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What Opportunities Do New Technologies Bring About for Price Statistics? 新技术为价格统计带来哪些机遇?
Russian Journal of Money and Finance Pub Date : 2021-03-01 DOI: 10.31477/RJMF.202101.120
V. Bessonov
{"title":"What Opportunities Do New Technologies Bring About for Price Statistics?","authors":"V. Bessonov","doi":"10.31477/RJMF.202101.120","DOIUrl":"https://doi.org/10.31477/RJMF.202101.120","url":null,"abstract":"The paper discusses new opportunities for Russian price statistics that present-day information and communication technologies bring about. The paper is a response to the study Isakov et al. (2021) dedicated to the effort of developing a toolset to build a price quotation database through automated internet data collection and construction of consumer price indexes based on it. Discussed are the potential implications of this activity for price statistics.","PeriodicalId":358692,"journal":{"name":"Russian Journal of Money and Finance","volume":"41 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131519766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Asymmetric Effects of Monetary Policy on the Armenian Economy 货币政策对亚美尼亚经济的不对称效应
Russian Journal of Money and Finance Pub Date : 2021-03-01 DOI: 10.31477/RJMF.202101.46
H. Igityan
{"title":"Asymmetric Effects of Monetary Policy on the Armenian Economy","authors":"H. Igityan","doi":"10.31477/RJMF.202101.46","DOIUrl":"https://doi.org/10.31477/RJMF.202101.46","url":null,"abstract":"Whether inflation and output respond symmetrically or asymmetrically to the same size of contractionary and expansionary monetary policy shock has important policy implications. This paper shows the presence of asymmetric responses in Armenian inflation and output to positive and negative monetary policy shocks of the same size by employing econometric models. Contractionary policy decreases inflation less than expansionary policy increases it. Output reacts in the opposite way. An estimated small open economy DSGE model with sticky wages and investment adjustment costs explains about half of the asymmetry observed in the monetary policy transmission mechanism. This paper finds that the main part of inflation reaction asymmetry is a result of a highly convex Phillips curve for the importers. The nonlinearities of the internal economy explain the predominant part of the asymmetry in output reaction.","PeriodicalId":358692,"journal":{"name":"Russian Journal of Money and Finance","volume":"479 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133805476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Variations in the Effects of a Single Monetary Policy: The Case of Russian Regions 单一货币政策影响的变化:以俄罗斯地区为例
Russian Journal of Money and Finance Pub Date : 2021-03-01 DOI: 10.31477/RJMF.202101.03
V. Napalkov, A. Novak, Andrey Shulgin
{"title":"Variations in the Effects of a Single Monetary Policy: The Case of Russian Regions","authors":"V. Napalkov, A. Novak, Andrey Shulgin","doi":"10.31477/RJMF.202101.03","DOIUrl":"https://doi.org/10.31477/RJMF.202101.03","url":null,"abstract":"This research analyses regional heterogeneity in the reaction of core inflation to shocks of a single monetary policy on the example of Russia. We use a global vector autoregression model to reveal impulse response functions of core inflation in Russian regions to monetary policy shocks. The average 5-year cumulative response of regional core inflation to a MIACR shock of 1 percentage point (pp) is ‒0.74 pp. For 77 out of 80 regions, the 5-year cumulative core inflation response is found to be statistically significant. If we exclude three statistically insignificant responses and discard the four regions with the highest and lowest responses, we get a spread of ‒0.55 to ‒0.93 pp with a standard deviation of 0.12. We show that, over a one-year horizon, the heterogeneous response to monetary policy shocks can moderately reduce the heterogeneity of the response of regional inflation to exchange rate shocks. However, the magnitude of this effect is limited. According to the analysis of the regional heterogeneity factors, the higher are the share of extractive industries in the gross regional product of a region, the share of loans to manufacturing sector, the share of loans to small enterprises, as well as the unemployment rate, the stronger will be the reaction of the core inflation to the monetary policy shock. The degree of heterogeneity in the Russian regions’ core inflation response to monetary policy shocks, the set of factors explaining this heterogeneity, and the explained variation in the regional response (30–40% depending on the model specification) turn out to be comparable to similar indicators in other countries with pronounced regional heterogeneity.","PeriodicalId":358692,"journal":{"name":"Russian Journal of Money and Finance","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123425829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Forecasting Russian Macroeconomic Indicators Based on Information from News and Search Queries 基于新闻和搜索查询信息预测俄罗斯宏观经济指标
Russian Journal of Money and Finance Pub Date : 2020-12-01 DOI: 10.31477/rjmf.202004.75
Filipp Ulyankin
{"title":"Forecasting Russian Macroeconomic Indicators Based on Information from News and Search Queries","authors":"Filipp Ulyankin","doi":"10.31477/rjmf.202004.75","DOIUrl":"https://doi.org/10.31477/rjmf.202004.75","url":null,"abstract":"Modern economic literature features quite a number of various indices of economic activity. Some of them are based on public opinion polls (‘manual’ indices), while others are based on unstructured data from the Internet (‘automatic’ indices). However, the question as to which of these approaches is the most effective remains open. In this paper, we compare several different indices of economic activity in terms of their explanatory and predictive power. We build ‘automatic’ indices using machine learning methods. Search queries, news articles and user comments under news posts from social media are used as source data. The analysis of the resulting indices of economic activity shows that the search and news indices Granger-cause ‘manual’ indices and also better explain and predict the set of macroeconomic variables selected for research. The good explanatory power of the current values of macroeconomic indicators by means of current indices of economic activity with a lag in the output of macroeconomic statistics makes them suitable for nowcasting.","PeriodicalId":358692,"journal":{"name":"Russian Journal of Money and Finance","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116461998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Modelling the Effects of a Health Shock on the Armenian Economy 健康冲击对亚美尼亚经济的影响建模
Russian Journal of Money and Finance Pub Date : 2020-12-01 DOI: 10.31477/rjmf.202004.18
A. Ani, Vahagn Davtyan, H. Igityan, Hasmik Kartashyan, Hovhannes Manukyan
{"title":"Modelling the Effects of a Health Shock on the Armenian Economy","authors":"A. Ani, Vahagn Davtyan, H. Igityan, Hasmik Kartashyan, Hovhannes Manukyan","doi":"10.31477/rjmf.202004.18","DOIUrl":"https://doi.org/10.31477/rjmf.202004.18","url":null,"abstract":"This paper extends the closed economy DSGE model in order to evaluate the impact of the coronavirus on the economy. Our model makes it clear that people,s decisions to reduce consumption and working hours due to the health crisis lead to an economic recession. As a result, the spread of the virus declines. Expansionary monetary policy decreases the size of GDP decline, but it is costly in terms of public health. This result shows that there is a trade-off between the output loss caused by the epidemic and the health consequences of the epidemic.","PeriodicalId":358692,"journal":{"name":"Russian Journal of Money and Finance","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128907093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Assessing the Consequences of the Pandemic for the Russian Economy Through an Input-Output Model 通过投入产出模型评估疫情对俄罗斯经济的影响
Russian Journal of Money and Finance Pub Date : 2020-12-01 DOI: 10.31477/rjmf.202004.03
Aleksey A. Ponomarenko, S. Popova, A. Sinyakov, Natalya Turdyeva, D. Chernyadyev
{"title":"Assessing the Consequences of the Pandemic for the Russian Economy Through an Input-Output Model","authors":"Aleksey A. Ponomarenko, S. Popova, A. Sinyakov, Natalya Turdyeva, D. Chernyadyev","doi":"10.31477/rjmf.202004.03","DOIUrl":"https://doi.org/10.31477/rjmf.202004.03","url":null,"abstract":"This paper evaluates the impact of anti-coronavirus measures on the dynamics of economic activity. In addition to primary shocks directly caused by restrictive measures, we assess their secondary effects through inter-industry relationships. Our assessments show that secondary effects impact more industries than primary effects do. The overall impact of secondary effects on the economy proves to be of a larger scale than the impact of primary effects with high heterogeneity of dynamics by industry.","PeriodicalId":358692,"journal":{"name":"Russian Journal of Money and Finance","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121743045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
A Multi-Country BVAR Model for the External Sector 对外部门的多国BVAR模型
Russian Journal of Money and Finance Pub Date : 2020-12-01 DOI: 10.31477/rjmf.202004.98
O. Korotkikh
{"title":"A Multi-Country BVAR Model for the External Sector","authors":"O. Korotkikh","doi":"10.31477/rjmf.202004.98","DOIUrl":"https://doi.org/10.31477/rjmf.202004.98","url":null,"abstract":"This paper describes a multi-country BVAR model developed and used by the Monetary Policy Department of the Bank of Russia. The model makes it possible to build coordinated scenario forecasts for the main macro-variables of the USA, the euro area, and China. The simultaneous modelling for the three economies makes it possible to take into account multi-country interactions of the variables and, thus, improve the predictive performance of the model compared to VAR analogues intended for individual countries. The model is based on the deviations of the variables from their potential values, which enhances GDP growth forecasts compared to a non-detrended design. A wide range of macroeconomic and financial indicators in the model makes the forecast of overall inflation more accurate against simpler benchmarks.","PeriodicalId":358692,"journal":{"name":"Russian Journal of Money and Finance","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128350668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Modelling the Risk-taking Channel of Monetary Policy in the Russian Economy 俄罗斯经济中货币政策风险承担渠道的建模
Russian Journal of Money and Finance Pub Date : 2020-09-01 DOI: 10.31477/rjmf.202003.30
I. Semina
{"title":"Modelling the Risk-taking Channel of Monetary Policy in the Russian Economy","authors":"I. Semina","doi":"10.31477/rjmf.202003.30","DOIUrl":"https://doi.org/10.31477/rjmf.202003.30","url":null,"abstract":"The main purpose of this paper is to test the efficiency of the risktaking channel in the Russian economy. The existence of this channel may be an additional argument for the Bank of Russia’s cautious policy regarding changes in the key rate, since its sharp decline may cause financial instability, as banks reallocate their funds to riskier higheryield assets. Z-score and the level of non-performing loans calculated according to the quarterly financial statements of credit institutions have been selected as a measure of risk. Econometric analysis revealed a shift toward riskier operations in response to a decrease in key and market interest rates. It also confirmed the hypothesis that the risktaking channel is less effective for large banks.","PeriodicalId":358692,"journal":{"name":"Russian Journal of Money and Finance","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123924459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Bank Complexity and Risk 银行复杂性与风险
Russian Journal of Money and Finance Pub Date : 2020-09-01 DOI: 10.31477/rjmf.202003.75
Elizaveta Kamaraeva
{"title":"Bank Complexity and Risk","authors":"Elizaveta Kamaraeva","doi":"10.31477/rjmf.202003.75","DOIUrl":"https://doi.org/10.31477/rjmf.202003.75","url":null,"abstract":"The consolidation of banks into banking groups and holdings has been a prominent recent trend in Russia’s banking sector. To evaluate the effect of consolidation on the risk of a banking group, one needs a specific metric that captures organisational, business, and geographic complexity. In this paper, I consider different complexity types and proxies, and examine how complexity affects the risk of a banking group. Using data for 76 banking groups in Russia for 2015–2019, I find that for most of the complexity indicators there is a positive relationship between the organisational and business complexity on the one hand, and the risk of a banking group on the other hand. I also show that, in combination, different types of complexity have a positive effect on risk.","PeriodicalId":358692,"journal":{"name":"Russian Journal of Money and Finance","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134281075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Methods for Estimating the Gross Regional Product Leading Indicator 地区生产总值领先指标的估算方法
Russian Journal of Money and Finance Pub Date : 2020-09-01 DOI: 10.31477/rjmf.202003.03
V. Boyko, N. Kislyak, M. Nikitin, O. Oborin
{"title":"Methods for Estimating the Gross Regional Product Leading Indicator","authors":"V. Boyko, N. Kislyak, M. Nikitin, O. Oborin","doi":"10.31477/rjmf.202003.03","DOIUrl":"https://doi.org/10.31477/rjmf.202003.03","url":null,"abstract":"This paper discusses two methods for estimating the quarterly values of the gross regional product (GRP) leading indicator. The first method is based on Rosstat methodology using the growth rates of indicators that reflect the output for main economic activities in the region. The second method uses temporal disaggregation (disaggregation in time). A distinctive feature of the second method is the possibility of obtaining high-frequency series using not only the indicators specified in Rosstat methodology but also other variables reflecting the dynamics of business activity in regions. The research suggests that temporal disaggregation methods provide more accurate estimates of quarterly values of the physical GRP volume index as compared to methods based on Rosstat methodology. The particular temporal disaggregation model used to forecast GRP for seven federal districts (i.e., all except the North Caucasian District) is chosen based on the performance in forecasting the gross domestic product (GDP) volume, which is close in economic terms to the overall GRP for Russia.","PeriodicalId":358692,"journal":{"name":"Russian Journal of Money and Finance","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124092088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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