arXiv subjects

Andres Gomez-Lievano

Publications and source records attributed to Andres Gomez-Lievano.

10 recordsLinked to original sources

arXiv2024

Industrial complexity and the evolution of formal employment in developing cities

What drives formal employment creation in developing cities? We find that larger cities, home to an abundant set of complex industries, employ a larger share of their working age population in formal jobs. We propose a hypothesis to explain this pattern, arguing that it is the organised nature of formal firms, whereby workers with complementary skills are coordinated in teams, that enables larger cities to create more formal employment. From this perspective, the growth of formal employment is dependent on the ability of a city to build on existing skills to enter new complex industries. To test our hypothesis, we construct a variable which captures the skill-proximity of cities' current industrial base to new complex industries, termed 'complexity potential'. Our main result is that complexity potential is robustly associated with subsequent growth of the formal employment rate in Colombian cities.

econ.GN↗

arXiv2024

The benefits and costs of agglomeration: insights from economics and complexity

There are many benefits and costs that come from people and firms clustering together in space. Agglomeration economies, in particular, are the manifestation of centripetal forces that make larger cities disproportionately more wealthy than smaller cities, pulling together individuals and firms in close physical proximity. Measuring agglomeration economies, however, is not easy, and the identification of its causes is still debated. Such association of productivity with size can arise from interactions that are facilitated by cities ("positive externalities"), but also from more productive individuals moving in and sorting into large cities ("self-sorting"). Under certain circumstances, even pure randomness can generate increasing returns to scale. In this chapter, we discuss some of the empirical observations, models, measurement challenges, and open question associated with the phenomenon of agglomeration economies. Furthermore, we discuss the implications of urban complexity theory, and in particular urban scaling, for the literature in agglomeration economies.

physics.soc-ph↗

arXiv2023

Bridging the short-term and long-term dynamics of economic structural change

Economic transformation -- change in what an economy produces -- is foundational to development and rising standards of living. Our understanding of this process has been propelled recently by two branches of work in the field of economic complexity, one studying how economies diversify, the other how the complexity of an economy is expressed in the makeup of its output. However, the connection between these branches is not well understood, nor how they relate to a classic understanding of structural transformation. Here, we present a simple dynamical modeling framework that unifies these areas of work, based on the widespread observation that economies diversify preferentially into activities that are related to ones they do already. We show how stylized facts of long-run structural change, as well as complexity metrics, can both emerge naturally from this one observation. However, complexity metrics take on new meanings, as descriptions of the long-term changes an economy experiences rather than measures of complexity per se. This suggests relatedness and complexity metrics are connected, in a hitherto overlooked way: Both describe structural change, on different time scales. Whereas relatedness probes transformation on short time scales, complexity metrics capture long-term change.

physics.soc-ph↗

arXiv2021

Estimating the drivers of urban economic complexity and their connection to economic performance

Estimating the capabilities, or inputs of production, that drive and constrain the economic development of urban areas has remained a challenging goal. We posit that capabilities are instantiated in the complexity and sophistication of urban activities, the knowhow of individual workers, and the city-wide collective knowhow. We derive a model that indicates how the value of these three quantities can be inferred from the probability that an individual in a city is employed in a given urban activity. We illustrate how to estimate empirically these variables using data on employment across industries and metropolitan statistical areas in the US. We then show how the functional form of the probability function derived from our theory is statistically superior when compared to competing alternative models, and that it explains well-known results in the urban scaling and economic complexity literature. Finally, we show how the quantities are associated with metrics of economic performance, suggesting our theory can provide testable implications for why some cities are more prosperous than others.

physics.soc-ph↗

arXiv2020

Artificial Increasing Returns to Scale and the Problem of Sampling from Lognormals

We show how increasing returns to scale in urban scaling can artificially emerge, systematically and predictably, without any sorting or positive externalities. We employ a model where individual productivities are independent and identically distributed lognormal random variables across all cities. We use extreme value theory to demonstrate analytically the paradoxical emergence of increasing returns to scale when the variance of log-productivity is larger than twice the log-size of the population size of the smallest city in a cross-sectional regression. Our contributions are to derive an analytical prediction for the artificial scaling exponent arising from this mechanism and to develop a simple statistical test to try to tell whether a given estimate is real or an artifact. Our analytical results are validated analyzing simulations and real microdata of wages across municipalities in Colombia. We show how an artificial scaling exponent emerges in the Colombian data when the sizes of random samples of workers per municipality are $1\%$ or less of their total size.

econ.GN↗

arXiv2020

An information-theoretic approach to the analysis of location and co-location patterns

We propose a statistical framework to quantify location and co-location associations of economic activities using information-theoretic measures. We relate the resulting measures to existing measures of revealed comparative advantage, localization and specialization and show that they can all be seen as part of the same framework. Using a Bayesian approach, we provide measures of uncertainty of the estimated quantities. Furthermore, the information-theoretic approach can be readily extended to move beyond pairwise co-locations and instead capture multivariate associations. To illustrate the framework, we apply our measures to the co-location of occupations in US cities, showing the associations between different groups of occupations.

stat.AP↗

arXiv2018

Machine-learned patterns suggest that diversification drives economic development

We develop a machine-learning-based method, Principal Smooth-Dynamics Analysis (PriSDA), to identify patterns in economic development and to automate the development of new theory of economic dynamics. Traditionally, economic growth is modeled with a few aggregate quantities derived from simplified theoretical models. Here, PriSDA identifies important quantities. Applied to 55 years of data on countries' exports, PriSDA finds that what most distinguishes countries' export baskets is their diversity, with extra weight assigned to more sophisticated products. The weights are consistent with previous measures of product complexity in the literature. The second dimension of variation is a proficiency in machinery relative to agriculture. PriSDA then couples these quantities with per-capita income and infers the dynamics of the system over time. According to PriSDA, the pattern of economic development of countries is dominated by a tendency toward increased diversification. Moreover, economies appear to become richer after they diversify (i.e., diversity precedes growth). The model predicts that middle-income countries with diverse export baskets will grow the fastest in the coming decades, and that countries will converge onto intermediate levels of income and specialization. PriSDA is generalizable and may illuminate dynamics of elusive quantities such as diversity and complexity in other natural and social systems.

physics.soc-ph↗

arXiv2018

Methods and Concepts in Economic Complexity

Knowhow in societies accumulates as it gets transmitted from group to group, and from generation to generation. However, we lack of a unified quantitative formalism that takes into account the structured process for how this accumulation occurs, and this has precluded the development of a unified view of human development in the past and in the present. Here, we summarize a paradigm to understand and model this process. The paradigm goes under the general name of the Theory of Economic Complexity (TEC). Based on it, we present a combination of analytical, numerical and empirical results that illustrate how to characterize the process of development, providing measurable quantities that can be used to predict future developments. The emphasis is the quantification of the collective knowhow an economy has accumulated, and what are the directions in which it is likely to expand. As a case study we consider data on trade, which provides consistent data on the technological diversification of 200 countries across more than 50 years. The paradigm represented by TEC should be relevant for anthropologists, sociologists, and economists interested in the role of collective knowhow as the main determinant of the success and welfare of a society.

physics.soc-ph↗

arXiv2018

On the scaling patterns of infectious disease incidence in cities

Urban areas with larger and more connected populations offer an auspicious environment for contagion processes such as the spread of pathogens. Empirical evidence reveals a systematic increase in the rates of certain sexually transmitted diseases (STDs) with larger urban population size. However, the main drivers of these systemic infection patterns are still not well understood, and rampant urbanization rates worldwide makes it critical to advance our understanding on this front. Using confirmed-cases data for three STDs in US metropolitan areas, we investigate the scaling patterns of infectious disease incidence in urban areas. The most salient features of these patterns are that, on average, the incidence of infectious diseases that transmit with less ease-- either because of a lower inherent transmissibility or due to a less suitable environment for transmission-- scale more steeply with population size, are less predictable across time and more variable across cities of similar size. These features are explained, first, using a simple mathematical model of contagion, and then through the lens of a new theory of urban scaling. These theoretical frameworks help us reveal the links between the factors that determine the transmissibility of infectious diseases and the properties of their scaling patterns across cities.

physics.soc-ph↗

arXiv2016

Explaining the Prevalence, Scaling and Variance of Urban Phenomena

The prevalence of many urban phenomena changes systematically with population size. We propose a theory that unifies models of economic complexity and cultural evolution to derive urban scaling. The theory accounts for the difference in scaling exponents and average prevalence across phenomena, as well as the difference in the variance within phenomena across cities of similar size. The central ideas are that a number of necessary complementary factors must be simultaneously present for a phenomenon to occur, and that the diversity of factors is logarithmically related to population size. The model reveals that phenomena that require more factors will be less prevalent, scale more superlinearly and show larger variance across cities of similar size. The theory applies to data on education, employment, innovation, disease and crime, and it entails the ability to predict the prevalence of a phenomenon across cities, given information about the prevalence in a single city.

physics.soc-ph↗