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Assessment of underground economy and tax evasion: Empirical evidence from Pakistan

  • 2017 | Volume: 1 | Issue: 1 | Page: 19-30


Underground economy has serious implications for economic performance and public policy of a country. The purpose of this paper is to estimate the size of underground economy and tax evasion in Pakistan for the period 1973-2016. This study uses monetary approach for estimation of size of the underground economy and tax evasion in Pakistan. The results indicated that increase in taxes, intensity of regulation, and inflation were the driving force of underground economy. The estimates show that the size of underground economy in Pakistan showed an increasing trend from 1974 onward and attained its maximum value in 1998. Thereafter, its size exhibited decreasing trend with small fluctuations. Interestingly, the impact of taxation reforms introduced in 1997 was not considerable. Results indicated that the tax burden is the driving force for the existence of underground economy which need to be appropriately set and enforced. This may discourage people from indulging in underground economies. The results from this study can be used for effective policy formulations with respect to underground economy.

Keywords and JEL Classification


Underground Economy, Tax Evasion, Tax Burden

JEL Classification

E26; H26

1. Introduction

   The underground economy may be defined as those activities which have no record in the official statistics and no taxes have been paid on them. These activities consist of monetary as well as non-monetary transactions. Underground economy exists not only in developing countries but also in developed countries. Many measures are taken such as prosecution, education and growth in different sectors of the formal economy to discourage people' and businesses' participation in the underground economy. Gathering reliable information about the nature and size of underground economy is almost impossible (Spiro, 1993). Many studies have been undertaken to estimate the size of the underground economy, its impact and determinants in various countries. The existence of underground economy and unreliable estimates about its size, makes the data on national accounts such as unemployment rate, inflation rate, and GDP growth rate questionable. Ignoring the underground part of the economy in policy formulations at macro level could have strong implications for the direction of the economy.

   Underground economy can have extremely negative impacts on cultural, social and economic development of a country, especially for Pakistan which is already facing severe revenue shortfall with high fiscal deficit. It not only affects the equitable distribution of economic resources but also decreases the efficiency. Since the underground and undocumented part of the economy is out of general tax net, it tends to increase tax burden on formal sector of the economy (Iqbal, Qureshi, & Mahmood,1998). Similarly, increase in the size of underground economy is a lost revenue for governments. Since underground economy is not counted in the official estimates of the national incomes, it could also have strong effect on inflation as well. There is a lack of public trust on governmental institutions, and quality of goods and services produced in the underground economy is compromised. Moreover, underground economy may distort the labour market due to lack of enforcement of the labour laws.

   Monetary transactions remain out of the tax net and national accounts either due to negligence of tax collecting authorities or due to its small size or illegality of its nature. These transactions include income from unregistered employment, assets formation from unreported work (like agriculture, housing, hunting, furs like garments and decoration, transaction in property, fishing, medical services, enterprises, restaurants and hotels, catering, transportation, etc.), working “off the books” or “moon lighting” (second jobbing) for cash, sale of information (publication of books, production of posters, video recording, etc.), informal trade (i.e. working without permit), selling home-grown/home-made products, financial instruments (like trade in bonds and stocks), covert rentals (like rent a car, house, shop, etc.), acceptance of tips, currency transaction (money changer), illegal trade in drugs (alcohol and tobacco), theft, prostitution, bribery, smuggling, gambling, corruption, begging and kidnapping (often called Mafia), etc. Given the size of the underground economy in many countries, it is pertinent to discuss the factors that could affect the underground economy (Tanzi, 1980; Thomas, 1999; Yasmin, Bushra, & Rauf, 2003; Khalid, 2002; Kemal, 2007). The volume of shadow economy is associated with many economic and non-economic factors. Rise in tax burden and social transfer, intensity of regulations in the labour market like reduction in working hours, early retirement, decline in tax moral, and restriction on second jobbing are some of the major economic factors which affect its size and extent. The non-economic factor like unwillingness to show the accurate income and tacit cooperation with dishonest officials are some other reasons which play vital role in the expansion of its size (Zaman, & Goschin, 2015; Khan, & Khalil, 2017).

   Underground economy has very strong negative impacts on social, cultural and economic conditions of a country. It challenges the writ of the government by violating the established rules and regulations (e.g. no tax payment, no work permits and licenses, provision of illegal unlawful products etc.) and becomes a huge obstacle for the government to achieve the determined budgetary targets. Its effect can also be seen from the perspective of economic policy making, where part of the labour force (unemployed in actual statistics) actually work and earn in the underground part of economy which leads to ineffectiveness of the macroeconomic policies (Ahmad, & Ahmad, 1995). One the other hand, increase in its size results in further loses in tax revenue, which not only puts additional pressure on revenue generating authorities to increase taxes in the formal sector of the economy, but also increases incentives to hide taxes and escape into the shadow economy (Aslam, 1998). Likewise, the unregistered firms take benefit of not paying taxes which increases the cost of production to the registered firms which pay high taxes. Despite of these negative effects, the underground activities also have some positive effects. The lower cost structure in the informal sector leads to provision of wider opportunities of employment in the unregistered labour market. Due to low entry cost and no permit acquisition by the informal sector's firms, their costs are lower making the unregistered firms charge lower prices than the registered ones. Furthermore, such underground activities provides better competitive environment (i.e. lower prices with high sale volume) for their sustainability and growth in the long run (Tanzi, 1999).

   Keeping in view the unreliability about the extent and size of the underground economy and its detrimental effect on the formal part of economy, it is very important to estimate the size of the underground economy as well what determines the size of such economy. Therefore, this study is an effort towards this end.

2. Literature Review

   This section discusses the previous literature on estimating the size of the underground economy and its effect in various parts of the world. The relevant literature is summarised as follows:

   Many researchers used the monetary approach to estimate the size of underground economy. Shabsigh (1995) used ratio of currency in circulation (CC) to demand deposits as a dependent variable and real interest rate, real per capita income, banking services and tax revenue from imports as explanatory variables. He reported that the size of the underground economy was about 20.74 % of GDP for the period from1975 -1990. Similarly, Ahmad and Ahmad (1995) used the ratio of CC to M2, and ratio of CC plus bearer bonds to M2 as dependent variables while interest rate on time deposits, ratio of total tax revenue to GDP, and a dummy for the period 1960-71 to capture the impact of currency holdings were used as explanatory variables. They reported that underground economy declined to 35.09% in 1990 from 51.96% in 1960.

   Ogunc and Yilmaz (2000) estimated the size of underground economy in Turkey by applying an indirect monetary approach using data from 1971-1999. They found that that the share of underground economy went from 13.9 % of GDP in 1971 to 20.5 % of GDP in 1999. Similarly, Schneider and Enste (2000) used the monetary approach for different European countries in mid 1990s. They found that the underground economy as a percent of GNP for Greece and Italy was 27-30, for Belgium, Spain, and Portugal was 20-24, for Denmark, Norway and Sweden was 18-23, for Germany, France, Ireland, Great Britain, and Netherlands was 13-16 and for United States, Japan, Switzerland, & Austria was 8-10. Iqbal, Qureshi, & Mahmood (1998) also used monetary approach to estimate the size of the Pakistan's underground economy over the period 1973-1996. They regressed the ratio of CC to M2 on the banking services, growth rate of GDP, international trade tax, interest rate on time deposits, a dummy for structural adjustment program of 1988 and lagged dependent variable. They found an upward trend as the size of the underground economy was 20.2 % of GDP in 1973 to 51.3 % of GDP in 1996.

   Aslam (1998), Khalid (2002) and Kemal (2003) used ratio of CC plus foreign currency accounts to total money supply in their models. However, in explanatory variables they were quite different from one another. In Aslam (1998) the explanatory variables were total tax revenues, interest rate on time deposits and a dummy for foreign currency accounts introduced in 1991. Instead of using the same dummy, Khalid (2002) used structural adjustment program as a dummy variable in his analysis. He also used the banking services and lagged dependent variable in his explanatory part of the model. Instead of using real interest rate and the same dummy of Khalid (2002) model, Kemal (2003) used the dummy of Aslam (1998). Aslam (1998) estimates showed an upward trend from 29 % of GDP in 1960 to 43.9 % of GDP in 1990, stagnant between 1990 and 1996 at 43.8 %, and then declined to 35.5 % in 1998. Khalid (2002) estimates also showed an upward trend from 13.45 % of GDP in 1976 to 28.51 % of GDP in 1998. In Kemal (2003), the estimates went on increasing from 20.27 % of GDP in 1973 to 25.51 % of GDP in 1991, and then with a rapid increase it reached to 54.52 % of GDP in 1998 and then declined to 37.25 % of GDP in 2003. Finally, Kemal (2007) found an upward trend from 16.3 % of GDP in 1974 to 31.4 % of GDP in 2005, with highest 38.7 % value of GDP in 1998.

   Yasmin, Bushra & Rauf (2004) reported upward trend from Rs.12 billion to Rs.1085 billion during the period under analysis (1974-2002). A possible explanation of such enormous increase in underground economy could be the absence of tax reforms over a period under study. Qazi and Hussain (2006) used two models by adding tax reform dummy to the model used previously by Ahmad & Ahmad (1995). The estimates of the 1st model reported downward trend from 51.6 % of GDP in 1960 to 20.3 % of GDP in 2003. The estimates of the 2nd model also reported a downward trend. They noted that taxation reforms played a significant role in shrinking the size of underground economy. They found a positive relationship between black economy and corporate and personal tax rates. According to them, when these rates were at its peak (60%) in 1980s the black economy was also at its peak (51.6%), and with gradual decrease in its rate the size of black economy also went on decreasing from 56 % during 1980-86, to 28 % in 1993.

   Arby et. al. (2010) estimated the size of underground economy by using the monetary approach and applying an Autoregressive-Distributed Lag (ARDL) model by adding education as an additional factor affecting the size of shadow economy. They found that the size of the underground economy was 30 percent. Similarly, about 20 percent of the overall economic transactions were taking place in the informal sector of the economy. Blackburn et. al. (2012) found factors which play a role in motivating individuals and firms to conceal their true wealth to avoid taxes. In their analysis, they found that the presence of financial market imperfection, the amount of wealth disclosed by an individual and the level of financial development are the key factors which determine the degree of involvement in tax evasion and engagement in underground economy. Similarly, Capasso & Jappelli (2013) provided a theoretical and an empirical model to study the relationship between financial development and the size of underground economy in Italy. They found that local financial development (reduction in the cost of external finance) can reduce tax evasion and the size of underground economy. Mughal and Schneider (2018) also used the monetary approach for finding the extent of underground economy in Pakistan for a period of 1973-2015 and employing the ARDL and Granger causality methods. They found a significantly positive relationship between the official sector and shadow economy in the long run. The size of underground economy was recorded 25% on average for the period under analysis.

   Kireenko & Nevzorova (2015) studied the effect of shadow economy on the quality of life. They used a sample of 150 countries and divided them into 5 groups based on the size of their underground economies for the period of 1999-2007. They found that the quality of life (measured by life expectance at birth and the number of children in school) had a positive association with the size of underground economy. Furthermore, Zaman & Goschin (2015) developed an index for shadow economy in which they included three indicators: shadow economy measured in euro per inhabitants, shadow economy as percent of GDP and shadow economy of Romania as percentage of the total EU-28 shadow economies for the period of 1999-2012. Their results showed that the underground and formal economies were co-integrated.

   Ferrer-i-Carbonell and Gerxhani (2016) estimated a relationship between tax evasion and individual wellbeing in fourteen central and eastern European countries in 2013 and 2014 by focusing on the role of institutions and social capital. They found a negative association between tax evasion and individuals’ life satisfaction. On the other hand, Khan and Khalil (2017) incorporated some real factors of economy like employment level, political stability, tax to GDP ratio and cost of working to estimate the size of underground economy using the data for a period of 1972-2010. For estimating the size of informal sector, they used HP-Prescott filter method for obtaining the potential GDP and actual GDP series through feasible generalized least squares (FGLS), and found that 71 percent of the Pakistan's economy was informal.

3. Research Methods

4. Empirical Findings and Results

5. Conclusion and Policy Implications

   This study is an attempt towards knowing the unknown part of the economy. The monetary approach is used to estimate its size and what determines it. A set of four models were presented for the extended time period of 43 years, from 1973 to 2016. These estimates show that the size of informal sector and tax evasion went on increasing from 1974 and attained the maximum level in 1998. However, in the coming years its magnitude went on decreasing with slight variation in its path. The decrease in underground economy and tax evasion may be caused by increase in private investment, increase in smuggling regulations, taxation reform, and better policies of the government like increase in the growth rate of GDP and ease in credit facility to the private sector. Increase in taxes, intensity of regulation, and inflation were found to be the driving force of underground economy and tax evasion, which should be focused and regularized by the policy makers so that people have little incentives to indulge in underground activities. These estimates are different from one another, with small variation, which shows the sensitivity of the dependent variables to the explanatory variables. Moreover, the derived estimates of this study should not be taken an exact measure of underground economy and tax evasion. These results should be treated carefully because they are sensitive to the assumptions made, equations specified, and data used.


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