Shortage and Currency Substitution in Transition Economies:
Bulgaria, Hungary, Poland, and Romania
International Advances in Economic Research 7:2 (May 2001)
Robert F. Mulligan
Western Carolina University and the State University of New York at
Binghamton
Department of Economics, Finance, & International Business
College of Business
Western Carolina University
Cullowhee NC 28723 U.S.A
+1-828-227-3329
mulligan@wcu.edu
and
Erwin Nijsse
Royal Dutch Shell
Abstract
This paper examines currency substitution in four central European countries, Bulgaria, Hungary, Poland, and Romania, during the end of central planning and transition to market economies. Before liberalization, central European economies faced increasing shortage and repressed inflation in the official sector, and growing free, grey, and black-market sectors. The population held substantial portions of their wealth in real assets and foreign currency. Furthermore, part of savings was held as hunting money against potential opportunities to buy large quantities in official stores, or pay price premia on the black market. The shift from centrally-planned to market economies is modeled by including a shortage variable. Foreign currency demand and consumption functions are estimated by the Johansen procedure. Official-sector shortage is found to be an important determinant of foreign currency demand in each country.
1. Introduction
This paper examines currency substitution in four central European
economies, Bulgaria, Hungary, Poland, and Romania, from 1986 to 1994.
Currency substitution is an important concept in the history of economic
thought. Menger (1874, pp. 268-270) cites the instance of parallel
exchange commodities used in ancient Mexico during the transition from
a pure barter to a monetary economy. Interestingly, currency substitution
can therefore predate the establishment of money. The phenomenon
of currency substitution is a general precondition of which Gresham's law
is a special case: at least two currencies or exchange commodities
must circulate in parallel before one ("bad money") can drive out the other
("good money.") Gresham's law can thus be understood as an
extreme case of currency substitution resulting ultimately in abandonment
of one of the currencies. In Gresham's law, the good money's superior
store-of-value character leads to hoarding and the bad money's equal value
for transactions leads to it being used for all transactions.
In centrally-planned economies (CPEs), currency substitution
was a very singular phenomenon. Gresham's law never became fully
operable because although foreign currency (the "good money") had a superior
store-of-value character, both foreign and domestic currencies had separate,
complementary transactions uses in official and non-official sectors. In
most eastern European economies, the rate of currency substitution seems
strongly correlated with high inflation and uncertainty.
Experience of the transition economies closely resembles the
recent history of some Latin American countries, like Argentina, Bolivia,
Mexico, Peru and Uruguay (Sahay and Végh, 1995). Currency
substitution in Latin America received a great deal of attention in the
literature (see e.g. Calvo and Végh (1992), Rodriguez (1992), Rojas-Suarez
(1992), Savastano (1992), and Sturzenegger (1992)). Until recently,
currency substitution in the transition economies of central and eastern
Europe received much less attention, with the notable exceptions of Charemza
and Ghatak (1990), Aarle (1994), and Aarle and Budina (1995).
The remainder of this paper is organized as follows. Section
2 discusses the economic theory of currency substitution. Section
3 analyzes data for the four countries and presents shortage measures.
Section 4 presents empirical estimates of the foreign money demand function
derived in Section 2. Section 5 summarizes main points and draws
conclusions.
2. Background and Literature
The traditional view of CPEs as "shortage economies" (Kornai,
1980), states that central planning authorities arbitrarily divide the
money stock into household and state-enterprise sectors (Hartwig, 1983,
1985). In each sector, money flows play only a passive accounting
role, enforcing adherence to the central plan. Money demand does
not result from utility-maximizing agents' choice, but as a by-product
of central planning. Central planners typically chose a non-market-clearing
price vector, leading to excess demand and forced savings.
This traditional view, however, applies only to highly-idealized
CPEs without private sectors, or free, grey, or black markets to equilibrate
the economy. Unlike other economic agents in CPEs, households faced
hard budget constraints and always tried to maximize utility from real
and financial assets. Consequently, savings of the population in
CPEs were voluntary, never forced. It is logical to view their choice
of money holdings as resulting from constrained-optimization.
The range of alternative financial assets was broader in reality
than the traditional view assumed. Although households did not hold
either foreign or domestic bonds, real asset and foreign currency holdings
were often substantial. Foreign currency holdings consisted of private
hoards (mattress money,) deposits in banks abroad, and where permitted,
(as in Poland and Yugoslavia,) domestic deposits of foreign currency.
These general observations about household behavior in CPEs suggest
the importance of environmental constraints. Shortage in the official
sector, brought about by the central planning authorities' arbitrary selection
of a non-market-clearing price vector, is the most important feature of
these economies. In addition, availability of goods in the black
market, and the possibility of holding foreign currencies and real assets
as stores of value, must also be acknowledged. Households should
be viewed as utility-maximizing agents choosing optimal money holdings
subject to constraints. This view contrasts strongly with the traditional
one where households passively adapt their spending to goods availability.
Currency substitution is examined using quarterly data for Bulgaria,
Hungary, Poland, and Romania. Due to constraints on data availability
the study is not extended to more countries. Although many countries,
including Russia, now record data on foreign currency holdings, the time
span of data available before the end of central planning is too short
for econometric estimation.
Mulligan and Nijsse (1995) present a model where an official-sector
cash-in-advance constraint is augmented with a shortage variable.
The model includes transactions, precautionary, and portfolio motives for
holding money in a centrally-planned economy in transition. The transactions
motive is incorporated through two cash-in-advance constraints: one for
the official sector, where only domestic currency can be spent; and one
for total currency holdings similar to Lane (1992), and Nijsse and
Sterken (1995) who modeled the demand for money in Poland.
The precautionary motive is incorporated through shopping time,
which is a function of purchases in each sector, real balances of the two
currencies, and shortage. Shopping time eats away at leisure and
has a negative impact on utility. This captures the behavior Kornai
(1980, 457-458) described as purchaser alertness. Facing shortage,
consumers carry shopping money to take advantage of unpredictable, and
infrequent, opportunities to purchase large quantities at low prices in
the official sector. Both currencies are also stores of value, and
holdings also depend on their rates of return relative to goods.
If the shortage-augmented official-sector cash-in-advance constraint,
which binds as an equality, is used to marginalize with respect to domestic
money, the demand for foreign money is expressed as a function of the black
market exchange rate, aggregate household consumption, inflation, and shortage
in the official sector. The functional form of the foreign-money
demand equation depends on the form of the utility function, which is unknown
and unobserveable:
3. Data
Contrary to what is generally assumed, the four economies in
this study practised only partial, not full, central planning. Reforms
had already been started by the 1970s, especially in Hungary and Poland
(Jeffries, 1993). In Hungary, the "New Economic Mechanism," aiming
at greater enterprise autonomy, partial price liberalization, and flexible
wages, was implemented as early as 1968. In Poland, reforms in the
1970s were modest, but accelerated in the early 1980s. In Bulgaria
and Romania, credible reforms were implemented only in the second half
of the 1980s, and until late 1990, both economies remained highly centralized.
Following the reform programmes, the private sector in the four
CPEs expanded. During the 1970s private sector activities were dominated
by agriculture. In the 1980s the private sector broadened in scope
to include small retail stores, hotels, restaurants, and handcrafts.
Next to the legalized private sectors, black markets developed in several
consumer goods, including durables like flats and cars, as well as foreign
currency and precious metals. These markets not only satisfied excess
demand from the official sector, but had a speculative character.
Real assets were good investment alternatives to bank deposits in CPEs.
Especially in Poland, black-market activity was widespread and closely
followed by the authorities (Wyczanski, 1989). The existence of legal
and illegal private sectors had a positive impact on these economies, playing
an equilibrating role by allowing households to adjust spending and savings
to desired levels. However, at the same time, the relative profitability
of private sector activities induced reallocation of resources from the
socialized sector, preventing the socialized sector from functioning properly.
The financial sectors were liberalized in each of the four countries
at the end of the 1980s, before overall liberalization. This happened
in Hungary in 1987, in Poland in 1989, and in Bulgaria and Romania in 1990
(Calvo and Kumar, 1993). Traditional Monobank systems were reformed
into western-type two-tier banking systems. Interest rates on bank
deposits, which were traditionally fixed and often negative in real terms,
were gradually liberalized. With the implementation of monetary stabilization
programmes, positive real interest rates became an important instrument
to support tight monetary policies. At the same time, household savings
in the form of financial assets greatly expanded. In Hungary, for
example, the household savings rate increased from the traditional pre-reform
level of 2-4%, to 14% in 1992 (Bod, 1994). The strong increase in
savings rates was probably due more to the changing economic situation,
than interest rate policies of national banks at the end of the 1980s.
Before liberalization, people felt secure in terms of employment security
and pensions, but perspectives changed dramatically as the CPEs entered
transition. The transition economies still face political and economic
instability, high inflation, high unemployment, and only partially-indexed
social security allocations.
Foreign currency holdings
While the macroeconomic environment affects demand for foreign
currency, the supply of foreign currency depends critically on institutional
constraints. Poland and Yugoslavia, with fairly liberal banking systems,
saw higher dollarization rates before liberalization than after.
In other countries, the absence of significant dollarization was primarily
due to tight controls on foreign exchange and the banking system.
Foreign currencies were mainly supplied by smuggling and were held almost
exclusively as "mattress money," which cannot be estimated reliably.
In Bulgaria at the end of the 1980s, foreign currency as a percentage
of total money holdings (M2), increased from approximately 5% in 1986,
to above 34 percent by the first quarter of 1994. Hungary, having
much lower inflation, saw far less currency substitution. However,
the percentage of foreign currency deposits, 20% of M2 at the beginning
of 1994, shows an increasing trend.
In Poland, currency substitution was a much more significant
phenomenon, and the presence of an active black market suggests Poles held
foreign currency for transactions reasons. From 1985, foreign deposits
as a percentage of M2 increased strongly, reaching its record high at the
end of 1989, 75% of M2. In contrast to the other countries, Poland
saw "resubstitution" of foreign currencies back into zlotys at the end
of the 1980s, due to falling inflation and the rigorously-followed policy
of positive real interest rates on zloty deposits. Figures may exceed
official numbers because of the use of the black market exchange rate,
but considering the near-equality of the official and black market exchange
rate from March 1989, the general pattern is not dramatically different.
However, among the four countries considered, Poland was a special
case because from the beginning of the 1980s, zloty inflation was high
and foreign currency deposits could be freely held without a declaration
of source (Chawluk and Cross, 1993). Thus, in Poland, currency substitution
was already extensive before the end of central planning. In the
other countries, currency substitution faced greater restrictions.
In Romania, finally, foreign currency holdings displayed a strongly
increasing positive trend following liberalization of the banking system
at the end of 1990, representing approximately 35% of M2 in the beginning
of 1994. Comparing experiences of Romania, Bulgaria and Hungary,
with Poland, suggests restrictions on holding foreign currency deposits
in the former three countries were relatively severe under central planning.
There appears to be a generally strong correlation between macroeconomic
instability, represented by inflation, and foreign currency holdings.
Bulgaria and Romania, with annual inflation rates of 73% and 256% in 1994
(EBRD, 1994), show strongly rising foreign currency deposits. In
Poland and Hungary, the situation seems to have stabilized, although in
1994 the share of foreign currency holdings in both countries was slightly
higher than in 1993.
As Aarle and Budina (1995) note, currency substitution or "dollarization"
is likely to remain a significant phenomenon, even if the economies in
transition succeed in achieving macroeconomic stabilization. Empirical
evidence from Latin America supports this conclusion (Savastano, 1992).
For the four Central European economies, foreign currency as a percentage
of M2 appears to have stabilized only for Poland. Romania and, to
a lesser extent, Bulgaria and Hungary, show increasing positive trends.
Shortage
The analysis of shortage in CPEs has been thoroughly analyzed
(notably by Portes and Winter (1980), Portes (1981), Charemza and Quandt
(1982), Jansen (1982), and Kornai (1980). In these papers excess
demand is either directly or indirectly measured. In practice this
leads to highly different results, (for example, for Poland see Charemza
and Gronicki (1988) and Podkaminer (1982, 1989)) and simpler measures perform
fairly well (Charemza, 1992). Various shortage indicators have been
used in the literature: Hartwig (1987) uses the reciprocal of the velocity
of circulation; Payne (1990) uses real consumer credit; Feltenstein et
al (1990) use the part of savings explained by virtual prices, a combination
of official prices and real money; Lane (1992) criticizes earlier measures
as circular and uses instrumental variables to model expectations.
Nijsse and Sterken (1995) use four alternative measures for Poland:
first, the ratio of nominal household income growth to the growth of nominal
net material product corrected for imports and exports; second, the price
differential of the free market price index over the official food price
index; third, the ratio of nominal income to the growth of official retail
sales (after Chawluk and Cross, 1993); and fourth, the ratio of consumption
in the official sector to inventories held in this sector.
Data constraints forced the choice of a simple but highly plausible
shortage indicator which has been shown to work well empirically: the ratio
of the black-market over the official exchange rate (Peebles, 1991).
As with any shortage indicator, this one presents potential problems.
For the period before liberalization, the black-market exchange-rate was
overvalued in most CPEs, whereas the official exchange rate was undervalued
and followed developments in the black-market exchange rates slowly, with
a long and variable time lag. Shortage rose in all four countries
in the latter half of the 1980s, and in the case of Bulgaria and Hungary,
fell somewhat at the beginning of 1990, before liberalization.
At the moment of price liberalization the shortage indicator
is set arbitrarily at 1, since following price liberalization the Walrasian
auctioneer is assumed to work again, and in any case, the central planning
authorities stop fulfilling their function of selecting the non-market-clearing
price vector. The dates of liberalization were taken from Aarle and
Budina (1995): for Bulgaria, January 1991; Hungary, February 1991; Poland,
January 1990; and Romania, April 1991.
Shortage in Hungary was low compared to the other countries,
with Bulgaria having the worst shortage, in the third quarter of 1989.
This confirms earlier evidence found by Charemza and Ghatak (1990), for
example. In Hungary, prices followed market developments, except
for a basket of basic consumer goods that remained subsidized until the
end of the 1980s (Jeffries, 1993).
For Poland, shortage figures suggest a positive correlation
between foreign currency holdings and shortage; for the other three countries
the correlation seems negative. This is due in part to differences
in banking regulation under central planning, specifically that foreign
currency deposits were allowed in Poland, as discussed above. In
addition, during partial central planning in Poland, the transactions value
of foreign currency on the black market was much larger than in other countries,
where foreign currency seemed to be held mainly as a store of value.
The evidence found by Charemza and Ghatak (1990) for Hungary and Poland
supports this conclusion. Bulgaria, Poland, and Romania all seem
to suffer more severe shortage. Evidence suggests the scope for black
market trade was by far largest in Poland.
Exchange rates
All four countries in this study show steady depreciation of
the domestic currency. By 1994, all countries had implemented internal
current-account convertibility, except for tourism, where restrictions
remained on amounts people were allowed to take abroad. In general,
capital-account convertibility has not been implemented, but restrictions
on profit repatriation have loosened.
In Bulgaria, Hungary, and Romania, a spread between black market
and official exchange rates could be observed as late as the beginning
of 1994. This indicates restrictions remained on trade in foreign
currencies, or that central banks intentionally created a spread.
In Romania, for example, the interbank foreign exchange rate was unified
with the black market exchange rate only in 1994. The Romanian leu
has floated freely ever since. In Bulgaria, the black market exchange
rate was quoted as 73 lev per USD versus the official rate of 65 lev per
USD in the first quarter of 1994. The lev has been floating freely
since February 1991 and is internally convertible.
By 1994, the domestic currency in Hungary, the forint, was pegged to a basket of currencies consisting of 70% ECU and 30% USD. In Poland, the zloty is pegged to a basket of currencies as well, and depreciates at a pre-announced rate of 1.5% per month. Trade in foreign currencies was fully legalized as early as the beginning of 1989 and the spread between black-market and official exchange rates nearly vanished after the devaluation of the zloty on January 1, 1990.
4. Empirical Results
Unit Root Tests
Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests
were applied to check whether the single variables contain one or more
unit roots. Both the Lagrange-Multiplier (LM) test and the Schwarz
Criterion (SC) [also know as the Schwarz Bayesian Information Criterion
(SBIC)] were used to determine optimal lag length. First, the LM-test
was used to test for up-to-fourth-order serial correlation of the residuals
to define the most parsimonious model with white-noise residuals.
Then, a few lags were added to determine the optimal lag length by minimizing
the SC statistic.
Phillips-Perron (1988) tests were also performed. These
tests involve a nonparametric correction for short-run dependence, rather
than an autoregressive correction as in the ADF-test.
Table 1 presents ADF and PP unit root tests of real foreign currency
deposits, real consumption, inflation, black-market exchange rate, and
shortage. Inflation, pt, is used as the return on real assets. The
official price index was used as deflator. Each test was performed
with a constant and no trend. Since the residuals of the Phillips-Perron
test do not have to be white-noise, a standard lag-length of four was used
for this test. MacKinnon (1991) provides response surface estimates
of asymptotic critical values, which are printed below the t-tests in Table
1. The significance levels reported next to each test statistic are
small-sample significance levels computed by a bootstrap Monte Carlo simulation.
In Table 1, t-statistics indicate the null hypothesis of a unit root has
to be accepted at the five percent critical level for all variables, except
inflation in Hungary, with both tests based on the MacKinnon asymptotic
critical values.
Country | lags | ADF | sig. level | lags | PP | sig. level |
Bulgaria | ||||||
mtf | 0 | -2.48 | 0.99 | 4 | -2.55 | 0.99 |
ct | 1 | -0.24 | 1.00 | 4 | -0.18 | 1.00 |
pt | 4 | -1.32 | 0.96 | 4 | -1.86 | 0.99 |
et | 1 | 0.03 | 1.00 | 4 | 0.34 | 1.00 |
st | 1 | -0.96 | 1.00 | 4 | -1.06 | 1.00 |
Hungary | ||||||
mtf | 2 | -0.76 | 1.00 | 4 | -0.29 | 1.00 |
ct | 5 | -0.21 | 1.00 | 4 | 0.73 | 1.00 |
pt | 4 | -1.79 | 0.85 | 4 | -6.87 | 0.26 |
et | 1 | -0.75 | 1.00 | 4 | -0.84 | 1.00 |
st | 1 | -0.56 | 1.00 | 4 | -0.93 | 1.00 |
Poland | ||||||
mtf | 4 | -1.45 | 0.95 | 4 | -1.27 | 1.00 |
ct | 5 | -0.31 | 0.99 | 4 | -0.34 | 1.00 |
pt | 2 | -2.24 | 0.94 | 4 | -1.66 | 1.00 |
et | 1 | -1.49 | 1.00 | 4 | -1.24 | 1.00 |
st | 1 | -1.30 | 1.00 | 4 | -1.18 | 1.00 |
Romania | ||||||
mtf | 1 | 2.29 | 1.00 | 4 | 0.42 | 1.00 |
ct | 3 | -0.29 | 0.99 | 4 | -1.23 | 1.00 |
pt | 5 | -0.07 | 0.99 | 4 | -1.41 | 1.00 |
et | 1 | -0.27 | 1.00 | 4 | 3.67 | 1.00 |
st | 1 | -0.68 | 1.00 | 4 | -0.74 | 1.00 |
Critical Values |
1%
|
-3.50 |
5%
|
-2.89 |
10%
|
-2.58 |
The Phillips-Perron test for Hungarian inflation suggests it is I(0), although the ADF test suggests inflation is I(1). Because the Phillips-Perron test is more robust to different choices of lag length, it would normally govern. Monte Carlo evidence, however, shows that for all the variables tested, the small-sample distribution of both test statistics is shifted to the left, providing a bias toward rejecting the null hypothesis of an I(1) process. When the Phillips-Perron test for Hungarian inflation is evaluated in the light of its small-sample distribution, the test is well within the region of acceptance of the null hypothesis of I(1).
Monte Carlo Simulations
Asymptotic distribution theory often gives very misleading indications,
so a Monte Carlo experiment was performed to examine small-sample properties
of the test statistics for unit roots (ADF and Phillips-Perron (1988) statistics)
and cointegration (Johansen maximum eigenvalue and Trace test statistics).
One thousand bootstrap Monte Carlo iterations were seeded with 90210573,
using the empirical distribution of the actual data to simulate all variables
for each of the four countries. The bootstrap procedure is free of
any assumptions about the data generating process. In the bootstrap
procedure, observations are randomly drawn with replacement, from the sample
of actual observations. Because observations are drawn with replacement,
there is no limit to the number of iterations that can be performed.
In each iteration, ADF and Phillips-Perron statistics were calculated
and compared to the statistics calculated from the actual data. Following
Godfrey and Pesaran (1983), the percent of simulated test statistics more
extreme than the actual test statistic approximates the small-sample marginal
significance level of the actual. This approximation approaches the
true small-sample marginal significance level asymptotically.
The ADF and Phillips-Perron tests are negative one-tailed tests
with non-standard distributions; the percent simulated test statistics
smaller than the actual are reported as the small-sample marginal significance
levels in table 1. The Johansen maximum eigenvalue and Trace tests
are positive one-tailed tests with asymptotic distributions described by
Johansen (1989) and Osterwald-Lenum (1992).
Long-run estimates
Based on the derivation of the foreign money demand function
in Section 2, we assume the following exponential specification:
Country (lags) | r | Trace (LR)* | 5% crit. val. | c2 |
Bulgaria (2) | #4 | 0.695 | 3.76 | 35.63 |
#3 | 9.789 | 15.41 | ||
#2 | 28.47 | 29.68 | ||
#1 | 59.09 | 47.21 | ||
=0 | 117.1 | 68.52 | ||
Hungary (4) | #4 | 0.082 | 3.76 | 144.12 |
#3 | 12.39 | 15.41 | ||
#2 | 27.65 | 29.68 | ||
#1 | 65.18 | 47.21 | ||
=0 | 127.21 | 68.52 | ||
Poland (2) | #4 | 4.146 | 3.76 | 11.72 |
#3 | 17.86 | 15.41 | ||
#2 | 43.79 | 29.68 | ||
#1 | 94.40 | 47.21 | ||
=0 | 162.94 | 68.52 | ||
Romania (4) | #4 | 5.66 | 3.76 | 156.58 |
#3 | 15.24 | 15.41 | ||
#2 | 70.79 | 29.68 | ||
#1 | 141.00 | 47.21 | ||
=0 | 290.22 | 68.52 |
A Monte Carlo simulation with limited iterations indicated the
Johansen procedure has superlative small-sample properties as a test for
cointegration, and also has the desirable property of being extremely sensitive
in distinguishing between cointegration among stationary variables and
cointegration among non-stationary variables, a virtue not shared by either
the augmented Engle-Granger or Kremers tests.
Finally, Table 2 presents chi-square tests of restrictions on
the ß matrix. The restriction tested is that the shortage
elasticities in each cointegrating vector are jointly equal to zero.
If the null hypothesis is accepted, shortage may be deleted from the system,
and contributes no explanatory power. The null is clearly rejected
for all countries.
Table 3 gives estimates of the foreign-money-demand elasticities
and consumption functions for the four countries. Because at
least two cointegrating vectors were found for each country, the convention
was adopted of reporting two vectors with the first normalized with respect
to foreign-money-demand and the second with respect to real consumption
spending. Although the normalizations are arbitrary, it is convenient
to interpret them as a demand function for foreign currency, and a consumption
function.
Country | equation | constant | inflation | shortage | exchange rate |
Bulgaria | mf | 6.273 | 0.160 (0.128) | -0.392 (0.142)* | 1.087 (0.161)* |
consumption | 8.362 | -0.176 (0.030)* | -0.422 (0.034)* | 0.547 (0.038)* | |
Hungary | mf | -8.974 | -2.361 (1.59) | -4.636 (0.076)* | 3.759 (0.165)* |
consumption | 5.657 | -1.105 (0.522)* | 0.159 (0.025)* | 0.030 (0.054) | |
Poland | mf | 1.859 | -0.00326 (0.0011)* | -0.897 (0.368)* | 1.085 (0.132)* |
consumption | -2.032 | -0.00052 (0.0011)* | 0.218 (0.367) | 1.375 (0.131)* | |
Romania | mf | -8.547 | 1.219 (2.375) | -1.918 (0.286)* | 2.350 (0.334)* |
consumption | 5.873 | -3.416 (0.686)* | -0.755 (0.083)* | 0.765 (0.097)* |
The consumption functions have negative coefficients for inflation,
and positive coefficients for the exchange rate. Inflation coefficients
are statistically significant at conventional levels, except for Poland.
Exchange rate elasticities of consumption are significant except for Hungary.
An increase in the exchange rate indicates a decrease in the value of the
domestic currency unit against the dollar. Negative coefficients
for inflation and exchange rates in the consumption function reflect the
fact that consumption and income, expressed in real terms, fall as the
value of the domestic currency unit falls. Since the scope for black-market
consumption in Bulgaria and Romania was small, official sector consumption
should be interpreted as a proxy for income rather than actual consumption.
Foreign money predominated as a store of value in these economies rather
than a black-market means of payment. This is exactly what would
be expected for countries with less-well-developed black markets.
Hungary and Poland had better-developed black markets early on.
The shortage coefficients in the consumption functions are negative
and significant for Bulgaria and Romania, which indicates as official sector
shortage increased in severity, household consumption fell. In contrast,
consumption elasticities with respect to shortage are positive and significant
for Hungary and positive but not significant for Poland, indicating official
sector shortage brought about increased consumption spending. This
result could only have occurred with well developed, and highly active
black markets, which were in fact operating in these economies well before
the collapse of central planning.
Inflation coefficients in the consumption functions should be
unambiguously negative and significant because domestic inflation makes
foreign money a better store of value, shifting consumption out of the
official sector, and this is observed for all four countries.
In the foreign money demand functions, the inflation coefficients
are positive but not significant for Bulgaria and Romania, but negative
and not significant for Hungary and negative and significant Poland.
Again, this reflects the different roles played by foreign currency holdings
in transition economies with and without highly developed black markets.
In Bulgaria and Romania, where black markets were not well developed, foreign
currency played predominantly a store-of-value role, and foreign currency
holdings rose with high inflation. In Hungary and Poland, with their
highly-developed black markets, the transactions motive apparently predominated,
and in response to inflation, households ran down their foreign currency
balances in an effort to maintain steady consumption patterns. This
effect is seen most clearly in Poland, where the inflation coefficient
is negative and significant. Poland had the best-functioning black
markets, and therefore the greatest scope for increased black-market transactions
in response to high inflation, running down dollar balances held by Polish
households.
Shortage elasticities of foreign money demand are negative and
significant for all countries. This indicates that as shortage became
more severe, households shifted consumption to the black market, running
down foreign currency balances.
The black-market exchange-rate elasticity of foreign money demand
is positive and significant for all countries. As with inflation,
whenever domestic currency depreciates vis-à-vis foreign currency,
people tend to substitute domestic money for foreign money. As the
black-market exchange-rate rose, foreign money became a better store of
value. Bias might be expected due to collinearity between inflation
and the black-market exchange rate, but they were found to have very low
correlation coefficients. In addition, as the exchange rate rose, foreign
currency deposits expressed in terms of domestic currency went up even
if the amount of foreign currency on deposit was constant, for obvious
reasons.
5. Summary and Conclusion
This paper examined currency substitution in four transition
economies, Bulgaria, Hungary, Poland, and Romania, for 1986 to 1994.
Following liberalization of these economies in the beginning of the 1990s,
currency substitution became an important phenomenon. In most transition
economies, currency substitution seems strongly correlated with high inflation
and macroeconomic uncertainty.
A formal choice-theoretic two-currency shortage-augmented cash-in-advance
model was derived to account for both the period of central planning and
liberalization of the economies. Empirical estimates of the derived
foreign-currency demand and consumption functions were performed by the
Johansen procedure. Results showed foreign currency deposits are
explained very well by domestic official consumption, inflation, the black
market exchange rate, and shortage. The shortage variable, which
could be interpreted as a permanent dummy for regime-shifts, was highly
significant in explaining demand for foreign currency in all countries.
Recognizing the importance of the black market and currency substitution
shows formal choice-theoretic modeling extremely powerful for analyzing
money demand in these economies.
The high degree of currency substitution has unambiguously negative
effects for both fiscal and monetary policy in the transition economies.
First, currency substition reduces the scope for raising revenue through
an inflation tax. This implies that inflation will be higher, given
a certain fiscal deficit. Second, the high degree of currency substitution
complicates monetary stabilization, one of the prerequisites for a successful
transition to a market economy. Third, very small changes in exchange-rate
expectations might trigger large exchange-rate movements, due to substitution
back and forth. This further undermines the possibilities for monetary
stabilization and use of the exchange rate as an anchor in the transition
process. Therefore, monetary authorities should attempt to reduce
the degree of currency substitution in transition economies.
Currency substitution tends to bring about higher rates of both
depreciation of the domestic currency and inflation, than a transition
economy would experience in its absence of currency substitution.
Currency substitution is self-enforcing because higher depreciation and
inflation rates both contribute to even greater demand for foreign currency.
Taking into account its self-enforcing character, currency substitution
can be extremely harmful to macroeconomic liberalization and stabilization
programmes of the economies in transition.
Data appendix
All data sources used are official statistical publications of the four
countries, the International Financial Statistics (IMF), Short-term Economic
Indicators Central and Eastern Europe (OECD), and World Currency Yearbook
(International Currency Analysis Inc, New York). The latter publication
has been used for black-market exchange rates. Most data on Bulgaria, Hungary,
and Romania, were kindly provided by Bas van Aarle (see Aarle and Budina,
1995). Where data were lacking, we supplemented his data set to create
a homogenous data set for Bulgaria, Hungary, Poland and Romania for the
period 1986.1 to 1994.1 (for Poland we extended the data set to 1994.2).
The data on Poland were collected at the Money and Research Institute of
the National Bank of Poland. The specific data sources are printed under
each series.
Bulgaria- Units: Billion Leva; Sources: Aarle and Budina
(1995) (BNB, except et (black market exchange rate) from World Currency
Yearbook and ct (official-sector consumption) from OECD.)
Hungary- Units: Billion Forints; Sources: Aarle and Budina
(1995) (IMF, NBH, except et (black market exchange rate) from World
Currency Yearbook and ct (official-sector consumption from OECD.)
Poland- Units: Billion Zlotys; Source: Nijsse and
Sterken (1995), ct (official-sector consumption) from OECD.)
Romania- Units: Billion Leu; Source: Aarle and Budina
(1995) (IMF, NBR, except et (black-market exchange rate) from World Currency
Yearbook, and ct (official-sector consumption) from OECD.
Tables of the data are provided in Mulligan and Nijsse, 1995.
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