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'POVTIME': module to compute aggregate intertemporal poverty measures

'POVTIME': module to compute aggregate intertemporal poverty measures. Carlos Gradín Universidade de Vigo. Description. ‘povtime’ computes aggregate intertemporal poverty measures (poverty accounting for time) in a balanced panel of individuals.

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'POVTIME': module to compute aggregate intertemporal poverty measures

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  1. 'POVTIME': module to compute aggregate intertemporal poverty measures Carlos Gradín Universidade de Vigo

  2. Description • ‘povtime’ computes aggregate intertemporal poverty measures (poverty accounting for time) in a balanced panel of individuals. • The program computes the family of FGT-type intertemporal poverty measures proposed in: • Gradin, Del Rio, and Canto ("Measuring Poverty Accounting for Time", Review of Income and Wealth, 58(2): 330-354, 2012). • Other measures that can be interpreted as particular cases of this general family: • Foster (“A Class of Chronic Poverty Measures” in Poverty Dynamics: Interdisciplinary Perspectives, OUP, 2009) and • Bossert, D'Ambrosio and Chakravarty ("Poverty and Time", Journal of Economic Inequality, 2012.

  3. Measuring poverty • Poverty in a cross-section of individuals • y=(y1, y2, ... , yq , yq+1, ... , yN) • Poverty index: P(y; z) • Stata modules: povdeco, apoverty, sepov Poor z Non poor FGT(0) = Headcount rate (H=q/N) FGT(1) = Poverty gap ratio (HI) FGT(2) = Poverty severity

  4. Measuring longitudinal poverty • Poverty in a (balanced) panel • N Individuals observed T times • Poverty index?: P(y; z) • Stata modules: povtime

  5. i)summarize the complete individual information in time individual intertemporal poverty index ii) then construct an aggregate poverty index that takes into account a social preference for equality among individuals

  6. Gradín, Cantó and del Río (RIW, 2012) P satisfies all desirable properties for Foster (OUP 2009) Bossert, D’Ambrosio and Chakravarty (JOEI 2012)

  7. Advantages • A code that allows for measuring agggregate poverty in a panel • complementing existing codes for measuring poverty in a cross-section • following various measures recently proposed in the literature, • in a way consistent with how poverty is measured in a cross-section. • Easy to undertake in-depth analysis • robustness (dominance analysis), • decomposition into components (incidence, intensity, inequality), • analysis of the distribution of individual poverty indices, etc. • Easy to obtain inference using bootstrapping

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