Using Instrumental Varibles to Estimate the Share of Backward- Looking Firms
This paper examines the small-sample distribution of the instrumental variables (IV) estimation procedure employed by Gali and Gertler (1999) to assess the empirical fit of the New Keynesian Phillips Curve (NKPC) and the hybrid Phillips Curve (HPC). Their estimation method is now widely used to assess the importance of firms that act in a backward-looking manner. Unfortunately, the IV method is highly sensitive to the way the hybrid model is normalized. Using Monte Carlo simulations, I find that one normalization used by Gali and Gertler (and others) finds evidence of backward-looking firms even when there is none by construction. In addition, the IV estimates are also sensitive to the choice of normalization in a broader range of specifications. Using Monte Carlo experiments, I identify which normalizations work better than others. Finally, I find that the bootstrapped standard errors are, not surprisingly, bigger than the asymptotic ones reported by Gali and Gertler. When using my preferred normalization, I find that the NKPC is rejected at the 5 percent but not at the 1 percent level
|Date of creation:||03 Jun 2003|
|Date of revision:|
|Contact details of provider:|| Postal: Georgetown University Department of Economics Washington, DC 20057-1036|
Web page: http://econ.georgetown.edu/
|Order Information:|| Postal: Roger Lagunoff Professor of Economics Georgetown University Department of Economics Washington, DC 20057-1036|
Web: http://econ.georgetown.edu/ Email:
When requesting a correction, please mention this item's handle: RePEc:geo:guwopa:gueconwpa~03-03-24. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Marcia Suss)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.