Banking And Currency Crisis

Banking and Currency Crisis

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BANKING AND CURRENCY CRISIS

VIDYALANKAR INSTITUTE OF TECHONOLOGY

By – Shivani Solanki

Batch – A

Roll no. 17106A1064

Banking and Currency Crisis

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Abstract

Study the stylized facts of the banking crisis and the currency crisis. Banking uncertainty

was most frequent in the developed economies. Identify a set of characteristics of economic,

financial and structural conditions preceding the beginning of banking and currency crisis

in 40 advanced economies over period 1970-2010. Also the use of Classification and

Regression Tree Methodology (CART) and Random Forest (RF) extension, allows the

detection of key variables driving binary crisis outcomes, determines critical tipping points

and allows for interaction among key variables. Distinguish between country structural

characteristics, basic country conditions and international developments. It has been found

that crisis is more varied than they are similar. For banking crisis, I find that in long term it

is high house price inflation while in short term low interest rate spreads in the banking

sector and a shallow yield curve are most important forerunners. For currency crisis, in

short term high domestic rates with overvalued exchange rates are the most powerful

predictors. I find that both international developments and country structural

characteristics are relevant banking crisis predictors. Currency crisis, seem to be more

driven by country idiosyncratic and short term developments. I find that some variables

such as provide important unconditional signals, but it’s difficult to use them as conditional

signals, domestic credit gap and more impotently, to find relevant threshold values.

Keywords: Banking crisis, binary classification tree, currency crisis, early warning indicators

Banking and Currency Crisis

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Section I: INTRODUCTION

Away from the empirical debate on the direction of causality in the relationship between

finance and growth, it is widely acknowledged that good performance of the financial system

is favorable for economic development. Although the literature on crisis and early warning is

extensive, the research on the occurrence and early warning indicators of economic crisis in

developed countries is still relatively thin. However, recent experience has demonstrated the

relevance of the topic for developed economies. This paper tries to establish which stylized

facts on crisis occurrence and which early warning indicators are relevant for developed

countries by employing an advanced technique to overcome model uncertainty and by

utilizing a new quarterly data set. Traditionally, the literature on crisis has been focused on

emerging markets. More recently, large samples of countries, including both developing and

developed economies, have been explored. While currency crisis were the subject of

investigation in the pioneering studies, the recent literature has tried to encompass more

types of costly events, including various types of banking and debt crisis (Leaven and

Valencia, 2012; Levy-Yeyati and Panizza, 2011; Reinhart and Rogoff, 2011). The literature has

suggested that all types of crisis can be very costly and that there are possible causal

relationships between various types of crisis (Kaminsky and Reinhart, 1999; Reinhart and

Rogoff, 2011). While output losses are induced by disruptions of the credit supply in the case

of banking crisis, the massive devaluations inherent to currency crisis are detrimental to

trade flows. Debt crisis in turn mostly increase the cost of sovereign borrowing and are

usually followed by austerity measures that have an adverse impact on domestic demand.

The literature has also proposed various early warning indicators, such as depletion of

international reserves, real exchange rate misalignment or excessive domestic credit growth

for currency crisis in emerging markets, rapid growth in domestic credit and monetary

aggregates for both banking and currency crisis, a sharp increase in private indebtedness for

Banking and Currency Crisis

banking crisis, growth in global credit for costly asset price bubbles, a large real GDP decline

for debt crisis.

To address these issues we use Classification and Regression Tree (CART) methodology and

its generalization, Random Forest (RF) analysis, to model explicitly the non-linear

interactions between variables and deal with missing values and outliers, which are usually a

problem for regression-based frameworks. The CART and RF frameworks provide crisis

thresholds for key variables, thus significantly simplifying the interpretation of the results for

decision-makers and non-technical audiences.

This framework has both advantages and disadvantages compared with other common early

warning methods. On the one hand, it allows explicitly for the fact that not all crisis are alike

and accommodates non-linearity by including conditional thresholds. On the other hand, it