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Regular version of the site
Of all publications in the section: 177
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Article
Левина И. А. Прикладная эконометрика. 2013. Т. 29. № 1. С. 3-28.

The paper provides regression analysis of data on registration of orphans in Russian regions in 1999–2006. The purpose of analysis is to understand what factors — cultural, economic, political and, maybe, some else — influence the quantity of orphans yearly recorded in Russian regions. The analysis confirms hypotheses about significant influence of cultural and political factors on the acuity of orphanhood problem in Russian regions. The impact of economic factors on the acuity of orphanhood problem in Russia is ambiguous.

Added: Sep 24, 2014
Article
Козлов А. Ю., Шишов В. Ф., Мхитарян В. С. Прикладная эконометрика. 2010. № 3(19).
Added: Feb 20, 2011
Article
Пеникас Г. И. Прикладная эконометрика. 2008. № 4. С. 3-26.

The paper aims at finding the most optimal individual, collective, and combined yield curve forecasting models. It is shown that incorporating macroeconomic information improves the model's goodness-of-fit characteristics. It is also proved that combined forecasts perform better on average when are based upon weights for individual ones.

Added: Oct 14, 2012
Article
Польдин О. В. Прикладная эконометрика. 2011. Т. 1. № 21. С. 56-69.

This paper presents the results of econometric study on predicting first-year grade point average and dropout probability with national examination (EGE) results at the bachelor program in Economics in the Higher School of Economics. The use of a sum of four exams - math, social studies, Russian language and foreign language - shows worse fitting than a sum of three exams, excluding foreign language. In models with separate exams as regressors, the greatest effect on dependent variable provides math grades.

Added: Sep 3, 2012
Article
Лозинская А. М., Редькина А. Ю., Шенкман (Попова) Е. А. Прикладная эконометрика. 2020. Т. 60. С. 5-25.

In the article, a medium-term forecast of electricity consumption is built on monthly data from January 2008 to September 2019 for all regions of the Urals integrated power system. A key feature of the work is the use of linear combinations of forecasts that are produced with time series basic models with deterministic and stochastic seasonality. The proposed methodology demonstrates a high and robust forecast accuracy in comparison with the basic models and can be applied by various players in the electricity market.

Added: Sep 24, 2020
Article
Щетинин Е. И., Назруллаева Е. Ю. Прикладная эконометрика. 2012. № 4. С. 63-84.
Added: Mar 27, 2013
Article
Архипов Р. Ю., Катышев П. К. Прикладная эконометрика. 2016. Т. 44. С. 38-49.

We consider the problem of cointegration of the macro indices of Russian economy (GDP, money aggregate M2, budget expenses, real effective exchange rate) and electric power generation. It is assumed that on time interval (1999–2015) under consideration a structural change (regime shift) is allowed, and as a result the cointegration relationship may be changed. The existence of cointegration is established and the moment of the structural change is estimated.

Added: Oct 22, 2018
Article
Архипов Р. Ю. Прикладная эконометрика. 2016. Т. 44. С. 38-49.

We consider the problem of cointegration of the macro indices of Russian economy (GDP, money aggregate M2, budget expenses, real effective exchange rate) and electric power generation. It is assumed that on time interval (1999–2015) under consideration a structural change (regime shift) is allowed, and as a result the cointegration relationship may be changed. The existence of cointegration is established and the moment of the structural change is estimated.

Added: Feb 26, 2018
Article
Демидова О. А. Прикладная эконометрика. 2014. Т. 34. № 2. С. 19-35.

The present study suggests a generalization of the spatial autoregressive model for the case when considered regions are split into two different groups, which have a mutual influence on each other. The weighted matrix in this model is split into four parts and four spatial coefficients are estimated. The proposel model is applied for the analysis of three macroeconomic indicators using the data for Russian regions, previously divided into western and eastern. Our analysis revealed, 1) a positive spatial correlation of the main macroeconomic indicators for the western regions, 2) both positive and negative externalities for the eastern regions and 3) the asymmetric influence of eastern and western regions on each other. Usually "impulses" from the western regions have a positive effect on the eastern regions, but the "impulses" from the eastern regions usually do not affect the western regions.

Added: Apr 21, 2014
Article
Борзых Д. А., Хасыков М. А. Прикладная эконометрика. 2018. Т. 51. С. 126-139.

We suggest a hybrid algorithm for structural breaks detection when using a class of piecewise-specified GARCH(1,1) models. The algorithm comprises two steps. In the first step the moments of structural breaks are detected using KL-ICSS method based on (Kokoszka, Leipus, 1999) and (Inclán, Tiao, 1994). In the second step previously detected moments of structural breaks are refined with the help of a modified MML method. Therefore, the whole procedure is called ML-KL-ICSS algorithm. We also provide five numeric experiments to show the overall performance of the proposed procedure. Four of five experiments show that ML-KL-ICSS method is significantly more accurate in detecting structural breaks as opposed to one-step procedures. In one experiment the accuracy of both methods was comparable but ML-KL-ICSS method performed slightly better. Finally, we test our method using real data. In order to do that we detect structural breaks in common stocks returns volatility for the Russian “Gazprom” company. Detected moments of structural breaks correspond to significant events in the Russian economy.

Added: Sep 9, 2018
Article
А.В. Аистов, Е.А.Александрова Прикладная эконометрика. 2016. Т. 43. С. 5-28.

In this article we introduce econometric model specification that describes time-distributed treatment effect basing on the difference-in-differences approach. It gives us possibility to control for mobility in estimates of wage returns to professional training on the data of a Russian enterprise of 2006–2010. We show that wage growth after some kinds of professional trainings is well explained by the mobility

Added: Oct 14, 2016
Article
Засимова Л. С., Коссова Е. В. Прикладная эконометрика. 2016. Т. 42. № 2. С. 75-99.

The paper uses econometric tools (two-part model, Tobit model, Heckman model) to evaluate factors associated with consumer choice on the Russian pharmaceutical market. Using data from national public opinion survey conducted in 2014 by Levada Center we show that gender, health, retirement and single mother’s status are strongly associated with high expenditures on medicine. Incomes are positively associated with probability of spending on medicine, but marginal effect of incomes is small.

Added: Sep 8, 2016
Article
Макшанчиков К. Н. Прикладная эконометрика. 2020. Т. 60. С. 115-138.

This study aims to examine how Russian adults make their choices about expenditures on non-professional sports to improve their health. The data was taken from Levada-Center survey on the attitude of people to their health and the quality of medical care in Russia, conducted in 2017. Probabilistic models of binary choice, Heckman selection model and Semiparametric model by Newey were employed. The results of the study showed positive relationship between expenditures on sports and individual’s income. Gender, age, profession, rural and entourage were among other factors that determined individual expenditures on sport.

Added: Oct 2, 2020
Article
Румянцева Е. В., Фурманов К. К. Прикладная эконометрика. 2017. Т. 49. № 4. С. 22-43.

Time to realisation of mortgage property is studied using data from Russian mortgage agency. Factors indicating high risk of non-realisation are revealed. Obtained estimates indicate that time to realisation is determined mainly by a loan-to-value ratio, a type of mortgage property and its location in economically developed region.

Added: Sep 11, 2018
Article
Пересецкий А. А. Прикладная эконометрика. 2008. № 3. С. 3-14.
Added: Dec 26, 2010
Article
Дарховский Б. С., Айвазян С., Березняцкий А. и др. Прикладная эконометрика. 2015. Т. 39. № 3. С. 84-105.
Added: Mar 14, 2017
Article
Сидоровых А. С. Прикладная эконометрика. 2015. Т. 37. № 1. С. 43-56.

The paper analyzes the key determinants of real estate prices in Perm, with special attention to transport accessibility indicators. The issue of transport accessibility modeling is discussed. The valuation of  price hedonic model revealed that housing prices in Perm are affected mostly by the area of the apartment, the fact of its location on the first floor, number of public transport routes in the district, and time to the city centre

Added: Dec 5, 2015
Article
Шульгин А. Г. Прикладная эконометрика. 2014. Т. 36. № 4. С. 3-31.

This paper presents a three-sector DSGE model for a small open economy under the intermediate exchange rate regime. The central bank balance sheet equations are added to allow introducing two different monetary policy rules in the model. The principal question is how many independent monetary policy rules do we need to describe Russian monetary policy in 2001–2012. To get an answer we perform Bayesian estimation of the DSGE model for four different combinations of monetary policy rules. The main finding of the paper is that describing dynamics of 14 observable variables requires using Taylor rule together with the exchange rate adjustment rule. Two rules do not make an overdeterminacy; they have original transmission channels and reflect two different stabilization principles: output and inflation stabilization (Taylor rule) vs. balance of payments stabilization (exchange rate-based rule).

Added: Oct 10, 2014
Article
Засимова Л. С., Коссова Е. В., Рязанова М. Д. Прикладная эконометрика. 2014. № 34(2). С. 95-119.

The paper discusses factors that have impact on individual attitudes towards bans on smoking in a number of public places — hospitals, universities, work sites, sports facilities, cafes and restaurants, bars and clubs. Using data from national public opinion survey conducted in 2011 by Levada Center for HSE we show that support of smoking bans varies across types of public places and depends on different social and economic characteristics of individuals. Smoking is an important but not the only determining factor.

Added: Aug 5, 2014
Article
Котырло Е. С. Прикладная эконометрика. 2017. № 3. С. 74-99.

Study of users and their segmentation, based on users’ preferred topics of discussion and their networking, is the unique opportunity offered by social networks. Variety of approaches to social media analysis based on social network analysis and text mining is summarized in the paper. It is extended by concentration index application and visualizing of the results of social network analysis.

The study of a model set exhibits that: 1) users can be successfully segmented on the base of their most mentioned topics, which is useful for a product placement and other commercial purposes; 2) distribution of number of posts by authors is highly uneven regardless to the topic of discussion; 3) users connected on-line typically live in the same geographical area; 4) users’ number of posts and centrality indices are correlated.

Added: Oct 20, 2017
Article
Валеева Д. Р., Польдин О. В., Юдкевич М. М. Прикладная эконометрика. 2014. № 34(2). С. 80-94.

We estimate the correlation between student’s choice of specialization and the choices of the students connected by social ties. We use data on students of Economics department at one of the Russian universities and show that the choice is linked with the choice of friends as well as study assistants. The strongest effect is produced by those friends that are study assistants at the same time and those that have similar academic achievements. Mutual friendship ties show more significant effect than non-mutual ties. Results allow us to understand better the mechanisms of peer effects in choice of concentration.

Added: Jun 16, 2014