Safe asset demand and currency manipulation increase the dollar and the U.S. current account deficit. Deficits in manufacturing trade cause dislocation and generate protectionism. Dynamic OLS results indicate that U.S. export elasticities exceed unity for automobiles, toys, wood, aluminum, iron, steel, and other goods. Elasticities for U.S. imports from China are close to one or higher for footwear, radios, sports equipment, lamps, and watches and exceed 0.5 for iron, steel, aluminum, miscellaneous manufacturing, and metal tools. Elasticities for U.S. imports from other countries are large for electrothermal appliances, radios, furniture, lamps, miscellaneous manufacturing, aluminum, automobiles, plastics, and other categories. Stock returns on many of these sectors also fall when the dollar appreciates. Several manufacturing industries are thus exposed to a strong dollar. Policymakers could weaken the dollar and deflect protectionist pressure by promoting the euro, the yen, and the renminbi as alternative reserve currencies.
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.
This article provides an empirical assessment of global scientific mobility over the past four decades, based on bibliometric data. We find (i) an increasing diversity of origin and destination countries integrated in global scientific mobility, with (ii) the centre of gravity of scientific knowledge production and migration destinations moving continuously eastwards by about 1300 km per decade, (iii) an increase in average migration distances of scientists reflecting integration of global peripheries into the global science system, (iv) significantly lower mobility frictions for internationally mobile scientists compared to non-scientist migrants, (v) with visa restrictions establishing a statistically significant barrier affecting international mobility of scientists hampering the global diffusion of scientific knowledge.
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 find that having stronger close social networks at home has the opposite effect by reducing the likelihood of migration intentions, both internationally and locally.
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.
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.
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.
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.
Recent work suggests a connection between domestic debt and external default. We examine potential linkages for Venezuela, where the evidence reveals a nexus among domestic debt, financial repression, and external vulnerability. The financial repression tax (as a share of GDP) is similar to OECD economies, in spite of higher debt ratios in the latter. The financial repression “tax rate” is higher in years of exchange controls and legislated interest rate ceilings. We document a link between domestic disequilibrium and a weakening of the net foreign asset position via private capital flight. We suggest these findings are not unique to Venezuela.
Venezuela has an oil-dependent economy subject to large exogenous shocks and a rigid labor market. These features go straight to the heart of two weaknesses of real business cycle (RBC) theory widely reported in the literature: neither shocks are volatile enough nor real salaries suf ficiently flexible as required by the RBC framework to replicate the behavior of the economy. We calibrate a basic RBC model and compare a set of relevant statistics from RBC-simulated time series with actual data for Venezuela and the benchmark case of the United States (1950–2008). Despite Venezuela being a heavily regulated economy, RBC-simulated series provide a good fit, in particular with regard to labor markets.
This paper characterizes the evolution of the manufacturing and industrial export structure of Ireland since 1995 within the framework of Economic Complexity and the Product Space. We observe a high level of specialisation in Ireland’s export structure, coupled with high income per capita as compared to the complexity level of its industrial activities (as captured by its Economic Complexity Index). We identify a dual structure within the economy, with domestic and foreign-owned exporters exhibiting distinct characteristics. In the latter case, we observe a recent consolidation and reduction in complexity level by the foreign-owned high tech pharmaceuticals and electronics sectors, with limited evidence of spill-overs leading to growth of domestic firms in these sectors. This contrasts with a dynamic and growing domestic food and agriculture sector, which is well positioned for continued expansion of Ireland’s indigenous activities into more complex goods. Finally, we illustrate this framework as a tool for policy-makers by identifying some potential new sectors that share many inputs with Ireland’s current domestic capability base, and could increase Ireland’s complexity level for future growth.
In this paper, I question the idea that a country develops and democratizes merely by pursuing a model of deeper regional integration with more prosperous countries. I examine the case of Albania’s integration into the European Union to show that more often than not, transition reproduces hierarchies and inequities that usually underpin relations between a prosperous center and a backward periphery. Instead of being a cure, a solution to the political primitivism and underdevelopment, the story with Europeanization as a model of modernization suggests that despite noble intentions and goals, reforms in the name of the European Union end up foregrounding a security state apparatus, impose an ideological hegemony, and maintain a political culture that inhibits democratization, while discouraging and displacing the need for endogenous growth strategies.
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.
This article, in an effort to assist the selection and deployment of evidence-informed strategies, proposes a new conceptual framework for responding to community violence among youth. First, the phenomenon of community violence is understood in context using a new violence typology organized along a continuum. Second, the need for a new anti-community violence framework is established. Third, a framework is developed, blending concepts from the fields of public safety and public health. Fourth, evidence from systematic reviews and meta-analyses concerning community violence is summarized and categorized. Finally, an anti-violence framework populated with evidence-informed strategies is presented and discussed.
Social relations involve both face-to-face interaction as well as telecommunications. We can observe the geography of phone calls and of the mobility of cell phones in space. These two phenomena can be described as networks of connections between different points in space. We use a dataset that includes billions of phone calls made in Colombia during a six-month period. We draw the two networks and find that the call-based network resembles a higher order aggregation of the mobility network and that both are isomorphic except for a higher spatial decay coefficient of the mobility network relative to the call-based network: when we discount distance effects on the call connections with the same decay observed for mobility connections, the two networks are virtually indistinguishable.
The paper studies the nature and extent of Egyptian "crony" capitalism by comparing the corporate performance and the stock market valuation of politically connected and unconnected firms, before and after the 2011 popular uprising that led to the end of President Mubarak 30 years rule. First, we identify politically connected firms and conduct an event study around the events of 2011, as well as around previous events related to rumors about Mubarak’s health. We estimate the market valuation of political connections to be 20% to 23% of the value of connected firms. Second, we explore the mechanisms used for granting these privileges by looking at corporate behavior before 2011. It appears that these advantages allowed connected firms to increase their market size and power and their borrowings. We finally compare the performance of firms and find that the rate of return on assets of connected firms was lower than that of non-connected firms by nearly 3 percentage points. We argue that this indicates that the granting of privileges was not part of a successful industrial policy but instead, that it led to a large misallocation of capital towards less efficient firms, which together with reduced competition, led to lower economic growth.
This paper examines the microeconomic determinants of residential real estate prices in Caracas, Venezuela, using a private database containing 17,526 transactions from 2008 to 2009. The particular institutional characteristics of many countries in Latin America, and Venezuela in particular, where land invasions and expropriations (with only partial compensation) have been common threats to property owners, provide us with an opportunity to test the effects of these risks on housing prices using a unique database. The effect of these risks on property prices is negative and significant. To our knowledge, this is the first attempt to quantify these impacts in the Hedonic pricing literature applied to real estate. Size, the number of parking spaces, the age of the property, the incidence of crime, and the average income in the neighborhood are significant determinants of prices. Finally, this paper analyzes the microeconomic determinants of housing prices at the municipal level.
Aim of this paper is to introduce the complex system perspective into retail market analysis. Currently, to understand the retail market means to search for local patterns at the micro level, involving the segmentation, separation and profiling of diverse groups of consumers. In other contexts, however, markets are modelled as complex systems. Such strategy is able to uncover emerging regularities and patterns that make markets more predictable, e.g. enabling to predict how much a country’s GDP will grow. Rather than isolate actors in homogeneous groups, this strategy requires to consider the system as a whole, as the emerging pattern can be detected only as a result of the interaction between its self-organizing parts. This assumption holds also in the retail market: each customer can be seen as an independent unit maximizing its own utility function. As a consequence, the global behaviour of the retail market naturally emerges, enabling a novel description of its properties, complementary to the local pattern approach. Such task demands for a data-driven empirical framework. In this paper, we analyse a unique transaction database, recording the micro-purchases of a million customers observed for several years in the stores of a national supermarket chain. We show the emergence of the fundamental pattern of this complex system, connecting the products’ volumes of sales with the customers’ volumes of purchases. This pattern has a number of applications. We provide three of them. By enabling us to evaluate the sophistication of needs that a customer has and a product satisfies, this pattern has been applied to the task of uncovering the hierarchy of needs of the customers, providing a hint about what is the next product a customer could be interested in buying and predicting in which shop she is likely to go to buy it.
We propose and implement a new technique for measuring the total magnitude of a growth episode: the change in output per capita resulting from one structural break in the trend growth of output (acceleration or deceleration) to the next. The magnitude of the gain or loss from a growth episode combines (a) the difference between the post-break growth rate versus a counter-factual "no break" growth rate and (b) the duration of the episode to estimate the difference in output per capita at the end of an episode relative to what it would have been in the "no break" scenario. We use three "counter-factual" growth rates that allow for differing degrees of regression to global average growth: "no change" (zero regression to the mean), "world episode average" (full regression to the mean) and "unconditional predicted growth" (which uses a regression for each growth episode to predict future growth based only on past growth and episode initial level). We can also calculate the net present value at the start of an episode of the gain or loss in output comparing the actual evolution of output per capita versus a counter-factual. This method allows us to place dollar figures on growth episodes. The top 20 growth accelerations have Net Present Value (NPV) magnitude of 30 trillion dollars - twice US GDP. Conversely, the collapse in output in Iran between 1976 and 1988 produced an NPV loss of $143,000 per person. The top 20 growth decelerations account for 35 trillion less in NPV of output. Paraphrasing Lucas, once one begins to think about what determines growth events that cause the appearance or disappearance of output value equal to the total US economy, it is hard to think about anything else.