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.
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.
Venezuela’s business environment is systematically evaluated as one of the worst in the world. Producing and investing in the country imposes costs and risks arising from macroeconomic instability. Beyond the problems of inflation, fiscal deficit and trade balance; firms and entrepreneurs also face enormous difficulties and discouragement going from the uncertainty about property rights to lack of electricity. To identify binding microeconomic constraints for investment in Venezuela, we reviewed international rankings and experiences about key elements of the business environment and conducted interviews with members of guilds and managers at large companies in the country. We find that the most biding constraints to investment are within the functioning of institutions, including weak property rights, and arbitrary, unbalanced and unpredictable enforcement of the law. Also binding is the flawed functioning of markets, including access to inputs and price controls.
We document the heterogeneity across sectors in the impact labor and input-output links have on industry agglomeration. Exploiting the available degrees of freedom in coagglomeration patterns, we estimate the industry-specic benefits of sharing labor needs and supply links with local firms. On aggregate, coagglomeration patterns of services are at least as strongly driven by input-output linkages as those of manufacturing, whereas labor linkages are much more potent drivers of coagglomeration in services than in manufacturing. Moreover, the degree to which labor and input-output linkages are reflected in an industry's coagglomeration patterns is relevant for predicting patterns of city-industry employment growth.
Even before the oil price crisis began in 2014, progress in reducing poverty in Venezuela had ceased and official figures showed that. According to the INE, between 2008 and 2013, the percentage of the population living in poverty remained almost the same, going from 33.1% to 34.2%.
Estas son las últimas cifras oficiales de pobreza de ingreso que disponemos ya que la última contabilización oficial de porcentaje de población en situación de pobreza es la del segundo semestre de 2013. A partir de ese momento la descripción social de la pobreza en Venezuela ha dependido de estudios independientes realizados entre otros, por un consorcio de varias universidades del país que dan cuenta de la evolución de la pobreza entre 2014 y 2015 (ENCOVI, 2014 y 2015), años donde se precipitaron los precios del petróleo hasta un tercio de lo que llegaron a ser durante 2008 acelerando un proceso de deterioro en los indicadores de desempeño económico y bienestar del hogar.
Según estas fuentes independientes de información la pobreza de ingresos en Venezuela habría llegado hasta un 55% en 2014 y 76% en 2015. Cifras que por sí solas hablan de la necesidad diseñar un plan de reformas económicas y sociales para hacerle frente al impacto social de la caída de los precios del petróleo, así como al conjunto de factores, más allá de los precios del crudo, que han llevado al país a tres años continuos de recesión y aumento de la pobreza.
En atención a lo anterior, el presente trabajo se enmarca dentro del conjunto de ejercicios de investigación que son necesarios para poder diseñar un programa de estabilización económica y su correspondiente plan de protección social. En ese sentido, en lo que sigue trataremos de dimensionar el número de familias que necesitarían formar parte de este potencial plan de protección social.
Para ello nos valdremos como fuente de información de la ENCOVI 2014 y 2015, encuestas desde las cuales no sólo tenemos información para contabilizar los hogares e individuos en estado de necesidad, sino además las coberturas probables de los programas sociales (Misiones) que actualmente implementa el gobierno de Venezuela, para de esta forma estimar; en primer lugar, las familias en situación de pobreza que reciben beneficios sociales; en segundo lugar las que estando en esa condición de pobreza no los reciben y; por último, y con miras a la reforma de los programas y la introducción de elementos de progresividad distributiva, los beneficiarios que aún sin ser población objetivo, por no estar en situación de pobreza, son receptores de transferencias, pensiones o becas por parte del Estado.
Adicionalmente a lo anterior, las políticas de control de cambio y la regulación de los precios, aunado a los problemas de abastecimiento, han hecho que los precios de los bienes a los que tienen acceso los distintos grupos sociales varían según si se adquieren en los mercados controlados o en los informales. Estos diferenciales de precios son muy importantes y están generando impactos distributivos difíciles de estimar, pero fundamentales para entender las necesidades de protección social que requieren los hogares para cubrir la canasta de productos básicos.
Es por ello que este trabajo también se propone describir a muy alto nivel los problemas distributivos generados por los diferenciales de precios. Si bien probablemente no sea posible llegar a conclusiones definitivas, al menos plantearemos lo relevante del tema para entender como la escasez de productos y las regulaciones de precios han introducido un conjunto de distorsiones en los precios y en el acceso a los bienes esenciales y presentaremos algunos de los dilemas y preguntas que estas distorsiones generan al momento de analizar la capacidad de satisfacer necesidades básicas en Venezuela.
 En Agosto de 2016, el Instituto Nacional de Estadística (INE) publicó estadísticas sobre el porcentaje de hogares en situación de pobreza por primera vez desde el año 2013. La serie fue actualizada para incluir los datos de 2014 y el primer semestre de 2015. Para el primer semestre de 2014 la cifra de hogares en situación de pobreza por ingreso alcanzó 29,5%, para el segundo semestre de ese año llegó a 32,6% y finalmente para el primer semestre de 2015 33,1% de los hogares se encontraban en situación de pobreza por ingresos. Sin embargo, el INE no ha hecho públicas ni el valor de Canasta Alimentaria Normativa para 2015, ni las Encuestas de Hogares que sustentan este cálculo ni las cifras de pobreza por ingreso como porcentaje de la población.
 We refer to the National Survey of Living Conditions (ENCOVI) conducted in 2014 and 2015 by the Andrés Bello Catholic University, the Simón Bolívar University and the Central de Venezuela. The results and report of the 2014 survey can be seen in: Zuñiga, Genny and González, Marino. A look at the social situation of the Venezuelan population. National Survey of Living Conditions. 2014 . IIES-UCAB. Caracas. 2015, The report of the 2015 survey is being prepared but the database is available at the Institute of Economic and Social Research of the UCAB.
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.
Economists have long discussed the negative effect of Dutch disease episodes on the non-resource tradable sector as a whole, but little has been said on its impact on the composition of the non-resource export sector. This paper fills this gap by exploring to what extent concentration of a country’s non-resource export basket is determined by their exports of natural resources. We present a theoretical framework that shows how upward pressure in wages caused by a resource windfall results in higher export concentration. We then document two robust empirical findings consistent with the theory. First, using data on discovery of oil and gas fields and of commodity prices as sources of exogenous variation, we find that countries with larger shares of natural resources in exports have more concentrated non-resource export baskets. Second, we find capital-intensive exports tend to dominate the export basket of countries prone to Dutch disease episodes.
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.
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.
An increasing number of studies evidence large and persistent earning losses by displaced workers. We study whether these losses can partly be attributed to the skill mismatch that arises when workers’ human capital is underutilized at the new job. We develop a new method of measuring skill mismatch that accounts for asymmetries in the transferability of human capital between occupations, and link these measures to exceptionally rich German administrative data on individuals’ work histories. We find that displacement increases the probability of occupational switching and skill mismatch, primarily because displaced workers often move to less skill-demanding occupations. Event-study analyses show that these downskilled switchers suffer substantially larger displacement costs than occupational stayers. Workers moving to more skill-demanding occupations have similar earning losses as stayers, and do not experience any displacement costs conditional on being employed