- Anders, U., and O. Korn. (1996). âModel selection in neural networks.â In âCZEW Discussion Papers 96-21,â .
Paper not yet in RePEc: Add citation now
- Athey, S. (2019). âThe Impact of Machine Learning on Economics.â In âAjay Agrawal, Joshua Gans, and Avi Goldfarb (Eds.), The Economics of Artificial Intelligence: An Agenda,â 507â547, Chicago: University of Chicago Press.
Paper not yet in RePEc: Add citation now
Atkeson, A., and L. E. Ohanian. (2001). âAre Phillips curves useful for forecasting inflation?â Quarterly Review, Federal Reserve Bank of Minneapolis 2â11.
- Barnett, W., A. Medio, and A. Serletis. (2015). âNonlinear and Complex Dynamics in Economics.â Macroeconomic Dynamics 19, 8, 1749â1779.
Paper not yet in RePEc: Add citation now
Carriero, A., A.B. Galvão, and G. Kapetanios. (2019). âA comprehensive evaluation of macroeconomic forecasting methods.â International Journal of Forecasting 35, 4, 1226â1239.
Chakraborty, C., and A. Joseph. (2017). âMachine learning at central banks.â Bank of England Working Papers 674.
Cook, T. R., and S. Hall. (2017). âMacroeconomic Indicator Forecasting with Deep Neural Networks. â In âFederal Reserve Bank of Kansas City, Research Working Paper 17-11,â .
- Coulombe, P. G., M. Leroux, D. Stevanovic, and S. Surprenant. (2020). âHow is Machine Learning Useful for Macroeconomic Forecasting?â arXiv:2008.12477 .
Paper not yet in RePEc: Add citation now
- Cybenko, G. (1989). âApproximation by superposition of a sigmoidal function.â Mathematics of Control, Signals and Systems 2, 303â314.
Paper not yet in RePEc: Add citation now
- Diebold, F., and R. Mariano. (1995). âComparing Predictive Accuracy.â Journal of Business & Economic Statistics 13, 3, 253â263.
Paper not yet in RePEc: Add citation now
- Gaier, A., and D. Ha. (2019). âWeight Agnostic Neural Networks.â https://weightagnostic. github.io.
Paper not yet in RePEc: Add citation now
- Giacomini, R., and B. Rossi. (2010). âForecast Comparisons in Unstable Environments.â Journal of Applied Econometrics 25, 595â620.
Paper not yet in RePEc: Add citation now
- Giannone, D., M. Lenza, and G. Primiceri. (2015). âPrior selection for vector autoregressions.â Review of Economics and Statistics 97, 2, 436â451.
Paper not yet in RePEc: Add citation now
- Giannone, D., M. Lenza, and G. Primiceri. (2018). âEconomic predictions with big data: The illusion of sparcity.â Working paper, Northwestern University .
Paper not yet in RePEc: Add citation now
- Glorot, X., and Y. Bengio. (2010). âUnderstanding the difficulty of training deep feedforward neural networks.â Journal of Machine Learning Research - Proceedings Track 9, 249â256.
Paper not yet in RePEc: Add citation now
- Goodfellow, I. J., Y. Bengio, and A. Courville (2016). Deep Learning. MIT Press, http://www. deeplearningbook.org.
Paper not yet in RePEc: Add citation now
- Gu, S., B. Kelly, and D. Xiu. (2019). âEmpirical Asset Pricing via Machine Learning.â In âChicago Booth Research Paper No. 18-04; 31st Australasian Finance and Banking Conference 2018; Yale ICF Working Paper No. 2018-09.â, .
Paper not yet in RePEc: Add citation now
- Hanin, B., and D. Rolnick. (2018). âHow to start training: The effect of initialization and architecture. â In âAdvances in Neural Information Processing Systems 31,â 569â579, Curran Associates, Inc.
Paper not yet in RePEc: Add citation now
- Hasenzagl, T., F. Pellegrino, L. Reichlin, and G. Ricco. (2018). âA Model of the Fedâs View on Inflation.â Science Po OFCE Working Paper , 3.
Paper not yet in RePEc: Add citation now
Hazell, J., J. Herreno, E. Nakamura, and J. Steinsson. (2020). âThe Slope of the Phillips Curve: Evidence from U.S. States.â NBER Working Paper No 28005 .
- He, K., X. Zhang, Ren S., and J. Sun. (2015). âDelving deep into rectifiers: surpassing human-level performance on imagenet classification.â In âProceedings of the IEEE international conference on computer vision.â, 1026â1034.
Paper not yet in RePEc: Add citation now
- Ioffe, S., and C. Szegedy. (2015). âBatch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift.â arXiv:1502.03167 .
Paper not yet in RePEc: Add citation now
- Jain, P., and P. Kar. (2017). âNon-convex Optimization for Machine Learning.â Foundations and Trends in Machine Learning 10, 3-4, 142â336.
Paper not yet in RePEc: Add citation now
- Kingma, D., and J. Ba. (2015). âAdam: A method for stochastic optimization.â In âICLR,â .
Paper not yet in RePEc: Add citation now
- Ludvigson, S., and S. Ng. (2007). âThe empirical risk return relation: A factor analysis approach.â Journal of Financial Economics 83, 1, 171â222.
Paper not yet in RePEc: Add citation now
- McCracken, M. W., and S. Ng. (2016). âFRED-MD: A monthly database for Macroeconomic Research.â Journal of Business & Economic Statistics 34, 4, 574â589.
Paper not yet in RePEc: Add citation now
Medeiros, M. C., G. Vasconcelos, A. Veiga, and E. Zilberman. (2019). âForecasting Inflation in a Data-Rich Environment: The Benefits of Machine Learning Methods.â Journal of Business & Economic Statistics 1â45.
- Moody, J., and J. Utans. (1995). âArchitecture selection strategies for neural networks: application to bond rating prediction.â In âRefenes, A.-P.N. (ed.), Neural Networks in the Capital Markets,â New York: Wiley.
Paper not yet in RePEc: Add citation now
- Mullainathan, S., and J. Spiess. (2017). âMachine Learning: An Applied Econometric Approach.â Journal of Economic Perspectives 31, 2, 87â106.
Paper not yet in RePEc: Add citation now
- Nakamura, E. (2005). âInflation forecasting using a neural network.â Economics Letters 86, 373â 378.
Paper not yet in RePEc: Add citation now
- Refenes, A. N., and A. D. Zapranis. (1999). âNeural Model Identification, Variable Selection and Model Adequacy.â Journal of Forecasting 18, 299â332.
Paper not yet in RePEc: Add citation now
- Schmidt-Hieber, J. (2017). âNonparametric regression using deep neural networks with ReLU activation function.â .
Paper not yet in RePEc: Add citation now
- Sermpinis, G., C. Stasinakis, K. Theofilatos, and A. Karathanasopoulos. (2014). âInflation and Unemployment Forecasting with Genetic Support Vector Regression.â Journal of Forecasting 33, 471â487.
Paper not yet in RePEc: Add citation now
- Stock, J. H, and M. W. Watson. (2019). âSlack and Cyclically Sensitive Inflation.â NBER Working Paper No 25987 .
Paper not yet in RePEc: Add citation now
- Stock, J. H., and M. W. Watson. (1999). âForecasting Inflation.â Journal of Monetary Economics 44, 293â335.
Paper not yet in RePEc: Add citation now
- Stock, J. H., and M. W. Watson. (2002). âMacroeconomic forecasting with diffusion indexes.â Journal of Business & Economic Statistics 20, 147â162.
Paper not yet in RePEc: Add citation now
Stock, J. H., and M. W. Watson. (2007). âWhy Has U.S. Inflation Become Harder to Forecast?â Journal of Money, Credit and Banking. 39, 7, 1849â1849.
- Stone, M. (1974). âCross-Validatory choice and assessement of statistical predictions.â Journal of the Royal Statistical Society 36, 2, 111â147.
Paper not yet in RePEc: Add citation now
- Varian, H. R. (2014). âBig data: New tricks for econometrics.â The Journal of Economic Perspectives 28, 2, 3â27. A Data description
Paper not yet in RePEc: Add citation now