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This dissertation adds to the literature on least squares model averaging by studying and extending current least squares model averaging techniques. The first chapter reviews existing literature and discusses the contributions of this dissertation. The second chapter proposes a new estimator for least squares model averaging. A model average estimator is a weighted average of common estimates obtained from a set of models. I propose computing weights by minimizing a model average prediction criterion (MAPC). I prove that the MAPC estimator is asymptotically optimal in the sense of achieving the lowest possible mean squared error. For statistical inference, I derive asymptotic tests on the average coefficients for the "core" regressors. These regressors are of primary interest to researchers and are included in every approximation model. In Chapter Three, two empirical applications for the MAPC method are conducted. I revisit the economic growth models in Barro (1991) in the first application. My results provide significant evidence to support Barro's (1991) findings. In the second application, I revisit the work by Durlauf, Kourtellos and Tan (2008) (hereafter DKT). Many of my results are consistent with DKT's findings and some of my results provide an alternative explanation to those outlined by DKT. In the fourth chapter, I propose using the model averaging method to construct optimal instruments for IV estimation when there are many potential instrument sets. The empirical weights are computed by minimizing the model averaging IV (MAIV) criterion through convex optimization. I propose a new loss function to evaluate the performance of the estimator. I prove that the instrument set obtained by the MAIV estimator is asymptotically optimal in the sense of achieving the lowest possible value of the loss function. The fifth chapter develops a new forecast combination method based on MAPC. The empirical weights are obtained through a convex optimization of MAPC. I prove that with stationary observations, the MAPC estimator is asymptotically optimal for forecast combination in that it achieves the lowest possible one-step-ahead second-order mean squared forecast error (MSFE). I also show that MAPC is asymptotically equivalent to the in-sample mean squared error (MSE) and MSFE. / Thesis (Ph.D, Economics) -- Queen's University, 2013-07-17 15:46:54.442

This research utilizes the Model for Marketing in Small Professional Service Firms, based on Carson's Model for the Development of Small Firm Marketing, to examine the marketing of Physician Services in Puerto Rico. To achieve its objectives, a combination of quantitative(survey) and qualitative (cases) research is used. From the literature a series of statements is generated to form hypotheses that are tested utilizing the results of a questionnaire survey of 105 physicians in Puerto Rico. The results suggest a possible change of attitude of service providers towards marketing and its use. They reveal that physicians in Puerto Rico are in agreement with the marketing concept but most do not adopt "traditional" techniques of marketing- preferring to focus on the physician/patient relationship. Analysis of eight cases demonstrates the importance of this relationship and suggests that though is seen as important in attracting and retaining patients, most physicians do not see this as marketing, which is perceived to be mostly "advertising" and "selling." Many are cautious not to "commercialise" their practice and any differences in their behaviour can be explained by the way they believe the physician/patient relationship is best enhanced. The research proposes a Model for Marketing Solo Professional Service Firms that depicts the_ relation between the changes, over time, in the personal life cycle of the service provider/owner manager and the stages in the life cycle of the business practice. The model suggests that throughout there is a need to focus on one aspect of marketing for the practice, which may change over time, and that the elements determining the marketing activities at a particular time, how they are undertaken and why they are utilised, are constantly evolving. Thus the marketing practices of small professional firms appear to be contingent on both the external and internal environment of the practice.

Chinese tallow tree (Triadica sebifera (L.)) has become a threat to Southern United States forestlands because of the rapid colonization. To explore the growth rate of tallow, numerous growth models were constructed with destructive sampling method from oak-gum-cypress (Quercus/Liquidambar styraciflua/Taxodium distichum) and longleaf/slash pine (Pinus taeda/ Pinus echinata) forests in southern Mississippi. Moreover, stem profile was also fitted with segmented profile models: Max and Burkhart (1976), Cao (2009) modified Max and Burkhart, and Clark et al. (1991). Numerous results showed that: 1) diameter at breast height, volume and biomass of tallow grew faster in oak-gum-cypress forest while height grew faster with DBH in Longleaf/Slash pine forest; 2) the stem of tallow was generally sturdy in oak-gum-cypress forest while it was slender in longleaf/slash pine forest; however, there was no significant difference between them. Growth and taper models provide a tool for managers to estimate future stocking of tallow tree.

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In endogenous growth models, in contrast to the neoclassical growth models, government expenditure and taxation have an effect on the long run growth rate. In this thesis I examine whether the empirical evidence support the predictions of endogenous growth models or the neoclassical growth models in relation to fiscal policy. For this purpose I use panel data for fifteen European Union (EU) member and thirty-three developing countries between the years 1970 and 1999. I specifically test the following two propositions. The first proposition states that distortionary taxation decreases growth while non-distortionary taxation does not. The second, states that productive government expenditure increases growth while non-productive expenditure does not. The empirical results are quite different between European Union countries and developing countries. The results do not support endogenous growth especially for developing countries.

This thesis consists of an introduction and five research papers on topics related to conformal mapping, the Loewner equation and its applications, and Bergman-type spaces of holomorphic functions. The first two papers are devoted to the study of integral means of derivatives of conformal mappings. In Paper I, we present improved upper estimates of the universal means spectrum of conformal mappingsof the unit disk. These estimates rely on inequalities  obtained by Hedenmalm and Shimorin using Bergman space techniques, and on computer calculations. Paper II is a survey of recent results on the universal means spectrum, with particular emphasis on Bergman spacetechniques.Paper III concerns Bergman-type spaces of holomorphic functions in subsets of $\textbf{C}^d$ and their reproducing kernel functions. By expanding the norm of a function in a Bergman space along the zero variety of a polynomial, we obtain a series expansion of reproducing kernel functions in terms of kernels associated with lower-dimensionalspaces of holomorphic functions. We show how this general approach can be used to explicitly compute kernel functions for certain weighted Bergman and Bargmann-Fock spaces defined in domains in $\textbf{C}^2$.The last two papers contribute to the theory of Loewner chains and theirapplications in the analysis of planar random growth model defined in terms of compositions of conformal maps.In Paper IV, we study Loewner chains generated by unimodular L\'evy processes.We first establish the existence of a capacity scaling limit for the associated growing hulls in terms of whole-plane Loewner chains driven by a time-reversed process. We then analyze the properties of Loewner chains associated with a class of two-parameter compound Poisson processes, and we describe the dependence of the geometric properties of the hulls on the parameters of the driving process. In Paper V, we consider a variation of the Hastings-Levitov growth model, with anisotropic growth. We again establish results concerning scaling limits, when the number of compositions increases and the basic conformal mappings tends to the identity. We show that the resulting limit sets can be associated with solutions to the Loewner equation.We also prove that, in the limit, the evolution of harmonic measure on the boundary is deterministic and is determined by the flow associated with an ordinary differential equation, and we give a description of the fluctuations around this deterministic limit flow. / <p>QC 20100414</p>

In this thesis, we will relax two major assumptions in economic growth theory. First of all, we will study growth models with eterogeneous capital goods, the so called vintage capital models: technological advances are not incorporated in all generations of capital goods and there is an optimal age distribution of the capital stocks. We will devote the three first chapters of this thesis to this class of models. Several lessons on technology diffusion will be extracted, notably in connection with the nowadays hot debate on energy saving, technology progress, growth and environmental policy. Secondly, we will introduce explicitly the geographical dimension to the neoclassical growth models, which allow us to build a new class of models. We call them geographic growth models. In this framework, we will identify the consequences of capital mobility across space. In particular, we will examine the optimal stationary distribution of capital across space. Under this framework, we could (i) study the continuous space structure, and (ii) allow capital accumulation.