Innovation on Wings: Nonstop Flights and Firm Innovation in the Global Context
We study whether, when, and how better connectivity through nonstop flights leads to positive innovation outcomes for firms in the global context. Using unique data of all flights emanating from 5,015 airports around the globe from 2005 to 2015 and exploiting a regression discontinuity framework, we report that a 10% increase in nonstop flights between two locations leads to a 3.4% increase in citations and a 1.4% increase in the production of collaborative patents between those locations. This effect is driven primarily by firms as opposed to academic institutions. We further study the characteristics of firms and firm locations that are salient to the relation between nonstop flights and innovation outcomes across countries. Using a gravity model, we posit and find that the positive effect of nonstop flights on innovation is stronger for firms and subsidiaries with greater innovation mass (e.g., stocks of inventors and R&D spending), located in innovation hubs or countries that are deemed technology leaders, and that are separated by large cultural or temporal distance.
Research Summary: The Role of Nonstop Flights in Fostering Global Firm Innovation
Birthplace diversity and economic complexity: Cross-country evidence
We empirically investigate the relationship between a country’s economic complexity and the diversity in the birthplaces of its immigrants. Our cross-country analysis suggests that countries with higher birthplace diversity by one standard deviation are more economically complex by 0.1 to 0.18 standard deviations above the mean. This holds particularly for diversity among highly educated migrants and for countries at intermediate levels of economic complexity. We address endogeneity concerns by instrumenting diversity through predicted stocks from a pseudo-gravity model as well as from a standard shift-share approach. Finally, we provide evidence suggesting that birthplace diversity boosts economic complexity by increasing the diversification of the host country’s export basket.
What Can the Millions of Random Treatments in Nonexperimental Data Reveal About Causes?
We propose a new method to estimate causal effects from nonexperimental data. Each pair of sample units is first associated with a stochastic ‘treatment’—differences in factors between units—and an effect—a resultant outcome difference. It is then proposed that all pairs can be combined to provide more accurate estimates of causal effects in nonexperimental data, provided a statistical model relating combinatorial properties of treatments to the accuracy and unbiasedness of their effects. The article introduces one such model and a Bayesian approach to combine the O(n2) pairwise observations typically available in nonexperimental data. This also leads to an interpretation of nonexperimental datasets as incomplete, or noisy, versions of ideal factorial experimental designs. This approach to causal effect estimation has several advantages: (1) it expands the number of observations, converting thousands of individuals into millions of observational treatments; (2) starting with treatments closest to the experimental ideal, it identifies noncausal variables that can be ignored in the future, making estimation easier in each subsequent iteration while departing minimally from experiment-like conditions; (3) it recovers individual causal effects in heterogeneous populations. We evaluate the method in simulations and the National Supported Work (NSW) program, an intensively studied program whose effects are known from randomized field experiments. We demonstrate that the proposed approach recovers causal effects in common NSW samples, as well as in arbitrary subpopulations and an order-of-magnitude larger supersample with the entire national program data, outperforming Statistical, Econometrics and Machine Learning estimators in all cases. As a tool, the approach also allows researchers to represent and visualize possible causes, and heterogeneous subpopulations, in their samples.
Yet it Endures: The Persistence of Original Sin
Notwithstanding announcements of progress, “international original sin” (the denomination of external debt in foreign currency) remains a persistent phenomenon in emerging markets. Although some middle-income countries have succeeded in developing markets in local-currency sovereign debt and attracting foreign investors, they continue to hedge their currency exposures through transactions with local pension funds and other resident investors. The result is to shift the locus of currency mismatches within emerging economies but not to eliminate them. Other countries have limited original sin by limiting external borrowing, passing up valuable investment opportunities in pursuit of stability. We document these trends, analyzing regional and global aggregates and national case studies. Our conclusion is that there remains a case for an international initiative to address currency risk in low- and middle-income economies so they can more fully exploit economic development opportunities.
Horrible trade-offs in a pandemic: Poverty, fiscal space, policy, and welfare
We analyze how poverty and a country’s fiscal space impact policy and welfare in times of a pandemic. We introduce a subsistence level of consumption into a tractable heterogeneous agent framework, and use this framework to characterize optimal joint policies of a lockdown and transfer payments. In our model, a more stringent lockdown helps fighting the pandemic, but it also deepens the recession, which implies that poorer parts of society find it harder to subsist. This reduces their compliance with the lockdown, and may cause deprivation of the very poor, giving rise to an excruciating trade-off between saving lives from the pandemic and from deprivation. Transfer payments help mitigate this trade-off. We show that, ceteris paribus, the optimal lockdown is stricter in richer countries and the aggregate death burden and welfare losses smaller. We then consider a government borrowing constraint and show that limited fiscal space lowers the optimal lockdown and welfare, and increases the aggregate death burden during the pandemic. This is particularly true in societies where a larger fraction of the population is in poverty. We discuss evidence from the literature and provide reduced-form regressions that support the relevance of our main mechanisms. We finally discuss distributional consequences and the political economy of fighting a pandemic.
How production networks amplify economic growth
Technological improvement is the most important cause of long-term economic growth. In standard growth models, technology is treated in the aggregate, but an economy can also be viewed as a network in which producers buy goods, convert them to new goods, and sell the production to households or other producers. We develop predictions for how this network amplifies the effects of technological improvements as they propagate along chains of production, showing that longer production chains for an industry bias it toward faster price reduction and that longer production chains for a country bias it toward faster growth. These predictions are in good agreement with data from the World Input Output Database and improve with the passage of time. The results show that production chains play a major role in shaping the long-term evolution of prices, output growth, and structural change.
Media release: New study finds economic progress is aided by longer supply chains and deeper networks
Diagnosing Human Capital as a Binding Constraint to Growth: Tests, Symptoms and Prescriptions
The empirical literature on the contributions of human capital investments to economic growth shows mixed results. While evidence from OECD countries demonstrates that human capital accumulation is associated with growth accelerations, the substantial efforts of developing countries to improve access to and quality of education, as a means for skill accumulation, did not translate into higher income per capita. In this Element, we propose a framework, building on the principles of ‘growth diagnostics’, to enable practitioners to determine whether human capital investments are a priority for a country’s growth strategy. We then discuss and exemplify different tests to diagnose human capital in a place, drawing on the Harvard Growth Lab’s experience in different development context, and discuss various policy options to address skill shortages.
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Estimating the drivers of urban economic complexity and their connection to economic performance
Estimating the capabilities, or inputs of production, that drive and constrain the economic development of urban areas has remained a challenging goal. We posit that capabilities are instantiated in the complexity and sophistication of urban activities, the know-how of individual workers, and the city-wide collective know-how. We derive a model that indicates how the value of these three quantities can be inferred from the probability that an individual in a city is employed in a given urban activity. We illustrate how to estimate empirically these variables using data on employment across industries and metropolitan statistical areas in the USA. We then show how the functional form of the probability function derived from our theory is statistically superior when compared with competing alternative models, and that it explains well-known results in the urban scaling and economic complexity literature. Finally, we show how the quantities are associated with metrics of economic performance, suggesting our theory can provide testable implications for why some cities are more prosperous than others.
Economic development as self-discovery
In the presence of uncertainty about what a country can be good at producing, there can be great social value to discovering costs of domestic activities because such discoveries can be easily imitated. We develop a general-equilibrium framework for a small open economy to clarify the analytical and normative issues. We highlight two failures of the laissez-faire outcome: there is too little investment and entrepreneurship ex ante, and too much production diversification ex post. Optimal policy consists of counteracting these distortions: to encourage investments in the modern sector ex ante, but to rationalize production ex post. We provide some informal evidence on the building blocks of our model.
On the determinants of Original Sin: an empirical investigation
Most countries do not borrow abroad in their own currency, a fact that has been referred to as “Original Sin”. This paper describes the incidence of the problem and makes an attempt at uncovering its cause. The paper finds weak support for the idea that the level of development, institutional quality, or monetary credibility or fiscal solvency is correlated with Original Sin. Only the absolute size of the economy is robustly correlated. The paper also explores the determinants of a country’s capacity to borrow at home at long duration and in local currency. It finds that monetary credibility and the presence of capital controls are positively correlated with this capacity.