学位论文详细信息
Essays on the Iowa liquor market
Liquor;Random forest;Instrumental variables (IV);Regression discontinuity;License;Licensing;License fees;Iowa;Taxation;Tax;Sales tax;Instrument;RDD;Economics;Industrial organization (IO);Alcohol;Spirits
Schneider, John William
关键词: Liquor;    Random forest;    Instrumental variables (IV);    Regression discontinuity;    License;    Licensing;    License fees;    Iowa;    Taxation;    Tax;    Sales tax;    Instrument;    RDD;    Economics;    Industrial organization (IO);    Alcohol;    Spirits;   
Others  :  https://www.ideals.illinois.edu/bitstream/handle/2142/98154/SCHNEIDER-DISSERTATION-2017.pdf?sequence=1&isAllowed=y
美国|英语
来源: The Illinois Digital Environment for Access to Learning and Scholarship
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【 摘 要 】

This thesis presents three essays in the field of empirical industrial organiza-tion, with a particular focus on the retailer market for liquor in Iowa. Thiswork is divided into three chapters, with each focusing on a different aspectof retailer decision making and purchasing behavior.The first chapter presents new findings on the impact of retailer licensingfees on market structure and provision of services in market equilibrium forbottled liquor in Iowa. By utilizing a unique variable fee schedule with alarge recurring license fee, Iowa provides an opportunity for determining theeffects of licensing fees on market outcomes. Using a regression discontinuityapproach, this paper finds no effect on the number of retailers operating, butprovides some weak evidence for an increase in the volume sold per store.Two key implications follow. First, even relatively large regulatory burdenson retailers have a low impact on business outcomes. Second, increasinglicense fees is an inefficient way of restricting alcohol consumption. Thesefindings suggest that higher per-volume taxes on liquor may not be a goodpolicy for reducing alcohol consumption and abuse. We recommend futurework to address the potential management structure effects of licensing feeregimes.The second chapter investigates relatively novel techniques for demand es-timation. Random forest regression is quite new to economics, but is veryestablished as a predictive tool in other disciplines. Random forest regressionis better able to capture high-level interactions and nonlinearities than mostother estimation techniques, but is limited in its ability to be interpreted.Here we apply this technique to a unique dataset of liquor sales in the stateof Iowa to estimate demand among retailers for the top-selling liquor prod-ucts. We observe much more accurate predictions from the random forestmodel given the same datasets, but random forest regression exhibits a fewundesirable properties regarding error distribution.The final chapter focuses on the assortment decision faced by liquor retail-ers. Any retailer selling highly-diversified, imperfectly substitutable productsmust contend with difficult assortment selection decisions. Retailer assort-ment decisions depend on complex, interdependent cost and revenue func-tions along with strategic considerations regarding the assortment decisionsof competitors or potential market entrants. This paper contributes a novelidentification strategy to generate reduced-form estimates for the effects ofcompetitor assortment decisions among liquor retailers in Iowa. We find that,overall, retailers try to match each other’s assortment strategies, but thereis considerable heterogeneity across specific products.

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