binary, as often happens in microeconometric analysis. The paper is grounded
on a rigorous mathematical definition of поп-causality, which is shown to be
easily fitted into a dynamic version of the bivariate probit model. Particular
attention is placed in including covariates into the analysis, and in specializing
the definitions for longitudinal data sets. Panel type data for heterogeneous
individuals are in fact typical in microeconometric applications.
The paper implicitly suggests so many extensions to fill up a research agenda.
To make some examples: a more parsimonious representation of the dynamics;
allowing for unobserved heterogeneity; generalizing to a multivariate setting;
mixing binary and continuous variables; analyzing the impact of time aggrega-
tion.
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