This paper applies a time-varying parameter vector autoregressive approach to estimate the relative effects of housing and stock returns on the growth rate of US consumption over time. We use annual data from 1890 to 2012 and find that at the one- and two-year horizons and over time, generally...

We implement several Bayesian and classical models to forecast housing prices in 20 US states. In addition to standard vector-autoregressive (VAR) and Bayesian vector autoregressive (BVAR) models, we also include the information content of 308 additional quarterly series in some models. Several...

Our paper considers this channel whereby monetary policy, a Federal funds rate shock, affects the dynamics of the US housing sector. The analysis uses impulse response functions obtained from a large-scale Bayesian Vector Autoregression (LBVAR) model that incorporates 143 monthly macroeconomic...

We examine the time-series relationship between housing prices in eight Southern California metropolitan statistical areas (MSAs). First, we perform cointegration tests of the housing price indexes for the MSAs, finding seven cointegrating vectors. Thus, the evidence suggests that one common...

We employ a 10-variable dynamic structural general equilibrium model to forecast the US real house price index as well as its turning point in 2006:Q2. We also examine various Bayesian and classical time-series models in our forecasting exercise to compare to the dynamic stochastic general...

This paper provides out-of-sample forecasts of Nevada gross gaming revenue and taxable sales using a battery of linear and non-linear forecasting models and univariate and multivariate techniques. The linear models include vector autoregressive and vector error-correction models with and without...

This paper considers how monetary policy, a Federal funds rate shock, affects the dynamics of the US housing sector and whether the financial market liberalization of the early 1980s influenced those dynamics. The analysis uses impulse response functions obtained from a large-scale Bayesian...

We use several models using Bayesian and classical methods to forecast employment for eight sectors of the US economy. In addition to standard vector-autoregressive and Bayesian vector autoregressive models, we also include the information content of 143 additional monthly series in some models....