Can digital financial inclusion as an emerging and innovative financial service promote
economic growth? Based on a Bayesian macroeconomic analysis framework, this paper …

The 2006 sudden and immense downturn in US house prices sparked the 2007 global
financial crisis and revived the interest about forecasting such imminent threats for economic …

Technical analysis lies on the premiss that short‐term market price at any time is revealed by
pattern of prior price movements. Tests empirically the pattern of the real estate prices by …

This study extends the existing forecasting accuracy debate in the tourism literature by
examining the forecasting performance of various vector autoregressive (VAR) models. In …

We examine the time-series relationship between house prices in eight Southern California
metropolitan statistical areas (MSAs). First, we perform cointegration tests of the house price …

We examine the time-series relationship between house prices in Los Angeles, Las Vegas,
and Phoenix. First, temporal Granger causality tests reveal that Los Angeles house prices …

Vector auto regression modeling and forecasting Page 1 Journal of Forecasting, Vol. Vector
Autoregression Modelling and Forecasting KEN HQLDEN The Business School, Liverpool …

Purpose–The objective of this paper is to explore the sensitivity of industry‐specific stock
returns to monetary policy and macroeconomic news. The paper looks at a range of industry …

We employ a 10-variable dynamic structural general equilibrium model to forecast the US
real house price index as well as its downturn in 2006: Q2. We also examine various …

This article uses Bayesian vector autoregressive models to examine the usefulness of
leading indicators in predicting US home sales. The benchmark Bayesian model includes …