Some New Estimates of Shadow Economy for 80 Countries Using Pooled Mean Group Estimator

Abstract

The purpose of this study is to estimates the size of the shadow economy for 80 countries from nine regions spanning the period 1975-2012 based on Tanzi-type currency demand approach (CDA). This study contributes to the literature in three distinct ways. First, we augment CDA regression with a macroeconomic uncertainty index (MUI). Second, the construction of the uncertainty index is based on the dynamic factor model (DFM). Third, the pooled mean group (PMG) estimator allows in capturing the heterogeneity across countries in the short-run dynamics but imposing restrictions in the long-run parameters. The results confirm the existence of the longrun equilibrium relationship among the variables examined. All coefficients show expected signs along with statistical significance. More importantly, the macroeconomic uncertainty index variable show positive relationship, suggesting that public tend to hold more currency in an uncertain macroeconomic environment. In addition, we observe that developing regions (ranging from 19.9% to 37.3%) exhibit relatively large size of the shadow economy. On the contrary, developed regions have a considerable smaller estimate (ranging from 13.7% to 19.0%) of the size of shadow economy. On average, the world estimate of the shadow economy as a percentage of GDP is about 23.1%. Keywords: Shadow Economy; Currency Demand; Macroeconomic Uncertainty; Pooled Mean Group.

The Impacts of Monetary and Fiscal Policies on Economic Growth in Malaysia, Singapore and Thailand

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Size and Causes of the Shadow Economy in Iran: An Analysis with the MIMIC Approach

“…Several studies have confirmed this positive connection empirically (e.g. Almenar et al, 2020;Hassan & Schneider, 2016b;Tan et al, 2017).…”

Mitigating the shadow economy through financial sector development in Indonesia: some empirical results

“…Some studies attempted to estimate the size of Indonesia's shadow economy (see Table 1). For instance, Tan et al (2017) estimated that the average size of Indonesia's shadow economy during 1984 and 2012 was at around 28% of the official GDP. This figure is higher than the 19.8% average estimate by Medina and Schneider (2018).…”

“…Based on the findings from the studies by the ADB (2011) and Rothenberg et al (2016), we induce a hypothesis that using financial sector development to provide greater access for the population to financial resources can reduce Indonesia's shadow economy. In this study, we investigate whether financial sector development can reduce Sources: Elgin and Oztunali (2012), Alm and Embaye (2013), Tan et al (2017), Medina and Schneider (2018), Wibowo and Sharma (2005), Panjaitan (2007), Nizar and Purnomo (2011), Samuda (2016) by calculating from the quarterly figures, Azwar and Mulyawan (2017) by averaging from the quarterly figures, and Ramadhan (2019). Elgin and Oztunali (2012) also provide the size of Indonesia'a shadow economy for the period 1960-1969 as 32.78, 33.08, 33.08, 33.13, 33.37, 33.59, 33.66, 33.71, 33.9 and 33.94, respectively. the size of Indonesia's shadow economy.…”