Abstract

This paper presents a structural ranking of countries by their distance to frontier based on comparative advantages. The ranking is centered on the assumption that countries' productive capabilities across products are similar to those of other countries with comparable distance to frontier. It can be micro-founded using standard trade models, and the data strongly supports its main underlying assumption. The estimation strategy provides a general, non-parametric approach to uncovering a log-supermodular structure from the data, and I use it to also rank products by their complexity. The underlying theory provides a flexible micro-foundation for the Economic Complexity Index (Hidalgo and Hausmann, 2009). 

Abstract

We revisit the well-known fact that richer countries tend to produce a larger variety of goods and analyze economic development through (export) diversification. We show that countries are more likely to enter `nearby' industries, i.e., industries that require fewer new occupations. To rationalize this finding, we develop a small open economy (SOE) model of economic development at the extensive industry margin. In our model, industries differ in their input requirements of non-tradeable occupations or tasks. The SOE grows if profit maximizing firms decide to enter new, more advanced industries, which requires training workers in all occupations that are new to the economy. As a consequence, the SOE is more likely to enter nearby industries in line with our motivating fact. We provide indirect evidence in support of our main mechanism and then discuss implications: We show that there may be multiple equilibria along the development path, with some equilibria leading on a pathway to prosperity while others resulting in an income trap, and discuss implications for industrial policy. We finally show that the rise of China has a non-monotonic effect on the growth prospects of other developing countries, and provide suggestive evidence for this theoretical prediction. 

Abstract

We analyze how (amplified) superstar effects impact the allocation of talent across competing teams in large matching markets.  We show that a convex transformation of payoffs promotes positive assortative matching. This is a general result that holds under minimal assumptions on how skills translate into competition outcomes and how competition outcomes translate into payoffs. Our reduced-form analysis covers a wide range of special cases from the literature that micro-found convex transformations of payoffs through diverse mechanisms including globalization, technological change, urban agglomeration, and inter-occupational spillovers.

Abstract

Economic development is a path-dependent process in which countries accumulate capabilities that allow them to move into more complex products and industries. Inspired by a theory of capabilities that explains which countries produce which products, these diversification dynamics have been studied in great detail in the literature on economic complexity analysis. However, so far, these capabilities have remained latent and inference is drawn from product spaces that reflect economic outcomes: which products are often exported in tandem. Borrowing a metaphor from biology, such analysis remains phenotypic in nature. In this paper we develop a methodology that allows economic complexity analysis to use capabilities directly. To do so, we interpret the capability requirements of industries as a genetic code that shows how capabilities map onto products. We apply this framework to construct a genotypic product space and to infer countries’ capability bases. These constructs can be used to determine which capabilities a country would still need to acquire if it were to diversify into a given industry. We show that this information is not just valuable in predicting future diversification paths and to advance our understanding of economic development, but also to design more concrete policy interventions that go beyond targeting products by identifying the underlying capability requirements.  

Abstract

Economic complexity analysis (ECA) is a newly emerging research program that aims to understand what determines the set of goods and services that a country can make, and how this set changes over time. At its core, this research program assumes that production of a given good or service requires a combination of fine-grained and highly complementary capabilities. As a consequence, economic growth is driven by a process of diversification that is enabled by the acquisition of capabilities. This chapter traces the intellectual antecedents and origins of ECA and illustrates core tenets in a simple model of production that is analyzed using complex network theory. It then reviews current debates surrounding core concepts in the field -- in particular measures of relatedness and complexity of economic activities -- and reflects on policy implications. We conclude by sketching a broad research agenda, identifying five key areas: (1) relaxing overly restrictive assumptions of current models, (2) better connecting ECA to debates in the wider field of economics, (3) exploring connections across scales, from countries to cities to firms, (4) addressing questions related to capability coordination, and (5) developing applications to important large-scale societal transitions, such as the green transition and the digitization of work.