Faculty Working Papers

The prevalence of many urban phenomena changes systematically with population size¹. We propose a theory that unifies models of economic complexity^{2, 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.

Tourism is one of the most important economic activities in the world: for many countries it represents the single largest product in their export basket. However, it is a product difficult to chart: "exporters" of tourism do not ship it abroad, but they welcome importers inside the country. Current research uses social accounting matrices and general equilibrium models, but the standard industry classifications they use make it hard to identify which domestic industries cater to foreign visitors. In this paper, we make use of open source data and of anonymized and aggregated transaction data giving us insights about the spend behavior of foreigners inside two countries, Colombia and the Netherlands, to inform our research. With this data, we are able to describe what constitutes the tourism sector, and to map the most attractive destinations for visitors. In particular, we find that countries might observe different geographical tourists' patterns - concentration versus decentralization -; we show the importance of distance, a country's reported wealth and cultural affinity in informing tourism; and we show the potential of combining open source data and anonymized and aggregated transaction data on foreign spend patterns in gaining insight as to the evolution of tourism from one year to another.

Venezuela has one of the most abundant geological endowments in the world. Oil proven reserves are among the largest globally, even if a more conservative criterion than the one used by the current government is applied. However, these resources are qualitatively different than those of other abundant regions such as the Middle East. The large majority constitutes extra-heavy oil, which generally requires higher oil prices to be extracted profitably.

During the last decade, the Venezuelan oil industry wasted a unique opportunity to increase investment and production. At the high oil prices that prevailed, the massive oil reserves could have been monetized by rapidly increasing production with a large margin of profitability. Quite to the contrary, production steadily dropped due either to lack of investment in the new unconventional oil projects or for failing to compensate the decline of the older conventional fields. It is a tragic story of great potential with dismal performance.

A series of trends were negatively impacting the Venezuelan oil industry even before the oil price collapse in 2014. From the revenue side, although oil prices showed an increase in real terms of 120% between 2000 and 2014, the barrels that effectively generate cash for Venezuela have shown a continuous decline. This is not just because production has been declining for the most part during the last eighteen years (a trend that has gotten significantly worse during the last year), but also because of a number of developments. First, during that period, total exports have declined more rapidly than production, and recently, net exports have declined more than total exports. Consumption in the massively subsidized domestic market increased until 2013 (when it started to decline likely because of the recession in the local economy), while imports of oil products for the domestic market have increased since 2012. The domestic market not only generates negative cash-flow for the national oil company (NOC), PDVSA, but also its expansion reduced the barrels available to export. More recently, there has also been an increase in imports of light oil and naphtha as diluents for the extra-heavy oil. Second, the Venezuelan production basket has become heavier and the share of unconventional production, generally less profitable, has increased. Third, the production wholly operated by PDVSA has been falling much more rapidly, while the production share of joint-ventures increased. Fourth, a significant share of the exports to Latin America and the Caribbean is subsidized (although these exports have declined recently). Fifth, some oil exports are committed to repay debts of PDVSA and specially the Venezuelan government, limiting the actual cash flow received by the company. In particular, the government’s debt agreements with China involve a significant and increasing amount of production, although recently those agreements were restructured, allowing for a grace period with no capital amortization. From the expenditure side, PDVSA was increasingly responsible of carrying social expenditures and activities not related to the oil industry, which limited the resources for highly profitable investments. That is in addition to the increased fiscal take due to changes in the tax legislation. Also, higher investment requirements due to an increase in the equity share of PDVSA in joint venture projects, has had an impact on its cash flow.

The explanations for the underperformance of the Venezuelan oil industry basically fall into two connected categories: the multiple problems facing PDVSA; and the increase in above-ground risks for foreign investors operating in the country. The deterioration of the institutional framework, led to radical fiscal and regulatory changes, and to the nationalization of the majority of the industry. In 7 addition, the substantial over-extraction of resources from the NOC, the significant macroeconomic distortions affecting the cost structure of oil companies, and the constraints imposed by the energy infrastructure and human capital availability; have combined to produce dismal results. The massive firing of the majority of the management and technical experts from PDVSA in 2003 following the political conflict that led to a strike, has left the company with limited capabilities to operate effectively.

The recent decline in oil prices, and the changes in the international market structure, have exposed more dramatically the difficulties facing the Venezuelan oil sector, and call into question its ability to prevent a continuation of the declining trend in oil extraction. This situation becomes particularly severe if we take into account the cash flow constraints facing PDVSA, as well as its multiple operational problems, power cuts, and conflicts with oilfield services providers. These challenges are proportional to the enormous investments required to finance the projects in the Orinoco Oil Belt, where most of the reserves in Venezuela are located, and where the quality of the crude and the lack of development of the region, are just two of the many issues that need to be addressed.

Since this paper is part of a wider project to understand the macroeconomic challenges facing the country in 2016-17, it focuses narrowly on the financial problems of the oil industry in the short-term and the operational challenges that could impede its recovery in the next couple of years. Within this context, it largely analyzes the upstream operations, i.e. oil extraction, rather than the downstream, given that in the former is where the oil rents are generated and constitutes the main source of foreign exchange and fiscal revenues of Venezuela. Other areas for further research are mentioned at the end of the document.²

Official figures are used to the extent that they are publicly available. An important aspect that prevents an exhaustive evaluation of the oil sector in Venezuela is the lack of available information regarding key performance indicators affecting the cost structure of oil projects, the cash flow of PDVSA, and the fiscal contributions of the oil sector to the government, among other important variables. Thus, on occasion, estimations for variables of interest and explanations for their divergence from official figures are provided.

The paper has two main sections. The first one analyzes the issues affecting the cash flow of PDVSA, the effects of macroeconomic and fiscal variables on both revenues and costs, as well as other financial issues affecting the performance of the company. The second section discusses some of the operational challenges facing the industry and mentions areas for further research.

²For a more general overview of the recent developments of the oil sector in Venezuela see Monaldi (2015).

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.

Special Economic Zones (SEZ) have played an important role in Panama's successful growth story over the previous decade. SEZ have attracted local and foreign investment by leveraging a business-friendly environment of low transaction costs, and created many stable, well-paid jobs for Panamanians. Beyond that, SEZ shall be assessed as place-based policy by their capacity to boost structural transformations, namely attracting new skills and more complex know-how not to be found in the domestic economy.

The aim of this paper is to evaluate the three largest SEZ in Panama:

• Colon Free Zone
• Panama-Pacific
• City of Knowledge

Our results suggest that SEZ have been successful as measured by static indicators, such as foreign investment, job creation and productivity. We also find that SEZ have boosted inflows of high-skill immigrants, who are most likely generating positive knowledge spillovers on Panamanians productivity and wages. However, significant legal instruments and institutional designs are preventing Panama from taking full advantage of the skill variety hosted at the SEZ. Complex immigration processes inhibiting foreigners from transitioning out of the SEZ, a long list of restricted professions and even citizenships considered as a national security concern, are hindering the flow of knowledge, keeping the benefits coming from more complex multinational companies locked inside the gates of SEZ.

Panama has been one of the fastest growing economies in the world over the previous decade. Growth has been spearheaded by the development of a modern service sector on the activities surrounding the Canal, and non-residential construction. Large public infrastructure projects and the private provision for infrastructure demanded by the service sector, have fueled growth and created a vibrant labor market for non-skilled workers.

Two warning signals hover over Panama´s stellar performance. The construction sector has been growing for a decade at a rate that is equivalent to doubling its stock of structures every four years. The demand for non-residential construction cannot grow indefinitely at a higher rate than the rest of the economy. This feeds into the second signal: Income inequality. In spite of the minor improvements registered over the accelerated-growth spell, Panama remains amongst the world´s top five most unequal countries.

Both warning signals point out to the need of further diversifying the Panamanian economy, and promoting economic activity in the provinces so as to deconcentrate growth and make it more inclusive.

We deployed our Growth Diagnostic methodology in order to identify potential binding constraints to that process. Skilled labor, necessary to gradually diversify into more complex and high value-added activities, is relatively scarce. This scarcity manifests into large wage-premiums to foreigners across all occupations, which are particular large within more complex industries.

Major investments in education have improved indicators of schooling quantitatively, but quality remains a major concern. We find that Panama’s immigration policies are preventing skills from spilling over from their special economic zones into the rest of the economy. On top of that, the list of professions restricted to Panamanians and other constraints on skilled labor flows, are constraining even further the pool of skills. As we document here, these efforts are not helping the Panamanian workers, quite the contrary.

We also find that corruption, and to a lesser extent, red tape, are other important factors that shall be addressed in order to allow Panama to shift the gears of growth, tackle inequality and continue growing at a fast pace.

The economy of Panama has thrived for more than a decade, based on a modern service sector on the activities surrounding the Canal. Panama has inserted its economy into global value chains, providing competitive services in logistics, ship handling, financial intermediation, insurance, communication and trade. The expansion of the modern service sector required significant non-residential construction, including office buildings, commercial outlets, warehouses, and even shopping malls. Large public infrastructure projects such as the expansion of the Canal, the Metro, and Tocumen airport, have provided an additional drive and paved the road for productive diversification. But productive diversification does not spread randomly. A country diversifies towards activities that demand similar capacities than the ones already in place. Current capabilities and know-how can be recombined and redeployed into new, adjacent activities, of higher value added.

This report identifies productive capabilities already in place in Panama, as signaled by the variety and ubiquity of products and services that is already able to manufacture and provide competitively. Once there, we move on to identifying opportunities for productive diversification based on technological proximity. As a result, we provide a roadmap for potential diversification opportunities both at the national and sub-national level.

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).

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^[1]), 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^[2]) 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.^[3]

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.

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.

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.

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.

Since the Zapatista revolution of January 1994, Chiapas has received an enormous amount of resources from the federal government. The gaps in years of schooling between Chiapas and the rest of Mexico have been reduced, and numerous investments have been made that have improved road infrastructure, ports and airports. However, the gap that separates Chiapas from the rest of Mexico has been steadily widening. A multidisciplinary team of twelve experts has dedicated itself to studying different aspects of the productive, political and social dynamics of Chiapas. From there, five base documents have emerged: Institutional Diagnosis, Economic Complexity, Growth Diagnosis, Poverty Profile and a pilot of productive dialogue carried out in an indigenous community in Chiapas.

Our hypothesis is that Chiapas is in a low productivity trap. Modern production methods, closely linked to the growth and development process, require a set of complementary inputs that are absent in most of the territory of Chiapas. Thus, there are no incentives to acquire new knowledge that could be used in industries that do not exist. This inability to solve coordination problems and provide the inputs required by modern production has caused a good part of the social investment that has been poured into the entity to be wasted.

To overcome the current dilemma and ignite the spark of growth, Chiapas needs to solve its problems of coordination, connectivity, and gradually promote greater complexity. Our recommendations are based on taking advantage of the agglomerations of knowledge that already exist in the main urban centers of Chiapas, to address new productive sectors with greater added value and complexity. To overcome this challenge, it is necessary to create a public-private structure that iteratively solves the problems of coordination and provision of public goods that these high-potential sectors require. Public transport systems and housing policy are mechanisms to integrate the population surrounding urban centers to the new productive dynamics.

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.