Data and Market Power
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Firms using data to forecast future demand leads to increased markups, according to a new model by @JanEeckhout. Data-rich firms invest more, reduce costs, and shift production towards high-demand, high-markup goods, boosting economic efficiency.
Might firms' use of data create market power? To explore this hypothesis, we craft a model in which economies of scale in data induce a data-rich firm to invest in producing at a lower marginal cost and larger scale. Just like managers are taught to do in MBA programs, the firm decision makers in our model make investment decisions, taking risk into account. It is this effective risk aversion that causes firms to invest more when they have more data. Data is a tool to reduce risk. With less risk from random demand, a larger investment becomes optimal. Thus high-data firms do invest more, grow larger and exert more impact on prices But this simple story delivered some unexpected additional effects. We found that when managers price risk, markups reflect both market power and a compensation for risk. If data reduces risk by making uncertain outcomes more predictable, then is also reduces the risk premium and the markup. At the same time, firms react to data about demand by shifting their production to high-demand goods. These are high-markup goods. So data changes the composition of production. This composition effect leads firms to shift production toward high markup goods, which raises markups. The tug-of-war between risk reduction and the composition effects induced by data plays out different for product, firm and industry markups. A model designed to explore the logic of data and large firms turned out to explain why econometricians got different answers about what was happening to markups over time when they measured at different levels of aggregation. Out model suggests an new interpretation of existing facts. Constant product markups and rising firm and industry markups are not competing facts. They are consistent with an economy where firms are getting better and better at forecasting future demand.
Jan Eeckhout and Laura Veldkamp, "Data and Market Power," National Bureau Of Economic Research, May 2022, https://www.nber.org/papers/w30022
Primary Results: How Data Affects Markups
“…Figures 1 and 2 illustrate how the risk reduction and investment forces compete. When firminvestments greatly decrease marginal cost (low cc), then the cost channel is dominant and more data primarily increases investment, lowers costs and raises markups (Figure 1). When the cost reduction investment is inefficient (high cc), then data still prompts more investment, but this has little effect on marginal cost. Instead, the dominant force is risk reduction. Similarly, if the price of risk is high, risk reduction is also the dominant force. A data-rich firm faces less cost from taking on more risk with a large production plan. By producing more, data-rich firms drive prices down and lower markups (Figure 2)…”
“…Despite the fact that markups increase in one case and decrease in the other, both results paint a rosy picture of the role of data. Even when data increases markups, it decreases price. Markups only rise because the firm could produce at a lower cost. Both results point to the efficiency enhancing and welfare-boosting effects of data….”
“…Data Amplifies Market Power Costs. Figure 3 decomposes the welfare loss into risk aversionand market power. The loss due to market power is much higher on the right, where data is abundant…”




















Steve Comment: had a few questions about your “Profit Puzzle” paper. I’m sitting here looking at Figure 14 and find the results really surprising. Could the divergence btw private and public firm profits (given your using return to capital) largely be a function of the lower capital the intensity of private service firms? I’m shocked at the public firm series. I would have thought that would have had an upward slope given US firms’ international profits. Are taxes skewing this (Apple booking stuff in Ireland, etc)?
James Traina Comment: Thank you for reading! Capital intensity and tax differences are good hypotheses here. For the former, could you expand on what you have in mind? e.g. Are you thinking about physical vs financial capital differences? For the latter, we show in the “Solving the Puzzle” section that public vs aggregate tax rate differences are there, but they’re small and actually pointing the other way — they’re higher for public firms. That also relates to the rise of S-corps, which folks have attributed to tax advantages. The international dimension is much harder because we don’t have good data on it. Basically, there’s still a mismatch when we make our comparisons because “domestic” in Compustat means US incorporation, while “domestic” in the IMAs means US operation. It’s hard to say which direction this would bias our results. One thing that I find helpful to think about, but we didn’t fit into the paper: You can find the same kinds of results in *all* the standard profits / capital measures, e.g. ROA, ROIC, etc. So any explanation would have to work for all these measures jointly.
Steve Comment: Yes I have in mind firms of engineers, architects, or lawyers that have little physical or financial capital, but a lot of human capital. Could those firms be driving the high ROI of private firms relative to public? I’m genuinely curious about this, because it feels like a failure of economic efficiency to have private firms yielding so much more than public firms.
James Traina Comment: Ah yes, that’s possible! You’d need an accounting mismeasurement, though, where it doesn’t show up in labor income. You might be interested in this paper: https://bfi.uchicago.edu/insight/research-summary/the-rise-of-pass-throughs-and-the-decline-of-the-labor-share/ Public firms’ returns on the book value of assets are down ~ 50% from 1980 and private firms’ returns have doubled. @EconTraina @ASollaci @CarterDavisFin (135)