Securing Property Rights:

Evidence from China’s Rural Land Contracting Law and India’s Land Reform

Klaus Deininger and Songqing Jin

Motivation for Security Land Rights• Importance for development

– Determine investment incentives & efficiency of resource use

– Factor market development– Credit access and insurance substitute – Reduce conflicts

• Lack of such institutions often hurts the poor disproportionately

• Empirical support: Importance of property rights– Similar jurisdictions w diff’t institutions: Colonization

policies across countries & different land policies within India.

– Firm level data from Eastern Europe & China– Household level analysis finds a significant link between

property rights and investment.• But, little evidence on institutional change

– Adoption of good institutions far from automatic– Powerful interests can forestall beneficial change

Legal context in China• From collectivization to Household responsibility

– Collectivization in 1950s and 60s, disastrous consequences– Re-establishment of individual farming 1978 with big impact– But tenure remained highly insecure

• Post-1978 measures to increase tenure security – Extension of 15-year to 30-year contracts in 1998– Issuance of written certificates – Limited impact on tenure security

• Key problem: Unchecked power of local officials – Ability to reallocate land source of corruption– “Over-conversion” of land to provide resources for local

government– Source of conflicts and riots– Exacerbated by conflict of interest (leaders also resolve dispute)

• Key provisions of the RLCL (March 2003)– Puts transferable 30-year land contracts on legal basis – Prohibits “large” reallocation, clear conditions for “small” one (Art.

27)– Clarifies that the collective can not take land from individual users

without providing compensation determined by agricultural production (Art. 16)

– Makes it possible to redress for violations through the courts rather than only through administrative means.

Objectives of China’s RLCL study

• Two indicators used for the analysis:

– Whether or not a reallocation in contravention of the law (“illegal reallocation”) did occur and

– The amount of compensation received by households whose land was subject to expropriation, e.g., for infrastructure or private commercial use.

Hypotheses on impact of RLCL

• Will strengthen property rights in two dimensions– General security against internal redistribution– Amount of compensation in case of land

taking/expropriation– More effective if leaders are elected– Re-election increases leaders’ accountability

(repeated game)– Puts limits on amount of rent to be extracted– Will help with implementation of legal reform

• Knowledge of law important for effects to materialize – Ability to assert rights also depends on knowledge – Dissemination efforts by higher level governments

Data sources

• Two rounds of survey: NBS sample villages – First round 2003: 1,200 villages & 12 questions for

households– Follow-up in 800 villages in 2005

• Household survey – Quiz (8 questions) on knowledge of law: Leader & 10 farmers– Up to 4 households affected by land takings/expropriation– Amount of compensation paid (& other party) in case of

taking

• Key variables (2 periods) – “Illegal” land reallocation; Compensation paid in case of

taking – Village institutional conditions & income; reallocations from

1999 – Households’ knowledge of law, availability of certificate– Characteristics of land & process in case of expropriation

Estimation strategy (China)

• Illegal reallocation at village level (j)– Rjt or Ajt = α + βDt + γGj + δ(DtGj) + ρKj + θTj + ηEj +ξPj+εj

• Rjt = 1 if illegal reallocation occurred during period t, =0 otherwise• Ajt = area affected by illegal reallocation during period t• D = reform dummy; G = elections; K = Knowledge; T = certificate; E =

village characteristics

• Compensation at plot level – Cijt = α + βDt + Ej + δ (DtGj) + …+ εj

• Cijt = level of compensation for plot i that was acquired away in period t • Other variables include plot, household, village characteristics to

capture quality of land, type of takings, local economic condition and other factors that potentially determine Cijt

• Endogeneity of elections – Mandatory since 1998 but not implemented everywhere – Can depend on unobserved factors affecting reallocation– Issue discussed in other studies (Lin et al.; Zhang et al.) – Instruments: Previous leaders’ length of tenure (also squared &

interacted with reform dummy)

Village characteristicsTotal N, NW Coast Center SW

Households 427 507 327 423 439

Agric. (%) 78.61 80.20 51.02 86.91 90.14

Income pc (Y) 2989 2940 4596 2525 1983

Land pc (Mu) 1.24 1.89 0.97 1.17 0.94

Vill. inc. (10,000 Y) 22.41 15.66 58.25 9.55 4.87

From land (%) 36.53 38.97 37.16 10.47 45.59

Election (%) 70.18 70.11 75.72 64.89 68.16

Certificates (%) 82.81 66.50 86.86 84.36 93.04

Know big r. (leader; %)a 53.41 67.93 38.73 39.36 58.74

Know small (leader; %) 17.80 13.04 17.34 25.53 18.83

Know big r. (farmer; %)a 53.31 65.52 40.26 33.51 60.78

Know small r. (farm.; %)a 19.32 19.62 23.66 26.49 12.90

Admin. reallocations

Total N, NW Coast Center SW

Reall. after 2000 (%) 28.67 31.50 40.32 23.23 19.41

Area affected (mu) 745.74 1417.57 382.21 655.02 443.56

HHs affected 151.9 221.6 115.0 137.3 131.7

Before RLCL 13.18 13.78 18.96 12.11 8.69

After RLCL 8.31 10.27 9.89 6.32 6.36

“Illegal” before RLCL 6.15 5.75 12.10 4.04 2.74

“Illegal” after RLCL 3.46 4.00 6.99 1.01 1.27

Reason population (%) 45.42 43.48 47.78 50.00 41.51

Reason taking (%) 24.88 22.22 22.67 13.64 37.78

Takings: aggregateTotal N, NW Coast Center SW

Villages (%) 29.47 19.10 40.56 19.00 34.18

HHs affected 88.14 94.51 116.87 52.05 65.24

Before RLCL (%) 16.59 10.38 23.08 12.39 17.60

After RLCL (%) 22.52 13.68 31.62 16.81 23.97

Infrastructure (%) 51.39 52.94 35.94 48.48 69.37

Jobs generated (%) 28.01 30.71 31.43 26.32 24.33

Project completed 65.84 72.55 59.84 81.82 64.86

Project started 88.54 94.12 79.69 96.97 93.69

Linked to reall. (%) 27.95 35.29 18.75 48.48 29.09

Money comp. (%) 82.37 72.44 82.08 89.47 85.88

Y/mu before RLCL 13177 6056 21805 4881 8988

Y/mu after RLCL 17557 7627 28463 7648 11640

Vill. retains some 39.01 31.37 59.38 42.42 18.02

Takings: Household level

Total N, NW Coast Center SW

Area lost (mu) 1.23 1.52 1.33 1.06 1.05

Net inc.(Y/mu) 781 526 1148 616 639

Received $ (%) 82.37 72.44 82.08 89.47 85.88

Received land (%) 41.25 51.18 35.24 35.09 42.59

Y/mu before RLCL 6642.2 4258.7 7272.1 2655.3 7669.4

Y/mu after RLCL 8949.8 5649.8 11642 5003.3 9154.0

Welfare improved 22.91 19.69 12.04 31.58 31.66

… comp’n 16.77 30.77 18.42 19.05 10.98

…. job 55.69 50.00 63.16 52.38 54.88

Welfare worsened 18.36 24.41 19.91 10.53 15.83

… comp’n 60.00 62.86 50.91 33.33 75.61

…. comp’n & other 40.00 37.14 49.09 66.67 24.39

Det’s of “illegal” reallocation (IV) Probit Tobit

Reform dummy (β) 0.088 3.410

Leaders elected (γ) -0.048 -6.262

Election*Reform dummy (δ) -0.126 -9.415

Leaders’ knowledge of law -0.019 -2.735

Share of households w. certificate

-0.011 -1.486

Village per capita income -0.004 0.364

Share of agricultural income 0.017 2.022

β +δ -0.038*** -6.041***

Wald test of exogeneity, chi2(2) 3.31 0.85

Det’s of compensation levelsOLS IV_Tobit

Value of production (Y/mu) 0.639*** 0.711***

Land next to nat./prov. road 1.127*** 1.556**

Share of land received -2.329*** -2.562***

Village income (log) 1.916*** 1.806***

Reform dummy (α) 1.016 -0.017

Public land use dummy (σ) -1.781*** -1.305*

Public land use*Reform dummy (δ)

1.509** 0.662

Share with certificates 0.810* 1.179**

Leaders elected (β) 1.433*** 4.279

Election * Reform dummy (γ) 0.130 1.939

β+ γ 1.563*** 1.922***

σ+δ 0.272 -0.643

Wald test of exogeneity, chi2(2) 1.61

Key findings• While RLCL can not slow down the pace of land

takings, it however significantly increased the amount of compensation paid to households for the loss of land

• RLCL is effective in reducing illegal reallocation and raising the amount of compensation only if the officials are elected, pointing towards complimentarity between good governance and legal reform.

• RLCL also helped to eliminate the discrimination against public takings

• Knowledge of law is negatively related to illegal reallocation

• In terms of land value, reform would be predicted to increase land values by slightly more than 30% in areas where leaders are elected.

Broader relevance

• Long-term impacts– Investment, intensity of land use and agricultural

productivity– market development, contract types, change in farm

size, etc.

• Impact on labor markets– Participation in local non-farm labor markets and

migration

• Economics crisis– Role of land in farmer’s ability in copying with crisis– Does property rights reform help or hurt the poor

during the crisis?