We study risk perception and actual decision-making by the corporate elite, where we consider CEOs, CFOs and non-executives. We collect data for many members of the elite for Netherlands-based companies using the vignettes method. We find that CEOs are more risk tolerant but do not act accordingly b
We analyze the revision history of quarterly and monthly (seasonally unadjusted) macroeconomic variables for the Netherlands, Ireland, Luxemburg and the United States, where we focus on the degree of deterministic seasonality in these revisions. We document that the data show most deterministic seas
Monitoring involves the collection, analysis and evaluation of information over time. For many professionals, monitoring is a central aspect of their work. For example, policy- makers closely watch the e®ects of their current policies to set the right course for reform. Likewise, physicians monitor
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, to fo
We analyze five vintages of eighteen quarterly macroeconomic variables for the Netherlands and we focus on the degree of deterministic seasonality in these series. We document that the data show most such deterministic seasonality for their first release vintage and for the last available vintage. I
This paper puts forward a data collection method to measure weekly consumer confidence at the individual level. The data thus obtained allow to statistically analyze the dynamic correlation of such a consumer confidence indicator and to draw inference on transition rates, which is not possible for c
We develop a formal statistical approach to investigate the possibility that leading indicator variables have different lead times at business cycle peaks and troughs. For this purpose, we propose a novel Markov switching vector autoregressive model, where economic growth and leading indicators shar
Several lessons learned from a Bayesian analysis of basic economic time series models by means of the Gibbs sampling algorithm are presented. Models include the Cochrane-Orcutt model for serial correlation, the Koyck distributed lag model, the Unit Root model, the Instrumental Variables model and as
We present a road map for effective application of Bayesian analysis of a class of well-known dynamic econometric models by means of the Gibbs sampling algorithm. Members belonging to this class are the Cochrane-Orcutt model for serial correlation, the Koyck distributed lag model, the Unit Root mod
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