Frontiers in Finance Volume 1, 2015 doi: 10.14355/ff.2015.01.008
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Paradigm Reconstruction of Early-Warning System of Financial Crisis Yin Yu Economics & Management School, Shanghai Second Polytechnic University, Shanghai, China yuyin@sspu.edu.cn Abstract By analyzing the shortcoming of existing research paradigm of the early warning system of financial crisis, the conceptual framework of "pressure-state-impact-response" (PSIR) was introduced. A research paradigm of early warning system of financial crisis was created with the cyclical characteristics. And the CGE model was used to analyze the preparation of the early warning indicators and prediction for financial crisis. Keywords Financial Crisis; Early-warning System; PSIR Framework
Introduction Numerous scholars have studied early-warning system of financial crisis with hundreds of systems being established over the past three decades. However, early-warning system has been criticized in various aspects due to constant outbreaks of financial crisis. For example, the selection of indicators and threshold values for crisis depends on samples, which may be too casual; “Lucas critique” cannot be avoided; it is difficult to compare advantages and disadvantages among different systems and the results of assessment are indeed unsatisfactory (e.g. Beckmann et al., 2006; Duca and Peltonen, 2012). Facing questions and unsatisfactory assessment results, researchers began diagnosing various parts of earlywarning system and carried out constructive research. Previous researches aimed at improving the accuracy rate of early-warning system. Two neglected obvious conditions should be paid attention to. First, some crises are early warned without sufficient importance being attached to by authorities concerned. Second, some crises are warned with sufficient importance by authorities and with crucial policy intervention, however, the economic running system is still on sliding into crisis inertially. The reason is that the design purpose of an early-warning system is to offer warnings for possible crises to the policy makers and the market participators. These researches are based on an one-way research paradigm. This paradigm itself is one of the major reasons for a series of problems. Improving research paradigm may be a reasonable choice and an attempt to resolve these problems. Therefore, the view angle of forecasting accuracy should be jumped out of. The design purpose of early-warning system is identified for problems instead of crises. Depending on this orientation, a research paradigm based on a circular concept framework of “pressure-state-impact-response” is established in this paper. Defects of Existing Paradigm People followed this paradigm consciously related to research on early-warning system: define a crisis as per the scope of system, prepare the indicator (maybe a single indicator, a single composite indicator or an indicators set), select forecast models and put forward policy proposals based on forecast results. The research paradigm is named as “one-way paradigm”. Two large feedback courses exist in the early-warning systems built on the basis of this structure. First, based on a selected model, selected indicators and data, including time windows and sample status, are adjusted to adapt to
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the model, and then the definition of crisis is adjusted as per indicators and data. The other is tantamount to adjust the parts identified by researchers if prediction is unsatisfactory. This adjustment can be any part or even the whole prior to release of an early warning results, also includes details such as sample states and time windows. The two adjustments are the same in coordinating all parts of early-warning system so as to achieve the expectations of researchers to establish an effective early-warning system. They make the selection of threshold value for crisis recognition rely on samples inevitably and make it too casual owing to the difference in selection of samples by different researchers (Abiad, 2003). In accordance with the one-way paradigm, the precise definition of crises plays a critical role in selecting crisis measures. A crisis can be determined by indicators or events generally. However, great disagreement still exists even for the same type of crises(Perez, 2005). The disagreement on a crisis definition often makes different researchers select mutually contradictory decision-making variables while facing the same crisis. Response to the crisis still depends on the selection of indicators, originating from conclusions of experience on the cause of the crises. It is a method that some occurred serious crises as predictable events are analyzed to distinguish critical and non-critical factors. Knowledge of the cause of the crises varies from person to person so that each researcher will use new indicators. Specifically, in-sample and out-of-sample analysis is usually carried out. i.e. selecting one time window prior-crisis for in-sample analysis to screen critical indicators, and then analyzing the periodic crisis outbreak as out-of-sample period to assess the early warning effect, which falls into “Lucas Critique” inevitable. Maybe the early-warning system “conforms” better to the occurred crisis, or in other words, “explains” better the occurred crisis. However, it is unknown that whether it can forecast the next crisis efficiently. The destination of the one-way paradigm is policy proposals, and it cannot reflect the feedback of policy on earlywarning system. It seems that monitoring on the impact of policy suggestions proposed based on current earlywarning system on the financial system is the task of the subsequent early-warning system. However, feedback of policy on early-warning system actually exists. Those indicators being proven repeatedly have become not only the focus for policy proposals proposed by researchers, but also preventive indicators for crises by policy makers. Their feedback may impair predict effect (Goldstein and Razin, 2013; Goldstein et al., 2000). To the whole framework, the attention of people is drawn easily by the one-way paradigm towards the earlywarning accuracy. Especially, for people outside this research field, they care nothing about the hard and painstaking process for building an early-warning system, but the obvious consequences of the system. Optimal the Preparation System for Early-warning Indicators To make up for the inadequate of research paradigm of early-warning system, it is the key that the policy variables’ feedback is fitted into the early warning system. It should, firstly, affect the preparation of early-warning indicators. For this purpose, the early-warning indicators are decomposed into the four factors: the pressure, the state, the impact and the response, and then adopt the circular “pressure-state-impact-response” conceptual framework as the research paradigm of the early-warning system of financial crisis. PSIR Framework The PSIR (Winograd et al., 1999) conceptual framework, as the interaction paradigm for financial crisis earlywarning system, can allow us to identify the most important index elements and provide an alternative solution for preparing the complex-type index system. In the framework, one idea for preparing the index system is to divide the macro- and micro-economic variables into pressure variable, state variable, impact variable and response variable. (Yu et al., 2010) The pressure variables describe the underlying cause of the problem. They reflect the pressure bearing down on the financial system in the process of economic activity, or the problems existing in the financial system. The pressure variables also refer to the problem of the system which they don’t participate in researching the operation of finance.
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In general, we may face lots of pressure indicators during the analysis process. It requires to focus on those critical indicators really interested by the policy makers and investors. The state variables measure the system characteristics which are caused by the pressure variable. In the financial system, observable state usually can be measured by systematic quality, available or systematic efficiency, as well as systematic change in the selected time window and so on. The impact variables record the spread or spillover which is caused by the pressure and the states already in existence. The response variables are the countermeasures and economic policies for solving the problems of the financial system. The policies and countermeasures have direct or indirect influences on the system by acting on the pressure. The financial crises, in this circular structure, are the problems which fail to be softened or eliminated and exceed certain threshold values. Early-warning indicators should monitor the problems more than merely monitoring the crisis. In this case, the early-warning system doesn’t be simply evaluated on the basis of accuracy of crisis forecast. It shall also include improvement on existing problems of financial system, evaluation of solution degree. Application of Predicting Technique PSIR framework is a circular structure in which includes into the policy variables. How to measure the mutual influence among the variables is the fundamental problem. In the globular structure, the variables of each category are the inputs of the next category. Therefore, the circular relations among them can be converted into the inputoutput relationship in which the variables of each category are both “producer” and “user”. Then, we propose to use the computable general equilibrium model (CGE) to analyze the mutual linkage represented by various variables among the sectors of the national economy, as well as the calculation accounts, effects of policies and economic activities on these relations. The CGE model cannot only describe the mutual linkage between the sectors of the national economy and the calculation accounts, but also predict the effects of policies and economic activities. The CGE was also mainly used for analyzing the cases resulted from the financial crisis. Therefore, how to use a CGE model to predict the financial crisis shall be further studied. In addition, whether different forms of crises such as monetary crisis, bank crisis and the debt crisis can be listed into the analytical framework of a CGE model. Conclusions The paper analyzes the existing studies on financial crisis early-warning. The existing studies adopted a linear oneway paradigm on the basis of regulations of conventional research goals, thereby leading to defects mainly including large difference in crisis definition, randomness of index selection and disconnection between the policy suggestion and early-warning system. In order to avoid these drawbacks, the policy suggestion is included in building the early-warning system in the paper and PSIR paradigm is used to establish a selectable research paradigm of financial crisis early-warning. Furthermore, index selection, the application of CGE model in the financial crisis early-warning and further research direction are considered in the new mode. ACKNOWLEDGMENT
This paper is supported by MOE (Ministry of Education in China) Project of Humanities and Social Sciences (Project No.12YJAZH183), Innovation Program of Shanghai Municipal Education Commission (Project No. 12YS160). I would like to thank for their generousness. I am grateful to the anonymous referees for their comments and advice. REFERENCES
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[10] IMF, 1998. Financial Crises: Characteristics and Indicators of Vulnerability. Vol. 4 World Economic Outlook, Chapter IV. [11] Lewis, J.D. and S. Urata, 1984. "Anatomy of a Balance-of-Payments Crisis: Application of a Computable General Equilibrium Model to Turkey, 1978-1980." Economic Modelling 1, no. 3: 281-303. [12] Manasse, P. and N. Roubini, 2009. ""Rules of thumb" for sovereign debt crises." Journal of International Economics 78(2): 192-205. [13] Peltonen, T. A., 2006. "Are Emerging Market Currency Crises Predictable? A Test." European Central Bank Working Paper 571. [14] Perez, J., 2005. "Empirical identification of currency crises: differences and similarities between indicators." Applied Financial Economics Letters 1: 41-46. Yin Yu received her PhD degree in Management Science and Enginier from Donghua University, China in 2007. Currently, she is a Professor at the Economics & Management School, Shanghai Second Polytechnic University, China.
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