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Boosting diffusion indices
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Boosting diffusion indices (2009)Boosting diffusion indicesForecasting using a large number of predictors: Is Bayesian shrinkage a valid alternative to principal components? (2008)Forecasting using a large num…Forecasting economic time series using targeted predictors (2008)Forecasting economic time ser…Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions (2006)Confidence Intervals for Diff…The Generalized Dynamic Factor Model (2005)The Generalized Dynamic Facto…Inferential Theory for Factor Models of Large Dimensions (2003)Inferential Theory for Factor…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…Macroeconomic forecasting using factor models and machine learning: an application to Japan (2020)Macroeconomic forecasting usi…Understanding survey-based inflation expectations (2018)Understanding survey-based in…Predicting recessions with boosted regression trees (2017)Predicting recessions with bo…Revisiting useful approaches to data-rich macroeconomic forecasting (2016)Revisiting useful approaches …Mining Big Data Using Parsimonious Factor, Machine Learning, Variable Selection and Shrinkage Methods (2016)Mining Big Data Using Parsimo…Forecasting in Economics and Finance (2016)Forecasting in Economics and …Stock market volatility: Identifying major drivers and the nature of their impact (2015)Stock market volatility: Iden…Predicting Recessions with Leading Indicators: Model Averaging and Selection over the Business Cycle (2015)Predicting Recessions with Le…Forecasting with factor-augmented regression: A frequentist model averaging approach (2015)Forecasting with factor-augme…Viewpoint: Boosting Recessions (2014)Viewpoint: Boosting RecessionsVariable selection, estimation and inference for multi-period forecasting problems (2011)Variable selection, estimatio…Forecasting with Approximate Dynamic Factor Models: The Role of Non-Pervasive Shocks (2011)Forecasting with Approximate …To Combine Forecasts or to Combine Information? (2010)To Combine Forecasts or to Co…Forecasting large datasets with Bayesian reduced rank multivariate models (2010)Forecasting large datasets wi…Forecasting Financial and Macroeconomic Variables Using Data Reduction Methods: New Empirical Evidence (2010)Forecasting Financial and Mac…What is the Shape of the Risk-Return Relation? (2009)What is the Shape of the Risk…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)Trends and random walks in macroeconmic time series (1982)Trends and random walks in macroeconomic time series (1988)Forecasting Stock Returns (2013)Systemic risk and the macroeconomy: An empirical evaluation (2016)CAPITAL ASSET PRICES: A THEORY OF MARKET EQUILIBRIUM UNDER CONDITIONS OF RISK* (1964)New Indexes of Coincident and Leading Economic Indicators (1989)Transition Modeling and Econometric Convergence Tests (2007)Macroeconomic Forecasting Using Diffusion Indexes (2002)Measuring Uncertainty (2015)Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation (1991)Consistent Covariance Matrix Estimation with Spatially Dependent Panel Data (1998)Large Dimensional Factor Analysis (2008)A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models (2011)Grouped Patterns of Heterogeneity in Panel Data (2015)Comparing Predictive Accuracy (1995)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)In Search of a Job: Forecasting Employment Growth Using Google Trends (2020)Comparing Predictive Accuracy (1994)A comprehensive literature review of the demand forecasting methods of emergency resources from the perspective of artificial intelligence (2019)Questioning the news about economic growth: Sparse forecasting using thousands of news-based sentiment values (2019)Forecasting in the Presence of Instabilities: How We Know Whether Models Predict Well and How to Improve Them (2021)The Combination of Forecasts (1969)Forecasting Stock Return Volatility: A Comparison of GARCH, Implied Volatility, and Realized Volatility Models (2016)Technical analysis and stock return predictability: An aligned approach (2017)Sparse and stable Markowitz portfolios (2009)Now-Casting and the Real-Time Data Flow (2013)Panel Vector Autoregressive Models: A Survey (2013)Testing for a unit root in panels with dynamic factors (2004)Determining the Number of Factors in the General Dynamic Factor Model (2007)
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References

  • 2002Determining the Number of Factors in Approximate Factor Models4,110 cited
  • 2002Forecasting Using Principal Components From a Large Number of Predictors2,990 cited
  • 2003Inferential Theory for Factor Models of Large Dimensions1,688 cited
  • 2005The Generalized Dynamic Factor Model824 cited
  • 2008Forecasting economic time series using targeted predictors704 cited
  • 2006Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions629 cited
  • 2008Forecasting using a large number of predictors: Is Bayesian shrinkage a valid alternative to principal components?521 cited

Cited by

  • 2015Forecasting with factor-augmented regression: A frequentist model averaging approach141 cited
  • 2010Forecasting Financial and Macroeconomic Variables Using Data Reduction Methods: New Empirical Evidence138 cited
  • 2016Mining Big Data Using Parsimonious Factor, Machine Learning, Variable Selection and Shrinkage Methods119 cited
  • 2015Stock market volatility: Identifying major drivers and the nature of their impact118 cited
  • 2017Predicting recessions with boosted regression trees117 cited
  • 2010Forecasting large datasets with Bayesian reduced rank multivariate models109 cited
  • 2010To Combine Forecasts or to Combine Information?

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107 cited
  • 2015Predicting Recessions with Leading Indicators: Model Averaging and Selection over the Business Cycle104 cited
  • 2011Variable selection, estimation and inference for multi-period forecasting problems94 cited
  • 2014Viewpoint: Boosting Recessions71 cited
  • 2016Forecasting in Economics and Finance69 cited
  • 2016Revisiting useful approaches to data-rich macroeconomic forecasting67 cited
  • 2009What is the Shape of the Risk-Return Relation?65 cited
  • 2011Forecasting with Approximate Dynamic Factor Models: The Role of Non-Pervasive Shocks56 cited
  • 2020Macroeconomic forecasting using factor models and machine learning: an application to Japan53 cited
  • 2018Understanding survey-based inflation expectations46 cited