Shadow Economies in OECD Countries: DGE vs. MIMIC Approaches

Bu makalede OECD üyesi 38 ülke için iki farklı yöntemle kayıtdışı ekonomi tahmin seviyeleri ve kayıtdışı ekonominin belirleyicileri karşılaştırılmaktadır. Yöntemlerden biri MIMIC yöntemine diğeri ise Elgin ve Öztunalı (2012) çalışmasında geliştirilen iki sektörlü dinamik genel denge modeline dayanmaktadır. Sonuçlarımız, MIMIC yönteminin kayıtdışı ekonominin temel belirleyicileri olarak, gelir vergisi (%13.8) dolaylı vergiler (%14.1), vergi ahlakı (%14.5), işsizlik (%14.7), serbest-meslek oranı (%14.5), GSYİH büyümesi (%14.3) ve işletme özgürlüğü endeksi (%14.2)'ı işaret etmektedir. Ancak, dinamik genel denge yöntemine dayanan tahminler için ise temel belirleyiciler olarak GSYİH büyümesi (%24.7%) dolaylı vergiler (%18.5), işsizlik (%18.3), vergi ahlakı (%17.1),gelir vergisi (%11.2), serbest meslek oranı (%5.8), ve işletme özgürlüğü endeksini (%4.3) göstermektedir. Sonuçlarımız genel olarak iki yöntemin benzer büyüklük seviyeleri tahminlemesine karşın, kayıtdışı ekonominin belirleyicilerinin etkileri yönünden farklılaştığını ortaya koymaktadır.

OECD Üyesi Ülkelerde Kayıtdışı Ekonomi: Dinamik Genel Denge ve MIMIC Yöntemleri

In this paper we compare the levels and driving forces of shadow economies in 38 OECD countries using two different methodologies. One of these methods is the multipleindicators-multiple-causes (MIMIC) approach based on an estimation of a structural equation model. The other one is based on a two-sector dynamic general equilibrium (DGE) model developed by Elgin and Oztunali (2012). According to our results, the average driving forces of the shadow economy of the 38 OECD countries obtained using the MIMIC model show that personal income tax (13.8%), indirect taxes (14.1%), tax morale (14.5%), unemployment (14.7%), self-employment (14.5%), growth of GDP (14.3%) and business freedom index (14.2%) contribute more or less evenly to shadow economies. However, according to the estimates constructed using the DGE model, the growth of GDP per-capita has by far the largest effect (24.7%) followed by indirect taxes (18.5%), unemployment (18.3%), tax morale (17.1%), personal income tax (11.2%), self-employment (5.8%), and business freedom (4.3%). Our analysis generally shows that even though the two datasets are similar in levels and both illustrate a declining trend of shadow economy size over the period of the analysis, they indicate certain differences with respect to the effects of causal variables on shadow economies.

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