My bibliography
Save this item
Targeting with machine learning: An application to a tax rebate program in Italy
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Luca Villamaina & Paolo Acciari, 2023. "Taxation and labour supply decisions: an evaluation of the earned income tax credit in Italy," Working Papers wp2023-20, Ministry of Economy and Finance, Department of Finance.
- Michael J. Weir & Thomas W. Sproul, 2019. "Identifying Drivers of Genetically Modified Seafood Demand: Evidence from a Choice Experiment," Sustainability, MDPI, vol. 11(14), pages 1-21, July.
- Matilde Cappelletti & Leonardo M. Giuffrida, 2024. "Targeted Bidders in Government Tenders," CESifo Working Paper Series 11142, CESifo.
- Fontana, S.; & Guccio, C.; & Pignataro, G.; & Romeo, D.;, 2024. "Cash Transfers and Health Outcomes: Evidence from Italian Municipalities," Health, Econometrics and Data Group (HEDG) Working Papers 24/04, HEDG, c/o Department of Economics, University of York.
- Michael Allan Ribers & Hannes Ullrich, 2020.
"Machine Predictions and Human Decisions with Variation in Payoffs and Skill,"
CESifo Working Paper Series
8702, CESifo.
- Michael Allan Ribers & Hannes Ullrich, 2020. "Machine Predictions and Human Decisions with Variation in Payoffs and Skill," Papers 2011.11017, arXiv.org.
- Michael Allan Ribers & Hannes Ullrich, 2020. "Machine Predictions and Human Decisions with Variation in Payoffs and Skills," Discussion Papers of DIW Berlin 1911, DIW Berlin, German Institute for Economic Research.
- Michael Allan Ribers & Hannes Ullrich, 2019.
"Battling Antibiotic Resistance: Can Machine Learning Improve Prescribing?,"
Papers
1906.03044, arXiv.org.
- Michael A. Ribers & Hannes Ullrich, 2019. "Battling Antibiotic Resistance: Can Machine Learning Improve Prescribing?," Discussion Papers of DIW Berlin 1803, DIW Berlin, German Institute for Economic Research.
- Michael Allan Ribers & Hannes Ullrich, 2019. "Battling antibiotic resistance: can machine learning improve prescribing?," CESifo Working Paper Series 7654, CESifo.
- Resce, Giuliano & Vaquero-Piñeiro, Cristina, 2022.
"Predicting agri-food quality across space: A Machine Learning model for the acknowledgment of Geographical Indications,"
Food Policy, Elsevier, vol. 112(C).
- Resce, Giuliano & Vaquero-Pineiro, Cristina, 2022. "Predicting Agri-food Quality across Space: A Machine Learning Model for the Acknowledgment of Geographical Indications," Economics & Statistics Discussion Papers esdp22082, University of Molise, Department of Economics.
- Ignacio González García & Alfonso Mateos, 2021. "Use of Social Network Analysis for Tax Control in Spain," Hacienda Pública Española / Review of Public Economics, IEF, vol. 239(4), pages 159-197, November.
- Augusto Cerqua & Roberta Di Stefano & Marco Letta & Sara Miccoli, 2021.
"Local mortality estimates during the COVID-19 pandemic in Italy,"
Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(4), pages 1189-1217, October.
- Augusto Cerqua & Roberta Di Stefano & Marco Letta & Sara Miccoli, 2020. "Local mortality estimates during the COVID-19 pandemic in Italy," Discussion Paper series in Regional Science & Economic Geography 2020-06, Gran Sasso Science Institute, Social Sciences, revised Oct 2020.
- Augusto Cerqua & Roberta Di Stefano & Marco Letta & Sara Miccoli, 2020. "Local mortality estimates during the COVID-19 pandemic in Italy," Working Papers 14/20, Sapienza University of Rome, DISS.
- Garbero, Alessandra & Sakos, Grayson & Cerulli, Giovanni, 2023.
"Towards data-driven project design: Providing optimal treatment rules for development projects,"
Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
- Garbero, Alessandra & Sakos, Grayson & Cerulli, Giovanni, 2021. "Towards Data-driven Project design: Providing Optimal Treatment Rules for Development Projects," 2021 Annual Meeting, August 1-3, Austin, Texas 314016, Agricultural and Applied Economics Association.
- Cerqua, Augusto & Letta, Marco, 2022.
"Local inequalities of the COVID-19 crisis,"
Regional Science and Urban Economics, Elsevier, vol. 92(C).
- Cerqua, Augusto & Letta, Marco, 2021. "Local inequalities of the COVID-19 crisis," GLO Discussion Paper Series 875, Global Labor Organization (GLO).
- Radermacher, Jan W., 2023. "Mamma Mia! Revealing hidden heterogeneity by PCA-biplot: MPC puzzle for Italy's elderly poor," SAFE Working Paper Series 382, Leibniz Institute for Financial Research SAFE.
- Michael Allan Ribers & Hannes Ullrich, 2023. "Machine learning and physician prescribing: a path to reduced antibiotic use," Berlin School of Economics Discussion Papers 0019, Berlin School of Economics.
- Guido de Blasio & Alessio D'Ignazio & Marco Letta, 2020. "Predicting Corruption Crimes with Machine Learning. A Study for the Italian Municipalities," Working Papers 16/20, Sapienza University of Rome, DISS.
- Tobias Cagala & Ulrich Glogowsky & Johannes Rincke & Anthony Strittmatter, 2021.
"Optimal Targeting in Fundraising: A Machine-Learning Approach,"
Economics working papers
2021-08, Department of Economics, Johannes Kepler University Linz, Austria.
- Tobias Cagala & Ulrich Glogowsky & Johannes Rincke & Anthony Strittmatter, 2021. "Optimal Targeting in Fundraising: A Machine-Learning Approach," CESifo Working Paper Series 9037, CESifo.
- Kadriye Hilal Topal & Ebru Çağlayan Akay, 2020. "Hanehalkı Tüketim Harcamalarının Mikroekonometrik Analizi: LAD-LASSO Yöntemi," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(33), pages 13-31, December.
- Di Stefano, Roberta & Resce, Giuliano, "undated". "The Determinants of Missed Funding: Predicting the Paradox of Increased Need and Reduced Allocation," Economics & Statistics Discussion Papers esdp23092, University of Molise, Department of Economics.
- Antulov-Fantulin, Nino & Lagravinese, Raffaele & Resce, Giuliano, 2021. "Predicting bankruptcy of local government: A machine learning approach," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 681-699.
- Altındağ, Onur & O'Connell, Stephen D. & Şaşmaz, Aytuğ & Balcıoğlu, Zeynep & Cadoni, Paola & Jerneck, Matilda & Foong, Aimee Kunze, 2021.
"Targeting humanitarian aid using administrative data: Model design and validation,"
Journal of Development Economics, Elsevier, vol. 148(C).
- Onur Altindag & Stephen D. O’Connell & Aytug Sasmaz & Zeynep Balcioglu & Paola Cadoni & Matilda Jerneck & Aimee Kunze Foong, 2019. "Targeting Humanitarian Aid Using Administrative Data: Model Design And Validation," Working Papers 1343, Economic Research Forum, revised 20 Sep 2019.
- Onur Altındağ & Stephen D. O'Connell & Aytuğ Şaşmaz & Zeynep Balcıoğlu & Paola Cadoni & Matilda Jerneck & Aimee Kunze Foong, 2020. "Targeting humanitarian aid using administrative data: model design and validation," HiCN Working Papers 327, Households in Conflict Network.
- Ginevra Buratti & Alessio D'Ignazio, 2023. "Improving the effectiveness of financial education programs. A targeting approach," Questioni di Economia e Finanza (Occasional Papers) 765, Bank of Italy, Economic Research and International Relations Area.
- Caravaggio, Nicola & Resce, Giuliano, 2023. "Enhancing Healthcare Cost Forecasting: A Machine Learning Model for Resource Allocation in Heterogeneous Regions," Economics & Statistics Discussion Papers esdp23090, University of Molise, Department of Economics.
- Michael Allan Ribers & Hannes Ullrich, 2024. "Complementarities between algorithmic and human decision-making: The case of antibiotic prescribing," Quantitative Marketing and Economics (QME), Springer, vol. 22(4), pages 445-483, December.
- Tobias Cagala & Ulrich Glogowsky & Johannes Rincke & Anthony Strittmatter, 2021. "Optimal Targeting in Fundraising: A Causal Machine-Learning Approach," Papers 2103.10251, arXiv.org, revised Sep 2021.
- Battiston, Pietro & Gamba, Simona & Santoro, Alessandro, 2024. "Machine learning and the optimization of prediction-based policies," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
- de Blasio, Guido & D'Ignazio, Alessio & Letta, Marco, 2022. "Gotham city. Predicting ‘corrupted’ municipalities with machine learning," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
- Elliott Ash & Sergio Galletta & Tommaso Giommoni, 2021. "A Machine Learning Approach to Analyze and Support Anti-Corruption Policy," CESifo Working Paper Series 9015, CESifo.
- Gabriel Okasa, 2022. "Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance," Papers 2201.12692, arXiv.org.
- Hannes Ullrich & Michael Allan Ribers, 2023. "Machine predictions and human decisions with variation in payoffs and skill: the case of antibiotic prescribing," Berlin School of Economics Discussion Papers 0027, Berlin School of Economics.
- Lucchetti, Riccardo & Pedini, Luca & Pigini, Claudia, 2022. "No such thing as the perfect match: Bayesian Model Averaging for treatment evaluation," Economic Modelling, Elsevier, vol. 107(C).
- Andini, Monica & Boldrini, Michela & Ciani, Emanuele & de Blasio, Guido & D'Ignazio, Alessio & Paladini, Andrea, 2022.
"Machine learning in the service of policy targeting: The case of public credit guarantees,"
Journal of Economic Behavior & Organization, Elsevier, vol. 198(C), pages 434-475.
- Monica Andini & Michela Boldrini & Emanuele Ciani & Guido de Blasio & Alessio D'Ignazio & Andrea Paladini, 2019. "Machine learning in the service of policy targeting: the case of public credit guarantees," Temi di discussione (Economic working papers) 1206, Bank of Italy, Economic Research and International Relations Area.
- Dutt, Satyajit & Radermacher, Jan W., 2023. "Age, wealth, and the MPC in Europe: A supervised machine learning approach," SAFE Working Paper Series 383, Leibniz Institute for Financial Research SAFE.
- Strittmatter, Anthony, 2023. "What is the value added by using causal machine learning methods in a welfare experiment evaluation?," Labour Economics, Elsevier, vol. 84(C).
- Cerqua, Augusto & Letta, Marco, 2020. "Local economies amidst the COVID-19 crisis in Italy: a tale of diverging trajectories," MPRA Paper 104404, University Library of Munich, Germany.