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We study optimal dynamic Ramsey policies in a standard growth model with financial frictions. For developing countries with low financial wealth, the optimal policy intervention increases labor supply and lowers wages, resulting in higher entrepreneurial profits and faster wealth accumulation. This in turn relaxes borrowing constraints in the future, leading to higher labor productivity and wages. The use of additional policy instruments, such as subsidized credit, may be optimal as well. In the long run, the optimal policy reverses sign. Taking advantage of the tractability of our framework, we extend the model to study its implications for optimal exchange rate and sectoral industrial policies.
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We take an off-the-shelf model with financial frictions and heterogeneity, and study the mapping from a credit crunch, modeled as a shock to collateral constraints, to simple aggregate wedges. We study three variants of this model that only differ in the form of underlying heterogeneity. We find that in all three model variants a credit crunch shows up as a different wedge: efficiency, investment, and labor wedges. Furthermore, all three model variants have an undistorted Euler equation for the aggregate of firm owners. These results highlight the limitations of using representative agent models to identify sources of business cycle fluctuations.
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We analyze a model economy with many agents, each with a different productivity level. Agents divide their time between two activities: producing goods with the production-related knowledge they already have, and interacting with others in search of new, productivity-increasing ideas. These choices jointly determine the economy's current production level and its rate of learning and real growth. Individuals' time allocation decisions depend on the knowledge distribution because the productivity levels of others determine their own chances of improving their productivities through search. The time allocations of everyone in the economy in turn determine the evolution of its knowledge distribution. We construct the balanced growth path for this economy, thereby obtaining a theory of endogenous growth that captures in a tractable way the social nature of knowledge creation. We also study the allocation chosen by an idealized planner who takes into account and internalizes the external benefits of search, and tax structures that implement an optimal solution. Finally, we provide two examples of alternative learning technologies, as concrete illustrations of other directions that might be pursued.
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Motivated by evidence from the micro data that the type of financial frictions faced by individuals varies across regions within countries, we develop a general equilibrium framework that encompasses different micro financial underpinnings. We use it to compare the implications of two concrete frictions, limited commitment and moral hazard, and argue that these have potentially very different implications at both the macro and the micro level. Aggregate productivity is depressed in the two regimes but for completely different reasons: under limited commitment capital is misallocated across heterogeneous firms. In contrast, under moral hazard, productivity is endogenously lower at the firm level because entrepreneurs exert suboptimal effort. Occupational choice, productivity and firm size distribution, income and wealth inequality, and the speed of individual transitions also differ markedly. We also present an economy with different frictions in different regions. Such mixture regimes turn out to be different from simple convex combinations of the pure moral hazard and pure limited commitment regimes, and they produce interregional patterns of aggregate income, capital and labor flows and external finance that resemble rural-urban patterns observed in the data.
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We revisit the transmission mechanism of monetary policy for household consumption in a Heterogeneous Agent New Keynesian (HANK) model. The model yields empirically realistic distributions of household wealth and marginal propensities to consume because of two key features: multiple assets with different degrees of liquidity and an idiosyncratic income process with leptokurtic income changes. In this environment, the indirect effects of an unexpected cut in interest rates, which operate through a general equilibrium increase in labor demand, far outweigh direct effects such as intertemporal substitution. This finding is in stark contrast to small- and medium-scale Representative Agent New Keynesian (RANK) economies, where intertemporal substitution drives virtually all of the transmission from interest rates to consumption.
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Using recently available large-sample micro data from 36 countries, we document that experience-earnings profiles are flatter in poor countries than in rich countries. Motivated by this fact, we conduct a development accounting exercise that allows the returns to experience to vary across countries but is otherwise standard. When the country-specific returns to experience are interpreted in such a development accounting framework – and are therefore accounted for as part of human capital – we find that human and physical capital differences can account for almost two thirds of the variation in cross-country income differences, as compared to less than half in previous studies.
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The past forty years have seen a rapid rise in top income inequality in the United States. While there is a large number of existing theories of the Pareto tails of the income and wealth distributions at a given point in time, almost none of these address the fast rise in top inequality observed in the data. We show that standard theories, which build on a random growth mechanism, generate transition dynamics that are an order of magnitude too slow relative to those observed in the data. We then suggest parsimonious deviations from the basic model that can explain such changes, namely heterogeneity in mean growth rates or deviations from Gibrat's law. These deviations are consistent with theories in which the increase in top income inequality is driven by the rise of "superstar" entrepreneurs or managers.
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How much does life-cycle human capital accumulation vary across countries? This paper seeks to answer this question by studying U.S. immigrants, who come from a wide variety of countries but work in a common labor market. We document that returns to potential experience among U.S. immigrants are higher on average for workers coming from rich countries than for those coming from poor countries. To understand this fact we build a model of life-cycle human capital accumulation that features three potential theories, working respectively through cross-country differences in: selection, skill loss, and human capital accumulation. To distinguish between theories, we use new data on the characteristics of immigrants and non-migrants from a large set of countries. We conclude that the most likely theory is that immigrants from poor countries accumulate relatively less human capital in their birth countries before migrating. Our findings imply that life cycle human capital stocks are on average much larger in rich countries than poor countries.
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