1. Beyond the records: Data quality and COVID-19 vaccination progress in low- and middle-income countries. (2025). Markhof, Yannick ; Zezza, Alberto ; Wollburg, Philip.
   In: Journal of Development Economics.
   RePEc:eee:deveco:v:174:y:2025:i:c:s0304387824001986.

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2. Introduction to the journal of development economics special issue on methods and measurement. (2024). Udry, Christopher ; Karlan, Dean ; Dillon, Andrew ; Beegle, Kathleen.
   In: Journal of Development Economics.
   RePEc:eee:deveco:v:170:y:2024:i:c:s030438782400052x.

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3. Whom to ask? Testing respondent effects in household surveys. (2024). Fiala, Nathan ; Masselus, Lise.
   In: Journal of Development Economics.
   RePEc:eee:deveco:v:168:y:2024:i:c:s0304387824000142.

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4. Respondent biases in agricultural household surveys. (2024). Dillon, Andrew ; Mensah, Edouard.
   In: Journal of Development Economics.
   RePEc:eee:deveco:v:166:y:2024:i:c:s0304387823001542.

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5. Whom to ask? Testing respondent effects in household surveys. (2022). Fiala, Nathan ; Masselus, Lise.
   In: Ruhr Economic Papers.
   RePEc:zbw:rwirep:935.

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6. From Necessity to Opportunity : Lessons for Integrating Phone and In-Person Data Collection for Agricultural Statistics in a Post-Pandemic World. (2022). Zezza, Alberto ; Assefa, Thomas ; Gourlay, Sydney ; Wollburg, Philip Randolph ; McGee, Kevin Robert.
   In: Policy Research Working Paper Series.
   RePEc:wbk:wbrwps:10168.

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1. Athey, S. ; Imbens, G. Machine learning methods that economists should know about. 2019 Annual Review of Economics. 11 685-725

2. Beaman, L. ; Keleher, N. ; Magruder, J. Do job networks disadvantage women? Evidence from a recruitment experiment. 2018 Journal of Labor Economics. 36 147-161

3. Bound, J., Brown, C., & Mathiowetz, N. (2001). Measurement error in survey data. In Heckman, J. & Leamer, E. (Eds.), Handbook of econometrics (pp. 3705–3843). New York: North Holland Publishing, Elsevier.

4. De Weerdt, J., Gibson, J., & Beegle, K. (2019). What can we learn from experimenting with survey methods? Annual Review of Economics 3: Submitted. DOI: 10.1146/annurev-resource-103019-105958.

5. Deaton, A., & Zaidi, S. (2002). A Guide to Aggregating Consumption Expenditures, Living Standards Measurement Study, Working Paper 135.
   Paper not yet in RePEc: Add citation now
   

6. Dhar, D., Jain, T., & Jayachandran, S. (2018). Reshaping adolescents’ gender attitudes: Evidence from a school-based experiment in India. http://faculty.wcas.northwestern.edu/~sjv340/reshaping_gender_attitudes.pdf.

7. Donald, A. ; Koolwal, G. ; Annan, J. ; Falb, K. ; Goldstein, M. Measuring women's agency. Working Paper Series 8148. 2017 World Bank Group: Washington, DC
   Paper not yet in RePEc: Add citation now
   

8. Heckman, J., Jagelka, T., & Kautz, T. (2019). Some contributions of economics to the study of personality. NBER Working Paper No. 26459.

9. Hyslop, R. ; Imbens, G. Bias from classical and other forms of measurement error. 2001 Journal of Business & Economic Statistics. 19 475-481

10. Meyer, B. ; Mittag, N. Using linked survey and administrative data to better measure income: Implications for poverty, program effectiveness and holes in the safety net. 2019 American Economic Journal: Applied Economics. 11 176-204

11. West, B.T. ; Blom, A.G. Explaining interviewer effects: A research synthesis. 2017 Journal of Survey Statistics and Methodology. 5 175-211
    Paper not yet in RePEc: Add citation now
    

1. Navigating the Measurement Frontier: New Insights Into Small Farm Realities. (2025). Michelson, Hope.
   In: Agricultural Economics.
   RePEc:bla:agecon:v:56:y:2025:i:3:p:526-542.

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2. Matrix completion of world trade: An analysis of interpretability through Shapley values. (2023). Riccaboni, Massimo ; Nutarelli, Federico ; Gnecco, Giorgio.
   In: The World Economy.
   RePEc:bla:worlde:v:46:y:2023:i:9:p:2707-2731.

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3. Double Debiased Machine Learning Nonparametric Inference with Continuous Treatments. (2023). Lee, Ying-Ying ; Colangelo, Kyle.
   In: Papers.
   RePEc:arx:papers:2004.03036.

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4. Estimating Inequality with Missing Incomes. (2022). Verme, Paolo ; SALAS ROJO, PEDRO ; Salas-Rojo, Pedro ; Brunori, Paolo.
   In: Working Papers.
   RePEc:inq:inqwps:ecineq2022-616.

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5. Double Machine Learning based Program Evaluation under Unconfoundedness. (2022). Knaus, Michael.
   In: Papers.
   RePEc:arx:papers:2003.03191.

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6. Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium. (2022). Lechner, Michael ; Cockx, Bart ; Bollens, Joost.
   In: Papers.
   RePEc:arx:papers:1912.12864.

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7. Big Data in der makroökonomischen Analyse. (2021). Heidland, Tobias ; Hinz, Julian ; Hauber, Philipp ; Funke, Manuel ; Boysen-Hogrefe, Jens ; Bode, Eckhardt ; Beckmann, Joscha ; Ademmer, Martin ; Soder, Mareike ; Stamer, Vincent ; Stolzenburg, Ulrich ; Kooths, Stefan ; Jannsen, Nils.
   In: Kieler Beiträge zur Wirtschaftspolitik.
   RePEc:zbw:ifwkbw:32.

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8. The Effect of Sport in Online Dating: Evidence from Causal Machine Learning. (2021). Lechner, Michael ; Okasa, Gabriel ; Boller, Daniel.
   In: Economics Working Paper Series.
   RePEc:usg:econwp:2021:04.

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9. The Value Added of Machine Learning to Causal Inference: Evidence from Revisited Studies. (2021). Baiardi, Anna ; Naghi, Andrea A.
   In: Tinbergen Institute Discussion Papers.
   RePEc:tin:wpaper:20210001.

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10. Machine Learning and Central Banks: Ready for Prime Time?. (2021). Karagedikli, Ozer ; Genberg, Hans.
    In: Working Papers.
    RePEc:sea:wpaper:wp43.

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11. Technical efficiency and the adoption of multiple agricultural technologies in the mountainous areas of Northern Vietnam. (2021). To-The, Nguyen ; Nguyen-Anh, Tuan ; Lampach, Nicolas.
    In: Land Use Policy.
    RePEc:eee:lauspo:v:103:y:2021:i:c:s0264837721000120.

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12. LASSO+DEA for small and big wide data. (2021). Zelenyuk, Valentin ; Tsionas, Mike ; Chen, Ya.
    In: Omega.
    RePEc:eee:jomega:v:102:y:2021:i:c:s0305048321000281.

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13. Preventing rather than punishing: An early warning model of malfeasance in public procurement. (2021). Gallego, Jorge ; Martinez, Juan ; Rivero, Gonzalo.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:37:y:2021:i:1:p:360-377.

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14. Overlap in observational studies with high-dimensional covariates. (2021). Ding, Peng ; Lei, Lihua ; Sekhon, Jasjeet ; Feller, Avi ; Damour, Alexander.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:221:y:2021:i:2:p:644-654.

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15. Optimal Targeting in Fundraising: A Causal Machine-Learning Approach. (2021). Strittmatter, Anthony ; Glogowsky, Ulrich ; Cagala, Tobias ; Rincke, Johannes.
    In: Papers.
    RePEc:arx:papers:2103.10251.

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16. Confronting Machine Learning With Financial Research. (2021). el Harzli, Ouns ; Lommers, Kristof ; Kim, Jack.
    In: Papers.
    RePEc:arx:papers:2103.00366.

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17. The Value Added of Machine Learning to Causal Inference: Evidence from Revisited Studies. (2021). Baiardi, Anna ; Naghi, Andrea A.
    In: Papers.
    RePEc:arx:papers:2101.00878.

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18. Using Machine Learning to Create an Early Warning System for Welfare Recipients. (2021). Sansone, Dario ; Zhu, Anna.
    In: Papers.
    RePEc:arx:papers:2011.12057.

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19. Bottom incomes and the measurement of poverty and inequality. (2020). Verme, Paolo ; Hlasny, Vladimir ; Ceriani, Lidia.
    In: GLO Discussion Paper Series.
    RePEc:zbw:glodps:519.

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20. Which Model for Poverty Predictions?. (2020). Verme, Paolo.
    In: GLO Discussion Paper Series.
    RePEc:zbw:glodps:468.

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21. Double Machine Learning based Program Evaluation under Unconfoundedness. (2020). Knaus, Michael.
    In: Economics Working Paper Series.
    RePEc:usg:econwp:2020:04.

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22. Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium. (2020). Lechner, Michael ; Cockx, Bart ; Bollens, Joost.
    In: Economics Working Paper Series.
    RePEc:usg:econwp:2020:01.

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23. Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium. (2020). Lechner, Michael ; Cockx, Bart ; Bollens, Joost.
    In: ROA Research Memorandum.
    RePEc:unm:umaror:2020006.

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24. Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium. (2020). Lechner, Michael ; Cockx, Bart ; Bollens, Joost.
    In: Research Memorandum.
    RePEc:unm:umagsb:2020015.

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25. Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium. (2020). Lechner, Michael ; Cockx, Bart ; Bollens, Joost.
    In: Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium.
    RePEc:rug:rugwps:20/998.

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26. LASSO DEA for small and big data. (2020). Zelenyuk, Valentin ; Tsionas, Mike ; Chen, Ya.
    In: CEPA Working Papers Series.
    RePEc:qld:uqcepa:152.

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27. Long-Term Health Insurance: Theory Meets Evidence. (2020). Ziebarth, Nicolas ; Karlsson, Martin ; Fang, Hanming ; Atal, Juan Pablo.
    In: PIER Working Paper Archive.
    RePEc:pen:papers:20-009.

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28. What Can Economics Say About Alzheimers Disease?. (2020). Mommaerts, Corina ; Coile, Courtney ; Chandra, Amitabh.
    In: NBER Working Papers.
    RePEc:nbr:nberwo:27760.

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29. Machine Learning in Gravity Models: An Application to Agricultural Trade. (2020). Gopinath, Munisamy ; Beckman, Jayson ; Batarseh, Feras A.
    In: NBER Working Papers.
    RePEc:nbr:nberwo:27151.

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30. German Long-Term Health Insurance: Theory Meets Evidence. (2020). Ziebarth, Nicolas ; Karlsson, Martin ; Fang, Hanming ; Atal, Juan Pablo.
    In: NBER Working Papers.
    RePEc:nbr:nberwo:26870.

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31. Bottom Incomes and the Measurement of Poverty and Inequality. (2020). Verme, Paolo ; Hlasny, Vladimir ; Ceriani, Lidia.
    In: LIS Working papers.
    RePEc:lis:liswps:792.

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32. Dynamic Factor Trees and Forests – A Theory-led Machine Learning Framework for Non-Linear and State-Dependent Short-Term U.S. GDP Growth Predictions. (2020). Wochner, Daniel.
    In: KOF Working papers.
    RePEc:kof:wpskof:20-472.

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33. What Is at Stake without High-Stakes Exams? Students Evaluation and Admission to College at the Time of COVID-19. (2020). Loviglio, Annalisa ; Calsamiglia, Caterina ; Arenas, Andreu.
    In: IZA Discussion Papers.
    RePEc:iza:izadps:dp13838.

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34. Double Machine Learning Based Program Evaluation under Unconfoundedness. (2020). Knaus, Michael.
    In: IZA Discussion Papers.
    RePEc:iza:izadps:dp13051.

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35. Indicators of Economic Crises: A Data-Driven Clustering Approach. (2020). Araújo, Tanya ; Araujo, Tanya ; Gobel, Maximilian.
    In: Working Papers REM.
    RePEc:ise:remwps:wp01282020.

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36. Bottom incomes and the measurement of poverty and inequality. (2020). Verme, Paolo ; Hlasny, Vladimir ; Ceriani, Lidia.
    In: Working Papers.
    RePEc:inq:inqwps:ecineq2020-535.

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37. Which Model for Poverty Predictions?. (2020). Verme, Paolo.
    In: Working Papers.
    RePEc:inq:inqwps:ecineq2020-521.

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38. Does the estimation of the propensity score by machine learning improve matching estimation? : The case of Germanys programmes for long term unemployed. (2020). Lechner, Michael ; Goller, Daniel ; Wolff, Joachim ; Moczall, Andreas.
    In: IAB-Discussion Paper.
    RePEc:iab:iabdpa:202005.

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39. Good identification, meet good data. (2020). Zinman, Jonathan ; Udry, Christopher ; Karlan, Dean ; Dillon, Andrew.
    In: World Development.
    RePEc:eee:wdevel:v:127:y:2020:i:c:s0305750x19304450.

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40. Forecasting Costa Rican inflation with machine learning methods. (2020). Rodriguez Vargas, Adolfo ; Rodriguez-Vargas, Adolfo.
    In: Latin American Journal of Central Banking (previously Monetaria).
    RePEc:eee:lajcba:v:1:y:2020:i:1:s2666143820300120.

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41. Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium. (2020). Lechner, Michael ; Cockx, Bart ; Bollens, Joost.
    In: LIDAM Discussion Papers IRES.
    RePEc:ctl:louvir:2020016.

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42. Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium. (2020). Lechner, Michael ; Cockx, Bart ; Boolens, Joost.
    In: CEPR Discussion Papers.
    RePEc:cpr:ceprdp:14270.

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43. Priority of Unemployed Immigrants? A Causal Machine Learning Evaluation of Training in Belgium. (2020). Lechner, Michael ; Cockx, Bart ; Bollens, Joost.
    In: CESifo Working Paper Series.
    RePEc:ces:ceswps:_8297.

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44. Supervised learning for the prediction of firm dynamics. (2020). Riccaboni, Massimo ; Niederreiter, Jan ; Bargagli-Stoffi, Falco J.
    In: Papers.
    RePEc:arx:papers:2009.06413.

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45. A Pipeline for Variable Selection and False Discovery Rate Control With an Application in Labor Economics. (2020). Klose, Sophie-Charlotte ; Lederer, Johannes.
    In: Papers.
    RePEc:arx:papers:2006.12296.

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46. Application of Nonlinear Autoregressive with Exogenous Input (NARX) neural network in macroeconomic forecasting, national goal setting and global competitiveness assessment. (2020). Tang, Liyang.
    In: Papers.
    RePEc:arx:papers:2005.08735.

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47. Does the estimation of the propensity score by machine learning improve matching estimation? The case of Germany’s programmes for long term unemployed. (2019). Lechner, Michael ; Goller, Daniel ; Wolff, Joachim ; Moczall, Andreas.
    In: Economics Working Paper Series.
    RePEc:usg:econwp:2019:10.

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48. Priority to Unemployed Immigrants? A Causal Machine Learning Evaluation of Training in Belgium. (2019). Lechner, Michael ; Cockx, Bart ; Bollens, Joost.
    In: IZA Discussion Papers.
    RePEc:iza:izadps:dp12875.

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49. Does the Estimation of the Propensity Score by Machine Learning Improve Matching Estimation? The Case of Germanys Programmes for Long Term Unemployed. (2019). Lechner, Michael ; Goller, Daniel ; Wolff, Joachim ; Moczall, Andreas.
    In: IZA Discussion Papers.
    RePEc:iza:izadps:dp12526.

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50. Double debiased machine learning nonparametric inference with continuous treatments. (2019). Lee, Ying-Ying ; Colangelo, Kyle.
    In: CeMMAP working papers.
    RePEc:ifs:cemmap:54/19.

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