This paper develops a novel methodology for structurally estimating a multi-dimensional non-linear pricing scheme with more than one decision variable. Using a rich and unique panel data of residents' electricity consumption, we provide a structural analysis of how economic agents choose their...

Evaluating the returns to marketing spending and designing optimal budget allocations have been challenging tasks for businesses. New data availability and novel machine learning methods provide new opportunities to significantly improve such decisions. The goal of this paper is to prescribe the...

This paper provides both theoretical and empirical studies on the incentive effect of peer recognition on online content provision. Our theoretical model illustrates how a Bayesian influencer strategically determines her online contribution. Using unique data from the largest Chinese...

The outbreak of COVID-19 has caused huge disruptions to the world economy. As a number of countries make progress in containing this outbreak, some of them have started to reopen their economy. We study the curves of recovery after reopening the economy, using a unique real-time dataset of daily...

Medical crowdfunding has seen rapid growth in recent years and it has become a popular channel for people needing financial help. However, there exists large heterogeneity in donations across cases and fundraisers face significant uncertainty in whether their crowdfunding campaigns can meet...

Medical crowdfunding is a popular channel for people needing financial help paying medical bills to collect donations from large numbers of people. However, large heterogeneity exists in donations across cases, and fundraisers face significant uncertainty in whether their crowdfunding campaigns...

We investigate the supply strategy of a firm that faces uncertain seasonal demand. While additional demand information becomes available in the form of signals throughout a finite planning horizon, it also becomes more expensive to acquire the product. In this setting, we explore the tradeoff...

We show that the average difference between the implied volatilities of call and put options on individual equities, which we term the implied volatility spread (IVS), has strong predictive power for stock market returns at horizons between one and six months, with monthly in-sample and...

This paper proposes a new explanation of the negative correlation between VIX betas and expected stock returns documented by Ang et al. (2006). While the relation has been widely cited as the proof that market volatility risk is priced in the cross-section of stocks, we find this view highly...

With the rapid growth of e-commerce, financial products are being brought onto online platforms. However, due to the scarcity of data in this new product domain, online platforms face challenges in predicting users' purchase behavior. In this paper, we study whether we can "transfer'' knowledge...