Evidence of 'Greedflation'? - Nominal News

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Evidence of 'Greedflation'?<br>Recent development and research suggest ‘greedflation’ may come in different forms.

Nominal News<br>Jul 14, 2026

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‘Greedflation’ is a contentious topic that rose in popularity during the inflation surge of the Covid pandemic. Many economics commentators have criticized the idea that ‘greed’ mattered for inflation during the Covid pandemic. But recent news on price collusion between egg producers, reinvigorated the debate around ‘greedflation’ as an important driver of recent inflation. Although collusion is an easy example of what many perceive as ‘greedflation’, recent research by two Federal Reserve economists suggests that there may be more to ‘greedflation’ than previously thought.

Photo by Giorgio Trovato on Unsplash<br>Defining ‘Greedflation’

One problem with the ‘greedflation’ debate is that the term itself is undefined.

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Many economics commentators interpret greedflation as inflation that is caused by firms’ ‘greediness’ and often somewhat sarcastically argue that ‘when prices fall, firms must have gotten less greedy’.<br>I am not a fan of this definition. Unlike economics commentators, who do not view ‘greedflation’ and firm power as related, the public outrage about ‘greedflation’, appears to be focused on that firms may have too much power in dictating prices and that current competition levels do not sufficiently rein their pricing power in. Investigating this issue is something economists should do and many are doing. Did pricing power go up? If so – what could have caused it? Have competition levels deteriorated? Are firms better able to extract consumers’ willingness to pay? Is collusion up?<br>All of the above are valid questions, which I would capture under the umbrella of the word ‘greedflation’. Baslandze and Fuchs (2026) (“BF ”) looked at one potential channel of pricing power – supply chain disruptions may have enabled firms to increase prices above their own increase in cost.<br>Covid Pandemic and Supply Chain

BF first built a model that focuses on two elements that may affect an importing firm’s decision on pricing their product – the cost of producing product and the likelihood of receiving the needed shipments to make the product.<br>A Simple Example – ‘Perfect’ World<br>To understand the intuition, let’s start off with a hypothetical ‘perfect’ world scenario of a basketball-selling firm that imports the basketballs. In this perfect world, the basketball firm always has a basketball available to sell if a customer wants to buy it. Under this scenario, the price the basketball firm would charge depends on the cost to import the basketball and how much people really want basketballs in comparison to other sports equipment (this is typically referred to as the ‘elasticity of substitution’). Both of these parameters – the cost and the ‘elasticity’ – are outside of the control of the basketball firm, so they set their price using these two external factors.<br>A Simple Example – Adding Shipping<br>Now, in a more realistic world, the firm would have storage costs to keep all the basketballs, and so the firm would have a limited stock of these basketballs. To replenish the stock of basketballs, the firm would rely on import shipments. If we assume that the firm sells 100 basketballs a day, and receives a shipment every month, the firm needs to receive 3,000 basketballs per shipment.<br>In normal times, since these shipments are predictable, the firm would de facto charge a similar ‘perfect world’ price, as in the example above.<br>A Simple Example – Shipping Delays<br>Suppose, however, all of a sudden shipments are delayed by 3 months. Now the firm is in danger of running out of stock, as it will sell its entire 3,000 basketball inventory in 1 month. In response to this risk, the firm may resort to increasing prices, in order to reduce demand for the basketball. Basically, the firm needs to now sell a third of the basketballs per day, or around 33 basketballs a day – and the only way it can make that happen is by raising the price. (I imagine that this behavior would often be called ‘greedy’ by the public).<br>A Simple Example – Adding Competitor Shipping Delays<br>BF alter the above model with another interesting element – how competitor shipping delays may influence the pricing. Suppose, there is another basketball seller in the market. Normally, the two basketball firms sell a combined 200 basketballs a day. Each firm also receives shipments in the exact same way – every month, 3,000 basketballs are delivered to each firm.<br>Now, just like in the above example, suppose your competitor gets hit by the 3 month shipping delay, but...