1.2. OIL-PRICE VOLATILITY AND EXTERNAL RISK: IMPLICATIONS FOR THE MACROECONOMIES OF CENTRAL AND EASTERN EUROPE

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1 .. Oil-price volailiy and exernal risk: implicaions for he macroeconomies of CEE Sco William HEGERTY DOI:.855/dBEM.M7.n.ch.. OIL-PRICE VOLATILITY AND EXTERNAL RISK: IMPLICATIONS FOR THE MACROECONOMIES OF CENTRAL AND EASTERN EUROPE Summary In an era of increased global risk and he possibiliy of inernaional conagion, managers worldwide mus be cognizan of he role ha various ypes of volailiy migh have on heir counries and regions. In paricular, saisical analysis can provide esimaes of he macroeconomic implicaions of shocks o foreign asse and commodiy prices. This sudy performs such an analysis, applying ime-series economeric modelling o analysis of four Cenral European counries (Bulgaria, Croaia, Hungary, and Poland), as well as Russia and Ukraine. Using monhly daa and applying Vecor Auoregressive (VAR) ime-series mehods, his sudy firs models oil-price volailiy and real effecive exchange-rae volailiy. We hen sudy he effecs of hese volailiy erms and of changes in U.S. sock prices on credi growh, oupu growh, and he currency markes of our se of European counries. Overall, Granger Causaliy ess and Impulse Response Funcions show ha risk does have a srong impac on he region s economies, bu ha he effecs differ from counry o counry. For example, U.S. sock-price declines uniformly pu pressure on he region s currencies. A he naional level, oil-price volailiy pus pressure on he złoy (PLN) and also conribues o Polish growh, and also hurs Russian growh. Our findings herefore offer he region s indusries insighs ino heir exposure o global risk and he global macroeconomy. Keywords: Commodiy prices, volailiy, Cenral Europe, Easern Europe, ime series Inroducion Following a decade of large increases and decreases on global markes, commodiy prices began o drop significanly in. While he resuling revenue losses can hur emerging-marke commodiy exporers, oil-price declines may help lower coss and boos profis for manufacurers, paricularly in Cenral and Easern European (CEE) naions. A he same ime, however, large swings in commodiy prices creae volailiy ha migh be derimenal; increased risk hurs individual businesses and he overall macroeconomy. This paper invesigaes he impac of oil-price volailiy on he exchange markes of six CEE naions, as well as ineracions wih macroeconomic variables. Using ime-series mehods, we find imporan effecs ha differ from counry o counry. This sudy focuses on a measure of Exchange-Marke Pressure (EMP), which capures exchange-rae depreciaions as well as cenral-bank measures o comba hese depreciaions. This monhly measure is hen modelled as a funcion of U.S. sock prices and key macroeconomic variables. These include domesic credi growh, he growh rae of governmen borrowing, GDP growh, and inflaion. Previous research, by Phylakis and Ravazzolo (5), Van Poeck e al. (), Savárek (), Koseoglu and Cevik () and ohers shows hese variables o be significan deerminaes of EMP and currency crises in he CEE region. And while Hegery (, 9

2 Hegery, S. W. a, b) examines he link beween commodiy price changes and EMP in Lain America, Russia, and he Balics, he does no include price variabiliy in any specificaion. This sudy, herefore provides a key addiion o his imporan branch of he lieraure, providing business leaders wih increased abiliy o undersand and miigae his risk. Mehodology In his sudy, monhly daa for all variables are aken from he Inernaional Financial Saisics of he Inernaional Moneary Fund. The imespan differs from counry o counry, bu generally begins in he mid-99s and ends in lae. Firs, we calculae EMP as a funcion of exchange-rae depreciaions (an increase in he number of unis per U.S. dollar), reserve losses (as a percenage of he lagged moneary base), and he change in he ineres-rae differenial (money-marke rae) vis-à-vis he Unied Saes: EMP e RES US ln E ln E r r () MB RES Each componen is deflaed by is own sandard deviaion. Oil-price volailiy is nex calculaed as he sandard error of a rolling AR() regression (of he price on is lagged value), wih -monh windows. A similar calculaion is carried ou wih he real effecive exchange rae (REER), which represens a counry s compeiiveness versus a broad range of rade parners. This volailiy, herefore, represens anoher ype of exernal risk. Afer ploing hese ime series, we hen conduc Vecor Auoregressive (VAR) analysis o es for spillovers among variables. These allow for any variable in he specificaion o have an impac on any oher; for example, EMP and growh migh have effecs on each oher. We firs perform a bivariae Granger Causaliy es beween oil-price and REER volailiy o see wheher he addiion of one variable o a regression of he oher on is own lagged values increases he regression s explanaory power; if so, i has a significan impac. Our main es, however, is his es s mulivariae version, applied o he following vecor: EMP CRG, GOVGGROWTHINF,,, dlnusps, POILVOL, () The lag lengh of each VAR is chosen by minimizing he Schwarz goodness-of-ficrierion. In addiion, we make sure ha each variable in our analysis is saionary by performing a se of Phillips-Perron (988) saionary ess, and aking firs differences of any variable for which we are unable o rejec he null hypohesis of nonsaionariy. We herefore proceed wih VARs ha conain differen mixes of differenced and level variables, all of which are saionary. Once proper VARs are esimaed, significan Granger Causaly/Block exogeneiy saisics sugges ha one variable has an effec on he variable of ineres. We also generae a number of Impulse-Response Funcions (IRFs) following he Generalized VAR mehodology of Pesaran and Shin (998). These funcions plo he ime pah of one variable afer a shock o anoher, as well as significance bands o r

3 .. Oil-price volailiy and exernal risk: implicaions for he macroeconomies of CEE show wheher hese responses differ from zero. While he orhogonal VAR approach of Sims (98) depends on he proper ordering of variables in he sysem, he generalized approach does no. In an addiional analysis, we re-esimae Equaion () wih volailiy of he REER in place of oil-price volailiy, for a oal of separae esimaions. Our Granger Causaliy resuls and Impulse Response Funcions are shown below. Overall, we find ha no only does each of he six counries in our analysis behave differenly from one anoher for almos every variable, bu ha REER volailiy and oil-price variabiliy also generae surprisingly differen resuls. Resuls Figure shows he calculaed ime series of in he price of U.K. Bren and is volailiy from 99 o. We see increases in volailiy hroughou he sample period, bu he larges spike occurs immediaely before and during he 8 Global Financial Crisis. A he same ime, EMP increased during his period, as did real exchange-rae volailiy for hese CEE counries. Our goal is o es empirically he causes and inerlinkages of hese movemens. Figure : Oil Prices (U. Bren) and heir volailiy POILB (log changes in U.K. Bren price) 5 VOLPOILB (volailiy in oil price) Measured as he sandard errors of a rolling AR() regression over -monh windows. The lef side of Figure shows our generaed EMP series. Marke pressure increased during he 8 crisis noe he behaviour of he złoy, for example bu his paern is similar across counries. Each counry has is own idiosyncraic behaviour as well, which represens i unique inernal condiions (Bulgaria, for example, behaves differenly from he ohers). On he righ side is REER volailiy. Again, here are common evens, such as he 8 crisis, as well as individual movemens (Hungary s sands ou during ).

4 Hegery, S. W. Figure : Exchange marke pressure indices (lef side) and REER volailiy (righ side) EMP REERVOL POLAND HUNGARY POLAND HUNGARY BULGARIA CROATIA BULGARIA CROATIA RUSSIA UKRAINE RUSSIA UKRAINE Before proceeding wih our economeric analysis, we firs conduc he Phillips-Perron (988) saionariy es. Table : Phillips-Perron saionary es resuls Variable Bulgaria Poland Hungary Croaia Russia Ukraine EMP -5. (.) -9. (.) (.) -8.7 (.) -.77 (.) -7. (.) CRG -. (.) -.5 (.7) -. (.58) -.77 (.8) -.7 (.9) -.9 (.58) GOVG -.89 (.) -.7 (.9) -.75 (.) -.98 (.) -.5 (.) (.) GROWTH -.7 (.) -.8 (.) -. (.) (.) -.8 (.) -. (.) INF -. (.) -.5 (.) -. (.77) -.7 (.) -. (.8) -.75 (.) DLNUSPS -. (.) -. (.) -8.7 (.) -.7 (.) -9. (.) VOLPOILB -.99 (.) -.97 (.5) -.9 (.) -. (.8) -.9 (.5) -.7 (.8) REERVOL -. (.) -. (.) -. (.) -.57 (.) -.7 (.57) -.98 (.) P-values in parenheses. H o = he variable is nonsaionary. Macroeconomic variables are ofen nonsaionary, rising or falling over ime. This makes radiional saisical inference difficul, so one soluion is o difference he variables when necessary and o include only changes over ime in our analysis. The

5 .. Oil-price volailiy and exernal risk: implicaions for he macroeconomies of CEE resuls of our es, which ell us which variables need o be differenced and which do no, are presened in Table. EMP, for example, is always saionary wihou differencing, while credi growh mus be differenced for all six counries (and would be labelled DCRG o reflec his adjusmen). GDP growh mus be differenced for Ukraine, bu no Poland, for example. We nex es for direc spillovers beween volailiy measures using a bivariae Granger-causaliy es. The resuls are provided in Table. Table : Bilaeral Granger causaliy es resuls (p-values in parenheses) Poland Hungary Bulgaria Croaia Russia Ukraine REER POILB (.599) (.5) (.59) (.) (.5) (.8) POILB REER (.) (.) (.898) (.5) (.) (.) Bold = significan a 5 percen. H o = he lef-hand variable does no Granger-cause he righhand one. We see ha in four of he six counries, increased oil-price variabiliy spills over o he real effecive exchange rae. In oher words, oil price risk leads o risk in he erms of rade, or he compeiiveness of he CEE region. Only in Ukraine is he oher direcion of causaion significan a 5 percen. Perhaps world markes are sensiive o evens in his relaively small, bu highly influenial counry. Table shows he main Granger causaliy/block exogeneiy es resuls. Variables are differenced based on saionariy ess resuls ha are available upon reques. Table : Bilaeral Granger causaliy es resuls (p-values in parenheses) Poland EMP DCRG GROWTH DINF EMP.578 (.7).785 (.). (.7) DCRG. (.7) 7.79 (.5) 7.9 (.) GROWTH.57 (.9).9 (.5).97 (.) DINF. (.8).7 (.) 9.79 (.) DGOVG.8 (.77).5 (.9).77 (.5).7 (.8) DLNUSPS.5 (.). (.). (.57).7 (.79) DVOLPOILB.777 (.78).89 (.9). (.). (.5) All 5.8 (.5) 5. (.) 8. (.) 8.5 (.) Hungary EMP DCRG DGROWTH DINF EMP.9 (.8).7 (.579). (.7) DCRG.9 (.).5 (.7). (.99) DGROWTH. (.75).58 (.8).9 (.) DINF.5 (.85). (.7).8 (.58) DGOVG.5 (.).87 (.9).79 (.5).79 (.7) DLNUSPS.9 (.).5 (.). (.77).88 (.9) DVOLPOILB. (.5).8 (.7).89 (.5). (.558) All.98 (.55). (.55).958 (.) 7.85 (.5)

6 Hegery, S. W. Bulgaria EMP DCRG DGROWTH DINF EMP.557 (.5). (.57). (.5) DCRG.8 (.).8 (.97).5 (.5) DGROWTH.95 (.).9 (.8).57 (.55) DINF.5 (.7).5 (.5).8 (.7) GOVG. (.99). (.7).5 (.575). (.8) DLNUSPS.8 (.) 7.99 (.5).5 (.9) 5.5 (.) DVOLPOILB.5 (.5). (.9). (.957). (.979) All 9.7 (.) 9. (.9).97 (.55).9 (.7) Croaia EMP DCRG GROWTH DINF EMP.9 (.7).77 (.8). (.5) DCRG.7 (.). (.97) GROWTH.9 (.5). (.957).8 (.5) DINF. (.59).599 (.).9 (.8).75 (.9) DGOVG.5 (.9).8 (.87).85 (.).75 (.9) DLNUSPS. (.).7 (.5).8 (.5).8 (.77) DVOLPOILB.558 (.55). (.).59 (.9) 9.75 (.) All. (.) 9.79 (.).9 (.).5 (.7) Russia EMP DCRG DGROWTH DINF EMP.99 (.95).98 (.).7 (.58) DCRG.7 (.9).8 (.). (.978) DGROWTH.79 (.8).97 (.8).585 (.8) DINF.7 (.). (.8).8 (.7) DGOVG. (.55). (.).9 (.7).9 (.) DLNUSPS.8 (.9).5 (.78).5 (.). (.87) DVOLPOILB.79 (.9).88 (.7).5 (.).75 (.7) All 5.8 (.) 9.9 (.8) 5.8 (.).5 (.79) Ukraine EMP DCRG DGROWTH DINF EMP.8 (.58). (.55).75 (.85) DCRG.7 (.). (.8). (.) DGROWTH. (.7) 9.8 (.).9 (.) DINF.78 (.87).78 (.9). (.) GOVG. (.).89 (.9).9 (.8). (.887) DLNUSPS.5 (.8).87 (.5).785 (.9).77 (.7) DVOLPOILB.5 (.). (.89).87 (.85).7 (.78) All.789 (.). (.).87 (.). (.7) Our key iem of ineres is he effec of oil-price volailiy on EMP, credi growh, GDP growh (proxied by log changes in he monhly index of indusrial producion), and CPI inflaion. Our main finding is ha CEE exchange markes are less affeced by commodiy-price risk han are oher variables. Oil-price volailiy has a significan impac on credi growh in Poland and Croaia and on GDP growh in Russia. U.S. sock-price movemens significanly affec EMP growh in Poland and Croaia and indusrial-producion (GDP) growh in Russia. U.S. sock-price movemens significanly affec EMP, credi growh, and GDP growh in Poland and Croaia, and GDP growh in Russia. U.S. sock-price movemens significanly affec EMP, credi growh, and inflaion in Bulgaria, and GDP growh in Russia and Ukraine. The oher

7 .. Oil-price volailiy and exernal risk: implicaions for he macroeconomies of CEE macroeconomic variables (such as he linkage beween inflaion and credi growh and Poland) have imporan effecs as well. These resuls are confirmed by our Generalized IRF resuls, which are presened in Figure. I is imporan o noe ha he IRFs on he far righ of each column come from a se of separae esimaions (which replace oil-price volailiy wih REER volailiy). Since all bu he replacemen variables IRFs will be he same, o avoid redundancy and o conserve space, only he REERVOL IRFs are depiced. We can easily see he differences in response o shocks in each variable. Also, only hose responses ha are more han wo sandard errors from zero (using he error bands) are considered o be significanly posiive or negaive. Our main conclusion from he IRFs is ha macroeconomic variables respond differenly o oil-price and REER shocks. In many cases, higher U.S. sock prices reduce EMP (and falling prices pu pressure on he region s currencies); high sock prices are ofen beneficial o he region s growh. While here is a vas amoun of informaion in hese graphs, we can focus on some key resuls, counry by counry. In Poland, for example, oil-price volailiy raises EMP and increases credi growh, while REER volailiy reduces credi growh. Here, we see ha he wo ypes of exernal risk oil-price variabiliy and REER volailiy do indeed have differen effecs. In Hungary, REER volailiy reduces EMP as well as credi growh, bu oil prices have less of an effec. Oil-price volailiy increases Croaian credi growh, bu REER volailiy does no have he same effec. For Bulgaria, only limied effecs are observed overall. Neiher oil-price variabiliy nor REER volailiy generae significan impulse responses for any of Bulgaria s key macroeconomic variables in our sudy. Perhaps differences in he counry s exchange-rae regime (i alone has a currency-board-ype fixed exchange rae; ohers have floaing currencies) migh explain hese differences. Turning o he wo counries ha are mos closely ied o energy prices, we arrive a some ineresing conclusions. In Russia, oil-price volailiy increases EMP and reduces indusrial producion growh, confirming ha recen flucuaions in global energy markes will help desabilize no only he ruble (RUB), bu also Russia s real economy. A he same ime, increased REER volailiy leads o higher growh, which demonsraes he differences in responses o hese wo risk measures. In Ukraine, oilprice volailiy increases credi growh, while REERVOL reduces he same macroeconomic variable. The hryvnia is no affeced he way he ruble was in our analysis. These findings bring us o wo key conclusions. Firs, business leaders and policymakers mus be wary of he role ha commodiy-price flucuaions have on he macroeconomies of he counries in which hey operae. Bu, since his role varies from counry o counry, a one size fis all policy is no recommended, and policies mus herefore be ailored depending on he imporance of oil prices and he impac ha risk has on each paricular economy. 5

8 Hegery, S. W. Figure : Impulse-response funcions (wih ± sandard error bands) Poland Response o Generalized One S.D. Innovaions ± S.E. Response of EMP o EMP Response of EMP o DCRG Response of EMP o DLNUSPS Response of EMP o DVOLPOILB Response of EMP o REERVOL Response of DCRG o EMP Response of DCRG o DCRG Response of DCRG o DLNUSPS Response of DCRG o DVOLPOILB Response of DCRG o REERVOL Response of GROWTH o EMP Response of GROWTH o DCRG Response of GROWTH o DLNUSPS Response of GROWTH o REERVOL Response of GROWTH o DVOLPOILB Hungary Response o Generalized One S.D. Innovaions ± S.E. Response of EMP o EMP Response of EMP o DCRG Response of EMP o DLNUSPS Response of EMP o DVOLPOILB Response of EMP o DREERVOL Response of DCRG o EMP Response of DCRG o DCRG Response of DCRG o DLNUSPS Response of DCRG o DVOLPOILB Response of DCRG o DREERVOL Response of DGROWTH o EMP Response of DGROWTH o DCRG Response of DGROWTH o DLNUSPS Response of DGROWTH o DVOLPOILB Response of DGROWTH o DREERVOL Croaia Response o Generalized One S.D. Innovaions ± S.E...5 Response of EMP o EMP..5 Response of EMP o DCRG..5 Response of EMP o DLNUSPS Response of EMP o DVOLPOILB..5.. Response of EMP o REERVOL Response of DCRG o EMP Response of DCRG o DCRG Response of DCRG o DLNUSPS Response of DCRG o DVOLPOILB Response of DCRG o REERVOL Response of GROWTH o EMP Response of GROWTH o DCRG Response of GROWTH o DLNUSPS Response of GROWTH o DVOLPOILB Response of GROWTH o REERVOL

9 .. Oil-price volailiy and exernal risk: implicaions for he macroeconomies of CEE Bulgaria Response o Generalized One S.D. Innovaions ± S.E..8 Response of EMP o EMP.8 Response of EMP o DCRG.8 Response of EMP o DLNUSPS Response of EMP o DVOLPOILB.8.8 Response of EMP o REERVOL Response of DCRG o EMP Response of DCRG o DCRG Response of DCRG o DLNUSPS Response of DCRG o DVOLPOILB Response of DCRG o REERVOL Response of DGROWTH o EMP Response of DGROWTH o DCRG Response of DGROWTH o DLNUSPS Response of DGROWTH o DVOLPOILB Response of DGROWTH o REERVOL Russia Response o Generalized One S.D. Innovaions ± S.E..5 Response of EMP o EMP.5 Response of EMP o DCRG.5 Response of EMP o DLNUSPS Response of EMP o DVOLPOILB.5.5 Response of EMP o REERVOL Response of DCRG o EMP Response of DCRG o DCRG Response of DCRG o DLNUSPS Response of DCRG o DVOLPOILB Response of DCRG o REERVOL Response of DGROWTH o EMP Response of DGROWTH o DCRG Response of DGROWTH o DLNUSPS Response of DGROWTH o DVOLPOILB Response of DGROWTH o REERVOL Ukraine Response o Generalized One S.D. Innovaions ± S.E. Response of EMP o EMP Response of EMP o DCRG Response of EMP o DLNUSPS Response of EMP o DVOLPOILB Response of EMP o REERVOL Response of DCRG o EMP Response of DCRG o DCRG Response of DCRG o DLNUSPS Response of DCRG o DVOLPOILB Response of DCRG o REERVOL Response of DGROWTH o EMP Response of DGROWTH o DCRG Response of DGROWTH o DLNUSPS Response of DGROWTH o DVOLPOILB Response of DGROWTH o REERVOL

10 Hegery, S. W. Conclusion Commodiy-price volailiy, which has increased over he pas year wih he recen plunge in oil prices, has he poenial o inroduce risk ino he business environmen. In paricular, CEE counries migh find he coss of his risk o ouweigh he benefis brough by high energy prices. Therefore, hose who conduc business in he region mus be aware of how risk affecs each variable in he macroeconomy, and how hese effecs differ from counry o counry. This sudy models oil-price and real effecive exchange rae (REER) risk for six CEE economies before using Vecor Auoregressive (VAR) mehods o es for spillovers beween risk and a se of macroeconomic variables. Firs, a measure of Exchange Marke Pressure (EMP) is creaed for each counry o obain a measure of currency movemens and cenral bank inervenions combined. Risk in oil prices and he REER is also calculaed using saisical mehods, and hese variables are used alongside a number of macroeconomic variables in our empirical analysis. We es our hypohesis using Granger causaliy ess and by generaing Impulse Response Funcions. Our resuls show ha oil-price and REER volailiy have differing effecs on our se of macroeconomic variables, and ha overall he resuls differ from counry o counry. In general, U.S. sock price decreases pu pressure on he region s currencies. We find ha credi growh and oupu growh are mos affeced by oil-price risk, bu no for every counry in he sudy. In paricular, oil-price risk pus pressure on he złoy and leads o increased credi growh in Poland, while REER volailiy has more of an impac on Hungary s economy. Russia, he region s major oil exporer, experiences no only pressure o depreciae, bu also reduced GDP growh, when oilprice risk increases. We conclude ha differences in economic performance in he region are real, and ha policymakers and business leaders mus ake hese differences ino accoun when planning heir sraegies. References. Hegery, S.W. (): How Inegraed are he Exchange Markes of he Balic Sea Region? An Examinaion of Marke Pressure and is Conagion, Balic Journal of Economics, (), pp. 9-. hp://dx.doi.org/.8/99x..85. Hegery S.W. (a): Exchange Marke Pressure, Commodiy Prices, and Conagion in Lain America, Journal of Inernaional Trade & Economic Developmen, (), pp hp://dx.doi.org/.8/ Hegery, S.W. (b): Exchange Marke Pressure and Price Spillovers in Russia, Ukraine, and Belarus, Applied Economerics and Inernaional Developmen, ().. Koseoglu, S.D.; Cevik, E.I. (): Tesing for Causaliy in Mean and Variance Beween he Sock Marke and he Foreign Exchange Marke: An Applicaion o he Major Cenral and Easern European Counries, Czech Journal of Economics and Finance (Finance a uver), (), pp Pesaran, M.H.; Shin, Y. (998): Generalised Impulse Response Analysis in Linear Mulivariae Models, Economics Leers, 58, pp.7-9. hp://dx.doi.org/./s5-75(97)-. Phillips, P.; Perron, P. (988): Tesing for a Uni Roo in Time Series Regression, Biomerica, 75, pp. 5. hp://dx.doi.org/.9/biome/

11 .. Oil-price volailiy and exernal risk: implicaions for he macroeconomies of CEE 7. Phylakis, K.; Ravazzolo, F. (5): Sock Prices and Exchange Raes Dynamics, Journal of Inernaional Money and Finance, (7), pp Sims, C.A (98): Macroeconomics and Realiy, Economerica 8, pp. -8. hp://dx.doi.org/.7/97 9. Savárek, D. (): Comparison of Exchange Marke Pressure Across he New Par of he European Union, Emerging Markes Finance and Trade, 7, iss. sup. hp://dx.doi.org/.75/ree5-9x7s. Van Poeck, A.; Vannese, J.; Veiner, M. (): Exchange Marke Pressure in he Formerly Planned Cenral and Easern European Counries: The Role of Insiuions, Tijdschrif voor Economie en Managemen, 5(), pp

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