College of Humanities, Arts, and Social Sciences

This study examines how controlling misinformation on a social media platform in Pakistan affects users’ exposure to both accurate and false information. It combines an intervention to disseminate official information about the COVID-19 pandemic across the platform with a randomized experiment that measures the impact of fully controlling access to pandemic-related misinformation. The treatments rely on a higher-intensity, ex ante approach to moderating misinformation on the platform relative to the control, which relies on a typical ex post approach to moderation. Fully controlling misinformation, as in the treatments, reduces the number of daily users by 19%, indicating a distaste for moderation. Furthermore, the treatments reduce exposure to official information by 29% more than they reduce exposure to misinformation. A conceptual framework posits that these findings can be explained by the fact that, in this setting, official information is more trusted, and thus is more widely disseminated, relative to misinformation.

We measure the impact of two main signals of tertiary-level human capital accumulation, college quality and certification, on hiring in India. Using a correspondence experiment, we send 16,944 resumes to 1,412 job postings for recent engineering graduates at small and medium firms. We do not find evidence that either of the two signals that we consider have effects on callbacks separately. Specifically, the impact of having graduated from a mid-tier college ranked in the top 300 relative to an unranked college outside of the top 1000 is close to zero and precisely estimated, despite significant government investment in ranking colleges in India. There is also a precisely estimated null effect of scoring in the highest as opposed to the lowest quartile of a post-tertiary certification test that has been taken by millions of graduating students. Resumes with female names modestly benefit in this first stage of the hiring process.

Abstract: We estimate a matching model of teachers and elementary schools with rich data on teachers' applications and principals' ratings from a large, urban district in North Carolina. Both teachers’ and principals’ preferences deviate from those that would maximize the achievement of economically disadvantaged students: teachers prefer schools with fewer disadvantaged students, and principals' ratings are weakly related to teacher effectiveness. In equilibrium, these two deviations combine to produce a surprisingly equitable current allocation, where teacher quality is balanced across advantaged and disadvantaged students. To close achievement gaps, policies that address deviations on one side alone are ineffective or harmful, while policies that address both could substantially increase the achievement of disadvantaged students.

This article studies international reserves’ nominal exchange rate stabilizing impact in emerging markets and developing countries, with a particular focus on its nonlinearity and asymmetry across different states of the economy. Using the fixed-effects and dynamic panel threshold models, we find the reserves to short-term debt threshold ratio after which the marginal stabilizing effect of reserves begins to fall during tranquil times. Such diminishing returns, however, do not appear to exist even at the excessive level of reserves during the global financial crisis, partly justifying precautionary demand for international reserves. These results call for extending reserve pooling or swap arrangements to enhance efficiency of reserve management by holding adequate, rather than excess, international reserves with an access to emergency lending during the crisis.

Summary: We propose the construction of conditional growth densities under stressed factor scenarios to assess the level of exposure of an economy to small probability but potentially catastrophic economic and/or financial scenarios, which can be either domestic or international. The choice of severe yet plausible stress scenarios is based on the joint probability distribution of the underlying factors driving growth, which are extracted with a multilevel dynamic factor model (DFM) from a wide set of domestic/worldwide and/or macroeconomic/financial variables. All together, we provide a risk management tool that allows for a complete visualization of the dynamics of the growth densities under average scenarios and extreme scenarios. We calculate growth‐in‐stress (GiS) measures, defined as the 5% quantile of the stressed growth densities, and show that GiS is a useful and complementary tool to growth‐at‐risk (GaR) when policymakers wish to carry out a multidimensional scenario analysis. The unprecedented economic shock brought by the COVID‐19 pandemic provides a natural environment to assess the vulnerability of US growth with the proposed methodology.

Summary: We propose a per‐cluster instrumental variable (PCIV) approach for estimating linear correlated random coefficient models in the presence of contemporaneous endogeneity and two‐way fixed effects. This approach estimates heterogeneous effects and aggregates them to population averages. We demonstrate consistency, showing robustness over standard estimators, and provide analytic standard errors for robust inference. In Monte Carlo simulation, PCIV performs relatively well in finite samples in either dimension. We apply PCIV in estimating the price elasticity of gasoline demand using state fuel taxes as instrumental variables. We find significant elasticity heterogeneity and more elastic gasoline demand on average than with standard estimators.

Commodity booms generally induce real exchange rate appreciation in commodity-rich economies and make other tradable sectors less competitive. This “Dutch disease” phenomenon has been blamed for leading to structures of production with low diversification and undermining sustainable growth. In this paper, we explore whether capital controls can mitigate the transmission of commodity price changes to the real exchange rate and shield manufactured exports. Examining a panel of 37 commodity-abundant countries over the period 1980–2020, we find that a steeper commodity currency appreciation indeed has a more detrimental impact on manufactured exports. Restrictions on capital flows tend to reduce real appreciation pressures and the severity of the Dutch disease. Countercyclical capital controls seem to help foster economic diversification in commodity-dependent developing countries.

This study examines the dissemination of (mis)information on a social media platform in Pakistan. It combines an intervention to disseminate official information about the COVID-19 pandemic across the platform with a randomized experiment that measures the impact of fully controlling access to pandemic-related misinformation. The two treatments rely on a higherintensity, ex-ante approach to moderating misinformation on the platform relative to the control, which relies on a more standard ex-post approach to moderation. In one treatment, no misinformation was allowed on the platform, while in the other, it was allowed with an official rebuttal. Controlling misinformation, as in the treatments, reduces platform usage by 41%, indicating a distaste for moderation. Furthermore, the treatments reduce exposure to official information by 29% more than they reduce exposure to misinformation. A conceptual framework posits that these findings can be explained by the fact that, in this setting, official information is more trusted, and thus is more widely disseminated, relative to misinformation. We find evidence for two potential mechanisms for the observed distaste for moderation.