Abstract
This paper adopts a spatial probit approach to explain interaction effects among cross-sectional units when the dependent variable takes the form of a binary response variable and transitions from state 0 to 1 occur at different moments in time. The model has two spatially lagged variables: one for units that are still in state 0 and one for units that had already transferred to state 1. The parameters are estimated on observations for those units that are still in state 0 at the start of the different time periods, whereas observations on units after they transferred to state 1 are discarded, just as in the literature on duration modeling. Furthermore, neighboring units that had not yet transferred may have a different impact from units that had already transferred. We illustrate our approach with an empirical study of the adoption of inflation targeting for a sample of 58 countries over the period 1985–2008.
Original language | English |
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Pages (from-to) | 422-439 |
Number of pages | 18 |
Journal | Journal of Applied Econometrics |
Volume | 32 |
Issue number | 2 |
DOIs | |
Publication status | Published - 1 Mar 2017 |