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We developed a model of the relationship between product innovation and open innovation practice using a bivariate probit model.
However, using a bivariate probit model with partial observability we demonstrate that boardroom characteristics are important, while the type of owner is less relevant.
In fact, we joint estimate entrepreneurship and occupational choices, treating academic achievement as given, using a bivariate probit specification of equation (3) and (4).
Using a bivariate probit model that accounts for both endogeneity and non-linearity issues, we find both positive and negative effects of remittances on the likelihood of schooling.
The system of equations from the theoretical model building in the above equations will then be anticipated using a bivariate probit procedure.
In this study the Contingent Valuation Method with the double bounded dichotomous choice format was used to elicit WTP for agricultural heritage (AH) conservation, which was modeled using a Bivariate Probit specification.
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Controlling for potential endogeneity, we use a bivariate probit model to take into account the simultaneity of financial constraints and the decision to abandon an innovation project.
We therefore test the hypothesis that these two decisions are correlated and use a bivariate probit model that considers training provision and the use of temporary employment simultaneously.
The second stage of the microsimulation model uses a bivariate probit model to estimate the decision of current workers to move from one sector to another.
To address this potential endogeneity, we use a bivariate probit model to account for the presence of r as a binary endogenous variable (Roodman 2011) that equals one if the household receives remittances and zero otherwise.
We then used a bivariate probit (BVP) model to account for Friday admission as an instrument.
More suggestions(14)
using a bivariate Tobit
using a bivariate meta-analysis
using a binomial probit
using a trivariate probit
using a pooled probit
using a bivariate approach
using a cumulative probit
using a bivariate regression
using a bivariate correlation
using a binary probit
using a dynamic probit
using a bivariate animal
using a bivariate model
using a bivariate K-function
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