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评估政策变化对Nowcast的影响（英）

金融2023-07-01IMFL***

AI智能总结

Assessing the Impact of Policy Changes on a Nowcast

Sam Ouliaris and Celine Rochon

WP/23/153 IMF Working Papers

This paper aims to address the limitations of nowcasting estimators in assessing the impact of policy changes on a nowcast. Nowcasting allows policymakers to obtain forecasts of key macroeconomic indicators using higher frequency data, resulting in more timely information to guide proposed policy changes. However, existing nowcasting estimators have a "reduced-form" nature, which means they cannot be used to assess the impact of policy changes on the baseline nowcast of real GDP.

To address this problem, the authors propose two separate methodologies. The first methodology is a partial equilibrium approach that uses an existing baseline nowcasting regression and single-equation forecasting models for the high-frequency data in that regression. The second approach utilizes a non-parametric approach for generating high-frequency data.

The proposed methodologies have been tested on various datasets, and the results show that they are effective in improving the accuracy and providing more reliable forecasts than existing nowcasting estimators. The authors also demonstrate that these methodologies can be used to assess the impact of policy changes on the baseline nowcast of real GDP.

In conclusion, the proposed methodologies offer a valuable tool for policymakers to obtain more accurate and timely forecasts of key macroeconomic indicators. The results of this research can be used to inform policy decisions and improve the quality of economic information.

AssessingtheImpactofPolicyChangesonaNowcast SamOuliarisandCelineRochon WP/23/153 IMFWorkingPapersdescriberesearchinprogressbytheauthor(s)andarepublishedtoelicitcommentsandtoencouragedebate. TheviewsexpressedinIMFWorkingPapersarethoseoftheauthor(s)anddonotnecessarilyrepresenttheviewsoftheIMF,itsExecutiveBoard,orIMFmanagement. 2023 JUL ©2023InternationalMonetaryFundWP/23/153 IMFWorkingPaper InstituteforCapacityDevelopment AssessingtheImpactofPolicyChangesonaNowcastPreparedbySamOuliarisandCelineRochon AuthorizedfordistributionbySelimElekdagJuly2023 IMFWorkingPapersdescriberesearchinprogressbytheauthor(s)andarepublishedtoelicitcommentsandtoencouragedebate.TheviewsexpressedinIMFWorkingPapersarethoseoftheauthor(s)anddonotnecessarilyrepresenttheviewsoftheIMF,itsExecutiveBoard,orIMFmanagement. ABSTRACT:Nowcastingenablespolicymakerstoobtainforecastsofkeymacroeconomicindicatorsusinghigherfrequencydata,resultinginmoretimelyinformationtoguideproposedpolicychanges.Asignificantshortcomingofnowcastingestimatorsistheir“reduced-form”nature,whichmeanstheycannotbeusedtoassesstheimpactofpolicychanges,forexample,onthebaselinenowcastofrealGDP.Thispaperoutlinestwoseparatemethodologiestoaddressthisproblem.Thefirstisapartialequilibriumapproachthatusesanexistingbaselinenowcastingregressionandsingle-equation𝐴𝑅𝑀𝐴(𝑝,𝑞)forecastingmodelsforthehigh-frequencydatainthatregression.Thesecondapproachusesanon-parametricstructuralVARestimatorrecentlyintroducedinOuliarisandPagan(2022)thatimposesminimalidentifyingrestrictionsonthedatatoestimatetheimpactofstructuralshocks.Eachapproachisillustratedusingacountry-specificexample. RECOMMENDEDCITATION:OuliarisandRochon(2023) JELClassificationNumbers: E27 Keywords: Nowcasting;highfrequencyindicators;impulseresponses;structuralmodels Author’sE-MailAddress: crochon@imf.org;sam.ouliaris@gmail.com *TheauthorswouldliketothankDanielTaumoepeauforaccesstodataaspartofICD’sFPASTechnicalAssistancefortheNationalReserveBankofTonga. WORKINGPAPERS AssessingtheImpactofPolicyChangesonaNowcast PreparedbySamOuliarisandCelineRochon Contents Introduction5 FirstApproach6 FirstExample:LimitedData,NoFeedbackEffects7 SecondApproach12 SecondExample:LimitedData,GeneralFeedbackEffects14 Conclusion16 References16 Figures Figure1:Year-on-YearPercentageChange,2019-2022,RealGDPofDominica11 Figure2:Year-on-YearPercentageChange,2019-2023,RealGDPofDominica12 Tables Table1:BaselineNowcastingRegressionfortheRealGDPofDominica,2001-2021(Annual)8 Table2:PreferredARMA(p,q)ModelforTouristExpendituresinDominica,2000Q2-2021Q4(Quarterly)9 Table3:AnnualDataforBaselineNowcastingRegression10 Table4:Year-On-YearPercentageChange,2019-2022,RealGDPofDominica11 Table5:Year-On-YearPercentageChange,2019-2023,RealGDPofDominica12 Table6:BaselineNowcastingRegressionforTonga,2011S1-2021S114 Introduction Nowcastingisanessentialpartofapolicymaker’stoolkit.Itenablespolicymakerstoobtainforecastsoflowfrequencyindicatorsusinghigherfrequencydata,resultinginmoretimelyinformationtoguideimminentpolicychanges.Forexample,insomecountries,annualGDPisavailableonlywithalagofoneortwoyears.Insuchcases,monthlyindicators1mayhelpimprovetheassessmentofrealGDPrelativetopotentialonamoreregularbasisand,mostimportantly,duringcrisisepisodeswhendata-drivenpolicyadjustmentsarerequiredurgently. Whilestandardnowcastingtoolsareessentialforassessingthecurrentstateofthemacroeconomy,theyare“reduced-form”toolsandassuchcannotbeusedtoassesstheimpactofproposedpolicychangesonthebaselineforecast/nowcastforrealGDPforexample,whichisasignificantshortcoming.Thispaperproposestwomethodologiestoaddressthe“reduced-form”problemofstandardnowcastingmethods.Theapplicationoftheproposedmethodsyieldsestimatesofthesensitivityofanowcasttochangesinchosenpolicyindicatorsatleastoneperiodahead. AssumeasingleequationregressionmodelhasbeenformulatedtonowcastrealGDP.ItuseslagsofrealGDPandatleastonehighfrequencyindicatorconvertedtothesamelowerfrequencyasrealGDP.PolicymakersaretypicallyinterestedinassessingtheimpactofaproposedpolicyshockonrealGDP.WealsoassumenotenoughobservationsareavailabletoestimateastructuralVARatthefrequencyofrealGDP.Moreover,giventheavailabledata,anyfeasibleSVARinvolvinglessvariablesorlagswouldbefartoosimple(i.e.,poorlyspecified)toprovideusefulinformationtopolicymakers. Thefirstapproachtosolvethisproblemusessingle-equation𝐴𝑅𝑀𝐴(𝑝,𝑞)models,andinsomecasescanalsobeextendedtovectorautoregressions(VARs).WeapplythismethodtoestimatetheimpactofhigherrealoilpricesandhigherUSrealGDPonthe2022-23nowcastforrealGDPgrowthoftheCommonwealthofDominica.Asexpected,anincreaseinrealoilpricesreducesthenowcastofrealGDPgrowthforDominica,thoughwithasmallelasticity,whileanincreaseinUSrealGDPhasalargepositiveeffectonDominica’srealGDP.Thesecondapproachappliesanon-parametricstructuralestimatorrecentlyintroducedinOuliarisandPagan(2022)toestimatetheresponsivenessofanowcasttoastructuralshock.ThisestimatorisusedtoassesstheimpactonthenowcastfortheKingdomofTonga’srealGDPofapositiveunitshockintravelreceipts.Wefindthatapositive

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