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Estimating Dynamic Causal Effects with hetiv11 days ago
Introduction | Simulated data | Estimation | Heteroskedasticity-IV without controls | Heteroskedasticity-IV with controls | Proxy-IV | Proxy-IV with recursive zero restriction | Impact matrices | Impulse response functions | Impulse responses with confidence intervals | HET-IV estimates versus true IRF | HET-IV estimates versus misspecified model | HET-IV versus Proxy-IV | Proxy-SVAR with bootstrap bands | Shock extraction | Prediction from several horizons | Weak instrument test | References
Nowcasting revisions using the generalized Kishor-Koenig family2 months ago
Revision system | Nested models | Durbin-Koopman state-space form | Estimation in reviser | Example: Euro Area GDP revisions | Other KK-family specifications
Nowcasting revisions using the Jacobs-Van Norden model2 months ago
Revision decomposition | Durbin-Koopman state-space form | The reviser implementation | Measurement equation | Transition equation | Shock-loading matrix | Nested JVN specifications | Example: Euro Area GDP revisions | Other JVN specifications
Nowcasting revisions using the generalized Kishor-Koenig family2 months ago
Revision system | Nested models | Durbin-Koopman state-space form | Estimation in reviser | Example: Euro Area GDP revisions | Other KK-family specifications
Nowcasting revisions using the Jacobs-Van Norden model2 months ago
Revision decomposition | Durbin-Koopman state-space form | The reviser implementation | Measurement equation | Transition equation | Shock-loading matrix | Nested JVN specifications | Example: Euro Area GDP revisions | Other JVN specifications
Introduction to reviser2 months ago
Package conventions | Convert Long to Wide Format | Convert Wide to Long Format | Handling Multiple Series with id | Extracting Releases | Visualizing Vintage Data | Analyzing Data Revisions and Releases
Introduction to reviser2 months ago
Package conventions | Convert Long to Wide Format | Convert Wide to Long Format | Handling Multiple Series with id | Extracting Releases | Visualizing Vintage Data | Analyzing Data Revisions and Releases
Aggregation and Mixed-Frequency Modeling in bridgr3 months ago
The Bridge-to-MIDAS Spectrum | A Small Monthly-to-Quarterly Example | Deterministic Bridge Aggregation | Fixed numeric weights | Unrestricted Mixed-Frequency Regression | Parametric MIDAS-Style Weighting | Forecast Comparison | Picking an Aggregator on Out-of-Sample Performance | Choosing an Aggregation Strategy | Related packages
Getting Started with bridgr3 months ago
Overview | Example Data | Stationarity expectations | A Basic Bridge Model | Lags in the target equation | Standardized Output | Forecast Visualization | Multiple Indicators | Direct Alignment | Non-Standard Calendars | Optional Uncertainty Output | Where to Go Next
Uncertainty and Scenario Forecasting3 months ago
Overview | Fitting a Model with Default Uncertainty | Forecast Output | Reporting Only Forecasts Below a Width Tolerance | Summary Output | Scenario Forecasting with xreg | Optional Full-System Bootstrap | Point Forecasts Only | Interpretation
A Real-Time Nowcasting Exercise5 months ago
Why Real-Time Evaluation Matters | Setup | A Single-Quarter Illustration | Full Real-Time Loop | Method × Vintage Scoreboard | Forecasts vs. Realizations | Where to Go Next
Ragged-Edge Nowcasting with bridgr5 months ago
Why Ragged Edges Matter | A Ragged-Edge Example | Comparing Indicator Completion Rules | Visualizing the completed indicator paths | Direct Alignment | Explicit Missing Values | When to Use Which Option
Identifying an Efficient Release in Data Subject to Revisions7 months ago
Optimal Properties of Revisions | Initial Estimates as Truth Measured with Noise | The Challenge of Defining a Final Release | Iterative Approach for Identifying ( e ) | Importance of an Efficient Release | Example: Identifying an Efficient Release in GDP Data with reviser | References
Revision Patterns and Statistics7 months ago
Summary Statistics | Revision Size | 1. Mean Revision ("Bias (mean)") | 2. Mean Absolute Revision ("MAR") | 3. Minimum and Maximum Revisions ("Minimum", "Maximum") | 4. Percentiles of Revisions ("10Q", "Median", "90Q") | 5. Standard Deviation of Revisions ("Std. Dev.") | 6. Noise-to-Signal Ratio ("Noise/Signal") | Correlation of Revisions | 1. Correlation Between Revisions and Initial Releases ("Correlation") | 2. 1st order Autocorrelation of Revisions ("Autocorrelation (1st)") | 3. Autocorrelation of Revisions up to 1 year ("Autocorrelation up to 1yr (Ljung-Box p-value)") | Sign Switches | 1. Fraction of sign changes | 2. Fraction of sign changes in the growth rate | Hypothesis Tests | News and Noise Tests for Data Revisions | 1. The Noise Test | 2. The News Test | Test of Seasonality in Revisions | Friedman Test | Theil’s U Statistics | 1. Theil’s U1 Statistic ("Theil's U1") | 2. Theil’s U2 Statistic ("Theil's U2") | References
Identifying an Efficient Release in Data Subject to Revisions7 months ago
Optimal Properties of Revisions | Initial Estimates as Truth Measured with Noise | The Challenge of Defining a Final Release | Iterative Approach for Identifying ( e ) | Importance of an Efficient Release | Example: Identifying an Efficient Release in GDP Data with reviser | References
Revision Patterns and Statistics7 months ago
Summary Statistics | Revision Size | 1. Mean Revision ("Bias (mean)") | 2. Mean Absolute Revision ("MAR") | 3. Minimum and Maximum Revisions ("Minimum", "Maximum") | 4. Percentiles of Revisions ("10Q", "Median", "90Q") | 5. Standard Deviation of Revisions ("Std. Dev.") | 6. Noise-to-Signal Ratio ("Noise/Signal") | Correlation of Revisions | 1. Correlation Between Revisions and Initial Releases ("Correlation") | 2. 1st order Autocorrelation of Revisions ("Autocorrelation (1st)") | 3. Autocorrelation of Revisions up to 1 year ("Autocorrelation up to 1yr (Ljung-Box p-value)") | Sign Switches | 1. Fraction of sign changes | 2. Fraction of sign changes in the growth rate | Hypothesis Tests | News and Noise Tests for Data Revisions | 1. The Noise Test | 2. The News Test | Test of Seasonality in Revisions | Friedman Test | Theil’s U Statistics | 1. Theil’s U1 Statistic ("Theil's U1") | 2. Theil’s U2 Statistic ("Theil's U2") | References
Understanding Data Revisions7 months ago
Introduction: Why do data revisions occur? | Incorporation of newly available or updated data | Base data revisions | Benchmark revisions (methodological changes) | Minor changes in estimation methods | Technical adjustments & error corrections | Economic events & shocks | Technological advances in data collection | Some mathematical notation | Extracting revisions with reviser | The get_revisions() function | Example usage | Example 1: Revisions Using an Interval | Example 2: Revisions Relative to a Fixed Reference Date | Example 3: Revisions to the Nth Release | Example 4: How does the growth rate of GDP change over time? | References
Understanding Data Revisions7 months ago
Introduction: Why do data revisions occur? | Incorporation of newly available or updated data | Base data revisions | Benchmark revisions (methodological changes) | Minor changes in estimation methods | Technical adjustments & error corrections | Economic events & shocks | Technological advances in data collection | Some mathematical notation | Extracting revisions with reviser | The get_revisions() function | Example usage | Example 1: Revisions Using an Interval | Example 2: Revisions Relative to a Fixed Reference Date | Example 3: Revisions to the Nth Release | Example 4: How does the growth rate of GDP change over time? | References
The Role and Importance of Revisions in Time Series Data2 years ago
Introduction | Understanding the Magnitude of Revisions | The Dynamics of Revisions and What They Reveal | The Uses of Studying Revisions in Time Series Data | Conclusion
The Role and Importance of Revisions in Time Series Data2 years ago
Introduction | Understanding the Magnitude of Revisions | The Dynamics of Revisions and What They Reveal | The Uses of Studying Revisions in Time Series Data | Conclusion