The increasing use of demand-side management as a tool to reliably meet electricity demand at peak time has stimulated interest among researchers, consumers and producer organizations, managers, regulators and policymakers, This research reviews the growing literature on models used to study...

Assessing the migration potential and predicting future migration streams are among the most relevant, yet least well understood topics of migration research. The usual approach taken to address aggregate-level prediction problems is to fit ad hoc specifications to historical data, and to...

The current economic crisis requires fast information to predict economic behavior early, which is difficult at times of structural changes. This paper suggests an innovative new method of using data on internet activity for that purpose. It demonstrates strong correlations between keyword...

Using a recent Spanish database, we show that remittances respond to cross country differences in portfolio values. This behavior suggests that immigrants are sophisticated economic optimizers who take advantage of opportunities to invest trans-nationally given the networks that immigrants are...

Forecasting errors pose a serious problem of identification, often neglected in empirical applications. Any attempt of estimating choice models under uncertainty may lead to severely biased results in the presence of forecasting errors even when individual expectations on future events are...

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...