Duration Analysis of New Firms in the Banking Industry
This paper studies the duration or survival time of commercial banks active in the Moscovian three month Rouble deposits market, during the 1994-1997 period. The privatization process of the Russian commercial banking industry, after the 1988 banking reform, caused a massive entry of new banks followed by a period of high rates of exit. As a consequence, many firms went bankrupt without refunding their deposits. Therefore, both for the banks and for the banks- depositors, it is of interest to analyze which are the significant characteristics that motivate the exit or the closing of the bank. We propose a different methodology based on penalized weighted least squares which represents a very general, flexible and innovative approach for this type of analysis. The more relevant results are that smaller banks exit sooner, banks that enter the market in the last part of the study have shorter durations. As expected, the more experienced banks have a longer duration in the market. In addition, the mean survival time is lower for banks which offer extreme interest rates.
[1] Audretsch DB, Mahmood, T. New firm survival: new results using a
hazard function. Review of Economics and Statistics 1995; 77: 97-103.
[2] Dunne T, Roberts MJ, Samuelson L. The growth and failure of US
manufacturing plants. Quarterly Journal of Economics 1989; 104: 671-
698.
[3] Wagner J. The post-entry performance of new small firms in German
manufacturing industries. Journal of Industrial Economics 1994; 42: 141-
154.
[4] Mata J. Firm growth during infancy. Small Business Economics 1994; 6:
27-39.
[5] Arrighetti A. Entry, growth and survival of manufacturing firms. Small
Business Economics 1994; 6: 127-137.
[6] Audretsch DB, Mahmood T. Firm survival in the Netherlands. Review of
Industrial Organization 2000; 16: 1-11.
[7] Segarra A, Callejn M. New firms- survival and market turbulence: new
evidence from Spain. Review of Industrial Organization 2002; 20: 1-14.
[8] Esteve S, Sanchs A, Sanchs JA. The determinants of survival of Spanish
manufacturing firms. Review of Industrial Organization 2004: 25, 251-
273.
[9] Shumway T. Forecasting bankruptcy more accurately: a simple hazard
model. Journal of Business 2001; 74: 101-124.
[10] Wheelock DC, Wilson PW. Why do banks disappear? The determinants
of US bank failures and acquisitions. Review of Economics and Statistics
2000; 82: 127-138.
[11] Whalen G. A proportional hazards model of bank failure: an examination
of its usefulness as an early warning tool. Economic Review (Federal
Reserve Bank of Cleveland) 1991; 27: 21-31.
[12] Lane WS, Looney S, Wansley J. An application of the Cox proportional
hazards model to bank failure. Journal of Banking and Finance 1986; 10:
511-531.
[13] Carree MA. A hazard rate analysis of Russian commercial banks in the
period 1994-1997. Economic Systems 2003; 27: 255-269.
[14] Cox DR. Regression models and life-tables. Journal of Royal Statistical
Society-Series B 1972; 34: 187-220.
[15] Kaplan EL, Meier P. Nonparametric estimation from incomplete observations.
Journal of the American Statistical Association 1958; 53: 457-
481.
[16] Stute W. Consistent estimation under random censorship when covariables
are present Journal of Multivariate Analysis 1993; 45: 89-103.
[17] Stute W. Distributional convergence under random censorship when
covariables are present Scandinavian Journal of Statistics 1996; 23: 461-
471.
[18] Holl¨ander N, Schumacher M. Estimating the functional form of a
continuous covariate-s effect on survival time. Computational Statistics
and Data Analysis 2006; 50: 1131-1151.
[19] Orbe J. Un Modelo de Regresi'on Parcial Censurado para An'alisis de
Supervivencia. Unpublished Ph.D. Thesis, Departamento de Econometr'─▒a
y Estad'─▒stica, Facultad de Ciencias Econ'omicas y Empresariales, Universidad
del Pa'─▒s Vasco-Euskal Herriko Univertsitatea, Bilbao, Spain, 2000.
[20] Evans DS. Test of alternative theories of firm growth. Journal of Political
Economy 1987; 104: 671-698.
[21] Jovanovic B. Selection and the evolution of industry. Econometrica
1982; 50: 649-670.
[22] Davison AC, Hinkley DV. Bootstrap Methods and Their Application.
Cambridge University Press: Cambridge, 1997.
[1] Audretsch DB, Mahmood, T. New firm survival: new results using a
hazard function. Review of Economics and Statistics 1995; 77: 97-103.
[2] Dunne T, Roberts MJ, Samuelson L. The growth and failure of US
manufacturing plants. Quarterly Journal of Economics 1989; 104: 671-
698.
[3] Wagner J. The post-entry performance of new small firms in German
manufacturing industries. Journal of Industrial Economics 1994; 42: 141-
154.
[4] Mata J. Firm growth during infancy. Small Business Economics 1994; 6:
27-39.
[5] Arrighetti A. Entry, growth and survival of manufacturing firms. Small
Business Economics 1994; 6: 127-137.
[6] Audretsch DB, Mahmood T. Firm survival in the Netherlands. Review of
Industrial Organization 2000; 16: 1-11.
[7] Segarra A, Callejn M. New firms- survival and market turbulence: new
evidence from Spain. Review of Industrial Organization 2002; 20: 1-14.
[8] Esteve S, Sanchs A, Sanchs JA. The determinants of survival of Spanish
manufacturing firms. Review of Industrial Organization 2004: 25, 251-
273.
[9] Shumway T. Forecasting bankruptcy more accurately: a simple hazard
model. Journal of Business 2001; 74: 101-124.
[10] Wheelock DC, Wilson PW. Why do banks disappear? The determinants
of US bank failures and acquisitions. Review of Economics and Statistics
2000; 82: 127-138.
[11] Whalen G. A proportional hazards model of bank failure: an examination
of its usefulness as an early warning tool. Economic Review (Federal
Reserve Bank of Cleveland) 1991; 27: 21-31.
[12] Lane WS, Looney S, Wansley J. An application of the Cox proportional
hazards model to bank failure. Journal of Banking and Finance 1986; 10:
511-531.
[13] Carree MA. A hazard rate analysis of Russian commercial banks in the
period 1994-1997. Economic Systems 2003; 27: 255-269.
[14] Cox DR. Regression models and life-tables. Journal of Royal Statistical
Society-Series B 1972; 34: 187-220.
[15] Kaplan EL, Meier P. Nonparametric estimation from incomplete observations.
Journal of the American Statistical Association 1958; 53: 457-
481.
[16] Stute W. Consistent estimation under random censorship when covariables
are present Journal of Multivariate Analysis 1993; 45: 89-103.
[17] Stute W. Distributional convergence under random censorship when
covariables are present Scandinavian Journal of Statistics 1996; 23: 461-
471.
[18] Holl¨ander N, Schumacher M. Estimating the functional form of a
continuous covariate-s effect on survival time. Computational Statistics
and Data Analysis 2006; 50: 1131-1151.
[19] Orbe J. Un Modelo de Regresi'on Parcial Censurado para An'alisis de
Supervivencia. Unpublished Ph.D. Thesis, Departamento de Econometr'─▒a
y Estad'─▒stica, Facultad de Ciencias Econ'omicas y Empresariales, Universidad
del Pa'─▒s Vasco-Euskal Herriko Univertsitatea, Bilbao, Spain, 2000.
[20] Evans DS. Test of alternative theories of firm growth. Journal of Political
Economy 1987; 104: 671-698.
[21] Jovanovic B. Selection and the evolution of industry. Econometrica
1982; 50: 649-670.
[22] Davison AC, Hinkley DV. Bootstrap Methods and Their Application.
Cambridge University Press: Cambridge, 1997.
@article{"International Journal of Business, Human and Social Sciences:53386", author = "Jesus Orbe and Vicente Nunez-Anton", title = "Duration Analysis of New Firms in the Banking Industry", abstract = "This paper studies the duration or survival time of commercial banks active in the Moscovian three month Rouble deposits market, during the 1994-1997 period. The privatization process of the Russian commercial banking industry, after the 1988 banking reform, caused a massive entry of new banks followed by a period of high rates of exit. As a consequence, many firms went bankrupt without refunding their deposits. Therefore, both for the banks and for the banks- depositors, it is of interest to analyze which are the significant characteristics that motivate the exit or the closing of the bank. We propose a different methodology based on penalized weighted least squares which represents a very general, flexible and innovative approach for this type of analysis. The more relevant results are that smaller banks exit sooner, banks that enter the market in the last part of the study have shorter durations. As expected, the more experienced banks have a longer duration in the market. In addition, the mean survival time is lower for banks which offer extreme interest rates.
", keywords = "Banking, censored, duration, Kaplan-Meier.", volume = "4", number = "6", pages = "798-4", }
