We study the application of approximate mean field variational inference algorithms to Bayesian panel VAR models in which an exchangeable prior is placed on the dynamic parameters and the residuals follow either a Gaussian or a Student-t distribution. This reduces the estimation time of possibly...

We study the application of approximate mean field variational inference algorithms to Bayesian panel VAR models in which an exchangeable prior is placed on the dynamic parameters and the residuals follow either a Gaussian or a Student-t distribution. This reduces the estimation time of possibly...

The author develops and extends the asymptotic F - and t -test theory in linear regression models where the regressors could be deterministic trends, unit-root processes, near-unit-root processes, among others. The author considers both the exogenous case where the regressors and the regression...

Surveys of Professional Forecasters produce precise and timely point forecasts for key macroeconomic variables. However, the accompanying density forecasts are not as widely utilized, and there is no consensus about their quality. This is partly because such surveys are often conducted for...

Surveys of professional forecasters produce precise and timely point forecasts for key macroeconomic variables. However, the accompanying density forecasts are not as widely utilized, and there is no consensus about their quality. This is partly because such surveys are often conducted for...

A number of tests have been proposed for assessing the location-scale assumption that is often invoked by practitioners. Existing approaches include Kolmogorov-Smirnov and Cramer-von-Mises statistics that each involve measures of divergence between unknown joint distribution functions and...

In this work, we consider modeling the past volatilities through an asymmetric generalised autoregressive conditional heteroskedasticity (Garch) model with heavy tailed sampling distributions. In particular, we consider the Student-t model with unknown degrees of freedom and indicate how it may...

We derive new tests for proper calibration of multivariate density forecasts based on Rosenblatt probability integral transforms. These tests have the advantage that they i) do not depend on the ordering of variables in the forecasting model, ii) are applicable to densities of arbitrary...

Let X = (X1,...,Xp) be a stochastic vector having joint density function fX(x) with partitions X1 = (X1,...,Xk) and X2 = (Xk 1,...,Xp). A new method for estimating the conditional density function of X1 given X2 is presented. It is based on locally Gaussian approximations, but simplified in...

Der Autor war mit seinem Team u.a. aktiv an der Bekämpfung der letzten Ebola-Epidemie in Afrika beteiligt. In seinem Buch geht es am Rand auch um Beispiele von Pandemien oder Krankheiten wie der Spanischen Grippe, Zika oder Cholera, doch hauptsächlich wird die These erläutert, welche...

EuroMInd-D is a density estimate of monthly gross domestic product (GDP) constructed according to a bottom-up approach, pooling the density estimates of eleven GDP components, by output and expenditure type. The components density estimates are obtained from a medium-size dynamic factor model of...

We introduce a Bayesian approach to predictive density calibration and combination that accounts for parameter uncertainty and model set incompleteness through the use of random calibration functionals and random combination weights. Building on the work of Ranjan and Gneiting (2010) and...

This paper considers sampling proportional to expected size from a partly unknown distribution. The applied context is the exploration for undiscovered resources, like oil accumulations in different deposits, where the most promising deposits are likely to be drilled first, based on some...

We introduce a Bayesian approach to predictive density calibration and combination that accounts for parameter uncertainty and model set incompleteness through the use of random calibration functionals and random combination weights. Building on the work of Ranjan and Gneiting (2010) and...

This study investigates agglomeration effects for classical music production in a wide range of cities for a global sample of composers born between 1750 and 1899. Theory suggests a trade-off between agglomeration economies (peer effects) and diseconomies (peer crowding). I test this hypothesis...

In this paper, we see how much the average monthly frequency of price changes ties down the behavior of firms in steady-state in terms of the average length of price-spells across firms. We use the UK CPI data at the aggregate and sectoral level and find that the actual mean is about twice the...

The monthly frequency of price-changes is a prominent feature of many studies of the CPI micro-data. In this paper, we see how much this ties down the behavior of price-setters ("firms") in steady-state in terms of the average length of price-spells across firms. We are able to divide an upper...