No abstract

This paper assesses the current state of evidence on the impact of trade policy reform on poverty in developing countries. There is little empirical evidence addressing this question directly, but a lot of related evidence on specific aspects. We summarize this evidence using an analytic framework addressing four key areas: economic growth and stability; households and markets; wages and employment and government revenue. Twelve key questions are identified and empirical studies and results are discussed. We argue that there is no simple generalizable conclusion about the relationship between trade liberalization and poverty, and the picture is much less negative than is often suggested. In the long run and on average, trade liberalization is likely to be strongly poverty alleviating, and there is no convincing evidence that it will generally increase overall poverty or vulnerability. But there is evidence that the poor may be less well placed in the short run to protect themselves against adverse effects and take advantage of favorable opportunities.

Anti-poverty programmes often seek to improve their impact by targeting households for assistance according to welfare measures in a single time period. However, a growing literature shows the importance to poor households of fluctuations in their welfare from month to month and year to year. This study uses a five-year panel of 686 households from rural Pakistan to investigate the magnitude of chronic or transitory poverty making an explicit adjustment for measurement error. The impact of two types of policies (those designed to 'smooth' incomes and those designed to promote income growth) on the severity of chronic and transitory poverty is examined. Since the largest part of the squared poverty gap in our sample is transitory, large reductions in poverty can be achieved by interventions designed to 'smooth' incomes, but reducing chronic poverty in the long-term requires large and sustained growth in household incomes. The level and variability of incomes is then modelled as a function of household characteristics, education and assets. The resulting model of the income generation process is used to simulate the impact that a range of transfer and investment policies would have upon chronic and transitory poverty.

P o v e r t y S t a t u s a n d P o v e r t y T r a n s i t i o n s i n R u r a l P a k i s t a n I D S W O R K I N G PThe results show that while the incidence of income poverty in the sample villages was high, turnover among the poor was also rapid. In each year of the survey between 21 per cent and 29 per cent of households had incomes below the poverty line, but 46 per cent to 51 per cent of poor households exited poverty from one year to the next. Only 3 per cent of households were poor in all five years of the panel. Furthermore, the correlates of entries and exits from poverty were found to differ in important but unexpected ways from those of poverty status. The dependency ratio and geographic variables were important correlates of poverty status, but neither had much impact on entries into or exits from poverty. Other variables, such as education and livestock ownership, had asymmetric impacts on poverty transitions: increasing exit or reducing entry probabilities without influencing transitions in the opposite direction. Further analysis, however, is necessary to identify the events which preceded households moving into or out of poverty.The policy implications of these findings, if confirmed elsewhere, indicate that targeting anti-poverty policies using the characteristics of the currently poor is highly problematic. If governments care primarily about reducing the poverty headcount, they should focus their efforts on increasing exits from and decreasing entries into poverty. Focusing anti-poverty efforts on the correlates of poverty status means that it is the symptoms rather than the causes of poverty that are being addressed.* Respectively, Fellow and Research Officer, Institute of Development Studies at the University of Sussex. The authors thank IFPRI for granting them access to the Pakistan panel data set and Richard Adams, John Hoddinott, Stephen Jenkins and participants at seminars at the LSE, IDS and UoS for helping them think through the methodology. Stephen Devereux, Howard White and Adrian Wood made valuable comments on earlier versions of this paper, while Jenny Edwards provided excellent secretarial support. All errors remain the responsibility of the authors and senior authorship is not assigned.