Measuring Acute Multidimensional Poverty with Missing Indicators: Applications to Alkire-Foster MPI and its Dimensional Break Down in Iran

Although the importance of considering the capability approach in calculating poverty has been addressed in various studies, a major obstacle to achieving a measure like Alkire-Foster MPI in many countries is the lack of integrated micro indicators. In this study, we suggest a "repeated and random data generation" method using the macro amount of the missing indicator. Moreover, we apply this method to calculate and break down the acute poverty measure of Alkier and Foster in Iran. The results indicate that by using this method, we are able to achieve the desired level with very high precision. In addition, by breaking down multidimensional poverty into three dimensions of health, education, and standard of living, we show that during the last four decades, the share of educational deprivation in MPI is always increasing and has transformed into the most effective indicator in acute multidimensional poverty. Finally, by examining the characteristics of poor households, it can be noted that households with acute poverty have gradually become older, smaller, and less educated. Therefore, it seems that programs like subsidies to the entire society are no longer helpful for poverty reduction in Iran and it can be improved by better targeting and addressing educational deprivation.