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This work draws on one of my Ph.D. dissertation chapters prepared at the University of California, Los Angeles. I am grateful to Arnold Harberger for his guidance and comments. I would also like to thank Kenneth Sokoloff, Deepak Lal, Chris Thornberg, Benos Nikolaos, and Yongkul Won for helpful comments and suggestions. This paper has also benefited from discussion with my colleagues at UCLA as well as from participants at the 8th Annual Conference on Macroeconomic Analysis and International Finance and the 3rd International Conference of the Japan Economic Policy Association. All remaining errors are my own.
Cross-country comparisons by Balassa (1964) demonstrate a positive correlation between price levels and income levels.
Previous work quantitatively confirms the existence of large gaps in productivity improvements between the tradables and nontradables sectors in Japan. See Miyajima (2004).
Bhagwati (1984) is directly motivated by Kravis, Heston and Summers (1982), a work on international comparisons of national income and price structure. Kravis, Heston, and Summers confirm the finding of Balassa (1964) in that the price level of services is typically lower in poor countries, which is considered to be the consequence of smaller gaps in productivity growth between the tradables and nontradables sectors.
For instance, when RERs are regressed on a time trend, Harberger (2003) obtains 18 positive coefficients and 7 negative coefficients. The results of other regressions are found to be similar. Regarding significance (up to the 5 percent level), 13 positive and 5 negative coefficients are significant, while 5 positive and 2 negative coefficients are not.
Harberger (1997) demonstrates that this so-called two-deflator method is as reliable as one of the most sophisticated methods of modern growth accounting established by Jorgenson and his co-authors, which cross-classifies factor and intermediate inputs in order to account for quality differences. See, for instance, Jorgenson and Stiroh (2000).
Harberger (2003) implements a similar exercise, which looks for periods in which economic growth exceeds 5 percent per year over a period of at least one decade. So as not to count periods of huge spurts in GDP as secular growth, Harberger also insists that the initial and final years of the period should display growth rates of at least 4 percent. He finds 25 episodes of extended rapid growth.
The international price of tradable goods is estimated as a weighted average of WPI in France, Germany, Japan, the United Kingdom, and the United States, all expressed in terms of U.S. dollar. These are the five SDR countries defined by the IMF, and these countries are assumed to represent a large share of activities in international markets (Harberger, 1989). The most recent SDR weights are used for the estimation.
Engel (1999) finds that a large share of the movements in RERs is accounted for by the tradable component. Similar results are found in my data by estimating the mean square error statistics as in Engel (1999). Such a finding, however, does not conflict with this paper’s main results that the long-run trend in RERs is largely accounted for by the nontradable component.
Changes in labor quality are accounted for through the labor income-based approach, as opposed to the cost-based approach. The former approach assumes that wages equal to marginal product of labor and that wages capture the return on all investments in the formation of human capital. The latter approach uses years of education to capture human capital accumulation by assuming that the stock of human capital is linearly related to the number of years spent at school.
While one may argue that quality differences in output should be accounted for, this paper does not make such adjustments. This is simply because, as it is not clear how quality differences in output can be adjusted, such adjustments would remain arbitrary at best.
OECD STAN data.
Such adjustments are consistent with the assumption of profit-maximizing firms.
Chen and Rogoff (2003) use a similar set of regressions. They estimate several OLS using the data in levels and first differences. They consider alternative underlying data-generating processes, and estimate SOLS and DOLS as robustness checks.
Based on data for 14 OECD countries, correlation coefficients of these variables are mostly clustered around 0.9 in levels and around 0.3 in first differences. Hence, in equations (19) and (20), β is expected to be positive, especially using the data in first differences. There is no prior in terms of the sign of γ.
The unit root null is rejected for all series at least at the 10 percent level.
Table 5 summarizes measured TFP gains in the two sectors and estimation periods for each country. The sample includes US. T and NT stand for the tradables and nontradables sectors, respectively, and rates of growth are in terms of average per annum.
Australian Government Productivity Commission (2004).
While one may argue that agriculture in Europe is equally protected and subsidized, it is included in the tradable sector. In the literature, few adjustments at all seem to have been made to account for protection, and the tradables (T) and nontradables (N) sectors are defined simply as follows. In Balassa (1964), T = agriculture and manufacturing and NT = services. Officer (1976a) defines T = agriculture, mining, and manufacturing and N = other sectors. Hsieh (1982) sets T = manufacturing and N = other sectors. De Gregorio, Giovannini, and Wolf (1994), De Gregorio and Wolf (1994), and Chinn (1997) define T = agriculture, mining, manufacturing, and transportation and N = other sectors. In Ito, Isard, and Symansky (1997), T = manufacturing and N = services. Canzoneri, Cumby, and Diba (1996) set T = agriculture and manufacturing and N = more or less other sectors.