Arbeitspapier

Generalized reduced rank regression

to connected objects

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

Language
Englisch

Bibliographic citation
Series: Working Paper ; No. 2002-02

Classification
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
Subject
Regression
Schätztheorie
Theorie

Event
Geistige Schöpfung
(who)
Hansen, Peter Reinhard
Event
Veröffentlichung
(who)
Brown University, Department of Economics
(where)
Providence, RI
(when)
2002

Handle
Last update
10.03.2025, 11:44 AM CET

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Object type

  • Arbeitspapier

Associated

  • Hansen, Peter Reinhard
  • Brown University, Department of Economics

Time of origin

  • 2002

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