DEDOLLARIZATION IN TURKEY AFTER DECADES OF
DOLLARIZATION:
A MYTH OR REALITY?
Kıvılcım METİN-ÖZCAN*
*
Vuslat US**
Bilkent University, Department of Economics.
Phone: +90 (312) 290 2006, fax: +90 (312) 266 5140, e-mail: kivilcim@bilkent.edu.tr
**
Corresponding author, Central Bank of the Republic of Turkey, Research and Monetary Policy
Department.
Phone: +90 (312) 310 9238, fax: +90 (312) 324 2303, e-mail: vuslat.us@tcmb.gov.tr
The views expressed herein do not reflect the views of the affiliated institutions. The authors would
like to thank Pınar Özlü for very stimulating and useful suggestions as well as help with the data. Usual
caveats apply regarding the errors and omissions.
I. INTRODUCTION
Dollarization- replacement of domestic currency by a dominant foreign
currency - is an increasingly defining feature of many emerging market economies
(EMs). Even though foreign currency is generally chosen to be USD, dollarization is
a generic term where DM or Euro may well serve to the purpose of replacing the local
currency.
Dollarization has been analyzed extensively in the previous literature. The
earlier works on dollarization demonstrate that dollarization occurs as a result of
various factors depending on the structure of the economy. In developed economies,
like USA and Canada, dollarization is seen as a counterpart to heavy cross-border
trade whereas in Latin American countries, dollarization is usually perceived as a
hedging strategy against high inflation.
There are now several studies on the issue of dollarization in the Turkish
economy.1 While some of these studies focus on analyzing the determinants of
dollarization (Akçay et al., 1997; Selçuk, 1994, 1997; Civcir, 2002, 2003); others
inquire about the hysteresis nature of dollarization (ratchet effect), i.e. whether
dollarization ratios have reached an irreversible stage or not (Us, 2003a; Us and
Metin-Özcan, 2005). In view of the ample evidence that infer the irreversibility of
dollarization due to heavy switching costs, it is thus concluded that dollarization ratios
might not decline even after local currency is successfully stabilized. Yet, these
studies, which analyze the ratchet effect on dollarization in the Turkish case, confer
that, despite high dollarization rate in the Turkish economy, there is still a room for
the monetary policy to be effective.
Another line of research on dollarization issue in Turkey shows that
dollarization reduces the seigniorage and results in higher and more volatile inflation
than which is otherwise implied for a given level of budget deficit (Bahmani-Oskooee
and Domaç, 2003; Selçuk, 2001, 2003). Consequently, the decline in seigniorage that
occurs as the public switches from domestic to foreign money holdings is partially
compensated through increases in administered prices, which are translated into
higher inflation.
1
Inspired by the press releases2 of Central Bank of Turkey (CBRT) declaring
conditions of so-called reverse currency substitution3 that justify the enormous
reserve build-up despite conducting free float, the recent trend in studying
dollarization issue in the Turkish economy has now shifted towards analyzing
dedollarization- a reversal in dollarization trend. Coincidentally, dedollarization is
also in the agenda of other researchers around the globe. Apparently, dedollarization
is perceived as an endogenous outcome of a persistent process of disinflation and
stabilization (Galindo and Leiderman, 2005). Furthermore, seminal works such as Ize
and Levy-Yeyati (1998, 2003), Levy-Yeyati (2003a) and others that follow such as
Barajas and Morales (2003), Morón and Castro (2003) and Ize (2005) point out the
need for designing policies to fight actively against dollarization thus finding a way
out to dedollarization.
Initial attempts to study dedollarization in Turkey by Yılmaz (2005) and
Akıncı and Görmez (2005) bring alternative definitions to dollarization, the former
concentrating on financial dollarization whereas the latter focusing on asset
dollarization. Yet, these studies leave a gap for further research by not presenting
enough evidence on the existence of dedollarization and by not analyzing the
dedollarization from various aspects. More specifically, while the previous literature
on dollarization has focused on asset dollarization as measured by the ratio of foreign
denominated assets to broad money, the recent dollarization literature has mostly
concentrated on dollarization of liabilities.
1
For detailed information on the previous studies on dollarization in the Turkish economy, Us (2003b)
provides an extensive survey.
2
CBRT press release no 2004-32 states that conditions of reverse currency substitution warranted
foreign exchange intervention on May 11, 2004. Likewise, CBRT press release no. 2002-91 also stated
the same condition on account for foreign exchange intervention on December 2, 2002. Finally, CBRT
press release no 2003-26, dated May 5, 2003 clearly explains the conditions of reverse currency
substitution that mitigates for foreign exchange buying auctions.
3
“Reverse currency substitution” terminology was heavily used by CBRT officials in view of the
decline in foreign currency denominated assets with respect to M2Y. However, the term is obviously a
misnomer. Currency substitution is the situation where foreign currency replaces domestic currency at
various extents. However, by naming currency substitution as “reverse” it then implies the replacement
of foreign currency by domestic currency, which on the other hand does not call for a new terminology.
Instead, a more appropriate term would have been “reversal in the currency substitution” or “reversed”
currency substitution in order to describe the situation where people switch their money holding
preferences towards domestic money from foreign money. As it happens, reverse currency substitution
term was not used widely in the literature, but instead, “Dedollarization” was prevalently preferred
thanks to the prefix, the ambiguity was resolved.
2
Owing to the recent crisis track in Russia, East Asia, Argentina and Turkey,
liability dollarization came to be noticed after increased attention in analyzing
vulnerabilities faced by EMs. On contrary, being an emerging market itself with a
long history of crisis, Turkey has so far not been under scrutiny for analyzing the
issue of liability dollarization. Moreover, the hot debate over the existence of
dedollarization measured in terms of asset dollarization needs more light to be shed
on. Hence, a thorough analysis linking asset dollarization and liability dollarization
within an econometric framework is absolutely vital before going any further on
concluding that dollarization changed its route to dedollarization while going even
beyond as to prescribe policy advice accordingly.
In so doing, the paper will now proceed by going over some definitions of
dollarization. Consequently, the following section will provide a survey on
dollarization mostly emphasizing the recent trend of studying dollarization vis-à-vis
dedollarization, simultaneously mentioning about the normative view about why
countries should find strategies to dedollarize. In the next section, evolution of
dollarization in Turkey will be discussed. The following section will present empirical
evidence on dollarization versus dedollarization debate. Finally, the last section will
conclude this paper.
II. DEFINITIONS OF DOLLARIZATION
There are various definitions for specifying the type of dollarization since
dollarization is a very general concept that represents the substitution of domestic
money by a foreign currency without clarifying what type of money is essentially
being replaced. Earlier studies in the dollarization literature are mostly on currency
substitution, which has various definitions and some of these definitions vaguely
define the degree at which this substitution takes place. To give an example, Mizen
and Pentecost (1996) define currency substitution simply as the substitution between
two moneys. Fortunately, Cuddington (1983), and Calvo and Végh (1992), by
rendering a more precise definition, describe the term currency substitution to denote
the use of different currencies as a medium of exchange. For the transfer between
domestic and foreign interest-bearing assets on the other hand, the authors prefer to
use “capital mobility”. Alternative definitions to currency substitution exist such as
the “replacement of domestic currency in its traditional roles by foreign currencies”
3
by Selçuk (1994) or another definition as “the use of a stable foreign currency for
transactions” by Sturzenegger (1997).
The term “dollarization” has commonly been used to describe currency
substitution in the Latin American context. Yet, Calvo and Végh (1992) distinguished
between dollarization and currency substitution by using the former to imply the use
of foreign currency as a unit of account or as a store of value whereas the latter is the
use of foreign currency as a medium of exchange. Hence, theoretically, currency
substitution is the end stage of dollarization.
However, as dollarization often occurs for store of value purposes, it can
readily be observed as an increase in foreign currency denominated deposits. This
form of dollarization also called asset substitution or asset dollarization is a moreeasily-quantifiable measure of dollarization. On the other hand, currency substitution
is difficult to measure given the problems with obtaining reliable data on foreign
currency in circulation.
Previous studies on dollarization, however generally concentrated on
measuring the extent of currency substitution, proxying the size of foreign currency in
circulation by the ratio of foreign currency denominated deposits to a monetary
aggregate which in many instances has been broad money, M2Y. This commonly
used measure of currency substitution was supposed to imply a lower band for
dollarization. In other words, if residents are holding a portion of their wealth in
foreign currency denominated bank accounts, an unrecorded/unmeasurable portion,
which may be used for transaction purposes or “under the mattress” still exists. Thus,
measuring currency substitution in practice reduces to finding a proxy for asset
substitution.
After the Asia crises in 1998, the term dollarization has started to be used in
the context of countries that consider the use of a foreign currency by totally
abandoning their own national currencies (Calvo, 2001, 2002a; Edwards, 2001). Yet,
while a strand of literature has developed perceiving dollarization as such, another
strand used the term “full” dollarization in order to distinguish between dollarization
at various degrees from “officially” abandoning the domestic currency (Berg and
Borenzstein, 2000). Apparently, other authors used the term “official” or “de jure”
dollarization in order to imply “full” dollarization. Trivially, “unofficial”, “de facto”
4
or ”informal” dollarization implied not “full” dollarization (Savastano, 1992). For still
some others, dollarization already meant “full” dollarization where not “full”
dollarization was called “partial” dollarization.4
Yet another term was introduced in the dollarization literature that
distinguishes dollarization of assets from dollarization of liabilities. “Liability (loan,
credit) dollarization” therefore implies the share of liabilities that are denominated in
foreign exchange. Similarly, another distinction was made as “deposit dollarization”
in order to decompose asset dollarization into measurable part-deposits and
unmeasurable part-currency. In line with the term “liability dollarization”, still
another term came as “financial dollarization” or “dollarization of financial
intermediation” to denote the dollarized portion of all assets and liabilities in the
financial system of the domestic economy (Ize and Levy-Yeyati, 1998). A
corresponding definition is “real dollarization” that shows the extent to which prices
and wages are denominated in foreign currency while some others define real
dollarization as the degree of pass-through from exchange rate to prices.
These above arguments that put forward various definitions of dollarization
clearly demonstrate that controversies exist on how to approach the issue of
dollarization and which way to proceed. The next section will thus serve to the
purpose of showing how literature on dollarization has evolved in line with different
definitions of dollarization.
III.
A
SURVEY
ON
DOLLARIZATION
EN
ROUTE
TO
DEDOLLARIZATION
As the discussion of the previous section evidently presents, the distinction
among various definitions of dollarization might not be quite trivial. Even if the
distinction is clear however, their implications may be entirely different. As a matter
of fact, in a typically dollarized economy, dollarization (or currency substitution)
traditionally had implications about the stability of money by causing the monetary
policy to be less effective and more complex (Reinhart et al., 2003). In other words,
dollarization was considered to be an obstacle that challenged the pursuit of a
4
Schuler (2000) provides a detailed analysis on various terminologies in the dollarization literature.
Throughout this text, however, dollarization will be used to denote the use of foreign currency either in
5
coherent and independent monetary policy.5 The importance of measuring the degree
of dollarization thus has been mostly related to its implications regarding the conduct
of monetary policy as well as the choice of exchange rate regime. Hence, like any
definition for monetary aggregates, currency substitution occurred at a narrow to
broader level thus inferring weaker to stronger implications about the stability of
money.
Measuring currency substitution through the use of data on foreign currency
deposits however, often resulted in overlooking the implications of dollarization for
financial intermediation. Yet, the fact that foreign currency denominated deposits has
a mirror image that of liabilities is important to determine the characteristics and the
degree of dollarization. More specifically, the extent of liability dollarization
determines the credit risk faced by the financial system in the outcome of large
devaluations. Therefore, while dollarization is presumably believed to restrict the
scope for independent monetary and exchange rate policy, liability dollarization is
assumed to stress the role that foreign currency borrowing has vis-à-vis the
vulnerability of EMs to external shocks (Calvo, 2002a; Caballero and Krishnamurthy,
2000).
Reinhart et al. (2003) made the first attempt to introduce of a new measure of
dollarization that encompasses both asset and liability dollarization. The authors
based on this new measure which is composite index for dollarization also showed
that little empirical evidence exists for the supposed ineffectiveness of monetary
policy in dollarized economies. In other words, they showed that dollarization would
slightly hinder the effectiveness of monetary policy by making inflation higher and
more volatile. Yet, no evidence was observed suggesting that dollarization would
make it more difficult to bring down inflation or that it would change the complexity
of the monetary transmission. Furthermore, the seigniorage revenues or output
fluctuations were also found to be quite similar across countries with different degrees
the form of any asset or in the form of any liability where domestic currency still serves as the legal
tender.
5
This paper rather than presenting a comprehensive survey on currency substitution prefers to provide
a more modern view by giving a perspective on how studies on currency substitution evolved over time
to cover dollarization and consequently dedollarization issues. Yet, seminal works on currency
substitution should not be overlooked. These works include Miles (1978), Bordo and Choudri (1982),
Girton and Roper (1981), Ortiz (1983), Canzoneri and Diba (1992), Thomas (1985), Artis (1996),
Giovannini (1991), Giovannini and Turtelboom (1994), Guidotti (1993), Krueger and Ha (1995),
McKinnon (1982, 1985), Calvo and Végh (1992, 1996).
6
of dollarization. However, the authors found systematic differences in pass-through
from exchange rates to prices depending on the dollarization extent. Finally, the study
concluded that there was little evidence in support for successful dedollarization
attempts (namely in Israel and in Poland) where no heavy costs were incurred in
achieving large and lasting decline in dollarization.
Another attempt to inquire about the varieties of dollarization was flourished
as financial dollarization, which denoted the holdings by residents of foreign currency
denominated asset and liabilities (Levy-Yeyati, 2003b). This description implied that
the currency composition of residents and non-residents should differ with the former
more prone to invest in local currency assets than the latter. Hence, this view was
centered on the inability of some countries to develop deep local currency markets.
Moreover, the definition underlined the difference with the concept of “original sin”
which denotes the inability of a country to borrow abroad in its own currency.
Original sin is clearly a synonym for liability dollarization of governments.
The concept of “original sin” was developed after “balance sheet” approaches
to currency crises following the financial crises of the 1990s which led a number of
commentators to express the view that these crises were of a new kind, reflecting
fragility in the balance sheet of firms, banks and governments rather than current
account imbalances (Dornbusch, 1998; Krugman, 1999, 2002; Pettis, 2001; Allen et
al., 2002; Calvo, 2002b). Some of these views have centered on the idea that the
international community should take a new approach- balance sheet approach- to
understand the international financial crises (Jeanne and Zettelmeyer, 2002).
One source of balance sheet fragility that is often emphasized is foreign
currency debt. The reason why foreign currency debt is the original sin is that it is the
source of so many other problems as stated in the influential work by Eichengreen and
Hausmann (1999). This work was later followed by Eichengreen et al., (2005a,
2005b), Eichengreen and Hausmann (2005). These studies discuss the idea that
international financial integration, as opposed to stimulating growth in the developing
world by channeling scarce capital to deserving economies and facilitating
international risk sharing, instead has been an engine of instability leaving original sin
at the center of these problems. Original sin leads to less currency flexibility, thus
7
fear-of-float,6 more volatile and pro-cyclical interest rates and wider output
fluctuations. Furthermore, in countries with original sin, capital flows are more
volatile and prone to reversal, thus sudden-stops.7 Yet, these countries with original
sin have lower credit ratings and therefore have even less access to international
capital markets.
In view of these handicaps of dollarization, and due to fear-of-float, another
line of research concentrated on the choice of right exchange rate regimes that would
insulate an economy from financial crises. In view of the evidence against fixed or
”pegged” exchange rate regimes that led to financial crises in Mexico at the end of
1994; Thailand, Indonesia, and Korea in 1997; Russia and Brazil in 1998; Argentina
and Turkey in 2000 and 2001, and the fact that emerging market countries without
pegged rates including South Africa, Israel, Mexico, and Turkey have been able to
avoid such crises in 1998. Hence, during the past decade, many countries have
changed their exchange rate regimes, moving from crisis-prone “soft pegs”conventional pegs at adjustable rates- to either “hard pegs”- unconventional pegs with
a commitment to never to change the par value8- or floating regimes. The belief that
intermediate regimes between hard pegs and free float are unsustainable is known as
the “bipolar” view, or two-corner solution (Fischer, 2001).
The bipolar view led to another line of research that concentrated on the
proposal that EMs should completely give up their currencies and adopt an advanced
nation’s currency as legal tender (Berg and Borenzstein, 2000; Calvo, 2002a). This
proposal labeled as “official dollarization”9, which is a form10 of hard peg, was
6
Calvo and Reinhart (2002) argue that due to liability dollarization, EMs avoid free float; thus, these
countries are subject to “fear of floating”.
7
Calvo and Reinhart (2000) discuss that EMs are exposed to sudden capital reversals, which is named
as “sudden stops”.
8
A formal definition of hard peg may be provided as “a pegged exchange rate with a credible
commitment never to change the par value, thus subordinating monetary policy to the needs of the
exchange market and denying access to devaluation as a policy tool”. This definition is borrowed from
Alan V. Deardorff, Professor of International Economics at the University of Michigan Ann Arbor,
who supplies an extensive international economics glossary, which is available at
www.personal.umich.edu/~alandear/glossary/h.html.
9
As the discussion of the previous section clearly outlines, the term dollarization is used in the context
of “official” dollarization by some researchers.
10
Another form of a hard peg is a currency board where management of both the exchange rate and the
money supply are taken away from the central bank and given to an agency with instructions to back
every unit of circulating domestic currency with a specified amount of foreign currency. Examples of
hard pegs in practice are Gold Standard, European Monetary Union, Ecuador’s dollarization,
Argentina’s convertibility and the real plan in Brazil (Jameson, 2003).
8
presented as the ultimate way for achieving credibility, growth and prosperity such
that countries that render their currencies would be not be exposed to
macroeoconomic mismanagement.
Even though official dollarization eliminates all scope for an independent
monetary policy and also limits the capacity of the domestic monetary authorities to
provide the lender-of-last-resort services, it would eliminate the currency and maturity
mismatches that are particular threats to financial stability. Hence, official
dollarization is likely to increase country’s access to international capital markets at
more favorable terms thus decreasing both the level and the volatility of the interest
rates (Eichengreen and Hausmann, 1999). Thus, official dollarization would therefore
imply higher investment and superior economic performance (Dornbusch, 2001;
Alesina and Barro, 2001).
As opposed to the arguments for official dollarization by the descendents of
the view that dollarization would impede the effectiveness of the monetary policy,
another view has emerged promoting dedollarization- the reversal in dollarization.
On the grounds that in as much as dollarization influences the pricing behavior of
firms and individuals, the dollarized economies are induced to limit wide fluctuations
in the nominal exchange rate due to its adverse effects on inflation (Chang and
Velasco; 1998, 1999).
Even though some dollarization may be warranted as a hedging strategy
against exchange rate risk, widespread dollarization exposes the country to currency
imbalances, also leading to volatility in the real exchange rate and adverse wealth
effects. These adverse wealth effects consequently limit the effectiveness of monetary
policy (Aghion et al., 2001; Céspedes et al., 2004). On account of this limited
effectiveness of monetary policy due to dollarization, monetary authorities are less
willing to let the exchange rate respond, more willing to increase reserves and
aggressively intervene in the foreign exchange market or adjust short-term interest
rates (Haussmann et al.2001). Volatile interest rates increase the uncertainty and thus
the default risk by also lowering credit ratings. Dollarization consequently leads to
decreased economic stability, more volatile capital flows and more costly borrowing
(Eichengreen et al., 2005a).
9
Due to the abovementioned arguments against dollarization, there is a growing
consensus that a proactive stance should be adopted against dollarization and that the
passive stance, (learning-to-live-with-it) type of approach should now be discarded.
Hence, the new strategy should be built in order to limit the incentives that favor
dollarization and to foster the developments of local currency intermediation (LevyYeyati, 2003b).
However, before fighting against dollarization, another line of research has
focused on its persistence. Persistence in dollarization (hysteresis, ratchet effects and
dollarization traps) was analyzed deeply in the literature. The main findings show that
dollarization is persistent due to long-lasting memories of inflation (Savastano, 1996).
Another reason for persistence in dollarization would be the use of foreign currency
as a unit of account in economies with high nominal instability (Guidotti and
Rodriguez, 1992). Dollarization may also be persistent due to portfolio considerations
that justify dollarization for hedging purposes (Thomas, 1985; Ize and Levy-Yeyati,
2003). Another reason for the persistence in dollarization would be the timeinconsistency problem of a dollar-indebted government to repudiate its debt ex-post
through devaluation and inflation (Calvo and Guidotti, 1989).
Persistence in dollarization may also be attributed to the existence of currencyblind regulations that may introduce market distortions. More specifically, financial
safety nets such as deposit insurance or lender or last-resort policy (Broda and LevyYeyati, 2003), implicit debtor guarantees derived from the social and political costs of
massive bankruptcies (Burnside et al., 2001) and finally currency-blind financial
regulations as a result of a signaling problem (De la Torre et al., 2002) often result in
persistence in dollarization. Finally, dollarization may show patterns of persistence
merely due to habit formation due to heavy switching costs (Guidotti ad Rodriguez,
1992). Furthermore, monetary authorities may be impelled to launch foreign currency
deposit accounts to limit capital flight and to prevent bank runs induced by changes in
the currency composition of local portfolios during inflationary episodes (LevyYeyati, 2003b)
The pro-active measures to combat dollarization and hence its persistence is
proposed by Levy-Yeyati (2003a). The author suggests that any potential scheme for
dedollarization should entail a reward and punishment mechanism, carrot-and-stick-
10
approach, increasing the cost of dollar intermediation while expanding the menu of
local currency instruments and enhancing their attractiveness. Thus, the author
proposes a two-tail approach where on one hand, prudential regulation should be
revised to address ex-ante the externalities associated with financial dollarization
where the revision should be phased in equally. The author also adds that any
successful dedollarization strategy should be accompanied by sound monetary
policies as in Chile and in Israel. Furthermore, the other examples of dedollarization
attempts, namely Argentina, Peru and Uruguay demonstrate that not only sound
policies but also a proactive agenda with specific measures aimed at justifying the
presence of externalities and enhancing the attractiveness of local currency assets is
needed to complement conducive macro policies.
In line with the arguments set for taking initiatives towards dedollarization,
Morón and Castro (2003) discuss the experience of Peru. The authors remind that the
detrimental effects of financial dollarization are mostly experienced through balance
sheet effects which amplify the impact of adverse external shocks on real variables.
Hence, they search for drivers in dollarization, more specifically, the relation between
deposit dollarization and loan dollarization. The empirical results suggest that the
causality runs from deposit to loan dollarization, which is in accordance with the
intuition, that supply considerations dominate if banks are to keep their balance sheets
matched. However, a regulatory framework that is based on encouraging depositors
towards the use of local currency denominated assets may also lead to capital flight.
On the other hand, policy recipes in the form of reducing relative volatility of
inflation to real depreciation should help discourage depositors to switch to local
currency assets. Thus, an inflation targeting scheme is recommended as a useful
strategy to combat with dollarization.
The experience of Uruguay in dedollarization is discussed in Licandro and
Licandro (2003) where the authors propose a policy approach based on two
foundations: development of markets in national currency to generate a credible
alternative to foreign currency and strengthening of the safety net through the
regulatory recognition of non-marketable risks. The study underlines the fact that a
cooperative action among agencies, which in the case of Uruguay are bank regulator,
the pension funds regulator, the insurance companies regulator and the stock market
regulator in addition to the central bank, is essential.
11
Finally, in another paper by Herrera and Valdés (2004), the dedollarization
experience of Chile is discussed. As stated by the authors, even though Chilean
experience with dedollarization is a success, it cannot be generalized to other
countries since many policies that Chile pursued cannot be easily implemented
elsewhere. More specifically, some key characteristics of the Chilean dedollarization
process have been mostly related to its initial institutional conditions and
developments, and some others are connected to specific regulations inherent in
Chile. Yet, it should also be underlined that dedollarization in Chile has been a
success due to prudent fiscal policy, private and fully-funded pension system and
strict capital controls.
IV. EMPIRICAL ANALYSIS
In this section of our analysis, we will proceed by formally testing the traces
of dollarization versus dedollarization. In so doing, we will attempt to distinguish
between demand and supply considerations in a dollarized economy. An empirical
evaluation of this kind can be found in Barajas and Morales (2003) as well as Morón
and Castro (2003). These authors find that deposit dollarization is the source of loan
dollarization. More specifically, if banks are to keep their balance sheet matched,
deposit and loan correlation should not only exhibit a high correlation but also the
former should cause the latter.
In the spirit of the above studies, we will proceed by a co-integration analysis
to search for a relation between various sources of dollarization. More specifically, we
would like to see whether a long-run relation between asset dollarization and liability
dollarization exists. Thus, this study seeks to find out the relation between the
dollarized assets and liabilities of the non-banking sector. Similarly, we also search
for a long-run relation between dollarized assets and liabilities of the banking sector
vis-à-vis the liability dollarization of the non-banking sector. Finally, we would like to
see how all of them are related to each other simultaneously.
As discussed in Reinhart et al. (2003), foreign currency denominated deposits
constitute the dollarized portion of households’ and firm’s assets. Yet, the same
deposits are dollarized liabilities of banks. Furthermore, both households and firms
borrow from domestic banks in foreign currency. Hence, these foreign currency
denominated loans form the dollarized liabilities of households and firms, while, the
12
same loans are in the meantime the dollarized assets of the banking sector. Finally,
banks also borrow from abroad in addition to holding assets abroad.
In light of this information, we searched for appropriate variables to denote
asset and liability dollarization of the non-banking sector as well as the banking
sector.11 In order to measure the asset dollarization of the non-banking sector, we used
the ratio of foreign currency denominated assets to broad money, M2Y. The liability
dollarization of the non-banking sector is represented by the ratio of foreign currency
denominated loans to total loans. To measure the dollarization of liabilities and assets
of the banking sector, we used the ratio of the loans borrowed by the banking sector
from abroad to the assets of the banking sector held in foreign banks.
Apparently, the measure of asset dollarization of the non-banking sector used
in the empirical analysis excludes foreign currency holdings as well as foreign
currency linked government debt and foreign currency assets held abroad.
Furthermore, the measure of liability dollarization of the non-banking sector excludes
the external borrowings. The measure of the dollarized portion of assets of the
banking sector ignores the foreign currency loans and the measure of the dollarized
portion of liabilities of the banking sector ignores the foreign currency denominated
deposits of the non-banking sector as the inclusion of these variables constitute
misspecification problems in econometric testing.
Our data cover the period from 1996:06 to 2005:08. The asset dollarization of
the non-banking sector is represented as the logarithm of the ratio of foreign currency
denominated deposits to M2Y. The liability dollarization of the non-banking sector is
represented by the logarithm of the ratio of foreign currency denominated loans to
total loans. For the banking sector, we calculated the logarithm of the ratio of the
borrowings of banks from abroad to banks’ assets held in foreign banks. All data
sources are publicly available through CBRT electronic data dissemination system
(http://tcmbf40.tcmb.gov.tr/cbt.html). The graphical presentation of the data before
taking logarithms can be found in the Appendix.
11
Reinhart et al. (2003) clearly depicts the balance sheet of a partially dollarized economy covering
also the government as well as the central bank. This study falls short of analyzing the dollarization of
the public sector. A further research however may concentrate on original sin and also analyze the
dollarization in government debt.
13
In order to analyze the interaction between these various measures of
dollarization, we have first conducted Granger-causality tests. The results show that,
the liability dollarization of the non-banking sector Granger causes liability
dollarization of the banking sector over the period 1996-2002 whereas in the
aftermath of 2002, the evidence does not support Granger causality.
The Granger causality between asset dollarization of the non-banking sector
and the liability dollarization of the non-banking sector on the other demonstrates a
structural change before and after the crisis in February 2001. More specifically, prior
to the crisis, the test results show that asset dollarization Granger causes liability
dollarization whereas after the crisis, liability dollarization Granger causes asset
dollarization.12 Furthermore, asset dollarization of the non-banking sector Granger
causes liability dollarization of the banking sector over the whole sample.
The results indicate that foreign currency denominated loans are offered by the
banking system as long as individuals open bank accounts in foreign currency and as
the banking system offers credits in foreign currency, banks borrow from abroad. This
is another way of saying that as individuals open bank accounts in foreign currency;
banks lend in foreign currency and also borrow from abroad. This conclusion is in
line with the results obtained in Morón and Castro (2003). Thus, until the crisis, the
source of dollarization has mostly been driven by portfolio preference of the nonbanking sector towards holding foreign currency.13
However, after the crisis, the causality changed as follows: As banks offer
credits in foreign currency, individuals open foreign currency bank accounts. As
individuals open foreign currency bank accounts, banks borrow from abroad. Thus,
after the crisis the source of dollarization has changed. In other words, the
dollarization in the economy has been driven by liability dollarization of the nonbanking sector.
12
The results of Granger causality tests are available upon request.
This study does not cover an analysis on determinants of dollarization. Rather, it tries to give an idea
on where dollarization originates, i.e. either on the asset side or the liability side of the banks’ balance
sheets. However, another study on determinants of dollarization in Turkey by Metin-Ozcan and Us
(2005) provides a detailed analysis.
13
14
Our empirical analysis proceeds by testing stationarity. In order to test for the
stationarity properties of the series, we have implemented Augmented Dickey Fuller
(ADF) unit root tests. The test results suggest that all the series are I(1) (Table 1).
Table 1. Unit Root Tests
Level
Variables
AD (NBS)
LD (NBS)
LD (BS)
No intercept
Intercept
-0.696
-1.653***
0.403
-0.967
0.832
-2.960**
First-Difference
Trend and
intercept
-1.091
-0.441
-3.429**
No Intercept
Intercept
-6.778*
-9.647*
-15.239*
-6.794*
-9.843*
-15.233*
AD-Asset Dollarization
LD-Liability Dollarization
NBS-Non-Banking Sector
BS-Banking Sector
*significant at 1 percent
**significant at 5 percent
***significant at 10 percent
The results of the unit root test thus suggest that we should test for a
cointegrating relationship among the series. In particular, the Johansen test indicated
the existence of a cointegration vector of the form (after normalizing for liability
dollarization):
LD _ NBS t  3.753  0.004 * trend  1.856 * AD _ NBS t  0.215 * LD _ BS t
where:
LD_NBS = Liability dollarization of the non-banking sector
AD_NBS = Asset dollarization of the non-banking sector
LD_BS = Liability dollarization of the banking sector
We proceed by specifying a Vector Error Correction model (VECM). The
results of the VECM (Table 1 in Appendix) show that the lagged error term from the
cointegration vector is only significant in the equation for liability dollarization of the
non-banking sector. In other words, in the event of a shock that leads to a deviation in
any of the variables from their equilibrium relationship, only liability dollarization of
the non-banking sector will adjust to re-establish this equilibrium.
15
Our analysis so far has shown the dynamics of dollarization concentrating on
the varieties of dollarization. Yet, this analysis does not provide evidence for
determinants of dollarization. To that aim, we will proceed by a Vector
Autoregression (VAR) model where asset dollarization of the non-banking sector is
analyzed using variables such as output volatility, inflation volatility, exchange rate
volatility and expected depreciation. Due to high inflation for more than three decades
as well as the boom-bust cycle pattern, Turkish economy has been exposed to high
volatility as well (Ertuğrul and Selçuk, 2001). Volatility may thus lead to uncertainty
where agents may resort to foreign exchange for hedging purposes as discussed in the
earlier sections.
Volatility is usually calculated by measuring variance or coefficient of
variation. On the other hand, these calculations do not model the volatility but only
provide numerical figures. On the other hand, Autoregressive Conditional
Heteroskedasticity (ARCH) models are specifically designed to model and forecast
conditional variances. The variance of the dependent variable is modeled as a function
of past values of the dependent variable and independent, or exogenous variables.
ARCH models were introduced by Engle (1982) and generalized as GARCH
(Generalized ARCH) by Bollerslev (1986) and Taylor (1986). Thus, the volatility
measures o our analysis are calculated using Generalized Autoregressive Conditional
Heteroscedasticity (GARCH) model.
In dollarization models, it is a common practice to include expected
depreciation as an explanatory term. However, expected depreciation series can be
obtained using Expectations Survey of the CBRT, but this series is only available
after August 2001 when the survey started to be conducted. Thus, in order to measure
expected depreciation, we imposed the restriction that forward transactions of the
agents do reflect their expectations of the future, thus, we assumed that forward
exchange rate is equal to expected exchange rate. However, forward rate for USD/TL
do not exist as well. Thus, we calculated forward rate using Covered Interest Parity
condition where ft= st(1+i)/(1+i*) where ft is the forward rate for USD/TL and st is the
spot exchange rate. i shows the domestic interest rate and i*represents the foreign
interest rate. In order to calculate next month’s expected depreciation, we thus used
30-day Eurodollar rate to denote i* and 1-month time deposit rate for TL. Our data set
16
covers the period from 1990:03 to 2005:07. The frequency of the data is monthly and
data source is publicly available through CBRT electronic data dissemination system
at http://tcmbf40.tcmb.gov.tr/cbt.html. All the series are stationary.
The lag order of the VAR is chosen according Akaike Information Criterion
(AIC). AIC shows the optimal lag length to be 5 months. The output of the model is
provided in Table 2 in Appendix. The crisis in Aril 1994 is also included as a dummy
variable.
The results of the impulse response analysis shows that the response of asset
dollarization of the non-banking sector to a generalized one standard deviation of
expected depreciation, output volatility, inflation volatility and exchange rate
volatility increases the asset dollarization. Except output volatility, asset dollarization
increases indefinitely due to these shocks.
VI. CONCLUDING REMARKS
Dollarization, since the early 1970s, has been a topic of special interest in the
context of developing countries, especially in EMs. During periods of macroeconomic
and political uncertainty, many developing countries experienced a partial
replacement of their domestic currencies by a foreign currency either as a store of
value, unit of account or as a medium of exchange.
Dollarization literature has evolved over time in many ways. While, initial
strand of literature mainly analyzed currency substitution by focusing on its
implications for monetary policy and instability of money; the sequential financial
crises of the late 1990s and early 2000s put the dollarization issue on the forefront
both in academic circles as well as non-academic world. Dollarization was then
extensively studied from the standpoint of policymakers from many aspects and hence
came various views on dollarization. According to one view, the presence of high
dollarization in some countries called for a policy option in the form of official
dollarization or a currency board. According to another view, dollarization was also
perceived as a risk factor requiring for a combat strategy, thus the dollarization
literature moved towards discussing dedollarization schemes. For some countries, the
issue was discussed within the context of conjuncture; dollarization, therefore, was
17
viewed as an integral to globalization both with respect to international trade and
global capital markets. Hence, learning-to-live-it approach was adopted. For some
other countries with high dollarization rates, carrot-and-stick approach is
recommended as a dedollarization strategy. Despite these alternatives however, few
actions have been taken in practice. Hence, the issue still needs to be resolved yet
without a one-type-fits-all approach.
18
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24
APPENDIX
Figure 1. The Evolution of Dollarization in the Turkish Economy
Asset Dollarization of the Non-Banking Sector
0.7
0.6
0.5
0.4
0.3
0.2
0.1
Dec-03
Dec-01
Dec-99
Dec-97
Dec-95
Dec-93
Dec-91
Dec-89
Dec-87
Dec-85
0
Liability Dollarization of the Non-Banking Sector
0.6
0.5
0.4
0.3
0.2
0.1
0
Jun-96 Jun-97 Jun-98 Jun-99 Jun-00 Jun-01 Jun-02 Jun-03 Jun-04 Jun-05
25
Liability Dollarization of the Banking Sector
1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
Jan-04
Jan-02
Jan-00
Jan-98
Jan-96
Jan-94
Jan-92
Jan-90
Jan-88
Jan-86
0
26
Table 1. VECM Results
Variables
d(LD_NBS)
d(AD_NBS)
d(LD_BS)
Error correction
-0.244172
(0.07252)
[-3.36696]
0.039146
(0.03808)
[ 1.02797]
0.302902
(0.21207)
[ 1.42830]
d(LD_NBS(-1))
0.023218
(0.11072)
[ 0.20970]
0.214163
(0.05814)
[ 3.68351]
0.343344
(0.32378)
[ 1.06041]
d(LD_NBS(-2))
-0.045726
(0.11922)
[-0.38356]
-0.010916
(0.06260)
[-0.17436]
0.565246
(0.34863)
[ 1.62136]
d(LD_NBS(-3))
0.311104
(0.11816)
[ 2.63289]
0.027952
(0.06205)
[ 0.45049]
-0.463507
(0.34554)
[-1.34140]
d(LD_NBS(-4))
0.374536
(0.12169)
[ 3.07790]
0.062890
(0.06390)
[ 0.98421]
-0.561686
(0.35585)
[-1.57844]
d(LD_NBS(-5))
0.114135
(0.13345)
[ 0.85524]
-0.001212
(0.07008)
[-0.01730]
-0.254780
(0.39026)
[-0.65285]
d(LD_NBS(-6))
0.280513
(0.13123)
[ 2.13761]
-0.062140
(0.06891)
[-0.90176]
-0.241258
(0.38375)
[-0.62869]
d(LD_NBS(-7))
0.230444
(0.13426)
[ 1.71644]
0.015704
(0.07050)
[ 0.22275]
-0.317067
(0.39261)
[-0.80759]
d(LD_NBS(-8))
0.231796
(0.13466)
[ 1.72137]
-0.014493
(0.07071)
[-0.20496]
-0.459825
(0.39378)
[-1.16771]
d(LD_NBS(-9))
0.091585
(0.12974)
[ 0.70591]
-0.045172
(0.06813)
[-0.66304]
0.056762
(0.37940)
[ 0.14961]
d(AD_NBS(-1))
-0.200340
(0.24089)
[-0.83167]
0.361680
(0.12649)
[ 2.85927]
-1.268988
(0.70444)
[-1.80143]
d(AD_NBS(-2))
-0.587745
(0.24965)
[-2.35429]
0.042469
(0.13109)
[ 0.32396]
0.222485
(0.73005)
[ 0.30475]
27
d(AD_NBS(-3))
-1.131581
(0.25602)
[-4.41990]
0.048389
(0.13444)
[ 0.35993]
0.980274
(0.74868)
[ 1.30933]
d(AD_NBS(-4))
-0.571718
(0.29778)
[-1.91994]
-0.128797
(0.15637)
[-0.82368]
0.305426
(0.87080)
[ 0.35074]
d(AD_NBS(-5))
-0.081168
(0.28342)
[-0.28639]
0.215307
(0.14883)
[ 1.44668]
0.513862
(0.82881)
[ 0.62000]
d(AD_NBS(-6))
-0.466509
(0.27456)
[-1.69910]
0.114151
(0.14418)
[ 0.79174]
0.344516
(0.80291)
[ 0.42908]
d(AD_NBS(-7))
-0.357136
(0.27845)
[-1.28260]
-0.009102
(0.14622)
[-0.06225]
0.794724
(0.81427)
[ 0.97599]
d(AD_NBS(-8))
-0.243841
(0.27983)
[-0.87139]
-0.001770
(0.14694)
[-0.01205]
1.037128
(0.81831)
[ 1.26741]
d(AD_NBS(-9))
0.148204
(0.21276)
[ 0.69660]
0.022929
(0.11172)
[ 0.20523]
-1.400907
(0.62216)
[-2.25167]
d(LD_BS(-1))
-0.040688
(0.03718)
[-1.09427]
-0.006389
(0.01953)
[-0.32720]
-0.198402
(0.10873)
[-1.82466]
d(LD_BS(-2))
-0.026271
(0.03801)
[-0.69108]
-0.016295
(0.01996)
[-0.81633]
-0.088611
(0.11117)
[-0.79711]
d(LD_BS(-3))
-0.066230
(0.03828)
[-1.73026]
-0.013290
(0.02010)
[-0.66121]
0.014259
(0.11193)
[ 0.12739]
d(LD_BS(-4))
-0.029429
(0.03865)
[-0.76136]
0.022552
(0.02030)
[ 1.11106]
-0.146026
(0.11303)
[-1.29187]
d(LD_BS(-5))
-0.017018
(0.03756)
[-0.45312]
0.008484
(0.01972)
[ 0.43016]
-0.183400
(0.10983)
[-1.66985]
d(LD_BS(-6))
0.012293
(0.03726)
0.007061
(0.01956)
0.037861
(0.10895)
28
[ 0.32994]
[ 0.36090]
[ 0.34750]
d(LD_BS(-7))
0.073987
(0.03677)
[ 2.01239]
0.013693
(0.01931)
[ 0.70924]
0.043742
(0.10752)
[ 0.40684]
d(LD_BS(-8))
0.024685
(0.03691)
[ 0.66879]
0.010338
(0.01938)
[ 0.53339]
-0.173189
(0.10794)
[-1.60456]
d(LD_BS(-9))
0.021696
(0.03646)
[ 0.59505]
0.009093
(0.01915)
[ 0.47492]
0.114662
(0.10662)
[ 1.07543]
C
-0.002834
(0.00437)
[-0.64894]
-0.000237
(0.00229)
[-0.10322]
-0.000346
(0.01277)
[-0.02709]
0.451970
0.238847
0.116283
0.040188
2.120701
198.4132
-3.354716
-2.603840
-0.007815
0.046063
0.495284
0.299005
0.032064
0.021103
2.523373
263.4714
-4.642997
-3.892121
-0.002680
0.025205
0.408862
0.178975
0.994408
0.117521
1.778533
90.03398
-1.208594
-0.457717
0.003651
0.129699
R-squared
Adj. R-squared
Sum sq. resids
S.E. equation
F-statistic
Log likelihood
Akaike AIC
Schwarz SC
Mean dependent
S.D. dependent
Standard Errors are given in parentheses and t-values are given in brackets.
29
Table 2. VAR Results
Variables
AD_NBS
EXPDEP
INFVOL
OUTPUTVOL EXCHVOL
AD_NBS(-1)
1.372986
(0.09818)
[ 13.9839]
0.396370
(0.16161)
[ 2.45263]
-0.000251
(0.00025)
[-0.98834]
-0.000278
(0.00572)
[-0.04853]
0.004067
(0.00649)
[ 0.62640]
AD_NBS(-2)
-0.307110
(0.15893)
[-1.93242]
-0.737488
(0.26159)
[-2.81923]
-0.000187
(0.00041)
[-0.45557]
-0.008724
(0.00927)
[-0.94152]
-0.002147
(0.01051)
[-0.20431]
AD_NBS(-3)
-0.028582
(0.15275)
[-0.18712]
0.539614
(0.25142)
[ 2.14626]
6.75E-05
(0.00039)
[ 0.17109]
0.012339
(0.00891)
[ 1.38564]
0.003914
(0.01010)
[ 0.38748]
AD_NBS(-4)
-0.350240
(0.15322)
[-2.28579]
-0.424972
(0.25221)
[-1.68500]
0.000442
(0.00040)
[ 1.11591]
-0.000866
(0.00893)
[-0.09690]
-0.029045
(0.01013)
[-2.86638]
AD_NBS(-5)
0.265294
(0.09185)
[ 2.88836]
0.215918
(0.15118)
[ 1.42817]
-0.000136
(0.00024)
[-0.57425]
-0.003282
(0.00535)
[-0.61299]
0.023347
(0.00607)
[ 3.84376]
EXPDEP(-1)
-0.061525
(0.05011)
[-1.22775]
0.158957
(0.08248)
[ 1.92710]
-3.09E-05
(0.00013)
[-0.23881]
-0.002207
(0.00292)
[-0.75541]
-0.004827
(0.00331)
[-1.45659]
EXPDEP(-2)
-0.007037
(0.05267)
[-0.13361]
0.150094
(0.08669)
[ 1.73132]
0.000500
(0.00014)
[ 3.67036]
0.006616
(0.00307)
[ 2.15469]
0.015953
(0.00348)
[ 4.58008]
EXPDEP(-3)
-0.226384
(0.05766)
[-3.92632]
-0.249765
(0.09491)
[-2.63171]
0.000534
(0.00015)
[ 3.58026]
-0.005676
(0.00336)
[-1.68856]
-0.000747
(0.00381)
[-0.19590]
EXPDEP(-4)
0.193510
(0.06326)
[ 3.05884]
0.295707
(0.10413)
[ 2.83977]
-0.000357
(0.00016)
[-2.18242]
-1.85E-05
(0.00369)
[-0.00501]
0.009358
(0.00418)
[ 2.23693]
EXPDEP(-5)
0.006062
(0.04958)
[ 0.12227]
-0.050940
(0.08161)
[-0.62420]
0.000252
(0.00013)
[ 1.96329]
0.002878
(0.00289)
[ 0.99584]
-0.010973
(0.00328)
[-3.34671]
INFVOL(-1)
47.76624
(32.2892)
[ 1.47932]
-18.55615
(53.1483)
[-0.34914]
0.515622
(0.08345)
[ 6.17860]
-0.109536
(1.88247)
[-0.05819]
5.415320
(2.13533)
[ 2.53606]
INFVOL(-2)
5.902418
(35.5107)
[ 0.16622]
68.10700
(58.4509)
[ 1.16520]
-0.300156
(0.09178)
[-3.27041]
2.002323
(2.07029)
[ 0.96717]
3.907114
(2.34837)
[ 1.66375]
30
INFVOL(-3)
5.888545
(33.1671)
[ 0.17754]
-40.75975
(54.5933)
[-0.74661]
0.011770
(0.08572)
[ 0.13731]
-4.239978
(1.93365)
[-2.19273]
-6.348428
(2.19339)
[-2.89435]
INFVOL(-4)
-14.65139
(32.6398)
[-0.44888]
3.111972
(53.7253)
[ 0.05792]
0.079179
(0.08436)
[ 0.93860]
1.499188
(1.90291)
[ 0.78784]
-2.275045
(2.15851)
[-1.05399]
INFVOL(-5)
27.91265
(28.4816)
[ 0.98002]
72.27879
(46.8810)
[ 1.54175]
-0.009111
(0.07361)
[-0.12378]
0.243949
(1.66049)
[ 0.14691]
-0.799962
(1.88353)
[-0.42471]
OUTPUTVOL(-1)
1.780484
(1.33304)
[ 1.33565]
3.932263
(2.19420)
[ 1.79212]
0.009919
(0.00345)
[ 2.87893]
0.767948
(0.07772)
[ 9.88136]
-0.059779
(0.08816)
[-0.67810]
OUTPUTVOL(-2)
-1.814493
(1.72647)
[-1.05099]
-3.366557
(2.84178)
[-1.18466]
-0.007277
(0.00446)
[-1.63082]
-0.257898
(0.10065)
[-2.56224]
-0.123700
(0.11417)
[-1.08344]
OUTPUTVOL(-3)
-0.186624
(1.76627)
[-0.10566]
1.185969
(2.90729)
[ 0.40793]
0.009994
(0.00457)
[ 2.18935]
-0.180690
(0.10297)
[-1.75471]
0.233449
(0.11681)
[ 1.99860]
OUTPUTVOL(-4)
-0.956194
(1.80561)
[-0.52957]
0.224191
(2.97205)
[ 0.07543]
-0.004953
(0.00467)
[-1.06126]
0.292063
(0.10527)
[ 2.77448]
-0.082921
(0.11941)
[-0.69444]
OUTPUTVOL(-5)
0.978235
(1.40872)
[ 0.69442]
-1.887560
(2.31876)
[-0.81404]
0.008539
(0.00364)
[ 2.34528]
-0.446701
(0.08213)
[-5.43905]
-0.133506
(0.09316)
[-1.43308]
EXCHVOL(-1)
2.089800
(1.17223)
[ 1.78276]
-2.966766
(1.92950)
[-1.53758]
0.015842
(0.00303)
[ 5.22909]
0.002832
(0.06834)
[ 0.04143]
0.580883
(0.07752)
[ 7.49321]
EXCHVOL(-2)
-3.611690
(1.41896)
[-2.54530]
-0.722066
(2.33562)
[-0.30915]
-0.003748
(0.00367)
[-1.02200]
0.013303
(0.08273)
[ 0.16080]
0.327022
(0.09384)
[ 3.48497]
EXCHVOL(-3)
1.932038
(1.43440)
[ 1.34693]
5.556501
(2.36103)
[ 2.35342]
-0.011583
(0.00371)
[-3.12428]
0.018635
(0.08363)
[ 0.22284]
-0.038222
(0.09486)
[-0.40294]
EXCHVOL(-4)
0.809013
(1.33291)
[ 0.60695]
-1.807857
(2.19398)
[-0.82401]
0.005005
(0.00344)
[ 1.45291]
0.025198
(0.07771)
[ 0.32426]
-0.205577
(0.08815)
[-2.33221]
EXCHVOL(-5)
-1.249011
(0.99599)
-4.263031
(1.63940)
-0.000156
(0.00257)
-0.044238
(0.05807)
0.203417
(0.06587)
31
[-1.25404]
[-2.60035]
[-0.06054]
[-0.76185]
[ 3.08835]
C
0.172876
(0.05963)
[ 2.89916]
0.053297
(0.09815)
[ 0.54302]
0.000282
(0.00015)
[ 1.83007]
0.005517
(0.00348)
[ 1.58689]
-2.35E-05
(0.00394)
[-0.00596]
d1994
0.094402
(0.02685)
[ 3.51601]
0.423602
(0.04419)
[ 9.58507]
-0.000142
(6.9E-05)
[-2.05265]
0.002479
(0.00157)
[ 1.58345]
-0.002375
(0.00178)
[-1.33734]
0.975634
0.971109
0.087077
0.024940
215.6032
394.2098
-4.397722
-3.893615
3.796202
0.146725
0.579738
0.501689
0.235922
0.041051
7.427899
310.9849
-3.401016
-2.896910
0.033922
0.058153
0.706251
0.651697
5.82E-07
6.45E-05
12.94604
1389.230
-16.31413
-15.81003
0.000174
0.000109
0.614655
0.543091
0.000296
0.001454
8.588871
868.8485
-10.08202
-9.577911
0.002952
0.002151
0.809778
0.774451
0.000381
0.001649
22.92242
847.8004
-9.829945
-9.325839
0.001689
0.003473
R-squared
Adj. R-squared
Sum sq. resids
S.E. equation
F-statistic
Log likelihood
Akaike AIC
Schwarz SC
Mean dependent
S.D. dependent
Standard Errors are given in parentheses and t-values are given in brackets.
32
Figure 2. Generalized Impulse Responses to 1 Standard Deviation Shocks
Response of AD_NBS to Generalize d One
S.D. EXPDEP Innovation
.030
.025
.020
.015
.010
.005
.000
-.005
5
10
15
20
25
30
Response of AD_NBS to Generalized One
S.D. OUTPUTVOL Innovation
.020
.015
.010
.005
.000
-.005
-.010
-.015
5
10
15
20
25
30
33
Response of AD_NBS to Generalized One
S.D. EXCHVOL Innovation
.025
.020
.015
.010
.005
.000
-.005
-.010
5
10
15
20
25
30
Response of AD_NBS to Generalized One
S.D. INFVOL Innovation
.025
.020
.015
.010
.005
.000
-.005
5
10
15
20
25
30
34