The Multiple Effects of Capital Controls

Zehri, Chokri Article The Multiple Effects of Capital Controls Comparative Economic Research. Central and Eastern Europe Provided in Cooperation with: Institute of Economics, University of Łódź Suggested Citation: Zehri, Chokri (2020) : The Multiple Effects of Capital Controls, Comparative Economic Research. Central and Eastern Europe, ISSN 2082-6737, Łodz University Press, Łodz, Vol. 23, Iss. 4, pp. 169-185, https://doi.org/10.18778/1508-2008.23.33 This Version is available at: https://hdl.handle.net/10419/259254 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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Central and Eastern Europe Volume 23, Number 4, 2020 http://dx.doi.org/10.18778/1508-2008.23.33 Chokri Zehri The Multiple Effects of Capital Controls Chokri Zehri Assistant professor of economics, Prince Sattam Bin Abdulaziz University, College of Sciences and Humanities in Al-Sulail, Department of Business Administration, Al-Sulail, Saudi Arabia, e-mail: [email protected] Abstract Capital controls are seen as a means to promote financial stability or improve macro‑ economic adjustment in economies with nominal rigidities and suboptimal monetary policy. Such controls may take various forms, including explicit or implicit taxation of cross‑border financial flows and dual or multiple exchange rate systems. Using a quarter dataset on capital controls actions in 27 emerging economies from 2010 to 2018, the study analyzes the effectiveness of capital controls (CCs) along different angles. Since the 2008 financial crisis, strengthening capital controls has allowed more monetary policy autonomy and exchange rate stability, verifying the Mundell‑Flem‑ ing trilemma model. Following CCs, the results show that accumulating international reserves may compensate for the loss of inflows and lead to more effective policies. Tighter CCs on inflows cause significant spillovers, specifically in the conditions of li‑ quidity abundance. These spillovers originate from the problem of policy coordination of emerging economies and are mainly caused by capital controls being used as an instrument to manage capital flows. For governments that have to manage the risks associated with inflow surges or disruptive outflows, capital controls need to play a key role. Keywords: capital, controls, flows, impacts JEL: F21, F32, F41, F42 Introduction Itis important tounderstand international capital flows toenhance macroeconom‑ ic stability and design effective economic policies. Effective capital controls (CCs) re‑ duce the volume ofcapital flows, alter the composition from short‑term tolong‑term capital flows, make exchange rates more stable, and allow monetary policy autonomy 170 Chokri Zehri (Magud etal.2018, p.114). Previous studies highlighted various problems concerning CCs, but itis unclear whether these controls achieve their objective ornot (Korinek 2011, p.76; Bianchi and Mendoza 2011, p.45; Benigno etal.2013, p.73). The identified problems include the absence ofatheoretical framework todefine the macroeconomic consequences ofthese controls, the heterogeneity between countries that apply CCs, and the success ofthese restrictions. Several studies have also identified the difficulties that occur due toisolating the direct effect ofCCs, which limits the success ofcapital flows and their objectives (Fernandez etal.2015, p.82; Forbes etal.2015, p.32; Alfa‑ ro etal.2017, p.112). CCs are used incountries all around the globe, but their effectiveness isstill not clear. Itcomplicates the development ofastandard ofbest practices toaccomplish the influential regulation ofinternational capital flows due tothe specific character‑ istics ofeconomies and different market responses (Forbes etal.2015, p.41). There are two aspects ofstudying the effectiveness ofCCs: (a) actions oncapital control and (b)achieving macroeconomic objectives (autonomy ofmonetary policy, reduction ofexchange rate pressures, etc.). The present study discusses the impact ofcontrols onemerging markets. After the Great Recession of2008, several economies used restrictions, especially onshort term capital inflows, while others increased restrictions (Fernandez etal.2015, p.61). This study isassociated with the studies ofmonetary policy and exchange policy ininflu‑ encing the nature ofthe financial crisis. Recently, monetary policy has been restricted bythe global financial cycle under aflexible exchange rate regime when capital flow management ispreferable tomaintain monetary autonomy, and there isfree capital mobility (Rey 2015, p.83; Passari and Rey 2015, p.22). Optimal CCs and monetary pol‑ icy were explored with small, open countries, considering risk premium shocks (Farhi and Werning 2014, p.15). Those studies reported that CCs retain monetary autonomy inafixed exchange rate and work astrade manipulation inaflexible exchange rate regime. Exchange rate policies are beneficial tolower the severity ofafinancial crisis beyond CCs (Benigno etal.2016, p.31; Chamon and Garcia 2016, p.152). Likewise, Devereux, Young, and Yu(2017) showed that CCs can beconsidered state‑improving tools when optimally merged with monetary policy inthe presence ofpolicy commit‑ ment. Many older studies onCCs focused onthe incompatibility triangle, soCCs were usually related tothe hope ofkeeping adegree ofautonomy ofthe monetary policy while applying fixed exchange regimes. Inthe last several years, some emerging econ‑ omies (EEs) have tended touse amore flexible exchange rate. The fear offloating will cause these countries tointervene massively onthe exchange markets orto vary their director rate toprevent huge fluctuations inthe exchange rate. Wecontribute toprevious empirical studies intwo ways. First, weuse arecent, large dataset oncapital control acts, which allow usto more exactly detect the policy whose efficiency isevaluated. Most ofthe previous studies onthe effectiveness ofCCs used infrequent data, usually annual.Capital control measures thus used are less precise, and they suffer from two essential shortcomings: they donot reflect the fair intensi‑ 171 The Multiple Effects of Capital Controls ty oftheir application among countries, and they are often confused with other pol‑ icies simultaneously applied with CCs. The use ofquarterly data inthis study allows for alarger time interval and allows for amore correct analysis ofthe actions taken bypolicymakers. Second, the effectiveness ofCCs isexamined using amodel that regroups the com‑ ponents ofthe monetary policy trilemma, which indicates that itis difficult touse afixed exchange rate, together with anindependent monetary policy and anopen capital account. These components are usually studied independently. Amajor con‑ tribution ofthe paper isto regroup the three elements ofthe incompatibility triangle into one model. The incompatibility triangle framework also shows that the dejure and defacto changes inthe opening ofacapital account are related (Rebucci and Ma2019, p.35). This ishow wecan examine whether the applied controls are effective from this incompatibility triangle. Thus, using apanel VAR model, wetest whether capital markets affect both monetary policy autonomy and changes inthe exchange rate. Aspresented inseveral studies, CCs are endogenous, which highlights the re‑ current changes inthese controls among countries, and, therefore, wewill know their repercussions onother macroeconomic policies. Tothe best ofour knowledge, there isno previous study that used apanel VAR approach tostudy the repercussions ofCC changes onmonetary and exchange policies. Asregards CC effects, weanalyze domestic and multilateral impacts. Domestical‑ ly, our main finding isthat byreducing capital inflows, CCs make itpossible tobet‑ ter stabilize the economy. Itallows more independence tomonetary policy and allows less pressure onthe exchange policy atwhich the exchange rate manifests slight fluc‑ tuations. Empirical evidence shows that EEs accumulated excessive international reserves after the 2008 crisis. Our study has shown that despite the strict capital controls ap‑ plied byseveral emerging countries after the crisis, itdid not prevent the accumula‑ tion ofreserves. The latter supported the decisions ofmonetary policy and exchange rate policy. Tothe best ofour knowledge, few previous studies have highlighted the association between capital control actions with the accumulation ofinternational re‑ serves (Jeanne 2016, p.52; Korinek 2018, p.86). For the multilateral effects, the study presents anunderstanding ofthe spillovers that may happen following restrictions applied byacountry. Other countries will beaf‑ fected after the migration ofcapital flows totheir frontiers. Little empirical evidence exists onthis spillover effect (Forbes etal.2017, p.112; Lambert etal.2011, p.165). Weare among the first todemonstrate empirically these policy changes towards cap‑ ital controls asareaction tothe early policy ofanother country which has already ap‑ plied similar controls. Our paper isorganized asfollows. After presenting the literature review ofthe ef‑ fectiveness ofCCs inSection 2, wepresent the data and methodology inSection 3. The results ofthe model regressions are presented inSection 4. The last section gives conclusions. 172 Chokri Zehri Literature review Multiple effects on monetary and exchange policies The theoretical and empirical literature onthe effectiveness ofCC onmonetary and exchange policies has several methodological shortcomings. There are several criti‑ cisms ofthe indexes used toreflect the intensity ofCC. Itis often difficult toseparate the effects caused bythe controls from the effects caused byother macroeconomic policies, such asthe effectiveness ofprudential supervision. CCs have been successful indifferent countries; however, the degree ofsuccess isnot equal for all countries. The empirical literature shows multiple impacts ofCCs onproxy variables ofmon‑ etary and exchange policies. Some recent studies have shown evidence that these con‑ trols can effectively affect the monetary and exchange policies under some macroeco‑ nomic conditions, and they also can protect economies from external shocks (Pasricha etal.2018, p.176; Magud etal.2018, p.51). Some studies focused onthe macroeco‑ nomic framework inwhich CCs are instituted. Among these studies, Bayoumi etal. (2015) studied 37 countries that introduced outflow restrictions from 1995–2010. They found evidence that capital outflow restrictions reduce the pressure onboth policies under certain conditions. These conditions include strong macroeconomic funda‑ mentals (growth rate, inflation, and fiscal and current account balances), good institu‑ tions (World Bank Governance Effectiveness Index), and existing restrictions (intensi‑ ty ofCCs orcomprehensiveness). When none ofthe three conditions are met, controls will fail tosupport these policies. Furthermore, some studies suggest that controls are more effective inadvanced countries than inothers, perhaps because ofthe better quality ofinstitutions and regulations (Binici etal.2010). Some recent studies (Pasricha etal.2018; Magud etal.2018) analyzed the condi‑ tions ofsuccess ofcapital controls and especially their impacts onthe country that applies these controls compared tocountries that did not apply these restrictions. Pasricha etal. (2018) used arecent frequency dataset oncapital control instruments in16emerging market economies from 2001 to2012. They give novel evidence onthe domestic and multilateral impacts ofthese instruments. Increases infinancial liber‑ alization constrain monetary policy autonomy and decrease exchange rate instability, confirming the incompatibility trilemma. Magud etal. (2018) presented ameta‑anal‑ ysis ofthe literature onCCs, seeking tostandardize the results ofnearly 40 empirical studies. They build two indices ofcapital controls: the Capital Controls Effectiveness Index and the Weighted Capital Controls Effectiveness Index. Their results show that CCs oninflows seem tomake monetary policy more independent, and they alter the composition ofcapital flows (Zehri 2020, a); there isless evidence that they reduce real exchange rate pressures. Kim and Yang (2012) determined that afixed exchange rate allows CCs tosupport the independence ofthe monetary policy. This impact isclear‑ er with wide and long term CCs. 173 The Multiple Effects of Capital Controls Klein and Shambaugh (2015) found that economies with large CCs are more cov‑ ered concerning external monetary shocks. Meanwhile, Liu and Spiegel (2015) showed that the wide use ofCCs allows countries tomaintain adesired interest rate differen‑ tial between domestic and foreign markets. However, these strict controls did not have any link with the currency appreciation detected insome countries intheir sample. Ito, McCauley, and Chan (2015) studied asmall open economy and focused onsimple policy rules, while Devereux etal. (2019) investigated the optimal monetary policy and optimal CC. Amodel with fixed exchange rates, downward nominal wage rigidities, and free capital mobility was presented byBayoumi etal. (2015), where anoptimal devaluation eliminates the effects ofthe wage rigidity. Table 1 summarizes the results ofmost studies onthis issue and shows that the “Unclear” effect dominates the findings. Table 1. Summary of studies’ results Study Reducing Real Exchange Rate Pressure Autonomy of Monetary Policy Control on Inflows Brazil Unclear Unclear Chile Unclear Unclear Colombia Unclear Unclear Malaysia (1989) Yes Yes Malaysia (1994) Unclear Yes Thailand Unclear Unclear Malaysia (1998) Yes Yes Control on Outflows Brazil Yes Unclear Chile Unclear Yes Colombia Yes Unclear Thailand Unclear Unclear Multi‑country studies Unclear Unclear Source: author’s own elaboration. Indexes of capital controls Itis difficult togive anexact measure ofCC. The pre–2008 crisis literature utilizes in‑ dexes that measure the degree ofcapital restrictions. These indexes usually serve toset the extent ofrestrictions (the kind oftransactions controlled) and then define what isthe most appropriate when evaluating the effectiveness ofcontrols. Many improve‑ ments inmeasuring CCs have been made inthe recent literature. The relevant novelties ofthese studies gather data onvariations ininstitutional arrangements (Edison and Warnock 2003, p.63; Ocampo, Spiegel and Stiglitz 2008, p.23; Qureshi, Ostry, Ghosh, and Chamon 2011, p.91). The advantage ofthis method isthat itprecisely determines 174 Chokri Zehri the type ofpolicy action that isconsistent with the time ofthe action. Asdiscussed inthe introduction, the puzzle ofthe similarities ofpolicy effects over time and across EEs continues toappear with this approach. Older studies utilized diverse approaches toimprove the distinction ofcapital con‑ trol impacts. These approaches can bearranged into two classes: the first, called “split‑ ting‑the‑announcements” method, aims todefine similar and homogeneous macroe‑ conomic policies. Quantitatively, these policies must have relatively identical impacts, especially oncapital inflows. This needs torearrange the controls established inmore homogeneous subgroups ofcontrols. The second aims tocompute the opportunity cost ofcertain variations inregulation. This can beachieved bycomputing atax rate ofthe control actions (Benigno etal.2016, p.31; Forbes etal.2016, p.162; Baba and Kokenyne 2011, p.151). Unfortunately, this effective tax isonly applied for acertain type ofpolicy tool (e.g., unremunerated reserve requirements), which form aminori‑ ty ofthe actions made byEEs. Inthis study, wecombine the advantages ofboth approaches byemploying indexes constructed recently insome empirical studies (Fernández etal.2016; Chinn and Ito 2008). Fernández etal. (2016) presented anew data set ofCCs divided into ten asset categories along with the structure ofinflows and outflows. These indexes were applied to100 economies over the period 1995–2013. Our study uses the first three indexes among the ten asset categories ofCC: ka, kai, and kao (controls applied respectively togross flows, inflows, and outflows). Chinn and Ito (2008) create anew index that measures the extent ofopenness incapital account transactions, this index istermed kaopen, and itwas regularly updated (the last update isthere of2017). Table2 sum‑ marizes these indexes. Table 2. Capital Control Indexes Index Definition Source ka Overall restrictions index (all asset cate‑ gories) Fernández, Klein, Rebucci, Schindler, and Uribe (2016) “Capital Control Measures: A New Dataset” kai Overall inflow restrictions index (all asset categories) kao Overall outflow restrictions index (all asset categories) kaopen The extent of openness in capital account transactions Chinn, M. D., and H. Ito, The Chinn‑Ito Index, http://web.pdx.edu/~ito/Chinn‑Ito _website.htm, last updated July 2017 Source: author’s own elaboration. The principal distinction between both indexes isthat the kaopen index isalarg‑ er measure ofcapital account liberalization, including regulations tothe current ac‑ count ofthe balance ofpayments and the foreign exchange market, while the dataset ofFernández etal. (2016) issmaller, focusing especially oncapital flows. However, ithas further details onthe intensity ofcontrols, with distribution data onten asset 175 The Multiple Effects of Capital Controls categories. The indexes ofFernández etal. (2016) make itpossible todetect more time change when countries set regulations than the Chinn‑Ito index. These indexes ofChinn and Ito (2008) and Fernández etal. (2016) capture the cross‑country changes inthe level ofcapital account liberalization; unfortunately, how‑ ever, they are smaller inthe time scope due tothe way they are built and their annual frequency. Toovercome these shortcomings, wepropose duplicating the annual value ofeach ofthese indexes in4 equal sub‑values, asif they were quarterly data. This does nothing todiminish the robustness ofthis analysis since CCs are often long‑term po‑ litical instruments. This change will allow consistency with the frequency ofthe other variables inthe model, which are quarterly. Data and methodology Capital control instruments may affect aset ofvariables, but atthe same time, they can beaffected bythese variables. Thus, weuse apanel VAR model. This model includes asystem ofequations inwhich the dependent variables will berepresentative ofCCs, capital flows, monetary policy, and exchange rate policy. Our sample includes 27 EEs that used CCs over the period 2010Q1 to2018Q4. Weuse the interest rate differential asaproxy for monetary policy independence (rate variable). Acountry that maintains adifferential ofthe domestic and external interest rate makes itpossible toact onthe volume ofcapital inflows and, consequent‑ ly, tofreely define adomestic interest rate without having aconstraint with the exter‑ nal rate. The standard deviation ofthe bilateral exchange rate (tothe US $) isaproxy used for the volatility ofthe exchange rate (the xchge variable). Toseparate the effect ofthe capital flows variables, wedistribute them between inflows (the infl variable) and outflows (the outf variable), and for the global flows, weuse the “gross” variable. Also, weinclude aset ofexogenous variables tocontrol for drivers that can influence the endogenous variables (the short‑term interest rate inthe United States (us_rate), the price ofoil (oil), real gross domestic product growth inthe United States (gdp) and international reserves (ir). The impact ofCCs used bythe country can affect the inflows toother countries, and these spillover effects are presented bythe variable (spill). Apanel VAR isthe baseline model. The independent variables ofthis model are all considered endogenous and are explained bythe set ofexogenous variables previous‑ ly cited. The model iswritten asfollow: Yi,t = α0 + Z1yi,t−1 +…+ Znyi,t−n + W1xi,t−1 +…+ Wmxi,t−m + FEi + £i,t (1) Our model isdescribed byasystem ofequations, where Ytis the vector ofendog‑ enous variables for country i, x t is the vector ofexogenous variables common toall countries, £ i,t isthe vector ofresiduals, and “Z” and “W” represent the coefficients for the endogenous and exogenous variables, respectively. Factors that have omitted 176 Chokri Zehri and that can affect the dynamics ofthe model (e.g., administration efficiency) are re‑ grouped inthe term FEi, which represents the country fixed effects (FE variable). Toexamine ifthe cross‑sectional changes inCC can bewell used, weregress the model with the use ofthe Chinn‑Ito (Chinn and Ito 2008) and Fernández etal., (2016) indexes. All ofthe explicative variables are introduced with one lag difference. Addi‑ tionally, wepropose aregression with the levels ofthese indexes and analyze the ef‑ fect ofashock tothem. Results Inthis section, wepresent the evidence from the estimation ofthe PVAR model for the period 2010:1–2018:4. Weanalyze ifvariations inCCs affect monetary and exchange rate policies and are under the forecasts ofthe incompatibility triangle. Wealso inves‑ tigate the impact oninternational reserves and the multilateral effects. Weexamine the effect ofashock onCC, considered itas aninside policy instrument, and ondifferent national policy variables, including differential interest rate, exchange rate volatility, capital movements, international reserves accumulation, and spillover effect. The results ofthe PVAR analysis are displayed inTable 3. They show apositive and significant coefficient ofthe changes in“ka” and “kaopen” inthe equation inwhich the differential interest rate isthe independent variable. These findings show that chang‑ es incapital controls raise the differential ofthe interest rate and subsequently allow more autonomy ofthe monetary policy. The two other indexes ofcapital controls (kai and kao) donot affect the monetary policy. The results present negative and signifi‑ cant coefficients ofthe changes in“ka” and “kaopen” inthe equation ofexchange rate volatility (compared tothe US dollar) suggesting that capital controls support the sta‑ bility ofthe exchange rate policy, i.e., more liberalization isconducive tohigher ex‑ change rate instability. Table 3. PVAR Analysis Coefficient Std. Err. ZP>|z| [95% Conf. Interval] rate ka 0.019 0.055 2.17 0.006 –0.998 0.118 kai 0.049 0.767 0.58 0.365 0.915 3.157 kao 0.035 0.858 0.15 0.247 0.758 2.549 kaopen 0.541 0.467 3.58 0.000 1.625 4.457 xchge –0.227 –0.569 –4.00 0.000 –0.339 –0.116 gross 0.041 0.467 0.58 0.365 1.625 4.457 spill 0.045 0.658 1.15 0.247 0.958 3.549 ir 0.7195 0.085 2.44 0.000 –0.738 0.218 183 The Multiple Effects of Capital Controls Benigno,G., Chen,H., Otrok,C., Rebucci,A., Young, E.R.(2016), Optimal capital controls and real exchange rate policies: Apecuniary externality perspective, “Jour‑ nal ofMonetary Economics”,84, pp.147–165. http://dx.doi.org/10.1016/j.jmoneco .2016.10.004 Bianchi,J., Mendoza, M.E.G.(2011), Overborrowing, Financial Crises and “Macro‑Pru‑ dential’Policy?, No.11–24, International Monetary Fund. https://doi.org/10.5089/97 81455216710.001 Bianchi,J., Hatchondo, J.C., Martinez, L.(2018), International reserves and rollover risk, “American Economic Review”,108(9), pp.2629–2670. http://dx.doi.org/10.12 57/aer.20140443 Borio,C., Gambacorta, L.(2017), Monetary policy and bank lending inalow inter‑ est rate environment: diminishing effectiveness?, “Journal ofMacroeconomics”,54, pp.217–231. http://dx.doi.org/10.1016/j.jmacro.2017.02.005 Chamon,M., Garcia, M.(2016), Capital controls inBrazil: effective?, “Journal ofIn‑ ternational Money and Finance”,61, pp.163–187. http://dx.doi.org/10.1016/j.jimon fin.2015.08.008 Chinn, M.D., Ito, H.(2008), Anew measure offinancial openness, “Journal ofCom‑ parative Policy Analysis”,10(3), pp.309–322. http://dx.doi.org/10.1080/138769808 02231123 Devereux, M.B., Young, E.R., Yu, C.(2017), Capital Controls, Monetary Policy, and Sudden Stops. http://dx.doi.org/10.1016/j.jmoneco.2018.07.016 Edison, H.J., Warnock, F.E.(2003), Asimple measure ofthe intensity ofcapital con‑ trols, “Journal ofEmpirical Finance”,10(1–2), pp.81–103. http:// dx .doi .org /10 .10 16 /S0 9 27 ‑53 9 8 ( 0 2 ) 0 0 0 55 ‑5 Farhi,E., Werning, I.(2014), Dilemma not trilemma? 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Articles inpress. https:// doi.org/10.1002/ijfe.2182 Streszczenie Wielorakie skutki kontroli przepływu kapitału Kontrola kapitału jest postrzegana jako metoda zapewnienia stabilności finansowej lub poprawy programu dostosowań makroekonomicznych w gospodarkach, w któ‑ rych występują sztywności nominalne i nieoptymalna polityka pieniężna. Taka kon‑ trola może przybierać różne formy, w tym jawnego lub ukrytego opodatkowania transgranicznych przepływów finansowych oraz wprowadzenia systemu podwójnych lub wielokrotnych kursów walutowych. Wykorzystując kwartalne dane dotyczące kontroli kapitału w 27 gospodarkach wschodzących w latach 2010–2018, przeanali‑ zowano skuteczność kontroli kapitału pod różnymi kątami. Od kryzysu finansowego w 2008 r. wzmocnienie kontroli kapitału umożliwiło zwiększenie autonomii polityki pieniężnej i stabilności kursu walutowego, zgodnie z założeniami modelu Mundella‑ ‑Fleminga. Wyniki analizy pokazują, że gromadzenie rezerw międzynarodowych może rekompensować utratę wpływów i prowadzić do realizacji bardziej skutecznej polityki. Silniejsza kontrola napływu kapitału powoduje znaczne skutki uboczne, szczególnie w warunkach nadmiernej płynności. Te zewnętrzne efekty wynikają z problemu koor‑ dynacji polityki gospodarek wschodzących i są głównie spowodowane przez kontrolę kapitału stosowaną jako instrument zarządzania przepływami kapitału. W działaniach rządów, które muszą zarządzać ryzykiem związanym z gwałtownym napływem lub odpływem kapitału, kontrola kapitału powinna odgrywać kluczową rolę. Słowa kluczowe: kapitał, kontrola, przepływy, skutki JEL: F21, F32, F41, F42