Knowledge that Transforms

What is the pathway to development in a world marked by rising economic nationalism and less international integration? This paper answers this question within a framework that emphasizes the role of demand‐side constraints on national development, which is identified with sustained poverty reduction. In this framework, development is linked to the adoption of an increasing returns to scale technology by imperfectly competitive firms that need to pay the fixed setup cost of switching to that technology. Sustained poverty reduction is measured as a continuous decline in the share of the population living below $1.90/day purchasing power parity in 2011 U.S. dollars over a five‐year period. This outcome is affected in a statistically significant and economically meaningful way by domestic market size, which is measured as a function of the income distribution, and international market size, which is measured as a function of legally‐binding provisions to international trade agreements, including the General Agreement on Tariffs and Trade, the World Trade Organization, and 279 preferential trade agreements. Counterfactual estimates suggest that, in the absence of international integration, the average resident of a low‐ or lower‐middle‐income country does not live in a market large enough to experience sustained poverty reduction. Domestic redistribution targeted towards generating a larger middle class can partially compensate for the lack of an international market.

The U.S. spends significant amounts on non-medical transfers for its working-age population in a wide range of programs that support low and middle-income households. How valuable are these programs for U.S. households? Are there simpler, welfare improving ways to transfer resources that are supported by a majority? What are the macroeconomic effects of such alternatives? We answer these questions in an equilibrium, life-cycle model with single and married households who face idiosyncratic productivity risk, in the presence of costly children and potential skill losses of females associated with non-participation. Our findings show that a potential revenue-neutral elimination of the welfare state generates large welfare losses in the aggregate, although most households support the move as losses are concentrated among a small group. We fond that a Universal Basic Income program does not improve upon the current system. If instead per-person transfers are implemented alongside a proportional tax, a Negative Income Tax experiment, it becomes feasible to improve upon the current system. Providing per-person transfers to all households is costly, and reducing tax distortions helps to provide for resources to expand redistribution.

Two key features distinguish the general class of recursive preferences from the standard model of dynamic choice: (i) agents may care about the intertemporal distribution of risk, and (ii) their rates of time preference, rather than being fixed, may vary with the level of consumption. We investigate what these features imply in the context of a repeated strategic interaction. First, we show that opportunities for intertemporal trade may expand the set of feasible payoffs relative to that in a static interaction. Two distinct sources for such trade are identified: endogenous heterogeneity in the players' rates of time preference and a hedging motive pertaining to the intertemporal distribution of risk. The set of equilibrium payoffs may on the other hand shrink drastically as many efficient outcomes become unsustainable no matter the level of patience. This “antifolk” result occurs when the players prefer stage outcomes to be positively correlated rather than independent across time. Intuitively, such preferences make it inefficient to offset short‐term losses with future gains, while this is needed to ensure that security levels are met on path. We also establish a folk theorem: if security levels are met on path, such play can be sustained in a subgame perfect equilibrium provided that the players are sufficiently patient.

We propose a new simulation‐based estimation method, adversarial estimation, for structural models. The estimator is formulated as the solution to a minimax problem between a generator (which generates simulated observations using the structural model) and a discriminator (which classifies whether an observation is simulated). The discriminator maximizes the accuracy of its classification while the generator minimizes it. We show that, with a sufficiently rich discriminator, the adversarial estimator attains parametric efficiency under correct specification and the parametric rate under misspecification. We advocate the use of a neural network as a discriminator that can exploit adaptivity properties and attain fast rates of convergence.

In this paper, we formulate and estimate a flexible model of job mobility and wages with two‐sided heterogeneity. The analysis extends the finite mixture approach of Bonhomme, Lamadon, and Manresa (2019) and Abowd, McKinney, and Schmutte (2019) to develop a new Classification Expectation‐Maximization algorithm that ensures both worker and firm latent‐type identification using wage and mobility variations in the data. Workers receive job offers in worker‐type segmented labor markets. Offers are accepted according to a logit form that compares the value of the current job with that of the new job. In combination with flexibly estimated layoff and job finding rates, the analysis quantifies the four different sources of sorting: job preferences, segmentation, layoffs, and job finding. Job preferences are identified through job‐to‐job moves in a revealed preference argument. They are in the model structurally independent of the identified job wages, possibly as a reflection of the presence of amenities. We find evidence of a strong pecuniary motive in job preferences. While the correlation between preferences and current job wages is positive, the net present value of the future earnings stream given the current job correlates much more strongly with preferences for it. This is more so for short‐ than long‐tenure workers. In the analysis, we distinguish between type sorting and wage sorting. Type sorting is quantified by means of the mutual information index. Wage sorting is captured through correlation between identified wage types. While layoffs are less important than the other channels, we find all channels to contribute substantially to sorting. As workers age, job arrival processes are the key determinant of wage sorting, whereas the role of job preferences dictate type sorting. Over the life cycle, job preferences intensify, type sorting increases, and pecuniary considerations wane.

Since network data commonly consists of observations from a single large network, researchers often partition the network into clusters in order to apply cluster‐robust inference methods. Existing such methods require clusters to be asymptotically independent. Under mild conditions, we prove that, for this requirement to hold for network‐dependent data, it is necessary and sufficient that clusters have low conductance, the ratio of edge boundary size to volume. This yields a simple measure of cluster quality. We find in simulations that when clusters have low conductance, cluster‐robust methods control size better than HAC estimators. However, for important classes of networks lacking low‐conductance clusters, the former can exhibit substantial size distortion. To determine the number of low‐conductance clusters and construct them, we draw on results in spectral graph theory that connect conductance to the spectrum of the graph Laplacian. Based on these results, we propose to use the spectrum to determine the number of low‐conductance clusters and spectral clustering to construct them.

Identifying the strategies that are played is critical to understanding behavior in repeated games. This process is difficult because only choices (not strategies) are observable. Recently, a debate has emerged regarding whether subjects play mixed strategies in the indefinitely repeated prisoner's dilemma. We use an experimental approach to elicit mixed strategies from human subjects, thereby providing direct empirical evidence. We find that a majority of subjects use mixed strategies. However, the data also suggest subjects' strategies are becoming less mixed over time, and move toward three focal pure strategies: Tit For Tat, Grim Trigger, and Always Defect. We use the elicited strategies to provide an empirically‐relevant foundation for analyzing commonly used mixture model estimation procedures.

In this paper, I consider two normative questions: (1) how should policymakers approach tradeoffs that involve different age groups, and (2) at what rate should policymakers discount the consumption of future generations? I demonstrate that, under standard assumptions, these two questions are equivalent: caring more about the future means caring less about the elderly. Even small differences between the social discount rate and the market interest rate can have significant quantitative implications for the relative value placed on the consumption of different age groups.

We incorporate forward‐looking capital accumulation into a dynamic discrete choice model of migration. We characterize the steady‐state equilibrium; generalize existing dynamic exact‐hat algebra techniques to incorporate investment; and linearize the model to provide an analytical characterization of the economy's transition path using spectral analysis. We show that capital and labor dynamics interact to shape the economy's speed of adjustment toward steady state. We implement our quantitative analysis using data on capital stocks, populations, and bilateral trade and migration flows for U.S. states from 1965–2015. We show that this interaction between capital and labor dynamics plays a central role in explaining the observed decline in the rate of income convergence across U.S. states and the persistent and heterogeneous impact of local shocks.

How do political connections affect firm dynamics, innovation, and creative destruction? We extend a Schumpeterian growth model with political connections that help firms ease bureaucratic and regulatory burden. The model highlights how political connections influence an economy's business dynamism and innovation, and generates a number of implications guiding our empirical analysis. We construct a new large‐scale data set for the period 1993–2014, on the universe of firms, workers, and politicians, complemented with corporate financial statements, patent data, and election data, so as to define connected firms as those employing local politicians. We identify a leadership paradox: market leaders are much more likely to be politically connected, but much less likely to innovate. Political connections relate to a higher rate of survival, as well as growth in employment and revenues, but not in productivity—a result that we also confirm using the regression discontinuity design. At the aggregate level, gains from political connections do not offset losses stemming from lower reallocation and growth.