Dagpunar, J. (2007), Simulations and Monte Carlo: With Applications in Finance and MCMC , John Wiley & Sons Ltd., UK. Devroye, L. (2014), “Random Variate Generation for the Generalized Inverse Gaussian Dis- tribution,” Statistics and Computing , 24, 239–246. Drew, R. B. and Herbert, C. E. (2013), “Postrecession Drivers of Preferences for Homeown- ership,” Housing Policy Debate , 23, 666–687. Geraci, M. and Bottai, M. (2007), “Quantile Regression for Longitudinal Data Using the Asymmetric Laplace Distribution,” Biostatistics , 8, 140–154. Giuliano, P. and Spilimbergo, A. (2014), “Growing Up in a Recession,” The Review of Economic Studies , 81, 787–817. Greenberg, E. (2012), Introduction to Bayesian Econometrics , Cambridge University Press, New York. Jeliazkov, I. and Rahman, M. A. (2012), “Binary and Ordinal Data Analysis in Economics: Modeling and Estimation,” in Mathematical Modeling with Multidisciplinary Applications , ed. X. S. Yang, pp. 123–150, John Wiley & Sons Inc., New Jersey. Jeliazkov, I., Graves, J., and Kutzbach, M. (2008), “Fitting and Comparison of Models for Multivariate Ordinal Outcomes,” Advances in Econometrics: Bayesian Econometrics , 23, 115–156. Ji, Y., Lin, N., and Zhang, B. (2012), “Model Selection in Binary and Tobit Quantile Regres- sion using the Gibbs Sampler,” Computational Statistics and Data Analysis , 56, 827–839. Johnson, V. E. and Albert, J. H. (2000), Ordinal Data Modeling , Springer, New York. Kobayashi, G. (2017), “Bayesian Endogenous Tobit Quantile Regression,” Bayesian Analysis , 12, 161–191. 42