Accounts Receivable and Straight-line Depreciation Method

1. The company uses the straight-line depreciation method. The rental equipment is estimated to have a useful life of eight years. Thus, the monthly depreciation of the rental equipment is 240,000/96, or $2,500 per month.2. The note payable to Rent-It is good for one year. $100,000 and the accumulated interest are due on November 30, 2012. The account payable for office supplies is due in thirty days, or January 2, 2012. The account payable to Universal Utilities is due in thirty days, or January 30, 2012. The company declared a dividend of 10 cents per share, payable on January 15, 2012. Income taxes are payable in 2012.3. Susquehanna Equipment Rentals was named as a co-defendant in a $25,000 lawsuit filed on behalf of Kevin Davenport. The extent of the company’s legal and financial responsibility for this accident cannot be determined at this time.f) It does appear that the company is headed for insolvency. It has $100,000 is notes payable that are due January 2, 2012, and i t only has $65,000 cash. The company is expecting $9,900 in accounts receivable, but that is still not enough to cover the notes payable. A majority of the company’s assets are tied up in rental equipment, which is not a liquid asset. Thus, the company will not be able to meet its financial obligations to its lenders.g) It would be unethical for Patty Driver to maintain the accounting records for this company since she is one of the owners of the corporation. The accounting records must be maintained by someone independent of the organization in order for the reports to be fair and ethical.

Sarah’s Night

Sarah wanted to impress them. Maybe Sara did not have many friends, and she wanted to make sure to make a good Impression on these new friends. New friends can be exciting, and the thought of going to a party excited her more because she had never been to a party. Sarah was trying to impress these friends by doing things she had never done. The ways Sarah displayed cognitive dissonance was her excitement of having new friends, and doing something different, but at the same mime she was uneasy about going to the party because she knew she should be home and was worried that she may get caught, and get Into trouble with her parents.She still had fun at the party and was glad that she went, but she still knew she should have been at home, and should have obeyed her parent's rules. Sara conformed to her peer†s beliefs by going to the party with them. They told her how much fun she would have, and she would be missing out if she did not go. Sara gave into peer pressure. Even though she knew this would cause problems with her parents, she anted her new friends to like her. That is why she gave into the peer pressure.Sara also had the excitement of going to the party. She had never been to a party before and was excited as well as curious. Some of the reasons Jack was Interested In Sara was because he found her attractive, they both lived In the same neighborhood, and when they started talking they found out they had the same taste in music, and had some of the same hobbies. These are related to the factors of attraction. Physical attraction because Jack said Sara was beautiful. Proximity because Jack and Sara lives n the same neighborhood.Similarity because they found out they have the same taste In music, and had some of the same hobbles. Aggression was the type of social Interaction displayed through the fight at the party. The aggression started as yelling, and quickly turned into a physical fight. We are not sure what started the fight. It could have starte d as a simple misunderstanding, or maybe of the guys was talking to the other's girlfriend, and that started a fight. It could have been a case of bullying, alcohol may have been involved as well. There were also teens from different spinsterhood at the party.This could be an issue If one is from a better part of town, so he thinks he may be better than the teen that does not have as much. Social even Sara and her friends. Up to the point of the fight, everyone was having a nice time at the party, but that stopped almost everyone's good time. Sarah's behavior was mostly influenced by her friends almost all night long. Starting off when they wanted her to go to the party. I'm sure she felt pressure, and wanted to fit in with her new friends. I believe that is why she said yes to them, and went to the party.Obviously Sara knows right from wrong, but at 15 years old, she succumbed to peer pressure. Teenagers are easily more influenced at this age because they want to fit in with their friends. Sara was worried about get caught, and getting into trouble with her parents, but she knew she always had listened her parents, and never got into trouble. This made her think it would be all right, and she would not get into much trouble if she went to the party because she had never been in trouble. Sara and her friends were influenced to leave the party because of the fight that broke out.If not for the fight, I am sure they would have stayed much longer. Looking back on the night, I am sure Sara may have had mixed emotions. Some positive, and some negative. On the positive she got to experience her first party with her new friends, and she met a boy at the party. On the negative she probably let her parents down by breaking curfew, and had them worried about her. Sara had to wonder if it were worth lying to her parents to have fun, or is her new friends, and the party more important. This is something Sara will need to have a look at in her life.

Bhojraj Lee Paper

Accounting Research Center, Booth School of Business, University of Chicago Who Is My Peer? A Valuation-Based Approach to the Selection of Comparable Firms Author(s): Sanjeev Bhojraj and Charles M. C. Lee Source: Journal of Accounting Research, Vol. 40, No. 2, Studies on Accounting, Entrepreneurship and E-Commerce (May, 2002), pp. 407-439 Published by: Blackwell Publishing on behalf of Accounting Research Center, Booth School of Business, University of Chicago Stable URL: http://www. jstor. org/stable/3542390 . Accessed: 15/01/2011 08:35 Your use of the JSTOR archive indicates your acceptance of JSTORs Terms and Conditions of Use, available at . http://www. jstor. org/page/info/about/policies/terms. jsp. JSTORs Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at . ttp://www. jstor. org/action/showPublisher? publisherCode=black. . Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printed page of such transmission. JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [emailprotected] org. Blackwell Publishing and Accounting Research Center, Booth School of Business, University of Chicago are collaborating with JSTOR to digitize, preserve and extend access to Journal of Accounting Research. http://www. jstor. org Research Journalof Accounting Vol. 40 No. 2 May2002 in Printed U. S. A. Who Is My Peer? A Valuation-Based Approach to the Selection of Comparable Firms SANJEEV BHOJRAJ AND CHARLES M. C. LEE* Received4January2001;accepted4 September2001 ABSTRACT This study presents a general approach for selecting comparable firms in market-based research and equity valuation. Guided by valuation theory, we develop a warrantedmultiple for each firm, and identify peer firms as those having the closest warranted multiple. We test this approach by examining the efficacy of the selected comparable firms in predicting future (one- to three-year-ahead) enterprise-value-to-sales and price-to-book ratios. Our tests encompass the general universe of stocks as well as a sub-population of socalled new economy stocks. We conclude that comparable firms selected in this manner offer sharp improvements over comparable firms selected on the basis of other techniques. 1. Introduction Accounting-based market multiples are easily the most common technique in equity valuation. These multiples are ubiquitous in the reports and recommendations of sell-side financial analysts, and are widely used in *Johnson Graduate School of Management, Cornell University. We thank Bhaskaran Swaminathan, as well as workshop participants at the Australian Graduate School of ManConferagement, Cornell University, Indiana University, the 2001 Journal ofAccountingResearch ence, the 2001 HKUST Summer Symposium, Syracuse University, and an anonymous referee, for helpful comments. The data on analyst earnings forecasts are provided by I/B/E/S International Inc. 407 of of 2002 Copyright University Chicagoon behalfof the Institute Professional Accounting, ? , 408 S. BHOJRAJ C. M. C. LEE AND investment bankers fairness opinions (e. g. , DeAngelo [1990]). They also appear in valuations associated with initial public offerings (IPOs), leveraged buyout transactions, seasoned equity offerings (SEOs), and other merger and acquisition (M) activities. Even advocates of projected discounted cash flow (DCF) valuation methods frequently resort to using market multiples when estimating terminal values. Despite their widespread usage, little theory is available to guide the application of these multiples. With a few exceptions, the accounting and finance literature contains little evidence on how or why certain individual multiples, or certain comparable firms, should be selected in specific contexts. Some practitioners even suggest that the selection of comparable firms is essentially an art form that should be left to professionals. 2 Yet the degree of subjectivityinvolved in their application is discomforting from a scientific perspective. Moreover, the aura of mystique that surrounds this technique limits its coverage in financial analysis courses, and ultimately threatens its credibility as a serious alternative in equity valuation. In this study, we re-examine the theoretical underpinnings for the use of market multiples in equity valuation, and develop a systematic approach for the selection of comparable firms. Our premise is that the popularity of market-based valuation multiples stems from their function as a classic satisficingdevice (Simon [1997]). In using multiples to value firms, analysts forfeit some of the benefits of a more complete, but more complex, pro forma analysis. In exchange, they obtain a convenient valuation heuristic that produces satisfactory results without incurring extensive time and effort costs. In fact, we believe it is possible to compensate for much of the information these multiples fail to capture through the judicious selection of comparable firms. Our aim is to develop a more systematic technique for doing so, through an appeal to valuation theory. Specifically, we argue that the choice of comparable firms should be a function of the variables that drive cross-sectional variation in a given valuation multiple. For example, in the case of the enterprise-value-to-sales multiple, comparable firms should be selected on the basis of variables that drive cross-sectional differences in this ratio, including expected profitability, growth, and the cost-of-capital. 3 In this spirit, we use variables nominated by valuation theory and recent advances in estimating the implied cost-of-capital (i. . , Gebhardt, Lee, and Swaminathan [2001]) to develop a 1 For example, Kim and Ritter [1999] discuss the use of multiples in valuing IPOs. Kaplan and Ruback [1995] examine alternative valuation approaches, including multiples, in highly levered transactions. 2For example, Golz [1986], Woodcock (1992), and McCarthy (1999). We use the enterprise-value-to-sales ratio (EVS) rather than the price-to-sales (PS) ratio because the former is conceptually s uperior when firms are differentially levered (we thank the referee for pointing this out). We also report results for the price-to-book (PB) ratio. We focus on these two ratios because of their applicability to loss firm, which are particularly important among the so-called new economy (tech, biotech, and telecommunication) stocks. However, our approach is general, and can be applied to any of the widely used valuation multiples. WHO IS MYPEER? 409 warrantedmultiple for each firm based on large sample estimations. We then identify a firms peers as those firms having the closest warranted valuation multiple. Our procedures result in two end products. First, we produce warranted multiples for each firmn-that is, a warranted enterprise-value-to-sales (WEVS)and a warranted price-to-book (WPB)ratio. These warranted multiples are based on systematic variations in the observed multiples in crosssection over large samples. The warranted multiples themselves are useful for valuation purposes, because they incorporate the effect of cross-sectional variations in firm growth, profitability, and cost-of-capital. Second, by ranking firms according to their warranted multiples, we generate a list of peer firms for each target firm. For investors and analysts who prefer to conduct equity valuation using market multiples, this approach suggests a more objective method for identifying comparable firms. For researchers, our approach suggests a new technique for selecting control firms, and for isolating a variable of particular interest. Recent methodology studies have demonstrated that characteristic-matched control samples provide more reliable inferences in market-based research (e. . , Barber and Lyon [1997], Lyon et al. [1999]). Our study extends this line of research by presenting a more precise technique for matching sample firms based on characteristics identified by valuation theory. Our approach is designed to accommodate both profitable and loss firms, which have become pervasive in the so called new economy. In short, the methodology developed in this paper can be useful whenever the choice of control firms plays a prominent role in the research design of a market-related study. We test our approach by examining the efficacy of the selected comparable firms in predicting future (one- to three-year-ahead) EVSand PB ratios. 4Our tests encompass the general universe of stocks as well as a sub-population of new economy stocks from the tech, biotech, and telecommunication sectors. Our results show that comparable firms selected in this manner offer sharp improvements over comparable firms selected on the basis of other techniques, including industry and size matches. The improvement is most pronounced among the so-called new economy stocks. The main message from this study is that the choice of comparable firms can be made more systematic and less subjective through the application of valuation theory. In the case of the EVSmultiple, our approach almost triples the adjusted r-squares obtained from using simply industry or industry-size matched selections. The PB multiple is more difficult to predict in general, but our approach still more than doubles the adjusted r-square relative to industry or industry-size matched selections. Interestingly, we find that using the actual multiples from the best comparable firms is generally better than using the warranted multiple itself. Moreover, the choice of comparable 4We forecast future multiples because we do not regard the current stock price as necessarily the best benchmark for assessing valuation accuracy. As discussed later, forecasting future multiples is not equivalent to forecasting future prices or returns. 410 s. BHOJRAJAND C. M. C. LEE firms is, to some extent, dependent on the market multiple under consideration-the best firms for the EVSratio are not necessarily the best firms for the PB ratio. While we illustrate our approach using these two ratios, this technique can be generalized to other common market multiples, including: EBITDA/TEV, E/P, CF/P, and others. In the next section, we further motivate our study and discuss its relation to the existing literature. In section 3, we develop the theory that underpins our analysis. In section 4, we discuss sample selection, research design and estimation procedures. Section 5 reports our empirical results, and section 6 concludes with a discussion of the implications of our findings. . Motivationand Relationto PriorLiterature There are at least three situations in which comparable firms are useful. First, in conducting fundamental analysis, we often need to make forecasts of sales growth rates, profit margins, and asset efficiency ratios. In these settings, we typically appeal to comparable firms from the same industry as a source of reference. Second, in multiples-based valuation, the market multiples of comparable firms are u sed to infer the market value of the target firm. Third, in empirical research, academics seek out comparable firms as a research design device for isolating a variable of particular interest. Our paper is focused primarily on the second and third needs for comparable firms. 5 Given their widespread popularity among practitioners, market multiples based valuation has been the subject of surprisingly few academic studies. Three recent studies that provide some insights on this topic are Kim and Ritter (KR;[1999]), Liu, Nissim, and Thomas (LNT; [1999]), and Baker and Ruback (BR; [1999]). All three examine the relative accuracy of alternative multiples in different settings. KR uses alternative multiples to value initial public offers (IPOs), while LNT and BR investigate the more general context of valuation accuracy relative to current stock prices. KRand LNT both find that forward earnings perform much better than historical earnings. LNT shows that in terms of accuracy relative to current prices, the performance of forward earnings is followed by that of historical earnings measures, cash flow measures, book value, and finally, sales. In addition, Baker and Ruback [1999] discuss the advantages of using harmonic means-that is, the inverse of the average of inversed ratios-when aggregating common market multiples. None of these studies address the choice of comparable firms beyond noting the usefulness of industry groupings. 5 Our technique is not directly relevant to the first situation, because it does not match firms on the basis of a single attribute (such as sales growth, or profit margin). Instead, our approach matches firms on the basis of a set of variables suggested by valuation theory. Our paper also does not address the trivial case whereby a firm is its own comparable. As we point out later, in multiples-based valuation of public firms, a firms own lagged multiple is often the most useful empirical proxy for its current multiple. WHO IS MYPEER? 411 Closer to this study are three prior studies that either investigate the effect of comparable firm selection on multiple-based valuation, or examine the determinants cross-sectional variations in certain multiples. Boatsman and Baskin [1981] compare the accuracy of value estimated based on earningsto-price (EP) multiples of firms from the same industry. They find that, relative to randomly chosen firms, valuation errors are smaller when comparable firms are matched on the basis of historical earnings growth. Similarly, Zarowin [1990] examines the cross-sectional determinants of EPratios. He shows forecasted growth in long-term earnings is a dominant source of variation in these ratios. Other factors, such as risk, historical earnings growth, forecasted short-term growth, and differences in accounting methods, seem to be less important. Finally,Alford [1992] examines the relative valuation accuracy of EPmultiples when comparable firms are selected on the basis of industry, size, leverage, and earnings growth. He finds that valuation errors decline when the industry definition used to select comparable firms is narrowed to twoor three-digit SIC codes, but that there is no further improvement when a four-digit classification is used. He also finds that after controlling for industry membership, further controls for firm size, leverage, and earnings growth do not reduce valuation errors. Several stylized facts emerge from these studies. First, the choice of which multiple to use affects accuracy results. In terms of accuracy relative to current prices, forecasted earnings perform relativelywell (KR,LNT); the priceto-sales and price-to-book ratios perform relatively poorly (LNT). Second, industry membership is important in selecting comparable firms (Alford [1992], LNT, KR). The relation between historical growth rates and EP ratios is unclear, with studies reporting conflicting results (Zarowin [1999], Alford [1992], Boatsman and Baskin [1981]), but forecasted growth rates are important (Zarowin [1999]). Other measures, including risk-basedmetrics (leverage and size) do not seem to provide much additional explanatory power for E/P ratios. Our study is distinct from these prior studies in several respects. First, our approach is more general, and relies more heavily on valuation theory. This theory guides us in developing a regression model that estimates a warranted multiple for each firm. We then define a firms peers as those firms with the closest warranted market multiple to the target firm, as identified by our model. The advantage of a regression-based approach is that it allows us to simultaneously control for the effect of various explanatory variables. For example, some firms might have higher current profitability, but lower future growth prospects, and higher cost-of-capital. This approach allows us to consider the simultaneous effect of all these variables, and to place appropriate weights on each variable based on empirical relations established in large samples. Our empirical results illustrate the advantage of this approach. Contrary to the mixed results in prior studies, we find that factors related to profitability, growth, and risk, are strongly and consistently correlated with the EVS 412 S. BHOJRAJ C. M. C. LEE AND and PB ratios. Collectively, factors that relate to profitability, growth, and risk, play an important role in explaining cross-sectional variations of these multiples. In fact, we find that variables related to firm-specific profitability, forecasted growth and risk are more important than industry membership and firm size in explaining a firms future EVSand PB ratios. Second, we employ recent advances in the empirical estimation of cost-ofcapital (i. e. , Gebhardt et al. [2001]) to help identify potential explanatory variables for estimating our model of warranted market multiples. The risk metrics examined in prior studies are relatively simple, and the results are mixed. We follow the technique in Gebhardt et al. [2001] to secure additional explanatory variables that are associated with cross-sectional determinants of a firms implied cost-of-capital. Several of these factors turn out to be important in explaining EVSand PB ratios. Third, we do not assume that the current stock price of a firm is the best estimate of firm value. Prior studies compare the valuation derived by the multiples to a stocks current price to determine the valuation error. In effect, these studies assume that the current stock price is the appropriate normative benchmark by which to judge a multiples performance. Under this assumption, it is impossible to derive an independent valuation using multiples that is useful for identifying over- or under-valued stocks. Our less stringent assumption of market efficiency is that a firms current price is a noisy proxy for the true, but unobservable intrinsic value, defined as the present value of expected dividends. Moreover, due to arbitrage, price converges to value over time. As a result, price and various alternative estimates of value based on accounting fundamentals will be co-integrated over time. 6 Under this assumption, we estimate a warrantedmultiple that differs from the actual multiple implicit in the current price. Consistent with this philosophy, we test the efficacy of alternative estimated multiples by comparing their predictive power for a firms future multiples (e. g. , its one-, two-, or three-year-ahead EVSand PB ratios). Finally,our approach can be broadly applied to loss firms, including many new economy stocks. Prior studies that examine comparable firms (e. g. , Alford [1992], Boatsman and Baskin [1981], and Zarowin [1999]) focus solely on the EP ratio. A limitation of these studies is that they do not pertain to loss firms. This limitation has become more acute in recent years, as many technology, biotechnology, and telecommunication firms have reported negative earnings. 6 For a more formal statistical model of this co-integrated relationship between price and alternative estimates of fundamental value, see, Lee, Myers, and Swaminathan [1999]. 7 Note that forecasting future multiples is different from forecasting future prices or returns. In the current context, forecasting future price involves two steps: forecasting future multiples, and forecasting future fundamentals (e. g. , sales or book value per share). Our main interest is in the stability of the multiples relation, and not in forecasting fundamentals. An example of fundamental analysis that focuses on forecasting future fundamentals is Ou and Penman [1989]. WHO IS MY PEER? 413 Appendix A provides an indication of the magnitude of the problem. This appendix reports descriptive statistics for a sample of 3,515 firms from NYSE/AMEX/NASDAQ as of 5/29/2000. To be included, a firm must be U. S. domiciled (i. e. , not an ADR), have a market capitalization of over $100 million, and fundamental data for the trailing 12 months (i. . , not a recent IPO). Based on aggregate net income from the most recent four quarters, we divide the sample into profitable firms (78% of sample) and loss firms (22% of sample). Panel A reports the percentage of these firms that have positive EBIT,Operating Income, EBITDA, Gross Margin, Sales, One-year-ahead forecasted earnings (FY1), and book value. This panel shows that only 40% of the loss firms have positive operating income, only 47% have positive EBITDA, and only 34% have positive FY1forecasts. In fact, only 87% of the loss firms have positive gross margins. The only reliably positive accounting measures are sales (100%) and book value (94%). Clearly, these loss firms are difficult to value. However, they are also difficult to ignore. Panel B reports the distribution of realized returns in the past six months (11/31/99 to 5/29/00) separately for the profit firms and loss firms. The returns for the loss firms have higher mean (19. 6% versus 7. 8%), higher standard deviation (111. 3% versus 42. 3%), and fatter tails. As a group, the loss firms appear to be a high-stake game that constitutes a substantial proportion of the universe of traded stocks in the United States. Our study uses the two most reliably positive multiples (EVSand PB). Liu, Nissim, and Thomas [1999] show that these two ratios are relatively poor performers in terms of their valuation accuracy. We demonstrate that by choosing an appropriate set of comparable firms, the accuracy of these ratios can be improved sharply. In particular, we demonstrate the incremental usefulness of the technique for a sub-population of new economy stocks from the technology, telecom, and biotechnology sectors. 3. Development the Theory of The valuation literature discusses two broad approaches to estimating shareholder value. The first is direct valuation, in which firm value is estimated directly from its expected cash flows without appeal to the current price of other firms. Most direct valuations are based on projected dividends and/or earnings, and involve a present value computation of future cash flow forecasts. Common examples are the dividend discount model (DDM), the discounted cash flow (DCF) model, the residual income model (RIM), or some other variant. 8 The second is a relative valuation approach in We do not discuss liquidation valuation, in which a firm is valued at the breakup value of its assets. Commonly used in valuing real estate and distressed firms, this approach is not appropriate for most going concerns. 414 s. BHOJRAJAND C. M. C. LEE which firm value estimates are obtained by examining the pricing of comparableassets. This approach involves applying an accounting-based market multiple (e. g. , price-to-earnings, price-to-book, or price-to-sales ratios) from the comparable firm(s) to our accounting number to secure a value estimate. In relative valuation, an analyst applies the market multiple from a comparable firm to a target firms corresponding accounting number: Our estimated price = (Their market multiple) X (Our accounting number). In so doing, the analyst treats the accounting number in question as a summary statistic for the value of the firm. Assuming our firm in its current state deservesthe same market multiple as the comparable firm, this procedure allows us to estimate what the market would pay for our firm. Which firm(s) deservethe same multiple as our target firm? Valuation theory helps to resolve this question. In fact, explicit expressions for most of the most commonly used valuation multiples can be derived using little more than the dividend discount model and a few additional assumptions. For example, the residual income formula allows us to re-express the discounted dividend model in terms of the price-to-book ratio:10 * PB, Et[(ROEt+i re)Bt+i-l] (1 + re)i Bt i=1 (1) Bt where Pt* is the present value of expected dividends at time t, B, = book value at time t; Et [. ] = expectation based on information available at time t; re = cost of equity capital; and ROEt+i = the after-taxreturn on book equity for period t + i. This equation shows that a firms price-to-book ratio is a function of its expected ROEs, its cost-of-capital, and its future growth rate in book value. Firms that have similar price-to-book ratios should have present values of future residual income (the infinite sum in the right-hand-side of equation (1)) that are close to each other. In the same spirit, it is not difficult to derive the enterprise-value-to-sales ratio in terms of subsequent profit margins, growth rates, and the cost of capital. In the case ofa stable growth firm, the enterprise-value-to-salesratio can be expressed as: EV7 Et(PMxkx(1 + g)) _ (r- g) St where EVZ is total enterprise value (equity plus debt) at time t, St = total sales at time t; Et[. ] = expectation based on information available at 9 A third approach, not discussed here, is contingent claim valuation based on option pricing theory. Designed for pricing traded assets with finite lives, this approach encounters significant measurement problems when applied to equity securities. See Schwartz and Moon [2000] and Kellogg and Charnes [2000] for examples of how this approach can be applied to new economy stocks. 10See Feltham and Ohlson [1995] or Lee [1999] and the references therein for a discussion of this model. See Damodaran [1994; page 245] for a similar expression. WHO IS MYPEER? 415 time t; PM is operating profit margin (earnings before interest); k is a constant payout ratio (dividends and debt servicing costs as a percentage of earnings; alternatively, it is sometimes called one minus the plow-back rate); r = weighted average cost of capital; and g is a constant earnings growth rate. In the more general case, we can model the firms growth in terms of an initial period (say n years) of high growth, followed by a period of more stable growth in perpetuity. Under this assumption, a firms enterprise-valueto-sales ratio can be expressed as: (1+ EVt St EtPMxkx rL? gl)(1- ((1 + gg)n/(l r + r)n)) (1 + gi) n(l + g2) 1 (1+g1)n(1+ g2) nir- (1+r g ]ii (3) where EV7 is the total enterprise value (debt plus equity) at time t, St = total sales at time t; Et[. = expectation based on information available at time t; PM is operating profit margin; k is a constant payout ratio; r = cost of capital; gi is the initial earnings growth rate, which is applied for n years; and g2 is the constant growth rate applicable from period n+ 1 onwards. Equation (3) shows that a firms warranted enterprise-value-to-sales ratio is a function of its expected operating profit margin (PM), payout ratio (k), expected growth rates (gi and g2), and cost of capital (re). If the market value of equity and d ebt approximates the present value of expected cash flows, these variables should explain a ignificant portion of the cross-sectional variation in the EVS ratio. In the tests that follow, we employ a multiple regression model to estimate the warranted EVSand PB ratios for each firm. The explanatory variables we use in the model are empirical proxies for the key elements in the right-hand side of equations (1) and (3). 4. Research Design In this section, we estimate annual regressions that attempt to explain the cross-sectional variation in the EVSand PBratios. Our goal is to develop a reasonably parsimonious model that produces a warrantedmultiple (WEVS or WPB)for each firm. These warranted multiples reflect the large sample relation between a firms EVS (or PB) ratio and variables that should explain cross-sectional variations in the ratio. The estimated WEVS(or WPB) becomes the basis of our comparable firm analysis. 4. 1 ESTIMATING THE WARRANTED RATIOS We use all firms in the intersection of (a) the merged COMPUSTATindustrial and research files, and (b) the I/B/E/S historical database of analyst earnings forecasts, excluding ADRs and REITs. We conduct our analysis as of June 30th of each year for the period 1982-1998. To be included 416 AND s. BHOJRAJ C. M. C. LEE n the analysis a firm must have at least one consensus forecast of longterm growth available during the 12 months endedJune 30th. In the event that more than one consensus forecast was made in any year, the most recent forecast is used. We use accounting information for each firm as of the most recent fiscal year end date, and stock prices as of the end of June. To facilitate estimation of a r obust model, we drop firms with prices below $3 per share and sales below $100 million. We eliminate firms with negative book value (defined as common equity), and any firms with missing price or accounting data needed for the estimation regression. 2We require that all firms belong in an industry (based on two-digit SIC codes) with at least five member firms. In addition we eliminate firms in the top and bottom one percent of all firms ranked by EVS, PB, Rnoa, Lev, Adjpm,and Adjgroeach year (these variables are defined below). The number of remaining firms in the sample range from 741 (in 1982) to 1,498 (in 1998). For each firm, we secure nine explanatory variables. We are guided in the choice of these variables by the valuation equations discussed earlier, and several practical implementation principles. First, we wish to construct a model that can be applied to private as well as public firms, we therefore avoid using the market value of the target firm in any of the explanatory variables. Second, in the spirit of the contextual fundamental analysis (e. g. , see Beneish, Lee, and Tarpley [2000]), we anchor our estimation procedure on specific industries. In other words, we use the mean industry market multiples as a starting point, and adjust for key firm-specific characteristics. 3 Finally, to the extent possible, we try to use similar variables for estimating EVSand PB. Our goal is to generate relatively simple models that capture the key theoretical constructs of growth, risk, and profitability. Specifically, our model includes the following variables, which are also summarized and described in more detail in Appendix B: IndevsThe harmonic mean of the enterprise-value-to-salesmultiple for all the firms with the same two-digit SIC code. For example, for the 1982 regression, this variable is the harmonic mean industry EVS as of June 1, 1982. Enterprise value is defined as total market capitalization of equity, plus book value of long-term debt. This variable controls for industrywide factors, such as profit margins and growth rates, and we expect it to be positively correlated with current year firm-specific EVS and PB ratios. Indpb-The harmonic mean of the price-to-book ratio for all firms in the same industry. This variable controls for industry-wide factors that affect the PB ratio. In addition, Gebhardt et al. [2001] show firms with higher PB 12 The two exceptions are research and development expense and long-term debt. Missing data in these two fields are assigned a value of zero. More specifically, we use the harmonic means of industry EVSand PB ratios, that is, the inverse of the average of inversed ratios (see Baker and Ruback [1999]). WHO IS MYPEER? 417 ratios have lower implied costs of capital. To the extent that industries with lower implied costs-of-capital have higher market multiples, we expect this variable to be positively correlated with EVSand PB ratios. AdjpmThe industry-adjusted profit margin. We comput e this variable as the difference between the firms profit margin and the median industry profit margin. In each case, the profit margin is defined as a firms operating profit divided by its sales. Theory suggests this variable should be positively correlated with current year EVSratios. where Dum is 1 if Adjpm LosspmThisvariable is computed as Adjpm*Dum, is less than or equal to zero, and 0 otherwise. Used in conjunction with Adjpm,this variable captures the differential effect of profit margin on the P/S ratio for loss firms. Prior studies (e. g. , Hayn [1995]) show that prices (and returns) are less responsive to losses than to profits. In univariate tests, this variable should be positively correlated with EVSand PB. However, controlling for Adjpm,this variable should be negatively correlated with EVSand PB ratios. AdjgroIndustry-adjusted growth forecasts. This variable is computed as the difference between a firms consensus earnings growth forecast (from IBES) and the industry median of the same. Higher growth firms merit higher EVSand PB ratios. LevBook leverage. This variable is computed as the total long-term debt scaled by the book value of common equity. In univariate tests, Gebhardt et al. [2001] shows that firms with higher leverage have higher implied costsof-capital. However, controlling for market leverage, they find that book leverage is not significant in explaining implied cost-of-capital. We include this variable for completeness, in case it captures elements of cross-sectional risk not captured by the other variables. Rnoa-Return on net operating asset. This variable is a firms operating profit scaled by its net operating assets. Penman [2000] recommends this variable as a measure of a firms core operation profitability. In our context, having already controlled for profit margins, this variable also serves as a control for a firms asset turnover. We expect it to be positively correlated with the EVSand PB ratios. RoeReturn on equity. This variable is net income before extraordinary items scaled by the end of period common equity. Conceptually, this variable should provide a better profitability proxy in the case of the PB ratio. We use this variable in place of Rnoa as an alternative measure of profitability when conducting the PB regression. Rd-Total research and development expenditures divided by sales. Firms with higher RD expenditures tend to have understated current profitability relative to future profitability. To the extent that this variable captures profitability growth beyond the consensus earnings forecast growth rate, we expect it to be positively correlated with the EVSand PB ratios. In addition to these nine explanatory variables, we also tested three other variables-a dividend payout measure (actual dividends scaled by 418 S. BHOJRAJ AND C. M. C. LEE total assets), an asset turnover measure, and a measure of the standard deviation of the forecasted growth rate. The first two variables add little to the explanatory power of the model. The standard deviation measure (suggested by Gebhardt et al. 2001] as a determinant of the cost-ofcapital) contributed marginally, but was missing for a significant number of observations. Moreover, this measure would be unavailable for private firms. For these reasons, we excluded all three variables from our final model. To recap, our research design involves estimating a series of annual cross-sectional regressions of either the EVSor PB ratio on ei ght explanatory variables. The estimated coefficients from last years regressions are used, in conjunction with each firms current year information, to generate a prediction of the firms current and future ratio. We refer to this prediction as a firms warrantedmultiple (WEVSor WPB). This warranted multiple becomes the basis for our identification of comparable firms in subsequent tests. STATISTICS 4. 2 DESCRIPTIVE Table 1 presents annual summary statistics on the two dependent and nine explanatory variables. The overall average EVS of 1. 20 (median of 0. 94) and average PB of 2. 26 (median of 1. 84) are comparable to prior studies (e. g. , LNT, BB), although our sample size is considerably larger due to the inclusion of loss firms. This table also reveals some trends in the key variables over time. Consistent with prior studies (e. g. Frankel and Lee [1999]) we observe an increase over time in the accounting-based multiples (EVS, PB, Indps, and Indpb) and total RD expenditures (Rd). This non-stationarity in the estimated coefficients could be attributable to systematic changes in the composition of firms over time. For example, the increased importance of the RD variable could reflect the ris ing prominence of technology firms in the sample. The accounting-based rates of return (Rnoa and Roe) and book leverage (Lev) are relatively stable over time. As expected, the industry-adjustedvariables (Adjpm,Losspm,and Adjgro) have mean and median measures close to zero. Overall, this table indicates that the key input variables for our analysis make economical sense. Table 2 presents the average annual pairwise correlation coefficients between these variables. The upper triangle reports Spearman rank correlation coefficients; the lower triangle reports Pearson correlation coefficients. As expected, EVSis positively correlated with the industry enterprise-value-tosales ratio (Indevs) and price-to-book ratio (Indpb). It is also positively correlated with industry-adjusted measures of a firms profit margin (Adjpm) and expected growth rate (Adjgro). It is negatively correlated with book leverage (Lev), and positively correlated with accounting rates of return (Rnoa and Roe), as well as RD expense (Rd). To a lesser degree, EVS is also positively correlated with profit margin among loss firms (Losspm). The results are similar for the PB ratio. All the correlation coefficients WHO IS MY PEER? TABLE 1 StatisticsofEstimationVariables Summary 419 This table provides information on the mean and median of the variables used in the annual estimation regressions. All accounting variables are from the most recent fiscal year end publicly available byJune 30th. Market values are as of June 30th. EVSis the enterprise value to sales ratio, computed as the market value common equity plus long-term debt, divided by sales. PB is the price to book ratio. Indevsis the industry harmonic mean of EVSbased on two-digit SIC codes. Indpbis the industry harmonic mean of PB. Adjpmis the difference between the firms profit margin and the industry profit margin, where profit margin is defined as operating profit divided by sales. Losspmis Adjpm* indicator variable, where the indicator variable is 1 if profit is margin 0 and 0 otherwise. Adjgro the difference between the analysts consensus forecast of the firms long-term growth and the industry average. Lev is the total long-term debt scaled by book value of stockholders equity. Rnoa is operating profit scaled by net operating assets. Rd is the firms RD expressed as a percentage of net sales. year 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 mean median mean median mean median mean median mean median mean median mean median mean median mean median mean median mean median mean median mean median mean median mean median mean median mean median EVS 0. 3 0. 50 0. 98 0. 77 0. 84 0. 69 0. 88 0. 73 1. 07 0. 88 1. 22 1. 00 1. 09 0. 90 1. 07 0. 89 1. 09 0. 89 1. 10 0. 87 1. 15 0. 94 1. 22 1. 02 1. 20 1. 00 1. 36 1. 07 1. 49 1. 13 1. 51 1. 20 1. 59 1. 24 PB 1. 11 0. 93 1. 82 1. 48 1. 46 1. 26 1. 72 1. 46 2. 14 1. 82 2. 31 1. 92 1. 97 1. 70 2. 02 1. 70 1. 99 1. 64 1. 93 1. 54 2. 13 1. 76 2. 48 2. 04 2. 31 1. 98 2. 49 2. 08 2. 75 2. 24 2. 87 2. 41 3. 06 2. 55 Indevs Indpb Adjpm 0. 50 0. 006 0. 92 0. 000 0. 50 0. 92 1. 57 0. 76 0. 002 1. 59 0. 77 0. 000 1. 34 0. 69 0. 001 0. 000 1. 30 0. 72 0. 70 1. 45 0. 004 1. 30 0. 000 0. 72 0. 001 0. 85 1. 7 0. 000 0. 86 1. 69 0. 95 1. 95 -0. 002 0. 95 0. 000 1. 82 1. 69 0. 85 0. 002 0. 80 1. 61 0. 000 0. 84 1. 79 0. 003 0. 76 1. 63 0. 000 0. 83 1. 69 0. 002 0. 79 1. 49 0. 000 1. 65 0. 003 0. 80 1. 39 0. 000 0. 69 0. 87 1. 71 0. 005 0. 78 0. 000 1. 52 0. 90 1. 91 0. 002 0. 000 0. 86 1. 76 0. 89 0. 006 2. 02 0. 86 1. 91 0. 000 0. 95 0. 007 2. 06 0. 93 0. 000 2. 02 1. 01 0. 009 2. 18 0. 98 1. 99 0. 000 0. 005 1. 02 2. 12 1. 07 0. 000 2. 01 1. 09 0. 004 2. 20 0. 000 1. 08 2. 05 Losspm 0. 000 0. 000 -0. 003 0. 000 -0. 004 0. 000 -0. 002 0. 000 -0. 004 0. 000 -0. 007 0. 000 -0. 004 0. 000 -0. 03 0. 000 -0. 004 0. 000 -0. 002 0. 000 -0. 004 0. 000 -0. 002 0. 000 -0. 002 0. 000 -0. 001 0. 000 -0. 002 0. 000 -0. 003 0. 000 -0. 004 0. 000 Adjgro 0. 50 0. 00 0. 21 -0. 05 0. 44 -0. 01 0. 66 0. 00 0. 30 -0. 04 0. 18 -0. 10 0. 29 0. 00 0. 69 0. 00 0. 58 -0. 08 0. 45 -0. 12 0. 23 -0. 19 0. 55 -0. 09 0. 49 -0. 15 0. 73 0. 00 0. 40 -0. 13 0. 36 -0. 17 0. 43 0. 00 Lev 0. 45 0. 36 0. 49 0. 38 0. 43 0. 33 0. 44 0. 32 0. 50 0. 34 0. 54 0. 40 0. 56 0. 43 0. 57 0. 41 0. 61 0. 44 0. 59 0. 45 0. 59 0. 42 0. 58 0. 39 0. 58 0. 36 0. 56 0. 38 0. 58 0. 37 0. 61 0. 36 0. 63 0. 38 Rnoa 20. 85 19. 62 17. 8 16. 18 17. 85 16. 93 19. 96 18. 82 17. 58 16. 41 17. 27 16. 00 19. 05 17. 68 19. 90 18. 54 19. 77 17. 97 19. 00 16. 93 17. 86 15. 97 19. 80 17. 22 20. 08 17. 47 21. 66 18. 72 22. 19 18. 93 21. 56 18. 97 22. 84 20. 24 Roe 14. 39 14. 77 11. 88 12. 82 12. 04 13. 00 13. 49 14. 32 11. 45 12. 92 10. 63 12. 22 12. 61 12. 93 13. 90 14. 71 13. 29 13. 51 11. 91 12. 55 10. 31 11. 29 11. 87 12. 39 11. 57 12. 37 13. 48 13. 18 12. 57 13. 08 12. 46 12. 89 12. 31 12. 76 Rd 1. 23 0. 14 1. 33 0. 09 1. 51 0. 08 1. 66 0. 05 1. 75 0. 00 1. 94 0. 00 1. 83 0. 00 1. 94 0. 00 1. 86 0. 00 1. 96 0. 00 2. 03 0. 00 1. 9 0. 00 1. 90 0. 00 1. 77 0. 00 2. 01 0. 00 2. 01 0. 00 2. 25 0. 00 Pooled mean 1. 20 2. 26 median 0. 94 1. 84 0. 88 0. 81 1. 83 1. 72 0. 004 -0. 003 0. 44 0. 000 0. 000 -0. 05 0. 56 20. 00 12. 35 1. 86 0. 38 17. 96 13. 01 0. 00 are in the expected direction. Except for the correlation between Rnoa and Roe (which do not appear in the same estimation regression), none of the average pairwise correlation coefficients exceed 0. 60. These results suggest that the explanatory variables are not likely to be redundant. 420 S. BHOJRAJAND C. M. C. LEE TABLE 2 Correlation between EstimationVariables This table provides the correlation between the variables. The upper triangle reflects the Spearman correlation estimates; the lower triangle reflects the Pearson correlation coefficients. All accounting variables are based on the most recent fiscal year end information publicly available byJune 30th. Market values are as of June 30th. EVSis the enterprise value to sales ratio, computed as the market value common equity plus long-term debt, divided by sales. PB is the price to book ratio. Indevsis the industry harmonic mean of EVSbased on two-digit SIC codes. Indpbis the industry harmonic mean of PB. Adjpmis the difference between the firms profit margin and the industry profit margin, where profit margin is defined as operating profit divided by sales. Losspmis Adjpm*indicator variable, where the indicator variable is 1 if profit is margin 0 and 0 otherwise. Adjgro the difference between the analysts consensus forecast of the firms long-term growth and the industry average. Lev is the total long-term debt scaled by book value of stockholders equity. Rnoa is operating profit scaled by net operating assets. Rd is the firms RD expressed as a percentage of net sales. Average Correlation (Pearson/Spearman) EVS EVS PB Indevs PB 0. 52 Indevs Indpb 0. 51 0. 16 0. 09 0. 33 0. 35 0. 35 -0. 06 -0. 02 0. 04 0. 02 -0. 01 -0. 05 0. 08 -0. 09 -0. 02 0. 25 0. 03 0. 14 0. 10 0. 06 Adjpm Losspm Adjgro Lev Rnoa Roe 0. 54 0. 08 0. 21 -0. 07 0. 21 0. 28 0. 38 0. 14 0. 60 0. 59 0. 29 -0. 20 -0. 07 0. 04 -0. 01 0. 06 -0. 01 0. 05 0. 15 -0. 03 0. 06 -0. 04 -0. 14 0. 26 0. 06 -0. 17 0. 54 0. 55 0. 26 0. 06 -0. 03 0. 32 0. 28 0. 26 0. 04 0. 04 -0. 01 0. 10 0. 09 -0. 35 -0. 16 0. 02 -0. 12 -0. 02 0. 51 0. 07 -0. 24 0. 75 0. 32 0. 50 0. 38 0. 07 -0. 12 0. 66 0. 06 -0. 10 0. 09 -0. 23 -0. 03 -0. 6 Rd 0. 17 0. 08 0. 19 0. 11 0. 03 -0. 05 -0. 02 -0. 27 0. 03 -0. 03 0. 47 0. 50 0. 04 0. 15 0. 28 Indpb 0. 33 Adjpm 0. 59 0. 09 Losspm 0. 06 0. 29 Adjgro 0. 22 Lev -0. 03 -0. 07 Rnoa 0. 54 0. 22 0. 48 Roe 0. 23 Rd 0. 09 0. 24 5. Empirical Results 5. 1 MODEL ESTIMATION Table 3 presents the results of annual cross-sectional regressions for each year from 1982 to 1998. The dependen t variable is the enterprise-value-tosales ratio (EVS). The eight independent variables are as described in the previous section. Table values represent estimated coefficients, with accompanying p-values presented in parentheses. Reported in the right columns are adjusted r-squares and the number of observations per year. The last two rows report the average coefficient for each variable, as well as a Newey-West autocorrelation adjusted t-statisticon the mean of the time series of annual estimated coefficients. The results from this table indicate that a consistently high proportion of the cross-sectional variation in the EVS ratio is captured by the eight explanatory variables. The annual adjusted r-squares average 72. 2%, and range from a low of 66. 1% to a high of 76. 5%. The strongest six explanaRnoa, nd RD) have the same tory variables (Indevs,Adjpm,Losspm, Adjgro, directional sign in each of 17 annual regressions, and are individually significant at less than 1%. Indpbis positively correlated with EVS in 11 out of 17 years, and is significant at the 5% level. Controlling for Indpb,book WHO IS MY PEER? TABLE 3 Annual EstimationRegressions Warranted for Enterprise-Value-to-Sales This table reports the res ults from the following annual estimation regression: 8 421 EVSi,t = at + j=1 jtCj,i,t + Li,t where the dependent variable, EVS,is the enterprise value to sales ratio as ofJune 30th of each year. The eight explanatory variables are as follows: Indevs is the industry harmonic mean of EVSbased on two-digit SIC codes; Indpbis the industry harmonic mean of the price-to-book ratio; Adjpmis the difference between the firms profit margin and the industry profit margin, is where profit margin is defined as operating profit divided by sales; Losspm Adjpm indicator variable, where the indicator variable is 1 if profit margin 0 and 0 otherwise; Adjgrois the difference between the analysts consensus forecast of the firms long-term growth rate and the industry average; Lev is long-term debt scaled by book equity; Rnoa is operating profit as a percent of net operating assets; and Rd is RD expense as a percentage of sales. P-values are provided in parentheses. The last row represents the time-series average coefficients along with Newey-Westautocorrelation corrected t-statistics. The adjusted r-square (r-sq) and number of firms (# obs) are also reported. Year Intercept 1982 -0. 0623 (0. 13 5) 1983 -0. 0883 (0. 121) 1984 0. 0192 (0. 699) 1985 0. 1337 (0. 002) 1986 0. 0225 (0. 706) 1987 0. 1899 (0. 007) 1988 0. 1774 (0. 0) 1989 -0. 0455 (0. 347) 1990 0. 1083 (0. 027) 1991 0. 2321 (0. 00) 1992 0. 2064 Indevs 1. 2643 (0. 00) 1. 3531 (0. 00) 1. 2778 (0. 00) 1. 2231 (0. 00) 1. 3202 (0. 00) 1. 0908 (0. 00) 1. 0759 (0. 00) 1. 1264 (0. 00) 1. 1263 (0. 00) 1. 0740 (0. 00) 0. 8277 1. 0169 (0. 00) 1. 0027 (0. 00) 1. 0355 (0. 00) 1. 1690 (0. 00) 1. 1714 (0. 00) 1. 0157 (0. 00) 1. 1277 (0. 00) Indpb 0. 1648 (0. 00) -0. 0301 (0. 342) -0. 0015 (0. 964) -0. 0152 (0. 604) 0. 0047 (0. 856) -0. 0324 (0. 339) -0. 0097 (0. 63) 0. 0828 (0. 00) 0. 0322 (0. 019) 0. 0256 (0. 079) 0. 1150 0. 0579 (0. 097) 0. 0027 (0. 913) -0. 0211 (0. 512) 0. 0430 (0. 141) 0. 0366 (0. 264) 0. 1561 (0. 0) 0. 0360 (0. 031) Adjpm 6. 3052 (0. 00) 8. 1343 (0. 00) 6. 9266 (0. 00) 7. 9394 (0. 00) 9. 4308 (0. 00) 9. 8090 (0. 00) 8. 6458 (0. 00) 8. 4475 (0. 00) 9. 3485 (0. 00) 10. 4789 (0. 00) 10. 2810 Losspm -2. 8510 ( 0. 119) -5. 3800 (0. 00) -4. 2894 (0. 00) -4. 0951 (0. 00) -6. 2424 (0. 00) -6. 8296 (0. 00) -6. 9959 (0. 00) -5. 3691 (0. 00) -6. 0607 (0. 00) -6. 9779 (0. 00) -7. 9414 Adjgro 0. 0117 (0. 00) 0. 0392 (0. 00) 0. 0209 (0. 00) 0. 0177 (0. 00) 0. 0316 (0. 00) 0. 0363 (0. 00) 0. 0267 (0. 00) 0. 0225 (0. 00) 0. 0346 (0. 00) 0. 0316 (0. 00) 0. 0329 Lev 0. 0665 (0. 007) 0. 1414 (0. 00) 0. 0707 (0. 012) 0. 0238 (0. 351) -0. 0246 (0. 325) 0. 608 (0. 035) 0. 0228 (0. 27) 0. 0143 (0. 409) -0. 0381 (0. 065) -0. 0430 (0. 06) -0. 0567 Rnoa -0. 0091 (0. 00) -0. 0049 (0. 004) -0. 0088 (0. 00) -0. 0089 (0. 00) -0. 0080 (0. 00) -0. 0041 (0. 014) -0. 0054 (0. 00) -0. 0032 (0. 01) -0. 0037 (0. 005) -0. 0053 (0. 00) -0. 0037 Rd 0. 0194 (0. 00) 0. 0463 (0. 00) 0. 0197 (0. 00) 0. 0153 (0. 00) 0. 0118 (0. 01) 0. 0319 (0. 00) 0. 0281 (0. 00) 0. 0127 (0. 00) 0. 0191 (0. 00) 0. 0134 (0. 00) 0. 0157 0. 0253 (0. 00) 0. 0254 (0. 00) 0. 0680 (0. 00) 0. 0244 (0. 00) 0. 0313 (0. 00) 0. 0229 (0. 00) 0. 0253 (0. 00) R-sq # Obs 74. 40 741 70. 80 73. 45 74. 66 71. 11 66. 84 75. 44 74. 58 73. 54 76. 45 71. 63 71. 1 748 771 797 799 856 787 813 829 855 902 978 (0. 00) 1993 1994 1995 1996 1997 1998 All 0. 1811 (0. 004) 0. 2698 (0. 00) 0. 3148 (0. 00) 0. 0713 (0. 249) 0. 1192 (0. 048) -0. 0269 (0. 683) 0. 1072 (0. 007) (0. 00) (0. 00) (0. 00) (0. 00) (0. 00) (0. 004) (0. 008) (0. 00) 11. 4266 -6. 4058 (0. 00) (0. 00) 10. 6165 -7. 1717 (0. 00) (0. 00) 11. 9432 -9. 2245 (0. 00) (0. 00) 11. 3311-10. 6464 (0. 00) (0. 00) 12. 5771 -7. 5521 (0. 00) (0. 00) 13. 0309-10. 1430 (0. 00) (0. 00) 9. 8043 -6. 7162 (0. 00) (0. 00) 0. 0333 -0. 0129 -0. 0045 (0. 00) (0. 515) (0. 00) 0. 0312 0. 0219 -0. 0060 (0. 00) (0. 202) (0. 00) 0. 0419 0. 0100 -0. 0069 (0. 00) (0. 618) (0. 0) 0. 0623 0. 0001 -0. 0023 (0. 00) (0. 996) (0. 121) 0. 0452 0. 0201 -0. 0032 (0. 00) (0. 278) (0. 011) 0. 0421 0. 0362 -0. 0006 (0. 00) (0. 069) (0. 637) 0. 0330 0. 0184 -0. 0052 (0. 00) (0. 235) (0. 00) 73. 19 1102 75. 37 1190 66. 05 1341 71. 75 1440 66. 65 1498 72. 19 16447 422 AND C. M. C. LEE s. BHOJRAJ leverage (Lev) is not significantly correlated with EVS. Collectively, these results show that growth, profitability, and risk factors are incrementally important in explaining EVSratios, even after controlling for industry means. Note that the estimated coefficients on several of the key explanatory variables change systematicallyover time. For example, the estimated coefficient on the industry adjusted profit margin (Adjpm)and forecasted growth rate (Adjgro)both trend upwards over time, while the coefficient on the industry enterprise-value-to-sales ratio (Indevs) shows some decline in recent years. These patterns imply that, in forecasting future EVSratios, the estimated coefficients from the most recent year is likely to perform better than a rolling average of past years. In subsequent analyses, we use the estimated coefficients from the prior years regression to forecast current years warranted multiple. Table 4 reports the results of annual cross-sectional regressions for the PB ratio. The explanatory variables are the same as for the EVS regression in table 3, except for the replacement of Rnoa with Roe. Table 4 shows that all the variables except Lev contribute significantly to the explanation of PB. The coefficient on Indps is reliably negative. Otherwise, the variables are correlated with PB in the same direction as expected. Overall, the model is less successful at explaining PB than at explaining EVS. Nevertheless, the average adjusted r-square is still 51. 2%, ranging from a low of 32. 8% to a high of 61. 0%. FUTURE RATIOS 5. 2 FORECASTING Recall that our goal is to identify comparable firms that will help us to forecast a target firms future price-to-sales multiples. In this section, we examine the efficacy of the warranted multiple approach in achieving this goal. Specifically, we examine the relation between a firms future EVS and PB ratios, and a number of ex ante measures based on alternative definitions of comparable firms. The key variables in this analysisare defined below. EVSn and PBn, where n = 0, 1, 2, and 3-The current, one-, two-, and three-year-ahead EVSand PB ratios. These are our dependent variables. IEVS and IPBThe harmonic mean of the industry EVS and PB ratios, respectively. Industry membership is defined in terms of two-digit SIC codes. ISEVSand ISPBThe harmonic mean of the actual EVSand PB ratios for the four firms from the same industry with the closest market capitalization. and WPBThe warranted EVSand PB ratios. These variables are WEVS computed using the estimated coefficients from the prior years regression (tables 3 and 4), and accounting or market-based variables from the current year. COMPActual EVS (or PB) ratio for the closest comparable firms. This variable is the harmonic mean of the actual EVS (or PB) ratio of the four closest firms based on their warranted multiple. To construct this variable, WHO IS MY PEER? 423 TABLE 4 Price-to-Book Annual EstimationRegressions Warranted for This table reports the results from the following annual estimation regression: 8 PBi,t = at + E j=1 j,tCj,i,t + ti,t where the dependent variable, PB, is the price-to-book ratio as ofJune 30th of each year. The eight explanatory variables are as follows: Indevsis the industry harmonic mean of EVSbased on two-digit SIC codes; Indpbis the industry harmonic mean of the price-to-book ratio; Adjpm is the difference between the firms profit margin and the industry profit margin, where profit margin is defined as operating profit divided by sales; Losspmis AdjpmeDum, where Dum is 1 if profit margin 0 and 0 otherwise; Adjgrois the difference between the analysts consensus forecast of the firms long-term growth rate and the industry average; Lev is long-term debt scaled by book equity; Roe is net income before extraordinary items as a percent of book equity; and Rd is RD expense as a percentage of sales. The p-values are provided below each of the coefficients in parentheses. The last row represents the time-series average coefficients along with Newey-Westautocorrelation corrected t- statistics. The adjusted r-square (r-sq) and number of firms (# obs) are also reported. Year Intercept Indevs 1 982 -0. 2990 -0. 6056 (0. 00) (0. 00) 1983 -0. 3434 -0. 5129 (0. 00) (0. 001) 1984 -0. 1065 -0. 1806 (0. 143) (0. 099) 1985 -0. 3518 -0. 2882 (0. 00) (0. 09) 1986 0. 0998 -0. 3548 (0. 319) (0. 005) 1987 0. 0632 -0. 6468 (0. 584) (0. 00) 1988 0. 0568 -0. 5150 (0. 566) (0. 00) 1989 -0. 3306 -0. 5790 (0. 001) (0. 00) 1990 -0. 4592 -0. 9002 (0. 00) (0. 00) 1991 0. 0459 -0. 9010 (0. 613) (0. 00) 0. 1797 -0. 6645 1992 (0. 098) (0. 00) 1993 0. 2426 -0. 5925 (0. 111) (0. 00) 1994 -0. 0187 -0. 4753 1995 -0. 3095 (0. 008) 1996 -0. 0713 (0. 569) 1997 0. 1104 (0. 402) 1998 0. 0247 (0. 87) All -0. 0863 (0. 169) -0. 2491 (0. 00) -0. 3475 (0. 00) -0. 3565 (0. 00) -0. 3666 (0. 00) -0. 5021 (0. 00) Indpb 1. 1601 (0. 00) 1. 1696 (0. 00) 0. 9401 (0. 00) 1. 0448 (0. 00) 0. 9866 (0. 00) 1. 0956 (0. 00) 0. 8393 (0. 00) 1. 269 (0. 00) 1. 3508 (0. 00) 1. 0963 (0. 00) 1. 0051 (0. 00) 0. 7907 (0. 00) 1. 0234 0. 9481 (0. 00) 1. 0319 (0. 00) 0. 8816 (0. 00) 1. 0553 (0. 00) 1. 0321 (0. 00) Adjpm Losspm 2. 0331 -6. 2544 (0. 00) (0. 00) 3. 2891-11. 9301 (0. 00) (0. 00) 2. 0887 -5. 9880 (0. 00) (0. 00) 3. 0154 -8. 6571 (0. 00) (0. 00) 3. 6912 -6. 4419 (0. 00) (0. 00) 6. 0189 -9. 8553 (0. 00) (0. 00) 2. 0184 -9. 9218 (0. 00) (0. 00) 2. 6023-15. 3872 (0. 00) (0. 00) 1. 9280-10. 8096 (0. 00) (0. 00) 3. 0820-10. 7620 (0. 00) (0. 00) 3. 5272-12. 3146 (0. 00) (0. 00) 1. 6280-13. 7791 (0. 005) (0. 00) 3. 1253 -9. 8989 4. 3329 -9,7318 (0. 00) (0. 00) 4. 0730-13. 0282 (0. 00) (0. 0) 3. 8790-13. 5652 (0. 00) (0. 00) 3. 7902 -7. 1481 (0. 00) (0. 00) 3. 1837-10. 3220 (0. 00) (0. 00) Adjgro 0. 0371 (0. 00) 0. 1147 (0. 00) 0. 0527 (0. 00) 0. 0568 (0. 00) 0. 0883 (0. 00) 0. 0881 (0. 00) 0. 0694 (0. 00) 0. 0576 (0. 00) 0. 0815 (0. 00) 0. 0744 (0. 00) 0. 0781 (0. 00) 0. 0939 (0. 00) 0. 0834 Lev Roe -0. 2245 0. 0402 (0. 00) (0. 00) -0. 1545 0. 0541 (0. 01) (0. 00) -0. 2302 0. 0397 (0. 00) (0. 00) 0. 0585 -0. 2694 (0. 00) (0. 00) -0. 3075 0. 0542 (0. 00) (0. 00) 0. 0583 0. 0459 (0. 221) (0. 00) -0. 0675 0. 066 6 (0. 083) (0. 00) -0. 0474 0. 0574 (0. 176) (0. 00) -0. 0663 0. 0644 (0. 073) (0. 00) 0. 0683 -0. 1227 (0. 001) (0. 00) 0. 018 0. 0593 (0. 969) (0. 00) 0. 1131 0. 0828 (0. 02) (0. 00) 0. 1650 0. 0521 0. 0735 (0. 00) 0. 0649 (0. 00) 0. 0837 (0. 00) 0. 0674 (0. 00) 0. 0608 (0. 00) Rd 0. 0418 (0. 00) 0. 0627 (0. 00) 0. 0314 (0. 00) 0. 0013 (0. 845) 0. 0053 (0. 528) 0. 0323 (0. 001) 0. 0266 (0. 001) 0. 0111 (0. 122) 0. 0144 (0. 08) -0. 0052 (0. 477) 0. 0203 (0. 007) 0. 0468 (0. 00) 0. 0436 0. 0742 (0. 00) 0. 0147 (0. 133) 0. 0248 (0. 006) 0. 0341 (0. 00) 0. 0282 (0. 00) R-sq # Obs 55. 78 832 60. 99 57. 83 59. 15 56. 55 852 319 956 954 52. 97 1019 54. 15 52. 19 940 999 53. 16 1023 54. 88 1041 48. 51 1089 46. 82 1188 44. 96 1349 53. 52 1447 42. 76 1628 43. 00 1723 32. 2 1828 51. 18 19187 (0. 881) (0. 00) (0. 00) (0. 00oo)(0. 00) (0. 00) (0. 00) (0. 00) (0. 00) 0. 0908 0. 0409 (0. 284) (0. 00) 0. 1221 0. 1303 (0. 00) (0. 006) 0. 0948 0. 1596 (0. 00) (0. 00) 0. 0852 0. 2276 (0. 00) (0. 00) 0. 0805 -0. 0349 (0. 00) (0. 511) 424 s. BHOJRAJAND C. M. C. LEE we rank all the firms each year on the basis of their WEVS(or WPB), and compute the harmonic mean of the actual EVS (or PB) for these firms. ICOMPActual EVS(or PB) ratio for the closest comparable firms within the industry. This variable is the harmonic mean of the actual EVS (or PB) ratio of the four firms within the industrywith the closest warranted multiple. Essentially, this is the COMP variable with the firms constrained to come from the same industry. In short, we compute five different EVS (or PB) measures for each firm based on alternative methods of selecting comparable firms. IEVS and ISEVS(or, IPB and ISPB) correspond to prior studies that control for industry membership and firm size. The other measures incorporate risk, profitability, and growth characteristics beyond industry and size controls. We then examine their relative power in forecasting future EVS and PB ratios. As an illustration, Appendix C presents selection details for Guidant Corporation (GDT), a manufacturer of medical devices. This appendix illustrates the set of firms in the same two-digit SIC code, which are identified as peers of Guidant based on data as of April 30, 2001. Panel A reports the Panel B reports the closest firms based six closest firms based on WEVS, on WPB. We reviewed this list with a professional analyst who covers this sector. She agreed with most of the selections but questioned the absence of St. Jude Medical Devices (STJ), which she regarded as a natural peer. She agreed with our choices, however, after we discussed the profitability, growth, and risk characteristics of STJ in comparison to those of the firms listed. Table 5 reports the results for a series of forecasting regressions. In panel A, the dependent variable is EVSn, and in panel B, the dependent variable is PBn; where n = 0, 1, 2, 3, indicates the number of years into the future. In each case, we regress the future market multiple on various ex ante measures based on alternative definitions of comparable firms. 14 The table values represent the estimated coefficient for each variable averaged across 14 (n= 3) to 17 (n= 0) annual cross-sectional regressions. The bottom row reports the average adjusted r-square of the annual regressions for each model. These results show that the harmonic mean of the industry-matched firms explains 17. 5% (three-year-ahead) to 22. 9% (current year) of the crosssectional variation in future EVSratios. Including the mean EVS ratio from the closest four firms matched on size increases the adjusted r-squaresonly marginally, so that collectively IEVSand ISEVSexplain 18% to 23% of the variation in future EVSratios. These results confirm prior evidence on the usefulness of industry-based comparable firms. However, they also show that 14Even for the current year (n= 0), the warranted multiples are based on estimated coefficients from the prior years regression. Therefore, the models that involve warranted multiples are all forecasting regressions. TABLE 5 Prediction Regressions This table provides average estimated coefficients from the following prediction regressions: + EVSi,t+k = at + s j= j, tCji,t + I-i,t ES PBi,t+k = at + j=1 where k =0, 1, 2, 3. In Panel A, the dependent variable is the enterprise-value-to-sales ratio (EVS). I ratio (PB). The expanatory variables are: IEVS,the harmonic mean of the industry EVSbased on cur the harmonic mean of the actual EVS for the four closest firms matched on size after controlling for using the coefficients derived from last years estimation regressions and current year accounting and and ICOMP,the harmonic mean of the the actual EVS for the four closest firms matched on WEVS; after controlling for industry. The variables for Panel B are defined analogously, replacing EVSwith P coefficients from annual cross-sectional regressions. The bottom row reports the average adjusted r-sq Panel A: Enterprise-value-to-sales Currentyear EVS 0. 00 Inter 0. 24 0. 06 0. 00 0. 22 IEVS 1. 19 0. 08 -0. 27 -0. 26 1. 02 0. 16 0. 14 0. 16 0. 13 ISEVS COMP 0. 89 0. 16 0. 98 0. 83 WEVS 0. 33 ICOMP r-sq 22. 94 23. 46 54. 71 61. 68 62. 99 Panel B: Book-value-to-sales Current year PB 0. 07 -0. 06 -0. 07 Inter 0. 40 0. 5 IPB 1. 04 1. 19 0. 26 -0. 09 -0. 07 0. 07 ISPB 0. 16 0. 11 0. 10 0. 81 0. 35 COMP 0. 77 0. 71 WPB 0. 44 ICOMP r-sq 11. 80 12. 34 35. 21 41. 94 43. 20 One year ahead EVS 0. 01 0. 01 0. 07 0. 23 1. 05 0. 16 -0. 17 -0. 16 0. 14 0. 14 0. 12 0. 12 0. 83 0. 13 0. 80 0. 93 0. 27 21. 24 46. 14 51. 97 53. 23 One year ahead PB 0. 40 0. 15 0. 04 1. 00 0. 38 0. 12 0. 18 0. 14 0. 13 0. 65 0. 29 0. 59 8. 02 19. 91 22. 94 0. 24 1. 19 0. 27 1. 18 Two year ah 0. 0. 25 1. 06 0. 0. 0. 13 0. 20. 75 18. 37 18. 79 40. 0. 46 1. 17 0. 05 0. 12 0. 10 0. 51 0. 40 23. 38 0. 57 1. 16 Two year a 0. 50 0. 0. 96 0. 0. 0. 21 0. 7. 62 5. 01 5. 47 12. 426 S. BHOJRAJAND C. M. C. LEE he valuation accuracy of industry-based EVS ratios leaves much to be desired. In fact, industry-size based comparable firms explain less than 20% of the variation in two-year-aheadEVSratios. The predictive power of the model increases sharply with the inclusion of variables based on the warranted EVSratio (WEVS). average, a model that On includes IEVS,ISEVS,and COMPexplains over 40% of the cross-sectional variation in two-ye ar-ahead EVS ratios. Including WEVSin the model increases the average adjusted r-square on the two-year-aheadregressions to the actual WEVS ratio 45. 5%. Moreover, even after controlling for WEVS, of the closest comparable firms (COMPor ICOMP)is incrementally useful in predicting future EVSratios. It appears that comparable firms selected on the basis of their WEVS adds to the prediction of future EVSratios even after controlling for WEVS itself. COMPand ICOMPyield similar results. A model that includes IEVS,ISEVS,WEVS, ICOMPexplains between 63. 0% and (current year) and 43. 1% (three-year-ahead) of the variation in future EVS ratios. 5 Panel B reports forecasting regressions for PB. Compared to EVS,a much smaller proportion of the variation in PB is captured by these models. In the current year, the combination of IPB and ISPB explains only 12. 3% of the variation in PB. The inclusion of WPBand ICOMPincreases the adjusted r-square to 43. 2%. In future years, the explanatory power of all the models declines sharply. However, over all forecast horizons, models based on warranted multiples explain more than twice the variation in future PB ratios as compared to the industry-size matched model. The rapid decay in the explanatory power of the PB model is a possible concern with these results. Either PB ratios are difficult to forecast, or our model is missing some key forecasting variables. To shed light on this issue, we report below the serial correlation in annual EVSand PB ratios. Table values in the chart below are average Pearson correlation coefficients between the current years ratio, and the same ratio one, two, or three years later. Average Correlation Coefficient EVS1 EVSO PBO 0. 87 EVS2 0. 79 EVS3 0. 73 PB1 0. 72 PB2 0. 56 PB3 0. 44 These results show that with a one-year lag, EVSis serially correlated at 0. 7, suggesting an r-square of around 76%. With a three-year lag, EVSis serially correlated at 0. 73, suggesting an r-square of 53%. Similarly,with a one-year lag, PB is serially c orrelated at 0. 72, suggesting an r-square of 52%. With 5 We also conducted year-by-year analysis to examine the stability of these results over time. We find that a model that includes IEVS,ISEVS,WEVS, and ICOMPis extremely consistent in predicting future EVSratios. All four variables are incrementally important in predicting future EVSratios in each fore

Culture dependent vs culture independent methods Lab Report

Culture dependent vs culture independent methods - Lab Report Example 104). Some of the techniques that can be applied include, but not limited to performing rDNA PCR amplification on clinical specimens regarded sterile, such as blood. It is however advisable that this technique should not be employed with specimens originating from nonsterile sites such as faeces (Litton, 2010 p. 56). Collection of specimens such as conventional assays needs aseptic precautions. Litton (2010, p.57) claims that in order to curb contamination DNA brought by specimen collection vials, ensuring that the environment where work goes on is well organised also helps with this. Contamination linked to personnel working in the laboratory can be avoided by wearing cloves made of gloves or latex plus white coats. As for those contaminations resulting from consumable reagents and plastic wares, prior screening of each and every reagent before use in diagnostic assays (Litton, 2010 p. 56). 3. Find at least one peer-reviewed scientific research article regarding the bacteria that normally reside in the human mouth and provide references. Describe the groups of bacteria these studies identified to be present in the human mouth. Some of the bacteria that reside in the mouth include but not limited to, staphylococcus with the most common ones being S.epidermidis and S.aureus. They are oval in shape and posses a thick cell wall, named gram-positive. They cause infections in human population when presented with optimal conditions (â€Å"New bacterial species found in human  mouth† 2008, p.26). Bacteria from the genus streptococcus forms the largest number of all the organisms found in the mouth. Some of the species here include, but not restricted to, S. mutans, S. mitis, S. salivarius, S. pneumoniae and S. Pyogenes. They are also oval in shape like the staphylococcus. S.mutans is also responsible for cavity formation in teeth by converting sucrose sugar into lactic acid which

Court Report Criminal Essay Example | Topics and Well Written Essays - 1000 words

Court Report Criminal - Essay Example Paul’s Cathedral. The Old Bailey street would be on your left if you walk from Waterloo after crossing the Waterloo Bridge, turn right and keep going. It has two public gallery networks. Daily lists are in the notice board on the outside wall. Security is very strict so read the warning I have set out below. In Old Bailey Court you can wander in and out of dozens of courtrooms and see the most important judges like the Lord Chief Justice and the Master of the Rolls at work. Daily lists and lots of information are in the main hall (Anonymous, 2012). My Visit to the Central Criminal Court (â€Å"Old Bailey†) I went to visit a murder case at the Old Bailey criminal court on 3rd, October 2012 and followed the case again on 10th, October 2012. I went to court number 14 and sat in the public gallery where I was allowed to take notes about this case. In my first visit to the court on 3rd of October 2012, there was the cross examination of the Manzar Juma who was charged with m urder of Ruby Love. The prosecution was giving cell site evidence to the jury, and showing all the text messaging that was exchanged between Juma and deceased women Ruby Love. Prosecution gave copies of all relevant material such as text messages, mobile coverage and addresses to the jury as well as to the QC and counsel of the Mr Juma, both the judge and Mr Juma see all the copies and read them out one by one. Cell site evidence contained all the information regarding where Mr Juma was a day before the death of Ruby and all the text messaging that came along with all recorded times and the time of their conversation. It was heard that there were changing of unpleasant words you could say, that they were having an argument as such (Kelly and Camber, 2011). The judge seemed to have matters well under control in his courtroom and went on the legal proceeding moving forward expeditiously. The jury heard that on the day of Ruby’s death, where Juma was located and how he had two m obile phones that he communicated with Ruby and in one of the text messages he had arranged to pick her up (Darbyshire, 2011). On 29th of December 2011, police rang the phone number that they had found on the mobile of Ruby love and that number belonged to Mr Juma. Shortly after the cell site evidence the prosecution gave an indication and evidence of both Juma’s blood examination of any indication of drugs, and also Ruby’s blood evidence was read out (Hardiman, 2012). The forensic toxicologists’ examination showed that the blood of Ruby Love had traces of Methadone, heroin, Cocaine, Ecstasy pills, cannabis and alcohol. The blood of Mr. Juma was also examined and tested for alcohol and drugs and indicated that he had traces of basic drugs such as cannabis and alcohol in his blood. In addition to this, experts also gave evidence of Ruby’s body fluid. As the prosecution was finished giving his evidence, the QC of Mr Juma called Mr Juma to the stand and he w as asked many questions from his counsel (Kirk, 2012). The prosecutor provided a big contrast to the defence attorney. Mr Juma said that he did not have a very good relationship with his father, and only saw him up until he was 15 years old. He denies murder. His QC asked him whether he had any trouble at school whilst growing up, and he replied, yes he did, from the moment he found out that his mother had tumour and he became very angry and upset, therefore he did not do very well at

Islam or Shariah Law Essay Example | Topics and Well Written Essays - 250 words

Islam or Shariah Law - Essay Example Islam or ‘shariah’ law governs under the Islamic code mentioned in the Quran and Hadiths.   It is supposed to be the legal and moral code for every Muslim, comprising of religious matters financial positions and every day issues. Since the instigate of the 21stcentury many Muslim countries including Malaysia, Indonesia morocco and Pakistan, encouraged and responded to democracy and voiced their opinions of it being a much better system to govern countries. Whether the current sociopolitical and cultural settings are compatible with the ‘shariah’ law is the main point which plagues many Muslim men and women. The difficulties faced by Muslims all over are due to the confusion over the legal systems i.e. whether to follow the Islamic mode of punishment or to follow the state; whether the correct method of trade is the Islamic way (free of credit) or to follow the commercial and state policies. There have always been debates over the judicial system whether as to give harsh punishments or let the constitution decide? The debate goes on between political leader and scholars. Some Muslimscholarsbelieve that the amalgamation of ‘shariah’ laws in the legal system of a country is the best way to actually observe the Islamiclaws. One example of this is the fact that polygamy is punishable in several countries, but allowed by Islamic law. In India cows are considered sacred but they are part of the Islamic sacrificial ritual of Eid where they are slaughtered. These are situations where a Muslim cannot act based on his religion alone and has to consider the state laws first. The reaction of â€Å"secularizingIslam† has not always been a pretty sight. Just last year the Archbishop of Canterbury   was fiercely scrutinized by the Government and the political circle, his own Church and other religions after he supported the adoption of a few ‘shariah’ laws in the British system.While some British Muslim scholars ig nored it saying it will not and does not have enough votes by the community. The main point is that most nations support secular systems which are not compatible with Islamic law. The fact that the Archbishop was so heavily criticized shows that the majority in these nations do not support any such laws either. Muslims are therefore stuck in a situation where they must choose whether they wish to conform to the state law or follow their own.

Violence in the Workplace Essay Example | Topics and Well Written Essays - 750 words

Violence in the Workplace - Essay Example In 2008, Roy observed that workplace violence was assuming great importance for modern businesses. Quoting the U.S. National Institute for Occupational Safety and Health, he observes that on an average working day, 3 people are murdered on the job, 1000000 workers are assaulted and more than 1,000 are murdered every year in the U.S. According to the Labor Department, killing at the work place is the second major contributor to death on the job after road accidents. Statistics show that 111,000 incidents of work-place violence cost employers and others an estimated 6.2 million in 1992. With the issue of violence at the workplace gaining higher attention, many state bodies are coming together to combat this social threat. The 9/11 attacks gave a completely new perspective to violence at the workplace. The incident made the world wake up to the fact that a threat need not be limited to workers only, but could also be in the form of terrorists attacks from outside the workplace. The FBI's National Center for the Analysis of Violence Crime (NCAVC), Critical Incident Response Group (CIRG), coordinated with a select group of experts from law enforcement, private industry, government, law, labor, professional organizations, victim services, the military, academia, mental health, and CIRG's Crisis Negotiations Unit in 2004 and discussed the problem at length. "Workplace Violence: Issues in Response," a document detailing the duties of an employer, employee, the role of the state has been the written outcome of this effort. While there are no written rules about hiring or verifying the credentials of a prospective employee, the agencies have advised employers to exert utmost care in recruiting new people. Also, while businesses are bound by law to safeguard the employees' welfare and security under the Occupational Safety and Health Act, they can in no way guarantee complete safety for the employees from external threats. They can at most ensure that the workplace is "free from recognized hazards " in accordance with the "General Duty Clause." . To properly implement the civil rights requiring employers to protect employees from various forms of violence, it becomes essential fro the employers to pay extra attention to each employee's activities within and outside of the workplace. However, keeping a tab on such activities might lead to issues of privacy, defamation and discrimination against some employees. Not only while hiring, but also while firing employees, organizations have to be very careful th at the disgruntled employee doesn't become a threat to the company. As discussed in the paper, sometimes laws meant to protect an employee's rights become an obstacle in ensuring the employer's rights. The American Disabilities Act might prove a hurdle for an employer if the concerned person shows signs of being a threat to the company, but is not ready for counseling. Thus, while we can safely conclude that instances of violence at the workplace are increasing at a rapid rate, organizations have to be prepared for any kind of emergency. While hiring new people, they should also keep in mind the past records of the employee and take hints

Sexuality in Islam Essay Example | Topics and Well Written Essays - 1250 words

Sexuality in Islam - Essay Example Allah has described very dreadful punishments both in this world and in the world hereafter for the people who practice homosexuality. Allah says in the Quran, â€Å"What! Of all creatures do ye come unto the males, and leave the wives your Lord created for you? Nay, but ye are forward folk† (Qur'an 26:165 cited in â€Å"Islam and Homosexuality†). The people of Hazrat Lut (P.B.U.H.) practiced homosexuality. They practiced it both indoor and in the public. Prophet Lut (P.B.U.H.) repeatedly told them to stop this practice, but they would not listen, thus inviting the wrath of Allah and one day, those people were all destroyed together by Allah. Islam condemns homosexuality because it has myriad evil consequences. Homosexuality distorts the family system and deprives people of their gender traits. Islam allows the man to marry no more than four women at one time. Polygamy has been practiced by a lot of prophets in the history of Islam. Prophet Abraham, Prophet Moses, Proph et Jacob, and the Prophet Solomon had three, two, four, and 700 wives respectively (â€Å"An Introduction to Polygamy†). Critics say that if man is allowed to keep four wives at one time, the woman should also be allowed to keep up to four husbands at one time. But polygamy is in no circumstances allowed for the women in Islam. This makes sense. When a man marries four women, the child any of the wives would bear would be certainly his. On the contrary, when a woman makes love with more than one man at a time, there is no certainty in the child’s belongingness to a particular man unless the child is genetically tested. In addition to that, women generally outnumber men. Thus, when a man marries more than once, more women are likely to get married in their life than otherwise. Although polygamy for men is allowed in Islam, yet it is not practiced equally in all Islamic countries. Polygamy is so well-practiced by the Muslims in the Arabia, that it has also become a cultu ral trait. Polygamy is so ingrained in the Arab culture that a man keeps all the wives in the same home but in different rooms. In many Muslim countries including India and Pakistan, women cannot stand another wife of their husband. They cannot share their husband’s love with another woman. This is the reason why practicing polygamy for a Muslim man in these counties exposes him to a lot of cultural and social issues, though he is religiously justified as long as he does justice to all of the wives. There is a very sheer population of Muslim men in India and Pakistan that have more than one wife at the same time. This is purely a cultural issue. In these countries, women cannot even bear a look of their husband’s wife, what to talk of living in the same home like the Arabian women do. It is noteworthy that while Islam allows the man to keep up to four wives at one time, Islam also obliges the man to do justice to each of the four. This essentially means that a man has to distribute equal amount of money, time and assets among the wives. If a man has two wives and he lives with one more than the other, he is doing injustice and will be held accountable for his actions on the doom’s day. There are no age restrictions in marriage in Islam. A man can get married to an elder woman and so can a woman. Prophet Muhammad (P.B.U.H.) was only 25 years old when he was proposed by Hazrat Khadija (P.B.U.H.) who was 40 years old at

The critical race theory Essay Example | Topics and Well Written Essays - 1250 words

The critical race theory - Essay Example However, white privilege is dissimilar from conditions of extreme vestiges of racism and/ or prejudice, whereupon the predominant race actively finds it rational to oppress other racial tribes for their own gain. Similarly, theories of white privilege stipulate that the whites perceive their social, economic and cultural knowledge as a custom that everyone should experience, as opposed to a merit that should be kept at the expense of others (5-9). This normative discernment unreservedly restrains the discourse of racial dissimilarity within the predominate discussion. Ideally, such interpretations are limited certain particulars which are detailed to downgraded racial groups. These disadvantaged groups are assumed as having failed to realize the norm. Ironically, the resort concentrates on what should be done with a view to helping those racial groups accomplish the normal principles experienced by whites (Stefanic 22-24). Stefani argues that the theories of privilege affirm discussi ons on racial dissimilarity do not genuinely discuss variations between Non-white and whites social status. Come to think of it, these theories only converse about the malfunction of non-white racial groups to accomplish normal white status. This supposition on the hand turns the subject of race into a problem which doesn’t involve white racial groups (12-14). Racialization of individuality and ethnic downgrading of blacks and the colored formed the basis for ideological slavery and subjugation. Whiteness satisfies the expansive ideas of property as illustrated by classical theorists. Granted, whiteness stipulated the legal position of a person as free or a slave. White individuality awarded corporeal and valuable privileges. Ownership of property included the privileges of use and enjoyment. If these privileges were essential characteristics of property, it was the individuality of whiteness that had to enjoy them. Whiteness was perceived as an aspect of individuality and pr operty significance because it is something that can be experienced and dispatched as a resource (Stefanic 133-137). The United States is the patron of race subornation. In this context, the dominion of legal associations, judicial explanation of racial individuality primed on the white supremacy replicate that race underestimation at the institutional level. By metamorphosizing white into whiteness, the law disguises the ideological aspect of racial interpretation. The overall assertion of theories of white privilege is that the lack of racial equality can’t be determined only by looking at the life circumstances of the underprivileged groups. In this context, they thus state that imperative solutions to the viable challenges of lack of racial equality can be accomplished by overtly talking about the inherent merits that whites as a privileged racial group uphold in the community (Stefanic 77-76). According to Stefanic in the period of nineteenth century, the retinues of whi te laborers, while they were reimbursed relatively minimal wages, were remunerated in general through a public and psychological wage. These white laborers were also accorded public distinction and titles of honor since they were simply white. They were acknowledged unquestionably well with all other groups of white people of to best public schools, public places, and or public functions. Some of them were recruited into the American police. Additionally, these groups of people were treated with laxity by the American courts with a view to encouraging lawlessness. Besides, they freely voted for American public officials (185-188). However, this had

Marketing Strategies of Starbucks Coffee Company and Caff Nero Group Essay

Marketing Strategies of Starbucks Coffee Company and Caff Nero Group Ltd - Essay Example As the report declares the business of marketing strategy is to influence the decision of the customers towards a product. Marketing strategy therefore focuses much on building a strong customer base that eventually translates into increased profit margin for the customers. Having conducted a proper marketing research and conceiving the findings, marketing strategy then take effects. At this stage, the precursor of marketing strategy is the marketing plan which gives a structural breakdown of how the strategy will be rolled and the avenues to be explored when reaching the prospective customers effectively and efficiently with the least cost possible. A marketing plan considers what is popularly known as four Ps i.e. product, price, place, and promotion. This information assists in devising a proper marketing strategy. This paper stresses that marketing strategy is one of the most important inputs any business should endeavor to engage in however big or small the business may be. Unfortunately, most businesses are always hesitant to actively do appropriate marketing strategy simply because they do not understand the contribution of the same in business. It is obvious that for a business to thrive and grow exponentially in terms of building and restoring the customer base there has to be an aggressive marketing strategy that will be beneficial to the business. It is rated that Caffà ¨ Nero Group Ltd is position three in UK this is after Whitbread Group's Costa Coffee and Starbucks. The company enjoys a significant number of outlets to the tune of 420 which has spread to

Disaster Rehabilitation Complex Essay Example for Free

Disaster Rehabilitation Complex Essay Bamboo Hybrid Building Construction Material Foldable emergency houses through Bamboo Hybrid Building Construction Material. A revolutionary way of construction where the bamboos are being combined with structural Bolt Ball steel to act as struts (replacing the steel/aluminium material) and form as a structural joints to achieve stability and flexibility. Together with Contex-T: textile architecture, a fiber reinforced structural element that will act as the roofs and walls which provide good insulation, maximum flexibility in design and maximum mobility with a short construction period; and Liter of Light: soda bottle solar light, an innovative invention that will turn a soda bottle into a 50-60 watts light bulb during the day, which will be attached customarily to the bamboo struts in different areas of the foldable houses. -source; Building with Bamboo by Gernot Minke; WHAT IS THE PROJECT ABOUT? DESCRIBE. (STATEMENT OF USE/FUNCTION AND PURPOSE OF THE BUILDING BASED ON NBC) Philippine Red Cross Disaster Rehabilitation Complex: An Evacuation and Rehabilitation Facility under, Group D – Institutional (Government and Health Services) Division-1 No. 4 Principal use of The 2004 Revised IRR of P.D no. 1096 (as published by the DPWH), dedicated for the disaster and calamity victims, and also will become the new headquarters of   Red Cross; a development that will change the image of unsystematic and unorganized evacuation center in the Philippines that aims to educate people in their condition during calamities while providing them a complete set of recreational, medical, educational, conventional and administration facilities dedicated for their fully rehabilitation directly from Philippine Red Cross, while eliminating the issue of politics and providing an immediate response during and after the calamity. A formal evacuation center in the Philippines that can cater a huge amount of evacuees while providing them comfort, care and medical attention and a comfortable emergency houses through Bamboo foldable houses, where a locally found bamboo’s are being modified and turn it into a unique hybrid construction material where it is incorporated with structural bolt steel and organic fiber reinforced textile material that can provide a recyclable, flexible, and a faster installation while reducing the cost and maintaining the stability and the proper standards for an emergency houses. LOCATION (OPTIONAL) Tent City of Tacloban Marcos Highway cor. Amang Rodriguez Ave., Barangay Dela Paz, Pasig City. TARGET USERS: PRIMARY:Evacuees and victims of disaster and calamities SECONDARY:Volunteers Doctors Medical Staff’s TERTIARY: People in needs of medical assistant Security personnel Donors Visitors NO. OF USERS: (approximate no.) 100,000 Families OWNER(S) OR CLIENT(S): Philippine Red Cross PROJECT OBJECTIVE(S) OF THE OWNER (WHY IS THERE A NEED FOR THE PROJECT?) 1. To erase the image of the Philippine’s chaotic evacuation center 2. To provide new Headquarters of Philippine Red cross that will become a center of their public service and donations 3. To educate and raise the awareness of the people to the Emergencies, Calamities, and Disasters 4. To help people recover from their condition, in a faster service with a complete facility dedicated for them. 5. To reduce the health casualties occurring in the un-organized evacuation center. BUDGET/FINANCING SCHEME: The amount of financial funds will be according to the donations collected by the Philippine National Red Cross from the different organizations of the Government especially From Department of Interior and Local Government (DILG) and National Disaster Risk Reduction Management Council (NDRRMC) and from private sectors and individual charitable donations. Structural3,000 per square meter Electrical and telecoms1,000 per square meter Sanitary 2,500 per square meter Sprinkler1,000 per square meter Mechanical1,500 per square meter Architectural 5,000 per square meter Emergency houses550,000 (estimated cost of bunk houses of government) Note: the cost of land acquisition for the site is not yet included in the above mentioned costing.

Plan for Hydrogen-Powered Vehicles Entering Hong Kong Markets Essay Example for Free

Plan for Hydrogen-Powered Vehicles Entering Hong Kong Markets Essay Introduction Nowadays, the problem of global warming and greenhouse effect has raised concern all over the world. During energy generation, Fossil fuel releases large amount of chemical substances that exacerbates the problem. However, nowadays, there is still a great dependence on fossil fuel for generating energy in Hong Kong. To overcome the problem, hydrogen fuel is an opportunity for our society to minimize the environmental effects, enhance energy security, and the sustainability of global energy resources. In addition, many countries have been promoting the environmental protection at present. Therefore Hong Kong is not the exception. Our company – Ford has decided to introduce the hydrogen powered vehicle to Hong Kong by exporting from a car factory in United State and promote it to local citizens. In the following, various analyses including PESTLE analysis, marketing strategies, market entry modes, international operation management, and hiring and employee management will be illustrated. The Political, Economic, Socio-cultural, Technological, Legal and Environmental dimensions Political The Hong Kong Government has introduced some policies in promoting low air pollutants emitted transport. Firstly, tax Incentives for environmental friendly vehicles is provided. A 45% reduction in the first registration tax, subject to a cap of HK$75,000 per car, will be offered to buyers of newly registered environment-friendly cars. In addition, the government also encourages trial of green and low-carbon transport technologies. The Government has set up a $300 million Pilot Green Transport Fund for application by the public transport trade and goods vehicle owners. For vehicles, the subsidy level is the price premium between the alternative-fueled vehicle and the conventional vehicle or 50% of the cost of the alternative-fueled vehicle and 50% of the setting up cost of the related support facilities. The policies give lots of incentives to the users to transfer their car to the hydrogen powered one. Economic Hong Kong is a developed and affluent country. According to the statistic of Census and Statistics Department, in the second quarter of 2012, the Hong Kong Gross Domestic Product for is $473,171 million. And the private consumption expenditure increases by 3. 1% in the real term. The per capita GDP is $273,657 million in 2011. Moreover, there is about 55% of population belong to the middle class (people who receive income above median). The family monthly income is also rated 17 thousands to 30 thousand. It reflects that the hydrogen powered vehicle is affordable to the upper and middle class. Hong Kong is a high potential market for our product. Socio-cultural Hong Kong people are highly educated with a strong perception of environmental protection. With the rising environmental promotion from the government, the awareness of green concept is becoming popular gradually. Firstly, citizens promote going green in order to alleviate the air pollution problem. Secondly, a higher living standard can be achieved with improved air quality. Thirdly, our product promotes the use of renewable energy. Thus it helps solving the problem of energy shortage. Our product will attract local citizens with high environmental awareness. Technological The infrastructures and facilities in Hong Kong are well developed such as Tseng Ma Bridge, and Kwai Tseung Container Terminal is the third busiest port in the world since 2007. The fast and efficient shipping and delivery of the vehicles are supported. Moreover, businesses can obtain technical consultation and professional backup from science parks and the prestigious universities in Hong Kong. For instance, Hong Kong Science Park, Cyber Port, and the University of Hong Kong are well-known. Legal It is lawful to employ the hydrogen car in Hong Kong. Although people sometimes argue that hydrogen cars exist dangerous, we still believe that it will not happen nearly if we can control the quantity of hydrogen we use in cars. We will also set the knock sensor systems in the car to reduce the probability of knock occurrence and the impacts. Europe has just legitimate hydrogen cars and there are not any local laws said that is illegal in Hong Kong. Besides, as the fuel of the hydrogen powered vehicle is not fossil fuel anymore but replaced by hydrogen. Selling and buying large amount of hydrogen is legal in Hong Kong allowing the users to refuel. Environmental Distribution of Hourly API for General Stations for the period October 2012 | | Legend| | API| Percentage| | Severe (201-500)| 0. 00 | | Very High (101-200)| 0. 08 | | High (51-100)| 65. 23 | | Medium (26-50)| 34. 59 | | Low (0-25)| 0. 10 | | | According to the above table, the API for general stations is mainly at medium to high level but more at the high level (65.23%). Serious air pollution is a considerable problem in Hong Kong. Heavy traffic has contributed to the deterioration of the problem. The problem has been negatively affected not only physical health of local citizens, but also the tourism. According to the research from Civic Exchange, there are 90% interviewees, who are Hong Kong citizens, are caring about the issue of air pollution. Besides, the percentage of air quality dissatisfaction raised dramatically compared to 2001. The hydrogen powered car, which will help relieve the problem, will gain support from local citizens. This is an opportunity for our company to introduce hydrogen powered car to Hong Kong. The Market Entry Mode The market entry modes in Hong Kong are Foreign Direct Investment and exporting. Ford will set up a subsidiary to manage the businesses and also establish a specialty shop to promote and sell the hydrogen powered car. The hydrogen powered vehicle will be exported from the plant in China to the store in Hong Kong. Our firm undertakes FDI because of the combination of location advantage, ownership advantage, and internalization advantage. Location advantage Hong Kong has a comprehensive transportation network such as port and flexile highway which is beneficial for exporting the vehicles to Hong Kong. The advanced telecommunication also drives down the cost in communicating with the factory and the consumer. On the other hand, Hong Kong has a number of tax incentives under special arrangements on the Mainland. The key areas, including shipping, aviation, land transport and personal tax, can be exempted from double taxation and enhance the profitability of our firm. Ownership Advantage Ford has a strong brand name with the perception of good reputation and excellent performance of the vehicles in the consumer’s mind. It is useful and easily for promoting the vehicles in Hong Kong in order to gain more sales volume and increase the market share. In addition, our firm also possesses the hydrogen power technology outperforming with its competitors. It is a necessary part for the manufacturing and assists fighting in the keen and saturated competition of fossil fuel-powered automobiles. Internalization Advantage. As hydrogen-powered car is a new market in Hong Kong, Ford can gain a high market share by firstly introducing the car into the new market. Besides, the firms emphasizes on high standard of customer service, there will be better controlling by serving customers by ourselves rather than hiring an independent local company to offer it. For example, there is more clearly explanation and illustration to the queried customers by our experienced staffs. Marketing Strategy of hydrogen powered vehicle Product The factors Hong Kongs business environments have to be considered for the product strategy. For the national image, the brand name of Ford brings good reputation and excellent quality to the consumer’s mind. Consumer has confidence in purchasing our company manufactured vehicles that helps us to enter the market. In addition, hydrogen power is a complicated technology that is difficult to copy that prevents the creation of counterfeit goods. Place Our established specialty shop is responsible for consulting service and selling the hydrogen powered vehicle to the customers. Our distribution network is relatively short (manufacturer, specialty store, customers) to maintain a greater control over the planning and implementation. There is only an exclusive channel – owned specialty in the distribution channel in result of shorter channel length. It saves the cost of owning one store instead of having lots of intermediaries in the distribution channel. Price The pricing strategy our firm used is dual pricing that different selling price abroad than at home. As our firm adopts the differentiation strategy, we set the price based on the Hong Kong buyer’s value as well as the living standard. This method overcomes the problem of exchange rate and fits the local purchasing power which also increases our profitability for selling the vehicles. Promotion As our market and product are both new so that production invention of marketing communication strategy is used. Our firm is going to advertise on the famous car magazines and car forum to promote the new product launch. This can raise the car users’ awareness of this new product. Besides, our firm is going to use Public Relation tools for promotion. Celebrities will be invited to experience the hydrogen-powered vehicle before the product launch. Then the feedbacks or recommendations from the celebrities will create a world-of-mouth effect, as well as buzz in the entire society. Managing International Operations Production Strategy The production strategy of Ford hydrogen powered car is focus differentiation which aims to provide the hydrogen-powered car to the market of environmental friendly private car users. Facilities location Planning Besides, Ford adopts the location economies of the facilities location planning. The company produces the car in its largest production location in the United State. The production location offers sufficient technologies and experienced technical staffs and engineers required to produce the hydrogen-powered vehicle. Although the labor costs in developed countries must be relatively higher compared to some developing countries such as China, there are better quality control and productivity through utilizing the experienced labors and the local advanced machines in Germany. Moreover, the distance factory – United State to the market – Hong Kong is also relatively longer, but the transportation facilities and infrastructures are mature in both countries. For example, the seaports are available for the transportation. The company can deliver the car by water carriers in order to enjoy lower shipping cost to cover the high unit cost. JIT Manufacturing In order to further reduce its high manufacturing cost, Ford adopts the Just-In-Time manufacturing system decreasing its inventory costs. The inputs including the raw materials, component parts, and sub-assemblies can be minimized because those input are delivered as the factory receives the orders from the dealer in Hong Kong for the production process. The reduced cost not only gives the company higher profit margin, but also offers the product with a more acceptable and affordable price for the consumer in Hong Kong. Furthermore, as the hydrogen-powered car is not very common and popular in most cities, the demand is relative small and uncertain. JIT system can assist the company to avoid holding too much inventories and creating wastes which are costly. Hiring and Managing Employees Staffing Policy For recruiting the top managers in Hong Kong subsidiary, Ethnocentric Staffing is used that the top managers are from home country – United State as they understand the hydrogen-powered car project more clearly and own sufficient information and knowledge to handle the whole operation in Hong Kong more efficiently and effectively. It will also result in better planning in both short term and long run that gives a much more clear direction to the subsidiary. For employing the middle managers and non-managerial workers, geocentric staffing will be used to select the best-qualified individuals, regardless of nationality. Compensation of Managers Ford gives some compensation to the expatriate managers including cost-of-living effects and bonus and tax incentives as well. The company should not only make up the local goods and services differential, but also have to give the bonus and tax incentive to convince the top managers staying abroad longer. Moreover, the firms also should provide language training and sensitivity training to the oversea managers to better the ability of bridging cultural differences and living in foreign country. Labor-Management Relations Maintaining a strong relationship between managers and workers is extremely essential because it is affecting the productivity as well as cost. Workers should be constantly motivated to enhance their productivity by offering more deserved outcomes such as pay, benefits, and vacation time. Besides, badly treated employees may leave the organization if they have other employment options which cost an expensive hiring and training cost especially the experienced technical staffs. Therefore, Ford can collect the opinions and feedbacks from the employees as well as solve their problems through the labor union in order to boost the relationship. For example, the labor representatives can participate in high-level company meeting by actually voting on proposed actions. Conclusion To sum up, our company is confident of entering the Hong Kong market with the hydrogen powered vehicle through the above supportive analyses. The constructive marketing strategy will help firm to promote the vehicle more effectively. Furthermore, the effective and efficient international operation management and the human resource management will bring the success to become the market leader not only in Hong Kong. In the future, the hydrogen powered vehicles will be promoted in different parts of the world in order to maximize the profitability. References 1. Statistics of Middle Class population http://www. gov. hk/sc/about/abouthk/factsheets/docs/population. pdf 2. Statistics of income median and GDP http://www. hkcna.hk/content/2011/1031/118642_2. shtml http://www. censtatd. gov. hk/hkstat/sub/so50_tc. jsp 3. Hong Kong environmental policies http://www. epd. gov. hk/epd/tc_chi/about_epd/env_policy_mgt/env_policy. html 4. An overview of air quality in Hong Kong http://www. epd. gov. hk/epd/tc_chi/environmentinhk/air/air_maincontent. html http://www. epd. gov. hk/epd/tc_chi/environmentinhk/air/studyrpts/air_studyrpts. html 5. The public has the awareness and knowledge of environmental protection http://net2. hkbu. edu. hk/~enews/view_article. php? id=13430 http://www. info. gov. hk/gia/general/199902/23/0223epdc. htm.