Report NEP-CMP-2019-03-18

This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stan Miles issued this report. It is usually issued weekly.

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Other reports in NEP-CMP

The following items were announced in this report:

• Joseph, Andreas, 2019. "Parametric inference with universal function approximators," Bank of England working papers 784, Bank of England, revised 22 Jul 2020.
• Andreas Joseph, 2019. "From interpretability to inference: an estimation framework for universal approximators," Papers 1903.04209, arXiv.org, revised Dec 2024.
• Huong Dinh & Manannan Donoghoe & Neal Hughes & Tim Goesch, 2019. "A micro-simulation model of irrigation farms in the southern Murray-Darling Basin," Papers 1903.05781, arXiv.org.
• Alexander James & Yaser S. Abu-Mostafa & Xiao Qiao, 2019. "Nowcasting Recessions using the SVM Machine Learning Algorithm," Papers 1903.03202, arXiv.org, revised Jun 2019.
• Sandra Achten & Christian Lessmann, 2019. "Spatial inequality, geography and economic activity," CESifo Working Paper Series 7547, CESifo.
• Andrea Caggese & Ander Pérez-Orive, 2018. "Capital misallocation and secular stagnation," Economics Working Papers 1637, Department of Economics and Business, Universitat Pompeu Fabra, revised Feb 2019.
• Mkhabela, T. & Ntombela, S. & Mazibuko, N., 2018. "Pro et Contra of Agriculture Land Reform in South Africa: A Policy Brief," 2018 Annual Conference, September 25-27, Cape Town, South Africa 284782, Agricultural Economics Association of South Africa (AEASA).
• Enzo Busseti, 2019. "Derivative of a Conic Problem with a Unique Solution," Papers 1903.05753, arXiv.org, revised Mar 2019.
• Joan Gonzalvez & Edmond Lezmi & Thierry Roncalli & Jiali Xu, 2019. "Financial Applications of Gaussian Processes and Bayesian Optimization," Papers 1903.04841, arXiv.org.
• Michael Stiefel & Rémi Vivès, 2019. "“Whatever it Takes” to Change Belief: Evidence from Twitter," AMSE Working Papers 1907, Aix-Marseille School of Economics, France, revised Mar 2019.
• John M. Abowd & Joelle Abramowitz & Margaret C. Levenstein & Kristin McCue & Dhiren Patki & Trivellore Raghunathan & Ann M. Rodgers & Matthew D. Shapiro & Nada Wasi, 2019. "Optimal Probabilistic Record Linkage: Best Practice for Linking Employers in Survey and Administrative Data," Working Papers 19-08, Center for Economic Studies, U.S. Census Bureau.