In the digital economy, user data is typically treated as capital created by corporations observing willing individuals. This neglects users' roles in creating data, reducing incentives for users, distributing the gains from the data economy unequally, and stoking fears of automation. Instead, treating data (at least partially) as labor could help resolve these issues and restore a functioning market for user contributions, but may run against the near-term interests of dominant data monopsonists who have benefited from data being treated as “free.” Countervailing power, in the form of competition, a data labor movement, and/or thoughtful regulation could help restore balance.

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The link between happiness and overall inequality is best studied using an index that incorporates different aspects of inequality, and is measured consistently in different countries. One such index is the degree to which happiness itself varies among individuals. Its correlation with both happiness levels and social trust is substantially stronger than the corresponding correlation for income inequality. This remains so after allowing for bounded scale reporting, including a purely ordinal measure of dispersion. Moreover, the correlation is stronger for individuals who profess to care most about inequality. The link between happiness and inequality may thus be stronger than previously appreciated. (JEL I31, D6, D63, D31)

The link between happiness and overall inequality is best studied using an index that incorporates different aspects of inequality, and is measured consistently in different countries. One such index is the degree to which happiness itself varies among individuals. Its correlation with both happiness levels and social trust is substantially stronger than the corresponding correlation for income inequality. This remains so after allowing for bounded scale reporting, including a purely ordinal measure of dispersion. Moreover, the correlation is stronger for individuals who profess to care most about inequality. The link between happiness and inequality may thus be stronger than previously appreciated.

Do workers' first jobs affect their careers? Do such first-job effects (FJEs) vary across worker types? If so, can policy improve upon a “free” labor market by altering initial worker-employer matches? We study these questions using Norway's pre-2013 system of assigning doctors to their first job–residencies–through a random serial dictatorship. This generated individual-level variation in workers' choice sets over employers, which we use as instrumental variables to estimate FJEs. We then decompose workers' preferences over first employers into FJEs-on-earnings and employer “amenity value” components, showing how matches and worker welfare changed in the post-2013 decentralized labor market.