ANALYZING BOX OFFICE REVENUES OF UNITED STATES BY USING LONG RUN REGRESSION EQUATIONS

Abstract

This study analyzes the determinants of box office revenues by using four different cointegration reg­ression models (Fully Modified Ordinary Least Squares, Dynamic Ordinary Least Squares, Canonical Cointegrating Regression, and Autoregressive Distributed Lag) to provide macroeconomics framework. The data covers the years from 1980 to 2021 for the case of United States and uses income per capita, inflation, employment, population at cities, and number of movie tickets sold as determinants of box office revenues. The results of all regression methods indicate that box office revenue is positively affected by income per capita and movie tickets sold and negatively affected by employment, inflation, and population at cities in the long run.