Journal Articles

Based on the criteria of the factor endowment structure of state-owned enterprise (SOE) sectors in China between 1980 and 2018, this paper rationalizes the classified reforming of China's state sectors by constructing a Nash bargaining model to capture the dynamics of ownership restructuring, and the reduction process of policy burden on SOEs. We reveal that the interplay between policy burden bared by SOEs and the ownership restructuring process largely depends upon their factor intensities since the reform period in the 1980s. Our model identifies two Ownership Reform Irrelevance Points (ORIP), which serve as the benchmark for the dynamics of the ownership restructuring process of China's large SOEs, which saw them move from ‘mixed-ownership’ to ‘privatization’. ORIPs demonstrate the need for a reduction in social policy burdens with regards to the state sector's comparative advantage of factor endowment structure through SOE ownership restructuring. This study theoretically analyzes existing literatures on the classified reforms of China's state sectors from 1978 to 2018. This study is the first to base such an analysis on the criteria of factor endowment structure focusing on the connection between the policy burdens bared by SOEs and their ownership restructuring process.

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.

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

Economic complexity offers a potentially powerful paradigm to understand key societal issues and challenges of our time. The underlying idea is that growth, development, technological change, income inequality, spatial disparities, and resilience are the visible outcomes of hidden systemic interactions. The study of economic complexity seeks to understand the structure of these interactions and how they shape various socioeconomic processes. This emerging field relies heavily on big data and machine learning techniques. This brief introduction to economic complexity has three aims. The first is to summarize key theoretical foundations and principles of economic complexity. The second is to briefly review the tools and metrics developed in the economic complexity literature that exploit information encoded in the structure of the economy to find new empirical patterns. The final aim is to highlight the insights from economic complexity to improve prediction and political decision-making. Institutions including the World Bank, the European Commission, the World Economic Forum, the OECD, and a range of national and regional organizations have begun to embrace the principles of economic complexity and its analytical framework. We discuss policy implications of this field, in particular the usefulness of building recommendation systems for major public investment decisions in a complex world.

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 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.

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.

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.

Unlike most cross-country growth analyses, we focus on turning points in growth performance. We look for instances of rapid acceleration in economic growth that are sustained for at least eight years and identify more than 80 such episodes since the 1950s. Growth accelerations tend to be correlated with increases in investment and trade, and with real exchange rate depreciations. Political-regime changes are statistically significant predictors of growth accelerations. External shocks tend to produce growth accelerations that eventually fizzle out, while economic reform is a statistically significant predictor of growth accelerations that are sustained. However, growth accelerations tend to be highly unpredictable: the vast majority of growth accelerations are unrelated to standard determinants and most instances of economic reform do not produce growth accelerations.

This paper documents large cross-country differences in the long run volatility of the real exchange rate. In particular, it shows that the real exchange rate of developing countries is approximately three times more volatile than the real exchange rate in industrial countries. The paper tests whether this difference in volatility can be explained by the fact that developing countries face larger shocks (both real and nominal) and recurrent currency crises or by different elasticities to these shocks. It finds that the magnitude of the shocks and the differences in elasticities can only explain a small part of the difference in RER volatility between developing and industrial countries. Results from ARCH estimations confirm that there is a substantial difference in long term volatilities between these two sets of countries and indicate that there is also a much higher persistence of deviations of the variance of the RER from its long run value when the economy suffers shocks of various kinds.

This paper clarifies how the valuation of hidden assets—what we call “dark matter”—changes our assessment of the U.S. external imbalance. Dark matter assets are defined as the capitalized value of the return privilege obtained by U.S. assets. Because this return privilege has been steady over recent decades, it is likely to persist in the future or even to increase, as it becomes leveraged by an increasingly globalized world. Once this is included in future projections of U.S. current accounts, the U.S. external position looks much more balanced than depicted in official statistics.

When local cost discovery generates knowledge spillovers, specialization patterns become partly indeterminate and the mix of goods that a country produces may have important implications for economic growth. We demonstrate this proposition formally and adduce some empirical support for it. We construct an index of the “income level of a country’s exports,” document its properties, and show that it predicts subsequent economic growth.

Economies grow by upgrading the products they produce and export. The technology, capital, institutions, and skills needed to make newer products are more easily adapted from some products than from others. Here, we study this network of relatedness between products, or “product space,” finding that more-sophisticated products are located in a densely connected core whereas less-sophisticated products occupy a less-connected periphery. Empirically, countries move through the product space by developing goods close to those they currently produce. Most countries can reach the core only by traversing empirically infrequent distances, which may help explain why poor countries have trouble developing more competitive exports and fail to converge to the income levels of rich countries.

Current account statistics may not be good indicators of the evolution of a country's net foreign assets and of its external position's sustainability. The value of existing assets may vary independently of current account flows, so-called ‘return privileges’ may allow some countries to obtain abnormal returns, and mismeasurement of FDI, unreported trade of insurance or liquidity services, and debt relief may also play a role. We analyse the relevant evidence in a large set of countries and periods, and examine measures of net foreign assets obtained by capitalizing the net investment income and then estimating the current account from the changes in this stock of foreign assets. We call dark matter the difference between our measure of net foreign assets and that measured by official statistics. We find it to be important for many countries, analyse its relationship with theoretically relevant factors, and note that the resulting perspective tends to make global net asset positions appear relatively stable.