LEIBNIZ INSTITUTE OF AGRICULTURAL DEVELOPMENT
IN TRANSITION ECONOMIES
Land and Poverty Conference 2016| March 15, 2016
Land Reform in Transition:
The Effect on Kazakhstan‘s Land and Credit Markets
Vasyl Kvartiuk, Martin Petrick
IAMO
Land and Poverty Conference 2016 | March15, 2016 | Washington DC, USA
Introduction
Land Reforms in the CIS:
200
o Between 1990 and 2000 145 million ha were transfered in
private ownership;
150
10 years
75 years
100
o However, the extent of reforms varies greatly:
50
o Land sales are legally limited: Ukraine, Belarus;
30 years
0
CIS
Mexico
Brazil
o Land sales legally allowed: Moldova, Kazakhstan;
o Kazakhstan implemented a set of liberal land reforms in
2003-2005.
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Introduction
The aspirations of liberal land reforms:
o Efficiency improvements;
o Better access to land for the poor.
However, transition context is known for:
o Transaction costs;
o Risk associated with vague property rights;
o Thin land markets
Land rental markets may initiate land flows and provide access to
land for undercapitalized farmers (Sadoulet, Murgai & Janvry, 2001; Deininger &
Binswanger, 2001).
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Introduction
Kazakhstan is an interesting natural experiment to observe the
effect of reforms on land rental and credit markets.
o Law on Land 1995:
o „Conditional land shares“;
o Short-term and permanent tenancy;
o Sub-leasing was possible.
o Land Code 2003 (implemented in 2005)
o Short-term and permanent tenancy and private ownership recognized;
o Sub-leasing was outlawed;
o No land distribution.
o Individual farms, households, and corporate farms co-exist;
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Research Questions
How did land reforms affect land rental markets?
What are the implications of the reform for credit markets?
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Theory
Modelling farmers’ decisions to participate in land rental market based
on Yao (2000), Vranken & Swinnen (2006), and Deininger & Jin (2005):
o Utility maximization framework;
o A farm is more likely to rent in if
o Land endowment is smaller;
o Rental payments and transaction costs are lower;
o Marginal cost of labor supervision is lower and credit constraint less strict;
o Marginal productivity of land is high (agricultural ability, nature of agriculture, climatic
conditions, etc.)
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Theory
Credit-rationing framework (Boucher et al. (2009); Petrick, Oshakbaev, & Wandel (2014))
o Quantity rationing (collateral or cash flow constraints);
o Price rationing (interest rate);
o Transaction cost rationing (bureaucratic procedures);
o Risk rationing (riskiness of returns).
One of central reform aspirations: using owned land as a collateral for
credit access.
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Empirical Strategy
Data:
o Two waves of survey conducted in 2003 by WB and in 2012 by IAMO;
o Akmola and Almaty region;
o In total 600 households, 341 individual farms and 69 commercial farms
were interviewed;
o Logit, Tobit models along with descriptive statistics and non-parametric
regressions.
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Results: Land rental markets
Meaning of land ownership in 2002:
o Conditional land shares;
o Permanent land rental;
Meaning of land ownership in 2011:
o Full ownership (permanent land rental automatically recognized as ownership after reforms);
o Conditional land shares as shares in agricultural enterprises;
o Permanent land rental.
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Dynamics of farms distribution by tenancy
status and farm type
Households
Akmola region
Almaty region
100%
80%
60%
40%
20%
0%
60%
40%
20%
0%
A
B
C
D
E
F
Almaty region
100%
80%
60%
40%
20%
0%
A
B
B
C
D
D
E
F
E
F
Akmola region
100%
80%
60%
40%
20%
0%
A
C
Individual Farms
E
F
A
B
C
D
Agricultural Enterprises
Akmola region
Almaty region
100%
80%
80%
60%
60%
40%
40%
20%
20%
0%
0%
A
2003
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B
2011
C
D
E
F
A – landless who don’t rent in;
B – landless who rent in;
C – own land and don’t rent in or out;
A
B
C
D
E
D – own land and rent in;
E – renting in and out;
F – own land and rent out.
F
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Results: Land rental markets
Who do individual farms rent in land from?
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Results: Land rental markets
Lowess smoothers of the probability of renting in for individual
farms.
Source: Authors’ elaboration based on World Bank and IAMO Surveys.
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Results: Land rental markets
Renting in behavior by individual farms
AGE (manager’s age)
EDU (manager’s education, 1 to 8 scale)
LAND (owned land, ha)
LAND2
REGION (Almaty – 1, Akmola – 0)
YEAR (2011 – 1, 2002 – 0)
LIVESTOCK (livestock index)
ASSETS (non land assets, bln KZT)
AGRIEDU (special ag. education – 1,
none – 0)
FARMAGE (number of years since
establishment)
COOP (joint activities with other farms)
PROFIT_HA (profit per ha)
Logit, Dummy for
renting in (odds ratios)
1.000
(0.994)
1.487**
(0.019)
0.999**
(0.028)
1.000
(0.257)
0.163***
(0.001)
2.815*
(0.072)
1.005**
(0.017)
0.999
(0.776)
0.613
(0.232)
1.035
(0.439)
0.818
(0.725)
1.000
(0.810)
Logit, Dummy for
renting in (odds ratios)
1.007
(0.781)
1.790***
(0.006)
0.991 ***
(0.000)
1.000
(0.285)
0.058***
(0.000)
5.430
(0.654)
1.007***
(0.007)
1.000
(0.728)
0.759
(0.539)
1.020
(0.669)
1.094
(0.878)
1.000
(0.423)
1.029***
(0.000)
0.579
(0.350)
Tobit
Thousand ha rented in
4.060
(0.877)
406.035**
(0.013)
-0.783
(0.263)
0.000
(0.732)
-1606.457***
(0.006)
1238.716**
(0.046)
3.779***
(0.001)
0.000
(0.963)
-637.434
(0.110)
35.713
(0.441)
-703.079
(0.202)
-0.153
(0.300)
Tobit
Thousand ha rented in
18.762
(0.456)
495.109**
(0.013)
-6.704***
(0.001)
0.000
(0.989)
-2381.391***
(0.000)
1859.305
(0.565)
5.810***
(0.001)
0.001
(0.189)
-397.153
(0.348)
14.134
(0.760)
-596.789
(0.234)
-0.025
(0.861)
23.594***
(0.001)
-492.295
(0.337)
267
267
267
267
YEAR*LAND
YEAR*EDU
…
Observations
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Results: Credit markets
Lowess smoothers of a probability of making investments using
loans for individual farms.
Source: Authors’ elaboration based on World Bank and IAMO Surveys.
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Results: Credit markets
Dynamics of perceived credit rationing over a decade.
Individual farms
No problems
Price rationed
Transaction costs rationed
Quantitiy rationed
Risk rationed
0%
10%
20%
2002
30%
40%
50%
2011
Source: Author’s elaboration based on World Bank and IAMO Surveys.
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Results: Credit markets
Making investments using loans by individual farms
Logit, Dummy for having made
investments (odds ratios)
0.941* (0.066)
Logit, Dummy for having made
investments (odds ratios)
0.944* (0.057)
EDU (manager’s education, 1 to 8 scale)
1.190 (0.471)
1.124 (0.597)
LAND (owned land, ha)
1.000 (0.965)
0.999 (0.311)
LAND2
1.000 (0.766)
1.000 (0.562)
REGION (Almaty – 1, Akmola – 0)
0.769 (0.433)
0.587 (0.431)
7.758*** (0.006)
10.267 (0.139)
LIVESTOCK (livestock index)
1.002* (0.075)
1.007** (0.020)
ASSETS (non land assets, bln KZT)
1.000 (0.539)
1.000* (0.089)
AGRIEDU (special ag. education – 1, none –
0)
FARMAGE (number of years since
establishment)
COOP (joint activities with other farms)
1.093 (0.640)
1.218 (0.701)
1.000 (0.141)
1.000 (0.431)
0.825 (0.739)
0.903 (0.878)
PROFIT_HA (profit per ha)
1.000 (0.646)
1.000 (0.307)
AGE (manager’s age)
YEAR (2011 – 1, 2002 – 0)
YEAR*LAND
YEAR*ASSETS
1.000*** (0.006)
YEAR*LIVESTOCK
0.977** (0.033)
Constant
Observations
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1.005 (0.266)
0.093 (0.280)
267
0.083 (0.232)
267
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Conclusion
o Reforms were a step in the right direction but not sufficient;
o Individual farms tend to rent in more land after the Reforms (more so
in Akmola region because of nature of agriculture);
o Connection between the Reforms and flows of land to more educated
producers is vague;
o Land as a collateral did not improve access to credit market;
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Implications
o In transition context land rental markets can have important
efficiency and equity implications;
o Land sales markets should be stimulated (higher rent, reduced
bureaucratic burden, etc.)
o Credit markets may need to be stimulated by other instruments;
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Land Reform in Transition:
The Effect on Kazakhstan‘s Land and Credit Markets
Thank you for your attention!
Questions? Comments?
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