A Discrete Choice Model of Dividend Reinvestment Plans: Classification and Prediction
Thomas P. Boehm and Ramon P. DeGennaro
Working Paper 2007-22
We study 852 companies with dividend reinvestment plans in 1999 matched by total assets to 852 companies without such plans. We use discrete choice methods to predict the classification of these companies. We interpret the misclassified companies as being likely to switch their plan status. That is, if a firm's financial data suggest that a company should have had a dividend reinvestment plan in 1999 but did not, then we expect that it would be more likely to institute a plan than the other companies in the sample. Conversely, if it did have a plan but the financial data suggest that it should not, then we expect that the company would be more likely to drop the plan. We use data from 2004 to explore this conjecture and find evidence supporting it. Our model is an economically and statistically reliable predictor of changes in plan status. We also identify which variables have the most influence on a company's decision whether or not to offer a plan.
JEL classification: G20, G29, G35
Key words: dividend reinvestment, discrete choice, clustering
Ramon P. DeGennaro gratefully acknowledges the support of a summer research grant from the University of Tennessee's Finance Department. The authors thank participants at a session at the 2007 meetings of the Association of Private Enterprise Education for helpful comments. The views expressed here are the authors' and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System. Any remaining errors are the authors' responsibility.
Please address questions regarding content to Ramon P. DeGennaro, Visiting Scholar, Federal Reserve Bank of Atlanta, and SunTrust Professor of Finance, Finance Department, University of Tennessee, 423 Stokely Management Center, Knoxville, TN 37996, 865-974-1726, firstname.lastname@example.org, or Thomas P. Boehm, AmSouth Scholar and Professor of Finance, Finance Department, University of Tennessee, 430 Stokely Management Center, Knoxville, TN 37996-0540, 865-974-1723, email@example.com.
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