Knowledge that Transforms

This paper considers inference on fixed effects in a linear regression model estimated from network data. An important special case of our setup is the two‐way regression model. This is a workhorse technique in the analysis of matched data sets, such as employer–employee or student–teacher panel data. We formalize how the structure of the network affects the accuracy with which the fixed effects can be estimated. This allows us to derive sufficient conditions on the network for consistent estimation and asymptotically valid inference to be possible. Estimation of moments is also considered. We allow for general networks and our setup covers both the dense and the sparse case. We provide numerical results for the estimation of teacher value‐added models and regressions with occupational dummies.

We can often predict the behavior of those closest to us more accurately than that of complete strangers, yet we routinely engage in strategic situations with both: our social network impacts our strategic knowledge. Peer‐confirming equilibrium describes the behavioral consequences of this intuition in a noncooperative game. We augment a game with a network to represent strategic information: if two players are linked in the network, they have correct conjectures about each others' strategies. In peer‐confirming equilibrium, there is common belief that players (i) behave rationally and (ii) correctly anticipate neighbors' play. In simultaneous‐move games, adding links to the network always restricts the set of outcomes. In dynamic games, the outcome set may vary non‐monotonically with the network because the actions of well‐connected players help poorly‐connected players coordinate. This solution concept provides a useful language for studying public good provision, highlights a new channel through which central individuals facilitate coordination, and delineates possible sources of miscoordination in protests and coups.

We propose a framework to identify and estimate earnings distributions and worker composition on matched panel data, allowing for two‐sided worker‐firm unobserved heterogeneity and complementarities in earnings. We introduce two models: a static model that allows for nonlinear interactions between workers and firms, and a dynamic model that allows, in addition, for Markovian earnings dynamics and endogenous mobility. We show that this framework nests a number of structural models of wages and worker mobility. We establish identification in short panels, and develop tractable two‐step estimators where firms are classified in a first step. Applying our method to Swedish administrative data, we find that log‐earnings are approximately additive in worker and firm heterogeneity. Our estimates imply the presence of strong sorting patterns between workers and firms, and a small contribution of firms—net of worker composition—to earnings dispersion. In addition, we document that wages have a direct effect on mobility, and that, beyond their dependence on the current firm, earnings after a job move also depend on the previous employer.

We study Pareto optimal policy reforms aimed at overhauling retirement financing as an integral part of the tax and transfer system. Our framework for policy analysis is a heterogeneous‐agent overlapping‐generations model that performs well in matching the aggregate and distributional features of the U.S. economy. We present a test of Pareto optimality that identifies the main source of inefficiency in the status quo policies. Our test suggests that lack of asset subsidies late in life is the main source of inefficiency when annuity markets are incomplete. We solve for Pareto optimal policy reforms and show that progressive asset subsidies provide a powerful tool for Pareto optimal reforms. On the other hand, earnings tax reforms do not always yield efficiency gains. We implement our Pareto optimal policy reform in an economy that features demographic change. The reform reduces the present discounted value of net resources consumed by each generation by about 7 to 11 percent in the steady state. These gains amount to a one‐time lump‐sum transfer to the initial generation equal to 10.5 percent of GDP.

We study stability of two-sided many-to-one matching in which firms' preferences for workers may exhibit complementarities. Although such preferences are known to jeopardize stability in a finite market, we show that a stable matching exists in a large market with a continuum of workers, provided that each firm's choice is convex and changes continuously as the set of available workers changes. We also study the existence and structure of stable matchings under preferences exhibiting substitutability and indifferences in a large market. Building on these results, we show that an approximately stable matching exists in large finite economies. We extend our framework to ensure a stable matching with desirable incentive and fairness properties in the presence of indifferences in firms' preferences.

In a transformation model , where the errors are i.i.d. and independent of the explanatory variables , the parameters can be estimated by a pseudo‐maximum likelihood (PML) method, that is, by using a misspecified distribution of the errors, but the PML estimator of is in general not consistent. We explain in this paper how to nest the initial model in an identified augmented model with more parameters in order to derive consistent PML estimators of appropriate functions of parameter . The usefulness of the consistency result is illustrated by examples of systems of nonlinear equations, conditionally heteroscedastic models, stochastic volatility, or models with spatial interactions.

We provide a nonlinear characterization of the macroeconomic impact of microeconomic productivity shocks in terms of reduced‐form nonparametric elasticities for efficient economies. We also show how microeconomic parameters are mapped to these reduced‐form general equilibrium elasticities. In this sense, we extend the foundational theorem of Hulten (1978) beyond the first order to capture nonlinearities. Key features ignored by first‐order approximations that play a crucial role are: structural microeconomic elasticities of substitution, network linkages, structural microeconomic returns to scale, and the extent of factor reallocation. In a business‐cycle calibration with sectoral shocks, nonlinearities magnify negative shocks and attenuate positive shocks, resulting in an aggregate output distribution that is asymmetric (negative skewness), fat‐tailed (excess kurtosis), and has a negative mean, even when shocks are symmetric and thin‐tailed. Average output losses due to short‐run sectoral shocks are an order of magnitude larger than the welfare cost of business cycles calculated by Lucas (1987). Nonlinearities can also cause shocks to critical sectors to have disproportionate macroeconomic effects, almost tripling the estimated impact of the 1970s oil shocks on world aggregate output. Finally, in a long‐run growth context, nonlinearities, which underpin Baumol's cost disease via the increase over time in the sales shares of low‐growth bottleneck sectors, account for a 20 percentage point reduction in aggregate TFP growth over the period 1948–2014 in the United States.

Endogenous demand composition across sectors due to income elasticity differences, or Engel's Law for brevity, affects (i) sectoral compositions in employment and in value‐added, (ii) variations in innovation rates and in productivity change across sectors, (iii) intersectoral patterns of trade across countries, and (iv) product cycles from rich to poor countries. Using a two‐country model of directed technical change with a continuum of sectors under nonhomothetic preferences, which is rich enough to capture all these effects as well as their interactions, this paper offers a unifying perspective on how economic growth and globalization affect the patterns of structural change, innovation, and trade across countries and across sectors in the presence of Engel's Law. Among the main messages is that globalization amplifies, instead of reducing, the power of endogenous domestic demand composition differences as a driver of structural change.

Can participation in financial markets lead individuals to reevaluate the costs of conflict, change their political attitudes, and even their votes? Prior to the 2015 Israeli elections, we randomly assigned Palestinian and Israeli financial assets to likely voters and incentivized them to actively trade for up to 7 weeks. No political messages or nonfinancial information were included. The treatment systematically shifted vote choices toward parties more supportive of the peace process. This effect is not due to a direct material incentive to vote a particular way. Rather, the treatment reduces opposition to concessions for peace and changes awareness of the broader economic risks of conflict. While participants who were assigned Palestinian assets are more likely to associate their assets' performance with peace, they are less engaged in the experiment. Combined with the superior performance of Israeli stocks during the study period, the ultimate effects of Israeli and Palestinian assets are similar.

An empirical approach to optimal income taxation design is developed within an equilibrium collective marriage market model with imperfectly transferable utility. Taxes distort time allocation decisions, as well as marriage market outcomes, and the within household decision process. Using data from the American Community Survey and American Time Use Survey, we structurally estimate our model and explore empirical design problems. We allow taxes to depend upon marital status, with the form of tax jointness for married couples unrestricted. We find that the optimal tax system for married couples is characterized by negative jointness, although the welfare gains from jointness are modest. These welfare gains are then shown to be increasing in the gender wage gap, with taxes here, as in the case of gender based taxation, providing an instrument to address within household inequality.