Arbeitspapier
Generalized reduced rank regression
I introduce a technique to estimate parameters in regressions with reduced rank parameters in a general setting. The framework can handle a general class of parameter restrictions and allows for specifications with heteroskedastic and autocorrelated regression errors. Applications of this technique include: estimation of structural equations, estimation of reduced rank matrices in cross-section, panel, and time-series analysis, including estimation of cointegration relations in time series and panels. – Estimation ; Reduced Rank Regression ; FIML, Panel-cointegration, Cointegration with Heteroskedasticity and Autocorrelation
- Sprache
-
Englisch
- Erschienen in
-
Series: Working Paper ; No. 2002-02
Klassifikation
Wirtschaft
Estimation: General
Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models
Estimation: General
Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models
Thema
Regression
Schätztheorie
Theorie
Schätztheorie
Theorie
Ereignis
Geistige Schöpfung
(wer)
Hansen, Peter Reinhard
Ereignis
Veröffentlichung
(wer)
Brown University, Department of Economics
(wo)
Providence, RI
(wann)
2002
- Handle
- Letzte Aktualisierung
-
12.07.2024, 13:20 MESZ
Objekttyp
- Arbeitspapier
Beteiligte
- Hansen, Peter Reinhard
- Brown University, Department of Economics
Entstanden
- 2002
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