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.
In August 2016, the Government of Sri Lanka (GoSL) and the Building State Capability program of CID convened five teams of civil servants, tasking them with solving issues related to investment and export promotion. One of these teams, the “Targeting Team,” took on the task of formulating and executing a plan to identify promising new economic activities for investment and export promotion in Sri Lanka. With the assistance of CID’s Growth Lab, the Targeting Team assembled and analyzed over 100 variables from 22 datasets, studying all tradable activities and 29 representative subsectors. Their analysis highlighted the potential of investment related to electronics, electrical equipment and machinery (including automotive products), as well as tourism. Ultimately, the team’s recommendations were incorporated in GoSL strategies for investment promotion, export development, and economic diplomacy; extensions of the research were also used to help plan new export processing zones and target potential anchor investors.
This report summarizes the methodology and findings of the Targeting Team, including scorecards for each of the sectors studied.
Labor informality, associated with low productivity and lack of access to social security services, dogs developing countries around the world. Rates of labor (in)formality, however, vary widely within countries. This paper presents a new stylized fact, namely the systematic positive relationship between the rate of labor formality and the working age population in cities. We hypothesize that this phenomenon occurs through the emergence of complex economic activities: as cities become larger, labor is allocated into increasingly complex industries as firms combine complementary capabilities derived from a more diverse pool of workers. Using data from Colombia, we use a network-based model to show that the technological proximity (derived from worker transitions between industry pairs) of current industries in a city to potential new complex industries governs the growth of the formal sector in the city. The mechanism proposed has robust strong predictive power, and fares better than alternative explanations of (in)formality.
Cities thrive through the diversity of their occupants because the availability of complementary skills enables firms in the formal sector to grow, delivering increasingly sophisticated products and services. The appearance of new industries is path dependent in that new economic activities build on existing strengths, leading cities to both diversify and specialize in distinct areas. Hence, the location of necessary capabilities, and in particular the distance between firms and people with the skills they need, is key to the success of urban agglomerations. Using data for Colombia, this paper assesses the extent to which cities benefit from skills and capabilities available in their surrounding catchment areas. Without assuming a prioria a definition for cities, we sequentially agglomerate the 96 urban municipalities larger than 50,000 people based on commuting time. We show that a level of agglomeration equivalent to between 45 and 75 minutes of commuting time, corresponding to between 62 and 43 cities, maximizes the impact that the availability of skills has on the ability of agglomerations to generate formal employment. Smaller urban municipalities stand to gain more in the process of agglomeration. A range of policy implications are discussed.
The prevalence of many urban phenomena changes systematically with population size1 . We propose a theory that unifies models of economic complexity2,3 and cultural evolution4 to derive urban scaling. The theory accounts for the difference in scaling exponents and average prevalence across phenomena, as well as the difference in the variance within phenomena across cities of similar size. The central ideas are that a number of necessary complementary factors must be simultaneously present for a phenomenon to occur, and that the diversity of factors is logarithmically related to population size. The model reveals that phenomena that require more factors will be less prevalent, scale more superlinearly and show larger variance across cities of similar size. The theory applies to data on education, employment, innovation, disease and crime, and it entails the ability to predict the prevalence of a phenomenon across cities, given information about the prevalence in a single city.