Shadow economy in agriculture and specifics of its measurement

Despite the extensive list of works devoted to the analysis of the shadow economy, the issue of determining its scale at the regional level and a separate type of activity (according to the All-Russian Classifier OKVED 2. has not been resolved. This work aims at filling this gap by showing existing...

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Main Authors: S. V. Kiselev, S. K. Seitov, V. A. Samsonov, I. V. Filimonov
Format: Article
Language:Russian
Published: Federal Agricultural Research Center of the North-East named N.V. Rudnitsky 2024-12-01
Series:Аграрная наука Евро-Северо-Востока
Subjects:
Online Access:https://www.agronauka-sv.ru/jour/article/view/1821
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author S. V. Kiselev
S. K. Seitov
V. A. Samsonov
I. V. Filimonov
author_facet S. V. Kiselev
S. K. Seitov
V. A. Samsonov
I. V. Filimonov
author_sort S. V. Kiselev
collection DOAJ
description Despite the extensive list of works devoted to the analysis of the shadow economy, the issue of determining its scale at the regional level and a separate type of activity (according to the All-Russian Classifier OKVED 2. has not been resolved. This work aims at filling this gap by showing existing methods of accounting for the shadow economy in agriculture. The aim is to identify the scale of the shadow economy in agriculture at the regional level in Russia. The novelty lies in the development and application of a methodology for assessing the shadow economy in agriculture in the Russian regions. The paper uses economic and statistical, calculation, cartographic methods. The paper forms empirical basis on the official statistical data. As a result of using the authors’ methodology, the study finds that in the absolute majority of regions there is a moderate level of shadow transactions of legal entities in section A according to the All-Russian Classifier. Moreover, the level of differentiation is low. Only in Chukotka Autonomous Okrug, Chelyabinsk, Bryansk, Lipetsk regions, Mari El Republic there is a higher level of shadow transactions. In general, in 2017–2022 there is a trend towards a reduction in the share of shadow transactions of legal entities in the gross value added (GVA) of section A “Agriculture, forestry, hunting, fishing and fish farming” in the regions of Russia. It is largely achieved thanks to the introduction of federal government information systems that make shadow turnover difficult. At the same time, when interpreting the results, it is important to make an adjustment for that our methodology may underestimate the scale of the shadow economy, since it does not consider agricultural organizations that are small business entities, as well as peasant farms and individual entrepreneurs.
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spelling doaj-art-b68b3a18298a4c06b567431d3b19d94e2025-08-03T19:52:39ZrusFederal Agricultural Research Center of the North-East named N.V. RudnitskyАграрная наука Евро-Северо-Востока2072-90812500-13962024-12-012561191120410.30766/2072-9081.2024.25.6.1191-1204850Shadow economy in agriculture and specifics of its measurementS. V. Kiselev0S. K. Seitov1V. A. Samsonov2I. V. Filimonov3Lomonosov Moscow State UniversityLomonosov Moscow State UniversityLomonosov Moscow State UniversityLomonosov Moscow State UniversityDespite the extensive list of works devoted to the analysis of the shadow economy, the issue of determining its scale at the regional level and a separate type of activity (according to the All-Russian Classifier OKVED 2. has not been resolved. This work aims at filling this gap by showing existing methods of accounting for the shadow economy in agriculture. The aim is to identify the scale of the shadow economy in agriculture at the regional level in Russia. The novelty lies in the development and application of a methodology for assessing the shadow economy in agriculture in the Russian regions. The paper uses economic and statistical, calculation, cartographic methods. The paper forms empirical basis on the official statistical data. As a result of using the authors’ methodology, the study finds that in the absolute majority of regions there is a moderate level of shadow transactions of legal entities in section A according to the All-Russian Classifier. Moreover, the level of differentiation is low. Only in Chukotka Autonomous Okrug, Chelyabinsk, Bryansk, Lipetsk regions, Mari El Republic there is a higher level of shadow transactions. In general, in 2017–2022 there is a trend towards a reduction in the share of shadow transactions of legal entities in the gross value added (GVA) of section A “Agriculture, forestry, hunting, fishing and fish farming” in the regions of Russia. It is largely achieved thanks to the introduction of federal government information systems that make shadow turnover difficult. At the same time, when interpreting the results, it is important to make an adjustment for that our methodology may underestimate the scale of the shadow economy, since it does not consider agricultural organizations that are small business entities, as well as peasant farms and individual entrepreneurs.https://www.agronauka-sv.ru/jour/article/view/1821scale of shadow economycalculation methodgross value addedagricultural productionagricultural organizationsregions
spellingShingle S. V. Kiselev
S. K. Seitov
V. A. Samsonov
I. V. Filimonov
Shadow economy in agriculture and specifics of its measurement
Аграрная наука Евро-Северо-Востока
scale of shadow economy
calculation method
gross value added
agricultural production
agricultural organizations
regions
title Shadow economy in agriculture and specifics of its measurement
title_full Shadow economy in agriculture and specifics of its measurement
title_fullStr Shadow economy in agriculture and specifics of its measurement
title_full_unstemmed Shadow economy in agriculture and specifics of its measurement
title_short Shadow economy in agriculture and specifics of its measurement
title_sort shadow economy in agriculture and specifics of its measurement
topic scale of shadow economy
calculation method
gross value added
agricultural production
agricultural organizations
regions
url https://www.agronauka-sv.ru/jour/article/view/1821
work_keys_str_mv AT svkiselev shadoweconomyinagricultureandspecificsofitsmeasurement
AT skseitov shadoweconomyinagricultureandspecificsofitsmeasurement
AT vasamsonov shadoweconomyinagricultureandspecificsofitsmeasurement
AT ivfilimonov shadoweconomyinagricultureandspecificsofitsmeasurement