 The relationship between growth and poverty in forecasting framework: Pakistan's future in the year 2035Khalid Zaman () and Bashir Ahmad Khilji Economic Modelling, 2013, vol. 30, issue C, 468-491 Abstract: Forecasting poverty in the future is mostly a matter of forecasting economic growth. The objective of the study is to examine the inter-temporal link between growth and poverty in Pakistan, over the next 25years period i.e., from the years 2011 to 2035. The generalized version of variance decomposition and impulse response analysis is operated in this study to test the temporal causality among poverty measures (i.e., head count ratio, poverty gap and squared poverty gap), growth measures (i.e., average household income, industry value added and agriculture value added) and income inequality to see if the growth of income and poverty measures contains considerable information to predict each other, on the sectoral level of Pakistan i.e., rural, urban and national level. The results of variance decomposition analysis show that shock to household counts initially accounts for a considerable portion of the forecast error variance of average household income in all rural, urban and at national level respectively. Household counts have the highest impact on average income in Pakistan (approximately 93.2%), followed by urban region (approximately 90.5% in average) and the lowest in rural areas (approximately 82.3%) both in short- and long-run. Impulse response analysis demonstrates that growth, poverty measures and income inequality are so strongly knitted to one another that any positive shock to any one of them would be beneficial on the one hand and may be harmful on the other hand. The vicious cycle of poverty can only be scratched by giving consistent positive shocks to growth and negative shocks to income inequality. Keywords: Poverty; Growth; Income inequality; Variance decomposition; Impulse response function; Pakistan (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:30:y:2013:i:c:p:468-491 DOI: 10.1016/j.econmod.2012.07.021 Access Statistics for this article Economic Modelling is currently edited by S. Hall and P. Pauly More articles in Economic Modelling from Elsevier |
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