Publications

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.

Original version of this paper was published in 2016.

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.

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.

In this report we will be making extensive use of concepts described in more detail in the companion report "How Industry-Related Capabilities Affect Export Possibilities," especially with respect to Machine Learning techniques.

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.

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.