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Testing for Cointegrating Relationships with Near-Integrated Data

Published online by Cambridge University Press:  04 January 2017

Suzanna de Boef  and
Jim Granato
Suzanna de Boef
Affiliation:
Pennsylvania State University and Harvard University
Jim Granato
Affiliation:
Michigan State University
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Abstract

Testing theories about political change requires analysts to make assumptions about the memory of their time series. Applied analyses are often based on inferences that time series are integrated and cointegrated. Typically analyses rest on Dickey—Fuller pretests for unit roots and a test for cointegration based on the Engle—Granger two-step method. We argue that this approach is not a good one and use Monte Carlo analysis to show that these tests can lead analysts to conclude falsely that the data are cointegrated (or nearly cointegrated) when the data are near-integrated and not cointegrating. Further, analysts are likely to conclude falsely that the relationship is not cointegrated when it is. We show how inferences are highly sensitive to sample size and the signal-to-noise ratio in the data. We suggest three things. First, analysts should use the single equation error correction test for cointegrating relationships; second, caution is in order in all cases where near-integration is a reasonable alternative to unit roots; and third, analysts should drop the language of cointegration in many cases and adopt single-equation error correction models when the theory of error correction is relevant.

Type
Research Article
Information
Political Analysis , Volume 8 , Issue 1 , 1999 , pp. 99 - 117
Copyright
Copyright © 1999 by the Society for Political Methodology 

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References

Banerjee, Anindya, Dolado, Juan, Hendry, David F., and Smith, Gregor W. 1986. “Exploring Equilibrium Relationships in Econometrics Through Static Models: Some Monte Carlo Evidence.” Oxford Bulletin of Economics and Statistics 48: 253–277.Google Scholar
Banerjee, Anindya, Dolado, Juan, Galbraith, John, and Hendry, David F. 1993. Cointegration, Error Correction, and the Econometric Analysis of Non-Stationary Data. Oxford: Oxford University Press.Google Scholar
Beck, Nathaniel. 1992. “The Methodology of Cointegration.” Political Analysis 4: 237–248.CrossRefGoogle Scholar
Blough, Stephen R. 1992. “The Relationship Between Power and Level for Generic Unit Root Tests in Finite Samples.” Journal of Applied Econometrics 7: 295–308.Google Scholar
Box-Steffensmeier, Janet M., and Smith, Renee M. 1996. “The Dynamics of Aggregate Partisanship.” American Political Science Review 90: 567–580.Google Scholar
Box-Steffensmeier, Janet M., and Smith, Renee M. 1998. “Investigating Political Dynamics Using Fractional Integration Methods.” American Journal of Political Science 42: 661–689.Google Scholar
Clarke, Harold D., and Stewart, Marianne C. 1994. “Prospections, Retrospections, and Rationality: The ‘Bankers’ Model of Presidential Approval Reconsidered.” American Journal of Political Science 38: 1104–1123.Google Scholar
Clarke, Harold D., and Stewart, Marianne C. 1995. “Economic Evaluations, Prime Ministerial Approval and Governing Party Support: Rival Models Reconsidered.” British Journal of Political Science 25: 145–170.Google Scholar
Clarke, Harold D., and Stewart, Marianne C. 1996. “Economists and Electorates: The Subjective Economy of Governing Party Support in Canada.” European Journal of Political Research 29: 191–214.Google Scholar
Clarke, Harold D., Stewart, Marianne C., and Whitely, Paul. 1997. “Tory Trends: Party Identification and the Dynamics of Conservative Support Since 1992.” British Journal of Political Science 27: 299–319.Google Scholar
Davidson, J. E. H., Hendry, David F., Srba, F., and Yeo, S. 1978. “Econometric Modeling of the Aggregate Time-Series Relationship Between Consumers’ Expenditure and Income in the United Kingdom.” Economic Journal 88: 661–692.Google Scholar
De Boef, Suzanna. 1999. “Modeling Near-Integrated Data,” Working paper. Cambridge, MA: Harvard University.Google Scholar
De Boef, Suzanna, and Granato, Jim. 1997. “Near-Integrated Data and the Analysis of Political Relationships.” American Journal of Political Science 41: 619–640.Google Scholar
De Boef, Suzanna, and Granato, Jim. 1999. “Testing for Cointegrating Relationships when Data are Near-Integrated.” Political Institutions and Public Choice (PIPC) Working Paper No. 98-08. East Lansing: Michigan State University.Google Scholar
Dickey, David, and Fuller, Wayne. 1979. “Distribution of the Estimators for Autoregressive Time Series with a Unit Root.” Journal of the American Statistical Association 84: 427–431.Google Scholar
Durr, Robert H. 1993. “What Moves Policy Sentiment?” American Political Science Review 87: 158–170.Google Scholar
Elliott, Graham, and Stock, James. 1992. “Inference in Time Series Regression when the Order of Integration of a Regressor is Unknown.” National Bureau of Economic Research Technical Working Paper No. 122.Google Scholar
Engle, Robert F., and Granger, C. W. J. 1987. “Cointegration and Error Correction: Representation, Estimation and Testing.” Econometrica 55: 251–276.CrossRefGoogle Scholar
Engle, Robert F., and Yoo, B. S. 1991. Cointegrated Economic Time Series: An Overview with New Results. New York: Oxford University Press, pp. 237–266.Google Scholar
Engle, Robert F., Hendry, David, and Richard, Jean-Francois. 1983. “Exogeneity.” Econometrica 51: 277–304.Google Scholar
Evans, G. B. A., and Savin, N. E. 1981. “Testing for Unit Roots: 1.” Econometrica 49(3): 753–779.Google Scholar
Evans, G. B. A., and Savin, N. E. 1984. “Testing for Unit Roots: 2.” Econometrica 52(5): 1241–1269.Google Scholar
Granato, Jim, and West, William F. 1994. “Words and Deeds: Symbolic Politics and Decision Making at the Federal Reserve.” Economics and Politics 6(3): 231–253.Google Scholar
Granger, C. W. J., and Swanson, Norman R. 1996. “Further Developments in the Study of Cointegrated Variables.” Oxford Bulletin of Economics and Statistics 58: 537–553.Google Scholar
Green, Donald Philip, Palmquist, Bradley, and Schickler, Eric. 1998. “Macropartisanship: A Replication and Critique.” American Political Science Review 92(4): 883–899.Google Scholar
Hamilton, James D. 1994. Time Series Analysis. Princeton, NJ: Princeton University Press.Google Scholar
Hansen, Bruce. 1995. “Rethinking the Univariate Approach to Unit Root Testing.” Econometric Theory 11: 1148–1171.Google Scholar
Hendry, David. 1995. Dynamic Econometrics. New York: Oxford University Press.Google Scholar
Hendry, David, and Mizon, Grayham E. 1978. “Serial Correlation as a Convenient Simplification, Not a Nuisance: A Comment on the Study of the Demand for Money by the Bank of England.” Economic Journal 88: 549–563.Google Scholar
Hendry, David, Neale, Adrian, and Ericsson, Neil. 1990. “PC-NAIVE: An Interactive Program for Monte Carlo Experimentation in Econometrics,” Version 6.01.Google Scholar
Johansen, Soren. 1988. “Statistical Analysis of Cointegration Vectors.” Journal of Economic Dynamics and Control 12: 231–254.CrossRefGoogle Scholar
Krause, George A. 1998. “Rivalry, Reciprocity, and the Dynamics of Presidential-Congressional Institution Building.” Paper presented at the 1998 annual meeting of the American Political Science Association, Boston. Kremers, Jeroen, Neil Ericsson, and Juan Dolado. 1992. “The Power of Cointegration Tests.” Oxford Bulletin of Economics and Statistics 54: 325–348.Google Scholar
MacKinnon, James. 1990. Critical Values for Cointegration Tests. New York: Oxford University Press.Google Scholar
Ostrom, Charles, and Smith, Renee. 1992. “Error Correction, Attitude Persistence, and Executive Rewards and Punishments: A Behavioral Theory of Presidential Approval.” Political Analysis 4: 127–183.Google Scholar
Phillips, P C. B. 1987. “Towards a Unified Asymptotic Theory of Autoregression.” Biometrika 74: 535–548.CrossRefGoogle Scholar
Phillips, P C. B. 1988. “Regression Theory for Near-Integrated Time Series.” Econometrica 6: 1021–1043.Google Scholar
Rajmaira, Sheen, and Ward, Michael D. 1990. “Evolving Foreign Policy Norms: Reciprocity in the Superpower Triad.” International Studies Quarterly 34: 457–475.Google Scholar
Smith, Renee M. 1992. “Error Correction, Attractors, and Cointegration: Substantive and Methodological Issues.” Political Analysis 4: 249–254.Google Scholar
Stock, James. 1994. “Deciding Between I(1) and I(0).” Journal of Econometrics 63: 105–131.Google Scholar
Williams, John T. 1992. “What Goes Around Comes Around: Unit Root Tests and Cointegration.” Political Analysis 4: 229–235.CrossRefGoogle Scholar
Wlezien, Christopher. 1996. “Dynamics of Representation: The Case of U.S. Spending on Defense.” British Journal of Political Science 26: 81–103.Google Scholar