Poverty traps, convergence, and the dynamics of household income

Arunachalam, Raj; Shenoy, Ajay

doi:10.1016/j.jdeveco.2017.02.001

Cited by 15 publications

(14 citation statements)

References 55 publications

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“…The absence of evidence of poverty traps within caste groups in rural India is also consistent with Arunachalam and Shenoy (2017) who use the same data but a different econometric approach based on modelling mean household income growth rate changes.…”

Section: Resultssupporting

confidence: 75%

“…The data collection effort followed the same households over decades as part of the Rural Economic and Demographic Survey (REDS) survey and has been used in multiple seminal studies (e.g. Behrman et al, 1999;Foster & Rosenzweig, 2002; and in poverty trap analysis by Arunachalam & Shenoy, 2017). 4 In the processed data, household assets in each period were calculated as the value of buildings, land, farm equipment, animals, non-farm business assets, farm and non-farm inventory, consumer durables, cash and non-cash savings, and the value of loans owed to the household minus loans owed by the household.…”

Section: Context and Datamentioning

confidence: 99%

“…4 In the processed data, household assets in each period were calculated as the value of buildings, land, farm equipment, animals, non-farm business assets, farm and non-farm inventory, consumer durables, cash and non-cash savings, and the value of loans owed to the household minus loans owed by the household. Details on variable creation and descriptive statistics are in Arunachalam and Shenoy (2017). In total, we analyse current assets (observed in 1999) and past assets (observed in 1982) separately for 2023 high caste households and 1048 low caste households.…”

Section: Context and Datamentioning

confidence: 99%

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A new approach for detecting multiple‐equilibria poverty traps

Mohapatra

2021

J of Intl Development

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Despite a large literature, empirical evidence on multipleequilibria poverty traps remains elusive. Current empirical methods estimate average welfare-dynamics, which masks inherent heterogeneity across households. We develop an alternative approach that allows welfare-dynamics to differ across the household wealth distribution. Drawing on the literature on regression discontinuity designs, we propose a new statistical test for detecting multiple-equilibria and poverty traps. We demonstrate the approach using panel data on over 6000 rural households in India. Our application contributes to the economic development literature by examining poverty within caste, the main source of social stratification in India.caste, India, multiple equilibria, poverty trap, welfare dynamics | INTRODUCTIONTwo long-established views still inform much of the public policy discussion on poverty today. One view is the rags to riches story which claims that an individual's welfare and future prospects depends entirely on their own effort.

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Section: Resultssupporting

confidence: 75%

Section: Context and Datamentioning

confidence: 99%

Section: Context and Datamentioning

confidence: 99%

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A new approach for detecting multiple‐equilibria poverty traps

Mohapatra

2021

J of Intl Development

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“…Second, empirical studies reported the characteristics of rural income inequality in recent decades. Since rural income inequality is complex, these studies focused on overall regional inequality, and inter-and intra-regional inequality, to explore the space structures [11], trends in changes [12][13][14][15], and driving forces. Third, analyses of factors of income inequality and policy suggestions have been produced.…”

Section: Introductionmentioning

confidence: 99%

Factor Decomposition of the Changes in the Rural Regional Income Inequality in Southwestern Mountainous Area of China

Yang

et al. 2018

Sustainability

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This study aimed to determine factors of rural income inequality changes in Aba Tibetan and Qiang Autonomous Prefecture, Sichuan, China, to help formulate measures to reduce regional inequality and alleviate poverty in the southwestern mountainous area of China, which experiences frequent natural disasters and poor living conditions. Changes in rural income inequality are examined, which are then decomposed into different component factors based on the Gini index. Income inequality is comprised of four types of income source: wages, household operations, properties, and transfers. This analysis focuses on the period of 2003 to 2011—a special transitional stage during which the Wenchuan earthquake intervened. The results indicate that income from household operations plays a dominant role in income inequality. Its contribution to the overall inequality fluctuates from 36.40 to 50.39% and had a positive effect on reducing inequality after the earthquake. Wage income contributed the second-most to income inequality and had positive and negative effects on reducing inequality before and after the earthquake, respectively. Transfer and property incomes are important forces in income inequality that have different influencing mechanisms. Transfer income positively helps reduce income inequality. Exclusive favors or preferences should be granted to such areas.

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“…To better understand the interplay between these factors, it is important to systematically explore the rural livelihood-environment nexus.With respect to studies on rural livelihoods and the environment, most researchers have focused on one-sided effects instead of mutual relationships [27][28][29]. Researchers have concentrated on the correlations between rural livelihoods and the environment [30,31], poverty traps [32,33], and the spatial clustering of poor populations [34,35]. However, these studies have mostly been based on a single livelihood indicator (general per capita net income), which is insufficient to capture deeper relationships and might be biased.…”

mentioning

confidence: 99%

Coupled Relationship between Rural Livelihoods and the Environment at a Village Scale: A Case Study in the Mongolian Plateau

Dai

et al. 2020

Land

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Rural livelihoods, which are basic human activities, have long interacted with the environment. In light of the complexity of the human–environment system, more interdisciplinary analyses from geographical, environmental, and social sciences are needed. Using qualitative and quantitative methods from social, environmental, and geographical sciences, this study conducted a geographical regionalization and a comparative analysis of rural livelihoods in different zones in the Loess Plateau to explore the relationship between rural livelihoods and the environment. The results indicated that rural livelihoods are tightly coupled with the environment on a village scale, showing significant geographical regularity and spatial disparity. A combination of geographical location, resource endowment, and environmental sanitation affects rural livelihoods in terms of spatial patterns, development capacity, and quality of life in the context of the public ownership system, the utilization policy of land resources, and limited technical conditions. Coupling the relationship between rural livelihoods and a given environment on a village scale tends to lead to one of four types of relationships: “homeostatic”, “intense”, “transferred”, or “optimized”. Accordingly, governments and policymakers need to consider that countryside revitalization must be locally tailored and implemented through the four aspects of “rights revitalization”, “labor revitalization”, “industrial revitalization”, and “environmental revitalization”.

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Poverty traps, convergence, and the dynamics of household income

Cited by 15 publications

References 55 publications

A new approach for detecting multiple‐equilibria poverty traps

A new approach for detecting multiple‐equilibria poverty traps

Factor Decomposition of the Changes in the Rural Regional Income Inequality in Southwestern Mountainous Area of China

Coupled Relationship between Rural Livelihoods and the Environment at a Village Scale: A Case Study in the Mongolian Plateau

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