We study the changing international transmission of US financial shocks over the period 1971-2009. Financial shocks are defined as unexpected changes of a financial conditions index (FCI), recently developed by Hatzius et al. (2010), for the US. We use a time-varying factor-augmented VAR to...

We study 30 vintages of FRB/US, the principal macro model used by the Federal Reserve Board staff for forecasting and policy analysis. To do this, we exploit archives of the model code, coefficients, baseline databases and stochastic shock sets stored after each FOMC meeting from the model’s...

This paper is concerned with methods for analysing spatial data. After initial discussion on the nature of spatial data, including the concept of randomness, we focus most of our attention on linear regression models that involve interactions between agents across space. The introduction of...

We study how credit supply shocks in the US, the euro area and Japan are transmitted to other economies. We use the recently-developed GVAR approach to model financial variables jointly with macroeconomic variables in 33 countries for the period 1983-2009. We experiment with inter-country links...

This paper disentangles fluctuations in disaggregated prices due to macroeconomic and sectoral conditions using a factor-augmented vector autoregression estimated on a large data set. On the basis of this estimation, we establish eight facts: (1) Macroeconomic shocks explain only about 15% of...

When a supply and demand model is recursive, with errors uncorrelated across the two equations, ordinary least squares (OLS) is the recommended estimation procedure. Supply to a daily fish market is determined by the previous night’s catch, so this would appear to be a good example of a...

In this paper I develop the Discrete Choice Analytically Flexible (DCAF) model of demand for differentiated products. DCAF relaxes the constraints imposed on the matrix of own- and cross-price elasticities of demand by popular analytic discrete choice models such as the Multinomial Logit (MNL)...

We propose a classical approach to estimate factor-augmented vector autoregressive (FAVAR) models with time variation in the factor loadings, in the factor dynamics, and in the variance-covariance matrix of innovations. When the time-varying FAVAR is estimated using a large quarterly dataset of...

This paper sheds new light on the interactions between business cycles and the consumption distribution. We use CEX consumption data and a factor model to characterize the cyclical dynamics of the consumption distribution. We first establish that our approach is able to closely match business...

A method to estimate DSGE models using the raw data is proposed. The approach links the observables to the model counterparts via a flexible specification which does not require the model-based component to be solely located at business cycle frequencies, allows the non model-based component to...