• Purpose: This paper estimates the Tanzanian Shadow Economy (SE) from 2003 to 2015 and tests the statistical relationships between the SE and its potential causes and indicators. • Methodology approach: The econometric analysis is based on a multiple indicators multiple causes (MIMIC) model. To calibrate the SE from the estimates, we adopt the value of 55.4 percentage of the SE to official GDP from the literature for the base year 2005. • Findings: The SE ranges from 52 to 61% of official GDP and it slightly decreases from 2013 to 2015. Increase in inflation, unemployment and government spending were the main drivers of the SE dynamics. • Research limitations: Given the challenges facing estimation of the SE (e.g., small sample size, exogenous estimate to calibrate the model, meaning of the latent variable) quantification of SE should be considered to be rough measures. • Practical implications: To lower the size of the SE, the government need to keep inflation and unemployment and stable overtime; to reduce government spending because creates pressure on tax collection due to the limited tax base. • Originality: This is the first study specifically focused on Tanzanian SE based on MIMIC approach. Existing estimates of Tanzanian SE are calculated by monetary models or apply a common MIMIC specification to worldwide context.

Estimating shadow economy in Tanzania: an analysis with the MIMIC approach

DELL'ANNO, Roberto;
2018

Abstract

• Purpose: This paper estimates the Tanzanian Shadow Economy (SE) from 2003 to 2015 and tests the statistical relationships between the SE and its potential causes and indicators. • Methodology approach: The econometric analysis is based on a multiple indicators multiple causes (MIMIC) model. To calibrate the SE from the estimates, we adopt the value of 55.4 percentage of the SE to official GDP from the literature for the base year 2005. • Findings: The SE ranges from 52 to 61% of official GDP and it slightly decreases from 2013 to 2015. Increase in inflation, unemployment and government spending were the main drivers of the SE dynamics. • Research limitations: Given the challenges facing estimation of the SE (e.g., small sample size, exogenous estimate to calibrate the model, meaning of the latent variable) quantification of SE should be considered to be rough measures. • Practical implications: To lower the size of the SE, the government need to keep inflation and unemployment and stable overtime; to reduce government spending because creates pressure on tax collection due to the limited tax base. • Originality: This is the first study specifically focused on Tanzanian SE based on MIMIC approach. Existing estimates of Tanzanian SE are calculated by monetary models or apply a common MIMIC specification to worldwide context.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4686639
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