Factors revealed while posing mathematical modelling problems by mathematics student teachers

The purpose of this study is to reveal factors considered by mathematics student teachers while posing modelling problems. The participants were twenty-seven mathematics student teachers and posed their modelling problems within their groups. The data were obtained from the modelling problems posed by the participants, their solutions on these problems and the groups’ reflective diaries regarding their problem posing and solution processes. The data were analyzed by using content analysis and the codes were constructed according to the problems’ contents. The participants' diaries were examined in terms of generated codes and the expressions supporting/relating the codes were determined. While designing the problems, the participants considered the factors such as being interesting, understandable, appropriateness to real life and modelling process, model construction, and usability of different mathematical concepts. Their solutions were generally handled in terms of usage of the mathematical statements, appropriateness to the modelling process and being meaningful for real life. Modelling training should be provided to enable the student teachers to develop modelling problems and their designs should be examined and the feedbacks should be given. © 2018 Eurasian Society of Educational Research. All Rights Reserved

Parametric and nonparametric inference in equilibrium job search models

Equilibrium job search models allow for labor markets with homogeneous workers and firms to yield nondegenerate wage densities. However, the resulting wage densities do not accord well with empirical regularities. Accordingly, many extensions to the basic equilibrium search model have been considered (e.g., heterogeneity in productivity, heterogeneity in the value of leisure, etc.). It is increasingly common to use nonparametric forms for these extensions and, hence, researchers can obtain a perfect fit (in a kernel smoothed sense) between theoretical and empirical wage densities. This makes it difficult to carry out model comparison of different model extensions. In this paper, we first develop Bayesian parametric and nonparametric methods which are comparable to the existing non-Bayesian literature. We then show how Bayesian methods can be used to compare various nonparametric equilibrium search models in a statistically rigorous sense

Using VARs and TVP-VARs with many macroeconomic variables

This paper discusses the challenges faced by the empirical macroeconomist and methods for surmounting them. These challenges arise due to the fact that macroeconometric models potentially include a large number of variables and allow for time variation in parameters. These considerations lead to models which have a large number of parameters to estimate relative to the number of observations. A wide range of approaches are surveyed which aim to overcome the resulting problems. We stress the related themes of prior shrinkage, model averaging and model selection. Subsequently, we consider a particular modelling approach in detail. This involves the use of dynamic model selection methods with large TVP-VARs. A forecasting exercise involving a large US macroeconomic data set illustrates the practicality and empirical success of our approach

Large Time-Varying Parameter VARs

In this paper, we develop methods for estimation and forecasting in large time-varying parameter vector autoregressive models (TVP-VARs). To overcome computational constraints, we draw on ideas from the dynamic model averaging literature which achieve reductions in the computational burden through the use forgetting factors. We then extend the TVP-VAR so that its dimension can change over time. For instance, we can have a large TVP-VAR as the forecasting model at some points in time, but a smaller TVP-VAR at others. A final extension lies in the development of a new method for estimating, in a time-varying manner, the parameter(s) of the shrinkage priors commonly-used with large VARs. These extensions are operationalized through the use of forgetting factor methods and are, thus, computationally simple. An empirical application involving forecasting inflation, real output and interest rates demonstrates the feasibility and usefulness of our approach

Charles Everett Koop: the “Family doctor of America”

Charles Everett Koop was a great Surgeon General, probably the most influential in the history of the United States of America. He never missed courage in his life and often he had used it to tackle professional and personal tough problems. In his public activity, he faced controversial health problems of American people as smoking, abortion and the first occurrence of the epidemic Acquired Immune Deficiency Syndrome (AIDS). Koop was a rigorous man. The lodestar that guided Koop in his work, as a public servant was to do the best for health of Americans. In his prestigious and difficult role, he faced the pressing problems of health of millions of people trying to avoid political influence. During his mandate of eight years, Koop increased the influence and authority of his role. His appearance and behaviour were unmistakable: Lincolnesque beard and uniform, conduct hard and pure, exclusively oriented to the health of citizens, over the personal conveniences, political pressure and lobbying. An exemplary man, who for his passion for medicine and his sincere interest in promoting public health, was affectionately considered the "Family Doctor of America"

Bayesian analysis of endogenous delay threshold models

We develop Bayesian methods of analysis for a new class of threshold autoregressive models: endogenous delay threshold. We apply our methods to the commonly used sunspot data set and find strong evidence in favor of the Endogenous Delay Threshold Autoregressive (EDTAR) model over linear and traditional threshold autoregressions

A Monte Carlo comparison of Bayesian testing for cointegration rank

This article considers a Bayesian testing for cointegration rank, using an approach developed by Strachan and van Dijk (2007), that is based on Koop, Leon-Gonzalez, and Strachan (2006). The Bayes factors are calculated for selecting cointegrating rank. We calculate the Bayes factors using two methods - the Schwarz BIC approximation and Chib's (1995) algorithm for calculating the marginal likelihood. We run Monte Carlo simulations to compare the two methods.

Comparing effects of microplastic exposure, FPOM resource quality, and consumer density on the response of a freshwater particle feeder and associated ecosystem processes

Fine particulate organic matter (FPOM) is an important basal resource in stream ecosystems for deposit- and filter-feeding macroinvertebrates (collectively 'particle feeders'). Microplastics (MP) share many characteristics with FPOM (e.g. size range, surface area to volume ratios) and are potentially consumed by particle feeders. Accordingly, MP contamination of natural FPOM pools might affect particle feeder growth and survival, particularly when background FPOM resource quality is low, or intraspecific competition is high. We conducted a microcosm experiment to evaluate how a realistic (1400 particles/kg sediment) polyethylene MP (o = 45-53 mu m) concentration interacts with FPOM (o = 63-250 mu m) resource quality (low versus high nutrient content) and consumer density (10 versus 20 individuals per microcosm) to affect growth and survival of larval Chironomus riparius (Diptera: Chironomidae), a model particle feeder. We additionally quantified community respiration, based on three hour measurements of oxygen consumption in the microcosms at the end of the experiment. MP exposure reduced larval body lengths by 26.7%, but only under the low consumer density treatment. MPs reduced community respiration by 26.2%, but only in the absence of chironomids, indicating an impact on microbial respiration. In comparison, low resource quality and high consumer density were associated with 53.5-70.2% reductions in community respiration, chironomid body length and/or body mass. These results suggest that effects of contamination of FPOM with MPs at environmentally realistic concentrations on the life histories of particle feeders such as C. riparius might be limited, especially relative to the effects of resource quality and consumer density. However, the reduction in microbial respiration when MPs were present highlights the need for further research addressing MP impacts on microbes, given their key roles in ecosystem functioning