Appendix: Description of the Data
The data and programs used in this project are available upon request. The data has been carefully checked through a variety of diagnostic procedures, including descriptive statistics on the levels and differences of the data, and plotting the levels and differences. Numerous errors in the IFS data have been corrected.
Most of the relevant monthly data was collected from the IMF’s International Financial Statistics data base. The bilateral variables (IFS mnemonics) are as follows: period average bilateral (US$ PFX) exchange rates (rf and rh); industrial production index (66..c); CPI (64); PPI (63); and employment (67, 67..c, 67ey and 67eyc). The additional aggregate variables are: the U.S. MERM effective exchange rate (amx); the U.S. net merchandise trade balance (70-71); the global CPI (001..64x); and the industrial country industrial production index (110..66).
The monthly nominal bilateral trade data (all measured in U.S. dollars) is taken from the IMF’s Direction of Trade data base; mnemonics for exports and imports are given by xy…ZDz where “x” represents the country doing the trade; “z” represents the trading partner; and “y” is 71 for imports, 70 for exports. It is interesting and distressing that the data for, e.g., German exports to the United States are quite different from U.S. imports from Germany. The two variables are highly correlated in levels, but their growth rates have only a low (and, in the case of the United Kingdom, negative) correlation.
The monthly tariff data is available from Highlights of U.S. Export and Import Trade (FT 990), published by the U.S. Department of Commerce, Bureau of the Census. The data is taken from Section B, “Imports for Consumption--World Area and Country of Origin” (the exact table number varies over time). “Imports for consumption” measures total merchandise cleared through customs, either because it directly enters consumption channels, or because it is withdrawn for consumption from warehouses under customs’ custody. The data is available on a “customs value basis,” which represents the price actually paid for merchandise when sold for exportation to the United States, excluding U.S. import duties, freight, insurance, and other charges incurred in bringing the merchandise to the United States. Relationships between buyers and sellers should not influence the customs value.
Much of the annual data is available in Historical Statistics of the United States. This includes both measures of the tariff rate, bilateral imports and exports, and real GNP. The U.K. measure of real output is spliced from a variety of series, mostly taken from the Abstract of British Historical Statistics. Jeff Frenkel kindly provided us with the bilateral exchange rate and both U.K. and U.S. net national product price deflators (the data is mostly taken from Friedman and Schwartz). Further documentation is available along with the data.
Beveridge, S., and C. R. Nelson (1981), “A New Approach to Decomposition of Economic Time Series into Permanent and Temporary Components,” Journal of Monetary Economics 7, 151–74.
Branson, W.H. (1987), “Comments on ‘Macroeconomics and Protection’,” U.S. Trade Policies in a Changing World Economy (Stern, ed.) (MIT, Cambridge).
Chan, K. (1978), “The Employment Effects of Tariffs under a Free Exchange Rate Regime” Journal of International Economics 8, 414–24.
Dornbusch, R. (1987), “External Balance Correction: Depreciation or Protection?” Brookings Papers on Economic Activity 1, 249–69.
Eichengreen, B. (1981), “A Dynamic Model of Tariffs, Output, and Employment under Flexible Exchange Rates,” Journal of International Economics 11, 341–59.
Goldstein, M., and M. S. Khan (1985), “income and Price Effects in Foreign Trade,” Handbook of International Economics (R. W. Jones and P.B. Kenen, eds.), North Holland.
Helkie, W., A. J. Hughes Hallett, G.J. Hutson and J. Marquez (1989), “Protectionism and the U.S. Trade Deficit,” CEPR DP. No. 286.
Krugman, P. (1982), “The Macroeconomics of Protection with a Floating Exchange Rate,” Monetary Regimes and Protectionism (Carnegie-Rochester Series on Public Policy Volume 16, K. Brunner and A. Meltzer, eds.), 141–82.
Laursen, S., and L.A. Metzler (1950), “Flexible Exchange Rates and the Theory of Employment,” Review of Economics and Statistics 32, 281–99.
Ostry, J.D. (1988), “intertemporal Optimizing Models of Small and Large Open Economies with Nontradable Goods,” unpublished Ph.D. dissertation.
Stock, J. H., and M. W. Watson (1988), “Variable Trends in Economic Time Series,” Journal of Economic Perspectives, 2–3, 147–74.
Mr. Rose is Professor of Economics, University of California, Berkeley. This paper draws in part on Mr. Ostry’s Ph.D. dissertation submitted to the Department of Economics, University of Chicago. We thank Haydon Merkle and Mattie Halsey of the Foreign Trade Division of the Bureau of the Census, and Jeff Frankel for assistance with the data; Kellett Hannah for computer support; Eduardo Borensztein, Peter Garber, Charles Kindleberger, Cathy Mann, and seminar articipants at the Board of Governors of the Federal Reserve System for comments; and Robert Flood and Doug Purvis for discussions.
Helkie et al. (1988) use simulation techniques on a large macroeconomic model and conclude that protectionist policies are in effective in reducing trade imbalances while avoiding recession.
The exposition that follows is drawn from Dornbusch (1980, pp: 65-66) although a similar analysis may be found in other texts.
We assume in what follows that the government runs a balanced budget.
The presumption of a contractionary effect is strengthened when money is introduced into the model, since the redistributed tariff revenue creates an additional demand for money, requiring a fall in income from production to clear the money market (see Chan (1978), Eichengreen (1981) and Krugman (1982)).
Krugman (1982) argues that, even in those circumstances in which a tariff raises output and improves the terms of trade when other countries are passive, “symmetric retaliation” will result in lower output and unchanged terms of trade.
Standard trade theory shows that the tariff will tend to benefit the factor used intensively in the import-competing sector.
We choose the G-7 countries for intrinsic interest, noting that they account for over half of U.S. imports (both dutiable and duty-free) and tariff revenues during the sample in question. However, the bilateral tariff data exist for other countries, and it would be interesting to extend the results to, e.g., developing countries.
There does not appear to be any fundamental explanation of the apparent outlier in August 1978.
The volatilities of the growth rates of the tariff measures also vary noticeably, both across countries and tariff rate measures.
If there is incomplete specialization, there will be additional effects on domestic production and foreign consumption which may also contribute to substitution bias.
As our empirical work below indicates that the null hypothesis cannot generally be rejected, this bias strengthens our results, so long as standard errors are not substantially biased.
The data indicate that tariff revenues do not seem to be redistributed. In particular, the tariff rate, and, to a much smaller degree, tariff revenues, have positive but small correlations with the federal budget surplus.
This statement is true of all tests of Granger “Causality.”
In all cases, the hypotheses that imports and exports separately, as well as the nominal trade balance, have unit roots cannot be rejected at traditional significance levels.
Using the nominal trade balance in place of the real trade balance does not change results.
There is no reason for the tariff rate to be used as the sole regressand; the “reverse” regression with, e.g., the trade balance as the dependent variable (and the remaining four variables as regressors), can also be used as the cointegrating equation. We have calculated the augmented Dickey-Fuller cointegration tests for all 96 (six countries x two measures of trade balance x two measures of tariff rate x four alternative regressands) reverse regressions. Almost uniformly (in 92 out of 96 cases), they are consistent with the hypothesis that there is no cointegration between the trade balance, the exchange rate, domestic and foreign output, and the tariff rate.
The Johansen tests--which are valid under more general conditions than the standard Dickey-Fuller tests--indicate that there is one and possibly two cointegrating vectors in the five-variable system. This result is robust to various measures of the trade balance and the tariff rate.
The results do not change if the cointegrating residual is dropped.
The only exception occurs when the lag length is reduced to one year and the U.S. measure of trade with Italy is used, in which case (lags of) τ2 are statistically significant.
The relevant data is available for three countries: Canada, Germany, and Japan.
To implement the Beveridge and Nelson methodology, we assumed that (the logs of the) tariff rates follow IMA (1,6) processes, univariate models which appear to fit the data reasonably well.
Use of national accounts data necessitates estimation at the quarterly frequency.
In principle, the hypothesis that U.S.-U.K. trade is similar in composition to aggregate U.S. trade is testable on the basis of existing data. In particular, bilateral data exist at the annual frequency on an historical basis from Foreign Commerce and Navigation of the United States, but only at the commodity level.
All levies collected on goods because they enter the country.
Duties levied under the customs tariff schedule and annexes, but excluding consular fees, tonnage charges, statistical. taxes, fiscal duties, and other taxes.
The countries included are (listed by IFS code): the United Kingdom, Austria, Denmark, the Federal Republic of Germany, Italy, the Netherlands, Norway, Sweden, Switzerland, Canada, Japan, Finland, Greece, Iceland, Ireland, Malta, Portugal, Spain, Australia, New Zealand, Colombia, Costa Rica, the Dominican Republic, Nicaragua, Paraguay, Venezuela, Guyana, Cyprus, Nepal, the Philippines, Burundi, Cameroon, Zaïre, Malawi, Morocco, Uganda, Zambia, and Fiji.