Measuring the Shadow Economy in Bulgaria
Kyle, Steven; Warner, Andrew; et. al.
GDP accounts are customarily compiled in several alternative ways, each aggregating transactions in different ways, but all (at least in theory) adding to the same total. Two of the most common aggregations are that focused on expenditures (based on the standard national income accounting identity of C + I + G + X - M) and that based on revenues, or incomes. The two methods should, of course, add to the same number since they measure different sides of the same activity: what money people receive on the one side, and what they do with it on the other. However, Bulgarian GDP statistics using the revenue approach give growth rates 2 percentage points lower than the expenditure approach for 1998 and 1999. In other words, data based on what people actually spend show growth rates of 5.4% (1998) and 4.4% (1999), while official figures based on revenues are 3.5% and 2.4%, respectively. This can be interpreted as evidence that there are underreported incomes. It is of interest not only for statistical but also for economic policy purposes to have more detailed information about the discrepancies between official statistics and activities not covered by the official statistical system. It is particularly interesting to know the size and structure of unreported, hidden economic activities, or what has come to be called the “shadow economy.” Currently published estimates of the size of the shadow economy vary from 20 to 25% of officially measured GDP, implying that this is a far larger issue than that implied by the differential growth rates cited above. The objective of this study is to estimate the size of the informal sector, its structure, and the dynamics of its development since Bulgaria ended its long standing centrally directed command economy. Different methods were used to get results that are compatible for international comparisons; also, alternative calculations allow a range of estimates which can help to balance the methodological weaknesses of the individual approaches. The basic rationale of Physical Input Approaches to measuring the size of the shadow economy is that energy consumption (electricity, plus other sources) in a given country is proportional to total economic activity and any change in energy consumption which does not correspond to changes in the measured total activity level of the country indicates a change in the size of the shadow economy. These results provide useful indicators of changes in the shadow economy over time, but cannot be used to quantify its absolute size since this depends on an initial estimate of its size in the base year. This estimate is necessarily arbitrary to some degree in the absence of specific micro-level data allowing definition of an explicit relationship between energy use and economic activity. Results show that the Bulgarian shadow economy in 1998 declined below the estimated base year (1989) share of 30%. According to our calculations the share of the shadow economy in 1998 GDP in Bulgaria was 22%. The largest shares were observed in 1990 (32.2%) and 1996 (34.4%), declining thereafter. This study has shown that though the size of the shadow economy has declined from its peaks in the mid 1990’s, it remains a sizable portion of the Bulgarian economy. While in many ways shadow activities have the potential to be dynamic growth sectors, bringing them into official economy would help spread the burden of social programs more broadly. Our results show that a substantial portion of the response to policy initiatives is effectively hidden from official view. Thus, an ability to correctly estimate the size and structure of the shadow economy will not only provide more accurate statistics but can help improve growth policies as well.
WP 2001-09 July 2001
This work was supported by USAID’s consulting assistance on economic reform (CAER II Project). It was funded by the U.S. Agency for International Development, Bureau for Global Programs, Field Support and Research, Center for Economic Growth and Agricultural Development, Office of Emerging Markets, contract PCE-C-00-95-00015-00, Task Order #39.
Charles H. Dyson School of Applied Economics and Management, Cornell University