Prices, Engel Curves, and Time-Space Deflation: Impacts on Poverty and Inequality in Vietnam

Abstract

Many developing countries lack spatially disaggregated price data. Some analysts use "no-price" methods by using a food Engel curve to derive the deflator as that needed for nominally similar households to have equal food shares in all regions and time periods. This method cannot be tested in countries where it is used as a spatial deflator since they lack suitable price data. In this paper, data from Vietnam are used to test this method against benchmarks provided by multilateral price indexes calculated from repeated spatial price surveys. Deflators from a food Engel curve appear to be a poor proxy for deflators obtained from multilateral price indexes. To the extent that such price indexes reliably compare real living standards over time and space, these results suggest that estimates of the level, location, and change in poverty and inequality would be distorted if the Engel method deflator was used in their stead.

Toward better global poverty measures

“…The first relates to a deep, but poorly recognized, identification problem in longstanding efforts to set international poverty lines based on national lines while striving for global welfare consistency-that one judges poverty by a globally consistent welfare 31 Antecedents using empirical Engel curves to estimate price indices include Hamilton (2001) and Almås (2012). 32 In what appears to be the only test of the Engel curve method to date Gibson et al (2014) found that it performed poorly in Vietnam when compared to reliably-observed geographic price relatives. Further tests are needed.…”

Prices for Poverty Analysis in Africa

“…How reliable are Engel curve estimates of inflation? Most empirical applications (for example, Gibson, Le, and Kim 2014;Hamilton 2001;Olivia and Gibson 2013;Dabalen, Gaddis, and Nguyen 2016) control for broad relative prices and household-level factors that impact on the share of the budget spent on food, such as demographic composition. However, any movement in the Engel curve that cannot be explained by the covariates included in the regression model will be attributed to CPI bias (Hamilton 2001).…”

“…Empirical studies confirm that results from Engel curve estimations are not necessarily robust, especially in spatial contexts. Gibson, Le, and Kim (2014) compare Engel curve-based spatial deflators and spatially disaggregated inflation rates with multilateral price indexes computed from repeated spatial price surveys in Vietnam. In this validation exercise, the price indexes derived through Engel curve estimations appear to be poor proxies for cost-of-living differences.…”

Regional inequality in urban China, allowing for spatial cost of living differences: Evidence from a hedonic analysis of apartment prices

“…Lan and Sylwester (2010) find half-life divergences from the law of one price average just 2.4 months, which is twice the speed of adjustment in the United States. Moreover, this method compares badly with benchmark cost of living measures from price surveys (Gibson, Le, & Kim, 2017). Indeed, Moulton (1995, p. 181) notes that, "costs of shelter are the single most important component of inter-area differences in the cost-of-living."…”