POLITICAL ECONOMY OF LAND REFORMS IN WEST BENGAL 1978-98 1 Pranab Bardhan 2 and Dilip Mookherjee 3 This version: May 4, 2005 Abstract We examine determinants of political will of local governments to implement land reforms in a longitudinal sample of 88 villages in the Indian state of West Bengal. The evidence shows a inverted-U pattern between land reform and control of local governments by a Left party coalition, inconsistent with both polar hypotheses that political will is determined by ideology or electoral opportunism alone. The empiri- cal patterns are consistent with a hybrid competition-cum-ideology-cum-moral hazard model of greater incentive for competing party officials to implement land reforms when elections are more contested. 1 We thank the MacArthur Foundation Inequality Network for funding the data collection. Sankar Bhau- mik and Sukanta Bhattacharya of the Department of Economics, Calcutta University led the village survey teams that collected the data. Indrajit Mallick helped us obtain the election data. We are grateful to Debu Bandyopadhyay, Abhijit Banerjee, Partha Chatterjee, Esther Duflo, Andy Foster, Michael Kremer, Kevin Lang and Kaivan Munshi for useful discussions. Alfredo Cuecuecha, Nobuo Yoshida, Amaresh Ti- wari, Satadru Bhattacharya and especially Monica Parra Torrado provided excellent research assistance. Mookherjee thanks the John Henry Simon Guggenheim Foundation for funding a sabbatical year when part of this research was conducted. The paper has benefited from the comments of seminar participants at Ja- davpur, MIT, PennState, Stanford, Toulouse, World Bank, MacArthur Inequality network, and the Center for Studies in Social Science, Calcutta. 2 Department of Economics, University of California, Berkeley 3 Department of Economics, Boston University 1
56
Embed
POLITICAL ECONOMY OF LAND REFORMS IN WEST ...sanhati.com/wp-content/uploads/2007/04/wbpelref17.pdfPOLITICAL ECONOMY OF LAND REFORMS IN WEST BENGAL 1978-981 Pranab Bardhan2 and Dilip
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
POLITICAL ECONOMY OF LAND REFORMS IN WEST BENGAL
1978-981
Pranab Bardhan2 and Dilip Mookherjee3
This version: May 4, 2005
Abstract
We examine determinants of political will of local governments to implement land
reforms in a longitudinal sample of 88 villages in the Indian state of West Bengal.
The evidence shows a inverted-U pattern between land reform and control of local
governments by a Left party coalition, inconsistent with both polar hypotheses that
political will is determined by ideology or electoral opportunism alone. The empiri-
cal patterns are consistent with a hybrid competition-cum-ideology-cum-moral hazard
model of greater incentive for competing party officials to implement land reforms when
elections are more contested.
1We thank the MacArthur Foundation Inequality Network for funding the data collection. Sankar Bhau-
mik and Sukanta Bhattacharya of the Department of Economics, Calcutta University led the village survey
teams that collected the data. Indrajit Mallick helped us obtain the election data. We are grateful to
Debu Bandyopadhyay, Abhijit Banerjee, Partha Chatterjee, Esther Duflo, Andy Foster, Michael Kremer,
Kevin Lang and Kaivan Munshi for useful discussions. Alfredo Cuecuecha, Nobuo Yoshida, Amaresh Ti-
wari, Satadru Bhattacharya and especially Monica Parra Torrado provided excellent research assistance.
Mookherjee thanks the John Henry Simon Guggenheim Foundation for funding a sabbatical year when part
of this research was conducted. The paper has benefited from the comments of seminar participants at Ja-
davpur, MIT, PennState, Stanford, Toulouse, World Bank, MacArthur Inequality network, and the Center
for Studies in Social Science, Calcutta.2Department of Economics, University of California, Berkeley3Department of Economics, Boston University
1
1 Introduction
In many developing countries, land reforms have significant potential for simultaneously
reducing poverty and promoting agricultural growth. For instance, there is evidence that
small farms are more productive than large farms (e.g., Bardhan (1973), Berry and Cline
(1979), Binswanger and Rosenzweig (1986, 1993), Binswanger, Deininger and Feder (1993)),
that owner-cultivated farms are more productive than tenant farms (Bell (1977), Sen (1981),
Shaban (1987)), both of which imply agricultural output would rise following redistribution
of land. Banerjee, Gertler and Ghatak (2002) argue that protection of sharecroppers against
eviction and regulating sharecropping contracts in the Indian state of West Bengal in the late
1970s caused significant growth in agricultural yields. Besley and Burgess (2000) find that
implementation of land reforms (particularly with respect to tenancy protection legislation)
in Indian states between 1958 and 1992 led to significant reductions in rates of rural poverty.
Yet the extent of land reforms enacted typically remains small relative to what could
potentially be achieved. The causes are rooted mainly in the nature of governance: lack of
political will, the power of landed interests, and formidable legal and administrative barriers.
The latter stem from poor state of land records, pervasiveness of legal loopholes and legal
systems ill-equipped to deal with large volumes of litigation. It can be argued, however,
that persistence of legal and administrative barriers owe ultimately to lack of political will:
when governments really do intend to carry out land reforms they can improve the land
records, push through legislative reforms to close loopholes, and pursue necessary litigation.
From this standpoint political will is the fundamental sine qua non. If so, it is important
to understand the institutional determinants of political will of governments to carry out
land reform.
Post-Independence India represents a interesting instance of stated objectives of land
reform as a central priority of elected governments since the 1950s, where the actual progress
has been minor by comparison. The key problems have been in implementation of the stated
objectives. Agriculture being a state subject in the Indian Constitution, implementation of
land reforms has been left to the state governments, where landed interests often play an
important role. It is generally admitted that the pace of implementation has been largely a
2
matter of political will of the corresponding state governments (see, for example, the review
of the Indian land reform experience by Appu (1996)).
This paper focuses on the experience of West Bengal, an Indian state with a democrat-
ically elected Left Front government continuously since 1977, which is widely believed to
have enacted a successful land reform program during this period. From 1978 onwards,
they created a system of mandatory election to local governments with a five year term,
and devolved to them significant responsibility for implementation of the reforms. The
principal reform initiatives comprised land redistribution (patta program) and registration
of sharecroppers (barga program). Our analysis is based on a longitudinal dataset we have
assembled of 88 villages spread throughout the state spanning three decades.
West Bengal politics has been characterized by competition between two leading parties,
the Left Front coalition, and the Congress party. The Congress party dominated state
politics until the mid-1960s, whose traditional base in rural areas has been dominated by
big landlords. Since the late 1970s, the Left Front has dominated both the state legislature
and local governments. It represents a constituency dominated by landless and marginal
landholders, with big landowners stated as the ‘class enemy’ in the party’s ideology. Given
that the land reform program of West Bengal appeared to take off only after the advent
of the Left Front government in the late 1970s, a natural hypothesis is that differences
in redistributive ideology of elected governments accounted for the post-70s acceleration
in reforms. An alternative and more cynical view is that the compulsions of electoral
competition combined with opportunistic power-seeking motives were the real driving forces.
Given large degrees of landlessness, high population density and ‘land hunger’ emanating
from lack of adequate employment opportunities in industry, land reforms represented a
way for the Left parties to build up a large electoral constituency among the poor.
These alternate views correspond to different political economy theories. The ideology
based hypothesis (dating back to Lipset (1960) and Wittman (1973)) states that parties
or politicians have intrinsic policy preferences derived from their ideology (defined broadly
to include interests of constituents they represent). Combined with the assumption that
candidates cannot commit to their policy platforms, and that they ignore implications of
3
current policy choices for future re-election prospects, such a theory implies that policy
choices of elected candidates are entirely ‘ideology’ determined. Accordingly predicting
policy choices translates into predicting electoral success of parties with different ideologies.
In contrast, the theory of Downs (1957) stresses the role of competition and electoral
opportunism, by assuming that candidates have no intrinsic policy preferences. Policies are
chosen in order to secure votes in current or future elections. In a two candidate setting it
predicts policy convergence: both candidates select the same policy owing to their common
vote-maximization objective. Such a theory thus predicts policy choices are independent
of the identity of the winning candidate, and are explained instead by preferences and
turnout patterns of voters. In contrast to the ideology-based theory which stresses the role
of political parties, the Downsian view stresses the role of competitive electoral incentives:
that political will is driven ultimately by policy preferences of voters, not parties.
Simple correlations with the share of seats in local governments (gram panchayats (GP))
captured by the Left Front — either across villages over the entire twenty year period,
or within villages across successive elected local governments — show no support for the
ideology hypothesis. While the correlations are generally statistically insignificant, the data
shows an inverted U-pattern in both cross-section and longitudinal data, with the downward
sloping portion prevailing over most of the sample. The absence of a significant relationship
between Left share of local government seats and land reforms implemented are consistent
with the Downsian model.
However this inference is subject to two significant caveats. First, there is potential
endogeneity bias: the success of the Left is presumably jointly determined along with policies
implemented. Second, the inverted-U relationship if at all empirically significant would need
to be explained, as it is not consistent with the predictions of a standard Downsian model.
To address the first problem, we use instruments for observed success of the Left Front
in local elections. It turns out that changes in Left success in local government elections
were primarily explained by changes in the inflation rate in the region, and in the fortunes of
the Congress party in the national Parliament, in combination with historical incumbency
patterns in local areas, rather than changing socio-economic circumstances of the villages
4
concerned. The identification assumption underlying our analysis is that fluctuations in the
fortunes of the Congress party in national politics were uncorrelated with fluctuations in
preferences of rural voters for land reform in their respective villages. This is plausible given
that changes in national political coalitions were driven largely by events at the national
level, such as the assassinations of Indira Gandhi and Rajiv Gandhi, the rise of the Bharatiya
Janata Party and other regional parties in other parts of the country.4
It turns out that the patterns observed earlier continue to hold despite controlling for
endogeneity bias. So we then address the second problem, by developing a model of two
party competition which nests the standard Downsian and ideology-based models, besides
allowing for political moral hazard (in the form of rent-seeking or administrative effort).5
Interactions between moral hazard and evenness of electoral competition provides an expla-
nation for an inverted-U relationship, in terms of the greater susceptibility of a dominant
political party to moral hazard: a more lop-sided electoral contest (arising from more skewed
preferences amongst voters in favor of one party) translates into lower effort by the dominant
party to secure favor from a majority of poor voters by carrying out land reform.
In the case of the land distribution program, we subsequently find empirical evidence of a
statistically significant inverted-U, as well as the interaction effects predicted by the theory.
Correlations with demographic patterns and the local land distribution are also consistent
with the Downsian theory that voter preferences mattered. In the case of the sharecropper
registration program, the results are qualitatively similar but not as statistically precise.
Both programs additionally show significant spikes in pre-election or election years. These
results are difficult to reconcile with an ideology-based hypothesis. We are thus led to
the conclusion that electoral competitiveness motives predominated, in conjunction with
political moral hazard. The results suggest that evenness of political competition matters
in influencing political will, and therefore strengthening electoral institutions to promote
4Lagged Left share of GP positions provides another instrument for current Left share, controlling for
village fixed effects. This econometric specification is not rejected by the data.5This extends hybrid ideology-competition models of Lindbeck-Weibull (1993) and Dixit-Londregan
(1998) to accommodate moral hazard. Similar predictions would also result from the special interest models
of Baron (1994) and Grossman-Helpman (1996), as shown in an earlier version of this paper.
5
political competition can have benign effects on growth and poverty reduction.
The paper is organized as follows. Section 2 describes the institutional background to the
West Bengal land reforms. Section 3 presents descriptive statistics, and Section 4 describes
the polar hypotheses of ideology and opportunism in the context of a probabilistic voting
model. Section 5 presents censored regressions of land reform with respect to Left control
of local governments which indicate evidence against both theories. Section 6 explores
robustness of these findings with respect to endogeneity of Left control. Section 7 then
presents the hybrid model with political moral hazard, and Section 8 tests this empirically.
Finally, Section 9 concludes. Details of the data sources are described in the Appendix.
2 Historical Background
Following Independence in 1947, land reforms were an important priority for newly elected
governments at both the central and state levels in India. These included abolition of
intermediary landlords (zamindars), redistribution of lands above mandated ceilings, and
regulation of tenancy. Responsibility for agricultural policy was vested in state governments
under the Indian Constitution. Respective states proceeded to enact suitable legislation in
the early 1950s, with encouragement and assistance from the central government.
2.1 Land Redistribution Program
Legislation governing land reform in West Bengal for the period under study is defined by
the second West Bengal Land Reforms Act, passed in 1971. This Act imposed a limit of 5
‘standard’ hectares of irrigated land (equal to 7 hectares of unirrigated land) for a family
of up to five members, plus 12 hectares per additional family member, up to a maximum
of 7 hectares for each family.6 Landowners were required to submit a return (Form 7A)
providing details of the lands in their possession, their family size, and the surplus lands that
they would consequently surrender. Problems of implementation of the new Act however
6One hectare equals two and a half acres.Orchards were allowed 2 standard hectares, and religious and
charitable organizations up to 7 standard hectares (except in suitably deserving cases).
6
soon became evident, arising out of the need to identify the genuine family members of any
given landholder (Appu (1996, p.176)), and nonfiling of returns by an estimated one half of
all landholders.
In 1977, the Left Front came into power in the state, displacing the Indian National
Congress which had formed the government for all but three years since Independence. A
left-wing United Front government had briefly taken over for three tumultuous years in the
late 60s, a period too brief to implement any serious structural changes. Since 1977, the
Left Front has won a majority in all subsequent elections to the state legislature, in marked
contrast to all other Indian states where incumbents have frequently lost office and even
otherwise rarely secure an outright majority.
Immediately upon forming the government, the Left Front set about implementing the
1971 West Bengal Land Reforms Act, which had been amended in 1972. Some of the legal
loopholes (registration of land in religious and charitable trusts, and conversion into ponds)
were sought to be closed by a new amendment in 1981, which however was approved by
the country’s President only in 1986. The President had inserted a number of statutory
provisions (e.g., requiring the government to issue notices to landowners, and wait for their
returns before taking any action to recover surplus lands above the ceiling), which reduced
their effectiveness considerably. Owing both to this and the high degree of fragmentation
of holdings in process for a few decades that reduced the amount of land in large holdings,
the government was not able to vest (i.e., secure land from surplus landholders) as much
land as it had originally hoped to.7
Where the Left Front appears to have distinguished itself was distribution of vested
lands in the form of land titles or pattas to poor households, and the tenancy registration
program of Operation Barga. According to most accounts, this was largely a matter of po-
litical will (see, for example, Appu (1996), Bergmann (1984), Kohli (1987) or Lieten (1992,
p. 128-9)). A massive mass-mobilization campaign involving party leaders, local activists
and the administrators was mounted to identify surplus or barga land, and distribute (or
7Compared to other states, however, the West Bengal government appears to have performed significantly
better on this dimension — whereas in the early 70s West Bengal had an estimated 1.8% of all declared
surplus land in the country, by 1985 this had increased to 16% (Lieten (1992, p. 127)).
7
register) them. Election to local governments (panchayats) were mandated from 1978 on-
wards, and the active cooperation of the newly elected bodies was sought in this process.
The panchayats set up land reform committees (Bhumi Sanskar Sthayee Samiti) with the
state government’s junior land reform officer acting as convener, which was empowered to
form ‘lists’ of surplus lands and of suitable beneficiaries. Settlement camps were set up,
with follow up re-orientation camps, to create an open and participatory process for the
preparation of these lists, in which tenants and poor farmers participated widely (Lieten
(1992, pp 135-136)), Pramanick and Datta (1994, p. 17-18) and Webster (1992, pp. 74-78)).
Most commentators have reviewed the outcomes of this process favorably. P.S. Appu
(1996, Appendix IV.3) estimated the extent of land distributed in West Bengal until 1992 at
6.72% of its operated area, against a national average of 1.34%; only one other state (Jammu
and Kashmir) achieved a higher percentage, with the vast majority of states distributing
less than 1.5% of operated area.
2.2 Sharecropper Registration: Operation Barga
The Left Front government amended the law concerning sharecropping contracts immedi-
ately upon assuming power in 1977. These amendments made sharecropping hereditary,
rendered eviction by landlords a punishable offense, and shifted the onus of proof concerning
identity of the actual tiller on the landlord. The 1981 Amendment Act received Presidential
assent in 1986 restricted the scope of the Act to sharecroppers (bargadars) with less than
10 acres.
The Left Front government subsequently made Operation Barga the centerpiece of its
mass mobilization effort of poorer peasants throughout the state. Membership in the Kisan
Sabha swelled from 1.3 million in 1977-78 to 8.5 million by 1990. While the initial drive
in 1979 was interrupted by the floods, the operation was mounted again in 1980, with the
active cooperation of the panchayati institutions. Over a million bargadars were registered
by 1981, up from 242,000 in 1978 (Lieten (1992, Table 5.1)), and increasing to almost
one and a half million by 1990. Lieten (1992, p. 161) estimates on the basis of different
assumptions concerning the actual number of sharecroppers in the state, that upwards
8
of 80% of all sharecroppers were registered in the state. The government estimates of
sharecropper registration are somewhat lower, of the order of 65% by the early 1990s.
3 Descriptive Statistics
Table 1 provides the district-wise breakdown of the sample, as well as the percent seats
in the GPs secured by the Left front alliance party. The Left secured a majority in most
districts. The mean proportion of GP seats secured by the Left was 69%, with the median
slightly higher, and with the first quartile at approximately 50%. In three quarters of the
GP administrations, thus, the Left obtained an absolute majority. Most of the variation
in the political composition of the GPs thus represented the extent of majority control
of the Left, rather than switches in majority between the Left and its principal rival, the
Indian Congress party (or Congress, for short). Table 2 shows variation in the control and
popularity of these two parties over successive elections, aggregated across all the sample
villages. The control of the Left waxed somewhat in the 1983 elections, falling from 74% to
63%, but recovered thereafter to between 68–70% of GP seats. The vote shares of the Left
and Congress in the immediately preceding elections to the state legislature (or Assembly,
for short) indicate that these two parties together accounted for over 80% of all votes cast.
Their collective share of all GP seats was above 90% on average. Accordingly we shall view
the political contest as involving just these two parties.
Table 3 provides economic and demographic characteristics of the sample villages and
how these changed between 1978 and 1998. There was a sharp increase in the number of
households within villages, owing to population growth, migration, and splits of joint house-
holds. Landlessness grew, with landless households comprising over half the population by
1998. On the other hand, among landowners the land distribution became more equal, with
a significant redistribution of land (about 20%) from medium and big holdings to marginal
holdings.8 Illiteracy rates fell, especially among the landless and small landowners. Wage
rates rose by 28%, nonagricultural occupations became more important, and farm yields
8These shares closely parallel shares of different size classes in the state Agricultural Censuses between
1980 and 1995, lending confidence to our survey estimates of the land distribution.
9
doubled between the early 1980s and mid 1990s.
Tables 4 and 5 provide details of the land redistribution program. Between 15–20%
of operational land area had been vested, or secured from surplus owners by 1998. This is
consistent with the estimate reported by Appu (1992). However most of the vesting occurred
prior to 1978, confirming accounts that the Left Front did not achieve much progress on this
dimension since coming to power in 1977. Their achievement was much greater with regard
to distribution of land titles or pattas to the landless, as shown in Table 5. Approximately
70–75% all patta land in 1998 had been distributed after 1978. Most of the distributed land
was cultivable (ranging between 70 and 90%). We shall therefore focus on patta distribution
rather than vesting operations when examining the land redistribution program.
Distributed patta land in our sample constituted about 3% of operational land area in
the Gangetic part of West Bengal, and 5.5% for the state as a whole, somewhat below the
state government’s own statistics or the estimate of Appu already cited. The proportion
of households receiving pattas was 15%, higher than the proportion of operational land
area distributed. Patta holders constituted about 30% of all landless households, roughly
consistent with the statistics quoted by Lieten (1992). The land distribution program was
therefore far more significant in terms of the number of households that benefited from the
program, rather than actual land area distributed. Most recipients received plots below 1
acre in size, substantially below average holding sizes in the village.
The fact that land distributed (3–5%) was substantially less than the total amount
of land vested (16%) is somewhat surprising. One typically expects appropriation rather
than distribution to be the difficult component of land reform implementation, from either
political, legal or administrative standpoints. Why wasn’t the government distributing lands
it had already appropriated? One can only surmise the reasons for this, based on anecdotes
and opinions expressed by various people associated with the reforms. One account is that
lands officially listed as vested were still under litigation, and the process of identifying
suitable beneficiaries and granting them official land titles was lengthy and cumbersome.
Another is that local landed elites exercise influence over local governments to prevent
distribution of land titles to the poor, for fear that this will raise wage rates of hired labor,
10
and reduce dependence of the poor on them for credit and marketing facilities. The most
common account is that elected officials exploit undistributed vested lands for their personal
benefit in various ways. For instance, informal accounts allege that undistributed vested
lands are used by GP officials to allocate to select beneficiaries to cultivate on a temporary
basis, as instruments of extending their political patronage. There may also be outright
corruption whereby GP officials extract rents from the assigned cultivators.9 Irrespective
of which is the correct story, it is evident that the the availability of vested land did not
constrain the distribution of land titles; instead political will did.
Equally surprising is how small the patta program was in comparison to the changes
in land distribution occurring through market sales and/or household subdivision. Recall
from Table 3 that the proportion of non-patta land in medium and big holdings declined by
about 20%, through land sales or subdivision, and fragmentation of landholdings resulting
from splitting of households. This ‘market’ process was thus almost six times as large as
the redistribution achieved by the patta program, and thus unlikely to have been ‘caused’
by the latter. Accordingly we shall use the distribution of non-patta land as an independent
determinant of voter demand for land reform.
Turning now to the sharecropper registration process, Table 6 shows that the proportion
of cultivable land affected was of the order of 6–7%, and the proportion of households
registered was approximately 3–5%. Hence the barga program represented approximately
twice the land area, but considerably fewer households (one-third), compared with the patta
program. The proportion of sharecroppers registered was of the order of 50%, slightly below
the state-wide registration rates of 65% reported in the early 1990s.
Regarding timing of the reforms, the bulk occurred in the first two local government
administrations spanning the ten year period between 1978 and 1988. This is shown in
Table 7. Table 8 shows that a significant fraction of villages in the sample witnessed no
reforms at all — over one quarter over the entire twenty year period. Only 4–6 villages
out of 88 witnessed some reforms in every single administration. This indicates the need to
9We have been informed of this by Debu Bandyopadhyaya, the Land Reforms Commissioner during the
late 1970s and early 1980s. We have also recently heard such accounts in the course of our currently ongoing
surveys of these villages.
11
incorporate endogenous censoring in the empirical analysis.
4 Theory: the Polar Hypotheses of Ideology and Oppor-
tunism
In this section we present a model of probabilistic voting with electoral competition be-
tween two parties with differing assumptions concerning objectives of these parties, which
correspond to polar hypotheses of ideology and opportunism.
Consider any village v with total voter population normalized to unity, where voters
belong to different landowning classes c = l, g, s, m, b consisting respectively of the landless,
marginal,small, medium and big landowners. The last category consists of those holding
land above the legislated ceiling, from whom the government may seek to vest lands and
distribute to the landless. The demographic weight of class c is αc. Elected governments
select a policy π from some policy space P . Preferences of a voter in class c are represented
by utility Uc(π).
There are two parties denoted L and R. Let the policy of a party p candidate or elected
official be denoted πp. These represent either the policy platform of the candidate prior
to the election, which the candidate is committed to in the event of being elected. Or it
represents the policy actually carried out by the candidate while currently in office. In this
case, we shall assume that voters project the current policies into their future expectations,
so voting behavior in the next election is determined by these policies.
A fraction τc of class c voters turn out to vote in the election. Of these, a further
fraction βc are aware voters, the rest are impressionable.10 Aware voters respond to policy
differences as well as intrinsic loyalties to the two parties which are exogenously determined.
Impressionable voters vote entirely on the basis of their loyalties. We assume that within
village v, relative voter loyalty to the party L candidate is distributed uniformly with density
fc (which may be specific to the class c the voter belongs to) and mean εdct.
10Grossman and Helpman refer to them as ‘informed’ and ‘uninformed’ in their 1996 article, and as
‘strategic’ and ‘impressionable’ in their 2001 book.
12
An aware voter in class c with loyalty ε votes for the L party candidate if Uc(πL) + ε >
Uc(πR). An impressionable voter with relative loyalty ε to the Left party votes for that
party as long as ε > 0.
The resulting vote share of the Left party is (with γc denoting τcfc:)
VL =12
+1
∑c αcτc
[∑
c
αcγcεdct +
∑
c
αcβcγc{Uc(πL) − Uc(πR)}]. (1)
Vote shares determine the probability φL of the Left party winning the election, accord-
ing to φL = φ(VL), a strictly increasing, continuously differentiable function. The presence
of randomness in election turnout, and errors in vote counting cause this function to be
smooth rather than a 0 − 1 discontinuous function.
Turn now to the objectives of parties. In the Downsian model, each party has no
intrinsic policy preferences, and seeks only to maximize the probability of being elected.
Then each party seeks to maximize its vote share. It follows from expression (3) that
both parties must select the same policy π∗ which maximizes∑
c αc[βcγc]Uc(π)], a quasi-
utilitarian welfare function in which the welfare weight for any class βcγc is the product of its
turnout (τc), voter awareness (βc) rates, and the proportion of swing voters (fc) within that
class. In this case both parties converge to the same policy that is desired by the ‘average’
informed swing voter — implying that party background is irrelevant in predicting policy
choices. The probability that any given party is elected is then determined entirely by the
(exogenous) voter loyalties. Note that this result does not necessarily require that parties
or candidates commit to their policies in advance of the elections. It could be the result of
choices actually made by elected officials of either party, with the objective of maximizing
the probability of being subsequently re-elected.
In the ideology model, parties have intrinsic preferences over policy choices. These could
be ideologically determined in part, or driven by the interests of constituents that the party
represents. For expositional convenience, however, we shall refer to these as ‘ideology’, and
represent it by a set of welfare weights wic assigned by party i to the interests of class c. It
is natural to suppose that the Left party assigns greater weight to classes owning less land,
with the opposite true for the Right party, so the ideologically desired policies by the two
13
parties are ordered, with the Left party desiring greater land reform: π∗L > π∗
R where π∗i
maximizes∑
c αcwicUc(π).
In addition, one needs to assume that elected officials neglect the effect of current policies
on future re-election. Then elected officials select their ideologically most preferred policies.
Votes are cast in elections where voters anticipate these policy choices, so the probability of
winning the election are determined partly by ideology or policy differences, and partly by
voter loyalties. In contrast to the Downsian theory, here policies are determined by party
rather than voter preferences, and policy convergence does not occur. The more Left party
candidates in office, the greater will be the extent of land reform.11 Exogenous swings in
voter loyalties in favor of the Left will raise the fraction of Left candidates elected, and
leave the policies espoused by either party unchanged, resulting in greater land reform.12
In contrast, the Downsian model predicts that there will be no effect on land reform. Hence
the two models generate distinct predictions for the correlation between land reform and
the fraction of GP positions secured by the Left.
5 Preliminary Empirical Patterns
Tables 9 and 10 present regressions of different measures of land reforms implemented with
respect to the Left share of GP seats. The different measures are pattaland: proportion
of cultivable land in the village distributed in the form of pattas; pattadar: proportion of
households who received pattas; bargaland: proportion of cultivable land registered under
the barga program; and bargadar: proportion of households registered in this program.13
11Each local government or GP is a council of elected members, one from each electoral constituency. It
is reasonable to suppose that the chosen policy weights the desired policies of both parties, with the weight
on any party increasing in the fraction of seats secured by that party.12Indeed, given the natural assumption that party ideologies do not change from one election to the next,
changes in relative electoral success of the two parties must result from such loyalty swings, so there is a
one-to-one relation between these two variables.13We do not use the barga registration rate owing to the significant underreporting of tenancy in the
household survey, which artificially inflates the registration rate. For almost forty villages no land was
reported as under tenancy in 1978, while significant numbers of bargadars were recorded in the 1970s in
14
Owing to the significant censoring in the data, we report results of tobit regressions.
The cross-section tobits aggregate across the entire twenty year period 1978–98, while the
panel tobits aggregate within each five year period spanning a single GP administration14,
and use dummies for districts as well as for the four time blocks. We do not use village
fixed effects because of the well known inconsistency of tobit estimators with village fixed
effects. The number of fixed effects to be estimated declines substantially when they are
at the level of the district: consistency of the estimator refers to limiting properties as the
number of villages per district grows large, assuming that all the unobserved heterogeneity
arises at the district rather than village level. The cross-section patta tobits controls for the
proportion of land vested by 1978 which represented the land available for distribution, and
the population density in 1978 which represents a measure of the demographic pressure for
land distribution. The cross-section barga regressions control for the extent of unregistered
barga land or households in 1978, which represented the potential for registration.
In no case do we see evidence of a significant relationship of land reforms implemented
with Left control of the local GP. The signs and magnitudes of the estimated coefficients
imply that the nature of this relationship follows an inverted-U, with a turning point at or
below the mean and median Left share. This implies that for the majority of the sample,
higher Left control was associated, if at all, with less land reform. This is clearly contrary
to the pure ideology model. The absence of a statistically significant relationship may be
viewed as consistent with the predictions of the Downsian model.
However, the simple correlation between land reform and Left control may conceal
the true underlying relationship, if there are other factors correlated jointly with both
outcomes. For instance, it is natural to expect the landless to have a greater demand for
land reform, and greater loyalty to the Left. A rise in landlessness would then increase
both variables under either theory, implying that the observed correlation overstates the
those villages. The registration rate cannot be computed for these villages. We therefore express the scale
of the barga program relative to the total cultivable area and number of households in the village instead.14Election years are treated as part of the time block of the outgoing administration, given the existence
of lags arising from legal delays and the fact that a new administration usually assumes office in the second
half of the year.
15
true (partial) correlation. This is when turnout, awareness and ‘swing’ factors among the
landless are not significantly lower than for the remaining population. If on the other hand
the landless are significantly less aware, turn out less or less prone to switch votes in response
to policy differences than other classes, then a rise in demographic weight of the landless
would generate less land reform under the Downsian theory. Then rising landlessness would
generate a negative correlation between land reform and Left control, under the Downsian
theory. To test this theory, it is therefore important to control for demographic proportions
of different size classes, or other village characteristics that might be correlated with either
land reform or Left electoral success.
Tables 11 and 12 present results for censored regressions which control for village char-
acteristics such as demographic weight of different landowning size classes, land shares,
proportion of households belonging to scheduled castes or tribes, and illiteracy rates of non-
big (which aggregates landless, marginal and small landowners) and big landowners. Land
size classes are defined by ownership of cultivable non-patta land, with marginal, small,
medium and large categories defined by 0-2.5, 2.5–5. 5–12.5 and 12.5– acres respectively.
Village demographics, land distribution and illiteracy rates are interpolated for different
time blocks based on their respective rates of growth between the two survey years.
Tables 11 and 12 also reports results for the semiparametric trimmed LAD estimator
with village fixed effects proposed by Honore (1992). Besides controlling for inter-village
heterogeneity and censoring, the latter estimator avoids the normality assumption on resid-
uals, replacing it with only a symmetry (i.i.d.) restriction on the distribution of residuals.
Moreover, Tables 11 and 12 report regressions applied to yearly data, instead of aggre-
gates across five-year timeblocks corresponding to different elected GPs, and controls for
election and pre-election year dummies. Use of yearly data permits controlling for the tim-
ing of elections, which is an additional way to discriminate between hypotheses of electoral
opportunism and ideology. The former model would predict higher land reforms immedi-
ately before an election, when voters are more likely to project current policies to the future,
and elected officials pay more attention to their re-election prospects. Such election year
effects should not arise in a pure ideology model.
16
In addition, the use of yearly data permits the coefficients to be more precisely estimated
owing to an expansion in sample size, compared with data aggregated into five year time-
blocks corresponding to the tenure of each elected GP. On the other hand, standard errors
may be underestimated with yearly data if residuals are highly correlated across different
years within a given GP administration in a given village. In that case observing reforms
implemented in different years within the tenure of a given GP does not really constitute
more information than is contained in the aggregate for the entire five year block. How-
ever, this is a problem which tends to be significant only if the number of ‘groups’ is small
(Donald and Lang (2004)): in our context here a ‘group’ corresponds to a village-timeblock
combination, and our dataset contains over 300 village-timeblocks. So this problem should
not be particularly significant. Nevertheless the presence of serial correlation may imply
that the standard formulae for standard errors are subject to bias, if the nature of this serial
correlation cannot be represented by a fixed shock for each village-timeblock combination,
as pointed out by Bertrand, Duflo and Mullainathan (2004). For a later specification of
the TLAD regression we shall examine the robustness of our results with respect to this
potential problem, by reporting standard errors obtained from bootstrapping the estimator.
We see that virtually the same patterns as in Tables 9 and 10 are repeated in Tables 11
and 12 — absence of a monotone increasing relationship with Left share of GP seats, and an
inverted-U pattern whenever the coefficients are statistically significant (which is the case
for the pattadar and bargadar regressions with village fixed effects). There is a significant
election year positive spike in barga activity, and a negative election year spike in patta
activity. GP elections are held in the April of an election year, and the new government
tends to take charge by June. So an election year represents three months of an outgoing
administration, and six months of an incoming one. Both a positive or negative spike is
then consistent with the Downsian theory, where the positive component results from the
higher than average efforts of the outgoing administration or its hangover, and a negative
component from the lower than average efforts of the incoming one. It is much harder to
rationalize them under the ideology hypothesis, since party ideologies are unlikely to change
from one year to the next. So the evidence continues to still be inconsistent with the ideology
hypothesis. The inconsistency with the Downsian hypothesis is substantially less, but the
17
problem of explaining a significant inverted-U in pattadar and bargadar regressions remain.
It is possible, of course, that unobserved components of village voter preferences that
simultaneously change land reform and Left electoral success account for an inverted-U
under either hypothesis. The only way to deal with this problem of potential endogeneity
of Left control, is to seek suitable instruments for this variable.
6 Predicting Success of the Left in Local Elections
Probabilistic voting models allow voting behavior to reflect both loyalties of voters to dif-
ferent parties for various exogenous reasons (such as historical factors, incumbency, the
specific characteristics of candidates etc.), as well as their policy preferences. We can there-
fore search for measures or determinants of voter loyalty to the Left that reflect factors
external to the village, or historical circumstances orthogonal to land reform related issues
in the current election. The Left and Congress contest elections at different levels, such as
the state and federal legislatures (which we shall henceforth refer to as the Assembly and
Parliament). These elections are staggered across different years: the Assembly elections
are typically held one or two years before the GP elections (they were held in 1977, 1982,
1987, 1991 and 1996). The Left and the Congress are the principal adversaries in the state
assembly elections, as well as elections for seats representing West Bengal constituencies in
Parliament.
Given that local government elections were introduced for the first time in 1978, and
that most voters in India tend to view politics in terms of state or national rather than local
issues, it is plausible to suppose that voter loyalties in local elections were determined to a
large extent by regional or national issues. These may include inflation in consumer prices,
growth in factory employment, or the relative strength of the two parties in the national
Parliament. The Congress formed the national government between 1980 and 1984, and
reinforced its position between 1984 and 1989 following the assassination of Indira Gandhi
in 1984. Between 1989 and 1991 a non-Congress government prevailed at the national level,
representing a coalition of different regional parties supported by the West Bengal Left
18
Front. Then again from 1991 until 1996 the Congress formed a government at the national
level, with the Left in the opposition.
The fluctuating strength of the two parties in Parliament had considerable implications
for relations between the central and the state government over fiscal transfers, execution
of central government projects in the state, and other matters likely to have significant
spillovers into inflation, employment and public services in rural areas. For instance, a
Congress party member elected to a Parliamentary seat from a specific West Bengal con-
stituency would be in a position to direct public projects in railways and irrigation to his
constituency, thus boosting loyalties of voters towards the Congress in local GP elections.
Conversely, Left candidates often blame Congress dominated central governments for starv-
ing the state of fiscal transfers or public investments for partisan reasons, and use this in
their election rhetoric in order to mobilize voters against the Congress party.
Table 13 presents regressions predicting Left control of local GPs, on the basis of a
variety of factors both external and internal to the villages in question. The external
factors include the proportion of seats secured by the Congress in the currently elected
Parliament, the rate of inflation over the past five years in price index for agricultural
workers in the nearest regional center (among four centers in the state for which this index
is constructed by the government: Calcutta, Jalpaiguri, Ranigunj and Asansol), and the
growth in factory employment in the district over the last five years. The inflation and
employment variables are constructed at a much higher level of aggregation than a single GP:
there were approximately 200 GPs in each district, and between three and five districts in
each region. Hence these variables reflect economic changes covering a much larger area than
the jurisdiction of a single GP. We also include the average vote share difference between Left
and Congress candidates in the immediately preceding state Assembly elections, averaged
at the district level, as a proxy for prevailing voter loyalty to the two parties on the basis
of district, state or national issues.
The local factors that may affect electoral success of the Left in GP elections include
incumbency patterns in the GP, besides land distribution, literacy and caste in the village.
The regressions interact local incumbency with external factors, since voters reaction to
19
changes in inflation and employment may depend on which party has been dominating in
the local area. For instance, a rise in inflation is likely to cut into support of the local
incumbent and strengthen the position of the opposition party.
Table 13 shows results of the GP Left share regression applied to five successive GP
elections (1978, 1983, 1988, 1993 and 1998). The first two columns show cross-section least
squares results, while the remaining three show the panel estimates. In the panel we use
the Arellano-Bond (1991) estimator to avoid the bias that arises from a lagged dependent
variable (incumbency) as a regressor. The hypothesis of lack of first-order serial correlation
in the level of the time-varying errors (equivalently lack of second-order correlation in the
differenced residuals) is not rejected at most conventional levels of significance. Hence
(controlling for village fixed effects) lagged Left share is also a valid instrument for Left
share in the land reform regression.
The cross-section results show that the assembly vote share difference at the district
level was a strong predictor of local GP outcomes. Of remaining village characteristics,
only caste and literacy among the poor were statistically significant influences. The local
land distribution was not significantly related to local GP control secured by the Left. In
the panel, local literacy or caste become unimportant, while the role of voter loyalty at the
district level remains robust (last column of Table 13). Voter loyalties at the district level,
in turn, are shown in Table 14 to be related to lagged loyalty, regional inflation rate, and
Congress presence in Parliament.
The third and fourth columns of Table 13 replace the district voter loyalty variable
by its underlying determinants directly. These show that changing fortunes of the Left
in GP elections (conditional on incumbency patterns) were driven mainly by changes in
factors external to the villages — the regional inflation rate, and the presence of Congress
in the national Parliament — rather than changes in village characteristics.15 The nature of
these effects are intuitively plausible: rising inflation hurt the local incumbent, while rising
Congress fortunes at the national level helped the Congress in GP elections in constituencies
15Inclusion of lagged land reform in the village concerned on the right hand side did not yield a significant
coefficient either, irrespective of whether it was included by itself or in interaction with incumbency.
20
where they were already strong. This may reflect the tendency for Congress ministers in the
national government to favor their own constituencies in the location of central investment
programs. Somewhat more surprising is that a rise in the presence of the Congress at
the national level also benefited the Left party in areas where the Left was traditionally
powerful. We presume this reflected the ability of the Left to gain mileage in local elections
by blaming a Congress-dominated national government for local problems.
6.1 Instrumental Variable Estimates of the Land Reform-Left GP share
relationship
The preceding results imply that external and historical factors driving the fluctuations
in Left control of local GPs are suitable instruments which can be used to correct for
potential endogeneity of the Left share variable in the land reform regression. The presence
of Congress in the national Parliament seems particularly suitable as an instrument, as
these principally reflected the increasing importance of coalition politics at the national
level, and other events in the rest of the country (seccessionist movements in Punjab and
Kashmir, the assassinations of Indira Gandhi and Rajiv Gandhi which subsequently created
a pro-Congress wave, rising power of regional parties and the Bharatiya Janata Party in
other parts of India, and border tensions with Pakistan)). These factors are likely to be
uncorrelated with time-varying village specific voter preferences for land reform. Moreover,
Table 13 shows we cannot reject the hypothesis of absence of serial correlation in the Left
share regression after controlling for village fixed effects, which implies that incumbency
(lagged Left share) is also a valid instrument.
Accordingly, we use the fourth column of Table 13 to predict the Left share in each
GP, and then use these to generate instrumental variable tobit and TLAD estimates of the
land reform-Left share regressions. The correlation between the predicted and observed
changes was .32, so the IV estimates are unlikely to suffer from a weak instrument problem.
The IV estimates of the tobit and TLAD regression coefficients of Left share of GPs and
election/pre-election year dummies are reported in Tables 15 and 16. The standard errors
do not correct for the prediction errors with respect to the first stage regression, so represent
21
underestimates of the true standard errors. This does not matter here because even with
the underestimated standard errors we see no evidence of a significant positive relationship
between local Left control and land reforms implemented. Only in the case of the village
fixed effect TLAD regression for bargadar do we see a statistically significant relationship
at 5% significance or less, but this relationship follows an inverted-U. The election year
dummy is significant in this regression. Thus we continue to not find evidence in favor of
the pure ideology hypothesis.
The weak relationship with local Left control evidence indicates closer support for the
Downsian hypothesis. However, the inverted-U pattern for bargadar is not consistent with
it. It makes sense, therefore, to probe possible reasons for an inverted-U relationship. This
is the topic of the next section.
7 A Hybrid Model with Moral Hazard
We argue in this section that the inverted-U pattern can be interpreted as reflecting a form
of moral hazard among elected politicians, wherein those in a strong competitive position
(vis-a-vis potential challengers in the next election) can afford to slacken their land reform
effort. Moral hazard can emanate from costly effort that elected officials must undertake
in order to implement reforms, or from rents foregone from land vested that has not been
appropriated. A conflict of interest between voters and elected officials over the desired
extent of land reform can then emerge. Higher levels of land reform will be observed when
the electoral contest is more even, with the GP composition closer to 50-50. We now develop
an extension of the previous model with probabilistic voting to incorporate moral hazard.
We also extend the model to incorporate costly election campaigns mounted by parties
to mobilize impressionistic voters. Apart from moving the model closer to reality, it provides
parties with an additional instrument of electoral strategy which will turn out useful in the
characterization of electoral outcomes. Let Mi denote the size of the campaign mounted
by party i at cost θiMi, where θi > 0 is a given parameter. Then as in Grossman-Helpman
(1996) we assume that (while aware voters vote as supposed previously) an impressionable
22
voter with relative loyalty ε to the Left party votes for that party as long as h[ML−MR]+ε >
0, where h > 0 is a given parameter. The resulting vote share of the Left party is then
12
+1
∑c αcτc
[∑
c
αcγcεdct +
∑
c
αcβcγc{Uc(πL) − Uc(πR)}
+ h∑
c
αcγc(1 − βc)(ML − MR)]. (2)
Denote by χ ≡ h∑
c′ αc′τc′(1 − βc′)fc′ a parameter which represents the value of electoral
campaigns in mobilizing voters, which is proportional to the fraction of impressionable
voters. Then the vote share expression can be simplified to
VL =12
+1
∑c αcτc
[∑
c
γcεdct +
∑
c
αcβcγc{Uc(πL) − Uc(πR)} + χ(ML − MR)]. (3)
In contrast to the Grossman-Helpman (1996) theory, we assume that campaigns are financed
by parties themselves, rather than from contributions raised from special interest groups.
The previous version of this paper shows that similar results obtain in the presence of
campaigns financed by special interests such as big landowners that resist the reforms.16
Moral hazard arises from private costs to elected officials (either effort or foregone rents)
that depend upon the extent of land reform: e = e(π). Party objectives represent a mixture
of opportunism, ideology and moral hazard. The opportunistic component stems from the
opportunity to earn rents while in office. Part of these rents are exogenously fixed, and
denoted Ei for party i. These could represent ‘ego-rents’, or pecuniary rents arising from
the power of officials over other areas of policy apart from land reform. The remaining
variable rent component is represented by −ei(π), and hence the total rent is Ei − ei(π).
The combination of ideology and rent-seeking implies that the objective of candidates
is to maximize the expected value of
∑
c
αcwicUc(π) − e(π). (4)
The ex ante payoff of party i (with j �= i) denoting the other party, and φi, φj ≡ 1−φi their
16We choose the formulation with internal financing and political moral hazard because this seems more
natural in the West Bengal context. The special interest model would be driven by capture of the Left party
by big landowners, which seems rather far fetched.
23
respective win probabilities, is then
Oi(πi, Mi; πj , Mj) = φi[∑
c
αcwicUc(πi) − ei(πi) + Ei]
+(1 − φi)∑
c
αcwicUc(πj) − θiMi. (5)
This formulation presumes that parties commit to policy platforms in advance of the
election. The same characterization of equilibrium policy choices holds when such commit-
ment is not possible, but with voters forecasting future policies from current ones, so the
vote shares in the next election are given by the same function (3) of current policy choices.
Let Di denote the expected rents from future office, and δi the discount factor of a party i
incumbent. Then this incumbent will select πi, Mi to maximize
∑
c
αcwicUc(πi) − ei(πi) + Ei − θiMi + δiφi(Vi)Di. (6)
This model nests different polar theories of political competition. The Downsian model
obtains when we assume that candidates have no ideological preferences (wic ≡ 0), nor any
policy-related sources of personal rents (ei(πi) ≡ 0).17 The pure ideology model obtains
when incumbents cannot commit to their future policies, earn no rents (Ei = ei ≡ 0), and
discount the future at a high enough rate that they ignore implications of current policy
choices on future re-election prospects (δi ≡ 0).
The more general version presented here admits a hybrid of electoral opportunism, rent-
seeking, and ideology. The ingredients we add to the model can all be justified by an appeal
to the reality of the West Bengal political context, besides the need to accommodate the
facts. It is well known that the Left parties have been subject to internal debate concerning
the need to strike a balance between its traditional ideology and opportunism.18 As a
17Then with commitment the payoff of i reduces to maximization of φiEi−θiMi, and with no commitment
reduces to maximization of δiφiEi − θiMi. Hence the policy πi chosen by i must maximize the probability
of winning φi. Expression (3) shows that both parties will select the same policy π∗ which maximizes∑
The coefficient µ1 represents the interaction between moral hazard and competition missing
in the pure Downsian and ideology models. The Downsian model predicts no policy diver-
gence (µ0 = µ1 = µ2 = 0) and irrelevance of voter loyalties (λ1 = 0). The pure ideology
model also implies irrelevance of voter loyalties (µ1 = λ1 = 0), while policy divergence is
predicted (µ0 �= 0, µ2 �= 0). The hybrid model predicts that voter loyalties matter for policy.
If political moral hazard is severe enough in the sense explained in the previous section,
λ1 > 0, µ1 < 0.
Note that in the presence of significant interactions between moral hazard and competi-
tion, the land reform regression estimated previously was misspecified. The interaction ef-
fects are correlated with the Left share variable, causing the estimated coefficient of q(LSvt)
to be biased. The sign of this bias depends on the sign of the interaction effect. If Case 1
applies, the moral hazard-competition interaction causes policy divergence to narrow and
get reversed when voters shift loyalty to the Left, causing a downward bias in the estimated
coefficient µ0.
8.1 Empirical Results
Tables 17 and 18 present estimates of the TLAD land reform regressions corresponding to
(16) with village fixed effects. Both versions with observed and predicted Left shares are
shown (the latter using regional and national determinants of voter loyalties as instruments).
The new terms added are the relative loyalty at the district level (district-average vote share
difference in the most recent Assembly elections) as a measure of competitive strength of
the Left, and its interaction with Left share (both linear and quadratic terms). Standard
errors for the IV regressions are obtained by bootstrapping.20 As before, the regressions20To guard against the possibility of serial correlation in the residuals for any given village not captured
by village fixed effects, we use a block bootstrap as recommended by Bertrand, Duflo and Mullainathan
29
control for non-patta land distribution, literacy and low caste proportions, besides dummies
for different timeblocks, villages and election/pre-election year.
In the pattadar regression, we find a significant inverted-U with respect to Left share
itself, and a negative, significant interaction between Left share and relative voter loyalty.
Similar patterns emerge in the pattaland regression but the estimated coefficients are not
statistically significant. Recall also that the model imposed the restriction that the same
quadratic in LSvt applies in levels and in the interaction with voter loyalty, i.e., the associ-
ated turning points of the level and interaction effects are the same. In the IV regressions
this prediction is almost exactly borne out. Finally, the election year effect continues to be
negative and significant at 10%.
Table 18 shows corresponding estimates for the barga program. Here the interaction
effect is statistically insignificant, but has a negative sign in both IV regressions, again with
similar turning point as the Left share variable itself.
We therefore find some evidence consistent with the moral hazard hypothesis: shifts in
voter loyalty in favor of the Left were associated with a reduction in the gap between the
land reform efforts of the Left and the Congress. This provides part of the explanation for
the inverted-U pattern of land reform with respect to Left share. Since there continues to be
an inverted-U with respect to Left share despite controlling for this interaction effect, this
is only part of the explanation. According to the theory the relation with respect to Left
share ought to have been monotone, representing the effect of greater Left control per se over
GP decisions (the function q). The fact that we continue to find a non-monotone relation
indicates that there are still unobserved components of voter loyalty not captured by our
AVSD measure, which continues to bias downward the estimated slope with respect to Left
share. An alternative explanation is that the distribution of voter loyalty is thin towards
the tails (rather than uniform as supposed in the model), in which case the proportion of
marginal ‘swing’ voters declines when voter loyalties become more lopsided to favor the
(2004). All the data for a given village is kept as a single block, and 200 samples are generated by sampling
with replacement from the observed data blocks. Both first stage and second stage regressions are run for
each sample, so that the bootstrapped standard errors incorporate both first stage prediction errors, as well
as serially correlated residuals.
30
Left, causing a decline in land reform implemented by the Left.
The corresponding coefficients of other village characteristics in the patta and barga
regressions are shown in Table 19. The proportion of households receiving land titles was
significantly higher when there were more marginal landowning households, fewer medium
landowners, and a smaller fraction of non-patta land was in small holdings below 5 acres.
This is consistent with the notion that the patta program was responsive to voter preferences:
marginal and medium landowners are likely to have been the most politically active groups
on either side of the land reform issue within villages. Moreover, the greater the inequality
in landownership, the greater the scale of the patta program. Somewhat surprisingly, the
scale (in terms of land area, though not proportion of households) was significantly smaller
when the demographic weight of the low caste households increased, which could owe to
lower rates of turnout, political awareness or swing voters within these groups. No particular
patterns are evident for the barga program, except a similar pattern for land areas involved
to be smaller in the presence of a larger low caste population, and a positive effect of
illiteracy rates among the poor, which is not easily interpreted.
8.2 Extension to pre-1978 Period
The preceding results did not make full use of the land reform data available to us, which
covers 1971–98. It turns out that a significant amount of land reform was carried out even
preceding the advent of the Left Front government in 1977, comparable in magnitude to
the reforms enacted in the years following 1978. This was a period of rising competitive
pressure on the Congress administration at the level of the state government arising from
the increasing political strength of the Left parties during the 1970s. However the pre-1978
period did not have any elected local government, which was the reason that it was excluded
in the previous regressions. The responsibility for implementing land reform still remained
in the hands of the state bureaucracy during this period.
Nevertheless it could be argued that competitive pressure on the Congress government
at the state level to implement land reform arose in a manner similar to the post-1978
period. The Congress was aware of the rising political aspirations of the Left front, following
31
the participation of the latter in the 1969-71 United Front ministry in the state. It was
also concerned to restrict the influence of the ultra-left Naxalite party which had incited
a violent conflict in the state in the late 60s. Since the Left did not have any elected
political position in the state during 1974–78, it corresponds to a post-1978 context where
the Congress retained all the political power, i.e., a GP with a zero left share.
Tables 20 and 21 extend the results reported above to including the preceding five year
period 1974–78 (with GP Left share set equal to zero). The estimated coefficients in the
patta regressions with respect to the Left share variables are qualitatively similar, and now
gain in quantitative significance, with a significant negative interaction between competitive
strength and moral hazard. The coefficient of the voter loyalty variable by itself is now also
significant: the Congress enacted more land reform during 1974–78 in places where its
popularity was declining faster (between 1972 and 1977). In addition, there is a significant
pre-election year spike in patta activity. The evidence is therefore consistent with the view
that the 1974–78 Congress administration in charge of implementing land reforms at that
time, was influenced by competition from the rising popularity of the Left.
In the case of the bargadar regression, we continue to find a significant inverted-U with
respect to the Left share variables, a positive election-year spike, and a positive effect of the
voter loyalty variable. The interaction effect continues to be imprecisely estimated, though
its sign is consistently negative.
9 Concluding Comments
In summary, land reform implementation in West Bengal cannot be simply explained by ex-
ogenous differences in redistributive ideology between the Left and the Congress. We found
evidence consistent with the presence of electoral opportunism, and for land reform effort
to increase when electoral contests became less one-sided. We interpret this as implying
that the political will of local governments in West Bengal to implement land reforms was
influenced by electoral institutions, and the evenness of political competition in particular.
It suggests that democratic institutions that promote political competition (e.g., electoral
32
rules that limit the scope for manipulation of electoral outcomes by incumbents) can have
important economic effects on growth and poverty reduction.
Other useful results of our analysis include the fact that electoral success of the Left
in local government elections was driven primarily by factors exogenous to the villages
concerned, pertaining to voter loyalties at the district level, based on economic and political
events at the regional, state and national levels. This permits isolation of effect of a variety
of exogenous events on the extent of land reform implemented. In turn it provides a way to
identify the effect of these land reforms on various aspects of farm productivity and quality
of governance within these villages, a task we are currently undertaking in related research
on the effects of these land reforms.
The main shortcoming of our study pertains to the potential measurement error and
endogeneity bias with respect to controls for land market transactions, migration, fertility,
literacy or caste composition. Given the relatively small scale of the reforms we think the
potential for reverse causation is unlikely, but it cannot be ruled out. There is clearly greater
need to measure these control variables more precisely (though the primary variables of
concern — the land reform and Left share of local governments — are themselves precisely
measured). We are currently carrying out direct household surveys in order to better
measure these and understand patterns of household fragmentation and migration, which
should help to control for these factors better.
References
Arellano M. and S. Bond (1991), ‘Some Tests of Specification for Panel Data: Monte
Carlo Evidence and an Application to Employment Equations’, Review of Economic
Studies 58, 277-297.
Appu P.S. (1996), Land Reforms in India, Delhi: Vikas Publishing House.
Bandyopadhyay D. (1986), ‘Land Reforms in India: An Analysis,” Economic and Political
Weekly, XXI, 25/26: A50-A56.
33
Banerjee A., P. Gertler, and M. Ghatak (2002), ”Empowerment and Efficiency: Tenancy
Reform in West Bengal,” Journal of Political Economy, 110(2), 239-280.
Bardhan P. (1973), “Size, Productivity and Returns to Scale: An Analysis of Farm-Level
Data in Indian Agriculture,” Journal of Political Economy, 81(6), 1370–86.
Basu S.K. and S.K. Bhattacharya (1963), Land Reforms in West Bengal: A Study on
Implementation, Calcutta: Oxford Book Company.
Bell C. (1977), “Alternative Theories of Sharecropping: Some Tests Using Evidence from
Northeast India,” Journal of Development Studies, 13(4), 317–346.
Bergmann T. (1984), Agrarian Reform in India, with Special Reference to Kerala, Kar-
nataka, Andhra Pradesh and West Bengal. New Delhi: Agricole.
Berry A. and Cline W. (1979), Agrarian Structure and Productivity in Developing Coun-
tries, Baltimore: Johns Hopkins University Press.
Bertrand M., E. Duflo and S. Mullainathan (2004), “How Much Should We Trust
Diferences-in-Differences Estimates?” Quarterly Journal of Economics, February 2004,
249–275.
Besley T. and Burgess R. (2000) “Land Reform, Poverty Reduction and Growth: Evidence
from India,” Quarterly Journal of Economics 115, no. 2, 389-430.
Binswanger H., Deininger K., and Feder G. (1993), “Power, Distortions, Revolt and
Reform in Agricultural Land Relations,” in J. Behrman and T.N. Srinivasan (Ed.),
Handbook of Development Economics, vol. III, Amsterdam: Elsevier.
Binswanger H. and M. Rosenzweig (1993), “Wealth, Weather Risk and the Composition
and Profitability of Agricultural Investments,” Economic Journal, 56-78.
Bhattacharya, D. (1999), ‘Politics of Middleness: The Changing Character of the Com-
munist Party of India (Marxist) in Rural Bengal (1977-90),’ in B. Rogaly, B. Harriss-
White and S. Bose (Ed.), Sonar Bangla? Agricultural Growth and Agrarian Change
34
in West Bengal and Bangladesh, Sage Publications., New Delhi and Thousand Oaks,
London.
Case A. (2001), “Election Goals and Income Redistribution: Recent Evidence From
Albania,” European Economic Review, 45, 405-423.
Chatterjee P. (1984), Bengal 1920-47: The Land Question, Calcutta: K.P. Bagchi.
Cooper A. (1988), Sharecropping and Sharecroppers’ Struggles in Bengal, Calcutta: K.P.
Bagchi and Co.
Dixit A. and J. Londregan (1998), “Ideology, Tactics and Efficiency in Redistributive
Politics,” Quarterly Journal of Economics, May 1998, 497–529.
Donald S. and K. Lang (2004), “Inference with Difference in Differences and Other Panel
Data,” mimeo, Department of Economics, Boston University.
Downs A. (1957), An Economic Theory of Democracy, New York: HarperCollins.
Franda M. (1971), Radical Politics in West Bengal, Cambridge, MA: MIT Press.
Grossman G. and Elhanan Helpman, “Electoral Competition and Special Interest Poli-
tics,” Review of Economic Studies, 63, 265-286, 1996.
Honore B. (1992), ‘Trimmed LAD and Least Squares Estimation of Truncated and
Censored Regression Models with Fixed Effects,’ Econometrica, 60, 533-565.
Kohli A. (1987), State of Poverty in India, Cambridge: Cambridge University Press.
Lieten G.K. (1992), Continuity and Change in Rural West Bengal, New Delhi: Sage
Publications.
Lindbeck A. and J. Weibull (1993), “A Model of Political Equilibrium in a Representative
Democracy,” Journal of Public Economics, 51, 195–209.
Lipset S.M. (1960), Political Man. Baltimore: Johns Hopkins University Press.
Nossiter T.J. (1988), Marxist State Governments in India, London: Pinter Publishers.
35
Sengupta S. (1981), ‘West Bengal Land Reforms and the Agrarian Scene,” Economic and
Political Weekly, XVI, 25/26: A26-A75.
Webster N. (1992), Panchayati Raj and the Decentralisation of Development Planning in
West Bengal, Calcutta: K.P. Bagchi and Co.
Wittman D. (1973), ‘Parties as Utility Maximizers,” American Political Science Review,
67, 490–498.
36
Data Appendix: Description of Survey Methods and Data
Our data consists of 88 villages (or more accurately hamlets (mouzas)), spread over 16 out
of 18 districts in West Bengal.21 The villages form a sub-sample of an original stratified
random sample of West Bengal villages selected for a farm survey by the Socio-Economic
Evaluation Branch of the West Bengal Department of Agriculture, for purposes of estimat-
ing agricultural production costs in the state.22 The lowest level of village government is
the gram panchayat (GP), which covers on average 8-12 mouzas. Subsequent to our gath-
ering of farm records, the villages in the sample were surveyed to yield details concerning
composition and activities of local governments, besides patterns of landownership, tenancy,
occupational structure, demographics and literacy. The data includes details of elected GP
representatives for every five year term since 1977 (when GP elections were first held), and
a listing of all households in the village from a list of registered voters for a recent election
year (1998 in most instances) and an earlier year (1978 in most cases, otherwise 1983).
Data concerning the extent of land reforms legally implemented was directly collected
from the local block land records office (BLRO) which contained documents of all land
transfers (pattas) and registration of sharecroppers by village. The date on the documents
revealed the exact timing of the recordings, enabling us to construct a panel data set covering
the period 1971–98. This includes the entire Left Front regime until 1998 spanning four
successive sets of local governments, as well as the preceding five year period of Congress
rule at the state level.
The government’s land records record only the official land transfers, rather than the
landownership distribution at any given point of time. The former is the obvious measure
of the (outcomes of) effort of the government to implement the reforms. But these changes
need to be assessed relative to the existing land distribution (e.g., in constructing percent
21Calcutta and Darjeeling were excluded owing to the paucity of agriculture in those districts: Calcutta is
primarily urban while Darjeeling is a mountainous region dominated by tea plantations. District boundaries
within Dinajpur have changed within the period being studied so we aggregate all the data for Dinajpur
villages. We therefore end up with data for 15 districts.22The sub-sample excludes villages in the original sample for which disaggregated farm-level farm produc-
tion records from the 1970s could not be located at state government offices.
37
of land area that was distributed), and the latter can only be assessed by survey methods.
Efforts to use government land records to construct the landownership distribution within
each village did not succeed, owing to the difficulty of consolidating land titles by households.
We therefore conducted an ‘indirect survey’ whereby three or four village elders provided
details of each household on each voter list concerning land owned, leased or cultivated
(area, irrigation status, mode of acquisition for owned land, barga registration status for
tenants), caste, occupation and literacy status. This provided a complete description of
landownership, occupation and literacy distributions for 1998 and either 1978 or 1983. The
information provided was cross-checked across different elders. This was the only practical
method of constructing the landownership distribution by households within the village
and its change over the past two decades, within the timeframe and budget of the village
surveys.23 The alternative of a direct household survey would have been more expensive,
time consuming and subject to the reluctance of households in remote villages to disclose
their assets to outsiders.24 Our method exploits the fact that landholdings of different
households are well known within the village, and especially to village residents of long
standing. Moreover, our investigators did not perceive any reluctance by elders to disclose
ownership patterns in the village. Moreover, changes in the land distribution provided by
the surveys turned out to correspond closely, when aggregated across villages within the
same district, with district-based data on distribution of operational holdings from the state
Agricultural Censuses.25
23We are currently carrying out a direct household survey in order to ask each household concerning their
landholdings (and changes thereof over the past three decades), but the results will not be available for
research purposes for at least another year or so.24In private communication with us, Debu Bandyopadhyay the Land Reforms Commissioner at the time
when the bulk of the reforms were carried out, expressed his opinion that the indirect survey is likely to be
more reliable than a direct survey for the latter reason.25Details are available in the working paper version of this paper (Bardhan-Mookherjee (2004).
38
TABLE 1: DISTRICT-WISE ALLOCATION OF SAMPLE VILLAGES
DISTRICT NUMBER OF VILLAGES LEFT FRONT
IN SAMPLE PERCENT OF SEATS
IN GP (average 1978-98)
24 Parganas (N) 6 56
24 Parganas (S) 8 54
Bankura 5 87
Birbhum 5 58
Bardhaman 8 84
Cooch-Behar 8 85
Hooghly 6 70
Howrah 4 79
Jalpaiguri 5 74
Malda 2 60
Midnapur 8 78
Murshidabad 6 46
Nadia 5 79
Dinajpur 4 51
Purulia 8 62
WEST BENGAL 88 69
39
TABLE 2: LEFT SHARE IN GP SEATS AND
STATE ASSEMBLY VOTE SHARES
Time Left Front Left front Congress
Block % Seats in % vote in % vote in
in GP Assembly Assembly
(sample) (all WB) (all WB)
1978-83 74 47 23
1983-88 63 53 41
1988-93 71 54 41
1993-98 68 50 34
TABLE 3: CHANGES IN VILLAGE CHARACTERISTICS
1978 AVERAGE 1998 AVERAGE
Number of Households 220 389
Operational Land-household ratio 1.57 acres 0.87 acres
% hhs landless 46.83 51.48
% hhs marginal (0-2.5 acres) 35.27 39.76
% hhs small (2.5-5 acres) 11.41 6.45
% hhs medium (5-12.5 acres) 4.82 2.01
% hhs big (12.5 acres–) 1.66 0.29
% land marginal 27.43 45.75
% land small 28.66 28.17
% land medium 23.57 18.29
% land big 20.34 7.79
% poor hhs illiterate 45.36 32.18
% hhs scheduled castes/tribes 35.33 37.83
% hhs head in nonagri. occupation 39.90 50.26
Farm value added (1974 Rs/acre) 754.04 (in 1981) 1340.16 (in 1996)
Male wage (1974 Rs/hour) 0.65 (in 1981) 0.83 (in 1996)
40
TABLE 4 VESTED LAND: SAMPLE AVERAGES
Vested Land Land above % of
up to 1998 ceiling in 1978 Vested
(BLRO) as % of (survey) as % of land post
operational operational 1978
land in 1998 land in 1978 (BLRO-
(survey) (survey) subsample)
Average village 14.47 6.40 29.43
outside North Bengal
North Bengal village average 19.61 3.67 7.02
All villages average 16.06 5.55 18.38
TABLE 5 PATTA DISTRIBUTION: SAMPLE AVERAGES
(1) (2) (3) (4) (5) (6)
Excluding NB villages 3.76 71.21 90.50 13.77 27.91 54.82
North Bengal village average 9.50 75.22 70.80 18.39 32.60 56.86
All villages average 5.53 73.34 82.98 15.27 29.57 55.60
(1) 1998 Patta land (BLRO) as % of 1998 operational land survey
(2) Post 1978 Patta land as % of total patta land up to 1998 (BLRO)
(3) 1998 Patta cultivable as % of 1998 total patta land (survey)
(4) 1998 Pattadars (BLRO) as % of 1998 HH (survey)
(5) 1998 Pattadars (BLRO) as % of 1998 Landless (survey)
(6) 1998 Pattadars (BLRO) as % of 1978 Landless (survey)
41
TABLE 6: BARGA REGISTRATION: SAMPLE AVERAGES
(1) (2) (3)
Excluding NB villages 7.87 5.21 45.64
North Bengal villages 2.76 3.32 82.61
All villages 6.29 4.60 52.44
(1) 1998 Registered Barga land (BLRO) as % of 1998 operational land
(2) 1998 Registered Bargadars (BLRO) as % of 1998 HH (survey)
(3) 1998 Registered Bargadars (survey) as % of 1998 HH Leasing Land (survey)
TABLE 7: TIME PROFILE OF LAND REFORM
Time # Villages % households % cult. area # Villages % hhs % cult. area