Many countries, like Sri Lanka, are trying to diversify their economies but often lack the capabilities to lead diversification programs. One of these capabilities relates to targeting new sectors to promote and pursue through a diversification policy: countries know they are ‘doomed to choose’ sectors to target,1 but lack effective capabilities to do the targeting. This paper narrates a recent (and ongoing) initiative to establish this kind of capability in Sri Lanka. The initiative adopted a Problem Driven Iterative Adaptation (PDIA) process, where a team of Sri Lankan officials worked with Harvard Center for International Development (CID) facilitators to build capabilities. The paper tells the story of this process, providing documented evidence of the progress over time and describing the thinking behind the PDIA process. It shows how a reliable targeting mechanism can emerge in a reasonably limited period, when a committed team of public officials are effectively authorized and engaged. The paper will be of particular interest to those thinking about targeting for diversification and to those interested in processes (like PDIA) which are focused on building state capability and fostering policy implementation in public contexts.
1 The term here comes from Hausmann, R. and Rodrik, D. 2006. Doomed to Choose: Industrial Policy as Predicament. Draft.
Many countries, like Sri Lanka, are trying to diversify their economies but often lack thecapabilities to lead diversification programs. One of these capabilities relates to engaging new investors—in new sectors—to bring their FDI and know-how to a new country and kick-start new sources of activity. This paper narrates a recent (and ongoing) initiative to establish this kind of capability in Sri Lanka. The initiative adopted a Problem Driven Iterative Adaptation (PDIA) process, where a team of Sri Lankan officials worked with Harvard Center for International Development (CID) facilitators to build capabilities over a six-month period. The paper tells the story of this process, providing documented evidence of the progress over time (and describing thinking behind the PDIA process as well). It shows how an investment engagement approach can emerge in a reasonably limited period, when a committed team of public officials are effectively authorized and engaged. The paper will be of particular interest to those thinking about investor engagement challenges and to those interested in processes (like PDIA) focused on building state capability and fostering policy implementation in public contexts.
Many countries, like Sri Lanka, are trying to diversify their economies but often lack thecapabilities to lead diversification programs. One of these capabilities relates to preparing the investment climate in the country. Many governments tackle this issue by trying to improve their scores on ‘Doing Business Indicators’ which measure performance on general factors affecting business globally (like how long it takes to open a business or pay taxes). Beyond these common indicators, however, investors face context specific challenges when working in countries like Sri Lanka that are not addressed in global indicators. Governments often lack the capabilities to identify and resolve such issues. This paper narrates a recent initiative to establish these capabilities in Sri Lanka. The initiative adopted a Problem Driven Iterative Adaptation (PDIA) process, where a team of Sri Lankan officials worked with Harvard Center for International Development (CID) facilitators to build capabilities over a six-month period. The paper tells the story of this process, providing documented evidence of the progress over time (and describing thinking behind the PDIA process as well). The paper will be of interest to those thinking about the challenges associated with creating a climate that is investor or business friendly and to those interested in processes (like PDIA) focused on building state capability and fostering policy implementation.
Sri Lanka has an excessively complex tariff structure that distorts the structure of the economy in important ways. It is a priority for the Government of Sri Lanka (GoSL) to rationalize the system in order to facilitate a transition to greater economic diversification, stronger export growth, and the emergence of new, higher paying jobs. Sri Lanka’s New Trade Policy makes this tariff rationalization a priority. It also recognizes that tariff rationalization should go hand in hand with new trade adjustment assistance measures to support the adjustment of firms and of people. The New Trade Policy outlines the basic contours of tariff rationalization and trade adjustment assistance measures but does not provide a detailed roadmap.
This discussion paper was prepared at the invitation of the Ministry of Development Strategies and International Trade (MoDSIT) as part of the Center for International Development’s research project on sustainable and inclusive economic growth in Sri Lanka. The aim of the paper is to study policy tools that the GoSL could use to structure trade adjustment assistance in the context of tariff rationalization. In order to accomplish this aim, we begin by outlining the type of tariff rationalization that needs to take place in order to address key constraints to growth in a way that is sensitive to both government revenue needs and political economy considerations. We stress that tariff rationalization must be approached in a holistic way that treats the various tariffs and para-tariffs as interrelated, rather than an approach that attempts to address one part of the system at a time. A holistic approach would provide many degrees of freedom to solve the underlying problems in the system while increasing revenues and potentially generating strong public support. Critically, a holistic approach would allow for a single tariff rationalization plan to be phased in over a period of years in a predictable way, whereas attempts to rationalize the system one part at a time would lead to extreme uncertainty.
With the principles of smart tariff rationalization in place, we draw upon international lessons and Sri Lanka’s own institutional capabilities to recommend a two-tiered approach to helping industries and workers adjust. In each case, the first tier represents low-cost measures that can begin in the short term to help industries and workers, regardless of whether they will be negatively impacted by tariff rationalization, while the second tier of assistance applies only to trade-affected industries and workers and can be developed in the medium term. For industries, Tier 1 support involves the use of an innovative process of public-private problem solving of industry-specific constraints, and Tier 2 support involves the use of special safeguard measures to provide an objective and transparent process for determining which industries require longer phase out periods for tariff reductions versus the tariff rationalization plan. For workers, Tier 1 support involves improved access labor market information and training opportunities through the development of regional (or local) job centers. Tier 2 support provides government funding for training and job placement services. We conclude that this package of trade adjustment assistance measures could be used to complement a holistic tariff rationalization plan. But we caution that attempts to rush the implementation of these measures without careful design and communication could deeply undermine the potential for the reforms to work in solving underlying economic problems.
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.
Using a unique dataset on worldwide multinational corporations with precise location of headquarters and affiliates, I present evidence of a trade-off between distance to the headquarters and the knowledge intensity of the foreign subsidiary’s economic activity, emerging from dynamics related to the proximity-concentration hypothesis. This trade-off is strongly diminished the higher the overlap in working hours between the headquarters and its foreign subsidiary. In order to rule out biases arising from confounding factors, I implement a regression discontinuity framework to show that the economic activity of a foreign subsidiary located just across the time zone line that increases the overlap in working hours with its headquarters is, on average, about one percent higher in the knowledge intensity scale. I find no evidence of the knowledge intensity and distance trade-off weakening when a non-stop flight exists between the headquarters and the foreign subsidiary. The findings suggest that lower barriers to real-time communication within the multinational corporation play important role in the location strategies of multinational corporations.
Countries that specialize in commodities have in recent years been hit by high volatility in world prices for their exports. This paper suggests four ways that commodity-exporters can make themselves less vulnerable.
(1) Option contracts can be used to hedge against short-term declines in the commodity price without giving up the upside, as Mexico has shown.
(2) Commodity-linked bonds can hedge longer-term risk, and often have a natural ultimate counter-party in multinational corporations that depend on the commodity as an input.
(3) The well-documented pro-cyclicality of fiscal policy among commodity exporters can be reduced by insulating official forecasters against an optimism bias, as Chile has shown.
(4) Monetary policy can be made automatically more counter-cyclical, judged by the criterion of currency appreciation in reaction to positive terms-of-trade shocks, under either of two regimes: peggers can add the export commodity to a currency basket (CCB, for “Currency-plus-Commodity Basket”) and others can target Nominal Income instead of the CPI.
Venezuela is at a breaking point. The political, economic, financial, social and humanitarian crisis that has gripped the country is intensifying. This unsustainable situation raises several urgent questions: Which path will the embattled OPEC country take out of the current turmoil? What type of political transition lies ahead? What short-term and long-term impact will the crisis have on its ailing oil industry, economy and bond debt? What would be the best and most effective prescription for oil and economic recovery under a new governance regime? To discuss these matters, the Center on Global Energy Policy brought together on June 19, 2017 a group of about 45 experts, including oil industry executives, investment bankers, economists and political scientists from leading think tanks and universities, consultants, and multilateral organization representatives. This note provides some of the highlights from that roundtable discussion, which was held under the Chatham House rule.
We present the first evidence that international emigrant selection on education and earnings materializes through occupational skills. Combining novel data from a representative Mexican task survey with rich individual-level worker data, we find that Mexican migrants to the United States have higher manual skills and lower cognitive skills than non-migrants. Conditional on occupational skills, education and earnings no longer predict migration decisions. Differential labor-market returns to occupational skills explain the observed selection pattern and significantly outperform previously used returns-to-skills measures in predicting migration. Results are persistent over time and hold within narrowly defined regional, sectoral, and occupational labor markets.
Do export sanctions cause export deflection? Data on Iranian non-oil exporters between January 2006 and June 2011 shows that two-thirds of these exports were deflected to non-sanctioning countries after sanctions were imposed in 2008, and that at this time aggregate exports actually increased. Exporting firms reduced prices and increased quantities when exporting to a new destination, however, and suffered welfare losses as a result.