Inflation Forecasting: The Practice of Using Synthetic Procedures

The article contains a review of inflation forecasting models, including the most popular class of models as one-factor models: random walk, direct autoregression, recursive autoregression, stochastic volatility with an unobserved component and of the integrated model of autoregression with moving average. Also, we discussed the possibilities of various modifications of models based on the Phillips curve (including the “triangle model”), vector autoregressive models (including the factor-extended model of B. Bernanke’s vector autoregression), dynamic general equilibrium models and neural networks. Further, we considered the comparative advantages of these classes of models. In particular, we revealed a new trend in inflation forecasting, which consists of the introduction of synthetic procedures for private forecasts accounting obtained by different models. An important conclusion of the study is the superiority of expert assessments in comparison with all available models. We have shown that in the conditions of a large number of alternative methods of inflation modelling, the choice of the adequate approach in specific conditions (for example, for the Russian economy of the current period) is a non-trivial procedure. Based on this conclusion, the authors substantiate the thesis that large prognostic possibilities are inherent in the mixed strategies of using different methodological approaches, when implementing different modelling tools at different stages of modelling, in particular, the multifactorial econometric model and the artificial neural network

National Models of Technological Development: a Comparative Analysis

In the article, suggestions are made for the development of methodological approaches to using factor analysis of technological development of countries and revealing the related weaknesses. The article presents an overview of the ideas for the study of such categories as national innovation system, its elements – the scientific and technological sector and approaches to efficiency measurement and comparative analysis of national innovation systems of different countries. For the purposes of assessing the scientific and technological potential of countries, a method of constructing a scientific-technological balance which links the efficiency of the national economy to the sphere of generation of knowledge and technologies, is proposed. Analysis of the relative scientific and technological parameters showed that each country has its advantages and disadvantages for research and technological development. In particular, in China, the scale of research sector is not adequate to the scale of the national economy and its growth rate; Poland has been experiencing low returns from the sphere of applied research; in Russia the bottleneck for scientific and technological development is low efficiency of the scientific work expressed in the publication activity. Overall, the study showed that the scientific and technological balance constructing method is a successful one in assessing the impact of knowledge generation and technology development on the level of productivity in the economy

Risk Considerations in the Scenarios of Personal Income Tax Reform

The article deals with the problem of choosing one of the four scenarios of personal income tax reform. Three political factions (A Just Russia, the LDPR and the Communist party of the Russian Federation) advocate the introduction of a progressive income tax scale, while the Government of the Russian Federation offers to raise the flat rate from 13 to 15%. Each of these scenarios is characterized by the risk of non-compliance, which is necessary to consider when building a system of priorities for existing tax reform projects. The article proposes a questionnaire survey procedure that allows one to obtain expert estimates of the feasibility of these projects. The authors developed a generalized criterion for the effectiveness of the reform project in a multiplicative form. It takes into account the potential fiscal and social impact and reliability of each reform. The expert survey conducted by the authors and the quantitative estimates of the degree of reliability of tax reform projects made it possible to carry out applied calculations of the generalized criterion of the effectiveness of the available four variants of tax changes. The results of the calculations showed that the most optimal project is the project of the Government of the Russian Federation, involving the preservation of a flat scale with a slight increase in the standard rate. Projects envisaging the introduction of a progressive income tax scale have more modest estimates of the actual (real) performance. The ranking system for the projects based on the quantitative assessments produced the same result as the previously conducted simpler procedure for qualitative assessment of project risks. The main conclusion of the article is that it is premature to introduce progressive income tax in Russia. Such reform should be a matter of the more distant future.В статье рассмотрена проблема выбора одного из четырех проектов реформы подоходного налогообложения – трех политический фракций (партия «Справедливая Россия», ЛДПР и КПРФ), выступающих за введение прогрессивной шкалы подоходного налога, и Правительства Российской Федерации, предлагающего повысить ставку плоской шкалы с 13 до 15 %. Каждый из указанных сценариев характеризуется риском невыполнения, что должно быть учтено при построении системы приоритетов в отношении имеющихся проектов налоговой реформы. В статье предлагается процедура анкетного опроса, позволяющая получить экспертные оценки степени реализуемости рассматриваемых проектов. Авторы предлагают обобщенный критерий результативности проекта реформы в мультипликативной форме, который предполагает учет его потенциального фискально-социального эффекта и уровня надежности. Проведенный авторами экспертный опрос и полученные на его основе количественные оценки степени надежности проектов реформы позволили провести прикладные расчеты обобщенного критерия результативности имеющихся четырех вариантов налоговых изменений. Результаты расчетов показали, что самым предпочтительным проектом является проект Правительства Российской Федерации, предполагающий сохранение плоской шкалы с незначительным увеличением базовой ставки; проекты, связанные с введением прогрессивной шкалы подоходного налога, имеют более скромные оценки фактической (реальной) результативности. Построенная система ранжирования проектов на основе количественных оценок дала такой же результат, как проведенная ранее более простая процедура качественной оценки проектных рисков. На основе проведенного исследования авторы сделали вывод о преждевременности введения прогрессивного подоходного налога и налога на доходы физических лиц; подобная реформа должна стать делом более отдаленного будущего.Статья подготовлена в рамках государственного задания Правительства Российской Федерации Финуниверситету на 2018 год (проект АААА-А18-118052490046-4 «Разработка оптимальной модели подоходного налогообложения и оценка ее влияния на социальное неравенство в России»

Application of Neural Networks for Forecasting Inflation: New Opportunities

The article presents an overview of the latest achievements of neural networks in relation to the problem of inflation forecasting. It is shown that in many cases the accuracy of the forecasts obtained by neural network methods is higher than the accuracy of the forecasts obtained by traditional methods of economic science. Neural networks beat econometric instruments in accuracy of calculations, but lack meaningful theory. This contradiction can be eliminated by combining two types of predictive tools. In the article the authors propose a two-step model of short-term inflation forecasting. The essence of the authors’ approach is to build a small (fivefactor) econometric model of inflation, which has good statistical characteristics and provides an adequate theoretical explanation of the modeling process, but it does not allow for predicting the monthly rate of inflation with high accuracy. The authors show that this problem is typical of modern macroeconomics and is an individual manifestation of the so-called fundamental problem of data attribution in macro models. The problem has no solution in the framework of traditional macroeconomic models. In this regard, to improve the accuracy of forecasts the application of a neural network makes it possible to refine the calculations and bring their quality to the required level. The advantages of the proposed scheme are discussed in the conclusion.В статье представлен обзор последних достижений нейронных сетей применительно к задаче прогнозирования инфляции. Показано, что во многих случаях точность прогнозов, полученных с помощью нейросетевых методов, оказывается выше точности прогнозов, полученных традиционными методами экономической науки. Поднимается вопрос о глубинном противоречии между традиционным эконометрическим инструментарием и нейронными сетями, так как первые проигрывают вторым по точности расчетов, а вторые по сравнению с первыми не имеют под собой никакой осмысленной теории. Вместе с тем авторы показывают, что указанное противоречие может быть снято путем объединения двух видов прогнозного инструментария. В развитие данного тезиса в статье предложена двухшаговая модель краткосрочного прогнозирования инфляции. Сущность авторского подхода состоит в построении малоразмерной (пятифакторной) эконометрической модели инфляции, которая обладает хорошими статистическими характеристиками и дает адекватное теоретическое объяснение моделируемому процессу, однако при этом не позволяет прогнозировать месячные темпы инфляции с высокой точностью. Авторами показано, что данная проблема является типичной для современной макроэкономики и представляет собой частное проявление так называемой фундаментальной проблемы атрибуции данных в макромоделях. В статье показано, что данная проблема не имеет решения в рамках традиционных макроэкономических моделей. В связи с этим для повышения точности прогнозов был использован своеобразный вычислительный фильтр в виде нейронной сети, обучение которой позволило для отобранных факторов инфляции провести калибровку расчетов и довести их качество до необходимого уровня. Показаны преимущества предложенной схемы последовательного сопряжения эконометрической модели и нейронной сети.Статья подготовлена в рамках Государственного задания Правительства РФ Финансовому университету на 2018 год (тема «Методика оценки влияния немонетарных факторов на динамику инфляции», шифр АААА-А18-118052490081-5

Modern trends in identification of causative agents in infective endocarditis

Advances in the diagnosis and treatment of patients with infectious endocarditis are limited by the high frequency of cases with an unknown etiology and imperfection of microbiological (cultural) methods. To overcome these problems new approaches to the identification of infectious endocarditis pathogens were introduced, which allowed achieving certain positive results. However, it should be noted that despite the wide variety of diagnostic tools currently used, there is no ideal method for etiological laboratory diagnosis of infectious endocarditis. The article discusses the features and place of immunochemical, molecular biological (MALDI-TOF MS, real-time PCR, sequencing, in situ fluorescence hybridization, metagenomic methods, etc.), immunohistochemical methods, and their advantages and limitations

T-cadherin and the ratio of its ligands as predictors of carotid atherosclerosis: A pilot study

In the cardiovascular system, atherogenic low-density lipoproteins (LDL) and the protective hormone adiponectin bind to the same receptor, T-cadherin. In this study, we tested the hypothesis that the ratio of circulating LDL to high-molecular weight (HMW) adiponectin could predict the development of atherosclerosis. Using enzyme-linked immunosorbent assay, we measured the level of circulating HMW adiponectin in the blood of donors together with ultrasound measur-ing of intima-media thickness (IMT) of carotid arteries. Single-nucleotide polymorphisms in the T-cadherin gene were identified using polymerase chain reaction. We found that carotid artery IMT is inversely correlated with the level of HMW in male subjects. We also found that the G allele of rs12444338 SNP in the T-cadherin gene correlates with a lower level of circulating T-cadherin and thinner IMT and therefore could be considered as an atheroprotective genotype. Despite our data, we could not provide direct evidence for the initial study hypothesis. However, we did uncover an important correlation between circulating T-cadherin and thinner carotid IMT. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

ECG recordings of cardiac pacing in mice carriyng TRPV1

The data are ECG recordings acquired from mice whose cardiac muscle tissue carries the human TRPV1 channel. ECG was recorded with standard procedure on the limbs with disposable electrodes, with one or two electrodes. Myocardial stimulation was applied with an IR laser. Each archive contains the result of an ECG recording of one animal. Initial recordings are cut so that the unsuccessful recordings are excluded. File name Recording date Vector type Vector Amount No1 2022 06 22 AAV488 6x10-11 No2 2022 06 16 AAV479 6x10-12 No3 2022 06 22 AAV488 6x10-11 No4 2021 10 1