Economics - 2020

Mitchell, K., & Pearce, D. K. (2020). HOW DID UNCONVENTIONAL MONETARY POLICY AFFECT ECONOMIC FORECASTS? Contemporary Economic Policy, 38(1), 206–220. https://doi.org/10.1111/coep.12440

Muth, M. K., Okrent, A. M., Zhen, C., & Karns, S. A. (2020). Conducting cost-benefit analyses using scanner and label data. In Using Scanner Data for Food Policy Research (pp. 203–229). https://doi.org/10.1016/B978-0-12-814507-4.00008-0

Muth, M. K., Okrent, A. M., Zhen, C., & Karns, S. A. (2020). Estimating food demand systems using scanner data. In Using Scanner Data for Food Policy Research (pp. 141–175). https://doi.org/10.1016/B978-0-12-814507-4.00006-7

Muth, M. K., Okrent, A. M., Zhen, C., & Karns, S. A. (2020). Insights from past food research using scanner data. In Using Scanner Data for Food Policy Research (pp. 59–140). https://doi.org/10.1016/B978-0-12-814507-4.00005-5

Muth, M. K., Okrent, A. M., Zhen, C., & Karns, S. A. (2020). Methodological approaches for using scanner data. In Using Scanner Data for Food Policy Research (pp. 41–57). https://doi.org/10.1016/B978-0-12-814507-4.00004-3

Muth, M. K., Okrent, A. M., Zhen, C., & Karns, S. A. (2020). What is scanner data and why is it useful for food policy research? In Using Scanner Data for Food Policy Research (pp. 1–12). https://doi.org/10.1016/B978-0-12-814507-4.00001-8

Muth, M. K., Okrent, A. M., Zhen, C., & Karns, S. A. (2020). Label and nutrition data at the barcode level. In Using Scanner Data for Food Policy Research (pp. 31–39). https://doi.org/10.1016/B978-0-12-814507-4.00003-1

Muth, M. K., Okrent, A. M., Zhen, C., & Karns, S. A. (2020). Measuring the food environment using scanner data. In Using Scanner Data for Food Policy Research (pp. 177–202). https://doi.org/10.1016/B978-0-12-814507-4.00007-9

Muth, M. K., Okrent, A. M., Zhen, C., & Karns, S. A. (2020). Sources of scanner data across the globe. In Using Scanner Data for Food Policy Research (pp. 13–30). https://doi.org/10.1016/B978-0-12-814507-4.00002-X

Altunok, F., Mitchell, K., & Pearce, D. K. (2020). The trade credit channel and monetary policy transmission: Empirical evidence from US panel data. QUARTERLY REVIEW OF ECONOMICS AND FINANCE, 78, 226–250. https://doi.org/10.1016/j.qref.2020.03.001

Clark, R. L., & Ritter, B. M. (2020). How Are Employers Responding to an Aging Workforce? GERONTOLOGIST, 60(8), 1403–1410. https://doi.org/10.1093/geront/gnaa031

Mertens, E., & Nason, J. M. (2020). Inflation and professional forecast dynamics: An evaluation of stickiness, persistence, and volatility. QUANTITATIVE ECONOMICS, 11(4), 1485–1520. https://doi.org/10.3982/QE980

Ehlers, L., & Morrill, T. (2020). (Il)legal Assignments in School Choice. REVIEW OF ECONOMIC STUDIES, 87(4), 1837–1875. https://doi.org/10.1093/restud/rdz041

Kabukcuoglu, A., & Martinez-Garcia, E. (2020). A Generalized Time Iteration Method for Solving Dynamic Optimization Problems with Occasionally Binding Constraints. COMPUTATIONAL ECONOMICS. https://doi.org/10.1007/s10614-020-10037-x

Caner, M., & Han, X. (2020). An upper bound for functions of estimators in high dimensions. ECONOMETRIC REVIEWS. https://doi.org/10.1080/07474938.2020.1808370

Harless, P., & Phan, W. (2020). On endowments and indivisibility: partial ownership in the Shapley-Scarf model. ECONOMIC THEORY, 70(2), 411–435. https://doi.org/10.1007/s00199-019-01213-8

Nason, J. M., & Smith, G. W. (2020). Measuring the slowly evolving trend in US inflation with professional forecasts. JOURNAL OF APPLIED ECONOMETRICS. https://doi.org/10.1002/jae.2784

Parsons, G. N., & Clark, R. D. (2020). [Review of Area-Selective Deposition: Fundamentals, Applications, and Future Outlook]. CHEMISTRY OF MATERIALS, 32(12), 4920–4953. https://doi.org/10.1021/acs.chemmater.0c00722

Lenard, M., Morrill, M. S., & Westall, J. (2020). High school start times and student achievement: Looking beyond test scores. ECONOMICS OF EDUCATION REVIEW, 76. https://doi.org/10.1016/j.econedurev.2020.101975

Dur, U., Pathak, P. A., & Sonmez, T. (2020). Explicit vs. statistical targeting in affirmative action: Theory and evidence from Chicago's exam schools. JOURNAL OF ECONOMIC THEORY, 187. https://doi.org/10.1016/j.jet.2020.1049960022

Afacan, M. O., & Dur, U. M. (2020). Constrained stability in two-sided matching markets. SOCIAL CHOICE AND WELFARE. https://doi.org/10.1007/s00355-020-01252-4

Zeytoon Nejad Moosavian, S. A., Hammond, R., & Goodwin, B. K. (2020). Risk aversion over price variability: experimental evidence. APPLIED ECONOMICS LETTERS. https://doi.org/10.1080/13504851.2020.1717426

Ferraro, D., & Fiori, G. (2020). The Aging of the Baby Boomers: Demographics and Propagation of Tax Shocks. AMERICAN ECONOMIC JOURNAL-MACROECONOMICS, 12(2), 167–193. https://doi.org/10.1257/mac.20160419

Cacciatore, M., Fiori, G., & Traum, N. (2020). Hours and employment over the business cycle: A structural analysis. REVIEW OF ECONOMIC DYNAMICS, 35, 240–262. https://doi.org/10.1016/j.red.2019.07.001

Troyan, P., & Morrill, T. (2020). Obvious manipulations. JOURNAL OF ECONOMIC THEORY, 185. https://doi.org/10.1016/j.jet.2019.104970

Bugni, F. A., Caner, M., Kock, A. B., & Lahiri, S. (2020). Inference in partially identified models with many moment inequalities using Lasso. JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 206, 211–248. https://doi.org/10.1016/j.jspi.2019.09.013