The econometrics of individual risk: Credit, insurance, and marketing

The Econometrics of Individual Risk: Credit, Insurance, and Marketing

Volumn , Issue , 2011, Pages

  Gourieroux, Christian ^a   Jasiak, Joann ^a  

^a NONE

Author keywords

[No Author keywords available]

Indexed keywords

EID: 37049032289     PISSN: None     EISSN: None     Source Type: Book    
DOI: None     Document Type: Book

References (278)

1. Durand, D. 1941. Risk Elements in Consumer Installment Lending. Studies in Consumer Installment Financing, Volume 8. NewYork: National Bureau of Economic Research.
2. Fabozzi, F. 1992. The Handbook of Mortgage Backed Securities. Chicago, IL: Probus.
3. Fabozzi, F., and F. Modigliani. 1992. Mortgage and Mortgage Backed Securities. Harvard, MA: Harvard Business School Press.
4. Fitzpatrick, P. 1932.A comparison of ratios of successful industrial enterprises with those of failed firms. Certified Public Accountant 12:598-605, 659-62, 721-31.
5. Frachot, A., and C. Gourieroux. 1995. Titrisation et Remboursements Anticipés. Paris: Economica.
6. Hassett, M., and D. Stewart. 1999. Probability for Risk Management.Winsted, CT: Actex.
7. Klugman, S., H. Panjer, and G.Willmot. 2004. Loss Models: From Data to Decisions.Wiley.
8. Sandhusen, R. 2000. Marketing. Hauppauge, NY: Barron's.
9. Smith, P. 1964. Measuring risk installment credit. Management Science November:327-40.
10. Amemiya, T., and J. Powell. 1982.A comparison of the logit model and normal discriminant analysis, when the independent variables are binary. In Studies in Econometrics,Time Series and Multivariate Statistics (ed. S. Karlin, T. Amemiya, and L. Goodman). Academic Press.
11. Anderson, T. 1958. An Introduction to Multivariate Statistical Analysis.Wiley.
12. Anderson, T., and R. Bahadur. 1962. Classification into two multivariate normal distributions with different covariance matrices. Annals of Mathematical Statistics 33:420-31.
13. Ball, C., and A. Tscheogl. 1982. The decision to establish a foreign branch bank or subsidiary: an application of binary classification procedures. Journal of Financial and Quantitative Analysis 17:411-24.
14. Boyes,W., L. Hoffman, and S. Low. 1989.An econometric analysis of the bank credit scoring problem. Journal of Econometrics 40:3-14.
15. Cox, D. 1970. Analysis of Binary Data. London: Methuen.
16. Efron, B. 1975. The efficiency of the logistic regression compared to normal discriminant analysis. Journal of the American Statistical Association 70:892-98.
17. Granger, C. 1979. Outline of forecast theory using generalized cost functions. Spanish Economic Review March:161-74.
18. Hand, D. J., and W. E. Henley. 1997. Statistical classification methods in consumer credit scoring: a review. Journal of the Royal Statistical Society A160:523-41.
19. Hastie,T., R.Tibshirani, andA. Buja. 1994. Flexible discriminant analysis by optimal scoring. Journal of the American Statistical Association 89:1255-70.
20. Krzanowski, W. 1975. Discrimination and classification using both binary and continuous variables. Journal of the American Statistical Association 70:782-90.
21. Lachenbruch, P. 1975. Discriminant Analysis. NewYork: Hafner.
22. Lachenbruch, P., C. Sneeringer, and L. Revo. 1973. Robustness of the linear and quadratic discriminant function to certain types of non normality. Journal of the American Statistical Association 68:176-79.
23. McFadden, D. 1973. Conditional logit analysis of qualitative choice behavior. In Frontiers in Econometrics (ed. P. Zarembka). Academic Press.
24. McFadden, D. 1976. A comment on discriminant analysis versus logit analysis. Annals of Economic and Social Measurement 5:511-24.
25. Merton, R. 1974. On the pricing of corporate debt: the risk structure of interest rates. Journal of Finance 29:449-70.
26. O'Neil, T. 1980. The general distribution of the error rate of a classification procedure with application to logistic regression discrimination. Journal of the American Statistical Association 75:154-60.
27. Press, S., and S.Wilson. 1978. Choosing between logistic regression and discriminant analysis. Journal of the American Statistical Association 73:699-705.
28. Ripley, E. 1994. Neural networks and related methods for classification. Journal of the Royal Statistical Society B56:409-56.
29. Rosenberg, E., and A. Gleit. 1994. Quantitative methods in credit management: a survey. Operations Research 42:589-613.
30. Walker, S., and D. Duncan. 1967. Estimation of the probability of an event as a function of several independent variables. Biometrika 1:167-79.
31. Wiginton, J. C. 1980. A note on the comparison of the logit and discriminant models of consumer credit behaviour. Journal of Financial Quantitative Analysis 15:757-70.
32. Chesser, D. 1974. Predicting loan noncompliance. Journal of Commercial Bank Lending August:28-38.
33. Collins, R. 1980.An empirical comparison of bankruptcy prediction models. Financial Management 9:51-57.
34. Cox, D., and E. Snell. 1989. The Analysis of Binary Data. London: Chapman & Hall. Dambolena, I., and S. Khoury. 1980. Ratios stability and corporate failure. Journal of Finance 35:1017-26.
35. Dambolena, I., and S. Khoury. 1980. Ratios stability and corporate failure. Journal of Finance 35:1017-26.
36. Deakin, E. 1972.Adiscriminant analysis of predictors of business failure. Journal of Accounting Research 10:167-79.
37. Deakin, E. 1976. Distributions of financial accounting ratios: some empirical evidence. Accounting Review January:90-96.
38. Dopuch, N., R. Holthausen, and R. Leftwich. 1987. Predicting audit qualifications with financial and market variables. Accounting Review 62:431-54.
39. Ederington, L. 1985. Classification models and bond ratings. Financial Review 20:237-62.
40. Eisenbeis, R. 1977. Pitfalls in the application of discriminant analysis in business, finance and economics. Journal of Finance 32:875-900.
41. Epley, D., T. Cronan, and L. Perry. 1985. A research note on discrimination in mortgage lending. Journal of the American Real Estate and Urban Economics Association 13:446- 51.
42. Fitzpatrick, P. 1932.A comparison of ratios of successful industrial enterprises with those of failed firms. Certified Public Accountant 12:598-605, 659-62, 721-31.
43. Frecka, T., and W. Hopwood. 1983. The effects of outliers on the cross-sectional properties of financial ratios. Journal of Accounting Research January:115-28.
44. Freidman, J., T. Hastie, and R. Tibshirani. 1999. Additive logistic regression: a statistical view of bootstrapping.Working Paper, Stanford University.
45. Galitz, L. 1983. Consumer credit analysis. Managerial Finance 9:27-33.
46. Gentry, J., P. Newbold, and D. Whitford. 1987. Funds flow components, financial ratios and bankruptcy. Journal of Business Finance and Accounting 14:595-606.
47. Gourieroux, C. 1989. Econométrie des Variables Qualitatives, 2nd edn, Chapters 1 and 3. Paris: Economica. (English version, 2000: Econometrics of Qualitative Dependent Variables. Cambridge University Press.)
48. Hausman, J. 1982. Specification tests in econometrics. Econometrica 50:749-59.
49. Ho, K., and C. Robinson. 2000. Personal Financial Planning. Toronto: Captus. Horrigan, J. 1965. Some empirical bases of financial ratios analysis. Journal of Accounting Research July:558-68.
50. Horrigan, J. 1965. Some empirical bases of financial ratios analysis. Journal of Accounting Research July:558-68.
51. Johnson, C. 1970. Ratio analysis and the prediction of firm failure. Journal of Finance 25:1166-68.
52. Joy, M., and J. Tollefson. 1975. On the financial applications of discriminant analysis. Journal of Financial and Quantitative Analysis December:723-38.
53. Karel, G., and A. Prakash. 1987. Multivariate normality and forecasting of business bankruptcy. Journal of Business Finance and AccountingWinter:573-92.
54. Lev, B., and S. Sunder. 1979. Methodological issues in the use of financial ratios. Journal of Accounting and Economics December:187-210.
55. Lo, A. 1986. Logit versus discriminant analysis. Journal of Econometrics 31:151-78.
56. McDonald, B., and M. Morris. 1984. The statistical validity of the ratio method in financial analysis: an empirical examination. Journal of Business Finance and Accounting Spring:89-98.
57. McLeay, S. 1986a. The ratio of means and the mean of ratios and other benchmarks: an examination of characteristic financial ratios in the french corporate sector. Finance 7:75- 93.
58. McLeay, S. 1986b. Student's t and the distribution of financial ratios. Journal of Business Finance and Accounting Summer:209-21.
59. Maddala, G. S. 1983. Limited dependent and qualitative variables in econometrics, Chapters 2 and 4. Cambridge University Press.
60. Maddala, G. S. 1991. A perspective in the use of limited dependent and qualitative variables in accounting research. Accounting Review 66:788-807.
61. Martin, D. 1977. Early warning of bank failure: a logit regression approach. Journal of Banking and Finance 1:249-76.
62. Meyer, P., and H. Pifer. 1970. Prediction of bank failures. Journal of Finance 25:853-68.
63. Myers, J., and E. Forgy. 1963. The development of numerical credit evaluation systems. Journal of the American Statistical Association September:799-806.
64. O'Connor, M. 1973. On the usefulness of financial ratios to investors in common stocks. Accounting Review April:339-52.
65. Ohlson, J. 1980. Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research 18:109-31.
66. Orgler, Y. 1970. A credit scoring model for consumer loans. Journal of Money Credit and Banking November:435-525.
67. Perry, L., and T. Cronan. 1986.A note on rank transformation discriminant analysis. Journal of Banking and Finance 10:605-10.
68. Perry, L., T. Cronan, and G. Henderson. 1985. Industry classification, ordinal data and bond rating decision models. Decision ScienceWinter:14-24.
69. Pinches, G., and J. Trieschman. 1977. Discriminant analysis, classification results and financially distressed property-liability insurers. Journal of Risk and Insurance 44:289-98.
70. Santomero, A., and J.Vinso. 1977. Estimating the probability of failure for commercial banks and the banking system. Journal of Banking and Finance September:185-205.
71. SAS. 1995. User's Guide: The LOGISTIC Procedure, Version 6, Volume 2, pp. 1077-121. Cary, NC: SAS.
72. Scott, J. 1981. The probability of bankruptcy: a comparison of empirical predictions and theoretical models. Journal of Banking and Finance 5:317-44.
73. Sinkey, J. 1975. A multivariate statistical analysis of the characteristics of problem banks. Journal of Finance 29:21-35.
74. So, J. 1987. Some empirical evidence on the outliers and the non-normal distribution of financial ratios. Journal of Business Finance and Accounting 14:483-96.
75. Whittington, G. 1980. Some basic properties of accounting ratios. Journal of BusinessFinance and Accounting Summer:219-32.
76. Wilcox, J. 1971.Asimple theory of financial ratios as predictors of failure. Journal of Accounting Research Autumn:389-95.
77. Zavgren, C. 1983. The prediction of corporate failure: the state of the art. Journal of Accounting Literature Spring:1-38.
78. Zavgren, C. 1985. Assessing the vulnerability to failure of american industrial firms: a logistic analysis. Journal of Business Finance and Accounting 12:19-45.
79. Zavgren, C., M. Dugan, and J. Reeve. 1988. The association between probabilities of bankruptcy and market responses. A test of market anticipation. Journal of Business Finance and Accounting 15:27-95.
80. Zmijewski, M. 1984. Methodological issues related to the estimation of financial distress prediction models. Journal of Accounting Research 22(Supplement):58-86.
81. Gouriéroux, C. 1992. Courbes de performances et de discrimination. Annales d'Economie et de Statistique 28:107-23.
82. Lehmann, E. 1966. Some concepts of dependence. Annals of Mathematical Statistics 37:1137-53.
83. Kimeldorf, G., and A. Sampson. 1987. Positive dependence orderings. Annals of the Institute of Statistics and Mathematics 39:113-28.
84. Novak, T., de Leeuw, J., and B. McEroy. 1992. Richness curves for evaluating market segmentation. Journal of Marketing Research 29:254-67.
85. Schriever, B. 1987. An ordering for positive dependence. Annals of Statistics 15:1208-14.
86. Suppes, P. 1970. A Probabilistic Theory of Causality. Amsterdam: North-Holland.
87. Barnett, A., M. Abraham, and V. Schimmel. 1979. Airline safety: some empirical findings. Management Science 25:1045-56.
88. Besson, J., and C. Partrat. 1992. Trend et systèmes de bonus-malus. ASTIN Bulletin 22:11-31.
89. Brannas, K., and P. Johansen. 1996. Panel data regression for counts. Statistical Papers 37:191-213.
90. Cameron, A., and P. Trivedi. 1998. Regression Analysis of Count Data. Cambridge University Press.
91. Cameron, A., and P. Trivedi. 1999. Essentials of count data regression. In Companion in Econometric Theory (ed. B. Baltagi). Oxford: Blackwell.
92. Cameron, A., P. Trivedi, F. Milne, and J. Pigott. 1988. A microeconometric model of the demand for health care and health insurance in Australia. Review of Economic Studies 55:85-106.
93. Campbell, J. 1934. The Poisson correlation function. Proceedings of the Edinburgh Mathematical Society 2:18-26.
94. Chalk, A. 1986. Market forces and airline safety: the case of DC-10. Economic Inquiry 24:43-60.
95. Cummins, J., and A. Powell. 1980. The performance of alternative models for forecasting automobile insurance paid claim costs. ASTIN Bulletin 11:91-106.
96. Davutyan, N. 1989. Bank failures as Poisson variates. Economic Letters 29:333-38.
97. Delgado, M., and T. Kniesner. 1997. Count data models with variance of unknown form: an application to a hedonic model of worker absenteeism. Review of Economics and Statistics 79:41-49.
98. Dionne, G., and C.Vanasse. 1989.Ageneralization of automobile insurance rating models: the negative binomial distribution with a regression component. ASTIN Bulletin 19:199-221.
99. Edwards, C., and J. Gurland. 1961. A class of distributions applicable to accidents. Journal of the American Statistical Association 56:503-17.
100. Ganio, L., and D. Schafer. 1992. Diagnostics for overdispersion. Journal of the American Statistical Association 87:795-804.
101. Golbe, D. 1986. Safety and profits in the airline industry. Journal of Industrial Economics 34:305-18.
102. Gourieroux, C. 1989. Econométrie des Variables Qualitatives, 2nd edn, Chapter X. Paris: Economica.
103. Gourieroux, C. 1999a. Statistique de l'Assurance. Paris: Economica.
104. Gourieroux, C. 1999b. Econometrics of risk classification in insurance. Geneva Papers for Risk and Insurance 24:119-37.
105. Gourieroux, C., and J. Jasiak. 2000. Nonlinear panel data models with dynamics heterogeneity. In Panel Data Econometrics: Future Directions (ed. J. Krishnakumar and E. Ronchetti), pp. 127-47. Elsevier.
106. Gourieroux, C., A. Monfort, and A. Trognon. 1984. Pseudo maximum likelihood methods: application to Poisson models. Econometrica 52:701-20.
107. Graham, D., and M. Bowes. 1979. Do finances influence airline safety, maintenance and services? Report to the Civil Aeronautics Board, Contract 78-C-60. Public Research Institutes, Center for Naval Analysis.
108. Gurmu, S. 1991. Tests for detecting overdispersion in the positive Poisson regression model. Journal of Business and Economics Statistics 9:215-22.
109. Hamdan, M., and H. Al-Bayyati. 1971. Canonical expansion of the compound correlated bivariate Poisson distribution. Journal of the American Statistical Association 66:390-93.
110. Hausman, J., B. Hall, and Z. Griliches. 1984. Econometric models for count data with an application to the patents-R&D relationship. Econometrica 52:909-38.
111. Jung, J. 1968. On automobile insurance rate making. ASTIN Bulletin 5:41-48.
112. Kanafani, A., and T. Keeler. 1989. New entrants and safety: some statistical evidence on the effects of airline deregulation. In Safety Performance under Deregulation (ed. L. Moses and I. Savage). Oxford University Press.
113. Klugman, S. A., H. H. Panjer, and G. E.Willmot. 2004. Loss Models; from Data to Decisions, 2nd edn.Wiley.
114. Lawless, J. 1987. Negative binomial and mixed Poisson regression. The Canadian Journal of Statistics 15:209-25.
115. Lemaire, J. 1985. Automobile Insurance: Actuarial Models. Dordrecht: Kluwer-Nijhoff.
116. Lee, L. 1986. Specification test for Poisson regression models. International Economic Review 27:687-706.
117. Mullahy, J. 1986. Specification and testing in some modified count data models. Journal of Econometrics 33:341-65.
118. Ramaswamy, V., E. Anderson, and W. De Sarbo. 1993. A disaggregate negative binomial regression procedure for count data analysis. Management Science 40:405-17.
119. Rose, N. 1989. Financial influence on airline safety. In Safety Performance Under Deregulation (ed. L. Moses and I. Savage). Oxford University Press.
120. Rose, N. 1990. Profitability and product quality: economic determinants of airline safety performance. Journal of Political Economy 98:944-64.
121. Van Eeghen, J., E. Greup, and J. Nijssen. 1984. Rate making. Surveys of Actuarial Studies, Volume 2. Rotterdam: Nationale-Nederlanden, N.V.
122. Wang, P., M. Puterman, I. Cockburn, and N. Le. 1996. Mixed Poisson regression models with covariate dependent rates. Biometrics 52:381-400.
123. Wedel, M.,W. De Sarbo, J. Bult, and V. Ramaswany. 1993.A latent class Poisson regression model for heterogenous count data. Journal of Applied Econometrics 8:397-411.
124. Winkelmann, R. 1995. Duration dependence and dispersion in count data models. Journal of Business and Economic Statistics 13:467-74.
125. Winkelmann, R. 1997. Count Data Models: Econometric Theory and Application to Labor Mobility Springer.
126. Bartholomew, L., J. Berk, and R. Roll. 1988.Adjustable rate mortgages prepayment behaviour. Housing Finance Review 7:31-46.
127. Cox, D. R. 1962. Renewal Theory. London: Methuen.
128. Cox, D. R. 1972. Regression models and life tables. Journal of the Royal Statistical Society B34:187-220.
129. Cox, D. R. 1975. Partial likelihood. Biometrika 62:269-76.
130. Cox, D. R., and D. Oakes. 1984. Analysis of Survival Data. London: Chapman & Hall.
131. De Toldi, M., C. Gourieroux, and A. Monfort. 1995. Prepayment analysis for securitization. Journal of Empirical Finance 2:45-70.
132. Fons, J. 1994. Using default rates to model the term structure of credit risk. Financial Analyst Journal September:25-31.
133. Frachot, A., and C. Gourieroux. 1995. Titrisation et Remboursements Anticipés. Paris: Economica.
134. Gourieroux, C., and J. Jasiak. 1999. Durations. In Companion in Econometric Theory (ed. B. Baltagi). Oxford: Blackwell.
135. Gupta, S. 1991. Stochastic Models of interpurchase time with time dependent covariates. Journal of Marketing Research 28:1-15.
136. Hartman, R., and C. Wattes. 1987. The determination of average hospital length of stay: an economic approach. Quarterly Review of Economics and Business 18:83-96.
137. Hayre, L., K. Lauterbach, and C. Mohebbi. 1989. Prepayment models and methodologies. In Advances and Innovations in the Bond and Mortgage Markets (ed. F. J. Fabozzi), pp. 259- 304. Chicago, IL: Probus Publishing
138. Heckman, J. 1981. Heterogeneity and state dependence. In Studies in Labor Markets (ed. S. Rosen). University of Chicago Press.
139. Heckman, J., and B. Singer. 1974. Econometric duration analysis. Journal of Econometrics 24:63-132.
140. Heckman, J., and B. Singer. 1984. The identifiability of the proportional hazard model. Review of Economic Studies 52:231-41.
141. Jarrow, R., and S. Turnbull. 1992. Drawing the analogy. Risk Magazine 5:63-71.
142. Kalbfleisch, J., and R. Prentice. 1980. The Statistical Analysis of Failure Time Data.Wiley.
143. Kennan, J. 1985. The duration of contract strikes in U.S. manufacturing. Journal of Econometrics 28:5-28.
144. Lee, E. 1992. Statistical Methods for Survival Data Analysis.Wiley.
145. Meyer, B. 1990. Unemployment insurance and unemployment spells. Econometrica 58:757- 82.
146. Kiefer, N. 1984. A simple test for heterogeneity in exponential models of duration. Journal of Labor Economics 2:539-49.
147. Kim, I., K. Ramaswamy, and S. Sundaresan. 1993. Does default risk affect the valuation of corporate bonds? A contingent claims model. Financial Management Autumn:117-31.
148. Lancaster,T. 1985. Generalized residuals and heterogenous duration models, with application to theWeibull model. Journal of Econometrics 28:155-69.
149. Lancaster, T. 1990. The Econometric Analysis of Transition Data. Cambridge University Press.
150. Lee, L. 1984.Maximumlikelihood estimation and a specification test for normal distributional assumption for accelerated failure time models. Journal of Econometrics 24:159-79.
151. Merton, R. 1974. On the pricing of corporate debt: the risk structure of interest rates. Journal of Finance 29:449-70.
152. Richard, S., and R. Roll. 1989. Prepayments on fixed rate mortgage backed securities. Journal of Portfolio Management 15:73-82.
153. Van den Berg, G. 1997. Association measures for durations in bivariate hazard rate models. Journal of Econometrics 79:221-45.
154. Van den Berg, G. 2001. Duration models: specification, identification and multiple durations. In Handbook of Econometrics (ed. J. Heckman and E. Leamer), Volume 5, pp. 3381-480. Amsterdam: North-Holland.
155. Gumbel, E. 1960. Bivariate logistic distributions. Journal of the American Statistical Association 55:698-707.
156. Hartman, R. 1991. A Monte-Carlo analysis of alternative estimators in models involving selectivity. Journal of Business and Economic Statistics 9:41-50.
157. Hsieh, D., C. Manski, and D. McFadden. 1985. Estimation of response probabilities from augmented retrospective observations. Journal of the American Statistical Association 80:651-62.
158. Joy, O., and J. Toffelson. 1975. On the financial applications of discriminant analysis. Journal of Financial and Quantitative Analysis December:723-39.
159. King, G., and L. Zeng. 1999. Logistic regression in rare events data. Political Analysis 9:137- 63.
160. Lancaster, T., and G. Imbens. 1990. Choice based sampling of dynamic populations. In Panel Data and Labor Market Studies (ed. J. Hartog, G. Ridder, and J. Theeuwes), pp. 21-44. Amsterdam: North-Holland.
161. Manski, C. 1989.Anatomy of the selection problem. Journal of Human Resources 24:343-60.
162. Manski, C. 1994. The selection problem. In Advances in Econometrics, SixthWorld Congress (ed. C. Sims), pp. 143-70. Cambridge University Press.
163. Manski, C., and S. Lerman. 1987. The estimation of choice probabilities from choice based samples. Econometrica 45:1977-88.
164. Manski, C., and D. McFadden. 1991. Alternative estimation and sample designs for discrete choice analysis. In Structural Analysis of Discrete Data with Econometric Applications (ed. C. Manski and D. McFadden). Cambridge, MA: MIT Press.
165. Meng, C., and P. Schmidt. 1985. On the cost of partial observability in the bivariate probit model. International Economic Review 26:71-86.
166. Newey, J. 1988. Two step series estimation of sample selection models. Massachusetts Institute of Technology, Department of EconomicsWorking Paper, No. 99-04.
167. Palepu, K. 1986. Predicting takeover targets: a methodological and empirical analysis. Journal of Accounting and Economics 8:3-35.
168. Poirier, D. 1980. Partial observability in bivariate probit models. Journal of Econometrics 12:209-17.
169. Sawa, T. 1984. A generalization of the univariate logit model and its bivariate extension. London School of EconomicsWorking Paper EM/1984/93.
170. Xie, Y., and C. Manski. 1989. The logit model and response based samples. Sociological Methods and Research 17(3):283-302.
171. Blum, M., F. Lim, and C. McKinlay. 1998. The declining credit quality of US corporate debt: myth or reality?. Journal of Finance 53:1389-413.
172. Gantmacher, F. 1959. The Theory of Matrices. NewYork: Chelsea.
173. Grundy, B. 1997. Preferreds and taxes. The relative price of dividends and coupons. University of Pennsylvania Discussion Paper.
174. Hickman, W. 1958. Corporate Bond Quality and Investor Experience. Princeton University Press.
175. Janssen, J., and R. Manca. 1997.A realistic nonhomogeneous stochastic pension funds model on scenario basis. Scandinavian Actuarial Journal 2:113-37.
176. Lucas, D., and J. Lonski. 1992. Changes in corporate credit quality 1970-1990. Journal of Fixed Income 1:7-14.
177. McRae, E. 1977. Estimation of time varying Markov processes with aggregate data. Econometrica 45:183-98.
178. Pender, K. 1992. Demystifying the ratings game. San Francisco Chronicle, February 17.
179. Pitacco, E. 1995.Actuarial models for pricing disability benefits: towards a unifying approach. Insurance: Mathematics and Economics 16:39-62.
180. Spilerman, S. 1972. The analysis of mobility processes by the introduction of independent variables into a Markov chain. American Sociological Review 37:277-94.
181. Standard& Poor's. 1996. Standard& Poor's Corporate Ratings Criteria. NewYork: Standard & Poor's.
182. Allenby, G., and P. Lenk. 1994. Modeling household purchase behavior with logistic normal regression. Journal of the American Statistical Association 89:1218-31.
183. Amemiya, T., M. Saito, and K. Shimono. 1993. A study of household investment patterns in Japan: an application of generalized tobit models. The Economic Studies Quarterly 44:13-28.
184. Bertaut, C. 1992. Who holds stocks in the US? An empirical investigation. University of Maryland Discussion Paper (December).
185. Brennan, M. 1975. The optimal number of securities in a risky asset portfolio when there are fixed costs of transacting: theory and some empirical evidence. Journal of Financial and Quantitative Analysis 10:483-96.
186. Caroll, D., and A. Samwick. 1998. How important is precautionary saving? Review of Economics and Statistics 98:410-19.
187. Dambolena, I., and S. Khoury. 1980. Ratio stability and corporate failure. Journal of Finance 35:1017-26.
188. Domowitz, J. 1996. Empirical models of income uncertainty and precautionary saving. University of Michigan Discussion Paper.
189. Dumas, B., and E. Luciano. 1991. An exact solution to a dynamic portfolio choice problem under transaction costs. The Journal of Finance 46:577-95.
190. Gill, L., and A. Lewbel. 1992. Testing the rank and definiteness of estimated matrices with applications to factors, state space andARMA models. Journal of the American Statistical Association 87:766-76.
191. Goldsmith, D. 1976.Transaction costs and the theory of portfolio selection. Journal ofFinance 31:1127-39.
192. Gourieroux, C. 1989. Econométrie des Variables Qualitatives, 2nd edn. Paris: Economica.
193. Gourieroux, C., A. Monfort, and E. Renault. 1995. Inference in factor models. In Advances in Econometrics and Quantitative Economics (ed. G. Maddala, P. C. B. Phillips, and T. Srinivasan), pp. 311-53. Oxford: Blackwell.
194. Guiso, L.,T. Japelli, and D.Terlitzzese. 1996. Income risk, borrowing constraints and portfolio choice. American Economic Review 86:158-72.
195. Haliassos, M., and C. Bertaut. 1995. Why do so few hold stocks? The view from asset pricing theory. Economic Journal 105:1110-29.
196. Hess, A. 1991. The effects of transaction costs on households financial asset demand. Journal of Money, Credit and Banking 23:383-409.
197. Hsu, P. 1991. Canonical reduction of the general regression problem. Annals of Eugenics 11:42-46.
198. Kimball, M. 1990. Precautionary saving in the small and in the large. Econometrica 58:53-73.
199. Koo, H. 1991. Consumption and portfolio choice with uninsurable income risk. Princeton University Discussion Paper.
200. Lintner, J. 1971. The effect of short selling and margin requirements in perfect capital markets. Journal of Financial and Quantitative Analysis 5:1173-95.
201. Markowitz, H. 1992. Portfolio Selection: Efficient Diversification of Investment, 2nd edn. Wiley.
202. Paxson, C. 1990. Borrowing constraints and portfolio choice. Quarterly Journal of Economics 105:535-43.
203. Shorrocks,A. 1982. The composition of asset holdings in the United Kingdom. The Economic Journal 92:268-84.
204. Uhler, R., and J. Cragg. 1971. The structure of the asset portfolios of households. Review of Economic Studies 42:341-57.
205. Bockenholt, U. 1999. Mixed INAR(1) Poisson regression models: analyzing heterogeneity and serial dependencies in longitudinal count data. Journal of Econometrics 89:317-38.
206. Brannas, K., and J. Hellstrom. 2001. Generalization to the integer valued AR(1) model. Econometric Reviews 20:425-43.
207. Bucklin, R., and J. Lattin. 1991. A two-state model of purchase incidence and brand choice. Marketing Science 19:24-39.
208. Campbell, J. 1934. The Poisson correlated function. Proceedings of the Edinburgh Mathematical Society 2:18-26.
209. Carling, K., T. Jacobson, and K. Roszbach. 1998. Duration of consumer loans and bank lending policy: dormancy versus default risk. Stockholm School of Economics, Working Paper 280.
210. Chintagunta, P. 1993. Investigating purchase incidence, brand choice and purchase quantity decisions of households. Marketing Science 12:184-208.
211. Gourieroux, C., and J. Jasiak. 2004. Heterogeneous INAR(1) model with application to car insurance. Insurance: Mathematics and Economics 34:177-92.
212. Dirickx,Y., and L.Wakeman. 1976. An extension of the Bierman-Hausman model for credit granting. Management Science 22:1229-37.
213. Ehrenberg, A. 1988. Repeat Buying. Oxford University Press.
214. Engle, R., and J. Russell. 1997. Forecasting the frequency of change in quoted foreign exchange prices with the autoregressive conditional duration model. Journal of Empirical Finance 4:187-212.
215. Engle, R., and J. Russell. 1998. The autoregressive conditional duration model. Econometrica 66:1127-63.
216. Fisher, R. 1938. The statistical utilization of multiple measurements. Annals of Eugenics VIII:376-86.
217. Ghysels, E., C. Gourieroux, and J. Jasiak. 2003. Stochastic volatility duration models. Journal of Econometrics 119:413-33.
218. Gourieroux, C. 1999. The econometrics of risk classification in insurance. Geneva Papers for Risk and Insurance 24(2):119-37.
219. Gourieroux, C., and J. Jasiak. 1999. Nonlinear panel data model with dynamic heterogeneity. In Panel Data Econometrics: Future Directions (ed. J. Krishnakumar and E. Ronchetti), pp. 127-48. Amsterdam: North-Holland.
220. Gourieroux, C., and J. Jasiak. 2004. Heterogeneous INAR(1) model with application to car insurance. Insurance, Mathematics and Economics 34:177-92.
221. Gourieroux, C., and J. Jasiak. 2006. Autoregressive gamma process. Journal of Forecasting 25:129-152.
222. Gourieroux, C., and A. Monfort. 1996. Simulation Based Econometric Methods. Oxford University Press.
223. Gross, D., and N. Souleles. 1999. Howdo people use credit cards? University of Pennsylvania Discussion Paper.
224. Hamdan, M. and H. Al-Bagyati. 1971. Canonical expansion of the compound correlated bivariate Poisson distribution. Journal of the American Statistical Association 66:390-93.
225. Harvey, A., and C. Fernandez. 1989. Time series models for count or qualitative observations. Journal of Business and Economic Statistics 7:407-22.
226. McKenzie, E. 1988. Some ARMA models for dependent sequences of Poisson counts. Advances in Applied Probability 20:822-35.
227. Neslin, S., C. Henderson, and J. Quelch. 1985. Consumer promotions and the acceleration of product purchases. Marketing Science 4:147-65.
228. Roszbach, K. 1998. Bank lending policy, credit scoring and the survival of loans. Stockholm School of Economics,Working Paper 261.
229. Srinivasan, V., and Y. Kim. 1987. The Bierman-Hausman credit granting model: a note. Management Science 33:1361-62.
230. Zeger, S. 1988. A regression model for time series of counts. Biometrika 75:621-29.
231. Albanese, C. 1997. Credit exposure, diversification risk and coherent VaR. University of Toronto Discussion Paper.
232. Altman, E. I., and D. L. Kao. 1992. Rating drift in high yield bonds. Journal of Fixed Income 2:15-20.
233. Artzner, P., F. Delbaen, J. Eber, and D. Heath. 1997. Thinking coherently. Risk 10:68-71.
234. Artzner, P., F. Delbaen, J. Eber, and D. Heath. 1999. Coherent measures of risk. Mathematical Finance 9:203-28.
235. Bangia, A., F. Diebold, A. Kronimus, C. Schlagen, and T. Schuermann. 2002. Ratings migration and business cycle, with application to credit portfolio stress testing. Journal of Banking and Finance 26:445-74.
236. Basle Committee on Banking Supervision. 2003. The new Basle capital accord. Third Consultative Document (available at www.bis.org/bcbs/cp3full.pdf).
237. Basle Committee on Banking Supervision. 2004. Modifications to the capital treatment for expected and unexpected credit losses (available at www.bis.org/publ/bcbs104.pdf).
238. Bassi, F., P. Embrechts, and M. Kafetzaki. 1997. Risk management and quantile estimation. In Practical Guide to Heavy Tails (ed. R. Adler, R. Feldman, and M. Taqqu). Boston, MA: Birkhauser.
239. Black, F., and J. Cox. 1976. Valuing corporate securities: some effects of bond indenture provisions. Journal of Finance 31:351-67.
240. Brady, B., and R. Bos. 2002. Record default in 2001. The result of poor credit quality and a weak economy. Standard & Poor's Technical Report (February 2002).
241. Brady, B., D. Vazza, and R. J. Bos. 2003. Ratings performance 2002: default, transition, recovery, and spreads. Standard & Poor's Technical Paper.
242. Carey, M., and M. Hrycay. 2001. Parameterizing credit risk models with rating data. Journal of Banking and Finance 25:197-270.
243. Carty, L. 1997. Moody's rating migration and credit quality correlation, 1920-96. Moody's Investor Service Technical Report (July 1997).
244. Credit Suisse Financial Products. 1997. CreditRisk+: technical manual. CSFP (Financial Markets) Discussion Paper.
245. De Servigny, A., and O. Renault. 2002. Default correlation: empirical evidence. Standard & Poor's Technical Report (September 2002).
246. Dowd, K. 1998. Beyond Value at Risks: The New Science of Risk Management.Wiley. Duffie, D., and J. Pan. 1997. An overview of Value at Risk. Journal of Derivatives 4:7-49.
247. Embrechts, P., A. McNeil, and D. Straumann. 2002. Correlation and dependency in risk management: properties and pitfalls. In Risk Management, Value-at-Risk and Beyond (ed. M. Dempster), 176-223. Cambridge University Press.
248. Feng, D., C. Gourieroux, and J. Jasiak. 2004. The ordered qualitative model for credit rating transitions. CREF Discussion Paper.
249. Foulcher, S., C. Gouríeroux, and A. Tiomo. 2004. Term structure of defaults and ratings. Insurance and Risk Management 72:207-76.
250. Foulcher, S., C. Gouríeroux, and A. Tiomo. 2006. Latent variable approach to modelling dependence of credit risks: application to French firms and implications for regulatory capital. Annales d'Economie et Statistiques, forthcoming.
251. Frey, R., and A. McNeil. 2003. Dependent defaults in models of portfolio credit risk. Journal of Risk 6:59-62.
252. Gagliardini, P., and C. Gouríeroux. 2005a. Stochastic migration models. Journal of Financial Econometrics 3:188-226.
253. Gagliardini, P., and C. Gouríeroux. 2005b. Migration correlation: definition and consistent estimation. Journal of Banking and Finance 29:865-94.
254. Gourieroux, C., and J. Jasiak. 2000. Financial Econometrics. Princeton University Press.
255. Gourieroux, C., and J. Jasiak. 2004. Value at Risk. In Handbook of Financial Econometrics, forthcoming.
256. Gourieroux, C., and A. Monfort. 2002. Equidependence in duration models. CREST Discussion Paper.
257. Gourieroux, C., A. Monfort, and V. Polimenis. 2006. Affine model for credit risk analysis. Journal of Financial Econometrics 4:494-530.
258. Gupton, G., C. Finger, and M. Bhatia. 1997. Creditmetrics: technical document. JPMorgan Technical Report.
259. Hamilton, D., R. Cantor, and S. Ou. 2002. Default and recovery rates of corporate bond issuers: a statistical review of Moody's ratings performance 1970-2001. Moody'sWorking Paper.
260. Jarrow, R., and S. Turnbull. 1992. Drawing the analogy. Risk Magazine 5:63-71.
261. Jarrow, R., and S. Turnbull. 1995. Pricing derivatives on financial securities subject to credit risk. Journal of Finance 50:53-85.
262. Jorion, P. 1997. Value at Risk: The New Benchmark for Controlling Market Risk. Chicago, IL: Irwin.
263. JPMorgan. 1996. Risk Metrics Technical Document, 4th edn. NewYork: JPMorgan.
264. JPMorgan. 1997. CreditMetrics Technical Document. NewYork: JPMorgan.
265. Kim, I., K. Ramaswamy, and S. Sundaresan. 1993. Does default risk affect the valuation of corporate bonds? A contingent claims model. Financial Management Autumn:117-31.
266. Lando, D. 1998. On Cox processes and credit risky securities. Review of Derivatives Research 2:99-120.
267. Lando, D., and T. Skodeberg. 2002. Analyzing rating transitions and rating drift with continuous observations. Journal of Banking and Finance 26:423-44.
268. Loffler, G. 2004. An anatomy of rating through the cycle. Journal of Banking and Finance 28:695-720.
269. Lucas, D. 1995. Default correlation and credit analysis. Journal of Fixed Income March:76- 87.
270. Merton, R. 1974. On the pricing of corporate debt: the risk structure of interest rates. Journal of Finance 29:449-70.
271. Nagpal, K., and R. Bahar. 1999. An analytical approach for credit risk analysis under correlated default. CreditMetrics Monitor April:51-79.
272. Nickell, P., W. Perraudin, and S. Varotto. 2000. Stability of rating transitions. Journal of Banking & Finance 24:203-27.
273. Rosch, D. 2003. Correlations and business cycles of credit risks: evidence from bankruptcies in Germany. Financial Markets and Portfolio Management 17:309-31.
274. Rosch, D. 2005. An empirical comparison of default risk forecasts from alternative credit rating philosophies. International Journal of Forecasting 21:37-51.
275. Santomero,A., and D. Babbel. 1996. Risk management by insurers: an analysis of the process. Wharton Financial Institutions Center, Discussion Paper 96-16.
276. Stulz, R. 1998. Derivatives, Risk Management and Financial Engineering. Belmont, CA: Southwestern Publishing.
277. Wang, T. 1998.A characterization of dynamic risk measures. University of British Columbia Discussion Paper (October).
278. Zhou, C. 1997. A jump diffusion approach to modeling credit risk and valuing defaultable securities. Finance and Economics, Federal Reserve Board Discussion Paper.