外文翻譯---關(guān)于企業(yè)環(huán)境信息披露對(duì)股東回報(bào)影響的實(shí)證研究

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(guān)于企業(yè)環(huán)境信息披露對(duì)股東回報(bào)影響的實(shí)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(guó)，應(yīng)急計(jì)劃和社區(qū)知情權(quán)法案（1986）被授權(quán)披露企業(yè)有毒排放清單。這個(gè)法案要求所有雇傭超過(guò)10人的制造公司（代碼20-39）每年須提供年度報(bào)告，該報(bào)告包括300多種指定的有毒化學(xué)品排放情況。除美國(guó)以外，其他國(guó)家也相應(yīng)建立了類(lèi)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(yùn)用一個(gè)回歸模型來(lái)回答這個(gè)問(wèn)題。另外，我們還進(jìn)行一些魯棒性測(cè)試

57、。我們?nèi)?lái)自 “100強(qiáng)”企業(yè)污染統(tǒng)計(jì)數(shù)據(jù)為樣本，另外提供描述性統(tǒng)計(jì)和相關(guān)措施。結(jié)果發(fā)現(xiàn)企業(yè)的資產(chǎn)回報(bào)率越高，則托賓Q系數(shù)就越高（企業(yè)價(jià)值或股東財(cái)富）。廢物處理變量（有毒氣體排放）是一個(gè)統(tǒng)計(jì)學(xué)預(yù)測(cè)托賓Q系數(shù)作為預(yù)期，該標(biāo)志的回歸系數(shù)的廢物處置是消極的。此外，公司規(guī)模的大小對(duì)托賓Q系數(shù)有重大影響。公司測(cè)試的市盈率，以及公司治理變量都具有統(tǒng)計(jì)學(xué)意義。</p><p><b>　　1、簡(jiǎn)介</b>

58、</p><p>　　1984年發(fā)生發(fā)生在印度的因?yàn)槁?lián)合碳化物造成的災(zāi)難性事故和其他化學(xué)事故使得那些民眾開(kāi)始對(duì)于排放化學(xué)物質(zhì)的工廠焦慮起來(lái)。應(yīng)急計(jì)劃和社區(qū)知情權(quán)法案（1986）規(guī)定那些工廠應(yīng)披露有毒物質(zhì)排放清單。這個(gè)法案要求所有美國(guó)雇傭超過(guò)10人的制造公司（代碼-39）需提供一個(gè)關(guān)于300多種規(guī)定的有毒化學(xué)物品排放情況的年度報(bào)告。有毒物質(zhì)排放清單由美國(guó)環(huán)境保護(hù)局（美國(guó)環(huán)保署）向公眾公開(kāi)。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(jīng)濟(jì)學(xué)研究戰(zhàn)略（環(huán)保局，2004）認(rèn)識(shí)到把環(huán)境信息披露作為一個(gè)高度研究領(lǐng)域的好處。在此已發(fā)表了一些有趣的研究結(jié)果。例如，1989年，庫(kù)納爾和科恩（1997）發(fā)現(xiàn)有毒物質(zhì)排放清單的披露對(duì)于公司股價(jià)有消極作用。這些負(fù)面的股票收益使得企業(yè)不得不改變他們?cè)嫉男袨?。那些受到股市?fù)面影響的公司在1989年有毒物質(zhì)排放清單公開(kāi)以后開(kāi)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(guò)托賓Q系數(shù)來(lái)得知有毒物質(zhì)排放清單披露和公司價(jià)值衡量之間的關(guān)系。有毒物質(zhì)排放清單披露和公司價(jià)值兩者的關(guān)系將通過(guò)一個(gè)回歸模型的開(kāi)發(fā)和測(cè)試來(lái)發(fā)現(xiàn)。此外還要進(jìn)行幾次魯棒性試驗(yàn)。托賓Q系數(shù)是一種在金融文學(xué)中廣泛使用的用來(lái)解釋公司價(jià)值（龔帕斯，石井和梅特里克，2003），并作為本項(xiàng)研究中所用的因變量。</p><p>　　一些研究人員已經(jīng)進(jìn)行了研究并記錄了有毒物質(zhì)排放清單公開(kāi)對(duì)股票價(jià)格的負(fù)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(jià)的不良反應(yīng)會(huì)持續(xù)一至兩天?？死望溈藙诹郑?996）也發(fā)現(xiàn)公司的股價(jià)會(huì)受不良環(huán)境新聞的影響如漏油事件。但這些研究并沒(méi)有對(duì)長(zhǎng)期股票價(jià)格趨勢(shì)進(jìn)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(shù)據(jù)，距今有十八年了。為了克服這些困題，我們須使用最近的數(shù)據(jù)來(lái)自2000年披露的有毒物質(zhì)排放清單信息來(lái)建立一個(gè)新的回歸模型。有毒物質(zhì)排放清單披露的

62、數(shù)據(jù)是在從環(huán)保署提供的原始數(shù)據(jù)報(bào)告的基礎(chǔ)上進(jìn)行匯編 ，而不是根據(jù)個(gè)別公司具體情況進(jìn)行。搜集公司數(shù)據(jù)的困難使2000年有毒排放清單揭露了很多最近有效的數(shù)據(jù)。</p><p><b>　　2、先前的研究</b></p><p>　　卡波夫和洛特（1993）報(bào)告說(shuō)，當(dāng)公司的非法活動(dòng)和其他欺詐性財(cái)務(wù)計(jì)劃被公開(kāi)，則會(huì)造成股價(jià)下跌。為了估計(jì)無(wú)形資產(chǎn)的價(jià)值，我們建議將環(huán)境性能信息計(jì)

63、入到的解析變量中（庫(kù)納爾和科恩2001）。良好的環(huán)保性能可以贏得一個(gè)良好的生態(tài)公司聲譽(yù)，還可以增加投資者的信賴(lài)（ragothaman和Lau，2000）。相反，惡劣環(huán)境性能可導(dǎo)致股票價(jià)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(shù)據(jù)來(lái)自1989以后的數(shù)據(jù)和2000年披露的有毒物質(zhì)排放清單；2、托賓Q系數(shù)是根據(jù)金融學(xué)者的建議來(lái)測(cè)量的；3、回歸模型包括了一些新的變量和

64、運(yùn)用了一個(gè)橫截面回歸模型。本研究還提供了描述性統(tǒng)計(jì)和相關(guān)措施。從而得到了是關(guān)于環(huán)境信息披露對(duì)股東回報(bào)的影響的新見(jiàn)解。我們制定的托賓Q系數(shù)的公式是根據(jù)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(chǎng)價(jià)值加上總資產(chǎn)的賬面價(jià)值減去普通股股本所得到的值除以總資產(chǎn)的賬面價(jià)值。托賓Q系數(shù)用來(lái)衡量公司市場(chǎng)價(jià)值。在本文中，環(huán)境信息披露對(duì)公司市場(chǎng)價(jià)值的影響就可以通過(guò)托賓Q系數(shù)來(lái)說(shuō)明。</p>

65、<p>　　系統(tǒng)性風(fēng)險(xiǎn)指標(biāo)（beta系數(shù)）是衡量股票風(fēng)險(xiǎn)，通常用來(lái)測(cè)試市場(chǎng)風(fēng)險(xiǎn)的。庫(kù)納爾和科恩（1997）利用beta系數(shù)來(lái)控制因?yàn)橄到y(tǒng)性風(fēng)險(xiǎn)所獲得安全收益。在這項(xiàng)研究中，beta系數(shù)作為控制變量。在很多文獻(xiàn)中提到了各種公司規(guī)模的測(cè)試。道維爾，Hart和Young（2000）在審查中使用總資產(chǎn)對(duì)數(shù)得出混合的結(jié)果：公司全球標(biāo)準(zhǔn)對(duì)市場(chǎng)價(jià)值是有利也有弊。漢密爾頓（1995）在研究中使用的員工的人數(shù)來(lái)形容一個(gè)公司規(guī)模，研究有毒排放清

66、單數(shù)據(jù)、媒體與股票市場(chǎng)反應(yīng)這三者之間的關(guān)系。雇員人數(shù)的對(duì)數(shù)值（LEMP）是用來(lái)形容的公司規(guī)模的大小，并在模型被作為另一個(gè)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(lái)衡量的。廢物量與托賓Q系數(shù)呈負(fù)相關(guān)，因?yàn)樗軠y(cè)試企業(yè)“臟”的程度。庫(kù)納爾和科恩（1997）利用有毒的化學(xué)物質(zhì)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(lái)代替廢物量進(jìn)行研究。資產(chǎn)回報(bào)率

67、，是用來(lái)衡量企業(yè)績(jī)效，其值等于凈收益除以總資產(chǎn)。它是一個(gè)代理的盈利能力。資產(chǎn)回報(bào)率與托賓Q系數(shù)呈正相關(guān)，由于一些發(fā)展良好的企業(yè)比較重視市場(chǎng)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(rùn)來(lái)衡量盈利能力。</p><p>　　本研究中采用的另一個(gè)控制變量是市盈率。市盈率是衡量市場(chǎng)的公司的普通股的市場(chǎng)價(jià)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(zhǎng)。根據(jù)托賓Q

68、系數(shù)，正在迅速增長(zhǎng)的公司，應(yīng)該有一個(gè)比較高的市場(chǎng)價(jià)值。本文中使用的另一個(gè)控制變量是注冊(cè)會(huì)計(jì)師針對(duì)該企業(yè)財(cái)務(wù)報(bào)表出具的審計(jì)意見(jiàn)。李等人（2005）發(fā)現(xiàn)一些具有較高的股票市場(chǎng)回報(bào)的企業(yè)往往得到更多的保留（或者不合格）的審計(jì)意見(jiàn)。換句話(huà)說(shuō)，審計(jì)意見(jiàn)與公司的市場(chǎng)價(jià)值呈負(fù)相關(guān)?；艏热耍?004）進(jìn)行了實(shí)驗(yàn)研究項(xiàng)目并得出結(jié)論認(rèn)為，投資者對(duì)審計(jì)意見(jiàn)書(shū)的反映似乎暗示著管理戰(zhàn)略是解釋財(cái)務(wù)的最好結(jié)果。它可以假定，管理關(guān)注的是未來(lái)的業(yè)績(jī)，因此是對(duì)現(xiàn)在企業(yè)的

69、業(yè)績(jī)要有充分的了解。根據(jù)彩和杰特（1992），審計(jì)意見(jiàn)書(shū)表明，對(duì)未來(lái)現(xiàn)金流量的增加不確定，因此，未來(lái)公司的市場(chǎng)價(jià)值會(huì)受到不利的影響。</p><p>　　3、研究方法及數(shù)據(jù)來(lái)源</p><p>　　2004年，研究人員在麻州大學(xué)的政治經(jīng)濟(jì)研究中心發(fā)表，基于2000年公司披露的有毒排放清單數(shù)據(jù)列出了前100個(gè)大污染企業(yè)。有毒廢料（氣體釋放）報(bào)告中的數(shù)據(jù)以美元/磅為單位進(jìn)行報(bào)道。那些從標(biāo)準(zhǔn)數(shù)據(jù)

70、庫(kù)收集的數(shù)據(jù)是用來(lái)計(jì)算這100個(gè)公司的一些經(jīng)營(yíng)和財(cái)務(wù)指標(biāo)。以下獨(dú)立變量便是從標(biāo)準(zhǔn)數(shù)據(jù)庫(kù)數(shù)據(jù)庫(kù)獲得的：市場(chǎng)測(cè)試，資產(chǎn)報(bào)酬率，雇員人數(shù)的對(duì)數(shù)值，市盈率與審計(jì)意見(jiàn)。根據(jù)hirschey（2005），托賓Q系數(shù)的公式為：托賓Q系數(shù)=[資產(chǎn)總額+總資產(chǎn)的市場(chǎng)價(jià)值-權(quán)益的賬面價(jià)值]/總資產(chǎn)。托賓Q系數(shù)也是利用標(biāo)準(zhǔn)數(shù)據(jù)庫(kù)中的數(shù)據(jù)來(lái)進(jìn)行計(jì)算。由于在標(biāo)準(zhǔn)數(shù)據(jù)庫(kù)中缺少變量，有9家公司均下降。至少一個(gè)公司因?yàn)橐粋€(gè)極端的異常值而被刪除。最后的樣本便是來(lái)自剩余9

71、0家公司的數(shù)據(jù)。</p><p>　　本研究采用的是多元回歸模型：</p><p>　　托賓Q系數(shù)=f{市場(chǎng)測(cè)試（風(fēng)險(xiǎn)），lg雇員人數(shù)，排污許可收入，資產(chǎn)受益，市盈率，審計(jì)意見(jiàn)}</p><p>　　所研究的問(wèn)題轉(zhuǎn)化為零假設(shè)如下：</p><p>　　測(cè)試對(duì)托賓Q系數(shù)沒(méi)有重大影響</p><p>　　員工人數(shù)的規(guī)模對(duì)托

72、賓Q 系數(shù)沒(méi)有重大影響</p><p>　　廢水排放對(duì)托賓Q 系數(shù)沒(méi)有重大影響</p><p>　　資產(chǎn)報(bào)酬率對(duì)托賓Q系數(shù)沒(méi)有重大影響</p><p>　　市盈率對(duì)托賓Q系數(shù)沒(méi)有重大影響</p><p>　　公司的審計(jì)意見(jiàn)對(duì)托賓Q 系數(shù)沒(méi)有重大影響。</p><p><b>　　4、結(jié)論及分析</b&g

73、t;</p><p>　　表1為描述性統(tǒng)計(jì)報(bào)告表。其中樣本公司的托賓Q系數(shù)平均值為2.176 ；有毒氣體排放量的平均數(shù)額是0.0009鎊/美元。平均資產(chǎn)收益率是4.648%.平均風(fēng)險(xiǎn)測(cè)試是2.121</p><p><b>　　表1：描述性統(tǒng)計(jì)</b></p><p>　　Q ratio =托賓Q系數(shù)</p><p>　

74、　Beta=市場(chǎng)風(fēng)險(xiǎn)測(cè)試</p><p>　　LEMP =員工人數(shù)的對(duì)數(shù)值</p><p>　　Waste=每美元廢水廢物處理量</p><p>　　ROA=資產(chǎn)報(bào)酬率=</p><p>　　P/E ratio=市盈率</p><p>　　AUOP =審計(jì)意見(jiàn)</p><p>　　研究人員進(jìn)行了

75、托賓Q系數(shù)及六個(gè)解析變量和其他獨(dú)立變量的相關(guān)分析。相關(guān)結(jié)果報(bào)告內(nèi)容列示在表2</p><p>　　相關(guān)分析結(jié)果表明，托賓Q系數(shù)與資產(chǎn)報(bào)酬率是密切相關(guān)的。資本回報(bào)越高，則托賓Q系數(shù)越高，而托賓Q系數(shù)與公司規(guī)模及廢水排放量呈負(fù)相關(guān)。另外，市場(chǎng)風(fēng)險(xiǎn)測(cè)試與資產(chǎn)報(bào)酬率有較強(qiáng)的負(fù)相關(guān)。公司規(guī)模與廢水排放呈負(fù)相關(guān)。</p><p>　　獨(dú)立變量之間的多重共線(xiàn)性可能存在于數(shù)據(jù)中，從而有可能導(dǎo)致不穩(wěn)定的回歸

76、系數(shù)。一條由法官等人（1985）提出的經(jīng)驗(yàn)法則用來(lái)評(píng)估多重共線(xiàn)性的作用。他們認(rèn)為，一個(gè)嚴(yán)重的多重共線(xiàn)性問(wèn)題出現(xiàn)只有當(dāng)解釋變量之間的關(guān)系高于0.8 。在我們的數(shù)據(jù)庫(kù)，相關(guān)性最高的是資產(chǎn)報(bào)酬率和市場(chǎng)風(fēng)險(xiǎn)測(cè)試的相關(guān)性，其值為-0.411 。因此，目前線(xiàn)性度太小以至于無(wú)法估計(jì)結(jié)果。</p><p>　　一個(gè)普通多元二次回歸模型進(jìn)行為了調(diào)查托賓Q系數(shù)和有毒氣體排放，市場(chǎng)風(fēng)險(xiǎn)測(cè)試，資產(chǎn)報(bào)酬率，企業(yè)成長(zhǎng)和其他獨(dú)立的變量之間的關(guān)

77、系。回歸方法允許六個(gè)零假設(shè)同時(shí)發(fā)生的測(cè)試。托賓Q系數(shù)是因變量，而前面提到的六個(gè)解釋變量是獨(dú)立變量?；貧w系數(shù)、T統(tǒng)計(jì)(在括號(hào)中)以及重要性水平內(nèi)容列示在表3第I列。多元回歸模型有一個(gè)相當(dāng)大的平均平方數(shù)調(diào)整為31.3%。</p><p>　　來(lái)源：Ragothaman, Srinivasan Carr, David. 關(guān)于企業(yè)環(huán)境信息披露對(duì)股東回報(bào)影響的實(shí)證研究[J]. 國(guó)際管理雜志, 2008, (25):613-