Hostname: page-component-77c89778f8-n9wrp Total loading time: 0 Render date: 2024-07-23T21:37:13.687Z Has data issue: false hasContentIssue false
  • English
  • Français

The Effects of Measurement Error on Two-Stage, Least-Squares Estimates

Published online by Cambridge University Press:  04 January 2017

Donald Philip Green
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Two-stage least squares (2SLS) is a statistical procedure that is used to correct for simultaneity bias and errors in variables. When applied to certain kinds of models, however, 2SLS is itself susceptible to bias as a result of random and nonrandom measurement error in the data. Using data from the 1980 Center for Political Studies panel, I show how different assumptions about measurement error produce radically different impressions about the reciprocal relationship between party identification and presidential performance evaluations.

Type
Research Article
Information
Political Analysis , Volume 2 , 1990 , pp. 57 - 74
Copyright
Copyright © by the University of Michigan 1991 

References

Achen, Christopher H. 1975. “Mass Political Attitudes and the Survey Response.” American Political Science Review 69: 1218–31.Google Scholar
Asher, Herbert B. 1974. “Some Consequences of Measurement Error in Survey Data.” American Journal of Political Science 18: 469–85.CrossRefGoogle Scholar
Bartels, Larry M. 1989. “Instrumental and Quasi-Instrumental Variables.” Presented at the annual Political Methodology Conference, Minneapolis.Google Scholar
Brody, Richard A., and Rothenberg, Lawrence S. 1988. “The Instability of Partisanship: An Analysis of the 1980 Presidential Election.” British Journal of Political Science 18: 445–65.Google Scholar
Campbell, Donald and Fiske, Donald. 1959. “Convergent and Discriminant Validation by the Multitrait-Multimethod Matrix.” Psychological Bulletin 56: 81–105.Google Scholar
Converse, Philip E. and Markus, Gregory B. 1979. “Plus ca Change… : The New CPS Election Study Panel.” American Political Science Review 73: 32–49.Google Scholar
Couch, Arthur, and Keniston, Kenneth. 1960. “Yeasayers and Naysayers: Agreeing Response set as a Personality Variable.” Journal of Abnormal and Social Psychology 60: 151–74.CrossRefGoogle ScholarPubMed
Cotter, Patrick R., Cohen, Jeffrey, and Coulter, Philip B. 1982. “Race of Interviewer Effects on Telephone Interviews.” Public Opinion Quarterly 46: 278–84.CrossRefGoogle Scholar
Fiorina, Morris P. 1981. Retrospective Voting in American National Elections. New Haven: Yale University Press.Google Scholar
Green, Donald P. 1988. “On the Dimensionality of Public Sentiment Toward Partisan and Ideological Groups.” American Journal of Political Science 32: 758–80.Google Scholar
Green, Donald P., and Palmquist, Bradley L. 1990. “Of Artifacts and Partisan Instability.” American Journal of Political Science 34: 872–902.Google Scholar
Hatchett, Shirley, and Schuman, Howard. 1975. “White Respondents and Race of Interviewer Effects.” Public Opinion Quarterly 39: 523–28.Google Scholar
Jackson, John. 1975. “Issues and Party Alignment.” In The Future of Political Parties, ed. Maisel, Louis and Sacks, Paul. Beverly Hills: Sage.Google Scholar
Johnston, J. 1984. Econometric Methods. 3d ed. New York: McGraw-Hill.Google Scholar
Markus, Gregory B. 1982. “Political Attitudes during an Election Year: A Report on the 1980 NES Panel Study.” American Political Science Review 76: 538–60.Google Scholar
Markus, Gregory B., and Converse, Philip E. 1979. “A Dynamic Simultaneous Equation Model of Electoral Choice.” American Political Science Review 73: 1055–70.CrossRefGoogle Scholar
Page, Benjamin I., and Jones, Calvin C. 1979. “Reciprocal Effects of Policy Preferences, Party Loyalties, and the Vote.” American Political Science Review 73: 1071–89.Google Scholar
Palmquist, Bradley L., and Green, Donald P. 1989. “Assessing Nonrandom Measurement Error using Panel Data and Single-Indicator Models.” Presented at the annual meeting of the American Political Science Association, Atlanta.Google Scholar
Werts, Charles E., and Linn, Robert L. 1972. “A Multitrait-Multimethod Model for Studying Growth.” Educational and Psychological Measurement 32: 655–78.Google Scholar
Werts, Charles E., Joreskog, Karl G., and Linn, Robert L. 1976. “Analyzing Ratings with Correlated Intrajudge Measurement Errors.” Educational and Psychological Measurement 36: 319–28.Google Scholar
Wiley, James A., and Wiley, Mary Glenn. 1974. “A Note on Correlated Errors in Repeated Measurements.” Sociological Methods and Research 3: 172–88.Google Scholar