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This paper was written in connection with the IMF’s 2002 Article IV Consultations with Hong Kong SAR. I thank Jahangir Aziz, Tony Elson, Dora Iakova, Stefan Gerlach, Jiming Ha, Chandima Mendis, Markus Rodlauer, K.Y. Tang, and Wanda Tseng for helpful comments. I am grateful to Anna Maripuu and Fritz Pierre-Louis for their excellent research assistance, and I also thank Natalie Baumer and Jeanette Morrison for editorial comments. The paper has benefited from the comments of seminar participants at the East Asian Economic Association Convention in Malaysia, the Hong Kong Institute for Monetary Research, and the IMF.
Survey evidence suggests that the gap is rather large in absolute terms. CLSA (2001) reports that a basket of nondurable consumer goods is about 40 percent cheaper in Shenzhen.
All price level and inflation rate variables in this paper have been seasonally adjusted with the U.S. Bureau of Census X11.2 procedure. For presentational purposes, the percentage gaps are mean-standardized. All data are taken from CEIC and China Statistics Monthly. All of the following regressions have been estimated with OLS.
All lags in this paper refer to one-year lags.
The speed of convergence is meant to capture the extent of integration between markets or the efficiency with which price differentials between spatially separate locations are arbitraged away. See Obstfeld and Taylor (1997), and Ejrnaes and Persson (2000) for extensions.
The sample period is smaller than for the previous regressions due to limited data availability. The choice of quarterly frequency is motivated by the need to control for the cyclical component.
Over the sample period under review, the inflation variable is found to be stationary.
Due to differences in CPI aggregation between Shenzhen and Hong Kong SAR, inevitable problems arise when constructing comparable subcomponent CPI indices. For this reason, the Shenzhen subcomponent of “recreational, educational, and cultural articles” has been left out. As to the remaining components, a sufficiently close match has been achieved, although some differences remain: (1) the Shenzhen food index includes alcoholic drinks and tobacco; (2) the Shenzhen durable goods index excludes durable goods for recreational use; (3) the Shenzhen transportation index includes communication (4) the Shenzhen housing index includes gas, water, and electric; and (5) the services index has been left out for 2001 as the Shenzhen definition was changed that year.
The formula for calculating the contributions is
Ha and Fan use individual price data, compiled from cost-of-living surveys by the Economist Intelligence Unit, rather than aggregate CPI data. Further, sample sizes differ. While the use of individual price data allows for a richer data set in the cross-sectional dimension, the data is collected only semi-annually, with most individual price data for Shenzhen being available only from 1999 onwards.
CLSA Emerging Markets, 2001 “Hong Kong’s future. Tough choices to stay afloat,” Hong Kong Market Strategy Report (Hong Kong SAR), November.
Zitzewitz (2000) shows that, compared to OECD economies, price adjustment has historically been much faster in Hong Kong SAR. Mark-up margins are significantly more pro-cyclical in services, while only slightly more counter-cyclical in manufacturing. The shift to a service-based economy has therefore made economy-wide margins more pro-cyclical, contributing to a rate of price adjustment that is faster than in the OECD.
The incomplete adjustment of real wages, associated with higher unemployment, is not necessarily the result of inefficiency. Lack of adjustment could be explained by the reluctance of employers to lower nominal wages because of efficiency wage arguments: lower wage may lead to lower productivity and employers may therefore prefer to lay off employees. Also, the sole consideration of wage data distorts the degree of labor market flexibility as non-wage compensation items, such as bonuses, have declined significantly too.
Survey data indicate that SMEs (enterprises defined as having less than 100 employees) contribute 43 percent of value-added in the manufacturing sector, 59 percent in the construction sector, 78 percent in the distributive and catering trades, 32 percent in the transport, storage, and communication sector, and 66 percent in the financing, insurance, real estate, and business services sector.
Manove, Padilla, and Pagano (2001) show that over-reliance on collateral may lead to market equilibria in which the provision of cheap credit is inappropriately emphasized over project screening.