Herein I propose a moratorium on the use of the word “simple” immediately preceding the word “model” in any communication, written or verbal, between and among political scientists.

When compiling data for the article “Small Spaces for Different Faces: Political Science Scholarship on Asian Pacific Americans” (July 2004 PS), I inadvertently omitted the numbers for one issue of Social Science Quarterly. The omission does not change any of the rankings, but it does alter some figures slightly. The correct numbers for the affected totals are as follows:

Jo Michelle Beld's article on child support guidelines defends the efforts of the Minnesota Child Support Enforcement Division to maintain the state's formula for determining child support award amounts (2003). She responds to long-standing criticism, in this instance conveyed by Stephen Baskerville, that the child support enforcement community, which has a financial interest in child support amounts, exercises unchecked authority through the forced use of guidelines, and that as a result, child support awards are arbitrarily high (2002).

The names of the co-authors of the track three summary were inadvertently omitted in publication. Along with John Ishiyama, the authors of this summary include Thomas Baldino, Wilkes University; Bruce Caswell, Rowan University; Maqsood Choudary, Delta College; Michelle Deardorff, Jackson State University; Scott Erb, University of Maine, Farmington; Kerstin Hamann, University of Central Florida; Suzan Harkness, University of the District of Columbia; Richard Holtzman, University of Texas, Austin; Mariya Omelicheva, Purdue University; Candace Young, Truman State University.

This symposium presents seven presidential election forecasting models and their predictions of the popular two-party vote in the 2004 election. The modern age of election forecasting is now into its third decade. Models have been tested quite publicly in the heat of battle—with some doing well, others not quite so well, and still others making way for new models. In this introduction, I provide a brief overview of the models, a summary of this year's forecasts, and some thoughts about how the forecasts should be judged.

Yogi Berra might have said it: the best predictor of an election is, well, an election. Not a trial-heat conducted by opinion polls, but a real election of voters going to the polls. In the U.S., at least, what is known as a “general” election is preceded by a “primary” election, and that has been the case for presidential contests since 1912. So is the voting in presidential primaries a leading indicator of the vote in November? Remarkably so, as it turns out. How well presidential candidates do in primary elections foretells their prospects in the November election with great accuracy. What is more, the use of primaries as a vote predictor makes it possible to include in the forecast model both the candidate of the incumbent party and the candidate of the party out of the White House. The forecast for 2004 uses candidate vote shares in primaries, not just a win-lose dichotomy as done in the model used to predict the vote in 2000 (Norpoth 2001).

Forecasting provides the opportunity to put one's self to the test. Are our models of voting behavior accurate? It is easy to retrofit an explanation for what has happened in the past. Taking a chance on a forecast that can go wrong does not afford us that luxury. Forecasting can also teach a lesson in humility. Over the last decade, political scientists have been willing to gamble on their models. We have had some success. Everyone on the forecasting panel at the 1996 APSA Annual Meeting correctly forecast a Clinton victory. The forecasting of the 2000 presidential election was clearly a lesson in humility (at least for this author). None of the authors of this symposium forecast a Bush victory. Moreover, many forecast a rather substantial victory for Al Gore.

Despite mediocre approval ratings and below average economic growth, George W. Bush has a good chance of winning a second term in the White House according to the time-forchange forecasting model.

As the experience of 2000 shows, forecasting presidential elections is an inexact science. Everybody knows that “the economy” matters, but simple projection from economic conditions at the time of the forecast is not enough. And the most important economic shocks to the economy are the late shocks, which may arrive too late to be measured by the forecaster. Other events also impact, such as (in 2004) the Iraq war. Incorporating presidential approval into the model helps to control for “other” events that economic indicators ignore, but obviously only those that are observable by the time of the latest approval reading. They also don't reveal much about voters' comparative judgments of the two candidates. Of course one can forecast the presidential race from trial-heat polls available at the moment rather than trying to capture the fundamentals that will matter on Election Day. But the whole purpose of forecasting is to present information about the voters' future behavior that is not yet evident in the trialheat polls. Besides, early polls only tell us little about the final election outcome.

During spring 2000, we released to the press a preliminary forecast of a Gore victory. Indeed, one of us, in a widely-read quotation, declared, “It's not even going to be close” (Washington Post, May 26, 2000, p. 1). We were wrong, as were all of our fellow modelers. Indeed, among “five of the best forecasters” identified by Robert Kaiser (Washington Post, May 26, 2000, p. 1), the Gore projection ranged from 53% to 60% of the two-party popular vote, pointing to a Democratic landslide. Such gross error raises the question: Should the models be junked? Some journalists, pundits, and scholars have suggested the answer is “yes.” We disagree. Remember that forecasters of all stripes—modelers, pollsters, marketers, campaign experts—failed to call 2000. (See the review of 49 forecasts, from multiple and international sources, in Lafay and Lewis-Beck 2000). The virtually total inability to predict the Bush-Gore result also reminds us that no model will ever be perfect, that electoral behavior can never be fully determined. Still, while falling short of perfection, we believe that modeling can be improved.

The forecasting model presented here is a revised version of a model developed prior to the 1996 election (Holbrook 1996) and is essentially a referendum model. The original model regressed the incumbent party percent of the two-party vote on presidential popularity, an aggregate measure of satisfaction with personal finances, and a dummy variable coded “1” for years in which the incumbent party had held the White House for at least two consecutive terms and “0” for all other years. The first two variables are intended to capture the political and economic performance of the incumbent administration, while the latter variable (borrowed from Abramowitz 1988) is based on the idea that it may be easier to convince voters that it is “time for a change” if the incumbent party has held the White House for at least two consecutive terms. This model provided a fairly accurate forecast of the 1996 election and also had close out-of-sample post-dictions of elections from 1952–1992. However, the 2000 election represented a significant bump in the road, and the model over-predicted Gore's percent of the vote by approximately 10 percentage points.

The trial-heat poll and economy forecasting model is a simple model based on a simple principle. The model uses just two predictor variables to forecast the in-party presidential candidate's share of the national two-party popular vote. The first is the in-party presidential candidate's share of support between the major party candidates in the Gallup Poll's trial-heat (or preference) poll question around Labor Day. The second predictor is the Bureau of Economic Analysis' (BEA) measure of real growth in the Gross Domestic Product (GDP) in the second quarter of the election year (April through June). The GDP measurement is the “preliminary” measure released by the BEA at the end of August, the latest available in time to be used in the forecast. An in-party presidential candidate who is the incumbent is accorded full responsibility for the economy in the equation and a successor or non-incumbent in-party candidate is accorded half the credit or blame for the growth or decline in the economy. This partial credit or blame for successor candidates refl ects both past experience in forecasting (Campbell 2000) and independent findings regarding the effects of retrospective evaluations of the economy on voting behavior (Nadeau and Lewis-Beck 2001). The regression estimated forecasts based on these two predictors, estimated over the 14 presidential elections from 1948 to 2000, is a mix of about two-thirds trial-heat poll and one-third economic growth. In essence, with the preference poll at the center of the prediction, the forecast may be interpreted as an adjusted preference poll.

The Supreme Court's sweeping decision in December, 2003, in McConnell v. FEC was as unexpected as it was dramatic. For months the conventional wisdom had been that the Court was certain to overturn one and possibly both of the main parts of the McCain-Feingold law, or otherwise substantially narrow the statue. Instead, the justices, by a slim 5-4 majority, did just the opposite; not only upholding the law but doing so in terms that virtually echoed the defendants' arguments. Proponents were stunned and thrilled. Opponents were appalled; Justice Scalia called it the “opening act of a national tragedy.” Both sides agreed, however, that the decision in McConnell stands as one of the most important campaign finance and First Amendment precedents in several decades.

How did two political scientists, both lifelong Democrats, end up working for the Republican National Committee (RNC)? We did so with more than a little trepidation and only after consulting extensively with each other and our friends. Many considerations influenced our difficult decision to join the plaintiffs as expert witnesses in McConnell v. FEC, but the most important factor was that we shared a long-standing commitment to the party system and feared that the Bipartisan Campaign Finance Act (BCRA), the most significant campaign finance legislation to be passed in 25 years, marked the dangerous culmination of a regulatory regime, born of the Progressive era, that weakened the parties' ability to engage in those activities that have made them so important to the working of constitutional government in the United States. Moreover, we predicted that BCRA would shift money and the balance of power away from political parties and towards interest groups, with serious consequences for American democracy.

In some respects, our work in McConnell v. FEC began years before the passage of McCain-Feingold. During 1996–1997 we served on a commission organized by Herbert Alexander to create a political scientists' view of campaign financing. The majority voted 6 to 3 to recommend removing limits on the amounts that parties could contribute to candidates. Our dissent, with Janet Box-Steffensmeier, asserted that such a move would do little to strengthen parties or make elections more competitive, while increasing the potential for donors to corrupt parties (Citizens' Research Foundation 1997). Shortly afterward, we were contacted by lawyers from the FEC looking for expert witnesses in Colorado Republican II to argue on behalf of congressional limits on parties' “coordinated expenditures” (Sorauf and Krasno 1997). A few years later, we were asked by lawyers from the office of Missouri's Attorney General to testify on behalf of that state's regulation of party finances (modeled on FECA) in Missouri Shrink PAC v. Lamb (Krasno and Sorauf 2000). In all of these cases our “testimony” consisted of lengthy reports written for district courts or panels.

I start a course on Politics and Policy by asking 100 or so students from several dozen countries to say what comes to mind when they hear the word “science.” Terms mentioned are objectivity, truth-seeking, hypothesis testing, experiments, data, logic, and the like. I write them on the blackboard. I then ask what comes to mind to mind when they hear the word “politics.” Here they mention power, manipulation, ambition, conflict, partisanship, spin, ideology, and, less often, vision and purpose. This list is put on the blackboard. Then, with two word lists before us, I comment that because they have just joined a school of public policy they must have a view of what goes into thinking up, arguing about, designing, and implementing policy. After a bit of discussion it gradually it sinks in. Policy is the meeting ground of science and politics. It is where the two word-lists on the blackboard come together and thrash it out, neither side ever quite vanishing the other.

Political science, as we currently understand the label, was born, in Western Europe, in the early Fifties. One may say that it was “reborn”; but that would be inaccurate, for in the nineteenth century and until World War Two the label indicated a captive discipline largely dominated by juridical or historical approaches (as in the case, e.g., of Gaetano Mosca). So political science had a new start and became a field of inquiry in its own right about half a century ago. I was, at the time, one of its founders (with Stein Rokkan, Juan Linz, Mattei Dogan, Hans Daalder, Erik Allardt, S. N. Eisenstadt, and others. See: Comparative European Politics: The Story of a Profession, edited by H. Daalder, 1997). I am thus one of the witnesses of what the “young turks” of the time had in mind, of how we conceived and promoted political science. I am now an “ancient sage” and it now pleases me to reflect, some fifty years later, on where political science has gone and on whether it has taken the right course, the course that I had wished for and expected. Thus to ask today, in the middle of Mitteleuropa, where political science has been heading is also to ask whether the new beginnings of the discipline in Eastern Europe should or should not follow the path entered by our “big brother,” I mean, by American-type political science. I too have been somewhat swallowed by our big brother (to be sure, a benevolent and well meaning one) in the sense that I have been teaching in the United States for some thirty years. Let me add that I have largely benefited from my American exposure. Yet I have always resisted and still resist the American influence. And I take this occasion to say why I am unhappy about the American molding of present day political science.

Political science remains an emergent discipline; but research within it has congealed around a set of well-defined programs that has engaged an international community of scholars. Here I will identify three of these programs in order to show the continued intellectual vibrancy of the discipline. First, in normative theory, political scientists are working out the implications of John Rawls' A Theory of Justice in a program that has reinvigorated liberalism to make it speak to core political issues of our time. Second, in a program once embedded bureaucratically in “American Politics,” political scientists are working out the implications of Duncan Black's median voter theorem in an expanded set of democratic countries with different institutional details to address the core political issues of representation and accountability. Third, relying on extensive cross-sectional time-series data previously unavailable, on computer programs not imaginable a generation ago, and on theoretical developments in econometrics, political scientists are fulfilling a dream of the founders of the behavioral revolution (Stein Rokkan, S. M. Lipset, and Karl Deutsch) by addressing systematically the sources of democracy and political order. To be sure, there are other political science research programs, for example, in international relations, in comparative political economy, and in political psychology, that could well have been elucidated in this essay. My goal here, in addressing Professor Sartori's jeremiad, is not to show the scope of the field, but rather its quality, its internationalism, and its real-world relevance. This is best done with a few select examples.

In his reflections on “Where is Political Science Going?,” professor Sartori brightly points out some present flaws in the discipline: too much empiricism and too little applied research. At attacking “American-type” political science, however, I think he chooses a mistaken enemy. I will hold, in contrast, that the main source of the mentioned flaws is the weakness of political theory.

In the days following the 9/11 terrorist attacks, Osama bin Laden quickly became America's leading enemy. But as the Bush administration prepared its case for war against Iraq in the first half of 2002, officials began to avoid mentioning Osama bin Laden's name in public. At the same time, administration officials increasingly linked Saddam Hussein with the threat of terrorism in an effort to build public support for war. By the first anniversary of the 9/11 attacks it appeared that this public relations effort had produced results beyond all expectations: several polls released around the time of the anniversary revealed that majorities of Americans believed Saddam Hussein was personally responsible for 9/11.