Использование пространственных эконометрических моделей при прогнозе регионального уровня безработицы
We consider forecasting unemployment in Russian and German region with the help of econometric panel data models. Using regional data from 2005 till 2012 we show that spatial panel data models perform better in terms of forecasting accuracy than other models (on average and at least for some distinct regions) such as non-spatial panel data models, pooled OLS, models without exploratory variables and naive forecasts (average value for one or several previous periods).
This book focuses on the questions of how territorial differences in productivity levels and unemployment rates arise in the first place and why territorial differences in labor market performance persist over time. Unemployment divergence and unemployment club convergence have been touched on in a large number of works and have recently also been studied using spatial econometric analysis. In this book we aim to develop the debate to include several important new topics, such as: the reasons why structural changes in some sectors cause slumps in some regions but not in others; the extent to which agglomeration factors explain regional imbalances; the degree of convergence / divergence across EU countries and regions; the role of labor mobility in reducing / increasing regional labor market imbalances; the impact of EU and country-level regional policy in stimulating convergence; and the (unsatisfactory) role of active labor market policy in stimulating labor supply in the weakest economic areas.
This chapter is devoted to the investigation of spatial spillover effects of the regional unem- ployment in Germany. Due to historical reasons the differences between eastern and western regions of Germany persist over time. We explore the differences in the determinants of the re- gional unemployment as well as the differences in spatial effects by estimating spatial models. We use panel data for 407 out of 413 German regions (using the NUTS III regional structure) for 2001 through 2009. In order to account for possible spatial interactions between regions, we use a spatial weighting matrix of inverse distances. We estimate static and dynamic models by the maximum likelihood estimation approach, developed by Anselin (1988) specifically for spatial models and elaborated by Lee and Yu (2010a), Lee and Yu (2010b). We reveal that the unemployment in western regions is more of disequilibrium nature, while the unemployment in eastern regions is more of equilibrium nature. Using System-GMM approach we estimate the extended specification of the dynamic model and find that the unemployment in eastern regions affects both the unemployment in western and eastern regions of Germany, whereas the unemployment in western regions has an impact only on other western regions.
The paper assesses factors of regional unemployment and spatial spillover effects in Germany. Using panel data for 407 out of 413 German regions for 2001 through 2009, we explore differences between eastern and western regions in spatial effects. We estimate static and dynamic spatial models by the maximum likelihood estimation approach, elaborated by Lee and Yu (2010). In order to account for possible spatial interactions between regions, we use a spatial weights matrix of inverse distances in the regressions. We base our analysis on a combined set of factors according to equilibrium and disequilibrium views of regional unemployment variance. We find that the unemployment is of both equilibrium and disequilibrium nature. By extending the specification of the dynamic model, we find that the unemployment in eastern regions of Germany affects both the unemployment in western and eastern regions, whereas the unemployment in western regions of Germany has an impact only on other western regions.
The question about possibilities to use Twitter users’ moods to increase accuracy of stock price movement prediction draws attention of many researchers. In this paper we examine the possibility of analyzing Twitter users’ mood to improve accuracy of predictions for Gold and Silver stock market prices. We used a lexicon-based approach to categorize the mood of users expressed in Twitter posts and to analyze 755 million tweets downloaded from February 13, 2013 to September 29, 2013. As forecasting technique, we select Support Vector Machines (SVM), which have shown the best performance. Results of SVM application to prediction the stock market prices for Gold and Silver are discussed.
Neural networks are applied to the longterm prediction of parameter variation. Regulation of the heat treatment of ferroconcrete is considered as an example. Experimental results are presented. An algorithm is proposed for planning the operation of the executive mechanism.
Group of authors sets out new directions of development of the national economy, considering these processes not only domestic but also global positions. This issue is covered in the dynamics, since historical periods and describing the situation at the present stage, the time series ends with the prospects of Russia's development in the future. Moreover, different time periods, intertwined, forming single interconnected system. From the perspective of the economic entity as a separate element of the unified economic system highlights the issues of forecasting activity of the enterprise as a tool to reduce the economic risks. The book can be recommended to senior executives, civil servants and teachers of higher educational institutions, graduate students and senior students of economic specialties.
The article deals with different ways of using technology to develop learners' skill of prediction, as one of the metalinguistic skills the recent National Educational Standard puts emphasis on. The use of short videos, Power Point and Wordle word clouds for the purpose is described.
Smoking is a problem, bringing signifi cant social and economic costs to Russiansociety. However, ratifi cation of the World health organization Framework conventionon tobacco control makes it possible to improve Russian legislation accordingto the international standards. So, I describe some measures that should be taken bythe Russian authorities in the nearest future, and I examine their effi ciency. By studyingthe international evidence I analyze the impact of the smoke-free areas, advertisementand sponsorship bans, tax increases, etc. on the prevalence of smoking, cigaretteconsumption and some other indicators. I also investigate the obstacles confrontingthe Russian authorities when they introduce new policy measures and the public attitudetowards these measures. I conclude that there is a number of easy-to-implementanti-smoking activities that need no fi nancial resources but only a political will.
One of the most important indicators of company's success is the increase of its value. The article investigates traditional methods of company's value assessment and the evidence that the application of these methods is incorrect in the new stage of economy. So it is necessary to create a new method of valuation based on the new main sources of company's success that is its intellectual capital.