Teaching teachers in effectual entrepreneurship

Entrepreneurship and entrepreneurship education is seen by all kind of people to be important for economic growth. Teaching entrepreneurship needs another approach. Active learning and the constructivism is mostly seen as essential. Other elements that are influencing the teaching process are the competences, the culture and the teacher. So the teacher must be capable of using other methods and theory as he is used to. Effectuation, constructivism and andragogy are the key elements for the training of entrepreneurial teachers. From that perspective there has been made an education program that will start in September 2013 for teachers at universities of applied science. Until that time there are being held some minor experiments on parts of the program

Ontogenetic and temporal variability in the fat content and fatty acid composition of Atlantic herring (Clupea harengus) from the Bay of Fundy, Canada

Atlantic herring (Clupea harengus) is an ecologically and economically valuable species in many food webs, yet surprisingly little is known about the variation in the nutritional quality of these fish. Atlantic herring collected from 2005 through 2008 from the Bay of Fundy, Canada, were examined for variability in their nutritional quality by using total lipid content (n=889) and fatty acid composition (n=551) as proxies for nutritional value. A significant positive relationship was found between fish length and total lipid content. Atlantic herring also had significantly different fatty acid signatures by age. Fish from 2005 had significantly lower total lipid content than fish from 2006 through 2008, and all years had significantly different fatty acid signatures. Summer fish were significantly fatter than winter fish and had significantly different fatty acid signatures. For all comparisons (ontogenetic, annual, and seasonal) percent concentrations of omega-3, -6, and long-chain monounsaturated fatty acids were the most important for distinguishing between the fatty acid signatures of fish. This study underscores the importance of quantifying variation in prey quality synoptically with prey quantity in food webs over ontogenetic and temporal scales when evaluating the effect of prey nutritional quality on predators and on modeling trophic dynamics

Investigation of Nitrogen and Utilization and Efficiency in 17 Corn Inbred Lines

Nitrogen (N) is considered to be one of the major nutrient elements required in obtaining maximum crop production. It has been stated that in order to keep at the same production level that we have now, two to three times as much cropland would be required if we used 1930 technology and fertilizer. Nitrogen is an important resource. But with price increases, shortage possibilities and ecological implications of nitrogen toxicity, anew outlook on nitrogen utilization is being taken. Increases in the price of N are well known to everyone who is connected with agriculture. As for shortage possibilities, the United States, in 1950, used approximately 1 million tons. In 1974, 9 million tons were used with an expected yearly increase of 5% compounded annually. The world’s future needs for this energy requiring product can be expected to increase at a faster rate yet, The threat to drinking water from nitrate toxicity is also being visualized where an excess of nitrate is being leached deeper into the ground. In spite of these problems, nitrogen utilization is and has been an important aspect in crop production improvement programs, as can be seen by the vast amount of literature published. However, even more research is needed to better understand nitrogen efficiency and the role that it can play in crop production. The purpose of this research is to 1) investigate various areas of plant metabolism for nitrogen efficiency and 2) measure the genetic variability present in those areas of nitrogen efficiency in inbred lines of corn

Business and Default Cycles for Credit Risk

Various economic theories are available to explain the existence of credit and default cycles. There remains empirical ambiguity, however, as to whether or these cycles coincide. Recent papers_new suggest by their empirical research set-up that they do, or at least that defaults and credit spreads tend to co-move with macro-economic variables. If true, this is important for credit risk management as well as for regulation and systemic risk management. In this paper, we use 1927-1997 U.S. data on real GDP, credit spreads, and business failure rates to shed new light on the empirical evidence. We use a multivariate unobserved components framework to disentangle credit from business cycles. It turns out that cyclical co-movements arise between default rates, but not real GDP. There is, however, a contemporaneous correlation between real GDP and default rates. Regarding the longer term evolution of the series, credit spreads influence default rates and real GDP, but not vice versa. This corroborates some of the empirical findings in the recent literature on the correlation between macrovariables and default rates. It also suggests the use of credit spreads besides or instead of economic growth rates to forecast the dynamics of future default rates

The multi-state latent factor intensity model for credit rating transitions

A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic factors. The model has a generalized semi-Markov structure designed to accommodate many of the stylized facts of credit rating migrations. Parameter estimation is based on Monte Carlo maximum likelihood methods for which the details are discussed in this paper. A simulation experiment is carried out to show the effectiveness of the estimation procedure. An empirical application is presented for transitions in a 7 grade rating system. The model includes a common dynamic component that can be interpreted as the credit cycle. Asymmetric effects of this cycle across rating grades and additional semi-Markov dynamics are found to be statistically significant. Finally, we investigate whether the common factor model suffices to capture systematic risk in ratin

Long Memory Dynamics for Multivariate Dependence under Heavy Tails

We develop a new simultaneous time series model for volatility and dependence with long memory (fractionally integrated) dynamics and heavy-tailed densities. Our new multivariate model accounts for typical empirical features in financial time series while being robust to outliers or jumps in the data. In the empirical study for four Dow Jones equities, we find that the degree of memory in the volatilities of the equity return series is similar, while the degree of memory in correlations between the series varies significantly. The forecasts from our model are compared with high-frequency realised volatility and dependence measures. The forecast accuracy is overall higher compared to those from some well-known competing benchmark models

Tracking Growth and the Business Cycle: a Stochastic Common Cycle Model for the Euro Area

This paper proposes a new model-based method to obtain a coincident indicator for the business cycle. A dynamic factor model with trend components and a common cycle component is considered which can be estimated using standard maximum likelihood methods. The multivariate unobserved components model includes a stationary higher order cycle. Also higher order trends can be part of the analysis. These generalisationslead to a business cycle that is similar to a band-pass one. Furthermore, cycle shifts for individual time series are incorporated within the model and estimated simultaneously with the remaining parameters. This feature permits the use of leading, coincident and lagging variables to obtain thebusiness cycle coincident indicator without prior analysis of their lead-lag relationship. Besides the business cycle indicator, the model-based approach also allows to get a growth rate indicator. In the empirical analysis for the Euro area, both indicators are obtained based on nine key economic timeseries including gross domestic product, industrial production,unemployment, confidence indicators and interest rate spread. This analysis contrasts sharply with earlier multivariate approaches. In particular, our more parsimonious approach leads to a growth rate indicator for the Euro area that is similar to the one of EuroCOIN. The latter is based on a more involvedapproach by any standard and uses hundreds of time series from individual countries belonging to the Euro area

Pro-Cyclicality, Empirical Credit Cycles, and Capital Buffer Formation

We model 1927-1997 U.S. business failure rates using a time series approach based on unobserved components. Clear evidence is found of cyclical behavior in default rates. The cycle has a period of around 10 years. We also detect longer term movements in default probabilities and default correlations. Our findings have important implications for portfolio credit risk analysis. First, a static analysis of portfolio credit risk can underestimate credit risk significantly by not accounting for the dynamic and cyclical behaviour of default probabilities. Second, estimating default correlations over long horizons without accounting for time variation may lead to misspecified risk management models. We highlight the main effects in an actual credit risk experiment, addressing the issue of pro-cyclicality in ratings and capital buffer formation. It turns out that dynamic models anticipate much better on required capital buffer increases than rating strategies based on recent historical data. In this way, dynamic credit risk models may help to alleviate part of the pro-cyclicality problem