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State Space Models and MIDAS Regressions
16 references·16 citing·41 second hopsampled
State Space Models and MIDAS Regressions (2013)State Space Models and MIDAS RegressionsHandbook of Economic Forecasting (2013)Handbook of Economic Forecast…Real-Time Measurement of Business Conditions (2009)Real-Time Measurement of Busi…Macroeconomic Forecasting With Mixed-Frequency Data (2008)Macroeconomic Forecasting Wit…Why Do Absolute Returns Predict Volatility So Well? (2006)Why Do Absolute Returns Predi…There is a risk-return trade-off after all (2005)There is a risk-return trade-…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…A PANIC Attack on Unit Roots and Cointegration (2004)A PANIC Attack on Unit Roots …Monetary policy in a data-rich environment (2003)Monetary policy in a data-ric…Macroeconomic Forecasting Using Diffusion Indexes (2002)Macroeconomic Forecasting Usi…A new coincident index of business cycles based on monthly and quarterly series (2002)A new coincident index of bus…The Generalized Dynamic-Factor Model: Identification and Estimation (2000)The Generalized Dynamic-Facto…Systematic Monetary Policy and the Effects of Oil Price Shocks (1997)Systematic Monetary Policy an…Forecasting, Structural Time Series Models and the Kalman Filter (1990)Forecasting, Structural Time …New Indexes of Coincident and Leading Economic Indicators (1989)New Indexes of Coincident and…The Combination of Forecasts (1969)The Combination of ForecastsMonitoring banking system connectedness with big data (2019)Monitoring banking system con…Does Monetary Policy Affect Income Inequality in the Euro Area? (2019)Does Monetary Policy Affect I…Is the intrinsic value of a macroeconomic news announcement related to its asset price impact? (2017)Is the intrinsic value of a m…Google's MIDAS Touch: Predicting UK Unemployment with Internet Search Data (2016)Google's MIDAS Touch: Predict…A mixed frequency approach to the forecasting of private consumption with ATM/POS data (2016)A mixed frequency approach to…A comparison of MIDAS and bridge equations (2016)A comparison of MIDAS and bri…Forecasting GDP growth using mixed-frequency models with switching regimes (2014)Forecasting GDP growth using …Bayesian Mixed Frequency VARs (2014)Bayesian Mixed Frequency VARsReal-Time Forecasting with a Mixed-Frequency VAR (2013)Real-Time Forecasting with a …Mixed-Frequency Vector Autoregressive Models (2013)Mixed-Frequency Vector Autore…Forecasting macroeconomic variables using collapsed dynamic factor analysis (2013)Forecasting macroeconomic var…A Survey of Econometric Methods for Mixed-Frequency Data (2013)A Survey of Econometric Metho…Markov-Switching MIDAS Models (2012)Markov-Switching MIDAS ModelsMacroeconomics and the Reality of Mixed Frequency Data (2012)Macroeconomics and the Realit…Forecasting with Mixed-Frequency Data (2012)Forecasting with Mixed-Freque…Forecasting with Mixed Frequencies (2010)Forecasting with Mixed Freque…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)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)Forecasting Using Principal Components From a Large Number of Predictors (2002)Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure (2006)Measuring Uncertainty (2015)Econometric policy evaluation: A critique (1976)The federal funds rate and the channels of monetary transmission (1989)Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach (2005)Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market (2009)THE IMPACT OF OIL PRICE SHOCKS ON THE U.S. STOCK MARKET* (2009)A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle (1989)Forecasting Stock Returns (2013)The Sum of All FEARS Investor Sentiment and Asset Prices (2014)Fiscal Volatility Shocks and Economic Activity (2015)An Intertemporal Capital Asset Pricing Model (1973)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks (1993)The conditional CAPM does not explain asset-pricing anomalies☆ (2006)MIDAS Regressions: Further Results and New Directions (2007)Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)Testing for unit roots in heterogeneous panels (2003)A Simple Panel Unit Root Test in the Presence of Cross Section Dependence (2004)Introductory Econometrics for Finance (2008)CO2 emissions, economic growth, energy consumption, trade and urbanization in new EU member and candidate countries: A panel data analysis (2014)Time series forecasting using a hybrid ARIMA and neural network model (2003)25 years of time series forecasting (2006)Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy (2009)The Conditional CAPM and the Cross-Section of Expected Returns (1996)The Twin Crises: The Causes of Banking and Balance-of-Payments Problems (1999)Measuring the Output Responses to Fiscal Policy (2012)Testing the null hypothesis of stationarity against the alternative of a unit root (1992)Handbook on Constructing Composite Indicators (2005)Handbook on Constructing Composite Indicators: Methodology and User Guide (2008)
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References

  • 1990Forecasting, Structural Time Series Models and the Kalman Filter4,101 cited
  • 1969The Combination of Forecasts3,194 cited
  • 2002Macroeconomic Forecasting Using Diffusion Indexes2,550 cited
  • 2004A PANIC Attack on Unit Roots and Cointegration1,890 cited
  • 1989New Indexes of Coincident and Leading Economic Indicators1,795 cited
  • 2000The Generalized Dynamic-Factor Model: Identification and Estimation1,709 cited
  • 1997Systematic Monetary Policy and the Effects of Oil Price Shocks1,594 cited
  • 2013Handbook of Economic Forecasting1,216 cited
  • 2005There is a risk-return trade-off after all1,019 cited
  • 2009Real-Time Measurement of Business Conditions916 cited
  • 2005Predicting volatility: getting the most out of return data sampled at different frequencies813 cited
  • 2003Monetary policy in a data-rich environment702 cited
  • 2002A new coincident index of business cycles based on monthly and quarterly series631 cited
  • 2004The MIDAS Touch: Mixed Data Sampling Regression Models563 cited
  • 2008Macroeconomic Forecasting With Mixed-Frequency Data392 cited
  • 2006

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Why Do Absolute Returns Predict Volatility So Well?
379 cited

Cited by

  • 2010Forecasting with Mixed Frequencies130 cited
  • 2013A Survey of Econometric Methods for Mixed-Frequency Data121 cited
  • 2012Markov-Switching MIDAS Models110 cited
  • 2012Forecasting with Mixed-Frequency Data104 cited
  • 2017Is the intrinsic value of a macroeconomic news announcement related to its asset price impact?88 cited
  • 2019Does Monetary Policy Affect Income Inequality in the Euro Area?75 cited
  • 2012Macroeconomics and the Reality of Mixed Frequency Data73 cited
  • 2014Bayesian Mixed Frequency VARs64 cited
  • 2013Forecasting macroeconomic variables using collapsed dynamic factor analysis60 cited
  • 2016Google's MIDAS Touch: Predicting UK Unemployment with Internet Search Data57 cited
  • 2013Real-Time Forecasting with a Mixed-Frequency VAR54 cited
  • 2014Forecasting GDP growth using mixed-frequency models with switching regimes52 cited
  • 2016A mixed frequency approach to the forecasting of private consumption with ATM/POS data50 cited
  • 2016A comparison of MIDAS and bridge equations48 cited
  • 2013Mixed-Frequency Vector Autoregressive Models48 cited
  • 2019Monitoring banking system connectedness with big data47 cited