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Below results based on the criteria 'Benford'
Total number of records returned: 968

Can Voting Reduce Welfare? Evidence from the US Telecommunications Sector
Falaschetti, Dino

Uploaded 06-15-2004
Keywords Electoral Institutions
Voter Turnout
Capture Theory
Regulatory Commitment
Telecommunications Policy
Economic Welfare
Abstract Voter turnout is popularly cited as reflecting a polity's health. The ease with which electoral members influence policy can, however, constrain an economy's productive capacity. For example, while influential electorates might carefully monitor political agents, they might also "capture" them. In the latter case, electorates transfer producer surplus to consumers at the expense of social welfare - i.e., a "healthy" polity's economy rests at an inferior equilibrium. I develop evidence that the US telecommunications sector may have realized such an outcome. This evidence is remarkably difficult to dismiss as an artifact of endogeneity bias, and appears important for several audiences. For example, the normative regulation literature calls for constraints on producers' market power, while the institutions and commitment literature calls for checks on political agents' opportunism. Evidence that I develop here suggests that, unbound by similar constraints, electoral principals might effectively control their political agents while significantly retarding their economic agents' productive incentives.

Time-Series--Cross-Section Issues: Dynamics, 2004
Beck, Nathaniel
Katz, Jonathan

Uploaded 07-24-2004
Keywords Time-series--cross-section data
lagged dependent variables
Nickell bias
Abstract This paper deals with a variety of dynamic issues in the analysis of time-series--cross-section (TSCS) data raised by recent papers; it also more briefly treats some cross-sectional issues. Monte Carlo analysis shows that for typical TSCS data that fixed effects with a lagged dependent variable performs about as well as the much more complicated Kiviet estimator, and better than the Anderson-Hsiao estimator (both designed for panels). It is also shown that there is nothing pernicious in using a lagged dependent variable, and all dynamic models either implicitly or explicitly have such a variable; the differences between the models relate to assumptions about the speeds of adjustment of measured and unmeasured variables. When adjustment is quick it is hard to differentiate between the models, and analysts may choose on grounds of convenience (assuming that the model passes standard econometric tests). When adjustment is slow it may be the case that the data are integrated, which means that no method developed for the stationary case is appropriate. At the cross-sectional level, it is argued that the critical issue is assessing heterogeneity; a variety of strategies for this assessment are discussed.

Imitative and Evolutionary Processes that Produce Coordination Among American Voters
Mebane, Walter R.

Uploaded 07-11-2003
Keywords imitation
evolutionary game
strategic coordination
Abstract I examine the extent to which evolutionary game models based on the idea of pure imitation may help to explain recent empirical findings that the American electorate is involved in a situation of large-scale strategic coordination. Pure imitation in this context is the idea that some voters who are dissatisfied with their current strategy look around and adopt the strategy of the first voter they encounter who has attributes similar to theirs. The current analysis is part of a plan to use evolutionary models to motivate simulations based on National Election Studies data. The model implies that all voters ultimately use strategic coordination, although competing strategies disppear at different rates, depending on the voter's partisanship.

The Binomial-Beta Hierarchical Model for Ecological Inference: Methodological Issues and Fast Implementation via the ECM Algorithm
de Mattos, Rogerio S.
Veiga, Alvaro

Uploaded 10-17-2002
Keywords ecological inference
hierarchical models
binomial-beta distribution
ECM Algorithm
Abstract The binomial-beta hierarchical model from King, Rosen, and Tanner (1999) is a recent contribution to ecological inference. Developed for the 2x2 tables case and from a bayesian perspective, the model is featured by the compounding of binomial and beta distributions into a hierarchical structure. From a sample of aggregate observations, inference with this model can be made regarding values of unobservable disaggregate variables. The paper reviews this EI model with two purposes: First, a faster approach to use it in practice, based on explicit modeling of the disaggregate data generation process along with posterior maximization implemented via the ECM algorithm, is proposed and illustrated with an application to a real dataset; second, limitations concerning the use of marginal posteriors for binomial probabilities as the vehicle of inference (basically, the failure to respect the accounting identity) instead of the predictive distributions for the disaggregate proportions are pointed. In the concluding section, principles for EI model building in general and directions for further research are suggested.

State-Level Opinions from National Surveys: Poststratification using Hierarchical Logistic Regression
Park, David K.
Gelman, Andrew
Bafumi, Joseph

Uploaded 07-12-2002
Keywords Bayesian Inference
Public Opinion
Abstract Previous researchers have pooled national surveys in order to construct state-level opinions. However, in order to overcome the small n problem for less populous states, they have aggregated a decade or more of national surveys to construct their measures. For example, Erikson, Wright and McIver (1993) pooled 122 national surveys conducted over 13 years to produce state-level partisan and ideology estimates. Brace, Sims-Butler, Arceneaux, and Johnson (2002) pooled 22 surveys over a 25-year period to produce state-level opinions on a number of specific issues. We construct a hierarchical logistic regression model for the mean of a binary response variable conditional on poststratification cells. This approach combines the modeling approach often used in small-area estimation with the population information used in poststratification (see Gelman and Little 1997). We produce state-level estimates pooling seven national surveys conducted over a nine-day period. We first apply the method to a set of U.S pre-election polls, poststratified by state, region, as well as the usual demographic variables and evaluate the model by comparing it to state-level election outcomes. We then produce state-level partisan and ideology estimates by comparing it to Erikson, Wright and McIver's estimates.

Monotone Comparative Statics in Models of Politics: A Method for Simplifying Analysis and Enhancing Empirical Content
Bueno de Mesquita, Ethan
Ashworth, Scott

Uploaded 08-18-2004
Keywords game theory
formal theory
empirical implications of theoretical models
comparative statics

Abstract We elucidate a powerful yet simple method for deriving comparative statics conclusions for a wide variety of models: Monotone Comparative Statics (Milgrom and Shannon, 1994). Monotone comparative static methods allow researchers to extract robust, substantive empirical implications from formal models that can be tested using ordinal data and simple non-parametric tests. They also replace a diverse range of more technically di±cult mathematics (facilitating richer, more realistic models), a large set of assumptions that are hard to understand or justify substantively (highlighting the political intuitions underlying a model's results), and a complicated set of methods for extracting implications from models. We present an accessible introduction to the central monotone comparative statics results and a series of practical tools for using these techniques in applied models (with reference to original sources, when relevant). Throughout we demonstrate the techniques with examples drawn from political science.

Is All Politics and Economics Local? National Elections and Local
Wawro, Gregory
Himmelberg, Charles P.

Uploaded 07-14-2001
Keywords elections
economic conditions
voting behavior
Abstract Scholars have long sought to understand the causal relationships between economics and political participation. Of particular concern has been how economic experiences have affected individuals' decisions to participate in elections and cast votes for candidates of different political parties. Practically all of the studies on elections in the United States have focused on national aggregate economic conditions and national aggregate political outcomes, while only a handful of studies have focused on whether state and local economic conditions affect federal elections. The conclusion one would reach from these studies is that the adage ``all politics is local'' does not apply to economics and elections. In fact, despite the findings of some early studies (e.g. Tufte 1975), recent research would lead us to conclude that economic conditions have no direct effects on congressional elections (Erikson 1990; Alesina and Rosenthal 1995). According to these recent studies, the economy is related to congressional elections only indirectly through its effects on presidential elections. And even in presidential elections, a key economic indicator---unemployment---appears to have little to no effect on presidential elections. In this paper, we question the conclusions of previous studies by considering how the failure to correctly model vote shares at the local level could produce misleading results on the effects for economic conditions on elections in local analysis. We develop a model for local vote shares by adapting a model derived in the empirical literature on demand for differentiated products. Our model explicitly accounts for nonlinearity and aggregation in vote share functions and so avoids some of the problems of standard linear specifications of vote shares that are common in the literature. We estimate our model using data at the local level to assess the impact of economic conditions on presidential vote shares and turnout in the 1992 election. We find that local unemployment does affect presidential votes and these effects vary by demographic groups in interesting ways.

Estimating Risk and Rate Levels, Ratios, and Differences in Case-Control Studies
King, Gary
Zeng, Langche

Uploaded 05-06-2001
Keywords Logistic Models
Case-Control Studies
Relative Risk
Odds Ratio
Risk Ratio
Risk Difference
Hazard Rate
Rate Ratio
Rate Difference
Abstract Classic (or ``cumulative'') case-control sampling designs do not admit inferences about quantities of interest other than risk ratios, and then only by making the rare events assumption. Probabilities, risk differences, and other quantities cannot be computed without knowledge of the population incidence fraction. Similarly, density (or ``risk set'') case-control sampling designs do not allow inferences about quantities other than the rate ratio. Rates, rate differences, cumulative rates, risks, and other quantities cannot be estimated unless auxiliary information about the underlying cohort such as the number of controls in each full risk set is available. Most scholars who have considered the issue recommend reporting more than just risk and rate ratios, but auxiliary population information needed to do this is not usually available. We address this problem by developing methods that allow valid inferences about all relevant quantities of interest from either type of case-control study when completely ignorant of or only partially knowledgeable about relevant auxiliary population information.

Strategic voting in mixed-member electoral systems: The Italian case
Benoit, Kenneth
Laver, Michael
Giannetti, Daniela

Uploaded 08-26-2000
Keywords elections
strategic voting
ecological inference
Abstract The new Italian electoral system has two elements, a plurality element in single member districts and a PR element in larger multimember constituencies. The plurality element provides strong incentives for groups of parties to form pre-electoral coalitions. The PR element offers incentives for parties to contest the elections individually. We can think of two types of voter. The first type, whom we characterize as "strategic," votes for his or her first choice party in the PR election since there is no strategy that can improve on this. In the plurality election, a strategic voter supports the candidate sponsored by the coalition with which his or her first choice party is affiliated, even if this is not from the first choice party. The second type of voter, whom we characterize as "non-strategic," also votes for his or her first choice party in the PR election. In the plurality election, the non-strategic voter will vote for a first choice party if a candidate of this party is on the ballot but, if not, votes unpredictably. In this paper, we model the "strategic" and "non- strategic" elements of the vote flowing to candidates in the plurality element of the election. Using data from the 1996 and 1994 elections on both PR and plurality voting patterns in each single member district, and confining ourselves to districts where there is a run-off between two coalitions, we are able to estimate the relative numbers of strategic and non- strategic voters in each district, and characterize this in terms of a range of strategic variables.

Why Lagged Dependent Variables Can Suppress the Explanatory Power of Other Independent Variables
Achen, Christopher H.

Uploaded 07-14-2000
Keywords time series
serial correlation
arms races
Abstract In many time series applications in the social sciences, lagged dependent variables have no obvious causal interpretation, and researchers omit them. When they are left out, the other coefficients take on sensible values. However, when an autoregressive term is put in ``as a control,'' it often acquires a large, statistically significant coefficient and improves the fit dramatically, while many or all of the remaining substantive coefficients collapse to implausibly small and insignificant values. Occasionally, the substantive variables even take on the wrong sign. This paper explains why this phenomenon occurs and how the resulting confusions have often misled researchers into inaccurate inferences. The standard findings that government budgets are caused primarily by past budgets and that arms races are driven mainly by domestic forces are shown to be likely statistical artifacts. Applications are made to vector autoregressions, error-correction models, and panel studies.

The-Stage Estimation of Stochastic Truncation Models with Limited Dependent Variables
Boehmke, Frederick

Uploaded 04-13-2000
Keywords selection bias
stochastic truncation
maximum likelihood
monte carlo
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.

Multiculturalism, Diversity, and Prejudice
Branton, Regina P.
Jones, Bradford S.

Uploaded 03-27-1999
Keywords random coefficients
multilevel analysis
racial politics
Abstract In this paper, we consider the relationship between racial and ethnic diversity and individuals' assessments of racial and ethnic groups measured on several public opinion items. To examine these issues, we merge 1992 National Election Study data with U.S. Census Bureau demographic data measured at the congressional district level. We then develop an index of diversity that is based on the distribution of racial and ethnic groups in the congressional district. To examine the relationship between diversity and individual-level attitudes toward racial and ethnic groups, we estimate a series of models treating the response variable as a function of both individual-level attributes and district-level attributes. This approach allows us to assess, among other things, if diversity is associated with more positive or negative evaluations of racial and ethnic groups. The models herein are all estimated as mixed effects models to account for the clustering of observations within congressional districts. We find that diversity is associated with group affect and individuals' placement on policy issues; however, in contrast to some of the extant literature, we find that racial and ethnic diversity is nonlinearly associated with group affect: extremely low and extremely high levels of racial and ethnic diversity are associated with lower racial and ethnic group evaluations, while districts that are moderately diverse are associated with higher evaluations. This result also holds for some of the policy items examined. Specifically, we find that support for government assistance to blacks, and to a lesser extent, support for affirmative action, exhibits this nonlinearity with regard to racial and ethnic diversity. We also find this pattern for individuals' assessment of welfare recipients.

Does Size Matter? Exploring the Small Sample Properties of Maximum Likelihood Estimation
Hart, Jr., Robert A.
Clark, David H.

Uploaded 04-20-1999
Keywords small samples
Type II errors
Abstract The last two decades have witnessed an explosion in the use of computationally intensive methodologies in the social sciences as computer technology has advanced. Among these empirical methods are Maximum Likelihood (ML) procedures. ML estimators possess a variety of desirable qualities, perhaps most prominent of which is the asymptotic efficiency of the standard errors. However, the behavior of the estimators in general, of the estimates of the standard errors in particular, and thus of inferential hypothesis tests are uncertain in small sample analyses. In political science research, small samples are routinely the subject of empirical investigation using ML methods, yet little is known regarding what effect sample size has on a researcher's ability to draw inferences This paper explores the behavior of ML estimates in probit models across differing sample sizes and with varying numbers of independent variables in Monte Carlo simulations. Our experimental results allow us to conclude that: a) the risk of making Type I errors does not change appreciably as sample size descends; b) the risk of making Type II errors increases dramatically in smaller samples and as the number of regressors increases.

Deliberation and Voting at the Federal Convention of 1787
Londregan, John B.

Uploaded 07-13-1999
Keywords Scaling
Abstract This paper examines the deliberative voting of the Federal Convention of 1787, and contrasts this type of voting with the more commonly observed position taking behavior that characterizes most legislatures. The analysis constructs an empirical model that incorporates proposal valence, which at the federal convention corresponded to proposals' contribution to the ``ratifiability" of the constitution, and uses information contained in the authorship of proposals to overcome the identification problems that plague empirical spatial models of voting. The estimated issue positions of the state delegations reveal a significant cleavage on an two issue dimensions; one corresponding to the balance between the states and the central government and the other dealing with the extent of the powers granted to the federal governmen

Strategic Voting in Germany. Evidence employing King's Ecological Inference
Gschwend, Thomas

Uploaded 10-20-1999
Keywords Germany
Abstract Germany provides an especially interesting case for the study of strategic voting because they use two-ballot system on Election Day. Voters are encouraged to split their votes using different strategies. This is called emph{sophisticated voting}. I disentangle different types of sophisticated voting that have been mixed in the literature so far: On the first vote there is emph{tactical} voting, and on the second vote there is emph{loan} voting. Therefore, I focus particularly on ticket-splitting patterns. The data set I use contains official election results of first and second votes for all West-German districts from the federal election of 1998. To obtain estimates that determine quantity of straight and split-ticket voting between political parties I employ King's method of Ecological Inference (EI). Using these estimates as independent variables in linear regression models, I show that tactical and loan voters secured the representation of FDP and the Greens in the German Parliament.

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.

Cointegration Tests when Data are Near-Integrated
De Boef, Suzanna
Granato, Jim

Uploaded 04-22-1998
Keywords time series
DickeyFuller tests
Monte Carlo
Abstract Testing theories about political change requires analysts to make assumptions about the nature of the memory of their time series. Applied analyses are often based on inferences that the time series of interest are integrated and cointegrated. Typically these analyses rest on Dickey-Fuller pretests for unit roots and tests for cointegration based on the residuals from a cointegrating regression in the context of the Engle-Granger two-step methodology. We argue that this approach is not a good one and use Monte Carlo results to show that these tests can lead analysts to falsely conclude that the data are cointegrated (or nearly- cointegrated) when the data is near-integrated and not cointegrating. Further, analysts are likely to falsely conclude the relationship is not cointegrating when it is. We show how inferences are highly sensitive to sample size and the signal to noise ratio in the data. We suggest that analysts use the single equation error correction test for cointegrating relationships, and that caution be used in all cases where near-integration is a reasonable alternative to unit roots. Finally, we suggest that in many cases analysts can drop the language of cointegration and adopt single equation error correction models when the theory of error correction is relevant.

Democracy and Exchange Rates: An Experimental Study
Freeman, John R.
Hays, Jude
Stix, Helmut

Uploaded 07-17-1998
Keywords Markov switching model
exchange rates
comparative democracy
political economy
Abstract The world's financial markets are becoming increasingly liberalized and interconnected. There is much debate about whether this development is socially desirable. Of increasing interest in this debate are the implications of the globalization of finance for democracy. The relationship between the workings of currency markets and democratic institutions is studied. The economic literature on exchange rate determination is briefly reviewed. The Markov switching model is considered as one of the most useful with which to analyze the politics of exchange rate determination. Next, the political science literature is discussed, including the research on electoral systems and comparative democracy. Out of this discussion emerge several competing propositions about how political (re)equilibration affects currency markets, more specifically, what the Markov switching framework should show about the impact of electoral outcomes and political polls on compound returns (the log difference of the exchange rate) in some or all democracies. A design for testing these propositions then is laid out and implemented. The results support the view that democratic politics affects currency markets. In particular, opinion polls about chief executive and government performance have a direct effect on the probabilities of switches between currency regimes. This suggests that these polls cause currency traders to revise their expectations about the stability of governments and (or) the content of public policy. In addition, the results refute claims that pluralist and majoritarian forms of democracy are more likely to be a source of trader uncertainty and hence regime shifts than corporatist and consensual forms of democracy. There is some evidence that (democratic) institutional "incoherency" (Garrett, 1998) is a source of market uncertainty and therefore that the effects of opinion polls and other political variables on the probabilities of regime shifts are greater in the respective countries.

Intrainstitutional Mobility in the Postreform House of Representatives
Wawro, Gregory

Uploaded 08-26-1998
Keywords legislative entrepreneurship
legislative organization
maximum likelihood methods
mobility analysis
career concerns
vacancy competition
Abstract Theory: When deciding whom to promote to prestigious positions within the House, members will favor those individuals who are the most likely to use the resources associated with prestigious positions to produce legislation when there is substantial demand for it. Members will select those individuals who have demonstrated a propensity for engaging in legislative entrepreneurship because they are the most qualified in this regard. Hypothesis: "The job ladders hypothesis": Members who engage in legislative entrepreneurship are more likely to move up the job ladder to prestigious positions within the committee and party hierarchies in the House. Method: I develop measures of legislative entrepreneurship using data on the characteristics of bills sponsored by members and members' testimony before committees. I develop a statistical model that addresses the problems of analyzing intrainstitutional mobility and the problems with assessing entrepreneurial ability. With this model I perform a multivariate analysis to assess the effects of legislative entrepreneurship while accounting for other variables that previous studies have found to affect intrainstitutional mobility. Results: Engaging in legislative entrepreneurship increases the probability that members of the majority party will advance to full committee, subcommittee, and party leadership positions.

Electoral Reform and Legislative Structure: The Effects of Australian Ballot Laws on House Committee Tenure
Katz, Jonathan
Sala, Brian R.

Uploaded 01-01-1995
Keywords congress
personal vote
australian ballot
duration model
Abstract Most scholars agree that members of Congress are strongly motivated by their desire for reelection. This assumption implies that MCs adopt institutions, rules and norms of behavior in part to serve their electoral interests. Direct tests of the electoral connection are rare, however, because significant, exogenous changes in the electoral environment are difficult to identify. In this paper, we develop and test an electoral rationale for the norm of committee tenure, in which returning MCs typically retain their same assignments. We examine tenure patterns before and after a major, exogenous change in the electoral system -- the states' rapid adoption of Australian Ballot laws in the early 1890s. The ballot changes, we argue, induced new ``personal vote'' electoral incentives, which contributed to the adoption of ``modern'' Congressional institutions such as ``property rights'' to committee assignments. We demonstrate that there was a marked increase in assignment stability after 1892, when a majority of states had put the new ballot laws into force -- earlier than previous studies have suggested.

Estimating the Same Quantities from Different Levels of Data: Time Dependence and Aggregation in Event Count Models
King, Gary
Signorino, Curtis S.
Alt, James E.

Uploaded 00-00-0000
Keywords (none submitted)
Abstract Binary, count, and duration data all code for discrete events occurring at points in time. Although a single data generation process can produce any of these three data types, the statistical literature is not very helpful in providing methods to estimate parameters of the same process from each. In fact, only a single theoretical process exists for which known statistical methods can estimate the same parameters --- and it is generally limited to count and duration data. The result is that seemingly trivial decisions about which level of data to use can have important consequences for substantive interpretations. We describe the theoretical event process for which results exist, based on time-independence. We also derive a new set of models for a time-dependent process and compare their predictions to those of a commonly used model. Any hope of avoiding the more serious problems of aggregation bias in events data is contingent on first deriving a much wider arsenal of statistical models and theoretical processes that are not constrained by the particular forms of data that happen to be available.

Bootstrap Methods for Non-nested Hypothesis Tests
Mebane, Walter R.
Sekhon, Jasjeet

Uploaded 07-20-1996
Keywords Cox Test
Endogenous Switching Regression
Tobit-Style Censoring
Abstract Cox (1961; 1962) proposed a fairly general method that can be used to construct powerful tests of alternative hypotheses from separate statistical families. We prove that non-parametric bootstrap methods can produce consistent and second-order correct approximations to the distribution of the Cox statistic for non-nested LISREL-style covariance structure models. We use the method to investigate a question about the specification of a LISREL model used by Kinder, Adams and Gronke (1989). In a second application---a pair of non-nested endogenous switching regression models with tobit-style censoring, applied to real data---we illustrate how bootstrap calibration can be used to correct the size of the test when the test distribution is being estimated by Monte Carlo simulation due to concern about nonregularity.

Estimating the Probability of Events That have Never Occurred: When Does Your Vote Matter?
Gelman, Andrew
King, Gary
Boscardin, John

Uploaded 10-27-1997
Keywords conditional probability
decision analysis
electoral campaigning
political science
presidential elections
rare events
rational choice
subjective probability
voting power
Abstract Researchers sometimes argue that statisticians have little to contribute when few realizations of the process being estimated are observed. We show that this argument is incorrect even in the extreme situation of estimating the probabilities of events so rare that they have never occurred. We show how statistical forecasting models allow us to use empirical data to improve inferences about the probabilities of these events. Our application is estimating the probability that your vote will be decisive in a U.S. presidential election, a problem that has been studied by political scientists for more than two decades. The exact value of this probability is of only minor interest, but the number has important implications for understanding the optimal allocation of campaign resources, whether states and voter groups receive their fair share of attention from prospective presidents, and how formal ``rational choice'' models of voter behavior might be able to explain why people vote at all. We show how the probability of a decisive vote can be estimated empirically from state-level forecasts of the presidential election and illustrate with the example of 1992. Based on generalizations of standard political science forecasting models, we estimate the (prospective) probability of a single vote being decisive as about 1 in 10 million for close national elections such as 1992, varying by about a factor of 10 among states. Our results support the argument that subjective probabilities of many types are best obtained via empirically-based statistical prediction models rather than solely mathematical reasoning. We discuss the implications of our findings for the types of decision analyses that are used in public choice studies.

Heterogeneity and Disperson in the Beta-Binomial Model
Palmquist, Bradley

Uploaded 08-23-1997
Keywords beta-binomial
count models
Abstract Count variables built up from sums of independent and identically distributed (IID) binary random variables can be easily modeled by the binomial distribution. But what happens to sums of binary random variables if they are not IDD? King (1989) and others have presented the Beta Binomial and Extended Beta Binomial distributions as a way of handling the overdispersion that results from heterogeneity. This model seems to work well for some examples such as the distribution of state by state totals like the number of school districts banning a book in a given year. Heterogeneity of book banning rates across states would produce overdispersion (greater variability than expected from a binomial model). But another obvious example, the heterogeneity among Senators in vote counts aggregated by roll call, cannot be directly modeled by the Beta Binomial models in the same way. In the toxicology literature, from which political scientists have borrowed the Beta Binomial models, the heterogeneity observed is across units (``litters"), not within. Under the most reasonable assumptions, heterogeneity among Senators in response probabilities either produces pure Binomial variation in vote counts or contributes to underdispersion from roll call to roll call. These results are shown analytically and by simulation. Then a preliminary analysis of data of this type -- repeated votes on abortion in the Senate from 1974 to 1994 -- is presented.

A Process Control Model of Legislative Productivity: Testing the Effects of Congressional Reform
Gill, Jeff
Thurber, James A.

Uploaded 08-08-1997
Keywords Queueing Theory
Software Simulation
Congressional Reform
Productivity Equilibrium Model
Committee Efficiency
Abstract We examine the effects of congressional reform on legislative productivity using a completely new methodology in political science based on queueing theory and industrial simulation and control software. The foundation of our analysis is the development of a process control model of legislative development. The model establishes a status quo productivity equilibrium based on empirical data from the first 100 days of the $103^{rd}$ House of Representatives, then stresses the system using the mandated productivity of the first 100 days of the $104^{th}$ House of Representatives. We compare the agenda based distribution of bill assignments from the ``Contract with America'' with a uniform assignment and find that requiring a stable legislative system to greatly increase productivity has substantial effects on members' allocation of time. In particular, members are likely to reduce time considering legislation and increasingly rely upon partisan cues for vote decisions. The methodology is sufficiently general that it can be applied to almost any legislative setting. Our application focuses on the feedback response from an electoral shift, but the methodology can address any productivity question. Since all legislative bodies have defined processes by which initiatives flow, the modeling and simulating of these processes can illuminate efficiencies and inefficiencies. Queueing theory addresses the prevalent and generalizable scenario in which demand for legislative outcomes exceeds the short-term capacity of a legislative system.

Pattern Recognition of International Crises using Hidden Markov Models
Schrodt, Philip A.

Uploaded 06-30-1997
Keywords hidden Markov models
event data
early warning
international crisis
sequence analysis
Middle East
Abstract Event data are one of the most widely used indicators in quantitative international relations research. To date, most of the models using event data have constructed numerical indicators based on the characteristics of the events measured in isolation and then aggregated. An alternative approach is to use quantitative pattern recognition techniques to compare an existing sequence of behaviors to a set of similar historical cases. This has much in common with human reasoning by historical analogy while providing the advantages of systematic and replicable analysis possible using machine-coded event data and statistical models. This chapter uses "hidden Markov models" Ñ- a recently developed sequence- comparison technique widely used in computational speech recognition Ñ- to measure similarities among international crises. The models are first estimated using the Behavioral Correlates of War data set of historical crises, then applied to an event data set covering political behavior in the contemporary Middle East for the period April 1979 through February 1997. A split-sample test of the hidden Markov models perfectly differentiates crises involving war from those not involving war in the cases used to estimate the models. The models also provide a high level of discrimination in a set of test cases not used in the estimated, and most of the erroneously-classified cases have plausible distinguishing features. The difference between the war and nonwar models also correlates significantly with a scaled measure of conflict in the contemporary Middle East. This suggests that hidden Markov models could be used to develop conflict measures based on event similarities to historical conflicts rather than on aggregated event scores.

A Simulated Maximum Likelihood application to the 1988 Democratic Primary
Lawrence, Eric D.

Uploaded 03-28-1997
Keywords simulated maximum likelihood
multinomial probit
vote choice models
Abstract The multinomial probit model has some appealing advantages over models that do not allow for correlated errors, such as multinomial logit and conditional logit. With a few exceptions, however, multinomial probit models have not been estimated for vote choice models because of the computational costs inherent in evaluating high dimensional integrals. This paper explains one recently developed approach, simulated maximum likelihood combined with the GHK simulator, that makes it feasible to accurately estimate multinomial probit models. The method is demonstrated on a model of the 1988 Democratic Super Tuesday primary.

Treatment Spillover Effects Across Survey Experiments
Lee, Daniel
Transue, John
Aldrich, John

Uploaded 04-05-2005
Keywords survey experiments
survey methods
Abstract Embedding experiments within surveys has reinvigorated survey research in general and especially in political science. These designs use random assignment to create true experiments within (typically nationally) representative sample surveys. Thus, they combine the internal validity of experiments with the external validity of national surveys. We investigate whether experimental treatments spill over and effect later experiments in an unintended manner. Using the 1991 Race and Politics survey, we find evidence of experimental spillover. Specifically we find that experiments at the beginning of a survey influence later experiments. We also find (much less) evidence of adjacent experiments affecting subsequent experiments. The paper concludes with a discussion of designs for future research that could aid our understanding of experimental spillover.

Unemployment and Violence in Northern Ireland: a missing data model for ecological inference
Honaker, James

Uploaded 07-19-2005
Keywords Multiple Imputation
Ecological Inference
Count Data
Political Violence
Abstract Contrary to the body of literature in political violence, and the rhetoric of many parties of the conflict, time-series models of ``the troubles'' in Northern Ireland by White (1993) and Thompson (1989) have found no evidence that economic conditions effect the intensity, sources or direction of violence. I show that several methodological flaws exist in previous models. They fail to address the discrete, count nature of the data, the contagion present from aggregation over time, pooling issues from different types of violence, and the over dispersal of deaths. However, the key problem, acknowledged even by the authors themselves, is that all measures of unemployment aggregate Protestant and Catholic unemployment rates into one single measure. Using a model that combines methods of Multiple Imputation to recover missing data (King Honaker Joseph Scheve 2001) and the literature of models for Ecological Inference problems (especially King 1997) I estimate the disaggregated unemployment rates by religion from the available data. Unemployment is shown to be a leading cause of the violence by Republican factions in Northern Ireland.

Democracy as a Latent Variable
Treier, Shawn
Jackman, Simon

Uploaded 07-16-2003
Keywords democracy
latent variables
Bayesian statistics
item-response model
ordinal data
latent class analysis
democratic peace
Markov chain Monte Carlo
Abstract Measurement is critical to the social scientific enterprise. Many key concepts in social-scientific theories are not observed directly, and researchers rely on assumptions (tacitly or explicitly, via formal measurement models) to operationalize these concepts in empirical work. In this paper we apply formal, statistical measurement models to the Polity indicators of democracy and autocracy, used widely in studies of international relations. In so doing, we make explicit the hitherto implicit assumptions underlying scales built using the Polity indicators. We discuss two models: one in which democracy is operationalized as a latent continuous variable, and another in which democracy is operationalized as a latent class. Our modeling approaches allow us to assess the measurement error in the resulting measure of democracy. We show that this measurement error is considerable, and has substantive consequences when using a measure of democracy as an independent variable in cross-national statistical analysis. Our analysis suggests that skepticism as to the precision of the Polity democracy scale is well-founded, and that many researchers have been overly sanguine about the properties of the Polity democracy scale in applied statistical work.

A State-Space Approach to Economic Popularity Functions
Pickup, Mark

Uploaded 07-11-2006
Abstract Economic popularity functions are central to the debate over whether voters use evaluations of the economy in their decision to support their government or not. This is of particular importance to the key democratic principle of electoral accountability that parties in power should and are held accountable for the outcomes of their actions and policies through the electoral process. Given the evidence from many nations that the economy is an issue of importance to the electorate, which they believe the government has control over, the inconsistent findings with regards to the impact of the economy on party popularity has made conclusive evaluations of the principle of electoral accountability elusive. This study demonstrates that the difficulty lies in a series of methodological flaws found in current approaches to developing popularity functions. Most analysts using public opinion time-series data have not applied the necessary methods to take into account the problems which such data can pose – problems such as complex error structures, shifting and compound non-stationary dynamics and noisy data. Accordingly, this study explicates a state-space Bayesian approach that addresses these methodological issues. In doing so, it outlines a technique that may be applied to a wide range of public opinion dynamic modelling issues.

Designing and Analyzing Randomized Experiments
Horiuchi, Yusaku
Imai, Kosuke
Taniguchi, Naoko

Uploaded 07-05-2005
Keywords Bayesian inference
causal inference
randomized block design
Abstract In this paper, we demonstrate how to effectively design and analyze randomized experiments, which are becoming increasingly common in political science research. Randomized experiments provide researchers with an opportunity to obtain unbiased estimates of causal effects because the randomization of treatment guarantees that the treatment and control groups are on average equal in both observed and unobserved characteristics. Even in randomized experiments, however, complications can arise. In political science experiments, researchers often cannot force subjects to comply with treatment assignment or to provide the information necessary for the estimation of causal effects. Building on the recent statistical literature, we show how to make statistical adjustments for these noncompliance and nonresponse problems when analyzing randomized experiments. We also demonstrate how to design randomized experiments so that the potential impact of such complications is minimized.

Bayesian and Likelihood Inference for 2 x 2 Ecological Tables: An Incomplete Data Approach
Imai, Kosuke
Lu, Ying
Strauss, Aaron

Uploaded 12-16-2006
Keywords Coarse data
Contextual effects
Data augmentation
EM algorithm
Missing information principle
Nonparametric Bayesian Modeling.
Abstract Ecological inference is a statistical problem where aggregate-level data are used to make inferences about individual-level behavior. Recent years have witnessed resurgent interest in ecological inference among political methodologists and statisticians. In this paper, we conduct a theoretical and empirical study of Bayesian and likelihood inference for 2 x 2 ecological tables by applying the general statistical framework of incomplete data. We first show that the ecological inference problem can be decomposed into three factors: distributional effects which address the possible misspecification of parametric modeling assumptions about the unknown distribution of missing data, contextual effects which represent the possible correlation between missing data and observed variables, and aggregation effects which are directly related to the loss of information caused by data aggregation. We then examine how these three factors affect inference and offer new statistical methods to address each of them. To deal with distributional effects, we propose a nonparametric Bayesian model based on a Dirichlet process prior which relaxes common parametric assumptions. We also specify the statistical adjustments necessary to account for contextual effects. Finally, while little can be done to cope with aggregation effects, we offer a method to quantify the magnitude of such effects in order to formally assess its severity. We use simulated and real data sets to empirically investigate the consequences of these three factors and to evaluate the performance of our proposed methods. C code, along with an easy-to-use R interface, is publicly available for implementing our proposed methods.

Modeling Foreign Direct Investment as a Longitudinal Social Network
Jensen, Nathan
Martin, Andrew
Westveld, Anton

Uploaded 07-13-2007
Keywords foreign direct investment
social network data
longitudinal data
hierarchical modeling
mixture modeling
Bayesian inference.
Abstract An extensive literature in international and comparative political economy has focused on the how the mobility of capital affects the ability of governments to tax and regulate firms. The conventional wisdom holds that governments are in competition with each other to attract foreign direct investment (FDI). Nation-states observe the fiscal and regulatory decisions of competitor governments, and are forced to either respond with policy changes or risk losing foreign direct investment, along with the politically salient jobs that come with these investments. The political economy of FDI suggests a network of investments with complicated dependencies. We propose an empirical strategy for modeling investment patterns in 24 advanced industrialized countries from 1985-2000. Using bilateral FDI data we estimate how increases in flows of FDI affect the flows of FDI in other countries. Our statistical model is based on the methodology developed by Westveld & Hoff (2007). The model allows the temporal examination of each notion's activity level in investing, attractiveness to investors, and reciprocity between pairs of nations. We extend the model by treating the reported inflow and outflow data as independent replicates of the true value and allowing for a mixture model for the fixed effects portion of the network model. Using a fully Bayesian approach, we also impute missing data within the MCMC algorithm used to fit the model.

Misunderstandings among Experimentalists and Observationalists about Causal Inference
Imai, Kosuke
King, Gary
Stuart, Elizabeth

Uploaded 09-16-2007
Keywords matching
causal inference
experimental design
observational studies
average treatment effects
covariate balance
field experiments
survey experiments
Abstract We attempt to clarify, and suggest how to avoid, several serious misunderstandings about and fallacies of causal inference in experimental and observational research. These issues concern some of the most basic advantages and disadvantages of each basic research design. Problems include improper use of hypothesis tests for covariate balance between the treated and control groups, and the consequences of using randomization, blocking before randomization, and matching after treatment assignment to achieve covariate balance. Applied researchers in a wide range of scientific disciplines seem to fall prey to one or more of these fallacies, and as a result make suboptimal design or analysis choices. To clarify these points, we derive a new four-part decomposition of the key estimation errors in making causal inferences. We then show how this decomposition can help scholars from different experimental and observational research traditions better understand each other's inferential problems and attempted solutions. (This paper is forthcoming in the Journal of the Royal Statistical Society, but we have some time for revisions and would value any comments anyone might have. This is a revised and much more general version of an earlier paper, "The Balance Test Fallacy in Causal Inference".)

Teaching Bayesian applied statistics to graduate students in political science, sociology, public health, education, economics, ...
Gelman, Andrew

Uploaded 06-13-2008
Keywords Bayesian statistics
Abstract I share some thoughts on teaching applied regression and Bayesian methods to students in political science and other fields.

Research Opportunities - The 2009/10 British Election Study
Clarke, Harold
Sanders, David
Stewart, Marianne
Whiteley, Paul

Uploaded 07-07-2008
Keywords electons
public opinion
Abstract The 2009/10 British Election Study (BES) will include significant research opportunities for students of voting, elections and public opinion. The BES will have three major components: (a) in-person pre-post election surveys; (b) rolling campaign internet panel survey (RCPS); (c) 48 inter-election monthly continuous monitoring surveys (CMS) with annual panel components. Each CMS survey will offer researchers opportunities to include question batteries including experiments. Participation is free and data release is very fast. Proposals for research modules reviewed by BES Advisory Board and P.I.s. Proposals also entertained for research modules on core and RCPS components.

Understanding Wordscores
Lowe, Will

Uploaded 04-25-2007
Keywords content analysis
ideal point
item response theory
Abstract Wordscores is a widely-used procedure for inferring policy positions, or scores, for new documents on the basis of scores for words derived from documents with known scores. It is computationally straightforward, requires no distributional assumptions, but has unresolved practical and theoretical problems: In applications, estimated document scores are on the wrong scale and Wordscores does not specify a statistical model so it is unclear what assumptions the method makes about political text or how to tell whether they fit particular applications. The first part of the paper demonstrates that badly scaled document score estimates reflect deeper problems with the method. The second part shows how to understand Wordscores as an approximation to correspondence analysis which itself approximates a statistical ideal point model for words. Problems with the method are identified with the conditions under which these layers of approximation fail to ensure consistent and unbiased estimation of the parameters of the ideal point model.

Bayesian Combination of State Polls and Election Forecasts
Lock, Kari
Gelman, Andrew

Uploaded 09-21-2008
Keywords election prediction
pre-election polls
Bayesian updating
shrinkage estimation
Abstract In February of 2008, SurveyUSA polled 600 people in each state and asked who they would vote for in either head-to-head match-up: Obama vs. McCain, and Clinton vs. McCain. Here we integrate these polls with prior information; how each state voted in comparison to the national outcome in the 2004 election. We use Bayesian methods to merge prior and poll data, weighting each by its respective information. The variance for our poll data incorporates both sampling variability and variability due to time before the election, estimated using pre-election poll data from the 2000 and 2004 elections. The variance for our prior data is estimated using the results of the past nine presidential elections. The union of prior and poll data results in a posterior distribution predicting how each state will vote, in turn giving us posterior intervals for both the popular and electoral vote outcomes of the 2008 presidential election. Lastly, these posterior distributions are updated with the most recent poll data as of August, 2008.

Measuring the Effects of Voter Confidence on Political Participation
Levin, Ines
Alvarez, R. Michael

Uploaded 06-22-2009
Keywords voter confidence
causal effects
Abstract In this paper we study the causal effect of voter confidence on participation decisions in the 2006 Mexican Election. Previous research has shown that voter confidence was a relevant factor in explaining participation during the years of the PRI hegemony. An open question is whether this relationship is still significant after the democratic transition taking place in the years 1997-2000. Moreover, in the previous literature, this problem was studied in a regression framework. In this article we argue that, since voter confidence and participation decisions are affected by similar covariates, a regression approach may lead to results which are too model dependent, and do not account for the heterogeneity of effects across voters. To solve this problem, we use matching methods, and find that voter confidence has considerable effects on participation decisions, but substantially different in magnitude from those found using the usual regression approach.

Competing Solutions to the Principal-Agent Model
Haptonstahl, Stephen

Uploaded 07-23-2009
Keywords bargaining
risk aversion
quantal response equilibrium
strategic statistical model
random utility
Abstract Principal-Agent (PA) theory has been used for over three decades to model the relationship between an information-advantaged Agent and a Principal able to issue a contract ultimatum. For its common implementation as a game, the subgame-perfect Nash equilibrium is reasonably simple but generally wrong in predicting experimental or observational data. This paper implements PA theory theoretically and statistically as two kinds of strategic statistical model, then develops methods for testing competing behavioral hypotheses. I show that subgame-perfect Nash equilibrium, risk aversion/affinity, distributive justice/fairness theories, agent error, and random utility can be observationally distinct and how they might be distinguished statistically.

New Empirical Strategies to Model the Government Formation Process
Glasgow, Garrett
Golder, Matt
Golder, Sona

Uploaded 07-15-2010
Keywords discrete choice
mixed logit
random coefficients
government formation
Abstract Over the past decade, a "standard approach" to the quantitative study of government formation has developed. This approach involves the use of a conditional (CL) logit model to examine government choice with the government formation opportunity as the unit of analysis. In this paper, we reconsider this approach and make three methodological contributions. First, we demonstrate that the existing procedure used to test for the independence of irrelevant alternatives (IIA) is flawed and severely biased against finding IIA violations. Our new testing procedure reveals that many government alternatives share unobserved attributes, thereby violating the IIA assumption and making the CL model inappropriate. Second, we employ a mixed logit with random coefficients that allows us to take account of unobserved heterogeneity and IIA violations. Third, we return to a question that originally motivated this literature, namely, what determines the likelihood that a particular party enters government? Although scholars have generally abandoned this question due to perceived methodological limitations in our ability to address it, we demonstrate that calculating probabilities for parties entering office rather than governments is straightforward in a mixed logit framework.

Bayesian Methods: A Social and Behavioral Sciences Approach, ANSWER KEY TO THE SECOND EDITION. Odd Numbers.
Park, Hong Min
Gill, Jeff

Uploaded 09-14-2010
Keywords Bayes
Bayesian inference
Bayes Factor
Markov chain
Monte Carlo
hierarchical models
Abstract This is the odd-numbered exercise answers to the second edition of Bayesian Methods: A Social and Behavioral Sciences Approach (minus Chapter 13). Course Instructors can get the full set from Chapman & Hall/CRC upon request.

How Robust Standard Errors Expose Methodological Problems They Do Not Fix
King, Gary
Roberts, Margaret

Uploaded 07-13-2012
Keywords robust standard errors
clustered standard errors
heteroskedasticity-consistent standard errors
Abstract "Robust standard errors'' are used in a vast array of scholarship across all fields of empirical political science and most other social science disciplines. The popularity of this procedure stems from the fact that estimators of certain quantities in some models can be consistently estimated even under particular types of misspecification; and although classical standard errors are inconsistent in these situations, robust standard errors can sometimes be consistent. However, in applications where misspecification is bad enough to make classical and robust standard errors diverge, assuming that misspecification is nevertheless not so bad as to bias everything else requires considerable optimism. And even if the optimism is warranted, we show that settling for a misspecified model (even with robust standard errors) can be a big mistake, in that all but a few quantities of interest will be impossible to estimate (or simulate) from the model without bias. We suggest a different practice: Recognize that differences between robust and classical standard errors are like canaries in the coal mine, providing clear indications that your model is misspecified and your inferences are likely biased. At that point, it is often straightforward to use some of the numerous and venerable model checking diagnostics to locate the source of the problem, and then modern approaches to choosing a better model. With a variety of real examples, we demonstrate that following these procedures can drastically reduce biases, improve statistical inferences, and change substantive conclusions.

Conservative Vote Probabilities: An Easier Method for the Analysis of Roll Call Data
Fowler, Anthony
Hall, Andrew B.

Uploaded 08-08-2012
Keywords Roll Call
Supreme Court
State Legislatures
Abstract We propose a new roll-call scaling method based on OLS which is easier to implement and understand than previous methods and also produces directly interpretable estimates. This measure, Conservative Vote Probability (CVP), indicates the probability that an individual legislator votes "conservatively" relative to the median legislator. CVP is a flexible non-parametric statistical technique that requires no complicated assumptions but still produces legislator scalings that correlate with previous roll call methods at extremely high levels. In this paper we introduce the methodology behind CVP and off er several substantive examples to demonstrate its e efficacy as an easier, more accessible alternative to previous roll call methods.

How Legislators Respond to Localized Economic Shocks
Feigenbaum, James
Hall, Andrew B.

Uploaded 01-26-2014
Keywords congress
roll-call voting
economic conditions
Abstract We explore the effects of localized economic shocks from trade on roll-call behavior and electoral outcomes in the U.S. House, 1990--2010. We demonstrate that economic shocks from Chinese import competition---first studied by Autor, Dorn, and Hanson (2013a)---cause legislators to vote in the more protectionist direction on trade bills but cause no change in their voting on all other bills. At the same time, these shocks have no effect on the reelection rates of incumbents, the probability an incumbent faces a primary challenge, or the partisan control of the district. Though changes in economic conditions are likely to cause electoral turnover in many cases, incumbents exposed to negative economic shocks from trade appear able to fend off these effects in equilibrium by taking strategic positions on foreign-trade bills. In line with this view, we find that the effect on roll-call voting is strongest in districts where incumbents are most threatened, electorally. Taken together, these results paint a picture of responsive incumbents who tailor their roll-call positions on trade bills to the economic conditions in their districts.

Shaken, Not Stirred: Evidence on Ballot Order Effects from the California Alphabet Lottery, 1978 - 2002
Ho, Daniel E.
Imai, Kosuke

Uploaded 02-02-2004
Keywords ballots
causal inference
natural experiment
fisher test
partisan cue
Abstract We analyze a natural experiment to answer the longstanding question of whether the name order of candidates on ballots affects election outcomes. Since 1975, California law has mandated randomizing the ballot order with a lottery, where alphabet letters would be shaken vigorously and selected from a container. Previous studies, relying overwhelmingly on non-randomized data, have yielded conflicting results about whether ballot order effects even exist. Using improved statistical methods, our analysis of statewide elections from 1978 to 2002 reveals that in general elections ballot order has a significant impact only on minor party candidates and candidates for nonpartisan offices. In primaries, however, being listed first benefits everyone. In fact, ballot order might have changed the winner in roughly nine percent of all primary races examined. These results are largely consistent with a theory of partisan cuing. We propose that all electoral jurisdictions randomize ballot order to minimize ballot effects.

Empirical Modeling Strategies for Spatial Interdependence: Omitted-Variable vs. Simultaneity Biases
Hays, Jude
Franzese, Robert

Uploaded 07-24-2004
Keywords Spatial Lag Models
Omitted Variable Bias
Simultaneity Bias
Abstract Scholars recognize that time-series-cross-section data typically correlate across time and space, yet they tend to model temporal dependence directly while addressing spatial interdependence solely as nuisance to be “corrected” (FGLS) or to which to be “robust” (PCSE). We demonstrate that directly modeling spatial interdependence is methodologically superior, offering efficiency gains and generally helping avoid biased estimates even of “non-spatial” effects. We first specify empirical models representing two modern approaches to comparative and international political economy: (context-conditional) open-economy comparative political-economy (i.e., common stimuli, varying responses) and international political-economy, which implies interdependence (plus closed-economy and orthogonal-open-economy predecessors). Then we evaluate four estimators—non-spatial OLS, spatial OLS, spatial 2SLS-IV, and spatial ML—for analyzing such models in spatially interdependent data. Non-spatial OLS suffers from potentially severe omitted-variable bias, tending to inflate estimates of common-stimuli effects especially. Spatial OLS, which specifies interdependence directly via spatial lags, dramatically improves estimates but suffers a simultaneity bias, which can be appreciable under strong interdependence. Spatial 2SLS-IV, which instruments for spatial lags of dependent variables with spatial lags of independent variables, yields unbiased and reasonably efficient estimates of both common-stimuli and diffusion effects, when its conditions hold: large samples and fully exogenous instruments. A tradeoff thus arises in practice between biased-but-efficient spatial OLS and consistent- (or, at least, less-biased-) but-inefficient spatial 2SLS-IV. Spatial ML produces good estimates of non-spatial effects under all conditions but is computationally demanding and tends to underestimate the strength of interdependence, appreciably so in small-N samples and when the true diffusion-strength is modest. We also explore the standard-error estimates from these four procedures, finding sizable inaccuracies by each estimator under differing conditions, and PCSE’s do not necessarily reduce these inaccuracies. By an accuracy-of-reported-standard-errors criterion, 2SLS-IV seems to dominate. Finally, we explore the spatial 2SLS-IV estimator under varying patterns of interdependence and endogeneity, finding that its estimates of diffusion strength suffer only when a condition we call cross-spatial endogeneity, wherein dependent variables (y’s) in some units cause explanatory variables (x’s) in others, prevails.

Negotiated Compliance: Social Solutions to the 'Principal's Problem'
Whitford, Andrew B.
Miller, Gary J.
Bottom, William P.

Uploaded 07-11-2003
Keywords principal-agency theory
hierarchical logit
Abstract Principal-agency theory has typically analyzed the principal's problem1: how to write a contract with incentives that will induce an agent to provide the principal with the maximum feasible expected gain. In practice, principal-agent contracts are typically negotiated, not imposed. Experiments indicate that agent compliance is determined less by the negotiated terms of the contract than by expectations created by the negotiation process itself. We interpret this as justification for a renewed interest in the politics of negotiation and bureaucratic politics.

Designing Tests of the Supreme Court and the Separation of Powers
Sala, Brian R.
Spriggs II, James F.

Uploaded 09-13-2002
Keywords spatial voting theory
strategic behavior
Supreme Court
Abstract While "rational choice" models of Supreme Court decision making have enhanced our appreciation for the separation of powers built into the Madisonian Constitutional design, convincing empirical support for a separation-of-powers (SOP) constraint on justices' behavior has been elusive. We apply a standard spatial voting model to identify circumstances in which "Attitudinalist" and SOP predictions about justices' behavior diverge. Our reconsideration of the theory indicates that prior efforts to test quantitatively the two models have been biased by having included cases for which the two models' predictions do not differ. While our more focused test offers a fairer test of the SOP constraint, the results strongly reject the SOP model. Nonetheless, our analysis provides leverage on this issue by: (1) delineating and executing necessary research design protocols for crafting a critical test of the SOP model; and (2) rejecting the two exogenously fixed alternative SOP model and suggesting avenues for future research.

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