Prediction markets - markets used to forecast future events - have been used to accurately forecast the outcome of political contests, sporting events, and, occasionally, economic outcomes. This chapter summarizes the latest research on prediction markets in order to further their utilization by...

We review the efficacy of three approaches to forecasting elections: econometric models that project outcomes on the basis of the state of the economy; public opinion polls; and election betting (prediction markets). We assess the efficacy of each in light of the 2004 Australian election. This...

Interest in prediction markets has increased in the last decade, driven in part by the hope that these markets will prove to be valuable tools in forecasting, decision-making and risk management - in both the public and private sectors. This paper outlines five open questions in the literature,...

This paper uses a gravity model of migration to analyze how income differentials affect the flow of immigrants into U.S. states using annual data from the American Community Survey. We add to existing literature by decomposing income differentials into short- and long-term components and by...

The labor search and matching model plays a growing role in macroeconomic analysis. This paper provides a critical, selective survey of the literature. Four fundamental questions are explored: how are unemployment, job vacancies, and employment determined as equilibrium phenomena? What...

The paper derives analytical transitions probabilities following an exogenous shock to the deterministic component in the conditional logit model. The solution draws on the postestimation distribution of the models stochastic component, identified on the basis of a direct utility maximization...

This paper compares various forecasts using panel data with spatial error correlation. The true data generating process is assumed to be a simple error component regression model with spatial remainder disturbances of the autoregressive or moving average type. The best linear unbiased predictor...

This paper provides a novel approach to forecasting time series subject to discrete structural breaks. We propose a Bayesian estimation and prediction procedure that allows for the possibility of new breaks over the forecast horizon, taking account of the size and duration of past breaks (if...

This paper is concerned with empirical and theoretical basis of the Efficient Market Hypothesis (EMH). The paper begins with an overview of the statistical properties of asset returns at different frequencies (daily, weekly and monthly), and considers the evidence on return predictability, risk...