Looking Beyond Averages in the Trade and Poverty Debate

by Martin Ravallion

There has been much debate about how much poor people in developing countries gain from trade openness, as one aspect of ‘globalization’. Some observers have argued that poor people share amply in the gains from external trade in developing countries, while others argue that the benefits are captured by those who are not particularly poor.

Various methods have been used to address the issue empirically, including crosscountry comparisons, aggregate time series analyses at country level, and simulation methods using both partial and general equilibrium analyses. A common feature of all these methods is that one attempts to measure the impact of trade openness (or policies to promote openness) on some aggregate measure of inequality or poverty.

Micro data on the living conditions and circumstances of households have pointed to the potential inadequacy of this ‘macro lens’ on the trade-poverty relationship. At any given level of living one finds that some people are net consumers of food, for example, while some are net producers. Thus some gain but some lose from a shift in the relative price of food associated with trade openness. This heterogeneity carries an important lesson for the debate on trade and poverty: conventional poverty and inequality aggregates may hide much more than they reveal.

Evidence from crosscountry studies and time series data

The extensive literature using crosscountry comparisons has left ambiguous implications for the impact of trade openness on poverty within countries. Some studies find little or no effect of trade openness on inequality while other studies have reported adverse effects on inequality. Of course, the implications for measures of poverty will also depend on the growth impacts of openness. Empirical support for the view that trade openness promotes economic growth can be found in a number of studies, though not all. Trade openness does not appear to be a particularly robust predictor of economic growth.

Whether the growth effects are strong enough to entail that poverty falls with trade openness remains unclear. If one accepts the view that trade does not affect inequality but fosters growth then it is very likely to lead to lower absolute poverty (meaning that the poverty line is fixed in real terms). However, if (as some studies have suggested) the growth gains are captured more by the non-poor then this will naturally attenuate the impacts on poverty.

The study assembled new data on changes in aggregate poverty incidence between two household surveys for each of about 80 developing countries (with multiple observations for most countries). (1) This was collated with measures of the extent of trade openness, namely the ratio of exports plus imports to GDP.

The study found no robust sign of a systematic relationship between trade expansion and poverty reduction. There are continuing concerns about the data (notably measurement errors) and the methods (such as the choice of control variables). A negative correlation between trade openness and poverty does emerge when one looked at the longest possible time period for each country, though this was not robust to adding control variables for other factors influencing poverty. No convincing sign of a correlation was found for various changes in the data and methods used. The study’s findings casts doubt on any generalization that greater trade openness necessarily means lower (or higher) poverty in developing countries. There is clearly considerable heterogeneity across countries in the factors influencing the distributional impacts of trade expansion.

An alternative approach that might be able to better isolate the impacts of trade openness is to study time series data on poverty and inequality for a specific country during periods of trade expansion. China is an interesting case study for this purpose given that it has been argued by a number of observers that the country’s greater openness to external trade since Deng Xiaoping’s ‘Open-Door Policy’ of the early 1980s was the key to the subsequent success against poverty. For analytic purposes, China also has the attraction as a case study that going back to the early 1980s allows one to span both a large expansion in trade volume and one of the most dramatic poverty reductions in history; while China’s poverty rate today is probably slightly lower than the average for the world as a whole, it was a very different story around 1980 when the incidence of extreme poverty in China was one of the highest in the world.

However, a closer look at the time series evidence for China casts doubt on the view that greater openness to external trade has been the driving force in poverty reduction. Indeed, it is hard to even make the case from the available data that trade has helped the poor on balance in the short term, though longer-term impacts on productivity may well be more poverty reducing. More plausible candidates for explaining China’s success against poverty since 1980 or so can be found in the role played by the agrarian reforms starting in the late 1970s, subsequent agricultural growth (which had an unusually large impact on poverty given a relatively equitable allocation of land achieved in the wake of the early reforms to de-collectivize agriculture), reduced taxation of farmers, and macroeconomic stability

Household impacts of trade reforms in China and Morocco

Aggregate inequality or poverty need not change with trade reform even though there are both gainers and losers at all levels of living. Numerous sources of such ‘horizontal’ impacts of policy reform can be found in developing country settings. For example, geographic disparities in access to human and physical infrastructure affect prospects for participating in the opportunities created by greater openness to external trade. Similarly, differences in the demographic composition of families will influence consumption behaviour and hence the welfare impact of the shifts in relative prices often associated with trade openness. 

The study reviewed results from two studies in which the price changes induced by the trade policy change are first simulated from the computable general equilibrium model and then carried to the household level using large household surveys. This approach respects the richness of detail that is available from a modern integrated household survey. One can measure the expected impacts across the distribution of initial levels of living, and also look at how the impacts vary by other household characteristics, including location and demographic characteristics. This approach is thus able to provide a reasonably detailed ‘map’ of the predicted welfare impacts by location and socioeconomic characteristics.

The two studies were of China’s accession to the World Trade Organization (WTO) (which entailed substantial changes in tariffs and other trade restriction) and of the impacts of the de-protection of cereals in Morocco.

The China study found an overall gain of about 1.5% in mean income, all in the period leading up to WTO accession. Around the time of formal WTO accession, the incidence of poverty would have been slightly higher if not for the trade policy changes over the lead-up period to WTO accession. Looking forward after joining WTO, the study found negligible impact on poverty across a wide range of the distribution.

However, these aggregates hide both losers and gainers. The generally negative impacts for rural households were found to reach quite high levels amongst certain types of households in certain regions. Farm income is predicted to fall due to the drop in the wholesale prices of most farm products (plus higher prices for education and health care). About three-quarters of rural households are predicted to lose real income after WTO accession. This is true for only one-in-ten urban households. Impacts also differ widely across regions. One spatially contiguous region in the northeast of China stands out as losing the most from the reform. Nonnegligible welfare impacts were revealed in specific localities and for certain types of households, associated with how factors such as the demographic composition and stage of the life-cycle impacted on net trading positions in the relevant markets.

The Morocco study also found negligible aggregate impact on aggregate poverty of partial de-protection on the poverty rate. However, as in the China study, there was a sizeable, and at least partly explicable, variance in impacts across households. The simulations again suggested that rural families tend to lose; urban households tend to gain. Mean impacts for rural households in some parts of the country were over 10% of consumption. There are sizeable expected welfare losses amongst the poor in these specific regions.

These results again lead one to question the high level of aggregation common in past claims about welfare impacts of trade reform. As in the China case, the Morocco study finds diverse impacts at given pre-reform income levels. This ‘horizontal’ dispersion becomes more marked as the extent of reform (measured by the size of the tariff cut) increases. It is clear from these results that in understanding the social impacts of this reform, one should not look solely at income poverty as conventionally measured; rather one needs to look at impacts along horizontal dimensions, at given income.

In conclusion, based on the data available from cross-country comparisons, it is hard to maintain the view that trade openness is, in general, a powerful force for poverty reduction in developing countries. Nor does the aggregate time series evidence data for China suggest that trade reform has been an important factor in reducing poverty in that country.

Similarly, in studying the welfare impacts of specific trade reforms, the study found that WTO accession in China is likely to have had only a small poverty-reducing effect in the aggregate. And cereal de-protection in Morocco is predicted to have only a small adverse impact on poverty in the aggregate.

However, the same case studies point to considerable heterogeneity in impacts at any given level of income. In both China and Morocco, one finds a sizeable and at least partly explicable variance in impacts across households with different characteristics, as relevant to their consumption and production behaviour. This heterogeneity holds potentially important clues for the design of social protection policies to complement trade reforms.

(1) The poverty measures were the percentage of the population living below the widely-used international poverty line of US$1.08 a day at 1993 Purchasing Power Parity. This was estimated for all the surveys included in the World Bank’s data base at:

Martin Ravallion is with the World Bank’s Development Research Group. This article summarizes his paper under the same title prepared for the WIDER project, ‘The Impact of Globalization on the World’s Poor’, presented at a workshop at WIDER, October 2004. These are the views of the author and should not be attributed to the World Bank or any affiliated organization.