We study the effects of industrial robots on US labor markets. We show theoretically that robots may reduce employment and wages and that their local impacts can be estimated using variation in exposure to robots—defined from industry-level advances in robotics and local industry employment. We estimate robust negative effects of robots on employment and wages across commuting zones. We also show that areas most exposed to robots after 1990 do not exhibit any differential trends before then, and robots’ impact is distinct from other capital and technologies. One more robot per thousand workers reduces the employment-to-population ratio by 0.2 percentage points and wages by 0.42%.

We develop a tractable model of endogenous production networks. Each one of a number of products can be produced by combining labor and an endogenous subset of the other products as inputs. Different combinations of inputs generate (prespecified) levels of productivity and various distortions may affect costs and prices. We establish the existence and uniqueness of an equilibrium and provide comparative static results on how prices and endogenous technology/input choices (and thus the production network) respond to changes in parameters. These results show that improvements in technology (or reductions in distortions) spread throughout the economy via input–output linkages and reduce all prices, and under reasonable restrictions on the menu of production technologies, also lead to a denser production network. Using a dynamic version of the model, we establish that the endogenous evolution of the production network could be a powerful force towards sustained economic growth. At the root of this result is the fact that the arrival of a few new products expands the set of technological possibilities of all existing industries by a large amount—that is, if there are n products, the arrival of one more new product increases the combinations of inputs that each existing product can use from 2 n −1 to 2 n , thus enabling significantly more pronounced cost reductions from choice of input combinations. These cost reductions then spread to other industries via lower input prices and incentivize them to also adopt additional inputs.

Medical innovations during the 1940s quickly resulted in significant health improvements around the world. Countries with initially higher mortality from infectious diseases experienced larger increases in life expectancy, population, and subsequent social conflict. This cross-country result is robust across alternative measures of conflict and is not driven by differential trends between countries with varying baseline characteristics. A similar effect is also present within Mexico. Initial suitability conditions for malaria varied across municipalities, and anti-malaria campaigns had differential effects on population growth and social conflict. Both across countries and within Mexico, increased conflict over scarce resources predominates and this effect is more pronounced during times of economic hardship (specifically, in countries with a poor growth record and in drought-stricken areas in Mexico). At least during this time period, a larger increase in population made social conflict more likely.

Lack of trust in state institutions, often due to poor service provision, is a pervasive problem in many developing countries. If this increases reliance on non-state actors for crucial services, the resulting self-reinforcing cycle can further weaken the state. This paper examines whether such a cycle can be disrupted. We focus on dispute resolution in rural Punjab, Pakistan. We find that providing information about reduced delays in state courts leads to citizens reporting higher willingness to use state courts and to greater fund allocations to the state in two lab-in-the-field games designed to measure trust in state and non-state actors in a high-stakes setting. More interestingly, we find indirect effects on non-state actors. After receiving state positive information, respondents report lower likelihood of using non-state institutions and reduce funds allocated to them in field games. Furthermore, we find similar direct and indirect effects on a battery of questions concerning people's beliefs about these actors, including a decreased allegiance to the non-state actor. We rationalize these results with a model of motivated reasoning whereby reduced usage of non-state institutions makes people less likely to hold positive views about them. These results indicate that, despite substantial distrust of the state in Pakistan, credible new information can change beliefs and behavior. The feedback loop between state ineffectiveness and the legitimacy of non-state actors may be reversible.