The Impact of Real Estate Lending on Thrifts’ Franchise Values during the 2007-2009 Crisis: A Comparison with Commercial Banks Valentina Salotti Iowa State University - Department of Finance 3345 Gerdin Bldg., Ames, IA, 50011, USA
[email protected] Natalya A. Schenck The Office of the Comptroller of the Currency 400 7th Street SW, Washington, DC 20219, USA
[email protected] John H. Thornton Jr. Kent State University - Department of Finance 475 Terrace Drive, Kent, OH 44242, USA
[email protected]
Abstract
The 2007-2009 crisis brought renewed attention to the thrift charter. While some initially called for its repeal, the current debate focuses on the regulatory changes that would allow thrifts to operate in a bank-like regulatory environment, lessening its real estate lending concentration. We compare a sample of small and medium-sized publicly-traded thrifts to a size-matched sample of banks, and examine the effect of real estate exposure on their franchise values during the rise and burst of the real estate bubble. While thrifts are mostly exposed to residential real estate, banks have a higher concentration in commercial real estate (CRE), which is significantly associated with the decline in their franchise value. We conclude that the imposed limits to loan portfolio diversification, such as the limited exposure to CRE loans, are not detrimental to the thrift charter during and after the crisis period.
Note: The views herein are those of the authors and do not necessarily represent the views of the Office of the Comptroller of the Currency or the Department of the Treasury.
The Impact of Real Estate Lending on Thrifts’ Franchise Values during the 2007-2009 Crisis: A Comparison with Commercial Banks
Abstract The 2007-2009 crisis brought renewed attention to the thrift charter. While some initially called for its repeal, the current debate focuses on the regulatory changes that would allow thrifts to operate in a bank-like regulatory environment, lessening their real estate lending concentration. We compare a sample of small and medium-sized publicly-traded thrifts to a size-matched sample of banks, and examine the effect of real estate exposure on their franchise values during the rise and burst of the real estate bubble. While thrifts are mostly exposed to residential real estate, banks have a higher concentration in commercial real estate (CRE), which is significantly associated with the decline in their franchise value. We conclude that the imposed limits to loan portfolio diversification, such as the limited exposure to CRE loans, are not detrimental to the thrift charter during and after the crisis period.
Keywords: commercial banks; thrifts; real estate; franchise value; financial crisis JEL classification: G21, G28
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The Impact of Real Estate Lending on Thrifts’ Franchise Values during the 2007-2009 Crisis: A Comparison with Commercial Banks 1. Introduction The 2007-2009 financial crisis was arguably the most volatile period for the U.S. banking industry in many decades. Although both thrifts and banks were affected by the 20072009 financial crisis, some of the earliest and costliest failures of 2008 involved a few large thrifts supervised by the Office of Thrift Supervision (OTS).1 In the debate that arose during the crisis and continued in its aftermath, some advocated for the repeal of the charter, considering the required concentration in real estate and constraints on asset diversification unnecessary and obsolete (Chatman, 2013). Others favored its continuation citing the importance of thrifts for mortgage lending and the danger of leaving this segment exposed to the competition of non-bank lenders.2 Although the Obama administration initially supported the repeal of the thrift charter,3 the Dodd-Frank Wall Street and Consumer Protection Act (Dodd-Frank) of 2010 kept it alive without altering its real estate focus and statutory limits to commercial lending. 4 More recently, the discussion has shifted towards allowing more flexibility for thrifts to operate in a bank-like
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For example, Countrywide failed and was absorbed by the Bank of America in January of 2008, IndyMac was closed by the regulators in July of 2008, Washington Mutual was closed in September of 2008 and its banking operations and loan portfolio were acquired by J.P. Morgan Chase. AIG housed its problematic credit default swap business in a unit that was legally a thrift institution. 2 See ABA Memo, July 14, 2009. (http://www.aba.com/Tools/Function/Documents/ea2cc23963da40d3956276aa68678ac7ThriftCharterMemo.pdf) 3 In 2009, the Obama administration proposed the complete repeal of the charter. See the “Financial Regulatory Reform: A New Foundation” proposal by the U.S. Department of the Treasury in June of 2009 (www.treasury.gov/initiatives/Documents/FinalReport_web.pdf). 4 Dodd-Frank eliminated the OTS and moved the regulation of federally chartered thrift institutions to the Office of the Comptroller of the Currency (OCC), state-chartered thrifts to the Federal Deposit Insurance Corporation (FDIC), Savings and Loan Holding Companies (SLHC) to the Federal Reserve Board (FRB). Albeit the process of regulatory convergence between thrifts and commercial banks preceded the 2008 crisis, pursuant the Dodd-Frank most of the remaining advantages of the thrift charter were eliminated. See Appendix B for an overview of the changes made to the thrift charter.
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regulatory environment without undergoing a charter conversion.5 As the current debate circles around the necessity of maintaining or loosening the charter’s lending limits, the question that we pose is whether such limits were especially detrimental to franchise values during and after the crisis period.6 While the benefits of diversification are not unexplored (e.g. Diamond, 1984; Boyd and Prescott, 1986), the literature has not yet considered how imposing limits to lending diversification on certain intermediaries (thrifts), while allowing others (commercial banks) to choose their optimal level of diversification, might ultimately affect their market valuation, i.e. their franchise value. Comparing the franchise value of small and medium publicly-traded thrifts to a matched sample of banks during the 2000-2011 period, we demonstrate that the thrift charter continued to hold its value relative to banks even during 2007-2009 crisis. While franchise values decline for both types of charters during the crisis, banks suffer a steeper decline. Although thrifts have significantly lower franchise values during the pre-crisis period, by the end of the acute phase of the financial crisis (2009), the franchise values of the two charter types are essentially equal. While the total levels of real estate lending negatively impact banks’ franchise values during the
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For example, see the Testimony of Toney Bland, Senior Deputy Comptroller for Midsize and Community Bank Supervision, OCC, before the Committee on Banking, Housing and Urban Affairs, U.S. Senate, February 10, 2015 where he mentions a drafted legislation “that would give a federal savings association a choice: continue to operate as a traditional thrift or file a notice to be treated as a “covered savings association”. … “This option would provide a federal savings association with the flexibility to retain its current corporate form and governance structure without unnecessarily limiting the evolution of its business plan”. (http://www.banking.senate.gov/public/index.cfm?FuseAction=Hearings.Hearing&Hearing_ID=94d7e84d-339641cf-acdd-1d8aff386ca9) 6 Before proceeding further a note on terminology is needed. In the banking literature a more common term for what we denote as “franchise value” is “charter value” (e.g., Keeley, 1990; Nicolo, 2001; Saunders and Wilson, 2001; Osborne and Lee, 2001; Stolz, 2007; Frame and White, 2007). In the typical parlance of the banking literature, we study the effect of a depository institution’s charter (i.e. the right to operate that is granted to the institution by a regulatory authority) on its charter value (i.e. the present value of future abnormal profits). To avoid confusion between the institution’s charter and the institution’s charter value, henceforth we use the term “franchise value” exclusively.
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2007-2009 financial crisis, surprisingly there is no significant impact on thrifts.7 To explain these unexpected results, we look further into the real estate portfolio composition. While banks are disproportionally more invested in commercial real estate (CRE) loans, thrifts' exposure is mostly residential. These differences in the composition of the real estate lending portfolio of banks and thrifts stem from the imposed limits to thrifts' asset diversification at the center of the current debate. Besides the Qualified Thrift Lender (QTL) test which mandates a substantial exposure to residential real estate, the Home Owners Loan Act of 1933 (HOLA) still requires CRE loans to be capped at 400% of the thrift’s capital, and the exposure to commercial and industrial loans to be kept below 20%.8 In our regression analysis, we find that within real estate investments, CRE lending has a negative and significant impact on banks but not on thrifts. These findings agree with Cole and White (2012) which show that a higher concentration in construction and development, multi-family and CRE lending is associated with a higher probability of failure for commercial banks, while residential lending is either neutral or associated with a lower probability of failure. Thrifts' concentration in residential real estate and regulatory constraints on asset diversification did not negatively affect their value. Although our findings are surprising given the current perception of the inferiority of the thrift charter with its regulatory constraints on asset diversification, they are consistent with the notion that thrifts’ traditional focus in real estate makes them more effective in selecting real estate investments during the crisis.9 Moreover, limits to portfolio diversification imposed on
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We recognize that our analysis relies on publicly-traded thrifts and is therefore representative of larger institutions within the thrifts’ industry. For this reason, our results do not necessarily extend to the overall thrifts’ population and in particular to smaller privately held thrifts. 8 Loans secured by residential real estate, which include construction and development loans for single housing are included in QTL test. Moreover, small business loans that are included in QTL test, can also be classified as CRE if secured by commercial real estate. 9 Acharya et al., (2006) show that specialization in lending is accompanied by lower loan loss rates. As diversification often implies decreased monitoring, adverse selection and lower cost efficiency, it impairs bank
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thrifts acted as a safety mechanism during the recent crisis. In fact, these limits prevented thrifts from increasing their exposure to CRE as much as commercial banks, thereby cushioning the impact of the commercial real estate market crash. Cole and White (2012) policy implication is to revisit the capital requirements and impose concentration limits for CRE loans, given that CRE loans are associated with the higher probability of banks’ failures. The negative effects of the exposure to CRE loans are not only confirmed by our analysis, but the comparison with banks shows the positive effect of thrifts' more stringent capital requirements on CRE loans. From a policy perspective, our analysis supports the continuation of a separate thrift charter. Our valuation analysis shows that characteristics of the thrift charter currently under discussion did not expose small and medium-sized thrifts significantly more than banks to the real estate crisis. On the contrary, some of the limits on asset diversification cushioned the fall for smaller publicly held thrifts during the crisis. It appears that the limits to asset diversification do not pose a threat to the immediate future of the industry despite the competition from commercial banks. On the other hand, exposure to CRE had a negative effect on banks’ franchise value during the crisis. Our results show that the thrift charter is a viable business model for residential real estate lending which is supportive of the current policy: allowing thrifts the choice of converting to a commercial bank or keeping the same charter type. From a corporate decision making standpoint, the results of this study are useful to existing thrift managers to
return and simultaneously generates riskier loans for high-risk banks, and inefficient risk-return trade-off or marginal improvement for low-risk banks. Foos et al. (2010) find that real estate and mortgage banks, which generally originated low risk loans (subprime segment excluded) show comparatively lower losses. Results hold for a sample of savings and cooperative banks.
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weight the potential benefits and risks of a charter switch to a commercial bank in the DoddFrank era.10 2. Franchise Value The franchise value (or charter value) of a firm is the present value of the stream of abnormal profits that is expected to be earned by the firm as a going concern (Freixas and Rochet, 2008). In the banking and thrift industry, a higher franchise value can arise from limited competition due to regulatory barriers to entry or from underpriced deposit insurance. Buser et al. (1981) were among the first to introduce the concept of charter value, defined as “the value of their (the banks’) right to continue in business”, to explain the pricing of the FDIC deposit insurance, and the FDIC failed-bank resolution policy in general. Marcus (1984) augments the Merton (1977) model with a disciplining effect of bank charter value: under certain conditions healthy banks pursue a low risk strategy in order to protect a valuable bank charter to maximize equity value. On the other hand, undercapitalized banks experiencing loan losses may increase risk-taking and exploit the FDIC insurance (“go-for-broke” strategy). Demsetz et al. (1996) posit that decreasing the incentives to take on risk, charter value helps to mitigate the moral hazard problem arising from the federal safety net. Following Marcus (1984), Keeley (1990) is the first to use regression analysis to investigate franchise value in the banking industry, and to introduce Tobin's q as a proxy for
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Zaring and Donelson (2011) focus on risk adjusted returns of banks and thrifts, and a small sample of institutions that switched charters, "modestly" defend the performance of thrifts within the multi-regulator system, which, in turn, lends support to some of our conclusions. Very few publicly-traded depository institutions initiated a change in charter type (bank to thrift, and vice versa) during our sampling period. In addition, our study does not consider state and federal charters separately. With the data available and the current methodology we cannot directly address the impact of a charter switch on franchise values.
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bank franchise value.11 Keeley (1990) argues that an increase in competition causes bank franchise values to decline, which in turn leads to an increase in default risk. This hypothesis is based on the notion that in the 1980s thrift regulations were relaxed, which enabled thrifts to compete more effectively with banks. Demsetz et al. (1996) show that the decline in thrift franchise values during the Savings and Loans (S&L) crisis in 1980s was due to the development of secondary markets in mortgage securities, which reduced thrifts’ ability to earn profits from mortgage lending.
Thrifts
experienced a large reduction in capital in the late 1970s and early 1980s when the values of their mortgage portfolios fell as a result of higher interest rates. In addition, with 1980s deregulation, banks and thrifts were faced with increased competition from non-banking institutions.
In response to heightened competition, banks and thrifts undertook riskier
strategies, and thus had high levels of failure (Park and Peristiani, 2007). Furlong and Kwan (2006) demonstrate that franchise values of Banking Holding Companies (BHCs) rebounded in the 1990s and early 2000s from the lows in the 1980s. They find that besides market cycles and changes in the competitive environment, bank specific factors such as core deposits and lending relationships are important determinants of franchise values. Huizinga and Laeven (2012) show that the decline in banks’ Tobin’s q during the 20072009 crisis was mostly due to the deterioration of the real estate market. Since the link between franchise values and risk has been well-established by the literature, franchise value is also expected to be affected by the banks' ability to diversify their investments. The effect of diversification on financial intermediaries is highly debated. Diamond's delegated monitoring argument (1984) supports the view of diversification as 11
Tobin’s q measure used in Keeley (1990) paper was based, in turn, on a q ratio of Brainard and Tobin (1968) as a proxy for growth opportunities.
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beneficial for financial intermediation. Similarly, Boyd and Prescott (1986) suggest that banks should be "fully diversified" across sectors. Berger et al. (1999) find that the increase in the diversification of risks following the industry consolidation of the early nineties does not generate any cost efficiency improvement. More recently, Acharya et al. (2006) investigate a sample of Italian banks and find that diversification in banking assets does not necessarily promote efficiency or decrease risk in banks. Risk-weighted regulatory capital requirements may also act as an incentive to over-invest in a specific loan category, which might distort the bank's risk taking incentives, and portfolio diversification strategies (Acharya and Richardson, 2009). Looking at the recent crisis, Cole and White (2012) show that higher concentration in construction and development, multi-family housing and CRE is associated with higher probability of failure for commercial banks, while residential lending is either neutral or is associated with a lower probability of failure. An earlier study by Helwege (1996) which follows the S&L crisis and covers a sample of thrifts from 1979 to 1990, finds that residential mortgages had a greater impact on thrifts' survival rate in the second half of the 1980s compared to CRE and land development loans, while mortgage backed securities (MBS) holdings had no effect on the reduction of thrift failures. The positive effects of portfolio diversification can be offset by lower capital ratios and increase in riskier commercial loan portfolios at large BHCs (Demsetz and Strahan, 1997). 3. Sample Selection Our sample period begins with the first quarter of 2000 and ends with the last quarter of 2011. The time period 2000 - 2011 includes the height of the housing bubble, the subsequent collapse, the recession, and the financial crisis of 2008. The ending point of our study period
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coincides with the elimination of the primary thrift regulator, OTS, and the beginning of formal integration of supervisory and reporting policies for commercial banks and thrifts.12 We begin our sample selection with publicly traded banks and thrifts listed on the SNL Financial Bank and Thrift Index. The direct comparison of the financial statements of banks and thrifts is complicated due to the historic differences in reporting formats for these charters. We obtain bank and thrift financial data from SNL Financial and the OCC Integrated Banking Information System database (IBIS) which provide direct mapping of reporting line items for banks and thrifts. The accounting information utilized by our study refers to the “traded entity” since the calculation of the franchise value requires stock data. If the trading entity is a holding company, then the designation as “bank” or “thrift” for the purpose of our study is determined by the charter type of the primary subsidiary of the holding company. 13 During our sample period, the total number of banks and thrifts has significantly declined, in part due to the merger and acquisition process and in part due to the failures during the financial crisis: 168 publicly-traded institutions failed and were placed in the FDIC receivership between 2000 and 2011. Only 37 of these failed institutions were thrifts, 36 of them were acquired by banks, and one by a thrift, through an FDIC-assisted acquisition.14 We exclude systemically important financial institutions with total assets over $50 billion from our study because these institutions differ significantly from the rest of the sample by the types of products, structure, and the level of supervisory
12
Commencing with the first quarter of 2012, thrift institutions are required to submit Call Reports, and SLHC are required to prepare reports in FR Y-9 format similar to BHC. 13 Unitary Thrift Holding Companies (UTHC) are sometimes used by non-banking institutions to compete with banks bypassing the Federal Reserve oversight. The lack of oversight might influence the values of these companies and might be a concern in our analysis. In unreported results, the inclusion of a UTHC indicator in our regression analysis does not change our empirical findings. 14 The mean (median) assets at the time of failure were $1.01 billion ($286 million) for banks and $8.99 billion ($458 million) for thrifts. These numbers are definitely influenced by the notorious large thrift failures. There were a total of 1369 mergers over our sampling period: 295 thrifts were acquired, 176 by banks and 119 by other thrifts. Regular mergers declined in the crisis period. Before the crisis there were approximately 100-150 mergers per year. This number declined to 95 in 2008, 23 in 2009, 43 in 2010 and 65 in 2011.
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attention. While some studies use different cut offs ($100 or $250 billion) to identify the systemically important or TBTF institutions, we use the Dodd-Frank definition of the systemically important depository institutions with its $50 billion in total assets threshold, although we include the largest institutions in our sample as a robustness check. In addition, we identify “charter switchers”, i.e. the banks that switched their charter to a thrift charter and vice versa. We do not consider state and federal charters separately, and the “charter switchers” do not materially affect our results given their limited number. The final panel data covers 48 quarters, from the first quarter of 2000 to the end of 2011, with 442 publicly traded financial institutions, 118 thrifts and 324 banks. The full sample has 5,501 firm-quarters for thrifts and 15,364 firm-quarters for banks. 4. Hypotheses Development and Research Design The main variable of interest in our study is franchise value (FV) for banks and thrifts, which is proxied by Tobin's q. Although Keeley (1990) uses Tobin’s q as a proxy of franchise value, he acknowledges the possibility of measurement error, since the ex post Tobin’s q reflects asset return realization rather than ex ante market power. Jones et al. (2011) note that while Tobin’s q may not be an accurate cardinal measure of franchise value, it is a good ordinal measure. The majority of the empirical studies that follow Keeley (1990) adopt Tobin’s q or its variations as a proxy of bank franchise value (e.g. Demsetz et al., 1996; Nicolo, 2001; Saunders and Wilson, 2001; Osborne and Lee, 2001; Stolz, 2007; Frame and White, 2007). We follow these studies in adopting Tobin’s q as a primarily proxy of franchise value in our comparison study of banks and thrifts.
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The franchise value is defined as the market value of equity plus book value of liabilities divided by book value of assets excluding goodwill: FV =
Market Value of Equity+Book Value of Liabilities Book Value of Assets−Goodwill
(1)
This measure (1) is greater than one if the firm has market power, and equal to or less than one in the absence of market power.15 Previous studies find a strong correlation between franchise value and economic cycles (e.g., Saunders and Wilson, 2001). Therefore, we expect franchise values for both institutions to decline during the crisis. Moreover, we expect thrift franchise values to experience a steeper decline given the much-criticized level of thrift supervision prior to the crisis and their concentration in real estate investments.16 This consideration gives rise to the following hypothesis: H1 . Given the higher concentration in real estate loans, thrifts experience steeper declines in franchise values compared to banks during the crisis. Real estate lending was one of the most negatively affected areas of investment for banking industry in the 2007-2009 financial crisis. We therefore proceed to test the following hypothesis: H2 . Higher concentration in real estate loans has significantly and negatively affected thrift franchise values during the crisis. Following Cole and White (2012), we also investigate whether, among all real estate loans, CRE are associated with lower franchise values. We further segment total real estate
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The franchise value variable was winsorized by 1% at each tail to control for outliers. Since it is not feasible to re-create the QTL test and its applicability for each thrift due to the lack of internal thrift data on specific loan classifications needed for this test, we focus initially on the total level of real estate lending, with further segmentation into the residential RE and CRE loans. For a detailed description of the QTL test refer to: http://www.occ.gov/publications/publications-by-type/comptrollers-handbook/m-qtl.pdf 16
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lending into the loans secured by residential and commercial real estate and examine the impact of each separately. While the exposure to CRE is unlimited for banks, under the Home Owners Loan Act of 1933 (HOLA) the aggregate amount thrifts can lend for CRE is capped at 400% of the thrift’s total capital. In addition, investment in commercial loans is capped at 20%. Loans secured by residential real estate, which include construction and development loans for single housing are included in QTL test. Cole and White (2012) observe that while non-traditional risk exposure to “toxic” assets, such as residential mortgage-based securities, was detrimental to the largest commercial banks during the 2007-2009 crisis, the probability of failure for mediumsized and small institutions can be well-explained by traditional risk factors such as capital, asset quality, earnings, and liquidity, in addition to portfolio mix variables. Complementary to our analysis of franchise values, we explore the risk-return trade-off that characterizes banks and thrifts during our sampling period. From a risk analysis perspective, the thrifts’ specialized-lender model is consistent with overall lower stock returns correlation with the market. Banks, which enjoy a more diversified business model, are expected to be more sensitive to the economic cycle. If the decline in franchise value corresponds to a progressive increase in risk taking (Keeley, 1990), we should also observe an increase in the overall risk exposure of thrifts and banks throughout our sampling period. 4.1 Franchise value regressions Following the general structure of Furlong and Kwan (2006), we model franchise value as determined by proxies for the institution’s asset quality, deposit mix, profitability, size, regulatory capital, and the loan portfolio mix (i.e. commercial and industrial loans, consumer loans, and real estate, further segmented into commercial and residential real estate).
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We use non-performing assets ratio (to total assets) as a proxy for asset quality. Nonperforming assets reflect the institution’s internal lending policies and its level of risk taking as well as macroeconomic trends. Alternative measures of asset quality such as the allowance for loan losses, a contra-asset to loans outstanding, suffer from managerial discretion and are less timely measures of loan portfolio deterioration than non-performing assets (Liu and Ryan, 1995).17 Our loan portfolio mix proxies include the fraction of commercial and industrial loans (C&I Loans), consumer loans (Consumer Loans), and real estate loans (RE Loans) scaled by total assets. Within real estate loans, we distinguish between commercial real estate loans (CRE) and residential real estate (1-4 Fam. RE Loans). We also include some alternative proxies for exposure to real-estate investments that are particularly relevant to the 2007-2009 crisis. Mortgage-backed securities (MBS) scaled by total assets is included in place of total real estate loans. Other Real Estate Owned (OREO), scaled by total assets, is used as an alternative proxy for asset quality in place of non-performing assets. To control for profitability, we include the return on assets (ROA) (Gan, 2004) and the net interest margin (Net Intr. Margin), a primary measure of bank long-term performance (Holton, et al., 2013), which reflects, among other factors, the size of bank transactions, degree of competition, and variance of interest rates (Ho and Saunders, 1981). We also include the level of non-interest income (Non Intr. Income), a broad proxy of non-traditional and off-balance sheet activities (Calmès and Théoret, 2010; Demsetz and Strahan, 1997).
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The loan loss provision involves management judgment about the probability of the repayment of the loan and collateral valuations. Charges to the loan loss provisions can serve to smooth reported earnings (Kanagaretnam et al., 2003). Although the ratio of loan loss provisions to net interest revenues has been considered as a determinant of bank franchise value, for example, by De Jonghe and Vennet (2008), it is not found to have a statistically significant impact.
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All regressions also control for size (Total Assets), regulatory capital (Tier 1 capital) as a standard proxy for bank leverage which is also related to profitability (Berger, 1995), and the fraction of core deposits to total deposits (Core Deposits) which is generally considered a proxy for funding stability (Furlong and Kwan, 2006). To control for macro-economic conditions we include a broad market index (S&P500), and, alternatively, the SNL Banks’ & Thrifts market index (Bank & Thrift Index), and the yield to maturity on a 10-year treasury note (Yield-10-year Tr.). All regressions carried on samples of banks and thrifts include time-varying charter-type indicators to investigate the existence of a “charter effect.” Following Petersen (2009) we report regression estimates with firm and year clustered standard errors.18 Results for our cross-sectional analysis are reported in Tables 3-6.19 A detailed description of the variables used can be found in Appendix A. 5. Empirical Results 5.1 Descriptive statistics During the 2000-2011 sampling period, thrifts are significantly smaller than banks. The mean (median) of total assets of the full sample is $1.7 billion ($529 million) for thrifts and $2.7 billion ($1 billion) for commercial banks. Given the size disparity between two charters, we provide descriptive statistics and carry on part of our empirical analysis on a size-matched sample. During the entire sample period from 2000 to 2011, the mean franchise value of banks in 18
A caveat of our definition of franchise values is that Tobin’s q may mechanically change as the result of changes in the book value of leverage. Since the market-to-book ratio does not suffer from the same problem, we repeated our analysis with market-to-book ratio as a dependent variable. Results are unchanged. 19
We show our results for the contemporaneous non-performing assets. Recognizing that the asset quality may have lagged effect, we repeat our analysis with non-performing assets lagged by two quarters and, alternatively, two forward quarters, with the results consistent with our main findings (the output is not shown for brevity).
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a full sample (1.049) and size-matched banks (1.036) is significantly higher than that of thrifts (1.023) (Table 1). While the overall exposure to real estate loans is only slightly higher for thrifts than for size-matched commercial banks (53.57% versus 50.09%), its composition is significantly different. Residential real estate loans (1-4 Family RE Loans) are 35.65% of thrifts' assets, on average, while they only account for 18.74% for size-matched banks. Banks, on the other hand, are more exposed to commercial real estate (32.00% for size-matched banks and 22.90% for thrifts). In Table 2 (Panel A and B), we compare the means of our explanatory variables for thrifts and banks using t-test for three sub-periods: pre-crisis (2000-2007.Q2), crisis (2007.Q22009) and post-crisis (2010-2011) for the full sample (Panel A) and matched sample (Panel B). Although the National Bureau of Economic Research (NBER) identifies the end of 2007 as the starting point of the downturn,20 we select the third quarter of 2007 as the beginning of the crisis period because the preceding quarter witnessed the failure of the first few subprime mortgage lenders. Similarly, we extend the ending point of the crisis identified by NBER from June 2009 by two quarters, to the fourth quarter of 2009.21 The franchise value of thrifts is significantly lower than banks’ in the full sample for all three sub-periods, and the difference decreases during the crisis and post-crisis (Table 2, Panel A). The results for the matched sub-sample confirm this trend: the difference between bank and thrift franchise values decreases and becomes insignificant during crisis and post-crisis (Table 2, Panel B). Although the level of total real estate loans increased for both banks and thrifts pre-
20
http://www.nber.org/cycles.html The decision to include the entire 2009 in the crisis period is driven by banking-specific events that extend to 2009. For example, the fourth quarter of 2009 witnessed the final round of investments under the Troubled Assets Relief Program (TARP) and Capital Purchase Program (CPP). Moreover, while the financial crisis started in 200708, the first wave of systemic bank failures occurred in 2009. 21
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crisis, the increase was mostly due to the growth in CRE portfolios. We do not observe a significant growth in residential real estate portfolios held on the balance sheet of banks or thrifts, and the levels of MBS remains relatively flat for banks and thrifts in our full and matched samples.22 The t-test analysis (Table 2) shows that during pre-crisis thrifts held a significantly larger proportion of the assets in MBS than banks. The levels of MBS holdings increased during the crisis period for both types of institutions and became equal post-crisis. Prior to crisis, thrifts displayed lower asset quality, expressed by the significantly higher levels of non-performing assets: 0.533% for thrifts and 0.484% (full sample) and 0.448% (matched sample) for banks. Similar trend is observed for OREO: 0.152% for thrifts compared to 0.103% (full sample) and 0.093% (matched sample) for banks. However, the asset quality for the banks significantly deteriorated during the crisis period compared to thrifts. The level of nonperforming assets and OREO exceed that of thrifts and become significantly higher during postcrisis period in the matched sample. The recent literature focusing on the lending behavior during the 2007-2009 financial crisis describes a substantial shift in financial institutions portfolios in favor of real estate lending (e.g., Loutskina and Strahan, 2011). To show the extent to which banks and thrifts increased their exposure to real estate, and commercial real estate, we calculate the maximum proportion of real estate loans (to total assets) held by a bank (thrift) during the crisis and subtract its maximum exposure in the pre-crisis period (“Shift RE”, “Shift CRE”). Banks increase their exposure to real estate more than thrifts: 77% of banks increase their maximum exposure to real estate during the crisis compared to their maximum exposure in the pre-crisis period. On the other hand, 52% of thrifts increase their real estate lending during the crisis. This indicates that banks, more than
22
Our full sample excludes the largest institutions with the total assets exceeding $50 billion.
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thrifts, significantly changed their lending behavior in favor of real estate leading up to the crisis period. Exposure to CRE loans is also significantly more pronounced for banks: 48% of commercial banks increase their maximum exposure to CRE, while only 7% of thrifts increased their exposure to CRE.23 5.2 Franchise value regressions results In Figure 1 we plot the evolution of franchise values for banks and thrifts from 2000 to 2011 on a quarterly basis for the full sample. It is apparent that the franchise values for banks, although generally higher than that of the thrifts, experience a much steeper decline than thrifts during the financial crisis.24 Average bank franchise values are significantly higher than thrift franchise values from 2000 to 2008. Bank and thrift franchise values begin to decline in 2007, coincident with the beginning of the financial crisis. However, bank franchise values decrease more rapidly during the crisis. By the fourth quarter of 2008, the average franchise values of the two types of financial institutions are essentially equal, both economically and statistically. Banks’ franchise values decrease to 0.998 versus 0.986 for thrifts and remain higher than thrifts’ post-crisis, the difference is not significant in the matched sample during and post-crisis. This trend is consistent with the erosion of regulatory differences between banks and thrifts in the time period leading to the approval of the Dodd-Frank Act, which was signed into law in July of 2010. We further examine the effect of the institution charter on the decline in the franchise values in our sample with the regression analysis (H1 ). Several model specifications (Tables 3 and 4) for the full and size-matched sample include dummy variables equal to one if the 23
Results not tabulated for brevity but available upon request from the authors. We confirm this trend with t-tests for the full and size-matched sample for three sub-periods (Table 2, Panel A and B), as well as on a quarterly basis (quarterly analysis is not reported for brevity). 24
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institution held a bank charter in a given year.
The results confirm the univariate results
presented earlier. The positive estimates for the interaction variables of year and bank dummies for the pre-crisis period (2000 to 2007) become negative and significant for both the crisis and the post-crisis period. Therefore, H1 is rejected.25 The results are robust, albeit slightly weaker, to the use of an industry-specific index (SNL Bank and Thrift Index) and the yield-to-maturity on a 10-year Treasury note to proxy for interest rate risk (Table 3, Model 4).26 In order to account for the changes in the real estate lending environment and impact of securitization, we control for MBS held by banks and thrifts (Table 3, Model 2, and Table 4, Models 2 and 3). While MBS is not significant for the entire period, the main results of previous analysis still hold and show a more rapid and significant decline of banks’ franchise values during the crisis and post-crisis period for the full sample. We refine our analysis further by examining the impact of real estate loans in each of the sub-periods for the size-matched sample (Table 5). We find that during the crisis period the real estate loans ratio had negative and significant impact on banks’ but not on thrifts’ franchise values. While real estate loans positively affect the franchise values of banks and thrifts from 2000 to 2007, during the crisis the real estate loans negatively impacted banks’ franchise values and had no significant impact on thrifts. H2 is rejected. The absence of a significant effect of real estate exposure on thrifts' franchise values is possibly due to the lack of variability in the thrifts' portfolio composition. Deregulation in the banking industry allowed banks to increase their exposure to real estate lending in the years preceding the crisis, and to take advantage of the real estate boom. Thrifts' exposure on the other hand was kept high, in part because of the QTL test,
25
Results are similar when the institutions with over $50 billion in total assets are included in the sample. Results available upon request from the authors. 26 As expected, the SNL Banks and Thrifts’ index absorbs much of the time variation in franchise values.
18
but more stable during the pre-crisis and crisis period. Post-crisis, the real estate loans have a strongly negative impact on banks’ franchise values, while the negative impact on thrifts is smaller and only weakly significant. Non-performing loans have a strongly negative impact on franchise values for the entire sample, and for all three sub-periods for banks and thrifts with the exception of the pre-crisis period for thrifts. These results confirm prior findings in the literature that asset quality is one of the strong negative determinants of franchise value, for both types of charters. We turn to a detailed analysis of the impact of (commercial and residential) real estate loans separately for the banks and thrifts with the results presented in Table 6. In Model 1, the interaction terms “CRE*crisis” and “1-4 Family RE*crisis” are negative and significant for our size-matched bank sample, which is consistent with the results reported in Table 5 for total real estate loans. Although the residential lending negatively impacts the franchise value of banks and not thrifts during the crisis, the impact is only weakly significant. As speculation in the real estate market was one of the main precursors of the crisis, we build a proxy to reflect how a shift towards real estate lending in the years leading up to the crisis relates to the loss of franchise value. Since the growth in real estate lending retained on the books is mostly due the increase in CRE, we focus on growth in overall real estate lending, and specifically in CRE segment. The “Shift RE” variable corresponds to the difference between the maximum real estate exposure during the crisis and the pre-crisis maximum. By comparing the maximum level of real estate lending pre-crisis and during the crisis, we control for the pre-crisis banks’ (thrifts’) attitude towards this type of lending. “Shift RE” is positive and significant (0.0018) for thrifts (Table 6, Model 2) but insignificant for banks. Our results indicate that CRE lending (in levels) significantly and negatively affected banks and not thrifts. Negative and 19
significant “Shift CRE” (-0.0008) confirms that the negative and significant impact from increase in real estate lending for banks was due to the increase in CRE lending (Table 6, Model 3). 5.3 Stock performance of banks and thrifts during the crisis. A calendar time portfolio regression approach To provide further robustness to our franchise value analysis, we use a calendar-time portfolio regression approach to compare how thrift and bank stock fared during the crisis period, dependent on their exposure to real estate. First, we identify sub-samples of thrifts and banks characterized by relatively high (low) exposure to real estate lending during the crisis. Second, for each of these portfolios we hypothesize an investment strategy in which a generic investor assumes a “long” position on thrifts and a “short” position on banks during the crisis period. Third, we use calendar-time regressions to evaluate the portfolio performance during the investment period. In these regressions, which are based on the Fama and French three-factor model (1993) augmented by the momentum factor (Carhart, 1997), Rpt-Rft=α+β(Rm-Rft)+sSMBt+hHMLt+mUMDt+ept ,
(2)
the dependent variable Rpt-Rft is the long-short portfolio monthly return Rpt minus Rft, the one-month Treasury bill rate, the explanatory variables are the excess market return factor Rm-Rft, the small-minus-big size factor SMBt, the high-minus-low book-to-market factor HMLt and the up-minus-down momentum factor UMDt. The intercept term α represents the portion of the portfolio mean return not explained by the model. A positive (negative) and significant α means that the long-short portfolio yields a return above (below) the expected return (based on risk).
20
In Table 7 Panel A and B, we report the results of two sets of calendar-time regressions on equally-weighted portfolios “long” on thrifts and “short” on size-matched banks. In Panel A, Shift RE(CRE)-based portfolios (1 and 2), we select thrifts and size-matched banks in the upper (High Exposure) and lower (Low Exposure) quartiles of the distribution of “Shift RE” (“Shift CRE”), the same variable introduced in Table 6. The investment period for these portfolios starts on July 1st, 2007 and ends on Dec. 31st, 2009. In Panel B, RE (CRE) Loans-based portfolios (1 and 2), we select thrifts and sizematched banks in the upper (High Exposure) and lower (Low Exposure) quartiles of the distribution of RE (CRE) Loans for a given quarter within the crisis period. For these portfolios, the event period starts 12-months before the selected high (low) exposure quarter. The stock is kept in the portfolio for the following 12 months. During the crisis, the High Exposure portfolios yield an unexpected positive abnormal return (a positive and significant α), while the Low Exposure portfolios have no abnormal performance. An investment strategy "long" in thrifts and "short" in banks, both highly exposed to real estate, yields an unexpected positive return during the crisis period. Since the portfolio is "short" on banks, these findings imply that after controlling for expected returns, a high exposure to real estate (upper quartile) is, at the least, more detrimental for banks that it is for thrifts. These results support our franchise value findings and are consistent with our conjecture that thrifts traditional specialization in real estate generates a better performance for thrifts during the crisis.27 The observed better than expected performance can also be interpreted as thrifts possibly being undervalued (or banks overvalued) at the start of the crisis. The same analysis repeated for CRE loans leads to very similar, slightly stronger results. This analysis 27
For robustness we limit the investment period to 2007Q3-2009Q2. Results are consistent, albeit weaker compared to the ones reported.
21
reinforces our earlier conclusion reached with the franchise value analysis: thrifts are a valuable charter option even after the 2007-2009 crisis.28 5.4 Robustness checks We performed numerous robustness checks, which support the main findings of this study.29 These robustness checks include the treatment of TARP recipients, of mergers and acquisitions, of “too-big-to-fail” institutions, reduced-form models, models including the efficiency ratio,30 and the effect of off-balance sheet exposure as determinants of the franchise value. Finally, following Ashcraft et al. (2010) and Frame (2012), we also control for the effect of Federal Home Bank Loan (FHBL) advances scaled by total assets, on thrifts and banks. FHLBs were key sources of funding to depository institutions during the onset of the financial crisis (see Ashcraft, et al. 2010), and can be used as an alternative way of assessing financial distress. Even though FHLB advances have a negative sign in our franchise value regressions, as expected, the variable is not significant and our main results are robust to the inclusion of this variable.
28
We also calculate buy-and-hold (compound) abnormal returns (BHAR) using a standard two-step event study procedure. The investment strategy is again “long” on thrifts and “short” on banks from July 1st 2007 to Dec. 31st, 2009 and portfolios are selected in upper (High Exposure) and lower (Low Exposure) quartiles of the distribution of “Shift RE” (“Shift CRE”). The Generalized Sign Test and Hall’s T-test reject the null hypothesis of zero abnormal buy-and-hold returns, i.e. both portfolios yield better than expected returns during the crisis period. Returns are significantly higher for the high-exposure portfolios, which is consistent with our calendar-time portfolio regression findings: at high levels of exposure to (commercial) real estate, thrifts outperform banks during the crisis period. 29 The majority of these tests are reported in the unpublished Appendix to the paper, which is available from the authors upon request. 30 As a robustness check, we re-run our main regression model (Table 3) and include the variable “Efficiency Ratio.” This variable is defined as the level of noninterest expense, less amortization of intangible assets, divided by net interest income on a fully taxable equivalent basis and noninterest income. Results are unchanged.
22
6. Conclusion The U.S. banking system has been undergoing significant regulatory and competitive changes in the last decades, starting with the S&L crisis of the 1980s. These changes were accelerated by the 2007-2009 financial crisis, and resulted, among other things, in a regulatory convergence of commercial banks and thrifts. In this study we compare franchise values of thrifts to commercial banks during the 2000-2011 period which included the rise and subsequent collapse of the real estate market bubble. Since thrift institutions traditionally maintain a significantly higher level of real estate loans, we pay a special attention to the real estate lending concentration to examine the effect of the real-estate bubble on these specialized lenders. We find that the franchise values of both the banks and thrifts declined during the recent crisis, which is expected and consistent with the prior research, e.g. Keeley (1990) who observed a similar decline during the S&L crisis, or Huizinga and Laeven (2012) during the 2007-2009 crisis. Our major finding calls into question the perceived inferior performance of thrifts during the recent financial crisis. Results in the pre-crisis period agree with the popular perception of inferiority of the thrift charter. We find that average bank franchise values were significantly higher than thrift franchise values in the period before the financial crisis. As expected, both the franchise value of banks and thrifts declined during the 2007-2009 financial crisis. However, during the crisis period, franchise values of the commercial banks experienced a significantly steeper decline than thrifts’ despite the existing regulatory constraints on lending diversification and, specifically, the higher concentration in residential real estate loans required for the thrift institutions. By the end of 2009, there were essentially no differences between bank and thrift franchise values. It appears that firm specific sources of franchise values for the smaller publicly 23
traded thrifts – better asset quality, possibly a result of a higher competency stemming from a specialization in real estate lending, and fewer commercial real estate loans – offset any disadvantages of the thrift charter such as regulatory imposed focus in certain types of lending (e.g., residential lending). It is also possible that the on-going and anticipated regulatory convergence contributed to equalization of the franchise values for banks and thrifts during the 2007-2009 crisis. To add robustness to our franchise value analysis, we also show that an investment strategy “long” on thrift stock and “short” on banks with comparable high exposure to (commercial) real estate generates a positive and significant abnormal return during the crisis with thrifts outperforming banks. Our study shows that despite the well-known large thrift failures during the 2007-2009 financial crisis and regulatory constraints on lending diversification, the remaining thrift institutions did not perform worse than commercial banks in terms of their franchise values and stock performance. Regardless of the differences in loan portfolio mix and the remaining regulatory constraints on lending for thrifts, both types of charter display a convergence in their average franchise values following the financial crisis.
24
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Appendix A - Variable Description Variables Total Assets
Total Deposits Core Deposits Tier 1 Ratio Non-performing Assets
OREO
ROA Non Intr. Income Net Intr. Margin
Total Real Estate Loans
Total Consumer Loans 1-4 Family Residential Loans Commercial Real Estate (CRE) Loans C&I Loans MBS
Description All assets owned by the company as of the date indicated, as carried on the balance sheet and defined under the corresponding accounting principles. [In logarithmic function] Amounts in customers' banking deposits; any accounts subject to federal banking deposit insurance, including any portions in jumbo deposits that are not insured but subject to the FDIC deposit regulations. Deposits, less time deposit accounts with balances over $100,000, foreign deposits and unclassified deposits [Scaled by total deposits] Tier 1 capital scaled by of total risk-adjusted assets. The sum of total nonaccrual loans; loans and leases restructured and in compliance with modified terms; total other real estate owned; and nonaccrual debt securities and other assets. Loans 30 to 90 days past due are not included. [Scaled by total assets] The book value, less accumulated depreciation, if any, of all real estate other than bank premises owned or controlled by the bank and its consolidated subsidiaries. Mortgages and other liens on such property are not deducted. Amounts are reported net of any applicable valuation allowances. Any property necessary for conducting banking business is excluded. [Scaled by total assets] Net income before extra-ordinary expenses as scaled by total assets Non-interest income (fiduciary income, service charges, trading revenue and other non-interest income). [Scaled by total assets] Net interest income, on a fully taxable-equivalent basis if available. [Scaled by total assets] Gross amount of on-balance sheet real estate loans. This information is collected as reported in the loan detail. Includes loans secured by real estate with original maturities of 60 months or less made to finance land development or construction, loans secured by farmland, loans secured by 1-4 family residential properties, loans secured by multifamily (5 or more) residential properties, loans secured by nonfarm residential properties. [Scaled by total assets] Gross amount of on-balance sheet consumer loans in domestic offices. This information is collected as reported in the loan detail. Consumer loans include home equity, credit card, vehicle and other consumer loans. [Scaled by total assets] Gross amount of first and second liens (including HELOCs) loans secured by 1-4 family properties Gross amount of real estate secured by 5+ properties, and non-farm nonresidential properties, and construction and development loans. Gross amount of on-balance sheet commercial loans in domestic offices. This information is collected as reported in the loan detail. [Scaled by total assets] All held-to-maturity (at amortized cost) and available-for-sale (at fair value) holdings of certificates of participation in pools of residential mortgages, i.e. 30
single-class pass-through securities. [Scaled by total assets] Goodwill
Excess of purchase price paid over value of net assets acquired.
Market Capitalization
Aggregate market capitalization of all issues of common equity whether traded or non-traded, including convertible common stock on a one-to-one basis until the conversion window opens, and then at the conversion rate. If pricing is not available for secondary classes, the price of the primary class is applied.
Charter type (0/1)
Binary variable. Equals “1” for commercial bank charter and “0” for thrift.
Bank & Thrift Index
Value-weighted index including all traded banks and thrifts. SNL financial.
Yield (10-year Tr.)
Yield to maturity of the 10-year treasury note
S&P500
S&P 500 index level
31
Appendix B -Regulatory Changes in Bank and Thrift Industries Thrifts were established as mutual companies specializing in residential lending pursuant to the Home Owners’ Loan Act (HOLA) of 1933. Subsequently, the National Housing Act of 1934 created Federal Savings and Loan Insurance Corporation (FSLIC). The original purpose of the thrift charter was to promote homeownership following the economic shock of the Great Depression. For a long time the thrift lending focus and its specific mandate differentiated thrifts from banks, while statutory advantages, for example extensive inter-state branching rights, were designed in support of national residential lending. Statutory limitations on lending were also designed to keep the charter focused on real estate lending while limiting risks.31 Over the years many of the charter peculiarities were directly and indirectly eradicated, or relaxed, making bank and thrift charters more similar. The progressive demise of the thrift industry started in the mid-1980s following the S&L crisis with regulatory changes that reduced the competitiveness of thrifts and blurred most of the distinctions with banks. The Financial Institutions Reform, Recovery, and Enforcement Act of 1989 (FIRREA) abolished FSLIC and established OTS. FIRREA reinforced the specialization of thrifts in residential mortgage lending by placing restrictions on CRE lending and increasing QTL limits related to residential lending (Helwege, 1996). Following FIRREA there were several legislative proposals attempting to abolish OTS and merge it with OCC (Kushmeider, 2005). Such proposals and documents asserted that the expansion of commercial banks and other financial institutions into home lending made the thrift specialization unnecessary and the charter itself obsolete (Treasury Department, 2008). The deregulation process produced by the Riegle-
31
For example, until the 1980s thrifts had restrictions on making commercial loans and taking time deposits, but eventually, with the passage of the Depository Institutions and Deregulation Control Act of 1982, they were allowed to make consumer and commercial real estate loans both capped at 20% of the total assets (Chatman, 2013).
32
Neal Interstate Banking and Branching Efficiency Act of 1994 eliminated more privileges of the thrift charter by allowing commercial banks to branch more easily in other states. Subsequently, the Gramm-Leach-Bliley Act (GLBA) also known as the Financial Services Modernization Act (FMSA) of 1999 allowed the consolidation of commercial banks, investment banks and insurance companies and changed the competitive landscape and riskiness of the U.S. banking industry (Berger et al., 1999; Akhigbe and Whyte, 2001; Akhigbe and Whyte, 2004). For BHCs the GLBA for the first time allowed insurance underwriting. The act essentially eliminated any pre-existing differential treatment regarding the integration of banking and commerce. The act also denied the creation of any new industrial or commercial unitary thrift holding company (UTHC) after May 4, 1999. More specifically, GLBA prohibited commercial companies to utilize UTHC to acquire a thrift institution. Prior to GLBA, the non-bank unitary thrift holding company platform provided one of the passageways for non-financial companies to engage in both depository and non-depository activities (Carow and Heron, 2002). Immediately before Dodd-Frank, thrifts still enjoyed a few advantages over commercial banks, such as the consolidated supervision by the OTS of both the thrift and its parent Savings and Loan Holding Company (SLHC), broad inter-state branching authority, “field preemption” under OTS regulation of lending and depository activities of federal thrifts, and the absence of regulatory holding company capital requirements (Maxwell and Swhier, 2010). Trade-offs to those benefits were the limits placed on commercial lending and the QTL test which requires thrifts to hold at least 65% percent of its portfolio in Qualified Thrift Investments (QTI) such as residential real estate, home equity loans, educational loans, small business loans, credit card loans, mortgage-backed securities (MBS) and other QTI established by the OTS (Office of Thrift
33
Supervision, 2002). The QTL test remains one of the most distinguishing features of the thrift charter (Zaring and Donelson, 2011). The Dodd-Frank mandated the elimination of the OTS, which took effect on July 21, 2011, and transferred the regulation of federally chartered thrift institutions to the Office of the Comptroller of the Currency (OCC) and the supervision of state-chartered thrifts to the FDIC, with the regulation of the SLHC passed on to the Federal Reserve Board (FRB). Dodd-Frank also intervened on capital requirements, branching and dividend policy of the chartered thrifts. Prior to Dodd-Frank, SLHCs were not subject to any formal capital requirement; after its passage, thrift holding companies have the same capital and activity standards required for bank holding companies under the Bank Holding Company Act of 1956 and the subsequent FRB regulations.32 While nationwide branching was for a long time a privilege of federal thrifts, Dodd-Frank provides out-of-state commercial banks with the same de novo branching power.33 Finally, another privilege of federal thrifts eliminated by Dodd-Frank was the regulator reliance on HOLA to permit the field preemption of state laws against federal thrifts and allowed thrifts for a long time to enjoy more freedom from state supervision than commercial banks. FIRREA granted the OTS the power to preempt state law when conflicting with HOLA and FIRREA. In 1996, the OTS regulation established the right of federal savings and loans associations to “extend credit as authorized under federal law…without regard to state laws purporting to
32
The Dodd-Frank Act further impacts the UTHC exemption (in Section 626) by giving an authority to the Federal Reserve Board to require the grandfathered UTHC to set up an intermediate holding company, “if a grandfathered unitary savings and loan holding company conducts activities other than financial activities”, or in any other instances as deemed necessary for the appropriate supervision. 33 State and national banks can now open a de novo branch in another state if the law of that state would permit a local state chartered bank to open the branch.
34
regulate or otherwise affect their credit activities”.34 However, the competitive advantage granted to thrifts was short lived as in 2004 the OCC adopted preemption rules for national banks akin in scope to federal thrifts field preemption. The Dodd-Frank act eliminates the federal thrift preemption and applies the same standards applicable to national banks. The act also limits the extent to which state consumer protection regulation can be preempted.35
34 35
12 C.F.R § 560.2 (a). See Section 1044 of the Dodd-Frank Act.
35
Table 1 Descriptive Statistics for the full and size-matched sample This table presents descriptive statistics for the thrifts, banks, and size-matched banks for the sample period 2000-2011. Franchise value is calculated as (Market Value of Equity+ Book Value of Liabilities)/(Book Value of Assets-Goodwill) on a quarterly basis. Core Deposits are scaled by total deposits. All other financial statement items are scaled by total assets. Observations are matched by quarters and with replacement. For a detailed description of the variables refer to Appendix A. Mean
Franchise Value Core Deposits (% of Total Deposits) Consumer Loans (% of Total Assets) C&I Loans (% of Total Assets) RE Loans (% of Total Assets) 1-4 Family RE Loans (% of Total Assets) CRE Loans (% of Total Assets) OREO (% of Total Assets) MBS (% of Total Assets) Tier 1 Ratio (% of Risk-weighted Assets) Non-performing Assets (% of Total Assets) Net Interest Margin (% of Total Assets) Total Assets ($000) Non-Interest Income (% of total income) ROA N
Thrifts 1.023 84.908 3.792 7.515 53.569 35.651 22.897 0.408 12.426 17.212 1.523 3.215 1,669,643 0.565 1.035 5501
Banks 1.049 82.089 11.404 7.334 48.927 18.254 30.497 0.365 10.326 13.149 1.473 3.980 2,683,709 1.159 1.535 15364
Median Matched Banks 1.036 82.600 6.889 10.970 50.088 18.742 32.004 0.395 9.811 13.184 1.596 3.985 1,681,773 1.107 1.202 4606
36
Thrifts 1.013 86.539 2.568 6.701 53.167 37.032 17.767 0.100 8.835 14.200 0.611 3.236 528,574 0.440 1.580 5501
Banks 1.045 84.233 9.619 6.021 49.276 17.923 29.096 0.090 8.594 11.920 0.560 3.910 1,071,763 0.960 2.267 15364
Standard deviation Matched Banks 1.031 84.500 5.650 8.906 50.095 18.253 30.648 0.090 7.865 12.150 0.565 3.920 537,884 0.850 1.982 4606
Thrifts 0.066 10.002 3.878 6.272 14.590 14.495 17.623 0.782 11.776 9.228 2.471 0.686 3,947,446 0.832 3.253 5501
Banks 0.068 10.203 7.406 6.019 13.375 9.472 13.603 0.690 9.372 14.589 2.422 0.830 4,540,332 1.153 4.405 15364
Matched Banks 0.065 10.100 5.791 7.407 12.996 9.249 13.154 0.746 9.047 4.749 2.638 0.814 3,927,911 1.487 4.745 4606
Table 2 Means and t-tests for the full and size matched sample. Pre-crisis, crisis and post-crisis periods. Franchise value is calculated as (Market Value of Equity+Book Value of Liabilities)/(Book Value of Assets-Goodwill) on a quarterly basis. Core Deposits are scaled by total deposits. All other financial statement items are scaled by total assets. For a detailed description of the variables refer to Appendix A. *, ** and *** denote statistical significance at the 0.10, 0.05 and 0.01 levels, respectively. Pre-crisis (2000-2007Q2) Crisis (2007Q3-2009) Post-crisis (2010-2011) t-ratio Panel A: Full Sample Thrifts Banks t-ratio Thrifts Banks t-ratio Thrifts Banks Franchise Value Core Deposits (% of Total Deposits) C&I Loans (% of Total Assets) Consumer Loans (% of Total Assets) RE Loans (% of Total Assets) OREO (% of Total Assets) MBS (% of Total Assets) 1-4 Family RE Loans (% of Total Assets) CRE Loans (% of Total Assets) Tier 1 Ratio (% of Risk-weighted Assets) Non-performing Assets (% of Total Assets) Net Interest Margin (% of Total Assets) Total Assets ($000) Non-Interest Income (% of total income) ROA N
1.042 85.248 3.39 7.63 52.772 0.152 12.282 36.901 19.734 17.101 0.533 3.222 1474447 0.57 1.803 3412
1.075 82.36 11.894 7.421 46.874 0.103 9.817 18.824 28.113 13.52 0.484 4.128 2236979 1.227 2.52 9562
Panel B: Matched Sample
Thrifts
Matched Banks
Franchise Value Core Deposits (% of Total Deposits) C&I Loans (% of Total Assets) Consumer Loans (% of Total Assets) RE Loans (% of Total Assets) OREO (% of Total Assets) MBS (% of Total Assets) 1-4 Family RE Loans (% of Total Assets) CRE Loans (% of Total Assets) Tier 1 Ratio (% of Risk-weighted Assets) Non-performing Assets (% of Total Assets) Net Interest Margin (% of Total Assets) Total Assets ($000) Non-Interest Income (% of total income) ROA N
1.042 86.2 3.39 7.63 52.772 0.152 12.282 36.901 20.871 17.101 0.533 3.222 1474447 0.57 1.803 3412
1.065 83.0 11.768 6.954 48.111 0.093 8.737 19.21 29.989 13.295 0.448 4.155 1472815 1.189 2.283 2628
-22.38 12.44 -58.76 1.45 18.81 4.83 5.71 23.15 -9.44 13.33 3.82 -55.4 -10.00 -19.81 -16.67
*** *** *** *** *** *** *** *** *** *** *** *** *** ***
t-ratio 12.98 -11.2 41.9 -3.89 -12.13 -4.59 -7.76 -23.15 9.44 -17.9 5.05 44.25 -0.02 15.13 8.75
*** *** *** *** *** *** *** *** *** *** *** *** *** ***
1.009 82.406 4.174 7.55 55.41 0.394 13.091 33.71 28.942 17.434 1.894 3.084 1840781 0.526 0.106 1152
1.018 80.549 11.424 6.934 53.073 0.373 10.258 17.439 35.237 11.95 2.00 3.711 3262696 1.09 -0.136 3225
Thrifts
Matched Banks
1.009 85.90 4.174 7.55 55.41 0.394 13.091 33.71 28.942 17.434 1.894 3.084 1840781 0.526 0.106 1152
1.006 80.6 10.741 6.469 53.086 0.386 10.849 18.164 35.692 12.661 2.019 3.722 1876281 1.029 -0.218 1108
37
-4.52 5.26 -32.4 2.91 4.63 0.72 4.81 12.5 -3.71 15.78 -1.39 -27.77 -9.00 -15.46 -1.44
*** *** *** *** *** *** *** ** *** *** *** ***
t-ratio 1.05 -11.84 22.37 -4.20 -3.96 -0.23 -3.45 -12.50 3.71 -13.21 1.31 21.83 0.20 7.78 -1.34
*** *** *** *** *** *** *** *** *** ***
0.986 86.277 4.177 7.14 53.612 0.863 11.854 33.511 26.977 17.319 4.087 3.355 2024792 0.603 -0.03 937
0.998 83.177 9.713 7.529 50.974 0.925 12.142 17.285 32.914 13.324 4.317 3.792 3535726 1.008 0.159 2577
Thrifts
Matched Banks
0.986 86.6 4.177 7.14 53.612 0.863 11.854 33.511 26.977 17.319 4.087 3.355 2024792 0.603 -0.03 937
0.987 84 8.911 7.22 52.239 0.99 11.677 17.963 34.335 13.515 4.524 3.808 2065251 0.962 -0.255 870
-6.58 8.45 -22.72 1.94 4.87 0.97 -0.53 13.21 -3.72 13.47 -1.53 -17.14 -8.00 -9.74 -1.01
*** *** *** * ***
*** *** *** *** *** ***
t-ratio 0.33 -3.37 15.78 0.33 -2.23 1.76 -0.30 -13.21 3.72 -11.75 2.32 13.95 0.17 5.36 -0.90
*** *** ** * *** *** *** ** *** ***
Table 3 Regression Analysis for the full and matched sample. Clustered Standard Errors. The dependent variable is the quarterly franchise value for banks and thrifts. Franchise value is calculated as (Market Value of Equity+Book Value of Liabilities)/(Book Value of Assets-Goodwill) on a quarterly basis. Core Deposits are scaled by total deposits. All other financial statement items are scaled by total assets. For a detailed description of the variables refer to Appendix A. Bank 2001-2011 is a 0/1 indicator taking the value of “1” for bank charter and respective year. Reported t-ratios are for clustered standard errors. Standard errors are clustered by firm and year. *, ** and *** denote statistical significance at the 0.10, 0.05 and 0.01 levels, respectively.
Core Deposits Total Assets (log) RE Loans C&I Loans Consumer Loans Tier 1 Capital ROA Non-performing Assets Net Intr. Margin Non Intr. Income MBS Yield (10-year Tr.) Bank & Thrift Index S&P500 Bank Charter (0/1) Bank 2001 (0/1) Bank 2002 (0/1) Bank 2003 (0/1) Bank 2004 (0/1) Bank 2005 (0/1) Bank 2006 (0/1) Bank 2007 (0/1) Bank 2008 (0/1) Bank 2009 (0/1) Bank 2010 (0/1) Bank 2011 (0/1) Intercept N R2 Adj. R2
Model 1
Model 2
Model 3
Model 4
Full Sample
Full Sample
Matched Sample
Matched Sample
Coeff.
t-ratio
0.0002 0.0182 -0.0003 -0.0008 -0.0008 -0.0002 0.0008 -0.0047 0.0211 0.0014
1.28 11.61 -1.66 -3.12 -2.88 -0.32 3.16 -5.50 9.72 0.90
0.0171 -0.0158 0.0157 0.0265 0.0485 0.0652 0.0545 0.0544 0.025 -0.0028 -0.0241 -0.0225 -0.0327 0.6953 15007 50.17% 50.09%
4.22 -2.32 6.73 7.52 12.43 16.39 14.22 13.39 5.52 -0.59 -4.47 -4.38 -6.41 23.08
*** * *** *** *** *** ***
*** ** *** *** *** *** *** *** *** *** *** *** ***
Coeff.
t-ratio
0.00019 0.01824 -0.00032 -0.00009 -0.00081 -0.00079 -0.00021 0.00085 -0.00471 0.02111 0.00131
1.21 11.25 -1.70 -0.41 -3.11 -2.90 -0.38 3.16 -5.45 9.64 0.86
0.01651 -0.01634 0.01561 0.02697 0.04857 0.06566 0.05498 0.05507 0.02572 -0.00194 -0.02367 -0.02205 -0.03187 0.70087 14882 50.38% 50.30%
4.04 -2.24 6.35 7.37 11.61 15.39 13.29 12.62 5.34 -0.38 -4.06 -3.97 -5.64 22.67
Coeff. *** * *** *** *** *** ***
*** ** *** *** *** *** *** *** *** *** *** *** ***
38
0.0002 0.0213 -0.0001 -0.0006 -0.0006 0.0009 0.0002 -0.0051 0.0143 -0.0004
0.0142 -0.0006 0.0179 0.0161 0.0431 0.0542 0.0449 0.0437 0.0135 -0.0168 -0.0326 -0.0313 -0.0385 0.6594 5805 51.20% 51.12%
t-ratio
Coeff.
1.07 12.35 *** -0.65 -2.08 ** -2.10 ** 1.56 0.70 -4.09 *** 5.10 *** -0.26
2.29 -0.07 3.29 2.71 6.80 8.43 7.30 7.18 2.11 -2.74 -4.62 -4.35 -5.45 19.93
t-ratio
0.00024 0.02154 -0.00012 -0.0006 -0.00065 0.00095 0.0002 -0.00331 0.01592 -0.00045
1.58 12.34 *** -0.78 -1.96 * -2.26 ** 1.59 0.76 -3.10 *** 5.69 *** -0.34
0.00593 0.00714
2.17 ** 6.89 ***
** *** *** *** *** *** *** ** *** *** *** *** ***
0.00381 0.01061 0.00854 0.03288 0.03247 0.02109 0.00893 -0.01574 -0.01539 -0.0151 -0.01716 -0.01597 0.58105 5805 49.91% 49.71%
0.32 1.79 1.29 3.72 3.20 2.08 0.88 -1.49 -1.50 -1.73 -1.77 -1.54 18.74
* *** *** ***
* * ***
Table 4 Regression Analysis for the full sample. Clustered Standard Errors. The dependent variable is the quarterly franchise value for banks and thrifts. Franchise value is calculated as (Market Value of Equity+Book Value of Liabilities)/(Book Value of Assets-Goodwill) on a quarterly basis. Core Deposits are scaled by total deposits. All other financial statement items are scaled by total assets. For a detailed description of the variables refer to Appendix A. Bank Pre-crisis/crisis/Post-crisis is a 0/1 indicator taking the value of “1” for bank charter and respective sub-period. In Model 2, MBS scaled by the total assets substitutes RE Loans. In Model 3, MBS & RE Loans is the sum of RE Loans and MBS scaled by the total assets. Reported t-ratios are for clustered standard errors. Standard errors are clustered by firm and year. *, ** and *** denote statistical significance at the 0.10, 0.05 and 0.01 levels, respectively. Model 1 Core Deposits Total Assets (log) RE Loans MBS MBS & RE Loans C&I Loans Consumer Loans Tier 1 Capital ROA OREO Non-performing Assets Net Intr. Margin Non Intr. Income Bank Charter (0/1) S&P500 Bank crisis (0/1) Bank post-crisis (0/1) Intercept N R2 Adj. R2
Coeff. 0.0003 0.0190 0.0000
t-ratio 1.72 12.41 -0.23
Model 2 * ***
-0.0006 -0.0007 0.0001 0.0009
-2.32 -2.73 0.13 3.18
** ***
-0.0055 0.0180 0.0014 0.0283 0.0232 -0.0503 -0.0683 0.6600 15007 44.78% 44.72%
-6.28 8.73 0.89 4.73 10.58 -17.15 -17.82 22.69
*** ***
***
*** *** *** *** ***
Model 3
Coeff. 0.0003 0.0186
t-ratio 1.62 11.61
0.0003
1.32
-0.0005 -0.0007 0.0000 0.0009
-2.40 -2.64 -0.06 3.15
** ***
-0.0053 0.0186 0.0016 0.0287 0.0240 -0.0506 -0.0693 0.6584 14882 44.03% 43.98%
-6.19 9.03 1.01 4.92 10.43 -18.50 -17.94 24.98
*** ***
***
***
*** *** *** *** ***
39
Coeff. 0.0003 0.0191
t-ratio 1.85 12.32
0.0001 -0.0004 -0.0006 0.0002 0.0009 -0.0055
0.88 -1.71 -2.31 0.44 3.14 -6.39
0.0178 0.0015 0.0298 0.0230 -0.0513 -0.0690 0.6424 15007 44.82% 44.76%
8.90 0.93 4.90 10.55 -17.18 -17.51 22.50
* ***
* ** *** *** *** *** *** *** *** ***
Table 5 Regression Analysis on the banks and thrifts for the matched sample. Clustered Standard Errors. Pre-crisis, crisis and post-crisis periods. The dependent variable is the quarterly franchise value for banks and thrifts. Franchise value is calculated as (Market Value of Equity+Book Value of Liabilities)/(Book Value of Assets-Goodwill) on a quarterly basis. Core Deposits are scaled by total deposits. All other financial statement items are scaled by total assets. For a detailed description of the variables refer to Appendix A. Reported t-ratios are for clustered standard errors. Standard errors are clustered by firm and year. *, ** and *** denote statistical significance at the 0.10, 0.05 and 0.01 levels, respectively. Pre-crisis (2000-2007Q2) Thrifts Core Deposits Total Assets (Log) RE Loans C&I Loans Consumer Loans Tier 1 ratio ROA Non-performing Assets Net Intr. Margin Non Intr. Income S&P500 Intercept N R2 Adj. R2
Coeff. 0.0001 0.0296 -0.0006 -0.0031 -0.0008 0.0018 -0.0013
t-ratio 0.33 7.14 -1.3 -1.83 -1.29 2.17 -0.58
-0.0026
-0.37
0.0266 0.0034 0.0285 0.5392 701 48.87% 48.65%
2.56 0.96 2.67 8.09
Crisis (2007Q3-2009)
Matched Banks
*** * **
** *** ***
Thrifts
Coeff. 0.0000 0.0244 0.0008 0.0007 -0.0005 0.0011 0.0048
t-ratio 0.02 10.21 3.53 2.11 -1.49 1.03 2.7
***
Coeff. -0.0002 0.0237 0.0002 -0.0018 -0.0002 0.0024 -0.0015
t-ratio -0.33 6.7 0.61 -1.66 -0.19 2.11 -2.71
*** *** **
-0.0071
-2.88
***
-0.0071
-3.44
0.0129 0.0009 0.0029 0.6177 1848 40.05% 39.79%
4.47 0.35 0.57 11.79
***
-0.0097 0.0006 0.0364 0.6365 365 59.91% 59.54%
-1.02 0.17 4.7 6.88
***
40
Post-crisis (2010-2011)
Matched Banks t-ratio 1.63 4.4 -3.3 -2.7 -1.57 -4.97 0.44
*** *** ***
** ***
Coeff. 0.0004 0.0096 -0.0007 -0.0009 -0.0006 -0.0033 0.0001
***
-0.0058
-3.41
0.0219 -0.0004 0.0426 0.7904 849 47.62% 47.14%
6.16 -0.43 8.94 19.52
*** *
*** ***
Thrifts Coeff. 0.0009 0.0278 -0.0005 -0.0007 0.0000 0.0003 0.0003
t-ratio 2.00 9.39 -1.7 -0.75 -0.04 0.39 0.88
***
-0.0035
-3.21
***
0.0046 -0.0148 -0.0092 0.5817 287 70.37% 70.04%
0.64 -3.1 -0.83 10.44
***
*** ***
Matched Banks ** *** *
*** *** ***
Coeff. 0.0007 0.0086 -0.0008 -0.0009 -0.0010 -0.0021 -0.0001
t-ratio 2.84 2.71 -3.21 -2.09 -1.65 -2.94 -0.28
-0.0027
-2.53
**
0.0026 0.0033 -0.0016 0.9009 691 20.62% 19.72%
0.62 1.13 -0.17 17.51
***
*** *** *** ** ***
Table 6 Regression Analysis on the banks and thrifts for the matched sample. Clustered Standard Errors. Pre-crisis, crisis and post-crisis periods. The dependent variable is the quarterly franchise value for banks and thrifts. Franchise value is calculated as (Market Value of Equity+Book Value of Liabilities)/(Book Value of Assets-Goodwill) on a quarterly basis. Shift RE (CRE) is the difference between the Max. RE (CRE) exposure during the crisis and the Max. RE (CRE) exposure before the crisis. Max. is based on the value of RE (CRE) Loans scaled by total assets. Core Deposits are scaled by total deposits. All other financial statement items are scaled by total assets. For a detailed description of the variables used refer to Appendix A. 1-4 Family RE, CRE, MBS, C&I and Consumer Loans *crisis are the cross-product of 1-4 Family RE, CRE, MBS, C&I and Consumer Loans and a crisis indicator (0/1). Reported t-ratios are for clustered standard errors. Standard errors are clustered by firm and year. *, ** and *** denote statistical significance at the 0.10, 0.05 and 0.01 levels, respectively. Model 1 Model 2 Model 3 Thrifts Coeff.
Shift RE Shift CRE Core Deposits Non Intr. Income Total Assets (log) Non-perform. Assets 1-4 Fam. RE Loans CRE Loans C&I Loans Consumer Loans 1-4 Fam.RE*crisis CRE*crisis Cons. Loans*crisis C&I Loans*crisis ROA Tier 1 Ratio Net Intr. Margin S&P500 Intercept N R2 Adj. R2
0.0001 0.0178 0.0291 -0.0125 0.0002 -0.0012 -0.0046 -0.0008 -0.0005 -0.0005 -0.0025 0.0010 -0.0004 -0.0024 0.0261 0.0017 0.6499 553 60.57% 59.39%
t-ratio
1.01 2.12 5.08 -3.33 0.56 -1.72 -1.83 -0.69 -0.94 -1.57 -3.16 0.60 -0.47 -1.67 2.58 0.12 7.47
** *** ***
*
***
** ***
Matched Banks
Thrifts
Coeff.
Coeff.
-0.0001 0.0002 0.0174 -0.0114 0.0001 0.0000 -0.0001 -0.0009 -0.0005 -0.0004 -0.0006 0.0001 0.0002 -0.0013 0.0203 0.0044 0.7700 3324 41.01% 40.74%
t-ratio
-0.27 0.07 4.17 -7.24 0.26 -0.09 -0.35 -2.13 -1.78 -2.32 -1.15 0.32 0.51 -0.8 5.77 0.25 7.76
*** ***
** * **
*** ***
t-ratio
0.0018
3.04
0.0001 0.0155 0.0259 -0.0121 -0.0006 -0.0008 -0.0003 -0.0035
1.54 2.30 6.60 -2.88 -1.03 -1.58 -0.34 -1.44
-0.0030 -0.0005 -0.0003 -0.0016 0.0171 -0.0017 0.6948 545 59.46% 58.31%
-2.79 -0.32 -0.37 -1.33 3.24 -0.12 10.51
41
*** ** *** ***
***
*** ***
Matched Banks
Thrifts
Coeff.
Coeff.
t-ratio
Coeff.
0.0002 0.0001 0.0128 0.0303 -0.0114 -0.0004 -0.0010 -0.0002 -0.0040
0.26 0.34 1.79 6.77 -2.43 -0.47 -2.11 -0.16 -1.54
-0.0008 0.0001 0.0007 0.0173 -0.0127 0.0000 -0.0001 -0.0008 0.0002
-2.09 0.34 0.27 4.01 -8.30 0.09 -0.41 0.48 -1.38
-0.0025 -0.0005 -0.0015 -0.0018 0.0235 0.0021 0.6181 448 62.04% 60.72%
-2.96 -0.36 -1.24 -1.20 3.35 0.13 7.40
-0.0007 -0.0016 0.0001 -0.0013 0.0198 0.0089 0.7491 2750 41.00% 40.67%
-1.23 -2.78 0.12 -0.75 5.16 0.55 7.22
t-ratio
0.0000
-0.01
0.0001 0.0005 0.0176 -0.0122 0.0001 -0.0002 -0.0008 0.0002
0.21 0.20 4.18 -8.08 0.16 -0.57 -1.55 0.52
-0.0007 -0.0017 0.0001 -0.0012 0.0197 0.0087 0.7469 3025 40.27% 39.97%
-1.28 -2.78 0.24 -0.74 5.30 0.53 7.43
*** ***
*** *** ***
Matched Banks
*** ** **
**
** ***
t-ratio
* *** ***
** *** ***
Table 7 Long-Short portfolio Returns and Real Estate Exposure Panel A and B report calendar-time portfolio regressions based on the Fama and French three-factor model (1993) augmented with the momentum factor (Carhart, 1997). Models are based on monthly returns. b(p), s(p), h(p), and u(p) are respectively the market, SMB, HML and UMD factor coefficients. All Long-short portfolios are equally-weighted portfolios “long” on thrifts and “short” on sizematched banks. In Panel A, Shift RE (CRE)-based portfolios are portfolios of thrifts and size-matched banks in the upper (High Exposure) and lower (Low Exposure) quartiles of the distribution of “Shift RE” (“Shift CRE”). The investment period starts on July 1st 2007 and ends on Dec. 31st, 2009. In Panel B, RE (CRE) Loans-based portfolios are portfolios of thrifts and size-matched banks in the upper (High Exposure) and lower (Low Exposure) quartiles of the distribution of the variable RE (CRE) Loans for a given quarter within the crisis period. For these portfolios, the event period starts 12-months before the selected high (low) exposure quarter and the stock is kept in the portfolio for the following 12 months. The regression intercept (alpha) is the OLS estimate of the average abnormal return with heteroscedasticity consistent standard errors. *, ** and *** denote statistical significance at the 0.10, 0.05 and 0.01 levels, respectively. Panel A. Calendar time regressions. Long-short portfolios of banks and thrifts in the upper (High Exposure) and lower (Low Exposure) quartiles of the distribution of Shift RE and Shift CRE Shift RE- based portfolios Shift CRE-based portfolios
Intercept (alpha) b(p) s(p) h(p) u(p)
(1) High Exposure Coeff. HC t-ratio
Coeff.
0.0117 -0.1396 -0.1897 -0.5369 0.0436
0.0013 -0.0907 -0.2061 -0.3664 0.0575
2.43** -1.64* -1.02 -2.86*** 0.69
(2) Low Exposure HC t-ratio 0.36 -1.61* 1.37* -2.13** 1.18
58.90% 59.47% R2 2 52.58% 53.23% Adj. R 9.92*** 9.54*** F Panel B. Calendar time regressions. Long-short portfolios of banks and thrifts Exposure) quartiles of the distribution of RE Loans and CRE Loans RE Loans-based portfolios
(1) High Exposure Coeff. HC t-ratio
(2) Low Exposure Coeff. HC t-ratio
0.0153 -0.3029 -0.2309 -0.7642 0.1525
0.0114 -0.2844 -0.2618 -0.8652 0.2034
2.35** -3.27*** -0.87 3.20*** 1.68*
1.48 -2.30** -0.86 2.43** 1.96*
65.88% 63.80% 15.48*** 14.22*** 0.0153 0.0114 in the upper (High Exposure) and lower (Low CRE Loans-based portfolios
Intercept (alpha) b(p) s(p) h(p) u(p)
(1) High Exposure Coeff. HC t-ratio 0.0056 2.29** -0.0068 -0.12 -0.1939 -1.91** -0.1332 -1.35* 0.0199 0.59
(2) Low Exposure Coeff. HC t-ratio -0.0026 -1.52* 0.019 -0.52 -0.0025 -0.02 -0.2232 -2.92*** -0.0286 1.13
(1) High Exposure Coeff. HC t-ratio 0.0136 2.73*** -0.0897 -1.03 -0.6148 -1.80* -0.6437 -3.00*** 0.0570 0.63
(2) Low Exposure Coeff. HC t-ratio 00.0038 -0.94 -0.2603 -2.99*** -0.3269 -1.58* -0.7257 -3.62*** -0.0154 0.30
R2 Adj. R2 F
16.32% 9.20% 2.29*
31.18% 25.32% 5.32***
43.68% 38.89% 9.11***
64.92% 61.93% 21.74***
42
1.12
1.08
1.04
1.00
Pre-Crisis
Crisis
Post-Crisis
0.96 2000Q4
2002Q4
2004Q4
2006Q4
Franchise Value (Banks)
2008Q4
2010Q4
Franchise Value (Thrifts)
Fig. I Mean Franchise Values (FV) for Banks and Thrifts during 2000-2011. This graph illustrates quarterly mean franchise values for banks and thrifts from 2000Q1 to 2011Q4 for the full sample. Franchise value is calculated as (Market Value of Equity+Book Value of Liabilities)/(Book Value of Assets-Goodwill) on a quarterly basis. Precrisis period is 2000Q1 to 2007Q2, crisis period is 2007Q3 to 2009Q4, post-crisis period is 2010Q1 to 2011Q4.
43
