Are the well-known facts about urbanization in the United States also true for the developing world? We compare American metropolitan areas with analogous geographic units in Brazil, China and India. Both Gibrat’s Law and Zipf’s Law seem to hold as well in Brazil as in the U.S., but China and India look quite different. In Brazil and China, the implications of the spatial equilibrium hypothesis, the central organizing idea of urban economics, are not rejected. The India data, however, repeatedly rejects tests inspired by the spatial equilibrium assumption. One hypothesis is that spatial equilibrium only emerges with economic development, as markets replace social relationships and as human capital spreads more widely. In all four countries there is strong evidence of agglomeration economies and human capital externalities. The correlation between density and earnings is stronger in both China and India than in the U.S., strongest in China. In India the gap between urban and rural wages is huge, but the correlation between city size and earnings is more modest. The cross-sectional relationship between area-level skills and both earnings and area-level growth are also stronger in the developing world than in the U.S. The forces that drive urban success seem similar in the rich and poor world, even if limited migration and difficult housing markets make it harder for a spatial equilibrium to develop.
The prevalence of many urban phenomena changes systematically with population size1. We propose a theory that unifies models of economic complexity2,3 and cultural evolution4 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.
The prevalence of many urban phenomena changes systematically with population size1. We propose a theory that unifies models of economic complexity2, 3 and cultural evolution4 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.
Since the Zapatista revolution of January 1994, enormous amount of resources coming from the federal government have poured over Chiapas. The gap in years and quality of education has been reduced significantly; and road, port and airport infrastructure have undergone a dramatic transformation. And yet, the income gap between Chiapas and the rest of Mexico has only widened. To understand why, a multi-disciplinary team of twelve experts have devoted significant time and resources to study different aspects of the development dynamic of Chiapas. As a result, 5 base documents have been published analyzing Chiapas:
- Complexity profile - Growth Diagnostic - Institutional Diagnostic - Poverty profile - Pilot of productive dialogs and inclusive growth in an indigenous community
This report resumes the findings from these and articulates their corresponding recommendations into a policy plan.
According to our hypothesis, Chiapas is wedged in a low productivity trap. A modern production system, responsible for productivity increases, income and development elsewhere in the world, requires a number of complementary inputs or capacities that are absent in Chiapas. As a result, its economy consists of a few primary products of little or no technological sophistication, and a vibrant service industry fueled by public expenditure in its larger cities. In this situation, there are no incentives to acquire additional education or skills because there is no demand for them in the economy. As we have proved, the few that manage to emigrate earn salaries elsewhere in Mexico slightly above other migrants with similar qualifications. As it turns out, it is not about the Chiapanecos, it is about Chiapas.
To overcome the current dilemmas and spark the engine of growth, Chiapas needs to resolve its issues of coordination, connectivity and gradually promote economic activities of higher complexity. Yazaki, one of the few manufacturers present in Chiapas, is an example of the role of the state in helping the economy to overcome the chicken-and-egg dilemmas, providing the public goods required - in an initial push – by a more complex economy. Our recommendations are based in identifying the productive capabilities embedded within the current productive structure of Chiapas four largest urban agglomerations, and leveraging on them to board on different potential, more complex industries that use a similar base of knowledge. To conquer those industries and diversify its economy, Chiapas needs a public-private agency empowered to iteratively solve the issues and bottlenecks these potential industries face in each particular place. Public transport and housing policy can be used as means to incorporating the surrounding communities into the increasingly modern economies of urban centers. Special economic zones and agro-industrial parks can be used to spur productivity in those areas where labor and appropriability are the most binding constrains.
In order to appropriately understand the sports sector, its magnitude, embeddedness in the economy, and strategic value, it is necessary to develop a framework through which to study it. Having a standardized and comprehensive methodology to analyze the sports sector will allow policymakers, academics, and other stakeholders to look at the sports sector at a new level of detail and rigor.
Previous work has outlined the numerous data quality and aggregation challenges currently present in the sports economy literature (Russell, Barrios & Andrews 2016). In light of these challenges, this paper attempts to build on the suggested categorization of the sports industry and develop a sound strategy to analyze the sector through an empirical exercise in a specific context: the Mexican Economy.
To this end, we first attempt to understand how connected the sports sector is to other activities in the economy and identify which sectors share similar know-how with m1. Additionally, we attempt to determine the relative magnitude of the sports sector through variables such as value added and employment.
Similarly, we consider study the spatial considerations around sports related economic activities at a subnational level. The advancement of spatial economics has allowed us to understand a new dimension of how an economic sector can develop and how characteristics inherent to a given geography can play a role in determining why some activities end up appearing and developing in the places they do.
Lastly, some descriptive and regression analysis efforts in this paper enabled us to better understand and characterize the sports sector. Such exercises allow us to learn what type of workers typically comprises the sports sector, and whether such profile is different across the different categories of sports activities. Among the variables analyzed I the descriptive exercise, we can look at education level and wages–among others–of those who work on this sector, and compare them to the overall employed population.
This paper is structured as follows: Section 1 will make the case for how publicly available data in Mexico meets the level of detail required for this type of study. Section 2 will look at the way in which the sports sector is nested in the overall economy. Section 3 studies the magnitude of the sports sector through different metrics. Section 4 looks at the type of jobs that comprise the sports sector. Section 5 looks at the differences in intensity of sports activities and early work on its potential causal roots. Section 6 provides some conclusions.
Data on the sports economy is often difficult to interpret, far from transparent, or simply unavailable. Data fraught with weaknesses causes observers of the sports economy to account for the sector differently, rendering their analyses difficult to compare or causing them to simply disagree. Such disagreement means that claims regarding the economic spillovers of the industry can be easily manipulated or exaggerated. Thoroughly accounting for the industry is therefore an important initial step in assessing the economic importance of sports-related activities. For instance, what do policymakers mean when they discuss sports-related economic activities? What activities are considered part of the "sports economy?" What are the difficulties associated with accounting for these activities? Answering these basic questions allows governments to improve their policies.
The paper below assesses existing attempts to understand the sports economy and proposes a more nuanced way to consider the industry. Section 1 provides a brief overview of existing accounts of the sports economy. We first differentiate between three types of assessments: market research accounts conducted by consulting groups, academic accounts written by scholars, and structural accounts initiated primarily by national statistical agencies. We then discuss the European Union’s (EU) recent work to better account for and understand the sports economy. Section 2 describes the challenges constraining existing accounts of the sports economy. We describe two major constraints - measurement challenges and definition challenges - and highlight how the EU's work has attempted to address them. We conclude that, although the Vilnius Definition improves upon previous accounts, it still features areas for improvement.
Section 3 therefore proposes a paradigm shift with respect to how we understand the sports economy. Instead of primarily inquiring about the size of the sports economy, the approach recognizes the diversity of sports-related economic activities and of relevant dimensions of analysis. It therefore warns against attempts at aggregation before there are better data and more widely agreed upon definitions of the sports economy. It asks the following questions: How different are sports-related sectors? Are fitness facilities, for instance, comparable to professional sports clubs in terms of their production scheme and type of employment? Should they be understood together or treated separately? We briefly explore difference in sports-related industry classifications using data from the Netherlands, Mexico, and the United States. Finally, in a short conclusion, we discuss how these differences could be more fully explored in the future, especially if improvements are made with respect to data disaggregation and standardization.
No matter which way you look at it, Chiapas is the most backward of any state in Mexico. Its per capita income is the lowest of the 32 federal entities, at barely 40% of the national median (Figure 1). Its growth rate for the decade 2003-2013 was also the lowest (0.2%),1 causing the income gap separating Chiapas from the national average to increase from 53% to 60%. That is to say that today the average income for a worker in Mexico is two and a half times greater than the average in Chiapas. The two next poorest states, Oaxaca and Guerrero, are 25% and 30% above Chiapas.2 According to the Instituto Nacional de Estadística y Geografía de México (INEGI, National Institute of Statistics and Geography), Chiapas is also the state with the highest poverty rate (74.7%) as well as extreme poverty (46.7%).3
These major differences in income levels among Mexican federal entities are reproduced as in a fractal within Chiapas. In fact, while the wealthiest entity (Mexico City) is wealthier than the poorest (Chiapas) by a factor of six, the difference within Chiapas between the wealthiest municipality (Tuxtla Gutiérrez) and the poorest (Aldama and Mitontic) is by a factor greater than eight.4
As there are different "Mexicos" within Mexico,5 in Chiapas there are also different sorts of Chiapas (Figure 2). Income per capita in Tuxtla Gutiérrez, to the right of the distribution, is five standard deviations above the state average. Next comes a series of intermediate cities, San Cristóbal de las Casas, Comitán de Domínguez, Tapachula, and Reforma, between two and a half to four standard deviations above the average. The remaining municipalities of Chiapas follow (122 in all), clustered to the far left of the distribution. In addition, both the statistics available at the town level and our visits to various municipalities in Chiapas seem to indicate that significant differences also exist within these municipalities.
From this vantage point, questions as to why Chiapas is poor, or what explains its significant backwardness compared to other areas of Mexico, become much more complex. Why do some regions in Chiapas have high income levels, while other regions remain stagnant, fully dependent on federal transfers and deprived from the benefits of modern life?
1 This is the non-oil gross domestic product growth rate reported by INEGI, considered to be more representative of the productive spectrum. In any case, the overall rate of growth in Chiapas (-0.2%) was also the lowest amongst all Mexican entities for the decade. 2 Refers to non-oil GDP; in general terms, Guerrero and Oaxaca are 19% and 16% above Chiapas. 3 Growth figures refer to the decade 2003-2013, poverty figures are those published by INEGI for 2012. 4 Comparisons of Chiapas municipalities are made based on the data from the 10% sample of the 2010 Population Census, which is representative at the state level. 5 This is a reference to the report, A tale of two Mexicos: Growth and prosperity in a two-speed economy, McKinsey Global Institute (2014).
The comparative advantage of a location shapes its industrial structure. Current theoretical models based on this principle do not take a stance on how comparative advantages in different industries or locations are related with each other, or what such patterns of relatedness might imply about the underlying process that governs the evolution of comparative advantage. We build a simple Ricardian-inspired model and show this hidden information on inter-industry and inter-location relatedness can be captured by simple correlations between the observed patterns of industries across locations or locations across industries. Using the information from related industries or related locations, we calculate the implied comparative advantage and show that this measure explains much of the location’s current industrial structure. We give evidence that these patterns are present in a wide variety of contexts, namely the export of goods (internationally) and the employment, payroll and number of establishments across the industries of subnational regions (in the US, Chile and India). The deviations between the observed and implied comparative advantage measures tend to be highly predictive of future industry growth, especially at horizons of a decade or more; this explanatory power holds at both the intensive as well as the extensive margin. These results suggest that a component of the long-term evolution of comparative advantage is already implied in today’s patterns of production.
This paper evaluates if, after ten years of implementation, the conditional cash transfer program Progresa/Oportunidades has had an effect on labor market outcomes among young beneficiaries in rural Mexico. We use a specific module for the young aged 14 to 24 in the 2007 wave of the Rural Households Evaluation Survey and apply a multi-treatment methodology for different time exposition to the program to identify effects on employment probability, wages, migration and intergenerational occupational mobility. Our results show very little evidence of program impacts on employment, wages or inter-generational occupational mobility among the cohort of beneficiaries under study. This suggests that, despite well documented effects on human capital accumulation of the beneficiaries, labor market prospects in the localities under the program remain sparse.
Violence has increased all around Mexico in the last years, reflecting an uprise in the rate of homicides, and especially after some federal intervention took place to fight the drug cartels in some states. In this paper we use data at the municipal level to link social and institutional factors with the rates of homicides. We exploit the entrance for federal army interventions in 2007 and 2008 in some states to fight drug cartels. Using different estimation methods, we find that inequality, access to social security and income, as well as local provision of security and law are relevant in explaining homicides. We also find that the army interventions have increased not only drug related homicides, but also general homicides in municipalities under intervention compared with those with no intervention.
The large economies have each, in sequence, offered "models" that once seemed attractive to others but that eventually gave way to disillusionment. Small countries may have some answers. They are often better able to experiment with innovative policies and institutions and some of the results are worthy of emulation. This article gives an array of examples. Some of them come from small advanced countries: New Zealand’s Inflation Targeting, Estonia’s flat tax, Switzerland’s debt brake, Ireland’s FDI policy, Canada’s banking structure, Sweden’s Nordic model, and the Netherlands’ labor market reforms. Some examples come from countries that were considered "developing" 40 years ago, but have since industrialized. Korea stands for education; among Singapore’s innovative polices were forced saving and traffic congestion pricing; Costa Rica and Mauritius outperformed their respective regions by, among other policies, foreswearing standing armies; and Mexico experimented successfully with the original Conditional Cash Transfers. A final set of examples come from countries that export mineral and agricultural commodities -- historically vulnerable to the "resource curse" -- but that have learned how to avoid the pitfalls: Chile’s structural budget rules, Mexico’s oil option hedging, and Botswana’s "Pula Fund."
The past 20 years have been a period of important reforms in Mexico. Since the late 1980s, the country has undergone an impressive process of liberalization, opening of the economy, and macroeconomic stabilization. Extreme vulnerability to external shocks, double-digit inflation, and current account and fiscal deficits seem to have been overcome. However, a number of weaknesses continue to drag the country’s productivity and hence its potential for sustained economic growth and the well-being of its citizens. In spite of a very benign external environment in the period 2003–07, Mexico’s growth rates have been disappointing, and the challenges facing the country have become even greater in the context of the current major economic and financial crisis — one of the most serious in decades — affecting the United States and the rest of the world. The Mexico Competitiveness Report 2009 aims at providing Mexico’s policymakers, business leaders, and all relevant stakeholders with a unique tool that identifies the country’s main competitiveness flaws and strengths, together with an in-depth analysis of areas that are key to the country’s potential for long-term growth. In doing so, the Report aims to support the country’s reform process and contribute to the definition of a national competitiveness agenda of the priority issues that need to be tackled for Mexico to boost its competitiveness in the face of the present daunting economic outlook. The Report is organized into three thematic parts. Part 1 assesses the current state of Mexico’s competitiveness and its potential for sustained growth using the broad methodological framework offered by the Global Competitiveness Index (GCI) 2008–2009. Part 2 features contributions from a number of experts providing additional insights and diagnostics related to particular aspects of the competitiveness challenges faced by the country. Part 3 includes detailed profiles for Mexico and 10 selected countries and offers a comprehensive competitiveness snapshot for each of these countries.