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.
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.
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.
When workers are displaced from their jobs in mass layoffs or firm closures, they experience lasting adverse labor market consequences. We study how these consequences vary with the amount of skill mismatch that workers experience when returning to the labor market. Using novel measures of skill redundancy and skill shortage, we analyze individuals’ work histories in Germany between 1975 and 2010. We estimate difference-in-differences models, using a sample in which we match displaced workers to statistically similar non-displaced workers. We find that displacements increase the probability of occupational change eleven fold, and that the type of skill mismatch after displacement is strongly associated with the magnitude of post-displacement earnings losses. Whereas skill shortages are associated with relatively quick returns to the counterfactual earnings trajectories that displaced workers would have experienced absent displacement, skill redundancy sets displaced workers on paths with permanently lower earnings.
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.
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.
This paper presents a descriptive analysis of wage inequality in Colombia by cities and industries and attempts to evaluate the impact of the inequality of industries on inequality of cities. Using the 2010-2014 Colombian Social Security data, we calculate the gini coefficient for cities and industries and draw comparisons between their distributions. Our results show that while cities are unequal in similar ways, industries differ widely on how unequal they can be with ginis. Moreover, industrial structure plays a significant role to determine city inequality. Industrial framework proves to be a key element in this area for researches and policymakers.
The Growth Lab at Harvard's Center for International Development, the Los Grobo Foundation, and the School of Senior Management and Business Administration of Barcelona (EADA), with the support of the Ministry of Finance and Public Credit of the Government of Mexico, have partnered to conduct an exploration of the productive attitudes and skills of the indigenous communities of Chiapas. Given the high degree of dispersion of these communities, we have decided to select a pilot location, relatively close to urban areas, and implement the methodology of the Empower Communities program developed by the Los Grobo Foundation there.
Our final objective is to increase the understanding of the social, political, cultural and productive complexity of the indigenous communities of Chiapas, using as a vehicle a methodology that promotes participatory diagnosis, identifies capacities and resources, in the process of designing a collective development plan. territorial. Through the pilot implementation of Empower Communities, the team seeks to create a knowledge base that allows us to strengthen our capacity to design and implement development policies in indigenous communities with a productive aspect, as a complement to the social assistance policies that predominate in the place.
Who introduces structural change in regional economies: Entrepreneurs or existing firms? And do local or non‐local founders of establishments create most novelty in a region? Using matched employer/employee data for the whole Swedish workforce, we determine how unrelated and therefore how novel the activities of different establishments are to a region’s industry mix. Up‐ and downsizing establishments cause large shifts in the local industry structure, but these shifts only occasionally require an expansion of local capabilities because the new activities are often related to existing local activities. Indeed, these incumbents tend to align their production with the local economy, deepening the region’s specialization. In contrast, structural change mostly originates via new establishments, especially those with non‐local roots. Moreover, although entrepreneurs start businesses more often in activities unrelated to the existing regional economy, new establishments founded by existing firms survive in such activities more often, inducing longer‐lasting changes in the region.
This paper explores the role that uncertainty plays in the emergence of new products or services for export in developing countries. Using a comparative case study method, I explore the degree to which those entrepreneurs who discovered new export activities faced uncertainty, and what the nature of this uncertainty was. I then document how this uncertainty, when present, was resolved, and how this affected subsequent diffusion of the newly discovered activity. The cases suggest two important dimensions of uncertainty in the emergence of new export activities: productivity characteristics and demand characteristics. A new activity could feature one, both, or neither types of uncertainty. The reasons for lower inherent uncertainty in these cases suggest a new theory of product similarity that is heterogeneous, multi-dimensional, and operating at a highly disaggregated level. Furthermore, the degree of uncertainty has implications for the expected ‘triggers’ of discovery, and these are born out in the cases. Finally, when uncertainty was present, its resolution often provided significant benefits to subsequent entrants, and the manner in which high uncertainty was overcome suggests potential avenues for policy.