Gate log system using rf-id reader

Chapter oneGATE LOG SYSTEM USING RF-ID READER1.1 What is RFIDShort for wireless frequence designation, RFID is a dedicated short scope communicating ( DSRC ) engineering. The term RFID is used to depict assorted engineerings that use wireless moving ridges to automatically place people or objects. RFID engineering is similar to the saloon codification designation systems we see in retail shops everyday ; nevertheless one large difference between RFID and saloon codification engineering RFID does non trust on the line-of-sight reading that saloon codification scanning requires to work. 1.2 Why RFIDIn an progressively disconnected, regulated, and unsure universe, Texas Instruments ‘ ( TI ) RFID engineering gives concerns, authoritiess, and consumers a safe, private, and unnoticeable manner to maintain path of it all. Consumers benefit from shorter lines at check-out procedure counters, in infirmaries, libraries, and gas Stationss because RFID fast-tracks them to the forepart of the waiting line. They can besides profit from lower monetary values because of the efficiencies RFID brings to the supply concatenation. Business and establishments are turning to RFID engineering as they comply with authorities product-tracking ordinances, seeking to restrict larceny, cut down out-of-stock losingss, strengthen trade name trueness, and do interaction with clients a more positive experience. RFID is a mature, exhaustively tested engineering. In most RFID applications, the period of tests, proving, and economic feasibleness surveies is over. Large-scale RFID system rollouts are underway. 1.3 RFID Application OverviewThere are about as many RFID applications as there are concern types. Titanium has established a leading place in these basic classs:Automotive– Auto-makers have added security and convenience into an car by utilizing RFID engineering for anti-theft immobilizers and passive-entry systems.Animal Tracking– Ranchers and farm animal manufacturers use RFID engineering to run into export ordinances and optimise farm animal value. Wild animate beings are tracked in ecological surveies, and many pets that are tagged are returned to their proprietors.Asset Tracking– Hospitals and pharmaceuticss meet tough merchandise answerability statute law with RFID ; libraries limit larceny and maintain books in circulation more expeditiously ; and athleticss and amusement enterprisers find that â€Å" smart tickets † are their ticket to a better underside line and happier clients.Contact less Payments– Blue-chip companies such as American Ex press, Exxon Mobil, and MasterCard use advanced signifier factors enabled by TI RFID engineering to beef up trade name trueness and encouragement gross per client.Supply Chain– WalMart, Target, BestBuy, and other retail merchants have discovered that RFID engineering can maintain stock lists at the optimum degree, cut down out-of-stock losingss, bound shrinkage, and velocity clients through check-out lines.About from the beginning, TI was there: assisting set up criterions ; back uping the RFID supply concatenation of inlay and label makers ; and systematically using leading-edge semiconducting material engineering to the nucleus of RFID, the transponder. 1.4 Why this undertaking is of importWhat we are be aftering to make is a gate log system based on the new engineering which is the RF-ID READER, the user will hold a CARD that will let him to come in the gate, when he acquire near to the gate the receiving system will observe the card and read the informations stored on the card wirelessly by mean of the rf-id reader. The microcontroller on the receiving system will read the informations from the RF-ID reader and if the user is allowed to come in the microcontroller will give the signal to open the motor ( gate ) .else a message will look on the LCD and the motor will non open. An of import portion of our undertaking is the Personal computer interfacing so all of the operations and the event will be displayed on a log tabular array. 1.5 System block diagram: –The chief constituents that will be usedmovie microcontroller ( pic16f876A )DC-motor ( little motor for simulate open/close )Consecutive interface bit ( this bit will manage the electromotive force degrees between the microcontroller and the personal computer )RF ID-readerH-bridge this is a will known circuit which have two inputs from the microcontroller to drive the motor clock wise or counter clock wiseLCD ( liquid crystal show ) that will be used to expose the user figure and any coveted notes such as ( non known user )1.6 Features that leads to take ID-12d as the rf-id reader for this undertaking:It requires 5V supply ( it can be supplied from the same supply as movie )125kHz read frequence ( compatible with most sorts of releasing factor cards )EM4001 64-bit RFID ticket compatible9600bps TTL and RS232 end product ( can be connected straight to pic microcontroller utilizing the usart faculty )100mm read scope ( good reading distance )1.7 Method of operationThe end product of the rf-id reader is consecutive which will be connected straight to pic microcontroller, when the reader detects any rf-cards in scope it will read it and direct the ruddy informations ( 64-bit ) serially, the microcontroller will have those bytes and hive away them in a twine, so it will compare whether this Idaho is existed or non, this action will be displayed on the liquid crystal display. If the user is allowed to come in the gate so the microcontroller will publish the bid to the h-bridge to open the dc_motor, wait certain clip so publish the shutting bid. Besides the microcontroller will direct the information to the personal computer ( serially ) to be stored in a log tabular array Needed packagemikrobasic compiler, this will be used to compose the codification for the microcontrollerocular basic.NET, this package will be used to compose the plan that will have the information from the microcontroller and show it on a tabular array.

The Usefulness of Accounting Estimates for Predicting Cash Flows

The Usefulness of Accounting Estimates for Predicting Cash Flows and Earnings Baruch Lev* New York University Siyi Li University of Illinois Theodore Sougiannis University of Illinois and ALBA January, 2009 * Contact information: Baruch Lev ([email  protected] nyu. edu), Stern School of Business, New York University, New York, NY 10012.The authors are indebted to the editor and reviewers of the Review of Accounting Studies for suggestions and guidance, and to Louis Chan, Ilia Dichev, John Hand, James Ohlson, Shiva Rajgopal, and Stephen Ryan for helpful comments, as well as to participants of seminars at Athens University of Economics and Business, London Business School, Penn State University, Purdue University, University of Illinois at Urbana-Champaign, University of Texas at Dallas, Washington University in St.Louis, the joint Columbia–NYU Seminar, the 16th Financial Economics and Accounting Conference, the 2006 AAA FARS Midyear Meeting, and the 2008 AAA Annual Meeting. 1 ABSTRACT Estimates and projections are embedded in most financial statement items. These estimates potentially improve the relevance of financial information by providing managers the means to convey to investors forward-looking, inside information (e. g. , on future collections from customers via the bad debt provision).On the other hand, the quality of financial information is compromised by: (i) the increasing difficulty of making reliable forecasts in a fastchanging, often turbulent economy, and (ii) the frequent managerial misuse of estimates to manipulate financial data. Given the ever-increasing prevalence of estimates in accounting data, whether these opposing forces result in an improvement in the quality of financial information or not is among the most fundamental issues in accounting. We examine in this study he contribution of accounting estimates embedded in accruals to the quality of financial information, as reflected by their usefulness in the prediction of enterpr ise cash flows and earnings. Our extensive out-of-sample tests, reflecting both the statistical and economic significance of estimates, indicate that accounting estimates beyond those in working capital items do not improve the prediction of cash flows. Estimates do, however, improve the prediction of next year’s earnings, though not of subsequent years’ earnings. Our economic significance tests corroborate that accounting estimates do not improve cash flow or earnings prediction.We conclude that the usefulness of accounting estimates to investors is limited, and provide suggestions for improving their usefulness. 2 The Usefulness of Accounting Estimates For Predicting Cash Flows and Earnings 1. Introduction Financial statement information, be it balance sheet items such as net property, plant and equipment, goodwill and other intangibles, accounts receivable and inventories, or key income statement figures, such as revenues, pension expense, in-process R&D, or the rec ently expensed employee stock options, is largely based on managerial estimates and projections.The economic condition of the enterprise and the consequences of its operations as portrayed by quarterly and annual financial reports are therefore an intricate and ever changing web of facts and conjectures, where the dividing line between the two is largely unknown to information users. With the current move of accounting standard-setters in the U. S. and abroad toward increased fair-value measurement of assets and liabilities, the role of estimates and projections in financial reports will further increase.We ask in this study: what is the effect of the multitude of managerial estimates embedded in accounting data on the usefulness of financial information? straightforward. The answer is far from On the one hand, estimates/projections are potentially useful to investors because they are the primary means for managers to convey credibly forward-looking proprietary information to invest ors1. Thus, for example, the bad debt provision, if estimated properly, informs investors on expected future cash flows from customers, restructuring charges predict future employee severance payments and plant closing costs, and the capitalized portion of We say â€Å"credibly† primarily because post Sarbanes-Oxley the firm’s CEO and CFO have to certify that â€Å"†¦information contained in the periodic report fairly represents, in all material respects, the financial condition and results of operations of the issuer†¦Ã¢â‚¬  3 software development costs (SFAS 86) informs investors about development projects that passed successfully technological feasibility tests and are accordingly expected to enhance future revenues and earnings. 2 This potential contribution of managerial estimates to investors’ ssessment of future enterprise cash flows underlies the oft-quoted statement by the Financial Accounting Standard Board (FASB) in its Conceptual Framewor k about the superiority of accruals earnings—mostly based on estimates—over the largely fact-based cash flows in predicting future enterprise cash flows: Information about enterprise earnings based on accruals accounting generally provides a better indication of an enterprise’s present and continuing ability to generate favorable cash flows than information limited to the financial aspects of cash receipts and payments (FASB, 1978, p. IX).On the other hand, the contribution of estimates to the usefulness of financial information is counteracted by two major factors: (i) Objective difficulties. In the current volatile and largely unpredictable business environment, due to fast-changing market conditions (deregulation, privatization, emerging economies) and rapid technological changes, it is increasingly difficult for managers to make reliable projections of business events. Consider, for example, the estimated future return on pension assets—a key componen t of the pension expense: This estimate is essentially a prediction of the long-term performance of capital markets.Are managers better predictors of market performance than investors? 3 Or, reflect on the generally large impairment charges of fixed assets and acquired intangibles (including goodwill) mandated by SFAS 121 and SFAS 142: The determination of these 2 Indeed, Aboody and Lev (1998) document a positive association between capitalized software development costs and future earnings. 3 Consider, for example, the 2001 pension footnotes of three financial institutions, Merrill Lynch, Bank of NewYork, and Charles Schwab, which report the following estimates of the expected returns on pension assets: 6. 60%, 10. 50%, and 9. 00%, respectively (Zion, 2002). The wide range of estimates (6. 6%-10. 5%) of the long term performance of capital markets reflects the inherently large uncertainty (unreliability) of the pension expense estimate. 4 charges requires managers to estimate futur e cash flows from tangible and intangible assets. In today’s highly competitive and contested markets the reliability of asset cash flows forecasted over several years is obviously questionable.Accordingly, the accounting estimates and projections underlying financial information introduce a considerable and unknown degree of noise, and perhaps bias to financial information, clearly detracting from their usefulness. 4 (ii) Manipulation. Add to the above objective difficulties in generating reliable estimates the expected and frequently documented susceptibility of accounting estimates to managerial manipulation, and the consequent adverse impact of estimates on the usefulness of financial information becomes apparent.Given that it is very difficult to â€Å"settle up† with manipulators of estimates—even if an estimate turns out ex post to be far off the mark, it is virtually impossible to prove that ex ante the estimate was intentionally manipulated—there are no effective disincentives for managers to manipulate accounting estimates. Indeed, many of the Securities and Exchange Commission (SEC) enforcement cases alleging financial reporting manipulation concern misuse of estimates underlying accruals (e. g. Dechow et al. , 1996). Thus, the impact of estimates underlying accounting measurement and reporting procedures on the usefulness of financial information is an open question, to be examined in this study. The relevance of this examination cannot be overstated. Accounting estimates and projections underlie much of Generally Accepted Accounting Principles (GAAP) and consume 4 A case in point (Wall Street Journal, August 4, 2004, p. c1): â€Å"Investors in Travelers have needed more than that ed umbrella protection from what has been raining on them since the company was spun out from Citigroup in early 2002. Late last month, St. Paul Travelers Cos. , †¦ announced what Morgan Stanley termed a ‘blockbuster reserve chargeà ¢â‚¬â„¢ of $1. 625 billion. The charge was about twice as large as analysts have been expecting. The insurer contends that the charge stems largely from the need to reconcile differing accounting treatments at the two companies [Travelers and its acquisition—St. Paul Cos. ]. It was just a â€Å"reserve valuation adjustment,† the company said†¦.Sadly there seems to be little reason why Travelers’ executives didn’t anticipate problems with St. Paul’s insurance methodologies†¦ Mr. Benet [Travelers’ CFO] said:†¦we recognized early on that there was a difference in some of the methodologies [to estimate reserves] that would have to be addressed. † (emphasis ours). Thus, different accounting methodologies used to estimate the same reserves, all approved by auditors, yield a difference of $1. 625 billion. 5 most of standard-setters’ time and efforts.Just consider the major issues addressed by the FASB in recent yearsâ₠¬â€financial instruments, employee stock options, fixed assets and goodwill impairment, and the valuation of acquired intangibles, to name a few—all require major estimates and forecasts in the process of accounting measurement and reporting. If these and other accounting estimates do not contribute significantly to the usefulness of financial information, the efforts of accounting regulators, and even more importantly, the resources society devotes to the generation of estimates in the process of financial statement preparation and their auditing, are misdirected.Worse yet, if financial information users are led by the estimates-based accounting information to misallocate resources, an additional dead-weight cost is imposed on society. We define and test the usefulness of estimates embedded in accrual earnings in terms of their ability to predict enterprise performance. 5 This predictive use of financial information is central to security analysis and valuation and is also a fundamental premise of the FASB’s Conceptual Framework as indicated by the quote above. Future enterprise performance is mainly reflected by cash flows and earnings.Future cash flows are at the core of asset and liabilities accounting valuation rules. Thus, for example, asset impairment (SFAS 144) is determined by expected cash flows, and the useful lives of acquired intangibles (SFAS 142) are a function of future cash flows. More fundamentally, asset or enterprise cash flows are postulated by economic theory as the major determinants of their value. Given a certain ambiguity about the specific definition of cash flows used by investors, we perform our tests with two widelyused and frequently prescribed cash flow constructs: cash from operations (CFO) and free cash flows (FCF).Much of prior related research focused on CFO. Free cash flows are central to 5 There are, of course, other uses of financial data, such as in contracting arrangements, which are not aimed at predicti ng future enterprise performance. 6 many practitioners’ valuation models (e. g. Brealey and Myers, 2003), and play an important role in research too (e. g. , FCF is a primary variable in the valuation constructs of Feltham and Ohlson, 1995). Cash flow prediction is thus a predominant element of accounting measurements and practitioners’ valuation processes.Despite the prominence of cash flows in economic asset valuation models, there is no denying that many investors and analysts are using financial data to predict earnings. The underlying heuristics are somewhat obscured; perhaps investors predict earnings first, and derive future cash flow estimates from the predicted earnings. In any case, earnings prediction is prevalent in practice, and we therefore also examine the usefulness of accounting estimates for the prediction of earnings, both operating and net income.The focus of this study is on accounting estimates, but many of the estimates underlying financial infor mation are not disclosed in the financial reports. 6 We, therefore, focus in this study on accruals, most of which are based on estimates. In particular, we distinguish between accruals which are largely unaffected by estimates (changes in working capital items, excluding inventory), and accruals which are primarily based on estimates (most non-working capital accruals). This enables us to draw sharper inferences on the effect of estimates on the usefulness of financial information.We also analyze a smaller sample of firms with data on specific estimates which we split into recurring and non-recurring to separate noise (the non-recurring estimates) from information (the recurring estimates). Our empirical analysis is based on a sample of all non-financial Compustat firms with the required data—ranging from roughly 1,500 to 3,200 companies per year—and spanning the 6 For example, General Electric reports in its revenue recognition footnote that various components of rev enues derived from long-term projects are based on the estimated profitability of these projects.GE, however, does not break down total revenues into estimates and â€Å"facts. † 7 period 1988-2005. Our tests are conducted in three stages: (1) In-sample, industry-by-industry, predictions of future enterprise cash flows and earnings, based on: (a) current cash flows only (the benchmark), (b) earnings, and (c) the set of cash flows, the change in working capital (excluding inventory), and various components of accruals based on estimates. Here we follow the regression procedures of Barth, Cram, and Nelson (2001) and find, on more recent data, results which are generally consistent with Barth et al.This is our departure point. (2) Out-of sample firm specific predictions of future cash flows and earnings using the industry specific parameter estimates of the in-sample regressions. The focus of this analysis is on the improvement in the quality of predictions brought about by the addition of estimates (accruals) to the predictors. We thus predict cash flow from operations, free cash flows, net income before extraordinary items, and operating income over various horizons: one year ahead, second year ahead, aggregate two years ahead, and aggregate three years ahead.Our results show that accounting estimates do not improve the prediction of future cash flows (both operating and free cash flows), compared with predictions based on current CFO and the change in working capital excluding inventory. However, accruals do improve next year’s prediction of net and operating income. Notably, cash flow predictions based on current earnings only are significantly inferior to those generated by current CFO, contrary to Kim and Kross (2005). In our small sample analysis, neither recurring nor nonrecurring estimates improved significantly the predictions of either cash flows or earnings.The bottom line—accounting estimates beyond those in working capital items (except inventory) do not improve the prediction of cash flows. 8 (3) Finally, we examine the economic significance of estimates. These tests complement stage two, which is based on the statistical significance of differences in the quality of alternative predictors. Since it is difficult to gauge economic significance from statistical significance, we perform various portfolio tests, where portfolios are constructed from predicted cash flows and earnings based on various predictors, some of which are based on estimates.The abnormal returns on these portfolios, generated by alternative predictors, are our gauge of economic significance. The focus here is on comparing the returns on portfolios constructed from predictions based on current cash flows only (the benchmark), with returns on portfolios constructed from predictions based on current earnings or current cash flows plus changes in working capital and estimates. The results from these tests generally corroborate the out-of-sa mple prediction tests.In practically all our portfolio tests the model that uses current operating cash flows only to predict firm performance generates higher abnormal returns than models which add estimates to the prediction process used for the portfolio formation, though most of these returns are insignificant. Furthermore, the portfolios constructed from predictions based on current cash flows only yield abnormal returns with generally lower standard deviation than the alternative portfolios which include earnings or estimates among the predictors. We caution against sweeping conclusions.We examine the usefulness of accounting estimates in terms of predictive ability with respect to future firm performance. Accounting information is used for other purposes too (contracting, national accounting), for which estimates may be useful. Furthermore, our prediction tests are based on fairly simple models. Users may be using different, more sophisticated models where estimates could pro ve to be useful. 9 Nevertheless, we believe that our findings draw attention to the significant vulnerability of financial information from the multitude of underlying estimates and projections, and to the urgent need for improving the eliability of estimates, on which we comment in the concluding section. The order of discussion is as follows: Section 2 relates our findings to available research, and Section 3 outlines our research design. Section 4 describes our sample, and Section 5 reports our prediction tests. Section 6 informs on a battery of robustness checks, and Section 7 focuses on a subsample with an extended set of accounting estimates. Section 8 reports our portfolio (economic significance) tests, while Section 9 concludes the study. 2.Relation to Available Research Our study interfaces with several active research areas, and below we comment on the relation between our work and various representative studies. We are not familiar with empirical studies which assess the impact of accounting estimates on the informativeness of financial information, but there is a substantial number of studies that examine the contribution of accruals to the prediction of future cash flows and other variables. These studies can be roughly classified into regression-based (in-sample) analyses, and out-of-sample prediction tests.An example of the former is the comprehensive work by Barth, Cram and Nelson (2001), who regress CFO on lagged values of CFO and components of accruals (primarily the changes in accounts receivable, inventories, and accounts payable, as well as depreciation & amortization and other accruals). The authors report (p. 27) that â€Å"each accrual component reflects different information relating to future cash flows†¦[and] is significant with the predicted sign in predicting future cash flows, incremental to current cash flows. Note that 10 predictive ability is assessed in this and similar studies by the significance of the estimated accrua ls’ coefficients and by the improvement inR 2. 7 An interesting extension of the regression strand is provided by Subramanyam and Venkatachalam (2007) who examine the relative explanatory power of earnings and cash flows with respect to an ex post measure of the intrinsic value of equity which uses Ohlson’s (1995) equity valuation framework, based on realized values of earnings and book values.The authors argue that such measurement of equity values avoids the necessity to assume capital market efficiency, as in Dechow’s (1994) study relating accruals to contemporaneous stock returns. Dechow documents a significant association between accruals and stock returns, but the implications of such association for market efficiency are challenged by Sloan’s (1996) findings of strong return reversals (market inefficiency) following extreme accruals.Subramanyam and Venkatachalam (2007) conclude that operating cash flows are more strongly associated with future cash flows than earnings, and that current earnings are more strongly associated with future earnings than cash flows. Regressing the ex-post equity measure on earnings and cash flows indicates that earnings exhibit a higher explanatory power than cash flows. By and large, the in-sample regression studies suggest that accruals are associated with subsequent cash flows and contemporaneous equity values, a finding we largely update and corroborate in the initial stage of our analysis (Section 5. ). However, as is argued in Section 5. 1, in-sample regressions are not prediction tests, and may even provide misleading inferences concerning prediction power. We move, therefore, to out-of-sample tests. An early and innovative out-of-sample prediction test is Finger (1994), who concludes from a sample of 50 companies with long historical data that cash flow is marginally superior to 7 Bowen et al. (1986) and Greenberg et al. (1986) perform similar regression-based, in-sample predictions. 11 ear nings for short-term predictions and performs similar to earnings in long-term cash flow predictions.However, time-series and cross-sectional out-of-sample short-term prediction tests by Lorek and Willinger (1996) and Kim and Kross (2005), respectively, show that current earnings predict more accurately future cash flows than current cash flows do. Thus, a mixed picture emerges from the out-of-sample tests, calling for further research. Note also that most previous studies, in- and out-of-sample, focus on the prediction of cash from operations, despite the fact that free cash flows (a measure included in our tests) is frequently used by analysts and investors.Barth, Beaver, Hand and Landsman (2005) provide an interesting perspective on the usefulness of accruals. Using the valuation framework of Feltham and Ohlson (1995, 1996), they examine the ability to predict equity value of various disaggregations of earnings: aggregate earnings, cash flows and total accruals, as well as cash f lows and four major components of accruals. The prediction methodology is out-of-sample in a particular sense: cross-sectional valuation models are run for each year (equity values regressed on contemporaneous earnings disaggregations), excluding each time a particular sample firm.The equity value of that firm is then predicted from the estimated coefficients of the models. Barth et al. (2005, p. 5) â€Å"†¦find evidence of some reduction in mean prediction errors from disaggregating earnings into cash flows and total accruals, and some additional reduction from disaggregating total accruals into its four major components†¦median prediction errors generally support disaggregation of earnings only into cash flows and total accruals. Overall, these findings vary considerably by industry, and appear to indicate a more consistent success for the cash flows and total accruals model than for the cash flows and disaggregated accruals model. 8 8 Studies such as Bathke et al. (198 9) and Lorek et al. (1993) also perform out-of-sample prediction tests. 12 The substantial body of research on the accruals anomaly initiated by Sloan (1996) is tangentially related to our study.This research establishes that accruals are often misinterpreted by investors: large (small) accruals firms are contemporaneously overvalued (undervalued) in capital markets, and these misvaluations are largely reversed within a couple of years. Notably, much of the accruals anomaly resides in small, thinly traded firms, which are unattractive to most institutional investors (Lev and Nissim, 2006), a fact that contributes significantly to the persistence of this anomaly. It is important to note that our focus in this study is different from the ccruals anomaly research: we do not examine investors’ perceptions of accruals, and the consequences of such perceptions. Rather, we focus on the contribution of accruals and by implication of the embedded estimates to the primary role of finan cial information—assisting users in predicting future enterprise performance. The short-term market inefficiencies highlighted by the accruals anomaly are, of course, worth noting, but they do not inform much on the presumed role of accruals—to improve the prediction of enterprise performance.Stated differently, while extreme accruals are often mispriced contemporaneously by investors, a misperception corrected fairly shortly thereafter, accounting accruals in general, prevalent in every financial report, may still enhance the multi-year prediction of firm performance. It is this fundamental role of accruals and their underlying estimates that is the main theme of our study. The lack of convergence of the extant accruals’ usefulness research makes it very difficult to draw firm conclusions.Some studies are in-sample, while others are out-of-sample; some researchers relate accruals to contemporaneous returns or equity values whereas others to future values. Some predict cash flows while others predict equity values based on models using forecasted or realized residual earnings. Our main contribution to extant research is the focus on the estimates embedded in accruals and the provision of certain closure to the usefulness of 13 accruals issue. We distinguish between accruals which are largely based on facts and those primarily reflecting estimates, to focus on the usefulness of accounting estimates.Our main tests are out-of-sample predictions, replicating what most investors actually do—predict, with no ex post information (as implicitly assumed by in-sample studies), various versions of future earnings and cash flows. The comprehensiveness of our predicted performance measures (two versions of earnings and two of cash flows), and the number of future periods examined (years t+1, t+2, and aggregate next two years and next three years) enables us, we believe, to draw general conclusions about the contribution of estimates to firm perf ormance rediction. Furthermore, our study is the first, we believe, to examine both the statistical and economic performance of accruals-based prediction models. Inferences from statistical significance are sometimes difficult to draw and generalize. Consider, for example, the Barth, Beaver, Hand and Landsman (2005, p. 5) conclusion: â€Å"we find evidence of some reduction in mean prediction errors from disaggregating earnings†¦Ã¢â‚¬  (emphasis ours). While definitely interesting, this conclusion leaves open the important question of: how material is â€Å"some reduction†?Is it, for example, sufficiently large to support the current move of the FASB and IASB toward increased reliance on estimates in financial reports (fair value, stock option expensing, etc. )? Statistical significance coupled with economic significance, as provided below, allows for a more comprehensive evaluation of the evidence. 9 The focus on accounting estimates, the out-ofsample methodology, and the examination of both statistical and economic significance, all bringing certain closure to the research question, is our main contribution. 3. Research Design Examples of studies including economic significance tests are Ou and Penman (1989), Stober (1992), Abarbanell and Bushee (1998), and Piotroski (2000). 14 Our research design consists of three stages: (a) in-sample association tests of cash flows (earnings) regressed on lagged values of these variables and accruals, (b) out-of-sample forecasts of cash flows (earnings) based on these variables and accruals and (c) calculation of hedge future excess returns on portfolios constructed from the out-of-sample predicted cash flows (earnings) in stage (b).We conduct the first stage as a link to and departure from previous research by estimating cross-sectional in-sample regressions as in the Barth, Cram and Nelson (2001) study (BCN hereafter). We use several prediction constructs, primarily to distinguish between accruals largely based on facts and those based on estimates. At one extreme of the accruals disaggregation we classify all the accruals in the â€Å"operations† section of the cash flow statement into working capital changes excluding inventory (? WC*) and the remaining accruals, termed â€Å"estimates† (EST): EARNINGSCash from Working Capital Operations Change excluding (CFO) inventory (? WC*) Estimates (EST) ACCRUALS Working capital items with the exception of inventory, such as accounts payable and short-term marketable securities, are generally not materially impacted by managerial estimates,10 whereas 10 The accounts receivable change, net of the provision, is an exception, since it is subject to an estimate. But this estimate is included in our second accruals component, EST. 15 most of the remaining accruals are in fact pure estimates (e. g. , depreciation and amortization, bad debt provision, in-process R&D).At the other end of the accruals disaggregation we separate out the c hange in inventory (? INV) from the aggregate estimates (EST), given the evidence (e. g. , Thomas and Zhang, 2002) that much of the accruals anomaly resides in inventory, probably due to intentional and unintentional misestimations of this item. We further break out depreciation and amortization (D&A) and deferred taxes (DT) from other estimates because the identification of these items is possible from Compustat data over the entire sample period. This disaggregation is depicted thus: EARNINGS CFO WC* (minus inventory) ?Inventory (? INV) Dep. & Amortization (D&A) ACCRUALS Def. Taxes (DT) Other estimates (EST*) The various components of accruals along with cash from operations (CFO),11 depicted in the two exhibits above are the independent variables in the estimation models underlying our in-sample predictions. We add to these variables the cash flow statement figure of capital expenditures (CAPEX), since the dependent variables in our models are future cash flows or earnings, which are generally affected by current investment (capital expenditures). We believe 11We measure CFO as in Barth et al. (2001), namely net cash flow from operating activities, adjusted for the accrual portion of extraordinary items and discontinued operations. 16 that the addition of capital expenditures to the regressors improves the specification of the insample prediction models, and sharpens our focus on the relative performance of the accruals components, our focus of study. Indeed, the capital expenditures variable is statistically significant in most of our annual in-sample predictions models. 12 3. 1 Prediction tests Our prediction tests take the following general form.We predict two versions of cash flows (cash from operations and free cash flows) and two constructs of earnings (net income before extraordinary items and operating income) in years t+1 and t+2, as well as in aggregate years t+1 & t+2, and t+1 through t+3. To gain insight into the usefulness of estimates in predi cting firm performance, we use five prediction models with increasing disaggregation of accruals (regressors): Model 1: current CFO only—the benchmark model; Model 2: current net income (NI) only; Model 3: current CFO and the change in working capital items excluding inventory (?WC*)—namely, largely fact-based regressors; Model 4: current CFO, the change in working capital items excluding inventory ? WC*, and total remaining accruals, largely based on estimates (EST); and Model 5: current CFO, the change in working capital items excluding inventory ? WC*, the change in inventories (? INV), depreciation & amortization (D&A), the change in deferred taxes (DT), and all other estimates (EST*)—the most disaggregated model. The purpose is to examine whether the gradual addition of components of accruals 12 For robustness, we reran our predictions (reported in Table 3) without capital expenditures, and conclude that one of our inferences changes in the absence of capit al expenditures. 17 estimates to current cash flows (the benchmark) improves the prediction of future cash flows or earnings. Increasing the disaggregation of accruals should, in general, enhance the quality of prediction (from model 1 to 5), since the individual accrual components are allowed to have different effects (multiples) on the predicted values. We examine model 2 because the predictor, earnings, is a summary accounting variable that has been extensively investigated for its information content and has been used in most prior studies (e. . BCN and Kim and Kross 2005). It is important to note that the cross-sectional estimates of the five in-sample prediction models are obtained for 2-digit SIC industry groups. These industry specific estimates make the implicit assumption of constancy of coefficients across firms reasonably tenable. We implement the second stage of our research design by using the industry specific estimated coefficients from each of the above five predict ion models to calculate firm specific predicted values for cash from operations (CFO), free cash flows (FCF), net income (NI) and operating income (OI).We then calculate firm specific prediction errors as the difference between the actual and predicted values of each variable examined. The following examples of the prediction of free cash flows (FCF) will clarify our prediction procedures. A. Prediction of next year’s free cash flows, FCF (t+1) (a) Benchmark Model using CFO only (example for 1990): 1. Estimate cross-sectionally for each 2-digit industry the following regression: FCF (89) = ? + ? CFO(88) + ? . , 2. Predict for each firm in a given 2-digit industry: EFCF (90) = ? + ? CFO(89) using the previously determined industry specific estimated coefficients. . Determine prediction error for each firm in a given 2-digit industry: EFCF (90) . FCF (90) – 18 Here we predict 1990 free cash flows (EFCF(90) from current cash from operations, CFO (89) (and capital expendit ures). First, for each 2-digit industry we regress cross-sectionally free cash flows of 1989 on CFO in 1988, and obtain the estimated coefficients ? and . ? Those coefficients are then used to predict firm specific free cash flows (EFCF) in 1990, using the firm’s actual CFO of 1989. Then, a firm specific prediction error is determined by comparing the firm’s actual 1990 FCF with the predicted one.The same procedure is repeated for every firm and sample year. (b) Restricted Estimates, Model 4 (example for 1990): Estimate cross-sectionally for each 2-digit industry: FCF (89) = ? + ? 1CFO(88) + ? 2? WC * (88) + ? 3EST (88) + ? . The subsequent prediction and error determinations are done as in (a) above. Here we predict 1990 free cash flows from CFO, ? WC* (change in working capital items excluding inventory), EST (estimates), and capital expenditures (not shown in the equation). First, a cross-sectional regression of 1989 free cash flows is run on the 1988 values of CFO, ? WC*, and EST, yielding coefficients ? ? 1, ? 2, and ? 3. Then, firm specific 1990 free cash flows are predicted, using the four industry specific estimated coefficients and the 1989 actual values of CFO, ? WC*, and EST. Finally, these 1990 FCF predictions are compared with the 1990 actual free cash flows to determine the prediction error. The same procedure is repeated for each firm and sample year. (c) Expanded Estimates, Model 5 (example for 1990): Estimate cross-sectionally for each 2-digit industry: FCF (89) = ? + ? 1 CFO(88) + ? 2 ? WC * (88) + ? 3? INV (88) + ? 4 D & A(88) + ? 5 DT (88) + ? 6 EST * (88) + ? . 19The prediction and error determinations are done as in (a) above. Here we predict 1990 free cash flows from 1989 CFO, capital expenditures, and the disaggregated set of estimates (see second diagram at the beginning of this Section). Once more, we run by industry a cross-sectional regression of 1989 FCF on the 1988 values of the independent variables, estimating the ? and ? 1†¦ ? 6 coefficients (and a ? 7 coefficient for 1988 capital expenditures). The firm-specific 1990 free cash flows are predicted using these industry specific coefficients and the actual values of the independent variables in 1989.Computation of the 1990 FCF prediction error follows. B. Prediction of year 2 free cash flows, FCF (t+2) Benchmark Model (example for 1992): 1. Estimate cross-sectionally by 2-digit industry: FCF (90) = ? + ? 1CFO(88) + ? 2. Predict for each firm in a given 2-digit industry: EFCF (92) = ? + ? 1CFO(90) 3. Prediction Error for each firm in a given 2-digit industry: FCF (92) – EFCF (92) This is the prediction of free cash flows in t+2. It follows the earlier procedure with one difference: Here the cross-sectional estimate (first equation) and the forecast (second equation) involve a two-year lag (e. . , FCF in 1990 regressed on CFO of 1988). Same procedure is performed for each firm and sample year. The expanded prediction models incorpora ting disaggregated accruals follow steps (b) and (c), above. We also predict free cash flows for aggregate years t+1 plus t+2, and t+1 through t+3. These predictions are based on the procedures described above, except that aggregated future free cash flows are substituted for single year free cash flows as left-hand variables in the various models. The procedure demonstrated above for FCF is also used to predict cash from operations 20 CFO) in t+1, t+2, and aggregated future years, and to predict earnings in t+1, t+2 and aggregated future years. Two versions of earnings—net income before extraordinary items (NI) and operating income (OI)—are predicted. The various prediction models for earnings are identical to those of free cash flows described above, except that earnings in t+1 and t+2 are substituted for FCF in those models. To summarize, we perform out-of-sample predictions of two versions of cash flows and two versions of earnings from current values of CFO, curre nt values of NI, and CFO plus changes in working capital and various combinations of accruals.To evaluate the quality of the out-of-sample predictions, we compute summary measures of prediction errors derived from the firm- and year-specific estimated errors: the mean and median signed prediction errors indicating the bias in the forecasts, and the mean and median absolute prediction errors which abstract from the sign of the error and indicate forecast accuracy. The firm-specific prediction error in a given year is computed as the realized value of cash flow or earnings minus the predicted cash flow or earnings, divided by average total assets in year t. . 2 Portfolio analysis The third stage of our research design is motivated by Poon and Granger (2003, p. 491) who note: â€Å"Instead of striving to make some statistical inference, [prediction] model performance could be judged on some measures of economic significance. † We interpret their statement as saying that we shoul d not rely solely on the statistical significance of our prediction errors calculated in stage two but should also examine and perhaps even rely more on measures of economic significance.To gauge the economic significance of the contribution of estimates to the usefulness of financial information we perform a series of portfolio tests focusing on the incremental stock returns generated by the estimates-based prediction models. 21 Essentially, we use the out-of-sample predicted values of cash flows (CFO and FCF) and alternatively of earnings (NI and OI), obtained in the second stage of our analysis, to form portfolios.Specifically, for each sample year we rank all firms (across all industries) on predicted firm-specific cash flows or earnings (four rankings, two for cash flows and two for earnings), scaled by average total assets in the end of year t. We then form ten portfolios from each annual ranking and compute risk-adjusted (size & book-to-market adjusted) returns from holding t hese portfolios over several future periods. In assessing the performance of the various predictors (CFO, NI, ? WC*, accruals of estimates), we primarily focus on a zero-investment (hedge) strategy: going long (investing) in the top ortfolio (the 10% of firms with the largest (scaled) predicted cash flows or earnings), and shorting (selling) the bottom portfolio (10% of firms with the lowest predicted cash flows or earnings). The abnormal returns on these zeroinvestment portfolios indicate the economic contribution to investors of using accounting estimates as predictors. Thus, if estimates are useful to investors then portfolios constructed from predictions based on current cash flows and estimates-based accruals should consistently outperform portfolios formed from predictions based on current cash flows only.It should be noted that if markets are efficient concerning the information in accruals—a big if, in light of Sloan (1996)—and if investors select securities us ing procedures similar to our industry-based prediction models specified above, then our subsequent portfolio abnormal returns should be roughly zero. Our purpose in these portfolio tests, however, is not to examine market efficiency, rather to compare the performance of portfolio selection procedures with the estimates-based accruals against similar procedures without accruals (based on past cash flows only).We are thus focusing on the with- and without-accruals comparisons, being agnostic about market efficiency. Stated differently, the comparative abnormal hedge returns across the 22 five prediction models, rather than the statistical significance of those returns, is our focus of analysis. 4. Sample Selection and Descriptive Statistic We obtain accounting data from the 2006 Compustat annual industrial, full coverage, and research files, and use data from the statement of cash flows because Collins and Hribar (2002) suggest that such data are preferable to accruals derived from t he balance sheet.Since reporting a statement of cash flows was mandated by SFAS 95 in 1987, our accounting data span the period 1988 to 2005. 13 In the in-sample regression analysis, each year from 1988 to 2004 is a predictor year (generating the independent variables) while each year from 1989 to 2005 is a predicted year (providing the dependent variables). Thus, 17 in-sample annual regressions are estimated for each industry. Our sample selection procedure is as follows. We start with 75,571 observations with values for NI, CFO, ? WC*, INV, D&A, DT, EST, EST* and CAPEX for the current year, year t, and for NI over a three-year horizon, t-1 to t+1. Firms with all fiscal year ends are included. We control for outliers by following the procedures in Barth et al. (2001). Thus, after eliminating the top and bottom one percentile of current NI and CFO we are left with 73,324 firm-year observations. By excluding observations with market value of equity or sales of less than $10 million, or with share prices below $1, to eliminate economically marginal firms, the number of observations decreases to 51,301.By deleting observations with studentized residuals greater than 3 or less than -3, we are left with 50,288 observations. Since we conduct industry-byindustry in-sample regression analysis we require each industry to have a minimum of 600 observations over the period 1988 to 2004. This criterion reduces the sample to its final size of 13 Valid statement of cash flows data for the year 1987 are available for a relatively small number of firms not enough to do a meaningful industry-by-industry analysis. Thus, we do not use 1987 data. 23 41,124 observations.We obtain stock returns data for the portfolio analysis from the 2006 CRSP files. 14 Table 1 provides summary statistics (variables are scaled by average total assets) and a correlation matrix for out test variables. Panel A shows that depreciation and amortization (D&A) constitutes the bulk of the estimates underl ying accruals (EST): The mean (median) of D&A is 0. 054 (0. 047), close to the mean (median) of EST, 0. 059 (0. 052). The mean of net estimates (EST*), excluding D&A and deferred taxes, is quite large, 0. 019, and is driven mainly by large positive values, as the median value of 0. 04, Q1 of 0. 000 and Q3 of 0. 019 imply. CFO has the lowest while NI has the highest variability (standard deviations of 0. 129 versus 0. 149) among the various earnings and cash flow variables. In panel B all correlations are significant at the 5% level or better. We note the high negative correlations of our estimates variables, EST and EST*, with the income variables, NI and OI. However, the correlations of EST and EST* with both the cash flow variables, CFO and FCF, are much lower; positive for EST and negative for EST*. 4 We repeated all of our analyses with a sample without any outlier removal, namely where we only require non- missing values for the key variables, and at least 600 observations in e ach 2-digit SIC over the sample period 19882004. This sample consists of 65,178 observations and is substantially larger than the sample of 41,124 observations used in the analysis reported below. We find that for many industries the R-squares in the in-sample regressions are higher for the un-truncated data than for the truncated data.The forecast error results are essentially identical to the results from the truncated sample in terms of inferences but the errors are larger. The portfolio abnormal returns results exhibit similar patterns to the results from truncated data. Overall, the un-truncated data yield very similar results to those of the truncated data reported below. 24 5. Empirical Findings: Prediction Tests 5. 1 Stage one: In-sample Regressions Table 2 reports cross-sectional annual regressions, by industry, of CFO (cash from operations) on lagged values of CFO and earnings components (Model 5 in Section 3).The reported coefficient estimates for each industry are the me ans of the yearly coefficients over the 17 year period, 1988 to 2004. The significance of these mean coefficients is based on (nonreported) t-statistics calculated using the mean and standard errors of the 17 yearly coefficients, as in Fama and MacBeth (1973). We report the results for the CFO regressions so that they can be compared to the CFO results reported by BCN. The, in-sample regression results for FCF, NI and OI are very similar to those reported in Table 2. It is evident that in each of the twenty-three ndustries in Table 2 the lagged CFO and ? WC* (change in working capital minus inventory) are highly significant. In the majority of the industries, ? INV (inventory change) is also significant, as is D&A. However, DT (deferred taxes) and EST* (other accruals estimates) are significant for about half of the industries only. These results are quite consistent with BCN’s results reported in their Table 6, Panel B (note that the sum of our DT and EST* variables is the O TH variable in BCN). The fairly large R2s, ranging across industries from 0. 29 to 0. 71, are also consistent with the R2s reported by BCN.Thus, the BCN regression results over the period 1987 to 1996 hold well over our longer period, 1988-2004. Overall, the estimates indicate a strong association between CFO and lagged earnings components, raising expectations about strong out-of-sample performance as well. However, it is important to note that a regression analysis of a given variable on lagged values of that variable along with other data, as frequently conducted in accounting and finance research, is not a conclusive test of predictive ability. As noted in Poon and Granger’s (2003, p. 25 92) survey: â€Å"In all forecast evaluations, it is important to distinguish in-sample and out-ofsample forecasts. In-sample forecast, which is based on parameters estimated using all data in the sample, implicitly assumes parameter estimates are stable through time. In practice, time v ariation of parameter estimates is a critical issue in forecasting. A good forecasting model should be one that can withstand the robustness of an out-of-sample test, a test design that is closer to reality. In our analyses of empirical findings†¦ we focus our attention on studies that implement out-of-sample forecasts. A dramatic example of misplaced inferences drawn on the basis of regression analysis has been recently provided by Goyal and Welch (2007). Their focus is on the prediction of stock market returns based on a variety of variables suggested by prior studies (e. g. dividend yield, earnings-price ratio, book-to-market ratio), using in-sample regression models. After a comprehensive analysis, Goyal and Welch conclude that â€Å"these models have predicted poorly both in-sample and out-of-sample for thirty years now; these models seem unstable, as diagnosed by their out-of-sample predictions nd other statistics; and these models would not have helped an investor with access only to available information to profitably time the market† (Abstract). This important insight motivates our primary analysis which focuses on out-of-sample prediction tests. In the case of predicting stock returns, Goyal and Welch’s concern, in-sample regression results are generally weak and it is therefore not surprising that the out-of-sample predictions of Goyal and Welch perform poorly too.In contrast, in our case of predicting cash flows and earnings, the in-sample regressions (Table 2) perform well, so, whether the more realistic out-of-sample predictions of cash flows and earnings perform equally well is an important empirical issue which we examine next. 26 5. 2 Stage two: Out-of-sample Prediction Tests Table 3 summarizes our main out-of-sample prediction findings. Recall that we predict four key performance indicators: cash from operations (CFO); free cash flows, defined as CFO minus capital expenditures (FCF); net income before extraordinary items (N I); and operating income (OI).There are four prediction horizons: next year, second year ahead, aggregate next two years, and aggregate next three years. Five prediction models are examined (they were discussed and demonstrated in Section 3), where the predictive (independent) variables are: (1) CFO only—the benchmark model, (2) NI only, (3) CFO and the annual change in working capital items excluding inventory (? WC*), (4) CFO plus the change in working capital items excluding inventory (? WC*), as well as the total remaining accruals (EST) which are largely estimates based, including the change in inventory, and (5) our most disaggregated model: CFO, ?WC*, the change in inventories, depreciation and amortization, deferred taxes, and all remaining estimates. Current capital expenditure is included as an additional variable in each of the five models. We report in Table 3 four summary statistics for the prediction errors of our five models: the pooled firm-specific mean absol ute error (MAER) of each of the five models, the pooled mean signed error, or bias (MER), the mean R2s from annual regressions of firm-specific actual values of future cash flows or earnings on the corresponding predicted values, and the average over the years of Theil’s U-statistics. 5 We indicate with an ampersand (&), asterisk (*) or a hash (#) the pooled mean absolute prediction errors (MAER) which are significantly different 15 The reported Theil's U-statistic is the average of the yearly U-statistics. Theil’s U is defined as the square root of ?(actual-forecast)2/? (actual)2. The U statistic can range from zero to one, with zero implying a perfect forecast. Thus, models generating better predictions should have lower U statistics. 27 between Models 1 and 2, Models 1 and 3, and Models 3 and 4, and Models 3 and 5, respectively. 6 We have also computed the sample median signed errors, median absolute errors, and root mean square errors. Results from these indicators are very similar to those reported in Table 3 (we comment in the text on the occasional differences). Below are the main inferences we draw from Table 3, and additional analyses: 1. Prediction of cash flows. Considering the prediction of cash from operations (CFO) and free cash flows (FCF)—left two quadruples of columns in Table 3—we note that the predictions derived from net income only (Model 2) are always significantly inferior to the predictions based on cash from operations only (Model 1).This is true across the four forecast horizons and the four error summary statistics. For example, in predicting one-year-ahead cash from operations (top left panel), the MAER, MER and Theil’s U are lower for Model 1 than for Model 2 (0. 056 vs. 0. 062, 0. 001 vs. 0. 003, and 0. 58 vs. 0. 64, respectively), while the R2 of Model 1 is higher than that of Model 2 (0. 46 vs. 0. 37). The difference in the MAERs is statistically significant, as indicted by the & sign. This pat tern is evident across all eight panels reporting predictions of cash from operations and free cash flows for various horizons.Thus, for one- to three-year forecast horizons, current cash from operations is a better predictor of future cash from operations and free cash flows than current net income. This result is inconsistent with Kim and Kross (2005) findings that in one-year-ahead predictions of cash flows current earnings performs better than current cash flows. 17 16 All the absolute forecast errors (MAER) in Table 3 are statistically significant, with p-values of 0. 01 or better. The majority of the signed errors (MER) are also significant at p-values of 0. 1 or better, and many are statistically significant at least at p-values of 0. 05. The following signed errors are insignificant: Model 1 in forecasting Years 12 CFO, Models 1 and 3 in forecasting Years 1-3 CFO, and Models 2, 4 and 5 in forecasting Years 1-3 OI. 17 It is important to note that Kim and Kross (2005) use bala nce sheet items to calculate cash from operations while we use statement of cash flows data. We were able to replicate the out-of-sample prediction results of Kim and 28Moving on to Model 3, (predictors: CFO and the change in working capital items minus inventory), we note that the CFO and FCF predictions derived from current CFO only (Model 1) under-perform predictions based on current CFO and the change in working capital items excluding inventory, ? WC*. Thus, the mean absolute errors of Model 3 are significantly lower than those of Model 1 in all CFO and FCF panels, except in the FCF panel for the aggregate next three years horizon (bottom FCF panel). 18 The reported R2s and Theil’s U statistics also indicate the under-performance of Model 1 relative to Model 3.For example, in predicting one-yearahead cash from operations (top left panel), the MAER and Theil’s U are lower for Model 3 than for Model 1 (0. 054 vs. 0. 056, and 0. 56 vs. 0. 58, respectively), while the R2 of Model 3 is higher than that of Model 1 (0. 50 vs. 0. 46). Thus, for one- to three-year forecast horizons, the total change in working capital items excluding inventory is incrementally informative over current cash flows. This is relevant for our focus on the usefulness of accounting estimates, because the working capital items, excluding inventory, and with the exception of accounts receivable, are largely free of estimates.We now move to examine the contribution of accounting estimates to cash flow prediction. We do this by comparing the performance of Models 4 and 5 to that of Model 3, where Model 3 becomes now our benchmark given its superior performance up to this point. We note that CFO and FCF predictions derived from Model 4 (based on CFO, the change in working capital items excluding inventory (? WC*), as well as all other accruals including the change in inventory) and Model 5 (based on CFO, ? WC*, the change in inventories, depreciation and amortization, Kross usin g balance sheet items for our sample period.Accordingly, the difference in the results between the two studies is due to the data used. As shown by Collins and Hribar (2002), the cash from operations, and accruals derivation from the statement of cash flows is preferable. 18 Note that despite the very small difference between the MAERs of Models 1 and 3, the mean differences are statistically significant at the 0. 05 level or better (see asterisks). 29 deferred taxes, and all remaining accruals) equally perform or under-perform the predictions from Model 3 (based on CFO and ?WC*). Specifically, the mean absolute errors of Model 3 are significantly lower than or equal to the mean absolute errors of Models 4 and 5 in all the CFO and FCF panels. Furthermore, the reported MERs, R2s and Theil’s U statistics are also consistent with the under-performance of Models 4 and 5 relative to Model 3. For example, in predicting one-year-ahead cash from operations (top left panel), the MAER, MER and Theil’s U for Model 3 are either equal to or lower than for Models 4 and 5 (0. 054 vs. 0. 054 and 0. 055; 0. 001 vs. 0. 02 and 0. 002; and 0. 56 vs. 0. 57 and 0. 57, respectively), while the R2 of Model 3 is equal to or higher than the R2s of Models 4 and 5 (0. 50 vs. 0. 50 and 0. 49). Accordingly, we conclude that for one- to three-year forecast horizons the accounting estimates embedded in accruals, either as a lump sum or disaggregated, do not improve cash flow predictions over current cash from operations and the change in working capital (excluding inventory). 19 Conclusions: Neither total earnings, nor disaggregated estimates-based accruals ystematically improve the prediction of cash flows (CFO or FCF) over the predictions based on current CFO and the change in working capital (excluding inventory). This finding is inconsistent with the FASB’s conceptual stipulation that â€Å"Information about enterprise earnings†¦generally provides a better indi cation of an enterprise’s present and continuing ability to generate favorable cash flows than information limited to the financial aspects of cash receipts and payments† (FASB, 1978, p. IX), though our data start ten years after this statement was issued 2. Prediction of earnings.The two quadruples of columns to the right of Table 3 report prediction performance statistics for net income (NI) and operating income (OI). Here, the 19 These inferences do not change when we examine median signed and absolute prediction errors (available on request). 30 predictions derived from net income (Model 2) significantly outperform those based on cash from operations only (Model 1), for the one-year-ahead forecasts. For example, in predicting next year’s operating income (top right panel), the MAER of Model 2 is significantly lower than that of Model 1 (0. 057 vs. 0. 061).The R2s and Theil’s Us confirm the stronger performance of Model 2, for one-year predictions. Inte restingly, Model 2’s predictions are significantly inferior to Model 1’s in the two-years-ahead and aggregate next three years predictions (second and bottom NI and OI panels). For example, in predicting aggregate three-years-ahead operating income (bottom right panel), the MAER of Model 2 is significantly higher than that of Model 1 (0. 257 vs. 0. 253). Thus, for a one-year-ahead forecast horizon, current net income is a better predictor of future net income and operating income than current cash from operations. 0 Of the five models examined for earnings predictions, the best performer is Model 4— with three variables: CFO, ? WC* (change in working capital excluding inventory), and EST (all other accruals)—for all forecast horizons. Intriguingly, Model 5, where EST is disaggregated to several estimates-based accruals, is somewhat inferior to Model 4. Apparently, predicting from disaggregated accruals results in noisy forecasts. Conclusions: Earnings is a better predictor of near-term earnings than cash flow.Accounting accruals, when disaggregated to working capital items and other accruals, improve further the prediction of operating and net income. No further improvement is achieved from a finer disaggregation of accruals. 6. Robustness Checks 1. How good are our prediction models? 20 Our prediction models are admittedly The median absolute errors are lower for Model 2 than for Model 1 in all NI and OI panels except in the bottom two panels (for the aggregate next two and three years horizons). 31 simple—they obviously abstract from many of the complexities of real life security analysis.Nevertheless, the R2s in Table 3—derived from annual regressions of actual values (future cash flows or earnings) on predicted values—are quite large. Thus, for example, for next year’s predictions (top panels of Table 3), the R2 range is 0. 33-0. 58. As expected, the R2s drop for second year predictions, yet they are still in the reasonable range of 0. 21-0. 37. Thus, despite their simplicity, our prediction models perform reasonably well. 2. Trimming extreme prediction errors. The results of Table 3 are after trimming the top 2% of the absolute forecast errors.We also computed prediction errors after trimming the top and bottom 1% of the forecast errors and without any trimming. The resulting patterns of prediction errors (not reported) are in both cases very similar to those of Table 3. As expected, Table 3 trimmed errors are substantially smaller than the non-trimmed errors, the R2s are larger, and the Theil’s U statistics are lower, yet our conclusions regarding the relative performance of the five models equally apply to the non-trimmed errors. substantially our inferences. 3. Classification by size of accruals.Since the estimates we examine are components of total accruals, we classified the sample firms into three groups, by the size of accruals, to check whether accruals size affe cts our findings. Specifically, for each sample year we ranked the firms by the size of total accruals (scaled by total assets), and then formed three groups: the top 25% of firms (high accruals), the middle 50% (medium accruals), and the bottom 25% (low accruals). We then generated cash flow and earnings predictions for each of the three accruals g

Structured society relies on people knowing how to survive in Western Civilization

Structured society relies on people knowing how to survive, and also how to survive with others. According to Owen, (1997), there exist the general skeleton of the social order which is so well distinct, planned, and planned that there’s room for personal freedom and creativity within the organization. In structured society, people works while every individual knowing his duty, for example if the society is structured, socially politically and economically. There need to be law and order hence need for specialization, this reduces conflict in terms of role assignment. The specialization is known to be the major drive for civilization. When mixed with division of labor, specialization allows for maintenance of law and order. In such societies duties and responsibilities are stated, for example in political structure we have the roles of the president affirmed and written in the constitution therefore one has guidelines to abide with. The leader has to have subject to rule, it’s not possible to have rulers if you have no people to rule, hence need for structured society whereby people are civilized and are able to live together in harmony. Law and order is very vital in such societies (Owen, 1997). Christiano (2004) observes that when we live within the law, we share in the common good which helps all, and provides for a better world to grow and live in. But In Aristotelian scholasticism, ethics which are the basis for law are understood to mean the science for good life (Barford, 1996). In the same context, man is regarded as rational animal and therefore able to act in accordance with the right reason and also able to act justly and courageous. As members of the society, we are supposed to come together and advance based on the laws of the society we live in. Reilly (2000) thinks that liberty was necessary for revolution only when used like a guiding rule, he emphasized that independence of each person must be respected. However, according to him total freedom for all cannot exist as a basis of the society. For one person to have entirely autonomy over another person, the other person will have to give up their freedom to allow the former to survive. When people move from their tribal clique, races to join new people in the working places for example town, they are said to undergo civilization which is a slow process which started long time ago more than 5000 years ago (Jessop, 1998). Civilization brings positive competition where everyone will do his best to be on the top of other ladder, sparkle. Civilized People are able to live together irrespective of their social background; it has increased trust between individuals to an extent that people are able to collect each other whenever a neighbor go astray, therefore togetherness in the community. Natural law is viewed by many philosophers as the instrument used in the exploration of gods will. As Martin, (1999) explains, natural law is different from theology, in that it does not rely fully on supernatural law or revealed sources but on empirical evidence concerning human existence and nature. Natural law is a source of social norm in the society. It provides the basis for moral system in different religious group. According to Owen (1997), in whatever setting of the society and religion, all share the common frame work of natural law. Looking at the process of absorbing social norm, members of a society utilize socialization and education to distinguish between the good and the evil. Social norms are based on human nature and are important convections required to achieve social stability. The major objective of natural law is to make or sustain socially valued roles for people in their society, in case where an individual holds valued social roles, one is highly likely to receive in return those good things in life that are obtainable in that society hence the society always a way of paying those people who adhere to its norms. In additional all sorts valued things that other people are able to pass on are almost involuntarily accorded to a person who holds societal appreciated roles, at least within the resources and norms ones society. (Barford, 1996). Most human being societies have adopted certain societal norms which result either from ethics or from intrinsic ideas. But according to Young, (2003), consequences are that they partially result to human societies being unable to forbid impunity. Eventually, serious tensions picks in the society that may lead to society’s demolition. Men in general learn to differentiate between good and evil through learning and socialization. Through reason, a man is able to distinguish between what is unacceptable and what can be accepted in a particular society. Some norms are vital for social stability and in this sense such norms are based on human natural history, they are conventions that we need to have a stable society. Therefore society norms and ethics have a major role in setting the society free from disorder (Barford, 1996). If law totally breaks down, then society is worse off than before (Owen, 1997). Socrates believed in this statement and totally refused to break the law. He wondered what kind of citizen he will be if he refused to accept the ruling of the jury. In addition Reilly (2000) in his book the social organization of today are dissimilar from the first civilizations in that primitive cultures depended on unity of people to live. However currently everyone depends on cash inform of monitory value and it has established the same as the common good. According to Kibuka (2000), the society without cash would work mainly because it goes against individual nature. No matter how genuine and accountable people are civilized, people always need a reward. He continue to express criticism that without the reward everything will have no value hence the world will still be far away from civilization. In his book Reilly (2000) argues that an operational, liberated and just society must rest on a basic principle. Right liberty cannot be real for all, unless the civil liberties of all are valued by all, these right can be liberty and the pursuit of happiness. According to Karl Marx, order is highly important for the organization and for maintenance of all human societies and to bring about civilization. He said the higher rank of order a society achieves, the more superior the society tends to be unable to find order and indeed the more chaotic it become (young, 2003). Marx contradicts with Reilly (2000) who thought civilization goes hand in hand with law and order in the system. He points out that through the period of anarchy and revolution a society mainly lack order and therefore becomes chaotic. Both Marx and Reilly (2000) however converge on the same thoughts that societies have a lot of the attributes of the united system; through swapping matter and energy to their surroundings as they add to their order specialization tend to develop. The world is an island and therefore we all need each other to survive and we communication which is the key to the organization and development of all human societies; this involves use of words and symbols. It’s therefore very vital to have a pattern of value, order and norms so that law and order will be maintained in a society; this explains why in a structured society there is need for law and order. In addition order and pattern is the core of social union and function (Cohen & Arato, 2001). Karl Marx quoted that though much energy is put in a society to maintain order, change is unavoidable hence he believed that every society can be destroyed if unity is not maintained by law and order (Young, 2003). At this juncture, Marx was in agreement with (Reilly 2000) who argued out that for there to be order in the society we need law to be followed for law and orders go hand in hand. Reilly (2000) believed that rational societies were structured to attain goals flexibly and were able to meet the test of time therefore adjusting for better. In what I regard as the major achievement of the Greek and Roman Empires, the ancient Greek empire has contributed a lot to civilization of the west. Since inception the Greek philosophy, it has continued to shape the whole of western thought impacting on modern philosophy and modern science (Jessop, 1998). Although many philosophers believe that neither inquiry nor the reason began with the ancient Greeks, the Socratic methods together with his ideas of form are entirely from the Greek. Socrates who was the teacher for Plato was an Athenian philosopher who believed that a person should strive always to do well. He emphasized that one should always know you and he was known for disobeying the bad command (Barford, 1996). Aristotle and Plato work forms the major philosophies that have greatly influenced the western philosophy. The Greece’s were very good in art, history, art and science which many countries including western countries borrowed to shape their growth of civilization. All these cultures begun with what is known as golden age of Greece: it’s the time of cultural prosperity peace and time of law and order in Greece. More so myths, Olympics, democracy rule of law all originated in Greece. Greek’s had a very rich culture which influenced western civilization. The most notable was mainly their philosophy and its culture which dictates their rich norms and values (Hefner, 1998). Greek scientist made radical discoveries in several fields like in mathematics, physics, medicine, biology and astronomy. This forms part of the reason why Greek civilization is still regarded as mother of discoveries. On addition it was first in Greeks where commercial trading post and colonies were founded this led to the growth of trade which in turn led to adoption of septic alphabetical scrip. These scripts led to the development of the subject mathematic. The Greek had several enemies who wanted to conquer them. The conflicts with the Persians did not only make the Greek Empire become very strong but also allowed establishing a very strong form of government which favored specialization (Hefner, 1998). To an extent ancient Greece affected civilization of the west with politics, this is because the Greece was the first to establish the democratic systems. Laws as it’s in many western countries laws were voted on and proposed directly by the assembly of all citizens therefore Greece offered a form of government which is used by the western countries including the US. A form of government which has the Executive branch, the judicial branch and the judicial branch began with the Greece and later borrowed by the west. Greece was the first to realize the important of sports and make sport their tradition hence the first Olympic was held there. Surprisingly, up to date the western countries still compete on the same sports which were held on the first Olympics (Martin, 1999). For ancient Roman, Engineering was a main issue influencing western civilization. Nowadays the Greek technologies are used to build bridges, harbors and roads were buildings in the west. Cohen and Arato (2001) express no doubt that civilization of the west has been shaped and largely based on Greece’s powerful politics, philosophers, medics, sports and classical art. The society has played a big role in the invention of law, in order to advance the concept of the common good. The common good was crucial to normative vision of what can be regarded as good life during the time of the Greek moral philosophy that formed the basis of western thought. The common good entails grasping idea that a person as sacred and social. Common good is based on understanding that human rights and dignity together with well being and human potential are achieved in one’s moral ecology. On the other hand it is the social justice that orients the moral action to the common good. Every person in the society who is dedicated to the quality of life and to the well being of every body gives in to the common good of all since. Plato asserted that in a just society, citizen bestowed themselves to the common good, act morally and wisely, and practices the occupation they are best suited. Aristotle contrary to that recommended that a state should be governed by middle class, because he thought that they are likely to struggle for fairness of the common good. Moreover he stressed that an individual depends on the society in order to survive a truly human life, and even that the state is a natural creation that precedes a person (Owen, 1997). As per St. Augustine, he diverted the natural law of society from one based on reason to one based on divine rule. In his argument, St Augustine Hefner (1998) apprehends God and churches as the vital base of civic virtue, law and order of the social order. Therefore religion is very important in shaping human destiny, for church offers laws and ethics to be followed. Its society’s role to come out with guidelines for defining what is norm and what is right. It is also the society role in general to mold its own people. It has a function of maintaining law and order hence protecting its people. Jessop, (1998) asserts that the main function of civil society is to compel human beings to respect one another’s rights. Civilization can be achieved only when the civil societies in the western countries protect its members to pursue diverse interest at the same time the political parties striving to guide the members towards party goals. Nevertheless, many philosophers predict that the western civilization is on the verge of collapsing. Cohen and Arato (2001) attribute the collapse to invasion of the west culture by other cultures. Although, the west citizens are slowly rejecting their community culture, they still hold some sense of commitment towards it.

The US presidency Essay Example | Topics and Well Written Essays - 2500 words

The US presidency - Essay Example Any sane resident of the United States knows for sure that the history of presidential authority had known 44 American presidents, that the first U.S. president was George Washington, "the father of all Americans," who ruled the country from 1789 to 1797, that the current State President, Barack Hussein Obama, was elected in 2009 from the Democratic Party and is the 44th the president, in general, and the first black leader in the states’ history. The past twentieth century presented the United States with Vivid, unforgettable leaders. In the face of the presidents of the twentieth century, from William McKinley and Theodore Roosevelt, at the beginning of last century, to George Herbert Walker Bush (1989-1993) and William Jefferson Clinton (1993-2001) at the end, the state had talented, intelligent, energetic leaders. However, their acts were not always beneficial for the state and sometimes brought evil and suffering to peoples all over the world. This paper will discuss two leaders of the American people, who were destined to govern the largest state in the world in a bygone age, democrat Lyndon Baines Johnson (1963-1969) and republican Richard Milhous Nixon (1969-1974). Lyndon Baines Johnson (1908-1973) began his political career in 1931 as secretary of Congressman R. Kleberg. By 1948, held the chair of senator and in 1955, he became the first leader of the Democratic Party. In 1960, Johnson decided to run for president. However, an election victory in 1960 was won by John Fitzgerald Kennedy (1961-1963), and Johnson preceded the powers of the Vice President on January 20, 1961. In 1963, Kennedy was assassinated on the 22 of November, and since that day Johnson began to serve as president. The end of the presidency of Lyndon Johnson was the 20th of January, 1969, when Nixon was inaugurated. After this event, the 36th U.S. President Lyndon Baines Johnson went to his ranch in Texas. He dropped out of high policy, wrote memoirs, and occasionally lectured at the University of Texas. He died on January 22, 1973, in his hometown of Stonewall of a third heart attack, caused by long smoking (Evans & Novak 1964). Richard Milhous Nixon's (1913-1994) became the youngest partner in the oldest law firm of Whittier’s "Wingert and Bewley" after graduating the Law School at Duke University in Durham (North Carolina) in 1934. And at age of 26 - became the youngest trustee of Whittier College. In August, 1942, he became a lieutenant of the Navy. He served as an officer in the aviation ground services in the Pacific. He was retired from the army in 1946 with the rank of Lieutenant Commander. In 1946, Nixon became a congressman. In 1950 - a senator. During the presidency of Dwight D. Eisenhower (1953-1961), Richard Nixon served as vice president. Eisenhower delegated much more power to his vice president, contrary to any of his predecessors. Nixon attended the majority of meetings between the president and the Cabinet of Ministers or Congress ional leaders. When being a chairman of the Presidential Commission for Public Contracts, Nixon took much pain to eliminate discriminatory hiring system. As a chairman of the Committee for Economic Development under the Cabinet of Ministers, he played an important role in ceasing the strike of steel workers in 1959. In three cases (1955, 1956 and 1957) he assumed the administrative functions of the president (during President’

Popular culture Essay Example | Topics and Well Written Essays - 1000 words

Popular culture - Essay Example The main character is ostensibly Jeff Winger (played by Joel McHale), a handsome, conniving lawyer who has to go to a community college when he is revealed to have a fake degree. However, the key character is actually Abed Nadir, a young Arab-American who has Asperger’s syndrome, a form of autism. This plays on the audience’s assumption that the handsome white man is always the hero and the most important character. For the first few episodes, the audience is led to believe that the show is about Jeff and his pursuit of the beautiful blonde Britta while a group of co-stars provide comic relief; later we see that the show is actually about Abed and his attempts to understand other people. Because of his Asperger’s syndrome, Abed is fixated on television and movies, and comparing everything in his life to TV and movies is his only way to relate to the people around him. Every episode either references the plot of specific movies and shows, or parodies a particular genre of movies. As the viewer watches for several episodes, it becomes apparent that the entire show is filtered through Abed’s perspective. This is different from other shows. With nearly all other TV shows, there is an unspoken agreement between the makers of the show and the audience that the audience will suspend their disbelief and pretend for an hour or a half an hour each week that the events in the show are true. Community betrays this agreement by subtly suggesting to the audience that the events in the show might not be real. Of course the audience knows this, but everyone is supposed to pretend that that’s not the case. It then makes the audience unsure of what is real within the world of the show. Is Abed real? Is he imagining everything, or just modifying reality a little bit? If we could see the show from outside of Abed’s perspective, would the characters even really be Abed’s friends, and would any of the events we’ve seen them ena ct have actually happened? The humor in the show requires the audience to have a base of knowledge about pop-culture in order to get the jokes. The show doesn’t assume that the audience is stupid and needs everything to be simple or have everything explained to them, but instead assumes a certain amount of shared cultural experience. The assumption is that enough people have seen The Breakfast Club, for example, or perhaps Pulp Fiction, that when an episode references one of those movies, most of the audience will get it. According to Steven Johnson, author of Everything Bad Is Good for You, this is a recent phenomenon in television. TV used to be much simpler and did not require the same amount of memory or mental work to understand. This points to an increase in the demand by audiences for more intelligent and challenging humor (85-87). Community also does not give the same clear-cut moral messages that other TV shows did in the past. Most television shows from previous era s held to the same moral and political values. They preached against racism and in favor of diversity, paid lip-service to feminism while still mostly showing women in traditional roles, and spoke in favor of traditional â€Å"family values.† Community portrays a world where things are not that simple. For example, it shows rather than tells us that race and diversity is a confusing topic and that things do not fit perfectly into a â€Å"

Education and Testing Standards Essay Example | Topics and Well Written Essays - 1250 words

Education and Testing Standards - Essay Example "Under No Child Left Behind, states are required to include annual assessments in reading/language arts and mathematics in grades 3 through 8 along with and at least once in grades 10 through 12. Additionally, all states are to begin annual assessment of their students in science at least once in each grade band 3-5, 6-9, and 10-12 (NCLB: Standards and Assessments, 2009). This paper deals with NCLB in the State of Texas. There isn't any significant difference in the NCLB for Texas when compared to the one in any other state. Nonetheless NCLB in Texas is unique to education in this state (Adopted Amendments to 19 TAC). The achievement standards have been set by time-bound plans that require the level of students' performance to rise within a set period after analyzing and improving the quality of teachers and the educational system which rewards schools that meet their targets and has consequences for schools that fail to meet the standards (Mitzel, Howard C; 2005). Simultaneously, the need to involve parents and also society in raising the achievement standards of the student are mentioned. Efforts are also being made to make the curriculum suitable for the students' grasp although no examples were outlined to show just how students could improve on the basis of the new curriculum. The curriculum consists... The credits for each discipline are provided (Adopted Amendments to 19 TAC). The methods of raising achievement levels are left to "extending existing achievement standards" and that "instruction will need to improve for students to meet future standards" (Mitzel, Howard C; 2005, p4). Teachers' Standards The achievement standards outlined for NCLB are tough considering that even teachers have to be updated on their skills in order to be equal to their tasks. The important aspect of making the right beginning is present in the NCLB and the state educational boards have been making the right moves by interacting with teachers and getting their skills updated and also keeping teachers under scrutiny to gauge their interaction with the students (Summary Description of California Housse). At one inspection it was found that "approximately one-third, or almost 5,000 of all school districts in considered rural. As Department officials have traveled the country listening to teachers and state and district officials, they frequently have heard that the highly qualified teacher provisions of the No Child Left Behind law don't adequately accommodate the special challenges faced by teachers in small, rural districts. Often, the teachers in these areas are required to teach more than one academic subject. This new flexibility is designed to recognize this challenge and provide additional time for these teachers to prove that they are highly qualified" (New No Child Left Behind Flexibility: Highly Qualified Teachers, 2004). National Standards For a nation with fifty states, it is difficult to pursue a uniform policy without coming across situations where different states see issues in a different way. Nonetheless, since NCLF has flexible measurements the states have been given

Competition Mergers of Companies Essay Example | Topics and Well Written Essays - 750 words

Competition Mergers of Companies - Essay Example It provides communication and entertainment answers to the majority of countries in the European Union. CaixaBank is a financial enterprise that is controlled entirely by the La Caixa Group of companies. It is the parent company of La Caixa Companies that deal with banking and other related activities. It mainly operates in Spain and other European countries and the international presence are felt through strategic alliances with key financial institutions. Banco Santander is the main company of the Banco Group of companies that deals major in international banking. It is active in retail banking, asset management, insurance and investment banking in most of the European Countries. Telefonica, CaixaBank and Banco Santander merge to form a new company. The companies are the notifying parties in the creation of Newco. The notifying companies provide the relevant documents that are used in the merger control of the joint venture. Newco will be active in Spain and it will develop an ecosystem that will be able to offer its members with numerous services. The services will be available online and will be accessible by many individuals online. Each of the Notifying parties will hold equal shareholding in Newco. They will have equal chances to exercise control over the company. It means that they will have a joint control over the Newco. Newco is expected to perform the functions of an economic enterprise in Spain. There will be a management team that will be run the day to day activities of the company. The management team will have access to the resources of the company that include finance and the assets of the company. The company will provide online services to numerous individuals in Spain. The services will include digital advertising services that will provide a chance to individuals in the digital world to advertise their products. The virtual community will be able to able to interact online and provide mobile-based couponing and loyalty services.     

Principles of tax income law Essay Example | Topics and Well Written Essays - 2750 words

Principles of tax income law - Essay Example In John’s case, he is an employee of a real estate agent but he is carrying out personalised investment activities. This can be seen with the purchase of the motel in order to sell it out as a kindergarten later. A purchase of this kind can be considered as an investment carried out with the intention to make a profit. In terms of the bigger picture, John’s investment activity can be considered as a business activity in ordinary usage since he invests money in order to derive a profit. Receipts or profits created through business activities are treated as ordinary income for most circumstances3 4. In cases where there may be payment complications or where receipts cannot be created from proceeds of business, income may not be seen as ordinary5. However, in John’s case, if the real estate sold out it would have produced a simple income receipt that would have been considered as ordinary income. The onset of the flood and the clearing up of the land can further be considered as business activities on John’s part in order to add value to his property. The assessment that John’s land carried underground hot water reservoirs merely added even more value to his land. John is now being offered money based on the value addition on the motel site he purchased. The value addition activities of John can be seen as business activities analogous to any other value addition properties carried out by any other business. As long as there is â€Å"sufficient connection† between John’s income derived from the sale of land and value addition on the land, John’s income will be categorised as ordinary income according to FCT v Consolidated Press Holdings Ltd (No 2)6 7. A scrutiny of John’s circumstances reveals that he purchased land with a view to make profit and his final transaction with Green Energy results in profit. Such income is considered ordinary income for taxation purposes. Problem Question 1B The capital ga ins tax (CGT) applies to any forms of capital gains made when an asset is disposed off except for certain exemptions. Most exemptions related to CGT in Australia are based on items of personal use as well as exemptions to promote certain business activities. Moreover, the CGT enforced in Australia provides for rollovers under certain circumstances. The contention behind CGT is to tax income that falls within the capital gain category so that it cannot be drained off for other purposes. Assessments for CGT rely on considering any net gains as part of the taxable income structure for a single tax year8. The net gains may result from the sale of owned assets or from any other forms of disposal of assets. Any form of assets held by an individual for a period of one year or more are given a fifty percent discount when considering the CGT on disposal9. CGT was introduced to Australia in 1985 and any assets held by a person before this are exempt from CGT. Assets acquired by a person in or after 1985 are considered alone in CGT deductions10. In the case of Kimberly, her assets were mostly formed well after 1985 so CGT applies to most of her assets except those that are exempt under current CGT laws. In addition to this observation, it is noteworthy that up to 1999, CGT applied after an assessment of the consumer price index (CPI). Under this scheme, changes in the price of an asset due to consumption

People with bad manners surround us Essay Example | Topics and Well Written Essays - 250 words

People with bad manners surround us - Essay Example According to the research findings bad manners disrupts other people, infringe their comfort, and as Nightingale explains, is a serious concerns when it interferes with expected utilities that people have paid for. Staring at people that you do not know, with a possible implication that they also do not recognize you, for instance, has a tendency of creating suspicion from the target. This may lead to discomfort, as a person may feel insecure or embarrassed for thoughts of improper conduct. Consequently, the observer interferes with the targets comfort. Gossiping loudly in the library is another example of bad manners that distracts people from the environment’s main activity. Being a place for either borrowing resources or studying the resources, the library should be quiet, conducive for study or communication with attendants. Loud gossips in the place therefore adversely affect other people, especially the studying group. Another form of bad manners in a public environment is swearing loudly. This has an impact of raising alarm among other people, leading to fear and animosity. Its negative effects on people may also lead to health complications from involuntary biological reactions. Staring at people that you do not know, gossiping loudly in the library, and swearing in the public therefore significantly pose adverse conditions to other people and are consequently bad manners.