The views expressed herein are those of the author(s) and not necessarily those of the National Bureau of Economic Research. ©2004 by Dennis W. Carlton. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source.

Since the start of economic reforms in 1978, China has experienced the largest increase in income inequality of all countries for which comparable data are available. According to the World Bank (1997), China’s Gini coefficient increased from 28.2 in 1981 to 38.8 in 1995 based on official survey data. Another study that used internationally standard definitions for incomes estimated China’s Gini ratio at 38.2 in 1988 and 45.2 in 1995, a level that already surpassed many developing economies in Asia (Azizur Khan and Carl Riskin, 1998). Are these income inequality changes the consequence of institutional reforms that replaced egalitarian rewards with work incentives, employment contracts, and labor mobility? This paper uses household survey data collected by China’s State Statistical Bureau (SSB) to investigate the sources and causes of this rising inequality. By analyzing Gini ratios and generalized entropy measures, I decompose the overall inequality into three sectoral components: ( i ) inequality within rural areas, ( ii ) inequality within urban areas, and (iii ) sectoral disparity. The data indicate that increases in rural – urban income differentials have been the driving factor behind the rising overall inequality in China. I argue that urbanbiased policies and institutions, including labor mobility restrictions, welfare systems, and financial policies of inflation subsidies and investment credits to the urban sector, are responsible for the long-term rural–urban divide and the recent increases in disparity.

This paper uses evidence on individual transaction prices to analyze price behavior. The evidence shows that, for many transactions, pricesremain rigid for periods exceeding one year. The rigidity of price ispositively correlated with industry concentration. For several productsthe correlation of price changes across buyers is low. The paper alsoinvestigates the relationship between price rigidity, price change, andthe length of time a buyer and seller have been doing business together. The author interprets the evidence as emphasizing the importance of nonprice rationing and the inadequacy of models in whichprice movements alone clear markets.

For many transactions, prices remain rigid for periods exceeding one year. Price rigidity is positively correlated with industry concentration. For several products, the correlation of price changes across buyers is low. The paper also investigates the relationship between price rigidity, price change, and the length of time a buyer and seller have been doing business. The evidence emphasizes the importance of non price rationing and the inadequacy of models in which price movements alone clear markets.