Fellow Working Papers

A growing body of research documents that the size and growth of an industry in a place depends on how much related activity is found there. This fact is commonly referred to as the "principle of relatedness." However, there is no consensus on why we observe the principle of relatedness, how best to determine which industries are related or how this empirical regularity can help inform local industrial policy. We perform a structured search over tens of thousands of specifications to identify robust – in terms of out-of-sample predictions – ways to determine how well industries fit the local economies of US cities. To do so, we use data that allow us to derive relatedness from observing which industries co-occur in the portfolios of establishments, firms, cities and countries. Different portfolios yield different relatedness matrices, each of which help predict the size and growth of local industries. However, our specification search not only identifes ways to improve the performance of such predictions, but also reveals new facts about the principle of relatedness and important trade-offs between predictive performance and interpretability of relatedness patterns. We use these insights to deepen our theoretical understanding of what underlies path-dependent development in cities and expand existing policy frameworks that rely on inter-industry relatedness analysis.

The empirical literature on the contributions of human capital investments to economic growth shows mixed results. While evidence from OECD countries demonstrates that human capital accumulation is associated with growth accelerations, the substantial efforts of developing countries to improve access to and quality of education, as a means for skill accumulation, did not translate into higher income per capita. In this paper, we propose a framework, building on the principles of Growth Diagnostics (Hausmann, Rodrik and Velasco, 2008), to enable practitioners to determine whether human capital investments are a priority for a country’s growth strategy. We then discuss and exemplify different tests to diagnose human capital in a place, drawing on the Harvard Growth Lab’s experience in different development context, and discuss various policy options to address skill shortages.

We develop novel measures of early-career skills that are more detailed, comprehensive, and labor-market-relevant than existing skill proxies. We exploit that skill requirements of apprenticeships in Germany are codified in state-approved, nationally standardized apprenticeship plans. These plans provide more than 13,000 different skills and the exact duration of learning each skill. Following workers over their careers in administrative data, we find that cognitive, social, and digital skills acquired during apprenticeship are highly – yet differently – rewarded. We also document rising returns to digital and social skills since the 1990s, with a more moderate increase in returns to cognitive skills.

South Africa’s labor market exhibits a unique equilibrium with one of the highest unemployment rates in the world and yet a low level of informal employment. The unemployment rate has remained high and persistent over recent decades, in spite of the formal demise of the apartheid regime and subsequent transition to democracy in 1994. This paper uses a matching model of the labor market to argue that spatial considerations combined with low productivity of informal work may be responsible for such an outcome. Spatial dispersion inherited from the apartheid regime thins the labor market, creating exclusion and perpetuating spatial segregation. In most developing countries, the result would be higher employment in informal or own account employment. However, with low productivity in the informal sector, the high rate of exclusion shows itself in higher unemployment rates instead. Transportation costs and housing deregulation may become key factors in improving the working of the labor market in South Africa especially if it is not possible to raise informal productivity.

Related project: Growth Through Inclusion in South Africa

Can South Africa’s segregation policies explain, at least partially, its current poor employment outcomes? To explore this question, we study the long-term impact of the forced resettlement of around 3.5 million black South Africans from their communities to the so-called “homelands” or “Bantustans”, between 1960 and 1991. Our empirical strategy exploits the variability in the magnitude of resettlements between communities. Two main findings. First, the magnitude of outgoing internal migrations was largest for districts close to former homelands. Second, districts close to former homelands have higher rates of non-employed population in 2011. Together the evidence suggests that districts that experienced racial segregation policies most intensely, as measured by outgoing forced resettlements, have worse current employment outcomes.

Related project: Growth Through Inclusion in South Africa

This report analyzes the economic legacy of spatial exclusion in South Africa, focusing on the long-term effects of the former Bantustan policy. Through quantitative analysis, the report explores the spatial dimension of economic activity in South Africa and specifically how this particular spatial institution has continued to shape current economic outcomes, despite past and present attempts to reverse the effect. The report also identifies areas for further research and potential intervention to enable more effective economic inclusion of the former homeland areas of the country.

Related project: Accelerating Growth Through Inclusion in South Africa

The report aims to inform the government’s strategic approach towards manufacturing by analyzing the potential and limits for job creation within the sector. To meet that goal, we analyze the sector’s main features and recent trajectory through the lens of global deindustrialization and South Africa’s particular industrial dynamics. Secondly, we provide evidence of how, when, and why South Africa has deviated from the global deindustrialization trends. Lastly, we provide a policy framework to address the bottlenecks that are preventing South Africa from getting back on a better track of industrial performance.

Related project: Accelerating Growth Through Inclusion in South Africa

This report analyzes the causes and consequences of South Africa’s high rates of unemployment and the unique nature of labor market exclusion in the country. It leverages a combination of new quantitative analysis using South African datasets and international datasets for benchmarking, together with synthesis of existing literature and case studies. The goal is to: (1) characterize the challenge of labor market exclusion in South Africa, (2) identify ways in which this is similar and different to other countries, (3) understand what drives the unique challenges of the labor market in South Africa, and (4) narrow down what policy areas are most important to address the underlying drivers. This report takes a diagnostic approach to understand the causes of South Africa’s unique pattern of low informality.

Related project: Accelerating Growth Through Inclusion in South Africa

This paper explores franchising in South Africa, and its potential to help resolve the economy’s challenges of low entrepreneurship and concentrated ownership. South Africa features a large franchising sector, with half a million formal workers and a large number of small businesses owners competing directly with vertically integrated chains. Traditional franchising may not have much space for further growth as a percentage of the economy, but it can be made more inclusive with innovations in franchise finance that broaden the base of potential franchisees, as well as enforcement of consumer protections to ensure franchisee-franchisor relationships are balanced. The expansion of the franchising model to less capital-intensive business concepts and serving lower-income consumers (micro-franchising) is one area with expanding growth potential for the country, while the application of the franchising model to public services and socially driven organizations is less promising. Finally, while the franchising model is only directly applicable to particular sectors, there are features of franchising and the capabilities built up around the franchising that could be applied to other priority areas of the economy, in particular to smallholder agriculture. The success of traditional franchising shows the power of a menu of standardized proposals and contracts in a marketplace with a range of franchisors (in this case, up- and downstream agriculture corporates) offering different opportunities to potential franchisees (in this case, smallholder farming communities), along with training and technology transfer at scale.

Related project: Accelerating Growth Through Inclusion in South Africa

In this case study, we introduce a user-centered design process for developing Metroverse, a narrative visualization platform that communicates urban economic composition and growth opportunities for cities. The primary challenge in making Metroverse stems from the complexity of the underlying research and data, both of which need to be effectively communicated to a wide range of end-users with different backgrounds. To unravel the complexity of the research, and to design the platform, we followed a user-centered design process. Our design process brought together researchers, designers, and various end-users, who collectively guided the design of the narrative visualization. Engaging end-users in the early phases of the project allowed us to identify the valuable insights in the data and subsequently design effective visualizations that convey those insights. We believe findings from our process can provide a template for similar projects that require translating complex research data and methodologies into user-friendly story structures.

Watch Paper Presentation at CHI 2023: The ACM CHI Conference on Human Factors in Computing Systems

This paper presents a structural ranking of countries by their distance to frontier. The ranking is based on comparative advantage. Hence, it reveals information on the productive capabilities of countries that is fundamentally different from GDP per capita. The ranking is centered on the assumption that countries’ capabilities across products are similar to those of other countries with comparable distance to frontier. It can be micro-founded using standard trade models. The estimation strategy provides a general, non-parametric approach to uncovering a log-supermodular structure from the data, and I use it to also derive a structural ranking of products by their complexity. The underlying theory provides a flexible micro-foundation for the Economic Complexity Index (Hidalgo and Hausmann, 2009).

In the short-term, economies shift preferentially into new activities that are related to ones they currently do. Such a tendency should have implications for the nature of an economy’s long-term development as well. We explore these implications using a dynamical network model of an economy’s movement into new activities. First, we theoretically derive a pair of coordinates that summarize long-term structural change. One coordinate captures overall ability across activities, the other captures an economy’s composition. Second, we show empirically how these two measures intuitively summarize a variety of facts of long-term economic development. Third, we observe that our measures resemble complexity metrics, though our route to these metrics differs significantly from previous ones. In total, our framework represents a dynamical approach that bridges short-and long-term descriptions of structural change, and suggests how different branches of economic complexity analysis could potentially fit together in one framework.

Few countries have embraced active labor market policies to the same extent as Saudi Arabia. In the aftermath of the Arab Spring, the imperative of increasing Saudi employment became paramount. The country faced one of the highest youth unemployment rates in the world while over 80 percent of its private sector consisted of foreign labor. Since 2011, a wave of employment nationalization efforts has been mainly implemented through a comprehensive and strictly enforced industry and firm specific quota system known as Nitaqat. This paper assesses the employment gains as well as the costs and unintended consequences resulting from Nitaqat and related policies between 2011 and 2017. We find that while job nationalization policies generated significant initial gains in Saudi employment and labor force participation, the effects were heterogeneous across workers, firms and sectors. Moreover, our analysis suggests that the resulting unintended consequences far outweighed the benefits over time generating a less cost-effective and productivity inhibiting labor market composition.
 

This paper analyzes the changes in Saudi employment and unemployment between 2009 and 2018 and argues that a supply-demand skill mismatch exacerbated by insufficient job creation, and prevalent Saudi preferences and beliefs about employment underpin the high unemployment problem that coexists with low Saudi employment in the private sector in the country.

We examine how inequality and openness interact in shaping the long-run growth prospects of developing countries. To this end, we develop a Schumpeterian growth model with heterogeneous households and non-homothetic preferences for quality. We show that inequality affects growth very differently in an open economy as opposed to a closed economy: If the economy is close to the technological frontier, the positive demand effect of inequality on growth found in closed-economy models may be amplified by international competition. In countries with a larger distance to the technology frontier, however, rich households satisfy their demand for high quality via importing, and the effect of inequality on growth is smaller than in a closed economy and may even be negative. We show that this theoretical prediction holds up in the data, both when considering growth in export quality at the industry level and when considering growth in GDP per capita.