1961
DOI: 10.2307/1909639
|View full text |Cite
|
Sign up to set email alerts
|

The Interpretation of Cross Section Estimates in a Dynamic Model

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
6
0

Year Published

1969
1969
2011
2011

Publication Types

Select...
8
1

Relationship

0
9

Authors

Journals

citations
Cited by 18 publications
(6 citation statements)
references
References 0 publications
0
6
0
Order By: Relevance
“…Implicit in the use of cross-sectional regression analysis is the assumption that the observations do in fact represent points of equilibrium. This, of course, is seldom if ever strictly true and, especially where an adjustment period of some length is likely, it is possible that the results may be distorted to some extent (Kuh 1959;Grunfeld 1961). It could be, for example, that the negative association we have observed between property taxes and home values is primarily a short-run phenomenon, which would disappear over a longer period of time.…”
Section: Taxes and The Tiebout Hypothesismentioning
confidence: 84%
“…Implicit in the use of cross-sectional regression analysis is the assumption that the observations do in fact represent points of equilibrium. This, of course, is seldom if ever strictly true and, especially where an adjustment period of some length is likely, it is possible that the results may be distorted to some extent (Kuh 1959;Grunfeld 1961). It could be, for example, that the negative association we have observed between property taxes and home values is primarily a short-run phenomenon, which would disappear over a longer period of time.…”
Section: Taxes and The Tiebout Hypothesismentioning
confidence: 84%
“…This suggests that time-series data illustrate adjustments along short-run equilibria, while cross-section data depict adjustments along long-run equilibria, a conjecture that is well established in the literature (Kuh 1959;Grunfeld 1961;Baltagi and Griffin 1984). Thus, models estimated with cross-section data should be interpreted appropriately.…”
Section: Caution In Using Farm-level Datamentioning
confidence: 79%
“…Y it and X 2it k are independent. This is in fact just the conditions derived in Grunfeld (1961) for a cross-section regression of the type described above to give an unbiased estimator of long-run parameters within the framework of a partial adjustment model with stationary variables. Repeating the arguments in the proof of Proposition 1 in Appendix A.1 the estimator obtained by regressing Y it on X 2it k is also consistent (as N !…”
Section: Cross-section Regressionmentioning
confidence: 85%