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Transitions at Different Moments in Time: A Spatial Probit Approach (replicat...
This paper adopts a spatial probit approach to explain interaction effects among cross-sectional units when the dependent variable takes the form of a binary response variable... -
Exponent of Cross-Sectional Dependence: Estimation and Inference (replication...
This paper provides a characterisation of the degree of cross-sectional dependence in a two dimensional array, {xit,i = 1,2,...N;t = 1,2,...,T} in terms of the rate at which the... -
Bayesian Graphical Models for STructural Vector Autoregressive Processes (rep...
This paper proposes a Bayesian, graph-based approach to identification in vector autoregressive (VAR) models. In our Bayesian graphical VAR (BGVAR) model, the contemporaneous... -
REALIZED BETA GARCH: A MULTIVARIATE GARCH MODEL WITH REALIZED MEASURES OF VOL...
We introduce a multivariate generalized autoregressive conditional heteroskedasticity (GARCH) model that incorporates realized measures of variances and covariances. Realized... -
Are output growth-rate distributions fat-tailed? some evidence from OECD coun...
This work explores some distributional properties of aggregate output growth-rate time series. We show that, in the majority of OECD countries, output growth-rate distributions... -
Nonlinearity in the Fed's monetary policy rule (replication data)
This paper investigates the nature of nonlinearities in the monetary policy rule of the US Federal Reserve (Fed) using the flexible approach to nonlinear inference. We find that... -
Monitoring structural change in dynamic econometric models (replication data)
The classical approach to testing for structural change employs retrospective tests using a historical data set of a given length. Here we consider a wide array of... -
Output and inflation in the long run (replication data)
Cross-country regressions explaining output growth often obtain a negative effect from inflation. However, that result is not robust, due to the selection of countries in... -
A threshold error-correction model for intraday futures and index returns (re...
Index-futures arbitragers only enter into the market if the deviation from the arbitrage relation is sufficiently large to compensate for transaction costs and associated... -
FEASIBLE CROSS-VALIDATORY MODEL SELECTION FOR GENERAL STATIONARY PROCESSES (r...
Cross-validation is a method used to estimate the expected prediction error of a model. Such estimates may be of interest in themselves, but their use for model selection is...
