The Impacts of Energy Price Shocks on Financial Stability

ABSTRACT

Stability of financial system has become very important not only for practitioners and policy makers but also for researchers, since lack of it can trigger to turmoil and bursts in global financial system. Besides, hazardous effects of financial instability states can quickly spread out globally thanks to financial connectedness and the last global financial crisis sets an example of this. Hence, there exist increasing number of studies in the literature which determine early warning indicators of financial instability states in order to avoid from their catastrophic effects into economy. In the light of this, empirical studies in the related literature constructed financial stress indexes in low frequency (weekly, monthly, quarterly or annually) or in high frequency (daily) in order to measure risks and fragilities of financial system. On the other hand, energy price shocks have detrimental effects into economies by different transmission channels due to energy dependency of emerging and developed countries. 1973 and 1979 oil price shocks set example of these effects since they harmfully affected both developed and emerging economies. Along with that, since oil usage consist of the greatest amount in total energy consumption, researchers investigated the impacts of oil price shocks on macro economies or financial systems of countries. In this study; in the first step, we identify systemic stress of financial systems of 9 countries (G-7, Norway and Turkey) with high frequency (daily) financial stress indexes which consists of daily financial market indicators. Graphical illustrations of financial stress indexes show that all indexes response effectively to well-known financial stress events. In the second step, the impacts of oil price shocks on financial stability are discussed for 9 net oil importer/exporter countries with an application of SVAR model. Finally, similarities/dissimilarities of impacts of oil price shocks on 9 net oil importer/exporter countries’ financial stabilities are analyzed.

MOTIVATION

• Measuring, analyzing and understanding systemic risk in financial system have become very important in the light of the recent global financial crisis.

• Studies in the related literature try to determine early warning indicators of financial instability states and try to avoid from their catastrophic effects into economy.

• Lack of (widely accepted) high frequency (daily) financial stress indexes for some countries (e.g., Turkey, Germany, France, Italy).

• Due to importance of energy usage on real sector and energy dependency of economies, energy price shocks can have detrimental effects into economies by different transmission channels.

• For example, 1973, 1979 oil crisis had not only negative impacts on developed countries’ economies, but they also hazardously affected emerging countries’ economies since oil usage constitutes the greatest amount of total energy consumption.

RESEARCH QUESTIONS

• Could it be possible to construct high frequency (daily) indexes to determine early warning symptoms of financial instability states?

• Do the financial stress indexes response to well-known financial stress events effectively?

• How do oil price shocks affect financial stability of countries in daily?

• Is the response of financial stability of a net oil importer country to oil price shock different than the response of financial stability of a net oil exporter country to oil price shock?

CONTRIBUTION

• We construct high frequency financial stress indexes for G-7 countries, Turkey and Norway. All indexes create proper signs for well-known financial stress events.

• We prefer using some new indicators (i.e. dynamic beta of banking sector (we measured financial contagion of 24 OECD countries by using dynamic beta of banking sectors (Atasoy, Polat and Ozkan; 2016)), realized volatility of slope of the yield curve) in addition to common used indicators in the related literature while constructing indexes.

• Analyzing similarities/dissimilarities of impacts of oil price shocks on financial stability for net oil importer/exporter countries give valuable information while developing different policies.

LITERATURE REVIEW (DEFINITION OF FINANCIAL STABILITY)

• Despite there is no common accepted definition on the term “financial stability”, it has been discussed by many researchers and has been tried to be defined.

• Some of these studies prefer describing the term to its counter correspondence “financial instability”: Bernanke and Gertler, 1987; Wolfson, 1990; Minsky, 1992; Crockett, 1996; Wyplosz, 1998; Mishkin, 1997; Bernanke and Gertler, 2000; Vercelli, 2000; Chant, 2003; Lai, 2000; Ferguson, 2003; Allen and Wood, 2006; Edwards, 2003; Iqbal et al., 2010.

• Stylized Facts: Deficit in investment of economy, weaknesses of balance sheets, fluctuations in the price of financial assets, increase in uncertainty, increase in interest rates, moral hazard and adverse selection in financial markets, rise in volatility, liquidity problems, propagation of international business cycles, booms and boosts in asset prices.

• Some other studies preferred defining financial stability more directly: Crockett, 1997; Schinasi, 2004; Haldane et al., 2005; Allen and Wood, 2006; Rosengren, 2011; Central Banks and international institutions; The World Bank, 2016; Financial System Review-Bank of Canada, 2015; Norges Bank, 2015; Bank of England, 2016; Bank of Japan, 2016; T.C.M.B., 2016; Deutsche Bundesbank Eurosystem, 2016; European Central Bank Eurosystem, 2016; Swiss National Bank, 2016.

• Stylized facts: Stability of key institutions in financial system, efficient allocation of economic resources, smooth consumption of individuals across time, efficient financing of investment projects, observable state of affairs, well functioning of financial intermediation, closeness of employment rate to its natural level, smooth functioning of the financial intermediation process, public trust and confidence in financial institutions, markets, infrastructure; proper functioning of financial system.

LITERATURE REVIEW (EMPIRICAL STUDIES FOR FINANCIAL STRESS INDEXES)

High frequency (daily) financial stress index studies: Illing and Liu, 2006 (Canada); Holmfeldt et al, 2009 (Switzerland); Oet et al., 2011 (US); Lousiz and Vouldis, 2012 (Greece); Islami and Kurz-Kim, 2013 (17 countries in Euro area).

The indicators that are used in high frequency (daily) financial stress indexes are given in Table 1.

Table 1. High Frequency Financial Stress Index Indicators

Low frequency financial stress index studies:

• Weekly financial stress indexes: Nelson and Perli, 2007 (US); Brave and Butters, 2011 (US); Hollo et al., 2012 (Euro Area); Cerquera and Murcia, 2015 (Spain); Kliesen and Smith, 2015 (US). The indicators that are used in weekly financial stress indexes are given in Table 2.

Table 2. Weekly Financial Stress Index Indicators

• Monthly financial stress indexes: Balakrishnan et al., 2009 (18 emerging countries); Hakkio and Keaton, 2009 (US); Morales and Estrada, 2010 (Colombia); Yiau et al., 2010 (Hong Kong); Caldarelli et al., 2011 (Developed 17 countries); Cevik et al., 2013 (Turkey).

The indicators that are used in monthly financial stress indexes are given in Table 3.

Table 3. Monthly Frequency Financial Stress Index Indicators

• Quarterly financial stress indexes: Sinenko et al., 2013 (Lithuania); Arzamasov and Penikas, 2014 (Israel); Eidenberger et al., 2014 (Australia); Vermeulen et al., 2015 (28 OECD countries).

• Annual financial stress indexes: Bordo et al., 2001 (US), Hatzius et al., 2010 (US).

LITERATURE REVIEW (IMPACTS OF ENERGY PRICE SHOCKS ON FINANCIAL AND MACROECONOMIC INDICATORS)

• The response of macroeconomic or financial indicators to oil price shocks have been investigated by researchers to determine the transmission channels of the shocks.

• Early studies dated to 1970’s found evidence of negative impact of oil price shocks on macroeconomic indicators of the US: Pierce et al., 1974; Rasche and Tatom, 1977.

• The bi-directional effects between oil price shocks and macroeconomic indicators constituted an important place in the 1980’s and 1990’s related studies: Hamilton, 1983; Burbidge and Harrison, 1984; Loungani, 1986; Mork, 1989, Mork et al., 1994; Lee et. al, 1995; Hooker, 1996; Ferderer, 1997; Raymond and Rich, 1997; Brown and Yucel, 1999.

• Some of these studies couldn’t find a significant relationship (Hamilton, 1983; Loungani, 1986).
• Some of them found asymmetric relationship among shocks and macroeconomic variables (Mork, 1989; Mork et al., 1994, Lee et al., 1995).

• Some of others found negative impacts of shocks on economic indicators of the United States (Hamilton, 1986; Ferderer, 1997, Brown and Yucel, 1999), and specifically during recession (Hooker, 1996; Raymond and Rich, 1997).

• The more recent studies investigated transmission channels of oil price shocks into macro economy: Lee et al., 2001; Papapetrou, 2001; Cuñado and Gracia, 2003, Hamilton and Herrera, 2004; Leduc and Sill, 2004; Barsky and Kilian, 2004; Huang et al., 2005; Jimenez-Rodriguez and Sánchez, 2005; Guo and Kliesen, 2005; Blanchard and Gali, 2007; Kilian, 2008; Lescaroux and Mignon, 2008; Cologni and Manera, 2009; Herrera and Pesavento, 2009; Tang et al., 2010; Álvarez et al., 2011; Herrera et al., 2011; Kormilitsina, 2011; Jiménez-Rodriguez and Sánchez, 2012; Blanchard and Riggi, 2013; Cavalcanti and Jalles, 2013; Allegret et al., 2015; Cuñado et al., 2015, Basnet and Upadhyaya, 2015; Herwatz and Plödt, 2016, Wei and Guo, 2016.

• In addition to the studies that found evidences about the impacts of oil price shocks to the economies, contrary another strand of studies found limited or no effects: Blanchard and Gali, 2007; Álvarez et al., 2011; Basnet and Upadhyaya, 2015; Cuñado et al., 2015.

• Some of these studies analyzed on the impacts of the oil price shocks on stock market indicators with different econometric methods: Granger Causality, GARCH, Haar A Trous Wavelet, SVAR, OLS, VAR (Chen et al., 1986; Kaneko and Lee, 1995; Jones and Kaul, 1996; Huang et al., 1996, Faff and Brailsford, 1999; Sadorsky, 1999; Ciner, 2001; Hammoudeh and Aleisa, 2005; Basher and Sadorsky, 2006; Cong et al., 2009; Park and Ratti, 2008; Apergis and Miller, 2009; Miller and Ratti, 2009; Arouri and Nguyen, 2010; Filis et al., 2011; Jammazi, 2012; Aloui et al., 2012; Kilian and Park, 2013; Wang et al., 2013; Cuñado and Gracia, 2014; Kang et al., 2015).

• Some recent studies directly investigated spillovers among oil price shocks and financial stress indexes: Chen et. al, 2014; Nazlioglu et al., 2015.

METHODOLOGY (FINANCIAL STRESS INDEXES)

• High frequency (daily) financial stress indexes are developed for a sample of oil importer/exporter countries with an application of Composite Indicator of Systemic Stress (CISS) method using variables that represent bond market, equity market, money market, foreign exchange market and banking sector. We select indicators of financial markets in this study as suggested by the related literature. We use dynamic conditional correlations between sub-indexes while aggregating them.

• Our methodology consists of two parts: Firstly, sub-financial market indexes are obtained by equal weighted average of indicators in each sub-financial market (bank, bond, equity, money and foreign exchange) segment. Secondly, sub-financial market indexes are aggregated with an application of CISS, based on dynamic conditional correlations between the sub-financial indexes.

CISS is defined as below:

\[CISS_{t} = \sqrt{(w \circ s_{t})C_{t}(w \circ s_{t})^{'}}\] Where, \(w=(w_{1},w_{2},w_{3},w_{4},w_{5})\) is sub index weight vector, \(s_{t}=(s_{1},s_{2},s_{3},s_{4},s_{5})\) is sub-markets index vector, \(w \circ s_{t}\) is Hadamart product, \(C_{t}\) is the estimated correlation coefficients matrix \((\rho_{ij,t})\) across sub-market indexes i (i=1,2,3,4,5) and j (j=1,2,3,4,5) given as follows:

\[C_{t} = \begin{bmatrix} 1 & \rho_{12,t} & \rho_{13,t} & \rho_{14,t} & \rho_{15,t} \\ \rho_{21,t} & 1 & \rho_{23,t} & \rho_{24,t} & \rho_{25,t} \\ \rho_{31,t} & \rho_{32,t} & 1 & \rho_{34,t} & \rho_{35,t} \\ \rho_{41,t} & \rho_{42,t} & \rho_{43,t} & 1 & \rho_{45,t} \\ \rho_{51,t} & \rho_{52,t} & \rho_{53,t} & \rho_{54,t} & 1 \end{bmatrix}\]

Once the conditional correlations are estimated for each pair of sub-market indexes, the dynamic correlation coefficient matrix, ????_???? is constructed.

Finally, daily financial stress index (CISS) is obtained by the following equation:

\[CISS_{t} = \sqrt{(w \circ s_{t})C_{t}(w \circ s_{t})^{'}}\]

METHODOLOGY (IMPACTS OF OIL PRICE SHOCKS ON FINANCIAL STABILITY)

The structural shocks are defined to capture oil price changes, oil prices volatility changes and changes in financial stability/instability states with VAR model. As a consequence, we identify structural oil price shocks (oil price changes and oil prices volatility changes) and structural financial shocks. Therefore, the representation of SVAR model is given as follows:

\[B_{0}y_{t}=\beta+\sum_{i=1}^{p} \beta_{i}y_{t-i}+\epsilon_{t}\] where \(y_{t}\)???????? is (3×1) vector that includes financial stress index, daily oil price returns (logarithmic difference of oil prices) and daily oil prices volatility (obtained by \(GARCH(1,1)\), \(B_{0}\) is contemporaneous coefficient matrix, \(\beta\)???? is vector of constant terms and \(\epsilon_{t}\)???? represents vector of serially and mutually uncorrelated error terms (structural shocks).

Therefore, structural shocks can be estimated by the following reduced form errors:

\[e_{t}=B_{0}^{-1}\epsilon_{t}\] The reduced-form VAR can be obtained as follows:

\[\begin{bmatrix} u_{1t} \\ u_{2t} \\ u_{3t} \end{bmatrix} = \begin{bmatrix} 1 & 0 & 0 \\ b_{21} & 1 & 0 \\ b_{31} & b_{32} & 1 \end{bmatrix} \times \begin{bmatrix} \epsilon_{financial shock} \\ \epsilon_{oil price shock} \\ \epsilon_{oil price volatility shock} \end{bmatrix}\]

SVAR is estimated by using 30 lags of each variable to determine potential long run impacts of oil price shocks on financial stability.

DATA

The indicators that are used financial stress indexes are given in Table 4.

Table 4. Financial Stress Index Indicators

FINANCIAL STRESS INDEXES OF TURKEY, THE U.S. AND GERMANY

In this section, the financial stress indexes of Turkey, the U.S. and Germany are given

WELL-KNOWN FINANCIAL STRESS EVENTS

Well-known financial stress events are given below:

• Mexican Peso devaluation on December 12, 1994
• Thai Baht’s peg collapse on July 2, 1997
• Russian Debt Moratorium on August 17, 1998
• Long Term Capital Management (LTCM) collapse on September 23, 1998
• Dot-Com Bubble on March 10, 2000
• Terrorist attack on September 11, 2001
• Stock market downturn on March 1, 2002
• Iraq war on March 20, 2003
• BNP Paribas Press Release on August 9, 2007
• Lehman Brother’s file for Chapter 11 bankruptcy protection on September 15, 2008
• Troubled Asset Relief Program (TARP) release on November 12, 2008
• Freddie Mac’s loss release on May 12, 2009
• Greece bailout on May 02, 2010
• European Financial Stability Facility (EFSF) on May 10, 2010
• Portugal bailout on November 20, 2010
• High tensions on the Euro market on November 11, 2011
• FED’s first tapering on May 22, 2013
• FED’s second tapering on December 18, 2013
• Federal Open Market Committee (FOMC)’s decision to conclude asset purchase (QE) program on October 29, 2014
• FOMC’s decision to hike interest rate from 0.25 to 0.5 firstly since 2006 on December 16, 2015
• Brexit referandum of UK on June 23, 2016
• The U.S. Presidential election on November 8, 2016

FINANCIAL STRESS INDEX OF TURKEY AND WELL-KNOWN FINANCIAL STRESS EVENTS

Daily financial stability for Turkey is measured by a financial stress index which is developed with an application of dynamic conditional correlation based CISS method. Next figure illustrates financial stress index for Turkey from 01/11/2005 to 11/17/2016.

Figure 1. Financial Stress Index of Turkey and Well-Known Financial Stress Events

FINANCIAL STRESS INDEX OF THE U.S. AND WELL-KNOWN FINANCIAL STRESS EVENTS

Daily financial stability for the U.S. is measured by a financial stress index which is developed with an application of dynamic conditional correlation based CISS method. Next figure illustrates financial stress index for the United States from 01/10/1993 to 11/18/2016.

Figure 2. Financial Stress Index of the U.S. and Well-Known Financial Stress Events

FINANCIAL STRESS INDEX OF THE GERMANY AND WELL-KNOWN FINANCIAL STRESS EVENTS

Daily financial stability for Germany is measured by a financial stress index which is developed with an application of dynamic conditional correlation based CISS method. Next figure illustrates financial stress index for Germany from 09/06/2004 to 11/29/2016.

Figure 3. Financial Stress Index of Germany and Well-Known Financial Stress Events

Dynamics of 9 Financial Stress Indexes from 2007/03/17 through 2016/11/17

THE IMPACTS OF OIL PRICE SHOCKS ON FINANCIAL STABILITY

• Short and long run impacts of energy price shocks on financial stability of G-7 countries, Turkey and Norway are investigated with an application of SVAR model (Net oil importing countries: Turkey, US, UK, Japan, Germany, France and Italy; net oil exporting countries: Canada and Norway).

Toda-Yamamoto approach is implemented in order to determine mean spillovers between the series.

DYNAMICS OF FSIS, OIL PRICES AND OIL PRICES VOLATILITY FROM 2007/03/17 THROUGH 2016/11/17

Dynamics of Financial Stress Indexes, Oil Prices and Oil Prices Volatility from 2007/03/17 to 2016/11/17

CORRELATION STRUCTURE OF FSIs, OIL PRICE ANDOIL PRICES VOLATILITY (FROM 2007/03/19 THROUGH 2016/11/17)

CORRELATION STRUCTURE OF FSIs, OIL PRICES ANDOIL PRICES VOLATILITY IN GLOBAL FINANCIAL CRISIS PERIOD (FROM 2007/08/01 THROUGH 2009/12/31)

TODA-YAMOMOTO TEST RESULTS

SVAR IMPULSE RESPONSES

CONCLUSIONS

• All financial stress indexes create proper signs for well-known financial stress events.

*There exist an increasing trend in all financial stress indexes during the last global financial crisis period (08/2007-12/2009). And, all financial stress indexes reach their peak values during 2008 financial crisis.

• Significant increase in financial stress indexes of 9 countries were observed on Brexit (June 23, 2016), while the highest increase occurs for the United Kingdom. Besides, financial stress indexes of Germany, France and Italy rise comparatively higher than other countries’ financial stress indexes in this period.

• There exist an important increase in Turkey’s financial stress index between May-June 2006 different than other countries’ financial stress indexes. This behavior may be related to have higher fragility of Turkey’s financial system to unfavorable developments in the international markets than other countries’ financial systems.

• There exist great amount of rises in financial stress indexes of European Union member countries (Germany, France, Italy), Norway and the United Kingdom during European debt crisis period. These countries’ financial stress indexes efficiently response to financial stress events (Greece bailout on May 02, 2010, European Financial Stability Facility (EFSF) on May 10, 2010 and Portugal bailout on November 20, 2010.

• Japan’s financial stress index reach high levels during 1997 Asian crisis as expected. It create proper signs the financial stress events during Asian financial crisis and following financial stress events (Thai Baht’s peg collapse on July 2, 1997, Russian debt moratorium on 17 August 1998, LTCM collapse on September 23, 1998). There exist an increasing trend in financial stress index of Japan after the President election held in the United States (November 08, 2016).

• Financial stress indexes of all countries response positively to positive oil prices volatility shocks in the long run.

• Financial stress indexes of Germany, France and Italy response to positive oil price volatility shock very similarly. This situation is most probably due to having similar financial stress indexes.

• Financial stress indexes of Japan and the U.K. response to positive oil price volatility shock similarly.

• Financial stress indexes of all countries and oil prices volatility are positively correlated.

• Financial stress indexes of Turkey, the United States, the United Kingdom, France and Italy and oil price volatility are positively and moderately correlated.

• Financial stress indexes of Japan, Canada and oil price volatility are positively and weakly correlated.

• Financial stress indexes of Germany, Norway and oil price volatility are positively and strongly correlated.

• With an exception of Turkey, oil price Granger causes financial stress indexes. Oil price volatility Granger causes financial stress indexes of all countries except for Canada.

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