We investigate identifiability issues in DSGE models and their consequences for parameter estimation and model evaluation when the objective function measures the distance between estimated and model impulse responses. We show that observational equivalence, partial and weak identification...

Analyzing commodity market dynamics, we observe that price volatility increases with reduced contract duration. In this paper, we derive a theoretical model depicting the price formation in two markets with altering product granularity. Supplemented by empirical evidence from German electricity...

The weighted-average least squares (WALS) approach, introduced by Magnus et al. (2010) in the context of Gaussian linear models, has been shown to enjoy important advantages over other strictly Bayesian and strictly frequentist model averaging estimators when accounting for problems of...

Following the recent work of Gómez-Déniz and Pérez-Rodríguez (2014), this paper extends the results obtained there to the normal-exponential distribution with dependence. Accordingly, the main aim of the present paper is to enhance stochastic production frontier and stochastic cost frontier...

An information matrix of a parametric model being singular at a certain true value of a parameter vector is irregular. The maximum likelihood estimator in the irregular case usually has a rate of convergence slower than the Ín-rate in a regular case. We propose to estimate such models by the...

The stochastic ray production frontier was developed as an alternative to the traditional output distance function to model production processes with multiple inputs and multiple outputs. Its main advantage over the traditional approach is that it can be used when some output quantities of some...

There is a huge interest in deriving and comparing socio-economic indicators across societal groups and domains. The indicators are usually derived from population surveys like the German Socio-Economic Panel (SOEP) by direct estimation. Small sample sizes in the domains can limit the precision...

This article brings new inputs to debate outsourcing in Brazil, using a new methodology based on administrative records. With this methodology, it is possible to identify 4.02 million outsourced workers, corresponding to 11.7% of total employees in the urban private sector. Moreover, with this...

Non-homogeneous regression models are widely used to statistically post-process numerical ensemble weather prediction models. Such regression models are capable of forecasting full probability distributions and correct for ensemble errors in the mean and variance. To estimate the corresponding...

Non-homogeneous post-processing is often used to improve the predictive performance of probabilistic ensemble forecasts. A common quantity to develop, test, and demonstrate new methods is the near-surface air temperature frequently assumed to follow a Gaussian response distribution. However,...