McCoy College of Business
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Item Economic Base: San Marcos, Hays County, Texas (1959-1971)(Southwest Texas State University, 1972-01) Savage, V. Howard; Morgan, Celia A.; Yeargan, Howard R.No abstract prepared.Item Southwest Texas State University and the San Marcos Community: An Economic Impact Analysis(Southwest Texas State University, 1985-01) Southwest Texas State UniversityNo abstract prepared.Item SWT and San Marcos: An Economic Impact Analysis, 1990(Southwest Texas State University, 1990-01) Savage, V. Howard; Kishan, Ruby P.At the request of President Robert Hardesty of Southwest Texas State University, the economic relationship between Southwest Texas State University, the economic relationship between Southwest Texas State University and San Marcos was studied for fiscal year 1985. This study was carried out through the use of the Caffrey-Isaacs cash flow model. In the 1985 fiscal year the university dominated the local economy.Item SWT and San Marcos: Economic Impact Study, 1999(Southwest Texas State University, 1999-01) Southwest Texas State UniversityNo abstract prepared.Item Percentiles of an Inflation Index by Quantile Regression(Texas State University-San Marcos, 2006-06) Blankmeyer, EricThis paper gives a methodology for estimating an inflation index using the quantile regression of Bassett and Koenker. The regression, which is orthogonal in the logarithmic price changes, is computed by linear programming for each percentile of inflation. The procedure is applied to monthly data on 25 raw materials.Item How Robust is Linear Regression with Dummy Variables ?(Texas State University-San Marcos, 2006-11) Blankmeyer, EricResearchers in education and the social sciences make extensive use of linear regression models in which the dependent variable is continuous-valued while the explanatory variables are a combination of continuous-valued regressors and dummy variables. The dummies partition the sample into groups, some of which may contain only a few observations. Such groups may easily contain enough outliers to break down the parameter estimates. Models with many fixed or random effects appear to be especially vulnerable to outlying data. This paper discusses the problem at an intuitive level and cites sources for the key theorems establishing bounds on the breakdown point in models with dummy variables.Item Improving the Small-sample Efficiency of a Robust Correlation Matrix: A Note(Texas State University-San Marcos, 2007-04) Blankmeyer, EricThis paper reports small-sample simulations of a correlation matrix estimated robustly by P. J. Rousseeuw's MCD algorithm. It appears that the statistical efficiency of MCD can be improved significantly if a pairwise-difference transformation is first applied to the data.Item The Economic Impact of Texas State University-San Marcos [2007](Texas State University-San Marcos, 2007-09) LeSage, James P.The impact of Texas State on the local, regional and state economics is greater than the direct spending by the University since money spent by the University is spent by employees, businesses, and their workers. As these expenditures give rise to additional business spending, this sets in motion a chain reaction of additional indirect and induced spending. These economics ripple effects impact the local, regional and state economics, and economists use an economic technique known as Input-Output Analysis to analyze the multiple impacts that arise. The IMPLAN input-output model was used to carry out this economic impact study.Item Log-linear Indexes of Nominal Wage Rates and Employment in Eight U. S. Regions(Texas State University-San Marcos, 2008-02) Blankmeyer, EricThis paper illustrates the use of log-linear indexes to estimate and test hypotheses about interregional differences in nominal wages and employment. A two-way analysis of variance is applied to cross sections of U. S. retailing and service categories in eight regions. The robustness of the estimated indexes is examined, and a test of consistent aggregation across sectors is proposed.Item Business Return in New Orleans: Decision Making Amid Post-Katrina Uncertainty(Public Library of Science, 2009-08-26) Lam, Nina S. N.; Pace, R. Kelley; Campanella, Richard; LeSage, James P.; Arenas, HelbertBackground: Empirical observations on how businesses respond after a major catastrophe are rare, especially for a catastrophe as great as Hurricane Katrina, which hit New Orleans, Louisiana on August 29, 2005. We analyzed repeated telephone surveys of New Orleans businesses conducted in December 2005, June 2006, and October 2007 to understand factors that influenced decisions to re-open amid post-disaster uncertainty. Methodology/Principal Findings: Businesses in the group of professional, scientific, and technical services reopened the fastest in the near term, but differences in the rate of reopening for businesses stratified by type became indistinguishable in the longer term (around two years later). A reopening rate of 65% was found for all businesses by October 2007. Discriminant analysis showed significant differences in responses reflecting their attitudes about important factors between businesses that reopened and those that did not. Businesses that remained closed at the time of our third survey (two years after Katrina) ranked levee protection as the top concern immediately after Katrina, but damage to their premises and financing became major concerns in subsequent months reflected in the later surveys. For businesses that had opened (at the time of our third survey), infrastructure protection including levee, utility, and communications were the main concerns mentioned in surveys up to the third survey, when the issue of crime became their top concern. Conclusions/Significance: These findings underscore the need to have public policy and emergency plans in place prior to the actual disaster, such as infrastructure protection, so that the policy can be applied in a timely manner before business decisions to return or close are made. Our survey results, which include responses from both open and closed businesses, overcome the “survivorship bias” problem and provide empirical observations that should be useful to improve micro-level spatial economic modeling of factors that influence business return decisions.Item A Brief Exploration in Statistics and Quantum Mechanics(Texas State University-San Marcos, 2011-05) Blankmeyer, EricQuantum mechanics has some probabilistic or statistical features that have been considered paradoxical or exotic; at least, this impression is frequently conveyed in introductory textbooks on the subject and informal explanations of quantum theory. The often idiosyncratic treatment of statistics and probability seems unhelpful to the student and the interested layperson: it may tend to exaggerate and mystify the real differences between the microscopic and the macroscopic worlds. In this paper I try to show that some of the statistical esoterica of quantum mechanics can be made more transparent by their very close analogies to several macroscopic topics.Item Errors in Variables or Bad Leverage at Some Observations ?(Texas State University-San Marcos, 2011-10) Blankmeyer, EricErrors-in-variables is a long-standing, difficult issue in linear regression; and progress depends in part on new identifying assumptions. I characterize measurement error as bad-leverage points and assume that fewer than half the sample observations are heavily contaminated, in which case a high-breakdown robust estimator may be able to isolate and downweight or discard the problematic data. In simulations of simple and multiple regression where eiv affected 25% of the data and R2 was mediocre, one high-breakdown estimator had small bias, very good coverage, and precision that improved when the sample size increased.Item Predictors of Business Return in New Orleans after Hurricane Katrina(Public Library of Science, 2012-10-24) Lam, Nina S. N.; Arenas, Helbert; Pace, R. Kelley; LeSage, James P.; Campanella, RichardWe analyzed the business reopening process in New Orleans after Hurricane Katrina, which hit the region on August 29, 2005, to better understand what the major predictors were and how their impacts changed through time. A telephone survey of businesses in New Orleans was conducted in October 2007, 26 months after Hurricane Katrina. The data were analyzed using a modified spatial probit regression model to evaluate the importance of each predictor variable through time. The results suggest that the two most important reopening predictors throughout all time periods were the flood depth at the business location and business size as represented by its wages in a logarithmic form. Flood depth was a significant negative predictor and had the largest marginal effects on the reopening probabilities. Smaller businesses had lower reopening probabilities than larger ones. However, the nonlinear response of business size to the reopening probability suggests that recovery aid would be most effective for smaller businesses than for larger ones. The spatial spillovers effect was a significant positive predictor but only for the first nine months. The findings show clearly that flood protection is the overarching issue for New Orleans. A flood protection plan that reduces the vulnerability and length of flooding would be the first and foremost step to mitigate the negative effects from climate-related hazards and enable speedy recovery. The findings cast doubt on the current coastal protection efforts and add to the current debate of whether coastal Louisiana will be sustainable or too costly to protect from further land loss and flooding given the threat of sea-level rise. Finally, a plan to help small businesses to return would also be an effective strategy for recovery, and the temporal window of opportunity that generates the greatest impacts would be the first 6∼9 months after the disaster.Item Monetary Transfers in the U.S.: How Efficient Are Tax Rebates?(Multidisciplinary Digital Publishing Institute, 2013-11) Vacaflores, Diego E.Recent debate on the effectiveness of tax rebates has concentrated on the degree to which they can affect economic activity, which depends on the methodology, the state of the economy, and the underlying assumptions. A better approach to assess the effectiveness of these monetary transfers is by comparing this method to alternative policies—like the traditional monetary injections through the financial intermediaries. A limited participation model calibrated to the U.S. economy is used to show that the higher the proportion of the monetary injection channeled through the consumers—instead of banks—leads to a less vigorous recovery of output but softens the detrimental effect on the utility of the representative household from the inherent inflationary pressure. This result is robust to the relative importance of the injection (utilization of resources) and alternative utility functions.Item The Economic Impact of Texas State University [2014](Texas State University-San Marcos, 2014-08) LeSage, James P.The impact of Texas State on the local, regional and state economics is greater than the direct spending by the University since money spent by the University is spent by employees, businesses, and their workers. As these expenditures give rise to additional business spending, this sets in motion a chain reaction of additional indirect and induced spending. These economic ripple effects impact the local, regional and state economics, and economists use an economic technique known as Input-Output Analysis to analyze the multiple impacts that arise. The IMPLAN input-output model was used to carry out this economic impact study.Item The Biggest Myth in Spatial Econometrics(Multidisciplinary Digital Publishing Institute, 2014-12) LeSage, James P.; Pace, R. KelleyThere is near universal agreement that estimates and inferences from spatial regression models are sensitive to particular specifications used for the spatial weight structure in these models. We find little theoretical basis for this commonly held belief, if estimates and inferences are based on the true partial derivatives for a well-specified spatial regression model. We conclude that this myth may have arisen from past applied work that incorrectly interpreted the model coefficients as if they were partial derivatives, or from use of misspecified models.Item Women's Reasons for Leaving the Engineering Field(Frontiers Media, 2017-06) Fouad, Nadya A.; Chang, Wen-Hsin; Wan, Min; Singh, RomilaAmong the different Science, Technology, Engineering, and Math fields, engineering continues to have one of the highest rates of attrition (Hewlett et al., 2008). The turnover rate for women engineers from engineering fields is even higher than for men (Frehill, 2010). Despite increased efforts from researchers, there are still large gaps in our understanding of the reasons that women leave engineering. This study aims to address this gap by examining the reasons why women leave engineering. Specifically, we analyze the reasons for departure given by national sample of 1,464 women engineers who left the profession after having worked in the engineering field. We applied a person-environment fit theoretical lens, in particular, the Theory of Work Adjustment (TWA) (Dawis and Lofquist, 1984) to understand and categorize the reasons for leaving the engineering field. According to the TWA, occupations have different "reinforcer patterns," reflected in six occupational values, and a mismatch between the reinforcers provided by the work environment and individuals' needs may trigger departure from the environment. Given the paucity of literature in this area, we posed research questions to explore the reinforcer pattern of values implicated in women's decisions to leave the engineering field. We used qualitative analyses to understand, categorize, and code the 1,863 statements that offered a glimpse into the myriad reasons that women offered in describing their decisions to leave the engineering profession. Our results revealed the top three sets of reasons underlying women's decision to leave the jobs and engineering field were related to: first, poor and/or inequitable compensation, poor working conditions, inflexible and demanding work environment that made work-family balance difficult; second, unmet achievement needs that reflected a dissatisfaction with effective utilization of their math and science skills, and third, unmet needs with regard to lack of recognition at work and adequate opportunities for advancement. Implications of these results for future research as well as the design of effective intervention programs aimed at women engineers' retention and engagement in engineering are discussed.Item Positive Disposition in the Prediction of Strategic Independence among Millennials(Multidisciplinary Digital Publishing Institute, 2017-11) Konopaske, Robert; Konopaske, Robert; Kirby, Eric G.; Kirby, Eric G.; Kirby, Susan L.; Kirby, Susan L.Research on the dispositional traits of Millennials (born in 1980–2000) finds that this generation, compared to earlier generations, tends to be more narcissistic, hold themselves in higher regard and feel more entitled to rewards. The purpose of this intragenerational study is to counter balance extant research by exploring how the positive dispositional traits of proactive personality, core self-evaluation, grit and self-control predict strategic independence in a sample of 311 young adults. Strategic independence is a composite variable measuring a person’s tendency to make plans and achieve long-term goals. A confirmatory factor analysis and hierarchical regression found evidence of discriminant validity across the scales and that three of the four independent variables were statistically significant and positive predictors of strategic independence in the study. The paper discusses research and practical implications, strengths and limitations and areas for future research.Item The Impact of Firm Characteristics and IT Governance on IT Material Weaknesses(IGI Global, 2018-04) Zhang, Peiqin; Zhao, Kexin; Kumar, Ram L.Accurate and timely reporting of organizational performance is becoming increasingly important and highly regulated. However, organizations face a variety of challenges in seeking to provide accurate and reliable information due to the existence of IT control problems. Hence it is important for end users including auditors and managers to understand how to manage IT material weaknesses ITMWs. While there is extensive accounting research on general material weaknesses MWs, ITMWs are under researched. This article identifies key firm characteristics that appear to be related to ITMWs. In addition, the authors suggest that IT governance may help firms mitigate such problems. To gain a deeper understanding of IT governance effects, this article proposes a model which includes an innovative construct, ITGOV, operationalized using secondary data. The authors empirically validate the proposed model based on a data set of 1,112 firms. Their study illustrates the differences between ITMWs and general MWs. These results can also help end users computing by offering insights into better management of ITMWs.Item Meta-Analysis of Coefficient Alpha for Scores on the Narcissistic Personality Inventory(Public Library of Science, 2018-12-04) Miller, Brian K.; Nicols, Kay M.; Clark, Silvia; Daniels, Alison; Grant, WhitneyThe Narcissistic Personality Inventory (NPI) has greatly facilitated the scientific study of trait narcissism. However, there is great variability in the reported reliability of scores on the NPI. This study meta-analyzes coefficient alpha for scores on the NPI and its sub-scales (e.g. entitlement) with transformed alphas weighted by the inverse of the variance of alpha. Three coders evaluated 1213 individual studies for possible inclusion and determined that 1122 independent samples were suitable for coding on 12 different characteristics of the sample, scale, and study. A fourth author cross-coded 15 percent of these samples resulting in 85 percent overall agreement. In the independent samples, comprised of 195,038 self-reports, the expected population coefficient alpha for the NPI was .82. The population value for alpha on the various sub-scales ranged from .48 for narcissistic self-sufficiency to .76 for narcissistic leadership/authority. Because significant heterogeneity existed in coded study alphas for the overall NPI, moderator tests and an explanatory model were also conducted and reported. It was found that longer scales, the use of a Likert response scale as opposed to the original forced choice response format, higher mean scores and larger standard deviations on the scale, as well as the use of samples with a larger percentage of female respondents were all positively related to the expected population alpha for scores on the overall NPI. These results will likely aid researchers who are concerned with the reliability of scores on the NPI in their research on non-clinical subjects.