{"id":6238,"date":"2025-08-27T09:54:56","date_gmt":"2025-08-27T07:54:56","guid":{"rendered":"https:\/\/eaa-online.org\/arc\/?p=6238"},"modified":"2025-08-28T09:35:31","modified_gmt":"2025-08-28T07:35:31","slug":"esrs-back-to-ball-brown-1968","status":"publish","type":"post","link":"https:\/\/eaa-online.org\/arc\/blog\/2025\/08\/27\/esrs-back-to-ball-brown-1968\/","title":{"rendered":"ESRS: Back to Ball & Brown (1968)?"},"content":{"rendered":"

In the current debate on the European Sustainability Reporting Standards (ESRS), one theme stands out as both surprising and irritating: Few \u2014 with <\/span>Christine Lagarde<\/span><\/a> or <\/span>PRI<\/span><\/a> among the notable exceptions \u2014 seem seriously interested in understanding whether the hundreds of widely contested ESRS data points are actually useful to stakeholders.<\/span><\/p>\n

The conversation is dominated by confident claims: \u201cMost of these data points are useless.\u201d \u201cNobody will ever use them.\u201d \u201cIt\u2019s disclosure overload.\u201d These statements are made with remarkable certainty \u2014 yet, as far as I can tell, with little systematic empirical evidence, apart from anecdotal experiences of few ESG-related questions being posed in investor calls or at annual shareholders\u2019 meetings. <\/span><\/p>\n

At the same time, preparers and users visibly disagree: Preparers tend to emphasize the cost and irrelevance of many ESRS disclosures. In contrast, at least some users see them as potentially informative. The gap between these perspectives is striking \u2014 and largely unexplored.<\/span><\/p>\n

This situation strongly recalls <\/span>Ball and Brown\u2019s legendary 1968 study<\/span><\/a>. For decades before them, accounting research had been normative, <\/span>a-priori<\/span><\/i> theorizing about how earnings <\/span>should<\/span><\/i> be calculated in order to matter. Ball and Brown, then Australian-born twenty-something Ph.D. students at the University of Chicago, were exasperated by the non-existent role for empirical evidence. In their <\/span>2014 retrospective<\/span><\/a>, they wrote: \u201cAn analogy [\u2026] is given by motor industry R&D. It was as if academics were saying \u2018[W]e have not collected data on whether or how consumers use cars as they currently are designed, but we know a priori that these cars are useless and all cars henceforth should be redesigned as 16-wheel trucks.\u2019\u201d<\/span><\/p>\n

Consequently, they decided to break with that tradition. Instead of speculating, they asked what investors actually did with accounting numbers. Their evidence showed that earnings were informative to markets \u2014 not because they were timely or novel, but because they reflected facts that investors considered relevant for valuing companies. The real breakthrough was methodological: They had brought empirics into a field dominated by <\/span>a-priori<\/span><\/i> reasoning.<\/span><\/p>\n

 <\/p>\n

An alternative story: What if the contested ESRS data points are actually useful?<\/b><\/p>\n

Let\u2019s challenge the dominant narrative that most ESRS data is a waste of resources. Suppose serious user analysis were to reveal that many of the contested ESRS data points actually <\/span>are<\/span><\/i> useful \u2014 at least to some stakeholder groups (let alone that many of those that may not be useful today may well become useful in the future \u2014 when disclosure supply creates its demand). Suppose further that some of these data points expose uncomfortable truths for companies: emissions hot spots, workforce issues, supply-chain dependencies, or governance weaknesses. In such a world, at least some firms would have strong incentives to downplay the usefulness of this information.<\/span><\/p>\n

What observable implications would we expect in that scenario?<\/span><\/p>\n