Bootstrap Confidence Bands for Forecast Paths

The problem of forecasting from vector autoregressive models has attracted considerable attention in the literature. The most popular non-Bayesian approaches use large sample normal theory or the bootstrap to evaluate the uncertainty associated with the forecast. The literature has concentrated on the problem of assessing the uncertainty of the prediction for a single period. This paper considers the problem of how to assess the uncertainty when the forecasts are done for a succession of periods. It describes and evaluates bootstrap method for constructing confidence bands for forecast paths. The bands are constructed from forecast paths obtained in bootstrap replications with an optimisation procedure used to find the envelope of the most concentrated paths. The method is shown to have good coverage properties in a Monte Carlo study.vector autoregression, forecast path, bootstrapping, simultaneous statistical inference

On the power of direct tests for rational expectations against the alternative of constant gain learning

In this paper we study the power of direct tests for rational expectations against the constant gain learning alternative. The investigation is by means of a Monte Carlo study. The tests considered use quantitative expectations data and qualitative survey data that has been quantified. The main finding is that the power of tests for rational expectations against constant gain learning may be very small, making it impossible to distinguish the hypotheses.adaptive learning, tests for rational expectations, quantification methods, constant gain least squares

Russian perspectives of online learning technologies in higher education: An empirical study of a MOOC

There has been a rapid growth of massive open online courses (MOOCs) in the global education market in the last decade. Online learning technologies are becoming increasingly widespread in the non-formal education sector and in higher and supplementary vocational education. The use of MOOCs in Russia to support the delivery of educational programmes at university level opens opportunities in terms of expanding the educational choice for students, the development of virtual academic mobility, reduction in the cost of educational services, and improvement in the accessibility of education. However, the effectiveness of using different online learning technologies at university level, and the consequences of their widespread adoption, has not been sufficiently explored. In this research study, a comparative analysis is made of the effects of different online learning models on student educational outcomes in a university setting. A study was undertaken in which different groups of students at the Ural Federal University, Russia, were encouraged to study technical and humanities disciplines using a framework of blended learning, and online learning with tutoring support. The results of the study were compared with the results of a reference (control) group of students who studied the same disciplines in a traditionally taught model. It was found that both models (blended and online) of MOOC implementation demonstrated greater learning gains, in comparison with the traditional model. For engineering and technical disciplines, there was no statistically significant difference between blended or online learning technologies. For the humanities discipline, where the communicative component of the learning process was significant, the blended learning technology produced better results. Conclusions of this empirical research may be useful for heads of educational organizations and teachers in helping them to make strategic decisions about the modernization of university courses by increasing the effectiveness of the implementation of new educational technologies. The results of this research project will be used for implementing the State Priority Project, ‘The Modern Digital Educational Environment of the Russian Federation’

The ethics of designer’s project activity

Статья посвящена определению этических аспектов дизайна как специфической социокультурной сферы творческой формообразующей деятельности. Низкая степень теоретической разработанности вопроса требует начальной систематизации этических проблем в ситуациях проектирования и использования продуктов дизайна, а также изучения реальных этических практик участников дизайн-процесса. Автор производит такую систематизацию на основе выработанного ранее представления о дизайне как системе.The article is devoted to defining the ethical aspects of design as a specific social and cultural sphere of creative formative activities. Lack of the theoretical elaboration of the issue requires an initial systematization of ethical problems in project- and using situations, and researches of ethical practices between the participants of the design process. The author makes a classification on the basis of the pre-formed ideas about design as a system

Calculating Joint Bands for Impulse Response Functions using Highest Density Regions

This paper proposes a new non-parametric method of constructing joint confidence bands for impulse response functions of vector autoregressive models. The estimation uncertainty is captured by means of bootstrapping and the highest density region (HDR) approach is used to construct the bands. A Monte Carlo comparison of the HDR bands with existing alternatives shows that the former are competitive with the bootstrap-based Bonferroni and Wald confidence regions. The relative tightness of the HDR bands matched with their good coverage properties makes them attractive for applications. An application to corporate bond spreads for Germany highlights the potential for empirical work

Skewness-Adjusted Bootstrap Confidence Intervals and Confidence Bands for Impulse Response Functions

This Article Investigates The Construction Of Skewness-Adjusted Confidence Intervals And Joint Confidence Bands For Impulse Response Functions From Vector Autoregressive Models. Three Different Implementations Of The Skewness Adjustment Are Investigated. The Methods Are Based On A Bootstrap Algorithm That Adjusts Mean And Skewness Of The Bootstrap Distribution Of The Autoregressive Coefficients Before The Impulse Response Functions Are Computed. Using Extensive Monte Carlo Simulations, The Methods Are Shown To Improve The Coverage Accuracy In Small And Medium Sized Samples And For Unit Root Processes For Both Known And Unknown Lag Orders

Confidence bands for impulse responses: Bonferroni versus Wald

In impulse response analysis estimation uncertainty is typically displayed by constructing bands around estimated impulse response functions. These bands may be based on frequentist or Bayesian methods. If they are based on the joint distribution in the Bayesian framework or the joint asymptotic distribution possibly constructed with bootstrap methods in the frequentist framework often individual confidence intervals or credibility sets are simply connected to obtain the bands. Such bands are known to be too narrow and have a joint confidence content lower than the desired one. If instead the joint distribution of the impulse response coefficients is taken into account and mapped into the band it is shown that such a band is typically rather conservative. It is argued that a smaller band can often be obtained by using the Bonferroni method. While these considerations are equally important for constructing forecast bands, we focus on the case of impulse responses in this study

Introduction of open E-learning system as a factor of regional development

The article analyses the economic and socio-cultural premises for introducing the open e-learning in the Ural region, as well as the potential economic effect of this type of educational activity. The article strives to prove a regular pattern of the universities’ transition to e-learning, also in connection with the changes of the educational paradigm and the nature of the educational system management. The hypothesis of the paper is connected with bringing the economic dimension to a humanitarian concept of e-learning, which becomes more and more widespread. The methodology of the article is based on the recognition of the fact that the macroeconomic processes in the information society and the processes occurring in a particular industry — higher education — are of isomorphic nature. On the basis of the analysis of global experience and basic theoretical approaches to e-learning, including the Lifelong Learning concept, the authors make a conclusion of the progressive growth of interest in different countries and regions. The e-learning is treated primarily as a tool to improve quality and efficiency of the educational process. The accuracy of understanding functions and peculiarities of e-learning allows one to determine a positive economic effect of its application for the university, the region, and the employers. The article shows organisational mechanisms and financial model of implementing e-learning in the Ural Federal University. The description is made of the cost options for open-type e-learning course development, investment parameters for their establishment, as well as costs of implementing educational programmes with the application of e-learning. The analysis of the activities of Ural Federal University on implementing e-learning gives the opportunity to further imagine the effect from the introduction of e-learning in other universities in the region. The results of the research may be applied in the institutions of secondary and higher education in the decision concerning the volume and form of the e-learning system