This note collects evidence related to possible constraints to economic growth, and their relation with GoSL’s industrial zone development agenda. We find that new zones are especially well-suited to help address Sri Lanka’s lack of industrial land and high policy uncertainty, both of which may be holding back growth. Less clear, however, are zones’ impact on Sri Lanka’s limited transport links beyond the Western Province. Finally, partnering with well-connected zone management companies may also help create opportunities to connect with firms in new, non-traditional sectors.
International aid is a complex system: it involves different issues, countries, and donors. In this paper, we use web crawling to collect information about the activities of international aid organizations on different health-related topics and network analysis to depict this complex system of relationships among organizations. By systematically collecting co-occurrences of issues, countries, and organization names from more than a hundred websites, we are able to construct multilayer networks describing, for instance, which issues are related to each other according to which organizations. Our results show that there is a surprising amount of homophily among organizations: organizations of the same type (multilateral, bilateral, private donors, etc.) tend to be co-cited in groups. We also create a taxonomy of issues that are generally mentioned together. Finally, we perform simulations, showing that messages originating from different organizations in the international aid community can have a different reach.
Setting a country’s structural growth rate on a higher path, i.e. sparking and sustaining a growth acceleration can have quantitatively huge implications for national income and, more broadly, for people’s wellbeing. We develop a novel statistical framework to identify systematically the set of binding constraints that were unlocked before the 135 growth acceleration episodes that took place between 1962 and 2002 worldwide. We employ this information to characterise the acceleration process, which tends to be preceded by a deep recession and major economic policy changes. Once we combined this information with a set of counterfactual analyses, we find however that successful acceleration strategies should not contain off-the-shelf approaches or necessarily all-encompassing “shock therapy” solutions. On the other hand, they call for a careful tailoring to local conditions. Richer countries tend to experience fewer accelerations, but once these have been ignited, they are better positioned to make the most out of them. Despite standard growth determinants doing a fairly good job at characterising successful accelerations, we note how take-offs remain extremely hard to engineer with a high degree of certainty.
Using a large individual-level survey spanning several years and more than 150 countries, we examine the importance of social networks in influencing individuals' intention to migrate internationally and locally. We distinguish close social networks (composed of friends and family) abroad and at the current location, and broad social networks (composed of same-country residents with intention to migrate, either internationally or locally). We find that social networks abroad are the most important driving forces of international migration intentions, with close and broad networks jointly explaining about 37% of variation in the probability intentions. Social networks are found to be more important factors driving migration intentions than work-related aspects or wealth (wealth accounts for less than 3% of the variation). In addition, we nd that having stronger close social networks at home has the opposite effect by reducing the likelihood of migration intentions, both internationally and locally.
Throughout 2016, CID conducted a growth diagnostic analysis for Sri Lanka in collaboration with the Government of Sri Lanka, led by the Prime Minister’s Policy Development Office (PDO), and the Millennium Challenge Corporation (MCC). This presentation report aggregates collaborative quantitative and qualitative analysis undertaken by the research team. This analysis was originally provided to the Government of Sri Lanka in April 2017 in order to make available a record of the detailed technical work and CID’s interpretations of the evidence. A written executive summary is provided here as a complement to the detailed presentation report. Both the report and the executive summary are structured as follows. First, the analysis identifies Sri Lanka’s growth problem. It then presents evidence from diagnostic tests to identify what constraints are most responsible for this problem. Finally, it provides a summary of what constraints CID interprets as most binding and suggests a “growth syndrome” that underlies the set of binding constraints.
In brief, this growth diagnostic analysis shows that economic growth in Sri Lanka is constrained by the weak growth of exports, particularly from new sectors. Compared to other countries in the region, Sri Lanka has seen virtually no diversification of exports over the last 25 years, especially in manufactured goods linked through FDI-driven, global value chains. We found several key causes behind this lack of diversified exports and FDI: Sri Lanka’s ineffective land-use governance, underdeveloped industrial and transportation infrastructure, and a very high level of policy uncertainty, particularly in tax and trade policy. We believe that these issues trace back to an underlying problem of severe fragmentation in governance, with a critical lack of coordination between ministries and agencies with overlapping responsibilities and decision-making authority.
The fact that firms benefit from close proximity to other firms with which they can exchange inputs, skilled labor or know-how helps explain why many industrial clusters are so successful. Studying the evolution of coagglomeration patterns, we show that which type of agglomeration benefits firms has drastically changed over the course of a century and differs markedly across industries. Whereas, at the beginning of the twentieth century, industries tended to colocate with their value chain partners, in more recent decades the importance of this channels has declined and colocation seems to be driven more by similarities industries' skill requirements. By calculating industry-specific Marshallian agglomeration forces, we are able to show that, nowadays, skill-sharing is the most salient motive in location choices of services, whereas value chain linkages still explain much of the colocation patterns in manufacturing. Moreover, the estimated degrees to which labor and input-output linkages are reflected in an industry's coagglomeration patterns help improve predictions of city-industry employment growth.
Macroeconomic adjustment in the euro area periphery was more recessionary than pre-crisis imbalances would have warranted. To make this claim, this paper uses a Propensity Score Matching Model to produce counterfactuals for the Eurozone crisis countries (Greece, Portugal, Ireland, Cyprus, Spain) based on over 200 past macroeconomic adjustment episodes between 1960-2010 worldwide. At its trough, between 2010 and 2015 per capita GDP had contracted on average 11 percentage points more in the Eurozone periphery than in the standard counterfactual scenario. These results are not dictated by any specific country experience, are robust to a battery of alternative counterfactual definitions, and stand confirmed when using a parametric dynamic panel regression model to account more thoroughly for the business cycle. Zooming in on the potential causes, the lack of an independent monetary policy, while having contributed to a deeper recession, does not fully explain the Eurozone’s specificity, which is instead to be identified in a sharper-than-expected contraction in investment and fiscal austerity due to high funding costs. Reading through the overall findings, there are reasons to believe that an incomplete Eurozone institutional setup contributed to aggravate the crisis through higher uncertainty.
The recent economic depression in Greece hit the population of Albanian migrants in Greece particularly hard, spurring a wave of return migration that increased the Albanian labor force by 5% in less than four years, between 2011 and 2014. We study how this return migration affected the employment chances and earnings of Albanians who never migrated. We find positive effects on the wages of low-skilled non-migrants and overall positive effects on employment. The gains partially offset the sharp drop in remittances in the observed period. An important part of the employment gains are concentrated in the agricultural sector, where most return migrants engage in self-employment and entrepreneurship. Businesses run by return migrants seem to pull Albanians from non-participation, unemployment and subsistence agriculture into commercial agriculture.
Who introduces structural change in regional economies: Entrepreneurs or existing firms? And do local or nonlocal establishment founders create most novelty in a region? We develop a theoretical framework that focuses on the roles different agents play in regional transformation. We then apply this framework, using Swedish matched employer–employee data, to determine how novel the activities of new establishments are to a region. Incumbents mainly reinforce a region’s current specialization: incumbent’s growth, decline, and industry switching further align them with the rest of the local economy. The unrelated diversification required for structural change mostly originates via new establishments, especially via those with nonlocal roots. Interestingly, although entrepreneurs often introduce novel activities to a local economy, when they do so, their ventures have higher failure rates compared to new subsidiaries of existing firms. Consequently, new subsidiaries manage to create longer-lasting change in regions.
Although Venezuela’s experience since the 1980s would seem to make it a classic example of the resource curse, that perspective fails to explain the country’s impressive economic, social and institutional performance—including healthy public debate—during the first five decades after oil was first produced on a large scale. This chapter takes a long view of the Venezuelan experience and argues that this initial performance was lengthy and positive but fragile, given the incapacity of the country’s institutions to adapt to the different environment that developed afterwards, characterized by high oil price volatility and significant and sudden declines in oil revenues. The prolonged initial period of equilibrium became a curse of sorts. Lacking adaptive efficiency, political institutions were forced to rely increasingly on maintaining an illusion of harmony, and as faltering performance became evident, Venezuelans began questioning the model and its hegemonic arrangements. The scope and magnitude of the economic, social and institutional devastation that followed were such that public debate became one the first casualties. One of the main problems in contemporary Venezuela is the polarization of politics. This makes it difficult for the country’s population to arrive at reasonable solutions through public discussion.
Networks are powerful instruments to study complex phenomena, but they become hard to analyze in data that contain noise. Network backbones provide a tool to extract the latent structure from noisy networks by pruning non-salient edges. We describe a new approach to extract such backbones. We assume that edge weights are drawn from a binomial distribution, and estimate the error-variance in edge weights using a Bayesian framework. Our approach uses a more realistic null model for the edge weight creation process than prior work. In particular, it simultaneously considers the propensity of nodes to send and receive connections, whereas previous approaches only considered nodes as emitters of edges. We test our model with real world networks of different types (flows, stocks, cooccurrences, directed, undirected) and show that our Noise-Corrected approach returns backbones that outperform other approaches on a number of criteria. Our approach is scalable, able to deal with networks with millions of edges.
How can the productive capabilities of each municipality be unleashed taking into consideration the resources available to them? A first pass at this ambitious question begins by understanding the set of outputs a municipality is capable of producing. We answer this by discovering relationships between agricultural inputs and outputs and ask a relatively simpler question: how similar are agricultural outputs in terms of the inputs they use? Answering this question is made difficult by the fact that most UPAs cultivate just one or two crops. This may be a rational response to economies of scale. Given a plot of land and inputs, it may be easier to cultivate one crop on the entire land than plant a number of them with each requiring a different care regimen3. It may be that the inputs available only allow for a few types of crops.
In this paper, we use the rural census data from Colombia to build an agricultural product space capturing the similarities between outputs. We test the predictive power of the product space and use this to answer the question above. In section 2, we discuss the various sources of data and how they are merged, cleaned, and transformed before processing. In section 3, we look at some high level features of the dataset and how inputs, outputs, and land use are related. In section 4, we explore the mechanics of diversification.
We construct similarity and density matrices and show that they do indeed predict what a municipality produces. Finally, in section 5 we use Machine Learning algorithms and the density matrices to predict municipalities that are best suited to produce a given output. Further, we identify "missing" municipalitiesoutput pairs i.e. municipalities that should be producing a given output at high yield but currently are not. Finally, we summarize our findings and suggest areas for further work.
The central question we will explore in this document is: Can we anticipate the opportunities that Colombian cities have to export specific products based on their existing productive capabilities?
In the following pages, we report a collection of results, analyses, and advances in which we assess how industry-related capabilities affect export possibilities. Our final goal will be to create a single measure that synthesizes all the knowledge and existing information about the productive capabilities of each city, both “horizontal” and “vertical”, and that quantifies how competitive a city can be if it aims at exporting a given product it does not yet export.
This document is broken in two main efforts: First, we want to understand the “mechanics” of diversification processes. And second, we want to be able to provide recommendations of products that are not produced in cities, but should be. The first effort requires a multitude of analyses, each trying to describe the characteristics of firms, of cities, and of the mechanisms that expand the export baskets of places. The second effort requires the development of a statistical model that is accurate when predicting the appearances of products in cities. These two efforts, explaining and predicting, are complementary, but different.
Explanations that lack the power of accurately predicting the future are useless in practice; predictions of phenomena for which we lack understanding are dangerous. But together they provide a unified story that can inform policy decisions.
Immigration and Economic Transformation: A Concept Note
Ljubica Nedelkoska, Tim O’Brien, Ermal Frasheri, Daniel Stock
In May 2017, CID prepared a concept note that described the connection between immigration and knowhow transfer internationally and profiled the current state of low immigration levels and immigration policy issues in Sri Lanka. The note identifies immigration policy reform as an important area of opportunity for unleashing higher levels of entrepreneurship and the introduction of new knowhow for economic diversification in Sri Lanka, but stops short of providing specific recommendations. Instead, the note lays out broad ideas for making immigration policy more flexible and encourages the Government of Sri Lanka to activate a cross-government policy team that is capable of developing reforms that meet Sri Lanka’s particular needs.
A Comparative View on of Immigration Frameworks in Asia: Enhancing the Flow of Knowledge through Migration
Ermal Frasheri, Ljubica Nedelkoska, Sehar Noor, Tim O’Brien
Later in 2017, at the request of a policy team of the Government of Sri Lanka, CID conducted research to compare immigration policy frameworks in other countries in Asia to understand promising policy options for Sri Lanka. Our resulting research note focuses on Indonesia, Vietnam, Thailand, Malaysia, Hong Kong, and Singapore. We find that the immigration policies of the six countries vary across numerous dimensions as each country prioritizes attracting the talents, skills and resources it needs from abroad in different ways. These variations provide a range of examples that may be relevant to decision-makers in Sri Lanka. Additionally, we find an emerging pattern among the six countries where more developed economies tend to have more elaborate immigration systems and target a more diverse set of people. By looking at available data, we also confirm that more elaborate immigration systems are closely associated with more actual immigration, higher presence of foreign firms, and higher levels of foreign direct investment (FDI) among this group of countries. Based on the comparative analysis, together with the issues identified by the Department of Immigration and Emigration’s Gap Analysis, it is possible to identify a number of principles around which future immigration reform in Sri Lanka should be organized.
In this study, we analyzed Albania’s industrial exports using the frameworks of the Product Space and Economic Complexity in order to determine which products Albania could diversify into in the near future. In particular, we identified groups of products that are technologically close to those which Albania already exports and which at the same time are technologically more sophisticated (more complex) than Albania’s average exports. This analysis does not suggest that products that do not fulfill the criteria of technological proximity and product complexity should not be invested in. However, it suggests that some products may have higher chances of succeeding in Albania because of its existing technological capabilities, while also bringing about diversification towards more complex, higher value-added production.
We find that the top two sectors that satisfy the criteria of being in close proximity to the existing technological capabilities in Albania, while also having relatively highly complex products, are Plastics/Rubbers and Agriculture/Foodstuffs. Within each of these sectors, we list more specific products that make for good candidates for diversification.
Using German social security data, we study inter-industry labor mobility to assess how industry-specific human capital is and to determine which industries have similar human capital requirements. We find that inter-industry labor flows are highly concentrated in just a handful of industry pairs. Consequently, labor flows connect industries in a sparse network. We interpret this network as an expression of industries similarities in human capital requirements, or skill relatedness. This skill-relatedness network is stable over time, similar for different types of workers and independent of whether workers switch jobs locally or over larger distances. Moreover, in an application to regional diversification and local industry growth, skill relatedness proves to be more predictive than colocation or value chain relations. To facilitate future research, we make detailed inter-industry relatedness matrices online available.
Are the well-known facts about urbanization in the United States also true for the developing world? We compare American metropolitan areas with analogous geographic units in Brazil, China and India. Both Gibrat’s Law and Zipf’s Law seem to hold as well in Brazil as in the U.S., but China and India look quite different. In Brazil and China, the implications of the spatial equilibrium hypothesis, the central organizing idea of urban economics, are not rejected. The India data, however, repeatedly rejects tests inspired by the spatial equilibrium assumption. One hypothesis is that spatial equilibrium only emerges with economic development, as markets replace social relationships and as human capital spreads more widely. In all four countries there is strong evidence of agglomeration economies and human capital externalities. The correlation between density and earnings is stronger in both China and India than in the U.S., strongest in China. In India the gap between urban and rural wages is huge, but the correlation between city size and earnings is more modest. The cross-sectional relationship between area-level skills and both earnings and area-level growth are also stronger in the developing world than in the U.S. The forces that drive urban success seem similar in the rich and poor world, even if limited migration and difficult housing markets make it harder for a spatial equilibrium to develop.
Using a worldwide firm-level panel dataset I document a "U-shaped" relationship between productivity growth and baseline levels within each country and industry. That is, fast productivity growth is concentrated at both ends of the productivity distribution. This result serves as a potential explanation to two stylized facts documented in the economic literature: the rising productivity dispersion within narrowly defined sectors, and the increasing market share of few yet highly productive firms.
Export diversification is associated with economic growth and development. Our paper explores competing mechanisms that mediate the emergence and growth of export products based on their economic relatedness to pre-existing exports. Our innovation is to simultaneously consider supply factors like labor, sourcing and technology; as well as demand factors like industry specific customer-linkages in a global setting. We find that, while technology and workforce similarity explain emergence and growth, pre-existing downstream industries remain a robust predictor of diversification, especially for jump starting new exports in developing countries. Our global stylized fact generalizes Javorcik’s (2004) view that spillovers are more likely in backward linkages.