| Literature DB >> 35270353 |
Hua Wu1, Taiwen Feng2, Wenbo Jiang3, Ting Kong4.
Abstract
Despite the importance of environmental penalties in environmental enforcement, how and under what situations they impact stock market reaction is still unclear. Drawing on the theories of expectancy violation and attention driven, a conceptual model is built to explore how environmental penalty influences stock market reaction through investor attention. Furthermore, it is explored that the air pollution and industry saliency facilitate the indirect relationship between environmental penalty and investor attention. We empirically test this theoretical framework using a sample of 88 listed companies that received the environmental penalty. Up to 31 December 2020, a total of 88 A-share listed companies in Shanghai and Shenzhen stock exchanges were obtained as samples by collecting the announcement of environmental penalties of listed companies on Juchao Network. Furthermore Baidu index is taken as a proxy for investor attention in this study. Our findings reveal that investor attention plays mediating role in the relationship between environmental penalty and abnormal returns, while the direct effect of environmental penalty on stock market reaction has not been verified, thus, investor attention plays a complete mediating role between them. In addition, air pollution moderates the relationship between Environmental penalties and investor attention. The study found that enterprises in heavy pollution industries might suffer safety-in-numbers effect, which would weaken the directly negative impact of environmental penalties, and verified the moderating effect of industry saliency. These findings provide theoretical and practical implications for understanding how environmental penalties influence on stock market reaction.Entities:
Keywords: air pollution; environmental penalties; industry saliency; investor attention; stock market attention
Mesh:
Year: 2022 PMID: 35270353 PMCID: PMC8910116 DOI: 10.3390/ijerph19052660
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Studies on environmental events and stock market reaction.
| Study | Research Setting | Applied Theory | Event | Modera-tor | Media-tor | Dependent Variable | Hypothesized Relationship | Main Findings |
|---|---|---|---|---|---|---|---|---|
| Garner& Lacina (2019) | USA oil and gas firms (2010) | Signal theory | British Petroleum oil spill; Deepwater explosion; President Obama’s drilling ban | - | - | Stock market reaction | Environmental disclosure->CAR (-) | Environmental disclosure ->stock market reaction (-) |
| Capelle-Blancard & Laguna (2010) | 64 explosions in chemical plants worldwide (1990–2005) | Event study | Injuries and fatalities; Toxic release | - | - | Abnormal returns; shareholder loss | Total number of fatalities and serious injuries; released toxic chemicals-> CAR; shareholder loss(-) | The fatality or serious injury is associated with an additional loss. The toxic release is associated with higher losses in longer event windows. |
| Jacobs et al. (2010) | 417 CEI announcements and 363 EAC announcements | Signal theory | Corporate Environmental Initiatives; Environmental Awards and Certifications | Revenue gains; Cost reduction | - | Abnormal returns | CEIs and EACs->the market reaction (+); The market reaction to EACs is greater than that for CEIs | Announcements of philanthropic gifts for environmental causes are associated with significant positive market reaction, voluntary emission reductions are associated with significant negative market reaction, and ISO 14001 certifications are associated with significant positive market reaction. |
| Xu et al. (2012) | 57 listed companies disclosed for environmental pollution in China (2010) | Event study | Pollution type; Disclosure source; Disclosure level; Modernization level; Major shareholder holding level; Company attribute | - | - | Abnormal returns | Pollution type; Disclosure source; level; Modernization level; Major shareholder holding level; Company attribute->CAR(-) | The negative environmental events of Chinese listed companies currently have weak impact on the stock market |
| Dasgupta et al. (2012) | Korean public disclosure program | Event study | The media report contained in these monthly violation lists. | - | - | Abnormal returns | Environmental news->CAR(-) | The average reduction in market value is higher than them in other countries. The extent of media coverage is positive influence reduction in market value. |
| Cordeiro &Tewari (2015) | 500 firms ranked by Newsweek US 2009 | Stakeholder theory | Firm’s position in the Newsweek Green Ranking | - | Firm size; firm legitimacy | Short-term and long-term stock market returns | Firm’s position in the Newsweek Green Ranking-> short-term and longer-term stock market reaction (+) firm’s industry-adjusted ranking based on its Green Score within the industry-> short-term and longer-term stock market reaction (+); firm size and organizational legitimacy as a moderator of investor reaction to environmental disclosure | Stock market investors react positively in terms of both the short and intermediate term; industry-adjusted rankings of environmental CSR and that the investor reaction is significantly influenced by firm size and firm legitimacy |
| Flammer & Caroline (2013) | Announcement of corporate news related to environment for all USA publicly traded companies (1980- 2009) | Environment-as-a-resource | Environmental CSR | - | - | Stock market reaction; CARs | The announcement of eco-friendly corporate initiatives-> shareholders react (+); the announcement of eco- harmful corporate initiatives-> shareholders react (-); the announcement of eco-harmful corporate events over time-> shareholders’ negative reaction (+); the announcement of eco-friendly corporate events over time-> positive shareholders’ reaction (-) | The negative stock market reaction to eco-harmful behavior has increased, while the positive reaction to eco-friendly initiatives has decreased; The positive (negative) stock market reaction to eco-friendly (-harmful) events is smaller for companies with higher levels of environmental CSR the negative stock market reaction to eco-harmful behavior has increased, while the positive reaction to eco-friendly initiatives has decreased |
| Grand& D’Elia (2012) | News appearing in Argentine newspapper La Nación (1995–2001) (2003–2008) | Signal theory | Positive environmental news; negative environmental news | - | - | AARs | ARit > 0 for positive announcements; ARit < 0 for negative events | The environmental news can cause impacts on stock returns in developing countries as high as those in developed ones. |
| Lanoie et al. (1998) | Firms on British Columbia’s lists of polluters American and Canadian | SIMM (single-index market model) | Release of information | - | - | Average abnormal return AAR | Large polluters are affected more significantly by such release than smaller polluters | The capital markets react to the release of information in large polluters are affected more significantly from such release than smaller polluters |
| Carpentier & Suret (2015) | 161major accidents reported on the front page of the New York Times from (1959 – 2010) | - | Accident announcement | - | - | Average compounded abnormal return | Major accident announcement -> market value in the mid-term (-); The negative mid-term effect of an accident announcement on the firm’s market value is lower for environmental than for non-environmental accidents; the negative mid-term effect following an accident announcement on the firm’s market value is stronger for airline accidents than for non-airline accidents; The negative mid-term effect following an accident announcement on market value is stronger for accidents followed by government intervention | The deterrence effect of the stock market in the mid-term for environmental problems is weak |
| Konar & Cohen (1997) | Firms with TRI emissions USA 1988–1990 and 1991–1992 | Market-based incentive | Information on toxic chemical emissions | - | - | Abnormal returns | Market reacted more to unexpected TRI disclosures than to those that were already expected | Firms with the largest stock price decline on the day this information became public subsequently reduced emissions more than their industry peers |
Figure 1Conceptual model linking environmental penalty and stock market reaction.
Figure 2Timeline illustration of event periods.
Descriptive statistics for the whole sample.
| Age | Total Assets | Sales | Net Profit | Employees | Penalty Amount | |
|---|---|---|---|---|---|---|
| Year | $million | $million | $million | s | $million | |
| Mean | 19.506 | 981.830 | 590.385 | 5.496 | 3681 | 0.1324 |
| Median | 19 | 495.163 | 212.078 | 1.910 | 2576 | 0.2 |
| S.D. | 4.552 | 170.484 | 0.523 | 0.523 | 350.15 | 0.7261 |
Abnormal returns for the whole sample of 88 firms that were penalized for environmental pollution.
| Event Days () |
| Median |
| Mean |
| % Negative |
|
|---|---|---|---|---|---|---|---|
| 0 | 88 | −1.00% | −1.599 | 0.12% | −0.409 | 58.00% | −0.428 |
| 1 | 88 | −0.65% | −1.727 * | −0.49% | −2.006 * | 40.90% | −1.599 * |
| 2 | 88 | −0.60% | −1.831 * | −0.68% | −1.491 | 59.09% | −1.599 * |
| 3 | 88 | −0.94% | −2.064 ** | −0.94% | −1.872 * | 59.09% | −1.599 * |
| 4 | 88 | −0.88% | −2.288 ** | −1.14% | −2.229 ** | 59.09% | −1.599 * |
| 5 | 88 | −1.30% | −1.639 | −0.91% | −1.542 | 59.09% | −1.599 * |
| 6 | 88 | −0.65% | −1.153 | −0.53% | −0.8 | 56.82% | −1.173 |
| 7 | 88 | −0.97% | −1.277 | −0.48% | −0.604 | 56.82% | −1.173 |
| 8 | 88 | −1.30% | −1.419 | −0.64% | −0.713 | 57.95% | −1.386 |
| 9 | 88 | −1.51% | −1.897 | −1.35% | −1.309 | 53.41% | −0.533 |
| 10 | 88 | −1.16% | −1.964 * | −1.70% | −1.714 * | 55.68% | −0.959 |
| (0,1) | 88 | −0.65% | −1.582 | −0.62% | −1.265 | 56.81% | −1.173 |
| (0,5) | 88 | −3.12% | −2.064 ** | −4.03% | −1.769 ** | 60.47% | −2.025 * |
| (6,10) | 88 | −6.98% | −1.739 | −4.69% | −1.133 | 55.68% | −0.959 |
| (0,10) | 88 | −2.46% | −1.943 * | −8.73% | −1.465 | 59.09% | −1.599 |
** p ≤ 0.05; * p ≤ 0.10. a Z-statistics for medians were obtained using Wilcoxon signed-rank tests. b Z-statistics for % negatives were obtained using binomial sign tests. Note: Event Day 0 denoted the date of the announcement of environmental penalties.
Descriptive statistics for the sample firms in heavy pollution industry and non-heavy pollution industry Panel A. Heavy pollution industry.
| Age | Market Value | Total Assets | Sales | Net Profit | Employees | Penalty Amount | |
|---|---|---|---|---|---|---|---|
| year | $million | $million | $million | $million | s | $million | |
| Mean | 18.581 | 1499.3 | 1532.744 | 648.140 | 35.004 | 3887.419 | 0.061 |
| Median | 18 | 1061.147 | 774.5282 | 278.028 | 15.608 | 2943 | 0.030 |
| S.D. | 5.02 | 1302.967 | 2170.029 | 1064.731 | 56.129 | 3504.478 | 0.074 |
| Panel A. Heavy pollution industry | |||||||
| Mean | 19.5 | 1123.231 | 823.962 | 388.933 | 14.362 | 3525.292 | 1.747 |
| Median | 19.5 | 722.024 | 706.288 | 153.346 | 6.004 | 2335.5 | 0.041 |
| S.D. | 3.833 | 1292.624 | 762.037 | 570.632 | 32.898 | 3245.003 | 7.917 |
| Panel B. Non-heavy pollution industry | |||||||
Stock market reaction for the sample firms in heavy pollution industry and non-heavy pollution industry.
| Event Days () |
| Median |
| Mean |
| % Negative |
|
|---|---|---|---|---|---|---|---|
| 0 | 59 | −0.10% | −0.523 | 0.47% | 1.267 | 54.23% | −0.657 |
| 1 | 59 | −0.80% | −1.774 * | −0.48% | −1.209 * | 62.71% | −1.823 * |
| 2 | 59 | −0.50% | −0.966 | −0.23% | −0.415 | 59.32% | −1.302 |
| 3 | 59 | −0.90% | −1.532 | −0.73% | −1.295 | 59.32% | −1.302 |
| 4 | 59 | −0.90% | −1.940 ** | −0.98% | −1.776 * | 59.32% | −1.302 |
| 5 | 59 | −0.78% | −1.004 | −0.82% | −1.28 | 55.93% | −0.781 |
| 6 | 59 | 0.49% | −0.589 | −0.47% | −0.757 | 55.93% | −0.781 |
| 7 | 59 | −0.84% | −0.981 | −0.78% | −1.154 | 57.62% | −1.042 |
| 8 | 59 | −1.24% | −1.585 | −1.19% | −1.664 | 59.32% | −1.302 |
| 9 | 59 | −1.51% | −1.897 * | −1.96% | −2.049 | 54.24% | −0.521 |
| 10 | 59 | −1.11% | −1.985 ** | −2.17% | −2.235 ** | 57.62% | −1.042 |
| (0,1) | 59 | −1.04% | −0.823 | −0.01% | −0.007 | 59.32% | −1.302 |
| (0,5) | 59 | −3.12% | −2.768 | −2.77% | −1.085 | 62.71% | 1.823 * |
| (6,10) | 59 | −6.10% | −1.623 | −6.56% | −1.827 * | 54.24% | −0.521 |
| (0,10) | 59 | −9.95% | −1.744 * | −9.33% | −1.681 * | 59.32% | −1.302 |
| Panel A. Heavy pollution industry | |||||||
| 0 | 29 | −0.14% | −1.435 | −0.60% | −1.399 | 58.62% | 0.945 |
| 1 | 29 | −0.33% | −1.829 ** | −1.26% | −1.871 * | 58.33% | −0.743 |
| 2 | 29 | −0.92% | −1.762 * | −1.60% | −2.002 * | 58.33% | −0.743 |
| 3 | 29 | −1.43% | −1.416 | −1.36% | −1.349 | 58.33% | −0.743 |
| 4 | 29 | −0.84% | −1.33 | −1.46% | −1.428 | 58.33% | −0.743 |
| 5 | 29 | −2.52% | −1.178 | −1.08% | −0.875 | 65.52% | −1.486 |
| 6 | 29 | −2.09% | −0.941 | −0.65% | −0.411 | 58.33% | −0.743 |
| 7 | 29 | −2.44% | −0.66 | −0.14% | 0.071 | 55.17% | −0.371 |
| 8 | 29 | −2.29% | −0.335 | 0.48% | 0.206 | 55.17% | −0.371 |
| 9 | 29 | −1.73% | −0.66 | −0.10% | −0.042 | 51.72% | 0 |
| 10 | 29 | −1.66% | −0.638 | −0.75% | −0.327 | 51.72% | 0 |
| (0,1) | 29 | −0.24% | −0.962 | −1.11% | −1.118 * | 51.72% | 0 |
| (0,5) | 29 | −3.78% | −1.503 | −6.61% | −1.435 | 58.33% | −0.743 |
| (6,10) | 29 | −8.37% | −0.681 | −0.88% | −0.086 | 58.33% | −0.743 |
| (0,10) | 29 | −21.08% | −0.854 | −7.49% | −0.524 | 58.33% | −0.743 |
| Panel B. Non-heavy pollution industry | |||||||
** p ≤ 0.05; * p ≤ 0.10. a Z-statistics for medians were obtained using Wilcoxon signed-rank tests. b Z-statistics for % negatives were obtained using binomial sign tests. Note: Event Day 0 denoted the date of the announcement of environmental penalties.
Descriptive statistics and correlations.
| M | S.D. | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Age | 19.489 | 4.528 | ||||||||||
| Firm sizes | 9.818 | 15.992 | 0.124 | |||||||||
| Sales | 5.904 | 11.472 | 0.051 | 0.552 ** | ||||||||
| Net profit | 5.496 | 0.523 | 0.037 | −0.058 | −0.046 | |||||||
| Punished numbers | 1.421 | 1.036 | 0.215 * | 0.141 | 0.078 | −0.043 | ||||||
| Ownership type | 0.38 | 0.487 | 0.276 ** | 0.295 ** | 0.328 ** | −0.082 | 0.231 * | |||||
| Environmental penalty | 0.046 | 0.267 | 0.17 | 0.15 | 0.249 * | −0.018 | 0.733 ** | 0.206 | ||||
| Investor attention | 0.255 | 0.471 | −0.067 | −0.002 | 0.02 | −0.016 | −0.250 * | −0.044 | −0.279 ** | |||
| Air pollution | 0.067 | 0.368 | −0.032 | −0.064 | −0.138 | 0.087 | −0.109 | −0.043 | −0.178 | 0.036 | ||
| Industry saliency | 0.67 | 0.473 | 0.033 | 0.175 | 0.028 | −0.152 | −0.066 | −0.056 | −0.220 * | 0.157 | −0.024 | |
| Abnormal return | −0.006 | 0.034 | 0.043 | −0.091 | 0.171 | −0.059 | 0.023 | 0.245 * | 0.01 | 0.206 | −0.269 * | 0.102 |
Note: p ≤ 0.05; p ≤ 0.10.
Results of Regression Analyses.
| Variables | Abnormal Returns | Abnormal Returns | Investor Attention | Investor Attention | Investor Attention | Investor Attention | Investor Attention |
|---|---|---|---|---|---|---|---|
| Model1 | Model2 | Model3 | Model4 | Model5 | Model6 | Model7 | |
| Age | 0.006 | 0.008 | −0.012 | −0.012 | −0.013 | −0.02 | −0.018 |
| Total assets | −0.318 * | −0.318 * | −0.002 | −0.002 | −0.001 | −0.025 | −0.006 |
| Sales | 0.287 * | 0.269 * | 0.088 | 0.087 | 0.095 | 0.085 | 0.073 |
| Net profit | −0.043 | −0.039 | −0.02 | −0.019 | −0.018 | −0.003 | −0.001 |
| Punished numbers | 0.073 | 0.089 | −0.076 | −0.076 | −0.049 | −0.097 | −0.121 |
| Ownership type | 0.248 ** | 0.248 ** | −0.003 | −0.003 | −0.011 | 0.011 | 0.032 |
| Environmental penalty | −0.12 | −0.068 | −0.279 ** | −0.243 ** | −0.282 ** | −0.200 ** | −0.251 ** |
| Investor attention | 0.214 * | ||||||
| Air pollution | −0.002 | −0.014 | |||||
| Industry saliency | 0.109 | 0.015 | |||||
| Environmental penalty * Air pollution | 0.274 * | ||||||
| Environmental penalty * Industry saliency | −0.184 ** | ||||||
|
| 0.142 | 0.181 | 0.09 | 0.079 | 0.075 | 0.1 | 0.095 |
| Adjusted | 0.067 | 0.101 | 0.01 | 0.046 | 0.064 | 0.009 | 0.062 |
|
| 1.894 * | 2.226 ** | 7.280 ** | 3.608 ** | 6.976 ** | 1.098 * | 2.929 ** |
Standard errors are in parentheses. ** p ≤ 0.05; * p ≤ 0.10.
Figure 3Moderation effect of air pollution on the relationship between environmental penalty and investor attention.
Figure 4Moderation effect of industry saliency on the relationship between environmental penalty and investor attention.
The results on penalty amount and investor attention.
| Panel A. Heavy pollution industry | |||||||
|
|
|
|
|
|
|
| |
| Environmental penalty | 59 | 0.16% | −4.731 *** | 0.55% | 1.836 * | 8.48% | −6.093 *** |
| Investor attention (0) | 59 | 1.50% | −3.550 *** | 15.62% | 3.670 *** | 20.34% | −3.846 *** |
| Investor attention (1) | 59 | 1.82% | −3.550 *** | 30.70% | 1.557 | 20.34% | −3.846 *** |
| Panel B. Non−heavy pollution industry | |||||||
|
|
|
|
|
|
|
| |
| Environmental penalty | 29 | 1.18% | −2.960 ** | 12.95% | 1.526 | 17.24% | −3.213 *** |
| Investor attention (0) | 29 | 6.68% | −1.784 * | 9.19% | 1.19 | 31.04% | −1.857 * |
| Investor attention (1) | 29 | 11.61% | −2.206 ** | 15.05% | 1.714 ** | 27.59% | −2.228 ** |
All tests are two-tailed: *** p ≤ 0.01; ** p ≤ 0.05; * p ≤ 0.10. a Z-statistics for medians were obtained using Wilcoxon signed-rank tests. b Z-statistics for % negatives were obtained using binomial sign tests.
Figure 5Median CARs for the sample.