A Joint Model for Longitudinal and Time-to-event Data in Social and Life Course Research: Employment Status and Time to Retirement

Longitudinal studies including a time-to-event outcome in social research often use a form of event history analysis to analyse the influence of time-varying endogenous covariates on the time-to-event outcome. Many standard event history models however assume the covariates of interest to be exogenous and inclusion of an endogenous covariate may lead to bias. Although such bias can be dealt with by using joint models for longitudinal and time-to-event outcomes, these types of models are underused in social research. In order to fill this gap in the social science modelling toolkit, we introduce a novel Bayesian joint model in which a multinomial longitudinal outcome is modelled simultaneously with a time-to-event outcome. The methodological novelty of this model is that it concerns a correlated random effects association structure that includes a multinomial longitudinal outcome. We show the use of the joint model on Danish labour market data and compare the joint model to a standard event history model. The joint model has three advantages over a standard survival model. It decreases bias, allows us to explore the relation between exogenous covariates and the longitudinal outcome and can be flexibly extended with multiple time-to-event and longitudinal outcomes.

Testing conditional moment restriction models using empirical likelihood

An empirical likelihood test is proposed for parameters of models defined by conditional moment restrictions, such as models with non-linear endogenous covariates, with or without heteroscedastic errors or non-separable transformation models. The number of empirical likelihood constraints is given by the size of the parameter, unlike alternative semi-parametric approaches. We show that the empirical likelihood ratio test is asymptotically pivotal, without explicit studentisation. A simulation study shows that the observed size is close to the nominal level, unlike alternative empirical likelihood approaches. It also offers a major advantages over two-stage least-squares, because the relationship between the endogenous and instrumental variables does not need to be known. An empirical likelihood model specification test is also proposed.

Decentralization estimators for instrumental variable quantile regression models

The instrumental variable quantile regression (IVQR) model (Chernozhukov and Hansen (2005)) is a popular tool for estimating causal quantile effects with endogenous covariates. However, estimation is complicated by the nonsmoothness and nonconvexity of the IVQR GMM objective function. This paper shows that the IVQR estimation problem can be decomposed into a set of conventional quantile regression subproblems which are convex and can be solved efficiently. This reformulation leads to new identification results and to fast, easy to implement, and tuning‐free estimators that do not require the availability of high‐level “black box” optimization routines.

Modeling the Evolutionary Mechanism of China’s Domestic Air Transport Network

With the rapid expansion of China’s domestic air transport network (CATN), it is fundamental to model which factors and mechanisms impact this development. This paper investigates how the combined endogenous and exogenous factors influencing the evolution of CATN based on longitudinal data by utilizing a more all-encompassing methodology of stochastic actor based-modeling (SABM). Endogenous variables include a density effect, a betweenness effect, a transitivity closure effect, and a ‘number of distances-two’ effect. Exogenous variables incorporate airport hierarchy, a distance effect, presence or absence of low-cost carriers (LCCs) and high-speed rail (HSR). The systematic classification of Chinese airports into more than the typical two or three tiers allows the impacts of the four endogenous covariates to be revealed. Overall, the CATN has tended to evolve into a more compacted and non-concentrated network structure through the creation of non-stop routes and closed triads. The integrated inclusion of low-cost carrier and high-speed rail effects highlights the importance of market presence to the initiation of new routes at initial stages, cultivating potential demand and increasing accessibility. In addition, the construction of HSR to one primary airport within a multi-airport system can raise “shadow effects” for other airports. Our findings provide policy suggestions for airport operators in terms of developing accurate positions in the hierarchy and strengthening transfer ability.

Exploring Gender Differences in Marriage and Parental Income Premiums among Financial Advisors

This study examined marriage and parental income premiums among financial advisors. Financial advisors provide an interesting context for exploring such premiums, as financial advising is a historically male-dominated profession that has been found to exhibit large unadjusted gender pay gaps. Using a large sample of financial advisors recruited via a professional continuing education website (n=555), this study investigates whether gender differences exist among financial advisors with respect to the marriage premium, the parenthood premium, the parental leave effect, and the stay-at-home spouse premium. This study examined premiums both with and without potentially endogenous human capital covariates. Without including potentially endogenous covariates, a marriage premium was observed among men but not women, a parenthood premium was observed among women but not men, a parental leave premium was observed among neither men nor women, and a stay-at-home spouse premium was observed among men but not women. When potentially endogenous covariates were included, a marriage penalty was observed among women but not men, a parenthood premium was observed among women while a parenthood penalty observed among men, a parental leave premium was observed among men but not women, and a stay-at-home spouse premium was observed among men while a stay-at-home spouse penalty was observed among women. Exploratory Blinder-Oaxaca decomposition analyses revealed sizeable unadjusted income gaps by gender (16.7%), marriage (32.8%), parenthood (8.1%), parental leave (16.7%), and spousal employment (39.8%).