Land Policies and Land Reforms in India: Progress and Implications for the Future

Klaus Deininger

The World Bank

and

Hari Nagarajan

National Council of Applied Economic Policy Research

Prepared for Presentation at tbe Brookings-NCAER India Policy Forum 2007New Delhi

July 17-18, 2007

Conference DraftNot for Citation

Land policies and land reforms in India:

Progress and implications for the future

Klaus Deininger1, Hari K. Nagarajan2

1 World Bank, Washington DC, USA

2 National Council for Applied Economic Research, New Delhi, India

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Land policies and land reforms in India: Progress, and implications for the future

Abstract: Perhaps not surprisingly, given the serious and harmful long term consequences of the land ownership inequality established and maintained under colonial rule, land policy in India has been heavily focused on state-led land redistribution. We argue that greater reliance on markets can help achieve original land reform goals. Data from the 1982/99 ARIS/REDS are used to demonstrate that (i) the productivity-impact of rental markets is very positive; (ii) they transfer land to the poor on a large scale; and (iii) state-level rental restrictions have a large negative impact on supply of land for rental. These data also show that sales markets have been much less biased against the poor than often argued. To prevent an unraveling of the gains from land reforms, provide the basis for well functioning land markets, and avoid that insecure property rights develop into an obstacle to future growth and poverty reduction, more attention to land administration is needed. A review of different states’ experience in computerizing their land records and automating registries highlights differential progress (including scope for leapfrogging by latecomers), helps identify the elements of a comprehensive system, and points towards ways of addressing them in a way building on India’s comparative advantage. The paper concludes by drawing out implications for policy and research.

1. Motivation and background

Land reforms have for a long time constituted a central element of India’s policy for rural poverty

reduction and growth. However, given that most of the relevant policies were put in place long time ago

and that high levels of economic growth continue to profoundly transform India’s economic landscape but

also create new demands for land policy, questions on the continued adequacy of such policies and a

potential need to refocus overall policy and implementation have emerged. A key justification for India’s

land reform policies was that (i) markets on their own will not accomplish the redistribution of land to the

poor and marginalized that is necessary to overcome the legacy of deprivation, increase productivity, and

move towards greater equality of opportunity and that (ii) bureaucratic action can accomplish this goal

more effectively and at a lower cost.

While this is likely to have been the case true when such measures had been conceived, the pace of land

reform implementation has slowed considerably while economic growth and government policies to help

backward regions advance have helped to attenuate many of the market imperfections that provided the

justification for government intervention. Despite restrictions on their functioning in many states, markets

for rental of land have picked up considerably. However, empirical evidence on the extent to which they

contribute to increased productivity and the impact of policies on their functioning remains limited.

Three observations suggest that more detailed exploration of this issue may be of relevance. First, with

about 15 million farm households participating in land rental even according to existing data, the number

of households who access land through rental markets every year exceeds that of those who obtained land

through land reforms, defined as either tenancy reform or redistribution of ceiling surplus land,

throughout India’s entire post-independence period. Second, economic development is both a cause and a

consequence of increased demand for land transactions. However, in marked contrast to China, where,

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despite a much more egalitarian distribution of land, the amount of land rental increased more than four-

fold between 1995 and 2001, the amount of rental transactions in India shows a steady and secular decline

since 1971, with the share of households involved in land rental in 2001 (11.6%) less than half of that 30

years earlier (25.8%). As in China land rental has been shown to be not only critical for farmers to take up

non-agricultural employment but also to be associated with productivity increases of about 60%, this

could indeed have far-reaching consequences. Although more detailed analysis will be required, the fact

that a recent survey shows that 29% of owners leave all or part of their land fallow during the main

growing season in Karnataka and Tamil Nadu while 15% do so in Bihar -all states where tenancy is either

explicitly prohibited or made impossible by the fact that tenants acquire permanent rights to the land they

cultivate- is consistent with the notion that such legislation could indeed have non-trivial productivity

impacts the magnitude of which is likely to increase over time.

In this context, this paper has tow goals. First, noting that much of the debate has been based on

ideological prejudice more than on rigorous and representative quantitative evidence, we use unique

household-level data from NCAER to provide evidence on the functioning of land rental and some extent

sales markets to assess not only the extent to which these contributed to higher productivity and improved

land access but also how reform-related regulations have affected operation of land markets and the

associated economic outcomes. Second, as markets depend on the extent to which property rights are

clear, well defined, and information on them is available and their transfer and enforcement is possible at

low cost, we assess the extent to which India’s system of land administration provides the elements

needed for an optimum functioning of markets with the goal to draw lessons from advanced states on the

extent to which IT-related opportunities can help to make land reform policies more market-friendly

while at the same time improving overall service delivery in the land sector.

2. Do rental restrictions affect productivity of land use?

In this section, we describe the rationale for and characteristics of rental restrictions in India, sketch out a

framework that allows us to make predictions on their impact, test the extent to which these notion are

borne out by actual data, and draw conclusions for policy.

2.1 Origins and nature of rural tenancy restrictions in India

Under colonial rule, the main goal of India’s land administration system was to obtain government

revenue. The de facto award of land rights to revenue collectors (zamindars) in large parts of the country

has consequences that affect development to this day (Banerjee and Iyer 2005). Agrarian reform was thus

at the top of the immediate post-independence agenda and the fact that land was put under the

competence of states rather than the Center led to considerable diversity in the timing, substance, and

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implementation of reforms across states. Abolition of rent-collecting intermediaries was tackled swiftly

and successfully virtually everywhere. However, ceiling legislation -aiming to legislate a maximum land

holding and force owners to dispose of all that was owned beyond this limit- and tenancy reform -which

had the goal of limiting the rent to be paid for land and prohibiting tenant evictions- took a long time. 1

The existence of wide variations in legislation across states provides ample scope to analyze the impact of

such policies on outcomes. To do so, we use the share of households who benefited from key policies as

an indicator for policy-induced constraints to the operation of rental markets. Specifically, we construct

for each state the share of households who were awarded tenancy rights and the share of ceiling surplus

area that was actually transferred to beneficiaries.2 As none of the Indian states permit sub-leasing of

lands to which tenants had received permanent rights and most states also impose restrictions on transfers

of land received in the course of implementing ceiling legislation, this is proxies for direct restrictions on

the operation of land rental markets. Both figures provide an approximation for a state government’s level

of implementation effort, a variable that is exogenous to households’ decisions (Banerjee et al. 2002).

A detailed look at the time dimension of this effort allows a number of conclusions (Kaushik 2005). First,

even without accounting for abolition of intermediaries, land reform was a major effort; up to 2000, it

resulted in the transfer of almost 10 mn ha, 2.5 mn ha via ceiling surplus redistribution and 7.35 mn ha via

tenancy legislation.3 However, after a spurt in the 1970s and early 1980s, implementation slowed down;

in fact between 1995/96 and 2003/04, i.e. for almost a decade, progress almost completely halted.4

2.2 International evidence and conceptual framework

Although empirical evidence on the impact of rent ceilings and other forms of tenancy control in rural

areas is limited, the issue has been analyzed in urban contexts where rent control is a textbook example

for policies that transfer resources from landlords to sitting tenants in the short term but that will be

associated with inefficiencies in the medium to long run (Arnott 2003). The key reason is that, by fixing

rents below their equilibrium level, controls reduce the supply of new housing (or maintenance of existing

1 The fact that implementation started in earnest only after 1972 allowed landlords to “prepare” by resuming self cultivation, evicting tenants or transforming them into wage workers, or implement spurious subdivisions. Using census figures, Appu (1997) estimates that, to avoid having to give rights to tenants, landlords evicted about 30 mn tenants or about one third of the total agriculturally active population, similar to evidence from other countries with similar policies (Deininger 2003). 2 We use area rather than beneficiaries because in some cases ceiling surplus land was distributed to a collective entity such as a cooperative so that the number of beneficiaries would be misleading. Also, the existence of large discrepancies between the amount of land expropriated and actually distributed -which is due to the fact that in some cases land that had been distributed could not occupied by beneficiaries or was taken back after some time- led us to focus on land actually distributed. 3 The amount of land involved is much larger than what was redistributed in other Asian land reforms such as Japan (2 mn has), Korea (0.58 mn has) and Taiwan (0.24 mn has). In terms of total area distributed, this puts India on par with Mexico which, in a much more land-abundant setting, and starting in 1917, managed to distribute slightly more than 13 mn ha (Deininger 2003). 4 The increment in ceiling surplus land transferred during the period amounted to only 10,800 ha which is only about one tenth of the land declared ceiling surplus which had not been distributed. The fact that all the remainder remains tied up in litigation suggests that further progress in achieving redistribution of ceiling land could be slow -it would take almost 90 years to dispose of remaining ceiling surplus cases if the current pace is maintained- and that, by clogging up the court system and preventing it from quickly dispensing justice in other urgent matters, the ceiling legislation may impose external effects beyond land rental markets (Moog 1997).

5

stock) due to artificially reduced prices (Gyourko and Linneman 1990), thus making access to rental more

difficult thereafter (Basu and Emerson 2000). With a constant or decreasing number of beneficiaries and

an increasing number of new entrants who need to access to land in distorted markets, social cost of

maintaining land rental restrictions will increase over time (Glaeser 2002). Identifying other policies that

can be better targeted and have fewer undesirable side-effects is thus desirable (Munch and Svarer 2002).

As, in rural areas, the impact of rental restrictions goes beyond the price effects on which urban literature

has focused, it may be more far-reaching. First, due to labor market imperfections, the way in which rural

land is used will have an clear impact on productive efficiency (Binswanger et al. 1995). Second, housing

supply will be more inelastic than that of productive land as owners can not revert to own- or wage labor-

based cultivation as in the case of agricultural land (Appu 1997). Third, as rural rents are an in-kind

output share, contract terms will be less flexible than urban ones, limiting the scope for circumventing

them by adjusting rental rates (Basu and Emerson 2003). Finally, rights given to tenants are heritable but

non-transferable and still require rent payment to the landlord, thus reducing both parties’ incentives for

land-related investments and the scope to increase allocative efficiency through sub-leasing.

To explore the impact of such restrictions on rental markets, we use a simple model where a key rationale

for producers to enter land markets is the desire to adjust for differences in their existing endowments of

land and family labor. Let household i be endowed with fixed amounts of labor ( iL ) and land ( iA ), and

agricultural ability ( iα ). 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. Relative land scarcity, together with

the cost of supervising labor (Frisvold 1994) makes wage-labor based cultivation undesirable 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 ( iw ). Renting of land

incurs transaction costs TCin for renting-in and TCout for renting-out because of the need to obtain

information on market conditions, to negotiate and enforce payments, and the presence of regulations that

restrict transferability or completely outlaw certain contract types. Transaction costs are assumed to be

proportional to the size of land transferred. With households able to structure rental contracts in a way

that allows those lacking liquidity to enter into arrangements, thus allowing to defer rental payments until

the harvest, household i’s decision problem is to choose Ai, li,a and li,o to solve

)])([()])([(),,(,, ,,

,,

outi

outinii

inoiiaii

ioiai

TCrAAITCrAAIwlAlpfAll

Max−−++−−+α (1)

s.t. li,a+li,o≤ L (1a) li,a, li,o, Ai ≥ 0 (1b)

6

where p is the price of agricultural goods, r is the rental rate, Ai is the operational land size, inI is a

indicator variable for rent-in (=1 for rent-in, 0 otherwise), outI is an indicator for rent-out (=1 for rent-

out, and 0 otherwise), TCin and TCout are transaction costs, and all other variables are as defined above.

From the first order conditions, we can derive three propositions that can be tested empirically.5

Proposition 1: The amount of land rented in (out) is strictly increasing (decreasing) in households’

agricultural ability, αi, and strictly decreasing (increasing) in the land endowment iA . Land rental will

transfer land to efficient, but land-poor producers, thereby contributing to higher levels of productivity

and more efficient factor use in the economy.

Proposition 2: The 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 TCin or

TCout 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.

Proposition 3: Increases of the exogenously given wage for off-farm employment will imply that 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. This leads to a decrease in the equilibrium rental rate which

will prompt high-ability workers to rent in more land and specialize in agricultural production.

From the model, producers’ land market participation depends on their marginal productivity in autarky,

MP( A )compared to the net rental paid rin(T) or received rout(T) as a function of transaction costs. These

variables define three regimes (rent out, in, and autarky) that can be estimated in an ordered probit model.

)2(

3Pr

2Pr1Pr

654321099

3210

654321099

3210

654321099

3210

654321099

3210

−−−−−−−+++>Φ==−−−−−−−+++<

<−−−−−−−+++Φ==−−−−−−−+++<Φ==

O}EKLADZS{ε)ob(yO}EKLADZS

OEKLADZS{ ) ob(yO}EKLADZS{ ) ob(y

iii

ii

ii

βββββαββδδδδβββββαββδδδδ

εβββββαββηηηηβββββαββηηηηε

Variables we expect to affect marginal productivity are agricultural ability (α) which we derive from a

panel production function, a dummy for landlessness, the log of the land endowment for A , labor as

proxied by the number of members aged 14-60 and below 14 for L , the value of assets for K, the head’s

age to proxy experience, a dummy for primary education to represent human capital E, and mean village

income O to represent off-farm opportunities. Transaction cost of land rental is affected by producer’s

5 For a more detailed derivation see (Deininger and Jin 2006)

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caste (Z), a time dummy (D99), and policy (S), proxied by the share of households recognized via tenancy

reform, the share of area distributed under ceiling legislation, or the number of tenancy laws.

The propositions from the model allow predictions on signs of individual coefficients. Factor equalization

(prop. 1) implies 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). Wealth bias in rental markets, possibly

due to credit market imperfections, translates into β4>0. Diversification effects (prop. 3) imply that

producers with better education and off farm opportunities will be less likely to rent in land (β5<0; β6<0).

Proposition 2 implies that, by moving the cut-off points where producers shift from renting out to autarky

and from autarky to renting in, respectively, rental market restrictions expand the range of autarky but do

not affect producers’ marginal product.6 We thus expect η1>0 and δ1<0, respectively. By the same logic,

higher transaction costs for producers from scheduled and backward castes imply η2>0, and δ2<0 while a

reduction over time in transaction costs due to better access to information implies η3<0 and δ3>0.

2.3 Data sources and descriptive evidence

The data used here and below come from two rounds of NCAER’s ARIS/REDS survey conducted in

1982 and 1999, respectively. This survey, the first rounds of which were implemented in 1968-71 covers

all of India’s major states. The 1982 sample covers some 5,000 households (Foster and Rosenzweig 1996)

and adding replacements and splits yields about 7,500 households in 1999 (Foster and Rosenzweig 2004).

Table 1 presents household characteristics by rental participation status (rent in, rent out, or autarky). It

highlights a large increase in the level of land market activity over the period; from 5.3% and 2% for

renting out and renting in, respectively, in 1982, the share of market participants has increased to 10.7%

and 4.1%, in 1999.7 Descriptive figures also support the propositions from our model and the notion of

better rental market functioning in the second, as compared to the first period. Comparing the per capita

land endowment for land owners who either remained in autarky (0.51 ha and 0.36 ha in 1982 and 1999,

respectively), rented in (0.28 ha and 0.20 ha), or rented out (0.68 ha and 0.64 ha) illustrates that, in both

periods, rental provided opportunities for land-scarce and labor-abundant households to gain access to

land. Land markets transferred land from households with more educated and female heads to male

headed ones with less education. The share of landless who had gained access to land through rental

6 It is intuitive that rental restrictions will directly affect whether or not households participate but, unless there are selectivity issue, are unlikely to affect producers’ marginal productivity. Indeed testing for selectivity of rental market participation, by including rental restrictions in the marginal product equation as well, did not produce conclusive results. 7 While this is a large change, the level of rental market activity increased more rapidly, and in a shorter period, in other Asian countries such as China or Vietnam, despite the fact that the more egalitarian land ownership distribution in these countries would put greater limits on the potential of land markets to equalize operational holdings than in India. In Vietnam, the share of households renting in increased form 3.8% to 15.8% in the 5-year period between 1993 and 1998 (Deininger and Jin 2007). In China, the same figure increased from 2.3% in 1996 to 9.4 in 2001 (Deininger and Jin 2005).

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markets increased from 12% in the first to 37% in the second period, suggesting a marked expansion of

outreach towards this group over time. Noting that our sample represents about 130 mn rural households,

in 1999 about 15 mn households -a quarter of them landless- were able to use markets as a means to get

access to land. This is not only much larger than the number of those who got access to land through land

reform but also highlights that, given the magnitudes involved, even policies with “modest” impact on the

functioning of land rental markets could have implications for a large number of households.

Comparing levels of consumption and assets for households who differ in the nature of their land market

participation reinforces the notion that rental provides opportunities for poor segments of the population

to access productive resources and thereby improve their well-being. The value of all assets owned by

households renting in 1999 was, with Rs. 33,839, more than 25% below the average, compared to asset

ownership that is similar to the mean for autarkic households and about 33% higher than the mean for

those renting out, supporting the notion that it is the asset-poor who benefit from the access to land which

rental markets provide. The narrowing of the gap between rent-in and average households with respect to

per capita expenditure is consistent with the hypothesis of land markets making a positive contribution to

the livelihood of participants. Finding significant differences in the composition of the asset portfolio

between rent-in and rent-out households, with the former having relatively more of their wealth in

farming and livestock, and the latter in off-farm and financial assets, is not too surprising.

The high share of renters engaging in (agricultural) wage employment suggests that land rental provides

wage laborers with ways to earn additional income. The fact that -in contrast to 1982- non-farm self

employment is much higher among rent-in households than either the mean or those who remained in

autarky suggests that land rental is not an obstacle to participation in the rural non-farm economy.

2.4 Econometric results

Results from ordered probit estimation of the rental market participation equation using the pooled sample

for 1982 and 1999 and with and without ability which is defined only for those producing in both periods,

are reported in table 2. The pairs of columns correspond to policy variables, i.e. recognition of tenants,

distribution of ceiling land, and tenancy laws. To interpret these, recall the coding of 1 for rent-out, 2 for

autarky, and 3 for rent-in regimes so that positive coefficients increase the probability of renting out.

The highly significant coefficient on ability implies that, as expected, rental markets improve productivity

of land use by transferring land from less to more efficient producers. The magnitude is large; according

to the estimates, the probability for the most efficient household in the sample to rent in is more than

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double that for the average household.8 There is also a strong factor equalization effect. Higher land and

lower labor endowments -especially for 14-60 year olds- increase the propensity to supply land to the

rental market, support that, by transferring land to labor-rich but land-poor households, markets allow

gainful employment of rural labor. The large and significant coefficient of the landless dummy suggests

that rental is important for landless households to access land. Landless producer’s propensity to rent is, at

5.4 to 8.6 points above that for land owners almost double that of the former. Lack of significance for the

coefficient on total assets suggests that rental markets are not biased in favor of the wealthy.9 A strong

diversification effect also emerges. Completion of primary education by the head increases (decreases)

the propensity to rent out (in) land, by about 2.1% and 1.1%, respectively. Mean village income increases

the tendency to rent out, too, implying that as the level of income increases, households will be more

likely to move out of agriculture, supply land to the rental market, and allow those remaining behind to

increase their holdings and income levels, as is also observed in other countries, e.g. China.

Regarding the lower bound equation, regressions suggest that policy restrictions will lead to a significant

and quantitatively large reduction of land supply to rental markets. Estimated effects are weakest for the

number of laws (columns 5 and 6) and strongest for recognition of tenants (col. 1 and 2), consistent with

the notion that implementation is more important than mere legislation and that landlords will be less

willing to rent out if doing so can attenuate their property rights or if there are limits on their ability to

negotiate the amount of rent. The share of land affected by redistribution of ceiling land is in the middle

between these two, consistent with expectations that ceiling legislation poses less of a threat than tenancy

regulation -as the latter applies to all market participants irrespective of their holding size- and enforcing

it is more politically controversial and administratively complex than implementing tenancy legislation.

The 1999 dummy illustrates that, over time, land rental supply increased significantly. To quantify the

impact of policy restrictions we compute, for every household, the predicted probability to rent out with

actual values for all right hand side variables and with the tenancy restriction variable taking a value of

zero. Taking the difference between these two values as a measure for the impact of tenancy restrictions

suggests that their removal could lead to a considerable increase in renting out, by between 40% and 70%.

Turning to the (upper) bound between autarky and renting in, positive coefficients on all policy variables

suggest that these also depressed demand, making it more difficult for households to obtain land through

rental. Across policy variables, those relating to the intensity of enforcement are again more significant;

in fact the number of laws, while of the expected sign, is not different from zero at conventional levels. In

8 While lack of data on profits before and after rental participation makes it difficult to assess the net impact on productivity, evidence from China, where rental helped increase productivity gains by some 60% (Deininger and Jin 2006), suggest that these can be large. 9 Inclusion of an interaction between the time dummy and asset ownership (not reported) suggests that land rental markets had been biased in favor of the wealthy in 1982 but that, presumably due to better credit market access in the study areas, this bias had disappeared by 1999.

10

most equations, coefficients are bigger for the upper as compared to the lower bound, suggesting that the

impact of policy-induced restrictions will be larger on the demand side. Simulations suggest that removal

of tenancy restriction could double participation rates by rent-in households. Backward and scheduled

castes are more likely to remain in autarky and over time, the size of the autarky area has decreased, i.e.

land rental markets have become more active.

While this is encouraging sign and suggests that time may partly offset undesirable impacts of rental

regulation, the magnitude of the coefficients is small; estimated coefficients imply that almost a century

will be required to offset these effects. Time is thus unlikely to eliminate the negative effects of tenancy

regulation or do so in an equitable manner, in line with case study evidence suggesting that circumventing

legislation is easier for the rich than the poor (Yugandhar 1996, Thangaraj 2004). Interacting policy

variables with producers’ estimated productive efficiency (not reported) allows more detailed exploration

of rental restrictions’ impact on efficiency with results reinforcing the notion that rental restrictions

significantly curtail efficiency of land use by preventing land access by the most efficient producers.

2.5 Policy implications

In rural India, there is an increasing recognition of the importance of land rental markets to bring land to

more productive uses while at the same time providing a basis for development of the rural non-farm

economy. Although the continued need for restrictions on the operation of land rental markets has been

debated at an abstract level in numerous case studies, quantitative evidence of its impact has been scant,

giving rise to a debate that is highly ideological in nature. Use of a national sample, jointly with cross-

state variation in tenancy legislation, allows us to provide evidence on the impact of rental markets in

general and restrictions on the operation of such markets in particular.

Contrary to what is often assumed, our data suggest that, by allowing higher ability individuals to access

land and equalizing factor ratios, rental markets improve productivity and equity. The level of activity has

increased significantly over time and wealth bias that had characterized such markets earlier evaporated

as the economy has diversified. While land markets make an essential contribution to the emergence of

the non-agricultural economy, rental restrictions limit the level of market activity and the ability of the

most productive producers to access more land, thus reducing overall welfare. These results, which are in

line with case study evidence from a number of states, highlight the importance of taking action on

eliminating rental market restrictions, as articulated in the Government’s 10th 5-year plan (Government of

India 2002) and reiterated more forcefully in the documents circulated in preparation for the 11th plan.10

10 “…freedom in leasing of land, both 'leasing in' and 'leasing out' will help generate income for both lessee and lessor/contractor. A legislation needs to be enacted to facilitate the land utilisation by making land transactions easier and facilitating leasing and contract farming.” (Government of India 2002, p. 528). Note that political resistance to abolition of tenancy restrictions can likely be minimized by taking sitting

11

These results will also be of great relevance for neighboring countries, many of which have equally

restrictive land rental policies that are likely to have similar impacts.

3. Do land sales markets harm the poor through distress sales?

Although less restricted than land rental, it is often argued that, due to imperfections in other markets,

land sales can lead to outcomes that are undesirable both under equity and efficiency considerations. We

review the underlying argument and review the available evidence from the data at hand.

3.1 Motivation

Few interventions have been as passionately debated, and subject to a larger number of policy restrictions

than the operation of land sales markets. Proponents argue that the ability to sell land in a freely operating

market is crucial not only to maximize productivity of land use and facilitate optimal resource allocation

but also for financial market development, by allowing use of land as collateral and thus a reduction of

the cost of providing credit. Government should, it is argued, strive to set a framework within which land

markets can operate and otherwise adopt a laissez-faire approach. Opponents retort that land is more than

just a commodity and that, with multiple imperfections in other markets, free operation of land markets

will often not enhance efficiency. They maintain that historic inequalities in land access, and a danger of

distress sales or speculative acquisition, make concentration of land likely and that, unless government

intervenes or even prohibits land sales, sales markets will yield undesirable social and economic effects.

While theoretical models that put land sales markets into the general context of a household’s choice of

an optimum asset portfolio can generate widely divergent predictions, empirical evidence to assess the

extent to which these correspond to actual outcomes -and key underlying factors- is often scant. In fact, as

land sales markets are normally very thin, large or sufficiently long samples will be required to be able to

observe causes and consequences of land market participation. Existing studies are often based on

comparatively small samples (Sarap 1995, Lanjouw and Stern 1998) or rely on retrospective information

(Baland et al. 2007). The implied selectivity and lack of initial characteristics makes it in many cases

difficult for analysis to go beyond simple descriptive statistics or transition matrices with little scope to

help identify underlying factors and thus provide much-needed insight to enlighten the policy debate.

3.2 Conceptual framework and estimation strategy

If households do not face subsistence or borrowing constraints that would otherwise prevent them from

fully insuring against risk, everybody has access to the same set of information, and switching transaction

tenants’ welfare into account and by proceeding in a stepwise manner, starting with states characterized by high agricultural potential, and by carefully documenting the results from doing so.

12

partners is costless, the market for land sales will not be different from that 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 market transactions 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 outcomes that may be neither socially nor

economically optimal originates in three observations, namely that (i) imperfections in markets for credit

and insurance will affect decisions on whether or not to participate in land markets, and that in particular

subsistence constraints can force households to take decisions based on short term requirements that are

inconsistent with maximization of welfare in the long term; (ii) differences in producers’ access to

information will lead to variation in transaction costs; and (iii) land may be acquired for speculative

purposes unrelated to its use in agricultural production.

Households’ decision problem 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 between these

two assets to maximize utility over the entire lifetime and 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 credit market imperfections and risk, households’ need to

satisfy basic subsistence needs 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 with a lower but more stable return to land

even if transaction costs were modest and they had access to credit to acquire it. 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 Carter 2003). Similarly, others may be forced to sell use land markets 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). In

addition to these factors, macroeconomic instability, expectations of future land price hikes, lack of

sufficiently attractive alternative assets, policies, and the valuation of land for non-productive reasons, all

will affect households’ participation in land sales markets independently from their innate productivity.

We model these two sets of factors that will affect land markets in a rather independent manner in our

13

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

depending on whether or not risk is high. .

As India inherited a highly unequal distribution of land from its colonial masters, it is not surprising that

land reform was at the center of policy discussions for a long time. In this environment where other factor

markets were highly imperfect, distress sales had historically played a major role (Kranton and Swamy

1999). Evidence suggests that households’ access to insurance substitutes allowing them to buffer

consumption during crisis had a significant impact on whether land sales markets helped to equalize

endowments or contributed to further dis-equalization (Cain 1981). To halt these tendencies, virtually all

states implemented, during the 1960s and 70s, different types of land reform measures, mainly in the form

of land ceilings and security against eviction as well as rent ceilings for tenants.11 In addition to these,

legislation in virtually all states prohibits land transfers from tribals to non-tribals. Transaction cost are

further increased by stamp duty which has to be paid upon registration of a sale and which in most cases

amounts to more than 10% of land value (Alm et al. 2004).

Based on the above, we explore three issues, namely (i) whether land sales promote efficiency of land use

by transferring it to households with higher levels of ability; (ii) the extent to which land sales contribute

to equalization of endowments, i.e. transfer land from labor-poor and land-rich to labor-rich and land-

poor households; and (iii) whether shocks and policies affect the outcomes observed in land sales

markets. Further, we are interested to see how land sales compare to non-market transfers. We distinguish

factors that affect households’ or dynasties’ latent demand for land due to their level of productivity from

other factors, unrelated to productivity, that may prevent them from exercising this demand or force them

to sell even if doing so runs counter to long-term maximization of productivity using an ordered probit

model with variable upper and lower thresholds for land market participation. Latent demand is

determined by their current and expected future ability to make productive use of the land. Actual

participation decisions will, in addition, be affected by factors unrelated to productivity such as

transaction costs and shocks. Formally, we assume that latent demand for land depends on long-term

productivity which can be expressed as a reduced form equation

f(α, A ,L,K,O)= β0 + β1α + β2 A + β3K + β4L+ β5N (3)

11 Ceilings on the amount of land that could be held by an individual or household although implementation effort varied widely and generally was much delayed until the early 1970s. Contrary to Korea, where land owners’ anticipation of such ceilings led to a tremendous increase in land sales market transactions that transferred income to former tenants and increased productivity (Jeon and Kim 2000), they were largely evaded by spurious subdivisions (Kaushik 2005). Where, as in West Bengal, implementation of land reform legislation was effective, ceilings are still credited with having led to greater land sales market activity (Bardhan and Mookherjee 2006).

14

Thresholds for the transition between sales and autarky and autarky and purchase are defined as follows:

pS(T) = η0 +η1S+η2C+η3G+η4(C×S)+ η5(G×S)+ η6Z (4)

pB(T) = δ0 +δ1S+ δ2C+δ3G+ δ4(C×S)+ δ5(G×S)+ δ6Z (5)

where S denotes whether or not the household experienced a weather shock, defined as a level of rain

below the average for two consecutive growing seasons, C denotes credit access, G local availability of

mechanisms for risk coping, in particular the employment guarantee scheme, Z is a vector of other

characteristics, and the βs, δs andηs are parameters to be estimated.

Factors affecting the extent of participation in the main equation are the level of ability and the dynasty’s

endowment with land, labor, and assets, the length of the households’ independent existence in 1999 and

the position in the life cycle which are represented empirically by a dummy for whether a household is

from a landless dynasty and the dynasty’s land endowment to represent A and initial asset endowments

and levels of per capita consumption to proxy for K. To proxy for lifecycle events and concerns about

inter-generational transmission, the number of unmarried sons aged between 5 and 25 years in 1981. We

expect β1 > 0 and β2 < 0 as high levels of agricultural ability increase producers’ marginal product and

thus their competitiveness in land markets while standard assumptions for the production function imply a

negative relationship between land endowment and marginal product. In other words, higher agricultural

ability or lower land endowment will increase a household’s likely propensity to shift from autarkic to

land purchase and less likely to move away from autarkic to land sale. As, with imperfections in credit

and labor markets, higher levels of wealth or family labor will increase a household’s marginal

productivity, we expectβ3>0, β4>0, and β5>0.

Concerning the variables in the threshold equations, note that Z includes policy constraints on tribals’

land market participation, the inequality of land holdings in the village that will affect transaction costs in

the land market, and the growth rate of village income to proxy for non-farm opportunities. We expect

negative weather shocks to increase the supply of land to the market through (distress) sales and safety

nets to reduce it as they improve poor people’s ability to cope with unanticipated shocks, thus η1>0, and

η3<0. While presence of banks also improves the ability to cope with shocks, it will also provide greater

liquidity that would increase land market activity, making the sign of η2 indeterminate. As safety nets and

banks improve the ability to cope with shocks, we expect η4<0 and η5<0.

On the supply side, we expect shocks (village employment schemes) to increase (decrease) land supply to

the market, hence δ1<0, and δ3>0. By the same liquidity argument as above we expect that δ3<0. If

access to banks and safety nets reduces the supply of land to markets through distress sales and less

supply would reduce the number of those being able to buy land, we expect δ4>0 and δ5>0. Finally, the

15

presence of constraints on market participation by tribals leads us to expect a negative (positive) sign on

the coefficient for ST/SCs in the upper (lower) threshold equation. On the other hand, by increasing the

scope for productivity-enhancing land transactions, economic growth at the village level is expected to

increase land market activity, thus we expect the coefficient on this variable to be positive (negative) in

the upper and lower threshold equations, respectively.

To compare effects of market transactions to those of non-market transactions (i.e., inheritance, gift,

dowry, etc), we run an ordered probit model that identifies key determinants for non-market land transfers

with some modifications of the variables to be included in the ordered probit model. For example, the

entire argument of transaction costs associated with land sale and land purchase will not be relevant to

inheritance and gift exchange. Correspondingly, we treat the two thresholds in the ordered probit model

as constant. As discussed earlier in the estimation strategy section, we treated the lower and upper bounds

of the ordered probit model as constant because the transaction costs are unlikely to be relevant to non-

market transactions.

3.3 Descriptive statistics

The share of households who, in 1982-1999, obtained or transferred land through market (i.e. sale and

purchase) compared to non-market (i.e. inheritance) mechanisms, is presented in table 2. With 15% and

8% (or 0.88% and 0.47% annually) of the population and 9% and 5% of the land involved in purchasing

or selling land, respectively, the level of land sales market activity in the data is in line with what has been

reported by other Indian studies (Mani and Gandhi 1994, Dreze et al. 1997, Rawal 2001).12 It is of interest

to note significant regional differences, with land purchase markets being quite inactive in the North (6%

of population and 3% of land) but relatively active in the South (25% and 18% of population and land).

Access to land through non-market channels is, with 10% in terms of households (or 7% in terms of

land), less frequent than access through markets, and overlap between the two minimal. Also, even in the

most active areas, land sales and purchase markets are much less active than those for rental in which

15% and 9% participated in 1999 alone (Deininger et al. 2006). As attrition was carefully controlled for,

and most household splits were actually traced, the fact that the share of those reporting to have purchased

land during the period is higher than that of those who sold is most likely due to the fact that sellers sold

land in small plots to more than one buyer.

Moving from aggregate to household-level information, table 3 describes initial and final characteristics

for the whole sample and by households’ participation in market transactions (i.e., selling, buying, and

12 Rawal (2001) reports a number of studies from India that find that in most cases the share of land transacted annually was below 0.5%. Part of the reason for this low figure may be the fact that in the studies quoted, the denominator was total village land rather than the land owned by survey respondents.

16

remaining in autarky, in columns 2, 3 and 4) and non-market transfers (i.e., inherited out and autarky in

columns 6 and 5) during the period under concern.13 The top panel provides information on initial

conditions in 1982 while the bottom panel illustrates the status in 1999. We first discuss information for

market-participants followed by that for groups according to their non-market participation. 14

Initial conditions for market participants allow three main conclusions. First, data point towards strong

equalization of factor endowments through land sales; households who sold land had significantly smaller

initial adult populations and per capita landholdings than purchasers (3.8 vs. 4.4 persons in the 14-60 age

group and 2 vs. 1.3 ha per capita, respectively) and 15% of those purchasing land came from a landless

dynasty.15 At the same time, there were no significant difference in initial non-land asset endowments or

the level of per capita income between those who purchased and sold land and those remaining in autarky

although the two former groups had slightly higher initial consumption levels than the latter. Second, the

fact that the number of unmarried sons and daughters for sellers (1.08 and 0.78) and buyers (0.88 and

0.68) is markedly above that of those in autarky (0.73 and 0.51) points towards a link between land

market participation and live cycle events. Finally, with 9% and 13% in sales and purchase markets,

compared to 17% overall, land market participation by scheduled caste households was uniformly low.

Shifting from initial to final conditions in the bottom panel of table 3 provides a number of insights. First,

while differences in household size persisted in 1999, those who purchased land had made welfare gains

that were more than 50% above those for the rest. Compared to initial levels that were not different from

those by the rest or even slightly below average, purchasers’ levels of final asset ownership (Rs. 86,748

vs. about 57,000 for the rest of the sample), per capita income (Rs. 4,063 vs. 2,500), and expenditure

(1,908 vs. 1,579 and 1,724), were all significantly above non-participants’ and sellers’ in 1999.

This was accompanied by purchasers shifting from the bottom of the three groups in terms of per capita

land endowment to the top, with a significantly higher end-period level of 1.12 as compared to 0.7 ha per

capita, for the rest of the sample. The extent to which such performance was underpinned by higher levels

of productivity will have to be explored in the econometric analysis. Although 29% of sellers in the

sample became landless, their asset and income levels in 1999 were not significantly different from those

in the autarky group with their per capita income significantly above the latter. Even though some sales

13 Columns 2-4 identify changes in welfare over time between those who sold and purchased while columns 5 and 6 point towards generational differences between the old and the young generation for households who transferred land through inheritance and those who did not. In both cases, the results of t-tests for the significance of differences between the group transferring land and those remaining in autarky are indicated by stars as explained in the table. 14 The discrepancy of number of observations between 1982 and 1999 (5932 versus 3816) is due to household splits in the 1982-99 period. Of the 3816 households of the initial sample that could be traced in the second round, 1174 split and formed a total of 3290 new households while 2642 did not experience any change, bringing the total number to 5933. 15 In other words, more than 60% of those who had been landless at the start of the period were able to acquire land through the market. At the same time 2% of the sample who were landless in 1982 managed to acquire land but had sold it by the end of the period.

17

may have been undertaken out of distress, those who sold land did, on average, not become worse off and

may even have done slightly better than the rest, e.g. because they took up non-farm activities.

Turning to participants in non-market transactions, we note that, in the parent generation, those inheriting

out had significantly higher levels of land endowments, assets, incomes, and unmarried sons or daughters

than the rest. However, different from what had been observed for market transfers, households who

received land through inheritance did not manage to accumulate non-land assets or increase their

consumption over time faster than those who did not benefit from such inflows. Although their per capita

land endowment was, with 0.97 as compared to 0.72 ha still significantly above that for the rest, levels of

assets and per capita consumption both were insignificantly different from those for autarky households.

Although they have a slightly higher level of income than those who did not inherit, the difference is

smaller than for those who purchased land. This suggests not only that markets are an important avenue to

access land for those born into a landless dynasty but also that the latter are better able to make beneficial

use of such land than those who inherited it.

3.4 Econometric evidence

Ordered probit results for estimation of the main equation and the cut-off points for participation are

reported in table 4. Column 1 includes shocks and mitigation variables separately while column 2

interacts both to explore the risk mitigation effect of the latter more directly.16 A first finding of interest

from the main equation is the productivity-enhancing impact of land markets that is illustrated by the

positive coefficient on our measure of dynasties’ initial ability, suggesting that sales markets transferred

land to dynasties who had been more efficient producers in 1982. Interestingly, imperfections in credit

market, to the extent that they did exist, were not strong enough to overcome this tendency.17 Compared

to the least efficient dynasty in the sample, a member of the most productive would have a probability of

purchasing land (over the whole period) that is higher by about 3.8 percentage points (or 25%). The main

equation also supports the hypothesis of factor equalization through land sales markets as can be seen

from the negative coefficient on the dynasty’s land endowment, together with the positive and highly

significant coefficient on whether or not a household came from a landless dynasty. According to the

coefficient, members of a landless dynasty were 15 points more likely to buy land than ones with the

highest land endowment in the sample. Data also support the live-cycle hypothesis, suggesting that those

16 Recall the coding of 1 for sale, 2 for autarky, and 3 for purchase. 17 As agricultural ability is not available for those whose dynasty did not cultivate land in 1982, estimation of the ordered probit model without farming ability increases the sample by about 1,400. Results, which are available upon request, are generally consistent with those reported here. To interpret the results, recall that the coding 1 is for sale, 2 is for autarky and 3 is for renting in, i.e. that a positive coefficient implies that the variable under concern increases the probability of land purchase and reduces that of a land sale.

18

with unmarried sons in 1982 were significantly more likely to purchase land.18 In addition, households

with a longer independent existence were more likely to participate in land markets. Finally, the

insignificant sign on household’s total non-land assets suggests that, surprisingly, once other factors were

controlled for, ownership of other assets did not make it easier to purchase or sell land.

Results from estimating the lower bound between land sales and autarky and the upper bound between

autarky and purchase lead to a number of additional results of interest: The positive (negative) sign of

climatic shocks in the lower (upper) bound equations suggests that being affected by lack of rainfall or

floods for consecutive seasons significantly increase the odds of a household selling land and thus also

increased the odds of purchasing. Mechanisms to mitigate risk, in particular the employment guarantee

scheme (EGS), helps to counteract much of this effect; in fact we are not able to reject the hypothesis that,

in communities where the EGS was present, climatic shocks did not affect the cut point between sale and

autarky or autarky and land purchase. Finally, and in line with expectations, scheduled castes and tribes

(SCs and STs) are significantly less likely to sell land. The lower propensity to sell can be explained as a

possible result from policies restricting land sales by tribals whereas the fact that tribals’ ability to interact

with higher caste individuals is constrained may underlie their more limited participation in purchases.

Land sales and purchases are also found to have been more frequent in communities with bank access

than in those without. As local economic growth, which could be correlated with banks’ location choice,

is controlled for, the better liquidity afforded by bank presence is most likely at the root of this.

Interestingly, interacting bank access with the number of drought shocks leads to a significant leftward

shift of the cut-point between sales and autarky, supporting the hypothesis that, by providing credit and

other insurance substitutes, presence of banks reduces the propensity for distress sales. Higher growth at

the village level is estimated to shift the upper bound down, i.e. to encourage land purchases, without

affecting the boundary between sales and autarky. The finding that an unequal land distribution (proxied

by the Gini) at the village-level shifts the boundary between sales and autarky upwards while leaving the

upper bound unaffected, could suggest that the threat of ceiling legislation being implemented prompted

land owners to sell off land in anticipation of such policies (Bardhan and Mookherjee 2006).

Results from estimating a simple probit equation for participation in non-market transactions (not

reported) suggests that our ability measure is not significant for the inheriting out regression and only

marginally significant for inheriting in. This implies that, while inefficient producers would be better off

transferring their land to others, they do not do so through non-market channels and it would be of interest

to explore to what extent rental markets are used by those who receive land through non-market transfer

18 As presence of sons in the relevant age range is highly correlated with that of daughters (ρ= 0.4), we include only the former.

19

to bring about a more productivity-enhancing outcome. By contrast, life-cycle factors are of high

relevance; larger households and those with more unmarried children are more likely to transfer out land

through inheritance while longer independent existence of a household makes it more likely to have

received land thorough this channel. Not surprisingly, other village- and household-level variables

included in the land market regression do not have any impact on non-market transactions.19

In addition to not contributing to higher productivity, non-market transactions also do not help to equalize

the land ownership distribution. The positive but small coefficient of the initial land endowment in the

transfer-out equation highlights that those with higher endowments are more likely to transfer out land but

the initial endowment does not have a significant effect on the probability of receiving land through non-

market channels. Not surprisingly, being from a landless dynasty makes it harder to gain access to land

through inheritance. The positive and significant coefficient for initial asset value in the inheritance

equation suggests that access to land through non-market transfers is limited to the better off and any

redistribution through this channel will be limited. Thus, although optimum outcomes from land markets

will depend on an appropriate policy framework, markets have provided a key avenue to access land.

Also, to compare market- and non-market mediated land transfers, we estimate a probit similar to the one

in table 5 for market transactions. Results (not reported) support the notion that, most likely due to the

more limited range of potential transaction partners, the performance of non-market transactions is

inferior to that of market-mediated land transfers in most of the parameters of interest. Consistent with

ordered probit results, key differences between market-mediated and non-market land transfers are

confirmed with respect to productivity, equity, climatic shocks, and the village characteristics. On the

supply side, we find that, contrary to non-market transactions, less efficient producers with a higher per

capita land endowment (significant at 10%) who had been in existence for a longer time are more likely to

sell land while SC/ST households are less likely to do so. Unequal village level land distribution, having

experienced climatic shocks, and bank presence increases the likelihood of land sales while the

interaction between banks and shocks reduces it. Most of the household level variables on the demand

side are just a mirror-image of those estimated on the supply side, supporting the notion that, although

they are affected by credit market imperfections, land sales markets provide greater opportunities for the

landless to acquire land and for overall improvements in productivity of land use than those afforded by

non-market transactions. Furthermore, the lack of significance of coefficients on all the village

characteristics for non-market transfers supports their essentially static character compared to the more

dynamic evolution of market-mediated transactions in response to a changing environment.

19 We estimated equations where overall growth in the village, access to banks and employment guarantee schemes, shocks, and the land distribution were included but none of them are significant.

20

3.5 Policy implications

Key conclusions include first, the fact that the producers’ propensity to participate in land sales markets

was significantly increased by the number of times they experienced an unfavorable shock suggests that,

in the areas concerned, credit market imperfections and subsistence constraints are still an important

determinant of land sales. This is supported by our finding that ways to mitigate shocks, in particular local

presence of safety nets in the form of the employment guarantee schemes and banks, if interacted with the

frequency of shocks, helped counteract such negative impact. Second, although they were significantly

less active than rental markets, land sales markets helped equalize factor ratios and allowed the relatively

land-poor and labor abundant to improve their levels of asset ownership and welfare without making

sellers worse off. Still, controlling for other factors for, land sales transferred land to better cultivators,

thereby contributing to net gains in productivity. Neither the factor equalization nor the contribution to

improved productivity found here for land sales emerged for non-market transactions of land. More

importantly, and in addition to performing much better than non-market alternatives, land sales markets

were significantly more active where overall economic growth was higher, suggesting that as the

economy develops and other obstacles and factor market imperfections are gradually dealt with, they are

likely to performed an even more important role.

4. Does India’s land administration system provide a basis for well functioning markets?

The above suggests that the importance of market mediated transfers will increase with greater need to

adapt to changing economic conditions and that these imply a number of positive outcomes. However, as

transaction costs are important, well functioning institutions for land administration have an important

role to play. In the Indian context, a number of factors, including duplication of institutions and high fees,

limited coverage of the system and low reliability of the information it contains make it costly to obtain

reliable information on land ownership or to transfer it. This can cause growing informality where owners

see little gain in registering land transactions, thus further eroding the reliability and value of the land

administration system. In this section, we identify key challenges, namely (i) to eliminate duplication; (ii)

establish an integrated and self-updating process; (iii) identify gaps by linking up to spatial infrastructure

to plug them; and (iv) expand to areas that have not been covered by traditional land administration

institutions where either land values will increase most rapidly or poverty remains concentrated. We

explore how far these have been achieved by programs of computerization.

4.1 Key challenges

Most of the institutions and processes for administering land in India, which had been established by the

British with the prime goal of raising revenue, were adopted without major change at Independence. As a

21

consequence, the institutions and processes are ill suited with the requirements of a modern system of

land administration which should provide accurate and up-to date information on land ownership and

valuation so as to facilitate low-cost land transfers and use of land as collateral. Key problems that have

far-reaching implications for growth as well as equity are duplication of records and institutional overlap,

lack of unambiguous ownership records in peri-urban areas, and complete absence of land administration

structures in previously marginal areas. Before discussing possible solutions, it is appropriate to describe

briefly historical context and implications for each of them.

First, and most importantly, any piece of rural land that had been transacted through sale at any point after

1882 thereby entered the land registry system, implying that records about it are maintained not only by

the revenue but also the stamps and registration department. This duplication of institutions increases

transaction costs for land owners without providing commensurate benefits while at the same time

introducing a major source of tenure insecurity because, for many reasons including high stamp duties

that encourage informality, records maintained by both institutions may be inconsistent. A radical way of

dealing with this by merging the two departments may not be feasible politically and, even if it were, will

still depend on the necessary groundwork having been undertaken.

Second, rural areas at the urban fringe have increasingly become subject to urbanization. Although this is

associated with a significant increase of land values that would require a more precise survey, in many

states this implied that the survey department’s responsibility for maintaining an accurate spatial record of

land ownership lapsed. Responsibility for this doing so was de facto transferred to municipal corporations

who were interested in spatial records for tax purposes and often lacked technical competence. While

some have adjusted to the new requirements, implying that spatial records established for tax purposes

could, in principle, be used as a basis for ownership records, even where this was the case, the fact that

maps are not part of the ownership record is a main reason for high levels of land-related conflict (28% of

parcels according to one study) in peri-urban areas.

Last, but by no means least in importance, forest and even revenue lands that had previously been waste

and thus were not subject to settlement surveys have increasingly been brought under agricultural

cultivation. As the lack of legal recognition not only undermines investment incentives but also creates a

risk of expropriation without compensation in the case of outside investment, from a poverty perspective

one of the key challenges is to extend land administration to areas that have been left out. Doing so will

require clarification of the interface with the forest department and a broadening of tenure choices to be

accommodated within the land administration system to include, for example, communal ownership with

appropriate rules. Given the large number of land and people involved, and the high concentration of

poverty in these areas, surveying and settling these areas is of utmost priority for poverty reduction.

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4.2 Computerization of land records

Computerization of revenue records and land registries is a precondition for reaping the advantages of

modern technology. As table 5 illustrates, computerized records are now fully or partly operational in KA,

GJ, RJ, MP, MA, UP, and TN whose experience allows to draw lessons for successful implementation;

assess benefits at a descriptive level; and point towards areas to be addressed to replicate this success.

Successful states illustrate three principles: First, digitization will be useful only if computerized records

are routinely used, i.e. manual records are abolished so as to avoid duplication.20 Second, outsourcing of

digitization to private operators was not only key to success almost everywhere. A financially self-

sufficient system able to use the income generated to sustain and/or improve the system has helped to

reduce political interference and outsource specific tasks in cases where public sector capacity was

insufficient. Third, to ensure confidence in the system, it is essential that (i) a transparent process be

adopted, e.g. through verification involving active participation by land owners; (ii) integrity of the data,

be ensured through state data centers with appropriate security features and audit trails; and (iii) publicity,

i.e. making information on the internet help to de-mystify the process and to cross-check data.

Although limited rigorous evidence is as available, main benefits seem three-fold. First, computerizing

land records has simplified the system and significantly reduced petty corruption that was traditionally

involved in getting access to land records. While the amounts involved in individual cases may be small,

aggregate losses due to this phenomenon can be very large -a survey from Karnataka estimates that

computerization in this state saved Rs. 80 cr. of bribes and 6.6 cr. in waiting time per year, in addition to

non-quantifiable impacts on attitudes to officials.21 Second, where it is fully operational, computerization

improved the quality with which government services are delivered and is generating large surpluses from

user fees that can be ploughed back to expand and improve the system (e.g. through village-level access).

Third, though evidence is weak, and more rigorous study highly desirable, computerization helped to

improve credit access. Finally, a number of states demonstrate that computerized records allows to

integrate revenue records with the registry spatial data by automating the back-end of the process, efforts

to have surveys done before mutation, providing registry officials with access to the land records database

before registering a document, etc. to reduce or eventually eliminate institutional duplication.

While this points towards considerable potential for future improvements that should be rolled out, the

success of leading states should not conceal the fact that, in many instances, large amounts of money have

been spent on initiatives to computerize land records with as of yet little impact. The effectiveness of GoI

20 This also puts a premium on being selective in the information to be computerized and on speedy completion of digitization. 21 A recent study estimates that every year more than R 3,000 crore of bribes are paid by users of land administration services, equaling three-quarters total public spending on science, technology, and environment.

23

initiatives to do so can be enhanced by systematically incorporating the practices identified above in the

design of centrally funded initiatives. Specifically computerization initiatives may receive support if the

information to be digitized is relevant for land owners, if a plan for data verification and abolishing

manual records exists, if key elements of the process are outsourced to the private sector, if issues of data

integrity are satisfactorily addressed, and if they are based on a business model that has the potential to

fully cover operational cost. Implementation should also be regularly evaluated with results being

publicly available and used to feed back into future funding decisions.

Even for leading states, benefits from record computerization could be enhanced if guidance and model

regulations were available on a number of key issues that include but are not limited to (i) the nature of

information to digitize and a data architecture to allow minimum consistency and portability across states;

(ii) ways to automate mutation to synchronize revenue and registration, thus avoiding inconsistencies; (iii)

integrating these with urban property card systems; (iv) ways to improve village level access to land

records, e.g. through private kiosks; and (v) ways to integrate with spatial data to establish a property

rights system that will deliver unambiguous evidence on ownership in a cost-effective way.

4.3 Automating land registration

Registration of deeds is now fully or partly completed in AP, KA, MA, RJ, and TN (table 6). Key “best

practice” elements that helped in this accomplishment are the following: First, more than in the case of

land records, computerization of the registry has been based on re-engineering of the underlying business

practices involving standardization and simplification of deeds (contrary to digitizing virtually everything

on manual records), the development of a process to automate market valuation, and the setting of clear

performance standards. Second, to ensure financial sustainability, roll-out proceeded from offices with

high transaction volume to those with less land market activity, with adaptations made in the process.

Third, private sector outsourcing was key from the very beginning; with payment schedules to have high-

volume offices implicitly subsidize low-volume ones, to ensure equal user fees throughout the state.

The impact of doing so has been considerable. In a number of states, computerization has led to a

significant increase in the number of registered land transfers and increased revenue from duties even

though duty rates had in some cases been substantially reduced. This suggests that more transparent

processes for registration and property valuation increased the usefulness of services to customers and

that demand for registration is price elastic. Second, the fact that in some states encumbrance certificates

for a significant length of time are available helps to increase tenure security. Being able to obtain these

electronically via the internet implies a significant reduction in the transaction costs for sellers and

purchasers as well as banks although evidence regarding its impact on credit market activity is still

limited. Finally, computerizing registry data created the preconditions for a functional integration between

24

registration and records that will have to be a key element of any effort to make the land administration

system more conclusive, thereby reducing transaction costs and insecurity involved in dealing with land.

Given the revenue potential, computerizing of land registration is simple from a commercial perspective

and the main source of resistance is likely to be political, often from people in the system whose ability to

obtain rents would be negatively affected. A number of policy issues need to be addressed even in more

advanced states. First, even though some states have moved to reduce high levels of stamp duty that

tended to drive transactions into informality, the fees levied on property transfers in India remain among

the highest in the world (in contrast to land taxes). Unless they are reduced, even the best technical

solutions for improving land records are unlikely to be sustainable. Options to partially replace stamp

duty with land taxes-levied on market values and ideally shared between local bodies and states- would be

more in line with international best practice and need to be explored. Second, it will be important to

ensure completeness and consistency of revenue and registry records. This will require regulatory changes

to ensure that mutations, e.g. through succession, that did not need to be registered in the past, will be

registered automatically and free of charge, something that is easy if the systems are linked electronically.

Third, the lack of a consistent reference to spatial parcel identifiers in the registry is one of the key

sources of incompleteness and insecurity and needs to be tackled, as will be discussed in more detail

below. Finally, there is a strong perception about registry officials lacking accountability. This can be

addressed once these officials have easy access to the information needed to perform basic checks on the

transaction that are offered to them for registration.

While none of these issues poses insurmountable difficulties and many of them will require only small

administrative changes in regulations, leadership by GoI to support pilots, drive the process and ensure

communication across states is likely to have an important role, especially if it is linked to the provision

of finances. Similar the situation for revenue records, it will be important for GoI to provide states with

incentives that allow overcoming such resistance and draw equal with the more progressive states in

terms of computerizing registration. To the extent that the ease of transacting land provided by a well-

functioning registry will be a consideration in investment decisions by firms or individuals, failure to do

so can over time translate into widening disparities between more advanced and backward states.

4.4 Survey and settlement

Although a spatial framework that is comprehensive, reasonably accurate, and cost-effective will be key for

improving India’s land administration system, a history of neglect and gaps in institutional responsibility

have compromised quality and reliability of existing data. To deal with this, the public sector should focus

on (i) comprehensive coverage with a basic cadastral index map by combining existing spatial data (village

maps, tax maps, etc.) with new technology such as satellite imagery; (ii) pilots to develop scalable and cost-

25

effective ways to generate spatial data for archetypical situations;22 and (iii) regulation of private surveyors

and ways to expand their capacity to allow government to focus on providing true public goods rather than

crowding out private operators.

In fact, a cursory review of pilot surveying activities suggests that one reason of the failure to develop

replicable models in surveying is that “pilot” attempts neglected key success factors that were critical in

computerization of land records; namely (i) by starting from scratch with complete resurveys instead of

drawing on existing information and trying to identify and fill gaps; (ii) by narrowly defining “modern

technology” as equivalent to electronic total stations (ETS), an expensive option in which India has little

comparative advantage and which provides a level of precision that is not needed for at least 80% of the

country rather than considering a range of technology options and then focusing on cost-effective ones

where India has world class capacity; (iii) providing a 100% subsidy, thereby neglecting clients’ needs

and affordability; and (iv) relying completely on the public sector, in fact having surveying a government

monopoly in all but three Indian states (AP, KA, and MA)23 although none of the states that successfully

computerized textual records did so without outsourcing key components to the private sector.

Addressing this will require that (i) public sector activity focus on broad provision of clear public goods,

i.e. comprehensive coverage with a low precision cadastral index map that can be generated at modest

cost by combining satellite imagery with existing village and tax maps, instead of establishing islands of

high quality spatial data in an ocean that remains largely uncharted; (ii) pilots focus on developing

integrated, scalable, and cost-effective ways to generate spatial data and link them to textual records

applicable to archetypical situations (e.g. unrecorded subdivisions, complete change in land use patterns,

loss of spatial data, or complete lack of survey); (iii) lessons from pilots be translated into regulations and

guidelines for private actors; and (iv) an effort to expand capacity and increase the role of the private

sector (with structures for accountability) in areas where willingness and capacity to pay exist.

4.5 Strengthening the security of property rights to land

From the start, the goal of efforts to modernize land administration in India was to increase tenure

security and reduce the cost of transferring land. While modernization of textual and spatial records is a

necessary condition for this, it will be fully effective only if accompanied by an appropriate legal and

22 There is an urgent need to develop viable and replicable models to improve and maintain spatial records, along the lines of what was achieved for textual records. This is more difficult due to the specialized nature of surveying, the presence of strong vested interests pushing for technically sophisticated rather than the economically viable options, and the fact that surveying costs tend to increase exponentially with precision. A spatially differentiated approach will be needed that chooses strategies based on comparing the costs of available technical options to the likely benefits in a given environment and where cost recovery options are based on beneficiaries’ capacity to pay. However, the principles that helped to achieve success for textual records will be applicable in the area of surveying as well. 23 Even in these states what passes as ‘private sector’ appears de facto more as an appendix to the government that has limited autonomy either in financial (rates are set by the government) or technical matters (technology is narrowly prescribed and output has to be delivered in paper form and checked by officials).

26

regulatory framework. In this context, a key concern that is widely debated in policy circles, has been

whether, and if yes when and how, India should make the transition towards a system of title registration,

often also referred to as a Torrens system.

Both deeds and title registration are intended to put rights in land on public record. The key difference is

that, while under title registration, the register serves as primary evidence of ownership, a deed provides

only evidence of an isolated transaction that, at least in principle, says nothing about the validity of this

transaction. Simply put, under a deeds system potential purchasers will need to expend resources to

investigate whether the seller’s title is genuine whereas under a title system this is not needed as the

validity of such claims has already been checked for them by the registry system. The cost of a title search

by a potential buyer depends on (i) the completeness of the information contained in the registry; (ii) the

ease of searching it; and (iii) the reliability of registry information. To reduce these costs, steps to make

registration compulsory, computerizing it and facilitating searches by parcel as well as by person, and

ensuring that all documents entered into the registry have undergone at least rudimentary checks for

validity by the registrar have been adopted all around the world to improve deeds systems (e.g. in the

Netherlands, South Africa, US). Moreover, improved deeds systems of this nature constituted an essential

first step towards making the transition towards a title system. Taking these steps will be essential for

India irrespectively of whether or not an eventual transition to Torrens title is envisaged. Even where land

administration is most advanced, considerable further action will be required to reach the point where all

of these are implemented.

Once this is the case, the decision on whether to make the transition towards a full title registration system

will hinge on three factors. First, there needs to be political support to make legal and institutional

changes needed by a system of title over and above one of deeds registration. Second, even if the capacity

to run a title registration system is available, a consensus on the desirability of incurring these costs needs

to be reached. Finally, a key decision relates to the establishment of a guarantee fund, a key distinguishing

feature of title rather than a deeds registration system. In short, a title system is more expensive to run but

has lower costs of conveyancing whereas for deeds, the cost of operating is lower but the efforts required

from conveyancers is higher. Two key dimensions to be debated are thus the expected distribution of

benefits and sustainability. Given their higher cost, title systems are vulnerable to informality and can

become dysfunctional if many users are unwilling or -able to pay for the cost of running the system.

A better understanding of the magnitudes involved in the Indian context would be critical to reach an

informed decision on whether or not to go for a title registration system. Close monitoring of efforts to

move towards title that have been initiated in individual states is likely to yield important insights for

other Indian states faced with similar questions. Comparing the experience of England and Scotland, two

27

countries which, starting from a basis that was much superior to that encountered even in the most

advanced Indian states, made a successful transition from a deeds to a title system over a period of

decades with that of less successful experiences of developing countries trying to make such a transitions

without having in place the infrastructure to support such a system or being aware of the complex issues

involved suggests that trying to fast-track these processes carries a significant risks.

A more immediate goal, to be accomplished at least in the medium-term is to functionally integrate the

different databases used in land administration so as to be able to provide land owners with a certificate

that combines relevant and current information pertaining to a plot (i.e. ownership status, transaction

history, current and past mortgages and liens, and a map that allows identification of neighbors and

general boundaries) irrespectively of the government department maintaining the information. If

combined with options to maintain spatial data at low cost and regulations to ensure that any changes in

either textual or spatial records will automatically be effective throughout the system and to require

registry officials to perform at least basic validity checks before registering a document, this would allow

to realize 90% of the benefits from a title registration system at a fraction of the cost -while at the same

time providing a more appropriate basis to decide whether transition towards full title will be desirable.

5. Conclusion and policy implications

For India to successfully address the challenges posed by the land sector, actions are required both on

policy and on administrative processes. Although policy and administration are not independent from each

other, on the policy front, three inter-related key issue are to (i) liberalize land leasing; (ii) take measures to

make the benefits of land reform sustainable, critical to prevent evictions and make leasing liberalization

feasible; and (iii) provide a wider menu of tenure options (including truly communal ones) to allow

inclusion of those who currently remain outside the administration system. A comprehensive, efficient, and

accessible land administration system that provides land owners and other interested parties (e.g. banks)

with access to reliable information and reasonable levels of tenure security at low cost will be critical to

allow implementation of any land policy. Although upgrading India’s present land administration system to

provide these services will require significant resources, the benefits, which include land-related

investment, land use planning, more transparent operation of land markets (including transparent and

equitable acquisition of land on a larger scale), and financial sector development, options to provide these at

a cost that is likely to be economically viable are available.

Protect land rights by people on marginal land: Due to the absence of any settlement surveys on large parts

of marginal lands, the rights of the most vulnerable are often very weak. Recent legislation, if made

operational quickly and in a way that, for example, allows for registration of communal and individual

rights, provides an opportunity to remedy this defect and systematically clean up existing conflicts.

28

Liberalize lease markets: The above illustrates that widespread prohibition of land leasing, which may have

been a rational policy earlier when imperfections in other markets were pervasive, is no longer consistent

with original policy objective of helping the poor while at the same time hurting productivity and leading to

significant under-utilization of valuable land resources. Lifting these restrictions can help to increase land

access by the poor, allow those who currently lease land informally to formalize their transactions and thus

obtain access to institutional credit and other benefits, to the extent that it enhances owners’ security and

may allow adoption of longer-term contracts, is also likely to increase investment incentives by all parties.

Explore options to make land reform gains permanent: To prevent negative equity and possibly efficiency

impacts of liberalizing lease markets, it will be critical to prevent eviction of currently protected tenants. As

current arrangements where property rights of such tenants and owners overlap are unlikely to be conducive

to optimum utilization of land, combining this with a way of clarifying such property rights, e.g. by

initiatives that allow tenants to buy out the landlords’ residual right, could be desirable not only from an

equity point of view -by eliminating the danger of future disposession- but also an efficiency point of view.

Eliminate restrictions on land sales markets: In addition to allowing transferability of land by reform

beneficiaries, it will be desirable to drop restrictions on sale of land to non-agriculturalists and subdivision

which have little economic justification; and review legislation on compulsory land acquisition and,

subject to the prevention of undesirable externalities, allow farmers’ representatives to negotiate directly

with and transfer land to investors rather than having to go through government and often receive only

limited compensation.

Expand computerization, integration, and use of textual records to ensure full coverage: Even though

states that successfully computerized textual records benefited significantly from doing so, many progress

remains slow at best in others. GoI efforts to accelerate this effort could be improved by (i) clarifying

policy and establish clear criteria and accountability mechanisms for allocation of central funds on this;

(ii) identifying and publicizing best practice on technical and legal issues and promoting exchange and

communication among technical staff across states; (iii) emphasis on full functional integration between

records and registry and a process that keeps records up to date automatically.

Allow private sector participation in surveying, focusing government on a regulatory role: Given the size

of the gaps in spatial data and the limitations that make it difficult for the public sector to address them

comprehensively, the almost complete prohibition of private participation in survey is surprising -and

inconsistent with international best practice and India’s own experience in computerizing textual records.

Efforts to change this should focus on (i) providing a regulatory framework for application of a range of

survey methods with defined precision requirements; (ii) strengthening capacity in the private and the

29

public sector; and (iii) revamping survey processes, e.g. shifting from paper-based to electronic ones to

reduce cost and make survey more affordable.

Provide a basis for state-wide spatial coverage: Drawing on India’s capabilities to combine satellite

imagery with existing village maps and other readily available spatial products to generate a basic

cadastral index map would be a lower cost option to provide a comprehensive framework, identify gaps,

and use this as the basis for integrating spatial and textual data. These will need to be piloted first with

pilots to be targeted to archetypical situations arising from the nature of India’s land records (ryotwari,

zamindari and in each of them focusing on unrecorded subdivisions; inconsistencies across records,

decay/loss of maps, change of land use patterns, unsettled lands), and supervised by a technical working

group to steer the process. In fact, A central body to establish a regulatory framework and enforce

technical benchmarks and standards could speed up the roll-out of proven models and avoid costly ‘trial

and error’ on the more complex issues (and potentially costly) issues of spatial data. Given the importance

of a robust land administration system to allow India to meet the challenges of the 21st century, central

bodies such as the Planning Commission might be well placed to take the initiative on this.

30

Table 1: Key household characteristics by rental market participation status in 1982 and 1999

1982 1999 Rent-in Autarkic Rent-out Rent-in Autarkic Rent-out Basic Characteristics Household size 8.15 6.92 5.34 6.91 6.04 5.54

Members aged below 14 2.75 2.38 1.83 2.38 1.87 1.53

Members aged 14 – 60 4.90 4.20 3.10 4.17 3.77 3.45

Members older than 60 0.49 0.34 0.41 0.36 0.40 0.56

Land endowment (ha) 2.31 3.34 2.93 1.27 2.02 2.87

Land endowment p.c. 0.28 0.51 0.68 0.20 0.36 0.64

Landless dummy (%) 11.83 23.76 0.00 37.34 26.29 0.00

Head's age 51.85 49.97 51.71 47.41 48.98 51.65

Female head dummy (%) 2.15 6.67 12.03 3.30 6.54 8.90

Head with primary or above (%) 29.03 25.34 35.71 49.50 48.51 61.53

Agric. production profits (Rs/ha)

Consumption and asset ownership

Per capita consumption exp. (Rs.) 1426.98 1280.42 1697.84 1346.19 1549.19 2213.63

Value of all assets (Rs) 34783 17215 20333 33839 46568 62466

Financial and off-farm (%) 19.48 26.47 34.20 19.23 22.69 27.160

Farming and livestock (%) 32.12 15.70 7.69 21.67 20.91 13.26

House & cons. durables (%) 48.40 57.83 58.10 59.10 56.41 59.58 Participation in activities (%) Crop production 100.00 72.60 19.17 100.00 66.12 23.07

Livestock production 97.85 78.66 61.65 81.82 63.57 49.88

Non-farm self-employment 5.38 11.30 13.91 14.61 9.9 17.96

Salaried employment 18.28 16.84 28.2 10.71 15.98 30.05

Wage employment 26.88 38.82 19.92 59.74 44.93 23.94

Number of observations 266 4621 93 802 6366 308 Source: Own computation from 1982 and 1999 ARIS/REDS surveys All values are in 1982 Rs; 1999 values are deflated by state level deflators.

31

Table 2: Determinants of land rental market participation Policy measure in the upper/lower bound equations Tenants recognized Ceiling land redistributed No. of tenancy laws Main equation Cultivation ability 0.208**

(2.50) 0.226***

(2.68) 0.205**

(2.43) Landless dummy 0.623***

(18.09) 0.574***

(7.00) 0.626*** (17.81)

0.611*** (7.06)

0.622*** (17.91)

0.568*** (6.84)

Land endowment (ac) -0.012*** (4.63)

-0.024*** (6.42)

-0.013*** (5.14)

-0.024*** (6.50)

-0.011*** (4.61)

-0.024*** (6.46)

Members below 14 years 0.054*** (6.22)

0.040*** (3.17)

0.055*** (6.18)

0.043*** (3.32)

0.056*** (6.38)

0.041*** (3.23)

Members aged 14-60 years 0.063*** (7.97)

0.056*** (5.28)

0.062*** (7.74)

0.057*** (5.28)

0.060*** (7.55)

0.056*** (5.19)

Head's age 0.021*** (3.44)

0.031*** (3.18)

0.022*** (3.62)

0.032*** (3.22)

0.021*** (3.45)

0.031*** (3.10)

Head's age squared/100 -0.025*** (4.34)

-0.031*** (3.36)

-0.025*** (4.36)

-0.032*** (3.34)

-0.025*** (4.34)

-0.031*** (3.28)

Head has primary or above -0.148*** (4.59)

-0.116** (2.45)

-0.153*** (4.77)

-0.114** (2.42)

-0.161*** (4.99)

-0.118** (2.45)

Mean village income (log) -0.090*** (3.42)

-0.037 (0.96)

-0.077*** (2.91)

-0.007 (0.18)

-0.072*** (2.77)

-0.017 (0.46)

Total assets (log) 0.010 (0.59)

-0.008 (0.30)

0.008 (0.50)

-0.024 (0.86)

0.011 (0.65)

-0.010 (0.38)

Off-farm share in total assets -1.194*** (5.43)

-1.249*** (2.85)

-1.180*** (5.24)

-1.230*** (2.83)

-1.216*** (5.42)

-1.321*** (2.85)

Lower bound (rent out to autarky) Policy variable -12.300***

(6.50) -13.652***

(3.17) -1.502**

(2.53) -1.329 (1.40)

-0.110*** (6.07)

-0.043 (1.41)

ST/SC dummy -0.200*** (3.85)

-0.112 (1.26)

-0.178*** (3.38)

-0.134 (1.52)

-0.187*** (3.54)

-0.133 (1.51)

OBC dummy -0.105** (2.49)

-0.068 (1.04)

-0.104** (2.42)

-0.068 (1.02)

-0.093** (2.23)

-0.068 (1.03)

1999 dummy 0.527*** (8.73)

0.778*** (6.80)

0.454*** (7.49)

0.719*** (6.38)

0.451*** (7.53)

0.744*** (6.68)

Upper bound (autarky to rent in) Policy variable 12.697***

(4.18) 24.871***

(3.96) 2.551***

(2.71) 6.829***

(3.86) 0.018 (0.90)

0.008 (0.24)

ST/SC dummy 0.166** (2.52)

0.255** (2.43)

0.148** (2.24)

0.313*** (2.89)

0.165** (2.52)

0.312*** (2.97)

OBC dummy 0.148** (2.42)

0.223*** (2.79)

0.116* (1.87)

0.194** (2.39)

0.147** (2.42)

0.239*** (3.03)

1999 dummy -0.239*** (3.41)

-0.074 (0.71)

-0.245*** (3.43)

-0.113 (1.10)

-0.258*** (3.69)

-0.126 (1.25)

Observations 11331 5303 11147 5303 11221 5237 Log likelihood -4564.94 -1985.13 -4450.96 -1986.69 -4514.77 -1976.77 Robust z statistics in parentheses; * significant at 10%; ** significant at 5%; *** significant at 1%; constants and regional dummies included throughout but not reported.

32

Table 3: Household characteristics by market participation status Total Market transactions Non-market transactions sample Sale Autarkic Purchase Autarkic Inherit

1982 Household characteristics Household size 6.97 6.56** 6.95 7.32** 6.95 7.00 No. of people between 14 & 60 4.15 3.84*** 4.15 4.36*** 4.15 4.06 No. of unmarried sons (5-25 years) 0.80 0.88** 0.73 1.08*** 0.80 1.42*** No. of unmarried daughters (5-25 years) 0.56 0.68*** 0.51 0.78*** 0.57 0.86*** SC/ST share 17.53 9.18*** 19.25 13.41*** 17.38 12.24 Assets, income and consumption Per capita land endowment of the dynasty (ha) 1.47 2.00*** 1.45 1.30* 1.36 3.98*** Share of households from landless dynasty 20.99 2.41*** 24.18 14.87*** 23.31 5.43*** Value of all assets 15,906 16,408 15,866 15,820 15,196 23,979*** Per capita income (Rs.) 1,514 1,607 1,492 1,566 1,496 1,777* Per capita consumption exp. (Rs.) 1,275 1,376 1,255 1,318* 1,262 1,370 Income Sources Agricultural production 59.50 63.67 ** 59.48 57.31 * 57.87 74.74 *** Salary and self-employment 19.59 18.55 19.20 21.99 * 20.37 13.49 *** Wage income 17.90 14.39 ** 18.82 15.44 ** 18.72 9.00 *** No. of observations (dynasty households) 3816 329 2885 602 3431 118

1999 Household characteristics Household size 6.01 5.57*** 5.99 6.34*** 6.13 5.44*** No. of people between 14 & 60 3.74 3.53*** 3.69 4.08*** 3.85 3.27*** Assets, income and consumption Per capita land endowment of household (ha) 0.77 0.74 0.71 1.12*** 0.72 0.97*** Share of households landless 25.29 29.41 29.04 2.07*** 27.98 1.03*** Value of all assets 61,367 57,644 56,798 86,748*** 60,418 60,189 Per capita income 2,707 2,438 2,470 4,063*** 2,634 3,156** Per capita consumption exp. (Rs.) 1,640 1,724** 1,579 1,908*** 1,629 1,653 Income sources: Agricultural production 51.40 45.73 * 49.92 61.78 *** 48.87 66.44 *** Salary and self-employment 18.78 23.28 ** 18.12 19.80 19.55 15.63 ** Wage income 26.76 26.21 * 29.18 14.73 *** 28.68 16.38 *** No. of observations (including splits) 5932 459 4581 892 5059 593 a The 1982 figures for this item refers to those at the time when the current household head became head. b All values are in 1982 Rs with 1999 values deflated by state level deflators. *, **, *** significantly different from the sample mean at 10%, 5% and 1% respectively. Source: Own computation from NCAER ARIS/REDS survey data.

33

Table 4: Determinants of participation in land purchase and land sale (ordered probit) Specification (1) (2) Agricultural ability (technical efficiency) 0.164**

(2.30) 0.163** (2.27)

Household Size in 1982 0.008 (1.60)

0.008 (1.60)

No. of unmarried sons below 25 in 1981 0.067*** (3.73)

0.067*** (3.77)

Dynasty land endowment -0.004*** (3.71)

-0.004*** (3.71)

Landless dynasty dummy 0.122*** (2.84)

0.122*** (2.82)

Total asset value (log) 0.030 (1.56)

0.032 (1.62)

Years of independence in 1999 0.007** (2.42)

0.007** (2.36)

Lower bound equation (sale to autarky)

No.of climatic shocks 0.106*** (3.58)

0.234*** (4.46)

Employment guarantee scheme (EGS) 1982 -0.147** (2.09)

0.001 (0.01)

EGS in 1982 × No. of climatic shocks -0.062* (1.76)

Bank access 1982 0.169*** (2.68)

0.399*** (3.56)

Bank access in 1982 × No. of climatic shocks -0.084** (2.37)

Village income growth rate 1982-1999 1.127 (1.62)

1.219* (1.73)

Land Gini in village 0.916*** (4.70)

0.917*** (4.67)

ST/SC dummy -0.418*** (5.40)

-0.405*** (5.21)

Upper bound equation

(autarky to purchase)

No.of climatic shocks -0.129*** (4.49)

-0.132*** (2.70)

Employment guarantee scheme (EGS) 1982 0.136** (2.31)

0.199** (2.03)

EGS in 1982 × No. of climatic shocks -0.028 (0.84)

Bank access 1982 -0.130*** (2.58)

-0.235*** (2.61)

Bank access in 1982 × No. of climatic shocks 0.040 (1.33)

Village income growth rate 1982-1999 -1.867*** (3.10)

-1.885*** (3.10)

Land Gini in village 0.147 (1.01)

0.149 (1.02)

ST/SC dummy 0.200*** (3.50)

0.197*** (3.44)

Observations 4583 4583 Robust z statistics in parentheses. * significant at 10%; ** significant at 5%; *** significant at 1%. Regional dummies included throughout but not reported.

34

Table 5: Comparative status in modernization of land administration across states State Registry

computerized? Computerization of land

records Digitization of village

maps/FMBs Town and habitation

surveys/property cards Andhra Pradesh

Completed Not operational < 10% of VM vectorized. FMBs scanned.

Data not satisfactory, thus little activity.

Bihar Piloting Data entry No activity No activity Gujarat Roll-out Fully operational, manual

records banned. < 10% of VMs vectorized. Roll out for computerization of

property cards starting. 0.9 mn surveys (out of 2.3 mn cards) in progress; GIS support planned.

Himachal Pradesh

Piloting Roll-out; manual records not banned anywhere.

No activity No information.

Karnataka Completed Fully operational, manual records banned.

50% village maps vectorized, FMB scanning in pilot phase.

Limited coverage of cisty surveys with survey started in 48 cities. No computerization.

Kerala No, only indexes operational

Data entry stage No activity for village maps. Piloting digitization of FMBs

No information.

Maharashtra Completed Fully operational, manual records not banned.

All VMs scanned, vectorized, & geo-referenced. Scanning of FMBs ongoing.

Survey nearing completion. All property cards computerized & available via PCIS.

Madhya Pradesh

Only indexes operational

Operational, manual records not banned

VM digitization at pilot stage, problems with area.

Survey for 1/3 of cities ongoing since 1964; majority completed. No information on PCs.

Orissa Piloting Data entry & piloting Piloting of digitization of VMs & scanning of FMBs.

Punjab Piloting Data entry Limited piloting No survey for urban centers No property cards.

Rajasthan Near completion Fully operational, manual records banned.

No activity

Tamil Nadu Roll-out Fully operational in all taluks, manual records banned.

VMs scanned; not vectorized. Piloting digitization of FMBs

Natham survey almost complete. Survey done in corporations; roll-out in municipal towns.

Uttar Pradesh Piloting Fully operational in all taluks, manual records banned.

No activity

West Bengal Piloting Limited pilots Limited piloting of both. No information (only Kolkata is urban).

Source: World Bank (2007)

35

References

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