The paper presents a vector autoregression-based approach to evaluation of fiscal measures. Using both structural and bayesian VAR models, we estimate fiscal multipliers of overall government expenditure and its components: national defense, national economy, education and social policy expenditures. Results are checked for robustness using different lag length and model specifications and different sets of hyperparameters in Bayesian VAR case. The results regarding overall expenditures are quite stable across specifications and correspond well with results obtained in previous research in this field. National defense and social policy multipliers are shown to be negative (in contrast to previous research on Russian data), national economy and education expenditures multipliers are positive. Some policy implications are presented.
Throughout the period after the municipal reform in 2003, the governing of Russian cities has been changing. A city as an object of governance is located at the intersection of interests of different levels of public authorities and is not limited only to local authorities This article investigates how budget autonomy of Russian cities has been changing for the last 16 years, and how exogenous economic shocks and large-scale federal initiatives such as the “May Decrees” have influenced the budget autonomy of Russian cities. The paper considers a hypothesis that there was a transition to multi-level governance of Russian cities in 2006–2019, which led to significant reduction of the budget autonomy. Budgets of the 35 largest cities of Russia (except for city-regions like Moscow and Saint Petersburg) were collected and analyzed in terms of their revenue and expenditure sections to test the proposed hypothesis. The relationship between the economic level of development and budget sufficiency was investigated with cluster analysis. The main result of this research is that Russian cities have become dependent on the financial grants from regional governments since there is no national policy of stimulating the economic development of cities. The national economic crisis of 2014 accelerated the process of governance centralization. In addition, the budget autonomy of municipalities was reduced due to the fact that achieving indicators of the May Decrees had become the primary objective for the public authorities. The share of the income tax in local budgets increased significantly although the share and diversity of other income sources decreased.
The paper introduces the methods of assessing the effects of social assistance on work incentives, using representative Rosstat survey data as illustration. It also demonstrates the key steps of testing the hypothesis of the social benefits effect on work incentives, as well as the need for conducting multi-factor analysis coupled with impact evaluation methods. The key finding from descriptive analysis is that an average household that has recipients of social benefits among its members cannot rely on social benefits as a significant source of means of subsistence, therefore social transfers do not produce a sizeable effect on work behavior. Nevertheless, the authors propose a hypothesis that there are certain groups of social transfers beneficiaries whose work behavior may be strongly affected by social transfers. Firstly, this refers to recipients of social transfers, the size of which is comparable to the anticipated wage size. In such cases, social transfers can produce a negative employment effect. Secondly, this could refer to recipients, whose eligibility to social transfers is related to their belonging to a certain professional group. In this case, in all likelihood, social transfers create economic incentives to stay in these professional groups, reducing labor mobility. The testing and analysis of these hypothesis will be presented in forthcoming papers by the authors.
In the field of cryptoeconomics the Ethereum (Ethereum Foundation) project gave opportunity to create “own” cryptocurrency – new token based on its smart-contract platform to everyone without lowlevel programming skills. Then it became obvious that tokens could be used for crowdfunding as the Ethereum did in 2014. Unregulated and easy to access such scheme became popular among related to the blockchain tech startups. It was named Initial Coin Offering (ICO/or ITO). Despite its name, which is similar to IPO, this scheme is usually used for venture funding of a new project instead of expanding already well-established working business. The authors use machine-learning algorithms to classify ICOs and estimate ROI based on public digital data and web-sources. The goal of the research is to develop sustainable and efficient model, which will predict target profit ROI (profit trends) of ICO startup. Data collection and analysis period: Feb-Mar 2018. The prediction model and the application (service) of ICO startups’ selection are developed as the result of the study. Results. There were over 3000 samples of ICO-startups in the research dataset. After cleaning and elimination of outliers, it contained only 518. The number of samples with positive ROI (which means that these ICOs were profitable) was 234. Cross validation metric was confirmed to be accurate. The model achieved 79 % accuracy (average value). To prove this score separated prediction was executed the metrics: for test dataset AUC is 0.78; for profitable samples Precision: 0.76; Recall: 0.9 for profitable; F1-score: 0.82. Discussions. In order to achieve the objectives of this study, various IT components of the service architecture (applications) were developed to monitor, analyze and predict the risks of ICO startups. An artificial neural network was developed to solve the problem of ROI classification and prediction. The average ROI among profitable ICOS was 47 %. Taking into consideration that the crypto market is highly volatile and that there is a possibility that such investments will not bring any profit, this model of monitoring, analysis and prediction can be very valuable for the purposes of critical selection (exclusion) of a number of ICO projects from potential investment. Conclusion. The developed components can be used as a basis of monitoring service of ICO startups. The risk-forecasting model can be improved, foremost, by using the most complete (and wider) set of data. In this case, individual data collection and processing tasks can be performed manually, which will require additional resources. It should be noted that other types of neural networks can be developed for both text analysis and trading data analysis. This may lead to the logic of using a combination of models, which will potentially help to provide the most accurate predictions.
Nowadays tax incentives are widely used in many countries including Russia. Nevertheless, this tax instrument has a number of significant disadvantages. Firstly, they decrease budget revenues, and at the same time the efficiency of tax incentives usually is not estimated and seems to be not positive. Secondly, a lot of tax incentives can be replaced by more comfortable types of direct expenditures. Finally, as a rule, from an equity standpoint tax exemption is not a good, as recipients of tax exemption are usually wealthy people. This paper discusses main theoretical aspects of tax incentives (with focus on personal income taxation), provides a review of the world taxation practices and analyzes the tax exemptions in Russia. The results of analyses allow to outline the recommendations intended to improve the personal income taxation.
Innovative financial services foster both financial and real sector development. The research paper introduces multiperiod model of financial innovations, based on Harold Hotelling’s approach (model of a linear city). This model allows to identify factors incentivizing banks for creation new quality services and to comprehend what consumer groups are able to enhance innovative activity of banks.
The article presents an approach to monitoring of the initiative budgeting practices implementation. Within this monitoring the data is collected from the regional authorities and used in the framework of the Procedure for Interaction between the Ministry of Finance of the Russian Federation and the financial authorities of the constituent entities of the Russian Federation on the formation of the Report on Best Practices for Initiative Budgeting Development in the Subjects of the Russian Federation and Municipalities. Today this monitoring is the only federal source of data on how initiative budgeting practices are developed in Russia, therefore it solves the problems of not only studying, but also scaling the best practices of initiative budgeting in the country. The article describes the evolution of monitoring since 2015, its methodology, quantitative and qualitative indicators, characteristics and objectives of the transition from monitoring to evaluation of the effectiveness of such practices. In this study the authors analyze the data for 2017, create the typology of practices of subjects of the Russian Federation in the context of the applied citizen participation mechanisms, identify the most popular types of public infrastructure projects chosen by citizens. Furthermore, the article defines the problems associated with monitoring, in particular the inability to verify the real participation of citizens through the desk research methods.
The article analyzes the legal regulation of the procurement and budgetary process by the example of procurement standardization and reviews the implementation of public procurement standardization as well as its integration with the budgetary process. Definitions of the procurement standardization and standard costs are given by the author. The article presents recommendations to State authorities at the Federal level for preparation of their own acts and examples of standard costs calculation.
Fiscal (budget) transparency is a concept that was developed in the 1990s and became particularly relevant in times of financial crisis. Recent studies show that improving transparency results in better budget performance, lower borrowing costs and reduced corruption. This review describes the main approaches used in budget transparency evaluation and is addressed to practitioners and researchers dealing with budget transparency.