ABSTRACT
The positive correlation between mergers and stock prices should exist because business executives are more willing to merge their businesses when the stock prices they receive are increasing. Mergers should increase as economic activity increases. John B. Guerard found no causality association between mergers and industrial production. This study tests the existence of any statistically significant correlation among mergers, stock prices, and industrial production, using annual data from 1895 to 1973. Robust latent root regression analysis is a tool that might be useful in analyzing mergers, given the high degree of collinearity. Latent root regression adds a biased term while removing the ill-conditioning. Unbiased regression techniques produce a negative coefficient on the industrial production variable. Latent root regression produces positive and significant coefficients on the stock price and industrial production variables. Ordinary least squares regression analysis of the merger series during the 1895–1973 period, using stock prices and industrial production as the independent variables, is plagued by severe multicollinearity.
