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Comparing Dynamic Specifications: The Case of Presidential Approval

Published online by Cambridge University Press:  04 January 2017

Nathaniel Beck
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Abstract

This article compares a variety of models of presidential approval in terms of their dynamic properties and their theoretical underpinnings. Exponential distributed lags, partial adjustment, error correction, and transfer function models are considered. The major difference between the models lies in interpretation rather than statistical properties. The error correction model seems most satisfactory. Approval models based on individual level theories are examined, and found to give no additional purchase.

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Type
Research Article
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Political Analysis , Volume 3 , 1991, pp. 51 - 87
Copyright
Copyright © by the University of Michigan 1992 

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References

Beck, N. 1985. “Estimating Dynamic Models Is Not Merely a Matter of Technique.” Political Methodology 11: 71–90.Google Scholar
Beck, N. 1988. “Time Aggregation and Dynamic Estimation.” Paper presented at the annual meeting of the Political Methodology Society, UCLA.Google Scholar
Beck, N. 1989. “Estimating Dynamic Models Using Kalman Filtering.” Political Analysis 1: 121–56.Google Scholar
Beck, N. 1991. “The Economy and Presidential Approval: An Information Theoretic Perspective.” In Economics and Politics: the Calculus of Support, ed. Norpoth, H., Lewis-Beck, M., and Lafay, J.-D., 85–101. Ann Arbor: University of Michigan Press.Google Scholar
Box, G., and Jenkins, G. 1976. Time Series Data Analysis, Forecasting, and Control. Rev. ed. San Francisco: Holden Day.Google Scholar
Chappell, H., and Keech, W. 1985. “A New View of Political Accountability for Economic Performance.” American Political Science Review 79: 10–27.Google Scholar
Davidson, J., Hendry, D., Srba, F., and Yeo, S. 1978. “Econometric Modeling of the Aggregate Time-Series Relationship between Consumers’ Expenditures and Income in the United Kingdom.” Economic Journal 88: 661–92.CrossRefGoogle Scholar
Davidson, R., and MacKinnon, J. 1981. “Several Tests for Model Specification in the Presence of Alternative Hypotheses.” Econometrica 49: 781–93.CrossRefGoogle Scholar
Dickey, D., and Fuller, W. 1979. “Distribution of the Estimators for Autoregressive Times Series with Unit Root.” Journal of the American Statistical Association 74: 427–31.Google Scholar
Engle, R., and Granger, C. 1987. “Cointegration and Error Correction: Representation, Estimation, and Testing.” Econometrica 55: 251–76.CrossRefGoogle Scholar
Feldman, S. 1985. “Measuring Economic Self-Interest and the Vote: Evidence and Meaning.” In Economic Conditions and Electoral Outcomes: The United States and Western Europe, ed. Eulau, H. and Lewis-Beck, M., 141–66. New York: Agathon.Google Scholar
Freeman, J. 1989. “Systematic Sampling, Temporal Aggregation, and the Study of Political Relationships.” Political Analysis 1: 61–98.CrossRefGoogle Scholar
Freeman, J., Williams, J., and Lin, T. M. 1989. “Vector Autoregression and the Study of Politics.” American Journal of Political Science 33: 842–77.Google Scholar
Granger, C. 1990. “Aggregation of Time-Series Variables: A Survey.” In Disaggregation in Econometric Modeling, ed. Parker, T. and Pesaran, H., 17–34. London: Routledge.Google Scholar
Granger, C., and Morris, M. 1976. ‘Time-Series Modeling and Interpretation.” Journal of the Royal Statistical Society, ser. A 139: 246–57.Google Scholar
Granger, C., and Newbold, P. 1986. Forecasting Economic Time-Series. 2d ed. Orlando: Academic Press.Google Scholar
Harvey, A. 1990. The Econometric Analysis of Time-Series. 2d ed. Cambridge, Mass.: MIT Press.Google Scholar
Hendry, D., Pagan, A., and Sargan, J. 1984. “Dynamic Specification.” In Handbook of Econometrics, ed. Griliches, Z. and Intriligator, M., 2:1023–1100. Amsterdam: North-Holland.CrossRefGoogle Scholar
Hibbs, D. 1974. “Problems of Statistical Estimation and Causal Inference in Time-Series Regression Models.” In Sociological Methodology 1973-1974, ed. Costner, H., 252–308. San Francisco: Jossey-Bass.Google Scholar
Hibbs, D. 1987. The American Political Economy: Macroeconomics and Electoral Politics in the United States. Cambridge, Mass.: Harvard University Press.Google Scholar
Judge, G., Griffiths, W., Hill, R., Lutkepohl, H., and Lee, T.-C. 1985. The Theory and Practice of Econometrics. 2d ed. New York: Wiley.Google Scholar
Kernell, S. 1978. “Explaining Presidential Popularity.” American Political Science Review 72: 506–22.Google Scholar
Kernell, S. 1986. Going Public. Washington, D.C.: CQ Press.Google Scholar
King, G. 1988. Unifying Political Methodology: The Likelihood Theory of Inference. New York: Cambridge University Press.Google Scholar
King, G., and Ragsdale, L. 1988. The Elusive Executive. Washington, D.C.: CQ Press.Google Scholar
Koyck, L. 1954. Distributed Lags and Investment Analysis. Amsterdam: North-Holland.Google Scholar
Learner, E. 1978. Specification Searches: Ad Hoc Inference with Nonexperimental Data. New York: Wiley.Google Scholar
MacKinnon, J. 1991. “Critical Values for Cointegration Tests.” In Long-run Economic Relationships: Readings in Cointegration, ed. Engle, R. and Granger, C., 267–76. New York: Oxford University Press.Google Scholar
MacKuen, Μ. 1983. “Political Drama, Economic Conditions, and the Dynamics of Presidential Popularity.” American Journal of Political Science 28: 164–92.Google Scholar
MacKuen, M., Erickson, R., and Stimson, J. 1989. “Macropartisanship.” American Political Science Review 83: 1125–42.Google Scholar
Mueller, J. 1970. “Presidential Popularity from Truman to Johnson.” American Political Science Review 64: 18–34.Google Scholar
Norpoth, H. 1986. “Transfer Function Analysis.” In New Tools for Social Scientists: Advances and Applications in Research Methods, ed. Berry, W. and Lewis-Beck, M., 241–73. Beverly Hills, Calif.: Sage.Google Scholar
Norpoth, H. 1991. “The Popularity of the Thatcher Government: A Matter of War and Economy.” In Economics and Politics: The Calculus of Support, ed. Norpoth, H., Lewis-Beck, M., and Lafay, J.-D., 141–60. Ann Arbor University of Michigan Press.Google Scholar
Ostrom, C., and Smith, R. 1990. “Cointegration and Error Correction: Examining the Presidential Approval-Economy Connection.” Paper presented at the annual meeting of the Political Methodology Society, Washington University, St. Louis.Google Scholar
Sargan, D. 1980. “Some Tests of Dynamic Specification for a Single Equation.” Econometrica 48: 879–97.Google Scholar
Stock, J., and Watson, M. 1988. “Variable Trends in Economic Time-Series.” Journal of Economic Perspectives 2 (3): 147–74.Google Scholar
Whitely, P. 1984. “Inflation, Unemployment, and Government Popularity—Dynamic Models for the United States, Britain, and West Germany.” Electoral Studies 3: 3–24.CrossRefGoogle Scholar