A common belief about the growing medium of livestreaming is that its value lies in its "live" component. We examine this belief by comparing how the price elasticity of demand for live events varies before, on the day of, and after livestream. We do this using unique and rich data from a large livestreaming platform that allows consumers to purchase the recorded version of livestream after the stream is over. A challenge in our context is that there exist high-dimensional confounders whose relationships with treatment policy (i.e., price) and outcome of interest (i.e., demand) are complex and only partially known. We address this challenge via the use of a generalized Orthogonal Random Forest framework for heterogeneous treatment effect estimation. We find significant temporal dynamics in the price elasticity of demand over the entire event life-cycle. Specifically, demand becomes less price sensitive over time to the livestreaming day, turning to inelastic on that day. Over the post-livestream period, the demand for the recorded version is still sensitive to price, but much less than in the pre-livestream period. We further show that this temporal variation in price elasticity is driven by the quality uncertainty inherent in such events and the opportunity of real-time interaction with content creators during the livestream.
翻译:对不断增长的流动媒介的共同看法是,其价值在于其“活性”组成部分。我们通过比较活性活动需求的价格弹性在活性活动之前、当天和之后是如何变化的。我们使用一个大型流动平台的独特和丰富的数据来做到这一点,该平台允许消费者在流完后购买已记录的流流流。我们面临的一个挑战是,存在高维的迷惑者,他们与治疗政策(即价格)和感兴趣结果(即需求)的关系是复杂和仅部分为人所知的。我们通过使用常规的奥氏随机森林框架来应对这一挑战,以进行混杂治疗效果估计。我们发现在整个事件生命周期内需求的价格弹性具有显著的时间动态。具体地说,需求随着流出一天的流动,随着时间变得对价格敏感,变得无弹性。在流出后时期,对记录版本的需求仍然对价格敏感,但远比流前时期要少得多。我们进一步表明,在价格变化中,真实的时间变化与创造者在生前阶段内,其内在的弹性是,在价格变化中,这种时间变化是机会驱动的。