Using Leading Indicators to Forecast US Home Sales in a Bayesian VAR Framework

This paper uses Bayesian vector autoregressive models to examine the usefulness of leading indicators in predicting US home sales. The benchmark Bayesian model includes home sales, the price of homes, the mortgage rate, real personal disposable income, and the unemployment rate. We evaluate the forecasting performance of six alternative leading indicators by adding each, in turn, to the benchmark model. Out-of-sample forecast performance over three periods shows that the model that includes building permits authorized consistently produces the most accurate forecasts. Thus, the intention to build in the future provides good information with which to predict home sales. Another finding suggests that leading indicators with longer leads outperform the short-leading indicators.

Neuroimmune Interactions: a Bidirectional Flow that Leads to Health and Disease

The Vedic philosophy deals with harmony and balance between the mind and the body as well as interactions with nature. This ancient approach to health and well-being is being more and more appreciated in part as we understand the intimate relationship between the immune system, our major defense mechanism and the nervous system. Like other organ systems, the immune system is dependent on the central nervous system (CNS) and the endocrine system in its role for effective defense against foreign and domestic invaders.