Three Essays on Earnings Dynamics

dc.contributor.authorShang, Yingen
dc.contributor.departmentEconomicsen
dc.contributor.supervisorImai, Susumuen
dc.contributor.supervisorLapham, Beverlyen
dc.date2015-04-26 11:33:27.012
dc.date.accessioned2015-04-27T13:21:01Z
dc.date.available2015-04-27T13:21:01Z
dc.date.issued2015-04-27
dc.degree.grantorQueen's University at Kingstonen
dc.descriptionThesis (Ph.D, Economics) -- Queen's University, 2015-04-26 11:33:27.012en
dc.description.abstractThis thesis consists of three essays that use modern econometric methods to empirically study earnings dynamics in the United States using samples drawn from the Panel Study of Income Dynamics (PSID). In Chapter 2, I study a non-linear parametric model that allows an agent's future earning to depend on the earning quantile he occupies in the current period. Such dynamics reflect a different set of opportunities opened up to an agent once he changes position in the earning distribution. Chapter 3 extends the model presented in Chapter 2 to take into account the accumulation of agents' past experiences by allowing an agent's earning process to depend on both his current quantile position and the average of his previous quantiles. The current quantile position represents an agent's current opportunity or luck whereas the average of his previous quantiles assumes the role of his past experiences. I estimate the models using a method of indirect inference called simulated minimum distance. I find that the underlying process differs across the earning distribution. In particular, individuals in the bottom quantile have a unit root process whereas individuals in upper quantiles have a stationary process with the top quantile workers having the lowest autoregressive coefficients. Chapter 3 shows that a model specification with a higher weight assigned to luck, the current quantile position, has better predictions for the earning mobility presented from the data. This result implies that luck certainly plays a role in the earning process. In Chapter 4, I study the earning mobility of US households using nonparametric quantile regressions. I estimate future earning quantiles for individuals from every initial earning level. I find that earning mobility tends to improve in more recent years or over a longer time span. Moreover, the substantial non-linearity found in upper earning distribution suggests that relatively higher earners face more earning uncertainty than others. In addition, the slopes of quantiles as a function of initial earnings are flatter in the long run. Therefore, more than half of high earners experience an earning decline whereas the majority of low earners experience an earning increase in the long run.en
dc.description.degreePhDen
dc.identifier.urihttp://hdl.handle.net/1974/13002
dc.language.isoengen
dc.relation.ispartofseriesCanadian thesesen
dc.subjectEarning Processen
dc.subjectEarning Mobilityen
dc.subjectLabor Economicsen
dc.subjectEarning Dynamicsen
dc.titleThree Essays on Earnings Dynamicsen
dc.typethesisen

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