Prices differ across space: from province to province, from rural (or urban) areas in one province to rural (or urban) areas in another province, and from rural to urban areas within one province. Systematic differences in prices across a range of goods and services in different localities imply regional differences in the costs of living. If high-income provinces also have high costs of living, and low-income provinces have low costs of living, the use of nominal income measures in explaining such economic outcomes as inequality can lead to misinterpretations. Income should be adjusted for costs of living. We are interested in the sign and magnitude of the adjustments needed, their changes over time, and their impact on economic outcomes in China. In this article, we construct a set of (rural, urban, total) provincial-level spatial price deflators for the years 1984-2002 that can be used to obtain provincial-level income measures adjusted for purchasing power. We provide illustrations of the significant effect of ignoring spatial price differences in the analysis of China's economy. This is the Pre-Published Version 1 Spatial Price Differences in China: Estimates and Implications IntroductionPrice indices are standard statistical data that are constructed by statistical authorities across all countries. The key price index often is the Consumer Price Index (CPI). In the U.S., for example, the CPI serves as an economic indicator used in formulating fiscal and monetary policy, as a deflator of other economic series (for example, retail sales, or hourly and weekly earnings), and as a means of adjusting dollar values (for example, when social security benefits are indexed using the CPI). 1 But while the calculation and use of price indices are widespread, absolute price comparisons across localities are usually not po ssible. Thus, in the U.S., the Bureau of Labor Statistics compiles a nationwide urban CPI based on about 80,000prices recorded in 87 urban areas by aggregating individual commodity or area indices. 2 The commodities are specific to the local outlets; no data are collected on the price of one specific commodity in different areas of the U.S. A comparison of the absolute price level in one locality with that in another locality, thus, is not possible for the U.S.China's National Bureau of Statistics (NBS), like the Bureau of Labor Statistics in the U.S., publishes a number of official price indices, including national and provincial CPIs, as well as separate CPIs for rural and urban areas at both the national and the provincial level.These price indices allow a comparison of the changes in the level of consumer prices over time across different localities, but do not permit a comparison of absolute price levels between different localities at a given point in time. Like the Bureau of Labor Statistics, the NBS does not publish data on the individual prices and quantities underlying the provincial price indices it constructs.The ability to compare the absolute price level across localities at a point i...

Prices differ across space: from province to province, from rural (or urban) areas in one province to rural (or urban) areas in another province, and from rural to urban areas within one province. Systematic differences in prices across a range of goods and services in different localities imply regional differences in the costs of living. If high-income provinces also have high costs of living, and low-income provinces have low costs of living, the use of nominal income measures in explaining such economic outcomes as inequality can lead to misinterpretations. Income should be adjusted for costs of living. We are interested in the sign and magnitude of the adjustments needed, their changes over time, and their impact on economic outcomes in China. In this article, we construct a set of (rural, urban, total) provincial-level spatial price deflators for the years 1984-2002 that can be used to obtain provincial-level income measures adjusted for purchasing power. We provide illustrations of the significant effect of ignoring spatial price differences in the analysis of China's economy. IntroductionPrice indices are standard statistical data that are constructed by statistical authorities across all countries. The key price index often is the Consumer Price Index (CPI). In the U.S., for example, the CPI serves as an economic indicator used in formulating fiscal and monetary policy, as a deflator of other economic series (for example, retail sales, or hourly and weekly earnings), and as a means of adjusting dollar values (for example, when social security benefits are indexed using the CPI). 1 But while the calculation and use of price indices are widespread, absolute price comparisons across localities are usually not po ssible. Thus, in the U.S., the Bureau of Labor Statistics compiles a nationwide urban CPI based on about 80,000prices recorded in 87 urban areas by aggregating individual commodity or area indices. 2 The commodities are specific to the local outlets; no data are collected on the price of one specific commodity in different areas of the U.S. A comparison of the absolute price level in one locality with that in another locality, thus, is not possible for the U.S.China's National Bureau of Statistics (NBS), like the Bureau of Labor Statistics in the U.S., publishes a number of official price indices, including national and provincial CPIs, as well as separate CPIs for rural and urban areas at both the national and the provincial level.These price indices allow a comparison of the changes in the level of consumer prices over time across different localities, but do not permit a comparison of absolute price levels between different localities at a given point in time. Like the Bureau of Labor Statistics, the NBS does not publish data on the individual prices and quantities underlying the provincial price indices it constructs.The ability to compare the absolute price level across localities at a point in time can be important, however. The prices that consumers pay, even for identical products, are ...

Since the 1998 "wind of falsification and embellishment," Chinese official GDP statistics have repeatedly come under scrutiny. This paper evaluates the quality of China's GDP statistics in four stages. First, it reviews past and ongoing suspicions of the quality of GDP data and examines the evidence. Second, it documents the institutional framework for data compilation and concludes on the implications for data quality. Third, it asks how the National Bureau of Statistics could possibly go about credibly falsifying GDP data without being found out. Fourth, it examines if the first-and second-digit distributions of official GDP data conform to established data regularities (Benford's Law). The findings are that the supposed evidence for GDP data falsification is not compelling, that the NBS has much institutional scope for falsifying GDP data, and that certain manipulations of nominal and real data would be virtually undetectable. Official GDP data, however, exhibit few statistical anomalies (conform to Benford's Law) and the NBS thus either makes no significant use of its scope to falsify data, or is aware of statistical data regularities when it falsifies data.