1. Effects of Land Rights Certification on Rural Credit Market and the Market for Land Transfer
--Evidence from China
Longyao Zhang1 Wenli Cheng2 Bi Wu3
1 College of Finance, Nanjing Agricultural University, China
3 Department of Economics, Monash University, Australia
3 RCRE, Ministry of Agriculture of China, China
22 March 2017

2. Why property rights are important?
Introduction
Why property rights are important?
Better property rights institutions lead to improved economic outcomes (see North and Thomas,1973; Knack and Keefer,1995; and Acemoglu, Johnson, and Robinson, 2001).
De Soto (2000) have argued that the major barrier to prosperity in developing countries is the inability to convert property into usable assets, because of a lack of clear-cut legally recognized rights.
According to Deininger and Jin (2006), the theoretical effect of an improvement in the security of land-rights includes:
Providing stronger incentives for long-term investment
Promoting land transfers to more efficient producers
Improving access to credit …

3. Land titling programs in developing countries since 1980s
Introduction
Land titling programs in developing countries since 1980s
Land titling is increasingly considered one of the most effective public policies to benefit poor populations and encourage economic growth.
The World Bank and governments have sponsored various programs to systematically register land or to improve land administration in many countries.
Asia: Thailand (distribute 8.7 million land titles since early 1980s); Vietnam (issue land titles since 1993); Indonesia (1.87 million land titles , )…
Latin America: Peru (the largest urban titling program aimed at squatters, 1.2 million titles, in 1990s); Brazil (title 750,000 families, since 2003)…
Africa: Uganda (transition from customary to titled freehold landownership, the Land Act of 1998); Rwanda (land tenure regularization program, deliver titles for all land parcels by 2013)…

4. The importance of issuing titles to land is inconclusive.
Introduction
The importance of issuing titles to land is inconclusive.
The evidence on the impacts of land title on credit access is not clear:
Positive effect: Feder et al. (1986) and Feder (2002) in Thailand; SMERU Research Team (2002) in Indonesia; Petracco & Pender (2009) in Uganda; Piza et al. (2016) in Brazil
No effect: Boucher et al. (2005) in Nicaragua & Honduras; Field & Torero (2004) in Peru; Galiani & Schargrodsky (2006) in Buenos Aires; Do & Iyer (2008) in Vietnam; Ali et al. (2014) in Rwanda
Conditional positive effect: Carter & Olinto (2003, AJAE) in Paraguay, wealthier producer with land > 15ha; Besley et al. (2012, QJE) in Sri Lanka, nonlinear and heterogeneous by wealth group, and the extent of competition between lenders, the de soto effect

5. Introduction
The potential reasons for mixed empirical evidence of the impact of land titling on credit access:
Demand side: risk aversion and risk rationing of the agricultural producers (Boucher et al., 2008 AJAE)
Supply side: small land scale and high transaction costs; lack of political and legal environment and make foreclosure virtually impossible; lack of a liquid market to dispose of collateral (Deininger, 2003)

6. China’s land reform since 1978
Introduction
China’s land reform since 1978
Historical reforms since 1978
Household Responsibility System in 1982, land use contracts were for 15 years in The term was extended to 30 years in 1998.
The Law on Land Contract in Rural Areas in 2002 granted four rights to the household: the right to transfer, exchange, rent and subcontract
Land titling reform since 2011
Under the Property Law adopted in 2007, rural land use rights are property rights to be registered as immovable, which provided impetus for the Ministry of Agriculture to implement further land titling reforms beginning in 2011
Land titling provides legal verification of households land rights
Permission to use land rights as collateral
Reforms are implemented at the level of selected villages. Land titling proceeds village by village and applies to all households in the selected villages

7. China’s land titling reform since 2011
Introduction
China’s land titling reform since 2011
Left: Graphical part of village land parcel
Right: Farms put fingerprint on the land titling map (Taogouqiao village in Shandong)

8. Introduction Research question
In this paper, we use a new data set to address an old and basic question, namely: how an improvement of land-rights security can affect household credit access and land transfer in rural China?
More specifically:
How the recent rural land titling experiment in some pilot areas of China has affected households’ ability to obtain credit, both formal and informal credit?
How the recent rural land titling experiment in some pilot areas of China has affected households’ land rental activities, both renting in and renting out land?

9. Empirical challenges and strategies Identification issues
Introduction
Empirical challenges and strategies
Identification issues
The problem of the counterfactual
If we simply compare outcomes with only a point observation after the treatment, then it is impossible to reach a conclusion about the impact and cannot attribute causal impact of the program
Need for a proper comparison group (treated and non-treated groups)!!!
The problem of the selection bias
Treated and Non-treated groups might not be the same pre-intervention. So expected difference between groups might not be solely because of the intervention.

10. Empirical challenges and strategies
Introduction
Empirical challenges and strategies
Taking the gradual implementation of land titling in China as a natural experiment
Using the difference-in-differences (DID) approach to estimate the impact of land rights certification, by comparing the difference between 2010 and 2015 (before and after the reform) for treatment groups as compared to control groups
Treatment groups: villages that have implemented policy experiment of land titling
Control groups: villages that are geographical similar but not running the policy experiment of land titling
Selection bias test: whether there are any observable systematic differences between treatment villages and control villages?

11. Data
Introduction
Data
Empirical analysis
Conclusion

12. Data
Introduction
Data
Empirical analysis
Conclusion

13. Annual survey by Research Centre for Rural Economy (RCRE), the MOA
Data
Annual survey by Research Centre for Rural Economy (RCRE), the MOA
Annual national survey at both rural household and village levels in 31 provinces; known as Fixed Rural Observation Point System (FOPS)
FOPS annual survey began in 1984, but 2010 and 2015 selected
Panel data covers 23,000 rural households from 360 villages of 31 provinces
Supplementary survey in 2015 to FOPS, RCRE and NAU
Conducted in December, 2015 to January, 2016
Villages which are allocated both in the national experiment areas for rural land reforms and within the FOPS----Treatment villages
Within the FOPS other villages which are geographically similar to the treatment villages but were not running the experiment---- Control villages

14. Data
The distribution of treatment and control villages in 2010 and 2015
The dataset covers 40 villages in 36 counties of 17 provinces, and
includes 1,938 households for 2010(before), 2,073 households for 2015(after).

15. Empirical analysis
Introduction
Data
Empirical analysis
Conclusion

16. Table 1. Village characteristics differences in 2010
Empirical analysis
1. Testing endogeneity in the assignment of treatment villages
Table 1. Village characteristics differences in 2010
Variables
All villages
Treatment
Control
Difference N
(1)
(2)
(3)
(4)=(2)-(3)
Total cultivated land (mu) 36
Per capita cultivated land(mu)
1.68
1.30
1.95
-0.64
Share of land rented out
0.09
0.10
0.08
0.02
Share of labor working outside
0.35
0.40
0.31
Share of grain growing area
0.72
0.60
0.80
-0.20**
Per capita net income 28
Level of economic development
2.70
2.56
2.81
-0.25 37
Distance from main road
2.01
1.69
2.21
-0.52 33
Share of hardened road
83.84
85.90
82.86
3.04 31
Whether suburban
0.19
-0.00
Whether hosts town government
0.14
Whether poverty village
0.13
-0.02
Terrain: Plain
0.50
0.00 40
Hills
0.32
0.33
Mountainous
No. of Observations 18 22

17. Empirical analysis Pr（Treatment group = 1） Variables （1） （2） （3） （4）
（5）
（6）
（7）
ln（Total cultivated land）
-0.10
(0.20)
-0.04
(0.23)
Per capita cultivated land(mu)
-0.18
(0.16)
-0.13
(0.18)
Share of land rented out (2010)
1.20
(1.78)
-0.30
(2.06)
0.26
(2.07)
Share of labor working outside of village
2.26*
(1.23)
1.94
(1.51)
2.03
(1.40)
Share of grain growing area
-2.35**
(1.00)
-2.38*
(1.39)
-2.02
(1.46)
Level of economic development
-0.41
(0.32)
-0.37
(0.33)
-0.43
-0.42
(0.35)
-0.26
(0.36)
(0.38)
-0.16
(0.39)
Whether suburban
(0.66)
-0.21
(0.65)
0.04
(0.60)
0.14
(0.71)
-0.29
(0.72)
-0.32
(0.74)
Whether hosts town gov.
0.41
0.48
(0.78)
0.37
(0.68)
(0.63)
0.27
(0.75)
0.00
(0.73)
0.05
Whether poverty village
-0.24
(0.67)
-0.28
(0.64)
-0.02
(0.69)
-0.07
0.42
0.53
(0.80)
0.56
Terrain: Plain
-0.11
0.01
0.36
0.45
(0.70)
0.98
(0.85)
1.12
(0.92)
Hills
-0.01
0.10
0.16
0.32
(0.83)
0.47
(0.89)
Pseudo R2
0.06
0.18
0.19
No. of observations 36 34

18. Baseline specification(household level)
Empirical analysis
Baseline specification(household level)
: the dependent variable of household in village of
province in year
Household access to formal credit and informal credit
Household land rent-in and rent-out
: dummy variable, 0 for year 2010 and 1 for year 2015
: dummy variable, 1 if the village has completed land rights
certification and 0 otherwise
:Other control variables for observable household and village
characteristics

19. Descriptive Statistics (Household Level)
Empirical analysis
Descriptive Statistics (Household Level)
2010 Survey
2015 Survey
All
Titling
No titling
Diff
Mean
t-Stat
（1）
（2）
（3）
（4）
（5）
A: Credit access variables
Has formal loan
0.03
0.02
0.04
2.900***
Has informal loan
0.06
-2.477**
B: Land transactions
Rented-in land（mu）
0.85
1.06
0.64
0.99
1.414
Whether land rented in
0.11
0.10
0.15
0.09
-4.200***
Rented-out land（mu）
0.88
2.16
0.92
-0.486
Whether land rented out
0.19
0.42
0.23
0.17
-3.121***

20. Controls and Province FE
Empirical analysis
The effects of land rights certification on access to formal credit
Dependent variable=1
If household have access to formal credit
No Controls
Province FE
Excluding attrition
Households
With
Controls
Controls and Province FE
(1)
(2)
(3)
(4)
(5)
Title×Year
0.398**
0.361*
0.352*
0.534**
0.447*
(0.187)
(0.212)
(0.188)
(0.243)
(0.249)
Year
-0.460***
-0.520***
-0.462***
-0.753***
-0.815***
(0.111)
(0.135)
(0.208)
(0.210)
Title
-0.358***
-0.289
-0.312**
0.013
-0.119
(0.123)
(0.125)
(0.174)
(0.272)
Province fixed effects No
Yes
Prob>Waldchi2
0.000
No. of Observations
4,011
3,130
3,920
3,534
2,835
Robust standard errors in parentheses.

21. Controls and Province FE
Empirical analysis
The effects of land rights certification on access to informal credit
Dependent variable=1 If household have access to informal credit
No Controls
Province FE
Excluding attrition
Households
With
Controls
Controls and Province FE
(1)
(2)
(3)
(4)
(5)
Title×Year
-0.570***
-0.549***
-0.537***
-0.618***
-0.625***
(0.184)
(0.179)
(0.187)
(0.202)
(0.200)
Year
-0.184*
-0.227**
-0.187*
-0.330***
-0.356***
(0.106)
(0.103)
(0.107)
(0.127)
(0.130)
Title
0.250**
0.487***
0.217**
0.324***
0.655***
(0.102)
(0.131)
(0.119)
(0.194)
Province fixed effects No
Yes
Prob>Wald chi2
0.000
No. of Observations
4,011
3,806
3,920
3,534
3,251

22. Empirical analysis
Land right certification had the effect of increasing the probability of households obtaining formal credit
Increase effective demand for credit and investment
Lower the risk of credit and increase loan approval rate
Land rights certification reduced the probability of households gaining access to informal credit
The increased access to formal credit
Positive wealth/income effect

23. The effects of land rights certification on renting in land
Empirical analysis
The effects of land rights certification on renting in land
Dependent variable=1 If a household has rented-in land at the end of the current year (stock)
Dependent variable=1 If a household rented in land during the current year
(flow)
Dependent variable: Area of rented in land
at the end of the current year
(stock)
Dependent variable: Area of land rented-in during the current year
(1)
(2)
(3)
(4)
Title×Year
-0.270**
-0.012
-4.966**
-0.704
(0.134)
(0.170)
(2.137)
(2.676)
Year
-0.195*
-0.115
-1.606
-1.518
(0.107)
(0.141)
(1.793)
(2.395)
Title
1.007***
0.521***
15.601***
7.835***
(0.148)
(0.180)
(2.635)
(3.008)
Province fixed effects
Yes
Pseudo R2
0.194
0.160
0.109
0.100
Number of observations
3,448
3,163
3552

24. The effects of land rights certification on renting out land
Empirical analysis
The effects of land rights certification on renting out land
Dependent variable=1 If a household has rented-out land at the end of the current year (stock)
Dependent variable=1 If a household rented out land during the current year
(flow)
Dependent variable: Area of rented out land
at the end of the current year
(stock)
Dependent variable: Area of land rented out during the current year
(1)
(2)
(3)
(4)
Title×Year
-0.233**
-0.346***
-1.484**
-2.934**
(0.105)
(0.124)
(0.706)
(1.213)
Year
0.591***
0.244**
3.811***
2.306**
(0.085)
(0.099)
(0.602)
(0.962)
Title
-0.142
0.349***
-1.513**
2.748**
(0.131)
(0.722)
(1.292)
Province fixed effects Y
Pseudo R2
0.210
0.189
0.093
0.113
Number of observations
3,551
3,552

25. Possible explanations:
Empirical analysis
Surprising results: negative association between land rights certification and land rental market activities!!!
Possible explanations:
Omitted variables, such as village land reallocation
More willing to rent out to specialized agri producers, such as agri companies , modern farms and agri co-operatives
Increase transaction cost of land transfer

26. Conclusion Conclusion
The effects of land rights certification on rural households’ access to credit and land rental market activities in China
Land rights certification improved rural households access to formal credit and reduced their reliance on informal credit
There seems to be a negative association between land rights certification and households’ participation in both renting out and (to a lesser extent) renting in land

27. Conclusion
More questions raised…
How land rights certification has affected (1) households’ demand for credit, (2) the expression of their demand; (3) the extent of rationing in the market for credit; (4) the use of collateral in loan applications?
How land rights certification has affected (1) renting out to non-relative, such as agricultural companies, modern farms or rural co-operatives; (2) land transfer after taking the administrative land adjustment into account? (3) the transaction cost of land transfer?