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Marcelo C. Medeiros

Institution: University of Illinois at Urbana-Champaign

Primary Field: Econometrics (weighted toward more recent publications)

Homepage: https://economics.illinois.edu/profile/marcelom

First Publication: 2005

Most Recent: 2023

RePEc ID: pme53 ↗

Publication Scores

Scores use coauthorship adjustment: α/n credit per paper, where n = number of authors. α = 2.02: calibrated so average adjusted count equals average raw count (a zero-sum adjustment).

Period S (4x) A (2x) B (1x) C (½x) Total Percentile
Last 5 Years 0.00 5.38 2.09 0.34 7.80 92%
Last 10 Years 0.00 12.11 3.43 1.18 16.72 96%
All Time 0.00 19.64 8.81 1.68 30.14 96%

Publication Statistics

Raw Publications 29
Coauthorship-Adjusted Count 22.01

Publications (29)

Year Article Journal Tier Authors
2023 Sharpe Ratio analysis in high dimensions: Residual-based nodewise regression in factor models Journal of Econometrics A 3
2023 Machine learning advances for time series forecasting Journal of Economic Surveys C 3
2022 From zero to hero: Realized partial (co)variances Journal of Econometrics A 4
2022 Do We Exploit all Information for Counterfactual Analysis? Benefits of Factor Models and Idiosyncratic Correction Journal of the American Statistical Association B 3
2022 Short-term Covid-19 forecast for latecomers International Journal of Forecasting B 5
2022 Counterfactual Analysis and Inference With Nonstationary Data Journal of Business & Economic Statistics A 2
2021 Counterfactual Analysis With Artificial Controls: Inference, High Dimensions, and Nonstationarity Journal of the American Statistical Association B 2
2021 Forecasting Inflation in a Data-Rich Environment: The Benefits of Machine Learning Methods Journal of Business & Economic Statistics A 4
2020 A Smooth Transition Finite Mixture Model for Accommodating Unobserved Heterogeneity Journal of Business & Economic Statistics A 3
2018 ArCo: An artificial counterfactual approach for high-dimensional panel time-series data Journal of Econometrics A 3
2017 Modeling and Forecasting Large Realized Covariance Matrices and Portfolio Choice Journal of Applied Econometrics B 3
2017 Real-time inflation forecasting with high-dimensional models: The case of Brazil International Journal of Forecasting B 3
2016 Forecasting macroeconomic variables in data-rich environments Economics Letters C 2
2016 Instrument selection for estimation of a forward-looking Phillips Curve Economics Letters C 3
2016 ℓ1-regularization of high-dimensional time-series models with non-Gaussian and heteroskedastic errors Journal of Econometrics A 2
2016 Nonlinearity, Breaks, and Long-Range Dependence in Time-Series Models Journal of Business & Economic Statistics A 2
2014 Modeling and predicting the CBOE market volatility index Journal of Banking & Finance B 3
2011 Moment-based estimation of smooth transition regression models with endogenous variables Journal of Econometrics A 3
2011 Modeling and forecasting short‐term interest rates: The benefits of smooth regimes, macroeconomic variables, and bagging Journal of Applied Econometrics B 2
2011 Forecasting Realized Volatility with Linear and Nonlinear Univariate Models Journal of Economic Surveys C 2
2011 Linear programming-based estimators in simple linear regression Journal of Econometrics A 2
2009 MODELING MULTIPLE REGIMES IN FINANCIAL VOLATILITY WITH A FLEXIBLE COEFFICIENT GARCH(1,1) MODEL Econometric Theory B 2
2009 Asymmetric effects and long memory in the volatility of Dow Jones stocks International Journal of Forecasting B 2
2008 A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries Journal of Econometrics A 2
2008 A neural network demand system with heteroskedastic errors Journal of Econometrics A 3
2008 An alternative approach to estimating demand: Neural network regression with conditional volatility for high frequency air passenger arrivals Journal of Econometrics A 5
2008 Modeling and forecasting short-term electricity load: A comparison of methods with an application to Brazilian data International Journal of Forecasting B 2
2005 Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination International Journal of Forecasting B 3
2005 Reply International Journal of Forecasting B 3