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Dynamic Models in Space and Time
Author(s) -
Elhorst J. Paul
Publication year - 2001
Publication title -
geographical analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.773
H-Index - 65
eISSN - 1538-4632
pISSN - 0016-7363
DOI - 10.1111/j.1538-4632.2001.tb00440.x
Subject(s) - autoregressive model , econometrics , unemployment , time series , space (punctuation) , lag , space time , series (stratigraphy) , computer science , distributed lag , unemployment rate , order (exchange) , state space representation , economics , macroeconomics , algorithm , engineering , computer network , paleontology , finance , machine learning , chemical engineering , biology , operating system
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.