The study of the innovative output of firms often relies on a count of patents filed at one single office of reference such as the European Patent Office (EPO). Yet, not all firms file their patents at the EPO, raising the specter of a selection bias. Using a novel dataset of the whole population of patents by Belgian firms, we show that the singleoffice count results in a selection bias that a...

Bayesian model averaging (BMA) methods are regularly used to deal with model uncertainty in regression models. This paper shows how to introduce Bayesian model averaging methods in quantile regressions, and allow for di¤erent predictors to a¤ect di¤erent quantiles of the dependent variable. I show that quantile regression BMA methods can help reduce uncertainty regarding outcomes of future in‡a...

This paper extends the distributional theory for the problem of testing for structural change in the linear model when the timing of the change is unknown, and proposes a simple method of obtaining approximate critical values for the mean-Wald test. The results apply for a very wide range of regressor types, including integrated and trending regressors, and regressors that exhibit their own str...

We examine whether by adding a credit channel to the standard New Keynesian model we can account better for the behaviour of US macroeconomic data up to and including the banking crisis. We use the method of indirect inference which evaluates statistically how far a model’s simulated behaviour mimics the behaviour of the data. We …nd that the model with credit dominates the standard model by a ...

The validation of probability calibration is an inherently difficult task. We develop a testing procedure for credit-scoring models. The models comprise two components to check whether the ex-ante probabilities support the ex-post frequencies. The first component tests the level of the probability calibration under dependencies. In the long term, the number of events should equal the sum of ass...

In this paper we provide analytical, simulation, and empirical evidence on a test of equal economic value from competing predictive models of asset returns. We define economic value using the concept of a performance fee — the amount an investor would be willing to pay to have access to an alternative predictive model that is used to make investment decisions. We establish that this fee can be ...

Economic value calculations are increasingly used to compare the predictive performance of competing models of asset returns. However, they lack a rigorous way to validate their evidence. This paper proposes a new methodology to test whether utility gains accruing to investors using competing predictive models are equal to zero. Monte Carlo evidence indicates that our testing procedure, that ca...

The ability of Markov-switching (MS) autoregressive models to replicate selected classical business-cycle features found in US post-war consumption, investment and output is compared to that of linear models. Univariate MS models appear to offer more dynamically parsimonious representations, but generally are unable to reproduce features missed by linear models. In the multivariate models, some...

Technical traders base their analysis on the premise that the patterns in market prices are assumed to recur in the future, and thus, these patterns can be used for predictive purposes. This paper uses the daily Dow Jones Industrial Average Index from 1897 to 1988 to examine the linear and nonlinear predictability of stock market returns with simple technical trading rules. The nonlinear specif...

Minimizing Bias in Selection on Observables Estimators When Unconfoundness Fails We characterize the bias of propensity score based estimators of common average treatment effect parameters in the case of selection on unobservables. We then propose a new minimum biased estimator of the average treatment effect. We assess the finite sample performance of our estimator using simulated data, as wel...