Goods Prices and Availability in Cities

This paper uses detailed barcode data on purchase transactions by households in 49 U.S. cities to calculate the first theoretically-founded urban price index. In doing so, we overcome a large number of problems that have plagued spatial price index measurement. We identify two important sources of bias. Heterogeneity bias arises from comparing different goods in different locations, and variety bias arises from not correcting for the fact that some goods are unavailable in some locations. Eliminating heterogeneity bias causes 97 percent of the variance in the price level of food products across cities to disappear relative to a conventional index. Eliminating both biases reverses the common finding that prices tend to be higher in larger cities. Instead, we find that price level for food products falls with city size

Goods Prices and Availability in Cities

This paper uses detailed barcode data on purchase transactions by households in 49 U.S. cities to overcome a large number of problems that have plagued spatial price index measurement. We identify two important sources of bias. Heterogeneity bias arises from comparing different goods in different locations, and variety bias arises from not correcting for the fact that some goods are unavailable in some locations. Eliminating heterogeneity bias causes 97 percent of the variance in the price level of food products across cities to disappear relative to a conventional index. Eliminating both biases reverses the common finding that prices tend to be higher in larger cities. Instead, we find that price level for food products falls with city size.

"The Financial Requirements of Achieving Gender Equality and Women's Empowerment"

Although the Millennium Development Goals (MDGs) have been ratified in global and national forums, they have not yet been incorporated into operational planning within governments or international organizations. The weak link between the policies and the investments needed for their implementation is one barrier to progress. An assessment of the resources required is a critical first step in formulating and implementing strategies to achieve the MDGs. This is especially true for policies to promote gender equality and empower women. Although enough is known about such policies to implement them successfully, the costs of such interventions are not systematically calculated and integrated into country-level budgeting processes. Using country-level data, the paper estimates the costs of interventions aimed at promoting gender equality and women's empowerment in Bangladesh, Cambodia, Ghana, Tanzania, and Uganda. It then uses these estimates to calculate the costs of such interventions in other low-income countries. Finally, the paper projects the financing gap for interventions that aim directly at achieving gender equality, first for the five countries, and subsequently for all low-income countries.

How Much Do Official Price Indexes Tell Us About Inflation?

Official price indexes, such as the CPI, are imperfect indicators of inflation calculated using ad hoc price formulae different from the theoretically well-founded inflation indexes favored by economists. This paper provides the first estimate of how accurately the CPI informs us about “true” inflation. We use the largest price and quantity dataset ever employed in economics to build a Törnqvist inflation index for Japan between 1989 and 2010. Our comparison of this true inflation index with the CPI indicates that the CPI bias is not constant but depends on the level of inflation. We show the informativeness of the CPI rises with inflation. When measured inflation is low (less than 2.4% per year) the CPI is a poor predictor of true inflation even over 12-month periods. Outside this range, the CPI is a much better measure of inflation. We find that the U.S. PCE Deflator methodology is superior to the Japanese CPI methodology but still exhibits substantial measurement error and biases rendering it a problematic predictor of inflation in low inflation regimes as well.2012～2016年度科学研究費補助金[基盤研究(S)]「長期デフレの解明」(研究代表者 東京大学経済学研究科・渡辺努, 課題番号：24223003