While there is a wide consensus in using survey weights when estimating population parameters, it is not clear what to do when using survey data for analytic purposes (i.e. with the objective of making inference about model parameters). In the model-based framework (MB), under the hypothesis...

Inventory fluctuations are an important phenomenon in business cycles. However, the preliminary data on inventory investment as published in the German national accounts are tremendously prone to revision and therefore ill-equipped to diagnose the current stance of the inventory cycle. The Ifo...

This paper proposes the econometric evaluation of the New Keynesian Phillips Curve (NKPC) in the euro area, under a particular specification of the adaptive learning hypothesis. The key assumption is that agents? perceived law of motion is a Vector Autoregressive (VAR) model, whose coefficients...

All economists say that they want to take their model to the data. But with incomplete and highly imperfect data, doing so is difficult and requires carefully matching the assumptions of the model with the statistical properties of the data. The cointegrated VAR (CVAR) offers a way of doing so....

This paper introduces a new class of multivariate volatility models which is easy to estimate using covariance targeting, even with rich dynamics. We call them rotated ARCH (RARCH) models. The basic structure is to rotate the returns and then to fit them using a BEKK-type parameterization of the...

The paper examines the evolution of consumer confidence indices in Australia, Canada, France, Germany, Italy, Japan, the United Kingdom and the United States of America since the 1970s, by modelling them in a multivariate framework of common macroeconomic variables for each country. Results...

We show that the distribution of any portfolio whose components jointly follow a location-scale mixture of normals can be characterised solely by its mean, variance and skewness. Under this distributional assumption, we derive the mean-variance-skewness frontier in closed form, and show that it...

Measuring and displaying uncertainty around path-forecasts, i.e. forecasts made in period T about the expected trajectory of a random variable in periods T+1 to T+H is a key ingredient for decision making under uncertainty. The probabilistic assessment about the set of possible trajectories that...

We derive Lagrange Multiplier and Likelihood Ratio specifi cation tests for the null hypotheses of multivariate normal and Student t innovations using the Generalised Hyperbolic distribution as our alternative hypothesis. We decompose the corresponding Lagrange Multiplier-type tests into...

In this paper I analyze the relative performance of Gaussian and Student-t GARCH and FIGARCH type models for volatility and Value-at-Risk forecasting of daily stock-returns using data from the Spanish equity index IBEX-35. The in-sample analysis shows that the Student-t FIAPARCH process provides...