Business climate indicators are used to receive early signals for turning points in the general business cycle. Therefore methods for the detection of turning points in time series are required. Estimations of slopes of a smooth component in the data can be calculated with local polynomial...

Parsimony is a desirable feature of economic models but almost all human behaviors are characterized by vast individual variation that appears to defy parsimony. How much parsimony do we need to give up to capture the fundamental aspects of a population's distributional preferences and to...

This paper develops a specification of the credit scoring model with high discriminatory power to analyze data on loans at the retail banking market. Parametric and non- parametric approaches are employed to produce three models using logistic regression (parametric) and one model using...

Model specification and selection are recurring themes in econometric analysis. Both topics become considerably more complicated in the case of large-dimensional data sets where the set of specification possibilities can become quite large. In the context of linear regression models, penalised...

We revisit the problem of estimating the local average treatment effect (LATE) and the local average treatment effect on the treated (LATT) when control variables are available, either to render the instrumental variable (IV) suitably exogenous or to improve precision. Unlike previous...

We adopt the Jackknife Model Averaging (JMA) technique to conduct a meta-regression analysis of 925 renminbi (RMB) misalignment estimates generated by 69 studies. The JMA method accounts for model selection and sampling uncertainties, and allows for non-nested model specifications and...

We analyze the migration drivers within the European Union countries. For a set of 23 EU countries over the 1995-2019 period, we use Bayesian Model Averaging and quantile regression to assess notably the relevance of unemployment and earnings. We find that the existence of a common border...