Inference on power law spatial trends (Running Title: Power Law Trends)

Peter M. Robinson

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: Power law or generalized polynomial regressions with unknown real-valued exponents and coefficients, and weakly dependent errors, are considered for observations over time, space or space-time. Consistency and asymptotic normality of nonlinear least squares estimates of the parameters are established. The joint limit distribution is singular, but can be used as a basis for inference on either exponents or coefficients. We discuss issues of implementation, efficiency, potential for improved estimation, and possibilities of extension to more general or alternative trending models, and to allow for irregularlyspaced data or heteroscedastic errors; though it focusses on a particular model to .x ideas, the paper can be viewed as offering machinery useful in developing inference for a variety of models in which power law trends are a component. Indeed, the paper also makes a contribution that is potentially relevant to many other statistical models: our problem is one of many in which consistency of a vector of parameter estimates (which converge at different rates) cannot be established by the usual techniques for coping with implicitlydefined extremum estimates, but requires a more delicate treatment; we present a generic consistency result.J

Keywords: asymptotic normality; consistency; correlation; generalized polynomial; lattice; power law.0Út (search for similar items in EconPapers)
JEL-codes: J1 (search for similar items in EconPapers)
Pages: 46 pages
Date: 2011-05
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://eprints.lse.ac.uk/58100/ Open access version. (application/pdf)

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:ehl:lserod:58100

Access Statistics for this paper

More papers in LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library LSE Library Portugal Street London, WC2A 2HD, U.K.. Contact information at EDIRC.
Bibliographic data for series maintained by LSERO Manager ().