Pro-poor economic policies aim to increase the economic returns for the poor segments of the society. The objective of this research is multifold i.e., First, to examine the relationship between growth, inequality and poverty in the context of rural, urban and at national level, secondly, to look at the impact of intra-sectoral gains/losses and inter-sectoral shifts in population on aggregate changes in poverty in Pakistan. Thirdly is, to investigates the interrelation between social expenditures (i.e., human development, rural development, safety nets and community services), inequality, and poverty in Pakistan over a period of 1964-2011, and fourth is, to observe how economic growth may affect to the poors in the future (inter-temporal link) in Pakistan over the next 25 years period. The regression model encompasses the impact of economic growth and inequality on poverty reflects that one percent increase in income reduces poverty around 0.276 percent in national weighted regression, if distribution remains constant. An increase in Gini coefficient tends to increase poverty around 1.721 percent, if income remains constant. Subsequently, in urban and rural regions, it creates proportionally more poor households in the urban areas than in the rural areas. This study measures pro-poor growth index that shows gains and losses of growth rates due to changes in consumption. The gains imply pro-poor growth, while the losses imply anti-poor growth. Total growth spells in this study are 180 for overall Pakistan. The results conclude that out of 180 growth spells, 63 growth spells had negative growth rates and 117 spells had positive growth rates. Thus, growth processes have not generally been favorable to the poor. VThe result show that both the urban and rural sectors contributed to the increase in aggregate poverty, though the “interaction effect” and the “population shift effect” alleviated poverty, and the overall impact was negligible. The result point out that as compared to the non-poor, the poor overall benefited less from the revitalization of agricultural process; among the poor people the ultra-poor received proportionally more benefits. This study extends the concept of pro-poor growth measure that satisfies the monotonicity criterion relative with social expenditures. This measure indicates as ‘poverty equivalent social expenditure rate’, which shows how the benefits of these expenditures are distributed to the poor and the non-poor. The results found that the social expenditures in Pakistan are not intrinsically pro poor. Forecasting poverty in future is mostly a matter of forecasting economic growth. The generalized version of variance decomposition and impulse response analysis has operated in this study to test the inter-temporal causality among poverty. The result of variance decomposition analysis shows that household counts have the highest impact on average income i.e., 93.2 percent in Pakistan, 90.5 percent in urban and 82.3 percent in rural areas approximately. 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.