Macro finance early warning system

Abstract

In this paper, a financial early warning information system is developed based on the multi-dimensional climate approach that is featured with a multi-dimensional index construction and the relevant multi-dimensional analysis. Requirement analysis and design issues of building an information system supporting this multi-dimensional climate approach are discussed in detail. And a case using this system to study the macro financial issues is presented to illustrate how the proposed multi-dimensional approach works in the information system we design. This research is an interdisciplinary work of economic theories, macro financial empirical studies, and software engineering. With advanced macro financial early warning theories implemented in a web application, the Macro Financial Early Warning System (FEWS) developed in this research has been proved to be effective in a trial running in the Forecasting research institute of the Chinese Academy of Sciences.

Keywords

early warning systems / financial cycle / multidimensional approach

References

[1] Krugman P. A model of balance-of-payments crises. Journal of Money, Credit, and Banking, 1979, 11: 311-325

[2] ObstfeId M. Rational and self-fulfilling balance-of-payments crises. American Economic Review, 1986, 76: 72-78

[3] Mckinnon R I, Pill H. International overborrowing: a decomposition of credit and currency risks. World Development, 1998, 26: 1267-1282

[4] Chang R, Velasco A. A model of financial crises in emerging markets. Quarterly Journal of Economics, 2001, 116: 489-5l7

[5] Frankel J A, Rose A K. Currency crashes in emerging markets: an empirical treatment. Journal of International Economics, 1996, 41:35-66

[6] Kaminsky G L, Reinhart C M. The twin crises: the causes of banking and balance-of-payments problems. American Economic Review, 1999, 89: 473-500

[7] Bussicre M, Fratzscher M. Towards a new early warning system of financial crisis. European Central Bank Working Paper,2002, 2002l45

[8] Todd P, Benbasat I. The use of information in decision making: an experimental investigation of the impact of computer-based decision aids. MIS Quarterly, 1992, 16(3): 373-393

[9] Bharati P, Chaudhury A. An empirical investigation of decision making satisfaction in web-based decision support systems. Decision Support Systems, 2004, 37: 187-197

[10] Hu D P, Wang H C, Wu R M. Method for developing agent-based macro-economy decision support system. Journal of China University of Mining Technology, 2001, 30(1): 56-58

[11] Al-Othman AN. Implementing a web-based decision support system for macro-econometric models. Kuwait Journal of Science & Engineering, 2006, 33(1): 253-265

[12] Yang WC, Yang C. A decision engineering system over financial data warehouse. In: Proceedings of the 2005 International Conference on Neural Networks and Brain, 2005, 2: 1050-1052

[13] Klein P A, ed. Analyzing Modern Business Cycles: Essays in Honor of Geoffrey H. Moore, Armonk, N.Y: M.E. Sharpe, Inc, 1990

[14] Lahiri K, Moore G H. Leading Economic Indicators: New Approaches and Forecasting Records. USA: Cambridge University Press, 1991

[15] Achuthan L, Banerji A. Beating the Business Cycle: How to Predict and Profit from Turning Points in the Economy. New York: Random House, Inc, 2004

[16] Marcellino M. Leading indicators. In G Elliott, C W J Granger & A Timmermann (Eds.), Handbook of Economic Forecasting, 2006, 1: 879-960

[17] Carriero A, Marcellino M. A comparison of methods for the construction of composite coincident and leading indexes for the UK. International Journal of Forecasting, 2007, 23: 219-236

[18] Banerji A, Hiris L. A Multidimensional framework for measuring business cycles. International Journal of Forecasting, 2001(17): 333-348

[19] Han A, Zheng G H. Wang S Y. The generalized dynamic factor model with an application to coincident index. Systems Engineering- Theory & Practice, in press, 2008

[20] Zheng G H, Wang S Y. A study of multi-dimension prosperity and its application. Working Paper, 2008

[21] Nilsson R. OECD leading indicators. OECD economic studies, No.9, 1987

[22] Bry G, Boschan C. Cyclical analysis of time series: selection procedures and computer programs. National Bureau of Economic Research, N.Y, 1971

[23] Burns A F, Mitchell WC. Measuring business cycles. National Bureau of Economic Research, N.Y, 1946

[24] Moore G H, Shiskin J. Indicators of Business Expansions and Contractions. New York: Columbia University Press, 1967

[25] Forni M, Hallin M, Lippi M, . The generalized dynamic factor model: identification and estimation. Review of Economics and Statistics, 2000, 82: 540-554

[26] Forni M, Hallin M, Lippi M, . The generalized dynamic factor model: consistency and rates. Journal of Econometrics, 2004, 119: 231-255

[27] Dong W, Gao T M, Jiang S Z, . Economy Periodical Fluctuation: Analysis and Warning. China: Jilin University Press, 1998

[28] Zhang X, Zheng G H, Lai K K, . Forecasting macroeconomic using integrated early warning system. Advances in Forecasting Science and Risk Management I, Lecture Notes in Decision Sciences, 2007, 10: 256-278

[29] Banque De France. The financial cycle: factors of amplification and possible policy implications for financial and monetary authorities. Banque de France Bulletin, 2001, 95

[30] Zhang X, Zheng G H, Shang W, . An integrated decision support framework for macroeconomic policy making based on early warning theories. International Journal of Information Technology & Decision Making, in press, 2008

RIGHTS & PERMISSIONS

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg