A high proportion of skilled workers in the labor force implies a large market size for skill-complementary technologies, and encourages faster upgrading of the productivity of skilled workers. As a result, an increase in the supply of skills reduces the skill premium in the short run, but then it induces skill-biased technical change and increases the skill premium, possibly even above its initial value. This theory suggests that the rapid increase in the proportion of college graduates in the United States labor force in the 1970s may have been a causal factor in both the decline in the college premium during the 1970s and the large increase in inequality during the 1980s.

This paper proposes a microfoundation for social increasing returns in human capital accumulation. The underlying mechanism is a pecuniary externality due to the interaction of ex ante investments and costly bilateral search in the labor market. It is shown that the equilibrium rate of return on the human capital of a worker is increasing in the average human capital of the workforce even though all the production functions in the economy exhibit constant returns to scale, there are no technological externalities, and all workers are competing for the same jobs.

This paper explains why firms with identical opportunities may use different technologies and offer different wages. Our key assumption is that workers must engage in costly search in order to gather information about jobs (Stigler (1961)). In equilibrium, some firms adopt high fixed cost, high productivity technologies, offer high wages, and fill job openings quickly. Other firms adopt less capital-intensive technologies and offer low wages, hiring mostly uninformed workers. In equilibrium, the amount of wage dispersion leaves workers indifferent about whether to gather information, and the fraction of informed workers leaves firms indifferent about their wage and technology choice. We show that worker search, which would appear to be a rent-seeking activity in partial equilibrium, may be efficiency-enhancing in general equilibrium.

We show that even in the absence of diminishing returns in production and technological spillovers, international trade leads to a stable world income distribution. This is because specialization and trade introduce de facto diminishing returns: countries that accumulate capital faster than average experience declining export prices, depressing the rate of return to capital and discouraging further accumulation. Because of constant returns to capital accumulation from a global perspective, the world growth rate is determined by policies, savings, and technologies, as in endogenous growth models. Because of diminishing returns to capital accumulation at the country level, the cross-sectional behavior of the world economy is similar to that of existing exogenous growth models: cross-country variation in economic policies, savings, and technology translate into crosscountry variation in incomes. The dispersion of the world income distribution is determined by the forces that shape the strength of the terms-of-trade effects— the degree of openness to international trade and the extent of specialization.

Many technologies used by the LDCs are developed in the OECD economies and are designed to make optimal use of the skills of these richer countries' workforces. Differences in the supply of skills create a mismatch between the requirements of these technologies and the skills of LDC workers, and lead to low productivity in the LDCs. Even when all countries have equal access to new technologies, this technology-skill mismatch can lead to sizable differences in total factor productivity and output per worker. We provide evidence in favor of the cross-industry productivity patterns predicted by our model, and also show that technology-skill mismatch could account for a large fraction of the observed output per worker differences in the data.

We study the evolution of a social norm of “cooperation” in a dynamic environment. Each agent lives for two periods and interacts with agents from the previous and next generations via a coordination game. Social norms emerge as patterns of behaviour that are stable in part due to agents' interpretations of private information about the past, influenced by occasional commonly observed past behaviours. For sufficiently backward-looking societies, history completely drives equilibrium play, leading to a social norm of high or low cooperation. In more forward-looking societies, there is a pattern of “reversion” whereby play starting with high (low) cooperation reverts towards lower (higher) cooperation. The impact of history can be countered by occasional “prominent” agents, whose actions are visible by all future agents and who can leverage their greater visibility to influence expectations of future agents and overturn social norms of low cooperation.

During the nineteenth century most Western societies extended voting rights, a decision that led to unprecedented redistributive programs. We argue that these political reforms can be viewed as strategic decisions by the political elite to prevent widespread social unrest and revolution. Political transition, rather than redistribution under existing political institutions, occurs because current transfers do not ensure future transfers, while the extension of the franchise changes future political equilibria and acts as a commitment to redistribution. Our theory also offers a novel explanation for the Kuznets curve in many Western economies during this period, with the fall in inequality following redistribution due to democratization.

This paper offers a theory of training whereby workers do not pay for the general training they receive. The superior information of the current employer regarding its employees' abilities relative to other firms creates ex post monopsony power, and encourages this employer to provide and pay for training, even if these skills are general. The model can lead to multiple equlibria. In one equilibrium quits are endogenously high, and as a result employers have limited monopsony power and provide little training, while in another equilibrium quits are low and training is high. Using microdata on German apprentices, we show that the predictions of our model receive some support from the data.

Among countries colonized by European powers during the past 500 years, those that were relatively rich in 1500 are now relatively poor. We document this reversal using data on urbanization patterns and population density, which, we argue, proxy for economic prosperity. This reversal weighs against a view that links economic development to geographic factors. Instead, we argue that the reversal reflects changes in the institutions resulting from European colonialism. The European intervention appears to have created an “institutional reversal” among these societies, meaning that Europeans were more likely to introduce institutions encouraging investment in regions that were previously poor. This institutional reversal accounts for the reversal in relative incomes. We provide further support for this view by documenting that the reversal in relative incomes took place during the late eighteenth and early nineteenth centuries, and resulted from societies with good institutions taking advantage of the opportunity to industrialize.

We study the (perfect Bayesian) equilibrium of a sequential learning model over a general social network. Each individual receives a signal about the underlying state of the world, observes the past actions of a stochastically generated neighbourhood of individuals, and chooses one of two possible actions. The stochastic process generating the neighbourhoods defines the network topology. We characterize pure strategy equilibria for arbitrary stochastic and deterministic social networks and characterize the conditions under which there will be asymptotic learning—convergence (in probability) to the right action as the social network becomes large. We show that when private beliefs are unbounded (meaning that the implied likelihood ratios are unbounded), there will be asymptotic learning as long as there is some minimal amount of “expansion in observations”. We also characterize conditions under which there will be asymptotic learning when private beliefs are bounded.