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Primaries and Turnout Kanthak, Kristen Morton, Becky Uploaded 07-09-2003 Keywords primaries turnout bivariate probit selection model treatment effects Abstract We consider the effects of differences in primary systems on voter turnout in primaries as well as the effect of holding primaries on general election turnout and support for candidates chosen in primaries. The analysis is based on a group majority voting model of turnout where candidates from two major parties simultaneously make strategic entry decisions and mobilize voters strategically in primaries and general elections if they choose to enter. We evaluate the model's predictions using data from midterm Congressional primaries and general elections in the 1980s. We use a two-stage estimation process. First, the model's predictions concerning the effects of primary system differences on whether primaries occur and the vote totals in primaries is estimated using a maximum likelihood bivariate probit selection model. We find that primary system variables do have significant effects on whether primaries are held and to some extent affect vote totals in primaries, although there are interesting party specific differences suggesting that Republicans see advantages from mobilizing voters in open primary systems while Democrats benefit in semi-closed primary systems. Second, the estimated vote totals in the primaries are used as treatment variables via an instrumental variables approach in a simultaneous equation system with two dependent variables general election vote totals and the vote share of the Democratic party's candidate. We find that voting in primaries has a positive and significant effect on voting in general elections and significantly increase the vote share of the party holding the primary, suggesting that the arguments that primaries by their existence decrease voter turnout and hurt parties holding them have no support.

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The Two Faces of Public Opinion Berinsky, Adam Uploaded 04-13-1998 Keywords public opinion selection bias item non-response social desirability bivariate probit Abstract In this paper I trace out the aggregate effects of the social forces in the survey interview that might influence the opinions which individuals express. First, I advance the "Mediated Communication" theory of the survey response, which builds on existing models of public opinion in the political science literature by accounting for effects related to the social context of the survey setting. I then discuss how the aggregation process could compound these individual-level effects to create an opinion signal which is a poor representation of the collective public's policy preferences. As an illustration of these effects and the resulting difficulties involved in measuring aggregate opinion on socially sensitive issues, I use National Elections Study (NES) data from 1990-1994 to show that public opinion polls overstate support for school integration. Specifically, individuals who harbor anti-integration sentiments are likely to hide their socially unacceptable opinions behind a mask of indifference. Finally, in order to confirm the validity of these findings, I show that the same methods which predict that opinion polls understate true opposition to government involvement in school integration also predict the results of the 1989 New York City mayoral election -- an election where the charged racial atmosphere made accurate polling difficult, if not impossible -- more accurately than the marginals of the pre-election polls taken in the weeks leading to the election. All told, these results suggests that survey questions on school integration -- and more generally questions on racial attitudes -- may provide an inaccurate picture of true public sentiment on such sensitive issues.

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Senate Voting on NAFTA: The Power and Limitations of MCMC Methods for Studying Voting across Bills and across States Smith, Alastair McGillivray, Fiona Uploaded 07-09-1996 Keywords NAFTA MCMC Gibbs sampling bivariate probit Senate Abstract We examine similarities in senate voting within states and across two senate bills: the 1991 fast track authorization bill and the 1993 NAFTA implementation bill. A series of bivariate probit models are estimated by Markov Chain Monte Carlo simulation. We discuss the power of MCMC techniques and how the output of these sampling procedures can be used for Bayesian model comparisons. Having separately explored the similarities in votes across bills and within states, we develop a 4-variate probit model to explain voting on NAFTA. The power of MCMC techniques to estimate this complicated model is demonstrated with two different MCMC procedures. We conclude by discussing the data requirements for these techniques.

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Endogeneity in Probit Response Models Freedman, David Sekhon, Jasjeet Uploaded 05-28-2008 Keywords Bivariate probit sample selection identification indefinite Hessian optimization Abstract In this paper, we look at conventional methods for removing endogeneity bias in regression models, including the linear model and the probit model. The usual Heckman two-step procedure should not be used in the probit model: from a theoretical perspective, this procedure is unsatisfactory, and likelihood methods are superior. However, serious numerical problems occur when standard software packages try to maximize the biprobit likelihood function, even if the number of covariates is small. The log likelihood surface may be nearly flat, or may have saddle points with one small positive eigenvalue and several large negative eigenvalues. We draw conclusions for statistical practice. Finally, we describe the conditions under which parameters in the model are identifable; these results appear to be new.