000127656 001__ 127656
000127656 005__ 20180122221906.0
000127656 037__ $$a642-2016-44021
000127656 041__ $$aen_US
000127656 245__ $$aMeasuring the Shadow Economy in Bulgaria
000127656 260__ $$c2001-07
000127656 269__ $$a2001-07
000127656 300__ $$a28
000127656 336__ $$aWorking or Discussion Paper
000127656 490__ $$aWP
000127656 490__ $$a2001-09
000127656 520__ $$aGDP 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.
000127656 542__ $$fLicense granted by Kirsten Olson (olso5834@umn.edu) on 2012-07-16T14:20:04Z (GMT):

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000127656 650__ $$aPublic Economics
000127656 700__ $$aKyle, Steven C.
000127656 700__ $$aWarner, Andrew
000127656 700__ $$aDimitrov, Lubomir
000127656 700__ $$aKrustev, Radoslav
000127656 700__ $$aAlexandrova, Svetlana
000127656 700__ $$aStanchev, Krassen
000127656 8564_ $$s413405$$uhttps://ageconsearch.umn.edu/record/127656/files/Cornell_Dyson_wp0109.pdf
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  Previous issue date: 2001-07
000127656 982__ $$gCornell University>Department of Applied Economics and Management>Working Papers
000127656 980__ $$a642