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In order to cope with the decreasing availability of symphony jobs and collegiate faculty positions, many musicians are starting to pursue less traditional career paths. Also, to combat declining audiences, musicians are exploring ways to cultivate new and enthusiastic listeners through relevant and engaging performances. Due to these challenges, many…

In order to cope with the decreasing availability of symphony jobs and collegiate faculty positions, many musicians are starting to pursue less traditional career paths. Also, to combat declining audiences, musicians are exploring ways to cultivate new and enthusiastic listeners through relevant and engaging performances. Due to these challenges, many community-based chamber music ensembles have been formed throughout the United States. These groups not only focus on performing classical music, but serve the needs of their communities as well. The problem, however, is that many musicians have not learned the business skills necessary to create these career opportunities. In this document I discuss the steps ensembles must take to develop sustainable careers. I first analyze how groups build a strong foundation through getting to know their communities and creating core values. I then discuss branding and marketing so ensembles can develop a public image and learn how to publicize themselves. This is followed by an investigation of how ensembles make and organize their money. I then examine the ways groups ensure long-lasting relationships with their communities and within the ensemble. I end by presenting three case studies of professional ensembles to show how groups create and maintain successful careers. Ensembles must develop entrepreneurship skills in addition to cultivating their artistry. These business concepts are crucial to the longevity of chamber groups. Through interviews of successful ensemble members and my own personal experiences in the Tetra String Quartet, I provide a guide for musicians to use when creating a community-based ensemble.

ContributorsDalbey, Jenna (Author) / Landschoot, Thomas (Thesis advisor) / McLin, Katherine (Committee member) / Ryan, Russell (Committee member) / Solis, Theodore (Committee member) / Spring, Robert (Committee member) / Arizona State University (Publisher)

Created2013

Dissertation on generalized empirical likelihood estimators

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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…

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

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