Betting Odds May Predict Close Elections Better than Pollsters, Stanford Business School Study Suggests.

Business & News Editors/Political Writers

STANFORD, Calif.--(BUSINESS WIRE)--Oct. 1, 2002

Stanford Graduate School of Business faculty member Justin Wolfers predicts that on election day next month Republicans have a 7-in-10 probability of gaining majority control of the House of Representatives and a 1-in-3 chance of taking both the House and Senate. The latter probability represents a tremendous increase over the 1-in-8 probability estimated in early September before the threat of war with Iraq drew out the hawks.

Traditionally, political pundits and campaign managers could pay big money for a pollster to return these kinds of odds. But new research by Wolfers suggests an intriguing alternative: Call a sportsbookie, especially if the race is tight.

Wolfers, an assistant professor of economics who as a youth worked for a bookmaker in his native Australia, followed a hunch about the predictive power of betting markets in forecasting the outcome of political elections. With Andrew Leigh of the John F. Kennedy School of Government at Harvard, he co-authored a study examining the effectiveness of three tools for forecasting the outcome of Australia's 2001 federal elections: economic modeling, opinion polling, and betting odds.

While the study found that all three methods performed reasonably well, it introduced, for the first time in Australia, a new source of data for predicting elections--betting statistics from one of the country's largest bookmakers. The study's provocative conclusion is this: Particularly in marginal seats, the press may have better served its readers by reporting betting odds than by conducting polls.

Wolfers sets the scene: "Throughout much of the election cycle the candidate on the left, Kim Beazley of the Australian Labor Party, had been expected to win as Prime Minister in the November election. John Howard, the incumbent and leader of the Australian Liberal Party, saw the tide turn in his favor in the days following the Sept. 11 terrorist attacks on America, when the population rallied around their leader. At about the same time -- so it's hard to untangle the two events -- a boatload of Afghan refugees was found off the coast of Australia. Howard took a strong stand against allowing them to immigrate while Beazley chose something in the middle ground and was perceived to be a weak leader. This was argued by many political commentators in Australia to be the turning point of the election."

When the election was held on Nov. 10, 2001 the Liberal-National Party gained 50.5 percent of the vote and John Howard was re-elected Prime Minister.

So how did the three forecasting tools perform?

In the medium-term, which Wolfers identifies as one- to two years before the election, economic modeling -- based on predictions of how voters will react to various economic conditions -- can be effective in picking the election-day winner. This is somewhat surprising, he notes, because Australian election forecasting models have had mixed success, confounding political science researchers studying the impact of such economic indicators as unemployment and inflation on 18 post-war elections in Australia. However, if accurate economic measures are available, the forecasting power of economic modeling is quite substantial.

Using election-eve measures of economic indicators, Wolfers found that three econometric models performed extremely well, nailing precisely the predictions of an incumbent victory in one model, and missing by 0.1 percent and 0.4 percent in two others. "But in the real world, if it's the day before the elections, inferring indirectly off of things we know voters care a little bit about is not going to be as effective as going directly to the people and asking how they're going to vote," says Wolfers.

Pre-election opinion polls should be more accurate in Australia than in countries like the U.S., he points out, because Australia's compulsory elections eliminates the key variable of whether or not respondents will actually show up at the voting booth. Past experience indicates that opinion polls taken close to the election are quite accurate. Yet the lesson from Australia in 2001, like America's 2000 election imbroglio in Florida, points to the potential pitfalls of polling, particularly in very tight races. "The night before the election, Howard was ahead in two of three major polls," says Wolfers. "AC Nielsen was closest, predicting a 52 percent vote share for his Liberal-National Party, with Newspoll a close second, predicting a 53 percent share. Morgan polls were the most inaccurate, suggesting that Beazley's party would easily win the election."

Post-election commentators blamed the Morgan poll's error on its face-to-face data collection, compared to the other two that sampled voters by telephone. "Despite this missed target, the major polls were reasonably accurate on the eve of the election," says Wolfers. Six months out and longer, he cautions, polls lose their predictive power.

In contrast, data from Centrebet, Australia's largest bookmaker, demonstrated the impact of current events on the betting odds throughout the nine months leading up to the election, reflecting immediately the electorate's seesawing response to such events as leaders' televised debates and the Sept. 11 attacks in America. "By election day an enormous amount of money had been pumped into the betting market. More money had been bet on the election than on the football grand final, and Howard was the favorite with odds of $1.55, suggesting a 64 percent probability of his winning the election," says Wolfers. Howard won and Centrebet lost money on the election.

Digging deeper, the data yielded even more impressive results for oddsmakers. Centrebet also offered odds on the outcomes in 47 regional races. According to Wolfers, in 43 of 47 cases, the betting favorite won the election, even in the marginal seats. Moreover, in the three regional races where opinion polls had been conducted, the polls correctly predicted the winner in two contests; the betting market got all three right.

"The rationale for this happening comes from finance, which says that markets are efficient aggregators of information and equilibrium prices should reflect all available information," says Wolfers. "The data suggests the Australian betting market is extraordinarily efficient. And why not? There's a huge incentive for participants to do their homework, collect reliable information and make sure the price is right."

Stateside this election season, Wolfers handicaps the U.S. Congress: "Republicans have about a 40 percent probability to gain a majority in the Senate, and 70 percent probability to control the House. However, the two are not independent events, and so the probability of Republican control of both houses is an average of around one-third, a dramatic rise from a low of around 1-in-8 at the beginning of September, which can be directly attributed to the threat of war in Iraq."

Anyone care to make a wager on that?