An assessment of another decade of capital controls in Colombia: 1998–2008

KCCCRE

ieedreop

oEBsaBtEt

The Quarterly Review of Economics and Finance 51 (2011) 319– 338

Contents lists available at SciVerse ScienceDirect

The Quarterly Review of Economics and Finance

jo u rn al hom epage: www.elsev ier .com/ locate /qre f

n assessment of another decade of capital controls in Colombia: 1998–2008

lvaro Concha, Arturo José Galindo ∗, Diego Vasquez1

nter-American Development Bank, United States and Banco de la República, Colombia

r t i c l e i n f o

rticle history:eceived 15 October 2009eceived in revised form 20 July 2011ccepted 26 August 2011vailable online 10 September 2011

EL classification:21, F30, F32, F41

a b s t r a c t

We explore the effectiveness of capital controls in Colombia. We analyze the impact of administrativerestrictions to capital flows on aggregate capital flows, the composition of capital flows, the real exchangerate, and economic activity using restricted versions of vector error correction models (VEC) that controlfor exogenous global financial conditions. The models are estimated using monthly data ranging fromAugust of 1998 to May of 2008. In addition we estimate GARCH models to identify if capital controls havehad relevant impacts on the volatility of the nominal exchange rate and of other relevant asset prices.These models are estimated using weekly data covering the same time period. Results suggest that the

eywords:apital controlsapital flowsolombiaeserve requirement

capital controls used since 1998 have been ineffective in reducing capital flows and the trend of theColombian peso to appreciate. In addition there is no evidence suggesting a change in the compositionof capital flows induced by capital controls. We find some evidence in favor of capital controls reducingnominal exchange rate volatility at high frequencies.

xchange rates

. Introduction

Financial liberalization and economic globalization can bemportant drivers of long term economic growth.2 Despitevidence pointing towards long term benefits of financial lib-ralization, there is consensus that globalization leads to policyilemmas associated with the volatility of capital flows in the shortun.3 When capital flows into a country, there is a risk of real

∗ Corresponding author.E-mail address: ajgalindo@gmail.com (A.J. Galindo).

1 Concha works in the Colombian Country Office of the Inter-American Devel-pment and is also professor at Universidad Nacional. Galindo is the Regionalconomic Advisor for the Andean Countries at the Inter-American Developmentank. Vasquez works at the Central Bank of Colombia. We thank Camila Quevedo foruperb research assistance. The opinions in this paper are exclusively of the authorsnd do not necessarily represent those of the IDB, the Banco de la República, or itsoards of Directors. We are grateful for comments received on a previous version ofhis paper by two anonymous referees and by participants in Debates de Coyunturaconómica organized by Fedesarrollo and the Fundación Konrad Adenauer and athe 2008 LACEA conference in Rio de Janeiro, Brazil.

2 Henry (2007) surveys this literature and highlights recent evidence on hownvestment and economic growth follows capital flows liberalization.

3 Among the risks associated to capital flows volatility are those of exchange ratenstability, problems linked to sudden stops in capital flows, and financial contagion,mong others. See López-Mejía (1999) and IADB (2005) for discussions.

nclude capital controls to contain capital flows, particularly shorterm ones, limit the appreciation of domestic currencies, and avoidudden reversals of capital flows in turbulent times.4

Colombia has had a long tradition with capital controls. In factt is difficult to identify relatively long periods of time in recentistory in which capital controls have not been in place. Evenfter the adoption of several economic liberalization policies in thearly 1990s, that in theory included a liberalization of the capitalccount, capital controls have remained in place. During the pastwo decades, policy makers have used capital controls based on theremise that short term capital flows are harmful for the economynd need to be contained.

The instrument most commonly used to control capital flowsuring the past decade and a half, has been a Chilean style unremu-erated reserve requirement or deposit on portfolio flows and shorterm debt. The purpose of this policy has been to disincentive short

4 Some justifications for capital controls can be found in Krugman (1987),ichengreen, Tobin, and Wyplosz, 1995, and Kaplan and Rodrik (2001). Calvo (2010)rovides a skeptical view on capital flows and its distortive impacts.5 For many years, and until the beginning of the 1990s, capital controls were ori-

nted to limit capital outflows. Since the 1990s, capital controls have been orientedo diminish capital inflows, alter their composition in favor of long term capitalows, and avoid the appreciation of the Colombian peso.

3 f Econ

tiettr

peciifltimccap

estiapotiidid1ad

paaCatawC

(bteev

tgtit(to

betprr

ctDpsops

Tcictiif

qtttfie

ete(fi

20 A. Concha et al. / The Quarterly Review o

There is a wide range of studies carried out in different coun-ries that raise doubts about the effectiveness of capital controlsn terms of limiting capital flows and altering the trend of the realxchange rate. Despite the fact that some evidence suggests thathe composition of capital flows can be altered through capital con-rols, research supporting impacts on maintaining the exchangeate undervalued or reducing aggregate capital flows is very scarce.

The Chilean experience with capital controls is consideredaradigmatic by many authors and has been subject to consid-rable analysis. In most cases, empirical evidence indicates thatapital controls had an impact on the composition of foreign debtn favor of longer maturities but had no significant impact on keep-ng the local currency undervalued or reducing aggregate capitalows.6 Recently, a macro-prudential objective has also been linkedo capital controls, namely the possibility of reducing over borrow-ng during booms to avoid costly financial crises in the future.7 The

acro prudential objective can be achieved as long as the capitalontrols are effective. There is also some evidence suggesting thatapital controls contribute to diminish financial volatility, which islso considered an objective, though a second order one, of theseolicies.8

Studies for the Colombian case are not conclusive, though mostvidence obtained through various techniques and different dataets suggests that capital controls have had little impact on con-aining exchange rate appreciation. There is some consensus on thempact of capital controls on diminishing short term flows. Someuthors argue that as in Chile, capital controls have altered the com-osition of capital flows, but have not affected total capital flowsr the real exchange rate. Cárdenas and Barrera (1997) find thathe capital controls implemented between 1985 and 1995 had nompact on total capital flows but changed their composition. A sim-lar finding is reported by Rocha and Mesa (1998) who argue thaturing a similar period, capital controls reduced the short term

nterest rate differential reducing medium and long term foreignebt. Using a data set that covers the period between 1993 and998, Ocampo and Tovar (1999), Ocampo and Tovar (2003), Villarnd Rincón (2000) and Rincón (2000) argue that capital controlsiminished not only short term but also long term capital flows.

It is worth noting that these studies covered mostly a timeeriod in which the exchange rate was either managed through

crawling peg regime (up to 1993) or was partially managed in target zone (1993–1998). To our knowledge only this paper andlements and Kamil (2009) focus exclusively on a time period of

floating exchange regime in which one could argue that capi-al controls could play a stronger role in containing exchange rate

6 De Gregorio, Edwards, and Valdes (1998), De Gregorio, Edwards, and Valdes2000) analyze the effects of the non remunerated deposit on capital flows in Chileetween 1991 and 1998 on the interest rate, the real exchange rate, the volume andhe composition of capital flows. They find that capital controls had a significantffect on the composition of capital flows and increased temporarily the real inter-st rate. They also find that the impact on the real exchange rate is transitory andanishes rapidly.7 See Bianchi (2009) or Korinek (2009) for a discussion.8 Edwards (1999) estimates GARCH models and finds that even if capital con-

rols contributed to diminish volatility, they were not enough to isolate Chile fromlobal shocks particularly during the Asian crisis. Edwards and Rigobón (2005) showhat capital controls helped diminish the impact of external shocks on the nom-nal exchange rate, and despite that they increase the unconditional volatility ofhe exchange rate, they also reduced its sensitivity to shocks. Kaplan and Rodrik2001) suggest for the Malasian case, that capital controls contributed to increasehe effectiveness of monetary policy and the speed of recovery following the crisisf the 1990s.

citceor

omics and Finance 51 (2011) 319– 338

ince 2007 and find that they were successful in limiting externalorrowing, but had no significant impact on the volume of non-FDIows nor moderated the appreciation of the peso.

This paper looks at a wider time frame than most of the Colom-ian studies cited above and focuses on the whole period ofxchange rate flexibility (1998–2008).9 We consider that doinghis diminishes problems associated with credibility issues of theegs or quasi-pegs that may impact the way that the exchange rateesponds to fundamentals that if not controlled for can distort theelationships that we wish to identify.

Also, and as opposed to Clements and Kamil, we explore not onlyontrols on debt flows regulated by the Central Bank, but also con-rols on portfolio flows regulated either by the National Planningepartment (DNP) or the Ministry of Finance. Controls during theast decade have been both on portfolio flows as well as on foreignhort term debt. While most studies have focused only on controlsn short term foreign debt, we include in our analysis controls onortfolio flows as well. This is also a difference with respect to othertudies referenced above.

An important feature of our paper is that as in Ocampo andovar (1999), Rincón (2000) and Clements and Kamil (2009) weontrol for external factors that can alter capital flows and whosempact can sometimes be confused with that of capital controls. Ifontrols are implemented at the same time that global risk percep-ions increase, both events may lead to similar expected outcomesn terms of capital inflows and exchange rate behavior. However todentify the precise impact of each of them, it is crucial to controlor the other.

In addition, the methodology that we follow, allows us to ade-uately deal with certain endogeneity issues that come about inhis sort of analysis, and allows us to impose exogeneity restric-ions on the variables that measure global financial conditions anderms of trade fluctuations. This contributes to the precise identi-cation of the impact of changes in capital control policies on thendogenous variables of our study.

The empirical analysis is divided in two sections. First, wexplore the impact of capital controls on aggregate capital flows,he composition of capital flows (short vs. long term flows) the realxchange rate and economic activity in a vector error correctionVEC) model. Second, we analyze the impact of capital controls onnancial volatility using GARCH models.

Our findings suggest that capital control policies implementedn Colombia after 1998 have been ineffective in limiting the appre-iation of the domestic currency and reducing capital flows. We doot find evidence in favor of a change in the composition of capi-al flows. With respect to a reduction in financial volatility we findtatistical evidence in favor of this, but the impact is not relevantrom an economic point of view.

The paper has 6 parts. In part 2 we describe capital control poli-ies in Colombia. Part 3 describes a capital controls measure thats used for the empirical analysis in parts 4 and 5. Part 4 presentshe methodology and results of assessing the impacts of capitalontrols on capital flows, capital flows’ composition and the realxchange, and part 5 does the same for our analysis on the impact

9 Previous studies cover periods with different exchange rate regimes that include crawling peg, an exchange rate band, a transition regime between these two, and flotation regime, and do not include strategies to deal with regime shifts. It isorthwhile noting that since our sample differs from the sample used in other

tudies, the comparison of our results with those of other studies must be doneith caution.

A. Concha et al. / The Quarterly Review of Economics and Finance 51 (2011) 319– 338 321

Table 1Capital controls in Colombia.

(a) Controls on foreign debtRegulator Norm/resolution Deposit (% of loan) Duration of deposit

Banco de la República RE. 21/1993 (September 2) 47% 12 monthsBanco de la República RE. 7/1994 (March 15) 93% 12 months

64% 18 months50% 24 months

Banco de la República RE. 22/1994 (August 12) 140–42% 1–60 monthsBanco de la República RE. 3/1996 (February 15) 85–10% 6–48 monthsBanco de la República RE. 5/1996 (March 15) 50% 18 monthsBanco de la República RE. 4/1997 (March 12) 50% 18 monthsBanco de la República RE.5/1997(May 20) 30% 18 monthsBanco de la República RE.1/1998 (January 30) 25% 12 monthsBanco de la República RE. 10/1998 (September 18) 10% 6 monthsBanco de la República RE.8/2000 (May 4) 0% –Banco de la República RE.2/2007(May 6) 40% 6 months

11% 12 monthsBanco de la República RE. 18/2007 (November 23) 40% 6 months

11% 12 months20% portfolio flows 12 months

(b) Controls on portfolio flowsRegulator Norm/resolution Policy

DNP D. 4210/2004 (December 14) Portfolio investments of under 12 months are prohibitedMINHACIENDA D. 1940/2006 (June 13) Suspends decree 4210/2004MINHACIENDA D. 1801/2007 (May 23) 40% deposit on peso investments for less than 6 monthsMINHACIENDA D. 4814/2007(December 14) 40% deposit on peso or dollar investments for less than 6 months

S e 208

cwStaoo1i

iCiottauaIs

pmiidmpm

etwptNlficColombian firms to create a fac ade firm abroad to issue short termforeign debt without being subject to the capital controls.13

12 It is important to notice that controls have not been designed to discriminate

MINHACIENDA D. 1888/2008 (May 30)

ources: Resoluciones Externas of Banco de la República and modifications to decre

. Capital controls in Colombia

The use of capital controls in Colombia is by no means a recentolicy. Between 1967 and 1991, a very restrictive regime on capitalows was in place. Every foreign debt flow, either private or public,ad to be approved by the central bank.

During the first half of 1991, many administrative controls toapital flows were removed. In January of 1991, Law 9 that startedith the liberalization of capital flows was approved by Congress.

ome controls were lifted, and the monopoly of the central bank ashe unique foreign exchange market participant was also removedllowing additional intermediaries to participate in the exchangef foreign currency. Later that year, in June, with the expeditionf resolution 91, private foreign debt for maturities lower than2 months was fully liberalized, and minimum restrictions were

mposed for maturities greater than one year.10

In September of 1993 in the midst of a new wave of cap-tal inflows that were exerting pressure on strengthening theolombian peso, policy makers inspired on the Chilean experience,

mposed capital controls in the form of a non-remunerated depositn private foreign debt. The rationale for this policy was to reducehe exposure of the economy to the volatility of capital flows, par-icularly short term speculative ones. Initially the deposit was sett 47% of the foreign loan for a twelve month period. Since then andntil the year 2000, both the percentage of the reserve requirement,s well as the duration of the deposit were changed several times.n the year 2000 the deposit was set at a 0% rate. Panel (a) of Table 1hows the detailed evolution of capital controls in Colombia.

In May 2007, the Central Bank, reestablished the deposit on for-

10 Some restrictions on the use of foreign funds remained. In particular the servicesector had many limitations on its possibilities to access foreign debt.11 See Gómez (2007) for a discussion of capital controls up to mid 2007.

brceriet

50% deposit on peso or dollar investments for less than 6 months

eriod, and at 11% of disbursement of loans to pre-finance exportsor a twelve month period. This policy was kept in place untileptember 2008, when the deposit was set back to 0%.

Besides controls to short term foreign indebtedness, Colombianolicy makers have also imposed restrictions on portfolio invest-ents. Policies have ranged from completely forbidding short term

nvestments from abroad (2004–2006) to imposing deposits sim-lar to those on short term debt. In May 2007, a non remuneratedeposit on 40% of the portfolio investment was imposed for a sixonth period after an attempt of prohibiting short term foreign

ortfolio flows nearly two years before. Panel (b) of Table 1, sum-arizes these policies.12

Literature has shown that capital controls are subject to a vari-ty of loopholes. De Gregorio, Edwards, and Valdes (2000) showhat during the times they were used in Chile, several loopholesere closed in order to increase their effectiveness. During the timeeriod analyzed in this paper, only one mayor loophole was closedhough adjustments to regulation. Through its external resolutiono. 1 of 2008, in late April, the Central Bank closed an important

oophole by extending the deposit to foreign affiliates of Colombianrms that issued debt abroad, and transferred it to its Colombianounterpart as a capital investment. This loophole allowed many

y the nationality of the investors. Controls apply to all cross border foreign cur-ency transactions subject to the control, regardless of the nationality of the agentsarrying them out. In order to explore the role of residents positions in foreignxchange see Arbelaez and Steiner (2009) who analyze the role played by largeesident investors such as private pension funds in explaining exchange rate volatil-ty. Their research suggests that exchange rate transactions by such players do notxplain volatility. They also find that volatility is heavy influenced by the Treasury’sransactions or Central Bank interventions.13 Anecdotal evidence gathered by the authors with different sources suggests thathis was a common practice during the capital control periods.

322 A. Concha et al. / The Quarterly Review of Economics and Finance 51 (2011) 319– 338

lent o

ttlGVtpfittafl

widtaimdc

Epdmdstc

mtEa2itc

saCtirsAn inspection of the graphs appears to suggest that the last round

Fig. 1. Tax equiva

Our purpose here is to analyze the impact of these controlsn relevant endogenous variables such as the trend of the realxchange rate, total capital flows, the composition of capital flowsnd the volatility of financial variables.

. Measuring the intensity of capital controls

Evaluating the impact of capital controls requires the construc-ion of an indicator that measures the intensity of such policy. Forhis purpose we follow closely what has been done in the previousiterature on this field. Following Valdés-Prieto and Soto (1996), Deregorio, Edwards, and Valdes (1998), De Gregorio, Edwards, andaldes (2000) and Edwards (1999) among others, we construct a

ax equivalent measure of capital controls that reflects the implicitremium paid on local returns to compensate investors for thenancial costs associated with capital controls. The calculation ofhe tax equivalent measure depends on the type of capital con-rol imposed, and varies depending on whether it is in the form of

reserve requirement or a prohibition to certain types of capitalows.

In the case of a reserve requirement the tax equivalent is derivedrom the following condition:

1 − �)(1 + ik)k/12(1 + i∗)(h−k)/12 + � = (1 + i∗)h/12 (1)

here � is the reserve requirement, ik the return to investmentsn the local economy, i* the return to investments abroad, k theuration in months of the investment to obtain return ik, and hhe length in months of the requirement. Condition (1) is a nonrbitrage interest rate parity condition that shows that the return tonvestments in the local country net of the costs of capital controls

ust be equal to the return of investments abroad. The longer theuration of the requirement, the higher the premium needed toompensate investors. Eq. (1) can be rewritten as:

1 + i∗ + tx)k/12≡(1 + ik)k/12 = (1 + i∗)k/12 − �(1 + i∗)(h−k)/12

1 − �(2)

olving for tx, we obtain the tax equivalent measure of capitalontrols14:

x = �

1 − �

ki∗ (3)

14 To solve we use the approximation: (1 + i)x ≈ (1 + xi).

f capital controls.

q. (3) shows that the tax equivalent of capital controls dependsositively on the amount of the reserve requirement (�) and itsuration (h), and negatively on the duration of domestic invest-ents (k). The shorter the duration of investments vis a vis the

uration of the requirements, the costlier the capital controls mea-ure. The tax equivalent also depends positively on i*. The higherhe opportunity cost of investments in the domestic country, theostlier the controls.

In the case of a straight forward prohibition to short term flows,he interest rate parity condition for investments with a maturityhorter than the maturity up to which capital flows are bannedk < h) will be:

1 + i∗ + tx)k/12 = (1 + i∗)h/12 (4)

olving for tx:

x = h − k

ki∗ (5)

s Eq. (3), Eq. (5) also shows how the capital controls policyecomes costlier the longer the duration up to which flows areanned vis a vis the duration of investments.

Fig. 1 shows different estimates of tx for Colombia and for invest-ents with a 1,3, and 6 month maturities. Eq. (3) is used to compute

x in periods in which reserve requirements have been in place, andq. (5) in periods in which investments with durations lower than

year have been banned such as between December 2004 and June006 (Table 1, panel b). We assume that the alternative return of an

nvestment abroad is given by the 6 month Libor rate. The shorterhe maturity of local investments, the higher the cost of capitalontrols.

Once we have constructed this proxy for capital controls inten-ity, we explore its impact on relevant economic variables. Figs. 2nd 3 show the behavior of short and long term capital flows inolombia, the real exchange rate, and the intensity of capital con-rols. The lines in Fig. 2 show capital flows and the shaded region thentensity of capital controls.15 In Fig. 3, the line shows the bilateraleal exchange rate of the peso with respect to the US dollar, and thehaded area, once again indicates the intensity of capital controls.

f controls have led to a slow down in short term capital flowsnd have reduced the appreciating trend of the real exchange rate.owever, it is important to take into account that this slowdown

15 We depict the summation of capital flows during the last three months.

Fig. 2. Capital flows (three month summation) and capital controls.

e rate

tfitcnaavftiFipts

wroiri“

iobe cointegrated, and hence that the short run dynamics of the VARare influenced by the extent of deviations from their long run equi-librium. In fact, and as shown below, our tests reveal the existence

16 For the empirical exercises we use the tax equivalent measure of investmentswith a 6 month duration.

Fig. 3. Bilateral real exchang

lso coincides with difficulties in global financial markets associ-ted to the subprime mortgage crisis in the US and the financialurmoil that followed.

A rigorous analysis of the impacts of capital controls, shouldake into account several types of shocks, including of course globalnancial ones. This is done in the following sections through twoypes of econometric estimations. First we study the impact ofapital controls on capital flows, the real exchange rate and eco-omic performance, namely exploring if capital controls have hadn impact in detaining capital flows or changing their compositionnd depreciating the real exchange rate. This is done by estimatingector error correction models (VEC) using monthly data spanningrom mid 1998 and until May 2008. Second we explore if capi-al controls have diminished domestic financial volatility, whichs usually considered a second order objective of capital controls.or this, we estimate GARCH models of financial indicators includ-ng the nominal exchange rate, a stock exchange price index, and aublic debt price index, using a weekly data set that covers a similarime period for the exchange rate and the stock price index, but ahorter one, due to data availability for the public debt price index.

. Capital controls, capital flows and the real exchange rate

To estimate the impact of capital controls on macroeconomicariables, we estimate a VEC model including an index of industrial

olombia – Banco de la República, total capital inflows as reportedy the Colombian Central Bank, the tax equivalent measure of

index and capital controls.

apital controls described above,16 an index of terms of trade alsoonstructed by the Central Bank, and the global EMBI spread con-tructed by JP Morgan to control for global financial conditions.ppendix A reports the source and gives additional details on theata set. We estimate the following model:

�yt = c + ˛ˇ′yt−1 + �1�yt−1 + · · ·�p−1�yt−p−1 + ϕDt + εt

yt = (EMBIt, TOTt, Txt, CFt, RERt, IPt)(6)

here EMBI is the spread of emerging markets sovereign bondeturns with respect to US treasuries (in logs), TOT is the termsf trade index (in logs),17 Tx is the tax equivalent measure of cap-tal controls, CF are total net capital flows, RER is the multilateraleal exchange rate index (in logs), IP is the industrial productionndex (in logs), and D a dummy variable capturing changes in thepower” of capital controls as described below.

Previous research has used VARs to test the effectiveness of cap-tal controls.18 Here we use a VEC to account for the fact that mostf the variables involved in our empirical specification are likely to

17 We control for terms of trade fluctuations to reflect the fact that an increase inommodity prices may be associated with a boom of foreign exchange that may leadirectly to exchange rate appreciation or indirectly through foreign investment inommodity producing sectors.18 See for example De Gregorio, Edwards, and Valdes (2000) for the case of Chile.

3 f Econ

mcaInbr

Eraittf

Titthreiuptate

avmtmTaao

cdstbJcts

KˇwTmdtrmHinvwo

Wttastem

tesieactw(o

f co-integration in our data and hence support the choice of thepecification.

In this specification, the matrix � includes the partial adjust-ent coefficients of the error correction model, ˇ′yt−1 are the error

orrection terms, the matrixes � includes the short term dynamicdjustment parameters, and � is a vector of reduced form errors.n a first specification we estimate the model considering CF aset total capital flows and in further specifications we divide theseetween short and long term capital flows (FDI), according to dataeported by the central bank.

In addition, and in order to control for potential loopholes in cap-tal controls, we include a dummy variable labeled “power dummyD)” that takes a value of 1 when controls were strengthened and 0therwise. This dummy should capture the fact that controls mightork when they are initially implemented but as loopholes areiscovered they gradually lose power.19

In our empirical model we allow for the exogeneity of the globalMBI spread and of the terms of trade. To model it we imposeestrictions on the and � matrixes. We assume that the EMBInd terms of trade are exogenous in such a way that their dynam-cs only rely on their past and not on the short term behavior ofhe rest of the variables in the system, nor on the error correctionerms.20 This means that the matrixes and � take the followingorm21:

⎛⎜⎜⎜⎜⎝

00˛3˛4˛5˛6

⎞⎟⎟⎟⎟⎠

; �j =

⎛⎜⎜⎜⎜⎜⎜⎜⎝

�j,1,1 0 0 0 0 00 �j,2,2 0 0 0 0

�j,3,1 �j,3,2 �j,3,3 �j,3,4 �j,3,5 �j,3,6

�j,4,1 �j,4,2 �j,4,3 �j,4,4 �j,4,5 �j,4,6

�j,5,1 �j,5,2 �j,5,3 �j,5,4 �j,5,5 �j,5,6

�j,6,1 �j,6,2 �j,6,3 �j,6,4 �j,6,5 �j,6,6

⎞⎟⎟⎟⎟⎟⎟⎟⎠

he estimation of (6)–(7) requires checking first the order ofntegration of the variables and the number of co-integration rela-ionships in the data. We require that at least two of the variables inhe system are I(1). As shown in Appendix B, this condition amplyolds. The ADF and KPSS unit root tests show that the log of theeal exchange rate (log(RER)), long term capital flows (FDI), the taxquivalent of capital controls (Tx), the log of the terms of tradendex (log(TOT)), and the log of the EMBI spread (log(EMBI)) have anit root. The results of the tests are mixed for the log of industrialroduction (log(IP)), total capital flows (CF) and short term capi-al flows (ST CF) in which the ADF rejects the unit root hypothesisnd the KPSS rejects stationarity. Once first differenced, accordingo both tests, all variables are stationary. These results allow us to

The estimation of models (6) and (7) requires verifying that theariables are co-integrated, that is that there exists at least one

19 We base this, as suggested by a referee, on the work of De Gregorio, Edwards,nd Valdes (2000). Unfortunately our data does not allow us to replicate the powerariable as constructed there. In Chile, several modifications to the reserve require-ents regulations took place to close important loopholes. In Colombia, according

o our knowledge, the only loophole that was truly closed was done in May 2008, 4onths before capital controls were eliminated, and right at the end of our sample.

he loophole that was closed was one that allowed Colombian firms to get indebtedbroad through a foreign subsidiary and transferring the funds to Colombian branchs a capital investment without being subject to the reserve requirement. The restf modifications were aimed at increasing the reserve requirement.20 We also allowed for specifications in which the EMBI spread and the terms ofrade were correlated, but we did not find significant coefficients and do not reporthem here. Results, nonetheless, were unchanged.21 The model has two deterministic components: the constant and the powerummy. We assume that the coefficient of the power dummy in the EMBI and TOTquations are zero, to guaranty the exogeneity of the global EMBI spread and oferms of trade.

ombination between them that yields stationary residuals, andetermining the number of co-integrating vectors.22 Appendix Chows the results of the co-integration tests for the model withotal capital flows (upper panel) and for the model that dividesetween long and short term flows (lower panel). For the first, theohansen and Saikkonen and Lütkepohl tests suggest evidence ofo-integration, and indicate that there are two co-integration vec-ors at the 5% significance level. For the second model, the testsuggest three co-integration vectors.23

The model is estimated in two stages following Lütkepohl andratzig (2004). In a first stage we estimate the co-integration matrix

with restrictions on ˛. In the second stage we estimate the modelith the � restrictions and include ˇy′

t−1 as a regressor by FGLS.he bottom panels of the tables in Appendix D show LM tests forultivariate serial correlation. The tests reveal that there is no evi-

ence of serial correlation of up to the 12th order. To corroboratehis, in Appendix E, we report the correlation and partial autocor-elation functions of the residuals of each of the equations in theodel. In most equations the residuals appear to be well behaved.owever, there is some evidence of a high order serial correlation

n the IP equation, but due to the amount of parameters that wouldeed to be estimated to control for it, and the fact that the multi-ariate tests reject serial correlation of high orders, we do not dealith it and keep the specification as parsimonious as possible with

ne lag only.24

Appendix D reports the estimation results of the VEC models.e use these estimates to analyze the impact that capital con-

rols have had on the rest of the variables of the model. Recallhat capital controls were put in place to disincentive capital flowsnd reduce the appreciating trend of the Colombian peso. We con-truct impulse response functions of the endogenous variables inhe model with respect to changes in the Tx measure, based on ourstimates reported in Appendix D to test if these goals have beenet.Fig. 4 reports the impulse response functions for the model with

otal capital flows. Each of the columns shows the response of thendogenous variables of the model to a one standard deviationhock of the variables in the model.25 To assess the impact of cap-tal controls on capital flows, industrial production, and the realxchange rate, we should look at the responses of each of these to

shock to Tx (third row of Fig. 4, part a). The results of this exer-ise suggest that capital controls have a non significant effect onhe real exchange rate (third row, third column). This is associatedith a non significant response of capital flows to capital controls

third row, second column). In short, the effect of capital controlsn the relevant economic variables is very close to null.

Fig. 4 also shows that the dynamics of the real exchange rate andf capital flows depend significantly on external factors. The firstow shows the response of the endogenous variables to a one stan-

22 Being co-integrated means that there is at least one stable long-term relation-hip in the variables.23 The number of lags in the VEC model is determined following the Hannan-Quinnriterion. We found the optimal lag length for both models is 1.24 Appendix F reports of the density of the errors in each equation. While therrors are close to normal, Jarque–Bera tests, reject normality in some equations.his however in not an uncommon feature in VAR and VEC estimations.25 Given the EMBI spread and the TOT variables are modeled as exogenous, theiresponse to shocks to other variables in the model is zero and are not reported.n order to identify structural shocks we use the Choleski decomposition of theariance–covariance matrix. As robustness we allow for different ordering of theariables in the model.

Fig. 4. (part a) – Impulse response functions;Model with aggregate capital flows. Note: Dotted lines are 95% Hall confidence intervals, and dashed lines are Efron confidence intervals.

Fig. 5. (part a) – Impulse response functions.Model with short and long term capital flows; Note: Dotted lines are 95% Hall confidence intervals, and dashed lines are Efron confidence intervals.

f Econ

cttiCatc

htflwnaa

nflnI(

oswbbggt

stccdcta

riaiflsat

vfatryftnu

caebdipmitvtiS

A. Concha et al. / The Quarterly Review o

iminish. These results are not only statistically significant but alsore important economically. According to our estimations an 7.2%ncrease in the EMBI spread leads to up to a 2% depreciation of theeal exchange rate, and up to a nearly USD 50 million fall in monthlyapital flows.26

In our model we have allowed for the endogeneity of the capitalontrol variable.27 The first column of row 1 shows the response tohe capital controls variable to a rise in the EMBI spread. We findhat when the EMBI spread rises, capital control intensity dimin-shes. This is consistent with the motivation of capital controls inolombia. When global financial conditions are favorable, whichre reflected in a low EMBI spread, and capital flows are abundant,he exchange rate appreciates and economic authorities implementapital controls to try to detain it.

Another result worth noting is that in the first row and thirdolumn of Fig. 4 part b. There, the response of the real exchangeate to a one standard deviation shock of total capital flows (USD60 million) is plotted. A one standard deviation rise in capital flows

eads to a 1% appreciation of the peso.28

Row 1 and column 2 of Fig. 4 part b, shows the response of capitalontrols to a shock in the real exchange rate. As expected when thexchange rate appreciates, capital controls increase. We find thathis has nearly a six month lag.

This initial evidence suggests that capital controls have not beenble to contain currency appreciation or detain capital inflows. Theorecast error’s variance decomposition reported in Appendix Gupports the view that capital controls have played a small rolln explaining capital flows or the real exchange rate, in contrast toxternal variables such as the EMBI spread.

Studies on other countries have also shown that capital controlsave little impact on total capital flows,29 but they suggests thathey have been effective in changing the composition of capitalows in favor of long term flows. To test if this holds for Colombiae re-estimate the model replacing total net capital inflows foret FDI and net short term capital inflows (debt and portfolio) andnalyze similar types of impulse response functions. These resultsre reported in Fig. 5.

The impact of capital controls is observed in the third row of parta) in Fig. 5. Again we find no evidence that capital controls havead a significant impact on the real exchange rate or on short or

ong term capital flows. From this perspective we find no evidenceor Colombia that capital controls have affected the composition ofapital flows as has happened elsewhere.

As in the previous exercise, we see a strong response of endoge-ous variables to external shocks. Net FDI flows, short term capitalows, industrial production, and the real exchange rate exhibit sig-

n a similar fashion the fourth column of the fourth row of Fig. 5part a) and the forth column of the first row of Fig. 5 (part b),

26 The monthly average of total capital flows during this sample was USD 191illion.

27 This was suggested by an anonymous referee, and follows the work of Cardosond Goldfain (1998) and De Gregorio, Edwards, and Valdes (2000). Our estimatesssuming capital control exogeneity are similar to the ones reported and are avail-ble upon request.28 As noted by one of the referees, one puzzling result is found in the third columnf the second row of Fig. 4 part a, that shows that an increase in terms of trade has ahort lived positive effect on the real exchange rate. We believe that this may happenhen foreign inflation is highly correlated with the terms of trade shock. This may

e the case since much of the terms of trade shocks for Colombia are explainedy increases in oil and other hydrocarbon prices. These are strongly related withlobal inflation. A rise in terms of trade may be correlated in the short run withlobal inflation that may be proportionally higher than the nominal appreciation ofhe peso. This may lead to a short term depreciation of the real exchange rate.29 See De Gregorio, Edwards, and Valdes (2000) for the case of Chile.

woe(baatcwo

omics and Finance 51 (2011) 319– 338 327

how that the real exchange rate is very sensitive to FDI and shorterm capital flows fluctuations. Capital flows, independent of theiromposition, are the major driving force behind currency appre-iation. As above Appendix G reports the forecast error varianceecompositions, that confirm the limited role played by capitalontrols in explaining the endogenous variables of the model, andhe importance of global factors in explaining real exchange rateppreciation.

In order to order to confirm these results we perform severalobustness tests that are reported in Appendices H and I. First andn order to reduce the number of parameters to be estimated, wellow industrial production to enter the model exogenously.30 Thempulse response functions for the model with aggregated capitalows considering this variant are shown in Appendix H. As can beeen this assumption does not change the main results of the paper,nd the finding of no effects of capital controls on capital flows andhe real exchange rate remain.

Finally, and since we are using a Cholesky decomposition of theariance covariance matrix of the VEC model, we allow for dif-erent orderings of the variables in order to test if changes in thessumption of contemporaneous responses of the variables affecthe main results. To limit the amount of space used to report theseesults and allow the reader to focus on the main variables of anal-sis in this study, in Appendix I we plot the impulse responseunctions of aggregate capital flows and the real exchange rateo changes in the capital controls policy variable for seven alter-ative orderings of the variables in the model. Results remainnchanged.

. Capital controls and financial volatility

The results derived from the VEC analysis suggests that capitalontrols have not been useful in Colombia to limit exchange rateppreciation, detain capital flows or alter their composition. Thisvidence suggests that market participants frequently find ways ofypassing the controls and take advantage of return differentials ofomestic financial assets vis a vis foreign ones. Even if this is true,

t is likely that the sophisticated mechanisms developed by marketarticipants may lead to a reduction in foreign exchange move-ents or a reduction in the frequency of transactions. In such case

t is likely that capital controls, even if not having a direct impact onhe permanent level of the exchange rate, may have an impact on itsolatility as well as on the price of other financial assets. To explorehis hypothesis we estimate an empirical model that captures thempact of capital controls on the volatility of financial indicators.pecifically we estimate the following GARCH specification on a setf financial variables:

t = f (xt) + εt (8)

2t = ϕ + ˛1ε2

t−1 + ˛2�2t−1 + ˛3txt + ˛4Extt + t (9)

here Eq. (8) is the mean equation and (9) the variance equationf a financial variable x. The model is estimated using the nominalxchange rate (TRM), the Colombian Stock Exchange price indexIGBVC), and a public bond price index constructed by Corficolom-iana a local investment bank (IDP), as dependent variables. As

proxy for capital controls we use the same variable tx definedbove, and a dummy variable that takes values of 1, when con-rols have been in place and zero otherwise (DUM control). As

f the dependent variable chosen based on the autocorrelation

30 We thank one of the anonymous referees for this suggestion.

Table 2GARCH model estimation for the nominal exchange rate (NER).

Dependent variable: ( log(NER)(1) (2) (3) (4) (5)

Mean equationConstant −2.9E-04 −3.9E-04 −3.5E-04 −5.3E-04 −5.1E-04

4.4E-04 4.1E-04 4.2E-04 4.2E-04 4.2E-04( log(NER)t−1 0.346 0.344 0.342 0.336 0.326

0.043*** 0.043*** 0.043*** 0.044*** 0.044***

( log(NER)t−3 0.054 0.054 0.056 0.075 0.0560.037 0.036 0.037 0.036** 0.037

Variance equationConstant 4.0E-06 8.0E-06 5.4E-06 8.7E-06 6.1E-06

1.7E-06** 3.1E-06** 2.3E-06** 2.8E-06*** 1.8E-06***

ε2t−1 0.403 0.429 0.401 0.421 0.363

0.089*** 0.096*** 0.085*** 0097*** 0068***

�2t−1 0.665 0.620 0.670 0.609 0.654

0.055*** 0.064*** 0.050*** 0.063*** 0.048***

tx −1.4E-06 −9.0E-076.3E-07** 5.1E-07*

DUM Control −3.5E-06 −2.4E-062.1E-06* 1.4E-06*

log (EMBI) 1.3E-04 1.1E-043.8E-05*** 2.7E-05***

Obs 545 545 545 545 545Q(1) 0.12 0.13 0.14 0.18 0.27Q(6) 0.29 0.29 0.31 0.40 0.36Q(12) 0.41 0.42 0.43 0.51 0.48Q(24) 0.34 0.35 0.35 0.39 0.38Sample Weekly: September 1998–July 2008

Notes: Standard errors in italics.

* Significant at 10%.** Significant at 5%.

*** Significant at 1%.

nd partial autocorrelation functions of the error term. Eqs. (8)

ined by the statistical and economic significance of the coefficient

able 3ARCH model estimation for the Stock Price Index (IGBVC).

Dependent Variable: ( log(IGBVC)(1)

Mean equationConstant 0.004

0.002**

log (IGBVC)t−1 0.406

0.043***

Variance equationConstant 2.5E-04

7.8E-05***

ε2t−1 0.324

0.092***

�2t−1 0.390

0.140***

DUM Control

( log(EMBI)

Obs 547

Q(1) 0.10

0(6) 0.54

0(12) 0.58

0(24) 0.80Sample Weekly: September 1998–July 2008

otes: Standard errors in italics.* Significant at 10%.

** Significant at 5%.*** Significant at 1%.

3 estimated in Eq. (9). If capital controls reduce volatility the coef-

Tables 2–4 report the results of different estimations of Eqs.8) and (9), for TRM, IGBVC, and IDP respectively. The models arestimated using weekly data spanning from September 1998 to

(2) (3) (4) (5)

0.004 0.004 0.004 0.0040.002** 0.002** 0.002** 0.002**

0.398 0.399 0.402 0.4030.042*** 0.042*** 0.042*** 0.042***

1.9E-04 2.0E-04 1.9E-04 2.0E-046.6E-05*** 6.8E-05*** 6.5E-05*** 6.6E-05***

0.288 0.294 0.275 0.2760.089*** 0.089*** 0.086*** 0.085***

0.441 0.422 0.450 0.4410.139*** 0.142*** 0.133*** 0.134***

3.4E-05 2.8E-052.1E-05* 1.9E-05

1.0E-04 7.7E-056.4E-05 5.7E-05

1.3E-03 1.3E-037.8E-04* 7.9E-04*

547 547 547 5470.13 0.13 0.11 0.110.61 0.60 0.58 0.570.62 0.62 0.60 0.600.82 0.82 0.81 0.81

Table 4GARCH model estimation for the Public Debt Price Index (IDP).

Dependent variable: ( log (IDP)(D (2) (3) (4) (5)

Mean equationConstant 0.003 0.003 0.002 0.002 0.002

0.000*** 0.000*** 0.001*** 0.001*** 0.000***

AlogflDP),.! 0.172 0.172 0.172 0.165 0.1720.061*** 0.061*** 0.065*** 0.064** 0.062***

Alog(IDP)t.3 0.104 0.104 0.135 0.125 0.1000.055* 0.055* 0.052** 0.050** 0.053*

Variance equationConstant 4.5E-06 4.5E-06 7.4E-06 3.7E-06 6.7E-06

2.2E-06** 3.1E-06 2.9E-06** 1.8E-06** 3.8E-06***

ε2t−1 0.423 0.422 0.385 0.402 0.423

0.124*** 0.124*** 0.076*** 0.070*** 0.118***

�2t−1 0.607 0.608 0.592 0.624 0.585

0.078*** 0.080*** 0.063*** 0.049*** 0.082***

tx 1.1E-08 −1.9E-088.1E-07 4.6E-07

DUM Control −3.2E-06 −2.6E-062.2E-06 3.1E-06

Alog(EMBI) 1.1E-04 8.9E-053.4E-05*** 5.4E-05*

Obs 336 336 336 336 336Q(1) 0.92 0.92 0.94 0.97 0.91Q(6) 0.95 0.95 0.96 0.96 0.94Q(12) 0.45 0.45 0.54 0.52 0.43Q(24) 0.10 0.09 0.13 0.12 0.09Sample Weekly: January 2002–July 2008

Notes: Standard errors in italics.

Gmacci

anncsvcecr

tsrsiacrc

fisatt

itnteifursi

iiifttsas

* Significant at 10%.** Significant at 5%.

*** Significant at 1%.

une 2008 for the nominal exchange rate (TRM) and the stockarket price index, and since January 2002 for the public debt price

ndex.The first column of each table reports the estimation of a

ARCH(1,1) model that does not include additional controls (theost possible parsimonious model that yields white noise residu-

ls is presented). In columns (2) and (3) we control for the capitalontrols proxies (first we use the tax equivalent measure, then theapital controls dummy), and in columns (4) and (5) we control fornternational financial conditions (log(EMBI)).

Results reported in Table 2 show that capital controls have had statistically significant negative impact on the volatility of theominal Exchange rate. Results reported in columns (2)–(5) showegative and statistically significant coefficients, accompanying theapital controls proxies. Despite the fact that the coefficients aretatistically significant, the economic impact of capital controls onolatility is low. A one standard deviation increase in the capitalontrols tax equivalent measure (1.7) reduces the variance of thexchange rate between 1.2 and 1.8% depending on the specificationonsidered. An increase of the dummy variable from zero to oneeduces the variance in something between 2 and 2.6%.

Once again the volatility of the Exchange rate is closely linkedo International financial conditions. In all specifications the EMBIpread turns out to be positive and significant. According to theseesults a one standard deviation increase in the log of the EMBIpread (0.6) increases the variance of the nominal exchange raten something between 55 and 62% with respect to the estimatedverage of the variance. These results suggest that global finan-ial instability has severe impacts on the stability of the exchangeate, and these impacts are far more relevant than those of capital

Tables 3 and 4 show similar estimations for the IGBVC and IDP.n Table 3 the tax equivalent of capital controls appears significantn column 2, but this result is lost when controlling for international

nancial conditions in column 4. In Table 4 we do not find anyignificant evidence of capital controls affecting volatility. Asbove, international financial conditions captured in the change inhe log of the EMBI spread are positive and significant. Internationalurmoil increases the volatility of any kind of financial asset.

. Concluding remarks

Despite a long tradition with capital controls in Colombia, theres no evidence that supports their effectiveness. This paper exploreshe impact of capital controls from different perspectives. We findo significant evidence suggesting an impact of capital controls onotal capital flows, the composition of capital flows, and the realxchange rate. We do find some evidence suggesting a reductionn exchange rate volatility, though the impacts are not significantrom an economic point of view. Our findings raise doubt on thesefulness of capital controls in Colombia, not only to mitigateeal exchange appreciation, but also as a macro prudential tool,ince we find no evidence of their contribution to reduce foreignndebtedness.

Regarding the lack of effectiveness of capital controls, we arenclined to think that the existence of the large loopholes describedn the paper, explain our finding. During most of the period of theirmplementation, agents were able to transfer short term debt flowsrom affiliates abroad disguised as capital investment. To the extenthat this was a frequent practice, controlling short term debt flowshrough administrative policies was innocuous. The presence ofuch a loophole may explain the differences between our findingsnd the evidence found in Chile on the ability of capital controls tohare the term-profile of capital flows.

It is worthwhile noting the impact of external variableshroughout the exercises carried out in this paper. In all specifi-ation the global EMBI spread turns out to be significant. Externalnancial conditions are important determinants of fluctuations in

3 f Econ

ong and short term capital flows, of the real exchange rate, and ofhe volatility of asset prices.31 Finding a way to deal with external

31 This paper does not explore the determinants of capital flows to Colombia. Ref-rences on the underlying factors explaining capital flows to Colombia and otheratin American countries can be found in Izquierdo and Talvi (2008, 2009).

Variable Abbreviation Source

Real exchange rate index RER Banco de la Republica

Industrial production index IPI DANE

Capital flows CF Banco de la Republica

Short term capital flows ST CF Banco de la Republica

Foreign direct investment FDI Banco de la Republica

Terms of trade index TOT Banco de la Republica

EMBI global EMBI JP-Morgan

Tax equivalent of capital flows tx Banco de la Republica, NationPlanning Department and MiFinance

Nominal exchange rate NER Banco de la Republica

Public debt index IDP Corficolombiana

Stock exchange index IGBVC Bolsa de Valores de Colombia

Test statistic Critical value 5% Result

Log(IPI) −4.43c −3.410 Reject Ho

Log(RER) −2.14c −3.410 Do not rejeCF −4.11c −3.410 Reject Ho

ST CF −7.33 −2.860 Reject Ho

FDI −2.29c −3.410 Do not rejetx −1.45 −2.860 Do not rejeLog(TOT) −0.11c −3.410 Do not rejeLog(EMBI) −1.634 −2.860 Do not rejeLog(IPI)

Log(RER) −6.15 −2.860 Reject Ho

FDI −8.04 −2.860 Reject Ho

tx −6.02 −2.860 Reject Ho

Log(TOT) −9.25 −2.860 Reject Ho

Log(EMBI) −7.51 −2.860 Reject Ho

Ho: The variable has a unit root. The number or lags was chosen using the Hannan–Qui

H0:The variable is I(0). The band width is defined using the Bartlett kernel.c These tests include a trend in the auxiliary equation.

are a great deal for protecting themselves against inevitablend exogenous foreign shocks. Decisions on debt composi-ion, both in terms of currency and maturity, as well as on theevel of foreign indebtedness may be crucial to deal with harsh

oments.

ppendix A. Description of variables and sources

Frequency Definition

Monthly We use a multilateral real exchangerate

Monthly The index is constructed deflating thevalue of nominal industrial production,deflated using producer price indexes

Monthly Sum of net FDI and net short termcapital flows. Includes only privatecapital flows

Monthly Sum of short term net debt flows andnet portfolio flows

Monthly Net FDIMonthly Ratio of export to import prices.Monthly/weekly Spread between sovereign bond

returns and USA returnsalnistry of

Monthly/weekly Captures the impact of capital controls(see paper)

Monthly/weekly Weighted average of sales andpurchases of foreign exchange

Weekly Weighted average of prices ofgovernment bonds

Weekly Measures price variation of the mostrepresentative stocks

ppendix B. Unit root tests

Test statistic Critical value 5% Result

0.65c 0.146 Reject Hoct Ho 1.40c 0.146 Reject Ho

0.34c 0.146 Reject Ho0.33 0.463 Reject Ho

ct Ho 0.59c 0.146 Reject Hoct Ho 1.11 0.463 Reject Hoct Ho 1.04 0.146 Reject Hoct Ho 5.24 0.463 Reject Ho

0.13 0.463 Do not reject Ho0.41 0.463 Do not reject Ho0.03 0.463 Do not reject Ho0.01 0.463 Do not reject Ho0.05 0.463 Do not reject Ho0.34 0.463 Do not reject Ho0.46 0.463 Do not reject Ho

nn criteria.

f Economics and Finance 51 (2011) 319– 338 331

Saikkonen & Luktepohl Testr0 LR 95% 99%

0 152.98 83.80 92.261 95.92 59.95 67.242 48.56 40.07 46.203 16.63 24.16 29.114 6.23 12.26 16.105 0.22 4.13 6.93

Saikkonen & Luktepohl Testr0 LR 95% 99%

0 295.22 111.65 121.281 151.12 83.8 92.262 93.79 59.95 67.243 48.42 40.07 46.24 15.9 24.16 29.115 5.84 12.26 16.16 0.16 4.13 6.93

(CF) (log(RER)) (log(IP))

6 [−1.008] −158.639 [−0.494] 0.034 [1.165] 0.095 [1.319]2 [−0.247] 430.374 [0.381] −0.114 [−1.113] −0.438 [−1.721]

[5.699] 123.133 [0.869] 0.017 [1.428] −0.018 [−0.558] [−1.512] −0.312 [−3.653] 0.000 [0.338] 0.000 [−1.655]

[1.030] 2118.062 [2.154] 0.526 [6.351] 0.644 [2.899] [1.955] −600.762 [−1.575] 0.051 [1.599] −0.058 [−0.676] [0.421] 208.488 [2.004] −0.023 [−2.638] 0.015 [0.648]

[3.581] 1383.276 [0.664] 0.203 [1.155] 1.831 [3.890]

7 [−3.535] 57.358 [0.949] −0.001 [−0.117] −0.083 [−6.086]2.144] −356.023 [−1.908] −0.012 [−0.767] 0.235 [5.579]

[3.207] 0.001 [1.756] 6.096 [5.279] 5.271 [4.993] [2.066] 0.001 [2.645] 2.147 [5.031] −0.218 [−0.558]

((ST CF) ((FDI) (flog(RER)) ((log (IP))

−32.8420 [−0.204] −89.0490 [−0.290] 0.0370 [1.278] 0.0840 [1.173]234.6190 [0.408] 287.2800 [0.265] −0.1180 [−1.164] −0.4760 [−1.865]−67.3100 [−0.864] 205.5390 [1.404] 0.0120 [0.927] −0.0210 [−0.601]−0.1580 [−1.644] −0.2000 [−1.109] 0.0000 [1.188] 0.0000 [−0.201]−0.1500 [−3.076] −0.1100 [−1.199] 0.0000 [0.254] 0.0000 [−1.684]−454.3930 [−0.905] 2182.4680 [2.313] 0.5020 [6.141] 0.7120 [3.205]−320.6820 [−1.644] −245.0040 [−0.668] 0.0530 [1.653] −0.0620 [−0.713]−32.5660 [−0.608] 251.0290 [2.494] −0.0230 [−2.675] 0.0140 [0.606]−2712.3020 [−2.631] 4404.3670 [2.274] 0.1930 [1.147] 1.9750 [4.331]

20.647 [0.663] 30.523 [0.521] −0.001 [−0.241] −0.083 [−6.045]748.692 [5.739] −1052.662 [−4.295] 0.013 [0.591] 0.223 [3.862]−19.549 [−2.858] 9.703 [0.755] −0.002 [−1.817] −0.011 [−3.507]

−0.005 [−5.272] 0.000 [−0.367] −2.941 [−3.458] 6.662 [8.465]−0.001 [−4.047] 0.000 [5.358] 0.030 [0.141] 0.265 [1.361]0.016 [2.482] 0.007 [2.599] 26.914 [4.500] −1.959 [−0.354]

A. Concha et al. / The Quarterly Review o

ppendix C. Cointegration tests

Model includes: log (EMBI), log (TOT), Tx, Capital lows, log (RER), log(IP)Lags: 1Deterministic components: ConstantJohansen Trace Testr0 LR 95% 99%

0 173.01 103.68 112.88

1 113.64 76.81 84.84

2 60.49 53.94 60.81

3 27.56 35.07 40.78

4 14.59 20.16 24.69

5 5.65 9.14 12.53

Model includes: log(EMBI), log(TOT), Tx, FDI, ST CF, log(RER), log(IP)Lags:1Deterministic components: ConstantJohansen Trace Test

r0 LR 95% 99%

0 323.88 134.54 144.91

1 170.83 103.68 112.88

2 111.52 76.81 84.84

3 60.31 53.94 60.81

4 27.1 35.07 40.78

5 14.11 20.16 24.69

6 5.44 9.14 12.53

ppendix D. VEC estimation

Model with aggregate capital flowsEndogenous variable (log (EMBI)) (log(TOT)) (tx)

((log (EMBI))t−1 0.311 [3.476] – −0.17((log (TOT))t−1 – 0.159 [1.779] −0.15((tx)t−1 – – 0.444((CF)t−1 – – 0.000((log (IPI))t−1 – – 0.557((log (RER))t−1 – – 0.410Power Dummy – – 0.024Constant −0.006 [−0.837] 0.004 [1.684] 4.097Loading coefficientsec1t−1 – – −0.11ec2t−1 – – 0.22 [Estimated cointegration relations

1 0 0.3450 1 0.082

LM test for autocorrelation1st order 0.19006th order 0.141612th order 0.1274

Model with disaggregated capital flowsEndogenous variable ((log (EMBI)) ((log (TOT)) ((Tx)

((log (EMBI))t−1 0.3110 [3.475] – −0.1440 [−0.829]

((TOT)t−1 – 0.1590 [1.776] −0.0920 [−0.149]

((Tx)t−1 – – 0.4250 [5.099]

((STCF)t−1 – – 0.0000 [−0.890]

((FDI)t−1 – – 0.0000 [−1.259]

((log (RER))t−1 – – 0.3910 [0.727]

((log (IP))t−2 – – 0.4150 [1.986]

Power Dummy – – 0.0190 [0.330]

Constant −0.0060 [−0.838] 0.0040 [1.684] 3.7640 [3.412]

Loading coefficientsec1t−1 – – −0.122 [−3.647]

ec2t−1 – – 0.314 [2.249]

ec3t−1 – – −0.023 [−3.097]

Estimated cointegration relations1 0 0

LM test for autocorrelation1st order 0.07316th order 0.069712th order 0.0852

-statistics in brackets.

3 f Economics and Finance 51 (2011) 319– 338

A ons of residuals

ppendix E. Autocorrelation and partial autocorrelation functi

Model with aggregate capital flows.

f Economics and Finance 51 (2011) 319– 338 333

3 s and Finance 51 (2011) 319– 338

34 A. Concha et al. / The Quarterly Review of Economic

ppendix F. Distribution of errors: Kernel density estimation

odel with aggregate capital flows; Model with disaggregate capital flows.

s and Finance 51 (2011) 319– 338 335

A. Concha et al. / The Quarterly Review of Economic

ppendix G. Forecast error variance decomposition

odel with aggregate capital flows; Model with disaggregate capital flows.

ppendix H. (part a)–Robustness 1: Impulse response functions – model with aggregate capital flows: assuming industrialroduction is exogenous

ote: Dotted lines are 95% Hall confidence intervals, and dashed lines are Efron confidence intervals.

ppendix I. (part b)–Robustness 2: Impulse response functions – Model with aggregate capital flows: alternative ordering ofariables

Note: Dotted lines are 95% Hall confidence intervals, and dashed lines are Efron confidence intervals.

3 f Economics and Finance 51 (2011) 319– 338

eferences

rbelaez, María A. & Steiner, Roberto. (2009). Volatilidad cambiaria en Colombia:cuantificación y determinantes. Mimeo: Fedesarollo.

ianchi, Javier. (2009). Overborrowing and systemic externalities in the business cycle.Mimeo University of Maryland.

alvo, Guillermo. (2010). Controls on cyclical capital inflows; some skeptical notes.Mimeo: Columbia University.

árdenas S Mauricio & Barrera S Felipe. (1997). On the effectiveness of capital con-trols: the experience of Colombia during the 1990s. Journal of DevelopmentEconomics, 54.

ardoso S Eliana & Goldfajn, Ilan I. (1998). Capital flows to Brazil: the endogeneityof capital controls. Staff Papers-International Monetary Fund, 45, 161–202.

lements, B., & Kamil, H. (2009) Are capital controls effective in the 21st century?The recent experience of colombia, IMF WP/09/30.

e Gregorio, J., Edwards, S., & Valdés, R. (1998) “Capital controls in Chile: an assess-ment”. Mimeo.

e Gregorio, J., Edwards, S. & Valdés, R. (2000). Controls on capital inflows: do theywork? Journal of Development Economics, 63, 59–83.

dwards, Sebastian. (1999). How effective are capital controls? Journal of EconomicPerspectives, 13(4), 65–84.

dwards, S., & Rigobon, R. (2005), “Capital controls, exchange rate volatility andexternal vulnerability”, National Bureau of Economic Research, Working Paper11434.

ichengreen, Barry, Tobin, James & Wyplosz, Charles. (1995). Two cases for sand inthe wheels of international finance. The Economic Journal, 105.

ómez, C. (2007) “Decisiones de la Junta Directiva del Banco de la República sobrepolíticas monetaria y cambiaria”, Banco de la República, Reportes del Emisor.No. 98.

enry, Peter Blair. (2007). Capital account liberalizations: theory, evidence, andspeculation. Journal of Economic Literature, XLV, 887–935.

ADB. (2005). Unlocking credit: the quest for deep and stable bank lending. WashingtonDC: Johns Hopkins University Press.

zquierdo, A. & Talvi, E. (2009). Policy trade-offs for unprecedented times. Washington,DC: Inter-American Development Bank.

zquierdo, A., Izquierdo, A. & Talvi, E. (2008). All that glitters may not be gold.Assessing Latin America’s recent macroeconomic performance. Washington, DC:Inter-American Development Bank.

aplan, E., & Rodrik, D. (2001) “Did the Malaysian capital controls work?” NationalBureau of Economic Research, Working Paper 8142.

orinek, A. (2009). Regulating capital flows to emerging markets: an externality view.University of Maryland. Mimeo.

rugman, P. (1987). The narrow moving band, the Dutch disease and the competitiveconsequences of Mrs Tatcher. Journal of Development Economics, 27.

ópez-Mejía, A. (1999) Large capital flows: a survey of the causes, consequences andpolicy responses. IMF, Working Paper No. 17.

ütkepohl, H. & Kratzig, M. (2004). Applied time series econometrics. New York, UnitedStates: Cambridge University Press.

campo, J.A., & Tovar, C. (1999) Price-based capital account regulations: the Colom-bian experience, CEPAL, Revista de la CEPAL No. 81, Santiago de Chile.

campo, J.A., & Tovar, C. (2003) La experiencia colombiana con los encajes a losflujos de capital, CEPAL, Serie Financiamiento del Desarrollo, Santiago de Chile.

incón, H. (2000) Efectividad del Control a los Flujos de Capital: Un ReexamenEmpírico de la Experiencia Reciente en Colombia, Banco de la República, Bor-radores de Economía No. 132.

ocha, R., & Mesa, F. (1998) Flujos internacionales de capital: Un enfoque de portafo-lio” DNP, Archivos de Macroeconomía, Documento 78.

aldés-Prieto, S. & Soto, M. (1996). Es el control selectivo de capitales efectivo enChile? Su efecto sobre el tipo de cambio real. Cuadernos de Economía, 98, 77–108.

illar, L., & Rincón, H. (2000) “The Colombian economy in the nineties: capital flowsand foreign exchange regimes, Banco de la República”, Borradores de Economía,no. 149, Bogotá.

An assessment of another decade of capital controls in Colombia: 1998–2008

Documents

Transcript of An assessment of another decade of capital controls in Colombia: 1998–2008

Student Affairs - Just another WordPress site

Census 1998

Contemporary Latvian Theatre - A Decade Bookazine

1998. Mangrove Monitor Lizards

DECS Order no. 6 s. 1998 Jan 22 1998

AN INCREDIBLE DECADE FOR THE SMARTPHONE

Publicación Octubre 1998 - ONAPI

"Yet Another Crisis of the Book"

Hanoi, From a city to another

For Another Europe Carchedi

Another car loan victim - static.dvidshub.net

Computational Biology as Another 'Scientiific' Clusterfuck

ONE DECADE OF EDUCATION FOR ALL - CiteSeerX

"Another Darkchild Classic:" Phonographic Forgery and ...

Another epistemic culture - bonndoc

Another Year (cinefórum)

Site Specificity: Miwon Kwon's "Another Place"

Another book of verses for children

ANOTHER NINETY-FIVE - LarryJones.ca - Larry Jones

Strasbourg, April 1998 - Coe