Homer’s Iliad - The Shield of Achilles Essay -- Iliad essays

Homer’s Iliad - The Shield of Achilles Homer devotes the final passages of Book 18 of The Iliad to the description of the shield of Achilles. Only a quarter of the description concerns warfare, the essential grist of the epic. Instead, the bulk of the description presents a peaceful society and rural idylls, a curious choice for the most ferocious warrior of the Greeks, and an odd thing for both armies to fear. A narrative emerges from the scenes of the shield, and it is this that fits Achilles and repulses everyone else. We expect Achilles’ shield to unsettle his adversaries—that is, after all, one of the objectives of a shield. Indeed, Achilles returns to battle "shining in all his armour, a man like the murderous war god" (Iliad 20.46).1 Once he and Hektor are alone on the battlefield, the shield shines: like that star which comes on in the autumn and whose conspicuous brightness far outshines the stars that are numbered in the night’s darkening, the star they give the name of Orion’s Dog, which is brightest among the stars, and yet is wrought as a sign of evil and brings on the great fever for unfortunate mortals. (22.26-31) We need not wonder, then, when Priam and Hecuba supplicate Hektor to return to Troy in the face of this practically cosmic onslaught. But what is unusual is that Achilles’ own men avoid the shield: "None had the courage / to look straight at it. They were afraid of it" (19.14-15). Here even the narration relies on the pronoun "it" instead of explicitly identifying the shield as the source of... ...ictory. If Achilles had chosen to leave, not only would he have been a good son, but the Trojans might have won the war, meaning both he and Priam would have had something to which they could look forward, and three-fourths of the shield’s story would not have been left unfulfilled. In staying, he contributes not only to his own demise, but also to that of the Trojans. This knowledge causes "the anger to come harder upon him" (19.16), and yet "he was glad" (19.18). The great dilemma of Achilles is forever immortalized on his shield, so that some lesser man in the future would be able to read the narrative upon it and say: "This armor was Achilles’, a man who forfeited the rest of his life for grim combat. The gods do not force most men to choose like that." NOTES 1. Homer, The Iliad, trans. Richmond Lattimore (Chicago: University of Chicago Press, 1951).

Insulting language Essay

Great expectations might be read as a bildungsroman because it charts the progress of the main character, Pip, from childhood to adulthood. Traditionally, a bildungsroman contains a hero, who usually suffers early on in life, maturing and clashing with the social settings and eventually being accepted into it. The story focuses around this theme but doesn’t always play by its rules. In my essay I will be discussing to what point Great expectations can be read as a bildungsroman. â€Å"Great expectations† conforms to the genre of a bildungsroman right from the start of the book, in the opening scene we meet old pip talking about charting his life from when he was a little boy to a young gentleman. Like in most bildungsroman books Pip has suffered a loss at an early age, his parents, brothers and sisters. Pip has also had a harsh start to life because he lives with his sister who, even thought she is looking out for him, treats him quite badly. To even more extent the social hierarchy is established very early on as we find out that Mr. Joe is a blacksmith and this is important in order to judge Pip’s development, we can even tell from the language that he uses that he has a hard knock life and is not well off. The structure of the opening scene tells us a lot about how it conforms to the bildungsroman genre, the way Dickens immediately introduces us to both Pips. The old omnipotent storyteller Pip, who tells the story as he remembers it skipping out bits and stretching the truth a little. And the young â€Å"actor† Pip who acts out what is happening while narrating it in 1st person which allows us to feel the harshness and changes that he is going through as he does which supports the bildungsroman framework. As I have mentioned before the language shows a lot about the type of life and the harshness of his life. E.g. Dark, flat, wilderness, low leaden line. Finally Dickens introduces the Convict who reinforces the social order and emphasises the harshness of Pips life, lastly he introduces the beginning of Pip’s great expectations. We first meet young pip in a cold and desolate church yard, looking at the graves of his parents and brothers this is important as it shows the harsh life he has had. In Chapter 1 we find out that Pip Has not had a childhood, he was bought up â€Å"By hand† suggesting that he has been disciplined harshly and ill Treated But with only the best in mind. We also found out that Pip’s Sister, Mrs. Joe, his only Relative in the world Who disciplines him so severely, Married the local town blacksmith which shows that Pip’s Family is poor and that pip is not so well educated As he calls himself Pip which is the only words he could pronounce. Even with the convict Pip’s Personality shines through, it shows that even though the Convict is threatening him severely But Pip still feels sympathy for him â€Å"if he were eluding the hands of the dead people†, even when he is told that he must go and fetch him a file he still has the courtesy to say â€Å"good night, sir† but Pip was also nervous â€Å"he faltered† and scared â€Å"I was dreadfully frightened†. Old Pip is reporting what young Pip said and felt. As I have said in previous paragraphs Pip has had a hard life, Pip’s house is a small â€Å"wooden house† with a â€Å"ditch clock† which is a cheap clock. Pip is also mistreated as he â€Å"served as a connubial missile† and that he gets regular beatings from â€Å"tickler†. Pip is not the only one beaten â€Å"Knowing her (Mrs. Joe) to have a hard and heavy hand, and to be much in the habit of laying it upon her husband as well as upon me†. Mrs. Joe is important because she represents the raising of the children in Victorian society, she helps us to lets us see how truly far Pips has come from being forced to intimidate higher class to actually being it. Joe is a â€Å"fellow-sufferer† of Mrs. Joe and he and Pip both treat each other like equals and share secrets more of having an older brother than him actually raising him as a father figure. It is important to see Pip at his home as we can feel sympathy for him and empathize what he â€Å"is† going through. Dickens wants us to fell sympathy for him so we can realize what his life was like and how he has changed since his childhood. The robbery of the pie shows us how Pip’s fear for both Mrs. Joe and the convict and that his conscience about stealing from his sister, the one who brought him up â€Å"by hand† and fear from being caught or, if not doing it out of this fear, being killed by the convicts â€Å"friend†. In chapter 7 we learn a lot about Pips education. Everything he has learnt was form Mr. Wopsles great aunt’s school, but not from Mrs. Wopsle, from Biddy, her daughter. In Mrs. Wopsles School their only source of education was a single book that was passed around the class showing that Pip hasn’t had a very good education like many of the working class children in Victorian society. Pips education shows that he is slowly advancing in society and is trying to achieve his goals. However Pip thinks of himself as stupid when really he only thinks like this as he is not learning fast enough for him to like it and his surroundings make him believe it. Joe in comparison to Pip has had not much of an education, he cant even read where as Pip has become superior to him in his education and because of this we fell sorry for Joe because of the story of his childhood he tells us afterwards. Pip is invited to play at Miss Haversham’s house, this is important as it shows a crucial part of the bildungsroman genre, the â€Å"shunning out† of the society that he wants to be accepted by, when Pip is playing at Satis house he is mixing with the higher class which represents a small leap to achieving his goals, while also giving him something else to aim at, Estella. Pip is treated badly by Estella because of his class making him feel poor and â€Å"common†, insulting the language he uses â€Å"he calls the knaves, jacks!† showing the difference in class which makes him upset and cry but the fact that she gets to him means that he likes her, urging him to change class â€Å"the hands that have never bothered me before, look coarse and common now†. Joe responds to Pip with helpful advice, saying that if he wants to be â€Å"uncommon† he must do it the honest way because if he can’t he’ll never do it and we expect Pip to go and strike his goals.

Newell Company Essay

1. Does Newell have a successful corporate-level strategy? Does the company add value to the businesses within its portfolio? * Newell’s corporate-level strategy focuses on the growth through acquisitions of companies that manufactured low technology, nonseasonal, noncyclical, and nonfashionable products that volume retailers would always keep on their shelf. These companies usually manufacture brand-name staple products that ranked #1 or #2 but may not be efficiently managed. * Newell’s goal is to increase its sales and profitability by offering a comprehensive range of products and reliable service to the mass retail channel. Newell has chosen to develop its product line through key acquisitions, rather than internal organic growth. The strategy succeeds based on their two pronged approach of following an established acquisition process (Newellization) and ensuring corporate continuity across the division to support its performance in the market. This strategy helps Newell successfully diversify their portfolio of products for mass retailers. 2. What are Newell’s distinctive resources? * Pricing model that that covers across all product categories: Newell used different pricing point, â€Å"good,† â€Å"better,† and â€Å"best† to meet all customers needs achieving the critical mess 3. What challenges faced the company in the late 1990s? * One of the main challenges in the late 1990s was the increase in customer buying power. By 1997, three mass retailer chains controlled 80% of the discount retailer market. This allowed retailers to obtain significant leverage over price and scheduling. * Another challenge in the 1990s was the acquisitions of Calphalon and Rubbermaid. These were both major stepping stones for Newell in that both companies will bring greater brand recognition to the Newell brand. It was a challenge because of the speed in which the companies were acquired and the short amount of time between the two acquisitions. At the time, Calphalon was in a different market, and Newell wanted to enter the department and specialty store competition. This required changes within the Newell Company because of a different view of products and competition. Rubbermaid was a difficult acquisition because of the vastness of the company in general. Some  industry observers worried that this target would be too large to be â€Å"Newellized.†

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

Performance management & Performance appraisal Essay

Nowadays, every company has their human resources department that plays a large part of an organizations and a key to affect business succeeds or not. There are two core threads of human resources department are individual and organizational learning, individual and organizational performance. Human resource management should possess a good management systems and framework; ensure human ability is all used to achieve organization goals. Include strategic human resources management, equal employment opportunity, staffing, talent management and development, total rewards, risk management and worker protection, employee and labor relations. The best organizations understand that managing human resources effectively involves more than focusing only on current employees. It requires a long-term perspective that is responsive to the concerns of current employees; potential future employees and recent employees no longer work for. At the same time, the organizations strive to manage employees effectually, face to many challenges, for instance manning teams, the multicultural workforce, globalization, ethics and corporate social responsibility and metros. Human resources department responsible to provide effectual performance management and system to assist the company is going smooth. Performance management The purpose of performance management is one of the most important and positive developments, achievement of high performance by the organization, managing the business. This is the process of identifying, measuring, managing and developing the performance in an organization. There are showing how well employees perform and finally improve performance level. The further explain that create strategic, integrated process, develop a culture of constantly success to organizations by improving the performance of the people who work in them and by developing the capabilities of individual contributors and teams (Cardy & Leonard , 2011). The development of individuals with competence and commitment, working towards to shared meaningful objectives within an organization that supports the achievement. When the direction is correctly, performance management is a systematic analysis and measurement of workers performance. Also it is a critical and necessary component for individual and organizational effectiveness. When manage a group of workers or others, report the feedback to boss. It must be a process needed for improvement to occur. In performance management, it is getting the right workers into the production line or suitable staff into the system in a very important part of the overall process (Bergstedt, 2010). Performance appraisal Performance appraisal are part of a performance management system, it is ongoing process of evaluating and reviews of employee performance over time. Provide an opportunity for formal communication between management and the employees, concerning each employee what performing on organization. Create two-way interaction between people. It is a good opportunity and let employee express what their comment to bosses is. Open lines of communication throughout the year help to make effective working relationships. Allow management to make decisions about employees within the organization from this communication. Appraisals to make evaluative decisions concerning the workforce including pay raises, promotions, demotions, training, and development and so on. It cans measures skills and realization with reasonable accuracy and uniformity. The management can depend on this reliable information for making strategic planning, may enhance productivity for the firm as well. It provides a way to help identify areas for performance enhancement and to help promote professional growth. Each employee is entitled to a thoughtful and careful appraisal (Harzing, Pinnington, 2011, p.20-28). The success of the process depends on the supervisor’s willingness to complete a constructive and objective appraisal and on the employee’s willingness to respond to constructive suggestions and to work with the supervisor to reach future goals. Difference between performance management and performance appraisal Performance management focus is on performance management, identifies measures, manages, and develops the performance of people in the organization. It is designed to improve worker performance over time. Emphasis is on performance improvements of individuals, teams and the organization. It will continue process with periodical performance review discussions and then performance planning, analysis, review, development and improvements. Defining and setting performance standards are an integral part and designed by the human resources department but monitored under the each departments. Developmental needs are identified in the beginning of the year on the basis of the competency requirements for the coming year. There is review via mechanisms. However performance appraisal focus is on performance appraisal and ratings. It is just a part of the performance management process. Identifies measures, evaluates the employee’s performance, and then discusses that performance with the employee. Normally it is an annual exercise though periodic evaluations are made. The main functions are on ratings and evaluation. The most important component is rewards and recognition of good performance of staff. Designed and monitored by the human resource department. Developmental needs are identified at the end of the year on the basis of the appraisal of competency gaps. There are review mechanisms to ensure objectivity in ratings. (Fraser, 2007) Characteristics of an unsuccessful performance management system Normally, the good performance possesses ability, motivation and opportunity. It should make use of employee skills and have adequate incentives to urge them willingness to do the job. Provide work in an environment with support and way for expression. Unfortunately, driven by the some situational constraints including physical environment, working conditions, use of outcome of appraisal complexity of job, interdependence and lack of financial or human resources to make performance management system be an unsuccessful (Armstrong & Baron, 2005, p. 78-85). Causes of Failure of a performance management system have legislation affirmative action, lack of raters, less training, rating inflation or deflation, unclear purpose, without or ignore feedback, unfair reward system, appraisal instruments, performance Standards, rating accuracy, accountability of raters, management Commitment, no trust and participation and acceptance. ( Luecke & Hall,2006, p.93-98) Characteristics of a successful performance management system Successful performance management system can manage performance over time to ensure that remain productive, and hopefully become even more capable, as progress in their careers. Designing an effective performance management system should including mirror the corporate culture, clear definition and communications of what good performance ensure all senior management support and understand the level of performance. It may train managers in this performance management. To set a clear expectation for employee, acknowledging that people are doing a good job and recognizing them for a job well done. To set a clear manifest that performance in the company is differentiated and that differences in performance are recognized through the reward system. Differentiate performance fairly and effectively; through actions to show poor performance is being address, high performance will have a great rewards. Set an expectations or employee development, adjust the system if needed. Even compete performance management have a well strategic, developmental and administrative, also need line managers and senior management behave in a same way and support. That would be accomplished to achieve the organization goals. (Roberts Alan, 2012) An unsuccessful versus a successful performance management system When an unsuccessful compare a successful performance management system, if under unsuccessful performance management system. Without any clear objective, goals and fair rules in this organization. The whole company will face to employee leave, low morale and not belong to the company. Without employee support and the bad relationship between company. The business must be going worst. On the contrary, if company has a good performance management system with a clear fairly and effectively goals, the employee and management will all support and try the best to achieve goals. The business will be getting better for each part under a pleased environment. (Bhattacharyya, 2011, p.47-52) Some common errors and eliminated The common errors including distributional errors occur in three forms, severity or strictness, central tendency and leniency. There are based on a standard normal distribution. In severity or strictness error, the rater evaluates everyone or nearly everyone. Similarity error occurs when raters evaluate subordinates that judge or consider more similar as better employees. All have a tendency to feel more comfortable with people who feel are more similar. The similarity is based on demographic characteristics such as race. Allow this feeling of comfort with similar individuals to be reflected in the performance appraisal process. It can avoid similarity error by embracing diversity and objectively evaluating individual employees based on their actual performance. Contrast error is the rater compares and contrasts performance between two employees, rather than using absolute measures of performance to measure each employee. For example, the rater may contrast a good performer with an outstanding performer, and as a result of the significant contrast. This would be a contrast error. It can avoid contrast error by objectively evaluating individual employees based on actual performance. Management must use the ranking method correctly; each individual based on the items on the assessment form then rank the individuals based on their assessments. Halo and horn occurs when the evaluator has a generally positive or negative impression of an individual, and the evaluator then artificially extends that general impression to many individual categories of performance to create an overall evaluation of the individual that is either positive or negative In other words, if employees are judged by their supervisor to be generally good employees, and the supervisor then evaluates each of the areas of their performance as good, regardless of any behaviors or results to the contrary, the supervisor is guilty of halo error. It can avoid halo error by remembering that employees are often strong in some areas and weaker in others, and need to objectively evaluate individual employees based on actual performance for each and every item of assessment. Appraisal politics is refers to evaluators purposefully contorting a rating to achieve personal or organization goals. Factors other than performance affect the performance appraisal. These factors are internal in the appraisal system and the organization system. It is occur when raters are accountable to the employee and rated, it appear competing rating goals and direct linking current between performance appraisal and most desirable rewards. In order to lessen this matter, managers should keep in mind and pay attention a fair appraisal system. Central tendency error occurs when raters evaluate everyone under the control as average nobody is either really good or really bad. Proximity error states that similar marks may be given to items that are near each other on the performance appraisal form, regardless of differences in performance on those measures. Regency error occurs when raters use only the last few weeks or month of a rating period as evidence of their ratings of others. Attribution error. In simplified terms, attribution is a process where an individual assumes reasons or motivations such as attitudes, values, or beliefs for an observed behavior. Reducing rater errors is offer reeducating rating errors. Rater training undertaken to make managers aware of rating errors and helps develop strategies for minimizing those errors. This is consisting of the participants view vignettes designed to elicit rating errors, for example contrast. Rater Error Training called frame-of-reference training as well, emphasize the multidimensional nature of performance and raters with the actual content of various performance dimensions. Moreover, accuracy training seems can increasing accuracy and provided the training allows raters to practice making ratings and training feedback. Create a fair system should include train raters on the appropriate use of the process as discussed previously, build top management support for the appraisal system and actively discourage distortion, give raters some latitude to customer performance objectives and criteria for their rates, recognize employee accomplishments that are not self-promoted, make sure constraints for example a budget. Also make sure that appraisal processes are consistent across the company and foster a climate of openness to encourage employees to be honest the weakness. (Salaman, Storey & Billsberry, 2005, p.19-27) Conclusion In conclusion, this essay is proving that good performance management is one of the most important positions in the company. Seeing that it can help employee and management together to achievement the goals under high performance. At the same time, human resources department is a very chief role to develop perfect performance management system and need to avoid some common error. Thus, that’s why human resources are a big part in the organization and influence the whole company. Word count: 2013 Reference Armstrong Michael & Baron Angela (2005): Managing Performance: Performance Management in Action, Chartered Institute of Personnel and Development, CIPD House London, p. 78-85 Bergstedt Martin, (2010) [online] Available at: http://chenected.aiche.org/tools-techniques/the-performance-appraisal-system-part-2-of-effective-employee-performance-management [Accessed October 27, 2012]. Bhattacharyya Dipak Kumar, (2011): Performance Management Systems and Strategies, Dorling Kindersley India Pvt Ltd, licensees of Pearson Education in South Asia p.47-52 Cardy Robert L & Leonard Brian, (2011): Performance Management: Concepts, Skills, and Exercises Second Edition, M.E.Sharpe, Inc New York, p.134-156 Fraser Ross, (2007) [online] Available at: [Accessed July 5 2007]. Harzing Anne-Wil, Pinnington Ashly, (2011): International Human Resources Management Third Edition, SAGE Publications Asia-Pacific Ltd Singapore p.20-28 Luecke Richard, Hall Brian J, (2006): Performance Management: Measure and Improve the Effectiveness of Your Employees, Harvard Business School Press p.93-98 Roberts Alan, (2012) [online] Available at: [Accessed June 25, 2012]. Salaman Graeme, Storey John, Billsberry Jon, (2005): Strategic Human Resource Management: Theory and Practice Second Edition, Published in association with The Open University p.19-27

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