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

Most empirical work in economics has considered only a narrow set of measures as meaningful and useful to characterize individual behavior, a restriction justified by the difficulties in collecting a wider set. However, this approach often forces the use of strong assumptions to estimate the parameters that inform individual behavior and identify causal links. In this paper, we argue that a more flexible and broader approach to measurement could be extremely useful and allow the estimation of richer and more realistic models that rest on weaker identifying assumptions. We argue that the design of measurement tools should interact with, and depend on, the models economists use. Measurement is not a substitute for rigorous theory, it is an important complement to it, and should be developed in parallel to it. We illustrate these arguments with a model of parental behavior estimated on pilot data that combines conventional measures with novel ones.

There are striking differences in inequality and redistribution between the United States and Scandinavia. To study whether there are corresponding differences in social preferences, we conducted a large-scale international social preference experiment where Americans and Norwegians make distributive choices in identical environments. Combining the infrastructure of an international online labor market and that of a leading international data collection agency, we show that Americans and Norwegians differ significantly in fairness views, but not in the importance assigned to efficiency. We also provide causal evidence suggesting that fairness considerations are more fundamental for inequality acceptance than efficiency considerations.

This paper provides the first comprehensive global evidence on people’s fairness and efficiency preferences, beliefs about the sources of inequality and the efficiency cost of redistribution, and policy attitudes toward redistribution. Using a globally harmonized consequential experiment with more than 65,000 individuals across 60 countries, we show that the source of inequality plays a substantially larger role for inequality acceptance than the efficiency cost of redistribution. At the global level, implemented inequality increases by 85 percent when inequality is caused by merit rather than luck, compared to a 14 percent increase when redistribution entails a 50 percent efficiency cost. We document substantial heterogeneity in fairness views and beliefs both within and across societies. The meritocratic fairness view is most prominent in many richer Western societies, while libertarian and egalitarian fairness views are widespread in many other parts of the world. Globally, people are more likely to believe that inequality reflects luck rather than merit, while beliefs in large efficiency costs of redistribution are relatively weak. Fairness preferences and beliefs are strongly associated with redistribution attitudes and actual redistribution through taxes and transfers across countries. Our findings illustrate how the interaction between fairness views and beliefs may shape redistribution across societies, highlighting the importance of jointly understanding preferences and beliefs in the political economy of redistribution.

We exploit a unique data set, combining rich experimental data with high-quality administrative data, to study dropout from the college track in Norway, and why boys are more likely to drop out. The paper provides three main findings. First, we show that family background and personal characteristics contribute to explain dropout. Second, we show that the gender difference in dropout rates appears both when the adolescents select into the college track and after they have started. Third, we show that different processes guide the choices of the boys and the girls of whether to drop out from the college track.