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Clientelism and targeting of welfare benefits: Can a centralized formula-based system do better?

Local governments in India—known as panchayats—are sometimes criticised for failing to deliver benefits earmarked for vulnerable regions or households to the intended recipients. Mis-targeting of benefits is often attributed to political clientelism, where funds are diverted opportunistically to help incumbents get re-elected. Alternatively, mis-targeting is frequently attributed to elite capture, where funds are diverted to local elites instead of the target recipients, a form of corruption.

Studies which examine the expenditures of local governments in India find evidence that benefits are indeed mis-targeted. In the context of West Bengal, where we study the problem, most evidence indicates clientelism rather than elite capture as the primary cause. This suggests that a transition to a more centralized and rule-based distribution of benefits can improve pro-poor targeting by reducing the scope for local officials to exercise discretion in fund distribution.   

The key policy trade-off

Our study examines whether anti-poverty targeting improvements can realistically be achieved with a transition to a more centralized and rule-based distribution of government benefits. The main finding is that these alternatives do not improve performance relative to the status quo.

In the institutional context of contemporary West Bengal, several informational and administrative constraints hamper the capacity of the state and central government to target benefits accurately if they were to switch to a formula-bound or means-tested programme. For example, the government currently does not have access to critical information about the household characteristics relevant to determining poverty status. Nor can they implement transfers directly to households because a large section of the population still does not have access to formal financial institutions.

Hence, a realistic, formula-based programme would use a geographic targeting mechanism for determining the budgets of each local government—known as gram panchayats (GPs)—and delegate to them the `last mile delivery’ responsibility of allocating these funds among individual households. Moreover, the formula would have to be based on measures that only roughly proxy recipients’ need, based on census or existing survey data of the kind that are currently used by the government.

Consequently, we estimate the potential improvement to anti-poverty targeting of a transition to a more centralized and rule-based system for distributing GP budgets which uses the GP-level poverty measures actually in use by the West Bengal State Finance Commission (SFC).

In theory, there are no guarantees that centralizing pro-poor benefits in this manner will actually improve pro-poor targeting. Owing to its limited information base, the SFC formulas  may not accurately determine eligibility for a benefit and end up delivering it to ineligible areas by mistake. This risk has to be traded off against the possibility that a local government official with superior information may deliberately deliver benefits to less needy regions. Which is the bigger risk needs to be assessed empirically.

We use longitudinal household surveys spanning ten years (1998–2008) to examine the question. The data includes a sample of 2400 households throughout all rural areas of West Bengal and provides data on household characteristics and benefits received. Households are classified into four different categories, depending on the number of proxy measures of poverty they satisfy, based on landownership, caste, and education. 

Pro-poor targeting would not be improved by centralizing the distribution of benefits

We find that the observed, current distribution of anti-poverty benefits is progressive, meaning, both within and across GPs, poorer households and poorer GPs receive a larger share of benefits. Furthermore, this is explained by the political incentives which clientelism generates for local government officials: they are motivated to direct more resources to poorer areas because the voting behaviour of poorer households tends to be more responsive to the receipt of benefits from current incumbents.

Second, the cross-GP allocation of benefits is more progressive than would be achieved if the state switches to an SFC geographic-targeting formula. This reflects the inadequacy of information used by the formula, relative to the information available to local officials that currently allocate GP budgets.

To highlight the latter point, we find that only marginal improvements in anti-poverty targeting can be achieved even if state geographic targeting were based on the same information set or proxy means utilized by the SFC, but with different weights assigned to different dimensions. For employment benefits for instance, we estimate that the share going to the ultra-poor can, at best, increase from 18.4% to 19.2%, and for the moderately poor from 35.9% to 36.3%. The predicted changes for other anti-poverty benefits are of a similar order of magnitude.

In summary, the scope for improving pro-poor targeting by switching to formula-based GP budgets is limited at best, as long as the formula is based on indicators used by the West Bengal SFC. This owes partly to a degree of pro-poor accountability in West Bengal local governments, and partly to superior information of local government officials about the distribution of need compared with measures utilized by the SFC.

For formula-based budgeting to achieve further improvements, it requires better information regarding ownership of key assets of land and education at the household level. In the absence of better measures of geographic need, the current system of delegation of authority to local governments seems justified.

It is important to note some qualifications. We are not addressing the broader question of the overall anti-poverty effects of clientelism. Our analysis concerns only effects of discretionary budgeting on pro-poor targeting of private benefits within a clientelistic regime.

By focusing on pro-poor targeting, or vertical equity, we ignored horizontal equity considerations, for example, the allocation of benefits between different poor groups, either between or within villages. Indeed, by showing how this allocation seems to be manipulated for political purposes, the existing literature already demonstrates a pattern of unfair discrimination.

Another important dimension ignored in this paper is insurance with respect to uncertain shocks to household or village needs. Moreover, as often alleged, clientelistic systems can cause an under-supply of local public goods essential for long-term reduction of poverty, and undermine political competition, transparency, state legitimacy, and rule of law. Therefore, in the long run it may still be better for the government to enhance its information base and capacity to make direct transfers to households and individuals in a formula-bound manner.

Dilip Mookherjee is Professor of Economics and Director at the Institute for Economic Development at Boston University.

Anusha Nath is an economist at the Federal Reserve Bank of Minneapolis, USA.

The views expressed in this piece are those of the author(s), and do not necessarily reflect the views of the Institute or the United Nations University, nor the programme/project donors.