Citation: Morkunas, Mangirdas. 2022. Measuring the Cohesion of Informal Economy in Agriculture in New European Union Member States. Economies 10: 285. https://doi.org/ 10.3390/economies10110285 Academic Editor: Sanzidur Rahman Received: 20 October 2022 Accepted: 10 November 2022 Published: 16 November 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). economies Article Measuring the Cohesion of Informal Economy in Agriculture in New European Union Member States Mangirdas Morkunas Faculty of Economics and Business Administration, Vilnius University, 01513 Vilnius, Lithuania; mangirdas.morkunas@evaf.vu.lt Abstract: The present paper evaluates the size and development of the informal economy in agricul- ture in 10 new EU member states from 2004–2020. A novel agriculture-tailored multiple indicators Multiple Causes model was derived to estimate the size of the informal economy in agriculture. It was revealed that the share of the informal economy in agriculture has decreased from 40 to 31%. The level of cohesion of the informal economy in agriculture shows an opposite trend compared with other economic sectors, indicating an increasing divergence from mainstream economic trends. Keywords: agriculture; informal economy; new EU member states; MIMIC; sigma-convergence 1. Introduction Traditionally, the agricultural sector is characterized by a high level of informality (Schneider et al. 2022). A significant amount of unaccounted cooperative help (Ribašauskien ˙ e et al. 2019), family labor (Darpeix et al. 2014; Dupraz and Latruffe 2015; Chowdhury 2016), part-time agriculture (Barlett 2019), and internal consumption (Barick- man 2022) are prevalent in agriculture. However, they are not considered to not be subject to taxation in the eyes of society, although they are seen in a positive light, being regarded as a part of traditional activities that should be preserved (Cooper et al. 2009). Due to this cultural aspect, some countries exclude the agricultural sector from their computations when assessing the level of the informal economy within the country. This decreased interest from the authorities towards the informal activities in agriculture may have con- tributed to the development of the informal economy (Bender 2001; Drucza and Peveri 2018). The agricultural sector is considered as one of the main drivers of the informal economy (Pasovic and Efendic 2018). Due to its ambiguous nature, the informal economy can be only estimated approx- imately using indirect or hybrid methods. Typically, the shadow/informal/undeclared economy is estimated using variations of the multiple indicators multiple causes (MIMIC) approach (Abid 2016; Medina et al. 2017; Soares and Afonso 2019; Monarca et al. 2022), which is one of the most prevalent structural equation modelling techniques (Finch and French 2011). A significant criticism of general MIMIC models is that they fail to explic- itly distinguish between exogenous and endogenous causal factors. This may sometimes compromise the ability of the derived econometric models to precisely reflect the latent construct. Additionally, the MIMIC presumes relaxed separation between exogenous and endogenous variables to a point, such that ‘the indicator and causal variables of the MIMIC model match exactly to the endogenous and exogenous variables of econo- metrics’ (Breusch 2005, p. 6). This approach sometimes provokes criticism from the pure econometric perspective (Feige 2016). Another possible source of inaccuracies in the estimations of the informal economy in agriculture is the prevailing approach of applying variables used for the informal economy of the whole country also to the agricultural sector. For example, Schneider et al. (2022) directly apply the classical MIMIC model, which is extensively verified on a Economies 2022, 10, 285. https://doi.org/10.3390/economies10110285 https://www.mdpi.com/journal/economies