EconPapers    
Economics at your fingertips  
 

Noncausal Autoregressions for Economic Time Series

Markku Lanne and Pentti Saikkonen

Journal of Time Series Econometrics, 2011, vol. 3, issue 3, 32

Abstract: This paper is concerned with univariate noncausal autoregressive models and their potential usefulness in economic applications. In these models, future errors are predictable, indicating that they can be used to empirically approach rational expectations models with nonfundamental solutions. In the previous theoretical literature, nonfundamental solutions have typically been represented by noninvertible moving average models. However, noncausal autoregressive and noninvertible moving average models closely approximate each other, and therefore, the former provide a viable and practically convenient alternative. We show how the parameters of a noncausal autoregressive model can be estimated by the method of maximum likelihood and derive related test procedures. Because noncausal autoregressive models cannot be distinguished from conventional causal autoregressive models by second order properties or Gaussian likelihood, a model selection procedure is proposed. As an empirical application, we consider modeling the U.S. inflation which, according to our results, exhibits purely forward-looking dynamics.

Keywords: noncausal autoregression; non-Gaussian time series; inflation persistence (search for similar items in EconPapers)
Date: 2011
References: Add references at CitEc
Citations: View citations in EconPapers (73)

Downloads: (external link)
https://doi.org/10.2202/1941-1928.1080 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
Working Paper: Noncausal autoregressions for economic time series (2010) Downloads
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:bpj:jtsmet:v:3:y:2011:i:3:n:2

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/jtse/html

DOI: 10.2202/1941-1928.1080

Access Statistics for this article

Journal of Time Series Econometrics is currently edited by Javier Hidalgo

More articles in Journal of Time Series Econometrics from De Gruyter
Bibliographic data for series maintained by Peter Golla (peter.golla@degruyter.com).

 
Page updated 2025-01-08
Handle: RePEc:bpj:jtsmet:v:3:y:2011:i:3:n:2