Essays on city size distribution and real estate bubbles

This is a dissertation about urban systems; within this broad subject I tackle three issues, one that focuses on an observed inter-city relationship and two that focus on an intra-city phenomenon. In Chapter II I adapt a model of random emergence of economic opportunities from the firm growth literature to the urban dynamics situation and present several predictions for urban system dynamics. One of these predictions is that the older the city the larger and more diversified it is going to be on average, which I proceed to verify empirically using two distinct datasets. In Chapter III I analyze the Residential Real Estate Bubble that took place in Miami-Dade County from 1999 to 2006. I adopt a Spatial-Economic model developed for the Paris Bubble episode of 1984–1993 and formulate an innovative test of the results in terms of speculative intensity on the basis of proxies of investor activity available in my dataset. My results support the idea that the best or more expensive areas are also where the greatest speculative activity takes place and where the rapid increase in prices begins. The most significant departure from previous studies that emerges in my results is the absence of a wider gap between high priced areas and low priced areas in the peak year. I develop a measure of dispersion in value among areas and contrast the Miami-Dade and Paris episodes. In Chapter IV I analyze the impact on tax equity of a Florida tax-limiting legislation known as Save Our Homes. I first compare homesteaded and non-homesteaded properties, and second, look within the subset of homesteaded properties. I find that non-homesteaded properties increase their share of taxes paid relative to homesteaded properties during an up market, but that this is reversed during a down market. For the subset of homesteaded properties I find that the impact on tax equity of SOH will depend on differential growth rates among higher and lower valued homes, but during times of rapid home price appreciation, in a scenario of no differential growth rates in property values, SOH increases progressivity relative to the prior system.

Securitization of Lodging Real Estate Finance

In the early 1990s, the U.S. lodging industry witnessed a severe shortage of debt capital as traditional lenders exited the market. During this period hotel lending was revolutionized by the emergence of real estate debt securities. The author discusses key factors which have affected the growth and development of commercial mortgage backed securities and their changing role as a significant source of debt capital to the lodging industry.

Lodging Real Estate Finance: Securitization

Commercial Mortgage Backed Securities (CMBSs) introduced to the U.S. lodging industry in the early 1990’s were a panacea during a period of severe shortage of debt capital. These instruments changed commercial real estate capital markets by providing flexibility and liquidity to an otherwise illiquid investment As a relatively new form of financing to the lodging industry, the mechanics of securitization, the types of CMBS investments, and their structure are not well understood. The article illustrates the process of securitization and its importance as a significant source of debt financing to the lodging industry

A study of stock market fluctuations and their relation to business conditions

Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubblelike deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the nonfundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.

A Study of Stock Market Fluctuations and their Relations to Business Conditions

Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubble-like deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the non-fundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.

Travel Marketing: Industry Relationships and Benefits

In the discussion - Travel Marketing: Industry Relationships and Benefits - by Andrew Vladimir, Visiting Assistant Professor, School of Hospitality Management at Florida International University, the author initially states: “A symbiotic relationship exists among the various segments of the travel and tourism industry. The author has solicited the thinking of 37experts and leaders in the field in a book dealing with these relationships and how they can be developed to benefit the industry. This article provides some salient points from those contributors.” This article could be considered a primer on networking for the hospitality industry. It has everything to do with marketing and the relationships between varied systems in the field of travel and tourism. Vladimir points to instances of success and failure in marketing for the industry at large. And there are points of view from thirty-seven contributing sources here. “Miami Beach remains a fitting example of a leisure product that has been unable to get its act together,” Vladimir shares a view. “There are some first class hotels, a few good restaurants, alluring beaches, and a splendid convention center, but there is no synergism between them, no real affinity, and so while visitors admire the Fontainebleau Hilton and enjoy the food at Joe's Stone Crabs, the reputation of Miami Beach as a resort remains sullied,” the author makes a point. In describing cohesiveness between exclusive systems, Vladimir says, “If each system can get a better understanding of the inner workings of neighboring related systems, each will ultimately be more successful in achieving its goals.” The article is suggesting that exclusive systems aren’t really exclusive at all; or at least they shouldn’t be. In a word – competition – drives the market, and in order for a property to stay afloat, aggressive marketing integrated with all attendant resources is crucial. “Tisch [Preston Robert Tisch, currently – at the time of this writing - the Postmaster General of the United States and formerly president of Lowe’s Hotels and the New York Visitors and Convention Bureau], in talking about the need for aggressive marketing says: “Never...ever...take anything for granted. Never...not for a moment...think that any product or any place will survive strictly on its own merits.” Vladimir not only sources several knowledgeable representatives in the field of hospitality and tourism, but he also links elements as disparate as real estate, car rental, cruise and airlines, travel agencies and traveler profiles to illustrate his points on marketing integration. In closing, Vladimir quotes the Honorable Donna Tuttle, Undersecretary of Commerce for Travel and Tourism, “Uniting the components of this industry in an effective marketing coalition that can compete on an equal footing with often publicly-owned foreign tourism conglomerates and multi-national consortia must be a high priority as the United States struggles to maintain and expand its share of a rapidly changing global market.”

Maximum Justifiable Investment Analysis Determines Property Valuation

Investors and developers are often faced with the task of determining the worth or value of a real estate entity that presently exists or is proposed for development. This article explains the process for determining the value of a proposed project and, subsequently, the maximum investment dollars the project can cover, while at the same time producing a reasonable return for the investor. A proposed 300-room hotel serves as the real estate entity to be analyzed.