Asset versus consumption poverty and poverty dynamics in rural Ethiopia

Several studies have shown conceptually that assets form a more robust basis for identifying the poor than do flow variables like expenditures or income. Asset‐based poverty classification can be used to distinguish structural from stochastic poverty and can enable projection of poverty dynamics through time. Nonetheless, little work has empirically compared poverty measurement based on assets and expenditures to indicate the practical implications of the choice of poverty measure. This article uses panel data (between 1994 and 2004) from Ethiopia to generate asset‐ and expenditures‐based poverty classifications. Asset dynamics are then explored to test for the existence of multiple asset index equilibria that could constitute evidence of poverty traps. Results provide evidence of multiple equilibria and show that the asset‐based poverty classifications predict future asset and expenditures poverty status more accurately than expenditures‐based measures. The findings confirm that the asset‐based measure could be used to more carefully target poverty interventions.     

The impact of food price increases on caloric intake in China

World food prices have increased dramatically in recent years. We use panel data from 2006 to examine the impact of these increases on the consumption and nutrition of poor households in two Chinese provinces. We find that households in Hunan suffered no nutrition declines. Households in Gansu experienced a small decline in calories, though the decline is on par with usual seasonal effects. The overall nutritional impact of the world price increase was small because households were able to substitute to cheaper foods and because the domestic prices of staple foods remained low due to government intervention in grain markets.     

Public investment and regional inequality in rural China

This paper develops a method for decomposing the contributions of various types of public investment to regional inequality and applies the method to rural China. Public investments are found to have contributed to production growth in both the agricultural and rural non‐agricultural sectors, but their contributions to regional inequality have differed by type of investment and the region in which they are made. All types of investment in the least‐developed western region reduce regional inequality, whereas additional investments in the coastal and central regions worsen regional inequality. Investments in rural education and agricultural R&D in the western region have the largest and most favorable impacts on reducing regional inequality.     

Asset‐based poverty transition and persistence in rural China

This article tests empirically for transition and persistence of poverty in rural China based on the theory of asset‐based poverty traps. It proposes an analytical framework mitigating the problem of endogenous switching between accumulation regimes and disentangling the true state‐dependence of poverty. Specifically, a dynamic asset threshold separating households into downward and upward mobility regimes is identified after taking households’ unobserved characteristics and observed regime‐differentiated accumulation strategies into account. The static analysis identifies causality running from settling into a downward mobility regime to the probability of poverty measured by consumption. Furthermore, allowing for endogenous initial poverty status, the dynamic analysis finds strong true state‐dependence in poverty. Households with the same characteristics are nearly twice as likely to be poor as if they had not previously switched to the accumulation regime. Assets below the dynamic threshold serve as a conduit through which poverty propagates itself. Factors that help to break this vicious circle are identified.     

Pathways out of poverty in lagging regions: evidence from rural western China

How to reduce poverty in lagging regions remains much debated and underserved with solid empirical evidence. This study illustrates an empirical methodology to analyze the pathways households followed out of poverty and to explore their potential in the future using 2000–2004 rural household panel data from two lagging provinces of China, Inner Mongolia and Gansu. It finds that rising labor productivity in agriculture has been key in understanding poverty reduction in rural lagging areas of these provinces and that it still holds much promise. Circular migration has also been important in Gansu, though less so in Inner Mongolia. On average, rural diversification has not proven to contribute much to poverty reduction and income transfers and agricultural tax abolishment have only helped at the margin. The findings from these two case studies highlight that the scope for reducing poverty in rural lagging regions can still be substantial in agriculture, also when nonagriculture drives national growth.     

The effects of a large discrete maize price increase on the distribution of household welfare and poverty in rural Kenya1

This study estimates the effects of a large discrete maize price increase on the welfare of a sample of rural Kenyan households. The usual first‐order welfare approximation formula is extended to a second‐order formula that allows for supply and demand responses to the price change. Results show that many rural households are not affected greatly by the price change, and there are about as many gainers as losers. However, these full sample results mask important differences across regions. Welfare gains generally take place in major production areas while losses are in areas where most households are net buyers of maize. Semiparametric methods are used to investigate the relationship between income and the size of the welfare effect, and poverty dominance techniques are applied to study the impacts of the maize price increase on rural poverty.     

The impact of land reallocation on technical efficiency: evidence from China

China's rural reforms expose farm households to an increased risk of administrative land reallocation and adjustment. This study explores the impact of land reallocation on technical efficiency, based on a panel data set from rural households in Zhejiang, Hubei, and Yunnan provinces between 1995 and 2002. Our research indicates that the development of a land rental market could serve as a substitute for administrative land reallocation in optimizing the distribution of land resources. The results from the stochastic frontier production function show that land reallocation does have effects on technical efficiency. The different signs for different provinces indicate that the impact of land reallocation on technical efficiency is an empirical issue and depends on the specific institutional settings and the overall economic environment in each province.     

High growth and rising inequality in Kerala since the 1980s

Over the last three decades, the state of Kerala in South India has witnessed fast-paced growth, with the highest recorded inequality (in 2009–2010) among all the states in India; however, its human development indicators remain the highest in India. This marks a departure from the well-known development trajectory of Kerala – famously known as the Kerala model – of low growth and moderate inequality with high human development indicators. We conduct GDP and growth decomposition, inequality decomposition and a Marxian class analysis of the National Sample Survey data from Kerala in order to understand these recent phenomena. While the notion that economic liberalization adopted by the state and central governments is the main cause of this new state of affairs is generally valid, we provide a more nuanced account of the causal structures based on class analysis and the impact of outward labour migration to the Persian Gulf.     

Does human capital raise farm or nonfarm earning more? New insight from a rural Pakistan household panel

This study explores how human capital affects farm household earnings using two tools to refine measurement of human capital effects. First, it employs a two‐sector model to allow the allocation of family labor between farm and nonfarm activities. Second, it accounts for village fixed effects to evaluate whether results from panel data differ meaningfully from a cross‐sectional data analysis with local binary variables. The results show that education has a negligible effect on farm earnings; instead, experience appears to be the principal channel by which human capital affects agricultural performance in a traditional rural setting. Our results also suggest that prior models that fail to separate nonfarm activities spuriously exaggerated the effect of education to the farm sector. In addition, typical cross‐sectional analyses that ignore fixed effects may cause the effects of education on rural household earnings to be significantly overstated. The fact that panel data regressions accounting for village‐level fixed effects found only one instance of education raising earnings—the effect of literacy on nonfarm income—suggests that considerable heterogeneity may have been ignored in cross‐sectional data analyses, especially ones that omitted village‐level effects.     

Effect of intergenerational asset transfers on land distribution in rural Cambodia: case studies of three rice‐growing villages

After land reallocation in the early 1980s, inequality in landholdings has re‐emerged in rural Cambodia. Besides land sales and purchases, intergenerational transfers of assets may foster inequality in landholdings among “second generation” (2G) couples who, having wed after the 1980s reallocation, received no land from the government. Data analysis of three rice‐growing villages reveals that land received directly from parents accounts for 18–41% of inequality in landholdings among sample 2G couples. Although net land gain after marriage, primarily through purchases, is the largest contributor to the inequality, nonland assets received from parents positively affect the net gain. Direct and indirect effects combined, assets received from parents account for 35–57% of inequality in landholdings. The effect of assortative matching of the acreage received from parents has hitherto been small.     

The impact of coffee price changes on rural households in Uganda

Employing household survey data covering the periods 1992–1993, 1995–1996, and 1999–2000, this article shows for the case of Uganda that a coffee market liberalization followed by a price boom was associated with substantial reductions in poverty, which could even be sustained when prices went down again. Coffee is not planted by the richest farmers and the gains from higher coffee prices accrued to poorer and richer coffee farmers alike. Nor were poorer farmers hurt disproportionately when prices fell. In addition, we find strong spillovers from coffee production to other agriculture, which tends to favor the poor, and to nonagricultural activities. These multiplier effects are concentrated in coffee regions. In an economic environment characterized by a booming agricultural sector, coffee farmers were able to accommodate the negative price shock, in particular through agricultural diversification. General agricultural growth also cushioned possible negative multiplier effects in coffee regions. Overall, the case of coffee in Uganda thus lends support to the view that agricultural trade liberalization is beneficial for the poor.     

Implications of the global growth slowdown for rural poverty

Over the past 25 years, higher growth in developing countries has contributed to a dramatic fall in global poverty, although poverty rates in rural areas remain higher than in urban areas. Unfortunately, projected growth rates have fallen in recent years; this article examines the impact of this slowdown on the poor, particularly the rural poor. It first uses a global model to assess the impacts of lower productivity on key price and income variables. It then uses microsimulation models for almost 300,000 households to assess the impacts on their real incomes. Although poverty rates overall are projected to fall substantially, the poorest countries see the greatest slowdown in poverty reduction, with over 5% of their population projected to remain below the poverty line. In addition, poverty rates will remain alarmingly high in many countries. Overall, 38 million fewer people will leave extreme poverty compared to earlier projections. Farm households are at particular risk in middle‐income countries, with over 1.5% more of the farming population remaining trapped in poverty than previously estimated. By 2030, average extreme poverty in rural areas is projected at about 7.5%, rather than 7.1% under the earlier growth projections. Clearly, a strong focus on policies for poverty reduction will be vital for eliminating poverty by 2030.     

Sharecropping efficiency in Ethiopia: threats of eviction and kinship

We tested a theoretical model with the Marshallian inefficiency (H1) and threat of eviction (H2) hypotheses having opposite effects on land productivity on sharecropped plots. The model also assumes that kinship contracts may eliminate or reduce the Marshallian inefficiency (H3) and threat of eviction (H4) effects on land productivity. Our empirical findings were consistent with H2 and H4 being true. We found higher land productivity on sharecropped plots than on share tenants' own plots and higher land productivity on sharecropped plots of nonkin than of kin tenants. The nature of the data allowed controlling for unobservable household characteristics through household fixed effects and for observable plot characteristics. Analyses with and without plot characteristics revealed that these findings were stronger with plot characteristics than without them. Based on the plausible assumption that observable plot characteristics are positively correlated with unobservable plot characteristics this strengthens our conclusion. The results are also supported by first-order stochastic dominance analysis. Sharecropped plots' output value distribution unambiguously dominated the output value distribution from share tenants' own plots. Nonkin sharecropped plots' output value distribution also first-order stochastically dominated the output value distribution from kin sharecrop plots.     

Ex post impacts of improved maize varieties on poverty in rural Ethiopia

Public agricultural research has been conducted in Africa for decades. While many studies have examined its aggregate impacts, few have investigated how it affects the poor. This paper helps fill this gap by applying a new procedure to explore the ex post impacts of improved maize varieties on poverty in rural Ethiopia. Plot‐level yield and cost changes due to adoption are first estimated using instrumental variable and marginal treatment effect techniques where possible heterogeneity is carefully accounted for. A backward derivation procedure is then developed to link treatment effect estimates with an economic surplus model to identify the counterfactual household income that would have existed without improved maize varieties. Poverty impacts are finally estimated by exploiting the differences between observed and counterfactual income distributions. Improved maize varieties have led to a 0.8–1.3 percentage drop of poverty headcount ratio and relative reductions of poverty depth and severity. However, poor producers benefit the least from adoption due to the smallness of their land holdings.     

Assessing the impact of NERICA on income and poverty in central and western Uganda

Persistent food shortage and poverty in sub-Saharan Africa (SSA) are major development issues. New Rice for Africa (NERICA) was developed to boost crop yield and income of rural households in SSA. Although its high-yielding traits have become fairly well known, there is no empirical analysis of its impact on income and poverty. By taking the case of Uganda where a NERICA promoting program was initiated as one of the major poverty eradication measures, this study attempts to compare actual income with the hypothetical income without NERICA. We found that introduction of NERICA decreases poverty to a significant extent without deteriorating income distribution.     

The fourth industrial revolution,agricultural and rural innovation,and implications for public policy and investments: a case of India

The Indian Government and public–private partnerships are developing and disseminating a dizzying number of innovative, networked solutions, broadly known as the Digital India initiative, to increase the efficiency of safety nets and worker productivity and to improve life. Yet, challenges to turn the power of information and other technologies into a farmer‐friendly technological revolution for India's 156 million rural households are considerable, including: (1) reliable, up‐to‐date, location‐specific message content for a diverse agriculture to help stratified households shift to productive, knowledge‐intensive agriculture as a business—government, private sector, and civil society have big roles to play; (2) digital literacy, i.e., teaching farmers how to choose and use apps, even where the digital divide is absent; apps are, or soon to be, in regional languages; and (3) monitoring actual use and impacts on users’ lives by understanding the adoption and adaptation processes. These challenges call for bottom‐up, complementary investments in physical, human, and institutional capital, and farmer‐friendly e‐platforms, while forging ahead with many top‐down policy and institutional reforms currently underway, in which progress is real and constraints holding back greater success are better understood.