Modelling comovements of economic time series: a selective survey
DOI:
https://doi.org/10.6092/issn.1973-2201/3625Abstract
Modelling comovements amongst multiple economic variables takes up a relevant part of the literature in time series econometrics. Comovement can be defined as “move together”, that is as movement that several series have in common. The pattern of the series could be of different nature, such as trend, cycles, seasonality, being the results of different driving forces. As a results, series that comove share some common features. Common trends, common cycles, common seasonality are terms that are often found in the literature, different in scope but all aimed at modeling common behavior of the series. However, modeling comovements is not only a statistical matter, since in many cases common features are predicted by economic theory, resulting from the optimizing behavior of economic agents.References
AHN S, REINSEL G. 1988. Nested reduced-rank autoregressive models for multiple timeseries. Journal of the American Statistical Association 83: 849-856.
AHN SK, REINSEL GC. 1994. Estimation of partially nonstationary vector autoregressive models with seasonal behavior. Journal of Econometrics 62: 317-350.
ANDERSON HM, VAHID F. 1998. Testing multiple equation systems for common nonlinear components. Journal of Econometrics 84: 1-36.
ANDERSON T. 1984. An Introduction to Multivariate Statistical Analysis. Wiley, second edition. New York.
ANDERSON T. 1999. Asymptotic theory for canonical correlation analysis. Journal of Multivariate Analysis 70: 1-29.
ANDERSON T. 2002. Canonical correlation analysis and reduced rank regression in autoregressive models. Annals of Statistics 30: 1134-1154.
BAXTER M, KOUPARITSAS MA. 2005. Determinants of business cycle comovement: A robust analysis. Journal of Monetary Economics 52: 113-157.
BEVERIDGE S, NELSON C. 1981. A new apporach to decomposition of economic time series into permanent and transitory component with particular attention to measurement of the ‘business cycle’. Journal of Monetary Economics 7: 151-174.
BIERENS H. 2000. Nonparametric nonlinear cotrending analysis, with an application to interest and inflation in the United States. Journal of Business & Economic Statistics 18: 323-337.
CAMPBELL J. 1987. Does saving anticipate declining labor income? An alternative test of the permanent income hypothesis. Econometrica 55: 1249-1273.
CAMPBELL JY, MANKIW NG. 1990. Permanent income, current income, and consumption. Journal of Business & Economic Statistics 8: 265-279.
CHAPMAN DA, OGAKI M. 1993. Cotrending and the stationarity of the real interest rate. Economics Letters 42: 133-138.
CHRISTIANO LJ, EICHENBAUM M, EVANS CL. 2005. Nominal rigidities and the dynamic effects of a shock to monetary policy. Journal of Political Economy 113: 1-45.
CROUX C, FORNI M, REICHLIN L. 2001. A measure of comovement for economic variables: Theory and empirics. Review of Economics and Statistics 83: 232-241.
CUBADDA G. 1999. Common cycles in seasonal non-stationary time series. Journal of Applied Econometrics 14: 273-291.
CUBADDA G. 2001. Complex reduced rank models for seasonally cointegrated time series. Oxford Bulletin of Economics and Statistics 63: 497-511.
CUBADDA G. 2007. A unifying framework for analysing common cyclical features in cointegrated time series. Computational Statistics & Data Analysis 52: 896-906.
CUBADDA G, HECQ A. 2001. On non-contemporaneous short-run co-movements. Economics Letters 73: 389-397.
CUBADDA G, HECQ A. 2011. Testing for common autocorrelation in data-rich environments. Journal of Forecasting 30: 325-335.
CUBADDA G, HECQ A, PALM FC. 2008. Macro-panels and reality. Economics Letters 99: 537-540.
CUBADDA G, HECQ A, PALM FC. 2009. Studying co-movements in large multivariate data prior to multivariate modelling. Journal of Econometrics 148: 25-35.
CUBADDA G, OMTZIGT P. 2005. Small-sample improvements in the statistical analysis of seasonally cointegrated systems. Computational Statistics and Data Analysis 49: 333-348.
ENGLE RF, GRANGER CW. 1987. Cointegration and error correction: Representation, estimation and testing. Econometrica 55: 251-276.
ENGLE RF, HYLLEBERG S. 1996. Common seasonal features: Global unemployment. Oxford Bulletin of Economics and Statistics 58: 615-630.
ENGLE RF, ISSLER JV. 1995. Estimating common sectoral cycles. Journal of Monetary Economics 35: 83-113.
ENGLE RF, KOZICKI S. 1993. Testing for common features. Journal of Business & Economic Statistics 11: 369-380.
ENGLE RF, MARCUCCI J. 2006. A long-run pure variance common features model for the common volatilities of the Dow Jones. Journal of Econometrics 132: 7-42.
ENGLE RF, SUSMEL R. 1993. Common volatility in international equity markets. Journal of Business & Economic Statistics 11: 167-176.
ERICSSON NR. 1993. [Testing for common features]: Comment. Journal of Business & Economic Statistics 11: 380-383.
FLAVIN M. 1993. The excess smoothness of consumption: Identification and interpretation. Review of Economic Studies 60: 651-666.
FORBES K, RIGOBON R. 2002. No contagion, only interdependence: Measuring stock market comovements. Journal of Finance 57: 2223-2261.
GONZALO J, GRANGER CW. 1995. Estimation of common long-memory components in cointegrated systems. Journal of Business & Economic Statistics 13: 27-35.
GOURIEROUX C, PEAUCELLE I. 1988. Detecting a long run relationship (with an application to the P.P.P. hypothesis). Working Paper 8902, CEPREMAP.
GRANGER CW. 1981. Some properties of time series data and their use in econometric model specification. Journal of Econometrics 16: 121-130.
HALDRUP N, HYLLEBERG S, PONS G, SANSO A. 2007. Common periodic correlation features and the interaction of stocks and flows in daily airport data. Journal of Business & Economic Statistics 25: 21-32.
HALL RE. 1978. Stochastic implications of the life cycle-permanent income hypothesis: Theory and evidence. The Journal of Political Economy 86: 971-987.
HARDING D, PAGAN A. 2006. Synchronization of cycles. Journal of Econometrics 132: 59-79.
HECQ A, PALM F, URBAIN J. 2000. Testing for common cyclical features in nonstationary panel data models. In Advances Econometrics, VOL 15, 2000, Volume 15 of Advances in Econometrics: a Research Annual. JAI-Elsevier Science Inc, 131-160.
HECQ A, PALM F, URBAIN J. 2006. Common cyclical features analysis in VAR models with cointegration. Journal of Econometrics 132: 117-141.
HENDRY DF. 1996. A theory of co-breaking. mimeo, Nuffiled College, University of Oxford.
HYLLEBERG S, ENGLE R, GRANGER C, YOO B. 1990. Seasonal integration and cointegration. Journal of Econometrics 44: 215-238.
HYLLEBERG S, JØRGENSEN C, SØRENSEN NK. 1993. Seasonality in macroeconomic time series. Empirical Economics 18: 321-335.
IMBS J. 2004. Trade, finance, specialization, and synchronization. Review of Economics and Statistics 86: 723-734.
ISSLER JV, VAHID F. 2001. Common cycles and the importance of transitory shocks to macroeconomic aggregates. Journal of Monetary Economics 47: 449-475.
JOHANSEN S. 1988. Statistical analysis of cointegrating vectors. Journal of Economic Dynamics and Control 12: 231-254.
JOHANSEN S. 1991. Estimation and hypothesis testing of cointegrating vectors in Gaussian vector autoregressive models. Econometrica 59: 1551-1580.
JOHANSEN S. 1996. Likelihood-based Inference in Cointegrated Vector Autoregressive Models. Oxford University Press, second edition.
JOHANSEN S, SCHAUMBURG E. 1998. Likelihood analysis of seasonal cointegration. Journal of Econometrics 88: 301-339.
JUSELIUS K. 2006. The Cointegrated VAR Model. Oxford University Press.
JUSTINIANO A, PRIMICERI GE, TAMBALOTTI A. 2010. Investment shocks and business cycles. Journal of Monetary Economics 57: 132-145.
KHAN H, TSOUKALAS J. 2011. Investment shocks and the comovement problem. Journal of Economic Dynamics and Control 35: 115-130.
KING R, PLOSSER C, REBELO S. 1988. Production, growth and business cycles. 2. New directions. Journal of Monetary Economics 21: 309-341.
KING RG, PLOSSER CI, STOCK JH, WATSON MW. 1991. Stochastic trends and economic fluctuations. The American Economic Review 81: 819-840.
LEE H. 1992. Maximum likelihood inference on cointegration and seasonal cointegration. Journal of Econometrics 54: 1-47.
LONG JB, PLOSSER CI. 1983. Real business cycles. The Journal of Political Economy 91: 39-69.
LUCAS R. 1977. Understanding business cycles. Carnegie-Rochester Conference Series on Public Policy 5: 7-29.
LUCKE B. 1994. Analysis of West Germany macroeconomic data using common trends and common cycles. Discussion Paper 3, Free University of Berlin.
PARUOLO P. 2006. Common trends and cycles in I(2) VAR systems. Journal of Econometrics 132: 143-168.
PHILLIPS PC. 1994. Some exact distribution-theory for maximum-likelihood estimators of cointegrating coefficients in error-correction models. Econometrica 62: 73-93.
ROSIPAL R, KRAEMER N. 2006. Overview and recent advances in partial least squares. In Saunders G, Grobelnik M, Gunn S, ShaweTaylor J (eds.) Subspace, Latent Structure and Feature Selection, volume 3940 of Lecture Notes in Computer Science. Springer-Verlag Berlin, 34-51.
SCHLEICHER C. 2007. Codependence in cointegrated autoregressive models. Journal of Applied Econometrics 22: 137-159.
STOCK JH, WATSON MW. 1988. Testing for common trends. Journal of the American Statistical Association 83: 1097-1107.
TIAO GC, TSAY RS. 1989. Model specification in multivariate time series. Journal of the Royal Statistical Society. Series B (Methodological) 51: 157-213.
URGA G. 2007. Common features in economics and finance: An overview of recent developments. Journal of Business & Economic Statistics 25: 2-11.
VAHID F, ENGLE RF. 1993. Common trends and common cycles. Journal of Applied Econometrics 8: 341-360.
VAHID F, ENGLE RF. 1997. Codependent cycles. Journal of Econometrics 80: 199-221.
VAHID F, ISSLER JV. 2002. The importance of common cyclical features in VAR analysis: a Monte-Carlo study. Journal of Econometrics 109: 341-363.
VELU R, REINSEL G, WICHERN D. 1986. Reduced rank models for multiple time series. Biometrika 73: 105-118.
WOLD H. 1985. Partial least squares. In Kotz S, Johnson NL (eds.) Encyclopedia of Statistical Sciences, volume 6. New York: Wiley, 581-591.
ZELLNER A, PALM F. 1974. Time series analysis and simultaneous equation econometric models. Journal of Econometrics 2: 17-54.
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