Labor Unions and Coalitions in Buffalo

Labor unions have evolved tremendously since their inception in 1866 in the United States. Today, some unions in the Buffalo region are responding to free market fundamentalism with the development of multiple coalition partners. Coalitions are composed of unions and like-minded activist organizations. This creative response to a long-term economic crisis has created a high road social infrastructure. Unions have moved beyond their traditional roles of collective bargaining and representation to a more community-oriented mission of improving the quality of local jobs

Choosing Lag Lengths in Nonlinear Dynamic Models

Given that it is quite impractical to use standard model selection criteria in a nonlinear modeling context, the builders of nonlinear models often choose lag length by setting it equal to the lag length chosen for a linear autoregression of the data. This paper studies the performance of this procedure in a variety of circumstances, and then proposes some new and simple model selection procedures, based on linear approximations of the nonlinear forms. The idea here is to apply standard selection criteria to these linear approximations, rather than to autoregressions that make no provision for nonlinear behavior. A simulation study compares the properties of these proposed procedures with the properties of linear selection procedures.Nonlinear time series models, Neural networks, Model selection criteria, Polynomial approximations, Volterra expansions.

Developing strong social enterprises : a documentary approach

Social enterprises are diverse in their mission, business structures and industry orientations. Like all businesses, social enterprises face a range of strategic and operational challenges and utilize a range of strategies to access resources in support of their venture. This exploratory study examined the strategic management issues faced by Australian social enterprises and the ways in which they respond to these. The research was based on a comprehensive literature review and semi-structured interviews with 11 representatives of eight social enterprises based in Victoria and Queensland. The sample included mature social enterprises and those within two years of start-up. In addition to the research report, the outputs of the project include a series of six short documentaries, which are available on YouTube at http://www.youtube.com/user/SocialEnterpriseQUT#p/u. The research reported on here suggests that social enterprises are sophisticated in utilizing processes of network bricolage (Baker et al. 2003) to mobilize resources in support of their goals. Access to network resources can be both enabling and constraining as social enterprises mature. In terms of the use of formal business planning strategies, all participating social enterprises had utilized these either at the outset or the point of maturation of their business operations. These planning activities were used to support internal operations, to provide a mechanism for managing collective entrepreneurship, and to communicate to external stakeholders about the legitimacy and performance of the social enterprises. Further research is required to assess the impacts of such planning activities, and the ways in which they are used over time. Business structures and governance arrangements varied amongst participating enterprises according to: mission and values; capital needs; and the experiences and culture of founding organizations and individuals. In different ways, participants indicated that business structures and governance arrangements are important ways of conferring legitimacy on social enterprise, by signifying responsible business practice and strong social purpose to both external and internal stakeholders. Almost all participants in the study described ongoing tensions in balancing social purpose and business objectives. It is not clear, however, whether these tensions were problematic (in the sense of eroding mission or business opportunities) or productive (in the sense of strengthening mission and business practices through iterative processes of reflection and action). Longitudinal research on the ways in which social enterprises negotiate mission fulfillment and business sustainability would enhance our knowledge in this area. Finally, despite growing emphasis on measuring social impact amongst institutions, including governments and philanthropy, that influence the operating environment of social enterprise, relatively little priority was placed on this activity. The participants in our study noted the complexities of effectively measuring social impact, as well as the operational difficulties of undertaking such measurement within the day to day realities of running small to medium businesses. It is clear that impact measurement remains a vexed issue for a number of our respondents. This study suggests that both the value and practicality of social impact measurement require further debate and critically informed evidence, if impact measurement is to benefit social enterprises and the communities they serve

Forecasting the Volatility of Australian Stock Returns: Do Common Factors Help?

This paper develops univariate and multivariate forecasting models for realized volatility in Australian stocks. We consider multivariate models with common features or common factors, and we suggest estimation procedures for approximate factor models that are robust to jumps when the cross-sectional dimension is not very large. Our forecast analysis shows that multivariate models outperform univariate models, but that there is little difference between simple and sophisticated factor models.

Does Beta React to Market Conditions? Estimates of Bull and Bear Betas using a Nonlinear Market Model with an Endogenous Threshold Parameter

We apply a logistic smooth transition market model (LSTM) to a sample of returns on Australian industry portfolios to investigate whether bull and bear market betas differ. Unlike other studies, our LSTM model allows for smooth transition between bull and bear states and allows the data to determine the threshold value. The estimated value of the smoothness parameter was very large for all industries implying that transition is abrupt. Therefore we estimated the threshold as a parameter along with the two betas in a dual beta market (DBM) framework using a sequential conditional least squares (SCLS) method. Using Lagrange Multiplier type tests of linearity, and the SCLS method our results indicate that for all but two industries the bull and bear betas are significantly different.Logistic Smooth Transition Market Model (LSTM); Sequential Conditional Least Squares (SCLS); Linearity Tests; Bull/Bear Betas

Testing for co-jumps in high-frequency financial data: an approach based on first-high-low-last prices

This paper proposes a new test for simultaneous intraday jumps in a panel of high frequency financial data. We utilize intraday first-high-low-last values of asset prices to construct estimates for the cross-variation of returns in a large panel of high frequency financial data, and then employ these estimates to provide a first-high-low-last price based test statistic to detect common large discrete movements (co-jumps). We study the finite sample behavior of our first-high-low-last price based test using Monte Carlo simulation, and find that it is more powerful than the Bollerslev et al (2008) return-based co-jump test. When applied to a panel of high frequency data from the Chinese mainland stock market, our first-high-low-last price based test identifies more common jumps than the return-based test in this emerging market.Covariance, Co-jumps, High-frequency data, First-High-Low-Last price, Microstructure bias, Nonsynchronous trades, Realized covariance, Realized co-range.

Forecasting Under Strucural Break Uncertainty

This paper proposes two new weighting schemes that average forecasts using different estimation windows to account for structural change. We let the weights reflect the probability of each time point being the most-recent break point, and we use the reversed ordered Cusum test statistics to capture this intuition. The second weighting method simply imposes heavier weights on those forecasts that use more recent information. The proposed combination forecasts are evaluated using Monte Carlo techniques, and we compare them with forecasts based on other methods that try to account for structural change, including average forecasts weighted by past forecasting performance and techniques that first estimate a break point and then forecast using the post break data. Simulation results show that our proposed weighting methods often outperform the others in the presence of structural breaks. An empirical application based on a NAIRU Phillips curve model for the United States indicates that it is possible to outperform the random walk forecasting model when we employ forecasting methods that account for break uncertainty.Forecasting with Structural breaks, Parameter Shifts, break Uncertainty, Structural break Tests, Choice of Estimation Sample, Forecast Combinations, NAIRU Phillips Curve.

Nonlinear Correlograms and Partial Autocorrelograms

This paper proposes neural network based measures of predictability in conditional mean, and then uses them to construct nonlinear analogues to autocorrelograms and partial autocorrelograms. In contrast to other measures of nonlinear dependence that rely on nonparametric estimation of densities or multivariate integration, our autocorrelograms are simple to calculate and appear to work well in relatively small samples.Nonlinear autocorrelograms, Nonlinear time series models, Neural networks, Model selection criteria, Nonlinear partial autocorrelograms

Random Walk Smooth Transition Autoregressive Models

This paper extends the family of smooth transition autoregressive (STAR) models by proposing a specification in which the autoregressive parameters follow random walks. The random walks in the parameters can capture structural change within a regime switching framework, but in contrast to the time varying STAR (TV-STAR) speciifcation recently introduced by Lundbergh et al (2003), structural change in our random walk STAR (RW-STAR) setting follows a stochastic process rather than a deterministic function of time. We suggest tests for RW-STAR behaviour and study the performance of RW-STARmodels in an empirical setting. The out-of sample forecasting performance of our RW-STAR models is encouraging - better than AR, LSTAR and TV-STAR specifications with respect to point forecasts and on a par with TV-STAR speciÞcations with respect to forecast density evaluations.Forecast density evaluation, Non-constant parameters, Random walk

Using motivational interviewing and technology to increase confidence in nutritional counseling among dental hygienists: a thesis

Purpose: Research shows definite connections between food choices and caries, periodontal disease, and oral cancer. Dental hygienists have the unique opportunity to educate patients on how nutrition can improve oral health. Dental hygiene students are introduced to these concepts but struggle to gain confidence to share this knowledge with patients. This study looked at an educational module on motivational interviewing (MI) and an electronic assessment tool to build student confidence with nutritional counseling. Methods: Students participated in an educational module to review MI and introduce the electronic nutritional risk assessment and counseling tool. Prior to the module, participants completed a pretest about attitudes and confidence levels regarding MI and nutritional counseling. After three weeks of clinical practice, participants completed a posttest including the same questions, a report on the frequency of nutritional counseling sessions, and open-ended questions. Data was compared for quantitative changes and qualitative themes from participant responses. Results: Twenty-two students (n = 22) participated in both pretest and posttest. There were statistically significant changes in participants’ frequency of nutritional counseling sessions (p = 0.049) as well as in their confidence (p = 0.007) and comfort (p = 0.020) discussing nutrition with patients. Participants struggled to become more confident in MI as demonstrated with no significant change in their feelings surrounding MI (p = 0.150). Students reporting increased nutritional counseling sessions showed improvement in their confidence with nutritional counseling. Conclusion: Introducing MI with an electronic assessment tool to aid dental hygiene students can improve confidence with nutritional counseling