INVISIBLE LABOR FOR DATA: INSTITUTIONS, INFRASTRUCTURE, AND VIRTUAL SPACE

Americans are accustomed to a wide range of data collection in their lives: census, polls, surveys, user registrations, and disclosure forms. When logging onto the Internet, users’ actions are being tracked everywhere: clicking, typing, tapping, swiping, searching, and placing orders. All of this data is stored to create data-driven profiles of each user. Social network sites, furthermore, set the voluntarily sharing of personal data as the default mode of engagement. But people’s time and energy devoted to creating this massive amount of data, on paper and online, are taken for granted. Few people would consider their time and energy spent on data production as labor. Even if some people do acknowledge their labor for data, they believe it is accessory to the activities at hand. In the face of pervasive data collection and the rising time spent on screens, why do people keep ignoring their labor for data? How has labor for data been become invisible, as something that is disregarded by many users? What does invisible labor for data imply for everyday cultural practices in the United States? Invisible Labor for Data addresses these questions. I argue that three intertwined forces contribute to framing data production as being void of labor: data production institutions throughout history, the Internet’s technological infrastructure (especially with the implementation of algorithms), and the multiplication of virtual spaces. There is a common tendency in the framework of human interactions with computers to deprive data and bodies of their materiality. My Introduction and Chapter 1 offer theoretical interventions by reinstating embodied materiality and redefining labor for data as an ongoing process. The middle Chapters present case studies explaining how labor for data is pushed to the margin of the narratives about data production. I focus on a nationwide debate in the 1960s on whether the U.S. should build a databank, contemporary Big Data practices in the data broker and the Internet industries, and the group of people who are hired to produce data for other people’s avatars in the virtual games. I conclude with a discussion on how the new development of crowdsourcing projects may usher in the new chapter in exploiting invisible and discounted labor for data.

Studying the Causes and Consequences of Internal Labor Migration Using Survey and Administrative Data Sources

This dissertation comprises three chapters. The first chapter motivates the use of a novel data set combining survey and administrative sources for the study of internal labor migration. By following a sample of individuals from the American Community Survey (ACS) across their employment outcomes over time according to the Longitudinal Employer-Household Dynamics (LEHD) database, I construct a measure of geographic labor mobility that allows me to exploit information about individuals prior to their move. This enables me to explore aspects of the migration decision, such as homeownership and employment status, in ways that have not previously been possible. In the second chapter, I use this data set to test the theory that falling home prices affect a worker’s propensity to take a job in a different metropolitan area from where he is currently located. Employing a within-CBSA and time estimation that compares homeowners to renters in their propensities to relocate for jobs, I find that homeowners who have experienced declines in the nominal value of their homes are approximately 12% less likely than average to take a new job in a location outside of the metropolitan area where they currently reside. This evidence is consistent with the hypothesis that housing lock-in has contributed to the decline in labor mobility of homeowners during the recent housing bust. The third chapter focuses on a sample of unemployed workers in the same data set, in order to compare the unemployment durations of those who find subsequent employment by relocating to a new metropolitan area, versus those who find employment in their original location. Using an instrumental variables strategy to address the endogeneity of the migration decision, I find that out-migrating for a new job significantly reduces the time to re-employment. These results stand in contrast to OLS estimates, which suggest that those who move have longer unemployment durations. This implies that those who migrate for jobs in the data may be particularly disadvantaged in their ability to find employment, and thus have strong short-term incentives to relocate.

Trade Shocks and Local Labor Markets' Linkages: Theory and Evidence

In the past few years, there has been a concern among economists and policy makers that increased openness to international trade affects some regions in a country more than others. Recent research has found that local labor markets more exposed to import competition through their initial employment composition experience worse outcomes in several dimensions such as, employment, wages, and poverty. Although there is evidence that regions within a country exhibit variation in the intensity with which they trade with each other and with other countries, trade linkages have been ignored in empirical analyses of the regional effects of trade, which focus on differences in employment composition. In this dissertation, I investigate how local labor markets' trade linkages shape the response of wages to international trade shocks. In the second chapter, I lay out a standard multi-sector general equilibrium model of trade, where domestic regions trade with each other and with the rest of the world. Using this benchmark, I decompose a region's wage change resulting from a national import cost shock into a direct effect on prices, holding other endogenous variables constant, and a series of general equilibrium effects. I argue the direct effect provides a natural measure of exposure to import competition within the model since it summarizes the effect of the shock on a region's wage as a function of initial conditions given by its trade linkages. I call my proposed measure linkage exposure while I refer to the measures used in previous studies as employment exposure. My theoretical analysis also shows that the assumptions previous studies make on trade linkages are not consistent with the standard trade model. In the third chapter, I calibrate the model to the Brazilian economy in 1991--at the beginning of a period of trade liberalization--to perform a series of experiments. In each of them, I reduce the Brazilian import cost by 1 percent in a single sector and I calculate how much of the cross-regional variation in counterfactual wage changes is explained by exposure measures. Over this set of experiments, employment exposure explains, for the median sector, 2 percent of the variation in counterfactual wage changes while linkage exposure explains 44 percent. In addition, I propose an estimation strategy that incorporates trade linkages in the analysis of the effects of trade on observed wages. In the model, changes in wages are completely determined by changes in market access, an endogenous variable that summarizes the real demand faced by a region. I show that a linkage measure of exposure is a valid instrument for changes in market access within Brazil. By using observed wage changes in Brazil between 1991-2000, my estimates imply that a region at the 25th percentile of the change in domestic market access induced by trade liberalization, experiences a 0.6 log points larger wage decline (or smaller wage increase) than a region at the 75th percentile. The estimates from a regression of wages changes on exposure imply that a region at the 25th percentile of exposure experiences a 3 log points larger wage decline (or smaller wage increase) than a region at the 75th percentile. I conclude that estimates based on exposure overstate the negative impact of trade liberalization on wages in Brazil. In the fourth chapter, I extend the standard model to allow for two types of workers according to their education levels: skilled and unskilled. I show that there is substantial variation across Brazilian regions in the skill premium. I use the exogenous variation provided by tariff changes to estimate the impact of market access on the skill premium. I find that decreased domestic market access resulting from trade liberalization resulted in a higher skill premium. I propose a mechanism to explain this result: that the manufacturing sector is relatively more intensive in unskilled labor and I show empirical evidence that supports this hypothesis.