Knowledge of the investment risk of investment-grade commercial real estate (‘ICRE’) is important because it determines the approaches which should be taken to portfolio management. However, relatively little is known about this risk. This research expands the body of knowledge of ICRE investment risk by producing conclusions about the information content of prices and the distribution of returns in the ICRE context. It is broken into three main parts. First, the ICRE returns-generating process is characterised to form a basis for deducing theoretical conclusions about the information content of prices and the stochastic attributes of returns. The rationale for this approach lies in capital markets literature, which demonstrates that the characteristics of the information structure of markets, the decision-making processes of investors and the market trading mechanism determine the main attributes of the process of price evolution (which is assumed to be the main driver of returns). The analysis concludes that ICRE prices are partially informed, and changes in prices are described by a ‘jump’ process. Second, analysis of a database of ‘large’ price changes supplied by the Property Council of Australia is undertaken to empirically test the jump process hypothesis. This analysis provides evidence that natural events associated with changes in the leasing structure of properties are a primary driver of relatively large, infrequent dislocations in valuation-based prices. With parts one and two as a backdrop, the third part of this research empirically tests a discrete mixture of normals (‘DMON’) model of investment risk. Capital markets research shows that a DMON model flows naturally from jump price processes. DMON models fitted to cross-sectional returns on individual properties supplied by the PCA are found to be superior to the normal and stable Paretian models previously proposed by other researchers. In aggregate these conclusions have serious implications for the management of ICRE portfolios, and suggest a need for additional research. Some implications include: (1) Mean-lower partial variance is superior to mean-variance optimisation. (2) Forecasting the distribution of ICRE returns forms a new tool for active management. (3) Passive portfolio management is inappropriate. (4) Comparables-based valuations may be unreliable for investment decisions. / Subscription resource available via Digital Dissertations only.

Knowledge of the investment risk of investment-grade commercial real estate (‘ICRE’) is important because it determines the approaches which should be taken to portfolio management. However, relatively little is known about this risk. This research expands the body of knowledge of ICRE investment risk by producing conclusions about the information content of prices and the distribution of returns in the ICRE context. It is broken into three main parts. First, the ICRE returns-generating process is characterised to form a basis for deducing theoretical conclusions about the information content of prices and the stochastic attributes of returns. The rationale for this approach lies in capital markets literature, which demonstrates that the characteristics of the information structure of markets, the decision-making processes of investors and the market trading mechanism determine the main attributes of the process of price evolution (which is assumed to be the main driver of returns). The analysis concludes that ICRE prices are partially informed, and changes in prices are described by a ‘jump’ process. Second, analysis of a database of ‘large’ price changes supplied by the Property Council of Australia is undertaken to empirically test the jump process hypothesis. This analysis provides evidence that natural events associated with changes in the leasing structure of properties are a primary driver of relatively large, infrequent dislocations in valuation-based prices. With parts one and two as a backdrop, the third part of this research empirically tests a discrete mixture of normals (‘DMON’) model of investment risk. Capital markets research shows that a DMON model flows naturally from jump price processes. DMON models fitted to cross-sectional returns on individual properties supplied by the PCA are found to be superior to the normal and stable Paretian models previously proposed by other researchers. In aggregate these conclusions have serious implications for the management of ICRE portfolios, and suggest a need for additional research. Some implications include: (1) Mean-lower partial variance is superior to mean-variance optimisation. (2) Forecasting the distribution of ICRE returns forms a new tool for active management. (3) Passive portfolio management is inappropriate. (4) Comparables-based valuations may be unreliable for investment decisions. / Subscription resource available via Digital Dissertations only.

Knowledge of the investment risk of investment-grade commercial real estate (‘ICRE’) is important because it determines the approaches which should be taken to portfolio management. However, relatively little is known about this risk. This research expands the body of knowledge of ICRE investment risk by producing conclusions about the information content of prices and the distribution of returns in the ICRE context. It is broken into three main parts. First, the ICRE returns-generating process is characterised to form a basis for deducing theoretical conclusions about the information content of prices and the stochastic attributes of returns. The rationale for this approach lies in capital markets literature, which demonstrates that the characteristics of the information structure of markets, the decision-making processes of investors and the market trading mechanism determine the main attributes of the process of price evolution (which is assumed to be the main driver of returns). The analysis concludes that ICRE prices are partially informed, and changes in prices are described by a ‘jump’ process. Second, analysis of a database of ‘large’ price changes supplied by the Property Council of Australia is undertaken to empirically test the jump process hypothesis. This analysis provides evidence that natural events associated with changes in the leasing structure of properties are a primary driver of relatively large, infrequent dislocations in valuation-based prices. With parts one and two as a backdrop, the third part of this research empirically tests a discrete mixture of normals (‘DMON’) model of investment risk. Capital markets research shows that a DMON model flows naturally from jump price processes. DMON models fitted to cross-sectional returns on individual properties supplied by the PCA are found to be superior to the normal and stable Paretian models previously proposed by other researchers. In aggregate these conclusions have serious implications for the management of ICRE portfolios, and suggest a need for additional research. Some implications include: (1) Mean-lower partial variance is superior to mean-variance optimisation. (2) Forecasting the distribution of ICRE returns forms a new tool for active management. (3) Passive portfolio management is inappropriate. (4) Comparables-based valuations may be unreliable for investment decisions. / Subscription resource available via Digital Dissertations only.

Knowledge of the investment risk of investment-grade commercial real estate (‘ICRE’) is important because it determines the approaches which should be taken to portfolio management. However, relatively little is known about this risk. This research expands the body of knowledge of ICRE investment risk by producing conclusions about the information content of prices and the distribution of returns in the ICRE context. It is broken into three main parts. First, the ICRE returns-generating process is characterised to form a basis for deducing theoretical conclusions about the information content of prices and the stochastic attributes of returns. The rationale for this approach lies in capital markets literature, which demonstrates that the characteristics of the information structure of markets, the decision-making processes of investors and the market trading mechanism determine the main attributes of the process of price evolution (which is assumed to be the main driver of returns). The analysis concludes that ICRE prices are partially informed, and changes in prices are described by a ‘jump’ process. Second, analysis of a database of ‘large’ price changes supplied by the Property Council of Australia is undertaken to empirically test the jump process hypothesis. This analysis provides evidence that natural events associated with changes in the leasing structure of properties are a primary driver of relatively large, infrequent dislocations in valuation-based prices. With parts one and two as a backdrop, the third part of this research empirically tests a discrete mixture of normals (‘DMON’) model of investment risk. Capital markets research shows that a DMON model flows naturally from jump price processes. DMON models fitted to cross-sectional returns on individual properties supplied by the PCA are found to be superior to the normal and stable Paretian models previously proposed by other researchers. In aggregate these conclusions have serious implications for the management of ICRE portfolios, and suggest a need for additional research. Some implications include: (1) Mean-lower partial variance is superior to mean-variance optimisation. (2) Forecasting the distribution of ICRE returns forms a new tool for active management. (3) Passive portfolio management is inappropriate. (4) Comparables-based valuations may be unreliable for investment decisions. / Subscription resource available via Digital Dissertations only.

Knowledge of the investment risk of investment-grade commercial real estate (‘ICRE’) is important because it determines the approaches which should be taken to portfolio management. However, relatively little is known about this risk. This research expands the body of knowledge of ICRE investment risk by producing conclusions about the information content of prices and the distribution of returns in the ICRE context. It is broken into three main parts. First, the ICRE returns-generating process is characterised to form a basis for deducing theoretical conclusions about the information content of prices and the stochastic attributes of returns. The rationale for this approach lies in capital markets literature, which demonstrates that the characteristics of the information structure of markets, the decision-making processes of investors and the market trading mechanism determine the main attributes of the process of price evolution (which is assumed to be the main driver of returns). The analysis concludes that ICRE prices are partially informed, and changes in prices are described by a ‘jump’ process. Second, analysis of a database of ‘large’ price changes supplied by the Property Council of Australia is undertaken to empirically test the jump process hypothesis. This analysis provides evidence that natural events associated with changes in the leasing structure of properties are a primary driver of relatively large, infrequent dislocations in valuation-based prices. With parts one and two as a backdrop, the third part of this research empirically tests a discrete mixture of normals (‘DMON’) model of investment risk. Capital markets research shows that a DMON model flows naturally from jump price processes. DMON models fitted to cross-sectional returns on individual properties supplied by the PCA are found to be superior to the normal and stable Paretian models previously proposed by other researchers. In aggregate these conclusions have serious implications for the management of ICRE portfolios, and suggest a need for additional research. Some implications include: (1) Mean-lower partial variance is superior to mean-variance optimisation. (2) Forecasting the distribution of ICRE returns forms a new tool for active management. (3) Passive portfolio management is inappropriate. (4) Comparables-based valuations may be unreliable for investment decisions. / Subscription resource available via Digital Dissertations only.

Doctor of Philosophy / Department of Economics / Lance Bachmeier / This dissertation consists of one essay in financial econometrics and two essays in quantitative industrial organization. The first essay studies the relationship between stock return volatility and current and prior shocks to oil price volatility. We study the behavior of aggregate stock markets as well as individual industry sectors. Our results show that lagged stock return volatility is the main determinant of current stock return volatility in aggregate markets, with oil price volatility providing no additional information that can be used to forecast stock return volatility. For individual industry sectors, we find a robust and stable prediction relationship only for the chemicals industry. Additional estimation exercises confirm the robustness of these results. The second essay uses a Bertrand-Nash price-competition framework to models a vertically integrated provider (VIP) that is a monopoly supplier of an essential input for downstream production. An input price that is “too high” can lead to inefficient foreclosure and one that is “too low” creates incentives for nonprice discrimination. The range of non-exclusionary input prices is circumscribed by the input prices generated on the basis of upper-bound and lower-bound displacement ratios. The admissible range of the ratio of downstream to upstream “price-cost” margins for the VIP is increasing in the degree of product differentiation and reduces to a single ratio in the limit as the products become perfectly homogeneous. The third essay explores the relationship between upstream input prices and downstream market exclusion under a Stackelberg quantity-competition framework. Market exclusion is a concern when input prices are “too high” and “too low” because it can result in inefficient foreclosure and sabotage, respectively. Consistent with the results obtained in the second essay, the safe harbor range of downstream to upstream “price-cost” margin ratios is decreasing in the degree of product homogeneity and approaches a single ratio in the limit as the products become perfectly homogeneous. This single margin ratio preserves equality between the VIP’s wholesale and retail “price-cost” margins. A key finding for competition policy is that the bounds of non-exclusionary input prices are markedly wider under Bertrand-Nash competition than they are under Stackelberg competition. Hence, it is critical that the antitrust and regulatory authorities understand the nature of the industry competition so that rules governing permissible conduct are properly calibrated to yield efficient outcomes.

Doctor of Philosophy / Department of Agricultural Economics / Brian C. Briggeman / U.S. farm profitability is near historic highs. This fact raises many questions related to the economics of production agriculture. Three questions are examined in this dissertation. First, should farmers use a different benchmark for farm profitability? To answer this question, a benchmark of farm profitability is developed that adds balance sheet information to an established benchmark which uses only income statement data. The second and third questions focus on cooperatives since farmers rely on efficient cooperative management to maximize their return on investment in the cooperative and their own farm profitability. How should cooperatives allocate earnings to farmers? To answer this question, a model is developed to inform boards of directors regarding optimal equity allocation decisions. Finally, do cooperatives face agency costs? To answer this question, a variable cost model is estimated to examine the indirect costs of leverage. The first essay used data from Kansas farms to determine the effects of the use of debt on cost efficiency. A nonparametric cost efficiency model was used to examine these effects. Results indicated that farms which were more specialized, had higher capital costs, and used more equity to finance assets experienced larger increases in efficiency when the use of debt was included in the analysis. The second essay used information on effective tax rates and empirically-estimated risk aversion coefficients in a portfolio model to determine the effects of different tax rates on the distribution of earnings. Results indicated that even a large deviation in current effective tax rates is not likely to affect the optimal share of allocated earnings. However, member risk preferences had an economically significant effect on the optimal share of allocated earnings, suggesting that board members focus on understanding member risk preferences. The third essay used data from U.S. agricultural cooperatives to determine the presence of agency costs due to the use of debt. A variable cost function was estimated to generate an index of variable cost efficiency which was used to determine the indirect costs of leverage. A negative relationship between debt and variable cost efficiency was found, indicating that agency costs were present for agricultural cooperatives.

Master of Arts / Department of Economics / Tracy Turner / I analyze the impact of differences in the cigarette excise tax rates of bordering states on the price elasticity of demand for cigarettes in the home state. Using unique county-level data on the sales tax revenues collected from Kansas tobacco sellers by industry type provided by the Kansas Department of Revenue, as well as data on cigarette excise tax rates, distance to Kansas’ borders, and the combined state and county sales tax rate, I examine the determinants of tobacco sales tax revenue using a fixed effects model. The analysis allows me to infer cigarette demand effects, and I find that the price elasticity of demand for cigarettes in Kansas becomes significantly more elastic closer to a low tax border. Model estimates for gas stations with convenience stores and tobacco retailers suggest that a Kansas cigarette excise tax decrease would result in more sales tax revenue on average for counties within 50 miles of a low tax Kansas border, ceteris paribus.

Master of Science / Department of Statistics / Shie-Shien Yang / Many nonstationary univariate time series can be made stationary by appropriate differencing before ARMA models are fitted to the differenced series. However, when it comes to nonstationary vector time series, the situation is more complex. Since the dynamic of a multivariate time series is multidimensional, even if we can make each component stationary by appropriate differencing, the vector process of the differenced components may be still nonstationary. However, it is possible that the projections of a nonstationary vector time series in some directions may result in a stationary process. Engle and Granger(1987) formally demonstrated that it is possible for some linear combinations of the components of nonstationary vector time series to be stationary. They called this phenomenon Co-Integration. This concept of cointegration turned out to be extremely important in the modeling and analysis of non-stationary time series in economics. Although economic variables individually may exhibit disequilibrium behaviors, often time, due to economic forces, these disequilibrium economic variables corporately form a dynamic equilibrium relationship. Specifically, certain linear combinations of nonstationary time series may appear to be stationary. Engle and Granger developed statistical method for detecting and estimating this equilibrium relationship. They also proposed the so called error correction model to model Co-Integrated vector time series. In this report, I give a detail review on the concept of cointegration, the 2-step estimation procedure for the error correction models, and the 7 types of tests for testing cointegration. Since the test statistics for testing cointegration do not follow any known distribution, critical values were obtained based on two models by Engle and Granger. Augmented Dickey-Fuller and Dickey-Fuller tests were recommended as it is believed that their distributions are independent of the under lying process model. The critical values table presented in their paper is widely used in testing cointegration. In this report, we'll construct tables of critical values based on different models and compare them with those obtained by Engle and Granger. Also, to demonstrate the practical usage of cointegration, applications to currency exchange rates and US stock and Asian stock indexes are presented as illustrative examples.

Doctor of Philosophy / Department of Economics / Lance J. Bachmeier / Dong Li / For a unique sample of Israeli stocks that went public in the U.S. and then cross-listed in the home market, Tel Aviv Stock Exchange (TASE), this dissertation consists of three essays examining the dynamics of return spillovers and volume-return interactions across markets and the valuation effect around the event of cross-listing and delisting from the home market. In Chapter II, I investigate the role of trading volume in the information flow and return spillovers between the U.S. and Israeli markets. Findings suggest that the dynamics of volume-return interactions across markets can provide us with valuable information regarding future price movements, which can be a useful tool to predict future returns. I also find the home market to dominate the host market in pricing these stocks, which is consistent with the Home Bias hypothesis. In Chapter III, I analyze the impact of the event of cross-listing on stock returns and risk exposure. The behavior of abnormal returns around the cross-listing date implies that cross-listing in TASE is an effective mechanism in reducing market segmentation between the U.S. and the Israeli capital markets. Risk assessment following the cross-listing suggests a decline firms’ overall risk exposure, indicating a higher degree of integration between the two markets due to cross-listing. In Chapter IV, I evaluate changes in the cost-of-capital for Israeli firms after delisting voluntary from TASE, the home market, while maintaining their listing in the U.S., the host market. The results show a significant positive shift in U.S. and negative shift in Israeli market risk exposure after the delisting. These results indicate that firms delisting form their home market (TASE), face greater risk exposure, higher required returns on their stocks and, hence, higher cost-of-capital after delisting.