Survey-Based Forecasting: To Average or Not to Average

DOI10.1007/978-3-030-49728-6_5zbMath1479.91218OpenAlexW3047363354MaRDI QIDQ5015918

Naijing Huang, Zhentao Shi, Kayan Cheng

Publication date: 10 December 2021

Published in: Studies in Computational Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-030-49728-6_5

zbMATH Keywords

inflationforecast combinationinformation aggregationlassoprofessional forecasters

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Economic time series analysis (91B84) Macroeconomic theory (monetary models, models of taxation) (91B64)

Cites Work

• Unnamed Item
• Greedy function approximation: A gradient boosting machine.
• Econometric estimation with high-dimensional moment equalities
• Inflationary expectations and rationality revisited
• Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain
• LASSO-TYPE GMM ESTIMATOR
• Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
• Identifying Latent Structures in Panel Data
• Estimation of Sparse Structural Parameters with Many Endogenous Variables
• Random forests

This page was built for publication: Survey-Based Forecasting: To Average or Not to Average