Essays in Applied Industrial Organization

Thesis advisor: Julie H. MortimerThis dissertation investigates firms' strategic decisions in industries characterized by a retail sector and the subsequent welfare implications. The first chapter studies retailer assortment choices; the second investigates the effectiveness of retailer online advertising. In many industries producers reach consumers only through the retail sector. Retailer product assortment choices are crucial determinants of consumer welfare as well as retailers' and producers' profitability. Limited shelf space, an inherent characteristic of the brick-and-mortar retail sector, necessitates careful selection of product offerings. The assortment decision within a product category consists of two broad questions: "How many products to offer?" and "Which products to offer?". In sole-authored work, the first chapter focuses on the latter question and investigates the drivers and welfare consequences of retail product selections. While retailer assortment choices are primarily governed by consumers' preferences and retail sector competition, vertical contracts with producers may also influence product offerings, and, in turn, product availability in the market. From the producers' perspective, obtaining product distribution is imperative. Hence, producers frequently provide financial incentives to retailers to secure their patronage. These incentives often take the form of vendor allowances: lump-sum payments to retailers that do not directly depend on sales volume. They can take the form of slotting fees, warehousing allowances, cash discounts, allowances for damaged goods, or operating support (e.g. stocking personnel). Considering the spread of the retail sector, the impact of vertical contracts on product selections may substantially affect consumer welfare and firm profitability. Therefore, it is not surprising that vendor allowances have been the subject of policy discussion. Policy makers have raised concerns that these payments are harming disproportionately small producers and limiting consumer choice. Nevertheless, the Federal Trade Commission abstains from providing clear guidelines on the use of these payments due to unclear theoretical predictions and scarce empirical evidence. The main impediment to empirical analysis has been the proprietary nature of vertical contracts and firm costs. To overcome these data limitations, I develop a novel framework that allows me to quantify vendor allowances and analyze their effects on product selections and welfare. Using only data on retail prices, quantity sold, and retailer offerings, I estimate vendor allowances as retailers' opportunity cost of shelf space. Specifically, retailers face shelf-space limitations, hence, the opportunity cost of supplying a product is the sacrificed profits from not supplying a different product in its place. With limited assumptions on producer and retailer bargaining protocol, set estimates of vendor allowances are recovered. Additionally, by assuming that producers make take-it-or-leave-it offers, point estimates can be obtained. Lower bounds from set estimates imply that, on average, vendor allowances amount to at least 5% of retailer revenues. These results suggest that vendor allowances are likely important for retailer profitability, given that public grocery chains in the U.S. report profit margins on the order of 2-4% of revenues. To investigate the effects of these payments on product selections and welfare, I apply model estimates to simulate how market outcomes change in the absence of vendor allowances. The "what-if" experiment predicts that, absent vendor allowances, retailers fare worse, product variety is reduced as retailers replace "niche" products with "mainstream" options, but consumers are nevertheless better off. Small producers, which offer high-volume products, increase market distribution and profits, but, absent marginal cost data, consequences for large producers are uncertain. The work extends our understanding of how firms' strategic interactions in the marketplace may affect consumer welfare and firm profitability through product availability. The second chapter presents a coauthored work with Alexander Bleier and Maik Eisenbeiss that analyzes the use of online advertising personalization by an online retailer. Online advertising has become an important channel through which firms attempt to influence consumer behavior and increase sales. To improve effectiveness, firms today tailor their advertisements to individual consumers with a method called retargeting. In retargeting, firms track the shopping behaviors of individual consumers' visiting their online stores and, subsequently, deliver individualized display banner ads as consumers continue browsing the Web. While this method has gained traction in the online advertising industry, research in the field is still in its infancy. This work furthers our understanding of advertising personalization by analyzing two questions: How effective is ad personalization in attracting individual consumers back to the online store? And, do different personalization approaches have distinct impacts on consumers' engagement behaviors with the online store? To answer these research questions, we exploit unique data from a randomized field experiment conducted in cooperation with a major fashion and sporting goods retailer. This study compares the effects of online banners with very high, medium, and low degrees of content personalization. For example, very high personalization refers to ads showing consumers products that they had viewed at their previous visit to the retailer's online store. Medium personalization includes products from the most viewed category or brand of their previous visit. And low personalization delivers random products from the retailer's assortment without any connection to a consumer's previous shopping behavior. Results suggest that ads with very high personalization are more effective in bringing consumers back to the online store than the other campaigns. However, we also find that the gain in visits of very high- over medium-personalization banners stems mainly from visit with low consumer engagement.Thesis (PhD) — Boston College, 2016.Submitted to: Boston College. Graduate School of Arts and Sciences.Discipline: Economics

DENTON: Stata module to interpolate a flow or stock series from low-frequency totals via proportional Denton method

denton computes the proportional Denton method of interpolation of a low-frequency flow time series by use of an associated high-frequency "indicator series", imposing the constraints that the interpolated series obeys the low-frequency totals. The method is recommended in IMF publications as "relatively simple, robust, and well-suited for large-scale applications." It may be particularly useful in cases where, due to sizable statistical discrepancy, quarterly series do not integrate to annual totals. The indicator series only contribute their pattern to the interpolation. The routine can interpolate annual data to quarterly or monthly, and quarterly data to monthly. The stock option allows the routine to handle stock (rather than flow) series. A certification script for the package is provided. This version of the package also contains denton7 and dentonmq7, which should be used if you do not have Stata 11 or 12. These routines use a completely different command format and require more setup effort. dentonmq7 is a routine to perform the same task for monthly interpolation of a quarterly series. The programs may be applied to a single time series within a panel.benchmarking, time-series, interpolation