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• Article | Review of Financial Studies | June 2019

  Social Risk, Fiscal Risk, and the Portfolio of Government Programs

  Samuel G. Hanson, David S. Scharfstein and Adi Sunderam

  We develop a model of government portfolio choice in which a benevolent government chooses the scale of risky projects in the presence of market failures and tax distortions. These two frictions generate motives to manage social risk and fiscal risk. Social risk management makes attractive programs that ameliorate market failures in bad economic times. Fiscal risk management makes unattractive programs that entail large government outlays at times when other programs in the government's portfolio also require large outlays. We characterize the determinants of social and fiscal risk and argue that these two risk management motives often conflict. Using the model, we explore how the attractiveness of different financial stability programs varies with the government's fiscal burden and with characteristics of the economy.

  Keywords: Risk Management; Government and Politics; Programs;

  Citation:

  Hanson, Samuel G., David S. Scharfstein, and Adi Sunderam. "Social Risk, Fiscal Risk, and the Portfolio of Government Programs." Review of Financial Studies 32, no. 6 (June 2019): 2341–2382. (Internet Appendix Here.)  View Details

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• Working Paper | 2019

  Using Models to Persuade

  Joshua Schwartzstein and Adi Sunderam

  We present a framework for analyzing “model persuasion,” where persuaders influence people’s beliefs by proposing models (likelihood functions) that suggest how to organize past data (e.g., on investment performance) to make predictions (e.g., about future returns). Receivers are assumed to find models more compelling when they better explain the past. A key tradeoff persuaders face is that models that better fit the data induce less movement in receivers’ beliefs. Model persuasion sometimes makes the receiver worse off than if he interprets data through the lens of a default model. The receiver is most misled by persuasion when there is a lot of publicly available data that is open to interpretation and exhibits randomness, as this gives the persuader “wiggle room” to highlight false patterns. Even when the receiver is exposed to the true model, the wrong model often wins because it better fits the past. Competition more broadly pushes persuaders towards overfitting available data and as a result tends to neutralize the data by leading receivers to view it as unsurprising. With multiple receivers, a persuader is more effective when receivers share similar priors and default interpretations. We illustrate with examples from finance, politics, and law.

  Keywords: model persuasion; Data and Data Sets; Forecasting and Prediction; Mathematical Methods; Framework;

  Citation:

  Schwartzstein, Joshua, and Adi Sunderam. "Using Models to Persuade." Working Paper, July 2019.  View Details

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• Teaching Note | HBS Case Collection | June 2018 (Revised January 2019)

  Investing in Commodities at Global Endowment Management

  Adi Sunderam

  Teaching Note for HBS No. 218-005.

  Citation:

  Sunderam, Adi. "Investing in Commodities at Global Endowment Management." Harvard Business School Teaching Note 218-118, June 2018. (Revised January 2019.)  View Details

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