Ingvild Almås

Measurement of real income, inequality and poverty

"International Income Inequality: Measuring PPP Bias by Estimating Engel Curves for Food", American Economic Review, 102(2), 1093-1117, 2012

Purchasing power-adjusted incomes applied in cross-country comparisons are measured with bias. This paper estimates the purchasing power parity (PPP) bias in Penn World Table incomes and provides corrected incomes. The bias is substantial and systematic: the poorer a country, the more its income tends to be overestimated. Consequently, international income inequality is substantially underestimated. The methodological contribution is to exploit the analogies between PPP bias and the bias in consumer price index (CPI) numbers. The PPP bias and subsequent corrected incomes are measured by estimating Engel curves for food, an established method of measuring CPI bias. (JEL C43, D31, E31, O11, O12)

"Rags and Riches: Why Consumption Patterns Matter for Inequality" (with A. Kjelsrud), 2016.

It is well known that people’s consumption patterns change with income. Relative price changes therefore affect rich and poor consumers differently. Yet, the standard price indices are not income-specific and hence, the use of such indices mask these differences in cost-of-living. In this paper, we study consumption inequality in India, while fully allowing for non-homotheticity. That is, we produce different price indices for people with different level of affluence. Our analysis shows that the changes in relative prices in a large part of the period from 1993 to 2012 were pro-poor, in the sense that they favored the poor relative to the rich. As a result, we also find that the standard measures of consumption inequality significantly overestimate the rise in real consumption inequality. Moreover, we show that the allowance for non-homotheticity is quantitatively much more important in our application than the adjustment for substitution in consumption, despite the larger attention paid to the latter in the price index literature. We also illustrate how conventional measures produce biased results of inter-temporal changes in inequality when there is segregation in consumption/production, by which we mean that people’s consumption patterns are skewed towards goods intensively produced by people at the same affluence level.

We provide indicative evidence of this skewness by comparing households engaged in crop production with other types of households. The rural crop producers are poorer than the average household and they therefore also devote a larger share of their budget to necessities such as cereals and food grains. Their labor incomes react positively to increases in crop prices, but they also have to pay disproportionally for these price increases as their consumption consist of food grains to a larger extent than it does for the rest of the population on average. We find that decreases in the relative price of cereals are associated with increases in the conventional inequality measures. However, when we allow for non-homotheticity the association between cereal prices and inequality is substantially weaker and no longer statistically significant. This particular example illustrates that conventional measures that rely on homothetic preferences overstate changes in real inequality that are induces by relative price changes whenever there are elements of segregation in consumption/production.

"Global Income Inequality and Cost-of-Living Adjustment: The Geary-Allen World Accounts" (with E. Sørensen), Department of Economics, NHH, Discussion paper, 20/2012. Soon ready to be submitted.

Traditional price deflators such as the country-specific consumer price indices and the Penn World Table purchasing power parities give one price deflator for each year/country. As preferences are not homothetic, changes in prices of specific goods affect poor and rich differently. Hence, price deflators should be both year/country and income specific. We introduce a method that provides such income-specific deflators and provide an application to international comparisons and world inequality.

"Lost in Translation: What Do Engel Curves Tell Us about the Cost of Living?" (with Tim Beatty and Thomas Crossley), manuscript.

The Hamilton method for estimating CPI bias is simple and intuitively appealing and has been widely adopted. We show that the Hamilton method is internally inconsistent and conflates CPI bias with variation in cost of living across income levels. We demonstrate a method by which these two components can be disentangled. When applied to Hamilton's data our method gives larger estimates of CPI bias. Our approach can recover changes in cost of living for any income level and we exploit this to study growth in the median income for the United States.