Knowledge that Transforms

Diversity can pose fundamental challenges to state building and development. The Tanzanian Ujamaa policy—one of post-colonial Africa’s largest state-building experiments—addressed these challenges by resettling a diverse population in planned villages, where children received political education. We combine differences in exposure to Ujamaa across space and age to identify long-term impacts of the policy. Analysis of contemporary surveys shows persistent, positive effects on national identity and perceived state legitimacy. Our preferred interpretation, supported by evidence that considers alternative hypotheses, is that changes to educational content drive our results. Our findings also point to trade-offs associated with state building: while the policy contributed to establishing the new state as a legitimate central authority, exposure to Ujamaa lowered demands for democratic accountability and did not increase generalized inter-ethnic trust.

Industrial policies are widely used across the world. In practice, designing and implementing these policies is a complicated task. In this paper, we assess the long-term performance of different industrial policy instruments, which include production subsidies, investment subsidies, entry subsidies, and consolidation policies. To do so, we examine a recent industrial policy in China aiming to propel the country’s shipbuilding industry to the largest globally. Using firm-level data from 1998 to 2014 and a dynamic model of firm entry, exit, investment, and production, we find that (i) the policy boosted China’s domestic investment, entry, and international market share dramatically, but delivered low returns and led to fragmentation, idle capacity, as well as depressed world ship prices; (ii) the effectiveness of different policy instruments is mixed: production and investment subsidies can be justified by market share considerations, while entry subsidies are wasteful; (iii) counter-cyclical policies, firm-targeting, and shortening the intervention horizon can substantially reduce distortions. Our results highlight the critical role of firm heterogeneity, business cycles, and firms’ cost structure in policy design. Finally, when exploring potential rationales, we find support for nonclassical considerations, such as reducing freight rates to boost Chinese trade.

Calibration, the practice of choosing the parameters of a structural model to match certain empirical moments, can be viewed as minimum distance estimation. Existing standard error formulas for such estimators require a consistent estimate of the correlation structure of the empirical moments, which is often unavailable in practice. Instead, the variances of the individual empirical moments are usually readily estimable. Using only these variances, we derive conservative standard errors and confidence intervals for the structural parameters that are valid even under the worst-case correlation structure. In the over-identified case, we show that the moment weighting scheme that minimizes the worst-case estimator variance amounts to a moment selection problem with a simple solution. Finally, we develop tests of over-identifying or parameter restrictions. We apply our methods empirically to a model of menu cost pricing for multi-product firms and to a heterogeneous agent New Keynesian model.

This article studies the problem of optimally allocating treatments in the presence of spillover effects, using information from a (quasi-)experiment. I introduce a method that maximizes the sample analogue of average social welfare when spillovers occur. I construct semi-parametric welfare estimators with known and unknown propensity scores and cast the optimization problem into a mixed-integer linear program, which can be solved using off-the-shelf algorithms. I derive a strong set of guarantees on regret, i.e. the difference between the maximum attainable welfare and the welfare evaluated at the estimated policy. The proposed method presents attractive features for applications: (i) it does not require network information of the target population; (ii) it exploits heterogeneity in treatment effects for targeting individuals; (iii) it does not rely on the correct specification of a particular structural model; and (iv) it accommodates constraints on the policy function. An application for targeting information on social networks illustrates the advantages of the method.

We develop a method of solving rational expectations models with dispersed information and dynamic strategic complementarities. In these types of models, the equilibrium outcome hinges on an infinite number of higher-order expectations which require an increasing number of state variables to keep track of. Despite this complication, we prove that the equilibrium outcome always admits a finite-state representation when the signals follow finite ARMA processes. We also show that such a finite-state result may not hold with endogenous information aggregation. We further illustrate how to use the method to derive comparative statics, characterize equilibrium outcomes in HANK-type network games, reconcile with empirical evidence on expectations, and integrate incomplete information with bounded rationality in general equilibrium.

We develop a theory of information spillovers in sovereign bond markets in which investors can learn about default risk before trading in primary and secondary markets. If primary markets are structured as multi-unit discriminatory-price auctions, an endogenous winner’s curse leads to strategic complementarities in information acquisition. Shocks to default risk in one country may trigger crisis episodes with widespread information acquisition, sharp increases in the level and volatility of yields in risky countries, low and stable yields in safe countries, market segmentation, and arbitrage profits between primary and secondary markets. These predictions are consistent with the dynamics of auction informativeness during the Eurozone Sovereign Debt Crisis, which we measure using the reaction of secondary market yields to primary market yields.

Evidence across disciplines suggests that talk therapy is more curative than antidepressants for mild-to-moderate depression and anxiety. Yet, few patients use it. We develop a dynamic choice model to analyse patient demand for the treatment of depression and anxiety. The model incorporates myriad potential impediments to therapy use along with links between mental health improvements and earnings. The estimated model reveals that mental health improvements are valuable, directly through utility and indirectly through earnings. However, patient reluctance to use therapy is nearly impervious to reasonable counterfactual policies (e.g. lowering prices or removing other costs). Patient behaviour might reflect stigma, biases in beliefs about the effectiveness of therapy, or a distaste for discussing personal or painful issues with a stranger. More broadly, the benefits of therapy estimated in randomized trials tell only half the story. If patients do not use treatments outside of an experimental setting—and we fail to understand why or how to get them to—estimated treatment effects cannot be leveraged.

This study argues that the decline of coercive labour institutions over the course of industrialization was partly driven by complementarity between physical capital and effective labour in manufacturing. Given the difficulty of extracting labour effort in care-intensive industrial tasks through monitoring and punishment, capital-owning elites ultimately chose to emancipate workers to induce their supply of effective labour and, thus, boost the return to physical capital. This hypothesis is empirically examined in the context of serf emancipation in nineteenth-century Prussia. Exploiting variation in proto-industrialization across Prussian counties, the analysis finds that, consistent with the proposed hypothesis, the initial abundance of elite-owned physical capital is associated with a higher pace of serf emancipation and lower redemption payments to manorial lords.

We analyse the joint life-cycle dynamics of labour market and mental health outcomes while allowing for two-way interactions between work and mental health. We model selection into jobs on a labour market with search frictions, accounting for the level of exposure to stress in each job using data on occupational health contents. Taking our model to British data from Understanding Society combined with information from O*NET, we estimate the impact of job characteristics on health dynamics and the effects of health and job stress contents on career choices. We use our model to quantify the effects of job loss, health shocks, or job stress shocks that propagate over the life cycle through both health and work channels. We also estimate the (large) values workers attach to health, employment, or nonstressful jobs.

Social interactions determine many economic behaviours, but information on social ties does not exist in most publicly available and widely used datasets. We present results on the identification of social networks from observational panel data that contains no information on social ties between agents. In the context of a canonical social interactions model, we provide sufficient conditions under which the social interactions matrix, endogenous and exogenous social effect parameters are globally identified if networks are constant over time. We also provide an extension of the method for time-varying networks. We then describe how high-dimensional estimation techniques can be used to estimate the interactions model based on the adaptive elastic net Generalized Method of Moments. We employ the method to study tax competition across U.S. states. The identified social interactions matrix implies that tax competition differs markedly from the common assumption of competition between geographically neighbouring states, providing further insights into the long-standing debate on the relative roles of factor mobility and yardstick competition in driving tax setting behaviour across states. Most broadly, our identification and application show that the analysis of social interactions can be extended to economic realms where no network data exist.