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Dollarization and the Dynamics of the Unobserved Economy:What have
we learned from a decade of transition?
Edgar L. Feige*
*For presentation at CEFIR Seminar, October 15, 2003
Not for citation or quotation without prior consent of author
[email protected]
The Issues



Many efforts to evaluate the transition process after
a decade. (World bank, EBRD, IMF, etc).
Virtually all evaluations are based on the “stylized
facts” of observed GDP growth.
Although all studies acknowledge the shortcomings
of observed GDP as an indicator of the transition
experience,they proceed to evaluate the impact of
initial conditions, institutions and policies on the
success or failure of transition based exclusively on
observed GDP.
The Thesis of this Paper



Any evaluation of the transition process
should be based on the best available
information concerning the growth of total
economic activity (TEA).
TEA = Recorded Economy (Measured GDP)
+Unrecorded Economy.
Therefore, the first order of business is to
review what we know about the unrecorded
(unobserved) economy in transition.
Warnings




Avoid vague terms like “shadow economy” (Schneider and
Enste).
Avoid their emphasis on size of unrecorded economy and focus
on growth of unrecorded sector.
Be aware that different estimation methods: GDP
discrepancies, Labor market discrepancies, AGI-PI
discrepancies, CDM, Tanzi, ECM, MIMIC, measure different
concepts and therefore should not be uncritically lumped
together as if they were comparable.
Be aware of different definitions of underground economies
Definitions and Methods Matter
Distinguish between “observed” and “unobserved” economic
activity.
 Feige (1980) –”Observed sector of economy consists of those
economic activities that are regularly caught in the net of our
official statistical accounting mechanism.” (Recorded income)
 “Unobserved sector being the complement of the observed
sector, consists of those activities that escape the purview of
our current societal measurement apparatus.”
(Unrecorded income)

Definitions


Total Economic Activity (TEA) = recorded +
unrecorded income.
Almost a quarter of a century has passed since this
distinction was introduced, and now a consortium of
national and international agencies has produced
“The Handbook for the Measurement of Nonobserved Activities”(NOE) which presents a
“systematic strategy for achieving exhaustive
estimates of GNP.”
Handbook definitions





Takes account of “activities that are missing from basic data
used to compile the national accounts because they are
underground, illegal, informal, household production for final
use, or due to deficiencies in the basic data collection system.”
These comprise the NOE.
Sets out methods to measure NOE.
I will refer to “recorded economy” as comprising all economic
activities that are in fact included in the published national
accounts” , and “unrecorded economy” as those activities that
should be, but are not fully included in national accounts”
I use term “imputed unobserved income” (IUI) to describe the
estimate of “non-observed” activity that is actually already
included in the national accounts.
We must require that new exhaustive measures of national
accounts are consistent and transparent.
Methods for Estimating Unrecorded
Income




Micro imputations to achieve exhaustiveness in national
accounts (IUI) are very important, but they are also based on
numerous (and sometimes questionable) assumptions.
It therefore continues to be useful to employ macro indicator
models to obtain independent estimates of the growth of the
unrecorded economy.
To date, transition literature has only employed variants of
electric consumption method to estimate size and growth of
unrecorded economy although the monetary methods are the
most commonly used means of estimating the UG.
Limited monetary data, and the problem of currency substitution
has, to date, precluded estimates based on currency/deposit
ratio method (Feige, 1986, 1989).
ECM Approach





Assumes that growth of electric consumption can be
used as proxy for growth of TEA .Kaufmann-Kaliberda
(1996, Johnson et al. (1997)
Assumes unit or variable elasticity to estimate TEA.
Then: Unrecorded economy= TEA-recorded
Eilat-Zinnes (2000) use MEC approach that attempts to
take account of variations in electric prices, electricity
efficiency changes and changes in output composition.
All ECM and MECM estimates require initial benchmark
assumption about relative size of unrecorded sector.
Electric consumption method ECM




Simple unit and variable elasticity models
Assumes that electric power consumption is best
indicator of total economic activity
Assumes that elasticity of electric consumption is
best indicator of TEA
Then difference between growth rate of electric
consumption (TEA proxy) and recorded gdp yields
approximate growth rate of unrecorded income.
Shortcomings of simple ECM




Many unrecorded activities may not require large amounts of
electricity and may use other energy sources
Efficiency of energy use may change over time due to technical
progress, changes in industrial structure and changes in energy
prices
Johnson et.al. compensate for this by assuming different
elasticities for different groups of countries
Eilat/Zinnes use MECM –Try to first filter out effects of price
changes, changes in industrial structure and private sector
share of GDP and then use residual as proxy for TEA
Table 1: Assumed Output Elasticity of Electric
Consumption –Simple ECM
Central and Eastern Europe
“Energy efficient”
0.9
Baltic Countries
“Energy neutral”
1.0
Former Soviet Union
“Energy inefficient”
1.15
Initial condition problem




All methods must assume initial starting
values
Big disagreement about initial conditions
Russia (1989) Kaufman/Kaliberda Johnson
assume Yu/TEA =12%:Alexeev Pyle study
suggests 18%;EZ 14.7% and Kim 3.4%
For some transition countries estimates
range from 5 to 32.8% (Kazakhstan)
Replication Efforts



Importance: ECM models have been widely
used to test hypotheses about the causes
and consequences of unrecorded economy
and to understand the transition process.
Claims that observed fall in recorded output
is false signal if Yu and Yo are substitutes
To date: estimates only exist from 1990-1997
Most test are conducted using cross country
regressions.
Updates and extensions




Employing new revised data sources we
update ECM to 2001
Replication attempts using high and low start
values
Redo EZ procedure with GLS estimates
Results produce many negative estiamtes of
Yu/TEA
Evaluation of What we Know about UG





I attempt to replicate Johnson et al.
I re-estimate simple ECM for 1990-2001 for 25
transition countries, but use Alexeev-Pyle (2002)
initial values.
Estimate MECM for all transition countries.
Report all available estimates of IUI
Compare above to Eliat Zinnes (MECM) results.
Comparison of National Accounts and ECM Estimates of
Unrecorded Income
Average IUI/TEA
NIPA
Period
Average Yu/TEA
ECM-H
Average Yu/TEA
FUGLS
FSU
Armenia
1997-1999
20.1
19.7
26.0
Belarus
1999
10.7
22.2
21.2
Estonia
1997
10.2
32.4
33.6
Georgia
1997-1999
20.4
55.7
55.7
1999
18.9
20.5
16.2
1997-1998
12.1
64.4
65.2
Lithuania
1998
15.2
20.5
20.6
Moldova
1997-1998
15.7
58.9
58.0
Russian
Federation
1997-1998
17.5
44.0
44.2
Ukraine
1999
16.7
57.1
56.6
Uzbekistan
1998
12.3
31.0
34.5
Kazakhstan
Kyrgyz Republic
Table 2a: Estimates of Initial Starting Values of Unrecorded Income (% TEA)
FSU
Kaufmann
/Kaliberda;
Johnson
et.al. - 1989
Alexeev /
Pyle
1989
Eilat /
Zinne
s
1990
Feige/
Urban Low
1989
Feige / Urban
High
1989
Kim
1989
The Baltics
Estonia
12.0
22.1
19.9
12.0
22.1
1.5
Latvia
12.0
22.1
12.8
12.0
22.1
1.8
Lithuania
12.0
22.1
11.3
12.0
22.1
5.1
Belarus
12.0
28.6
15.4
12.0
28.6
3.3
Moldova
12.0
28.6
18.1
12.0
28.6
8.2
Russian
Federation
12.0
18.0
14.7
12.0
18.0
Ukraine
12.0
25.3
16.3
12.0
25.3
6.6
Armenia
NA
NA
23.4
12.0
32.8
8.6
Azerbaijan
12.0
32.8
21.9
12.0
32.8
9.8
Georgia
12.0
32.8
24.9
12.0
32.8
11.3
Western FSU
3.4
The Caucasus
ECM Estimates
Russian Federation
50
percent
40
30
20
10
0
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
year
Johnson Original Results
ECM - High Start Values
ECM - Low Start Values
Some Bad results
Poland
30
20
percent
10
0
-10
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
-20
-30
year
Johnson Original Results
ECM
MECM Estimates
percent
Russian Federation
50
45
40
35
30
25
20
15
10
5
0
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
year
EZ
FUEZ
FUGLS
MECM Replication
percent
Poland
30
25
20
15
10
5
0
-5 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
-10
-15
-20
year
EZ
FUEZ
FUGLS
Comparison of Recorded Growth, Growth of the Unrecorded
Economy and the Rate of Growth of Total Economic Activity:
FSU- 1989-2001
Average Growth
Average Growth
Average Growth
Recorded GDP
Unrecorded Economy
Total Economic Activity
Estonia
-0.9
-6.1
-2.3
Latvia
-1.8
-8.9
-3.6
Lithuania
-2.7
-8.0
-4.1
MEAN FOR GROUP:
-1.8
-7.7
-3.3
Belarus
-0.5
-12.5
-3.2
Moldova
-7.4
-2.8
-7.9
Russian Federation
-3.6
5.7
-1.5
Ukraine
-6.1
3.2
-3.0
MEAN FOR GROUP:
-4.4
-1.6
-3.9
FSU
The Baltics
Western FSU
Continued
The Caucasus
Armenia
-1.3
-12.7
-4.5
Azerbaijan
-3.7
3.7
-1.1
Georgia
-6.5
-0.3
-4.8
MEAN FOR GROUP:
-3.8
-3.1
-3.5
Kazakhstan
-1.7
-12.5
-4.4
Kyrgyz Republic
-2.9
8.7
1.8
Tajikistan
-4.9
3.6
-2.0
Turkmenistan
-1.1
2.8
-2.1
Uzbekistan
0.3
0.2
0.0
MEAN FOR GROUP:
-2.1
0.6
-1.3
MEAN FOR FSU:
-3.0
-2.4
-2.8
Central Asia
Comparison of Recorded Growth, Growth of the Unrecorded
Economy and the Rate of Growth of Total Economic Activity:
CEE- 1989-2001
CEE
Croatia
Average Growth
Average Growth
Average Growth
Recorded GDP
Unrecorded Economy
Total Economic Activity
3.7
-0.2
-0.7
Czech Republic
0.4
10.5
0.7
Hungary
0.8
-4.4
-0.4
Poland
2.2
-78.0
-0.7
Slovak Republic
0.7
-2.3
-1.2
Slovenia
2.0
16.2
3.8
MEAN FOR GROUP:
0.9
-9.0
0.3
Albania
1.5
15.7
6.7
Bulgaria
-2.0
-3.8
-2.7
Macedonia
-1.5
6.7
0.8
Romania
-1.5
-247.5
-4.2
MEAN FOR GROUP:
-0.9
-57.2
0.2
-28.3
0.3
MEAN FOR CEE:
0.2
Relationship between unrecorded and
recorded


5) Yu = 50.6 -.38 Yo - .05 Yo x D
R2 =.87
(36.5) (-16.1)
(-4.1)
N=318, Adj




The corresponding MECM equation employing the
FUGLS estimate of Yu is:
6) Yu = 47.6 - .34 Yo - .05 Yo x D
N=298, Adj
R2 =.85
(31.4) (-13.1)
(-4.1)
Evolution of Recorded and Unrecorded
Income-ECM Estimates
Russian Federation
Evolution of Recorded and Unrecorded Economy
ECM-H
100.0
80.0
60.0
40.0
20.0
0.0
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
Recorded
Unrecorded
Bad News
Poland
Evolution of Recorded and Unrecorded Economy
ECM-H
120.0
100.0
80.0
60.0
40.0
20.0
0.0
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
Recorded
Unrecorded
Observations




Size of unrecorded sector is highly dependent on initial
benchmark assumptions. What is important for transition
countries is growth of recorded and unrecorded
economy
ECM approach produces negative values for size of
unrecorded economy for several countries. It can not be
regarded as a reliable means of estimating the size of
UG in transition
May still be useful to estimate dynamics –growth rates in
unrecorded activity
Therefore we must move beyond simple cross country
tests and move to richer panel data testing
CDM Approach





De facto dollarization of many transition countries implies that
foreign currency in circulation (FCC) is an important component
of the effective currency supply and foreign currency deposits
(FCD) are an important component of the effective supply of
deposits.
I have now constructed estimates of FCC in transition countries
based on CMIR data.
Roughly 50% of US dollars are held abroad. Mostly in Latin
America and transition countries.
For transition countries I use (FCC+LCC)/(FCD+LDD) =(total
currency/total deposits) as the appropriate C/D ratio.
Since currency substitution will effect both denominator and
numerator, variations in C/D are assumed to largely reflect
changes in unrecorded sector which primarily uses cash as
medium of exchange to avoid a paper trail and hence reduces
probability of detection.
The US Currency Enigma
• $580 billion of US
currency in $1-$100
bills.
• $2200 per person$160 in 1961.
• $5500 per family
• 65% in $100 bills
• 14 $100 bills per
person
• 70 notes per person
Key Issues
• Who holds all of this currency?
– Households?
– Firms?
– The Underground Economy?
– Residents of other countries?
• How much of America’s currency is
held abroad?
• If Abroad, where is US currency
located?
• What are the implications of US
currency held overseas?
Allocation Of Currency
Survey Estimates
80
70
60
50
Households
Firms
Underground
Missing
40
30
20
10
0
Percent
Table 1 Countries with highest estimated Currency Substitution Index (CSI)
Country
Currency Substitution Index
Kazakhstan
95
Cambodia
94
Belarus
88
Russia
87
Azerbaijan
80
Argentina
80
Nicaragua
79
Uruguay
77
Bolivia
75
Georgia
74
Mongolia
73
Ukraine
72
Latvia
70
El Salvador
69
Peru
64
Dominican Republic
62
Costa Rica
62
Saudi Arabia
62
Bahrain
57
Estonia
57
Romania
54
Turkey
54
Kyrgyz Republic
52
Venezuela
51
Armenia
51
De facto Dollarization



Estimates employing various methods
suggest that roughly 50% of US currency is
held abroad, roughly $290 billion
However the location of dollars was
previously unknown.
I have now attempted to determine the
location of US currency held abroad
employing CMIR data.
Unofficial Dollarization



Behavioral adaptation of using FCC as
substitute for services of domestic money
Currency substitution refers to the use of
foreign currency as a medium of exchange
and unit of account
Asset substitution refers to use of foreign
denominated monetary assets as stores of
value
Why do we care how much cash is
abroad?






Required for estimation of domestic money
supply
Improves conduct of monetary policy
BOP estimates of cross border flows
Better monetary estimates of underground
economy
Seigniorage
Counterfeit detection and deterrence
Estimated Distribution of US Currency
Overseas
Distribution of US Currency Abroad
Asia
22%
CEE
2%
Africa
1%
Middle East
10%
Latin America
23%
FSU
40%
North America
2%
Dollarization



Present two measures of dollarization.
FCC per capita and Currency Substitution Index
(CSI)=FCC/(FCC+LCC)
For Russia my estimates suggest that per capita
dollar holdings amount to $903 only exceeded by
Kazakhstan with $1024 and Latvia with $1209
–
Unfortunately, the Russian Central Bank did not participate
in CEE/IMF effort to monitor Euro introduction. Therefore,
we have an incomplete picture of FCC in circulation, since
euro holding estimates are not available.
Alternative Measures of de facto
Dollarization –Select FSU Countries
CDI= (FCC+FCD) / (M2+FCC)
DI=FCD / M2
CDI Trend
DI Trend
Belarus
57.2
52.8
↑
↑
Ukraine
37.8
19.4
↑
↑
Moldova
27.3
27.3
↑
↑
Russia
73.5
24.5
↑
↑
Inter-temporal Correlations between
Comprehensive Dollarization Index (CDI)
and the IMF Dollarization Index (DI)
CDI-DI
Period
Russia
0.222
93-2001
Belarus
0.997
92-2001
Ukraine
0.596
92-2001
Currency (CSI) and Asset Substitution (ASI) Indices
Western FSU
Western FSU
CSI
ASI
CSI Trend
ASI Trend
Belarus
34
194
↑
↑
Moldova
NA
78
NA
↑
Russia
87
51
↑
↑
Ukraine
64
50
↑
↑
Cross Country CorrelationsDollarization - Currency and Asset
Substitution Indices
Region
CSI-ASI
CSI-CDI
CSI-DI
ASI-CDI
ASI-DI
FSU*
0.312
0.763
0.113
0.628
0.692
CEE
0.021
0.431
0.347
0.886
0.932
FSU*+CEE
0.355
0.748
0.218
0.711
0.695
Inter-temporal Correlations
CSI-ASI
Belarus
0.540
Russia
-0.039
Ukraine
0.534
ASI-CDI
ASI-DI
0.39
0.961
0.952
0.929 -0.10
0.279
0.988
0.938
0.783
0.942
CSI-CDI
0.455
CSI-DI
.275
Observations:




CDI and DI give quite different pictures of extent of
dollarization
CDI and DI are correlated over time but relationship
shows significant country differences
DI is better measure of asset substitution than
currency substitution
Relationship between currency substitution is more
complex and variable than is usually thought to be
the case, both over time and between countries
Implications of de facto dollarization









De facto dollarization is typically a rational response to agents
loss of confidence in the domestic currency, often resulting from
inflation, currency devaluations and/or currency confiscations.
May also be due to growth of underground economy
De facto dollarization results in loss of seigniorage
It thwarts the monetary authority from pursuing inflationary
finance
Inhibits its effectiveness in controlling exchange rates.
Efficiency gains from portfolio diversification
Reduced incentives for inflation finance and capital flight
Lowers costs of tax evasion and reduces ability of fiscal
authority to command resources from the private sector.
Growth of UG distorts macro information system making policy
formulation more difficult
Table 3: Comparison of Recorded Growth, Growth of the Unrecorded
Economy and the Rate of Growth of Total Economic Activity:
CDM Composite Estimates
FSU
Average Growth
Average Growth
Average Growth
Recorded GDP
Unrecorded
Economy
Total Economic
Activity
The Baltics
Estonia
-1.69
1.69
-1.47
Latvia
-3.06
2.13
-2.31
Lithuania
-3.32
-4.32
-3.85
MEAN FOR GROUP:
-2.69
-0.17
-2.54
Belarus
-1.27
-2.55
-1.95
Moldova
-9.01
-2.40
-8.33
Russian Federation
-4.08
11.84
0.70
Ukraine
-7.95
6.90
-1.89
MEAN FOR GROUP:
-5.58
3.45
-2.87
3.31
7.71
4.53
Azerbaijan
-5.08
11.28
0.13
Georgia
-7.51
2.00
-4.47
MEAN FOR GROUP:
-3.09
7.00
0.06
-3.04
4.89
-0.44
0.35
8.89
2.13
Tajikistan
-2.83
-6.08
-4.49
Turkmenistan
-3.88
7.88
-0.21
0.16
-1.91
-0.82
MEAN FOR GROUP:
-1.85
2.73
-0.77
MEAN FOR FSU:
-3.26
3.20
-1.52
Western FSU
The Caucasus
Armenia
Central Asia
Kazakhstan
Kyrgyz Republic
Uzbekistan
Table 3: Comparison of Recorded Growth, Growth of the Unrecorded
Economy and the Rate of Growth of Total Economic Activity:
CDM Composite Estimates
CEE
Average
Growth
Average
Growth
Average
Growth
Recorded
GDP
Unrecorded
Economy
Total
Economic
Activity
EU Border Countries
Croatia
2.83
4.14
2.93
-0.02
19.01
1.59
Hungary
0.53
-0.94
0.11
Poland
2.38
1.35
1.98
Slovak Republic
0.45
1.92
-0.09
Slovenia
4.25
6.42
4.27
MEAN FOR GROUP:
1.74
5.32
1.80
Albania
1.05
9.45
3.54
Bulgaria
-2.44
8.80
-0.39
0.33
11.96
2.60
Romania
-2.03
-1.06
-1.96
MEAN FOR GROUP:
-0.77
7.29
0.95
0.73
6.11
1.46
Czech Republic
The Balkans
Macedonia
MEAN FOR CEE:
Observations



Table 3 reveals that for FSU average rate of growth
of recorded economy was –3.26% while Unrecorded
economy grew by 3.20%. Therefore TEA fell by –
1.52% not, -3.26 as reflected in GDP growth.
For CEE GDP growth =.73% but unrecorded growth
was 6.11% therefore TEA grew by 1.46%
Russia and Ukraine showed greater overall growth
due to growth in UG. Tajikistan overall growth was
lower than recorded growth due to decline in UG.
Table 4. Estimate of Growth of Recorded (REC) and Total Economic Activity (TEA)
(Recorded and Unrecorded Over the Decade of Transition.
FSU
Base year
REC 2000
Index
TEA 2000
Index
The Baltics
Estonia
1989=100
79.8
83.6
Latvia
1989=100
64.2
73.4
Lithuania
1989=100
65.5
62.2
69.8
73.1
MEAN FOR GROUP:
Western FSU
Belarus
1989=100
84.1
78.1
Moldova
1989=100
32.1
36.2
Russian Federation
1989=100
61.8
104.1
Ukraine
1989=100
38.6
79.6
54.2
74.5
MEAN FOR GROUP:
The Caucasus
Armenia
1992=100
127.2
139.8
Azerbaijan
1989=100
51.1
98.0
Georgia
1989=100
34.5
53.4
70.9
97.0
MEAN FOR GROUP:
Central Asia
Kazakhstan
1989=100
69.4
90.6
Kyrgyz Republic
1993=100
99.1
109.0
Tajikistan
1992=100
77.6
71.4
Turkmenistan
1992=100
65.9
89.9
Uzbekistan
1989=100
100.5
89.7
MEAN FOR GROUP:
82.5
90.1
MEAN FOR FSU:
70.1
83.9
Table 4. Estimate of Growth of Recorded (REC) and Total Economic Activity (TEA)
(Recorded and Unrecorded Over the Decade of Transition.
CEE
Base year
REC 2000 Index
TEA 2000 Index
EU Border Countries
Croatia
1992=100
123.9
125.44
Czech Republic
1989=100
98.7
118.31
Hungary
1989=100
104.5
100.28
Poland
1989=100
127.2
123.59
Slovak Republic
1989=100
102.7
98.15
Slovenia
1992=100
139.5
139.36
116.1
117.52
MEAN FOR GROUP:
The Balkans
Albania
1989=100
102.9
141.50
Bulgaria
1989=100
74.8
93.03
Macedonia
1992=100
101.6
117.91
Romania
1989=100
78.3
78.80
89.4
107.81
105.4
113.64
MEAN FOR GROUP:
MEAN FOR CEE:
Table 5. Relationship Between the Recorded and Unrecorded Economies
and their Volatility.- CDM Estimates
Correlation
coefficient
Regression
coefficient
FSU
Standard
deviation
Standard
deviation
Recorded
economy
Unrecorded
economy
The Baltics
Estonia
-0.62
-1.62
8.48
22.02
Latvia
-0.32
-0.49
12.66
18.91
0.03
0.06
9.56
17.99
-0.30
-0.68
10.23
19.64
Belarus
-0.01
-0.03
7.99
18.04
Moldova
-0.62
-1.49
12.32
29.42
Russian Federation
-0.08
-0.22
6.59
18.54
0.00
0.00
8.13
8.18
-0.18
-0.44
8.76
18.54
Armenia
-0.02
-0.03
7.43
15.09
Azerbaijan
-0.41
-0.57
13.05
18.27
0.00
0.00
17.32
26.88
-0.14
-0.20
12.60
20.08
Kazakhstan
-0.05
-0.17
7.04
22.89
Kyrgyz Republic
-0.77
-2.90
10.21
38.67
Tajikistan
NA
NA
13.09
NA
Turkmenistan
NA
NA
16.19
NA
Uzbekistan
NA
NA
4.97
NA
MEAN FOR GROUP:
-0.41
-1.54
10.30
30.78
MEAN FOR FSU:
-0.24
-0.62
10.34
21.24
Lithuania
MEAN FOR GROUP:
Western FSU
Ukraine
MEAN FOR GROUP:
The Caucasus
Georgia
MEAN FOR GROUP:
Central Asia
Table 5. Relationship Between the Recorded and Unrecorded Economies
and their Volatility.- ECM Estimates
Correlation
coefficient
Regression
coefficient
CEE
Standard
deviation
Standard
deviation
Recorded
economy
Unrecorded
economy
EU Border Countries
Croatia
-0.32
-1.60
5.11
25.87
Czech Republic
-0.82
-8.28
4.53
45.83
Hungary
-0.38
-0.58
5.14
7.86
Poland
-0.19
-6.78
5.96
208.91
Slovak Republic
-0.27
-4.72
6.67
116.34
0.29
45.35
0.85
133.74
-0.28
3.90
4.71
89.76
Albania
0.13
0.23
12.47
21.12
Bulgaria
0.01
0.05
5.97
23.41
Macedonia
-0.04
-0.11
4.87
14.06
Romania
-0.13
-1.17
6.18
56.73
MEAN FOR GROUP:
-0.01
-0.25
7.37
28.83
MEAN FOR CEE:
-0.17
2.24
5.78
65.39
Slovenia
MEAN FOR GROUP:
The Balkans
Summary




Evaluation of transition experience requires estimates of
TEA.
IUI estimates are worthwhile but still incomplete and still
appear to underestimate the size and growth of
unobserved sector.
ECM results appear much less reliable than CDM
results.
Unrecorded and recorded economies are negatively
correlated suggesting that substitution effects dominate
income effects. The unrecorded sector serves as a buffer
for the recorded sector and is counter-cyclical and more
volatile.