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. 2022 Jun 15;17(6):e0268743. doi: 10.1371/journal.pone.0268743

Penalties for industrial accidents: The impact of the Deepwater Horizon accident on BP’s reputation and stock market returns

William McGuire 1, Ellen Alexandra Holtmaat 2,*, Aseem Prakash 3
Editor: J E Trinidad Segovia4
PMCID: PMC9200171  PMID: 35704560

Abstract

Do visible industrial accidents damage firms’ reputations and depress their stock market returns, and do these penalties spill over to other firms in the industry? On April 20, 2010, the Deepwater Horizon offshore oil rig in the Gulf of Mexico leased by BP exploded and sank, causing 11 deaths and the largest marine oil spill in US history. We examine the impact of this accident on BP’s reputation and stock market performance using data from YouGov’s BrandIndex and Capital IQ’s financial data for the period 2007–2017. We employ a synthetic control analysis to examine the extent and duration of these penalties. We find that in the aftermath of the Deepwater accident, BP’s reputation declined by approximately 50% relative to the synthetic control, and this decline persisted through the end of 2017. Yet, in terms of financial market returns, though the stock price dropped drastically in the first two months, we do not find a statistically significant decline in the stock market returns either in the mid-term (1–2 years) or the long term (2–7 years). In terms of spillover effects, we find no evidence of reputational damage or a decline in stock market returns for other oil and gas firms. These findings suggest that while environmental accidents invite swift and lasting reputational penalties, they might not depress the stock market performance in the long run. Moreover, the impact either on reputation or stock market returns does not necessarily spill over to other firms in the same industry.

Introduction

Climate concerns are leading to intense scrutiny of fossil fuel firms, including how they access capital, what sorts of subsidies they get from the government, and the ecological damage their activities pose to local communities. “Naming and shaming” of fossil fuel firms, along with their supply infrastructure such as banks and cloud computing companies such as Amazon, is an integral part of the advocacy tool kit of climate groups. While the ecological impact of fracking continued to draw public scrutiny, the issue of offshore oil spills seems to gather less attention [1]. This is problematic because offshore production accounts for about 30% of global crude output, and [2] oil spills occur quite regularly [2].

Industrial accidents can inflict lasting reputational and financial damage on firms. The 1979 Three Miles accident brought a halt to the construction of new nuclear plants in the United States. In the wake of the 2011 Fukushima accident, Germany decided to phase out its existing nuclear plants. Thus, by strategically leveraging both the reputational and financial harms of offshore accidents, the climate movement can exert additional pressure on fossil fuel firms to forgo offshore oil drilling and production, and the financial institutions not to fund such activities.

The 1989 Exxon Valdez disaster undermined the offshore industry’s claim about their state-of-the-art safe transportation technologies. In addition to lawsuits seeking financial damages from Exxon, this incident motivated the enactment of the Oil Pollution Act of 1990, which substantially increased oil transportation costs by requiring a double hull design for new tankers and barges. The industry also developed elaborate safety protocols [3].

The offshore oil industry suffered a major disaster in 2010 with the explosion and eventual sinking of the Deepwater Horizon oil platform in the Gulf of Mexico. In this paper we examine how this accident affected the corporate reputation and the stock market return of Deepwater’s operating firm, BP (formerly, British Petroleum). We focus on BP while recognizing that its contractors such as Schlumberger, Halliburton, Transocean, and Weatherford were also implicated in the spill [4].

Corporate reputation can be viewed as “the accumulated impressions that stakeholders form of the firm” [5]. It is a crucial asset for any firm [6] because outside stakeholders often do not possess information about the internal workings of the firm. To pass an evaluative judgment on the firm, they rely on proxies such as its corporate reputation. Consequently, firms view corporate reputations as important strategic resources [7] that create benefits such as a better relationship with regulators [8], lower cost of capital [9, 10], and attract and retain customers and managerial talent [11]. Given the substantial payoffs of a good reputation, firms invest vast sums in building and protecting their reputation, be it for high-quality products, ethical conduct, environmental stewardship, or community engagement [12].

But corporate reputations could be fragile. They could be damaged when firms suffer industrial accidents, recall faulty products, or face media scrutiny for poor labor or environmental practices. The Deepwater Horizon accident is probably one such event. On April 20, 2010, a blowout of the Deepwater Horizon offshore drilling rig led to the death of eleven workers and caused the largest marine oil spill in history. The oil spill caused catastrophic environmental damage to ecosystems in the Gulf of Mexico. BP was criticized sharply for the failures that led up to the accident and ultimately pled guilty to eleven counts of manslaughter and other misdemeanor and felony charges. To date, BP has paid over $60 billion to settle criminal and civil complaints along with other fines. We recognize that the reputational impact of industrial accidents is mediated by how the media covers it and the activists frame it [13]. In the case of BP the shock value of the event, the vivid footage of marine pollution, and the media attention were overwhelming [1416]. Environmental groups also sought to leverage it to promote their goals, including climate change. Thus, the scale of the accident, media coverage, and environmental groups’ political mobilization created the expectation of a negative reputational impact.

While BP became a subject of criticism and legal action, it is not clear the extent to which, and for how long, the Deepwater accident affected BP’s reputation in the eyes of citizens, the key actors granting firms the “social license to operate” [17]. Firms depend on the external environment for critical resources. They need physical infrastructure to produce goods and services, secure inputs, attract employees, and sell to their customers. For these activities, they rely on a supportive government that provides the appropriate regulatory environment. In addition, firms need a de facto “social license to operate”: citizens and communities must view firms as responsible actors who are meeting societal expectations. Without social legitimacy, firms might find it difficult to access physical inputs and financial capital as well as obtain permits and other resources to function. They may even face political and environmental protests [18]. Of course, profits may help firms to secure social legitimacy. But profits alone may not give them the social license to operate. Hence, even highly profitable firms invest in building their reputations for good citizenship, environmental stewardship, and workplace safety.

In addition to the reputational damage, we examine the impact of the disaster on BP’s stock market returns, as each might be driven by different mechanisms. Stock markets are a pillar of the market economy. By providing a summary measure of a firm’s performance, the stock price, they play an important role in capital allocation. Moreover, stock prices also provide a measure of the expected future earnings of the firm [19]. Indeed, for many corporations, executive compensation is often linked to the stock price. Thus, without a penalty on stock prices, the long-term implications of the accident for changes in corporate governance (in the absence of new regulations) remain unclear.

Firms’ stakeholders typically function in an information-scarce environment. They are also boundedly rational [20] and resort to stereotypes to economize on their limited cognitive capacities [21]. Sometimes, they make assumptions about all firms across the industry based on the actions of a single firm. This leads to the issue of reputational spillovers, where the actions of one firm can bear upon the reputations of other firms in the industry [22]. Indeed, this is an important reason why industry associations often develop industry-wide certification programs to protect the reputation of the industry as a whole [23, 24] and to insulate other firms from any reputation problems that a particular member might face.

Reputational spillovers are not inevitable because stakeholders could differentiate among firms that sell differentiated products. The Volkswagen diesel scandal did not necessarily sully the reputation of Toyota or even other German car companies such as BMW. Nevertheless, reputation spillovers remain a serious concern especially when firms sell an undifferentiated product such as gasoline. We extend our study beyond BP to see if the Deepwater Horizon disaster also affected the reputations of other firms in the oil and gas sector. These include integrated oil and gas companies like Chevron and Shell, exploration and production companies like Marathon, and refining and marketing companies like Valero, Citgo, and Sunoco. Our analysis suggests the absence of any significant reputational spillovers to other firms in the oil and gas industry.

Regarding stock market returns, we find no evidence that the Deepwater Horizon spill diminished BP’s stock market returns in the mid (1–2 years) or the long term (2–7 years), despite a drastic drop in BP’s stock price immediately after the spill. Moreover, we find no evidence that other firms in the oil and gas industry suffered declines in their stock market returns.

Data and empirical methodology

A key methodological challenge in assessing the reputational damage or changes in stock market returns from an industrial accident is the absence of a counterfactual: what would BP’s reputation have looked like if there would have been no accident? Comparing BP’s post-disaster reputation to its pre-disaster one is problematic because it imposes a strong assumption that no other events after April 2010 affected BP’s reputation. However, we could compare BP’s reputation to that of another firm provided we can establish that the comparison firm’s reputation was sufficiently similar to BP’s before the disaster. This is the logic motivating the synthetic control method: create a “synthetic brand” that closely resembles BP’s reputational record before the accident. We can then compare the change in BP’s reputation after the accident with that of the change in the synthetic brand’s reputation for the same period. This approach allows us to establish the impact of the Deepwater Horizon accident on BP’s reputation.

BP’s Deepwater Horizon accident occurred on April 20, 2010. To study the effect of this accident on BP’s reputation, we look for a change in reputation post-2010, with the pre-2010 reputation as the baseline. We draw on data from YouGov’s BrandIndex database. These data report respondents’ evaluation of the reputations of different corporate brands measured in terms of their general impression of the brand, the perceived quality of the product, the value for money, and the respondent’s willingness to work for the company [25]. These data are observed at the brand level rather than at the firm level. This is appropriate for our study because brands are typically the locus of a firm’s reputation. The data are recorded daily, but we construct monthly aggregates to make the model estimation less demanding. The data are collected through surveys and used to calculate “scores” by subtracting negative feedback from positive feedback. The scores can range from -100 to +100. A score of zero indicates equal amounts of positive and negative feedback. Scores closer to -100 indicate a predominance of negative feedback, while scores closer to +100 indicate a predominance of positive feedback.

Our objective is to compare the change in BP’s reputation before and after the accident to that of a “synthetic control” brand. This brand needs to be sufficiently similar to BP in terms of various attributes and yet should not have experienced the negative reputation impact of the Deepwater accident. This approach would reveal how BP’s reputation may have fared in the counterfactual scenario where the accident did not take place.

What might this control brand be? Rather than choose the control brand at random or by appealing to theory, we employ a nonparametric estimation method, “synthetic control,” to construct a counterfactual brand for BP, based on a weighted average of fifteen other brands (listed in Table 1 below) in our data set. The synthetic control estimator selects brands from our dataset of 660 brands based on their similarity with BP in terms of variables that correlate with corporate reputation (as opposed to the specific measure of corporate reputation that we employ as our dependent variable). These include respondents’ reported impression (favorable or not) of the brand, their sense of the value they get from the brand, the perceived quality of the brand, their satisfaction with the brand, their willingness to recommend the brand, and the “buzz” they’ve heard associated with the brand. The estimator then selects and attaches weights to these other brands to minimize the difference between selected variables used to construct the synthetic control and BP before "treatment" (i.e., the 2010 accident). The following is the weighted average "control" brand that is most similar to BP before the disaster:

Table 1. Components of synthetic control.

Weight Brand
0.756 Shell
0.054 Craigslist
0.046 Verizon Wireless
0.027 Walmart
0.026 Big Lots
0.012 Cialis
0.009 Visa
0.004 Costco
0.004 TJMaxx
0.004 YouTube
0.001 Red Bull
0.001 Abercrombie & Fitch
0.001 Kohl’s
0.001 Sunoco
0.001 Ikea

Note: Weights sum to one by construction

Reputation effect

The synthetic control method is nonparametric, meaning there is not a simple hypothesis test we can use to judge whether the accident had a "significant" effect on BP’s reputation. Instead, we can look at the apparent size of the treatment effect and perform additional robustness tests to ensure our result is meaningful. We begin by examining the standard synthetic firm graph, comparing the outcome for our treated brand (BP) against our synthetic control. This is presented in Fig 1 below:

Fig 1. Reputation of BP vs. synthetic firm.

Fig 1

Note: As Shell–which may itself have been impacted by the oil spill—is an important component of our synthetic control, we form a synthetic control excluding oil and gas firms as well. To address potential concerns that the brands in the synthetic control are not sufficiently similar to BP, we also form a synthetic control based on only oil and gas firms. We plot the synthetic controls in a graph in the S1 Appendix.

The vertical line indicates April 2010, the month of the Deepwater Horizon accident. We can see that our "treated unit" (BP) performed quite similarly to our synthetic control before the accident. Both exhibited a long-term upward trend in their reputation scores with a similar short-term variation.

After the 2010 accident, BP’s reputation dropped more than 50 points relative to the synthetic control (recall, the reputation scale range is 200 points, from a minimum of -100 to a maximum of +100 points). Though BP’s reputation recovered almost half of its losses over the next 18 months, it did not recover to the same level even by December 2017, the end of the period covered by our data set. BP’s reputation seems to have stabilized around a lower level (15 points) compared to the synthetic control, suggesting BP has suffered long-term reputational damage from the Deepwater accident.

We can also see the extent of the reputational damage by plotting the gap between the synthetic firm’s reputation and BP’s. Fig 2 presents this comparison, where a value of zero on the vertical axis represents no difference between the reputation of BP and synthetic control.

Fig 2. Gap between BP and synthetic control reputation.

Fig 2

This figure has the same intuitive interpretation as Fig 1. We can see the gap widened to approximately 50 points in the months immediately following the accident. About half of the reputational damage was undone within the next 18 months, but the size of the gap decreased only very slowly by the end of the period covered by our data set. Potentially media campaigns by BP to regain public trust might have played a role in undoing some of the initial reputational damage [16].

Robustness

Our reputational comparisons are meaningful only if the synthetic control brand is a good estimate of BP’s reputation in the counterfactual scenario where the Deepwater Horizon accident did not happen. Following the synthetic control literature, we perform a series of "placebo" tests to substantiate this claim [26]. The objective is to explore whether brands that make up our synthetic control experienced shifts in reputation similar to BP’s around the time of the Deepwater Horizon accident. If so, that would call into question our estimate of the reputational shock in Fig 1.

To conduct the placebo tests, we construct synthetic controls for each of the 15 brands listed in Table 1. Thus, for say Walmart, we construct a synthetic control using their own unique set of comparison brands. Our objective is to assess if reputational gaps between the focal brand and its synthetic control are similar to those revealed in Fig 2, where we examined the reputational gap between BP and its synthetic control. We do this by calculating the root mean square prediction error (RMSPE) in the case of BP vs. synthetic control and the RMSPE in the case of each brand in Table 1 vs. their respective synthetic controls. The RMSPE measures the extent to which the actual performance of the brand deviates from what we would have predicted based on the performance of the synthetic control brand. When treatment effects are large, we should expect a very low RMSPE before treatment and a large RMSPE after treatment. Fig 3 shows the ratio of post- vs. pre-April 2010 RMPSE for BP and the components of its synthetic firm list in Table 1.

Fig 3. RMPSE ratios for BP and components of synthetic firm.

Fig 3

The horizontal line corresponds to a value of one, indicating equivalent pre- and post-Deepwater Horizon RMPSE. The ratio for BP is over 12, indicating that the RMPSE was very low before the disaster and very high afterward. This is consistent with a large treatment effect. The ratio for the rest of the brands ranges from 4.8 for Youtube to 0.29 for Red Bull. The highest RMPSE ratios are for YouTube and Costco, but each of these brands collectively received a weight of 0.008 in the construction of the synthetic control. Their relatively large RMPSE ratios do not undermine our estimate of the treatment effects in Figs 1 and 2.

Spillover effects

Arguably, because gasoline is an undifferentiated product, an industrial accident in a single oil firm could have tarnished the reputation of other firms in the industry. It is also important to consider potential spillovers from a methodological perspective; the brands from which we selected BP’s synthetic control did include other oil and gas firms; in fact, the single largest component of BP’s synthetic control is Shell (75% weight). If Shell was positively or negatively affected by the Deepwater Horizon disaster, it would bias our measurement of the reputational shock in Figs 1 and 2.

To test for potential spillovers within the oil and gas industry, we constructed synthetic controls for every other oil and gas brand (individually) included in the YouGov database. These are Arco, Chevron, Citgo, Gulf, Marathon, Shell, Sunoco, and Valero. To account for possible spillovers within the oil and gas industry, we excluded other oil and gas brands from the construction of these synthetic controls. We then calculated the pre- and post-Deepwater Horizon RMSPE for each of these brands relative to their synthetic controls. The ratios of post- vs. pre-Deepwater Horizon RMSPE are presented in Fig 4:

Fig 4. RMSPE ratios for non-BP oil brands.

Fig 4

Once again, the horizontal line corresponds to a value of one, indicating no difference in post- vs. pre-Deepwater Horizon disaster RMSPE. If BP’s reputational shock spilled over to the rest of the industry, we would expect the ratios for other oil and gas brands to be higher than one. The highest ratio we see is for Valero, with a value of 1.01. The lowest is Citgo, with a value of 0.17. Shell, the largest component of BP’s synthetic control, exhibits a ratio of 0.49. This indicates that Shell more closely matched its synthetic control after the Deepwater Horizon disaster, a strong indication that there were no spillover effects that biased our results. The low level of RMSPE ratios among all of the oil and gas brands indicates the absence of any significant reputational spillovers within the oil and gas industry.

What might explain the apparent absence of reputational spillovers? Did the industry mount a concerted effort to assure stakeholders through say creating a self-regulatory program? Did individual oil and gas firms take some unilateral action? At the industry level, while the industry did not create a voluntary program, Chevron and other oil and gas companies founded the Marine Well Containment Company, which was tasked to provide a rapid response fleet to contain oil spills. The American Petroleum Institute (API) improved its safety standards and made them available to the public to show the standards in place to promote safety [3, 27, 28]. However, the 2010 annual reports of several oil and gas companies do not show any concrete actions other than a review of their own safety systems and some perfunctory distress about the accident.

Changes in stock market returns

A firm’s reputation is one of its most important intangible assets, which suggests that the negative reputational shock documented in the previous section should have (among other things such as regulatory and legal penalties) serious financial implications for BP. Yet one might argue that citizen perceptions about BP might diverge from those of stock market actors who influence the stock market returns. After all, stock analysts are supposed to have deep expertise about the industry and therefore are in a superior position to assess how an industrial accident might influence future stock returns. But if the Deepwater Horizon disaster led to a consumer boycott or expensive regulatory or legal penalties, then it would affect BP’s profitability and dividends. We should then see BP’s stock price decline after the disaster. On the other hand, stock analysts might assess the implications of the Deepwater disaster on future dividends differently. They may not view this disaster as affecting BP’s long-term financial health. If so, this disaster would not affect the stock market returns of the company in the long term.

As per the classic Miller-Modigliani model (1961), in competitive financial markets, a firm’s stock price represents the net present value of expected future dividends, or the value investors will receive for owning the company. Scholars report mixed evidence on the duration of stock price decline beyond two days. Kaplanski and Levy (2010) find that aviation disasters lead to an average decline in market capitalization of more than $60 billion per disaster [29]. However, after 2 days, the prices reverted to the normal level. In contrast, Capelle-Blancard and Laguna’s (2010) study of explosions in chemical plants and refineries finds that stock prices declined by 1.3% over two days and there was a further decline of 12% over six months [30]. Our paper is among the very few to investigate the long-term (7 years) consequences of an industrial accident on stock market returns.

We estimate the effect of the Deepwater Horizon spill on BP’s stock market returns using the same synthetic control approach described above. With this, we follow others, like Acemoglu et al. [31], who have applied the synthetic control method to model the counterfactual in the fields of economics and finance [26, 3137]. The synthetic control method is a novel approach and variation on other event study methods widely used in finance. It addresses some of other event study method’s shortcomings [31, 37]. The synthetic control method applies specific weights for each unit based on similarities in variables that are driving the outcome variable of interest, making sure the counterfactual is as similar as possible to the treated unit [31]. The synthetic control method is comparable to a control portfolio. The companies selected for the control portfolio, when using the synthetic control method, are those that are most similar to BP in the underlying characteristics that drive the stock market returns. This data-driven creation of a counterfactual is a more nuanced approach than for example using the market as a counterfactual. An added advantage is that for making causal inferences weaker assumptions are needed than in the traditional event study methods [38].

Once again, the key question is how to identify an appropriate counterfactual for BP–a firm that shows us what BP’s stock market returns would have been if the Deepwater Horizon disaster had not happened. We construct a synthetic control for BP using firms that were part of the S&P 500 in 2010, the year of the disaster. Our synthetic control is constructed by matching BP with a weighted average of other S&P 500 firms in terms of their total assets, gross profits, total debt, return on investment, volatility, and “broker recommendation” score that ranges from zero (lowest) to five (highest). All of these variables, along with the stock market returns, were gathered from S&P’s Capital IQ database. Unlike our reputational measures, our measures of financial performance are generally not constrained to vary within the same range of -100 to +100. To adjust for differences in initial levels, we normalized our measures of stock market returns, total assets, gross profit, and total debt to be equal to 100 in the first month of our data set, February 2007.

Using these data, we construct a synthetic control for BP based on 187 firms that were listed in the S&P 500 at the time of the Deepwater Horizon disaster. A comprehensive list, including weights (analogous to Table 1) is presented in S1 Appendix. The large number of components makes it difficult to compare BP to any individual firm, but we can compare the mean pre-disaster levels of our predictors between BP and its synthetic control, also known as the “predictor balance” [33]. The predictor balance is shown in Table 2:

Table 2. Predictor balance for financial performance.

  BP Synthetic Control
Total assets 108.59 108.69
Gross profit 102.34 102.5
Broker Recommendation 2.12 2.12
Total debt 126.09 125.13
Return on investment 8.32 8.35
Volatility 28.29 28.42

These results suggest that our synthetic control is a good match for BP’s pre-disaster stock market returns. Since this is a nonparametric estimation technique, we cannot perform a simple hypothesis test to see if there are significant differences between BP and its synthetic control after the Deepwater Horizon spill. As with our reputation analysis, we can simply look at the difference in stock market returns between BP and the synthetic control after the disaster. Fig 5 illustrates our results:

Fig 5. Total Returns of BP vs. synthetic control.

Fig 5

Note: In S1 Appendix, we have added the figure with the synthetic control without oil and gas companies. There is a necessary tradeoff here; restricting the set of possible components for the synthetic control may help address concerns about contagion but will also reduce the fit of the model. This is why we include oil and gas companies in the original synthetic control and test for spillovers in our robustness checks. Moreover, excluding oil and gas firms from the synthetic control yields essentially the same result as our original model. We also added a figure with the synthetic control based only on oil and gas companies, as comparison.

The figure above shows that the total returns for BP dropped abruptly below that of our synthetic control after the Deepwater Horizon disaster, which is indicated by the vertical line. This suggests that along with the reputational damage, the disaster also affected BP’s financial performance. Although BP was able to return to the initial level of total returns (normalized to 100) by the end of our sample period, its counterfactual had grown by roughly 200% over the same period. However, it is important to perform robustness checks before we draw any conclusions from this comparison, as we do below.

Robustness

The challenge is to be sure that our synthetic control is a good approximation of BP’s performance had the Deepwater Horizon disaster never happened. As we did in our reputational analysis, we do this by estimating synthetic control models for each component of BP’s synthetic control. Since there are 187 components, we are not able to present a comprehensive set of Post/Pre RMSPE ratios, as we did in Fig 3. In Fig 6 below, we plot the total returns prediction error for BP and all of its synthetic control components, analogous to what was presented in Fig 2.

Fig 6. Total return prediction error for BP vs. synthetic control components.

Fig 6

Ideally, BP (represented by the larger black line) would show a large negative prediction error, and all other components would have prediction errors near zero. Instead, we find a wide variation in prediction errors among our components, some even more negative than BP. If a significant number of the components of BP’s synthetic control also experienced large drops in their stock market returns after the Deepwater Horizon disaster, then we cannot be confident that we have identified the effect of the disaster on BP’s stock market returns.

Cunningham (2021) suggests computing the Post/Pre RMSPE ratio for the treated unit and each component of the synthetic control and seeing where the treated unit ranks in that distribution [39]. Table 3 shows BP’s ranking in the distribution of RMSPE ratios. We calculated this ranking for our full sample period, the two years following the disaster (“Short-term”), and the period two to seven years after the disaster (“Long-term”):

Table 3. BP post/pre RMSPE ratios and ranks.

  Full Sample (May 2010—July 2017) Short-Term (May 2010—June 2012) Long-Term (July 2012 –July 2017)
Post/Pre 5.84 1.65 6.79
RMSPE Ratio
Ratio Rank 37 90 37
(out of 187)
P-value 0.20 0.48 0.20
(implied by rank)

The ranking can also be used to calculate a p-value, which tells us the likelihood that we would observe BP’s RMSPE ratio if the disaster had no effect on its total returns. The p-value is simply the rank divided by the total number of firms, which is 187 in BP’s case. The results indicate that we cannot reject the null of no effect on stock market returns. We checked the effect both for the two years immediately following the disaster (“Short-term”) and for a longer-term period of seven years.

We also checked the robustness of our findings by using the more conventional analysis of abnormal returns. We use the capital asset pricing model (CAPM) to predict BP’s stock market returns had the Deepwater Horizon oil spill never happened. The capital asset pricing model uses the risk-free rate, BP’s beta, which captures the volatility of the stock vis-à-vis the market (in this case the S&P 500) and the expected market return (that of the S&P500). This is captured in the following formula:

R¯a=Rf+β(RmRf)

For the risk-free rate we use the US 10-year treasury bond, as is customary, and for the beta, we used BP’s two-year market beta. These data were obtained from the CapitalIQ database.

Subsequently, we compare the expected returns with BPs actual returns to calculate the abnormal returns. The abnormal returns are the actual returns, minus the returns we predicted using CAPM. Fig 7 shows the predicted and the actual returns. Showing that, although there is an immediate drop in market returns after the disaster, there is no clear break in the trend from before the disaster.

Fig 7. CAPM expected market returns vs. actual market returns BP.

Fig 7

Fig 8 plots the abnormal returns of BP. Which is the difference between the actual market returns and the expected market returns based on CAPM.

Fig 8. BP’s abnormal returns.

Fig 8

More formally, we use a simple regression model to see whether the abnormal returns are statistically significantly different after the disaster compared to before the disaster. Estimation results are reported in Table 4. We check for short-term (2 years) and long-term (2–7 years) differences, separately. We find no significant differences. We run the same analysis also excluding other integrated oil and gas companies and only oil and gas companies, finding similar results, which are reported in S1 Appendix. This means that we fail to reject the null that BP experienced no change in abnormal returns after the disaster. Though the decline in stock returns in the wake of the disaster is not statistically significant, we recognize that some might consider it to be economically significant (about 27% decline over a two-year period).

Table 4. BP abnormal returns pre vs post disaster.

(1)
Abnormal Returns
Short term (0–2 years) -1.132
(0.577)
Long term (2–7 years) -0.569
(0.722)
Constant -0.179
(0.887)
Observations 125

p-values in parentheses: * p<0.05, ** p<0.01, *** p<0.001

We also compare the cumulative abnormal returns (CAR) of BP with those of other integrated oil and gas companies. We find initial negative abnormal returns for BP in the first month after the disaster, but these stabilize over time and then slowly diminish in the long run. This, however, is in line with the cumulative abnormal returns for other integrated oil and gas companies as shown in Fig 9. The initial drop however is not recovered over time, and still signals an economically important drop in BP’s value.

Fig 9. Cumulative Abnormal Returns (CAR) for BP, Shell, Chevron, and ExxonMobil.

Fig 9

Spillover effects

Did the Deepwater Horizon oil spill influence the total returns of other firms in the oil and gas industry? Fig 10 gives a general impression of the behavior of the market returns of other oil and gas companies in the aftermath of the disaster. It also shows how BP’s performance may have dropped vis-à-vis other oil and gas firms, despite the effect of the oil spill not being statistically significant.

Fig 10. Market returns of oil and gas firms after deepwater horizon oil spill.

Fig 10

We also estimated synthetic control models for all of the S&P 500 firms in the Oil & Gas Exploration & Production and Integrated Oil & Gas GICS sub-industries. Although Shell is not included in the S&P 500, we included it in our analysis because it was one of the brands included in our reputation analysis. We report the RMSPE ratios and associated p-values in Table 5.

Table 5. Pre/post RMSPE ratios and P-values for oil & gas firms.
Name Full Sample (May 2010—July 2017) Short-Term (May 2010—June 2012) Long-Term (July 2012 –July 2017)
BP 5.84 1.65 6.79
(0.20) (0.48) (0.20)
Cabot Oil & Gas 5.46 2.41 6.24
(0.21) (0.26) (0.21)
Chevron 2.78 1.43 3.15
(0.59) (0.56) (0.58)
ConocoPhillips 2.06 0.48 2.41
(0.72) (0.94) (0.72)
Devon Energy 2.65 0.37 3.10
(0.57) (1.00) (0.57)
EOG Resources 1.63 1.13 1.79
(0.82) (0.70) (0.82)
ExxonMobile 6.18 0.99 7.24
(0.31) (0.77) (0.31)
Occidental Petroleum 1.17 1.63 0.94
(0.92) (0.48) (0.96)
Pioneer Natural Resources 2.57 1.67 2.84
(0.61) (0.48) (0.62)
Shell 6.69 0.87 7.84
(0.15) (0.81) (0.14)

Note: P-values in parentheses are calculated based on the firm’s rank among the components of its own synthetic control estimator. *** p<0.01, ** p<0.05, * p<0.1

Arco, Citgo, and Gulf are not represented in Table 5 because no stock market returns data were available. Arco has been a subsidiary of BP since 2000. Citgo is privately held, and Gulf merged with Chevron in 1985. Stock market returns data were available for Sunoco, but they exited the oil refining business in 2010, and so may not be an appropriate comparator for BP.

Spillover effects would be indicated by RMSPE ratios greater than one in Table 5. According to the results in Table 5, other Oil & Gas firms exhibited RMSPE ratios greater than one during our sample period, but we must also consider the significance of these results. As we did with BP, we calculated the rank of each firm’s RMSPE ratios among the components of their respective synthetic controls. The values in parentheses in Table 5 are the p-values calculated based on those rankings. We find no evidence of significant spillover effects on the stock market returns of other Oil & Gas firms. We interpret these results to mean that the Deepwater Horizon disaster did not spill over to stock market returns of other firms in the same industry.

We should note that this null result may reflect the steps other oil and gas firms took toward mitigating disasters after Deepwater Horizon. This response might have been motivated by the desire to preempt new regulations which could impact the sectors’ financial market performance, as Baron and Diermeier have argued [40]. If these steps were taken in anticipation of future effects on financial performance, they could bias the estimates presented here. However, we do not find much evidence of the evolution of any industry-level voluntary program, which would lead to an ex-ante response to mitigate accidents from happening in the first place. Recall the chemical industry launched its self-regulatory program, Responsible Care, in the aftermath of the 1984 Union Carbide’s Bhopal disaster. It outlined best practices that it expected its member firms to follow to prevent chemical disasters from taking place in the first place. Yet, no such ex-ante industry-level response emerged in the aftermath of Deepwater.

Also, Shell, while professing deep distress, defended offshore drilling as necessary to meet global demand and suggested that if it had been in charge, the accident would not have happened. Exxon Mobil and Chevron also followed the same playbook and took no substantial unilateral action.

What might explain the lack of long-term consequences for BP’s financial performance, given the plethora of risks resulting from the accident? BP’s 2012 annual report acknowledged:

The Gulf of Mexico oil spill has damaged BP’s reputation, which may have a long-term impact on the group’s ability to access new opportunities, both in the US and elsewhere. Adverse public, political and industry sentiment towards BP, and towards oil and gas drilling activities generally, could damage or impair our existing commercial relationships with counterparties, partners and host governments and could impair our access to new investment opportunities, exploration properties, operatorships or other essential commercial arrangements with potential partners and host governments, particularly in the US” [41].

The financial penalties BP incurred were substantial costs: $60 billion (in relation to BP’s market capitalization of about $170 billion in 2009) as fines, penalties, clean up and mitigating costs. Arguably, because BP took several steps to mitigate the reputational damage and change internal systems, these might have provided some cushion against a decline in stock market returns. BP’s response took place at multiple levels. In terms of public relations, it issued a series of public apologies. Its so-called “apology commercial”, featuring its CEO Tony Hayward, was criticized because it tended to highlight what BP had done in the past, instead of sufficiently and honestly taking responsibility for the oil spill. His Congressional testimony was more contrite, but Hayward seemed not to provide clear answers in response to questions posed by the Congressional committee. All in all, it is remarkable that BP suffered no significant decrease in stock market returns.

Conclusions

Our results have important implications for the literature on corporate environmental governance. We demonstrate that, beyond the obvious legal liability, citizens will hold firms accountable for their workplace safety and environmental records for a substantial period. Recall that since 2000, BP had invested a substantial sum in the "Beyond Petroleum" campaign to highlight its commitment to environmental protection. Further, after the Deepwater accident, it invested about $500 million in brand enhancement [42]. Yet, the reputational damage caused by the Deepwater accident has persisted. It needs to be mentioned however that the impact of a firm’s workplace safety and environmental conduct on its reputation is mediated by the attention it gets from media and activists. The scale of the Deepwater Horizon oil spill was so large that the issue got automatic visibility. For smaller accidents, reputational damages could increase if environmental groups and the media decide to focus on it in their campaigns.

Nevertheless, this finding should be a wake-up call for any firm as it develops its workplace safety and environmental management strategies. Information about firms’ safety records seems to have a lasting effect on their reputation. In addition, this research provides insights on reputational spillovers among firms selling an undifferentiated product and can help us understand under which conditions firms within the same sector hold their reputation in common.

While reputational effects are long-lasting, the financial markets appear to bounce back rather quickly after an initial shock. Brand reputation and financial market returns are driven by different mechanisms. Reputations could be influenced by consumers’ product experience and value perceptions, while stock market returns could be affected by profits, new product launches, and market volatility. Arguably brand reputations could certainly affect stock market returns but the opposite effect is less plausible. Factors such as industrial accidents or regulatory scrutiny could affect both. In this case, BP seems to have escaped any long-term consequences of its environmental disaster in terms of its stock market returns. This is in some ways disappointing: a major disaster should severely penalize the company’s financial market returns for a long time. Because corporate compensation is often linked with the stock price, top management will pay serious attention to the issue of industrial safety if their compensation is affected. Of course, in the aftermath of Deepwater, BP’s CEO resigned, and BP paid several billion dollars in penalties. Yet, we did not find a statistically significant effect on its stock market returns, which calls into question whether stock markets create sufficiently strong incentives for firms to pay careful attention to industrial safety.

The lack of a coordinated industry response to the disaster is also puzzling. Why might this be so? There are several possible reasons. First, this accident did not result in large-scale death or dislocation of communities (as in wildfires or hurricanes). Thus, after the initial shock and the graphic images of oil pollution and the destruction of marine life, the media tended to move on. Indeed, within 6 months of the accident, Louisiana (the state most impacted by the spill) politicians were demanding that the federal government should not over-regulate this industry. Mary Landrieu, the Democratic senator from Louisiana, demanded that the EPA lifts the ban on BP from securing federal contracts [43]. Interestingly, even the UK government lobbied the Obama administration that BP should not be forced to pay excessive compensation.

Moreover, environmental issues have become deeply partisan. As environmental groups saw the Deepwater accident as an opportunity to push the climate agenda by demanding an end to offshore drilling, partisan identities flared up. Conservatives rushed to defend the offshore oil industry—and during Trump’s Presidency, even some of the modest new regulations were rolled back. Thus, bipartisan efforts to hold the oil industry accountable were weak. A new federal regulation (based on the recommendations of the US Chemical Safety Board), the 2016 Wells Control Rule, emerged. The federal government created a new regulatory body, the Bureau of Safety and Environmental Enforcement (located in the Department of Interior), which is tasked with frequently inspecting offshore facilities for regulatory compliance. However, as Republicans took over the House in 2011, it was clear that new stringent federal regulations aimed at this industry will be difficult to enact. This might also be why the industry did not feel the need to invest in regulatory preemption via voluntary programs. This lack of industry-level efforts has not been systematically explored and requires future research.

Lastly, the lack of industry response could exactly be due to the lack of financial consequences of disasters. Several industry associations have sponsored voluntary programs that outline best practices, codes of conduct and so on. Scholars suggest that these industry-level clubs [23, 24] are vehicles to provide collective insurance, particularly in the context of industrial accidents; the assumption being that a mishap for one firm creates negative reputational spillovers across the industry. The classic case is the chemical industry’s Responsible Care Program whose emergence was partially motivated by the 1984 Bhopal disaster at Union Carbide’s facility [44]. Thus, via industry-level clubs, industry associations can build collective goodwill for environmental stewardship and secure some sort of reputational insurance for their members. Yet, our paper shows that even a major industrial accident such as Deepwater Horizon may not cause significant declines in stock market returns for oil and gas firms, despite long-term reputational damage. Hence, our finding challenges the fundamental motivation for industry associations to create industry-level regulatory clubs.

Supporting information

S1 Appendix

(DOCX)

S1 Dataset

(DOCX)

Acknowledgments

Earlier versions of this paper were presented at the Environmental and Politics Governance Conference 2020 and Western Political Science Association Conference 2021. We’d like to thank the reviewers and the panel for their feedback.

Data Availability

All data files are available from the Figshare database (https://doi.org/10.6084/m9.figshare.19758640.v1).

Funding Statement

We like to thank the Swiss National Science Foundation (snf.ch) for the Doc.Mobility grant P1GEP1_181399 for EAH. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

J E Trinidad Segovia

21 Jul 2021

PONE-D-21-16006

Penalties for industrial accidents: The impact of the Deepwater Horizon accident on BP's reputation and stock price

PLOS ONE

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Reviewer #1: I love your paper and your findings completely make sense to me. Three quick questions.

1. Why didn’t you apply the event study method for stock price analysis?

2. I am in sync with you that some scandal did not necessarily sully the reputation of other similar companies (e.g. the Volkswagen Diesel scandal did not affect other German car companies). One quick question that pops up in mind is the BP scandal could have the reverse effect on its competitors: the competitors’ stock prices might have risen in the wake of the oil spill. Could you check one more time whether the stock prices of BP’s competitors rose after the DeepWater Horizon? I am eager to see the graph of each competitor’s stock prices (APA Corp, Cabot, Chevron, Conoco Phillips, Devon Energy, EOG resources, Exxon Mobile, Marathon, Shell, and Valero) before/after the Deepwater Horizon. Could you display a list of graphs showing historical stock prices of each competitor?

3. I am really curious about the correlation between BP’s reputation and its stock prices. Could you please check the correlation between the two variables in separate time windows (before/after the Deepwater Horizon). Do they have sig relationships or not? It would be very interesting if we could see a more dynamic relation between the two variables (e.g., BP’s reputation might have had positive relationships with its stock prices for 1-2 months after the Deepwater Horizon scandal (i.e., both of them dropped after the negative event), but not 6 months later (i.e., BP’s reputation still suffered, but not its stock prices).

Reviewer #2: Penalties for industrial accidents: The impact of the Deepwater Horizon accident

on BP’s reputation and stock price

6/29/2021

Main point of this paper

Paper attempts to measure long term impact to BP after the 2010 Deepwater Horizon explosion using two metrics: the reputation variables obtained from YouGov’s Brand Index and financial data from Capital IQ. They develop a proxy for BP’s reputation and find a 50% decline after the accident and a persistent decline until 2017. When testing effect on stock prices, they only find a short-term effect. They conclude that even though reputation suffers in the long run, stock prices do not suffer in the long run.

Methodology issues

Some clarifications are needed to fully understand the data and methodologies used.

Some suggestions are provided for the comparison of stock performance.

Reputation

Data source and its limitations must be clearly stated.

YouGov data must be described and brands in the energy sector must be listed. The use of brands instead of companies must be clearly explained and when applicable, connect the brand with the firm, and state when brands belong to non-public firms.

Industries within the energy sector then must be clearly separated showing the main differences among them. BP is an integrated Oil and Gas company, like Chevron, Exxon and Shell. Firms like Marathon and ConocoPhillips are considered Exploration and Production while Valero, Sunoco, Citgo are in the refining and marketing of gasoline. An extremely important omission in this study is the absence of oil and gas services companies like Schlumberger, Halliburton, Transocean, Weatherford and others, which were directly involved in the accident. The absence, though caused by the data source, must be recognized as one of the weakness of the study.

More detail is needed on how the weights for the “control” brand are determined. For example, you start with a full sample of firms or a subsample? What’s the sample size? To be a candidate for inclusion in the synthetic control, do you remove oil & gas firms where suspected spillover occurs? How many firms are left? What is the technique used? Does the 0.756 for Shell means that the synthetic control is 75% Shell? Why do Marathon and Chevron not appear in the synthetic even though they are in the same industry?

Stock price

Methodology is not consistent with financial literature. At first glance it appears that they just want to adapt the methodology used when evaluating reputation to stock prices.

Evaluation of the performance of a company’s stock is normally done in total annual returns, which include price appreciation and dividend income.

If you concentrate on the performance of one firm, it must be compared against a portfolio of firms with similar characteristics. So, the formation of a good comparable portfolio is important. However, such portfolios must be constructed using meaningful financial ratios/variables, such as total assets, profitability, leverage, efficiency and risk. Authors used 6 ratios to match firms however only ROA and Broker recommendation can be reasonably used to match firms. Per share ratios are not commonly used.

Authors say 273 firms are used to build a synthetic control. Those are just too many firms for a “match”, especially if they want to match the risk of the company in question. if they want to use a broad index, they can just use the S&P 500 as a measure of the market and compare the firm against the overall US market.

Using data publicly available I make a quick comparison of the performance from May 2010 to July 2017 of BP vs the S&P500 index. Average annual return for BP is around 2.4% for the 7 years after the accident, while the market had an average annual return around 23%. That is an economically significant difference, and the numbers suggest that BP has not caught up with the normal behavior of the stock market, even after considering BP’s market beta.

Risk was not considered in this analysis. The market model is normally used in the literature and market-adjusted or beta-adjusted returns can be obtained when making a risk-adjusted comparison.

In summary. share price prediction is not a common practice in the literature and the RMSPE comparison is not convincing. It is suggested that authors create portfolios and then make point comparisons of CAR (cumulative abnormal return) and/or time series of monthly total returns (not prices) and then make comparisons against meaningful portfolios. Possible portfolios to use for comparison would be based on oil & gas industries (integrated, services, refining, exploration). To test the spillover effect, build portfolios with companies not in the energy sector but with equal risk on the period before 2010.

Reviewer #3: You are looking at an interesting topic, both for the management of environmental issues by firms, but also, more generally, for private regulation and the reduction of environmental damages.

In that spirit, the reputational implications are indeed fundamental, and the originality of your work is to focus on one specific case but also to use quantitative methods to do so. Overall, I like what you do in the paper and I find your analysis both interesting and convincing. My comments are thus mostly developmental.

One caveat, both in your empirics and in your interpretation of the results has to do with what firms do when they see a large damage happening. Contrary to what you suggest in your paper, both rival firms and industry associations should have incentives to self-regulate as much as possible in order to prevent both other spillages and reputation losses. This might be one of the key reasons why you don’t observe much regarding spillovers to other firms or long-term effects on stock-prices. Econometrically, this raises an important question as there is a set of key unobserved variables that have to do with what firms do when they observe BP’s pollution problem. Can you do something about this? Since you don’t have many firms to cover, it might be possible to collect some data on what industry rivals have reacted. It would strengthen your analysis for sure.

The biggest issue, though, is in the interpretation of the results. You argue in the Discussion section that the industry association plays no role but it might be the opposite: all firms might have reacted fast and in a coordinated way, and might thus have pre-empted the problem. This might be one of the reasons why there is no spillover to the rest of the sector. In that case, the industry association would both play a role in pushing towards self-regulation and in protecting the firms.

Note that this pre-emption argument is pretty much what the theoretical literature would predict. See for instance Baron and Diermeier in the Journal of Economics and Management Strategy.

Another question is that there are key players that are currently not accounted for in your paper: environmental activists and the media. These typically play an important role in creating saliency regarding the issue, thus impacting firms’ reputations. On this, see for instance the article by Breitinger and Bonardi on reputational damages in Business and Politics. There might be heterogeneity regarding environmental issues that way. Of course, one could argue that for a significant issue such as the one you are looking at here, this might be less relevant (since the issue is going to be very salient in any case). But I think you should at least mention this.

Last point that, I think, should be discussed is the difference between reputation and stock prices. At the moment, you treat these as the same thing and you hint that their evolution is driven by similar mechanisms. This would be an overstatement. I think you need to take these differences into account in the discussion of your results.

**********

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PLoS One. 2022 Jun 15;17(6):e0268743. doi: 10.1371/journal.pone.0268743.r002

Author response to Decision Letter 0


25 Jan 2022

Rebuttal Memo

Penalties for industrial accidents: The impact of the Deepwater Horizon accident on BP’s reputation and stock market returns

(previous title: Penalties for industrial accidents: The impact of the Deepwater Horizon accident on BP’s reputation and stock price)

(PONE-D-21-16006).

Dear Reviewers:

Thank you for your thoughtful, detailed, and constructive comments on our manuscript. We agree with the substance of your concerns and are encouraged by the strengths you see in the manuscript and the contributions our paper can make. We enclose a memo detailing your suggestions (in italics) and outlining how we address them in the revised manuscript

Regards,

Authors

Reviewer 1

I love your paper and your findings completely make sense to me. Three quick questions.

1. Why didn’t you apply the event study method for stock price analysis?

Response:

We include the event study method as a robustness check in the revised paper. Our substantive results do not change.

2. I am in sync with you that some scandal did not necessarily sully the

reputation of other similar companies (e.g. the Volkswagen Diesel scandal did not affect other German car companies). One quick question that pops up in mind is the BP scandal could have the reverse effect on its competitors: the competitors’ stock prices might have risen in the wake of the oil spill. Could you check one more time whether the stock prices of BP’s competitors rose after the DeepWater Horizon? I am eager to see the graph of each competitor’s stock prices (APA Corp, Cabot, Chevron, Conoco Phillips, Devon Energy, EOG resources, Exxon Mobile, Marathon, Shell, and Valero) before/after the Deepwater Horizon. Could you display a list of graphs showing historical stock prices of each competitor?

Response

Great point. We have included a new graph in the revised paper. As the graph shows, there is no consistent trend in competitor firms’ total or stock market returns (that Reviewer 2 wants us to focus on) in the aftermath of the accident.

3. I am really curious about the correlation between BP’s reputation and

its stock prices. Could you please check the correlation between the two variables in separate time windows (before/after the Deepwater Horizon). Do they have sig relationships or not? It would be very interesting if we could see a more dynamic relation between the two variables (e.g., BP’s reputation might have had positive relationships with its stock prices for 1-2 months after the Deepwater Horizon scandal (i.e., both of them dropped after the negative event), but not 6 months later (i.e., BP’s reputation still suffered, but not its stock prices).

Response

Excellent suggestion. Please see the graphs below.

BP’s reputation and total returns (as well as stock prices) appear to move in tandem before and after the accident.

Reviewer #2

Paper attempts to measure long term impact to BP after the 2010 Deepwater Horizon explosion using two metrics: the reputation variables obtained from YouGov’s Brand Index and financial data from Capital IQ. They develop a proxy for BP’s reputation and find a 50% decline after the accident and a persistent decline until 2017. When testing effect on stock prices, they only find a short-term effect. They conclude that even though reputation suffers in the long run, stock prices do not suffer in the long run.

1. YouGov data must be described and brands in the energy sector must

be listed. The use of brands instead of companies must be clearly explained and when applicable, connect the brand with the firm, and state when brands belong to non-public firms.

Response

We have included this information in the revised paper. We now have an appendix with all the brands in YouGov data and highlight those brands in the energy sector.

2. Industries within the energy sector then must be clearly separated

showing the main differences among them. BP is an integrated Oil and Gas company, like Chevron, Exxon and Shell. Firms like Marathon and ConocoPhillips are considered Exploration and Production while Valero, Sunoco, Citgo are in the refining and marketing of gasoline. An extremely important omission in this study is the absence of oil and gas services companies like Schlumberger, Halliburton, Transocean, Weatherford and others, which were directly involved in the accident. The absence, though caused by the data source, must be recognized as one of the weakness of the study.

Response

We have clarified which GICS sub-industries are included in our analysis, and acknowledged the absence of other relevant firms such as Schlumberger, Halliburton, Transocean, and Weatherford.

3. More detail is needed on how the weights for the “control” brand are

determined. For example, you start with a full sample of firms or a subsample? What’s the sample size? To be a candidate for inclusion in the synthetic control, do you remove oil & gas firms where suspected spillover occurs? How many firms are left? What is the technique used? Does the 0.756 for Shell means that the synthetic control is 75% Shell? Why do Marathon and Chevron not appear in the synthetic even though they are in the same industry?

Response

We have clarified these issues in the manuscript.

Sample size:

For the reputation analysis, the initial sample size was 660 brands, while for stock price analysis, it was 189 companies.

Subsample:

Within the full sample, we identify the combination of firms and weights for each firm that would create a synthetic firm with underlying characteristics that are as close as possible to the underlying characteristics of BP before the disaster. For reputation analysis, the underlying characteristics are the general impression of the brand, the perceived quality of the product, the value for money, and the respondent’s willingness to work for the company. For financial analysis, these are total assets, gross profits, total debt, return on investment, volatility, and “broker recommendation” score.

Excluding oil and gas firms:

To create synthetic control for BP, we included oil and gas firms in the sample (and then allowed the estimator to identify which specific firms to include in the synthetic control).

How many firms are left?

For reputation analysis, the synthetic control consists of 15 (of the 660 in the initial sample) firms, while for the financial analysis, it consists of 188 (of the 189 in the initial sample) firms.

Technique used:

To identify firms for including in the synthetic control and assigning them weights (to minimize the difference between the underlying characteristics of the synthetic control compared to BP), we use the estimator designed by Abadie et al. Here is the citation: Abadie A, Diamond A, Hainmueller J. 2015. Comparative politics and the synthetic control method. American Journal of Political Science, 59(2):495–510.

Is synthetic control 75% Shell?

Yes, it is.

Why are Marathon and Chevron not part of the synthetic control:

The reason is that the estimator was able to create a closer match with BP’s underlying characteristics by excluding these firms.

Spillovers:

In creating the synthetic control for BP, we did not exclude oil and gas firms. In this analysis of the spillover effect, we formed synthetic controls that exclude other oil and gas firms.

4. Stock Price: Methodology is not consistent with financial literature. At

first glance it appears that they just want to adapt the methodology used when evaluating reputation to stock prices. Evaluation of the performance of a company’s stock is normally done in total annual returns, which include price appreciation and dividend income.. If you concentrate on the performance of one firm, it must be compared against a portfolio of firms with similar characteristics. So, the formation of a good comparable portfolio is important. However, such portfolios must be constructed using meaningful financial ratios/variables, such as total assets, profitability, leverage, efficiency and risk. Authors used 6 ratios to match firms however only ROA and Broker recommendation can be reasonably used to match firms. Per share ratios are not commonly used.

Response

We have revised our methodology (and the paper title) for the financial analysis. Importantly, we now use total returns (or stock market returns) as our dependent variable and conduct a robustness check by calculating BP’s abnormal returns within the CAPM framework. To construct the synthetic control for financial analysis, we now use total assets, gross profits, total debt, return on investment, volatility, and broker recommendation, as suggested.

5. Authors say 273 firms are used to build a synthetic control. Those are

just too many firms for a “match”, especially if they want to match the risk of the company in question.

Response

We have clarified this issue in the paper. We now start with a sample of 189 firms. This number differs from our previous draft due to missing observations for some variables we now use to construct the synthetic control. To reiterate, not all 189 firms necessarily become part of the synthetic control. The reason is that the estimator creates the synthetic control by selecting specific firms and assigning them weights to minimize the difference between the synthetic control and BP in terms of their (pre-intervention) characteristics. Based on your very helpful suggestions, we have now updated the variables impacting market returns and included risk (volatility) as a variable informing the formation of our synthetic control.

6. If they want to use a broad index, they can just use the S&P 500 as a

measure of the market and compare the firm against the overall US market. Using data publicly available I make a quick comparison of the performance from May 2010 to July 2017 of BP vs the S&P500 index. Average annual return for BP is around 2.4% for the 7 years after the accident, while the market had an average annual return around 23%. That is an economically significant difference, and the numbers suggest that BP has not caught up with the normal behavior of the stock market, even after considering BP’s market beta.

Risk was not considered in this analysis. The market model is normally used in the literature and market-adjusted or beta-adjusted returns can be obtained when making a risk-adjusted comparison.

Response

In the revised paper, we have included a robustness check to calculate the abnormal returns and compare BP’s returns to the market returns of S&P 500 companies. We do not find that the abnormal returns are statistically significantly different between pre-disaster and post-disaster time periods.

7. In summary. share price prediction is not a common practice in the literature and the RMSPE comparison is not convincing. It is suggested that authors create portfolios and then make point comparisons of CAR (cumulative abnormal return) and/or time series of monthly total returns (not prices) and then make comparisons against meaningful portfolios. Possible portfolios to use for comparison would be based on oil & gas industries (integrated, services, refining, exploration). To test the spillover effect, build portfolios with companies not in the energy sector but with equal risk on the period before 2010.

Response:

In the revised paper, we compare BP’s cumulative abnormal returns to other integrated oil and gas companies. We find that the cumulative abnormal returns of BP do go down over time, but more so starting from two years after the oil spill. The same trend is visible, however, in other integrated oil and gas companies, which suggests likely other factors at play in this divergence from the market, particularly given the absence of a short-term negative impact. We have noted this in the revised manuscript.

Reviewer 3

1. You are looking at an interesting topic, both for the management of environmental issues by firms, but also, more generally, for private regulation and the reduction of environmental damages.

In that spirit, the reputational implications are indeed fundamental, and the originality of your work is to focus on one specific case but also to use quantitative methods to do so. Overall, I like what you do in the paper and I find your analysis both interesting and convincing. My comments are thus mostly developmental.

Response

Thank you

2. One caveat, both in your empirics and in your interpretation of the results has to do with what firms do when they see a large damage happening. Contrary to what you suggest in your paper, both rival firms and industry associations should have incentives to self-regulate as much as possible in order to prevent both other spillages and reputation losses. This might be one of the key reasons why you don’t observe much regarding spillovers to other firms or long-term effects on stock-prices. Econometrically, this raises an important question as there is a set of key unobserved variables that have to do with what firms do when they observe BP’s pollution problem. Can you do something about this? Since you don’t have many firms to cover, it might be possible to collect some data on what industry rivals have reacted. It would strengthen your analysis for sure.

Response

This is an excellent point. We mention this in the revised manuscript to temper our conclusions.

How did individual firms respond to the BP accident, and whether this mitigated the spillover effect on their stock market returns? Regarding responses of other oil and gas firms, not much was done. We have noted this in the manuscript.

BP’s response took place at multiple levels. In terms of public relations, it issued a series of public apologies. Its so-called “apology commercial”, featuring its CEO Tony Hayward, was criticized because it tended to highlight what BP had done in the past instead of sufficiently and honestly taking responsibility for the oil spill. Hayward’s Congressional testimony was more contrite, but Hayward seemed not to provide clear answers in response to questions posed by the Congressional committee. While professing deep distress, Shell defended offshore drilling as necessary to meet global demand and suggested that if it had been in charge, the accident would not have happened. Exxon Mobil and Chevron also followed the same playbook also did nothing significant unilaterally

3. The biggest issue, though, is in the interpretation of the results. You

argue in the Discussion section that the industry association plays no role but it might be the opposite: all firms might have reacted fast and in a coordinated way, and might thus have pre-empted the problem. This might be one of the reasons why there is no spillover to the rest of the sector. In that case, the industry association would both play a role in pushing towards self-regulation and in protecting the firms. Note that this pre-emption argument is pretty much what the theoretical literature would predict. See for instance Baron and Diermeier in the Journal of Economics and Management Strategy.

Response

This is an excellent point; theoretically, we could have expected an industry-level response to a collective reputation problem, perhaps coordinated by the American Petroleum Institute. And, this response might have been motivated by the desire to preempt new regulation, as Baron and Diermier have argued.

The industry responded in a limited (ex post) way. They claimed that the lack of an offshore fleet to deal with spills was a major problem. Thus, instead of individual companies creating their individual offshore relief fleet, the big companies created a Marine Well Containment Company (MWCC), and the smaller companies created HWCG. These fleets can be deployed quickly to the accident site to cap the spilling wells and capture the spilled oil until a relief well is drilled.

Regarding industry-level action, the American Petroleum Institute (API) announced that it had improved its safety standards and made them available to the public to show the standards in place to promote safety.

However, we do not find much evidence of the evolution of any industry-level voluntary program, which would lead to an ex-ante response to mitigate accidents from happening in the first place. Recall the chemical industry launched its self-regulatory program, Responsible Care, in the aftermath of the 1984 Union Carbide’s Bhopal disaster. It outlined best practices that it expected its member firms to follow to prevent chemical disasters from taking place in the future. Yet, no such ex-ante industry-level response emerged in the oil and gas industry in the aftermath of Deepwater.

Why might this be so? There are several possible reasons. First, this accident did not result in deaths or massive dislocation of communities (as in wildfires or hurricanes). Thus, after the initial shock and the graphic images of oil pollution and the destruction of marine life, the media tended to move on. Indeed, within six months of the accident, Louisiana (the state most impacted by the spill and highly dependent on oil and gas royalties) politicians were demanding that the federal government not over-regulate this industry. Mary Landrieu, the Democratic senator from Louisiana, demanded that the EPA lifts the ban on BP from securing federal contracts. Interestingly, even the UK government lobbied the Obama administration that BP should not be forced to pay excessive compensation!

Moreover, environmental issues have become deeply partisan. As environmental groups saw the Deepwater accident as an opportunity to push the climate agenda by demanding an end to offshore drilling, partisan identities flared up. The conservatives rushed to defend the offshore oil industry -- and during Trump’s Presidency, even some of the modest new regulations were rolled back. Thus, bipartisan efforts to hold the oil industry accountable were few and weak. A new federal regulation (based on the recommendations of the US Chemical Safety Board), the 2016 Wells Control Rule, emerged. The federal government created a new regulatory body, the Bureau of Safety and Environmental Enforcement (located in the Department of Interior), which is tasked with frequently inspecting offshore facilities for regulatory compliance. However, as Republicans took over the House in 2011, it was clear that new stringent federal regulations aimed at this industry would be difficult to enact (this is probably also why the industry did not feel the need to invest in regulatory pre-emption via voluntary programs). We include this question in the concluding section of the manuscript.

4. Another question is that there are key players that are currently not

accounted for in your paper: environmental activists and the media. These typically play an important role in creating saliency regarding the issue, thus impacting firms’ reputations. On this, see for instance the article by Breitinger and Bonardi on reputational damages in Business and Politics. There might be heterogeneity regarding environmental issues that way. Of course, one could argue that for a significant issue such as the one you are looking at here, this might be less relevant (since the issue is going to be very salient in any case). But I think you should at least mention this.

Response

Great suggestion. We have noted this in the revised paper. Our sense is that the scale of the disaster was huge that the issue initially got automatic visibility. Environmental activists did mobilize and launched campaigns to boycott BP. But your point is well taken; for smaller, less visible accidents, reputational damages could increase if environmental groups and the media decide to focus on them in their campaigns. We have noted this in the revised manuscript.

4. Last point that, I think, should be discussed is the difference between

reputation and stock prices. At the moment, you treat these as the same thing and you hint that their evolution is driven by similar mechanisms. This would be an overstatement. I think you need to take these differences into account in the discussion of your results.

Responses

Fair point. Arguably brand reputations could affect stock market returns, but the opposite effect is less plausible. Reputations could be influenced by consumers’ product experience and value perceptions, while stock market returns could be affected by profits, new product launches, and market volatility. Factors such as industrial accidents or regulatory scrutiny could affect both. We have noted this in the revised paper.

Attachment

Submitted filename: plos bp paper Response to Reviewers.docx

Decision Letter 1

J E Trinidad Segovia

25 Feb 2022

PONE-D-21-16006R1Penalties for industrial accidents: 

The impact of the Deepwater Horizon Accident on BP’s reputation and stock market returnsPLOS ONE

Dear Dr. Holtmaat,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, I feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, I invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Although the manuscript has been significantly improved in this new version, one the reviewers still show major concerns about the methodology used. The reviewer considers that conclusions are not supported by the results, so the manuscript cannot be accepted until these doubts are not attended.

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Reviewer #1: Thanks for your great work! You addressed my concern and appreciate your efforts. One last thing. BP's stock prices indeed dropped and suffered at least for a month in the wake of the crisis. If you look at the BP's SP it was $59 on Apr 16, 2010 and dropped to $28 in June. Just two months, but it is clearly true that the SP dropped A LOT. My sense is you should be a little more careful when you argue that the SP was not influenced by the spill; it was affected although in a very short period of time. In the mid- long-term, the SP was recovered from the crisis. So please modify your argument in a more reasonable way. The reputation was damaged, but the SP was not at least in the mid- or long-term "although it had suffered for a very short period time". Please add this one in your abstract. In your current abstract you said "Yet, in terms of financial market returns, we do not find a decline in the stock market returns either in the short term (1-2 years) or the long term (2-7 years)" some people may think short-term should be 1 month, not 1 year. So to avoid any controversy please add that the SP dropped for a month but it was quickly recovered. Thanks.

Reviewer #2: Penalties for industrial accidents: The impact of the Deepwater Horizon accident on BP’s reputation and stock market returns

2/19/2022

Second review

I appreciate the effort done trying to address the methodology issues mentioned in my first review.

I disagree with your interpretation/conclusion there is no evidence that the spill diminished BP stock returns. Your discussion dismisses the fact that -1.458 x 12 = a loss of 17.5% per year and investors did suffer a cumulative loss of about 35% in the 2 years following the accident. That may be statistically insignificant yet is economically significant. Your analysis fails to show the relative underperformance of BP compared to other firms in the oil & gas industry. While such underperformance may not be statistically significant, the paper seems to ignore economically important drops in BP value, especially when compared to its peers.

I still have several concerns regarding the methodologies used in this paper, as outlined below

I recommend authors refer to Kothari, S.P., and Jerold B. Warner, 2004, "Econometrics of Event Studies” and use long term event study methodology. You will probably need a colleague in the finance department to review the manuscript and help you with this paper.

Comments about change of focus

You completely changed your emphasis to stock market returns (title and most discussions) but you probably overdid it. Some examples:

• Rows 103-104 say ”stock market returns provide a measure of the expected future earnings of the firm”. Previously you had stock prices. Stock prices do that, but not stock returns.

• Row 105 says “penalty on stock market returns”. This doesn’t sound right.

• Row 303 “influence stock market returns, especially its future earnings.” Should only say “influence future stock returns”

Please review the usage of “stock price”, “stock returns” and try to make clarifications as needed. Not all instances must be “returns”

Reputation study

Getting a synthetic control is a good idea. However, assigning 76% weight on another oil and gas company raises concerns about the assumptions made and the soundness of the weighting mechanism.

Allowing for the possibility of a contagion effect, you should not be using any oil and gas firms in the synthetic control. That would be a “clean” control. That would remove the issue of using too much of an oil and gas company in your market control. You already remove oil and gas firms when you create synthetic controls for other oil and gas firms (rows 267-268), why not do it for the main subject of study, BP?

In addition to the clean market control, you should create another synthetic with oil and gas firms/brands without BP. That would be your industry control, which would bring these changes:

1. Figure 1 would have a third line (the industry) and contagion can be expected immediately after the explosion. In fact, one can argue that the blue line has the lowest reputation score post-accident right after the explosion, suggesting a minor contagion effect.

2. Figure 2 would have two lines, one for the industry control and one for BP. This chart would show when the industry recovers from any possible contagion.

Figures 3 & 4 makes sense for oil and gas companies/brands. I suggest you remove figure 3.

Stock market study

There is no need to use “the same synthetic control approach described above” (row 322) on returns. In fact, most of the tests used and the charts/tables presented are uncommon in the finance literature. I strongly recommend authors refer to Kothari, S.P., and Jerold B. Warner, 2004, "Econometrics of Event Studies” and use long term event study methodology. If you really want to adapt novel methodologies to stock prices/returns, please find literature that has done it before and include it in reference list. If unavailable, state that you are trying something new, as that may be one of the contributions of the paper. Unfortunately, in my opinion, it is not working.

I am including suggestions below for the figures/tables/methods in the section of Stock Market returns. Hope they help.

In finance we use two main methods to weight stocks into portfolios: market value weight or equal weight. Your method is unclear and unnecessary. For example, how can your calculations assign 40% of the weight to Kellog, the food company? And why do you accept this? Similar issue when you accept 76% of your control to be Shell, an oil company.

Just selecting the 188 firms that are “similar” to BP and assigning equal weight would be enough. If you want to use market value weights, that is also ok. But using your arbitrary weighting mechanism doesn’t look right. In fact, you could even use a broad index as benchmark and that would also work. Personally, I would remove all the oil and gas firms from the 188 firms you matched to BP. I also suggest you study an industry index, to test for a possible contagion effect and as a second benchmark for BP.

Thank you for the appendix. The list of firms and their weights confirmed my suspicion on the methodology. If you follow my suggestions about the formation of portfolios, you won’t need to include it in the final version of the paper.

Table 2 predictor balance is not necessary. What is normally reported in finance studies is the simple (non-normalized) averages of the variables used to match the firm under study. Pre and Post averages can be included.

Figure 5 Total returns of BP vs synthetic control

Don’t call it synthetic control unit when you are analyzing stocks. Common practice in finance is to form/use control portfolios. Why is the starting point Jul 2017? You should make March 2010 your month 0 on any of your charts (figure 6, 7, etc). Chart looks good, but it needs label on the Y axis and change labels: BP instead of treated unit and control portfolio instead of “synthetic control unit”; and make March 2010 equals 100. Probably helpful if you can use the same colors as figure 1. BTW, try to use markers in addition to colors so color blind people can identify which one is BP and which one is the control.

Figure 6, table 3 and the robustness test shown in rows 362-393 unnecessary. Please remove them. There is no reason to test the soundness of the portfolio.

Figure 7 Doesn’t make sense to plot expected and realized. Try just plotting abnormal returns (the difference of the 2). Personally, I would plot the absolute value of the abnormal return or the square of the abnormal return. That way you can see if volatility went up after the event and when volatility goes back to the pre-event levels

Table 4. The regression implied in Table 4 is unclear. Is Y monthly abnormal returns? For explanatory variables, did you use 2 dummies just separating the first 2 years and then the last 5 years? You don’t need a regression for that!. Just t-tests would suffice and would make it clear what is the Pre-event average (constant). My guess is that the -1.458 is the monthly average from Apr 2010 to Mar 2012. However, in another table you say that you start measuring returns May 2010. Why? If the explosion occurred Apr 20, 2010, then 3/31/2010 is the last monthly price pre-event and 4/30/2010 is the first monthly price post event. Obviously, the stock return for Apr 2010 includes the initial reaction to the tragedy. So the return for that month can’t be ignored; it must be included as part of the Post event sample.

Figure 8 Good chart but March 2010 must be the starting point, not Jul 2017. I also suggest using markers so it’s easy to distinguish companies for color blind people.

Figure 9 Total returns. What do you mean total returns? Why do they start at 100? Are they just cumulative unadjusted returns? Starting point must be March 2010. I also suggest using markers so it’s easy to distinguish companies for color blind people. Should also include the industry control portfolio

Table 5 RMSPE ratios for stocks are hard to interpret. The Pre/post ratios for BP are 15, 23 and 87 with expected value of 1 and you still find it insignificant? The calculation of p-value using firm’s rank lacks details and why wasn’t that method used for reputation analysis (in addition to figure 3)?

Including results for other companies is good but show average abnormal returns, not RMSPE ratios. You should also study standard deviation of abnormal returns and include it in table if you find something interesting.

Reviewer #3: Thank you very much for your revision of the paper. I think you have done an excellent job there, and the robustness checks and alternative specifications you provide really make the paper stronger.

I don’t have anything of substance to add.

Just one minor comment: I think you should check the paper for writing and grammatical errors. There are few of them, starting with the first sentence of the Abstract.

The Abstract would also gain by being streamlined. There are repetitions there that could be avoided.

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PLoS One. 2022 Jun 15;17(6):e0268743. doi: 10.1371/journal.pone.0268743.r004

Author response to Decision Letter 1


29 Apr 2022

Rebuttal Memo

Penalties for industrial accidents: The impact of the Deepwater Horizon accident on BP’s reputation and stock market returns

(PONE-D-21-16006R1)

Dear Reviewers:

Thank you for your comments on our manuscript. We enclose a memo detailing your suggestions (in italics) and outlining how we address them in the revised manuscript.

Regards,

Authors

Reviewer #1

1. Thanks for your great work! You addressed my concern and appreciate your efforts. One last thing. BP's stock prices indeed dropped and suffered at least for a month in the wake of the crisis. If you look at the BP's SP it was $59 on Apr 16, 2010 and dropped to $28 in June. Just two months, but it is clearly true that the SP dropped A LOT. My sense is you should be a little more careful when you argue that the SP was not influenced by the spill; it was affected although in a very short period of time. In the mid- long-term, the SP was recovered from the crisis. So please modify your argument in a more reasonable way. The reputation was damaged, but the SP was not at least in the mid- or long-term "although it had suffered for a very short period time". Please add this one in your abstract. In your current abstract you said "Yet, in terms of financial market returns, we do not find a decline in the stock market returns either in the short term (1-2 years) or the long term (2-7 years)" some people may think short-term should be 1 month, not 1 year. So to avoid any controversy please add that the SP dropped for a month but it was quickly recovered. Thanks.

Response

Excellent point. We have modified the abstract to the following: “Yet, in terms of financial market returns, though the stock price dropped drastically in the first two months, we do not find a statistically significant decline in the stock market returns either in the mid-term (1-2 years) or the long term (2-7 years).”

Reviewer #3

1. Thank you very much for your revision of the paper. I think you have done an excellent job there, and the robustness checks and alternative specifications you provide really make the paper stronger. I don’t have anything of substance to add. Just one minor comment: I think you should check the paper for writing and grammatical errors. There are few of them, starting with the first sentence of the Abstract.

The Abstract would also gain by being streamlined. There are repetitions there that could be avoided.

Response

Thank you. We have checked the paper for errors and streamlined the abstract.

Reviewer #2

1. I appreciate the effort done trying to address the methodology issues mentioned in my first review. I disagree with your interpretation/conclusion there is no evidence that the spill diminished BP stock returns. Your discussion dismisses the fact that -1.458 x 12 = a loss of 17.5% per year and investors did suffer a cumulative loss of about 35% in the 2 years following the accident. That may be statistically insignificant yet is economically significant.

Response

We added the following sentences to the manuscript: “Though the decline in stock returns in the wake of the disaster is not statistically significant, we recognize that some might consider it to be economically significant (about 27% decline over a two-year period).”

2. Your analysis fails to show the relative underperformance of BP compared to other firms in the oil & gas industry. While such underperformance may not be statistically significant, the paper seems to ignore economically important drops in BP value, especially when compared to its peers.

Response

Please see the response above. To acknowledge this, we also added the following sentences: “The initial drop however is not recovered over time, and still signals an economically important drop in BP’s value.” And “It also shows how BP’s performance may have dropped vis-à-vis other oil and gas firms, despite the effect of the oil spill not being statistically significant.”

3. I still have several concerns regarding the methodologies used in this paper, as outlined below. I recommend authors refer to Kothari, S.P., and Jerold B. Warner, 2004, "Econometrics of Event Studies” and use long term event study methodology. You will probably need a colleague in the finance department to review the manuscript and help you with this paper.

Response

Thank you for this useful reference. Though we believe the synthetic control method is an improvement on existing event studies, we still use the suggested event studies as a robustness check. More specifically, to address the concerns, we also added robustness checks, using an event study with CAPM to compare BP to the S&P500 minus oil and gas firms and one with only oil and gas firms. Our key results hold.

4. Comments about change of focus

You completely changed your emphasis to stock market returns (title and

most discussions) but you probably overdid it. Some examples:

• Rows 103-104 say ”stock market returns provide a measure of the expected future earnings of the firm”. Previously you had stock prices. Stock prices do that, but not stock returns.

• Row 105 says “penalty on stock market returns”. This doesn’t sound right.

• Row 303 “influence stock market returns, especially its future earnings.” Should only say “influence future stock returns”

Please review the usage of “stock price”, “stock returns” and try to make clarifications as needed. Not all instances must be “returns”

Response

Thank you; we have made changes accordingly.

5. Reputation study

Getting a synthetic control is a good idea. However, assigning 76% weight on another oil and gas company raises concerns about the assumptions made and the soundness of the weighting mechanism.

Allowing for the possibility of a contagion effect, you should not be using any oil and gas firms in the synthetic control. That would be a “clean” control. That would remove the issue of using too much of an oil and gas company in your market control. You already remove oil and gas firms when you create synthetic controls for other oil and gas firms (rows 267-268), why not do it for the main subject of study, BP?

Response

We do it for the other oil and gas firms so we can specifically check for spillover effects. In the main study we don’t do it, because there is a necessary tradeoff here; restricting the set of possible components for the synthetic control may help address concerns about contagion but will also reduce the fit of the model. In the appendix of the revised manuscript, we have added the figure with the synthetic control without oil and gas companies and one with only oil and gas companies. Excluding oil and gas firms from the synthetic control yields essentially the same result as our original model. We have noted this in the revised paper and included the results in the Appendix.

6. In addition to the clean market control, you should create another synthetic

with oil and gas firms/brands without BP. That would be your industry control, which would bring these changes:

1. Figure 1 would have a third line (the industry) and contagion can be expected immediately after the explosion. In fact, one can argue that the blue line has the lowest reputation score post-accident right after the explosion, suggesting a minor contagion effect.

2. Figure 2 would have two lines, one for the industry control and one for BP. This chart would show when the industry recovers from any possible contagion.

Figures 3 & 4 makes sense for oil and gas companies/brands. I suggest you remove figure 3.

Response

- Following your suggestion, we added a graph with the synthetic control based on all firms in the data set, all firms minus integrated oil and gas companies and only oil and gas companies to the appendix, both for the reputation analysis and the stock market analysis. We did the same for the CAPM analysis but plotted the lines in different graphs for clarity.

We hope that by showing similar results when using your suggested methods, we have responded to your input.

Figure 3 is necessary to address concerns that the differences apparent in Figures 1 and 2 are due to simultaneous changes in the reputations of the components of BP’s synthetic control. We acknowledge that contagion effects are an important concern, but we believe that issue has been adequately addressed in the analysis summarized in Figure 4.

7. Stock market study

There is no need to use “the same synthetic control approach described above” (row 322) on returns. In fact, most of the tests used and the charts/tables presented are uncommon in the finance literature. I strongly recommend authors refer to Kothari, S.P., and Jerold B. Warner, 2004, "Econometrics of Event Studies” and use long term event study methodology.

If you really want to adapt novel methodologies to stock prices/returns, please find literature that has done it before and include it in reference list. If unavailable, state that you are trying something new, as that may be one of the contributions of the paper. Unfortunately, in my opinion, it is not working.

Response

We added the following text to explain the synthetic control method vis-à-vis the event study method: “With this we follow others, like Acemoglu et al (31), who have applied the synthetic control method to model the counterfactual in the fields of economics and finance (26,31–37). The synthetic control method is a novel approach in finance that addresses some shortcomings of the more traditional event study method (31,37). The synthetic control method is a variation on other event study methods widely used in finance. The main difference is that the synthetic control method applies specific weights for each unit based on similarities in variables that are driving the outcome variable of interest, making sure the counterfactual is as similar as possible to the treated unit (31). This data-driven creation of a counterfactual is thus a more nuanced approach, than simply using all other companies in the market as a counterfactual. An added advantage is that for making causal inference, weaker assumptions are needed than in the traditional event study methods (38).”

8. I am including suggestions below for the figures/tables/methods in the section of Stock Market returns. Hope they help.

In finance we use two main methods to weight stocks into portfolios: market value weight or equal weight. Your method is unclear and unnecessary. For example, how can your calculations assign 40% of the weight to Kellog, the food company? And why do you accept this? Similar issue when you accept 76% of your control to be Shell, an oil company.

Response

Thank you. Just to be clear, the 40% weight for Kellog and 76% weight for Shell are for the reputation analysis. The synthetic control of stock market returns is based on 187 firms in our dataset, each taking up an almost equal share as you can see in the appendix. To be safe we run the same analysis using CAPM where we compare BP to the overall S&P500 (and S&P500 minus oil and gas and only oil and gas companies in the appendix).

In the main analysis, we are following the well-established synthetic control method (see Abadie A, Diamond A, Hainmueller J. “Comparative politics and the synthetic control method”, American Journal of Political Science. 2015; 59(2):495–510 with 4463 citations), which chooses weights for companies based on similarities in the underlying variables that drive the estimated variable. The selection of components and weight is thus based on similarity. Importantly, we make no assumptions about which brands should be better comparators for BP. We have addressed the concerns about spillovers in our robustness checks.

9. Just selecting the 188 firms that are “similar” to BP and assigning equal

weight would be enough. If you want to use market value weights, that is also ok. But using your arbitrary weighting mechanism doesn’t look right. In fact, you could even use a broad index as benchmark and that would also work. Personally, I would remove all the oil and gas firms from the 188 firms you matched to BP. I also suggest you study an industry index, to test for a possible contagion effect and as a second benchmark for BP.

Response

Thank you: this is what we do in the CAPM analysis. We compare BP to the S&P 500. In the appendix, we now provide an analysis comparing BP to the rest of the S&P500 firms minus oil and gas companies and BP versus the oil and gas industry. We also assess the abnormal returns compared to the rest of the market.

10. Thank you for the appendix. The list of firms and their weights confirmed my

suspicion on the methodology. If you follow my suggestions about the formation of portfolios, you won’t need to include it in the final version of the paper.

Response

Since the synthetic control approach is central to our paper, we are retaining the information on the list of firms and the weights.

11. Table 2 predictor balance is not necessary. What is normally reported in

finance studies is the simple (non-normalized) averages of the variables used to match the firm under study. Pre and Post averages can be included.

Response

Following the literature, including the predictor balance provides a good sense of how well the counterfactual matches BP on the underlying characteristics. This is quite similar to what is normally reported in finance studies – as you describe. Hence, we retained it in the paper.

12. Figure 5 Total returns of BP vs synthetic control

Don’t call it synthetic control unit when you are analyzing stocks. Common practice in finance is to form/use control portfolios.

Response

The synthetic control method is comparable to a control portfolio. The companies selected for the control portfolio, when using the synthetic control method, are those that are most similar to BP in the underlying characteristics that drive the stock market returns. We have noted this point in the revised paper.

13. Why is the starting point Jul 2017? You should make March 2010 your

month on any of your charts (figure 6, 7, etc).

Response

February 2007 is the starting point of our data. We have revised the paper accordingly.

14. Chart looks good, but it needs label on the Y axis and change labels: BP

instead of treated unit and control portfolio instead of “synthetic control unit”; and make March 2010 equals 100. Probably helpful if you can use the same colors as figure 1. BTW, try to use markers in addition to colors so color blind people can identify which one is BP and which one is the control.

Response

Done.

15. Figure 6, table 3 and the robustness test shown in rows 362-393 unnecessary. Please remove them. There is no reason to test the soundness of the portfolio.

Response

These robustness checks are standard in the synthetic control literature. Here we check how likely it is to receive this discrepancy between BP and the synthetic control, whether this could have occurred if in fact the oil spill had no impact on the stock price. This is akin to the p-value. However, if the editor advises, we can move them to the appendix.

16. Figure 7 Doesn’t make sense to plot expected and realized. Try just plotting

abnormal returns (the difference of the 2). Personally, I would plot the absolute value of the abnormal return or the square of the abnormal return. That way you can see if volatility went up after the event and when volatility goes back to the pre-event levels.

Response

Done, we now added a plot of BP’s abnormal returns.

17. Table 4. The regression implied in Table 4 is unclear. Is Y monthly abnormal

returns? For explanatory variables, did you use 2 dummies just separating the first 2 years and then the last 5 years? You don’t need a regression for that!. Just t-tests would suffice and would make it clear what is the Pre-event average (constant). My guess is that the -1.458 is the monthly average from Apr 2010 to Mar 2012. However, in another table you say that you start measuring returns May 2010. Why? If the explosion occurred Apr 20, 2010, then 3/31/2010 is the last monthly price pre-event and 4/30/2010 is the first monthly price post event. Obviously, the stock return for Apr 2010 includes the initial reaction to the tragedy. So the return for that month can’t be ignored; it must be included as part of the Post event sample.

Response

We measure from May 2010 as we have monthly data from the 1st of each month. So the 1st of April is the last observation before the spill and the 1st of May is the first observation after the oil spill.

18. Figure 8 Good chart but March 2010 must be the starting point, not Jul 2017.

I also suggest using markers so it’s easy to distinguish companies for color blind people.

Response

We have updated Figure 8.

19. Figure 9 Total returns. What do you mean total returns?

Response

We mean stock market returns.

20. Why do they start at 100?

Response

Our objective is to create a baseline and make the price fluctuations comparable with one another.

21. Should also include the industry control portfolio.

Response

We provide this in the appendix.

22. Table 5 RMSPE ratios for stocks are hard to interpret. The Pre/post ratios

for BP are 15, 23 and 87 with expected value of 1 and you still find it insignificant? The calculation of p-value using firm’s rank lacks details and why wasn’t that method used for reputation analysis (in addition to figure 3)?

Response

We explained the calculation of the p-value: “Cunningham (2021) suggests computing the Post/Pre RMSPE ratio for the treated unit and each component of the synthetic control and seeing where the treated unit ranks in that distribution (39). Table 5 shows BP’s ranking in the distribution of RMSPE ratios. We calculated this ranking for our full sample period, the two years following the disaster (“Short-term”), and the period two to ten years after the disaster (“Long-term”)” “The p-value is simply the rank divided by the total number of firms, which is 188 in BP’s case.” Figure 3 is a visual representation of the RMSPE ratios, showing that BP’s ratio stands out vis-à-vis the other oil and gas firms, making a table with RMSPE ratios and p-values redundant. Given that the financial synthetic control consists out of many more component firms, we use p-values to give an impression of the relative size of RMSPE-ratios, instead of a figure.

23. Including results for other companies is good but show average abnormal

returns, not RMSPE ratios. You should also study standard deviation of abnormal returns and include it in table if you find something interesting.

Response

RMSPE ratios are standard in the synthetic control literature and are used here to determine the statistical significance of the results we observed. The cumulative abnormal returns of other oil and gas companies are captured in figure 9. The standard deviation of abnormal returns is interesting and important, but not directly related to our research question.

Attachment

Submitted filename: Response memo.docx

Decision Letter 2

J E Trinidad Segovia

9 May 2022

Penalties for industrial accidents: 

The impact of the Deepwater Horizon Accident on BP’s reputation and stock market returns

PONE-D-21-16006R2

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Acceptance letter

J E Trinidad Segovia

23 May 2022

PONE-D-21-16006R2

Penalties for industrial accidents: The impact of the Deepwater Horizon accident on BP’s reputation and stock market returns

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