The paper examines whether the poverty transition or poverty persistency in India, as well as in Indian rural states, is due to state dependence or unobserved heterogeneity. Using panel data from the India Human Development Survey for 2005 and 2012, the study found that structural chronic poverty is high in Bihar, Odisha, Maharashtra, and Uttar Pradesh. Furthermore, general caste and scheduled tribe households have achieved upward mobility due to structural reasons whereas other backward class households have made a stochastic transition and come out of poverty. The bivariate Probit model suggests that there exists a state dependence of the probability of being poor; meaning that past poverty experience does matter in determining the present poverty status of a given household in India. The findings also indicate that female education is one of the important indicators for moving out of poverty. Hence, a crucial policy decision is needed for reducing poverty in a more sustainable way, which will include a targeted social safety net program along with improving the skill level of the household.

中文翻译：

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使用印度家庭面板数据得出的贫困的结构性和随机性转变

本文研究了印度以及印度农村国家的贫困转变或贫困持续性是由于国家依赖性还是未观察到的异质性所致。使用来自印度人类发展调查2005年和2012年的面板数据，该研究发现，比哈尔邦，奥里萨邦，马哈拉施特拉邦和北方邦的结构性长期贫困率很高。此外，由于结构原因，普通种姓和有计划的部落家庭实现了向上流动，而其他落后的家庭则进行了随机过渡并摆脱了贫困。双变量Probit模型表明存在状态差的可能性，这与状态有关。意味着过去的贫困经历对于确定印度给定家庭的当前贫困状况至关重要。调查结果还表明，女性教育是摆脱贫困的重要指标之一。因此，需要一项至关重要的政策决定，以更可持续的方式减少贫困，其中将包括有针对性的社会安全网计划以及提高家庭技能水平。