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Category Archives: C33

The Effect of Marriage on the Wages of Americans: Gender and Generational Differences

By William Song and Theresa Tong

A substantial body of literature on the wage effects of marriage finds that married American men earn anywhere from 10% to 40% higher wages than unmarried men on average, while married American women earn up to 7% less than unmarried women, even after controlling for traits such as background, education, and number of children. Because this literature focuses heavily on men born in a single time period, we study both men and women in two different generational cohorts of Americans (Baby Boomers and Millennials) from the National Longitudinal Surveys of Youth to examine how the wage effects of marriage differ between genders and across time. Using a fixed effects approach, we find that Millennial women—but not Baby Boomer women—experience an increase in wages after marriage, and we replicate the finding from the literature that men experience an increase in wages after marriage as well. However, after controlling for wage trajectory-based selection into marriage by using a modified fixed effects approach that allows wage trajectories to vary by individual, we find that the wage effects of marriage are no longer statistically significant for any group in our data, suggesting that the wage differences between married and unmarried individuals found in previous studies are primarily a result of selection.

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Advisors: Professor Marjorie McElroy, Professor Michelle Connolly | JEL Codes: C33; D13; J12; J13; J22; J30

ICT Behavior at the Periphery: Exploring the Social Effect of the Digital Divide through Interest in Video Streaming

By Erik W. Hanson and Justin C. LoTurco

We investigate the factors that influence changes in consumer behavior with regard to video streaming. We focus our analysis on the effect of bandwidth impairment to explore a potential consequence of the digital divide. To measure the change in relative popularity of video streaming services, we use Google Trends data as a proxy. We then investigate whether broadband speed improvements in rural vs. urban regions affect the proxy differently. We find that increasing the broadband speeds in rural regions appears to stimulate greater interest in video streaming than equivalent speed increases in urban regions.

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Advisors: Professor Michelle Connolly, Professor Grace Kim | JEL Codes: C33; J11; L96

Geo-Spatial Modeling of Online Ad Distributions

By Mitchel Gorecki

The purpose of this document is to demonstrate how spatial models can be integrated into purchasing decisions for real-time bidding on advertising exchanges to improve ad selection and performance. Historical data makes it very apparent that some neighborhoods are much more interested in some ads than others. Similarly, some neighborhoods are also much more interested in some online domains than others, meaning viewing habits across domains are not equal. Basic data analysis shows that neighborhoods behave in predictable ways that can be exploited using observed performance information. This paper demonstrates how it is possible to use spatially correlated information to better optimize advertising resources.

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Advisor: Charles Becker | JEL Codes: C3, C33, C53, M37 | Tagged: Ad Distribution, Advertising, Online, Real Time Bidding, Spatial

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