Dynamic unobserved effects model: Difference between revisions

Revision as of 16:41, 17 April 2019

Revision as of 03:31, 26 July 2020

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{{Technical|date=January 2018}}

A '''dynamic unobserved effects model''' is a [[statistical model]] used in [[econometrics]] for [[panel analysis]]. It is characterized by the influence of previous values of the [[dependent variable]] on its present value, and by the presence of unobservable [[explanatory variable]]s.

The term “dynamic” here means the dependence of the dependent variable on its past history; this is usually used to model the “state dependence” in economics. For instance, for a person who cannot find a job this year, it will be harder to find a job next year because her present lack of a job will be a negative signal for the potential employers. “Unobserved effects” means that one or some of the explanatory variables are unobservable: for example, consumption choice of one flavor of ice cream over another is a function of personal preference, but preference is unobservable.

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A typical dynamic unobserved effects model is represented<ref>Wooldridge, J. (2002): Econometric Analysis of Cross Section and Panel Data, MIT Press, Cambridge, Mass, pp 300.</ref> as:

:<math>P(y_{y_{it}} = 1│y_{1 \mid y_{i,t-1}}, ...\dots , y_{y_{i,0} }, z_i z_i, c_i c_i) = G (z_{z_{it}} δ\delta + ρ\rho y_{y_{i,t-1}} + c<sub>ic_i)</submath>)

where c_i is an unobservable explanatory variable, z_it are explanatory variables which are exogenous conditional on the c_i, and G(∙) is a [[cumulative distribution function]].

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Based on the estimates for (''δ, ρ'') and the corresponding variance, values of the coefficients can be tested<ref>Whitney K. Newey, Daniel McFadden, Chapter 36 Large sample estimation and hypothesis testing, In: Robert F. Engle and Daniel L. McFadden, Editor(s), Handbook of Econometrics, Elsevier, 1994, Volume 4, Pages 2111–2245, {{ISSN|1573-4412}}, {{ISBN|9780444887665}},</ref> and the average partial effect can be calculated.<ref>Chamberlain, G. (1980), “Analysis of Covariance with Qualitative Data,” Journal of Econometrics 18, 5–46</ref>

== See also ==

* [[Arellano–Bond estimator]]

==References==