2021. vol. 25. No. 1

This paper estimates the treatment effect of Priority Development Areas (PDA) on a total factor productivity growth in Russian monotowns. There are two basic sources of data: SPARK-Interfax for Russian companies for the period from 2014 to 2018 and the Ministry of Economic Development list of Priority Development Areas (PDA) for 2016 and 2017. The database includes information on 443512 unique firms from 8 sectors of economic activities. Thus, all indicators are aggregated due to the transition from the level of firms to the second level facility of OKATO (districts, regions, cities). The effect is measured by comparing cities with the same probability of receiving the PDA status. This approach solves the problem of endogeneity (if the PDA status is related to the characteristics of the city). The estimation results show higher total factor productivity growth in cities with Priority Development Areas compared to the cont­rol group selected by the matching procedure. The source of higher total factor productivity growth is an increase in efficiency among firms that have already operated in towns with Priority Development Areas. There is no evidence of this policy’s effect on the entry/exit dynamic of firms. This approach has limitations: the effect of the PDA creation on economic development could not be extrapolated to the areas that differ in characteristics from the territories where PDA were created.

The number of free trade agreements (FTA) in international trade is rapidly growingand it makes them the main tool for countries’ trade liberalization. Created in the 2015, the Eurasian economic union (EAEU), that has the competence of the customs union, also started actively building a network of FTAs. To date, four such preferential agreements and one non-preferential trade agreement are in force, and at least three other agreements are expected to be signed in 2021–2025.

Some specific features can be attributed to the emerging network that will impact the economic development of the EAEU Member States and will allow its partners to adapt their foreign trade policies accordingly. The geography of the EAEU agreements demonstrates the intention to create a wide network of FTA covering primarily the Eastern hemisphere, with the potential to extend it to all major regions. The EAEU partners are generally small States and notthe strongest economies, and the content of FTA agreements is not yet as broad and deep as, for example, concluded by the EU. It is noteworthy that the system almost does not contain WTO-extra provisions. However, the EAEU is only at the beginning of building an FTA network that may change the EAEU position in the international trade system.

The main goal of the article is to track the distinct features of this new EAEU trade policy and to identify specifics and prospects for the emerging FTA network, based on the already concluded agreements and the coming ones.

Monitoring the current situation and forecasting ways of developing economic activity based on official statistical estimates of the various indicators’ values is critical for making timely economic and political decisions and business planning. In this regard, revaluation of data and forecasts based on earlier or later estimates can potentially lead to completely different economic and political decisions. At least five planned or regular revaluations of the gross domestic product indicator are published according to the official Rosstat methodology.

Apart from planned revaluations, Rosstat conducts unscheduled recalculations of GDP, associated, for example, with changes in the classifiers of economic activities or with the agricultural census.

According to authors’ own methodology, this work reflects data collected on planned and unplanned revaluations of the nominal volume of GDP (in billion rubles) and the index of the physical value of GDP from Q1 1994 to Q1 2020, published monthly in the summary «Short-term economic indicators of the Russian Federation»; vintages of these indicators were shaped both in annual and quarterly terms; Russian specific terms being therefore not well-established in the domestic literature were optionally proposed; results of the analysis of the revisions’ statistical property of the indicators of the gross domestic product of the Russian Federation, both in annual and quarterly frequency were presented.

In particular, the analysis was made with regard to systematic biases in the revaluation of indicators of the standardized value of gross domestic product and the index of the physical quantity of GDP, changes in their dynamic properties, average characteristics of revisions, the presence (or absence) of noise and news components in both indicators.

In this paper, we evaluate the impact of regional integration on insurance companies' performance to assess whether integration is always favorable for the insurance market. In exi­sting literature, the most common method of evaluating the impact of integration on insurance companies has been observing how certain indicators change over time and attributing these changes to integration, with another approach consisting of using the share of the insurance lines mostly subject to foreign competition as an explanatory variable. The results, however, are mixed. As a measure of the degree of integration, we use the share of imports from other countries that are members of the trade agreement in the country's imports of direct insurance services. The evaluation is carried out using data on 64 companies from Canada, Mexico and the United States from 2005 to 2016, then verified using data on 145 companies spanning 2005– 2018. The production function is assumed to be translog. It is shown that a higher share of other member countries in the imports of direct insurance services leads to an increase in the operating expenses incurred by life insurance companies and a decrease in the operating expenses incurred by international companies, while there is no statistically significant impact on the profits of most types of companies.

In this paper we test some hypotheses about individual decision making under risk based on the unique Russian TV show «Sdelka?!» participants behavioral data. The show presents the game where participants are supposed to choose between guaranteed amount of money and lottery which may result in gains or losses. Participants are assumed to make decisions based on prospect theory and cumulative prospect theory including both subjective probability trans formation and reference-dependent behavior. Herewith it is assumed that reference point is dynamic so it may change through the game. In order to estimate parameters associated with participants decision making mechanism we propose econometric binary choice model based on quasi maximum likelihood method. The results suggest that contestants adapt reference point depending on the game process. Adaptation seems to be asymmetric since reference point shifts noticeably to the right in response to gains and substantially less to the left if the game goes poorly. In addition, we have found weak evidence in favor of loss aversion effect. In order to demonstrate the robustness of the results we are using various approaches to subjective proba­bilities transformation. According to Akaike information criteria econometric models incorporating probability transformation are superior to objective probability mode.

This paper pioneers the identification of artificial intelligence (AI) enablers like technology feasibility, sophistication, data integrity, interoperability and perceived benefits that can boost operational efficiency of firms in Indian food processing industry. With the food processing industry contributing significantly to do­mestic gross value added and generating an export earning of close to USD 40 billion from agricultural and processed food exports, the study examines the role of AI in overcoming the existing inefficiencies of firms, particularly the small and medium enterprises (SMEs) involved in food processing. For this, questionnaire wascirculated to 500 respondents comprising of IT and supply chain professionals, managers of food processing companies and academicians working in this do main, of which 341 complete responses were received. These responses were then analysed using PLS–SEM modeling, through which the relationship between AI adoption and operational efficiency of firm was established. The study found a significant relationship between AI adoption and operational efficiency. The R square and Q square values substantiate the predictive power of the model used in the study. The research has significant implications for supply chain professionals as technology adoption would boost resilience, integration and transparency of these firms. The study is also relevant for addressing issues pertaining to food security, employment generation, enhancing industrial output and export growth. Policy makers can also get perspectives on harnessing the benefits of AI technology while creating an enabling environment for different supply chain partners.