Banbura et al 2013 - Now-casting and the Real-Time Data Flow
Routing Summary
Full capture of Bańbura, Giannone, Modugno & Reichlin (2013), ECB Working Paper 1564 (substitute for the closed-access Mariano & Murasawa 2003, whose aggregation scheme it reproduces), plus one concept note on sensor fusion (E96-E99). 6 notes.
- Need paper on a page and section map? → Banbura et al 2013 - Now-casting and the Real-Time Data Flow - Overview
- Need stock/flow aggregation and Mariano-Murasawa weights? → Banbura 2013 - Mixed Frequency State Space and Mariano-Murasawa Aggregation
- Need dynamic factor model, PC / two-step / EM, mixed-frequency VAR? → Banbura 2013 - Factor Models, Estimation and the Ragged Edge
- Need news, nowcast revision, real-time vintages? → Banbura 2013 - News Decomposition and Real-Time Vintages
- Need bridge, MIDAS, the US GDP exercise? → Banbura 2013 - Partial Models and the Empirical GDP Application
- Need multi-instrument fusion, identification, localisation? → Banbura 2013 - Sensor Fusion in State-Space Form (Concept Note)
Concept Map
| Concept | Note | Type | Depends On | Key Result |
|---|---|---|---|---|
| Mariano-Murasawa aggregation | Banbura 2013 - Mixed Frequency State Space and Mariano-Murasawa Aggregation | definition | Linear-Gaussian State-Space Models | weights 1,2,3,2,1 |
| Dynamic factor nowcast | Banbura 2013 - Factor Models, Estimation and the Ragged Edge | definition | The Kalman Filter | EM ML is state of the art |
| News | Banbura 2013 - News Decomposition and Real-Time Vintages | theorem | Kalman moments | revision = weighted news |
| Bridge / MIDAS | Banbura 2013 - Partial Models and the Empirical GDP Application | definition | none | no news available |
| Sensor fusion | Banbura 2013 - Sensor Fusion in State-Space Form (Concept Note) | concept | all above | rank, bias, drift checks |
Notes
- Banbura et al 2013 - Now-casting and the Real-Time Data Flow - Overview — CONTAINS: summary, E96-E99 links, Source Map.
- Banbura 2013 - Mixed Frequency State Space and Mariano-Murasawa Aggregation — CONTAINS: stock/flow, aggregation theorem, MM approximation, Python.
- Banbura 2013 - Factor Models, Estimation and the Ragged Edge — CONTAINS: DFM, estimation, daily model, VAR, Kalman-with-missing code.
- Banbura 2013 - News Decomposition and Real-Time Vintages — CONTAINS: news theorem, real-time design, 2008Q4 episode.
- Banbura 2013 - Partial Models and the Empirical GDP Application — CONTAINS: bridge, MIDAS, Table 1 data, findings.
- Banbura 2013 - Sensor Fusion in State-Space Form (Concept Note) — CONTAINS: multi-sensor model, E96-E99 patterns, PyMC sketch.
Sources
- Banbura Giannone Modugno Reichlin 2013 - Now-casting and the Real-Time Data Flow
See Also
Linear-Gaussian State-Space Models · Marginal Likelihood via the Kalman Filter · The RTS Smoother