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Forecasting GDP growth using mixed-frequency models with switching regimes
16 references·1 citing·37 second hop
Forecasting GDP growth using mixed-frequency models with switching regimes (2014)Forecasting GDP growth using mixed-freque…Handbook of Economic Forecasting (2013)Handbook of Economic Forecast…Stock Market Volatility and Macroeconomic Fundamentals (2012)Stock Market Volatility and M…Nowcasting: The real-time informational content of macroeconomic data (2008)Nowcasting: The real-time inf…MIDAS Regressions: Further Results and New Directions (2007)MIDAS Regressions: Further Re…There is a risk-return trade-off after all (2005)There is a risk-return trade-…The Generalized Dynamic Factor Model (2005)The Generalized Dynamic Facto…Predicting volatility: getting the most out of return data sampled at different frequencies (2005)Predicting volatility: gettin…The MIDAS Touch: Mixed Data Sampling Regression Models (2004)The MIDAS Touch: Mixed Data S…Combination forecasts of output growth in a seven‐country data set (2004)Combination forecasts of outp…Inferential Theory for Factor Models of Large Dimensions (2003)Inferential Theory for Factor…Macroeconomic Forecasting Using Diffusion Indexes (2002)Macroeconomic Forecasting Usi…Forecasting Using Principal Components From a Large Number of Predictors (2002)Forecasting Using Principal C…Determining the Number of Factors in Approximate Factor Models (2002)Determining the Number of Fac…The Generalized Dynamic-Factor Model: Identification and Estimation (2000)The Generalized Dynamic-Facto…Can the Markov switching model forecast exchange rates? (1994)Can the Markov switching mode…A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle (1989)A New Approach to the Economi…Quantum Computing and Deep Learning Methods for GDP Growth Forecasting (2021)Quantum Computing and Deep Le…Time Series Analysis: Forecasting and Control (1977)Macroeconomics and Reality (1980)Statistical analysis of cointegration vectors (1988)Chapter 4 Forecast Combinations (2006)Carbon Tail Risk (2018)Empirical Asset Pricing via Machine Learning (2020)Tests for Unit Roots: A Monte Carlo Investigation (1989)Forecasting inflation (1999)A PANIC Attack on Unit Roots and Cointegration (2004)Panel Data Models With Interactive Fixed Effects (2009)New Indexes of Coincident and Leading Economic Indicators (1989)Large Bayesian vector auto regressions (2009)Real-Time Measurement of Business Conditions (2009)Prior Selection for Vector Autoregressions (2014)Business Cycle Modeling Without Pretending to Have Too Much A Priori Economic Theory (1977)Panels with Nonstationary Multifactor Error Structures (2006)Exploring the international linkages of the euro area: a global VAR analysis (2007)U.S. Monetary Policy and the Global Financial Cycle (2020)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)By Force of Habit: A Consumption‐Based Explanation of Aggregate Stock Market Behavior (1999)Risks for the Long Run: A Potential Resolution of Asset Pricing Puzzles (2000)Dynamic spillover effects among crude oil, precious metal, and agricultural commodity futures markets (2016)Climate policy uncertainty and world renewable energy index volatility forecasting (2022)Geopolitical risk and dynamic connectedness between commodity markets (2022)CAPITAL ASSET PRICES: A THEORY OF MARKET EQUILIBRIUM UNDER CONDITIONS OF RISK* (1964)Transition Modeling and Econometric Convergence Tests (2007)Trends and random walks in macroeconmic time series (1982)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis (1989)ARCH modeling in finance (1992)Introductory Econometrics for Finance (2008)The Combination of Forecasts (1969)Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy (2009)Forecasting Stock Returns (2013)Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500 (2016)Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure (2006)Measuring Uncertainty (2015)
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References

  • 1989A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle9,681 cited
  • 2002Determining the Number of Factors in Approximate Factor Models4,110 cited
  • 2002Forecasting Using Principal Components From a Large Number of Predictors2,990 cited
  • 2002Macroeconomic Forecasting Using Diffusion Indexes2,550 cited
  • 2000The Generalized Dynamic-Factor Model: Identification and Estimation1,709 cited
  • 2003Inferential Theory for Factor Models of Large Dimensions1,688 cited
  • 2013Handbook of Economic Forecasting1,216 cited
  • 2008Nowcasting: The real-time informational content of macroeconomic data1,153 cited
  • 2004Combination forecasts of output growth in a seven‐country data set1,138 cited
  • 2012Stock Market Volatility and Macroeconomic Fundamentals1,122 cited
  • 2005There is a risk-return trade-off after all1,019 cited
  • 2007MIDAS Regressions: Further Results and New Directions1,003 cited
  • 2005The Generalized Dynamic Factor Model824 cited
  • 2005Predicting volatility: getting the most out of return data sampled at different frequencies813 cited
  • 2004The MIDAS Touch: Mixed Data Sampling Regression Models563 cited

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  • 1994Can the Markov switching model forecast exchange rates?415 cited
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    • 2021Quantum Computing and Deep Learning Methods for GDP Growth Forecasting47 cited