Attracting New Maine Residents: The Effects of Educational Attainment and Age on Interstate Mobility

Paul Leparulo
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Abstract

MAINE POLICY REVIEW • Vol. 28, No. 2 • 2019 Appendix 1 Attracting New Maine Residents: The Effects of Educational Attainment and Age on Interstate Mobility by Paul Leparulo APPENDIX I use a regression model to estimate the economic and statistical significance between educational attainment and interstate mobility. The particular type of regression (probit model) is designed for situations where the outcome variable is binary rather than continuous. In this case, the outcome variable represents whether an individual made an interstate move and the regressions yield the predicted probability of a move. More specifically, the regression model examines the potential relationships between moving and such variables as bachelor’s degree holder, age and homeownership. Age and homeownership are included as control variables as they are correlated with both the likelihood of moving and educational attainment. To more accurately model these relationships, I allow for nonlinearities in the relationship between moving and age and include interaction terms. The regression output of primary importance is the marginal effect of having at least a four-year degree on the propensity to make an interstate move. The marginal effect quantifies the causal relationship between these variables. I focus on the average marginal effect (AME), which is the average of all marginal effects across all observations, (i.e., the average effect of having at least a four-year degree on the probability of an interstate move for all 23to 55-year-olds in the restricted sample), and the marginal effect for persons of a representative age (e.g., the marginal effect of having at least a four-year degree for the average 25-year-old). From this regression model I am also able to produce the predicted probabilities of an interstate move for an average individual of a representative age.
吸引缅因州新居民:教育程度和年龄对州际流动的影响
《吸引缅因州新居民:受教育程度和年龄对州际流动的影响》作者:Paul Leparulo这种特殊类型的回归(概率模型)是为结果变量是二元而不是连续的情况而设计的。在这种情况下,结果变量表示个人是否进行州际迁移,回归产生预测的迁移概率。更具体地说,回归模型检验了搬家与学士学位持有者、年龄和房屋所有权等变量之间的潜在关系。年龄和房屋所有权作为控制变量包括在内,因为它们与搬家的可能性和受教育程度相关。为了更准确地模拟这些关系,我考虑了运动和年龄之间关系的非线性,并包括相互作用项。最重要的回归输出是至少拥有四年制学位对跨州迁移倾向的边际效应。边际效应量化了这些变量之间的因果关系。我关注的是平均边际效应(AME),这是所有观察结果中所有边际效应的平均值,(即,在受限样本中,所有23至55岁的人至少拥有4年学位对州际迁移概率的平均影响),以及具有代表性年龄的人的边际效应(例如,平均25岁的人至少拥有4年学位的边际效应)。从这个回归模型中,我还能够为具有代表性年龄的普通个人产生跨州移动的预测概率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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