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Forecasting financial and macroeconomic variables using data reduction methods: New empirical evidence

Journal of econometrics, 2014-01, Vol.178 (2), p.352-367

2014

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Testing for structural stability of factor augmented forecasting models

Journal of econometrics, 2014-09, Vol.182 (1), p.100-118

2014

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Big data analytics in economics: What have we learned so far, and where should we go from here?

The Canadian journal of economics, 2018-08, Vol.51 (3), p.695-746

2018

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Mining big data using parsimonious factor, machine learning, variable selection and shrinkage methods

International journal of forecasting, 2018-04, Vol.34 (2), p.339-354

2018

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A survey of dynamic Nelson-Siegel models, diffusion indexes, and big data methods for predicting interest rates

Quantitative finance and economics, 2019-01, Vol.3 (1), p.22-45

2019

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New evidence of the marginal predictive content of small and large jumps in the cross-section

Econometrics, 2020-06, Vol.8 (2), p.1-52

2020

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Empirical evidence on the importance of aggregation, asymmetry, and jumps for volatility prediction

Journal of econometrics, 2015-08, Vol.187 (2), p.606-621

2015

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Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis: Essays in Honor of Halbert L. White Jr

1. Aufl., 2013

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Robust forecast superiority testing with an application to assessing pools of expert forecasters

Journal of applied econometrics (Chichester, England), 2023-06, Vol.38 (4), p.596-622

2023

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Fixed and long time span jump tests: New Monte Carlo and empirical evidence

Econometrics, 2019-03, Vol.7 (1), p.1-32

2019

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Forecasting volatility using double shrinkage methods

Journal of empirical finance, 2021-06, Vol.62, p.46-61

2021

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Jackknife estimation of a cluster-sample IV regression model with many weak instruments

Journal of econometrics, 2023-08, Vol.235 (2), p.1747-1769

2023

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Further Evidence on the Usefulness of Real-Time Datasets for Economic Forecasting

Quantitative finance and economics, 2017-01, Vol.1 (1), p.2-25

2017

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Predicting interest rates using shrinkage methods, real‐time diffusion indexes, and model combinations

Journal of applied econometrics (Chichester, England), 2020-08, Vol.35 (5), p.587-613

2020

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Nowcasting and forecasting GDP in emerging markets using global financial and macroeconomic diffusion indexes

International journal of forecasting, 2019-04, Vol.35 (2), p.555-572

2019

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Macroeconomic and financial mixed frequency factors in a big data environment

Journal of the Royal Statistical Society Series C: Applied Statistics, 2024-06, Vol.73 (3), p.682-714

2024

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Methods for backcasting, nowcasting and forecasting using factor‐MIDAS: With an application to Korean GDP

Journal of forecasting, 2018-04, Vol.37 (3), p.281-302

2018

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Money and output viewed through a rolling window

Journal of monetary economics, 1998-06, Vol.41 (3), p.455-474

Swanson, Norman R.

1998

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ROBUST FORECAST COMPARISON

Econometric theory, 2017-12, Vol.33 (6), p.1306-1351

2017

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Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors

Journal of forecasting, 2020-01, Vol.39 (1), p.18-36

2020

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Testing for jumps and jump intensity path dependence

Journal of econometrics, 2018-06, Vol.204 (2), p.248-267

2018

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A Model Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks

The review of economics and statistics, 1997-11, Vol.79 (4), p.540-550

1997

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Mixing mixed frequency and diffusion indices in good times and in bad: an assessment based on historical data around the great recession of 2008

Empirical economics, 2023-03, Vol.64 (3), p.1421-1469

2023

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Consistent Estimation with a Large Number of Weak Instruments

Econometrica, 2005-09, Vol.73 (5), p.1673-1692

2005

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Impulse Response Functions Based on a Causal Approach to Residual Orthogonalization in Vector Autoregressions

Journal of the American Statistical Association, 1997-03, Vol.92 (437), p.357-367

1997

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Forecasting financial and macroeconomic variables using data reduction methods: New empirical evidence

Testing for structural stability of factor augmented forecasting models

Big data analytics in economics: What have we learned so far, and where should we go from here?

Mining big data using parsimonious factor, machine learning, variable selection and shrinkage methods

A survey of dynamic Nelson-Siegel models, diffusion indexes, and big data methods for predicting interest rates

New evidence of the marginal predictive content of small and large jumps in the cross-section

Empirical evidence on the importance of aggregation, asymmetry, and jumps for volatility prediction

Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis: Essays in Honor of Halbert L. White Jr

Robust forecast superiority testing with an application to assessing pools of expert forecasters

Fixed and long time span jump tests: New Monte Carlo and empirical evidence

Forecasting volatility using double shrinkage methods

Jackknife estimation of a cluster-sample IV regression model with many weak instruments

Further Evidence on the Usefulness of Real-Time Datasets for Economic Forecasting

Predicting interest rates using shrinkage methods, real‐time diffusion indexes, and model combinations

Nowcasting and forecasting GDP in emerging markets using global financial and macroeconomic diffusion indexes

Macroeconomic and financial mixed frequency factors in a big data environment

Methods for backcasting, nowcasting and forecasting using factor‐MIDAS: With an application to Korean GDP

Money and output viewed through a rolling window

ROBUST FORECAST COMPARISON

Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors

Testing for jumps and jump intensity path dependence

A Model Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks

Mixing mixed frequency and diffusion indices in good times and in bad: an assessment based on historical data around the great recession of 2008

Consistent Estimation with a Large Number of Weak Instruments

Impulse Response Functions Based on a Causal Approach to Residual Orthogonalization in Vector Autoregressions

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