Analysis of international debt problem using artificial neural networks and statistical methods

Neural Computing and Applications

Volumn 19, Issue 8, 2010, Pages 1207-1216

  Yazici, Berna ^a   Memmedli, Memmedaga ^a   Aslanargun, Atilla ^a   Asma, Senay ^a  

^a ANADOLU UNIVERSITY   (Turkey)

Author keywords

Artificial neural network; Backpropagation algorithm; Conjugate gradient method; Logistic and probit regression; Quasi Newton method; Rescheduling and non rescheduling of the international debts

Indexed keywords

ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION NEURAL NETWORKS; ECONOMIC PROBLEMS; NEURAL NETWORK MODEL; QUASI-NEWTON METHODS; RESCHEDULING AND NON-RESCHEDULING OF THE INTERNATIONAL DEBTS; SCIENTIFIC RESEARCHES;

BACKPROPAGATION ALGORITHMS; CONJUGATE GRADIENT METHOD; NETWORK ARCHITECTURE; NETWORK LAYERS; NEWTON-RAPHSON METHOD; OPTIMIZATION; REGRESSION ANALYSIS;

NEURAL NETWORKS;

EID: 77958481827     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-010-0422-4     Document Type: Article

References (33)

1. Aslanargun A, Mammadagha M, Yazici B, Yolacan S (2007) Comparison of ARIMA, neural networks and hybrid models in time series: tourist arrival forecasting. J Stat Comput Simul 77(1): 29-53.
2. Bhaya A, Kaszkurewich E (2004) Steepest descent with momentum for quadratic functions is a version of the conjugate gradient method. Neural Netw 17: 65-71.
3. Bishop CM (1995) Neural networks for pattern recognition. Clarenden Press, Oxford.
4. Burell PR, Folarin BO (1997) The impact of neural networks in finance. Neural Comput Appl 6(4): 193-200.
5. Cooper JCB (1985) Country creditworthiness: a canonical correlation analysis. Glasgow Caledonian University economics discussion paper, no. 3.
6. Cooper JCB (1999) Artificial neural networks versus multivariate statistics: an application from economics. J Appl Stat 26: 909-921.
7. Cheng B, Titterington D (1994) Neural networks: a review from a statistical perspective. Stat Sci 9(1): 2-54.
8. Dhonte P (1975) Describing external debt situations: a roll over approach. IMF Staff Papers 24: 159-186.
9. Feder G, Just R (1977) A study of debt servicing capacity applying logit analysis. J Dev Econ 4: 25-38.
10. Frank CR, Cline WR (1971) Measurement of debt service capacity: an application of discriminant analysis. J Int Econ 1: 327-344.
11. Hagan MT, Demuth HB, Beale MH (1996) Neural network design. PWS, Boston.
12. Haykin S (1999) Neural networks: a comprehensive foundation. Prentice Hall, New Jersey.
13. Kharas H (1984) The long run creditworthiness of developing countries: theory and practice. Quart J Econ 99: 415-439.
14. Kahler M (1985) Politics and international debt: explaining the crisis. Int Organ 39(3): 357-382.
15. Kim TY, Oh KJ, Sohn I, Hwang C (2004) Usefulness of artificial neural networks for early warning system of economic crisis. Expert Syst Appl 26(4): 583-590.
16. Kuan CM, White H (1994) Artificial neural networks: an economic perspective. Econ Rev 13(1): 1-91.
17. Kumar UA (2005) Comparison of neural networks and regression analysis: a new insight. Expert Syst Appl 29: 424-430.
18. Leung MT, Chen A, Daouko H (2000) Forecasting exchange rates using general regression neural networks. Comput Oper Res 27: 1093-1110.
19. Moller M (1993) Scaled conjugate gradient algorithm for fast supervised learning. Neural Netw 6(4): 525-533.
20. Montgomery DC, Peck EA, Vining GG (2001) Introduction to linear regression analysis. Wiley, New York.
21. Nocedal J, Wright SJ (1999) Numerical optimization. Springer, New York.
22. Pettifor A (2003) Resolving international debt crises fairly. Ethics Int Aff 17(2): 2-9.
23. Powers DA, Yu X (2000) Statistical methods for categorical data analysis. Academic Press, London.
24. Qian N (1999) Efficient backpropagation learning using optimal learning rate and on the momentum term in gradient descent learning algorithms. Neural Netw 102(1): 145-151.
25. Riedmiller M, Braun H (1993) A direct adaptive method for faster backpropagation learning: the RPROP algorithm. In: Proceedings of the IEEE international conference on neural networks.
26. Roy J, Cosset J (1990) Forecasting country risk ratings using a neural network. In: Proceedings of the 23rd Hawaii international conference on systems sciences. 4: 327-334.
27. Sharda R (1994) Neural networks for the MS/OR analyst: an application bibliography. Interfaces 24(2): 116-130.
28. Wellons PA (1985) International debt: the behavior of banks in a politicized environment. Int Organ 39(3): 441-471.
29. Wilson R, Sharda R (1992) Neural networks. OR/MS Today, August, 36-42.
30. Wong B, Bodnovich T, Selvi Y (1995) A bibliography of neural networks business application research: 1988-September 1994. Expert Syst 12(3): 253-262. http://www.worldbank.org/data/countrydata.
31. Yoon-Dae E (1979) Commercial banks and the creditworthiness of less developed countries. UMI Research Press, Ann Arbor, MI.
32. Yu XH, Chen GA (1997) Efficient backpropagation learning using optimal learning rate and momentum. Neural Netw 10(3): 517-527.
33. Zhang GP, Patuwo EB, Hu MY (1998) Forecasting with artificial neural networks: the state of the art. Int J Forecast 14: 35-62.