We propose a novel Bayesian test under a (noninformative) Jeffreys' prior specification. We check whether the fixed scalar value of the so- called Bayesian Score Statistic (BSS) under the null hypothesis is a plausible realization from its known and standardized distribution under the...

We propose a novel statistic to test the rank of a matrix. The rank statistic overcomes deficiencies of existing rank statistics, like: a Kronecker covariance matrix for the canonical correlation rank statistic of Anderson [Annals of Mathematical Statistics (1951), 22, 327–351] sensitivity to...

The failure to describe the time series behaviour of most real exchange rates as temporary deviations from fixed long-term means may be due to time variation of the equilibria themselves, see Engel (2000). We implement this idea using an unobserved components model and decompose the observations...

Several Bayesian model combination schemes, including some novel approaches that simultaneously allow for parameter uncertainty, model uncertainty and robust time varying model weights, are compared in terms of forecast accuracy and economic gains using financial and macroeconomic time series....

We propose in this paper a likelihood-based framework for cointegration analysis in panels of a fixed number of vector error correction models. Maximum likelihood estimators of the cointegrating vectors are constructed using iterated Generalized Method of Moments estimators. Using these...

We construct a novel statistic to test hypothezes on subsets of the structural parameters in an Instrumental Variables (IV) regression model. We derive the chi squared limiting distribution of the statistic and show that it has a degrees of freedom parameter that is equal to the number of...

We show that three convenient statistical properties that are known to hold for the linear model with normal distributed errors that: (i.) when the variance is known, the likelihood based test statistics, Wald, Likelihood Ratio and Score or Lagrange Multiplier, coincide, (ii.) when the variance...

Root cancellation in Auto Regressive Moving Average (ARMA) models leads to local non-identification of parameters. When we use diffuse or normal priors on the parameters of the ARMA model, posteriors in Bayesian analyzes show an a posteriori favor for this local non-identification. We show that...

We present a new framework for the joint estimation of the default-free government term structure and corporate credit spread curves. By using a data set of liquid, German mark denominated bonds, we show that this yields more realistic spreads than traditionally obtained spread curves that...

We obtain invariant expressions for prior probabilities and priors on the parameters of nested regression models that are induced by a prior on the parameters of an encompassing linear regression model. The invariance is with respect to specifications that satisfy a necessary set of assumptions....