The impact of data revisions on the robustness of growth determinants: A note on 'determinants of economic growth: will data tell?'

Arbeitspapier

Ciccone and Jarocínski (2010) show that inference in Bayesian model averaging (BMA) can be highly sensitive to small changes in the dependent variable. In particular they demonstrate that the importance of growth determinants in explaining growth varies tremendously over different revisions of Penn World Table (PWT) income data. They conclude that 'agnostic' priors appear too sensible for this strand of growth empirics. In response, we show that the instability found owes much to a specific BMA set-up: the variation in results can be considerably reduced by applying an evenly 'agnostic', but exible prior.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Working Papers in Economics and Finance ; No. 2010-12

Classification and Topics

• Classification: Wirtschaft ; Bayesian Analysis: General ; Statistical Simulation Methods: General ; Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts ; Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
• Subject: Bayesian model averaging ; Growth determinants ; Zellner's g prior ; Model uncertainty

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Feldkircher, Martin ; Zeugner, Stefan
• Event: Veröffentlichung
• (who): University of Salzburg, Department of Social Sciences and Economics
• (where): Salzburg
• (when): 2010

Further information

• Handle: http://hdl.handle.net/10419/71859
• Last update: 10.03.0048, 11:43 AM CET