Knowledge that Transforms

We develop models that take point forecasts from the Survey of Professional Forecasters (SPF) as inputs and produce estimates of survey-consistent term structures of expectations and uncertainty at arbitrary forecast horizons. Our models combine fixed-horizon and fixed-event forecasts, accommodating time-varying horizons and availability of survey data, as well as potential inefficiencies in survey forecasts. The estimated term structures of SPF-consistent expectations are comparable in quality to the published, widely used short-horizon forecasts. Our estimates of time-varying forecast uncertainty reflect historical variations in realized errors of SPF point forecasts, and generate fan charts with reliable coverage rates.

International trade has rapidly increased in the past decades, affecting production and labor demand across various economic sectors. The impact of trade on employment and welfare relies heavily on data about worker reallocation, which often contains coding errors. This study demonstrates that such errors bias the estimated effects of trade and structural parameters in standard models. An econometric framework is developed to estimate misclassification probabilities, correct mobility matrices, and structural parameters. The findings reveal that the true effects of trade shocks differ significantly from those estimated using uncorrected data, highlighting the importance of addressing coding errors in economic analyses.

Many economic panel and dynamic models, such as rational behavior and Euler equations, imply that the parameters of interest are identified by conditional moment restrictions. We introduce a novel inference method without any prior information about which conditioning instruments are weak or irrelevant. Building on Bierens (1990), we propose penalized maximum statistics and combine bootstrap inference with model selection. Our method optimizes asymptotic power by solving a data-dependent max-min problem for tuning parameter selection. Extensive Monte Carlo experiments, based on an empirical example, demonstrate the extent to which our inference procedure is superior to those available in the literature. [C12, C36].

We propose a new inference method in high-dimensional regression models and high-dimensional IV regression models. The method is shown to be valid without requiring the exact sparsity or Lp sparsity conditions. Simulation studies demonstrate superior performance of this proposed method over those based on LASSO or random forest, especially under less sparse models. We illustrate an application to production analysis with a panel of Chilean firms.

This paper examines how to bundle household health insurance, treating each member’s policy as a product in the bundle. Two regimes are analyzed: pure bundling and bundle discounts. Pure bundling is socially optimal when willingness to pay differs across members, when the bundle is valued more than individual components, or when households prefer insuring costlier members, implying within-household adverse selection. Using Vietnam’s Social Health Insurance data, structural estimates show substantial heterogeneity in willingness to pay, driven mainly by health-type differences. A pure bundling policy increases consumer surplus by 43% relative to bundle discounts.

We experimentally examine how individuals commit to a cutoff stopping rule when facing a sequence of independent lotteries. We identify two main behavior patterns: (a) a small share of participants consistently choose stopping rules whose gain bound (i.e., the accumulated gain at which the sequence stops) is larger than the loss bound, and (b) a larger share of participants consistently choose rules whose loss bound is larger than the gain bound. We introduce a procedural choice model that accounts for these patterns and show that the behavior of most of our participants is inconsistent with prominent theories of decision under risk.

We study college admissions markets where students can attend the same college under different financial terms. The deferred acceptance algorithm identifies a stable allocation where funding is allocated based on merit and the set of meritbased stable allocations is small. When students are heterogeneous in the way they trade off program characteristics and contractual terms, the set of stable allocations is large and different stable allocations differ in the number of assigned students. In Hungary, where such heterogeneity is present, a non-merit-based stable allocation would increase the number of assigned applicants by 1.9% relative to any merit-based stable allocation.

We study the implications of the presence of foreign multinationals on regional corporate tax policies of a country. We develop and estimate a quantitative spatial model with multinational production (MP) and local corporate taxes. Exploiting China's 2008 corporate tax reform, we find that firm production across regions is twice as footloose as estimates in the literature on cross-country production. Counterfactual analysis shows that (i) China's 2008 corporate tax reform shifted foreign-firm productions to western provinces and increased Chinese welfare by 0.86%; (ii) regional tax competition would significantly reduce China's corporate tax revenue, lowering the welfare by 5.56%; (iii) the nationally optimal corporate tax schedule would increase Chinese welfare by 3.10%. Finally, without the presence of foreign multinationals, the welfare loss from regional tax competition would be 2.04%, while the gain from the nationally optimal corporate taxes would be only 0.06%.

Recently, mandatory pension contributions in Iceland were increased substantially in the private sector while remaining unchanged in the public sector. Taking this as a large natural experiment, this paper studies the effects of this change on households’ voluntary saving, using comprehensive third-party reported information on income, assets, and debt for all taxpayers. Using difference-in-differences, we find that households do not reduce voluntary saving when faced with a rise in mandatory saving. Our results are supported by an event study of workers switching from the private sector to the public sector. Survey evidence suggests widespread ignorance about the pension system.

I show that parents select schools that improve the student-school match. Using the centralized algorithm for offers to primary schools in London, I compare the achievement of students who are as good as randomly enroled in schools ranked differently in their application. Enroling at the first choice compared to a school ranked lower increases achievement by 0.03 standard deviations per year beyond the average school value-added across students. Match effects arise from unobserved student's and school's attributes, and are larger for relatively advantaged students. Results imply that parental choice can increase aggregate learning.