Applied Econometrics Methods and Monetary Policy: Empirical Evidence from the Mexican Case

Luis Miguel Galindo () and Horacio Catalán
Additional contact information
Luis Miguel Galindo: UNAM

Chapter 16 in New Tools of Economic Dynamics, 2005, pp 273-293 from Springer

Abstract: Summary The main objective of this paper is to illustrate, using Mexican data, how the results yield by modern econometric methods are dependent upon each specific technique as well as upon the statistical properties of the series analyzed. The problems are even stronger and more evident in the case of economic series with structural changes and high variability as is the case of Mexico. Applied econometrics should be explicitly based upon a probability viewpoint, and different methods should be taken to produce only approximations to the actual data generation process. Thus, alternative techniques can only show distinctive features of the actual data that still need to be validated with the rest of empirical evidence. This indicates that applied econometricians have to look for maximum information by correctly applying different techniques without forgetting the relevance of economic reasoning. Using Mexican data, alternative econometric estimations are evaluated indicating that the formulation of a monetary policy only on the basis of some specific technique, without considering its potential pitfalls, should not be recommended.

Date: 2005
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:lnechp:978-3-540-28444-4_16

Ordering information: This item can be ordered from
http://www.springer.com/9783540284444

DOI: 10.1007/3-540-28444-3_16

Access Statistics for this chapter

More chapters in Lecture Notes in Economics and Mathematical Systems from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().