In this paper we consider regression models with forecast feedback. Agents' expectations are formed via the recursive estimation of the parameters in an auxiliary model. The learning scheme employed by the agents belongs to the class of stochastic approximation algorithms whose gain sequence is...

As both the natural level of output and the New Keynesian output gap cannot be observed in practice, there is quite some debate on the question how these variables look like in practice. Rather than taking the standard approach of using a time trend or the HP-filter to obtain estimates of these...

This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation of the...

We propose a new approach to deal with structural breaks in time series models. The key contribution is an alternative dynamic stochastic specification for the model parameters which describes potential breaks. After a break new parameter values are generated from a so-called baseline prior...

We introduce a statistical test for comparing the predictive accuracy of competing copula specifications in multivariate density forecasts, based on the Kullback-Leibler Information Criterion (KLIC). The test is valid under general conditions: in particular it allows for parameter estimation...

We extend the class of dynamic factor yield curve models for the inclusion of macro-economic factors. We benefit from recent developments in the dynamic factor literature for extracting the common factors from a large panel of macroeconomic series and for estimating the parameters in the model....

Exchange market pressure (EMP) measures the pressure on a currencyto depreciate. It adds to the actual depreciation a weightedcombination of policy instruments used to ward off depreciation,such as interest rates and foreign exchange interventions, where theweights are their effectiveness. The...

Data Envelopment Analysis (DEA) has become an established tool in comparative analyses of efficiency strategies in both the public and the private sector. The aim of this paper is to present and apply a newly developed, adjusted DEA model – emerging from a blend of a Distance Friction...

This paper documents that factors extracted from a large set of macroeconomic variables bear useful information for predicting monthly US excess stock returns and volatility over the period 1980-2005. Factor-augmented predictive regression models improve upon both benchmark models that only...

We summarize the general combination approach by Billio et al. [2010]. In the combination model the weights follow logistic autoregressive processes, change over time and their dynamics are possible driven by the past forecasting performances of the predictive densities. For illustrative...