A Fast Literature Search Engine based on top-quality journals, by Dr. Mingze Gao.

• Patterson, C. (2023). The Matching Multiplier and the Amplification of Recessions. American Economic Review, 113, 982–1012.

  This paper shows that the unequal incidence of recessions in the labor market amplifies aggregate shocks. Using administrative data from the United States, I document a positive covariance between workers' marginal propensities to consume (MPCs) and their elasticities of earnings to GDP, which is a key moment for a new class of heterogeneous-agent models. I define the matching multiplier as the increase in the multiplier stemming from this matching of high MPC workers to more cyclical jobs. I show that this covariance is large enough to increase the aggregate MPC by 20 percent over an equal exposure benchmark.

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• Redding, S. J., Rossi-Hansberg, E., & s, P. A. (2023). Globalization and Pandemics. American Economic Review, 113, 939–981.

  We provide theory and evidence on the relationship between globalization and pandemics. Business travel facilitates trade and travel leads to human interactions that transmit disease. Trade-motivated travel generates an epidemiological externality across countries. If infections lead to deaths, or reduce individual labor supply, we establish a general equilibrium social distancing effect, whereby increases in relative prices in unhealthy countries reduce travel to those countries. If agents internalize the threat of infection, we show that their behavioral responses lead to a reduction in travel that is larger for higher-trade-cost locations, which initially reduces the ratio of trade to output.

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• Sraer, D., & Thesmar, D. (2023). How to Use Natural Experiments to Estimate Misallocation. American Economic Review, 113, 906–938.

  We propose a method to estimate the effect of firm policies (e.g., bankruptcy laws) on allocative efficiency using (quasi-)experimental evidence. Our approach takes general equilibrium effects into account and requires neither a structural estimation nor a precise assumption on how the experiment affects firms. Our aggregation formula relies on treatment effects of the policy on the distribution of output-to-capital ratios, which are easily estimated. We show this method is valid for a large class of commonly used models in macrofinance. We apply it to the French banking deregulation episode of the mid-1980s and find an increase in aggregate TFP of 5 percent.

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• Dávila, E., & Parlatore, C. (2023). Volatility and Informativeness. Journal of Financial Economics, 147, 550–572.

  This paper studies the relation between volatility and informativeness in financial markets. We identify two channels (noise-reduction and equilibrium-learning) that determine the volatility-informativeness relation. When informativeness is sufficiently high (low), volatility and informativeness positively (negatively) comove in equilibrium. We identify conditions on primitives that guarantee that volatility and informativeness comove positively or negatively. We introduce the comovement score, a statistic that measures the distance of a given asset to the positive/negative comovement regions. Empirically, comovement scores (i) have trended downwards over the last decades, (ii) are positively related to value and idiosyncratic volatility and negatively to size and institutional ownership.

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• García, D., Hu, X., & Rohrer, M. (2023). The Colour of Finance Words. Journal of Financial Economics, 147, 525–549.

  Our paper relies on stock price reactions to colour words, in order to provide new dictionaries of positive and negative words in a finance context. We extend the machine learning algorithm of Taddy (2013), adding a cross-validation layer to avoid over-fitting. In head-to-head comparisons, our dictionaries outperform the standard bag-of-words approach (Loughran and McDonald, 2011) when predicting stock price movements out-of-sample. By comparing their composition, word-by-word, our method refines and expands the sentiment dictionaries in the literature. The breadth of our dictionaries and their ability to disambiguate words using bigrams both help to colour finance discourse better.

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• Li, X., Liu, T., & Taylor, L. A. (2023). Common Ownership and Innovation Efficiency. Journal of Financial Economics, 147, 475–497.

  How does common ownership affect innovation? We study this question using project-level data on pharmaceutical startups and their venture capital (VC) investors. We find that common ownership leads VCs to hold back projects, withhold funding, and redirect innovation at lagging startups. Effects are stronger where R&D costs are larger, consistent with common owners aiming to cut duplicate costs. Effects are also stronger where technological similarity is greater and preexisting competition is lower, consistent with common owners seeking market power for their surviving projects. Overall, common VC ownership appears to generate social benefits, via improved innovation efficiency, but also social costs.

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• Bauer, M. D., & Swanson, E. T. (2023). An Alternative Explanation for the “Fed Information Effect.” American Economic Review, 113, 664–700.

  Regressions of private-sector macroeconomic forecast revisions on monetary policy surprises often produce coefficients with signs opposite to standard macroeconomic models. The "Fed information effect" argues these puzzling results are due to monetary policy surprises revealing Fed private information. We show they are also consistent with a "Fed response to news" channel, where both the Fed and professional forecasters respond to incoming economic news. We present new evidence challenging the Fed information effect and supporting the Fed response to news channel, including: regressions that control for economic news, our own survey of professional forecasters, and financial market responses to FOMC announcements.

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• Bhatt, M. P., Cook, P. J., Davis, J. M. V., Dodge, K., Farkas, G., Fryer, R. G., … Stoddard, G. (2023). Not Too Late: Improving Academic Outcomes among Adolescents. American Economic Review, 113, 738–765.

  Improving academic outcomes for economically disadvantaged students has proven challenging, particularly for children at older ages. We present two large-scale randomized controlled trials of a high-dosage tutoring program delivered to secondary school students in Chicago. One innovation is to use paraprofessional tutors to hold down cost, thereby increasing scalability. Participating in math tutoring increases math test scores by 0.18 to 0.40 standard deviations and increases math and non-math course grades. These effects persist into future years. The data are consistent with increased personalization of instruction as a mechanism. The benefit-cost ratio is comparable to many successful early-childhood programs.

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• Carlino, G., Drautzburg, T., Inman, R., & Zarra, N. (2023). Partisanship and Fiscal Policy in Economic Unions: Evidence from US States. American Economic Review, 113, 701–737.

  Partisanship of state governors affects the efficacy of US federal fiscal policy. Using close election data, we find partisan differences in the marginal propensity to spend federal intergovernmental transfers: Republican governors spend less than Democratic governors. Correspondingly, Republican-led states have lower debt, (delayed) lower taxes, and initially lower economic activity. A New Keynesian model of partisan states in a monetary union implies sizable aggregate effects: The intergovernmental transfer impact multiplier rises by 0.58 if Republican governors spend like Democratic governors, but due to delayed tax cuts, the long-run multiplier is higher with more Republican governors, generating an intertemporal policy trade-off.

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• Corrao, R., Flynn, J. P., & Sastry, K. A. (2023). Nonlinear Pricing with Underutilization: A Theory of Multi-part Tariffs. American Economic Review, 113, 836–860.

  We study the nonlinear pricing of goods whose usage generates revenue for the seller and of which buyers can freely dispose. The optimal price schedule is a multi-part tariff, featuring tiers within which buyers pay a marginal price of zero. We apply our model to digital goods, for which advertising, data generation, and network effects make usage valuable, but monitoring legitimate usage is infeasible. Our results rationalize common pricing schemes including free products, free trials, and unlimited subscriptions. The possibility of free disposal harms producer and consumer welfare and makes both less sensitive to changes in usage-based revenue and demand.

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