Burns, A.F. and W.C. Mitchell, Measuring Business Cycles, New York: Columbia University Press (for National Bureau of Economic Research) (1946).
Camen, Ulrich, “Concepts and Measurement of World Business Cycles,” Discussion Paper Graduate Institute of International Studies, Geneva (1987).
Frisch, Ragnar, “Propagation Problems and Impulse Problems in Dynamic Economics.” In Economic Essays in Honor of Gustav Cassel, London: Allen and Unwin (1933).
Long, J.B., Jr. and C.I. Plosser, “Sectoral vs. Aggregate Shocks in the Business Cycle,” American Economic Review, 70 (March 1987), pp. 333–336.
Muhlenfels, A. von, International Konjunkturzusammenhange, Jahrbuch fur Nationaleokonomie and Statistik, 130 (1929), pp. 801–828.
McKinnon, R.I., Currency Substitution and Instability in the World Dollar Market, American Economic Review, 72 (June 1982), pp. 320–333.
Nelson, C.R. and C.I. Plosser, “Trends and Random Walks in Macroeconomic Time Series: Some Evidence and Implications,” Journal of Monetary Economics, 10 (September 1982), pp. 139–162.
Norrbin, S.C. and D.E. Schlagenhauf, “An Inquiry into the Sources of Macroeconomic Fluctuations,” Journal of Monetary Economics, 22 (July 1988), pp. 44–70.
Norrbin, S.C. and D.E. Schlagenhauf, “Sources of Output Fluctuations in the United States During the Inter-War and Post-War Years, Journal of Economic Dynamics and Control, forthcoming (1990).
Prescott, E.C., “Theory Ahead of Business Cycle Measurement,” Real Business Cycles. Real Exchange Rates and Actual Policies, eds., K. Brunner and A.H. Meltzer. Carnegie-Rochester Conference Series on Public Policy, 25 (Autumn 1986), pp. 11–44.
Sargent, Thomas J. and Christopher A. Sims, “Business Cycle Modeling Without Pretending to Have Too Much a Priority Economic Theory,” in New Methods in Business Cycle Research, Minneapolis: Federal Reserve Bank of Minneapolis (1980).
Schumpeter, Joseph, Business Cycles: A Theoretical. Historical and Statistical Analysis of the Capital Process (New York: McGraw-Hill, 1939).
Stockman, A.C., “Sectoral and National Aggregate Disturbances To Industrial output in Seven European Countries.” Journal Monetary Economics, 21 (March/May 1988), pp. 387–409.
Swoboda, A., “Exchange Rate Regimes and U.S. - European Policy Interdependence,” Staff Papers, International Monetary Fund (Washington), Vol. 30 (1983), pp. 75–102.
Watson, M.W. and R.F. Engle, “Alternative Algorithms for Estimation of Dynamic MIMIC, Factor, and Time Varying Coefficient Regression Models,” Journal of Econometrics23 (March 1983), p.p. 285–400.
Zarnowitz, V., “Recent Work on Business Cycles in Historical Perspective: A Review of Theories and Evidence,” Journal of Economic Literature 23 (June 1985), pp. 523–580.
This paper was written while the latter author was a visiting scholar in the Research Department, International Monetary Fund.
Haberler (1937) summarizes many of the business cycle theories in the pre-Keynesian period. Zarnowitz (1985) presents a more current review of the theories and evidence on business cycles.
The DYMIMIC model is a type of index model. Sargent and Sims (1980) have used an index model to study business cycles. They employ a frequency domain method with unrestricted lag distributions. The Watson and Engle estimation approach is a time domain method.
We attempt to avoid local optimization results by examining various starting values and employing a very severe convergence criteria, (i.e., .000001).
In the application of the state space model employed in this paper, the only exogenous variable in Z1t is a constant term as each of the composite variable can be mapped into lagged Yt. Hence, the Z1t variable could be deleted in the following discussion. We leave this variable in the discussion so that general discussion on how to calculate the moving average representation of a state space model is available.
It is a straightforward extension to allow for multivariate forecasting equations.
The univariate forecasting equations were estimated with a constant.
McCallum (1988) notes that Solow’s method assumes that current capital and labor are the only relevant inputs. If adjustment costs exist, then labor and/or capital hoarding might cause the estimated Solow residuals to overstate the technological shock variance.
It would be preferable to estimate the model over each exchange rate regime to see if the results are robust across regimes. The results from such an exercise would be questionable given the number of parameters to be estimated and the length of the data samples at this time.
Both this paper and Stockman’s paper imposes the restriction that an industry specific technological shock influences that specific industry in all countries at the same time. This restriction may be a partial explanation for the large idiosyncratic error term. In addition, in Norrbin and Schlagenhauf (1988) we employ a similar framework where the disaggregation is across regions and industries. The importance of industry-specific shocks are more important.