Running a factory involves a constant balancing act. Too much inventory ties up cash and warehouse space. Too little means missed sales and frustrated customers. The executives who oversee these decisions bring their own personalities to the job, and those personalities can leave traces in the accounting records.
A new analysis published in Applied Economics Letters looks at what happens to a company’s inventory patterns when its chief executive tends toward overconfidence. The finding: firms led by overconfident CEOs show more erratic inventory levels, and the pattern is more pronounced at companies with weaker positions in their industries.
The question behind the research
Researchers have spent years documenting how overconfident CEOs behave in the realm of corporate finance. They tend to overinvest, favor internal financing, and pay too much for acquisitions. What has received less attention is whether that same behavioral tendency reaches into daily operations, the sort of decisions about how much to produce and how much stock to keep on hand.
Jaeseog Na of Duksung Women’s University in Seoul examined this question. The starting hypothesis was straightforward: executives who overestimate their ability to predict demand and control processes may frequently revise production plans, generating adjustment costs and swings in inventory. That instability itself is a form of operational risk, one that can ripple through supply chains and eat into profitability.
Measuring confidence and volatility
Na drew on data covering U.S. manufacturing firms from 1992 through 2020, pulling financial information from Compustat and executive data from Execucomp. The final sample included 16,363 firm-year observations across 1,407 firms.
Measuring something as slippery as “overconfidence” required a proxy. Na used a widely applied method known as Holder 67, which infers optimism from how CEOs handle their stock options. The logic is that a CEO who hangs onto deeply in-the-money options longer than a rational actor would is signaling belief that the company’s stock will keep climbing. Specifically, executives who held options where the ratio of the option’s intrinsic value to its exercise price exceeded 0.67, in at least two years of their tenure, were classified as overconfident.
Inventory volatility was calculated using quarterly inventory figures, adjusted for seasonality by comparing each quarter to a rolling four-quarter average. Market share was defined as a firm’s sales divided by total sales in its industry, using two-digit industry codes.
The analysis controlled for a range of firm characteristics that might independently affect inventory swings: capital expenditure levels, cash flow, return on assets, firm size, working capital efficiency, and abnormal inventory adjustments. Industry and year fixed effects absorbed broader trends and sector differences.
What the numbers showed
Overconfident CEOs were associated with statistically higher inventory volatility. In the baseline model, the presence of an overconfident CEO was linked to a measurable uptick in the swing of inventory levels quarter to quarter.
The second finding involved competitive positioning. When Na added an interaction between overconfidence and market share, the coefficient came out negative and significant. Translated: the effect of overconfidence on inventory swings was stronger at firms with smaller market shares. At companies commanding larger shares of their industry, the same behavioral tendency in the corner office produced a milder effect.
Na interprets this pattern through the lens of behavioral agency theory. Firms in weaker competitive positions face more pressure to change course and often have fewer structural constraints on the CEO. Both conditions give an overconfident executive more room to act on hunches about demand or production, which can translate into more frequent adjustments and larger inventory swings.
Addressing the chicken-and-egg problem
A recurring challenge in this kind of research is that the two variables of interest might be shaped by unobserved factors. Perhaps something about a firm’s environment attracts overconfident leaders and independently produces volatile inventory.
Na attempted to address this in two ways. The first was an instrumental variable approach using whether a CEO’s total compensation exceeded the industry-year average as a proxy signal for overconfidence. Prior research has linked outsized pay relative to peers with hubristic tendencies, while pay itself is set through board negotiations that shouldn’t directly determine inventory patterns. The second approach used propensity score matching, comparing firms with overconfident CEOs to otherwise similar firms without them. Both approaches produced results consistent with the main analysis.
Na acknowledges that these methods cannot completely eliminate the possibility that overconfidence and inventory volatility are jointly determined by something unmeasured. The findings should be read as a strong association rather than a definitive causal claim.
Practical takeaways
For firms, the results suggest that behavioral traits at the top of the organization can leak into operational metrics in ways that boards and supply chain managers might otherwise miss. Na suggests that companies could benefit from more structured forecasting processes, stronger coordination across departments, and governance mechanisms designed to check bias-driven adjustments to operational plans.
The findings also point to a heightened vulnerability for smaller players in an industry. When a firm is chasing bigger rivals, an overconfident leader appears more likely to translate that ambition into whipsawing production and inventory decisions. Boards at such companies may want to pay closer attention to how much operational discretion sits with a single executive.
One caveat worth keeping in mind: the sample ends in 2020 and does not capture the pandemic-era supply chain disruptions. The study period does include the 2008 financial crisis, so it isn’t limited to calm economic weather, but readers should be cautious about extrapolating directly to the post-2020 environment where supply chain volatility became a defining business challenge.
