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State of HawaiiState of HawaiiDepartment of TaxationDepartment of Taxation

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Revenue Forecasting Phase I ReportRevenue Forecasting Phase I Report

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Jerry NickelsburgJerry Nickelsburg

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Jerry NickelsburgJerry NickelsburgSenior Economist, Senior Economist, UCLA Anderson ForecastUCLA Anderson Forecast

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June 25, 2009June 25, 2009

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WWW.UCLAFORECAST.COM

Econometric Model Econometric Model For Forecasting The State of Hawaii For Forecasting The State of Hawaii

General Fund Tax RevenuesGeneral Fund Tax Revenues

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General Fund Tax RevenuesGeneral Fund Tax Revenues

1.1. Statement of Work.Statement of Work.A multiA multi year project to analyze State of Hawaii tax revenue year project to analyze State of Hawaii tax revenue

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eme A multiA multi--year project to analyze State of Hawaii tax revenue year project to analyze State of Hawaii tax revenue

forecasting, develop new forecasting modeling and improve forecasting, develop new forecasting modeling and improve accuracy and informational content of forecastsaccuracy and informational content of forecasts

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1.1. Existing model and data review Existing model and data review –– January 8January 8--9, 20099, 200922 Research Strategy and Goals Approval Research Strategy and Goals Approval –– January 8January 8--9 20099 2009

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ch 2.2. Research Strategy and Goals Approval Research Strategy and Goals Approval January 8January 8 9, 20099, 20093.3. Phase I Draft Report ReviewPhase I Draft Report Review–– June 15June 15--17 200917 20094.4. Phase I Report Submittal Phase I Report Submittal –– June 23, 2009June 23, 200955 Phase I Report Presentation and Discussion Phase I Report Presentation and Discussion –– June 24June 24--25 25

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e 5.5. Phase I Report Presentation and Discussion Phase I Report Presentation and Discussion June 24June 24 25, 25, 20092009

6.6. Phase I Forecast Implementation Phase I Forecast Implementation –– July TBD, 2009July TBD, 2009

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Project TeamProject Teamen

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Project TeamProject TeamContractor: Contractor:

UCLA Anderson ForecastUCLA Anderson Forecast

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Anderson School of ManagementAnderson School of ManagementUniversity of California, Los AngelesUniversity of California, Los Angeles

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Team Members:Team Members:

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P t i i N D h d P t i i N D h d

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e Patricia Nomura, Demographer and Patricia Nomura, Demographer and Statistical AnalystStatistical Analyst

AkinoriAkinori TomaharaTomahara, Economist, Economist

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AkinoriAkinori TomaharaTomahara, Economist, EconomistGeorge Lee, Technical SupportGeorge Lee, Technical Support

Research StrategyResearch Strategyen

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Research StrategyResearch Strategyan

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♦♦ Structural and Time Series ModelsStructural and Time Series Models–– Structural: Structural:

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♦♦Personal Income TaxPersonal Income Tax♦♦Transient Accommodations TaxTransient Accommodations Tax

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♦♦Corporate Income TaxCorporate Income Tax

–– Time Series:Time Series:Ei h ll Ei h ll

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Research StrategyResearch Strategyen

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Research StrategyResearch Strategyan

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♦♦ Specification and EstimationSpecification and Estimation–– StructuralStructural

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♦♦Establish Establish StationarityStationarity of Dataof Data♦♦Find principal determinates of variationFind principal determinates of variation

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p pp p♦♦Evaluate Forecast Performance and Model FitEvaluate Forecast Performance and Model Fit

–– Time Series ModelsTime Series ModelsE bli h E bli h S i iS i i

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General Excise Tax ModelGeneral Excise Tax Modelen

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General Excise Tax ModelGeneral Excise Tax Model

2500

3000 General Excise Tax (Millions of Current Dollars)(1967-2008)

1200General Excise Tax (Millions of Constant Dollars)(1967-2008)

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1500

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GE

2001970 1975 1980 1985 1990 1995 2000 2005

GE_REAL

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Real GE data shows impact of recessionsReal GE data shows impact of recessionsData series not stationaryData series not stationary

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General Excise Tax ModelGeneral Excise Tax Modelen

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General Excise Tax ModelGeneral Excise Tax Model

.08

.12

.16General Excise Revenue Model

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Model: Differences of logarithmic transformed dataModel: Differences of logarithmic transformed dataPrincipal determinates of variationPrincipal determinates of variation

Vi it A i lVi it A i l

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RecessionRecessionCA RecessionCA Recession

Personal Income Tax ModelPersonal Income Tax Modelen

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Personal Income Tax ModelPersonal Income Tax Model

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2000Personal Income Tax (Millions of Current Dollars)(1967-2008) 700

800Personal Income Tax (Millions of Constant Dollars)(1967-2008)

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PY_TAX

1001970 1975 1980 1985 1990 1995 2000 2005

PY_TAX_REAL

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Real PY data shows impact of recessionsReal PY data shows impact of recessionsData series not stationaryData series not stationary

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Personal Income Tax ModelPersonal Income Tax Modelen

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Personal Income Tax ModelPersonal Income Tax Model

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RecessionRecessionU.S. Defense SpendingU.S. Defense Spending

Transient Accommodations Transient Accommodations Tax ModelTax Model

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Tax ModelTax Model

200

240Transient Accomodations Tax(Millions of Current Dollars)(1971 2008)

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1.1Transient Accomodations Tax(Millions of Constant Dollars)(1971 20080

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TA

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Real TA data shows impact of recessionsReal TA data shows impact of recessionsData series not stationaryData series not stationary

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Transient AccommodationsTransient AccommodationsTax ModelTax Model

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Tax ModelTax Model

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.3Transient Accommodations Model(Changes in Constant Dollar Revenues)(1972-2008)

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Corporate Income Tax ModelCorporate Income Tax Modelen

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Corporate Income Tax ModelCorporate Income Tax Model

160

200Corporate Income Tax (Millions of Current Dollars)(1967-2008) .8

.9Corporate Income Tax (Millions of Constant Dollars)(1967-2008)

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CORP1

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Real CY data possibly stationary Real CY data possibly stationary with autoregressive persistencewith autoregressive persistence

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Corporate Income Tax ModelCorporate Income Tax Modelen

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Corporate Income Tax ModelCorporate Income Tax Model

0 6

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Model: Data in levels with lagged endogenous CYModel: Data in levels with lagged endogenous CYPrincipal determinates of variationPrincipal determinates of variation


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Minor Tax ModelsMinor Tax Models

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Minor Tax ModelsMinor Tax Models

Series roughly Series roughly 20

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Model: taxi t = βi 0 + βi 1*taxi t-1 + βi 2* taxi t-2 + βi 3* taxk t-1 +

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i,t βi,0 βi,1 i,t-1 βi,2 i,t-2 βi,3 k,t-1βi,4* taxk,t-2 + … ( for all i,k )

Next StepsNext Stepsen

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Next StepsNext Steps

♦♦ Implementation (July 2009)Implementation (July 2009)

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♦♦ Phase II and Phase IIIPhase II and Phase III–– Define each Phase Define each Phase SoWSoW

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♦♦ Research Recommendations Research Recommendations

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ch –– HI real personal income modelHI real personal income model–– Construction employment & completions Construction employment & completions

modelsmodels

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e modelsmodels–– Interval ForecastingInterval Forecasting–– Quarterly Forecasting (advance warning)Quarterly Forecasting (advance warning)

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Q y g ( g)Q y g ( g)–– Incorporation of PriorsIncorporation of Priors

The UCLAThe UCLA--Anderson Forecast can also provide individual services for your Anderson Forecast can also provide individual services for your organization.organization.

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Speaking at conferences and eventsSpeaking at conferences and eventsEconomic research consulting servicesEconomic research consulting services

UCLAUCLA A d F t tl k iA d F t tl k i

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Corporate promotional sponsorships for UCLA Forecast quarterly and Corporate promotional sponsorships for UCLA Forecast quarterly and regional eventsregional events

F fF f

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Sherif HannaSherif HannaManaging DirectorManaging Director

For more information contact:For more information contact:

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Managing DirectorManaging Director323323--932932--04110411

[email protected]@agsm.ucla.edu

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For general information about the UCLAFor general information about the UCLA--Anderson Anderson Forecast and upcoming events, please go toForecast and upcoming events, please go to

www UCLAForecast comwww UCLAForecast com

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WWW.UCLAFORECAST.COM1616

www.UCLAForecast.comwww.UCLAForecast.com

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