How much has market power increased in the United States in the last fifty years?  We document that from 1970 to 2020:

1. The aggregate markup has gone up from 1.10 to 1.23; that is, from 10% of price over marginal cost to 23%; and

2. Aggregate returns to scale have risen from 1.00 to 1.13 because of rising fixed costs and changes in technology.

We connect these indicators of aggregate market power to the profit share by showing that the aggregate profit share can be expressed in terms of the aggregate markup, aggregate returns to scale, and a sufficient statistic for production networks that captures double marginalization in the economy. 

We find that despite the rise in market power, the profit share in the United States has been constant at 18% of GDP because the increase in monopoly rents has been completely offset by rising fixed costs and changes in technology. Our empirical results have subtle implications for policymakers: overly aggressive enforcement of antitrust law could decrease firm dynamism and paradoxically lead to lower competition and higher market power.

Using a growth-accounting framework for open and distorted economies with input-output linkages, I document that the evolution of aggregate TFP in Spain has been less dismal than previously thought.  This is because distortions introduce a downward bias in traditional measures of Spanish TFP based on Solow's residual. An unbiased measure of TFP—Hall's residual— reveals that TFP in Spain started declining in 1995, not in 1988, and that it declined by 7, not 10, percentage points. 

To understand what is driving the decline of aggregate TFP, I decompose TFP into technical efficiency, domestic reallocation, and international trade.  I find that the decline in Spanish TFP is mostly driven by declines in technical efficiency and negative reallocation effects. International trade had a large, positive impact on TFP.

I show that despite declining TFP, welfare increased by 10 percentage points from 1995 to 2010. This is because Spanish households benefited from positive technological- and reallocation effects across the globe. Results for Italy can be found in the paper.

Health is typically imperfectly measured. How important is this imperfect observability to evaluate the costs of bad health? We estimate a dynamic, structural life-cycle model of savings and labor supply with health risk under two assumptions on the observability of health. The first one, which is prevalent in much of the literature, is that health is perfectly observable. The second one is that, while health is not observable, a battery of noisy measures of health is available to the researcher  (e.g., limitations with activities of daily living.)  We find that:

• Ignoring measurement error in health leads to substantially underestimating both the persistence of health and the time costs of being unhealthy. 

• Ultimately, measurement error has an effect on the estimated lifetime costs of bad health—as measured by labor earnings, hours worked, consumption, and assets—leading to underestimate these by as much as 300%. 

A key message of our paper is that estimating the lifetime costs of bad health using structural economic models requires researchers to worry about measurement error in health.

2022 MEBDI Machine Learning Competition. Find my written report here.