Increasing longevity and social security reforms

Arbeitspapier

The presence of cross-sectionally correlated error terms invalidates much inferential theory of panel data models. Recently work by Pesaran (2006) has suggested a method which makes use of cross-sectional averages to provide valid inference for stationary panel regressions with multifactor error structure. This paper extends this work and examines the important case where the unobserved common factors follow unit root processes and could be cointegrated. It is found that the presence of unit roots does not affect most theoretical results which continue to hold irrespective of the integration and the cointegration properties of the unobserved factors. This finding is further supported for small samples via an extensive Monte Carlo study. In particular, the results of the Monte Carlo study suggest that the cross-sectional average based method is robust to a wide variety of data generation processes and has lower biases than all of the alternative estimation methods considered in the paper.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: CESifo Working Paper ; No. 1789

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Hypothesis Testing: General ; Estimation: General ; Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models
• Thema: Sterblichkeit ; Alternde Bevölkerung ; Soziale Sicherung ; Gesundheitsreform ; Rentenreform ; Overlapping Generations ; Theorie

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Andersen, Torben M.
• Ereignis: Veröffentlichung
• (wer): Center for Economic Studies and ifo Institute (CESifo)
• (wo): Munich
• (wann): 2006

Weitere Informationen

• Handle: http://hdl.handle.net/10419/25833
• Letzte Aktualisierung: 10.03.2025, 11:44 MEZ