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Forecasting China's GDP growth using dynamic factors and mixed-frequency data
16 references·4 citing·31 second hop
Forecasting China's GDP growth using dynamic factors and mixed-frequency data (2017)Forecasting China's GDP growth using dyna…OPENING THE BLACK BOX: STRUCTURAL FACTOR MODELS WITH LARGE CROSS SECTIONS (2009)OPENING THE BLACK BOX: STRUCT…Macroeconomic Forecasting With Mixed-Frequency Data (2008)Macroeconomic Forecasting Wit…MIDAS Regressions: Further Results and New Directions (2007)MIDAS Regressions: Further Re…Chapter 4 Forecast Combinations (2006)Chapter 4 Forecast Combinatio…Chapter 10 Forecasting with Many Predictors (2006)Chapter 10 Forecasting with M…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…Forecasting Output and Inflation: The Role of Asset Prices (2003)Forecasting Output and Inflat…Forecasting Output and Inflation: The Role of Asset Prices (2003)Forecasting Output and Inflat…Macroeconomic Forecasting Using Diffusion Indexes (2002)Macroeconomic Forecasting Usi…Determining the Number of Factors in Approximate Factor Models (2002)Determining the Number of Fac…Asymptotic Inference about Predictive Ability (1996)Asymptotic Inference about Pr…Comparing Predictive Accuracy (1995)Comparing Predictive AccuracyComparing Predictive Accuracy (1994)Comparing Predictive AccuracyNew Indexes of Coincident and Leading Economic Indicators (1989)New Indexes of Coincident and…Business Cycle Modeling Without Pretending to Have Too Much A Priori Economic Theory (1977)Business Cycle Modeling Witho…Nowcasting Chinese GDP in a data-rich environment: Lessons from machine learning algorithms (2023)Nowcasting Chinese GDP in a d…On using predictive-ability tests in the selection of time-series prediction models: A Monte Carlo evaluation (2020)On using predictive-ability t…Forecasting India’s economic growth: a time-varying parameter regression approach (2019)Forecasting India’s economic …Forecasting China's wastewater discharge using dynamic factors and mixed-frequency data (2019)Forecasting China's wastewate…Tests for Unit Roots: A Monte Carlo Investigation (1989)Forecasting inflation (1999)Measuring Uncertainty (2015)Empirical Asset Pricing via Machine Learning (2020)The Combination of Forecasts (1969)A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle (1989)Combining forecasts: A review and annotated bibliography (1989)Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy (2009)Investor Sentiment Aligned: A Powerful Predictor of Stock Returns (2014)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)The Generalized Dynamic-Factor Model: Identification and Estimation (2000)Forecasting Using Principal Components From a Large Number of Predictors (2002)Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure (2006)Distribution of the Estimators for Autoregressive Time Series With a Unit Root (1979)Business conditions and expected returns on stocks and bonds (1989)The Twin Crises: The Causes of Banking and Balance-of-Payments Problems (1999)Postwar U.S. Business Cycles: An Empirical Investigation (1997)25 years of time series forecasting (2006)Approximately normal tests for equal predictive accuracy in nested models (2006)Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory* (2000)Why Has U.S. Inflation Become Harder to Forecast? (2007)Credit Spreads and Business Cycle Fluctuations (2012)Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation (1991)Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts (1998)Forecasting Economic Time Series (2000)A Comprehensive Look at The Empirical Performance of Equity Premium Prediction (2007)Strictly Proper Scoring Rules, Prediction, and Estimation (2007)The macroeconomy and the yield curve: a dynamic latent factor approach (2005)Testing the equality of prediction mean squared errors (1997)Consumption, Aggregate Wealth, and Expected Stock Returns (2001)Deep learning with long short-term memory networks for financial market predictions (2017)
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References

  • 1994Comparing Predictive Accuracy5,578 cited
  • 1995Comparing Predictive Accuracy5,370 cited
  • 2002Determining the Number of Factors in Approximate Factor Models4,110 cited
  • 2002Macroeconomic Forecasting Using Diffusion Indexes2,550 cited
  • 1989New Indexes of Coincident and Leading Economic Indicators1,795 cited
  • 2003Forecasting Output and Inflation: The Role of Asset Prices1,488 cited
  • 1996Asymptotic Inference about Predictive Ability1,415 cited
  • 2006Chapter 4 Forecast Combinations1,318 cited
  • 2004Combination forecasts of output growth in a seven‐country data set1,138 cited
  • 2003Forecasting Output and Inflation: The Role of Asset Prices1,076 cited
  • 2007MIDAS Regressions: Further Results and New Directions1,003 cited
  • 1977Business Cycle Modeling Without Pretending to Have Too Much A Priori Economic Theory708 cited
  • 2004The MIDAS Touch: Mixed Data Sampling Regression Models563 cited
  • 2009OPENING THE BLACK BOX: STRUCTURAL FACTOR MODELS WITH LARGE CROSS SECTIONS394 cited
  • 2008Macroeconomic Forecasting With Mixed-Frequency Data392 cited
  • 2006

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Chapter 10 Forecasting with Many Predictors
382 cited

Cited by

  • 2019Forecasting China's wastewater discharge using dynamic factors and mixed-frequency data31 cited
  • 2020On using predictive-ability tests in the selection of time-series prediction models: A Monte Carlo evaluation27 cited
  • 2023Nowcasting Chinese GDP in a data-rich environment: Lessons from machine learning algorithms24 cited
  • 2019Forecasting India’s economic growth: a time-varying parameter regression approach14 cited