We contribute to the growing empirical literature on monetary and fiscal interactions by applying a sign restriction identification scheme to a structural TVP-VAR in order to disentangle and evaluate the policy shocks and policy transmissions. This in turn allows us to study the Great Recession...

In this paper we introduce the general setting of a multivariate time series autoregressive model with stochastic time-varying coefficients and time-varying conditional variance of the error process. This allows modeling VAR dynamics for non-stationary times series and estimation of time varying...

Following Giraitis, Kapetanios, and Yates (2014b), this paper uses kernel methods to estimate a seven variable time-varying (TV) vector autoregressive (VAR) model on the data set constructed by Smets and Wouters (2007). We apply an indirect inference method to map from this TV VAR to time...

This paper uses kernel methods to estimate a seven variable time-varying (TV) vector autoregressive (VAR) model on the US data set constructed by Smets and Wouters. We use an indirect inference method to map from this TV VAR to time variation in implied Dynamic Stochastic General Equilibrium...

When faced with a big problem, it is natural to summarize the data en route to a solution. But accepting summary as fact gives up evidence for convenience. Statistical measures from aggregate data may only be capable of indication or trends over time. Only consistency provides a mathematical...

Robust control theory is a tool for assessing decision rules when a decision maker distrusts either the specification of transition laws or the distribution of hidden state variables or both. Specification doubts inspire the decision maker to want a decision rule to work well for a ∅ of models...

This paper extends the standard New Keynesian dynamic stochastic general equilibrium (DSGE) model to agents who cannot smooth consumption (i.e. spenders) and are affected by external consumption habits. Although these assumptions are not new, their joint consideration strongly affects some...

Using a panel data set for OECD countries we replicate the typical features of the New Keynesian Phillips curve models (NPCs) that have been estimated on country data. While this corroborates the NPC also on the macro panel data set, a different conclusion is reached when we test whether the NPC...

This paper develops an estimator for higher-order spatial autoregressive panel data error component models with spatial autoregressive disturbances, SARAR(R,S). We derive the moment conditions and optimal weighting matrix without distributional assumptions for a generalized moments (GM)...

This paper re-examines inference for cluster samples. Sensitivity analysis is proposed as a new method to perform inference when the number of groups is small. Based on estimations using disaggregated data, the sensitivity of the standard errors with respect to the variance of the cluster...