Working Papers

Super-Robust Endogenous Growth: Theory and Estimation with Pietro Peretto, [Paper coming soon] [Online presentation]
We propose an endogenous growth model that accommodates increasing, constant, or decreasing aggregate returns to scale with respect to the growth driving factor: technological knowledge accumulated by firms through in-house R&D that improves product quality. When aggregate production is non-linear in firm knowledge, the profitability of firms reflects that property, and entry (new product creation) responds accordingly. The consequent changes in market share offset the non-constant aggregate returns to scale and deliver constant firm-level returns to innovation in steady-state. Because returns to innovation are constant, the steady-state growth rate of income per capita is constant and fully endogenous (i.e., dependent on policy parameters). The non-linearity with respect to the growth driving factor has testable implications for convergence dynamics. Specifically, the speed of convergence is decreasing (increasing) in the distance from the steady-state when aggregate returns to firm knowledge are increasing (decreasing), causing asymmetric convergence that determines an inequality between average growth and steady-state growth in the presence of MIT shocks. The model reduces the growth dynamics to a single quadratic differential equation in the growth rate of GDP per capita. The quadratic term captures the non-linearity in convergence and uniquely identifies the aggregate returns to firm knowledge. We estimate this equation on a panel of countries in the post-industrial revolution era finding evidence of increasing aggregate returns to firm knowledge.

Turbulent Growth: Business Dynamism and Aggregate Productivity, [Updated: December 2024] 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 the market share through innovation. When firms increase their technological knowledge, they gain market share by lowering their price. This reduces the marginal value of further gains in market share. Therefore, the central force in the model is that the incentive to perform cost-reducing innovation in house decreases in firms’ relative size. Allowing for firm-specific idiosyncratic shocks, this mechanism generates churning and a stationary firm-size distribution. These outcomes are robust to introducing entry and exit. A counterfactual exercise studies the effects of a smaller right tail of the R&D productivity distribution of startups. If the decline in job reallocation rates across incumbents observed in the early 2000 is attributable exclusively to that change, the model can explain almost all of the decline in productivity growth in the same period, without invoking a commensurate reduction in R&D.

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 February 2025]

This paper proposes a modification to popular productivity growth accounting decompositions useful for calibrating endogenous growth models. Specifically, the within-firm component is further decomposed to show the covariance of firms’ productivity growth rates and relative levels. This moment provides information about the systematic churning within the relative productivity distribution that, in endogenous growth models, stems from firms’ investment behavior, thus affecting aggregate income growth. This decomposition allows assessing modeling assumptions and quantifying parameters that introduce or affect differential incentives to grow across firms.