Publication

Dynamic models in space and time

Elhorst, J. P., Apr-2001, In : Geographical Analysis. 33, 2, p. 119-140 22 p.

Research output: Contribution to journalArticleAcademicpeer-review

APA

Elhorst, J. P. (2001). Dynamic models in space and time. Geographical Analysis, 33(2), 119-140.

Author

Elhorst, J.P. / Dynamic models in space and time. In: Geographical Analysis. 2001 ; Vol. 33, No. 2. pp. 119-140.

Harvard

Elhorst, JP 2001, 'Dynamic models in space and time', Geographical Analysis, vol. 33, no. 2, pp. 119-140.

Standard

Dynamic models in space and time. / Elhorst, J.P.

In: Geographical Analysis, Vol. 33, No. 2, 04.2001, p. 119-140.

Research output: Contribution to journalArticleAcademicpeer-review

Vancouver

Elhorst JP. Dynamic models in space and time. Geographical Analysis. 2001 Apr;33(2):119-140.


BibTeX

@article{3c6cb77bb42c4c64b0346f618d11a38f,
title = "Dynamic models in space and time",
abstract = "This paper presents a first-order autoregressive distributed lag model in both space and time. It is shown that this model encompasses a wide series of simpler models frequently used in the analysis of space-time data as well as models that better fit the data and have never been used before. A framework is developed to determine which model is the most likely candidate to study space-time data. As an application, the relationship between the labor force participation rate and the unemployment rate is estimated using regional data of Germany, France, and the United Kingdom derived from Eurostat, 1983-1993.",
keywords = "LABOR-FORCE PARTICIPATION, AUTOREGRESSIVE MODELS, REGRESSION-MODELS, SPECIFICATION, UNEMPLOYMENT, DEPENDENCE, ESTIMATORS, RATES",
author = "J.P. Elhorst",
year = "2001",
month = apr,
language = "English",
volume = "33",
pages = "119--140",
journal = "Geographical Analysis",
issn = "0016-7363",
number = "2",

}

RIS

TY - JOUR

T1 - Dynamic models in space and time

AU - Elhorst, J.P.

PY - 2001/4

Y1 - 2001/4

N2 - This paper presents a first-order autoregressive distributed lag model in both space and time. It is shown that this model encompasses a wide series of simpler models frequently used in the analysis of space-time data as well as models that better fit the data and have never been used before. A framework is developed to determine which model is the most likely candidate to study space-time data. As an application, the relationship between the labor force participation rate and the unemployment rate is estimated using regional data of Germany, France, and the United Kingdom derived from Eurostat, 1983-1993.

AB - This paper presents a first-order autoregressive distributed lag model in both space and time. It is shown that this model encompasses a wide series of simpler models frequently used in the analysis of space-time data as well as models that better fit the data and have never been used before. A framework is developed to determine which model is the most likely candidate to study space-time data. As an application, the relationship between the labor force participation rate and the unemployment rate is estimated using regional data of Germany, France, and the United Kingdom derived from Eurostat, 1983-1993.

KW - LABOR-FORCE PARTICIPATION

KW - AUTOREGRESSIVE MODELS

KW - REGRESSION-MODELS

KW - SPECIFICATION

KW - UNEMPLOYMENT

KW - DEPENDENCE

KW - ESTIMATORS

KW - RATES

M3 - Article

VL - 33

SP - 119

EP - 140

JO - Geographical Analysis

JF - Geographical Analysis

SN - 0016-7363

IS - 2

ER -

ID: 677053