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# Working Papers

## Turbulent Growth: Business Dynamism and Aggregate Productivity, R&R at European Economic Review

Turbulence is the process of endogenous reallocation of resources (e.g., jobs) across firms due to entry, exit, and churning (movements within the firm-size distribution). This paper formulates a model of turbulent endogenous growth built on the insight that the forces that drive aggregate productivity growth also drive turbulence because the two are manifestations

of a single underlying process: profit-driven competition for market share through innovation.

When firms increase their technological knowledge, they gain market share by lowering their relative price, thus reducing the marginal value of further gains in market share. This leads to the emergence of diminishing returns in relative terms. Therefore, incentives to innovate decline in relative size, all else constant, generating churning endogenously as mean reversion.

This mechanism delivers a stationary, non-degenerate, and endogenous firm-size distribution dependent on R&D. Meanwhile, constant returns to the cumulative factor (technological knowledge) drive a trendless aggregate growth rate determined by R&D. Endogenous entry and exit entail selection effects that shape the characteristics of the firm population, and generate a firm life cycle, affecting R&D, thus growth.

Business Cycles, R&D, and Hysteresis: An Empirical Analysis with Hedieh Shadmani [updated May 2024], R&R at Macroeconomic Dynamics

This paper investigates the permanent effect on total factor productivity (TFP) of temporary shocks. We estimate a structural vector

autoregression to test the predictions of endogenous growth models over the business cycle. According to theory, the stock of technological knowledge promotes its flow as researchers “stand on the shoulders of giants.” Therefore, if R&D investment is pro-cyclical — as data show and theory predicts—a recession leads to a temporary deviation of the R&D level from its trend, thus reducing new knowledge creation. The consequent technological stock loss sets the economy on a parallel but

permanently lower trend. The results are in line with the main theoretical prediction. Specifically, the US economy loses approximately 1.5% in TFP following an increase in cyclical unemployment that peaks at 1 percentage point above mean. The historical variance decomposition shows a particularly strong positive effect during the boom of the late ‘60s, and particularly strong negative effects around the Volcker disinflation period and the Great Recession. Finally, we estimate the effects

on R&D of an exogenous increase in TFP to discriminate between various theories. Our results are consistent with models where financial frictions or nominal rigidities drive R&D’s pro-cyclicality.

Revisiting Productivity Growth Accounting Decompositions [updated August 2024]

Productivity growth accounting decompositions are sensitive to the definition of aggregate productivity, which usually takes the form of a weighted geometric or arithmetic average of firms’ productivities. This paper shows explicitly why the two differ. It further proposes a modification to a popular decomposition highlighting the contribution of the component responsible for this discrepancy, namely the covariance of productivity growth rates and levels. The argument favoring this modified decomposition is that the novel component offers relevant information for applied theoretical purposes, thus increasing the usefulness of aggregate productivity decompositions. Finally, the paper argues that standard theoretical assumptions support (i) a proposed separation between aggregate and average productivity, and (ii) the adoption of the arithmetic average definition as opposed to the more popular geometric average.

###### Work In Progress

## Water Salinity and Economic Activity in Coastal Areas: A Model of Adaptation to Sea Level Rise with Robert Nazarian and William F. Vasquez

Business Cycle, R&D, and Hysteresis: Searching for Asymmetries with Hedieh Shadmani

Super-Robust Endogenous Growth: An Estimation with Pietro Peretto

Research: Education

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