We document a causal impact of online user-generated information on real-world economic outcomes. In particular, we conduct a randomized field experiment to test whether additional content on Wikipedia pages about cities affects tourists' choices of overnight visits. Our treatment of adding information to Wikipedia increases overnight stays in treated cities compared to non-treated cities. The impact is largely driven by improvements to shorter and relatively incomplete pages on Wikipedia. Our findings highlight the value of content in digital public goods for informing individual choices.

We analyze the relationship between unemployment and the supply of online labor for microtasking. Using detailed U.S. data from a large microtasking platform between 2011 and 2015, we study the participation and the number of hours supplied by workers in the U.S. We found that more individuals registered on the platform and completed microtasks as the unemployment level in the commuting zone increased. This effect was strongest in regions with a high share of low-skilled workers. Our analyses of the intensive margin, wage elasticity, and temporal work patterns suggest that the increased participation was likely motivated by an effort to substitute income. Our findings suggest that microtasking platforms are an interesting online labor market for less educated workers. However, we also observed very low retention rates, indicative of a solely transient participation effect.

Using data on 4.1 million apps at the Google Play Store from 2016 to 2019, we document that GDPR induced the exit of about a third of available apps; and in the quarters following implementation, entry of new apps fell by half. We estimate a structural model of demand and entry in the app market. Comparing long-run equilibria with and without GDPR, we find that GDPR reduces consumer surplus and aggregate app usage by about a third. Whatever the privacy benefits of GDPR, they come at substantial costs in foregone innovation.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

We show that review platforms reduce healthcare interruptions for patients look- ing for a new physician. We employ a difference-in-differences strategy using physi- cian retirements as a “disruptive shock” that forces patients to find a new physician. Using insurance claims data combined with web-scraped physician reviews, we show that physician reviews help patients find a new physician faster. Our results are robust to including a variety of controls and various instruments for the availability of physician reviews, but are not found for patients of nonretiring physicians. By reducing interruptions in care, reviews can improve clinical outcomes and lower costs.

We show that review platforms reduce healthcare interruptions for patients looking for a new physician. We employ a difference-in-differences strategy using physician retirements as a 'disruptive shock' that forces patients to find a new physician. We combine insurance claims data with web-scraped physician reviews and highlight a substantial care-gap resulting from a physician's retirement. We then show that online physician reviews reduce this gap and help patients find a new physician faster. Our results are robust to including a variety of controls and various instruments for the availability of physician reviews, but are not found for patients of nonretiring physicians. By reducing interruptions in care, reviews can improve clinical outcomes and lower costs.

Are there positive or negative externalities in knowledge production? We analyze whether current contributions to knowledge production increase or decrease the future growth of knowledge. To assess this, we use a randomized field experiment that added content to some pages in Wikipedia while leaving similar pages unchanged. We compare subsequent content growth over the next 4 years between the treatment and control groups. Our estimates allow us to rule out effects on 4-year growth of content length larger than twelve percent. We can also rule out effects on 4-year growth of content quality larger than four points, which is less than one-fifth of the size of the treatment itself. The treatment increased editing activity in the first 2 years, but most of these edits only modified the text added by the treatment. Our results have implications for information seeding and incentivizing contributions. They imply that additional content may inspire future contributions in the short- and medium-term but do not generate large externalities in the long term.

We analyze whether an informal second channel for communication can improve the efficiency of knowledge transfer in an electronic network of practice. We explore this question by analyzing the effect of chat rooms in the well-known Q&A forum Stack Overflow. We identify the causal effect using a difference-in-differences approach, which exploits a feed functionality that non-selectively pushed all questions from the Q&A into the relevant chat rooms. We report two main findings: First, chat rooms reduced the time until a question in the main Q&A received a satisfactory answer. Second, chat rooms disproportionately benefited new users who asked low-quality questions. Our study has clear managerial implications: A second channel for communication can complement the main channel in online communities to enhance both efficiency and inclusion.

Economic crises have a harmful effect on employment. However, whereas the resulting loss of jobs has been shown to have many negative consequences for the affected individuals, it may also push them into new activities, such as provision of service to their communities. In this paper, we show how individuals engage in socially useful activities after an increase in unemployment. Specifically, we document increased online content generation at Wikipedia, the world’s largest user-generated knowledge repository. Leveraging German district-level and European country-level unemployment data, we analyze the relationship between the economic crisis in 2008–2010 and contributions to Wikipedia. We find increased socially valuable activity in the form of knowledge acquisition and contributions to Wikipedia. For German districts, we observe an increase in the rate of content generation on Wikipedia in more severely affected districts. These effects are even stronger at the European country level. Our findings suggest that public goods provision increases as a positive side effect of economic crises. We stress that similar patterns could apply to other digital content platforms. Under the backdrop that the potential value of the outcome of online volunteering and its societal impact is expected to grow drastically in the next years, we show that platforms could benefit from negative economic conditions in attracting volunteers. Moreover, in the coming years, the rapid development of artificial intelligence will call for a rise of online volunteering platforms. Therefore, the potential value of the outcome of online volunteering and its societal impact is expected to grow drastically in the next years.

The enactment of the General Data Protection Regulation by the European Union has been the largest regulatory intervention in the recent history of datadriven (online) markets. We study the effect on the market of mobile smartphone applications. Specifically, we analyze how the enactment of the regulation has affected exit, entry, and consumer welfare in this market. To understand the shortrun effects of the regulation, we pursue a difference-in-differences strategy that compares differences between apps affected by the regulation to apps that operate in unaffected markets before and after the regulation. Our first results indicate that the enactment has a drastic effect on entry and exit in the app market. In a second step, we exploit the regulatory shock to quantify the value of data for consumers and app developers, and to shed light on the welfare implications of the GDPR.

Policy makers are increasingly concerned about the combination of market power and massive data collection in digital markets. This concern is fueled by the theoretical prediction that more market power causes firms to collect ever more data from their users. We investigate the relationship between market power and data collection empirically. We analyze data about more than 1.5 million mobile applications in several thousand submarkets of Google’s Play Store. We observe these data for over two years and combine information on an app’s data collection with information about its competitive environment. Our analysis highlights a robust positive relationship between market power and data collection. We find that more data are being collected in concentrated markets, and apps with higher market shares collect more data. This pattern robustly emerges across a series of cross-sectional and panel regressions as well as a series of specifications that exploit exogenous variation.

Does greater attention from a wider audience generate more productive input? I analyze how salience-driven viewership affects article edits in a highly influential user-generated public good (German-language Wikipedia). I identify the causal effect of more extensive viewership on edits, using data on 15,732 articles and 93 pseudo-experimental shocks. These shocks result from a spillover of attention that originates from advertisements of neighboring articles on Wikipedia's home page. I document three findings: (1) Additional viewership results in additional edits and greater participation; (2) the conversion-rate of salience-driven attention to content production occurs at a ratio of 1000:1; (3) salience-driven users contribute relatively small edits to relatively long articles with a low readership. My results show that attracting salience-driven attention is a powerful way of fostering contributions to collaborative content and helping users to discover editing opportunities. Further findings on users' editing choices warrant attention to the efficient allocation of salience-driven effort.

Online labor markets experienced a rapid growth in recent years. They allow for long-distance transactions and offer workers access to a potentially 'global' pool of labor demand. As such, they bear the potential to act as a substitute for shrinking local income opportunities. Using detailed U.S. data from a large online labor platform for microtasks, we study how local unemployment affects participation and work intensity online. We find that, at the extensive margin, an increase in commuting zone level unemployment is associated with more individuals joining the platform and becoming active in fulfilling tasks. At the intensive margin, our results show that with higher unemployment rates, online labor supply becomes more elastic. These results are driven by a decrease of the reservation wage during standard working hours. Finally, the effects are transient and do not translate to a permanent increase in platform participation by incumbent users. Our findings highlight that many workers consider online labor markets as a substitute to offline work for generating income, especially in periods of low local labor demand. However, the evidence also suggests that, despite their potential to attract workers, online markets for microtasks are currently not viable as a long run alternative for most workers.

We analyze the data collection strategies of 65,000 developers in the market for mobile applications and track 300,000 applications over four years. Many apps belong to developers with multiple apps. This fact generates variation in the privacy behaviors of the same developer for our analysis. We uncover three stylized facts: First, developers “learn” to use increasingly intrusive data strategies as they become more experienced. Second, intrusive data collection is most likely in apps that target the 13 , and 16 age category, which raises concerns for the protection of young app consumers. Third, even within developers, critical and atypical permissions predict problematic usage of private user data most successfully. Our findings inform both regulators and scientists who wish to model supply in the market for mobile apps.

We study how developers’ access to user data mediates the relationship between market power and product innovation in the mobile app industry. Developers with market power might more easily access user data through active data collection, which might imply less user privacy. Better access to user data might then facilitate more successful product innovations. Our empirical evidence is based on data on nearly 2 million apps from Google’s Play Store which we obtained quarterly in 2015 and 2016. We augment these data with information on apps’ privacy-intrusiveness (from PrivacyGrade.org), and on app-specific innovation activity and usage of code libraries (from AppBrain.com). First results suggest both a positive relationship between (1) market power and data access and (2) between data access and innovation. JEL Classification: D12, D22, L15, L86

We analyze the role of local and global network positions for content contributions to articles belonging to the category "Economy" on the German Wikipedia. Observing a sample of 7635 articles over a period of 153 weeks we measure their centrality both within this category and in the network of over one million Wikipedia articles. Our analysis reveals that an additional link from the observed category is associated with around 140 bytes of additional content and with an increase in the number of authors by 0.5. The relation of links from outside the category to content creation is much weaker. Beyond the econometric analysis, our study sheds light on how the discipline of economics is represented on German Wikipedia. We find non-neoclassical themes to be highly prevalent among the top articles. (C) 2016 Published by Elsevier B.V.

We shed light on a money-for-privacy trade-off in the market for smartphone applications (“apps”). Developers offer their apps at lower prices in return for greater access to personal information, and consumers choose between low prices and more privacy. We provide evidence for this pattern using data from 300,000 apps obtained from the Google Play Store (formerly Android Market) in 2012 and 2014. Our findings show that the market’s supply and demand sides both consider an app’s ability to collect private information, measured by the apps’s use of privacy-sensitive permissions: (1) cheaper apps use more privacy-sensitive permissions; (2) given price and functionality, demand is lower for apps with sensitive permissions; and (3) the strength of this relationship depends on contextual factors, such as the targeted user group, the app’s previous success, and its category. Our results are robust and consistent across several robustness checks, including the use of panel data, a difference-in-differences analysis, “twin” pairs of apps, and various measures of privacy-sensitivity and app demand. This paper was accepted by Anandhi Bharadwaj, information systems.

In this paper, we address the impact of surging unemployment on online public good provision. Specically, we ask how drastically increased unemployment aects voluntary contributions of content to the online encyclopedia Wikipedia. We put together a monthly country-level data set, which combines country specic economic outcomes with data on contributions to the online encyclopedia. As a source of exogenous variation in the economic state we use the various economic crises in European countries following the nancial crisis in the US, which started in September 2008. We nd that economic downturn is associated with more viewership, which channels higher participation of volunteers in Wikipedia expressed in editing activity and content growth. We provide evidence for increased information search online or online learning as a potential channel of the change in public goods provision, which is a potentially important side eect of economic

We document a causal influence of online user-generated information on realworld economic outcomes. In particular, we conduct a randomized field experiment to test whether additional information on Wikipedia about cities affects tourists' choices of overnight visits. Our treatment of adding information to Wikipedia increases overnight visits by 9% during the tourist season. The impact comes mostly from improving the shorter and incomplete pages in Wikipedia.