Abstract

A business cycle coincident index (BCI) for the Midland-Odessa region is developed using a dynamic single factor modeling methodology. The model assumes that co-movements of metropolitan economic indicators have a common element that can be summarized as a single underlying and unobservable variable known as the “state of the economy.” The model utilizes a Kalman filter smoothing approach which smooths the index across time and across indicators, resulting in index movements that are less pronounced during expansions and recessions. Indicator series used to estimate the Midland-Odessa BCI are: employment, the unemployment rate, real retail sales, and total real wages. The estimated BCI exhibits movements that are correlated with national economic contractions and expansions, movements in oil prices, and an existing Midland-Odessa business cycle index.

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