Review of Economics and Statistics最新文献

{"title":"Corrigendum: Measuring Uncertainty and Its Impact on the Economy","authors":"Andrea Carriero, Todd E. Clark, Massimiliano Marcellino","doi":"10.1162/rest_e_01172","DOIUrl":"https://doi.org/10.1162/rest_e_01172","url":null,"abstract":"Abstract Carriero, Clark, and Marcellino (2018, CCM2018) used a large BVAR model with a factor structure to stochastic volatility to produce an estimate of time-varying macroeconomic and financial uncertainty and assess the effects of uncertainty on the economy. The results in CCM2018 were based on an estimation algorithm that has recently been shown to be incorrect by Bognanni (2022) and fixed by Carriero et al. (2022). In this corrigendum we use the algorithm correction of Carriero et al. (2022) to correct the estimates of CCM2018. Although the correction has some impact on the original results, the changes are small and the key findings of CCM2018 are upheld.","PeriodicalId":48456,"journal":{"name":"Review of Economics and Statistics","volume":"18 1","pages":"619a-619k"},"PeriodicalIF":8.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64436500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Review of Economics and Statistics 2022 Annual Report","authors":"","doi":"10.1162/rest_e_01173","DOIUrl":"https://doi.org/10.1162/rest_e_01173","url":null,"abstract":"","PeriodicalId":48456,"journal":{"name":"Review of Economics and Statistics","volume":"104 1","pages":"i-ii"},"PeriodicalIF":8.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45831099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global Trends in Differentiation of Population Income","authors":"D. А. Huchmazova","doi":"10.21686/2500-3925-2022-2-36-42","DOIUrl":"https://doi.org/10.21686/2500-3925-2022-2-36-42","url":null,"abstract":"Purpose of the study. Identification of global trends in inequality in the distribution of the population income. In accordance with the goal, the following tasks are set: 1) to examine current international research that addresses the problem of income distribution inequality of the population; 2) assess the differentiation of the population income at the global and regional levels; 3) on the basis of the Gini and Theil indexes, to analyze the dynamics of income inequality of the population within and between countries of the world.Materials and methods. In the process of preparing the article, theauthor used data from international reports, analytical statistical materials, scientific works of Russian and foreign scientists. The scientific methods of cognition were used in the work: analysis (to assess changes in indicators of income inequality of the population), synthesis (to determine the relationship between inter-country and intra-country income inequalities of the population), graphical (to build graphs that reflect the dynamics of changes in the distribution of national income and assets among the population, Gini coefficient, Theil index). These methods made it possible to identify the scale and trends in the differentiation of the population income in the world.Results. The problem of uneven distribution of the population income was investigated. It has been established that inequality in the population income differs significantly between regions of the world, and the level of inequality of the population in terms of income within countries is much higher than the level of inequality between countries. An assessment of the current state is given and trends in the differentiation of the population income in the world based on the Gini index and the Theil index are revealed.Conclusion. It has been established that the problem of income differentiation of the population is in the focus of attention of both the scientific community and international organizations, namely: the United Nations, the Organization for Economic Cooperation and Development, the World Bank, Oxfam. The level of differentiation of the population by income between regions of the world differs significantly. The scale of global income inequality of the population now has reached the level that was observed during the heyday of Western imperialism. With the help of the Gini and Theil indexes, it was revealed that intra-country inequality is significantly greater than the inter-country income inequality of the population.","PeriodicalId":48456,"journal":{"name":"Review of Economics and Statistics","volume":"3 1","pages":""},"PeriodicalIF":8.0,"publicationDate":"2022-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82307846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intelligent Data Processing Methods for the Atypical Values Correction of Stock Quotes","authors":"T. Zolotova, D. A. Volkova","doi":"10.21686/2500-3925-2022-2-","DOIUrl":"https://doi.org/10.21686/2500-3925-2022-2-","url":null,"abstract":"Purpose of the study. The purpose of the study is to carry out a comparative analysis of various methods for correcting atypical values of statistical data on the stock market and to develop recommendations for their use.Materials and methods. The article analyzes Russian and foreign bibliography on the research problem. Consideration of machine learning methods for detecting and correcting outliers in time series is proposed. The mathematical basis of machine learning methods is the Z-score method, the isolation forest method, support vector method for outlier detection, and winsorization and multiple imputation methods for outlier correction. To create the models, the Jupyter Notebook software tool, which supports the Python programming language, was used. To implement machine-learning methods, data from stock quotes of the Moscow Exchange are used.Results. The results of machine learning algorithms are demonstrated for sets of real statistical data representing the closing prices of shares of three Russian companies “Sberbank”, “Aeroflot”, “Gazprom” in the period from 01.12.2019 to 30.11.2020, obtained from the website of the Investment Company “FINAM”. A comparative analysis of methods for detecting and correcting outliers by standard deviation has been carried out. The Z-score statistical method allows you to accurately determine the distance from the suspicious observation to the distribution center, which is an advantage. The disadvantage of this method is the influence of outliers on the mean and standard deviation, which can contribute to the masking of outliers or their incorrect detection. The isolation forest method recognizes outliers of various types, and when implementing the method, there are no parameters that require selection; but the disadvantage is the slower detection rate of outliers compared to other methods. The support vector machine is a very fast method and is reduced to solving a quadratic programming problem, which always has a unique solution. The winsorization method for correcting outliers reduces the effect of outliers on the mean and variance, which is an advantage, but may introduce bias due to the selection of thresholds to separate observations in the sample. The multiple imputation method creates for each missing value not one, but many imputations, which avoids a systematic error, but at the expense of high computational costs. For the initial data used in the work, the best result was shown by the implementation of the multiple imputation algorithm based on the detected outliers by the support vector method.Conclusion. There is no universal method for detecting and/or eliminating outliers in data analysis theory. In general, the determination of outliers is subjective, and the decision is made individually for each specific dataset, considering its characteristics or existing experience in this area. The practical implementation of the methods for detecting and eliminating outliers used in this work can be","PeriodicalId":48456,"journal":{"name":"Review of Economics and Statistics","volume":"56 1","pages":""},"PeriodicalIF":8.0,"publicationDate":"2022-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72676881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Econometric analysis and modeling of the dynamics of the balance of payments’ development in Azerbaijan","authors":"N. Ayyubova","doi":"10.21686/2500-3925-2022-2-14-22","DOIUrl":"https://doi.org/10.21686/2500-3925-2022-2-14-22","url":null,"abstract":"Purpose of the study. The study is devoted to econometric analysis and modeling of the dynamics of the balance of payments’ development of Azerbaijan, the formation of a mathematical and statistical trend that can give a perspective assessment of the development of the balance of payments. In accordance with the goal, the tasks of choosing the best composition of explanatory factors for the model were set, using the characteristics and criteria of correlation and regression analysis, econometric tests, calculating estimates of the nature and closeness of the relationship between the explanatory factors, dependent and independent factors, testing the stationarity of the series.Materials and methods. The official statistical data of the State Statistics Committee and the Central Bank of Azerbaijan, scientific works and studies of scientists, specialists, both Azerbaijani and foreign, in the fields of economics, mathematical and economic modeling were used. For the empirical analysis of non-stationary time series, statistical methods of information processing are used inthe work; to check the adequacy and test the multivariate model, the appropriate criteria and modern econometric procedures are used, taking into account the impact of exogenous factors. For calculations, application packages such as Excel and Eviews 8 were used.Results. A multivariate regression model has been created that makes it possible to conduct an economic and statistical analysis of the dynamics of the current account of the balance of payments; the form and directions of the functional relationship between dependent and independent variables were determined, variability of variables was estimated, the results of multivariate regression analysis using econometric methods were analyzed; the quantitative characteristics of the mechanisms of influence of explanatory factors on the balance of payments were measured and interpreted; correlation dependencies for causal dependencies were investigated in the model, the Granger test was performed and factors were identified that reliably explain the outcome with high probabilities based on the Fisher criterion; the stationarity of the model was measured based on the Dickey-Fuller test. With differences of the first and second degree, the stationarity of the autoregressive model was determined based on the Student’s criterion by changing the lag value. In the process of modeling, the initially constructed model, covering the years 1995-2017 with five factors such as foreign investment, exports, imports, manat exchange rate, general investments, showed insufficient adequacy, that is, non-stationarity of the current account series of the balance of payments. The exchange rate of the national currency, which is involved in the model as an explanatory factor, subjected the values of the dependent series to large fluctuations, an increase in the variance in the residue, which created non-stationarity and which can be explained by the denom","PeriodicalId":48456,"journal":{"name":"Review of Economics and Statistics","volume":"34 1","pages":""},"PeriodicalIF":8.0,"publicationDate":"2022-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87448409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mortality in the Volgograd Region Against the COVID-19 Pandemic","authors":"A. Alpatov","doi":"10.21686/2500-3925-2022-2-23-35","DOIUrl":"https://doi.org/10.21686/2500-3925-2022-2-23-35","url":null,"abstract":"The COVID-19 pandemic, which began in Russia in March 2020, had a huge impact on socio-economic processes. In numerous studies analyzing mortality caused by coronavirus infection, it is concluded that the number of deaths is underestimated. The high morbidity and mortality caused by coronavirus infection has far-reaching consequences for the economy of the regions and the country as a whole: deterioration in health, a decrease in the working-age population, a change in the structure of consumption of goods and services, etc. In this regard, it is relevant to analyze the processes associated with mortality from coronavirus infection.The purpose of the study is to identify the main trends in the nosological and age-sex structure of mortality in the Volgograd region in the years preceding the COVID-19 pandemic, to assess the contribution of mortality from coronavirus infection to total mortality in 2020. Estimation of excess mortality was carried out taking into account the dynamics of age-specific mortality rates.Materials and methods. The main sources of information for the study of mortality were the Russian database on fertility and mortality and Rosstat data. In the work, when analyzing mortality from COVID-19, data from the operational headquarters were also used. The analysis of the mortality dynamics was carried out using such indicators as the average life expectancy at birth, the crude death-rate, age-specific mortality rates in absolute and  relative (per 1000 people) terms. The processing of statistical data was carried out using the Microsoft Excel application package and matplotlib, pandas, numpy (Python programming language), pyramid (R programming language) libraries.Results. In 2020, the number of deaths in the Volgograd region turned out to be more than in 2019 by 6647 people. If the trends in the dynamics of the intensity of mortality would persist in the year of the pandemic, then the total number of deaths in the Volgograd region would be equal to 32044 people. In this case, the excess mortality would have amounted to 7368 people.Conclusion. As a result of the study, it was revealed that a significant increase in the number of deaths in the Volgograd region during the pandemic is explained by Rosstat as the cause of coronavirus infection by only 33.2%. This discrepancy may be the result of incorrect accounting of deaths from coronavirus infection. Another factor in the increase in mortality during a pandemic may be a decrease in the quality of medical care. There has been a reorientation of the work of medical institutions to the treatment of patients with coronavirus infection; the burden on emergency medical care has increased.","PeriodicalId":48456,"journal":{"name":"Review of Economics and Statistics","volume":"27 1","pages":""},"PeriodicalIF":8.0,"publicationDate":"2022-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86897943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimating the Effect of Transaction Costs Using the Tick Size as a Proxy","authors":"Espen Sirnes","doi":"10.1515/roe-2021-0015","DOIUrl":"https://doi.org/10.1515/roe-2021-0015","url":null,"abstract":"Abstract A method is proposed for estimating the effect of transaction costs on volatility, using the tick size as a proxy. The method involves three steps: (1) collect only the cases in which the tick size changes from one regime to another; (2) estimate the effect with and without the order book size; and (3) use local data on the tick size and volatility but instruments from international markets. The first step handles stationarity and dependence. The second step is used to infer the effect of a symmetric transaction cost as the tick size is a revenue and not a cost for liquidity providers. Regressions with and without the order book may therefore indicate the extent to which this asymmetry is likely to affect the result. The third step handles endogeneity. The method is applied to intraday data from the Norwegian Stock Exchange. The results show that both the tick size and the inferred transaction costs have no significant effect on volatility.","PeriodicalId":48456,"journal":{"name":"Review of Economics and Statistics","volume":"1 1","pages":"57 - 77"},"PeriodicalIF":8.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83564072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Frontmatter","authors":"","doi":"10.1515/roe-2022-frontmatter1","DOIUrl":"https://doi.org/10.1515/roe-2022-frontmatter1","url":null,"abstract":"","PeriodicalId":48456,"journal":{"name":"Review of Economics and Statistics","volume":"18 1","pages":""},"PeriodicalIF":8.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77319419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cognitive Modeling of the Impact of Funding to Educational Institutions on the Innovative Activity of Organizations","authors":"A. A. Bryzgalov","doi":"10.21686/2500-3925-2022-1-62-68","DOIUrl":"https://doi.org/10.21686/2500-3925-2022-1-62-68","url":null,"abstract":"The purpose of research is to design a cognitive model for determining the degree of influence of targeted funding in educational programs on the innovative activity of an enterprise in different business conditions. As a tool for cognitive modeling, it is proposed to use the tools for constructing a cognitive map that allows analyzing different options of financing scenarios, which are alternatives to impulse modeling in the form of financing in a certain set of factors by introducing perturbations to the vertices of the cognitive map. The main reason for the study is that when creating new products or services for an organization, it is important to constantly increase their market share based on changes in the strategy of innovative activity of the enterprise, which is largely determined by the level of qualification of the workforce. The novelty of the research lies in the use of tools for constructing and using a cognitive map to solve the problem of substantiating the most preferred variant of a set of initial factors to achieve the required maximum values of the target indicators.The research methods are heuristic in nature, aimed at finding such a set of factors that will lead to a given change in the target factor. In order to obtain the final result of changing the target factor, impulse modeling is used, which is carried out by introducing influences into the selected set of vertices of the cognitive map, and in order to find the best set, scenario modeling is used aimed at forming various alternatives. The proposed materials and methods of cognitive modeling are based on the cognitive map, presented in the work of R.Karaev and others [4].Results. This article shows how organizations develop their innovative activities in production processes. This development process is associated with the interaction of enterprises and educational institutions, which is expressed in the joint training of specialists in the required field. To display the interrelation of factors influencing innovation activity in production processes, a model is proposed, which is reflected in the cognitive map of enterprise strategy management expanded by the author. As a result of cognitive modeling according to certain scenarios, recommendations are formed for decision makers on the choice of an innovative development strategy of an enterprise aimed at increasing the company’s market share.Conclusion. The conducted modeling and analysis of the results confirm that innovative activity allows to increase the market share and reduce the price of the company’s products due to investments in educational institutions. In addition to the required changes in the target factors, the proposed funding has a positive effect on other factors reflected in the cognitive map. As a result, the constructed cognitive map can reveal the factors determining the need for investment in educational institutions by organizations, which will increase their innovative activity and economic e","PeriodicalId":48456,"journal":{"name":"Review of Economics and Statistics","volume":"53 3","pages":""},"PeriodicalIF":8.0,"publicationDate":"2022-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72485808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Effectiveness of Research and Development in the Field of Transport and Space Systems in Russia: Analysis of Publication Activity","authors":"V. Zavarukhin, T. I. Сhinaeva, E. Churilova","doi":"10.21686/2500-3925-2022-1-28-45","DOIUrl":"https://doi.org/10.21686/2500-3925-2022-1-28-45","url":null,"abstract":"The aim of the study. Federal target program “Research and development in priority areas of development of the scientific and technological complex of Russia for 2014-2021” defines transport and space systems as a priority area of strategic importance for the country’s economy. The aim of the work is to study the state of research and development in the field of study and development of transport and space systems based on performance analysis, as well as to compare the effectiveness of scientific activities of educational organizations of higher education and scientific organizations in this area.Materials and methods. The information base of the study was statistical data and analytical information reflecting the state of research and development in the field of study and development of transport and space systems. The methodological base of the study is statistical methods of information analysis: analysis of variance, testing of statistical hypotheses, non-parametric criteria for comparing samples, analysis of time series, structural analysis.Results and discussion. The article reflects the results of the Institute for the Study of Science of the Russian Academy of Sciences monitoring the scientific potential of organizations conducting research and development in the priority area of scientific and technological development “Connectedness of the territory of the Russian Federation through the creation of intelligent transport and telecommunication systems, as well as the occupation and retention of leadership positions in the creation of international transport and logistics systems, the development and use of outer space and air space, the World Ocean, the Arctic and Antarctic”. This publication, in particular, analyzes the effectiveness of research and development in the priority area “Transport and space systems”.As a result of the analysis, conclusions were drawn about the main directions and trends of research and development in the field of studying and developing transport and space systems in Russia for the period 2015-2019. With the help of methods of dispersion analysis, nonparametric criteria, etc., a comparison was made of the effectiveness of scientific activity of educational organizations of higher education and scientific organizations.The analysis showed that international publishing analytical systems occupy a greater weight in the volume of publications compared to the Russian Science Citation Index (RSCI).Researchers of educational organizations of higher education have 5 times more publications than employees of scientific organizations, which can be explained by overestimated requirements for positions of faculty and the formation of “garbage” articles. In terms of citation, 2017 was the most successful year for Russian researchers in the field of transport and space systems. At the same time, the citation of researchers from educational organizations was 3-3.5 times higher in international publications and twice as hig","PeriodicalId":48456,"journal":{"name":"Review of Economics and Statistics","volume":"11 1","pages":""},"PeriodicalIF":8.0,"publicationDate":"2022-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77640405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}