. Autarky regime (A *i = A i ) :
III. Rent - in regime(Ai < A i ) :
*

MP(A ) + ε i < r(TC out )
out
in 
r(TC ) < MP(A ) + i < r(TC )

MP(A ) + ε i > r(TC in )

(7)
A producer’s marginal product MP( A ), will depend on his or her ability (α) as derived from the frontier
production function as well as endowments with land ( A ), family labor ( L ), assets (K), and the
opportunity cost of labor which in turn will be affected by the level of education (E) and local off-farm
opportunities (O). Defining a well-behaved net earning function g(α, A , L ,K,E,O) with first derivative
g’(.),we can linearize to obtain
MP( A )=g’(α, A , L ,K,E,O)= β0 + β1α + β2 A + β3 L + β4K + β5E + β6O.
(8)
Defining an index variable yi such that yi = 1 if A*< A ; yi = 2 if A*= A ; and yi = 3 if A*> A , we can
rewrite (8) as an ordered probit model to be estimated using maximum likelihood methods. Supply of
credit will reduce transaction costs of land rental, thus narrowing the range of producers staying in
autarky.
We thus can formulate predictions regarding individual coefficients’ sign. The factor equalization implied
in proposition 1 suggests that rental markets will transfer land to more productive producers (β1>0) with
lower levels of land endowments (β2<0) and more family labor (β3>0). Labor market imperfections imply
that households with more family labor will be more willing to expand cultivated area. The hypothesis of
wealth bias in rental markets, possibly due to credit market imperfections, translates into β4>0. To the
extent that education drives towards better off-farm opportunities, we expect that higher household with
better level of education will be less likely to rent in (β5<0) and that higher levels of non-agricultural
wages, proxied by O, will make renting in less likely (β6<0).
Because we do not have detailed information on non-agriculture wages and given the importance of
remittances in total household income, we introduce the average share of household in community who
8
migrated to assess as a proxy for the presence of off-farm labor markets. We complement the analysis
with additional household characteristics, such as the age of the household head which we expect to be
negatively (and possibly in a non-linear way) related to the probability of renting in more land.
3.3 Sales markets
If households do not face subsistence or borrowing constraints, i.e. can fully insure against risk, have
access to the same information set, and can transfer land without additional cost, markets for land sales
will not be different from those for land rental. Demand for land would be determined by producers’
ability to make best use of the land in farming and relative land endowments and the amount as well as
nature of land transfers will enhance social welfare by allowing small producers with higher levels of
productivity to bid land away from large and less productive land owners (Zimmerman and Carter 1999).
Land prices would equal the net present value of the stream of profits from the best available land use,
and potential buyers would be indifferent between renting land and purchasing it.
Policy-makers’ concern about land markets leading to socially and economically undesirable outcomes is
rooted in three observations, namely that (i) imperfections in credit and insurance markets will affect
decisions on whether or not to participate in land sales markets, with subsistence constraints of particular
relevance. (ii) transaction costs will vary with producers’ access to different types of information; and (iii)
land may be acquired for speculative purposes unrelated to its use in agricultural production. The relevant
considerations guiding households’ decisions on land sales or purchases in the context of their choice of
an optimal asset portfolio over their life time horizon have been illustrated in a large literature (Deaton
1991, Rosenzweig and Wolpin 1993, Fafchamps et al. 1998, Dercon and Krishnan 1998). The decision
problem faced can be illustrated by considering the option of holding two assets, one, e.g. land, with high
returns but that is also risky and illiquid, and another one, e.g. grain, with lower returns but less risk and
higher liquidity. At every point in time, households choose a combination of these two assets that will
maximize utility over the entire lifetime, subject to limits for borrowing and an overall budget constraint.
While an analytical solution to this problem is impossible unless more structure is imposed, numerical
simulations show that with credit market imperfections and risk, households’ need to satisfy basic needs
of subsistence can give rise to land being supplied to the market by producers who are forced to sell under
duress in bad years, often to individuals with access to non-covariate income streams outside the local
rural economy or large amounts of assets (Zimmerman and Carter 1999). In high-risk environments this
may lead the poor to rationally prefer assets that offer lower but more stable returns to land even if
transaction costs were modest and credit access was no problem. With imperfect credit markets, some
households will be able to buy and accumulate land not because they would be more productive but due
to their ability to better overcome such market imperfections (Carter and Salgado 2001, Zimmerman and
9
Carter 2003). Similarly, others may be forced to sell land in exchange for less risky assets to minimize
their exposure to risk even though they would be able to make more productive use of the land than those
who acquire it (Rosenzweig and Binswanger 1993). Thus, in addition to productivity, macroeconomic
conditions, expectations of future land price movements, lack of sufficiently attractive alternative assets,
and policies, all are factors that can compound, and possibly overwhelm, the impact of innate productivity
on households’ land sales market participation. 6 We model these two sets of factors that will affect land
markets in a rather independent manner in our ordered probit estimation as discussed below.
A direct consequence of this is that the productivity- and equity impact of land sales market operation will
depend on the extent to which other markets function and net effects of land sales markets are ambiguous
a priori and will have to be decided empirically. If risk is negligible or credit markets work well, one
would expect land markets to equalize factor endowments and transfer this factor to more able producers.
In fact, this seems to be confirmed by evidence from Paraguay (Carter and Galeano 1995) and Guatemala
(Barham et al. 1995) where sales markets in the context of an export boom transferred land to more
productive producers. 7 In fact, in central Uganda, land sales were found to perform a redistributive role
(Baland et al. 2007). Similarly, starting with a relatively egalitarian land ownership distribution, land
sales markets in Vietnam helped to improve efficiency and equity by transferring land from large and less
productive owners to more productive smallholders (Deininger and Jin 2008).
On the other hand, in regions where covariate shocks such as floods or droughts are prevalent, one would
expect the outcome of land market transactions to be more ambiguous. Comparing neighboring villages
from Bangladesh and India, it is found that, while in those that had access to safety net programs, the
majority of land sales were undertaken to undertake productive investments, in places where such safety
nets to smooth consumption were absent, the majority of land sales were prompted by distress to obtain
food and medicine. In Chile, capital market access soon led to re-concentration of land through sales
markets (Echenique and Rolando 1991, Carter and Salgado 2001), something that may also underlie the
phenomenon of land concentration observed in a number of African countries (Jayne 2003).
Formally, let latent demand for land under agricultural production be determined by producers’
agricultural ability α, their initial land endowment A , stock of labor L, and capital K. Latent demand for
land then will depend on long-term productivity which can be expressed as a reduced form equation
f’(α, A ,L,K,O)= β0 + β1α + β2 A + β 3K + β4L+ β5N + εi
6
(1)
For example, inflation and changes in real returns on alternative uses of capital were shown to be key factors explaining changes in land prices
in the United States. In Eastern Europe, the expectation of large capital inflows due to EU accession was a major reason underlying real estate
booms that propelled land prices far beyond the net present value of the flow of services that could be derived from the land (Deininger et al.
2004, Csaki et al. 2004)
7
Note that his is not universal and that the impact of export booms depended significantly on local conditions (Barham et al. 1995)
10
Thresholds for the transition between sales and autarky and autarky and purchase are defined as follows:
pS(T) = η0 +η1C+η2(C×S) + η3Z
(2)
pB(T) = δ0 +δ1C+ δ2(C×S) + δ3Z
(3)
where C denotes credit access, in particular banks, Z is a vector of other characteristics, and β, δ, and η,
parameters to be estimated. Factors affecting the extent of participation in the main equation are the level
of ability and the household’s endowment with land, labor, and assets,. We expect β1 > 0 and β 2 < 0 as
high levels of ability increase producers’ marginal product and their competitiveness in land markets
while standard assumptions for the production function imply a negative relationship between land
endowment and marginal product. Higher agricultural ability or lower land endowments will make it
more (less) likely for a household to shift from autarky to being net purchaser (seller) of land. In addition,
as imperfections in credit and labor markets imply that higher levels of wealth or family labor will
increase a household’s marginal productivity, we expect β 3>0, β4>0, and β 5>0.
4. Data sources and descriptive statistics
4.1 Characteristics of the rural economy
Our data are from the 2005 Albania Living Standard Measurement Survey, conducted on a sample of
3,840 households in 480 enumeration areas (EAs) from April to November 2005 by the Albanian Institute
of Statistics (INSTAT) in collaboration with the World Bank. Below, we focus on the sub-sample of
(1,849) households who engaged in agricultural production. Descriptive statistics, as illustrated in column
1 of table 1, illustrate that the rural population is older, less educated, and poorer than the average even
though household size is, with 4.6, close to the mean. With an average per capita income of 960 US$,
rural incomes are significantly poorer than the population as a whole, consistent with the notion that
poverty is concentrated in rural areas (World Bank 2007). Total output value amounts to $ 1802 per ha.
At the same time, disaggregation of income by source illustrates that, even in rural areas, agriculture and
livestock contribute only 40% of total income. The importance of transfer- (32%) compared to wage(22%) and especially self-employment income (6%) points towards limited scope for rural economic
activity. Concerning agricultural production, we note that, with a mean of 0.81 ha, households’ land
endowment is limited. At the same time, with an average of 3 plots, fragmentation does not seem too
much of an issue and only 47% of the small farmers have a legal title over the land they own.
Land was acquired mainly through privatization (70%) or inheritance (30%). However, activity in rental
markets is increasing; according to our survey, 10% of rural households were involved in such markets
with 6.22% renting in and 3.62% renting out in 2005. Participation in land sales markets is much lower by
11
comparison (6.65% who purchased land in the entire 2000-2005 period). The sample is unbalanced; only
1.57% of households reporting to have sold a plot of land and many sellers are likely to have left rural
communities in a phenomenon that is familiar from other countries (Deininger and Jin 2008).
4.2 Distinguishing by type of land market participation
Descriptive statistics with the sample split by households’ land rental market participation status (rent in,
rent out, or remain in autarky) are reported in columns 2-4 of table 1. Results from t-tests for equality of
means between the overall sample and the three different regimes, namely autarky, rent-in, and rent-out,
respectively, are indicated by stars.
The data provide some support to the notion that rental markets help to equalize factor markets. Tenants
are on average 10 years younger than landlords and there are marked differences in family size, with
tenants have 1.5 more members than households who rent out (5.1 vs. 3.5 members). Both highlight that
land markets have an important function in transferring land across generations and to those with higher
levels of family labor. At the same time levels of education do not differ significantly by status of rental
market participation. Similarly, land rental appears to have little impact on land consolidation; in fact the
number of plots owned by tenants is slightly larger than that of landlords or those in autarky.
A strong redistributive effect is also supported with respect to per capita income; those renting out have,
with US $ 1,204, a level of welfare that is some 50% higher than that of tenants ($ 803). Decomposition
of income by sources points towards a very high share of income for landlords (54%) coming either from
remittances or other transfers, compared to only 26% for tenants. This is consistent with other studies that
found that wealthy families are more likely to migrate (Stampini 2005, Miluka et al. 2007). By contrast,
landlords and tenants obtain 12% vs. 49% of their income from crops and livestock and 13% vs. 6% from
off-farm self employment that may be riskier but also more profitable.
The value of output per hectare (2150 US$/ha) for tenants is much larger than for all households in the
sample (1800 US$/ha) and almost an order of magnitude higher than what is achieved by landlords ($
275). Part of the difference is due to the fact that tenants have higher levels of irrigated area (0.86 vs. 0.27
for autarkic and 0.07 for landlord households). Still, with profits per hectare by tenants more than double
those by either households in autarky or landlords, descriptive statistics suggest that rental markets do
transfer land to more productive producers, something that is to be explored using econometric methods.
Most farmers renting out received a deed from 1991 (91%), with the remainder having received land
documents during the 1946 agrarian reform which may be less secure. As the survey contains little on
credit availability for individual farmers, we use the community-level distance to the next bank. Although
the fact that banks’ choice of location is endogenous precludes us from interpreting this as a causal
12
relationship, survey data suggest that proximity to banks is much higher among those who participate in
land rental than among those who do not.
Despite the previous regime made massive investments in irrigation and drainage between 1950 and
1975, the breakdown of cooperatives and state farms created a need for institutional changes in
management and operation of the irrigation and drainage systems. Surface irrigation is the primary
method in Albania, and small family farms suffer from the lack of an entity responsible for coordinating
and monitoring the distribution of water, collect water charges, and organizing operation and
maintenance. As a result, irrigation matters for deciding to embark in agriculture activities. Household
renting in land have three times more irrigated land compared to household renting out land which seems
to suggest that household that want to embark in agriculture activity are using rental arrangements to
consolidate their holding and being able to access to irrigated land.
Because sale market is still at an early stage of development we prefer to mention just the main
characteristics of households involved in the sale market. The demand for land comes from younger
household head, with more years of education. Family size does not represent a distinguish factor among
type of households. To be noted that the demand for land in the rental market comes from individuals 3
years younger than household head in the sale market. Although households who purchase land seem to
experience large revenue over land, compared to household who sell but especially compared to the
demand of land in rental market, they seem to spend much less on input. This suggests that land is used
for growing main crops and most of the income come from off farm activities. In fact the share of income
from wage or from self employment of households who purchase land is almost 50% of total household
income. This suggests that sale market is used for residential purpose, whereas rental market is used to
embark in agriculture activities.
5. Econometric results
5.1 Determinants of productivity of land use
Table 2 and 3 report results from estimation of the stochastic frontier and determinants of agricultural
efficiency. Coefficients on land endowment, share of land irrigated, labor, and traditional inputs are
highly significant and positive while our, admittedly coarse, measure of agricultural capital (a dummy for
a water pump and number of machinery), has the expected sign but remains insignificant. Productivity
differences are pronounced; as results from estimating the stochastic frontier production function in table
2 indicate, 48% of observed variation in farmers’ output can be attributed to technical inefficiency.
Results regarding determinants of technical inefficiency in table 3 provide a number of interesting
insights. First, presence of perennial crops and, even more importantly, having received extension advice,
13
has a very large and highly significant efficiency-enhancing impact of one third and two thirds,
respectively. Efficiency is also much higher (by about one third) on land that has been inherited,
presumably due to farmers having been able to acquire knowledge about the fertility potential and
limitations of specific plots. Similarly, higher age is estimated to have a clear productivity-enhancing
impact, with each additional year increasing the level of productivity by 0.8 percentage points. Second,
the fact that both household-level education and receipt of remittances are associated with significantly
lower levels of efficiency (with every additional year reducing efficiency by some 4 points and a 10%
increase in transfer income resulting in a 5 percentage point reduction of efficiency) suggests that, rather
than to help farmers overcome credit constraints, off-farm occupation and migration detract attention
from farming. Third, and quite surprisingly, the highly significant coefficients on the number of plots and
its square point towards an ‘optimum’ level of fragmentation rather than an automatic productivity
decrease due to this phenomenon. The coefficients suggest that productivity is predicted to increase in
plot number up to a total of about 3.8 plots, and decrease thereafter, suggesting that tenants (but less so
those in autarky and those who rent out) operate at the optimum fragmentation level. Finally, we note that
distance to banks that can provide either government or private credit has a significant, but quantitatively
quite small productivity-enhancing impact.
5.2 Determinants of land market participation
Results from the ordered probit regression for land rental market participation as reported in table 4
support insights from descriptive analysis but also provide additional insights. To interpret coefficients,
recall that the dependent variables takes the value of 1 for renting out, 2 for autarky, and 3 for households
renting in land. The main equation points to three results of interest. First, whereas in other settings rental
transfers land from large to small producers, in the Albanian context of highly equal land ownership,
rental helps to consolidate holdings by providing an opportunity for larger land owners to get additional
land. At the same time, and consistent with descriptive evidence, it does transfer land to households with
younger heads with higher family labor endowments. By contrast, neither households’ initial wealth nor
the local infrastructure index have a significant impact. Second, the Albanian setting, migration is a key
determinant of land rental market decisions; those living in communities with higher incidence of outmigrants will be significantly more likely to rent in land. Finally, results in column 2 which include our
measure of agricultural ability derived from the stochastic frontier production function suggest that more
productive producers are significantly more likely to rent in land, in line with the hypotheses that rental
markets help to bring land to more productive users, thereby not only helping those who remain in rural
areas to enlarge their farm size but also to increase overall productivity.
14
Results from the threshold equations imply that, consistent with expectations, the legal status of the land
but not he way in which it was acquired (i.e. inheritance or redistribution) is of relevance as a determinant
for renting out but does not have any impact on renting in. This can be explained as a consequence of the
risk of not getting back land that has been rented out and the fact that having formal title reduces this risk
significantly. At the same time, we find that greater distance from banks has a separate and positive
impact on renting in, possibly as a result of out-migration.
Results from the sales market equation suggest that sales markets work indeed quite differently from
those for rental. Contrary to what was observed there, they are estimated to transfer land to smaller
owners with lower labor endowment, and with no discernable impact of agricultural ability. The fact that
higher levels of infrastructure increase the frequency of land sales, together with the finding that in both
the threshold equations better bank access is estimated to increase land sales activity suggests that what is
observed in sales markets may be less related to agriculture and more to other factors.
6. Conclusion and policy implication
Scholars have long been concerned whether Albania’s radical reform that provided households with very
equitable access to land, while acting as a safety net in the short term, had a negative productivity effect
by inducing levels of fragmentation that were too high and that impeded the functioning of markets for
land rental and sales through high transaction costs. Using the 2005 Albania LSMS, our analysis suggests
that there is little reason for such concerns. First, we find no evidence for a decrease in productivity with a
larger number of plots; to the contrary, the optimum number of plots from our estimates is somewhat
(though by no means significantly) below the average, suggesting that, at least at present, efforts to
introduce consolidation might generate high costs but little benefits. Second, we note that rental markets
not only transfer land to more productive producers but contribute to consolidation and increased incomes
in rural areas.
The above analysis is essentially static in nature and we have no information on land-related investment
as well as the level of resources and effort expended in establishment and maintenance of land-related
infrastructure (e.g. irrigation channels). Similarly, insight on the nature and in particular the length of
contracts and possibly changes in this parameter over time would be of great interest to analyze whether
land rental reduces land-related investment, thereby possibly introducing a dynamic inefficiency. We also
know little about the nature of transfers and the links to migrants. Exploring these issues in greater detail
would not only be of conceptual interest but also help to provide advice for Albania’s rural sector in the
future.
15
Table 1: Descriptive statistics for entire sample and by rental market participation
Total
Sample
Rent out
Autarky
Household Characteristics
Head’s age (years)
52.21
56.49***
52.35
Head´s education (years)
7.94
8.3
7.88*
Household size
4.63
3.51***
4.65
Income and its composition
Per capita income (US$)
959.41
1204.06**
960.34
… from wage (%)
0.22
0.21
0.21
… from self employment (%)
0.06
0.13**
0.06
… from transfers-other (%)
0.32
0.54***
0.32**
… from crops (%)
0.15
0.05***
0.15
… from livestock (%)
0.25
0.07***
0.26
Agricultural Production
Total land owned (ha)
0.81
1.06***
0.77***
No. of plots owned
3
3.22
2.93***
Irrigated area (ha)
0.3
0.07*
0.27***
Value of ag output (US$/ha)
1802.28
275.91**
1839.16
No. of machines
9.11
0.22
9.16
Land acquisition and documentation
Land is privatized (%)
0.7
0.91***
0.69***
Land is inherited (%)
0.3
0.13***
0.31***
Dummy has deed from land since 1991 (%)
0.72
0.96***
0.71***
Dummy has deed from land since 1946 (%)
0.2
0.09**
0.22***
Distance to bank (km)
3.85
1.51
4.09**
No of observations
1849
67
1667
Source: Own computation from Albania LSMS 2005.
Stars for T tests on the equality of means *significant at 10%; ** significant at 5%; *** significant at 1%
16
Rent in
47.65***
8.54*
5.10***
803.47**
0.19
0.06
0.26**
0.18
0.31**
1.24***
3.83***
0.86***
2157
13.61
0.71
0.25
0.76
0.08***
1.77*
115
Table 2: Estimation of stochastic frontier production function
Log Total Value
of Ag. Production
Log ha of land owned
0.470***
(3.57)
Log land irrigated
0.019**
(1.98)
Log value of hired labor
0.053
(1.64)
Log number of family members working on farm
0.329***
(4.44)
Log cost of total inputs except hired labour)
0.496***
(19.09)
No. of machines
0.001*
(1.78)
Dummy has water pump
0.005
(0.04)
Constant
4.796***
(21.61)
Observations
1796
Sigma v
48%
Notse: Dependent variable is total value of agricultural production. Dummies for districts included throughout but not reported.
Absolute value of z statistics in parentheses: * significant at 10%; ** significant at 5%; *** significant at 1%.
17
Table 3: Determinants of technical inefficiency
Technical Inefficiency
-0.438***
(-5.56)
0.030***
(3.12)
-0.334***
(-2.82)
0.041***
(3.52)
-0.008***
(-3.06)
-0.041***
(-2.09)
-0.327
(-1.31)
-0.644***
(-3.86)
1.042***
(8.30)
0.003
(0.80)
-0.068
(-0.67)
-0.364***
(-4.03)
No. of plots
No. of plots squared
Perennial crop dummy
Education (highest year in household)
Head’s age
Household size
Dummy has participated to an irrigation program
Dummy has received soil advices
Share of transfer income
Length of possession
Dummy has deed from land since 1991
Dummy land is inherited
Community level variables
Interaction of distance to bank and access to credit from govt and private bank
-0.015***
(-3.37)
Interest rate for getting a loan to start a small business at the community level
0.002
(0.41)
Dummy source of credit within the community
0.100
(1.12)
Constant
3.479***
(12.59)
Absolute value of z statistics in parentheses: * significant at 10%; ** significant at 5%; *** significant at 1%
18
Table 4: Ordered probit regression for land rental market participation
Rental Market
Total land owned
0.196***
(3.06)
0.244***
(7.13)
-0.015***
(4.04)
-0.010
(0.72)
-0.093
(1.24)
-0.019***
(2.72)
-0.059
(1.20)
0.054
(0.52)
0.177***
(2.74)
1.009***
(5.58)
0.234***
(6.87)
-0.016***
(4.30)
-0.011
(0.81)
-0.100
(1.29)
-0.016**
(2.26)
-0.035
(0.69)
0.062
(0.61)
0.962***
(3.17)
-0.154
(0.72)
-0.011
(1.33)
0.036
(0.24)
1.035***
(3.38)
-0.110
(0.52)
-0.012
(1.39)
0.006
(0.99)
Agriculture ability
Number of family member working on farm
Age head of hh
Years of education head of hh
Wealth index
Average share of hh in community who migrated
infrastructure index
Dummy conflict over land in community
Lower Bound (rent out to autarky)
Dummy has deed from land since 1991
Dummy land is inherited
Distance to nearest bank (km)
Access to bank credit (com’y level))
Upper Bound (autarky to rent in or purchase)
Share of deeded land in community
-1.206
-1.172
(1.08)
(1.03)
Distance to nearest bank (km)
0.009**
0.010**
(2.04)
(2.05)
Access to bank credit (com’y level))
-0.132
-0.122
(1.07)
(0.04)
No. of observations
1796
1796
Dummies for districts estimated but not reported. Robust z statistics in parentheses (*, **, and ***:sig. at 10%, 5%; and 1%.
19
Table 5: Ordered probit regression for land rental market participation
Specification
Land owned
Without ability
-0.239***
(3.83)
-0.091*
(1.96)
-0.003
(0.74)
0.001
(0.06)
-0.077
(1.03)
-0.009
(1.23)
-0.106*
(1.87)
-0.014
(0.14)
2.136
(1.22)
With ability
-0.232***
(3.78)
-0.223
(1.08)
-0.086*
(1.81)
-0.002
(0.71)
0.000
(0.03)
-0.077
(1.02)
-0.010
(1.32)
-0.111*
(1.96)
-0.016
(0.15)
2.462
(1.31)
0.659
(0.37)
-0.252
(1.02)
-0.017*
(1.82)
0.070
(0.35)
-0.753
(0.39)
-0.262
(1.05)
-0.020*
(1.83)
-0.166
(0.35)
Agricultural ability
Number of family member working on farm
Age head of hh
Years of education head of hh
Wealth index
Average share of hh in community who migrated
infrastructure index
Dummy conflict over land in community
Constant
Lower Bound (sell to autarky)
Share of deeded land in community
Dummy land is inherited
Distance to nearest bank (km)
Access to bank credit (com’y level))
Upper Bound (autarky to purchase)
Share of deeded land in community
-0.704
0.648
(0.61)
(0.39)
Distance to nearest bank (km)
0.020*
0.017*
(1.84)
(1.85)
Access to bank credit (com’y level))
-0.173
0.070
(1.38)
(1.32)
No. of observations
1796
1796
District dummies included throughout but not reported. Robust z statistics in parentheses (*, **, and ***:sig. at 10%, 5%; and
1%.
20
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