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The-Stage Estimation of Stochastic Truncation Models with Limited Dependent Variables Boehmke, Frederick Uploaded 04-13-2000 Keywords selection bias stochastic truncation maximum likelihood simulation monte carlo initiative interest groups Abstract Recent work has made progress in estimating models involving selection bias of a par­ ticularly strong nature: all nonrespondents are unit nonresponders, meaning that no data is available for them. These models are reasonable successful in circumstances where the dependent variable of interest is continuous, but they are less practical empirically when it is latent and only discrete outcomes or choices are observed. I develop a method in this paper to estimate these models that is much more practical in terms of estimation. The model uses a small amount of auxiliary information to estimate the selection equation and these parameters are then used to estimate the equation of interest in a maximum likelihood setting. After presenting monte carlo analysis to support the model, I apply the technique to a substantive problem: which interest groups are likely to turn to the initiative process to achieve their policy goals.

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Coordination, Moderation and Institutional Balancing in American House Elections at Midterm Mebane, Walter R. Sekhon, Jasjeet Uploaded 09-02-1999 Keywords congressional elections rational expectations voter equilibrium midterm cycle stochastic choice model turnout Abstract Individuals' turnout decisions and vote choices for the House of Representatives have been coordinated in recent midterm election years, with each eligible voter (each elector) using a strategy that features policy moderation. Coordination is defined as a rational expectations equilibrium among electors, in which each elector has both common knowledge and private information about the election outcome. Stochastic choice models estimated using individual-level data from the American National Election Study Post-Election Surveys of years 1978-1998 support coordination, but a model in which electors act non-strategically to moderate policy has very similar behavioral implications and also works well. The empirical coordinating model satisfies the fixed point condition that defines the common knowledge expectation electors have about the election outcome in the equilibrium of the theoretical model. Both the coordinating and non-strategic models are capable of generating a midterm cycle in which the President's party usually loses vote share at midterm. Both models correctly flag 1998 as an exception to that pattern: the Republican party had policy positions that were too conservative for most electors. Moderation at midterm has usually been based on electors' expectations that the House will dominate the President in determining post-election policy.

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Estimating Time-Varying Parameters with Flexible Least Squares Wood, B. Dan Uploaded 07-02-1998 Keywords time series time-varying parameters stochastic parameters flexible least squares Abstract A common assumption among time series analysts is that estimated coefficients remain constant through time. Yet this strong assumption often has little grounds in substantive theory or empirical tests. If coefficients vary through time in an infinite time sequence, but are estimated with constant coefficient methods in a finite time sequence, then this can lead to significant information loss, as well as to errors of inference. This paper demonstrates a method for exploring the relative stability of time series coefficients, Flexible Least Squares (FLS). In particular, FLS is superior to other such methods, in that it enables the analyst to diagnose the magnitude of coefficient variation, as well as detect which particular coefficients are changing. FLS also provides an estimated vector of time-varying coefficients that can be used for exploratory or descriptive purposes. FLS properties are demonstrated through simulation analysis and an evaluation of the time-varying equilibrium between federal revenues and expenditures from 1904-1996.

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Bargaining and Society: A Statistical Model of the Ultimatum Game Signorino, Curtis Uploaded 07-18-2007 Keywords bargaining random utility models strategic ultimatum game equilibrium stochastic Abstract In this paper we derive a statistical estimator for the popular Ultimatum bargaining game. Using monte carlo data generated by a strategic bargaining process, we show that the estimator correctly recovers the relationship between dependent variables, such as the proposed division and bargaining failure, relative to substantive variables that comprise players' utilities. We then use the model to analyze bargaining data in a number of contexts. The current example examines the effects of demographics on bargaining behavior in experiments conducted on U.S. and Russian participants.