A Comparison of Alternative Models for Estimating Firm's Growth Rate

36 Pages Posted: 31 Aug 2015

See all articles by Ivan E. Brick

Ivan E. Brick

Rutgers Business School

Hong-Yi Chen

National Chengchi University - Department of Finance

Chia-Hsun Hsieh

National Central University

Cheng-Few Lee

Rutgers University, Newark, School of Business-Newark, Department of Finance & Economics

Date Written: February 3, 2015

Abstract

The growth rate plays an important role in determining a firm’s asset and equity values, nevertheless the basic assumptions of the growth rate estimation model are less well understood. In this paper, we demonstrate that the model makes strong assumptions regarding the financing mix of the firm. In addition, we discuss various methods to estimate firms’ growth rate, including arithmetic average method, geometric average method, compound-sum method, continuous regression method, discrete regression method, and inferred method. We demonstrate that the arithmetic average method is very sensitive to extreme observations, and the regression methods yield similar but somewhat smaller estimates of the growth rate compared to the compound-sum method. Interestingly, the ex-post forecast shows that arithmetic average method (compound-sum method) yields the best (worst) performance with respect to estimating firm’s future dividend growth rate. Firm characteristics, like size, book-to-market ratio, and systematic risk, have significant influence on the forecast errors of dividend and sales growth rate estimation.

Keywords: Arithmetic average method; Compound-sum method; Continuous regression method; Discount cash flow model; Discrete regression method; Dividend growth model; Geometric average method; Gordon’s growth model; Growth rate; Internal growth model; Sustainable growth model

JEL Classification: G31, G35

Suggested Citation

Brick, Ivan E. and Chen, Hong-Yi and Hsieh, Chia-Hsun and Lee, Cheng-Few, A Comparison of Alternative Models for Estimating Firm's Growth Rate (February 3, 2015). Review of Quantitative Finance and Accounting, Forthcoming, Available at SSRN: https://ssrn.com/abstract=2652597

Ivan E. Brick

Rutgers Business School ( email )

111 Washington Avenue
Newark, NJ 07102
United States
973-353-5155 (Phone)
973-353-1233 (Fax)

Hong-Yi Chen (Contact Author)

National Chengchi University - Department of Finance ( email )

No. 64, Chih-Nan Road
Section 2
Wenshan, Taipei, 11623
Taiwan

Chia-Hsun Hsieh

National Central University ( email )

No. 300, Zhongda Road
Chung-Li Taiwan, 32054
Taiwan

Cheng-Few Lee

Rutgers University, Newark, School of Business-Newark, Department of Finance & Economics ( email )

111 Washington Avenue
Newark, NJ 07102
United States
732-445-3907 (Phone)
732-445-5927 (Fax)

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