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- Genre: Doctoral Dissertation
Description
The objective of this dissertation is to empirically analyze the results of the retail location decision making process and how chain networks evolve given their value platform. It employs one of the largest cross-sectional databases of retailers ever assembled, including 50 US retail chains and over 70,000 store locations. Three closely related articles, which develop new theory explaining location deployment and behaviors of retailers, are presented. The first article, "Regionalism in US Retailing," presents a comprehensive spatial analysis of the domestic patterns of retailers. Geographic Information Systems (GIS) and statistics examine the degree to which the chains are deployed regionally versus nationally. Regional bias is found to be associated with store counts, small market deployment, and the location of the founding store, but not the age of the chain. Chains that started in smaller markets deploy more stores in other small markets and vice versa for chains that started in larger markets. The second article, "The Location Types of US Retailers," is an inductive analysis of the types of locations chosen by the retailers. Retail locations are classified into types using cluster analysis on situational and trade area data at the geographical scale of the individual stores. A total of twelve distinct location types were identified. A second cluster analysis groups together the chains with the most similar location profiles. Retailers within the same retail business often chose similar types of locations and were placed in the same clusters. Retailers generally restrict their deployment to one of three overall strategies including metropolitan, large retail areas, or market size variety. The third article, "Modeling Retail Chain Expansion and Maturity through Wave Analysis: Theory and Application to Walmart and Target," presents a theory of retail chain expansion and maturity whereby retailers expand in waves with alternating periods of faster and slower growth. Walmart diffused gradually from Arkansas and Target grew from the coasts inward. They were similar, however, in that after expanding into an area they reached a point of saturation and opened fewer stores, then moved on to other areas, only to revisit the earlier areas for new stores.
ContributorsJoseph, Lawrence (Author) / Kuby, Michael (Thesis advisor) / Matthews, Richard (Committee member) / Ó Huallacháin, Breandán (Committee member) / Kumar, Ajith (Committee member) / Arizona State University (Publisher)
Created2013
Description
Schennach (2007) has shown that the Empirical Likelihood (EL) estimator may not be asymptotically normal when a misspecified model is estimated. This problem occurs because the empirical probabilities of individual observations are restricted to be positive. I find that even the EL estimator computed without the restriction can fail to be asymptotically normal for misspecified models if the sample moments weighted by unrestricted empirical probabilities do not have finite population moments. As a remedy for this problem, I propose a group of alternative estimators which I refer to as modified EL (MEL) estimators. For correctly specified models, these estimators have the same higher order asymptotic properties as the EL estimator. The MEL estimators are obtained by the Generalized Method of Moments (GMM) applied to an exactly identified model. The simulation results provide promising evidence for these estimators. In the second chapter, I introduce an alternative group of estimators to the Generalized Empirical Likelihood (GEL) family. The new group is constructed by employing demeaned moment functions in the objective function while using the original moment functions in the constraints. This designation modifies the higher-order properties of estimators. I refer to these new estimators as Demeaned Generalized Empirical Likelihood (DGEL) estimators. Although Newey and Smith (2004) show that the EL estimator in the GEL family has fewer sources of bias and is higher-order efficient after bias-correction, the demeaned exponential tilting (DET) estimator in the DGEL group has those superior properties. In addition, if data are symmetrically distributed, every estimator in the DGEL family shares the same higher-order properties as the best member.
ContributorsXiang, Jin (Author) / Ahn, Seung (Thesis advisor) / Wahal, Sunil (Thesis advisor) / Bharath, Sreedhar (Committee member) / Mehra, Rajnish (Committee member) / Tserlukevich, Yuri (Committee member) / Arizona State University (Publisher)
Created2013
Description
I show that firms' ability to adjust variable capital in response to productivity shocks has important implications for the interpretation of the widely documented investment-cash flow sensitivities. The variable capital adjustment is sufficient for firms to capture small variations in profitability, but when the revision in profitability is relatively large, limited substitutability between the factors of production may call for fixed capital investment. Hence, firms with lower substitutability are more likely to invest in both factors together and have larger sensitivities of fixed capital investment to cash flow. By building a frictionless capital markets model that allows firms to optimize over fixed capital and inventories as substitutable factors, I establish the significance of the substitutability channel in explaining cross-sectional differences in cash flow sensitivities. Moreover, incorporating variable capital into firms' investment decisions helps explain the sharp decrease in cash flow sensitivities over the past decades. Empirical evidence confirms the model's predictions.
ContributorsKim, Kirak (Author) / Bates, Thomas (Thesis advisor) / Babenko, Ilona (Thesis advisor) / Hertzel, Michael (Committee member) / Tserlukevich, Yuri (Committee member) / Arizona State University (Publisher)
Created2013
Description
The present essay addresses the epistemic difficulties involved in achieving consensus with respect to the Hayek-Keynes debate. In particular, it is argued that the debate cannot be settled on the basis of the observable evidence; or, more precisely, that the empirical implications of the theories of Hayek and Keynes are such that, regardless of what is observed, both of the theories can be interpreted as true, or at least, not falsified. Regardless of the evidence, both Hayek and Keynes can be interpreted as right. The underdetermination of theories by evidence is an old and ubiquitous problem in science. The present essay makes explicit the respects in which the empirical evidence underdetermines the choice between the theories of Hayek and Keynes. In particular, it is argued both that there are convenient responses one can offer that protect each theory from what appears to be threatening evidence (i.e., that the choice between the two theories is underdetermined in the holist sense) and that, for particular kinds of evidence, the two theories are empirically equivalent (i.e., with respect to certain kinds of evidence, the choice between the two theories is underdetermined in the contrastive sense).
ContributorsScheall, Scott (Author) / Creath, Richard (Thesis advisor) / Armendt, Brad (Committee member) / French, Peter (Committee member) / Arizona State University (Publisher)
Created2012
Description
The jobless recovery of the Great Recession has led policymakers and citizens alike to ask what can be done to better protect regions from the cascading effects of an economic downturn. Economic growth strategies that aim to redevelop a waterfront for tourism or attract high growth companies to the area, for example, have left regions vulnerable by consolidating resources in just a few industry sectors or parts of town. A promising answer that coincided with growing interest in regional innovation policy has been to promote entrepreneurship for bottom-up, individual-led regional development. However, these policies have also failed to maximize the potential for bottom-up development by focusing on high skill entrepreneurs and high tech industry sectors, such as green energy and nanotechnology. This dissertation uses the extended case method to determine whether industry cluster theory can be usefully extended from networks of high skill innovators to entrepreneurs in traditional trades. It uses U.S. Census data and in-person interviews in cluster and non-cluster neighborhoods in Dayton, Ohio to assess whether traditional entrepreneurs cluster and whether social networks explain high rates of neighborhood self-employment. Entrepreneur interviews are also conducted in Raleigh, North Carolina to explore regional resilience by comparing the behavior of traditional entrepreneurs in the ascendant tech-hub region of Raleigh and stagnant Rustbelt region of Dayton. The quantitative analysis documents, for the first time, a minor degree of neighborhood-level entrepreneur clustering. In interviews, entrepreneurs offered clear examples of social networks that resemble those shown to make regional clusters successful, and they helped clarify that a slightly larger geography may reveal more clustering. Comparing Raleigh and Dayton entrepreneurs, the study found few differences in their behavior to explain the regions' differing long-term economic trends. However, charitable profit-seeking and trial and error learning are consistent behaviors that may distinguish traditional, small scale entrepreneurs from larger export-oriented business owners and contribute to a region's ability to withstand recessions and other shocks. The research informs growing policy interest in bottom-up urban development by offering qualitative evidence for how local mechanics, seamstresses, lawn care businesses and many others can be regional assets. Future research should use larger entrepreneur samples to systematically test the relationship between entrepreneur resilience behaviors to regional economic outcomes.
ContributorsAuer, Jennifer Claire (Author) / Chapman, Jeffrey (Thesis advisor) / Johnston, Erik W., 1977- (Committee member) / Jurik, Nancy (Committee member) / Arizona State University (Publisher)
Created2013
Description
Estimating cointegrating relationships requires specific techniques. Canonical correlations are used to determine the rank and space of the cointegrating matrix. The vectors used to transform the data into canonical variables have an eigenvector representation, and the associated canonical correlations have an eigenvalue representation. The number of cointegrating relations is chosen based upon a theoretical difference in the convergence rates of the eignevalues. The number of cointegrating relations is consistently estimated using a threshold function which places a lower bound on the eigenvalues associated with cointegrating relations and an upper bound on the eigenvalues on the eigenvalues not associated with cointegrating relations. The proposed estimator performs better with a large number of cross-sectional observations and moderate time series length.
ContributorsNowak, Adam (Author) / Ahn, Seung C (Thesis advisor) / Liu, Crocker (Committee member) / Kallberg, Jarl (Committee member) / Arizona State University (Publisher)
Created2012
Description
Unrestricted Mexican exports of sugar into the U.S. is considered the most pressing issue facing the U.S. sugar industry. The goal of this dissertation is to analyze the trade of sugar between Mexico and the U.S. as well as analyze additional primary issues confronting the U.S. sugar industry. Chapters 1 and 2 provide an introduction to the U.S. sugar industry. Chapters 3 through 6 develop trade models which analyze sugar trade between Mexico and the U.S. The trade models estimate how NAFTA, USDA sugar forecast errors and Mexican ownership of twenty percent of the Mexican sugar industry each impact U.S. producer surplus and Mexican welfare. Results validate that U.S. producer surplus and in some instances Mexican welfare were decreased by full implementation of NAFTA. U.S. producer surplus and Mexican welfare were decreased due to USDA sugar production forecasting errors. U.S. producer surplus would be increased if the Mexican government did not own twenty percent of Mexican sugar production. Using an online choice experiment, Chapter 7 assesses U.S. consumers' preferences and willingness to pay (WTP) for imported and genetically modified (GM) labeled sugar and sugar in soft drinks. Results indicate that consumers prefer bags of sugar and soft drinks labeled as "Not GM". Furthermore, consumers prefer sugar from Canada and the U.S. over sugar from Mexico, Brazil and the Philippines. Evidence is also provided that participants are more likely to choose actual products in the choice set rather than the "none of these" options when controlling for hypothetical bias by using consequentiality techniques. A non-hypothetical experimental auction was used in Chapter 8 to determine consumers' WTP for soft drinks labeled with sweetener and calorie information and analyzed the role of taste panels in an experimental auction. Results indicate that sugar is consumers' most preferred sweetener and calorie labeling is ineffective at influencing consumers to choose healthier soft drinks. Including taste in an experimental auction caused significant reductions in consumers' WTP for all soft drinks. Chapter 9 concludes by summarizing the results of this dissertation and discussing the future challenges facing the U.S. sugar industry.
ContributorsLewis, Karen Elizabeth (Author) / Schmitz, Troy (Thesis advisor) / Grebitus, Carola (Committee member) / Manfredo, Mark (Committee member) / Ketcham, Andrea (Committee member) / Arizona State University (Publisher)
Created2014
Description
This dissertation consists of three essays that broadly deal with the international economics and development. The first chapter provides empirical evidence of the prevalence and importance of intangible capital transfer within multinational corporations (MNCs). Using a unique data set of Korean multinational foreign affiliates, I find that most of the foreign affiliates have managers transferred from their parent, while almost half are isolated from the parent in terms of physical trade. Furthermore, the transferred managers are positively associated with labor productivity, while physical trade from the parent is less so. I consider two possibilities for this productivity effect: (1) the managers transferred from the parent are simply more efficient than native managers; and (2) they provide knowledge that increases the productivity of all inputs. I find that the latter is consistent with the data. My findings provide evidence that transferring managers from the parent is a main source of benefit from foreign direct investment (FDI) to foreign affiliates because the managers transfer firm-specific knowledge. The second chapter analyzes importance role of service or other sectors for economic growth of manufacturing. Productivity in agriculture or services has long been understood as playing an important role in the growth of manufacturing. In this paper we provide an endogenous growth model in which manufacturing growth is stimulated by the non-manufacturing sector that provides goods used for both research and final consumption. The model permits to evaluatation of two policy options for stimulating manufacturing growth: (1) a country imports more non-manufacturing goods from a foreign country with a higher productivity; or (2) the country increases productivity of domestic non-manufacturing. We find that both policies increase welfare of the economy, but depending on the policy the manufacturing sector responses differently. Specifically, employment and value added in manufacturing rise with policy (1), but contract with policy (2). Therefore, specialization through importing non-manufacturing goods explains how some Asian economies experience fast growth in the manufacturing sector without progress in the other sectors. The third chapter tests for the importance of composition effects in affecting levels and changes of education wage premiums. In this paper I revisit composition effects in the context of Korea. Korea's large and rapid expansion of education makes it an ideal place to look for composition effects. A large, policy-induced increase in attainment in the 1980s offers additional scope for identifying composition effects. I find strong evidence that the policy-induced expansion of education lowered education wage premiums for the affected cohorts, but only weak evidence that the trend expansion of education lowered education wage premiums.
ContributorsCho, Jaehan (Author) / Silverman, Daniel (Thesis advisor) / Prescott, Edward C. (Committee member) / Schoellman, Todd (Committee member) / Arizona State University (Publisher)
Created2014
Description
It is well understood that decisions made under uncertainty differ from those made without risk in important and significant ways. Yet, there is very little research into how uncertainty manifests itself in the most ubiquitous of decision-making environments: Consumers' day-to-day decisions over where to shop, and what to buy for their daily grocery needs. Facing a choice between stores that either offer relatively stable "everyday low prices" (EDLP) or variable prices that reflect aggressive promotion strategies (HILO), consumers have to choose stores under price-uncertainty. I find that consumers' attitudes toward risk are critically important in determining store-choice, and that heterogeneity in risk attitudes explains the co-existence of EDLP and HILO stores - an equilibrium that was previously explained in somewhat unsatisfying ways. After choosing a store, consumers face another source of risk. While knowing the quality or taste of established brands, consumers have very little information about new products. Consequently, consumers tend to choose smaller package sizes for new products, which limits their exposure to the risk that the product does not meet their prior expectations. While the observation that consumers purchase small amounts of new products is not new, I show how this practice is fully consistent with optimal purchase decision-making by utility-maximizing consumers. I then use this insight to explain how manufacturers of consumer packaged goods (CPGs) respond to higher production costs. Because consumers base their purchase decisions in part on package size, manufacturers can use package size as a competitive tool in order to raise margins in the face of higher production costs. While others have argued that manufacturers reduce package sizes as a means of raising unit-prices (prices per unit of volume) in a hidden way, I show that the more important effect is a competitive one: Changes in package size can soften price competition, so manufacturers need not rely on fooling consumers in order to pass-through cost increases through changes in package size. The broader implications of consumer behavior under risk are dramatic. First, risk perceptions affect consumers' store choice and product choice patterns in ways that can be exploited by both retailers and manufacturers. Second, strategic considerations prevent manufacturers from manipulating package size in ways that seem designed to trick consumers. Third, many services are also offered as packages, and also involve uncertainty, so the effects identified here are likely to be pervasive throughout the consumer economy.
ContributorsYonezawa, Koichi (Author) / Richards, Timothy J. (Thesis advisor) / Grebitus, Carola (Committee member) / Park, Sungho (Committee member) / Arizona State University (Publisher)
Created2014
Description
This dissertation applies the Bayesian approach as a method to improve the estimation efficiency of existing econometric tools. The first chapter suggests the Continuous Choice Bayesian (CCB) estimator which combines the Bayesian approach with the Continuous Choice (CC) estimator suggested by Imai and Keane (2004). Using simulation study, I provide two important findings. First, the CC estimator clearly has better finite sample properties compared to a frequently used Discrete Choice (DC) estimator. Second, the CCB estimator has better estimation efficiency when data size is relatively small and it still retains the advantage of the CC estimator over the DC estimator. The second chapter estimates baseball's managerial efficiency using a stochastic frontier function with the Bayesian approach. When I apply a stochastic frontier model to baseball panel data, the difficult part is that dataset often has a small number of periods, which result in large estimation variance. To overcome this problem, I apply the Bayesian approach to a stochastic frontier analysis. I compare the confidence interval of efficiencies from the Bayesian estimator with the classical frequentist confidence interval. Simulation results show that when I use the Bayesian approach, I achieve smaller estimation variance while I do not lose any reliability in a point estimation. Then, I apply the Bayesian stochastic frontier analysis to answer some interesting questions in baseball.
ContributorsChoi, Kwang-shin (Author) / Ahn, Seung (Thesis advisor) / Mehra, Rajnish (Committee member) / Park, Sungho (Committee member) / Arizona State University (Publisher)
Created2014