We construct a data set of all 429 tied at the half regular season National Football League (NFL) games between 1994 and 2012. We then examine whether or not the path taken to reach the tie (e.g., rushing yards, turnovers, etc.) has any ability to predict the eventual winner. Our main finding is that only the point spread is significantly predictive, although there is weak evidence to suggest that allowing more sacks reduces the chances of winning. Surprisingly, we find that the team receiving the first possession of the second half does not enjoy a statistically significant advantage. Teams should thus simply try to maximize their first half lead without expecting that first half strategies such as ''establishing the run'' will pay dividends in the second half.

We develop a model of competitive gambling markets addressing two empirical puzzles. First, why do bookmakers not set unbiased lines that try to equalize betting on both sides, and thus profit from commissions with minimal risk? Second, why is there little evidence of bookmakers competing through lower commissions? We show that the interaction between bookmakers' and gamblers' private information can induce biased lines even when all players are maximizing their chances of winning. We also offer an explanation for persistently high commissions charged by seemingly competitive bookmakers; these commissions are necessary to compensate books for assuming the disadvantage of moving first.Stage 3: Gamblers choose over or under We solve the model backwards, beginning with a gambler's problem for a fixed vig v, a line y, publicly available information z 1 , and private information z 2 . A gambler's probability of winning equals G(y|z 1 , z 2 ) if she plays under and 1 À G(y|z 1 , z 2 ) if she plays over. Her utility is given by Economica

This article introduces firm‐specific learning by doing into a real business cycle (RBC) model. This assumption results in indeterminacy of the wage over a large portion of the parameter space: when firms use sufficiently high discount factors and when newly employed labour is relatively unproductive. When firms and households use the same discount factor, the effects of indeterminacy are limited to adding volatility to the wage rate. If these discount factors differ, however, then indeterminacy also destabilises newly employed labour and total hours. This result helps to explain the high amount of volatility that newly employed labour exhibits in the US data.

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