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dc.contributor.advisorGlenn Ellison.en_US
dc.contributor.authorChiou, Lesley Cen_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Economics.en_US
dc.date.accessioned2007-08-03T15:36:19Z
dc.date.available2007-08-03T15:36:19Z
dc.date.copyright2005en_US
dc.date.issued2005en_US
dc.identifier.urihttp://dspace.mit.edu/handle/1721.1/33838en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/33838
dc.descriptionThesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Economics, 2005.en_US
dc.descriptionIncludes bibliographical references.en_US
dc.description.abstractIn this dissertation, I present three empirical essays that encompass topics in industrial organization. The first essay examines the degree of competition and spatial differentiation in the retail industry by exploiting a unique dataset that describes a consumer's choice of store, product of purchase, item price, and demographics. I estimate a consumer's choice of retailer in the sales market for DVDs among online, mass merchant, electronics, video specialty, and music stores, and I allow for unobserved heterogeneity in preferences for store types and disutility of travel. A consumer's traveling cost varies by income, and substitution occurs proportionately more among stores of the same type. The second essay investigates an intriguing puzzle in the movie industry: "why do studios cluster their big theatrical hits during the July 4th weekend?" A series of recent papers by Einav (2002) indicate that although the underlying demand for theatrical movies remains high around Labor Day, studios tend to release their high quality movies at the beginning of the summer. I employ data from the home video industry to provide more evidence on whether booms in theatrical revenues are supply- or demand-driven and to investigate why firms might cluster their releases as they do.en_US
dc.description.abstract(cont.) The third essay presents examples based on actual and synthetic datasets to illustrate how simulation methods can often mask identification problems in the estimation of mixed logit models. Typically, simulation methods approximate an integral (that does not have a closed form) by taking draws from the underlying distribution of the random variable of integration. The examples reveal how a "low" number of draws can generate estimates that appear identified, but in fact, are either not theoretically identified by the model or not empirically identified by the data. The number of draws required to reveal the identification problem will depend on the data, model, and type of draws used. These examples emphasize the importance of checking the stability of the estimates with respect to the number of draws.en_US
dc.description.statementofresponsibilityby Lesley C. Chiou.en_US
dc.format.extent121 leavesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/33838en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582
dc.subjectEconomics.en_US
dc.titleEmpirical essays in industrial organizationen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Economics
dc.identifier.oclc65431420en_US


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