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 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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