Guy D. Whitten

Cross-national analyses of economic voting

Abstract The present paper replicates and extends Powell and Whittens study of comparative economic voting (Powell, G. Bingham and Whitten, Guy D. (1993) A Cross-National Analysis of Economic Voting: Taking Account of the Political Context. American Journal of Political Science 37 , 391–414). We extend Powell and Whittens research in three ways. First, we have developed a theoretically more appealing method for dividing our cases according to the clarity of government responsibility. Second, we consider whether the electoral effect of economic growth varies with government composition, with large coalitions focusing on the consensual goal of improving economic growth. Third, 40 new cases have been added to the original 102 analyzed by Powell and Whitten. Using a more appropriate methodology and an expanded data set, we find strong confirmation of the results presented in Powell and Whittens study. We also find evidence that supports our theory about coalition governments and economic growth.

Heightening comparativists concern for model choice: voting behavior in Great Britain and the Netherlands

As the research methodology more closely approximates the causal process being analyzed, the inferences and predictions derived from that methodology will better represent actual behavior. Statistical models were specified on the basis of accepted theories of voting behavior and political cleavages in the Netherlands and Great Britain. We hypothesize that multinomial models provide a more accurate characterization of voting behavior in countries with more than two political parties competing for votes. Binomial logit, multinomial logit, and nested multinomial logit models of voting behavior are estimated on Dutch and British National Election Study data. Compared to binomial methods, we find that multinomial models of voting behavior produce results that are more congruent with accepted theories of Dutch and British politics.

Government competence, economic performance and endogenous election dates

Abstract Empirical research in comparative politics has largely demonstrated that favorable economic conditions improve the electoral fortunes of incumbent government parties. Thus, in parliamentary democracies in which the government can choose when to call an election there is an incentive for government parties to act strategically by calling early elections when economic conditions are favorable. Alesina, Cohen and Roubini, however, cast doubt on this proposition, finding only weak evidence of a relationship between economic factors and election timing. In this paper, we reconsider the relationship between economic conditions and endogenous election dates using new data, controlling for political factors, and applying more appropriate econometric techniques. From analyses of twelve parliamentary democracies, we find that macroeconomic performance and political context exert significant influence on election timing. All other factors being equal, better performances in terms of economic growth, inflation, and unemployment will make a government more likely to call an early election. Controlling for government ideology, we find that right-wing governments are more sensitive to inflation performance while left-wing governments are more sensitive to the level of unemployment.

The Electoral Impact of Unexpected Inflation and Economic Growth

This article supports two theoretical changes to models of comparative economic voting. The first is that the distinction between expected and unexpected components of inflation and economic growth is important. We posit that voters are primarily concerned with unexpected inflation and unexpected growth since these changes have real income effects and serve as better indicators of government competence. Empirical analyses of data from nineteen industrialized nations in 1970–94 reveal stronger electoral effects for the unexpected components of inflation and growth than for their overall levels. The second innovation is the relaxation of the assumption of homoscedasticity, which led to the finding that the relationship between economic factors and incumbent vote has become more volatile over time and is less volatile when policy-making responsibility is more obscured.

The Two Faces of Tactical Voting

In a recent Note we investigated the incidence of tactical voting in the British election of 1987. A major hypothesis was that in situations where it made sense (i.e., in which voters preferred a party that was a long way from contention, so that a vote for that party was likely to be ‘wasted’), tactical voting would be much more frequent than had hitherto been assumed. We discovered that this was indeed the case; in what we called ‘objectively tactical situations’, tactical voting was as high as 25 per cent or more in the general case, rising to more than 50 per cent among highly educated weak partisans who had strong negative feelings about the winning party. In the process, however, we discovered what appeared to be an anomaly in need of further exploration.

But Wait, There’s More! Maximizing Substantive Inferences from TSCS Models

Political scientists rarely take full advantage of the substantive inferences that they can draw from time-series cross-section data. Most studies have emphasized statistical significance and other standard inferences that can be drawn from single coefficients over one time period. We show that by simulating the quantities of interest over longer periods of time and across theoretically interesting scenarios, we can draw much richer inferences. In this article, we present a technique that produces graphs of dynamic simulations of relationships over time. Graphical simulations are useful because they represent long-term relationships between key variables and allow for examination of the impact of exogenous and/or endogenous shocks. We demonstrate the technique’s utility by graphically representing key relationships from two different works. We also present a preliminary version of the dynsim command, which we have designed to extend the Clarify commands in order to produce dynamic simulations.

People Who Live in Glass Houses: A Response to Evans and Heath's Critique of our Note on Tactical Voting

In a recent Research Note, Evans and Heath cast doubt on the validity of our measure of tactical voting. We and our critics agree on a set of ‘Main reason’ tactical voters – those who said they voted tactically in response to the question, ‘What comes closest to the main reason you voted the way you did?’ Unlike our critics, we reasoned that many of those who cast a tactical vote would not be identified so simply. Some respondents may have been reluctant to say they had voted for other than the best party. Others may have convinced themselves that the ‘best’ party was one that had a chance of winning and therefore answered in such a way as to place themselves squarely among non-tactical voters even though in other tactical circumstances they would have voted differently. Consequently, we sought to identify tactical behaviour through additional questions. Our final measure of tactical voting can be regarded as containing two components: the ‘main reason’ voters, who expressly told interviewers they voted for one party while ‘really preferring’ some other party, and ‘Other reason’ voters, whom we identified as tactical by their responses to additional questions. It is the ‘Other reason’ voters who are at issue.

The effects of immigration and integration on European budgetary trade-offs

ABSTRACT What affects government policy-making continues to be an important question for researchers interested in political competition and policy priorities. In this contribution, we bring together a theoretical framework that focuses on the influence of globalizing forces on government policy decisions with a methodological emphasis on explaining dynamic budgetary trade-offs. While comparative public policy and budgetary scholars typically have focused on entire budgets or amounts spent on specific policies, we look at the political priorities embedded in budgets by modeling the budget as a pie. Then, we theorize about how governments respond to external shocks by altering the allocations to the various policy areas. Using this approach, we find that governments of different ideological types react to external shocks by altering their different policy priorities.

‘Introduction: Political Budgeting from a Comparative Perspective’

ABSTRACT Research on budgeting has taken various theoretical and methodological approaches, and these differences have prevented scholars using these various approaches from discussing their common topic. In this collection, we have gathered a group of prominent scholars to explore the intermingling of budgets and politics from an assortment of theoretical and methodological perspectives. This culminated in a collection that highlights not only the breadth of current research but also the range of what remains underexplored.

The Fundamentals of Political Science Research: Descriptive Statistics and Graphs

OVERVIEW Descriptive statistics and descriptive graphs are what they sound like – they are tools that describe variables. These tools are valuable, because they can summarize a tremendous amount of information in a succinct fashion. In this chapter we discuss some of the most commonly used descriptive statistics and graphs, how we should interpret them, how we should use them, and their limitations. KNOW YOUR DATA In Chapter 5 we discussed the measurement of variables. A lot of thought and effort goes into the measurement of individual variables. Once measurement has been conducted, it is important for the researcher to get a good idea of the types of values that the individual variables take on before moving to testing for causal connections between two or more variables. What do “typical” values for a variable look like? How tightly clustered (or widely dispersed) are the these values? Before proceeding to test for theorized relationships between two or more variables, it is essential understand the properties and characteristics of each variable. To put it differently, we want to learn something about what the values of each variable “look like.” How do we accomplish this? One possibility is to list all of the observed values of a measured variable.