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• Working Paper | HBS Working Paper Series | 2018

  Complex Disclosure

  Ginger Zhe Jin, Michael Luca and Daniel Martin

  Disclosure policies have the potential to help consumers and make markets more efficient. Yet, the effectiveness of disclosure policies can be undermined if firms strategically make unfavorable information unnecessarily complicated to understand. To explore the incentives for using complexity in disclosure, we implement a game of mandatory disclosure where senders are required to report their private information truthfully, but can choose how complex to make their reports. We find that senders use complex disclosure over half the time, and most of this obfuscation is profitable because receivers make systematic mistakes in assessing complex reports. Stated beliefs suggest that receivers correctly infer the strategic implications of complexity, but are overconfident about their ability to assess complex reports.

  Citation:

  Jin, Ginger Zhe, Michael Luca, and Daniel Martin. "Complex Disclosure." Harvard Business School Working Paper, No. 18-105, May 2018.  View Details

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• Article | American Economic Association Papers and Proceedings | May 2018

  Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change

  Edward L. Glaeser, Hyunjin Kim and Michael Luca

  Data from digital platforms have the potential to improve our understanding of gentrification and enable new measures of how neighborhoods change in close to real time. Combining data on businesses from Yelp with data on gentrification from the Census, Federal Housing Finance Agency, and Streetscore (an algorithm using Google Streetview), we find that gentrifying neighborhoods tend to have growing numbers of local groceries, cafes, restaurants, and bars, with little evidence of crowd-out of other types of businesses. For example, the entry of a new coffee shop into a zip code in a given year is associated with a 0.5 percent increase in housing prices. Moreover, Yelp measures of local business activity provide leading indicators for housing price changes and help to forecast which neighborhoods are gentrifying.

  Keywords: Forecasting Models; Simulation Methods; Regional Economic Activity: Growth, Development, Environmental Issues, and Changes; Geographic Location; Local Range; Transition; Data and Data Sets; Measurement and Metrics; Economic Growth; Forecasting and Prediction;

  Citation:

  Glaeser, Edward L., Hyunjin Kim, and Michael Luca. "Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change." American Economic Association Papers and Proceedings 108 (May 2018): 77–82.  View Details

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• Case | HBS Case Collection | April 2018

  Shanda Family Office

  Christopher Malloy, Lauren Cohen and Essie Alamsyah

  Tianqiao Chen, founder and CEO of Shanda Group, has set up his family office in the U.S. in 2016 after exiting from Shanda's Internet games business in China in 2014, again pioneering an unconventional approach to the management of a family office.

  Keywords: China; United States;

  Citation:

  Malloy, Christopher, Lauren Cohen, and Essie Alamsyah. "Shanda Family Office." Harvard Business School Case 218-102, April 2018.  View Details

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