A flexible decomposition of a time series into stochastic cycles under possible non-stationarity is specified, providing both a useful data analysis tool and a very wide model class. A Bayes procedure using Markov Chain Monte Carlo (MCMC) is introduced with a model averaging approach which...

We propose a novel Bayesian test under a (noninformative) Jeffreys’ prior speciï¬ca- tion. We check whether the ï¬xed scalar value of the so-called Bayesian Score Statistic (BSS) under the null hypothesis is a plausible realization from its known and standard- ized distribution...

The high ranking of the Econometric Institute, as listed in recent leading scientific journals, is examined for a fifty year period using similar standard measures. The distribution of the publications over different research areas is analyzed and a time-series model is specified to describe and...

In this paper we discuss the similarity between the Anderson-Rubin test for overidentification in a Simultaneous Equations Model and the Johansen test for cointegration in a Vector Autoregressive model. The similar structure of the two models is shown to be important in this respect. An...

Jan Tinbergen was the first Nobel Laureate in Economics in 1969. This paper presents a brief survey of his many contributions to economics, in particular to macro-econometric modelling, business cycle analysis, economic policy making, development economics, income distribution, international...

In this paper we show some further experiments with neural network sampling, a class of sampling methods that make use of neural network approximations to (posterior) densities, introduced by Hoogerheide et al. (2007). We consider a method where a mixture of Student's t densities, which can be...

Several lessons learnt from a Bayesian analysis of basic macroeconomic time series models are presented for the situation where some model parameters have substantial posterior probability near the boundary of the parameter region. This feature refers to near-instability within dynamic models,...

This short note presents the R package AdMit which provides flexible functions to approximate a certain target distribution and it provides an efficient sample of random draws from it, given only a kernel of the target density function. The estimation procedure is fully automatic and thus avoids...

In this paper we discuss several aspects of simulation based Bayesian econometric inference. We start at an elementary level on basic concepts of Bayesian analysis; evaluating integrals by simulation methods is a crucial ingredient in Bayesian inference. Next, the most popular and well-known...

We propose a natural conjugate prior for the instrumental variables regression model. The prior is a natural conjugate one since the marginal prior and posterior of the structural parameter have the same functional expressions which directly reveal the update from prior to posterior. The...