1、<p>　　2400單詞，3600漢字，12660英文字符</p><p>　　出處：Ragothaman, Srinivasan Carr, David. The Impact of Environmental Information Disclosures on Shareholder Returns in a Company: An Empirical Study[J]. Internationa

2、l Journal of Management, Dec2008, Vol.25 Issue 4, p613-620</p><p><b>　　原文二：</b></p><p>　　The Impact of Environmental Information Disclosureson Shareholder Returns in a Company: An Em

3、pirical Study</p><p>　　Srinivasan Ragothaman</p><p>　　University of South Dakota</p><p>　　David Carr</p><p>　　University of South Dakota</p><p>　　The Emerg

4、ency Planning and Community Right to Know Act (1986) has mandated Toxic Release Inventory (TRI) disclosures in the United States. This Act requires all</p><p>　　manufacturing companies (SIC code 20-39) who e

5、mploy more than 10 people to provide an annual report about the release of more than 300 specified toxic chemicals. Similar legislation exists in other countries as well. How is this information used by investors and cor

6、porations? We develop and test a regression model to answer this question. We also perform a few robustness tests. Our sample comes from TRI disclosures for “top 100” corporate polluters based on COMPUSTAT data. Descript

7、ive statistics</p><p>　　1. Introduction</p><p>　　The disastrous Union Carbide accident that occurred in India in 1984 and other smaller chemical accidents have caused anxiety in the public’s min

8、d about the release of chemicals from factories. The Emergency Planning and Community Right to Know Act (1986) has mandated Toxic Release Inventory TRI disclosures. This Act requires all manufacturing companies (SIC code

9、 20-39) in the United States who employ more than 10 people to provide an annual report about release of more than 300 specified toxic </p><p>　　EPA’s Environmental Economics Research Strategy (EPA, 2004) id

10、entifies measuring the benefits of environmental information disclosures as one of its high priority research areas. Some interesting research results have already been published. For example, Konar and Cohen (1997) repo

11、rt negative stock price reactions to TRI disclosures in 1989. These negative stock returns forced companies to change their behavior. Those firms with the largest negative stock market returns to TRI announcements in 1&l

12、t;/p><p>　　Several researchers have conducted event studies and documented negative stock price reactions to TRI announcements (Hamilton 1995 and Khanna et al. 1998). Event studies examine the stock price react

13、ions on one or two days when the environmental information is disclosed. Klassen and McLaughlin (1996) also reported significant negative stock price reactions to bad environmental news such as oil spills. These event st

14、udies do not analyze longer-term stock price trends. These studies have generally</p><p>　　2. Prior Research</p><p>　　Karpoff and Lott (1993) report that when corporate illegal activities and ot

15、her fraudulent financial schemes are revealed, stock price declines have been the result. In order to estimate the value of intangible assets, we propose to include environmental performance information among the explana

16、tory variables (see Konar and Cohen 2001). Good environmental performance can translate into a good reputation for the firm as an ecology-friendly company and this can increase investor trust (Ragothaman </p><

17、p>　　This research builds on prior research and expands knowledge in several different and new ways. 1) Data used in this study are more recent (than 1989) and come from TRI disclosures for the year 2000; 2) Tobin’s q

18、is measured in accordance with suggestions from finance scholars; 3) The regression model includes some new variables; and a cross-sectional regression model is used. Descriptive statistics and correlation measures are a

19、lso provided. New insights are gained about the impact of environme</p><p>　　Beta is a measure of the risk associated with owning shares in a firm and is commonly used to measure market risk. Konar and Cohen

20、 (1997) utilize beta to control for the systematic risk in security returns. Beta is included in this study as a control variable. Various measures of firm size appear in the literature. Dowell, Hart, and Young (2000) us

21、e the logarithm of total assets with mixed results in examining whether corporate global standards create or destroy market value. Hamilton (1995) use</p><p>　　Waste (toxic air release) is measured as waste

22、disposal in pounds per revenue-dollar. Waste should be negatively related to Tobin’s q, as it measures the extent to which firms are “dirty.” Konar and Cohen (1997) use toxic chemical releases and the number of lawsuits

23、to proxy waste. Hamilton (1995) uses the number of superfund sites to proxy waste. Return on assets (ROA), defined as net income divided by total assets, is used as a measure of firm-level performance. It is a proxy for

24、profitability</p><p>　　Another control variable used in this study is the price-to-earnings ratio. The price-to-earnings (PE) ratio is measured as the market price of a firm’s common stock divided by the fir

25、m’s income-per-share of common stock. The PE ratio is included in the model as a control variable to pick up the effect of firm-level growth. Firms that are growing rapidly should have a higher market valuation, as measu

26、red by Tobin’s q. Yet another control variable used in this paper is “audit opinion” which is a </p><p>　　3. Methodology and data sources</p><p>　　Researchers at the Political Economy Research I

27、nstitute (PERI) at the University of Massachusetts released, in 2004, the list of the top 100 corporate air polluters based on TRI data disclosed by companies in the year 2000. The toxic (air release) waste data are repo

28、rted in pounds per revenue dollar. Data from COMPUSTAT were used to compute several operating and financial ratios for these 100 firms. The following independent variables were obtained from the COMPUSTAT database: marke

29、t beta, retur</p><p>　　The multiple regression model used in this study is:</p><p>　　Tobin’s q = f {market beta (risk), logarithm of number of employees, waste discharge per revenue dollar, retu

30、rn on assets, P/E ratio and audit opinion}</p><p>　　The research questions are transformed into null hypotheses as given below:</p><p>　　H1: Beta has no significant effect on Tobin’s q.</p>

31、;<p>　　H2: Size as measured by number of employees has no significant effect on Tobin’s q.</p><p>　　H3: Waste discharge has no significant effect on Tobin’s q.</p><p>　　H4: Return on asse

32、ts has no significant effect on Tobin’s q.</p><p>　　H5: Growth as measured by the P/E ratio has no significant effect on Tobin’s q.</p><p>　　H6: Corporate governance as measured by audit opinion

33、 has no significant effect on Tobin’s q.</p><p>　　4. Results and discussion</p><p>　　The descriptive statistics are reported in Table 1. The average Tobin’s q for the sample firms is 2.176. The

34、average amount of toxic air release (waste discharge) is 0.0009 pounds per revenue dollar. The mean for return of assets is 4.648 percent. The average beta (risk measure) is 1.121</p><p>　　Table 1: Descripti

35、ve Statistics</p><p>　　Q ratio = Tobin’s Q</p><p>　　Beta = Market beta (risk)</p><p>　　LEMP = Logarithm of number of employees</p><p>　　Waste = Waste disposal per reven

36、ue-dollar</p><p>　　ROA = Return on assets</p><p>　　P/E ratio = Price Earnings ratio</p><p>　　AUOP = Audit opinion</p><p>　　A correlation analysis of these six explanato

37、ry variables with the Tobin’s q and other independent variables was performed. The correlation results are reported in Table 2.</p><p>　　The correlation analysis results indicate that Tobin’s q is strongly r

38、elated to return on assets. The higher the return on assets, the higher is Tobin’s q. Beta, firm size and waste discharge are all negatively related to Tobin’s q. Beta and return on assets have strong negative correlatio

39、n. Firm size and waste discharge are negatively correlated.</p><p>　　Multicollinearity among independent variables may be present in the data and can potentially lead to unstable regression coefficients. A r

40、ule of thumb is suggested by Judge et al. (1985) to assess the impact of multicollinearity. They argue that a serious multicollinearity problem arises only when correlations among the explanatory variables are higher tha

41、n 0.8. In our dataset, the highest correlation is between return on assets and beta at -0.411. Hence, the degree of collinearity present appea</p><p>　　An ordinary least-squares regression model was develope

42、d to investigate the relationship between Tobin’s q and toxic air release, beta, return on assets, growth and other independent variables. Regression methodology permits the testing of six null hypotheses simultaneously.

43、 Tobin’s q was the dependent variable and the six explanatory variables mentioned earlier were the independent variables. The regression coefficients, t-statistics (in parentheses), and significance levels are reported i

44、n Tab</p><p>　　4. Results and discussion</p><p>　　The descriptive statistics are reported in Table 1. The average Tobin’s q for the sample firms is 2.176. The average amount of toxic air release

45、 (waste discharge) is 0.0009 pounds per revenue dollar. The mean for return of assets is 4.648 percent. The average beta (risk measure) is 1.121</p><p>　　Table 1: Descriptive Statistics</p><p>　

46、　Q ratio = Tobin’s Q</p><p>　　Beta = Market beta (risk)</p><p>　　LEMP = Logarithm of number of employees</p><p>　　Waste = Waste disposal per revenue-dollar</p><p>　　ROA

47、 = Return on assets</p><p>　　P/E ratio = Price Earnings ratio</p><p>　　AUOP = Audit opinion</p><p>　　A correlation analysis of these six explanatory variables with the Tobin’s q and

48、 other independent variables was performed. The correlation results are reported in Table 2.</p><p>　　The correlation analysis results indicate that Tobin’s q is strongly related to return on assets. The hig

49、her the return on assets, the higher is Tobin’s q. Beta, firm size and waste discharge are all negatively related to Tobin’s q. Beta and return on assets have strong negative correlation. Firm size and waste discharge ar

50、e negatively correlated.</p><p>　　Multicollinearity among independent variables may be present in the data and can potentially lead to unstable regression coefficients. A rule of thumb is suggested by Judge

51、et al. (1985) to assess the impact of multicollinearity. They argue that a serious multicollinearity problem arises only when correlations among the explanatory variables are higher than 0.8. In our dataset, the highest

52、correlation is between return on assets and beta at -0.411. Hence, the degree of collinearity present appea</p><p>　　An ordinary least-squares regression model was developed to investigate the relationship b

53、etween Tobin’s q and toxic air release, beta, return on assets, growth and other independent variables. Regression methodology permits the testing of six null hypotheses simultaneously. Tobin’s q was the dependent variab

54、le and the six explanatory variables mentioned earlier were the independent variables. The regression coefficients, t-statistics (in parentheses), and significance levels are reported in Tab</p><p><b>

55、　　譯文二：</b></p><p>　　關于企業(yè)環(huán)境信息披露對股東回報影響的實證研究</p><p>　　Srinivasan Ragothaman</p><p>　　University of South Dakota</p><p>　　David Carr</p><p>　　University

56、 of South Dakota</p><p>　　在美國，應急計劃和社區(qū)知情權法案（1986）被授權披露企業(yè)有毒排放清單。這個法案要求所有雇傭超過10人的制造公司（代碼20-39）每年須提供年度報告，該報告包括300多種指定的有毒化學品排放情況。除美國以外，其他國家也相應建立了類似的法案。那么投資者和合作者提供的這些信息有什么用處呢？我們可以建立并運用一個回歸模型來回答這個問題。另外，我們還進行一些魯棒性測試

57、。我們取來自 “100強”企業(yè)污染統(tǒng)計數據為樣本，另外提供描述性統(tǒng)計和相關措施。結果發(fā)現(xiàn)企業(yè)的資產回報率越高，則托賓Q系數就越高（企業(yè)價值或股東財富）。廢物處理變量（有毒氣體排放）是一個統(tǒng)計學預測托賓Q系數作為預期，該標志的回歸系數的廢物處置是消極的。此外，公司規(guī)模的大小對托賓Q系數有重大影響。公司測試的市盈率，以及公司治理變量都具有統(tǒng)計學意義。</p><p><b>　　1、簡介</b>

58、</p><p>　　1984年發(fā)生發(fā)生在印度的因為聯(lián)合碳化物造成的災難性事故和其他化學事故使得那些民眾開始對于排放化學物質的工廠焦慮起來。應急計劃和社區(qū)知情權法案（1986）規(guī)定那些工廠應披露有毒物質排放清單。這個法案要求所有美國雇傭超過10人的制造公司（代碼-39）需提供一個關于300多種規(guī)定的有毒化學物品排放情況的年度報告。有毒物質排放清單由美國環(huán)境保護局（美國環(huán)保署）向公眾公開。那么投資者和公司合作者如何

59、利用這些信息呢？</p><p>　　環(huán)保署的環(huán)境經濟學研究戰(zhàn)略（環(huán)保局，2004）認識到把環(huán)境信息披露作為一個高度研究領域的好處。在此已發(fā)表了一些有趣的研究結果。例如，1989年，庫納爾和科恩（1997）發(fā)現(xiàn)有毒物質排放清單的披露對于公司股價有消極作用。這些負面的股票收益使得企業(yè)不得不改變他們原始的行為。那些受到股市負面影響的公司在1989年有毒物質排放清單公開以后開始減少其排放量，并且其排放量低于同行業(yè)的其他

60、公司水平。本研究目的在于通過托賓Q系數來得知有毒物質排放清單披露和公司價值衡量之間的關系。有毒物質排放清單披露和公司價值兩者的關系將通過一個回歸模型的開發(fā)和測試來發(fā)現(xiàn)。此外還要進行幾次魯棒性試驗。托賓Q系數是一種在金融文學中廣泛使用的用來解釋公司價值（龔帕斯，石井和梅特里克，2003），并作為本項研究中所用的因變量。</p><p>　　一些研究人員已經進行了研究并記錄了有毒物質排放清單公開對股票價格的負面作用（

61、漢密爾頓1995和康納等人1998）。研究人員發(fā)現(xiàn)，在環(huán)境信息披露以后，公司股價的不良反應會持續(xù)一至兩天?？死望溈藙诹郑?996）也發(fā)現(xiàn)公司的股價會受不良環(huán)境新聞的影響如漏油事件。但這些研究并沒有對長期股票價格趨勢進行分析。再者這些研究一般都只用了較小的樣本。此外，他們所使用的1989年的數據，距今有十八年了。為了克服這些困題，我們須使用最近的數據來自2000年披露的有毒物質排放清單信息來建立一個新的回歸模型。有毒物質排放清單披露的

62、數據是在從環(huán)保署提供的原始數據報告的基礎上進行匯編 ，而不是根據個別公司具體情況進行。搜集公司數據的困難使2000年有毒排放清單揭露了很多最近有效的數據。</p><p><b>　　2、先前的研究</b></p><p>　　卡波夫和洛特（1993）報告說，當公司的非法活動和其他欺詐性財務計劃被公開，則會造成股價下跌。為了估計無形資產的價值，我們建議將環(huán)境性能信息計

63、入到的解析變量中（庫納爾和科恩2001）。良好的環(huán)保性能可以贏得一個良好的生態(tài)公司聲譽，還可以增加投資者的信賴（ragothaman和Lau，2000）。相反，惡劣環(huán)境性能可導致股票價格下降。</p><p>　　本研究是建立在先前的研究和不同新方法的發(fā)展上：1、本研究所使用的數據來自1989以后的數據和2000年披露的有毒物質排放清單；2、托賓Q系數是根據金融學者的建議來測量的；3、回歸模型包括了一些新的變量和

64、運用了一個橫截面回歸模型。本研究還提供了描述性統(tǒng)計和相關措施。從而得到了是關于環(huán)境信息披露對股東回報的影響的新見解。我們制定的托賓Q系數的公式是根據Chung和普魯特（1994）、Hirschey和康納利（2005）的研究，Q等于流通普通股的市場價值加上總資產的賬面價值減去普通股股本所得到的值除以總資產的賬面價值。托賓Q系數用來衡量公司市場價值。在本文中，環(huán)境信息披露對公司市場價值的影響就可以通過托賓Q系數來說明。</p>

65、<p>　　系統(tǒng)性風險指標（beta系數）是衡量股票風險，通常用來測試市場風險的。庫納爾和科恩（1997）利用beta系數來控制因為系統(tǒng)性風險所獲得安全收益。在這項研究中，beta系數作為控制變量。在很多文獻中提到了各種公司規(guī)模的測試。道維爾，Hart和Young（2000）在審查中使用總資產對數得出混合的結果：公司全球標準對市場價值是有利也有弊。漢密爾頓（1995）在研究中使用的員工的人數來形容一個公司規(guī)模，研究有毒排放清

66、單數據、媒體與股票市場反應這三者之間的關系。雇員人數的對數值（LEMP）是用來形容的公司規(guī)模的大小，并在模型被作為另一個控制變量。</p><p>　　廢物（有毒氣體排放）量是廢物處理量以磅/美元單位來衡量的。廢物量與托賓Q系數呈負相關，因為它能測試企業(yè)“臟”的程度。庫納爾和科恩（1997）利用有毒的化學物質排放情況和一些代理訴訟案件。漢密爾頓（1995）采用有毒廢物堆污染清楚基金來代替廢物量進行研究。資產回報率

67、，是用來衡量企業(yè)績效，其值等于凈收益除以總資產。它是一個代理的盈利能力。資產回報率與托賓Q系數呈正相關，由于一些發(fā)展良好的企業(yè)比較重視市場盈利，前提條件為其他條件不變的情況下。Hirschey和康納利（2005）用邊際利潤來衡量盈利能力。</p><p>　　本研究中采用的另一個控制變量是市盈率。市盈率是衡量市場的公司的普通股的市場價格除以公司的每股收益。市盈率被包含在模型作為控制變量反映影響企業(yè)成長。根據托賓Q

68、系數，正在迅速增長的公司，應該有一個比較高的市場價值。本文中使用的另一個控制變量是注冊會計師針對該企業(yè)財務報表出具的審計意見。李等人（2005）發(fā)現(xiàn)一些具有較高的股票市場回報的企業(yè)往往得到更多的保留（或者不合格）的審計意見。換句話說，審計意見與公司的市場價值呈負相關。霍吉等人（2004）進行了實驗研究項目并得出結論認為，投資者對審計意見書的反映似乎暗示著管理戰(zhàn)略是解釋財務的最好結果。它可以假定，管理關注的是未來的業(yè)績，因此是對現(xiàn)在企業(yè)的

69、業(yè)績要有充分的了解。根據彩和杰特（1992），審計意見書表明，對未來現(xiàn)金流量的增加不確定，因此，未來公司的市場價值會受到不利的影響。</p><p>　　3、研究方法及數據來源</p><p>　　2004年，研究人員在麻州大學的政治經濟研究中心發(fā)表，基于2000年公司披露的有毒排放清單數據列出了前100個大污染企業(yè)。有毒廢料（氣體釋放）報告中的數據以美元/磅為單位進行報道。那些從標準數據

70、庫收集的數據是用來計算這100個公司的一些經營和財務指標。以下獨立變量便是從標準數據庫數據庫獲得的：市場測試，資產報酬率，雇員人數的對數值，市盈率與審計意見。根據hirschey（2005），托賓Q系數的公式為：托賓Q系數=[資產總額+總資產的市場價值-權益的賬面價值]/總資產。托賓Q系數也是利用標準數據庫中的數據來進行計算。由于在標準數據庫中缺少變量，有9家公司均下降。至少一個公司因為一個極端的異常值而被刪除。最后的樣本便是來自剩余9

71、0家公司的數據。</p><p>　　本研究采用的是多元回歸模型：</p><p>　　托賓Q系數=f{市場測試（風險），lg雇員人數，排污許可收入，資產受益，市盈率，審計意見}</p><p>　　所研究的問題轉化為零假設如下：</p><p>　　測試對托賓Q系數沒有重大影響</p><p>　　員工人數的規(guī)模對托

72、賓Q 系數沒有重大影響</p><p>　　廢水排放對托賓Q 系數沒有重大影響</p><p>　　資產報酬率對托賓Q系數沒有重大影響</p><p>　　市盈率對托賓Q系數沒有重大影響</p><p>　　公司的審計意見對托賓Q 系數沒有重大影響。</p><p><b>　　4、結論及分析</b&g

73、t;</p><p>　　表1為描述性統(tǒng)計報告表。其中樣本公司的托賓Q系數平均值為2.176 ；有毒氣體排放量的平均數額是0.0009鎊/美元。平均資產收益率是4.648%.平均風險測試是2.121</p><p><b>　　表1：描述性統(tǒng)計</b></p><p>　　Q ratio =托賓Q系數</p><p>　

74、　Beta=市場風險測試</p><p>　　LEMP =員工人數的對數值</p><p>　　Waste=每美元廢水廢物處理量</p><p>　　ROA=資產報酬率=</p><p>　　P/E ratio=市盈率</p><p>　　AUOP =審計意見</p><p>　　研究人員進行了

75、托賓Q系數及六個解析變量和其他獨立變量的相關分析。相關結果報告內容列示在表2</p><p>　　相關分析結果表明，托賓Q系數與資產報酬率是密切相關的。資本回報越高，則托賓Q系數越高，而托賓Q系數與公司規(guī)模及廢水排放量呈負相關。另外，市場風險測試與資產報酬率有較強的負相關。公司規(guī)模與廢水排放呈負相關。</p><p>　　獨立變量之間的多重共線性可能存在于數據中，從而有可能導致不穩(wěn)定的回歸

76、系數。一條由法官等人（1985）提出的經驗法則用來評估多重共線性的作用。他們認為，一個嚴重的多重共線性問題出現(xiàn)只有當解釋變量之間的關系高于0.8 。在我們的數據庫，相關性最高的是資產報酬率和市場風險測試的相關性，其值為-0.411 。因此，目前線性度太小以至于無法估計結果。</p><p>　　一個普通多元二次回歸模型進行為了調查托賓Q系數和有毒氣體排放，市場風險測試，資產報酬率，企業(yè)成長和其他獨立的變量之間的關

77、系。回歸方法允許六個零假設同時發(fā)生的測試。托賓Q系數是因變量，而前面提到的六個解釋變量是獨立變量?；貧w系數、T統(tǒng)計(在括號中)以及重要性水平內容列示在表3第I列。多元回歸模型有一個相當大的平均平方數調整為31.3%。</p><p>　　來源：Ragothaman, Srinivasan Carr, David. 關于企業(yè)環(huán)境信息披露對股東回報影響的實證研究[J]. 國際管理雜志, 2008, (25):613-