This paper constructs a two-stage sequential game model to shed light on the spillover effect of inward FDI on the efficiency of domestic firms in host countries. Our model shows that, given an optimal joint-venture policy made by foreign firms, the impact of the spillover effect of inward FDI is contingent upon the productivity gap between the domestic firms and foreign ones. In particular, we demonstrate that the spillover effect of inward FDI varies negatively with the productivity gap between domestic low-productivity firms and foreign firms but works in the opposite way for high-productivity firms. This suggests that once the productivity gap widens, the entry of foreign firms will increase the efficiency of high-productivity firms but reduce the efficiency of low-productivity firms. In support of our theoretical model, we provide robust empirical results by using the dataset of annual survey of Chinese industrial enterprises.
As the literature has studied the financing method of Chinese-listed firms for a long time, but with inconclusive indications, this research thus adopts non-financial Chinese-listed firms’ data from 2003 to 2015 to investigate the relationship between long-term debt financing and financing deficit. We pay particular attention to three channels (ownership concentration, market timing, and state ownership) that potentially affect the adoption of long-term debt financing when there is a financing deficit. The empirical analysis documents a positive relationship between financing deficit and changes in the long-term debt ratio in our sampled firms for both static and dynamic panel models. Moreover, among the three channels we show that state ownership has the strongest positive impact on the adoption of long-term debt financing, followed by ownership concentration, while the weakest channel is the market timing’s negative effect. In general, our empirical analysis finds that the important external financing method of long-term debt is most likely to be impacted by the state ownership aspect.
The Government of Western Australia (WA), acting through its Department of Primary Industries and Regional Development (DPIRD), invited the Growth Lab of the Center for International Development at Harvard University to partner with the state to better understand and address constraints to economic diversification through a collaborative applied research project. The project seeks to apply growth diagnostic and economic complexity methodologies to inform policy design in order to accelerate productive transformation, economic diversification, and more inclusive and resilient job creation across Western Australia.
This report is organized in six sections, including this brief introduction. Section 2 is an Executive Summary. Section 3 explains the methodologies of Growth Diagnostics and Economic Complexity, including its theoretical foundations and main concepts. Section 4 describes the main findings of the Economic Complexity Report, including a characterization of Western Australia’s complexity profile. This is done at the state, regional, and city levels. Additionally, this section identifies diversification opportunities with high potential and organizes them into groupings to capture important patterns among the opportunities. This section also contextualizes the opportunities further by identifying relevant viability and attractiveness factors that complement the complexity metrics and consider local conditions. Section 5 highlights the main findings of the Growth Perspective Report. This section describes the economic growth process of Western Australia — with a focus on the past two decades — and identifies several issues with the way that growth has occurred. This section highlights three key channels through which negative externalities have manifested: labor market imbalances, pro-cyclicality of fiscal policy, and a misalignment of public goods. The section provides perspectives on the ways in which each of these channels have hampered the quality of growth and explores the deep-rooted factors that underpin these adverse dynamics. Section 6 introduces a policy framework that can be leveraged by WA to capitalize on revealed diversification opportunities and address the factors that impact the quality of the growth process of the state.
The Government of Western Australia (WA), acting through its Department of Primary Industries and Regional Development (DPIRD), invited the Growth Lab of the Center for International Development (CID) at Harvard University to partner with the state to better understand and address constraints to economic diversification through a collaborative applied research project. The project seeks to apply growth diagnostic and economic complexity methodologies to inform policy design in order to accelerate productive transformation, economic diversification, and more inclusive and resilient job creation across Western Australia.
This Economic Complexity Report is organized in six sections, including this brief introduction. Section 2 explains the methodology of economic complexity, including its theoretical foundations and main concepts, as well as the adjustments that were required to obtain the required export data at a subnational level and incorporate the service sector to the analysis. Section 3 describes the structure of the WA economy, identifying its productive capacities and exploring its complexity profile. This is done at the state, regional, and city levels. Section 4 identifies industries with high potential and organizes them into groupings to capture important patterns among the opportunities. Section 5 contextualizes the opportunities further by identifying relevant viability and attractiveness factors that complement the complexity metrics and consider local conditions, as well as a criterion for regional participation in the state-wide diversification strategy. Finally, Section 6 summarizes the main findings of this report and discusses implications for Government of WA strategy and policy toward capitalizing on these revealed opportunities.
The Government of Western Australia (WA), acting through its Department of Primary Industries and Regional Development (DPIRD), invited the Growth Lab of the Center for International Development at Harvard University to partner with the state to better understand and address constraints to economic diversification through a collaborative applied research project. The project seeks to apply growth diagnostic and economic complexity methodologies to inform policy design in order to accelerate productive transformation, economic diversification, and more inclusive and resilient job creation across Western Australia. As its name implies, this Growth Perspective Report aims to provide a set of perspectives on the process of economic growth in WA that provide insights for policymakers toward improving growth outcomes.
This Growth Perspective Report describes both the economic growth process of Western Australia — with a focus on the past two decades — and identifies several problematic issues with the way that growth has been structured. In particular, this report traces important ways in which policies applied during the boom and subsequent slowdown in growth over the last twenty years have exacerbated a number of self-reinforcing negative externalities of undiversified growth. The report analyzes three key channels through which negative externalities have manifested: labor market imbalances, pro-cyclicality of fiscal policy, and a misalignment of public goods. The report includes sections on each of these channels, which provide perspectives on the ways in which they have hampered the quality of growth and explore the reasons why problematic externalities have become self-reinforcing. In some cases, new issues have emerged in the most recent iteration of WA’s boom-slowdown cycle, but many issues have roots in the long-term growth history of WA.
Assignment models in trade predict that countries with higher productivity levels are assortatively matched to industries that make better use of these higher levels. Here, we assume that the driver of productivity differences is the differential distribution of factors among countries. Utilizing such a structure, we define and estimate the average factor level (AFL) for countries and products using only the information about the production patterns. Interestingly, our estimates coincide with the complexity variables of (Hidalgo and Hausmann, 2009), providing an underlying economic rationale. We show that AFL is highly correlated with country-level characteristics and predictive of future economic growth.
Economic growth is associated with the diversification of economic activities, which can be observed via the evolution of product export baskets. Exporting a new product is dependent on having, and acquiring, a specific set of capabilities, making the diversification process path-dependent. Taking an agnostic view on the identity of the capabilities, here we derive a probabilistic model for the directed dynamical process of capability accumulation and product diversification of countries. Using international trade data, we identify the set of pre-existing products, the product Ecosystem, that enables a product to be exported competitively. We construct a directed network of products, the Eco Space, where the edge weight corresponds to capability overlap. We uncover a modular structure, and show that low- and middle-income countries move from product communities dominated by small Ecosystem products to advanced (large Ecosystem) product clusters over time. Finally, we show that our network model is predictive of product appearances.
The comparative advantage of a location shapes its industrial structure. Current theoretical models based on this principle do not take a stance on how comparative advantages in different industries or locations are related with each other, or what such patterns of relatedness might imply about the evolution of comparative advantage. We build a simple Ricardian-inspired model and show that hidden information on inter-industry and inter-location relatedness can be captured by simple correlations between the observed structure of industries across locations, or the structure of locations across industries. We then use this recovered information to calculate a measure of implied comparative advantage, and show that it explains much of the location’s current industrial structure. We give evidence that these patterns are present in a wide variety of contexts, namely the export of goods (internationally) and the employment, payroll and number of establishments across the industries of subnational regions (in the US, Chile and India). In each of these cases, the deviations between the observed and implied comparative advantage in the past tend to be highly predictive of future industry growth, especially at horizons of a decade or more; this explanatory power holds at both the intensive as well as the extensive margin. These results suggest that a component of the long-term evolution of comparative advantage is already implied in today’s patterns of production.
Non-Pharmaceutical Interventions (NPIs) have been for most countries the key policy instrument utilized to contain the impact of the COVID-19 pandemic. In this article, we conduct an empirical analysis of the impact of these policies on the virus’ transmission and death toll, for a panel of 152 countries, from the start of the pandemic through December 31, 2020. We find that lockdowns tend to significantly reduce the spread of the virus and the number of related deaths. We also show that this benign impact declines over time: after four months of strict lockdown, NPIs have a significantly weaker contribution in terms of their effect in reducing COVID-19 related fatalities. Part of the fading effect of quarantines could be attributed to an increasing non-compliance with mobility restrictions, as reflected in our estimates of a declining effect of lockdowns on measures of actual mobility. However, we additionally find that a reduction in de facto mobility also exhibits a diminishing effect on health outcomes, which suggests that lockdown fatigues may have introduce broader hurdles to containment policies.
We examine how inequality and openness interact in shaping the long-run growth prospects of developing countries. To this end, we develop a Schumpeterian growth model with heterogeneous households and non-homothetic preferences for quality. We show that inequality affects growth very differently in an open economy as opposed to a closed economy: If the economy is close to the technological frontier, the positive demand effect of inequality on growth found in closed-economy models may be amplified by international competition. In countries with a larger distance to the technology frontier, however, rich households satisfy their demand for high quality via importing, and the effect of inequality on growth is smaller than in a closed economy and may even be negative. We show that this theoretical prediction holds up in the data, both when considering growth in export quality at the industry level and when considering growth in GDP per capita.
With the exception of some flashpoints in Northern and Southern Africa, the continent has been largely spared from the direct health effect of Covid-19. However, the African economy has been significantly hurt by the economic consequences. This eBook summarises recent research on the economic effect of the Covid-19 pandemic in the continent covering a wide array of topics focusing on the response of firms, households, governments, and international organisations.
COVID-19 pandemic had a devastating effect on both lives and livelihoods in 2020. The arrival of effective vaccines can be a major game changer. However, vaccines are in short supply as of early 2021 and most of them are reserved for the advanced economies. We show that the global GDP loss of not inoculating all the countries, relative to a counterfactual of global vaccinations, is higher than the cost of manufacturing and distributing vaccines globally. We use an economic-epidemiological framework that combines a SIR model with international production and trade networks. Based on this framework, we estimate the costs for 65 countries and 35 sectors. Our estimates suggest that up to 49 percent of the global economic costs of the pandemic in 2021 are borne by the advanced economies even if they achieve universal vaccination in their own countries.
The literature on wage gaps between Chiapas and the rest of Mexico revolves around individual factors, such as education and ethnicity. Yet, twenty years after the Zapatista rebellion, the schooling gap has shrunk while the wage gap has widened, and we find no evidence indicating that Chiapas indigenes are worse-off than their likes elsewhere in Mexico. We explore a different hypothesis and argue that place-specific characteristics condition the choices and behaviors of individuals living in Chiapas and explain persisting income gaps. Most importantly, they limit the necessary investments at the firm level in dynamic capabilities. Based on census data, we calculate the economic complexity index, a measure of the knowledge agglomeration embedded in the economic activities at the municipal level. Economic complexity explains a larger fraction of the wage gap than any individual factor. Our results suggest that the problem is Chiapas, and not Chiapanecos.
The investment promotion process in Albania is underperforming versus its potential. Between 2014 and 2018, the Albanian economy saw accelerating growth and transformation, which has been tied to the arrival of foreign companies. However, Albania has the potential to realize much more and more diversified foreign direct investment (FDI), which will be critical to accelerating growth in the period of global recovery from the COVID-19 pandemic. As the Albanian economy weathers the storm of COVID-19, it is critical to look to the future by enhancing the investment promotion process to be more targeted and proactive such that Albania can attract transformative global companies aligned with the country’s comparative advantages. This is not only a critical step toward faster and more resilient economic growth in Albania; it also happens to have very high returns in comparison to the limited fiscal spending required to implement the actions required.
The targeted investment promotion approach discussed in this note would capitalize on Albania’s many existing comparative advantages for attracting efficiency-seeking FDI. It would not displace Albania’s Strategic Investment Law nor the activities of the Albanian Investment Corporation (AIC), which aim to expand the country’s comparative advantages. Efficiency-seeking FDI — global companies that expand into Albania to serve global markets because it makes them more productive — do not need extensive tax incentives, regulatory exemptions, or other subsidies. In fact, an overreliance on these approaches can crowd out firms that do not want or need to rely on government support. Adding targeted investment promotion to Albania’s growth strategy would lead to more jobs, better quality jobs, more inclusive job growth, faster convergence with the income levels of the rest of Europe, and ultimately less outmigration.
This note summarizes the Growth Lab’s observations of the investment promotion process in Albania, over the last year in particular, and lays out recommendations to capture widespread opportunities for economic transformation that have been missed to date. The recommendations provided at the end of this note provide a roadmap for building an enhanced network for targeted investment promotion that is specific to Albania’s context. These recommendations recognize the current constraints that the COVID-19 pandemic creates but also look past the pandemic to prepare for opportunities that will emerge during the global recovery.
Cities and countries undergo constant structural transformation. Industries need many inputs, such as regulations, infrastructure or productive knowledge, which we call capabilities. And locations are successful in hosting industries insofar as the capabilities that they can provide. We propose a capabilities-based production model and an empirical strategy to measure the Sophistication of a product and the Production Ability of a location. We apply our framework to international trade data and employment data in the United States, recovering measures of Production Ability for countries and cities, and the Sophistication of products and industries. We show that both country- and city-level measures have a strong correlation with income and economic growth at different time horizons. Product Sophistication is positively correlated with indicators of human capital and wages. Our model-based estimations predict product appearances and disappearances through the extensive margin.
What is the economic rationale for investing in science? Based on an open economy model of creative destruction, we characterize four key factors of optimal investment in basic research: the stage of economic development, the strength of the manufacturing base, the degree of openness, and the share of foreign‐owned firms. For each of these factors, we analyze its bearings on optimal basic research investment. We then show that the predicted effects are consistent with patterns observed in the data and discuss how the factor‐based approach might inform basic research policies.
Loreto es un lugar de contrastes. Es el departamento más grande del Perú, pero se encuentra entre los de menor densidad poblacional. Su capital, Iquitos, está más cerca de los estados fronterizos de Brasil y Colombia que de las capitales de sus regiones vecinas en el Perú - San Martín y Ucayali. Sólo se puede llegar a Iquitos por vía aérea o fluvial, lo que la convierte en una de las mayores ciudades del mundo sin acceso por carretera. Desde la fundación del departamento, la economía de Loreto ha dependido de la explotación de recursos naturales, desde el boom del caucho a finales del siglo XIX y principios del XX hasta la extracción petrolera y explotación de recursos forestales que predomina en nuestros días. Este modelo ha traído consigo daños ambientales significativos y ha producido un patrón de crecimiento lento y volátil, que ha abierto una brecha cada vez más amplia entre la economía de la región y la del resto del país. Entre 1980 y 2018, Loreto creció a una tasa promedio compuesta anual cuatro veces menor a la del resto del Perú. Es decir, mientras el resto del Perú triplicó el tamaño de su economía, la de Loreto creció algo menos que un tercio.
En la última década (2008-2018), la región también se ha venido distanciando de sus pares amazónicos en el país (Ucayali, San Martín y Madre de Dios), que han crecido a una tasa promedio anual cinco veces mayor. En este período, el ingreso promedio por habitante en Loreto ha pasado de ser tres cuartas partes del promedio nacional en 2008 a menos de la mitad para 2018. Además del rezago económico - o quizás como consecuencia de él -, Loreto también se ubica entre los departamentos con peores indicadores de desarrollo social, anemia y desnutrición infantil del Perú.
En este contexto, el Laboratorio de Crecimiento de la Universidad de Harvard se asoció con la Fundación Gordon and Betty Moore para desarrollar una investigación que proporcionara insumos y recomendaciones de política para acelerar el desarrollo de la región y generar prosperidad de forma sostenible.
The literature extensively discusses the increasing commitment toward comprehensive structural reform of China’s economy as it targets to achieve high quality and sustainable economic growth. This research investigates the inherent relationship between supply-side structural reform (SSSR) and dynamic capital structure adjustment in Chinese-listed firms. Our results show that SSSR’s introduction has significantly improved the adjustment speed toward the optimal debt ratio, especially for firms with high indebtedness and low investment performance. Importantly, China’s bond market plays a crucial role through SSSR for firms’ debt ratio to adjust toward their optimal level. However, there is no such evidence among state-owned enterprises (SOEs), suggesting that the structural reform concerning corporate capital structure for SOEs is more challenging and longstanding when compared with non-SOEs.
This research constructs a simple dynamic model to illustrate the micro‐mechanism of industrial upgrading along the global value chains. Our model predicts that as firms move up from downstream to upstream stages, (a) there is higher profitability if and only if the following three conditions are satisfied. First, the increasing rate of sunk cost (including R&D expenditure) over sequential stages of production cannot be sufficiently large (endogenous sunk cost effect). Second, the decreasing rate of change of intermediate input demand with respect to the price set by firms at a production stage cannot be sufficiently high (intermediate input price effect). Third, the decreasing rate of change of intermediate input demand with respect to the pricing dynamics over the sequential stages of production cannot be sufficiently large (sequential pricing uncertainty effect); (b) total cost is lower if and only if the decreasing rate of change of input demand with respect to the price is sufficiently large; (c) output is higher if and only if and the decreasing rate of change of input demand with respect to the price is not sufficiently large; and (d) the price decreases. We show that the empirical patterns revealed in China are consistent with our model's predictions.
We describe a problem in complex networks we call the Node Vector Distance (NVD) problem, and we survey algorithms currently able to address it. Complex networks are a useful tool to map a non-trivial set of relationships among connected entities, or nodes. An agent—e.g., a disease—can occupy multiple nodes at the same time and can spread through the edges. The node vector distance problem is to estimate the distance traveled by the agent between two moments in time. This is closely related to the Optimal Transportation Problem (OTP), which has received attention in fields such as computer vision. OTP solutions can be used to solve the node vector distance problem, but they are not the only valid approaches. Here, we examine four classes of solutions, showing their differences and similarities both on synthetic networks and real world network data. The NVD problem has a much wider applicability than computer vision, being related to problems in economics, epidemiology, viral marketing, and sociology, to cite a few. We show how solutions to the NVD problem have a wide range of applications, and we provide a roadmap to general and computationally tractable solutions. We have implemented all methods presented in this article in a publicly available open source library, which can be used for result replication.