Shooting an Elephant :: essays research papers

A police officer in the British Raj, the supposedly 'unbreakable'; ruling force, was afraid. With his gun aimed at a elephant's head, he was faced with the decision to pull the trigger. That officer was George Orwell, and he writes about his experience in his short story, 'Shooting an Elephant';. To save face, he shrugged it off as his desire to 'avoid looking the fool'; (George Orwell, 283). In truth, the atmosphere of fear and pressure overwhelmed him. His inner struggle over the guilt of being involved in the subjugation of a people added to this strain, and he made a decision he would later regret enough to write this story. Early on in his essay, Orwell describes how the abuses and treatment he witnessed oppressed him '… with an intolerable sense of guilt,'; (Orwell,277). This is not some minor pang, or nagging worry. The shame pressed down on his shoulders with an unbearable weight. He also describes the injustices in detail, using vivid pictures like 'The wretched prisoners huddling in the stinking cages…'; (Orwell,277). This does not come from someone who condones such behavior. It stems from a troubled, remorseful soul. The mob, thousands by his description, also pressured him. 'I could feel their two-thousand wills pressing me forward, irresistibly,'; he emphasizes (Orwell, 280). It is hard to resist the peer pressure of one or two people, much less a crowd of thousands. He admits, '…in reality I was only an absurd puppet pushed to and fro by the faces behind.'; Thus, the desire and will of the crowd urge him on, ominously. The people despised him. He speaks of being 'hated by large numbers of people'; and the 'sneering yellow faces of young men that met me everywhere..." (Orwell, 276). As one man, how could he dare to go against them? Two thousand could easily overtake one. They would not have aided him, should anything go wrong, and eagerly anticipated that eventuality. He describes his fear that they would watch him be '…pursued, caught, trampled on, and reduced to a grinning corpse…'; should the elephant charge (Orwell, 281).

Role of Computer in Daily Life

Financial Crises and Bank Liquidity Creation Allen N. Berger †  and Christa H. S. Bouwman †¡ October 2008 Financial crises and bank liquidity creation are often connected. We examine this connection from two perspectives. First, we examine the aggregate liquidity creation of banks before, during, and after five major financial crises in the U. S. from 1984:Q1 to 2008:Q1. We uncover numerous interesting patterns, such as a significant build-up or drop-off of â€Å"abnormal† liquidity creation before each crisis, where â€Å"abnormal† is defined relative to a time trend and seasonal factors.Banking and market-related crises differ in that banking crises were preceded by abnormal positive liquidity creation, while market-related crises were generally preceded by abnormal negative liquidity creation. Bank liquidity creation has both decreased and increased during crises, likely both exacerbating and ameliorating the effects of crises. Off-balance sheet guarantees such as loan commitments moved more than on-balance sheet assets such as mortgages and business lending during banking crises.Second, we examine the effect of pre-crisis bank capital ratios on the competitive positions and profitability of individual banks during and after each crisis. The evidence suggests that high capital served large banks well around banking crises – they improved their liquidity creation market share and profitability during these crises and were able to hold on to their improved performance afterwards. In addition, high-capital listed banks enjoyed significantly higher abnormal stock returns than low-capital listed banks during banking crises.These benefits did not hold or held to a lesser degree around marketrelated crises and in normal times. In contrast, high capital ratios appear to have helped small banks improve their liquidity creation market share during banking crises, market-related crises, and normal times alike, and the gains in market shar e were sustained afterwards. Their profitability improved during two crises and subsequent to virtually every crisis. Similar results were observed during normal times for small banks. †  University of South Carolina, Wharton Financial Institutions Center, and CentER – Tilburg University.Contact details: Moore School of Business, University of South Carolina, 1705 College Street, Columbia, SC 29208. Tel: 803-576-8440. Fax: 803-777-6876. E-mail: [email  protected] sc. edu. †¡ Case Western Reserve University, and Wharton Financial Institutions Center. Contact details: Weatherhead School of Management, Case Western Reserve University, 10900 Euclid Avenue, 362 PBL, Cleveland, OH 44106. Tel. : 216-368-3688. Fax: 216-368-6249. E-mail: christa. [email  protected] edu. Keywords: Financial Crises, Liquidity Creation, and Banking. JEL Classification: G28, and G21.The authors thank Asani Sarkar, Bob DeYoung, Peter Ritchken, Greg Udell, and participants at presentations at the Summer Research Conference 2008 in Finance at the ISB in Hyderabad, the International Monetary Fund, the University of Kansas’ Southwind Finance Conference, and Erasmus University for useful comments. Financial Crises and Bank Liquidity Creation 1. Introduction Over the past quarter century, the U. S. has experienced a number of financial crises. At the heart of these crises are often issues surrounding liquidity provision by the banking sector and financial markets (e. . , Acharya, Shin, and Yorulmazer 2007). For example, in the current subprime lending crisis, liquidity seems to have dried up as banks seem less willing to lend to individuals, firms, other banks, and capital market participants, and loan securitization appears to be significantly depressed. This behavior of banks is summarized by the Economist: â€Å"Although bankers are always stingier in a downturn, [†¦] lots of banks said they had also cut back lending because of a slide in their current or expe cted capital and liquidity. 1 The practical importance of liquidity during crises is buttressed by financial intermediation theory, which indicates that the creation of liquidity is an important reason why banks exist. 2 Early contributions argue that banks create liquidity by financing relatively illiquid assets such as business loans with relatively liquid liabilities such as transactions deposits (e. g. , Bryant 1980, Diamond and Dybvig 1983). More recent contributions suggest that banks also create liquidity off the balance sheet through loan commitments and similar claims to liquid funds (e. g. Holmstrom and Tirole 1998, Kashyap, Rajan, and Stein 2002). 3 The creation of liquidity makes banks fragile and susceptible to runs (e. g. , Diamond and Dybvig 1983, Chari and Jagannathan 1988), and such runs can lead to crises via contagion effects. Bank liquidity creation can also have real effects, in particular if a financial crisis ruptures the creation of liquidity (e. g. , Dellâ⠂¬â„¢Ariccia, Detragiache, and Rajan 2008). 4 Exploring the relationship between financial crises and bank liquidity creation can thus yield potentially interesting economic insights and may have important policy implications.The goals of this paper are twofold. The first is to examine the aggregate liquidity creation of 1 â€Å"The credit crisis: Financial engine failure† – The Economist, February 7, 2008. According to the theory, another central role of banks in the economy is to transform credit risk (e. g. , Diamond 1984, Ramakrishnan and Thakor 1984, Boyd and Prescott 1986). Recently, Coval and Thakor (2005) theorize that banks may also arise in response to the behavior of irrational agents in financial markets. 3James (1981) and Boot, Thakor, and Udell (1991) endogenize the loan commitment contract due to informational frictions. The loan commitment contract is subsequently used in Holmstrom and Tirole (1998) and Kashyap, Rajan, and Stein (2002) to show how banks can provide liquidity to borrowers. 4 Acharya and Pedersen (2005) show that liquidity risk also affects the expected returns on stocks. 2 1 banks around five financial crises in the U. S. over the past quarter century. 5 The crises include two banking crises (the credit crunch of the early 1990s and the subprime lending crisis of 2007 – ? and three crises that can be viewed as primarily market-related (the 1987 stock market crash, the Russian debt crisis plus the Long-Term Capital Management meltdown in 1998, and the bursting of the dot. com bubble plus the September 11 terrorist attack of the early 2000s). This examination is intended to shed light on whether there are any connections between financial crises and aggregate liquidity creation, and whether these vary based on the nature of the crisis (i. e. , banking versus market-related crisis). A good nderstanding of the behavior of bank liquidity creation around financial crises is also important to shed light on whether banks create â€Å"too little† or â€Å"too much† liquidity, and whether bank behavior exacerbates or ameliorates the effects of crises. We document the empirical regularities related to these issues, so as to raise additional interesting questions for further empirical and theoretical examinations. The second goal is to study the effect of pre-crisis equity capital ratios on the competitive positions and profitability of individual banks around each crisis.Since bank capital affects liquidity creation (e. g. , Diamond and Rajan 2000, 2001, Berger and Bouwman forthcoming), it is likely that banks with different capital ratios behave differently during crises in terms of their liquidity creation responses. Specifically, we ask: are high-capital banks able to gain market share in terms of liquidity creation at the expense of low-capital banks during a crisis, and does such enhanced market share translate into higher profitability? If so, are the high-capital banks able t o sustain their improved competitive positions after the financial crisis is over?The recent acquisitions of Countrywide, Bear Stearns, and Washington Mutual provide interesting case studies in this regard. All three firms ran low on capital and had to be bailed out by banks with stronger capital positions. Bank of America (Countrywide’s acquirer) and J. P. Morgan Chase (acquirer of Bear-Stearns and Washington Mutual’s banking operations) had capital ratios high enough to enable them to buy their rivals at a small fraction of what they were worth a year before, thereby gaining a potential competitive advantage. 6 The recent experience of IndyMac Bank provides 5Studies on the behavior of banks around financial crises have typically focused on commercial and real estate lending (e. g. , Berger and Udell 1994, Hancock, Laing, and Wilcox 1995, Dell’Ariccia, Igan, and Laeven 2008). We focus on the more comprehensive notion of bank liquidity creation. 6 On Sunday, Mar ch 16, 2008, J. P. Morgan Chase agreed to pay $2 a share to buy all of Bear Stearns, less than onetenth of the firm’s share price on Friday and a small fraction of the $170 share price a year before. On March 24, 2008, it increased its bid to $10, and completed the transaction on May 30, 2008.On January 11, Bank of America announced it would pay $4 billion for Countrywide, after Countrywide’s market capitalization had plummeted 85% during the preceding 12 months. The transaction was completed on July 1, 2008. After a $16. 4 billion ten-day bank 2 another interesting example. The FDIC seized IndyMac Bank after it suffered substantive losses and depositors had started to run on the bank. The FDIC intends to sell the bank, preferably as a single entity but if that does not work, the bank will be sold off in pieces.Given the way the regulatory approval process for bank acquisitions works, it is likely that the acquirer(s) will have a strong capital base. 7 A financial cris is is a natural event to examine how capital affects the competitive positions of banks. During â€Å"normal† times, capital has many effects on the bank, some of which counteract each other, making it difficult to learn much. For example, capital helps the bank cope more effectively with risk,8 but it also reduces the value of the deposit insurance put option (Merton 1977). During a crisis, risks become elevated and the risk-absorption capacity of capital becomes paramount.Banks with high capital, which are better buffered against the shocks of the crisis, may thus gain a potential advantage. To examine the behavior of bank liquidity creation around financial crises, we calculate the amount of liquidity created by the banking sector using Berger and Bouwman’s (forthcoming) preferred liquidity creation measure. This measure takes into account the fact that banks create liquidity both on and off the balance sheet and is constructed using a three-step procedure. In the f irst step, all bank assets, liabilities, equity, and off-balance sheet activities are classified as liquid, semi-liquid, or illiquid.This is done based on the ease, cost, and time for customers to obtain liquid funds from the bank, and the ease, cost, and time for banks to dispose of their obligations in order to meet these liquidity demands. This classification process uses information on both product category and maturity for all activities other than loans; due to data limitations, loans are classified based solely on category (â€Å"cat†). Thus, residential mortgages are classified as more liquid than business loans regardless of maturity because it is generally easier to securitize and sell such mortgages than business loans.In the second step, weights are assigned to these activities. The weights are consistent with the theory in that maximum liquidity is created when illiquid assets (e. g. , business loans) are transformed into liquid liabilities (e. g. , transactions deposits) and maximum liquidity is destroyed when liquid assets (e. g. , treasuries) are transformed into illiquid liabilities â€Å"walk†, Washington Mutual was placed into the receivership of the FDIC on September 25, 2008. J. P. Morgan Chase purchased the banking business for $1. 9 billion and re-opened the bank the next day.On September 26, 2008, the holding company and its remaining subsidiary filed for bankruptcy. Washington Mutual, the sixth-largest bank in the U. S. before its collapse, is the largest bank failure in the U. S. financial history. 7 After peaking at $50. 11 on May 8, 2006, IndyMac’s shares lost 87% of their value in 2007 and another 95% in 2008. Its share price closed at $0. 28 on July 11, 2008, the day before it was seized by the FDIC. 8 There are numerous papers that argue that capital enhances the risk-absorption capacity of banks (e. g. , Bhattacharya and Thakor 1993, Repullo 2004, Von Thadden 2004). (e. g. , subordinated debt) or equity. In the third step, a â€Å"cat fat† liquidity creation measure is constructed, where â€Å"fat† refers to the inclusion of off-balance sheet activities. Although Berger and Bouwman construct four different liquidity creation measures, they indicate that â€Å"cat fat† is the preferred measure. They argue that to assess the amount of liquidity creation, the ability to securitize or sell a particular loan category is more important than the maturity of those loans, and the inclusion of off-balance sheet activities is critical. We apply the â€Å"cat fat† liquidity creation measure to quarterly data on virtually all U. S. commercial and credit card banks from 1984:Q1 to 2008:Q1. Our measurement of aggregate liquidity creation by banks allows us to examine the behavior of liquidity created prior to, during, and after each crisis. The popular press has provided anecdotal accounts of liquidity drying up during some financial crises as well as excessive liquidity p rovision at other times that led to credit expansion bubbles (e. g. , the subprime lending crisis).We attempt to give empirical content to these notions of â€Å"too little† and â€Å"too much† liquidity created by banks. Liquidity creation has quadrupled in real terms over the sample period and appears to have seasonal components (as documented below). Since no theories exist that explain the intertemporal behavior of liquidity creation, we take an essentially empirical approach to the problem and focus on how far liquidity creation lies above or below a time trend and seasonal factors. 10 That is, we focus on â€Å"abnormal† liquidity creation.The use of this measure rests on the supposition that some â€Å"normal† amount of liquidity creation exists, acknowledging that at any point in time, liquidity creation may be â€Å"too much† or â€Å"too little† in dollar terms. Our main results regarding the behavior of liquidity creation around f inancial crises are as follows. First, prior to financial crises, there seems to have been a significant build-up or drop-off of â€Å"abnormal† liquidity creation. Second, banking and market-related crises differ in two respects.The banking crises (the credit crunch of 1990-1992 and the current subprime lending crisis) were preceded by abnormal positive liquidity creation by banks, whereas the market-related crises were generally preceded by abnormal negative liquidity creation. In addition, the banking crises themselves seemed to change the trajectory of aggregate liquidity creation, while the market-related crises did not appear to do so. Third, 9 Their alternative measures include â€Å"cat nonfat,† â€Å"mat fat,† and â€Å"mat nonfat. † The â€Å"nonfat† measures exclude offbalance sheet activities, and the â€Å"mat† measures classify loans by maturity rather than by product category. 0 As alternative approaches, we use the dollar amo unt of liquidity creation per capita and liquidity creation divided by GDP and obtain similar results (see Section 4. 2). 4 liquidity creation has both decreased during crises (e. g. , the 1990-1992 credit crunch) and increased during crises (e. g. , the 1998 Russian debt crisis / LTCM bailout). Thus, liquidity creation likely both exacerbated and ameliorated the effects of crises. Fourth, off-balance sheet illiquid guarantees (primarily loan commitments) moved more than semi-liquid assets (primarily mortgages) and illiquid assets (primarily business loans) during banking crises.Fifth, the current subprime lending crisis was preceded by an unusually high positive abnormal amount of aggregate liquidity creation, possibly caused by lax lending standards that led banks to extend increasing amounts of credit and off-balance sheet guarantees. This suggests a possible dark side of bank liquidity creation. While financial fragility may be needed to induce banks to create liquidity (e. g. , Diamond and Rajan 2000, 2001), our analysis raises the intriguing possibility that the causality may also be reversed in the sense that too much liquidity creation may lead to financial fragility.We then turn to the second goal of the paper – examining whether banks’ pre-crisis capital ratios affect their competitive positions and profitability around financial crises. To examine the effect on a bank’s competitive position, we regress the change in its market share of liquidity creation – measured as the average market share of aggregate liquidity creation during the crisis (or over the eight quarters after the crisis) minus the average market share over the eight quarters before the crisis, expressed as a proportion of the bank’s average pre-crisis market share – on its average pre-crisis capital ratio and a set of control variables. 1 Since the analyses in the first half of the paper reveal a great deal of heterogeneity in crises, we run these regressions on a per-crisis basis, rather than pooling the data across crises. The control variables include bank size, bank risk, bank holding company membership, local market competition,12 and proxies for the economic circumstances in the local markets in which the bank operates. Moreover, we examine large and small banks as two separate groups since the results in Berger and Bouwman (forthcoming) indicate that the effect of capital on liquidity creation differs across large and small banks. 13 11Defining market share this way is a departure from previous research (e. g. , Laeven and Levine 2007), in which market share relates to the bank’s weighted-average local market share of total deposits. 12 While our focus is on the change in banks’ competitive positions measured in terms of their aggregate liquidity creation market shares, we control for â€Å"local market competition† measured as the bank-level Herfindahl index based on local market deposit mar ket shares. 13 Berger and Bouwman use three size categories: large, medium, and small banks. We combine the large and medium bank categories into one â€Å"large bank† category. 5One potential concern is that differences in bank capital ratios may simply reflect differences in bank risk. Banks that hold higher capital ratios because their investment portfolios are riskier may not improve their competitive positions around financial crises. Our empirical design takes this into account. The inclusion of bank risk as a control variable is critical and ensures that the measured effect of capital on a bank’s market share is net of the effect of risk. We find evidence that high-capital large banks improved their market share of liquidity creation during the two banking crises, but not during the market-related crises.After the credit crunch of the early 1990s, high-capital large banks held on to their improved competitive positions. Since the current subprime lending crisis was not over at the end of the sample period, we cannot yet tell whether highcapital large banks will also hold on to their improved competitive positions after this crisis. In contrast to the large banks, high-capital small banks seemed to enhance their competitive positions during all crises and held on to their improved competitive positions after the crises as well.Next, we focus on the effect of pre-crisis bank capital on the profitability of the bank around each crisis. We run regressions that are similar to the ones described above with the change in return on equity (ROE) as the dependent variable. We find that high-capital large banks improved their ROE in those cases in which they enhanced their liquidity creation market share – the two banking crises – and were able to hold on to their improved profitability after the credit crunch. profitability after the market-related crises. They also increased theirIn contrast, for high-capital small banks, profitabilit y improved during two crises, and subsequent to virtually every crisis. As an additional analysis, we examine whether the improved competitive positions and profitability of high-capital banks translated into better stock return performance. To perform this analysis, we focus on listed banks and bank holding companies (BHCs). If multiple banks are part of the same listed BHC, their financial statements are added together to create pro-forma financial statements of the BHC.The results confirm the earlier change in performance findings of large banks: listed banks with high capital ratios enjoyed significantly larger abnormal returns than banks with low capital ratios during banking crises, but not during market-related crises. Our results are based on a five-factor asset pricing model that includes the three Fama-French (1993) factors, momentum, and a proxy for the slope of the yield curve. 6 We also check whether high capital provided similar advantages outside crisis periods, i. e. , during â€Å"normal† times.We find that large banks with high capital ratios did not enjoy either market share or profitability gains over the other large banks, whereas for small banks, results are similar to the smallbank findings discussed above. Moreover, outside banking crises, high capital was not associated with high stock returns. Combined, the results suggest that high capital ratios serve large banks well, particularly around banking crises. In contrast, high capital ratios appear to help small banks around banking crises, marketrelated crises, and normal times alike. The remainder of this paper is organized as follows.Section 2 discusses the related literature. Section 3 explains the liquidity creation measures and our sample based on data of U. S. banks from 1984:Q1 to 2008:Q1. Section 4 describes the behavior of aggregate bank liquidity creation around five financial crises and draws some general conclusions. Section 5 discusses the tests of the effects of pre crisis capital ratios on banks’ competitive positions and profitability around financial crises and â€Å"normal† times. This section also examines the stock returns of high- and low-capital listed banking organizations during each crisis and during normal† times. Section 6 concludes. 2. Related literature This paper is related to two literatures. The first is the literature on financial crises. 14 One strand in this literature has focused on financial crises and fragility. Some papers have analyzed contagion. Contributions in this area suggest that a small liquidity shock in one area may have a contagious effect throughout the economy (e. g. , Allen and Gale 1998, 2000). Other papers have focused on the determinants of financial crises and the policy implications (e. g. Bordo, Eichengreen, Klingebiel, and Martinez-Peria 2001, Demirguc-Kunt, Detragiache, and Gupta 2006, Lorenzoni 2008, Claessens, Klingebiel, and Laeven forthcoming). A second strand examines the e ffect of financial crises on the real sector (e. g. , Friedman and Schwarz 1963, Bernanke 1983, Bernanke and Gertler 1989, Dell’Ariccia, Detragiache, and Rajan 2008, Shin forthcoming). These papers find that financial crises increase the cost of financing and reduce credit, which adversely affects corporate investment and may lead to reduced 14Allen and Gale (2007) provide a detailed overview of the causes and consequences of financial crises. 7 growth and recessions. That is, financial crises have independent real effects (see Dell’Ariccia, Detragiache, and Rajan 2008). In contrast to these papers, we examine how the amount of liquidity created by the banking sector behaved around financial crises in the U. S. , and explore systematic patterns in the data. The second literature to which this paper is related focuses on the strategic use of leverage in product-market competition for non-financial firms (e. g. , Brander and Lewis 1986, Campello 2006, Lyandres 2006).This literature suggests that financial leverage can affect competitive dynamics. While this literature has not focused on banks, we analyze the effects of crises on the competitive positioning and profitability of banks based on their pre-crisis capital ratios. Our hypothesis is that in the case of banks, the competitive implications of capital are likely to be most pronounced during a crisis when a bank’s capitalization has a major influence on its ability to survive the crisis, particularly in light of regulatory discretion in closing banks or otherwise resolving problem institutions.Liquidity creation may be a channel through which this competitive advantage is gained or lost. 15 3. Description of the liquidity creation measure and sample We calculate the dollar amount of liquidity created by the banking sector using Berger and Bouwman’s (forthcoming) preferred â€Å"cat fat† liquidity creation measure. In this section, we explain briefly what this acronym stand s for and how we construct this measure. 16 We then describe our sample. All financial values are expressed in real 2007:Q4 dollars using the implicit GDP price deflator. 3. 1. Liquidity creation measureTo construct a measure of liquidity creation, we follow Berger and Bouwman’s three-step procedure (see Table 1). Below, we briefly discuss these three steps. In Step 1, we classify all bank activities (assets, liabilities, equity, and off-balance sheet activities) as liquid, semi-liquid, or illiquid. For assets, we do this based on the ease, cost, and time for banks to dispose of their obligations in order to meet these liquidity demands. For liabilities and equity, we do this 15 Allen and Gale (2004) analyze how competition affects financial stability. We reverse the causality and examine the effect of financial crises on competition. 6 For a more detailed discussion, see Berger and Bouwman (forthcoming). 8 based on the ease, cost, and time for customers to obtain liquid fund s from the bank. We follow a similar approach for off-balance sheet activities, classifying them based on functionally similar on-balance sheet activities. For all activities other than loans, this classification process uses information on both product category and maturity. Due to data restrictions, we classify loans entirely by category (â€Å"cat†). 17 In Step 2, we assign weights to all the bank activities classified in Step 1.The weights are consistent with liquidity creation theory, which argues that banks create liquidity on the balance sheet when they transform illiquid assets into liquid liabilities. We therefore apply positive weights to illiquid assets and liquid liabilities. Following similar logic, we apply negative weights to liquid assets and illiquid liabilities and equity, since banks destroy liquidity when they use illiquid liabilities to finance liquid assets. We use weights of ? and -? , because only half of the total amount of liquidity created is attrib utable to the source or use of funds alone.For example, when $1 of liquid liabilities is used to finance $1 in illiquid assets, liquidity creation equals ? * $1 + ? * $1 = $1. In this case, maximum liquidity is created. However, when $1 of liquid liabilities is used to finance $1 in liquid assets, liquidity creation equals ? * $1 + -? * $1 = $0. In this case, no liquidity is created as the bank holds items of approximately the same liquidity as those it gives to the nonbank public. Maximum liquidity is destroyed when $1 of illiquid liabilities or equity is used to finance $1 of liquid assets. In this case, liquidity creation equals -? $1 + -? * $1 = -$1. An intermediate weight of 0 is applied to semi-liquid assets and liabilities. Weights for off-balance sheet activities are assigned using the same principles. In Step 3, we combine the activities as classified in Step 1 and as weighted in Step 2 to construct Berger and Bouwman’s preferred â€Å"cat fat† liquidity creat ion measure. This measure classifies loans by category (â€Å"cat†), while all activities other than loans are classified using information on product category and maturity, and includes off-balance sheet activities (â€Å"fat†).Berger and Bouwman construct four liquidity creation measures by alternatively classifying loans by category or maturity, and by alternatively including or excluding off-balance sheet activities. However, they argue that â€Å"cat fat† is the preferred measure since for liquidity creation, banks’ ability to securitize or sell loans is more important than loan maturity, and banks do create liquidity both on the balance sheet and off the balance sheet. 17 Alternatively, we could classify loans by maturity (â€Å"mat†).However, Berger and Bouwman argue that it is preferable to classify them by category since for loans, the ability to securitize or sell is more important than their maturity. 9 To obtain the dollar amount of liq uidity creation at a particular bank, we multiply the weights of ? , -? , or 0, respectively, times the dollar amounts of the corresponding bank activities and add the weighted dollar amounts. 3. 2. Sample description We include virtually all commercial and credit card banks in the U. S. in our study. 18 For each bank, we obtain quarterly Call Report data from 1984:Q1 to 2008:Q1.We keep a bank if it: 1) has commercial real estate or commercial and industrial loans outstanding; 2) has deposits; 3) has an equity capital ratio of at least 1%; 4) has gross total assets or GTA (total assets plus allowance for loan and lease losses and the allocated transfer risk reserve) exceeding $25 million. We end up with data on 18,134 distinct banks, yielding 907,159 bank-quarter observations over our sample period. For each bank, we calculate the dollar amount of liquidity creation using the process described in Section 3. 1.The amount of liquidity creation and all other financial values are put in to real 2007:Q4 dollars using the implicit GDP price deflator. When we explore aggregate bank liquidity creation around financial crises, we focus on the real dollar amount of liquidity creation by the banking sector. To obtain this, we aggregate the liquidity created by all banks in each quarter and end up with a sample that contains 97 inflation-adjusted, quarterly liquidity creation amounts. In contrast, when we examine how capital affects the competitive positions of banks, we focus on the amount of liquidity created by individual banks around each crisis.Given documented differences between large and small banks in terms of portfolio composition (e. g. , Kashyap, Rajan, and Stein 2002, Berger, Miller, Petersen, Rajan, and Stein 2005) and the effect of capital on liquidity creation (Berger and Bouwman forthcoming), we split the sample into large banks (between 330 and 477 observations, depending on the crisis) and small banks (between 5556 and 6343 observations, depending on the crisis), and run all change in market share and profitability regressions separately for these two sets of banks.Large banks have gross total assets (GTA) exceeding $1 billion at the end of the quarter before a crisis 18 Berger and Bouwman (forthcoming) include only commercial banks. We also include credit card banks to avoid an artificial $0. 19 trillion drop in bank liquidity creation in the fourth quarter of 2006 when Citibank N. A. moved its credit-card lines to Citibank South Dakota N. A. , a credit card bank. 10 and small banks have GTA up to $1 billion at the end of that quarter. 19,20 4.The behavior of aggregate bank liquidity creation around financial crises This section focuses on the first goal of the paper – examining the aggregate liquidity creation of banks across five financial crises in the U. S. over the past quarter century. The crises include the 1987 stock market crash, the credit crunch of the early 1990s, the Russian debt crisis plus Long-Term Capital M anagement (LTCM) bailout of 1998, the bursting of the dot. com bubble and the Sept. 11 terrorist attacks of the early 2000s, and the current subprime lending crisis. We first provide summary statistics and explain our empirical approach.We then discuss alternative measures of abnormal liquidity creation. Next, we describe the behavior of bank liquidity creation before, during, and after each crisis. Finally, we draw some general conclusions from these results. 4. 1. Summary statistics and empirical approach Figure 1 Panel A shows the dollar amount of liquidity created by the banking sector, calculated using the â€Å"cat fat† liquidity creation measure over our sample period. As shown, liquidity creation has increased substantially over time: it has more than quadrupled from $1. 369 trillion in 1984:Q1 to $5. 06 trillion in 2008:Q1 (in real 2007:Q4 dollars). We want to examine whether liquidity creation by the banking sector is â€Å"high,† â€Å"low,† or at a à ¢â‚¬Å"normal† level around financial crises. Since no theories exist that explain the intertemporal behavior of liquidity creation or generate numerical estimates of â€Å"normal† liquidity creation, we need a reasonable empirical approach. At first blush, it may seem that we could simply calculate the average amount of bank liquidity creation over the entire sample period and view amounts above this sample average as â€Å"high† and amounts below the average as â€Å"low. However, Figure 1 Panel A clearly shows that this approach would cause us to classify the entire second half of the sample period (1996:Q1 – 2008:Q1) as â€Å"high† and the entire first half of the sample period (1984:Q1 – 1995:Q4) as â€Å"low. † We therefore do not 19 As noted before, we combine Berger and Bouwman’s large and medium bank categories into one â€Å"large bank† category. Recall that all financial values are expressed in real 2007:Q4 dol lars. 20 GTA equals total assets plus the allowance for loan and lease losses and the allocated transfer risk reserve.Total assets on Call Reports deduct these two reserves, which are held to cover potential credit losses. We add these reserves back to measure the full value of the loans financed and the liquidity created by the bank on the asset side. 11 use this approach. The approach we take is aimed at calculating the â€Å"abnormal† amount of liquidity created by the banking sector based on a time trend. It focuses on whether liquidity creation lies above or below this time trend, and also deseasonalizes the data to ensure that we do not base our conclusions on mere seasonal effects.We detrend and deseasonalize the data by regressing the dollar amount of liquidity creation on a time index and three quarterly dummies. The residuals from this regression measure the â€Å"abnormal† dollar amount of liquidity creation in a particular quarter. That is, they measure how far (deseasonalized) liquidity creation lies above or below the trend line. If abnormal liquidity creation is greater than (smaller than) $0, the dollar amount of liquidity created by the banking sector lies above (below) the time trend.If abnormal liquidity creation is high (low) relative to the time trend and seasonal factors, we will interpret this as liquidity creation being â€Å"too high† (â€Å"too low†). Figure 1 Panel B shows abnormal liquidity creation over time. The amount of liquidity created by the banking sector was high (yet declining) in the mid-1980s, low in the mid-1990s, and high (and mostly rising) in the most recent years. 4. 2. Alternative measures of abnormal liquidity creation We considered several alternative approaches to measuring abnormal liquidity creation. One possibility is to scale the dollar amount of liquidity creation by total population.The idea behind this approach is that a â€Å"normal† amount of liquidity creation may exi st in per capita terms. The average amount of liquidity creation per capita over our sample period could potentially serve as the â€Å"normal† amount and deviations from this average would be viewed as abnormal. To calculate per capita liquidity creation we obtain annual U. S. population estimates from the U. S. Census Bureau. Figure 2 Panel A shows per capita liquidity creation over time. The picture reveals that per capita liquidity creation more than tripled from $5. 8K in 1984:Q1 to $18. 8K in 2008:Q1.Interestingly, the picture looks very similar to the one shown in Panel A, perhaps because the annual U. S. population growth rate is low. For reasons similar to those in our earlier analysis, we calculate abnormal per capita liquidity creation by detrending and deseasonalizing the data like we did in the previous section. Figure 2 Panel B shows abnormal per capita liquidity creation over time. 12 Another possibility is to scale the dollar amount of liquidity creation by GD P. Since liquidity creation by banks may causally affect GDP, this approach seems less appropriate.Nonetheless, we show the results for completeness. Figure 2 Panel C shows the dollar amount of liquidity creation divided by GDP. The picture reveals that bank liquidity creation has increased from 19. 9% of GDP in 1984:Q1 to 40. 4% of GDP in 2008:Q1. While liquidity creation more than quadrupled over the sample period, GDP doubled. Importantly, the picture looks similar to the one shown in Panel A. Again, for reasons similar to those in our earlier analysis, we detrend and deseasonalize the data to obtain abnormal liquidity creation divided by GDP.Figure 2 Panel D shows abnormal liquidity creation divided by GDP over time. Since these alternative approaches yield results that are similar to those shown in Section 4. 1, we focus our discussions on the abnormal amount of liquidity creation (rather than the abnormal amount of per capita liquidity creation or the abnormal amount of liquid ity creation divided by GDP) around financial crises. 4. 3. Abnormal bank liquidity creation before, during, and after five financial crises We now examine how abnormal bank liquidity creation behaved efore, during, and after five financial crises. In all cases, the pre-crisis and post-crisis periods are defined to be eight quarters long. 21 The one exception is that we do not examine abnormal bank liquidity creation after the current subprime lending crisis, since this crisis was still ongoing at the end of the sample period. Figure 3 Panels A – E show the graphs of the abnormal amount of liquidity creation for the five crises. This subsection is a fact-finding effort and largely descriptive. In Section 4. , we will combine the evidence gathered here and interpret it to draw some general conclusions. Financial crisis #1: Stock market crash (1987:Q4) On Monday, October 19, 1987, the stock market crashed, with the S&P500 index falling about 20%. During the years before the cra sh, the level of the stock market had increased dramatically, causing some 21 As a result of our choice of two-year pre-crisis and post-crisis periods, the post-Russian debt crisis period overlaps with the bursting of the dot. com bubble, and the pre-dot. com bubble period overlaps with the Russian debt crisis.For these two crises, we redo our analyses using six-quarter pre-crisis and post-crisis periods and obtain results that are qualitatively similar to the ones documented here. 13 concern that the market had become overvalued. 22 A few days before the crash, two events occurred that may have helped precipitate the crash: 1) legislation was enacted to eliminate certain tax benefits associated with financing mergers; and 2) information was released that the trade deficit was above expectations. Both events seemed to have added to the selling pressure and a record trading volume on Oct. 9, in part caused by program trading, overwhelmed many systems. Figure 3 Panel A shows abnormal bank liquidity creation before, during, and after the stock market crash. Although this financial crisis seems to have originated in the stock market rather than the banking system, it is clear from the graph that abnormal liquidity creation by banks was high ($0. 5 trillion above the time trend) two years before the crisis. It had already dropped substantially before the crisis and continued to drop until well after the crisis, but was still above the time trend even a year after the crisis.Financial crisis #2: Credit crunch (1990:Q1 – 1992:Q4) During the first three years of the 1990s, bank commercial and industrial lending declined in real terms, particularly for small banks and for small loans (see Berger, Kashyap, and Scalise 1995, Table 8, for details). The ascribed causes of the credit crunch include a fall in bank capital from the loan loss experiences of the late 1980s (e. g. , Peek and Rosengren 1995), the increases in bank leverage requirements and implementation o f Basel I risk-based capital standards during this time period (e. g. Berger and Udell 1994, Hancock, Laing, and Wilcox 1995, Thakor 1996), an increase in supervisory toughness evidenced in worse examination ratings for a given bank condition (e. g. , Berger, Kyle, and Scalise 2001), and reduced loan demand because of macroeconomic and regional recessions (e. g. , Bernanke and Lown 1991). To some extent, the research supports virtually all of these hypotheses. Figure 3 Panel B shows how abnormal liquidity creation behaved before, during, and after the credit crunch. The graph shows that liquidity creation was above the time trend before the crisis, but declining.After a temporary increase, it dropped markedly during the crisis by roughly $0. 6 trillion, and the decline even extended a bit beyond the crunch period. After having reached a noticeably low level in the post-crunch period, liquidity creation slowly started to bottom out. This evidence suggests that the 22 E. g. , â€Å"R aging bull, stock market’s surge is puzzling investors: When will it end? † on page 1 of the Wall Street Journal, Jan. 19, 1987. 14 banking sector created (slightly) positive abnormal liquidity before the crisis, but created significantly negative abnormal liquidity during and fter the crisis, representing behavior by banks that may have further fueled the crisis. Financial crisis #3: Russian debt crisis / LTCM bailout (1998:Q3 – 1998:Q4) Since its inception in March 1994, hedge fund Long-Term Capital Management (â€Å"LTCM†) followed an arbitrage strategy that was avowedly â€Å"market neutral,† designed to make money regardless of whether prices were rising or falling. When Russia defaulted on its sovereign debt on August 17, 1998, investors fled from other government paper to the safe haven of U. S. treasuries.This flight to liquidity caused an unexpected widening of spreads on supposedly low-risk portfolios. By the end of August 1998, LTCMâ€⠄¢s capital had dropped to $2. 3 billion, less than 50% of its December 1997 value, with assets standing at $126 billion. In the first three weeks of September, LTCM’s capital dropped further to $600 million without shrinking the portfolio. Banks began to doubt its ability to meet margin calls. To prevent a potential systemic meltdown triggered by the collapse of the world’s largest hedge fund, the Federal Reserve Bank of New York organized a $3. billion bail-out by LTCM’s major creditors on September 23, 1998. In 1998:Q4, many large banks had to take substantial write-offs as a result of losses on their investments. Figure 3 Panel C shows abnormal liquidity creation around the Russian debt crisis and LTCM bailout. The pattern shown in the graph is very different from the ones we have seen so far. Liquidity creation was abnormally negative before the crisis, but increasing. Liquidity creation increased further during the crisis, countercyclical behavior by banks that may have alleviated the crisis, and continued to grow after the crisis.This suggests that liquidity creation may have been too low entering the crisis and returned to normal levels a few quarters after the end of the crisis. Financial crisis #4: Bursting of the dot. com bubble and Sept. 11 terrorist attack (2000:Q2 – 2002:Q3) The dot. com bubble was a speculative stock price bubble that was built up during the mid to late 1990s. During this period, many internet-based companies, commonly referred to as â€Å"dot. coms,† were founded. Rapidly increasing stock prices and widely available venture capital created an environment in which 15 any of these companies seemed to focus largely on increasing market share. At the height of the boom, it seemed possible for dot. com’s to go public and raise substantial amounts of money even if they had never earned any profits, and in some cases had not even earned any revenues. On March 10, 2000, the Nasdaq composite ind ex peaked at more than double its value just a year before. After the bursting of the bubble, many dot. com’s ran out of capital and were acquired or filed for bankruptcy (examples of the latter include WorldCom and Pets. com). The U. S. economy started to slow down and business nvestments began falling. The September 11, 2001 terrorist attacks may have exacerbated the stock market downturn by adversely affecting investor sentiment. By 2002:Q3, the Nasdaq index had fallen by 78%, wiping out $5 trillion in market value of mostly technology firms. Figure 3 Panel D shows how abnormal liquidity creation behaved before, during, and after the bursting of the dot. com bubble and the Sept. 11 terrorist attacks. The graph shows that before the crisis period, liquidity creation moved from displaying a negative abnormal value to displaying a positive abnormal value at the time the bubble burst.During the crisis, liquidity creation declined somewhat and hovered around the time trend by t he time the crisis was over. After the crisis, liquidity creation slowly started to pick up again. Financial crisis #5: Subprime lending crisis (2007:Q3 – ? ) The subprime lending crisis has been characterized by turmoil in financial markets as banks have experienced difficulty in selling loans in the syndicated loan market and in securitizing loans. Banks also seem to be reluctant to provide credit: they appear to have cut back their lending to firms and individuals, and have also been reticent to lend to each other.Risk premia have increased as evidenced by a higher premium over treasuries for mortgages and other bank products. Some banks have experienced massive losses in capital. For example, Citicorp had to raise about $40 billion in equity to cover subprime lending and other losses. Massive losses at Countrywide resulted in a takeover by Bank of America. Bear Stearns suffered a fatal loss in confidence and was sold at a fire-sale price to J. P. Morgan Chase with the Fed eral Reserve guaranteeing $29 billion in potential losses. Washington Mutual, the sixth-largest bank, became the biggest bank failure in the U.S. financial history. J. P. Morgan Chase purchased the banking business while the rest of the organization filed for bankruptcy. The Federal Reserve intervened in some 16 unprecedented ways in the market, extending its safety-net privileges to investment banks. In addition to lowering the discount rate sharply, it also began holding mortgage-backed securities and lending directly to investment banks. Subsequently, IndyMac Bank was seized by the FDIC after it suffered substantive losses and depositors had started to run on the bank. This failure is expected to cost the FDIC $4 billion – $8 billion.The FDIC intends to sell the bank. Congress also recently passed legislation to provide Freddie Mac and Fannie Mae with unlimited credit lines and possible equity injections to prop up these troubled organizations, which are considered too big to fail. Figure 3 Panel E shows abnormal liquidity creation before and during the first part of the subprime lending crisis. The graph suggests that liquidity creation displayed a high positive abnormal value that was increasing before the crisis hit, with abnormal liquidity creation around $0. 0 trillion entering the crisis, decreasing substantially after the crisis hit. A striking fact about this crisis compared to the other crises is the relatively high build-up of positive abnormal liquidity creation prior to the crisis. 4. 4. Behavior of some liquidity creation components around the two banking crises It is of particular interest to examine the behavior of some selected components of liquidity creation around the banking crises. As discussed above (Section 4. 3), numerous papers have focused on the credit crunch, examining lending behavior.These studies generally find that mortgage and business lending started to decline significantly during the crisis. Here we contrast the cr edit crunch experience with the current subprime lending crisis, and expand the components of liquidity creation that are examined. Rather than focusing on mortgages and business loans, we examine the two liquidity creation components that include these items – semi-liquid assets (primarily mortgages) and illiquid assets (primarily business loans). In addition, we analyze two other components of liquidity creation.We examine the behavior of liquid assets to address whether a decrease (increase) in semi-liquid assets and / or illiquid assets tended to be accompanied by an increase (decrease) in liquid assets. We also analyze the behavior of illiquid off-balance sheet guarantees (primarily loan commitments) to address whether illiquid assets and illiquid off-balance sheet guarantees move in tandem around banking crises and whether changes in one are more pronounced than the other. Figure 4 Panels A and B show the abnormal amount of four liquidity creation components around 17 h e credit crunch and the subprime lending crisis, respectively. For ease of comparison, the components are not weighted by weights of +? (illiquid assets and illiquid off-balance sheet guarantees), 0 (semiliquid assets), and –? (liquid assets). The abnormal amounts are obtained by detrending and deseasonalizing each liquidity creation component. Figure 4 Panel A shows that abnormal semi-liquid assets decreased slightly during the credit crunch, while abnormal illiquid assets and especially abnormal illiquid guarantees dropped significantly and turned negative.This picture suggests that these components fell increasingly below the trendline. The dramatic drop in abnormal illiquid assets and abnormal illiquid off-balance sheet guarantees (which carry positive weights) helps explain the significant decrease in abnormal liquidity creation during the credit crunch shown in Figure 3 Panel B. Figure 4 Panel B shows that these four components of abnormal liquidity creation were above the trendline before and during the subprime lending crisis.Illiquid assets and especially off-balance sheet guarantees move further and further above the trendline before the crisis, which helps explain the dramatic buildup in abnormal liquidity creation before the subprime lending crisis shown in Figure 3 Panel E. All four components of abnormal liquidity creation continued to increase at the beginning of the crisis. After the first quarter of the crisis, illiquid off-balance sheet guarantees showed a significant decrease, which helps explain the decrease in abnormal liquidity creation in Figure 3 Panel E.On the balance sheet, during the final quarter of the sample period (the third quarter of the crisis), abnormal semi-liquid and illiquid assets declined, while abnormal liquid assets increased. 4. 5. General conclusions from the results What do we learn from the various graphs in the previous analyses that indicate intertemporal patterns of liquidity creation and selected liquidi ty creation components around five financial crises? First, across all the financial crises, there seems to have been a significant build-up or drop-off of abnormal liquidity creation before the crisis.This is consistent with the notion that crises may be preceded by either â€Å"too much† or â€Å"too little† liquidity creation, although at this stage we offer this as tentative food for thought rather than as a conclusion. Second, there seem to be two main differences between banking crises and market-related crises. 18 The banking crises, namely the credit crunch and the subprime lending crisis, were both preceded by positive abnormal liquidity creation by banks, while two out of the three market-related crises were preceded by negative abnormal liquidity creation.In addition, during the two banking crises, the crises themselves seem to have exerted a noticeable influence on the pattern of aggregate liquidity creation by banks. Just prior to the credit crunch, abnorm al liquidity creation was positive and had started to trend upward, but reversed course and plunged quite substantially to become negative during and after the crisis. Just prior to the subprime lending crisis, aggregate liquidity creation was again abnormally positive and trending up, but began to decline during the crisis, although it remains abnormally high by historical standards.The other crises, which are less directly related to banks, did not seem to exhibit such noticeable impact. Third, liquidity creation has both decreased during crises (e. g. , the 1990-1992 credit crunch) and increased during crises (e. g. , the 1998 Russian debt crisis / LTCM bailout). Thus, liquidity creation likely both exacerbated and ameliorated the effects of crises. Fourth, off-balance sheet illiquid guarantees (primarily loan commitments) moved more than semi-liquid assets (primarily mortgages) and illiquid assets (primarily business loans) during banking crises.Fifth, while liquidity creation i s generally thought of as a financial intermediation service with positive economic value at the level of the individual bank and individual borrower (see Diamond and Rajan 2000, 2001), our analysis hints at the existence of a â€Å"dark side† to liquidity creation. Specifically, it may be more than coincidence that the subprime lending crisis was preceded by a very high level of positive abnormal aggregate liquidity creation by banks relative to historical levels.The notion that this may have contributed to the subprime lending crisis is consistent with the findings that banks adopted lax credit standards (see Dell’Ariccia, Igan, and Laeven 2008, Keys, Mukherjee, Seru, and Vig 2008), which in turn could have led to an increase in credit availability and off-balance sheet guarantees. Thus, while Diamond and Rajan (2000, 2001) argue that financial fragility is needed to create liquidity, our analysis offers the intriguing possibility that the causality may be reversed a s well: too much liquidity creation may lead to financial fragility. 9 5. The effect of capital on banks’ competitive positions and profitability around financial crises This section focuses on the second goal of the paper – examining how bank capital affects banks’ competitive positions and profitability around financial crises. We first explain our methodology and provide summary statistics. We then present and discuss the empirical results. In an additional check, we examine whether the stock return performance of high- and low-capital listed banks is consistent with the competitive position and profitability results for large banks.In another check, we generate some â€Å"fake† crises to analyze whether our findings hold during â€Å"normal† times as well. 5. 1. Empirical approach To examine whether banks with high capital ratios improve their competitive positions and profitability during financial crises, and if so, whether they are able to h old on to this improved performance after these crises, we focus on the behavior of individual banks rather than that of the banking sector as a whole.Because our analysis of aggregate liquidity creation by banks shows substantial differences across crises, we do not pool the data from all the crises but instead analyze each crisis separately. Our findings below that the coefficients of interest differ substantially across crises tend to justify this separate treatment of the different crises. We use the following regression specification for each of the five crises: ? PERFi,j = ? + ? 1 * EQRATi,j + B * Zi,j (1) where ?PERFi,j is the change in bank i’s performance around crisis j, EQRATi,j is the bank’s average capital ratio before the crisis, and Zi,j includes a set of control variables averaged over the pre-crisis period. All of these variables are discussed in Section 5. 2. Since we use a cross-sectional regression model, bank and year fixed effects are not included . In all regressions, t-statistics are based on robust standard errors. Given documented differences between large and small banks in terms of portfolio composition (e. g. Kashyap, Rajan, and Stein 2002, Berger, Miller, Petersen, Rajan, and Stein 2005) and the effect of capital on liquidity creation (Berger and Bouwman forthcoming), we split the sample into large and small banks, and run all regressions separately for these two sets of banks. Large banks have gross total assets (GTA) exceeding $1 billion at the end of the quarter preceding the crisis and small banks have GTA up to 20 $1 billion at the end of that quarter. 5. 2. Variable descriptions and summary statistics We use two measures of a bank’s performance: competitive position and profitability.The bank’s competitive position is measured as the bank’s market share of overall liquidity creation, i. e. , the dollar amount of liquidity created by the bank divided by the dollar amount of liquidity created by the industry. Our focus on the share of liquidity creation is a departure from the traditional focus on a bank’s market share of deposits. Liquidity creation is a more comprehensive measure of banking activities since it does not just consider one funding item but instead is based on all the bank’s on-balance sheet and off-balance sheet activities.To establish whether banks improve their competitive positions during the crisis, we define the change in liquidity creation market share, ? LCSHARE, as the bank’s average market share during the crisis minus its average market share over the eight quarters before the crisis, normalized by its average pre-crisis market share. To examine whether these banks hold on to their improved performance after the crisis, we also measure each bank’s average market share over the eight quarters after the crisis minus its average market share over the eight quarters before the crisis, again normalized by its average marke t share before the crisis.The second performance measure is the bank’s profitability, measured as the return on equity (ROE), i. e. , net income divided by stockholders equity. 23 To examine whether a bank improves its profitability during a crisis, we focus on the change in profitability, ? ROE, measured as the bank’s average ROE during the crisis minus the bank’s average ROE over the eight quarters before the crisis. 24 To analyze whether the bank is able to hold on to improved profitability, we focus on the bank’s average ROE over the eight quarters after the crisis minus its average ROE over the eight quarters before the crisis.To mitigate the influence of outliers, ? LCSHARE and ? ROE are winsorized at the 3% level. Furthermore, to ensure that average values are calculated based on a sufficient number of quarters, we 23 We use ROE, the bank’s net income divided by equity, rather than return on assets (ROA), net income divided by assets, since banks may have substantial off-balance sheet portfolios. Banks must allocate capital against every offbalance sheet activity they engage in. Hence, net income and equity both reflect the bank’s on-balance sheet and off-balance sheet activities.In contrast, ROA divides net income earned based on on-balance sheet and off-balance sheet activities merely by the size of the on-balance sheet activities. 24 We do not divide by the bank’s ROE before the crisis since ROE itself is already a scaled variable. 21 require that at least half of a bank’s pre-crisis / crisis / post-crisis observations are available for both performance measures around a crisis. Since the subprime lending crisis was still ongoing at the end of the sample period, we require that at least half of a bank’s pre-subprime crisis observations and all three quarters of its subprime crisis observations are available.The key exogenous variable is EQRAT, the bank’s capital ratio averaged over the eight quarters before the crisis. EQRAT is the ratio of equity capital to gross total assets, GTA. 25 The control variables include: bank size, bank risk, bank holding company membership, local market competition, and proxies for the economic environment. Bank size is controlled for by including lnGTA, the log of GTA, in all regressions. In addition, we run regressions separately for large and small banks. We include the z-score to control for bank risk. 26 The z-score indicates the bank’s distance from default (e. g. Boyd, Graham, and Hewitt 1993), with higher values indicating that a bank is less likely to default. It is measured as a bank’s return on assets plus the equity capital/GTA ratio divided by the standard deviation of the return on assets over the eight quarters before the crisis. To control for bank holding company status, we include D-BHC, a dummy variable that equals 1 if the bank was part of a bank holding company. Bank holding company membership m ay affect a bank’s competitive position because the holding company is required to act as a source of strength to all the banks it owns, and may also inject equity voluntarily when needed.In addition, other banks in the holding company provide cross-guarantees. Furthermore, Houston, James, and Marcus (1997) find that bank loan growth depends on BHC membership. We control for local market competition by including HERF, the bank-level HerfindahlHirschman index of deposit concentration for the markets in which the bank is p

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Jennifer Danh English 2010 Dr. Panko 4 Dec. 2014 A Right to Privacy Technology has proposed a variety of different options to support the privacy rights of people. At the same time, technology has also done the opposite, making it almost impossible for anyone to have secured privacy. Nowadays, there are multiple hacking programs or devices that can help protect private information; however, they can also be used to invade privacy. Modern-day society has records of incidents and events involving the invasion of privacy, including those not only in private homes, but as well as national and international levels. Is it possible to sustain our privacy to levels that are deemed safe when you are on your cellphone, computer, or even in the†¦show more content†¦In the article, â€Å"Shopping for Privacy on the Internet,† James P. Nehf states that â€Å"†¦ [Our] consumer privacy in the United States is largely the responsibility of individuals who are expected to guard their personal information and take steps to mini mize the risk that it will be used in an unauthorized way† (Nehf, 351). Fortunately, there are multiple routes you can take to help protect and preserve your personal information, such as doing something as simple as changing passwords and double checking all the links we click or be cautious of websites we encounter that has strange behavior. However, technology also has a small catch: putting your private information at risk for invasion. Just when you believe our personal materials are guaranteed safety, the same content can be hacked or tapped into by a person or group of individuals with the knowledge of how to work a computer, they can use this skill for negative intentions. Knowing that technology is constantly changing, we must understand just how much our personal information is at threat. In many cases it seems as if you need to be a step ahead of the criminal. In order to determine the best course of action, we must think like one to increase our confidential inform ation. This is another route to take to deepen our understanding of the elements within privacy. In 1997, the U.S government passed the consumer Internet Privacy Protection Act. (Nehf) This bill provided the consumer the right to all information that an

The Character Of An Individual s Ambition On Self And Others

Elvira Nurmambetova English 20-1 Mrs. Malloy Discuss the idea developed by the text creator in your chosen text about the impact of an individual’s ambition on self and others. Ambition is devil’s creation. Ambition is an admirable trait that enabled famous writers and scholars to attain an unbelievable greatness. However, highly ambitious people often end up failing because they are unable to fill up an insatiable hole of greed that leads them to constant frustration and dissatisfaction. Just as an excessive ambition can start with malice, it can end in anguish and despair. In the play, Macbeth, by William Shakespeare, the main protagonist, Macbeth, and his wife, Lady Macbeth, demonstrate an ambition that has an exacerbating impact on them that slowly leads to the self-destruction and obliteration of people around. After Lady Macbeth clouded Macbeth’s mind, Macbeth killed a benevolent king Duncan. But even with crown and power, Macbeth spend his life in fear and anxiety, until the weight of the ambition was relieved by his downfall. Through Macbeth’s character, Shakespeare shows that the extreme ambition that was emerged out of feroc ious passion could devour an individual’s moral goodness, which in turn would carve the path directly to the total misery. Possessing such ambition makes the individual live in a self-imposed fretfulness and expose the closest people under consequential threats. It is in human nature to see them good and validateShow MoreRelatedThe Great Gatsby And Death Of A Salesman1241 Words   |  5 PagesAmbition. It is a vital characteristic required for an individual wanting achieve their goals. Being ambitious alone is crucial to success as it is the drive that propels one toward it. It is and always will be a human trait. Perhaps that is why the theme of ambition has been so prevalent in literature. 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This creates a problem for those who wish to not only explore the idea of selflessness but share it. This problem was keenly felt by Confucian, Daoist and Buddhist poets. To escape this problem, they created tools used to convey selflessness. Poets used things like themes, language and format within poetry to convey a selflessness. They used themes like rejecting desire, becoming a recluse and living a simple life. To reinforce these themes,Read MoreFrankenstein And The Psychologic And Moralistic Effects Of Community1521 Words   |  7 Pagesdeviation from the troubled man and creation of Mary Shelley ’s novel â€Å"Frankenstein†. Mary Shelley’s Frankenstein is much more than a lunatic scientist; he is a complicated human that leaves society to create a monster out of fervent ambition. It is this unchecked ambition and mental state at causes him to create a creature against the natural order and abandon it, ultimately leading to his demise. 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While Roderigo is present for the duration, Iagos disclosures seem consistent with his real character - during his dialogues with Roderigo he seems to come closest to revealing his true psyche to another individual. Iagos indifference to Roderigos presence during these spiels is indicative of the contemptuous disdain he holds for him. Iago has so little respect for the mental facultyRead MoreThe Nature Of Evil : Macbeth By William Shakespeare1664 Words   |  7 Pagesevil or is something decided and developed by the individual mind. In the beginning of the story, are introduced to the main character Macbeth Thane of Glamis, the play gives many heavy implications that he generally liked by the people and the king especially. Macbeth was a warrior of the king and owned his own estate which really only the rich and powerful could acquire, so it can be assumed that even though as humans we all have secret ambitions or wishes, he was a relatively happy and successful

Project Proposal for Planning and Organising - myassignmenthelp

Question: Discuss about theProject Proposal for Planning and Organising. Answer: Thesis statement: Effective communication is important for the development of an organisation. Overview of the argument: As commented by Argenti[1], the way by which the managers of an organisation carry on their basic management activities is by the means of effective communication. In order to carry on basic activities like planning, organising, leading or controlling, effective communication is required. It is the only means by which the management of the organisation carry on their job responsibilities. Communication can result in the change in attitude of the members in the organisation and that would enhance the activities in getting socialising with others. In fact, communication also acts as a controlling factor that helps to control the behaviour of other individuals[2]. If the activities of an organisation are taken into consideration, it has to be said that there are many levels in an organisation on which the organisational structure is based on. There is a hierarchical structure in fact and the information from one stage to the other can only pass when there will be communication among the individuals. In order to comply with the policies of the organisation and perform their activities effectively, the only means is by communicating with the members. Various issues and problems can be overcome if the organisation communication is carried on in an effective manner. In case of such organisations where trusts and relationship among the employees are important and as pointed out by Dunbar[3], communication actually creates that space where the employees can be bind with each other by a level of trust and security. When people communicate, it reduces the level of uncertainty among the employees and creates a state of company where every single individual can easily communicate with each other and feel more secured and wanted in the organisation. Thus, there is no doubt that effective communication can help in the survival of the overall organisational activities. Problem statement: It has been evident that many organisations failed to carry on effective communication in their organisation that leads to failure of their overall business activities as they are not being able to communicate with each other properly[4]. In case of Saudi Military, the importance of effective communication within the organisation holds true importance in order to understand the needs and requirements of the organisation. If things are not properly communicated, the overall organisational activities would not work effectively. This is the reason, understanding the scope of effective communication and formulating the same in the organisational activities holds true importance. Three main points on the topic: The importance of carrying out effective communication in an organisation can be summed up into three main points as below: Effective communication among the managers of the organisation helped to perform the basic activities like planning, organising, leading and controlling. It is the only effective means of carrying out the job responsibilities and duties in an effective way because it is only by the means of effective communication, the members in the organisation can reach a particular conclusion[5]. Communication also helps to motivate the existing people in the organisation by helping socialising the activities and bringing people together. Significance of the argument: The significance of effective communication lies in the fact that an organisation activity is carried on only by the mean of better communication among the people in the organisation. It helps to carry out the planning and processes in a proper way. It is also a way of motivating people because it clarifies why the particular job is done and people feel encouraged or socialise in the area of their operation[6]. This is the reason, carrying out effective communication is indeed important as it helps to strengthen the organisational values. Moreover, when it comes to comes to organisations like Saudi Military, the importance of communication knew no bounds and it becomes the most crucial element in an organisation to follow. Research limitations: The limitations while carrying the research faced were the limited time that was given for carrying out the complete research. If more time was given, the research process would have been a bit effective. In addition to this, there was limited access to the books and journal articles on the effectiveness of communication in an organisation. The limited information available for the research resulted in some sort of limitation of the study. References: Argenti, Paul A.Corporate communication. McGraw-Hill Higher Education, 2015. Buil, Isabel, Sara Cataln, and Eva Martnez. "The importance of corporate brand identity in business management: An application to the UK banking sector."BRQ Business Research Quarterly19, no. 1 (2016): 3-12. Dunbar, Kwamie. "Faculty Share Views on Importance of Creative Thinking in the Workplace." (2014). Ferraro, Gary P., and Elizabeth K. Briody.The cultural dimension of global business. Taylor Francis, 2017. Sulaiman Al Jahwari, Dawood, Dawood Sulaiman Al Jahwari, Ercan Sirakaya-Turk, Ercan Sirakaya-Turk, Volkan Altintas, and Volkan Altintas. "Evaluating communication competency of tour guides using a modified importance-performance analysis (MIPA)."International Journal of Contemporary Hospitality Management 28, no. 1 (2016): 195-218. Wu, Runze, Zhengrui Bao, Hao Wu, and Bing Fan. "An importance evaluation method combining multiple factors fusion for power communication services in smart grid." InSystems and Informatics (ICSAI), 2016 3rd International Conference on, pp. 270-275. IEEE, 2016.

Fast Drawing Techniques. Essay Example For Students

Fast Drawing Techniques. Essay Finally, the device independent bitmap (DIB) and color palettes are discussed. In the graphics example Of the previous chapter, the area enclosed in a rectangle rounding the shape being formed is redrawn whenever the mouse moves. This causes the entire rectangular area to flicker while drawing. Drawing techniques can be used that only need to change the area within the shape being drawn. When the shape is an ellipse, the shape itself need only be erased and redrawn, rather than the entire rectangular area surrounding the ellipse. But a way to erase its previous shape from the screen needs to be provided prior to redrawing it in its new shape, In this chapter such techniques, which promote fast drawing and minimum screen flicker, are explained. Using Exclusive-or and Exclusive-nor for Fast Redraws The first fast drawing technique presented is the use of either of the fast drawing modes: exclusive-or or exclusive-nor. This technique is demonstrated by modifying the graphics program presented in the previous chapter in Listing 3-3. The running program is shown in Figure 4-1. The program called Faster looks a lot like the graphics program with the exception that the menu item ROPE has been replaced with a new menu item, Postgraduate, which creates a popup menu with two choices: Corrode or Moderated. These menu choices, of course, are used to set the parameters of the fast drawing mode; Corrode gives the choice Of drawing With the exclusive-or mode, and Moderated gives the choice of drawing with the exclusive-nor mode. Figure 4-1: Executing straw Program This Faster program refreshes the screen faster by using a new drawing technique in the Anonymousness() message handling function rather than using the call to Invalidated(), as was done in the graphics program of Chapter Three. When the mouse moves with the left button down, Inpatient is no longer called. Instead, when the left button is down and the mouse has moved, the old form of the current shape is exclusive-or-De (or exclusive-nor-De) often screen and the new form is exclusive-or-De (or exclusive-nor-De) onto the screen. This fast redraw technique depends on the property of exclusive-or (or exclusive- nor) or that a second exclusive-or (or exclusive-nor) removes the shape from the screen, restoring the screen to its state bettor the first exclusive-or (or exclusive- nor), Drawing a second time restores the colors on the screen to what they were before the first drawing, which in essence erases the shape. Listing 4-1 shows the changes that must be made to the previous graphics program, given in Listing 3-3, to create this new program, Faster. (Of course, the code for the application class is the same, so it is not shown. ) Some of the changes in the new program are due to the changes in the menu items. The resource files, faster_RCA and resource_h, are changed but are not shown because their changes are minor. All of the mainframe. H file has been shown for clarity, With the new code in bold and deleted lines Of code commented out. Since most of the code in mainframe. Cap is the same as the program of Listing 3-3, here practical only the new or changed functions are shown. The new code is shown in bold. As well as preceded with an arrow to distinguish it from the code that was previously there. The code that was previously there is not bold. If a line of code that was previously there is no longer needed, it is commented out (preceded with a double slash and because it is a change from the previous code, it is also preceded with an arrow to highlight that a change has occurred. The following changes can be seen in the file mainframe. Cap: A new virtual function Drawn(Client*) of class C_Shape is defined. .u4eb2df23ef1aaff36770c3b5017a56c6 , .u4eb2df23ef1aaff36770c3b5017a56c6 .postImageUrl , .u4eb2df23ef1aaff36770c3b5017a56c6 .centered-text-area { min-height: 80px; position: relative; } .u4eb2df23ef1aaff36770c3b5017a56c6 , .u4eb2df23ef1aaff36770c3b5017a56c6:hover , .u4eb2df23ef1aaff36770c3b5017a56c6:visited , .u4eb2df23ef1aaff36770c3b5017a56c6:active { border:0!important; } .u4eb2df23ef1aaff36770c3b5017a56c6 .clearfix:after { content: ""; display: table; clear: both; } .u4eb2df23ef1aaff36770c3b5017a56c6 { display: block; transition: background-color 250ms; webkit-transition: background-color 250ms; width: 100%; opacity: 1; transition: opacity 250ms; webkit-transition: opacity 250ms; background-color: #95A5A6; } .u4eb2df23ef1aaff36770c3b5017a56c6:active , .u4eb2df23ef1aaff36770c3b5017a56c6:hover { opacity: 1; transition: opacity 250ms; webkit-transition: opacity 250ms; background-color: #2C3E50; } .u4eb2df23ef1aaff36770c3b5017a56c6 .centered-text-area { width: 100%; position: relative ; } .u4eb2df23ef1aaff36770c3b5017a56c6 .ctaText { border-bottom: 0 solid #fff; color: #2980B9; font-size: 16px; font-weight: bold; margin: 0; padding: 0; text-decoration: underline; } .u4eb2df23ef1aaff36770c3b5017a56c6 .postTitle { color: #FFFFFF; font-size: 16px; font-weight: 600; margin: 0; padding: 0; width: 100%; } .u4eb2df23ef1aaff36770c3b5017a56c6 .ctaButton { background-color: #7F8C8D!important; color: #2980B9; border: none; border-radius: 3px; box-shadow: none; font-size: 14px; font-weight: bold; line-height: 26px; moz-border-radius: 3px; text-align: center; text-decoration: none; text-shadow: none; width: 80px; min-height: 80px; background: url(https://artscolumbia.org/wp-content/plugins/intelly-related-posts/assets/images/simple-arrow.png)no-repeat; position: absolute; right: 0; top: 0; } .u4eb2df23ef1aaff36770c3b5017a56c6:hover .ctaButton { background-color: #34495E!important; } .u4eb2df23ef1aaff36770c3b5017a56c6 .centered-text { display: table; height: 80px; padding-left : 18px; top: 0; } .u4eb2df23ef1aaff36770c3b5017a56c6 .u4eb2df23ef1aaff36770c3b5017a56c6-content { display: table-cell; margin: 0; padding: 0; padding-right: 108px; position: relative; vertical-align: middle; width: 100%; } .u4eb2df23ef1aaff36770c3b5017a56c6:after { content: ""; display: block; clear: both; } READ: Logic Computer Design EssayThis new function draws the shape on a small segment of the screen, so it uses a Client device context. Addition/deletion of variables of the class C_MainFrame, as highlighted in the code, Two new message map entries and their corresponding handler functions. (These result from the changed menu items and displace the three previous entries on the old menu. ) Slight modifications to the Inpatient() function. (We no longer set the ROPE mode for the entire screen area. Substantial modifications to the functions Anonymousness() and Malnutrition(), which are discussed in detail following the listing. The Inpatient Function The easiest way for an appli cation to handle the drawing Of graphics and text in its client area is to call CNN::alienated() (or when the client area is to be repainted) and put all the drawing code in the member function Inpatient(). The reason this way is the easiest is that Inpatient() needs to contain the screen. Drawing code any. Ay, in order to respond to resizing and uncovering of the window. The graphics program uses this approach. As discussed earlier, the Inpatient function will redraw the entire client area r will redraw that portion of the client area of its window which is specified in the first argument of The graphics program to Listing 3-3 will redraw all of the shapes in the shape list that are within the area being redrawn (the entire screen or the specified Correct). In this graphics program, the function is used when redrawing the entire screen is desired, which is indicated when the ROPE code or the m_Become code is changed. Use the function when you want to redraw only a portion of the screen, which is done when the new shape is being drawn and formed. The Inpatient function loops over the elements of the array of pointers to shape objects (ellipses and rectangles) that the user has created, calling the Draw() virtual member function on each shape, The virtual function mechanism built into C++ ensures that the corresponding Draw() function will be called in each case. The Background Color The function CDC::Stockroom(COLORED) sets the background color. This color is used for filling the update area between the hatch lines when using a hatched brush, for filling the background of character cells, and for filling the gaps in dashed lines. The system also uses this background color when converting bitmaps between color and monochrome device contexts. This fill is only done when the background mode is OPAQUE, as set by This background is more properly defined as the color of the interstices in brush patterns and nonsolid pen lines. Windows SO also uses the term background to refer to an unrelated concept, namely the background brush tort the window. This brush, named hypochondriac, is used to erase the clipping region before drawing in the client area. The variable hypochondriac is essentially the background color and pattern f the client area. The default value that MFC assigns to hypochondriac is a solid white brush. The value of hypochondriac can be changed for a window, if desired, by assigning a new value to it in the Abstractednesss() function (as discussed in Chapter One). These two types of background are not tied together in any way. For example, if the user changes the window background, the client areas background will be the new color, but the interstices in hatched fills of rectangles, etc. Will still be whatever color has most recently specified for the device context.