database, mostly covering the 1990s and 2000s.<sup>3</sup> Changes in poverty are estimated across consecutive household surveys that vary in duration (i.e., based on survey frequency). To avoid mixing very long with very short changes in poverty, we focus on observation in which the gap between consecutive surveys varies between one and five years of duration and test sensitivity to restrictions within that range. The poverty measures we focus on are changes (first differences) in the $1.25/day and $2/day headcounts, measured at 2005 international dollars. We also drop countries with very low levels of initial poverty (less than 5% in the $1.25 per day headcount) to exclude upper-middle income countries in which food is less important for both consumption and production, and to prevent the sample from being heavily overloaded with such countries.<sup>4</sup> While there are many challenges in measuring comparable poverty rates across countries and over time, one particular concern with POVCAL estimates is the possibility that they suffer from biases stemming from the use of consumer price indices (CPIs) to deflate nominal estimates of household expenditure or income (or equivalently, to deflate poverty lines). Here there are two sources of bias. First, if the weights in the CPI consumption basket differ substantially from the expenditure patterns of the poor, there is a possibility of CPI bias during periods of real increases in the price of food. However, the POVCAL series used herein contains adjustments for this problem whenever food weights in the CPI were deemed to be excessively low. Moreover, a recent World Bank study of poverty in Africa in fact found evidence that CPI bias during periods of high food inflation typically works in the opposite direction: corrections for CPI bias in Africa would lead to faster poverty reduction during the recent period of rising food prices (Beegle et al. 2016).<sup>5</sup> Second, when food prices increase, the poor will presumably do little to reduce the quantity of food consumed, particularly if their food expenditure is already focused on the cheapest sources of calories and if their calorie consumption is already close to minimum subsistence levels. In the extreme case, food quantities consumed might be entirely unaffected by higher prices, meaning that an increase in food prices would result in a commensurately large increase in food expenditure shares. Hence, even if the original food expenditure share used in the CPI calculation were correct prior to an increase in real food prices, it would be an underestimate of the amount the poor spend on food after an increase in real food prices. This second type of CPI bias—a classic index number problem—is likely to be smaller in magnitude than the first type of CPI bias referred to above, but both types of bias raise the concern that changes in food prices and changes in poverty could be spuriously correlated because of the way POVCAL data are calculated. It is partly for this reason that we also investigate the impacts of food price changes on FAO agricultural production statistics (see below), since the latter do not suffer from these CPI biases.

# _Food Price Indicators_

The explanatory variable of interest in all our regressions is the change in real food prices, measured as the ratio of the food CPI to the total CPI. Relative to other indicators of relative food price changes, this series seemed to have little signs of substantial measurement error (though we

> 3. The median endyear of changes in poverty in this sample is 2002.

> 4. Without this restriction, around one-third of observations would be derived from Eastern Europe and Central Asia and another third from Latin America and the Caribbean.

> 5. Personal communications with the researchers managing the POVCAL database confirmed that CPI adjustments were made for approximately 20 countries for which the weight on food products was deemed to be excessively low. For Africa, the aforementioned World Bank study used the assumption that differences in the food budget share among demographically similar households with the same level of consumption at different points in time would indicate the CPI’s mismeasurement of the true cost of living. Strikingly, the official CPIs seem to have overestimated changes in the cost of living for the poor in 13 of the 16 countries examined.

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