Hostname: page-component-586b7cd67f-gb8f7 Total loading time: 0 Render date: 2024-12-04T09:21:40.478Z Has data issue: false hasContentIssue false
  • English
  • Français

What To Do About Atheoretic Lags*

Published online by Cambridge University Press:  26 August 2015

Skyler J. Cranmer ,
Douglas R. Rice  and
Randolph M. Siverson
Get access Rights & Permissions [Opens in a new window]

Abstract

We examine a problem that is confronted frequently by political science researchers seeking to model longitudinal data: what to do when one suspects a lag between the realization of a regressor and its effect on the outcome variable, but one has no theoretical reason to suspect a particular lag length. We examine the theoretical challenges posed by atheoretic lags, review existing methods for atheoretic lag analysis—most notably distributed lag specifications—and their shortcomings, and present an alternative approach for atheoretic lag analysis based on Bayesian model averaging (BMA). We demonstrate the use and utility of our approach with two examples: the litigant signal model in American politics and modernization theory in political economy. Our examples show the increasing difficulty of analyzing models with atheoretic lags as the set of possible specifications increases, and demonstrate the effectiveness of BMA for the modal type of specification in time-series cross-sectional applications.

Type
Original Articles
Information
Political Science Research and Methods , Volume 5 , Issue 4 , October 2017 , pp. 641 - 665
Copyright
© The European Political Science Association 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

*

Skyler Cranmer, Carter Phillips and Sue Henry Associate Professor, Department of Political Science, The Ohio State University, 154 North Oval Mall, Derby Hall 2032, Columbus, OH 43210 ([email protected]). Douglas Rice, Assistant Professor, Department of Political Science, University of Mississippi, P.O. Box 1848, 228 Deupree Hall University, MS 38677-1848 ([email protected]). Randolph Siverson, Distinguished Professor Emeritus, Department of Political Science, University of California, Davis 578 Kerr Hall, One Shields Ave. Davis, CA 95616 ([email protected]). Thanks are due to Janet Box-Steffensmeier, James Fowler, Jeff Gill, Domonik Hangartner, Gary King, Lee Walker, and Chris Zorn for their helpful comments. SJC gratefully acknowledges the support of the National Science Foundation (SES-1461493 and SES-1357622) and the Alexander von Humboldt Foundation.

References

Akaike, Hirotugu. 1974. ‘A New Look at the Statistical Model Identification’. IEEE Transactions on Automatic Control 19(6):716–723.Google Scholar
Almon, Shirley. 1965. ‘The Distributed Lag Between Capital Appropriations and Expenditures’. Econometrica 33(1):178–196.Google Scholar
Amemiya, Takeshi, and Fuller, Wayne. 1967. ‘A Comparative Study of Alternative Estimators in a Distributed Lag Model’. Econometrica 35(3/4):509–529.CrossRefGoogle Scholar
Baird, Vanessa. 2004. ‘The Effect of Politically Salient Decisions on the U.S. Supreme Court’s Agenda’. The Journal of Politics 66(3):755–772.Google Scholar
Baird, Vanessa. 2007. Answering the Call of the Court: How Justices and Litigants Set the Supreme Court Agenda. Charlottesville, VA: University of Virginia Press.Google Scholar
Baird, Vanessa, and Jacobi, Tonja. 2009. ‘Judicial Agenda-Setting Through Signaling and Strategic Litigant Responses’. Washington University Journal of Law and Policy 29:215–239.Google Scholar
Barnard, George A. 1963. ‘New Methods of Quality Control’. Journal of the Royal Statistical Society, Series A 126(2):255–258.CrossRefGoogle Scholar
Bartels, Larry M. 1997. ‘Specification Uncertainty and Model Averaging’. American Journal of Political Science 41(2):641–674.CrossRefGoogle Scholar
Bartels, Larry M., and Zaller, John. 2001. ‘Presidential Vote Models: A Recount’. PS: Political Science and Politics 34(1):8–20.Google Scholar
Beck, Nathaniel. 1985. ‘Estimating Dynamic Models is Not Merely a Matter of Technique’. Political Methodology 11:71–89.Google Scholar
Beck, Nathaniel. 1991. ‘Comparing Dynamic Specification: The Case of Presidential Approval’. Political Analysis 3:27–50.Google Scholar
Beck, Neal, and Katz, Jonathan N.. 1996. ‘Nuisance Versus Substance: Specifying and Estimating Time-Series-Cross-Section Models’. Political Analysis 15:182–195.Google Scholar
Black, Ryan C., and Owens, Ryan J.. 2009. ‘Agenda Setting in the Supreme Court: The Collision of Policy and Jurisprudence’. The Journal of Politics 71(3):1062–1075.Google Scholar
Boix, Carles. 2003. Democracy and Redistribution. New York, NY: Cambridge University Press.Google Scholar
Boix, Carles, and Stokes, Susan. 2003. ‘Endogenous Democratization’. World Politics 55(4):517–549.CrossRefGoogle Scholar
Brenner, Saul, and Krol, John F.. 1989. ‘Strategies in Certiorari Voting on the United States Supreme Court’. The Journal of Politics 51(4):828–840.Google Scholar
Burkhart, Ross E., and Lewis-Beck, Michael S.. 1994. ‘The Economic Development Thesis’. American Political Science Review 88:903–910.Google Scholar
Caldeira, Gregory A. 1981. ‘The United States Supreme Court and Criminal Cases, 1935–1976: Alternative Models of Agenda Building’. British Journal of Political Science 11(4):449–470.Google Scholar
Caldeira, Gregory A., and Wright, John R.. 1988. ‘Organized Interests and Agenda Setting in the U.S. Supreme Court’. American Political Science Review 82(4):1109–1127.CrossRefGoogle Scholar
Caldeira, Gregory A., Wright, John R., and Zorn, Christopher J.W.. 1999. ‘Strategic Voting and Gatekeeping in the Supreme Court’. Journal of Law, Economics and Organization 15(3):549–572.Google Scholar
Chenery, Hollis B., and Taylor, Lance. 1968. ‘Development Patters: Among Countries and Over Time’. Review of Economic Statistics 50(4):391–416.Google Scholar
Clemen, Robert T. 1989. ‘Combining Forecasts: A Review and Annotated Bibliography’. International Journal of Forecasting 5(4):559–583.CrossRefGoogle Scholar
Cranmer, Skyler J., and Siverson, Randolph M.. 2008. ‘Demography, Democracy and Disputes: The Search for the Elusive Relationship Between Population Growth and International Conflict’. Journal of Politics 70(3):794–806.Google Scholar
Cutright, Phillips. 1963. ‘National Political Development: Social and Economic Correlates’. In Nelson W. Polsby, Robert A. Dentler and Paul A. Smith (eds), Politics and Social Life: An Introduction to Political Behavior. 569–581. Boston, MA: Houghton Mifflin.Google Scholar
Dahl, Robert A. 1971. Polyarchy: Participation and Opposition. New Haven, CT: Yale University Press.Google Scholar
DeBoef, Suzanna, and Keele, Luke. 2008. ‘Taking Time Seriously’. American Journal of Political Science 52(1):184–200.Google Scholar
Deutsch, Karl W. 1961. ‘Social Mobilization and Political Development’. American Political Science Review 55(3):493–510.Google Scholar
Draper, David. 1995. ‘Assessment and Propagation of Model Uncertainty’. Journal of the Royal Statistical Society, Series B 57(1):45–97.Google Scholar
Dufour, Jean-Marie, and Kiviet, Jan F.. 1998. ‘Exact Inference Methods for First-Order Autoregressive Distributed Lag Models’. Econometrica 66(1):79–104.Google Scholar
Epp, Charles. 1998. The Rights Revolution: Lawyers, Activists, and Supreme Courts in Comparative Perspective. Chicago, IL: University of Chicago.Google Scholar
Epstein, David L., Bates, Robert, Goldstone, Jack, Kristensen, Ida, and O’Halloran, Sharyn. 2006. ‘Democratic Transitions’. American Journal of Political Science 50(3):551–569.Google Scholar
Epstein, Lee, and Rowland, C.K.. 1991. ‘Debunking the Myth of Interest Group Invincibility in the Courts’. American Political Science Review 85(1):205–217.Google Scholar
Epstein, Lee, and Segal, Jeffrey A.. 2000. ‘Measuring Issue Salience’. American Journal of Political Science 44(1):66–83.Google Scholar
Epstein, Lee, and Kobylka, Joseph F.. 1992. The Supreme Court and Legal Change: Abortion and the Death Penalty. Chapel Hill, NC: University of North Carolina Press.Google Scholar
Erikson, Robert S., Bafumi, Joseph, and Wilson, Bret. 2001. ‘Was the 2000 Presidential Election Predictable’. PS: Political Science and Politics 34(4):815–819.Google Scholar
Fearon, James D., and Latin, David D.. 2003. ‘Ethnicity, Insurgency, and Civil War’. American Political Science Review 97(1):75–90.Google Scholar
Flemming, Roy, Dan Wood, B., and Bohte, John. 1999. ‘Attention to Issues in a System of Separated Powers: The Macrodynamics of American Policy Agendas’. Journal of Politics 61(1):76–108.CrossRefGoogle Scholar
Freund, Yoav, and Schapire, Robert. 1996. ‘Experiments With a New Boosting Algorithm’. In Machine Learning: Proceedings of the Thirteenth International Conference, Bari, Italy. 148–156.Google Scholar
Freund, Yoav, and Schapire, Robert. 1997. ‘A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting’. Journal of Computer and System Sciences 55(1):119–139.Google Scholar
Geer, John, and Lau, Richard R.. 2006. ‘Filling in the Blanks: A New Method for Estimating Campaign Effects’. British Journal of Political Science 36(2):269–290.Google Scholar
Gerber, Alan, Malhotra, Neil, Dowling, Conor, and Doherty, David. 2010. ‘Publication Bias in Two Political Behavior Literatures’. American Politics Research 38(4):591–613.Google Scholar
Geweke, John. 1978. ‘Temporal Aggregation in the Multiple Regression Model’. Econometrica 46(3):643–661.Google Scholar
Ghobarah, Hazem A., Huth, Paul, and Russett, Bruce. 2003. ‘Civil Wars Kill and Maim People-Long after the Shooting Stops’. American Political Science Review 97(2):189–202.CrossRefGoogle Scholar
Gill, Jeff. 2007. Bayesian Methods. Boca Raton, FL: Chapman & Hall/CRC.Google Scholar
Green, Donald, Kim, Soo Yeon, and Yoon, David. 2001. ‘Dirty Pool’. International Organization 55(2):441–468.Google Scholar
Hoeting, Jennifer A., Madigan, David, Raftery, Adrian E., and Volinsky, Chris T.. 1999. ‘Bayesian Model Averaging: A Tutorial’. Statistical Science 14(4):382–417.Google Scholar
Imai, Kosuke, and King, Gary. 2004. ‘Did Illegal Overseas Absentee Ballots Decide the 2000 U.S. Presidential Election?’ Perspectives on Politics 2(3):537–549.Google Scholar
Jackman, Simon. 2009. Bayesian Analysis for the Social Sciences. New York, NY: Wiley.Google Scholar
Koyck, Leendert M. 1954. Distributed Lags and Investment Analysis. Amsterdam: North-Holland.Google Scholar
Kuznets, Simon. 1966. Modern Economic Growth: Rate, Structure, and Spread. New Haven, CT: Yale University Press.Google Scholar
Leamer, Edward E. 1978. Specification Searches. New York, NY: Wiley.Google Scholar
Lerner, Daniel. 1958. The Passing of Traditional Society. New York, NY: Free Press of Glencoe.Google Scholar
Lipset, Seymour M. 1959. ‘Some Social Requisites of Democracy: Economic Development and Political Legitimacy’. American Political Science Review 53(1):69–105.CrossRefGoogle Scholar
Londregan, John B., and Poole, Keith T.. 1996. ‘Does High Income Promote Democracy’. World Politics 49(1):1–30.Google Scholar
Lütkepohl, Helmut. 1980. ‘Approximation of Arbitrary Distributed Lag Structures by a Modified Polynomial Lag: An Extension’. Journal of the American Statistical Association 75(370):428–430.Google Scholar
Madigan, David, and Raftery, Adrian E.. 1994. ‘Model Selection and Accounting for Model Uncertainty in Graphical Models Using Occam’s Window’. Journal of the American Statistical Association 89(428):1535–1546.Google Scholar
Martin, Andrew D., and Quinn, Kevin M.. 2002. ‘Dynamic Ideal Point Estimation Via Markov Chain Monte Carlo for the U.S. Supreme Court’. Political Analysis 10(2):134–153.Google Scholar
Martin, James E. 1967. ‘Isolation of Lagged Economic Responses’. Journal of Farm Economics 49(1):160–168.Google Scholar
McGuire, Kevin T., and Caldeira, Gregory A.. 1993. ‘Lawyers, Organized Interests, and the Law of Obscenity: Agenda-Setting in the Supreme Court’. American Political Science Review 87(3):715–726.Google Scholar
Montgomery, Jacob M., and Nyhan, Brendan. 2010. ‘Bayesian Model Averaging: Theoretical Developments and Practical Applications’. Political Analysis 18(2):245–270.Google Scholar
Moore, Barrington. 1966. Social Origins of Dictatorship and Democracy: Lord and Peasant in the Making of the Modern World. Boston, MA: Beacon Press.Google Scholar
Nelson, Charles R., and Schwert, G. William. 1974. ‘Estimating the Parameters of a Distributed Lag Model from Cross-Section Data: The Case of Hospital Admissions and Discharges’. Journal of the American Statistical Association 69(347):627–633.Google Scholar
Nicholson, Chris, and Collins, Paul. 2008. ‘The Solicitor General’s Amicus Curiae Strategies in the Supreme Court’. American Politics Research 36:382–415.Google Scholar
Perry, H.W. 1991. Deciding to Decide: Agenda Setting in the United States Supreme Court. Cambridge: Harvard University Press.Google Scholar
Peters, C. Scott. 2007. ‘Getting Attention: The Effect of Legal Mobilization on the U.S. Supreme Court’s Attention to Issues’. Political Research Quarterly 60(3):561–572.Google Scholar
Prezeworski, Adam. 1990. Democracy and the Market: Political and Economic Reforms in Eastern Europe and Latin America. New York, NY: Cambridge University Press.Google Scholar
Przeworski, Adam, and Limongi, Fernando. 1993. ‘Political Regimes and Economic Growth’. Journal of Economic Perspectives 7(3):51–69.Google Scholar
Przeworski, Adam, and Limongi, Fernando. 1997. ‘Modernization: Theories and Facts’. World Politics 49(2):155–183.Google Scholar
Przeworski, Adam, Alvarez, Michael E., Cheibub, Jose A., and Limongi, Fernando. 1996. ‘What Makes Democracies Endure?’ Journal of Democracy 7(1):39–55.Google Scholar
Przeworski, Adam, Alvarez, Michael E., Cheibub, Jose A., and Limongi, Fernando. 2000. Democracy and Development: Political Institutions and Well-Being in the World, 1950–1990. New York, NY: Cambridge University Press.Google Scholar
Raftery, Adrian E. 1995. ‘Bayesian Model Selection in Social Research’. Sociological Methodology 25:111–163.Google Scholar
Rostow, Walt W. 1960. The Stages of Economic Growth: A Non-Communist Manifesto. Cambridge: Cambridge University Press.Google Scholar
Rueschemeyer, Dietrich, Stephens, Evelyne H., and Stephens, John D.. 1992. Capitalist Development and Democracy. Chicago, IL: University of Chicago Press.Google Scholar
Simonsohn, Uri, Nelson, Leif, and Simmons, Joseph. 2014. ‘P-Curve: A Key to the File Drawer’. Journal of Experimental Psychology 143(2):534–547.Google Scholar
Solow, Robert M. 1960. ‘On a Family of Lag Distributions’. Econometrica 28(2):393–406.Google Scholar
Tibshirani, Robert. 1996. ‘Regression Shrinkage and Selection Via the Lasso’. Journal of the Royal Statistical Society, Series B 58:267–288.Google Scholar
Tibshirani, Robert. 1997. ‘The Lasso Method for Variable Selection in the Cox Model’. Statistics in Medicine 16:385–395.Google Scholar
Trivedi, Pravin K. 1985. ‘Distributed Lags, Aggregation and Compounding: Some Econometric Implications’. The Review of Economic Studies 52(1):19–35.Google Scholar
Ulmer, S. Sidney. 1984. ‘The Supreme Court’s Certiorari Decisions: Conflict as a Predictive Variable’. American Political Science Review 78(4):901–911.Google Scholar
Valentino, Nicholas, Brader, Ted, and Jardina, Ashley. 2013. ‘Immigration Opposition Among U.S. Whites: General Ethnocentrism or Media Priming of Attitudes About Latinos?’. Political Psychology 34(2):149–166.Google Scholar
Warren, T. Camber. 2014. ‘Not by the Sword Alone: Soft Power, Mass Media, and the Production of State Sovereignty’. International Organization 68(1):111–141.Google Scholar
Zaller, John R. 2004. ‘Floating Voters in U.S. Presidential Elections, 1948–2000’. In Willem Saris and Paul M. Sniderman (eds), Studies in Public Opinion: Attitudes, Nonattitudes, Measurement Error, and Change. 166:214. Princeton, NJ: Princeton University Press.Google Scholar