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Academics Must Do Good Work To Be Relevant

Sustainability reporting is a major, and contentious, topic. I wholeheartedly encourage academics to engage in topics like this — they matter. In theory, such engagement makes academic work extremely relevant. Consultants produce reports but sometimes these are over-optimistic, biased, or just plain wrong. This means academics can have an important place in improving the quality of discourse. Sadly, some bad habits in academic work cause problems that mean it doesn’t really matter how important or timely the topic is, the work doesn’t help anyone. My point is that academics must do good work to be relevant.

Voluntary Sustainability Reporting And Firm Value

A recent marketing paper looked at the impact of voluntary sustainability reporting on firm value. This area of investigation clearly matters. In the US, ESG (Environmental, Social, and Governance) reporting is a hot topic. There are people on all sides firmly committed to their positions who are looking for something to bolster their opinions. When producing something that speaks to this topic it is important to avoid bad academic habits or else one could end up impacting a contentious public debate inappropriately. This is the risk that Wesley Friske and colleagues take with their 2023 paper on the impact of voluntary sustainability reporting on firm value. They connect sustainability reporting measures to a dependent variable that isn’t used by managers because the metric isn’t what the authors say it is.

Tobin’s Q And Firm Value

Friske and colleagues use Tobin’s Q as a proxy for firm value in their 2023 paper. Why? Academics often use the “because other people did it” reason. It is essentially the same argument you will see used by kindergarteners when asked why they are sticking their fingers in a socket.

You may hope for more than social proof when academics argue for something, but academic papers — to focus on the “new bits” — often skim over what has been said before. This is a problem when the earlier discussions were flimsy or simply incorrect. A 2017 paper said Tobin’s Q was widely used as a performance measure and that is cited by the 2023 paper I am discussing here. Our paper, which said that using Tobin’s Q as a performance metric was nonsense, came out in 2018. The authors of the 2023 paper probably missed our paper as they don’t seek to rebut it, or even mention it. The challenge is that in our paper we outlined in great detail why the prior thinking they repeat is simply and obviously wrong.

As an aside, I would note that we got an initial rejection on the 2018 paper from one reviewer who said that marketing academics would never make the mistake of using Tobin’s Q as a firm performance metric and so our paper was unnecessary. That always struck me as ironic because Tobin’s Q was widely used as a firm performance metric in marketing in the 2010s. Since we published our paper I have seen some (slow) progress in rooting out Tobin’s Q as a performance metric. (Indeed, some Tobin’s Q proponents are now seeking to replace it with Total Q. See here, the summary is that Total Q is better but not by much). The Friske paper is more traditional — to be fair these projects take many years so they may have started in 2017 or before — it simply uses Tobin’s Q.

If you don’t know much about Tobin’s Q, and don’t want to bother reading my work, why should you believe me that their use doesn’t make sense? Well, its supporters say it is a magical metric that captures the future based on a dash of financial market prices and a dollop of accounting data. If you believe that argument I have some very bad news for you about the Easter Bunny.

Dependent Variables Matter

A problem I have with many marketing papers is how they treat the dependent variable (DV). The DV is typically what we are most interested in. Here the authors want a dependent variable that represents firm value, i.e., how much the firm is worth. Naively, you might expect that explaining the dependent variable would be the central element of academic papers. Getting the DV right seems so fundamental if you don’t have the right dependent variable why bother starting the investigation? Yet, marketing academics are largely taught to write papers that hide the dependent variable in the middle of the paper.

Even worse the justification given for the DV used is often minimal, as it is here with Friske and his colleague’s paper. They say Tobin’s Q is a metric that captures long-run performance justifying this with a citation but, like is common, there is no explanation of their logic only a citation to an earlier (sadly incorrect) argument.

Market-Based Measure?

They then say that Tobin’s Q is a market-based measure of firm value. Of course, there are pure market-based measures which this justification might have worked for but they didn’t use those. Instead, they chose a metric that is a hybrid of market and accounting data. You can see this easily in the formula they give. Notice DEBT and AT in the formula below, these are both from accounting, not market data. (“DEBT = (current liabilities – current assets) + (book value of inventories)+ (book value of long term debt), and AT = book value of total assets”, page 381). Their justification is like a company trying to get credit for an all-female board, even though half of the board are men.

The Formula They Used For Tobin’s q

Justifying Statements

The problem with the final justification they give is connected to the second. Again to be fair they do provide citations. But the problem with citations to earlier work without sufficient explanation is the whole edifice collapses if the past work made incorrect statements, and here the past work was demonstrably wrong. As clearly shown above Tobin’s Q relies on accounting data yet their final justification is.

Third, Tobin’s q is not as sensitive to accounting conventions as other popular measures of firm value, and thus it is easier to compare firms across industries (Lenz et al., 2017; Nekhili et al., 2017).

Friske, Hoelscher, and Nikolov (2023), page 381

Tobin’s Q is extremely sensitive to accounting conventions. After all, it is essentially driven by accounting conventions such as what can be classed as part of AT, total assets, on accounting statements. That is the core problem with Tobin’s Q that we outlined in our 2018 paper. I guess we don’t know what other measures they were comparing Tobin’s Q to, maybe some are indeed even worse, but Tobin’s Q is really terrible. In summary, their justifications for using Tobin’s Q are far from sufficient even accepting they simply overlooked our paper. (Missing a relevant paper is an easy mistake to make, that we all do at some point or another). Citing past work and recycling prior arguments is bad academic practice when the past work was wrong and you haven’t dug into why the prior paper said what it said.

Academics Must Do Good Work To Be Relevant

The authors conclude that voluntary sustainability reporting had a negative impact on firm value before 2018 but this has changed more recently. But honestly, by this point who cares? If the proxy for firm value used isn’t a meaningful proxy for firm value, it really doesn’t matter what is associated with this proxy. The results can’t speak to the questions around firm value that the paper is aiming to address.

I am all for relevance and work on the impact of sustainability reporting could be very important. Yet, a paper that links sustainability data to an incorrect dependent variable and splices in a twist of signaling theory isn’t doing much for the world. Academics must do good work to be relevant.

For more on Tobin’s Q see here, and Total Q see here.

Read: Wesley Friske, Seth A. Hoelscher and Atanas Nik Nikolov (2023) The impact of voluntary sustainability reporting on firm value: Insights from signaling theory. Journal of the Academy of Marketing Science 51(2): 372–392.

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