Universal basic income: inspecting the mechanisms

We consider the aggregate and distributional impact of Universal Basic Income (UBI). We develop a model to study a wide range of UBI programs and financing schemes and to highlight the key mechanisms behind their impact. The most crucial channel is the rise in distortionary taxation (required to fund UBI) on labor force participation. Second in importance is the decline in self-insurance due to the insurance UBI provides, resulting in lower aggregate capital. Third, UBI creates a positive income effect lowering labor force participation. Alternative tax-transfer schemes mitigate the impact on labor force participation and the cost of UBI

Financial Risk and Unemployment

Abstract There is a strong correlation between the corporate interest rate (BAA rated), and its spread relative to Treasuries, and the unemployment rate. We model how interest rates and potential default rates impact equilibrium unemployment in a Diamond-Mortesen-Pissarides model. We calibrate the model using US data without targeting business cycle statistics. Volatility in the corporate interest rate can explain about 80% of the volatility of unemployment, vacancies, and market tightness. Simulating the Great Recession shows the model can account for much of the rise in unemployment. Without Fed action, unemployment would have been 6% higher. JEL Classification:E22, E24, E32, E44, J41, J63, J6

Who Cares about Unemployment Insurance?

How is the optimal level of unemployment insurance affected when accounting for skill differences? We analyze this question using a general equilibrium model that has a number of key elements: (i) a search and matching friction in the labor market; (ii) workers who have the ability to save and cannot perfectly insure idiosyncratic risks; and (iii) ex-ante heterogeneity in unemployment risk and labor income. Considering a proportional tax and replacement rate UI system, our model suggests an optimal replacement rate of 32%, while a model without ex-ante heterogeneity calls for a much lower replacement rate (12%). We show that both dimensions of heterogeneity are responsible for these results. Specifically, we argue that income differences induce an incentive to redistribute consumption across skill groups. However, given the UI system, such redistribution is feasible only when there are differences in unemployment risk

The macroeconomics of automation: data, theory, and policy analysis

The U.S. economy has experienced a significant drop in the fraction of the population employed in middle wage, “routine task-intensive” occupations. Applying machine learning techniques, we identify characteristics of those who used to be employed in such occupations and show they are now less likely to work in routine occupations. Instead, they are either non-participants in the labor force or working at occupations that tend to occupy the bottom of the wage distribution. We then develop a quantitative, heterogeneous agent, general equilibrium model of labor force participation, occupational choice, and capital investment. This allows us to quantify the role of advancement in automation technology in accounting for these labor market changes. We then use this framework as a laboratory to evaluate various public policies aimed at addressing the disappearance of routine employment and its consequent impacts on inequality

How Exporters Grow

We document how export quantities and prices evolve after entry to a market. Controlling for marginal cost, and taking account of selection on idiosyncratic demand, there are economically and statistically significant dynamics of quantities, but no dynamics of prices. To match these facts, we estimate a model where firms invest in customer base through non-price actions (e.g. marketing and advertising), and learn gradually about their idiosyncratic demand. The model matches quantity, price and exit moments. Parameter estimates imply costs of adjusting investment in customer base, and slow learning about demand, both of which generate sluggish responses of sales to shocks

How Exporters Grow

We document how export quantities and prices evolve after entry to a market. Controlling for marginal cost, and taking account of selection on idiosyncratic demand, there are economically and statistically significant dynamics of quantities, but no dynamics of prices. To match these facts, we estimate a model where firms invest in customer base through non-price actions (e.g. marketing and advertising), and learn gradually about their idiosyncratic demand. The model matches quantity, price and exit moments. Parameter estimates imply costs of adjusting investment in customer base, and slow learning about demand, both of which generate sluggish responses of sales to shocks

Technological learning and labor market dynamics. Unpublished manuscript

We propose a resolution to two important business cycle puzzles for the searchand-matching model of the labor market, namely: (a) the weak amplification of shocks to fluctuations in unemployment, and (b) the strong correlation of unemployment and labor productivity over the cycle. We focus attention on the implementation process of technological innovation—specifically, the empirical findings that new technologies are subject to a learning process. We consider the idea that fluctuations in the ease or speed of technological learning are a source of business cycles. We find that these fluctuations generate realistic volatility of unemployment relative to that of labor productivity, and a realistic correlation between the two variables. Moreover, our model provides a new interpretation of “news shocks ” discussed in the recent business cycle literature