Essays On Measuring Systemic Risk

Author : Mustafa Akcay
Publisher :
ISBN 13 :
Total Pages : 223 pages
Book Rating : 4.:/5 (128 download)

DOWNLOAD NOW!

Download or read book THREE ESSAYS ON THE IMPACT OF MONETARY POLICY TARGET INTEREST RATES ON BANK DISTRESS AND SYSTEMIC RISK written by Mustafa Akcay and published by . This book was released on 2018 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: My dissertation topic is on the impact of changes in the monetary policy interest rate target on bank distress and systemic risk in the U.S. banking system. The financial crisis of 2007-2009 had devastating effects on the banking system worldwide. The feeble performance of financial institutions during the crisis heightened the necessity of understanding systemic risk exhibited the critical role of monitoring the banking system, and strongly necessitated quantification of the risks to which banks are exposed, for incorporation in policy formulation. In the aftermath of the crisis, US bank regulators focused on overhauling the then existing regulatory framework in order to provide comprehensive capital buffers against bank losses. In this context, the Basel Committee proposed in 2011, the Basel III framework in order to strengthen the regulatory capital structure as a buffer against bank losses. The reform under Basel III framework aimed at raising the quality and the quantity of regulatory capital base and enhancing the risk coverage of the capital structure. Separately, US bank regulators adopted the Dodd-Frank Wall Street Reform and Consumer Protection Act (2010) to implement stress tests on systemically important bank holding companies (SIBs). Concerns about system-wide distress have broadened the debate on banking regulation towards a macro prudential approach. In this context, limiting bank risk and systemic risk has become a prolific research field at the crossroads of banking, macroeconomics, econometrics, and network theory over the last decade (Kuritzkes et al., 2005; Goodhart and Sergoviano, 2008; Geluk et al., 2009; Acharya et al., 2010, 2017; Tarashev et al., 2010; Huang et al., 2012; Browless and Engle, 2012, 2017 and Cummins, 2014). The European Central Bank (ECB) (2010) defines systemic risk as a risk of financial instability "so widespread that it impairs the functioning of a financial system to the point where economic growth and welfare suffer materially." While US bank regulators and policy-makers have moved to strengthen the regulatory framework in the post-crisis period in order to prevent another financial crisis, a growing recent line of research has suggested that there is a significant link between monetary policy and bank distress (Bernanke, Gertler and Gilchrist, 1999; Borio and Zhu, 2008; Gertler and Kiyotaki, 2010; Delis and Kouretas, 2010; Gertler and Karadi, 2011; Delis et al., 2017). In my research, I examine the link between the monetary policy and bank distress. In the first chapter, I investigate the impact of the federal funds rate (FFR) changes on the banking system distress between 2001 and 2013 within an unrestricted vector auto-regression model. The Fed used FFR as a primary policy tool before the financial crisis of 2007-2009, but focused on quantitative easing (QE) during the crisis and post-crisis periods when the FFR hit the zero bound. I use the Taylor rule rate (TRR, 1993) as an "implied policy rate", instead of the FFR, to account for the impact of QE on the economy. The base model of distress includes three macroeconomic indicators-real GDP growth, inflation, and TRR-and a systemic risk indicator (Expected capital shortfall (ES)). I consider two model extensions; (i) I include a measure of bank lending standards to account for the changes in the systemic risk due to credit tightening, (ii) I replace inflation with house price growth rate to see if the results remain robust. Three main results can be drawn. First, the impulse response functions (IRFs) show that raising the monetary policy rate contributed to insolvency problems for the U.S. banks, with a one percentage point increase in the rate raising the banking systemic stress by 1.6 and 0.8 percentage points, respectively, in the base and extend models. Second, variance decomposition (VDs) analysis shows that up to ten percent of error variation in systemic risk indicator can be attributed to innovations in the policy rate in the extended model. Third, my results supplement the view that policy rate hikes led to housing bubble burst and contributed to the financial crisis of 2007-2009. This is an example for how monetary policy-making gets more complex and must be conducted with utmost caution if there is a bubble in the economy. In the second chapter, I examine the prevalence and asymmetry of the effects on bank distress from positive and negative shocks to the target fed fund rate (FFR) in the period leading to the financial crisis (2001-2008). A panel model with three blocks of control variables is used. The blocks include: positive/negative FFR shocks, macroeconomic drivers, and bank balance sheet indicators. A distress indicator similar to Texas Ratio is used to proxy distress. Shocks to FFR are defined along the lines suggested by Morgan (1993). Three main results are obtained. First, FFR shocks, either positive or negative, raise bank distress over the following year. Second, the magnitudes of the effects from positive and negative shocks are unequal (asymmetric); a 100 bps positive (negative) shock raises the bank distress indicator (scaled from 0 to 1) by 9 bps (3 bps) over the next year. Put differently, after a 100 bps positive (negative) shock, the probability of bankruptcy rises from 10% to 19% (13%). Third, expanding operations into non-banking activities by FHCs does not benefit them in terms of distress due to unanticipated changes in the FFR as FFR shocks (positive or negative) create similar levels of distress for BHCs and FHCs. In the third chapter, I explore the systemic risk contributions of U.S. bank holding companies (BHCs) from 2001 to 2015 by using the expected shortfall approach. Developed by analogy with the component expected shortfall concept, I decompose the aggregate systemic risk, as measured by expected shortfall, into several subgroups of banks by using publicly available balance sheet data to define the probability of bank default. The risk measure, thus, encompasses the entire universe of banks. I find that concentration of assets in a smaller number of larger banks raises systemic risk. The systemic risk contribution of banks designated as SIFIs increased sharply during the financial crisis and reached 74% at the end of 2015. Two-thirds of this risk contribution is attributed to the four largest banks in the U.S.: Bank of America, JP Morgan Chase, Citigroup and Wells Fargo. I also find that diversifying business operations by expanding into nontraditional operations does not reduce the systemic risk contribution of financial holding companies (FHCs). In general, FHCs are individually riskier than BHCs despite their more diversified basket of products; FHCs contribute a disproportionate amount to systemic risk given their size, all else being equal. I believe monetary policy-making in the last decade carries many lessons for policy makers. Particularly, the link between the monetary policy target rate and bank distress and systemic risk is an interesting topic by all accounts due to its implications and challenges (explained in more detail in first and second chapters). The literature studying the relation between bank distress and monetary policy is fairly small but developing fast. The models I investigate in my work are simple in many ways but they may serve as a basis for more sophisticated models.