IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this paper

Aggregating Phillips Curves

Listed author(s):
  • FAME,Eric Jondeau, University of Lausanne-HEC
  • Jean Imbs

    (Department of Economics and Econometrics University of Lausanne-HEC, CEPR and FAME)

  • Eric Jondeau

    (University of Lausanne-HEC and FAME)

  • Florian Pelgrin

    ()

    (University of Lausanne-HEC and IEMS)

Since it burst onto the scene of mainstream monetary economics, the New Neo-Classical Phillips Curve has been the focus of two important empirical debates. First, to what extent properly measured marginal costs affect inflation dynamics. Second, to what extent purely forward looking inflation can be reconciled with the data. In this paper, we show heterogeneity in the pricing behavior of firms, matters for both issues. If pricing is heterogeneous, estimations based on GMM techniques are flawed, to an extent that increases with the correlation between aggregate and disaggregate price dynamics. We use sectoral quarterly French data on prices and marginal costs to illustrate this possibility and quantify the magnitude and direction of the implied bias. Two results arise when the estimation accounts for the possibility of heterogeneity. First, marginal costs become substantially more important in affecting inflation dynamics (i.e. heterogeneity induces a negative bias in the response of aggregate inflation to marginal costs). Second, lagged inflation also becomes more important than previously reported using GMM techniques. We provide analytical expressions for the biases which arise when heterogeneity is not taken into account. It helps pinpoint the sources of the differences in results. These are relevant to our data, where they help explain the biases just described, but they also provide a toolkit with which to gauge the magnitude and direction of an aggregation bias in any disaggregated data.

To our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.

Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2006 with number 314.

as
in new window

Length:
Date of creation: 04 Jul 2006
Handle: RePEc:sce:scecfa:314
Contact details of provider: Web page: http://comp-econ.org/
Email:


More information through EDIRC

No references listed on IDEAS
You can help add them by filling out this form.

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:sce:scecfa:314. 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: (Christopher F. Baum)

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.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.