A Latent Class Panel Tobit Framework:Application to Modelling Charitable Donations
MetadataShow full item record
We extend the latent class literature by re-examining censored variable analysis within a panel data context. Specifically, we extend the standard latent class tobit panel approach to simultaneously include random effects, to allow for heteroskedasticity and to incorporate the inverse hyperbolic sine (IHS) transformation of the dependent variable. The IHS transformation ensures robustness to nonnormality in the original (untransformed) dependent variable. We then apply this framework to modelling charitable donations, an interesting application given the potential for divergent groups of individuals in the population with regard to their donating behaviour, which we uncover by the latent class approach. Our findings, which are based on U.S. panel data drawn from five waves of the Panel Study of Income Dynamics, do suggest two distinct classes. There is a clear disparity between the probabilities of zero donations across these classes, with one class dominated by the observed zero givers and associated with relatively low levels of predicted giving. We find clear evidence of both heteroskedasticity and random effects. All IHS parameters were significantly different from zero and different across classes. In combination, these findings endorse the importance of our three modelling extensions.
Showing items related by title, author, creator and subject.
An inverse hyperbolic sine heteroskedastic latent class panel tobit model: An application to modelling charitable donationsBrown, S.; Greene, W.; Harris, Mark N.; Taylor, K. (2015)We apply a latent class tobit framework to the analysis of panel data on charitable donations at the household level where the latent class aspect of the model splits households into two groups, which we subsequently ...
Modelling charitable donations: A latent class panel inverse hyperbolic sine heteroskedastic tobit approachBrown, S.; Greene, W.; Harris, Mark; Taylor, K. (2012)We make a methodological contribution to the latent class literature by re-examining censored variable analysis within a panel data context. Specifically, we extend the standard latent class tobit panel approach to include ...
Accounting for attribute non-attendance and common-metric aggregation in a probabilistic decision process mixed multinomial logit model: A warning on potential confoundingHensher, D.; Collins, A.; Greene, William (2013)Latent class models offer an alternative perspective to the popular mixed logit form, replacing the continuous distribution with a discrete distribution in which preference heterogeneity is captured by membership of ...