Estimating returns to soil conservation adoption in the northern Ethiopian highlands

Land degradation in the form of soil erosion and nutrient depletion presents a threat to food security and sustainability of agricultural production in many developing countries. Governments and development agencies have invested substantial resources to promote soil conservation practices as part of an effort to improve environmental conditions and reduce poverty. However, limited rigorous empirical work has been done on the economics of soil conservation technology adoption. This article investigates the impact of stone bunds on value of crop production per hectare in low and high rainfall areas of the Ethiopian highlands using cross-sectional data from more than 900 households, with multiple plots per household. We have used modified random effects models, stochastic dominance analysis (SDA), and matching methods to ensure robustness. The parametric regression and SDA estimates are based on matched observations obtained from the nearest neighbor matching using propensity score estimates. This is important, because conventional regression and SDA estimates are obtained without ensuring that there actually exist comparable conserved and nonconserved plots on the distribution of covariates. We use matching methods, random effects, and Mundlak's approach to control selection and endogeneity bias that may arise due to correlation of unobserved heterogeneity and observed explanatory variables.
We find that the three methods tell a consistent story. Plots with stone bunds are more productive than those without such technologies in semi-arid areas but not in higher rainfall areas, apparently because the moisture conserving benefits of this technology are more beneficial in drier areas. This implies that the performance of stone bunds varies by agro-ecology type, suggesting the need for designing and implementing appropriate site-specific technologies.     

Econometric mathematical programming: an application to the estimation of costs and risk preferences at farm level

This study belongs to the barely explored research strand of “Econometric Mathematical Programming” and presents a simultaneous estimation of the cost function and of the farmers’ risk attitude parameter in a programming model setup. Resource and policy constraints of the model are allowed to be not binding. We use crop shares as decision variables to avoid scale bias and we consider price and crop yield variances separately. The model is formulated as a bi‐level programming model and the empirical application concerns three unbalanced panels of specialized arable farms observed for at least three consecutive years in Northern Italy, in the Cologne‐Aachen area in Germany and in the Grandes‐Cultures area in France over the time period 1995–2007. We achieve a quite satisfactory fit in the estimation exercise and find own and cross price elasticities from sensitivity experiments in reasonable ranges. We also propose a novel approach to derive confidence intervals around parameter estimates for Econometric Mathematical Programming.     

Choice experiment adaptive design benefits: a case study*

Efficient experimental designs offer the potential to reduce required sample sizes, or to reduce confidence intervals for parameters of interest, in choice experiments. Choice experiment designs have typically addressed efficiency of utility function parameter estimates. The recently developed concept of C‐efficiency recognises the salience of willingness to pay estimates rather than utility function parameters in studies that seek to put money values on attributes. C‐efficiency design benefits have been illustrated in a theoretical context, but have not been tested in applied settings. This study reports a choice experiment field application that used initial responses to update statistical designs to maximise C‐efficiency. Consistent with theoretical predictions, the revised design delivered significant reductions in the variance of willingness to pay estimates, illustrating that C‐efficient designs can indeed decrease costs of choice experiments by reducing required sample sizes.     

Implications of high food prices for poverty in Pakistan

The study estimates the impacts of rising world food prices on poverty in rural and urban areas of Pakistan. Household income and expenditure data for 2004/2005 is used to estimate compensated and uncompensated price and expenditure elasticities using the linear approximation of the almost ideal demand system. Taking the unexpected component of higher domestic food prices in 2007/2008, own and cross price compensated elasticities are used to derive the changes in the quantity consumed, food expenditure and impacts on poverty assuming the food crisis happened in 2004/2005. The results indicate that poverty increased by 34.8%, severely affecting the urban areas where poverty increased by 44.6% as compared to 32.5% in rural areas. The estimates show that 2.3 million people are unable to reach even one‐half of poverty line expenditures while another 13.7 million are just below and 23.9 million are just above the poverty line. In the short run, it is important to ensure food availability to these people. In the long run, the policy environment of subsidizing urban food consumers by keeping wheat prices lower than the international price, needs to be reconsidered to provide the right incentives to increase food availability.     

Long-term consequences of short-term precipitation shocks: evidence from Brazilian migrant households

We find that large short-term precipitation shocks damage the long-term income of households that have permanently migrated from rural to urban areas. This outcome is consistent with the behavior of credit-constrained rural households who are willing to accept lower long-term income in urban areas following the depletion of their productive assets during an adverse shock. Our empirical evidence suggests that there may be a link between large precipitation shocks in rural areas and urban poverty. Further exploration is warranted on the mechanisms by which natural disasters cause these long-term losses.     

Price and quantity endogeneity in demand analysis: evidence from directed acyclic graphs

We propose to use the emerging method of directed graphs to study price/quantity endogeneity issues in empirical demand analysis. The approach is illustrated through the examination of U.S. meat consumption. We find that for two major meat products (beef and poultry), retail prices contemporaneously caused quantities consumed, thus were predetermined. In contrast, the quantity consumed of pork appeared to be predetermined relative to its price.     

Demand for meat and dairy products by Turkish households: a Bayesian censored system approach

We extend the Tobit (censored) linear equation system procedure to utility‐theoretic demand functions, along with a mapping mechanism to impose the adding‐up restriction implied by consumer utility maximization theory—a theoretical restriction very often ignored in previous empirical studies with censored demand systems. In this context, the Bayesian Markov Chain Monte Carlo (MCMC) procedure is applied to the censored linear approximate almost ideal demand system (LAIDS) for 12 food products, using data from the Turkish Household Expenditure Survey. All own‐price elasticities are negative and expenditure elasticities positive. Uncompensated own‐price elasticities for rural households are generally much higher than those for their urban peers, though demand for most food products are own‐price elastic for both types of households. The differential patterns in demand elasticities between urban and rural households become even more evident (almost twice) as relatively more expensive foodstuffs are consumed, showing that accessibilities to alternative products have made rural Turkish households more cognizant toward price changes in foods. Household characteristics play a key role in food expenditures, notably so in urban areas, and regional and seasonal differences are also present.     

Multidimensional poverty in Afghanistan: who are the poorest of the poor?

Taking a capability approach perspective, our paper aims at advancing our understanding of poverty in Afghanistan, and at identifying the most deprived, including persons with disabilities, in order to address the first Sustainable Development Goal to eradicate poverty in all its forms. We used data from a national survey carried out in Afghanistan in 2005. We calculated one index using two weights structures, the adjusted headcount ratio, part of the multidimensional poverty measures. Following a participatory process, we identified and validated 13 indicators clustered in seven dimensions of poverty, including three usually neglected dimensions. Findings suggest that exploring various domains of deprivation would better inform poverty eradication policies than an approach focused only on income. Our results also demonstrate that nearly all Afghan adults are deprived in at least one dimension and those residing in rural areas, from minority ethnic groups, women, elderly people and persons disabled at birth or of an unknown cause are the poorest of the poor. Efforts to improve well-being must acknowledge these inequalities so that public policies in Afghanistan aiming at alleviating poverty take these disparities into account, when facing a reduction in available resources.     

Robust Comparisons of Malnutrition in Developing Countries

We use Demographic and Health Surveys (DHS) to make international and inter–temporal welfare comparisons. While most poverty analyses rely on expenditures or income, we use anthropometric measures of nutrition as indicators of living standards. The advantages are that we observe individual—not household—well–being, deflators and exchange rates are unnecessary, and measurement techniques are similar across surveys. We test the robustness of the headcount results, and find that applying higher order Foster–Greer–Thorbecke poverty measures adds little information; although stochastic dominance testing of nutrition distributions reveals that changes in malnutrition are sensitive to the choice of the "nutrition poverty line."     

土地流转对农户贫困脆弱性的影响研究

研究目的:探究土地流转对农户贫困脆弱性的影响,为防范农户陷入贫困和解决农村贫困提供理论和实证依据。研究方法:本文借助2016年湖北省1682个农户实地调查数据,基于倾向得分匹配法(PSM)和回归方程的Shapley值分解法,分别考察国定贫困线、1.9美元贫困线和3.1美元贫困线下不同类型土地有无转出和转出面积对农户贫困脆弱性的影响。研究结果:土地转出能够显著降低农户的贫困脆弱性,且农户贫困脆弱性随着转出土地面积的增加而降低;从土地转出的异质性来看,水田转出对缓解农户贫困脆弱性的效果更为明显,旱地转出的效果次之。研究结论:应进一步加快农村土地流转,释放农村剩余劳动力,不断增加农户收入,从而降低农户贫困脆弱性。     

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.     

Modeling preference heterogeneity in stated choice data: an analysis for public goods generated by agriculture

Stated choice models based on the random utility framework are becoming increasingly popular in the applied economics literature. The need to account for respondents' preference heterogeneity in such models has motivated researchers in agricultural, environmental, health, and transport economics to apply random parameter logit and latent class models. In most of the published literature these models incorporate heterogeneity in preferences through the systematic component of utility. An alternative approach is to investigate heterogeneity through the random component of utility, and covariance heterogeneity models are one means of doing this. In this article we compare these alternative ways of incorporating preference heterogeneity in stated choice models and evaluate the sensitivity of estimated welfare measures to which approach is selected. We find that a latent class approach fits our data best, but all the models perform well in terms of out-of-sample predictions. Finally, we discuss what criteria a researcher can use to decide which approach is most appropriate for a given data set.     

Poverty targeting, resource degradation and heterogeneous endowments—a micro-simulation analysis of a less-favored Ethiopian village

Persistent and widespread poverty in less-favored areas (LFAs) is attributed to fragile natural resources and poor markets. Limited assets may keep households outside the reach of poverty policies targeted at LFAs. We explored in a stylized manner the role of heterogeneous household assets for (1) policies aimed at poverty reduction; (2) within-village income inequality; and (3) soil erosion. With a farm-household micro-simulation model we analyzed for each household in a remote Ethiopian village three sets of policies: technology improvement, infrastructure investment, and off-farm employment through migration or cash for work (CFW) programs. Combating poverty with a single policy, migratory off-farm employment reduces the poverty headcount most. Because of self-selection, CFW programs performed best in terms of reaching the poorest of the poor. CFW also reduced within-village income inequality most, while a price band reduction increased income inequality. Only technology improvements resulted in a trade-off between poverty and soil erosion. Price band and off-farm employment policies reduced erosion while outperforming technology improvements in terms of poverty reduction. We found that combining two policies was most helpful in assisting poorer households to overcome the limitations of their asset endowments. A CFW program combined with reduced price bands yielded most in terms of poverty reduction and income inequality. This policy complementarity is, however, less important for better-endowed households. Reducing the reliance of households on agriculture offered a win-win situation of reducing poverty and maintaining natural resources. Combining policies helped to overcome asset limitations, to target policies to the poorest households and to reduce income inequalities.     

精准扶贫与土地利用区划创新融合的实证研究

[目的]土地利用区划研究不仅对土地资源可持续利用有重要作用,也是扶贫开发的重要抓手。文章试图探索如何将扶贫因素纳入土地利用区划标准,实现扶贫开发与土地利用区划的创新融合,并选取云南省芒市这一典型贫困地区进行实证研究。[方法]运用文献综述法分析二者融合的内在机制;综合分析法和分区单元归并法进行综合分区;演绎法划分实施扶贫开发战略的土地利用保障区;空间迭置法构建芒市土地资源利用与扶贫开发统筹协调发展的措施体系。[结果]最后将芒市划分为4个土地利用区,即:Ⅰ东北部低山盆地区,Ⅱ东南部中低山河谷区,Ⅲ西南部低山盆地区和Ⅳ西北部中低山地区4个土地利用区域。[结论]理论探讨精准扶贫与土地利用区划的创新融合,为精准扶贫提供了新的切入点;通过实证研究,尝试提出各综合区精准扶贫与土地资源利用统筹协调发展的措施体系,对芒市乃至类似地区土地扶贫开发利用具有一定的理论价值和现实意义。     

Agriculture and small towns in Africa

Africa is urbanizing rapidly. Yet most dual economy models focus on the sectoral rather than spatial dimensions of development. This article adopts a “dual–dual” approach to measuring rural/urban and farm/nonfarm linkages. We develop an economy‐wide model of Ethiopia that distinguishes between cities, towns, and rural areas. The model captures detailed sectoral and regional linkages, internal migration flows, and externalities from urban agglomeration. We find larger linkages between agricultural production and small towns and show that redirecting urban growth toward towns rather than cities leads to broader‐based economic growth and poverty reduction. In contrast, industry and services, particularly within cities, are far less effective in reaching rural areas and the poor. Africa's current urbanization pattern—toward major cities rather than towns—will weaken national growth–poverty linkages. Urbanization that takes advantage of the synergistic relationship between agriculture and small towns has the potential to result in a more inclusive growth trajectory.     

人力资本对贫困地区农村家庭产出的贡献——基于黑龙江省的实证分析

[目的]"打赢脱贫攻坚战,是今明两年必须完成的硬任务",剩余贫困人口的脱贫和已脱贫人口的发展亟需释放贫困地区人力资本的力量。人力资本在脱贫阶段演进过程中起到不同的作用,是提高贫困地区农村家庭产出和实现脱贫的核心与关键。[方法]文章通过实地调研验证人力资本对脱贫的作用机理,并为实证分析提供数据支持,依据人力资本与贫困地区农村家庭产出的均衡方程,建立回归模型,结合人力资本在生产函数中的意义及规模报酬不变的条件约束,判断人力资本贡献率对农村家庭产出优化的影响。[结果]实地调研表明脱贫意愿对人力资本构成影响较大;回归分析表明人力资本对贫困家庭产出贡献大于资金资本,也大于知识技术资本;优化规划表明人力资本的积累有助于实现贫困地区农村家庭产出规模优化。[结论]应从健康状况、脱贫能力和脱贫意愿等方面加强人力资本积累,通过共享平台支撑促进人力资本与其他资本有机融合,以人力资本为核心构建内生脱贫模式。     

Sectoral and poverty impacts of agricultural policy adjustments in Colombia

We aim to assess the sectoral and poverty impacts of changes in agricultural policy in Colombia. For this, we use an agriculture specialized static computable general equilibrium model, together with a microsimulation model that allows employment to shift between sectors. Results indicate that the sectoral impact from policy changes tends to be small and that it considerably varies across crops. The macro model yields some gains in wages and capital rents, a relatively larger increase in land rents, and limited labor reallocation, together leading to small poverty impacts as calculated through the microsimulation model. The incidence of rural poverty decreases by less than 1% and the same happens to the poverty gap. In addition, poverty reductions are concentrated among households near the middle of the income distribution.     

Characterising Vulnerability to Poverty in Rural Haiti: A Multilevel Decomposition Approach

This article characterises vulnerability to poverty in Haiti using a unique survey conducted in 2007 in rural areas. In a first step, using two‐level linear random coefficient models of both per capita consumption and per capita income, the article assesses the impact of self‐reported shocks on households' economic well‐being. In a second step, the prediction model is used to calculate various measures of vulnerability to poverty, considering various types of shocks. Empirical findings show that self‐reported (or observable) idiosyncratic shocks, in particular health‐related shocks, have larger impact on vulnerability to poverty than observable covariate shocks. These results are in line with the fact that many households reported idiosyncratic health shocks as being the worst shocks they experienced. On the other hand, unobservable idiosyncratic shocks appear to have generally more influence on households' vulnerability to poverty than unobservable covariate ones. We also show that omitting self‐reported shocks in the analysis leads to an underestimate of households' vulnerability to poverty.     

Nutrition Transition and Changing Food Preferences in India

We present empirical evidence on how changes in food preferences have contributed to nutrition transition, where the dietary pattern of households shifts away from traditional staples. Using household-level time series cross-section survey data for India, we estimate time varying demand elasticities, revealing evidence of the declining importance of cereals in Indian household diets. The estimates show that Indian demand for cereals has become more income inelastic and price elastic. We also find that cereals are a substitute rather than a complement to animal products in household diets. Since changes in elasticities can only be attributed to variation in utility parameters, this indicates that cereals are losing favour with Indian households. These findings have implications for Indian food policy design and implementation.     

贫困地区精准扶贫与农村社区协同发展的思考

以贫困地区精准扶贫为研究对象,通过对云南省乌蒙山片区精准扶贫工作的实际调研,从精准扶贫和农村社区发展的关系入手,分析探讨二者协调发展的必要性,精准扶贫对农村社区发展的新挑战,在此基础上提出创新农村社区扶贫开发新理念、构建促进型农村社区组织、农村社区在精准扶贫和社区发展工作中全面贯彻五大发展理念的协同发展对策,能丰富和发展精准扶贫理论和社区发展理论,更好地指导贫困地区精准扶贫的推进和农村社区的建设,促进贫困地区经济的发展。能更好地促进精准扶贫与农村社区的协同发展,促进农村贫困地区到2020年全面脱贫,全面建成小康社会。