We develop distress prediction models for non-financial small and medium sized enterprises (SMEs) using a dataset from eight European countries over the period 2000-2009. We examine idiosyncratic and systematic covariates and find that macro conditions and bankruptcy codes add predictive power...

This chapter uses the marginal treatment effect (MTE) to unify and organize the econometric literature on the evaluation of social programs. The marginal treatment effect is a choice-theoretic parameter that can be interpreted as a willingness to pay parameter for persons at a margin of...

In the context of the multivariate Normal regression model, a mean squared error of prediction is developed for making the choice of subset of explanatory variables for predicting the response variable in future samples

A general statistical modeling problem is that given a class of competing models and new data, how one can improve the overall model performance. In general, there exist two solutions for this problem, namely model selection and model combination. Model selection is to select a single best model...

Existing results on the properties and performance of forecast combinations have been derived in the context of mean squared error loss. Under this loss function empirical studies have generally found that estimates of optimal forecast combination weights lead to higher losses than...

Some observers have worried that under or over-estimating the output gap may unnecessarily induce tightening or loosening of monetary conditions, causing real fluctuations. To investigate the relationship between the output gap and inflation, we examine models of inflation that do and do not use...

Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer of many limitations. HF data feature microstructure problem,...

Several authors have recently investigated the predictability of exchange rates by fitting a sequence of long-horizon error-correction regressions. We show that such a procedure gives rise to spurious evidence of predictive power. A simulation study demonstrates that even when using this...

In this paper we reconsider large Bayesian Vector Autoregressions (BVAR) from the point of view of Bayesian Compressed Regression (BCR). First, we show that there are substantial gains in terms of out-of-sample forecasting by treating the problem as an error-in-variables formulation and...

The ability of the New Keynesian Phillips curve to explain US inflation dynamics when official central bank forecasts (Greenbook forecasts) are used as a proxy for inflation expectations is examined. The New Keynesian Phillips curve is estimated on quarterly data spanning the period...