中文摘要
我们提出一种用于捆绑商品（bundles）需求的广义嵌套 Logit（Generalized Nested Logit）模型，该模型可分步（序贯）估计，从而消除大规模选择集带来的维度难题。我们运用该模型，通过模拟线性定价这一反事实情景，考察碳酸软饮料的数量折扣。结果显示，小容量 UPC（<2L）的价格下降 29.2%，而大容量 UPC（≥2L）的价格上升 16.8%；购买数量下降 19.5%，行业利润下降 6.3%。然而，消费者剩余仅小幅减少，这表明禁止对含糖饮料实行数量折扣，可能是一项限制添加糖摄入的简单而有效的政策。我们的测算证实，此类禁令的效果相当于对每盎司添加糖征收 1.5 的糖税，可使添加糖摄入减少 17.4%。相比之下，若嵌套 Logit 模型错误地忽略同一次购物行程中各 UPC 的联合购买，则只会模拟出添加糖摄入减少 3.9% 的结果。
Abstract
Abstract We introduce a Generalized Nested Logit model of demand for bundles that can be estimated sequentially, eliminating the challenge of dimensionality due to large choice sets. We use it to investigate quantity discounts for carbonated soft drinks by simulating a counterfactual with linear pricing. The prices of small-volume UPCs (<2L) decrease by −29.2% while those of large-volume UPCs (≥2L) increase by +16.8%. Purchased quantities decrease by −19.5% and industry profit by −6.3%. Consumer surplus however reduces only moderately, suggesting that a ban on quantity discounts on sugary drinks may be a simple and effective policy to limit added sugar intake. Our calculations confirm that such a ban would be as effective as a sugar tax of 1.5/oz of added sugar and reduce added sugar intake by −17.4%. A nested logit model that mistakenly ignores joint purchases of UPCs within shopping trips would instead simulate a reduction in added sugar intake of only −3.9%.