Political Science: The State of the Discipline II

By Ada W. Finifter | Go to book overview
issue that is important to the voter. A moderate pro-choice voter would prefer an extreme pro-choice candidate to a moderate pro-life candidate.
Brady ( 1991b) showed that a Poole-like estimator actually does produce statistically consistent estimates of both factor scores and factor loadings in a linear factor model. Rivers ( 1987) result, then, is partly the result of the non-linearities inherent in ideal point models. It can also be shown that the Poole estimator would yield correct results if there were no error in the model. These results suggest that the Poole estimator may not produce much bias if the amount of error is small.
Jackson and Kingdon ( 1992) have criticized the use of interest group scores to explain congressional votes, but their argument does not bear on the debate about the number of dimensions in legislative votes.
Indeed, Poole and Rosenthal recognized that the standard proof of consistency for maximum likelihood does not apply, but they made the odd statement (1991, 272) that "At a practical level, this caveat is not important. The key point is that data is being added at a far faster rate than parameters." Yet there are many examples in statistics where adding data faster than parameters does not ensure consistency. The Monte Carlo reports in their paper are more convincing; but much more work still needs to be done to assay the statistical properties of their innovative method for scaling roll-call votes.
This section draws heavily upon Bartels ( 1990), where some related points are discussed in more detail.
Fascinating questions about the role of theoretical expectations in statistical inference were raised by a Box-Jenkins ARIMA analysis in the Journal of Conflict Resolution ( Orme-Johnson et al. 1988), demonstrating that "a very small group practicing [the Maharishi technology of the unified field] in East Jerusalem appeared to influence overall quality of life in Jerusalem, Israel, and even in neighboring Lebanon." The editor of the journal ( Russett 1988, 773) did not know what to make of the finding and admitted that "The hypothesis has no place within the normal paradigm of conflict and peace research. Yet the hypothesis seems logically derived from the initial premises, and its empirical testing seems competently executed." Schrodt ( 1990) questioned whether the research was, in fact, competently executed; but whatever the truth in this case, the original article raises significant questions about what scientific hypotheses we should be willing to entertain and what proof we should require for their demonstration. How strongly should theory incline us to believe or disbelieve that there are "long cycles" in the severity of war in the international system ( Goldstein 1988, 1991; Beck 1991), or that postwar U.S. savings rates were influenced by changes in public perceptions of the threat of nuclear war ( Slemrod 1986)? As we add new and more powerful techniques to our kitbag of tools, it is worth remembering that good inferences require more than powerful techniques and large t- statistics.
It is striking how seldom, in footnotes of this sort, trying something different makes the results come out different.
The cross-validation criterion is simply the square root of the PRESS (PRediction Error Sum of Squares) criterion of Allen ( 1971) and is also closely related to the jackknife and bootstrap techniques ( Efron and Gong 1983).
Of course, the least squares and maximum likelihood criteria sometimes lead to the same estimator, as in the case of ordinary regression with normally distributed errors. In cases like this, researchers did maximum likelihood estimation in the same way they wrote prose, without knowing it.
King ( 1991, 2-3) reported the results of a content analysis in which the proportion of American Political Science Review articles using "quantitative data and methods in some way" has fluctuated around 50% since 1969.
Another approach to the problem of mass belief systems has been to reconceptualize political sophistication and ideological constraint. Luskin ( 1987) provided a magisterial overview of various measures of political sophistication and some of his own suggestions. Peffley and Hurwitz ( 1985) and Hurwitz and Peffley ( 1987) suggested an interesting approach based upon a hierarchical structure of attitudes with core beliefs informing broad postures which, in turn, are the basis for specific beliefs.
Later, Palmquist and Green ( 1992, 128) showed that the identification problem is even worse than in Achen's telling because "standard errors for the measurement error parameters [of the Wiley and Wiley ( 1974) model with correlated errors] are typically so large that it is not hard to see how implausible values could result simply from sampling error." With three waves of data it is not only impossible to distinguish between the two models but also virtually impossible to get informative estimates of the parameter estimates of the correlated error model.
Rivers ( 1986) independently proposed a similar solution to the Kramer problem, albeit with a somewhat different model and estimation strategy.


Achen, Christopher H. 1975. "Mass Political Attitudes and the Survey Response." American Political Science Review 69:1218-23.

Achen, Christopher H. 1977. "Measuring Representation: Perils of the Correlation Coefficient." American Journal of Political Science 21:805-15.

Achen, Christopher H. 1978. "Measuring Representation," American Journal of Political Science 22:475-510.

Achen, Christopher H. 1982. Interpreting and Using Regression. Beverly Hills: Sage Publications.

Achen, Christopher H. 1983a. "Toward Theories of Data: The State of Political Methodology." In Political Science: The State of the Discipline, ed. Ada W. Finifter. Washington, DC: American Political Science Association.

Achen, Christopher H. 1983b. "If Party ID Influences the Vote, Goodman's Ecological Regression Is Biased (But Factor Analysis Consistent)." University of California, Berkeley. Typescript.

Achen, Christopher H. 1984. "How to Estimate Party Loyalty Rates from Aggregate Voting Data." University of California, Berkeley. Typescript.

Achen, Christopher H. 1985. "Proxy Variables and Incorrect Signs on Regression Coefficients." Political Methodology 11:299-316.

Achen, Christopher H. 1986a. "Necessary and Sufficient Conditions for Unbiased Aggregation of Cross-Sectional Regressions." Presented at the annual meeting of the Political Science Association, Washington, DC.

Achen, Christopher H. 1986b. The Statistical Analysis of Quasi- Experiments. Berkeley: University of California Press.

Achen, Christopher H. 1987. Statistical Models for Event Data: A Review of Errors in Variable Theory. Paper presented at the First DDIR (Data Development for International Research) Conference on Event Data, Columbus, OH.

Achen, Christopher H., and W. Phillips Shively. n.d. Cross-level Inference: New Approaches.

Achen, Christopher H., and Duncan Snidal 1989. "Rational Deterrence Theory and Comparative Case Studies." World Politics 41:143-69.

Aldrich, John H., and Richard D. McKelvey. 1977. "A Method of Scaling with Applications to the 1968 and 1972 Presidential Elections." American Political Science Review 71:111-30.

Aldrich, John H., and Forrest D. Nelson. 1984. Linear Probability, Logit, and Probit Models. Beverly Hills: Sage Publications.

Alker, Hayward R., Jr. 1988. "The Dialectical Logic of Thucydides'Melian Dialogue."


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Political Science: The State of the Discipline II
Table of contents

Table of contents

  • Title Page i
  • Table of Contents v
  • Preface vii
  • Theory and Method 1
  • 1: Texts and Canons: The Status of the "Great Books" in Political Theory 3
  • Conclusion 21
  • Notes 22
  • Bibliography 23
  • 2: Political Theory in the 1980s: Perplexity Amidst Diversity 27
  • Notes 43
  • Bibliography 43
  • Additional Bibliography 46
  • 3: Feminist Challenges to Political Science 55
  • Notes 72
  • Bibliography 73
  • 4: Formal Rational Choice Theory: A Cumulative Science of Politics 77
  • Concluding Comments 97
  • Notes 98
  • Bibliography 101
  • 5: The Comparative Method 105
  • Conclusion 116
  • Notes 117
  • Bibliography 117
  • 6: The State of Quantitative Political Methodology 121
  • Conclusion 148
  • Notes 148
  • Bibliography 150
  • Political Processes and Individual Political Behavior 161
  • 7: Comparative Political Parties: Research and Theory 163
  • Conclusion 183
  • Notes 184
  • Bibliography 185
  • 8: The Not So Simple Act of Voting 193
  • Notes 213
  • Bibliography 214
  • 9: The New Look in Public Opinion Research 219
  • Notes 240
  • Bibliography 240
  • 10: Expanding Disciplinary Boundaries 247
  • Conclusion 269
  • Notes 271
  • Bibliography 271
  • 11: Citizens, Contexts, and Politics 281
  • Conclusion: Putting the Puzzle Back Together 299
  • Bibliography 300
  • 12: Political Communication 305
  • Conclusions 323
  • Bibliography 324
  • Political Institutions of the State 333
  • 13: Legislatures: Individual Purpose and Institutional Performance 335
  • Conclusions: Behavior, Institutions, and Theory 354
  • Notes 357
  • Bibliography 357
  • 14: Public Law and Judicial Politics 365
  • 15: Political Executives and Their Officials 383
  • Conclusion 402
  • Bibliography 403
  • 16: Public Administration: The State of the Field 407
  • Notes 423
  • Bibliography 424
  • Nations and Their Relationships 429
  • 17: Comparative Politics 431
  • Conclusion 443
  • Notes 444
  • Bibliography 446
  • 18: Global Political Economy 451
  • Conclusion 474
  • Notes 476
  • Bibliography 477
  • Conclusions 483
  • Conclusions 503
  • Notes 504
  • Bibliography 505
  • Appendix 511
  • Contributors 513
  • Index of Cited Authors 517


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