The HUMP-shaped behavior of macroeconomic fluctuations
Tóm tắt
We analyze the nature of persistence in macroeconomic fluctuations. The current view is that shocks to macroeconomic variables (in particular realGNP) have effects that endure over an indefinite horizon. This conclusion is drawn from the presence of a unit root in the univariate time series representation. Following Perron (1989), we challenge this assessment arguing that most macroeconomic variables are better construed as stationary fluctuations around a breaking trend function. The trend function is linear in time except for a sudden change in its intercept in 1929 (The Great Crash) and a change in slope after 1973 (following the oil price shock). Using a measure of persistence suggested by Cochrane (1988) we find that shocks have small permanent effects, if any. To analyze the effects of shocks at finite horizon, we select a member of theARMA(p, q) class applied to the appropriately detrended series. For the majority of the variables analyzed the implied weights of the moving-average representation have the once familiar humped shape.
Tài liệu tham khảo
Andrews DWK (1991) Heteroskedasticity and autocorrelation consistent covariance matrix estimation. Econometrica 59:817–858
Akaike H (1974) A new look at statistical model identification. IEEE Transactions on Automatic Control AC 19:716–23
Akaike H (1976) Canonical correlation analysis in time series and the use of an information criterion. In: System identification: Advances and case studies Mehra RK, Lainiotis DG (eds) New York: Academic Press 52–107
Balke NS, Gordon RJ (1986) Historical data appendix. In: The American business cycle: Continuity and change, Gordon RJ (ed) Chicago: The University of Chicago Press 781–850
Blanchard OJ (1981) What is left of the multiplier accelerator?. American Economic Review, Papers and Proceedings 71:150–154
Blanchard OJ, Quah D (1989) The dynamic effects of aggregate demand and supply disturbances. American Economic Review 79:655–673
Blinder AS (1981) Retail inventory behavior and business fluctuations. Brookings Paper on Economic Activity 2:443–505
Blinder AS (1986) Can the production smoothing model of inventory behavior be saved?. Quarterly Journal of Economics 101:431–453
Blinder AS, Holtz-Eakin D (1986) Inventory fluctuations in the United States since 1929. In: The American Business Cycle: Continuity and Change, Gordon RJ (ed) Chicago: The University of Chicago Press 183–236
Box GEP, Jenkins GM (1970) Time series analysis: Forecasting and Control, Holden Day, San Francisco
Box GEP, Tiao GC (1975) Intervention analysis with applications to economic and environmental problems. Journal of the American Statistical Association 70:70–79
Campbell JY, Mankiw NG (1987a) Are output fluctuations transitory?. Quarterly Journal of Economics 102:857–880
Campbell JY, Mankiw NG (1987b) Permanent and transitory components in macroeconomic fluctuations. American Economic Review, Papers and Proceedings 77:111–117
Campbell JY, Mankiw NG (1989) International evidence on the persistence of economic fluctuations. Journal of Monetary Economics 23:319–333
Cecchetti SG, Lam P-S (1991) What do we learn from variance ratio statistics? A study of stationary and nonstationary models with breaking trends. Mimeo
Clark PK (1987) The cyclical component of US economic activity. Quarterly Journal of Economics 102:798–814
Cochrane JH (1988) How big is the random walk inGNP. Journal of Political Economy 96:893–920
Dickey DA, Fuller WA (1979) Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association 74:427–431
Evans GW (1989) Output and unemployment dynamics in the United States: 1950–1985. Journal of Applied Econometrics 4:213–238
Friedman M, Schwartz AJ (1982) Monetary trends in the United States and the United Kingdom: Their relation to income, prices and interest rates 1867–1975 Chicago: University of Chicago Press
Nelson CR, Plosser CI (1982) Trends and random walks in macroeconomic time series. Journal of Monetary Economics 10:139–162
Perron P (1989) The great crash, the oil price shock and the unit root hypothesis. Econometrica 57:1361–1401
Perron P (1990) Testing for a unit root in a time series with a changing mean. Journal of Business and Economic Statistics 8:153–162
Perron P (1991) Further evidence of breaking trend functions in macroeconomic variables. Mimeo, Princeton University
Perron P, Ng S (1992) The exact error in estimating the spectral density at the origin. Mimeo, Princeton University
Perron P, Phillips PCB (1987) DoesGNP have a unit root? A reevaluation. Economics Letters 23:139–145
Phillips PCB, Ouliaris S (1988) Testing for cointegration using principal components methods. Journal of Economic Dynamics and Control 12:205–230
Priestly MB (1981) Spectral analysis and time series. Academic Press: New York
Raj B (1992) International evidence on persistence in output in the presence of an episodic change. Journal of Applied Econometrics 7:281–293
Raj B (1993) The size of the random walk in macroeconomic time series. Journal of Macroeconomics 15:139–151
Schwartz G (1978) Estimating the dimension of a model. Annals of Statistics 6:461–464
Stock JH, Watson MW (1986) DoesGNP have a unit root?. Economics Letters 22:147–151
Watson MW (1986) Univariate detrending methods with stochastic trends. Journal of Monetary Economics 18:1–27
Zivot E, Andrews DWK (1992) Further evidence on the great crash, the oil price shock and the unit root hypothesis. Journal of Business and Economic Statistics 10:251–270