US presidential election forecasting: An introduction

Abstract

The modern era of election forecasting is now almost thirty years old. Like many significant developments in science, it began as separate streams of work occurring at around the same time: the investigations of Lee Sigelman (1979), Michael Lewis-Beck and Tom Rice (1982), Richard Brody and Sigelman (1983) on the relationship between presidential approval ratings and the vote; economist Ray Fair's (1978) work on the predictive strength of the economy and presidential incumbency for the vote; Steven Rosenstone's (1983) construction of a forecasting model for the presidential vote in the States; the identification by geophysicist Vladimir Keilis-Borok and historian Allan Lichtman (1981) of thirteen general indicators or “keys” for foretelling the outcome of presidential elections. Soon thereafter, Michael Lewis-Beck and Tom Rice (1984) combined the presidential approval ratings with an indicator of economic conditions to create a core forecasting equation based on retrospective voting theory. Alan Abramowitz (1988) later added to this core idea his “time for a change” consideration of the number of consecutive terms that the president's political