Previous papers such as Russell, Barrios & Andrews (2016), Guerra (2016), and Russell, Tokman, Barrios & Andrews (2016) have aimed to provide an empirical view into the sports economy. This proves to be a difficult task, given the many definitions of ‘sports’ and data deficiencies and differences in the sports domain (between contexts and over time). The emerging view in these previous papers provides interesting information about the sports sector, however: it shows, for instance, that different contexts have differently intensive sports sectors, and that sports activities overlap with other parts of the economy. This kind of information is useful for policymakers in governments trying to promote sports activities and use sports to advance the cause of broad-based social and economic development.
This paper is written with these policymakers in mind. It intends to offer a guide such agents can use in constructing sports policies focused on achieving development goals (what we call development through sports), and discusses ways in which these policymakers can employ empirical evidence to inform such policies.
The paper draws on the concept of ‘governance’ to structure its discussion. Taking a principal-agent approach to the topic, governance is used here to refer to the exercise of authority, by one set of agents, on behalf of another set of agents, to achieve specific objectives. Building on such a definition, the paper looks at the way governmental bodies engage in sports when acting to further the interests of citizens, most notably using political and executive authority to promote social and economic development. This focus on governance for development through sports (asking why and how governments use authority to promote sports for broader social and economic development objectives) is different from governance of sports (which focuses on how governments and other bodies exercise authority to control and manage sports activities themselves), which others explore in detail but we will not discuss.
The paper has five main sections. A first section defines what we mean by ‘governance’ in the context of this study. It describes an ends-means approach to the topic—where we emphasize understanding the goals of governance policy (or governance ends) and then thinking about the ways governments try to achieve such goals (the governance means). The discussion concludes by asking what the governance ends and means are in a development through sports agenda. The question is expanded to ask whether one can use empirical evidence to reflect on such ends and means. One sees this, for instance, in the use of ‘governance indicators’ and ‘governance dashboards’ in the international development domain. A second section details the research method we used to address these questions. This mixed method approach started by building case studies of sports policy interventions in various national and sub-national governments to obtain a perspective on what these policies tend to involve (across space and time). It then expanded into an analysis of sports policies in a broad set of national and sub-national governments to identify common development through sport ends and means. Finally, it involved experimentation with selected data sources to show how the ends and means might be presented in indicators and dashboards—to offer evidence-based windows into development through sports policy regimes.
Based on this research, sections three and four discuss the governance ends and means commonly pursued and employed by governments in this kind of policy process. The sections identify three common ends (or goals)—inclusion, economic growth, and health—and a host of common means—like the provision of sports facilities, organized activities, training support, financial incentives, and more—used in fostering a development through sports agenda. Data are used from local authorities in England to show the difficulties of building indicators reflecting such policy agendas, but also to illustrate the potential value of evidence-based dashboards of these policy regimes. It needs to be stated that this work is more descriptive than analytical, showing how data can be used to provide an evidence-based perspective on this domain rather than formally testing hypotheses about the relationship between specific policy means and ends. In this regard, the work is more indicative of potential applications rather than prescriptive. A conclusion summarizes the discussion and presents a model for a potential dashboard of governance in a development through sports policy agenda.
 This terminology comes from Houlihan and White, who identify the “tension between development through sport (with the emphasis on social objectives and sport as a tool for human development) and development of sport (where sport was valued for its own sake)” (Houlihan & White 2002, 4).
 The paper relates to a vibrant literature on this topic, which investigates the reasons and ways governments support the sports sector (classic and recent studies in this literature include Adams and Harris (2014), Gerretsenand Rosentraub (2015), Grix and Carmichael (2012), Grix (2015), Hallman and Petry (2013), Houlihan (2002, 2005, 2016), Houlihan and White (2002), Hylton (2013), Koski and Lämsä (2015), Schulenkorf and Adair (2013), and Vuori et al. (1995).
 Work on the governance of sports assesses the way international entities like FIFA and the IOC work with national and local governmental bodies to oversee, regulate, and otherwise manage sports like football and the Olympic movement, using authority to create and implement rules on behalf of those involved in the sport itself. See, for instance Forster (2006), Geeraert (2013), and Misener (2014).
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.
As described in Russell, Barrios & Andrews (2016), past attempts to understand the sports economy have been constrained by a number of data limitations. For instance, many of these accounts use revenues when value added measures would be more appropriate. Similarly, many accounts use top-down definitions that result in double counting and an inflated estimate of the size of the sports economy. More importantly, past accounts have focused most of their efforts estimating the overarching size of the sports economy. Constrained by aggregated data that groups a wide range of sports-related economic activities together, they primarily discuss the size of the sports-related economic activity. Their focus on answering the question of "How big?" conceals substantial differences between activities. Core sports activities, such as professional sports teams, behave very differently than activities, like sporting goods manufacturing that are closer to the periphery of the sports economy. Likewise, there are even important differences amongst core sports activities. Professional sports teams are very different than fitness facilities, and they might differ in different respects.
Guerra (2016) demonstrates that, when detailed, disaggregated data are available, the possibilities to analyze and understand the sports are greatly increased. For instance, Guerra (2016) were able to conduct skills-based analyses, magnitude analyses, employment characterizations, geographic distribution analyses, and calculations of the intensity of sports activities. The sector disaggregation, spatial disaggregation, and database complementarity present in the Mexico data used in that paper therefore enables a more detailed and nuanced understanding of sports and sports-related economic activity.
Data with characteristics similar to those found in Mexico are few and far between. We have, unfortunately, been unable to completely escape such data limitations. However, we have compiled and analyzed a large array of employment data on sports-related economic activities in Europe. In the paper that follows, we describe our analyses of these data and the findings produced.
Section 1 begins with a discussion of employment in sports and an explanation of why we chose this variable for our analyses. Section 2 provides an overview of the data used in this paper particularly focusing on the differences between it and the Mexico data discussed in Guerra (2016). It also describes the methodology we use. We analyze these data using one of two related measures to understand the intensity of sports-related activities across different geographic areas in countries. We also construct measures at the level of a single country in order to compare across entire economies. At the international level, we adopt the revealed comparative advantage (RCA) measure that Balassa (1965) first developed to analyze international trade. Within specific countries, however, we use a population-adjusted version of the RCA measure known as RPOP. Section 3 presents the most relevant findings and Section 4 discusses their limitations. Section 5 concludes with the lessons learned and avenues for future research. While there are limitations on these analyses, they can give policymakers a better understanding of the distribution and concentration of sports across space. Such information can serve as an important input for sports-related investment decisions and other sports-related policies.
There is perhaps no larger sports policy decision than the decision to host or bid to host a mega-event like the FIFA World Cup or the Summer Olympics. Hosts and bidders usually justify their decisions by touting their potential impact. Many organizers and promoters either fund or widely disseminate ex-ante studies that tend to highlight the positive effects of the event. For instance, the consultancy firm Ernst & Young produced a 2010 report prior to the 2014 World Cup in Brazil that painted an optimistic picture of the event’s potential legacy. It estimated that an additional R$ 142.39 billion (4.91% of 2010 GDP) would flow through the Brazilian economy over the 2010-2014 period, generating 3.63 million jobs per year, R$ 63.48 billion (2.17% of 2010 GDP) of income for the population and additional tax collection of R$ 18.13 billion (0.62% of 2010 GDP) for the local, state and federal governments. Ernst & Young estimated that during the same period 2.98 million additional visitors would travel to Brazil, increasing the international tourist inflow up to 79%.
Such results, if true, would clearly attractive for governments considering a bid, but these expected impacts don’t always materialize. Moreover, hosting mega-events requires significant investments - and the cost of these investments is rising. Zimbalist notes emerging economies like China, Brazil, and South Africa have increasingly perceived "mega-events as a sort of coming-out party signaling that [they are] now a modernized economy, ready to make [their] presence felt in world trade and politics" (Zimbalist 2015). Their intentions may be noble, but the intention of using mega-events as a "coming-out party" means developing countries hoping to host them need to make massive investments. They are confronted by significant obstacles in that they lack sufficient stadiums, accommodations, transportation systems, and other sports-related infrastructure. As a result, each of the mega-events hosted by emerging economies has been exorbitantly expensive. The 2014 World Cup cost Brazil between USD 15 billion and USD 20 billion, while Beijing reportedly spent USD 40 billion prior to the 2008 Summer Olympic (Zimbalist 2015). Additionally, as the debt-ridden 1976 Summer Olympics in Montreal demonstrates, expensive mega-events are not limited to emerging economies alone. Flyvbjerg and Stewart have even shown that every Olympics since 1960 has gone over budget (Flyvbjerg and Stewart 2012).
Such incredible figures, in terms of both costs and benefits, beget the question: are mega-events worth it? Which type of reports should governments focus their attention on? What economic consequences should a government reasonably expect? With such high stakes, policymakers need to choose wisely. We attempt to answer these questions and aid the decisions of policymakers by providing a concise review of the rich academic literature on mega-events. For the purposes of this paper, we mainly focus on the Summer Olympic Games and the FIFA World Cup as mega-events. However, we also leverage information regarding events like the Winter Olympic Games, the UEFA football championships, and the Commonwealth Games. These events are organized on a smaller scale than the previous two, but they might provide some insights on how to best understand mega-events. We focus on claims surrounding the direct or indirect mechanisms that facilitate the impact that ex-ante studies predict. We provide a review of these claims and their validity according to the existing literature.
Section 1 focuses on the argument that mega-events lead to increased economic activity in the host economy. Specifically, we evaluate whether or not mega-events leads to access to previously inaccessible funds and increased investments. These investments could theoretically come from supranational organizations, private stakeholders, or public stakeholders. We also consider whether or not these new expenditures and investments have the multiplicative effect that many ex-ante studies assume they have. We finally investigate if the economic activity surrounding mega-events leads to increased revenues and tax collection for host governments. Overall, the existing academic literature suggests that any increased economic activity resulting from the event is routinely dwarfed by additional public budgetary commitments. Moreover, the arguments regarding multiplicative effects and increased revenues also tend to be exaggerated.
Section 2 shifts the focus to the potential impact of mega-events on a specific industry: tourism. We explore the effect of mega-events on the number of tourists visiting the host region and their spending habits. We explore this channel both for analyses specific to a single mega-event and for cross-country evaluations incorporating many events. Next, we consider the impact of a mega-event on a region’s brand and image in the international community with the idea of testing if hosting the competition will impact future tourism. Finally, we consider if mega-events lead to increases in the capacity of a city or country to welcome future tourists as a result of improved airport infrastructure, accommodations, and/or transportation systems. As was true in Section 1, the academic literature suggests that the claims of many ex-ante studies are misleading. Our review finds that there is some evidence for increases in tourist arrivals to certain events, but those increases are far smaller than what is generally predicted beforehand. These effects are also usually dependent on factors, such as the timing of the competition, that are specific to the host region and the event itself.
Section 3 briefly discusses other potential qualitative and social impacts of mega-events such as international business relations, crime reduction, and the "feel-good effect." In the penultimate section, Section 4, we discuss how these conclusions should impact the decision-making of policymakers. Finally, in a short conclusion, we summarize the findings of our review.
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.
Labor flows across industries reallocate resources and diffuse knowledge among economic activities. However, surprisingly little is known about the structure of such inter-industry flows. How freely do workers switch jobs among industries? Between which pairs of industries do we observe such switches? Do different types of workers have different transition matrices? Do these matrices change over time?
Using German social security data, we generate stylized facts about inter-industry labor mobility and explore its consequences. We find that workers switch industries along tight paths that link industries in a sparse network. This labor-flow network is relatively stable over time, similar for workers in different occupations and wage categories and independent of whether workers move locally or over larger distances. When using these networks to construct inter-industry relatedness measures they prove better predictors of local industry growth rates than co-location or input-based alternatives. However, because industries that exchange much labor typically do not have correlated growth paths, the sparseness of the labor-flow network does not necessarily prevent a smooth reallocation of workers from shrinking to growing industries. To facilitate future research, the inter-industry relatedness matrices we develop are made available as an online appendix to this paper.
Establishment closures leave many workers unemployed. Based on employment histories of 20 million German workers, we find that workers often cope with their displacement by moving to different regions and industries. However, which of these coping strategies is chosen depends on the local industry mix. A large local presence of predisplacement or related industries strongly reduces the rate at which workers leave the region. Moreover, our findings suggest that a large local presence of the predisplacement industry induces workers to shift search efforts toward this industry, reducing the spatial scope of search for jobs in alternative industries and vice versa.
After an era of generic support for economic development and innovation, narrowly targeted transformation policy is back on the table. Recent advances in the fields of new industrial policy and transition thinking converge on the idea that achieving structural change requires governments to take an active role in overcoming inertia. Rather than just leveraging R&D investments and setting framework conditions, policy makers are urged to participate in the development of socio-economic systems around particular technologies. Associated policy support typically involves a diverse portfolio of system-specific interventions.
The emergence of transformative policy, in this paper characterized by being selective, process-oriented and multi-instrumental, poses severe challenges to rising standards of public accountability. Evaluation methods for calculating the ‘bang for the buck’ of R&D-leveraging measures are ill-suited when policy mixes are supposed to enact economic transformation. We argue that, in order to see if aptly chosen policy design is bringing about actual change, assessments should gauge policy contributions to building up technological innovation systems (TIS). The TIS-literature provides a concrete but untapped basis for tracking how policy efforts affect conditions favoring the creation and diffusion of new economic activities. This premise leads us to introduce a scheme for structuring analyses concerned with (the links between) the organization, orientation and aggregate impact of transformative policy. We test it in a tentative assessment of the Dutch ‘Topsector approach’.
Besides facilitating continuous policy learning, our assessment scheme also serves to strengthen policy maker’s ability to legitimize the adoption of heterodox economic approaches.
This document explores Albanian aquaculture in the context of European aquaculture and compares it to neighboring countries, especially Greece. Using information from fieldwork, multiple reports by the United Nations’ Food and Agriculture Organization (FAO), and interviews with experts in government and non-government institutions, we analyze the production of European seabass and Gilthead seabream in Europe in general and in Albania in particular. Albanian cultivation of seabass and seabream has increased sevenfold since production started in the early 2000’s, but it represented only 0.38% of European aquaculture of these two species in 2013. Albania has significantly lower productivity than its neighbors, especially Greece, the dominant actor in the market. The analysis indicates that Albania’s lower productivity is caused by: (i) high costs of cages, fingerlings, and feed; which are all imported; (ii) lack of a formal fish market; and (iii) lack of clarity in the regulation. The document concludes by offering recommendations to get over these impediments for growth including reducing tariffs; encouraging national production of cages, fingerlings, and feed through investment in research; offering more and better financing options for cage acquisition; improving quality controls; establishing a national fish market; and passing the Aquaculture Law to bring clarity to the sector regulation.
The literature on Dutch disease is extensive when it comes to documenting the negative impacts of natural resource exports on non-resource tradable goods as an aggregate. Little has been said on the impact of natural resources on non-resource export concentration, either from a broad perspective or at the product level.
We explore this relationship using a variety of non-resource export concentration indexes for the period 1985 - 2010. We find significant evidence indicating that countries with high share of natural resources in exports tend to have less diversified non-resource export baskets.
Furthermore, using highly disaggregated data at the product level we study what type of products are more likely to thrive or suffer in resource rich countries. We find that capital intensive goods tend to have larger shares on the non-resource export basket when natural resources are high.
We also find that homogeneous goods make for a larger share of the non-resource export basket the lower their technological sophistication. For differentiated goods the pattern is reversed: they tend to make for a larger share of the non-resource export basket, the higher they are in the technology scale.
Desde la revolución zapatista de enero de 1994, Chiapas ha recibido una enorme cantidad de recursos del gobierno federal. Las brechas en años de escolaridad entre Chiapas y el resto de México se han reducido, y se han realizado numerosas inversiones que han mejorado la infraestructura vial, puertos y aeropuertos. Sin embargo, la brecha que separa a Chiapas del resto de México se ha venido ampliando sostenidamente. Un equipo multidisciplinario de doce expertos se ha dedicado a estudiar diferentes aspectos de la dinámica productiva, política y social de Chiapas. De allí han surgido cinco documentos base: Diagnóstico institucional, Complejidad económica, Diagnóstico de crecimiento, Perfil de pobreza y un piloto de diálogo productivo realizado en una comunidad indígena de Chiapas. Este reporte resume los principales hallazgos surgidos del conjunto de investigaciones y articula sus correspondientes recomendaciones de política.
Nuestra hipótesis es que Chiapas se encuentra en una trampa de baja productividad. Los métodos de producción moderna, estrechamente ligados al proceso de crecimiento y desarrollo, requieren de un conjunto de insumos complementarios que están ausentes en la mayor parte del territorio de Chiapas. Así, no existen incentivos para adquirir nuevos conocimientos que podrían ser utilizados en industrias que no existen. Esta incapacidad para resolver los problemas de coordinación y proveer los insumos requeridos por la producción moderna ha hecho que se desperdicie una buena parte de la inversión social que se ha volcado sobre la entidad.
Para superar el dilema actual y encender la chispa del crecimiento, Chiapas necesita resolver sus problemas de coordinación, conectividad, y promover gradualmente una mayor complejidad. Nuestras recomendaciones se basan en el aprovechamiento de las aglomeraciones de conocimientos que ya existen en los principales centros urbanos de Chiapas, para abordar nuevos sectores productivos de mayor valor agregado y complejidad. Para superar este reto, es necesario crear una estructura público-privada que resuelva de forma iterativa los problemas de coordinación y de provisión de bienes públicos que requieren estos sectores de alto potencial. Los sistemas de transporte público y la política de vivienda son mecanismos para integrar a la población aledaña a los centros urbanos a la nueva dinámica productiva. Zonas económicas especiales o agro-parques industriales pueden ser herramientas para promover la productividad y el crecimiento en lugares en donde hemos detectado que la disponibilidad de mano de obra barata y problemas de apropriabilidad son los principales cuellos de botella.
Large international differences in the price of labor can be sustained by differences between workers, or by natural and policy barriers to worker mobility. We use migrant selection theory and evidence to place lower bounds on the ad valorem equivalent of labor mobility barriers to the United States, with unique nationally-representative microdata on both U.S. immigrant workers and workers in their 42 home countries. The average price equivalent of migration barriers in this setting, for low-skill males, is greater than $13,700 per worker per year. Natural and policy barriers may each create annual global losses of trillions of dollars.
For decades, migration economics has stressed the effects of migration restrictions on income distribution in the host country. Recently the literature has taken a new direction by estimating the costs of migration restrictions to global economic efficiency. In contrast, a new strand of research posits that migration restrictions could be not only desirably redistributive, but in fact globally efficient. This is the new economic case for migration restrictions. The case rests on the possibility that without tight restrictions on migration, migrants from poor countries could transmit low productivity (“A” or Total Factor Productivity) to rich countries—offsetting efficiency gains from the spatial reallocation of labor from low to high-productivity places. We provide a novel assessment, proposing a simple model of dynamically efficient migration under productivity transmission and calibrating it with new macro and micro data. In this model, the case for efficiency-enhancing migration barriers rests on three parameters: transmission, the degree to which origin-country total factor productivity is embodied in migrants; assimilation, the degree to which migrants’ productivity determinants become like natives’ over time in the host country; and congestion, the degree to which transmission and assimilation change at higher migrant stocks. On current evidence about the magnitudes of these parameters, dynamically efficient policy would not imply open borders but would imply relaxations on current restrictions. That is, the new efficiency case for some migration restrictions is empirically a case against the stringency of current restrictions.
Is labor mobility important in technological diffusion? We address this question by asking how plants assemble their workforce if they are industry pioneers in a location. By definition, these plants cannot hire local workers with industry experience. Using German social-security data, we find that such plants recruit workers from related industries from more distant regions and local workers from less-related industries. We also show that pioneers leverage a low-cost advantage in unskilled labor to compete with plants that are located in areas where the industry is more prevalent. Finally, whereas research on German reunification has often focused on the effects of east-west migration, we show that the opposite migration facilitated the industrial diversification of eastern Germany by giving access to experienced workers from western Germany.
In the wake of the financial crisis and the Great Recession, economics seems anything but a science. In this sharp, masterfully argued book, Dani Rodrik, a leading critic from within, takes a close look at economics to examine when it falls short and when it works, to give a surprisingly upbeat account of the discipline.
Drawing on the history of the field and his deep experience as a practitioner, Rodrik argues that economics can be a powerful tool that improves the world—but only when economists abandon universal theories and focus on getting the context right. Economics Rules argues that the discipline's much-derided mathematical models are its true strength. Models are the tools that make economics a science.
Too often, however, economists mistake a model for the model that applies everywhere and at all times. In six chapters that trace his discipline from Adam Smith to present-day work on globalization, Rodrik shows how diverse situations call for different models. Each model tells a partial story about how the world works. These stories offer wide-ranging, and sometimes contradictory, lessons—just as children’s fables offer diverse morals.
Whether the question concerns the rise of global inequality, the consequences of free trade, or the value of deficit spending, Rodrik explains how using the right models can deliver valuable new insights about social reality and public policy. Beyond the science, economics requires the craft to apply suitable models to the context.
The 2008 collapse of Lehman Brothers challenged many economists' deepest assumptions about free markets. Rodrik reveals that economists' model toolkit is much richer than these free-market models. With pragmatic model selection, economists can develop successful antipoverty programs in Mexico, growth strategies in Africa, and intelligent remedies for domestic inequality.
At once a forceful critique and defense of the discipline, Economics Rules charts a path toward a more humble but more effective science.
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).
Venezuela is an oil-dependent economy subject to large exogenous shocks, with a rigid labor market. These features go straight at the heart of two weaknesses of real business cycle (RBC) theory widely reported in the literature: Neither shocks are volatile enough nor real salaries are sufficiently flexible as required by the RBC framework to replicate the behavior of the economy. We calibrate a basic RBC model and compare a set of relevant statistics from RBC-simulated time series with actual data for Venezuela and the benchmark case of the United States (1950-2008). In spite of Venezuela being one of the most heavily intervened economies in the world, RBC-simulated series provide a surprisingly good fit when it comes to the non-oil sector of the economy, and in particular for labor markets. Large restrictions on dismissal and widespread minimum (nominal) wage put all the burden of adjustment on prices; which translate into highly volatile real wages.
The U.S. is home to more than 200,000 ethnic Albanians, about half of whom are emigrants from the Republic of Albania. Despite the significant Albanian population in the U.S., official trade of Albanian goods in the U.S. almost does not exist.
We surveyed about 200 Albanian-Americans and several stores offering goods imported from the Balkan region of Europe in three U.S. metropolitan areas with large Albanian population in order to study their purchasing habits. We found that the willingness to purchase products from the region of origin is certainly not matched by an adequate supply. The stores which offer such products are few, often hard to reach and offer limited supplies of a small variety of commodities. In the study, we recommend steps to strengthen the market for nostalgic good through continued market research, trade-related technical assistance, diaspora-donor partnerships for nostalgic trade development and trade fairs.
In an attempt to recuperate its dysfunctional electricity distribution system, Albania privatized its sole electricity distribution company in 2009. Disappointed with the results of the privatization, just five years later, the State of Albania renationalized the company.
The case study “Revitalizing the Albanian Electricity Sector” analyzes the key sources of inefficiencies in the electricity distribution sector in Albania and the structural problems of the current state-owned company. It explains how the tariff setting and the failed infrastructural investments triggered a chain effect of financial instability which spilled beyond the limits of the electricity sector and discusses possible reforms to the sector.
In this document we describe the size of the Poblacion Flotante of Bogota (D.C.). The Poblacion Flotante is composed by people who live outside Bogota (D.C.), but who rely on the city for performing their job. We estimate the Poblacion Flotante impact relying on a new data source provided by telecommunications operators in Colombia, which enables us to estimate how many people commute daily from every municipality of Colombia to a specic area of Bogota (D.C.). We estimate that the size of the Poblacion Flotante could represent a 5.4% increase of Bogota (D.C.)'s population. During weekdays, the commuters tend to visit the city center more.