A state-of-the-art matrix analysis of economic indicators modeling

Javier Calvo-Amodio, María Del Carmen Temblador Pérez, Mario G. Beruvides

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Literature reviews and compendiums on econometric modeling are vastly available and very detailed. Yet, it is hard to find one that provides a condensed overview of the field and that focuses on models of economic indicators. Most of the available literature reviews cover many applications of econometric modeling at the same time, and focus on underlying philosophies, mathematical/statistical strategies, and/or historical accounts on how econometric ideas evolved. Yet none are all inclusive, and appear biased in one way or another. In this paper, we present a State-of-the-Art Matrix Analysis (SAM) that provides a literature review focused on GDP modeling techniques. The resulting SAM provides a characterized literature review of the existing publications into econometric and economic methodologies employed, and proposes a cataloguing according to the main objective of the publication. The findings presented on this paper, serve as a starting point for engineering managers and researchers that are new to modeling economic indicators. Copyright, American Society for Engineering Management, 2011.

Original languageEnglish
Title of host publicationAnnual International Conference of the American Society for Engineering Management 2011, ASEM 2011
Pages581-588
Number of pages8
StatePublished - 2011
EventAnnual International Conference of the American Society for Engineering Management 2011, ASEM 2011 - Lubbock, TX, United States
Duration: Oct 19 2011Oct 22 2011

Publication series

NameAnnual International Conference of the American Society for Engineering Management 2011, ASEM 2011

Conference

ConferenceAnnual International Conference of the American Society for Engineering Management 2011, ASEM 2011
CountryUnited States
CityLubbock, TX
Period10/19/1110/22/11

Keywords

  • Business cycle
  • Econometrics
  • Economic indicators
  • Economic modeling
  • Engineering management
  • GDP estimation
  • Growth theory

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