Investment and Technological Change
Paper Session
Saturday, Jan. 6, 2024 8:00 AM - 10:00 AM (CST)
- Chair: Laura Veldkamp, Columbia University
Automation and the Rise of Superstar Firms
Abstract
We document evidence that the rise in automation technology contributed to the rise of superstar firms in the past two decades. We explain the empirical link between automation and industry concentration in a general equilibrium framework with heterogeneous firms and variable markups. A firm can operate a labor-only technology or, by paying a per-period fixed cost, an automation technology that uses both workers and robots as inputs. Given the fixed cost, more productive, larger firms are more likely to automate. Increased automation boosts labor productivity, enabling large, robot-using firms to expand further, which raises industry concentration. Our calibrated model does well in matching the highly skewed automation usage toward a few superstar firms observed in the Census data. Since robots substitute for labor, increased automation raises sales concentration more than employment concentration, also consistent with empirical evidence. A modest subsidy for automating firms improves welfare since productivity gains outweigh increased markup distortions.Investment under Up- and Downstream Uncertainty
Abstract
We study the transmission of uncertainty shocks in production networks and nd that theirimpact on economic activity depends on their source in supply chains. A real-option framework
with time-to-build predicts that only upstream uncertainty suppresses investment, since
upstream (downstream) uncertainty from suppliers (customers) affects the shorter-run (longer-run). Consistently, production-network data show that upstream uncertainty propagates downstream, affecting firm-level outcomes negatively. Conversely, downstream uncertainty propagates upstream more weakly but affects firm-level outcomes positively. At the macro-level, these two uncertainties oppositely predict aggregate growth and asset prices. Overall, downstream uncertainty has an expansionary effect, in contrast to other facets of uncertainty.
The Macroeconomics of BigTech
Abstract
This paper investigates the macroeconomics of BigTech. Compared to banks whose key characteristic is the standard collateral-based borrowing constraint, the essential feature of BigTech is the expected-earnings-based lending. Our model implications are twofold. First, BigTech has an efficiency-instability tradeoff as it leads to less misallocation but a higher default rate in the steady state. Second, BigTech can be interpreted as a different financial accelerator from the classical one as it generates persistent impacts on aggregate outputs through amplifying and propagating the second-moment micro-uncertainty shocks. Finally, we discuss the role of algorithm bias and optimal BigTech development.JEL Classifications
- C1 - Econometric and Statistical Methods and Methodology: General