On the fundamentals of research and development (R&D) spillovers in competitive markets

Rivals may voluntarily share Research and Development (R&D) results even in the absence of any binding agreements or collusion. In a model where rival firms engage in non-cooperative independent R&D process, we used optimization and game theory analysis to study the equilibrium strategy of the firms. Our work showed that, while minimal spillover is always equilibrium, there may be another equilibrium where firms may reciprocally choose high, sometimes perfect, spillover rates. The incentive for sharing R&D output is based on firms' expectations of learning from their rivals' R&D progress in the future. This leads to strategic complementarities between the firms' choices of spillover rates and thus policy implication follows. ^ Public research agencies can contribute more to social welfare by providing research as public goods. In a non-cooperative public-private research relationship where parallel R&D is conducted, by making its R&D results accessible, the public research agency can stimulate private spillovers, even if there exists rivalry among the private firms who can benefit from such spillovers. ^

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.

The use of computer graphic organizers for narrative writing by elementary school students with Specific Learning Disabilities

Writing is an academic skill critical to students in today's schools as it serves as a predominant means for demonstrating knowledge during school years (Graham, 2008). However, for many students with Specific Learning Disabilities (SLD), learning to write is a challenging, complex process (Lane, Graham, Harris, & Weisenbach, 2006). Students SLD have substantial writing challenges related to the nature of their disability (Mayes & Calhoun, 2005). ^ This study investigated the effects of computer graphic organizer software on the narrative writing compositions of four, fourth- and fifth-grade, elementary-level boys with SLD. A multiple baseline design across subjects was used to explore the effects of the computer graphic organizer software on four dependent variables: total number of words, total planning time, number of common story elements, and overall organization. ^ Prior to baseline, participants were taught the fundamentals of narrative writing. Throughout baseline and intervention, participants were read a narrative writing prompt and were allowed up to 10 minutes to plan their writing, followed by 15 minutes for writing, and 5 minutes of editing. During baseline, all planning was done using paper and pencil. During intervention, planning was done on the computer using a graphic organizer developed from the software program Kidspiration 3.0 (2011). All compositions were written and editing was done using paper and pencil during baseline and intervention. ^ The results of this study indicated that to varying degrees computer graphic organizers had a positive effect on the narrative writing abilities of elementary aged students with SLD. Participants wrote more words (from 54.74 to 96.60 more), planned for longer periods of time (from 4.50 to 9.50 more minutes), and included more story elements in their compositions (from 2.00 to 5.10 more out of a possible 6). There were nominal to no improvements in overall organization across the 4 participants. ^ The results suggest that teachers of students with SLD should considering use computer graphic organizers in their narrative writing instruction, perhaps in conjunction with remedial writing strategies. Future investigations can include other types of writing genres, other stages of writing, participants with varied demographics and their use combined with remedial writing instruction. ^

Essays in economic growth, political economy and institutions

This dissertation analyzes the effects of political and economic institutions on economic development and growth.^ The first essay develops an overlapping-generations political economy model to analyze the incentives of various social groups to finance human capital accumulation through public education expenditures. The contribution of this study to the literature is that it helps explain the observed differences in the economic growth performance of natural resource-abundant countries. The results suggest that the preferred tax rates of the manufacturers on one hand and the political coalition of manufacturers and landowners, on the other hand, are equal to the socially optimal tax rate. However, we show that owners of natural resources prefer an excessively high tax rate, which suppresses aggregate output to a suboptimal level.^ The second essay examines the relationship between the political influence of different social classes and public education spending in panel data estimation. The novel contribution of this paper to the literature is that I proxy the political power and influence of the natural resource owners, manufacturers, and landowners with macroeconomic indicators. The motivation behind this modeling choice is to substantiate the definition of the political power of social classes with economic fundamentals. I use different governance indicators in the estimations to find out how different institutions mediate the overall impact of the political influence of various social classes on public education spending. The results suggest that political stability and absence of violence and rule of law are the important governance indicators.^ The third essay develops a counter argument to Acemoglu et al. (2010) where the thesis is that French institutions and economic reforms fostered economic progress in those German regions invaded by the Napoleonic armies. By providing historical data on urbanization rates used as proxies for economic growth, I demonstrate that similar different rates of economic growth were observed in the regions of France in the post-Napoleonic period as well. The existence of different economic growth rates makes it hard to argue that the differences in economic performance in the German regions that were invaded by the French and those that were spared a similar fate follow from regional differences in economic institutions.^

Hypertension, poor glycemic control, and microalbuminuria in Cuban Americans with type 2 diabetes

Purpose: To investigate to what degree the presence of hypertension (HTN) and poor glycemic control (GC) influences the likelihood of having microalbuminuria (MAU) among Cuban Americans with type 2 diabetes (T2D).Methods: A cross-sectional study conducted in Cuban Americans (n = 179) with T2D. Participants were recruited from a randomly generated mailing list purchased from KnowledgeBase Marketing, Inc. Blood pressure (BP) was measured twice and averaged using an adult size cuff. Glycosylated hemoglobin (A1c) levels were measured from whole blood samples with the Roche Tina-quant method. First morning urine samples were collected from each participant to determine MAU by a semiquantitative assay (ImmunoDip).Results: MAU was present in 26% of Cuban Americans with T2D. A significantly higher percentage of subjects with MA had HTN (P = 0.038) and elevated A1C (P = 0.002) than those with normoalbuminuria. Logistic regression analysis showed that after controlling for covariates, subjects with poor GC were 6.76 times more likely to have MAU if they had hypertension compared with those without hypertension (P = 0.004; 95% confidence interval [CI]: 1.83, 23.05). Conclusion: The clinical significance of these findings emphasizes the early detection of MAU in this Hispanic subgroup combined with BP and good GC, which are fundamentals in preventing and treating diabetes complications and improving individuals’ renal and cardiovascular outcomes.

In Favor of Hospitality-Management Education

Despite the almost one-hundred-year history of hospitality-management education; the hundreds of well-established two-year, four-year, and graduate programs worldwide; and the hundreds of thousands of graduates those programs have prepared for careers in the industry, hospitality-management education’s merit and place in higher education are still questioned at times, to the dismay of hospitality educators the world over. This article delineates several features of hospitality management that make these programs valuable and unique and provides compelling arguments in its favor. The arguments include: 1) courses tailored to the hospitality industry, the world’s largest industry; 2) focus on small-business management as well as corporate enterprises; 3) emphasis on services and service management, not manufacturing; 4) programs and coursework focused on people management, which it at the core of the hospitality businesses; 5) unique focus on the specific issues of food and beverage management, the largest component of the hospitality industry; and 6) transferability of graduates’ knowledge and skill sets, which are in high demand among other service industries. While business programs focus on the fundamentals of management and production, hospitality- management programs prepare graduates who are aware of general management principles and are particularly well-versed in managing the guest experience and employees in a service environment.

An evaluation of an intervention strategy for retention and determination of predictors of success for high -risk students in an associate degree nursing program

The purpose of this study was twofold: (1) to evaluate the effect of a specific instructional Intervention, a Nursing Theory Laboratory, on increasing the retention of high risk students in the associate degree nursing program at Miami-Dade Community College in Miami, Florida; and (2) to identify predictors of success of high risk nursing students in this associate degree nursing program.^ Data were collected from the 195 nursing students enrolled in Nursing Fundamentals during the 1985-1987 academic years, and identified as high risk students. Control and experimental groups were selected based on enrollment in the Nursing Theory Laboratory.^ Results were determined by analyzing several cross-tabulations of selected variables and yielding chi square values, t-tests, and two discriminant analyses. There was no significant relationship between age or ethnic background and enrollment in the Nursing Theory Laboratory. There was no significant relationship between enrollment in the Nursing Theory Laboratory and success in Nursing 1 (Nursing Fundamentals). There was a significant relationship between enrollment in the Nursing Theory Laboratory and success in Nursing 3 (Medical-Surgical Nursing). Writing assessment test scores in two entrance tests and high risk categories, based on the number of enrollments in required science courses, were identified as predictors of success in this program.^ The conclusion was that the Nursing Theory Laboratory does not significantly improve retention of high risk associate degree nursing students if they are enrolled in this intervention at the same time they are enrolled in Nursing Fundamentals. Since those students who were enrolled in the Nursing Theory Laboratory had a significantly higher success rate in Nursing 3, than those students who were not enrolled in the Nursing Theory Laboratory, a recommendation of this study was to offer the Nursing Theory Laboratory to high risk students prior to the beginning of nursing courses. Another recommendation was that students deficient in reading and writing skills should be required to enroll in developmental courses prior to enrollment in the nursing course. ^

Novel online data cleaning protocols for data streams in trajectory, Wireless Sensor Networks

The promise of Wireless Sensor Networks (WSNs) is the autonomous collaboration of a collection of sensors to accomplish some specific goals which a single sensor cannot offer. Basically, sensor networking serves a range of applications by providing the raw data as fundamentals for further analyses and actions. The imprecision of the collected data could tremendously mislead the decision-making process of sensor-based applications, resulting in an ineffectiveness or failure of the application objectives. Due to inherent WSN characteristics normally spoiling the raw sensor readings, many research efforts attempt to improve the accuracy of the corrupted or "dirty" sensor data. The dirty data need to be cleaned or corrected. However, the developed data cleaning solutions restrict themselves to the scope of static WSNs where deployed sensors would rarely move during the operation. Nowadays, many emerging applications relying on WSNs need the sensor mobility to enhance the application efficiency and usage flexibility. The location of deployed sensors needs to be dynamic. Also, each sensor would independently function and contribute its resources. Sensors equipped with vehicles for monitoring the traffic condition could be depicted as one of the prospective examples. The sensor mobility causes a transient in network topology and correlation among sensor streams. Based on static relationships among sensors, the existing methods for cleaning sensor data in static WSNs are invalid in such mobile scenarios. Therefore, a solution of data cleaning that considers the sensor movements is actively needed. This dissertation aims to improve the quality of sensor data by considering the consequences of various trajectory relationships of autonomous mobile sensors in the system. First of all, we address the dynamic network topology due to sensor mobility. The concept of virtual sensor is presented and used for spatio-temporal selection of neighboring sensors to help in cleaning sensor data streams. This method is one of the first methods to clean data in mobile sensor environments. We also study the mobility pattern of moving sensors relative to boundaries of sub-areas of interest. We developed a belief-based analysis to determine the reliable sets of neighboring sensors to improve the cleaning performance, especially when node density is relatively low. Finally, we design a novel sketch-based technique to clean data from internal sensors where spatio-temporal relationships among sensors cannot lead to the data correlations among sensor streams.

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.