In this paper, we develop a heterogeneous agent general equilibrium framework to analyze optimal joint policies of a lockdown and transfer payments in times of a pandemic. In our model, the effectiveness of a lockdown in mitigating the pandemic depends on endogenous compliance. A more stringent lockdown 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. Lump-sum transfers help mitigate this trade-off. We identify and discuss key trade-offs involved and provide comparative statics for optimal policy. We show that, ceteris paribus, the optimal lockdown is stricter for more severe pandemics and in richer countries. 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. We finally discuss distributional consequences and the political economy of fighting a pandemic.
We introduce quality differentiation into a Ricardian model of international trade. We show that (1) quality differentiation allows industrialized countries to be active across the full board of products, complex and simple ones, while developing countries systematically specialize in simple products, in line with novel stylized facts. (2) Quality differentiation may thus help to explain why richer countries tend to be more diversified and why, increasingly over time, rich and poor countries tend to export the same products. (3) Quality differentiation implies that the gains from inter-product trade mostly accrue to developing countries. (4) Guided by our theory, we use a censored regression model to estimate the link between a country’s GDP per capita and its export quality. We find a much stronger relationship than when using OLS, in line with our theory.
This paper constructed a simple model to illustrate the global supply chain profit sharing and industrial upgrading mechanism, from which it was found that the average profitability distribution in the different supply chain stages was determined by two main factors: (1) the average product of the labor in the firms at each production stage; and (2) the ratio of the output elasticity of capital to the output elasticity of labor in each stage. This paper also proposed a new industrial upgrading mechanism, the ‘inter-supply chain upgrading’, for supply chain firms. Rises in production complexity and increased factor intensity in each production stage were found to be the two essential conditions for the inter-supply chain upgrading. The empirical study results were found to be broadly consistent with the proposed theories.
We analyze how globalization affects the allocation of talent across competing teams in large matching markets. Assuming a reduced form of globalization as a convex transformation of payoffs, we show that for every economy where positive assortative matching is an equilibrium without globalization, it is also an equilibrium with globalization. Moreover, for some economies positive assortative matching is an equilibrium with globalization but not without. The result that globalization promotes the concentration of talent holds under very minimal restrictions on how individual skills translate into team skills and on how team skills translate into competition outcomes. Our analysis covers many interesting special cases, including simple extensions of Rosen (1981) and Melitz (2003) with competing teams.
The degree to which modern technologies are able to substitute for groups of job tasks has renewed fears of near-future technological unemployment. We argue that our knowledge, skills and abilities (KSA) go beyond the specific tasks we do at the job, making us potentially more adaptable to technological change than feared. The disruptiveness of new technologies depends on the relationships between the job tasks susceptible to automation and our KSA. Here we first demonstrate that KSA are general human capital features while job tasks are not, suggesting that human capital is more transferrable across occupations than what job tasks would predict. In spite of this, we document a worrying pattern where automation is not randomly distributed across the KSA space – it is concentrated among occupations that share similar KSA. As a result, workers in these occupations are making longer skill transitions when changing occupations and have higher probability of unemployment.
An increasing number of studies evidence large and persistent earning losses by displaced workers. We study whether these losses can partly be attributed to the skill mismatch that arises when workers’ human capital is underutilized at the new job. We develop a new method of measuring skill mismatch that accounts for asymmetries in the transferability of human capital between occupations, and link these measures to exceptionally rich German administrative data on individuals’ work histories. We find that displacement increases the probability of occupational switching and skill mismatch, primarily because displaced workers often move to less skill-demanding occupations. Event-study analyses show that these downskilled switchers suffer substantially larger displacement costs than occupational stayers. Workers moving to more skill-demanding occupations have similar earning losses as stayers, and do not experience any displacement costs conditional on being employed