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Machine Learning for Economists: An Introduction. (2021). MEMON, SONAN.
In: PIDE Knowledge Brief.
RePEc:pid:kbrief:2021:33.

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  1. Aiken, Emily L, Bedoya, Guadalupe, Coville, Aidan, & Blumenstock, Joshua E. (2020). Targeting development aid with machine learning and mobile phone data: Evidence from an anti-poverty intervention in Afghanistan. In “Proceedings of the 3rd ACM SIGCAS Conference on Computing and Sustainable Societies” 2020, pp. 310–311.
    Paper not yet in RePEc: Add citation now
  2. Alpaydin, Ethem (2020). Introduction to machine learning, MIT Press.
    Paper not yet in RePEc: Add citation now
  3. Athey & Imbens, Guido W. (2019). Machine learning methods that economists should know about. Annual Review of Economics, 11, 685–725.

  4. Athey, et al. (2015). Machine learning for estimating heterogeneous causal effects. (Technical Report).

  5. Athey, Susan (2019). The impact of machine learning on economics. In “The economics of artificial intelligence,” University of Chicago Press, pp. 507–552.
    Paper not yet in RePEc: Add citation now
  6. Blei, David M., Ng, Andrew Y., & Jordan, Michael I. (2003). Latent dirichlet allocation. The Journal of Machine Learning Research, 3, 993–1022.
    Paper not yet in RePEc: Add citation now
  7. Blumenstock, Joshua, Cadamuro, Gabriel, & On, Robert (2015). Predicting poverty and wealth from mobile phone metadata. Science, 350(6264), 1073–1076.
    Paper not yet in RePEc: Add citation now
  8. Caria, Stefano, Kasy, Maximilian, Quinn, Simon, Shami, Soha, Teytelboym, Alex, et al. (2021). An adaptive targeted field experiment: Job search assistance for refugees in Jordan.

  9. Gentzkow, Matthew, Kelly, Bryan, & Taddy, Matt (2019). Text as data. Journal of Economic Literature, 57 (3), 535–74.

  10. Goldblatt, Ran, Stuhlmacher, Michelle F. & Tellman, Beth, Clinton, Nicholas, Hanson, Gordon, Georgescu, Matei, Wang, Chuyuan, Serrano-Candela, Fidel. Khandelwal, Amit K., Cheng, Wan-Hwa, et al. (2018). Using Landsat and night-time lights for supervised pixel-based image classification of urban land cover. Remote Sensing of Environment, 205, 253–275.
    Paper not yet in RePEc: Add citation now
  11. Hansen, Stephen, & McMahon, Michael (2016). Shocking language: Understanding the macroeconomic effects of central bank communication. Journal of International Economics, 99, S114–S133.

  12. James, Gareth, Witten, Daniela, Hastie, Trevor, & Tibshirani, Robert (2013). An introduction to statistical learning, Vol. 112, Springer.
    Paper not yet in RePEc: Add citation now
  13. Jean, Neal, Burke, Marshall, Xie, Michael, Davis, W. Matthew, Lobell, David B., & Ermon, Stefano (2016). Combining satellite imagery and machine learning to predict poverty. Science, 353(6301), 790–794.
    Paper not yet in RePEc: Add citation now
  14. Kock, Anders Bredahl & Callot, Laurent, A. F. et al. (2012). Oracle efficient estimation and forecasting with the adaptive lasso and the adaptive group lasso in vector autoregressions. School of Economics and Management.

  15. Larsen, Vegard H., Thorsrud, Leif Anders, & Zhulanova, Julia (2021). News-driven inflation expectations and information rigidities. Journal of Monetary Economics, 117, 507–520.

  16. Mahajan, Aprajit, & Mittal, Shekhar (2017). Enforcement in value added tax: Is third party verification effective? (International Growth Centre Working Paper S-89412-INC-1).
    Paper not yet in RePEc: Add citation now
  17. Mullainathan, Sendhil & Spiess, Jann (2017). Machine learning: An applied econometric approach. Journal of Economic Perspectives, 31(2), 87–106.

  18. Steele, Jessica E., Sundsøy, Pål Roe, Pezzulo, Carla, Alegana, Victor A., Bird, Tomas J., Blumenstock, Joshua, Bjelland, Johannes, Engø-Monsen, Kenth, De Montjoye, Yves-Alexandre, & Iqbal, Asif M. et al. (2017). Mapping poverty using mobile phone and satellite data. Journal of The Royal Society Interface, 14(127), 20160690.
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