This paper employs classical bivariate, factor augmented (FA), slab and spike variable selection (SSVS)-based, and Bayesian semiparametric shrinkage (BSS)-based predictive regression models to forecast the US real private residential fixed investment series over an out of sample period of 1983Q1...

This paper uses small set of variables-- real GDP, the inflation rate, and the short-term interest rate -- and a rich set of models -- athoeretical and theoretical, linear and nonlinear, as well as classical and Bayesian models -- to consider whether we could have predicted the recent downturn...

This paper applies a time-varying parameter vector autoregressive (TVP-VAR) approach to estimate the relative effects of housing and stock prices on US consumption over time. We use annual data from 1890 to 2012 and find that over different horizons and over time, generally the housing price...

This paper provides out-of-sample forecasts of linear and non-linear models of US and Census regions housing prices. The forecasts include the traditional point forecasts, but also include interval and density forecasts of the housing price distributions. The non-linear smooth-transition...

This study assesses how fiscal policy affects the dynamics of asset markets, using Bayesian vector autoregressive models. We use sign restrictions to identify government revenue and government spending shocks, while controlling for generic business cycle and monetary policy shocks. In addition...

This paper examines the causal relationships between the real house price index and real GDP per capita in the U.S., using the bootstrap Granger (temporal) non-causality test and a fixed-size rolling-window estimation approach. We use quarterly time-series data on the real house price index and...

This paper investigates whether changes in monetary transmission mechanism respond to variations in asset prices. We distinguish between bull and bear markets and employ a TVP-VAR approach with stochastic volatility to assess the evolution of the monetary policy in relation to housing and stock...

This study applies wavelet analysis to examine the relationship between the U.S. real estate and stock markets over the period 1890-2012. Wavelet analysis allows the simultaneous examination of co-movement and causality between the two markets in both the time and frequency domains. Our findings...

This paper examines the relationship between US crude oil and stock market prices, using a Markov-Switching vector error-correction model and a monthly data set from 1859 to 2013. The sample covers the entire modern era of the petroleum industry, which typically begins with the first drilled oil...

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...