Date of Award
Spring 2024
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Economics
First Advisor
Zilibotti, Fabrizio
Abstract
Over the past few decades, economic growth has transformed the world, lifting billions of individuals out of poverty. For example, in the early 1980s, roughly 45% of the global population lived on less than $2.15 per day (adjusted for 2017 purchasing power parity). By 2019, this proportion had fallen to below 10%, while the world's GDP per capita increased nearly tenfold (World Bank, 2024). Understanding the drivers of economic growth and identifying policies that can promote it are thus among the most critical questions in social science. In this dissertation, I examine two of the primary drivers of economic growth identified in the literature: technological change (Chapters 1-2) and institutions (Chapter 3). In the first two chapters, I focus on understanding the innovation dynamics underlying the rise and obsolescence of different technologies. I provide a thorough theoretical and empirical characterization of the innovation life cycle experienced by technologies, analyzing the strategic choices society faces regarding the allocation of R&D resources to emerging versus established technologies. In the third chapter, my coauthor Alvaro Cox and I investigate how weak institutions, manifested as corruption, can impact local growth, firm entry, and location decisions. Chapter 1: Growth with New and Old Technologies Is growth driven by the emergence of new paradigms or mostly through the perfection of existing technologies? And is the allocation of research effort between emerging technologies versus established ones efficient? To study these questions, I propose a new semi-endogenous growth model that incorporates technology vintages and the endogenous evolution of multiple technological paradigms through directed innovation. Despite the fact that technologies continuously emerge, making the state space unbounded, the model is remarkably tractable, allowing me to provide a comprehensive characterization of both the balanced growth equilibrium and the transitional dynamics.From a positive perspective, the model can rationalize two distinct empirical patterns of innovation over time and across technologies. Using two centuries of U.S. patent data, I first document that the age profile of patents has a pronounced hump-shape: the majority of contemporary patents are built upon technologies that are between 70 and 100 years old. Second, this age profile has remained remarkably stable throughout the past century. From a normative standpoint, the theory underscores a misallocation of research effort induced by the tendency among profit-maximizing firms to overinvest in further developing mature technologies. This fundamental inefficiency yields a suboptimally slow development of emerging technologies near the technological frontier. An estimated version of my model implies that transitioning from a laissez-faire equilibrium to the efficient allocation would increase the average growth rate of the economy from an annual 2% to 2.18% over the course of a century. These results shed new light on policy discussions concerning the prioritization of emerging technologies versus established ones. For instance, they provide a rationale for public policy to support investments in cutting-edge technologies, such as quantum computing or metabolic engineering. Chapter 2: Directed Technical Change and Technology Diffusion The canonical model of Directed Technical Change (DTC), established by Acemoglu (1998, 2002) and Acemoglu and Zilibotti (2001), has become the workhorse framework in the growth literature for analyzing the direction and bias of innovation across different technologies. In this chapter, I propose a theory that retains the tractability and structure of the canonical DTC model but accounts for scenarios of technology diffusion, where an emerging technology progressively supplants the incumbent, possibly following an S-shaped adoption curve. The model is easily applied to empirical data, facilitating both quantitative and normative analyses. To illustrate this and to provide evidence on the direction of innovation in experiences of technology diffusion, I construct a dataset with adoption and innovation metrics during important technological transitions within sectors such as communication, transportation, and energy. I calibrate the model to the steelmaking industry in 1890-1935. I find that the declining technology during the time, the Bessemer process, was responsible for 15% of the total productivity growth. Chapter 3: Spatial Consequences of Corruption - Entry and Location Decisions of Firms In many developing countries, corruption is a pervasive phenomenon, widespread across districts and local officials. In this chapter, Alvaro Cox and I study the impact of corruption on the spatial distribution of economic activity and its dynamic effects on local and aggregate growth. Our investigation focuses on a federal policy in Brazil that randomly selected local governments for audits on the use of public funds received through transfers. While evidence suggests this program effectively reduced corruption and enhanced political accountability, its implications for firms remain less understood. For example, diminishing corruption could optimize the allocation of procurement contracts by prioritizing efficiency over political connections, fostering competition. Building upon Colonnelli and Prem (2021), we use a difference-in-differences analysis to reveal the positive impact of corruption reduction on local economic activity. As all eligible municipalities were aware of the policy, this approach captures the relative effects of audits on firm outcomes. To discern the policy's aggregate effects, we develop a spatial model wherein firms' entry decisions and choice of production locations are endogenously determined. Variations in corruption levels influence relative productivity and potentially lead to misallocation. In our model, audited municipalities witness a more significant decrease in corruption, creating favorable conditions for business initiation. We derive equations from the model that directly correspond to the empirical difference-in-differences coefficient. This relationship between the model's structural parameters and empirical findings enables us to estimate the upper and lower bounds of the policy's aggregate impact.
Recommended Citation
Silva de Carvalho Ribeiro, Bernardo, "Essays on Economic Growth" (2024). Yale Graduate School of Arts and Sciences Dissertations. 1334.
https://elischolar.library.yale.edu/gsas_dissertations/1334
