3

Technological progress in the form of automation spurs productivity, but temporarily disrupts labor markets through worker displacement and reduced earnings. I study the role of unions in shaping employment and wages of workers exposed to labor replacement during technological transitions. I document that unionization shifts the transitional costs in the form of wage and employment decline from incumbent to incoming workers, consistent with insider-outsider dynamics. I further document that unions have aggregate implications, accelerating the decline of overall employment among exposed workers, resulting in a more severe employment drop early in the transition and a subsequent slow catch-up of employment decline in less unionized labor markets. To quantify the intergenerational transfer generated by unions, I build a quantitative model of technology adoption and unionization. In the model, the distributional and aggregate effects of unionization result simultaneously from the static and dynamic effects of labor adjustment costs in the context of gradual technology adoption over time. I find that unionization increases the welfare cost of automation for young workers by 2% of permanent consumption along the transition, whereas the cost of automation to incumbent workers falls by 4% of permanent consumption. Unionization further creates spillover effects by suppressing wages in the non-adopting sector early in the transition driven by the accelerated employment decline in the adopting sector and corresponding reallocation of workers.

Benchmark finance and macroeconomic models appear to deliver conflicting estimates of the natural rate and bond risk premia. This natural rate puzzle applies not only in the U.S. but across many advanced economies. We use a unified no-arbitrage macro- finance model with two trend factors to estimate the natural rate r∗ for 10 advanced economies. We cover a longer and wider sample than previous studies and draw on new sources to construct yield curves and excess returns. The two-trend model im- proves the explanatory power of yield regressions and return forecasts. Most variation in yields is due to the macro trends r∗ and π∗, and not bond risk premia. Global compo- nents of unexpected bond returns are influential, while the local components of natural rates are large. Our r∗ estimates covary with growth and demographic variables in a manner consistent with theory and previous findings.

We build a unified quantitative theory of increasing life expectancy and income growth in the last two centuries, and the emergence and expansion of a modern health sector in the 20th century. To do so, we develop a two-sector overlapping generations model with endogenous and directed technical change in which income growth, life expectancy, the size of and technological progress in the health and the final goods sector are jointly determined in general equilibrium. The model interprets the historical record as three phases of a dynamic equilibrium in which households are initially poor and the quality-adjusted price of health goods is prohibitively high so that demand for them is non-existent, and life expectancy is short and stagnant. As technological progress starts to fuel income growth, households commence consuming basic health goods (such as a better diet and basic domestic hygiene), remaining life expectancy at age 20 starts to rise in the first half of the 19th century. 100 years later, further directed technological progress eventually leads to the emergence (in ca. 1940) and then the expansion of a modern health sector. In counterfactual analyses the model suggests that about 20% of the life-expectancy gains between 1940 and 2020 are attributed to increased spending in the modern health sector. Furthermore, public spending on health, in the form of subsidies to health R&D during WW II and subsequently, due to the emergence of Medicare, plays a major role in the kickoff of the modern health sector during WWII and its expansion afterwards.

This paper introduces higher-order earnings risk consistent with recent empirical findings into a benchmark heterogeneous-agent macro model to examine its implication for the distribution of wealth. I find that higher-order earnings dynamics induce higher earnings inequality driven primarily by persistent earnings losses at the bottom. Poor households respond by strongly cutting consumption leading to more consumption and less wealth inequality which reinforces the known issue of generating the empirically observed wealth dispersion in this class of models. In addition to lower overall consumption, the higher-order earnings moments, particularly excess kurtosis, are passed through to consumption dynamics of the poor. Both effects combined mean that those households are willing to pay up to 1.7% of permanent consumption to avoid higher-order earnings risk. Moreover, the latter effect induces consumption dynamics of the poor to be predominantly driven by idiosyncratic earnings changes which significantly reduces the correlation between their consumption and aggregate output. Since wealthier households are not affected strongly the implications for the aggregate dynamics of the economy are negligible. Methodologically, I develop a new General Polynomial Chaos Expansion approach to solve for the aggregate dynamics of this class of models, and contrast its efficiency with previous methods.