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2019 | OriginalPaper | Buchkapitel

11. The Distribution of Productive Assets and the Economics of Rural Development and Poverty Reduction

verfasst von : Michael R. Carter, Aleksandr Michuda

Erschienen in: The Palgrave Handbook of Development Economics

Verlag: Springer International Publishing

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Abstract

In the 1960s and 1970s, academic and policy debates on agrarian issues often spun around the distribution of land, with some arguing that neither rural development nor poverty reduction was possible without asset redistribution. While resting on defensible theoretical foundations, the argument for large-scale redistribution gave way to microfinance and other less radical interventions intended to allow low wealth households to do more with their existing, modest asset endowments. While also resting on defensible theoretical foundations, this “lend, don’t redistribute wealth” perspective coincided with a shift of development economics away from big picture theorizing towards an impact evaluation economics focused on reliable identification of microfinance and other singular interventions. Interestingly, despite the promise of microfinance to substitute for asset redistribution, impact evaluation economics found it to have at best modest effects on the class positions and living standards of poor households. In a perhaps ironic twist, a new generation of programs built around the transfer of tangible assets has shown much more promise in terms of changing household economic strategies and placing them on trajectories of sustained economic advance. While sharing some similarities with older perspectives on asset redistribution, these new approaches reflect new learning on both the psychology of poverty and the economics of asset accumulation by poor households.

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Vorheriges Kapitel Income Inequality in Developing Countries, Past and Present

Nächstes Kapitel Institutions and the Process of Industrialisation: Towards a Theory of Social Capability Development

In his own day, Chayanov was involved in a debate with Lenin among others on whether or not the Russian peasantry was stable or whether it was differentiating into a structure of large farm capitalists and landless workers. Using his variant of the model developed below, Chayanov argued that the peasantry was stable despite regular cycles of farm growth and contraction, which he argued were explicable solely by demographic lifecycle factors.

The assumption that the utility of consumption and the disutility of work are additively separable is both faithful to Chayanov’s discussion and rules out pesky cross-partial derivatives that add clutter but little additional insight to the model. Note also that the assumption that household well-being depends on per-capita values of consumption and works ignores the overwhelming evidence that neither consumption goods nor work hours are shared equally between members of the household (see Folbre 1984 for an early and still compelling exposition).

Access to labor markets at which they could sell their labor at a fixed \( w>\tilde{w} \) would ameliorate the poverty of these households as would the option to exploit their cheap labor by renting-in land from land-abundant households with higher price labor (Feder 1985).

In the language of Elster (1994), this peasant-like self-exploitation is an example of endowment necessitated behavior. That is, people are not born peasants, but they adopt peasant-like behavior when it is the best they can do given their endowments and the constraints they face (an observation also recorded by Lehmann 1986).

In fact, as Feder (1985) suggests, there does not need to be full contractibility in all three markets, but rather only a working capital and land market. In that case, each household would lease enough land to maintain an operational size proportionate to the size of their family and achieve the social optimum.

This point was actually made as early as John Brewster’s “The Machine Process in Agriculture and Industry” in 1950, where it described moral hazard in labor hiring as being one of the reasons for the persistence of family farming even as agriculture became more mechanized (because on the family farm, all labor has residual claimant incentives to provide optimal effort).

Bardhan (1984) pushes this even further, asserting that imperfectly aligned incentives are also linked to how institutions form. Institutional formation is not just cursory to economic outcomes or should be seen as “just being there,” but may be shaped by both information asymmetries and power asymmetries caused by these misaligned incentives. Economies with higher rates of moral hazard in labor can see sharecropping arrangements form. Or perhaps, high initial inequality in land and assets can lead to inefficiently large latifundia farms that can limit households’ outside opportunities as in Conning (2002).

As well as a few more, including that u^′′ = 0; α = β = 1 and assuming a fixed cost to cultivate.

Note that for the family labor farm, the opportunity cost of labor is w, while w(1 + s′) is for the larger farm that hires in labor that must be supervised.

Models of occupational choice (e.g., Banerjee and Newman 1993; Ghatak and Jiang 2002; Buera et al. 2018) consider the sorting of a population into entrepreneurs and workers based on wealth endowments and access to capital. While this literature is not specifically agrarian in orientation, it revisits the same issue about whether and how the distribution of initial wealth shapes the structure of an economy and its performance.

Indeed, not all classes will exist at all factor price configurations.

Eswaran and Kotwal employ a Benthamite social welfare function, giving equal weight to all households in the economy, regardless of the distribution of initial endowments.

Indeed, what Eswaran and Kotwal (as well as Marxian economists like John Roemer) call class structure, neoclassical economics would call occupational choice.

In order to keep aggregate credit constant when varying θ, Eswaran and Kotwal also vary ϕ, by the equation \( \phi ={B}_T-\theta \overline{T}, \) where B_T is the aggregate amount of credit in the economy.

Another limitation of both the asymmetric information-based model of Eswaran and Kotwal and the original Chayanovian model is that they treat the distribution of land endowments as fixed. While that treatment is unobjectionable in the short run, it is less defensible over the longer term if we consider time as a degree of freedom that might also allow households to lower consumption and build up stocks of money to either self-finance production or purchase land and gain access to capital that way. We return to these dynamic issues in Sect. 5.

In an important theoretical study, Conning 2005 asks whether the presumed benefits of joint liability lending (symmetric information and costless mutual monitoring) are in fact more imagined than real. Conning notes that Yunnus and the Grameen Bank itself began shifting to individual liability loans, closely monitored by bank officers. …

One of us attended graduate school in the late 1970s when a series of RCTs were implemented with US government sponsorship to study the impacts of different social welfare programs and work and labor supply incentives.

Despite its lagged publication date, the RCT for this study was implemented beginning in 2006.

The net compliance rate of an experiment is the difference between the fraction of individuals in the treatment group who took or complied with their treatment (e.g., a microfinance loan) and the fraction of individuals in the control group who also took the treatment. Note that in a classic well-controlled medical trial, the net compliance rate will be 100%, with all the treatment groups taking their medicine and the control group only taking a placebo. The ability to detect treatment impacts declines precipitously with net compliance.

As Barrett and Carter 2010 discuss, one of the unfortunate, but avoidable, side effects of the shift of development to impact evaluation is that theoretical insights have often been left aside with the economics profession following the programming decisions of government and non-governmental organizations (NGOs).

Boucher, Carter, and Guirkinger (2008) argue that risk rationed households are in a sense involuntarily rationed because they would be expected to borrow if the available contract offered higher interest rates but lower collateral requirements. A similar argument could be made for self-excluding microfinance borrowers who fear placing their few social relationships at risk as collateral for group loans.

While the Boucher et al. (2008) results are theoretical, they also show empirical evidence from four countries showing that as much as 25% of the small farmer population is risk rationed and that their failure to exploit available loan contracts leaves them poorer than they need be and in a circumstance akin to that of households that are completely excluded from credit markets.

The BRAC analysis compares “selected” with “non-selected” ultra-poor households. Non-selected households passed the means test for inclusion in the program, but failed to otherwise qualify for the program based on other characteristics. At baseline, the non-selected control group was modestly better off than the group selected for inclusion in the TUP program.

Four years after the study’s inception, control group households were brought into the program. The seven-year results reported by Bandiera et al. (2017) assume that the control group replicated the pattern of the treatment group in the first years of the study and synthetically reduce downward the position of control households at year 7 in order to obtain estimates of the long-term impacts on the treatment group.

Interestingly, Bandiera et al. (2017) show that these average impacts disguise a pattern of heterogeneity in which roughly 40% of households benefit modestly from the program, while the rest benefit substantially more than the average treatment effects indicate. In a study of small farm development program in Nicaragua, Carter et al. (2018) discuss in more detail the reasons why such heterogeneity exists in programs intended to address rural poverty with asset transfers and other interventions intended to place households on an entrepreneurial pathway.

As discussed by these authors, identification of the impact of such land reform programs has historically proven difficult because major redistribution efforts typically take place in the midst of a broader mix of political and economic changes (see, e.g., the studies in Thiesenhusen 1989).

Numerical dynamic programming solutions to this type of model are found in Ikegami et al. (2017).

Note that at the steady-state position, marginal returns to further investment are worth less than the certain cost of the foregone consumption required to finance the accumulation. Given that these costs are certain and that the gains from further accumulation are uncertain, it is suboptimal for the household to try to move beyond the low equilibrium steady-state value.

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Titel: The Distribution of Productive Assets and the Economics of Rural Development and Poverty Reduction
verfasst von: Michael R. Carter
Aleksandr Michuda
Verlag: Springer International Publishing
Buch: The Palgrave Handbook of Development Economics
Print ISBN: 978-3-030-13999-5

Electronic ISBN: 978-3-030-14000-7

Copyright-Jahr: 2019
DOI: https://doi.org/10.1007/978-3-030-14000-7_11

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