Does Life-Cycle Stage Affect Companies’ Revenue Predictability? Evidence from Borsa Istanbul

Yıl 2022, Cilt: 21 Sayı: 2, 813 - 823, 30.04.2022

Gökberk Can , Samet Günay

https://doi.org/10.21547/jss.1025389

Öz

In this paper we test the relationship between life-cycle stages and revenue predictability. We used three-year revenue divided by average total assets as the revenue predictability. Our life-cycle estimation is based on Dickinson’s (2011) cash-flow proxy model. Instead of using dummy variables and omitted the category with least observations, following Hansen et al. (2018), we assigned values of 0, 0.25, 0.50, 0.75, and 1 for the stages of introduction, growth, mature, shake-out, and decline, respectively. We used firm/year fixed effects regression to estimate our model. Our empirical evidence points out that companies' revenue predictability increases as the revenue volatility decreases.

Anahtar Kelimeler

Life-cycle Stage, Borsa Istanbul, Revenue Predictability

Yaşam Döngüsü Şirketlerin Hasılat Tahmin Edilebilirliğini Etkiler mi? Borsa İstanbul Bulguları

Öz

Bu çalışmada, yaşam döngüsü ile gelir öngörülebilirliği arasındaki ilişki test edilmiştir. Gelir öngörülebilirliği üç yıllık hasılatın standart sapmasının ortalama toplam varlıklara bölünmesiyle elde edilmiştir. Yaşam döngüsü tahminimiz, Dickinson'ın (2011) nakit akışı modeline dayanmaktadır. Hansen vd. (2018), giriş, büyüme, olgunlaşma, durgunluk ve düşüş aşamaları için sırasıyla 0, 0,25, 0,50, 0,75 ve 1 atadık. Modelimizi tahmin etmek için firma/yıl sabit etkiler regresyonunu kullandık. Ampirik kanıtlarımız, hasılat oynaklığı azaldıkça şirketlerin hasılat tahmin edilebilirliğinin arttığına işaret ediyor.

Anahtar Kelimeler

Yasam Döngüsü, Borsa Istanbul, Hasılat Tahmin Edilebilirliği

Kaynakça

• Abdullah, A. A., & Mohd-Saleh, N. (2014). Impact of Firms’ Life-cycle on Conservatism: The Malaysian Evidence. Procedia - Social and Behavioral Sciences, 145, 18–28. https://doi.org/10.1016/j.sbspro.2014.06.007
• De Oliveira, A. S., & Girão, L. F. de A. P. (2018). Accuracy in Earnings Forecast and Organizational Life Cycle Stages : Evidences in the Brazilian Capital Market. Journal of Education and Research in Accounting, 12(1), 115–138.
• DeAngelo, H., DeAngelo, L., & Stulz, R. M. (2006). Dividend policy and the earned/contributed capital mix: a test of the life-cycle theory. Journal of Financial Economics, 81(2), 227–254. https://doi.org/10.1016/j.jfineco.2005.07.005
• Dickinson, V. (2011). Cash Flow Patterns as a Proxy for Firm Life Cycle. The Accounting Review, 86(6), 1969–1994. https://doi.org/10.2308/accr-10130
• Esteve-Pérez, S., Pieri, F., & Rodriguez, D. (2018). Age and productivity as determinants of firm survival over the industry life cycle. Industry and Innovation, 25(2), 167–198. https://doi.org/10.1080/13662716.2017.1291329
• Hansen, J. C., Hong, K. P., & Park, S. H. (2018). Accounting conservatism: A life cycle perspective. Advances in Accounting, 40(January), 76–88. https://doi.org/10.1016/j.adiac.2017.10.001
• Park, Y., & Chen, K. H. (2006). The effect of accounting conservatism and life-cycle stages on firm valuation. Journal of Applied Business Research, 22(3), 75–92. https://doi.org/10.19030/jabr.v22i3.1428
• Yang, C. S., & Shyu, J. (2019). Do institutional investor and group, firm and time effects matter in enterprise performance in the corporate life cycle? Cogent Business and Management, 6(1), 1–18. https://doi.org/10.1080/23311975.2019.1606473
• Zeileis, A. (2004). Econometric Computing with HC and HAC Covariance Matrix Estimators. Journal of Statistical Software, 11(10), 1–21. https://doi.org/10.18637/jss.v011.i10
• Zeileis, A., & Hothorn, T. (2002). Diagnostic Checking in Regression Relationships. R News, 2(3), 7–10. https://cran.r-project.org/doc/Rnews/.