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FİNANSAL BAŞARISIZLIĞI BELİRLEYEN ETKENLER: TÜRKİYE İMALAT SEKTÖRÜ ÖRNEĞİ

Year 2018, Volume: 40 Issue: 2, 181 - 207, 11.01.2019

Arhan Sabri Ertan , Ömer Ersan

Abstract

Bu çalışma 2000–2014 yılları arasında Borsa İstanbul’da işlem görmüş olan 208 imalat sektörü işletmesi için finansal başarısızlık riski üzerinde etkili olan faktörleri belirlemeyi amaçlamaktadır. Analizlerde işletmelere özgü finansal oranlar ve kurumsal yönetim ile ilgili değişkenlere ek olarak finansal piyasalar, makroekonomi ve küresel ekonomi ile ilgili göstergeler de göz önüne alınmıştır. Ampirik tahmin yöntemleri olarak yarı parametrik (Cox orantılı riskler) ve parametrik (panel probit, panel logit, tamamlayıcı log-log, log-logistic) sağ kalım ve panel rastsal etkiler yöntemleri kullanılmıştır. Bulgulara göre Cox orantılı riskler yöntemi, işlem karakteristiği eğrileri, başarı ve hata (tip-1 ve tip-2) oranları açısından kıyaslanan yöntemler arasında en yüksek başarıyı elde etmiştir.

Keywords

İşletme başarısızlığı finansal gerilim sağ kalım analizi

References

  • ALLISON, P. D. (2014). Event History and Survival Analysis (Quantitative Applications in the Social Sciences), Sage Publications.
  • ALTMAN, E. I. (1968). Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. The Journal of Finance, 23(4): 589–609.
  • BEAVER, W. H. (1966). Financial Ratios As Predictors of Failure. Journal of Accounting Research, 4, 71.
  • BEAVER, W., McNichols, M., & Rhie, J. W. (2005). Have Financial Statements Become Less Informative? Evidence from the Ability of Financial Ratios to Predict Bankruptcy. Review of Accounting Studies, 10.
  • BHOJRAJ, S., & Sengupta, P. (2003). Effect of Corporate Governance on Bond Ratings and Yields: The Role of Institutional Investors and Outside Directors. The Journal of Business, 76(3): 455–475.
  • BLUM, M. (1974). Failing Company Discriminant Analysis. Journal of Accounting Research, 12(1): 1–25.
  • CAMPBELL, J. Y., Hilscher, J., & Szilagyi, J. (2008). In Search of Distress Risk. Journal of Finance, 63(6): 2899–2939.
  • CARVALHO, J., Divino, J. A., & Orrillo, J. (2013). Default and Bankruptcy in an Entrepreneurial Economy with Incomplete Markets. Journal of Banking and Finance, 37(7): 2162–2172.
  • CHAUDHURI, A. (2013). Bankruptcy Prediction Using Bayesian, Hazard, Mixed Logit and Rough Bayesian Models: A Comparative Analysis. Computer and Information Science, 6(2): 103–125.
  • COX, D. R. (1972). Regression Models and Life Tables. Journal of the Royal Statistical Society. Series B, 34(2).
  • DEAKIN, E. (1972). A Discriminant Analysis of Predictors of Business Failure. Journal of Accounting Research, 10(1): 167–179.
  • DIETRICH, J. R., & Kaplan, R. S. (1982). Empirical Analysis of the Commercial Loan Classification Decision. The Accounting Review, 57(1): 18–38.
  • EDMISTER, R. O. (1972). An Empirical Test of Financial Ratio Analysis for Small Business Failure Prediction. Journal of Financial and Quantitative Analysis, 7(2): 1477–1493.
  • FERRAGINA, A., Pittiglio, R., & Reganati, F. (2012). Multinational Status and Firm Exit in the Italian Manufacturing and Service Sectors. Structural Change and Economic Dynamics, 23(4): 363–372.
  • GANDY, A. (2012). Performance Monitoring of Credit Portfolios Using Survival Analysis. International Journal of Forecasting, 28(1): 139–144.
  • GENTRY, J. A., Newbold, P., & Whitford, D. T. (1985). Classifying Bankrupt Firms with Funds Flow Components. Journal of Accounting Research, 23(1): 146–160.
  • GRICE, J. S., & Ingram, R. W. (2001). Tests of the Generalizability of Altman’s Bankruptcy Prediction Model. Journal of Business Research, 54(1): 53–61.
  • GUPTA, J., Gregoriou, A., & Ebrahimi, T. (2018). Empirical Comparison of Hazard Models in Predicting SMEs Failure. Quantitative Finance, 18(3): 437–466.
  • HUNTER, J., & Isachenkova, N. (2001). Failure Risk: A Comparative Study of UK and Russian Firms. Journal of Policy Modeling, 23(5): 1–26.
  • JENKINS, S. P. (1995). Easy Estimation Methods for Discrete‐Time Duration Models. Oxford Bulletin of Economics and Statistics, 57(1): 129–136.
  • JONES, S., & Hensher, D. A. (2004). Predicting Firm Financial Distress: A Mixed Logit Model. The Accounting Review, 79(4): 1011–1038.
  • KEASEY, K., & Watson, R. (1987). Non‐Financial Symptoms and the Prediction of Small Company Failure: A Test of Argenti’s Hypotheses. Journal of Business Finance and Accounting, 14(3): 335–354.
  • LAITINEN, E. K., & Laitinen, T. (2000). Bankruptcy Prediction: Application of the Taylor’s Expansion in Logistic Regression. International Review of Financial Analysis, 9(4): 327–349.
  • LI, H., & Sun, J. (2011). Predicting Business Failure Using Forward Ranking-Order Case-Based Reasoning. Expert Systems with Applications, 38(4): 3075–3084.
  • LIN, H. W., Lo, H. C., & Wu, R. S. (2016). Modeling Default Prediction with Earnings Management. Pacific Basin Finance Journal, 40: 306–322.
  • LIN, T. H. (2009). A Cross Model Study of Corporate Financial Distress Prediction in Taiwan: Multiple Discriminant Analysis, Logit, Probit and Neural Networks Models. Neurocomputing, 72(16–18): 3507–3516.
  • LUO, S., Kong, X., & Nie, T. (2016). Spline Based Survival Model for Credit Risk Modeling. European Journal of Operational Research, 253(3): 869–879.
  • GEORGETA, V., & Maricica, M. (2012). Business Failure Risk Analysis Using Financial Ratios. Procedia – Social and Behavioral Sciences, 62: 728–732.
  • MARTIN, D. (1977). Early Warning of Bank Failure. A Logit Regression Approach. Journal of Banking and Finance, 1(3): 249–276.
  • OHLSON, J. A. (1980). Financial Ratios and the Probabilistic Prediction of Bankruptcy. Journal of Accounting Research, 18(1): 109.
  • PRENTICE, R. L., & Gloeckler, L. A. (1978). Regression Analysis of Grouped Survival Data with Application to Breast Cancer Data. Biometrics, 34(1): 57–67.
  • SALEHI, M., & Abedini, B. (2009). Financial Distress Prediction in Emerging Market: Empirical Evidences from Iran. Business Intelligence Journal, 2(2): 398–409.
  • SHUMWAY, T. (2001). Forecasting Bankruptcy More Accurately: A Simple Hazard Model. The Journal of Business, 74(1): 101–124.
  • SINKEY, J. F. (1975). A Multivariate Statistical Analysis of the Characteristics of Problem Banks. The Journal of Finance, 30(1): 21–36.
  • TAFFLER, R. J. (1983). The Assessment of Company Solvency and Performance Using a Statistical Model. Accounting and Business Research, 13(52): 295–308.
  • WEST, R. C. (1985). A Factor-Analytic Approach to Bank Condition. Journal of Banking and Finance, 9(2): 253–266.
  • WU, Y., Gaunt, C., & Gray, S. (2010). A Comparison of Alternative Bankruptcy Prediction Models. Journal of Contemporary Accounting and Economics, 6(1): 34–45.
  • ZMIJEWSKI, M. (1984). Methodological Issues Related to the Estimation of Financial Distress Prediction Models. Journal of Accounting Research, 22, 59–82.

Year 2018, Volume: 40 Issue: 2, 181 - 207, 11.01.2019

Arhan Sabri Ertan , Ömer Ersan

Abstract

References

  • ALLISON, P. D. (2014). Event History and Survival Analysis (Quantitative Applications in the Social Sciences), Sage Publications.
  • ALTMAN, E. I. (1968). Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. The Journal of Finance, 23(4): 589–609.
  • BEAVER, W. H. (1966). Financial Ratios As Predictors of Failure. Journal of Accounting Research, 4, 71.
  • BEAVER, W., McNichols, M., & Rhie, J. W. (2005). Have Financial Statements Become Less Informative? Evidence from the Ability of Financial Ratios to Predict Bankruptcy. Review of Accounting Studies, 10.
  • BHOJRAJ, S., & Sengupta, P. (2003). Effect of Corporate Governance on Bond Ratings and Yields: The Role of Institutional Investors and Outside Directors. The Journal of Business, 76(3): 455–475.
  • BLUM, M. (1974). Failing Company Discriminant Analysis. Journal of Accounting Research, 12(1): 1–25.
  • CAMPBELL, J. Y., Hilscher, J., & Szilagyi, J. (2008). In Search of Distress Risk. Journal of Finance, 63(6): 2899–2939.
  • CARVALHO, J., Divino, J. A., & Orrillo, J. (2013). Default and Bankruptcy in an Entrepreneurial Economy with Incomplete Markets. Journal of Banking and Finance, 37(7): 2162–2172.
  • CHAUDHURI, A. (2013). Bankruptcy Prediction Using Bayesian, Hazard, Mixed Logit and Rough Bayesian Models: A Comparative Analysis. Computer and Information Science, 6(2): 103–125.
  • COX, D. R. (1972). Regression Models and Life Tables. Journal of the Royal Statistical Society. Series B, 34(2).
  • DEAKIN, E. (1972). A Discriminant Analysis of Predictors of Business Failure. Journal of Accounting Research, 10(1): 167–179.
  • DIETRICH, J. R., & Kaplan, R. S. (1982). Empirical Analysis of the Commercial Loan Classification Decision. The Accounting Review, 57(1): 18–38.
  • EDMISTER, R. O. (1972). An Empirical Test of Financial Ratio Analysis for Small Business Failure Prediction. Journal of Financial and Quantitative Analysis, 7(2): 1477–1493.
  • FERRAGINA, A., Pittiglio, R., & Reganati, F. (2012). Multinational Status and Firm Exit in the Italian Manufacturing and Service Sectors. Structural Change and Economic Dynamics, 23(4): 363–372.
  • GANDY, A. (2012). Performance Monitoring of Credit Portfolios Using Survival Analysis. International Journal of Forecasting, 28(1): 139–144.
  • GENTRY, J. A., Newbold, P., & Whitford, D. T. (1985). Classifying Bankrupt Firms with Funds Flow Components. Journal of Accounting Research, 23(1): 146–160.
  • GRICE, J. S., & Ingram, R. W. (2001). Tests of the Generalizability of Altman’s Bankruptcy Prediction Model. Journal of Business Research, 54(1): 53–61.
  • GUPTA, J., Gregoriou, A., & Ebrahimi, T. (2018). Empirical Comparison of Hazard Models in Predicting SMEs Failure. Quantitative Finance, 18(3): 437–466.
  • HUNTER, J., & Isachenkova, N. (2001). Failure Risk: A Comparative Study of UK and Russian Firms. Journal of Policy Modeling, 23(5): 1–26.
  • JENKINS, S. P. (1995). Easy Estimation Methods for Discrete‐Time Duration Models. Oxford Bulletin of Economics and Statistics, 57(1): 129–136.
  • JONES, S., & Hensher, D. A. (2004). Predicting Firm Financial Distress: A Mixed Logit Model. The Accounting Review, 79(4): 1011–1038.
  • KEASEY, K., & Watson, R. (1987). Non‐Financial Symptoms and the Prediction of Small Company Failure: A Test of Argenti’s Hypotheses. Journal of Business Finance and Accounting, 14(3): 335–354.
  • LAITINEN, E. K., & Laitinen, T. (2000). Bankruptcy Prediction: Application of the Taylor’s Expansion in Logistic Regression. International Review of Financial Analysis, 9(4): 327–349.
  • LI, H., & Sun, J. (2011). Predicting Business Failure Using Forward Ranking-Order Case-Based Reasoning. Expert Systems with Applications, 38(4): 3075–3084.
  • LIN, H. W., Lo, H. C., & Wu, R. S. (2016). Modeling Default Prediction with Earnings Management. Pacific Basin Finance Journal, 40: 306–322.
  • LIN, T. H. (2009). A Cross Model Study of Corporate Financial Distress Prediction in Taiwan: Multiple Discriminant Analysis, Logit, Probit and Neural Networks Models. Neurocomputing, 72(16–18): 3507–3516.
  • LUO, S., Kong, X., & Nie, T. (2016). Spline Based Survival Model for Credit Risk Modeling. European Journal of Operational Research, 253(3): 869–879.
  • GEORGETA, V., & Maricica, M. (2012). Business Failure Risk Analysis Using Financial Ratios. Procedia – Social and Behavioral Sciences, 62: 728–732.
  • MARTIN, D. (1977). Early Warning of Bank Failure. A Logit Regression Approach. Journal of Banking and Finance, 1(3): 249–276.
  • OHLSON, J. A. (1980). Financial Ratios and the Probabilistic Prediction of Bankruptcy. Journal of Accounting Research, 18(1): 109.
  • PRENTICE, R. L., & Gloeckler, L. A. (1978). Regression Analysis of Grouped Survival Data with Application to Breast Cancer Data. Biometrics, 34(1): 57–67.
  • SALEHI, M., & Abedini, B. (2009). Financial Distress Prediction in Emerging Market: Empirical Evidences from Iran. Business Intelligence Journal, 2(2): 398–409.
  • SHUMWAY, T. (2001). Forecasting Bankruptcy More Accurately: A Simple Hazard Model. The Journal of Business, 74(1): 101–124.
  • SINKEY, J. F. (1975). A Multivariate Statistical Analysis of the Characteristics of Problem Banks. The Journal of Finance, 30(1): 21–36.
  • TAFFLER, R. J. (1983). The Assessment of Company Solvency and Performance Using a Statistical Model. Accounting and Business Research, 13(52): 295–308.
  • WEST, R. C. (1985). A Factor-Analytic Approach to Bank Condition. Journal of Banking and Finance, 9(2): 253–266.
  • WU, Y., Gaunt, C., & Gray, S. (2010). A Comparison of Alternative Bankruptcy Prediction Models. Journal of Contemporary Accounting and Economics, 6(1): 34–45.
  • ZMIJEWSKI, M. (1984). Methodological Issues Related to the Estimation of Financial Distress Prediction Models. Journal of Accounting Research, 22, 59–82.
There are 38 citations in total.

Details

Primary Language Turkish
Journal Section Makaleler
Authors

Arhan Sabri Ertan 0000-0001-9730-8391

Ömer Ersan 0000-0002-7880-0724

Publication Date January 11, 2019
Submission Date September 1, 2018
Published in Issue Year 2018 Volume: 40 Issue: 2

Cite

APA Ertan, A. S., & Ersan, Ö. (2019). FİNANSAL BAŞARISIZLIĞI BELİRLEYEN ETKENLER: TÜRKİYE İMALAT SEKTÖRÜ ÖRNEĞİ. Marmara Üniversitesi İktisadi Ve İdari Bilimler Dergisi, 40(2), 181-207. https://doi.org/10.14780/muiibd.511028
AMA Ertan AS, Ersan Ö. FİNANSAL BAŞARISIZLIĞI BELİRLEYEN ETKENLER: TÜRKİYE İMALAT SEKTÖRÜ ÖRNEĞİ. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi. January 2019;40(2):181-207. doi:10.14780/muiibd.511028
Chicago Ertan, Arhan Sabri, and Ömer Ersan. “FİNANSAL BAŞARISIZLIĞI BELİRLEYEN ETKENLER: TÜRKİYE İMALAT SEKTÖRÜ ÖRNEĞİ”. Marmara Üniversitesi İktisadi Ve İdari Bilimler Dergisi 40, no. 2 (January 2019): 181-207. https://doi.org/10.14780/muiibd.511028.
EndNote Ertan AS, Ersan Ö (January 1, 2019) FİNANSAL BAŞARISIZLIĞI BELİRLEYEN ETKENLER: TÜRKİYE İMALAT SEKTÖRÜ ÖRNEĞİ. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi 40 2 181–207.
IEEE A. S. Ertan and Ö. Ersan, “FİNANSAL BAŞARISIZLIĞI BELİRLEYEN ETKENLER: TÜRKİYE İMALAT SEKTÖRÜ ÖRNEĞİ”, Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi, vol. 40, no. 2, pp. 181–207, 2019, doi: 10.14780/muiibd.511028.
ISNAD Ertan, Arhan Sabri - Ersan, Ömer. “FİNANSAL BAŞARISIZLIĞI BELİRLEYEN ETKENLER: TÜRKİYE İMALAT SEKTÖRÜ ÖRNEĞİ”. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi 40/2 (January 2019), 181-207. https://doi.org/10.14780/muiibd.511028.
JAMA Ertan AS, Ersan Ö. FİNANSAL BAŞARISIZLIĞI BELİRLEYEN ETKENLER: TÜRKİYE İMALAT SEKTÖRÜ ÖRNEĞİ. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi. 2019;40:181–207.
MLA Ertan, Arhan Sabri and Ömer Ersan. “FİNANSAL BAŞARISIZLIĞI BELİRLEYEN ETKENLER: TÜRKİYE İMALAT SEKTÖRÜ ÖRNEĞİ”. Marmara Üniversitesi İktisadi Ve İdari Bilimler Dergisi, vol. 40, no. 2, 2019, pp. 181-07, doi:10.14780/muiibd.511028.
Vancouver Ertan AS, Ersan Ö. FİNANSAL BAŞARISIZLIĞI BELİRLEYEN ETKENLER: TÜRKİYE İMALAT SEKTÖRÜ ÖRNEĞİ. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi. 2019;40(2):181-207.

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