U.S. Tax Revenues and Policy Implications A Time Series Approach Group C: Liu He Guizi Li Chien-ju Lin Lyle Kaplan-Reinig Matthew Routh Eduardo Velasquez

Outline The Objectives The Data The Technique The Results The Conclusions

The Objectives Model & forecast U.S. tax revenues To better estimate future governmental budget projections To understand tax policy implications surrounding those projections.

The Data – Total Revenue Quarterly data from 1988 – 2007

The Data – Total Revenue Histogram for Total Revenue

The Data – Total Revenue Correlogram & Unit Root Test for Total Revenue

The Technique Natural logging Seasonal differencing Autoregressive Moving average Autoregressive conditional heteroskedasticity (ARCH) test – not significant

Final Estimated Model Dependent Variable: SD2LNTOTAL Method: Least Squares Date: 05/31/08 Time: 14:42 Sample (adjusted): 1989:1 2007:4 Included observations: 76 after adjusting endpoints Convergence achieved after 11 iterations Backcast: 1988:2 1988:4 VariableCoefficientStd. Errort-StatisticProb. C AR(2) MA(1) MA(2) MA(3) R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic) Inverted MA Roots i i -.54

Correlogram of Final Model

Government Revenue Growth in revenue partly from cuts in: Top marginal income taxTop marginal income tax Capital gains taxCapital gains tax Corporate taxCorporate tax

Corporate Income Tax Receipts as a Share of GDP, 1985–2007 Corporate Income Tax Cuts Boost Federal Revenues The economy has boomed since the 2003 tax cuts, leading to the highest level of corporate tax receipts in over 20 years.

The Data – Corporate Tax Trace for Corporate Income Tax

The Data – Corporate Tax Histogram for Corporate Income Tax

Correlogram for Corporate Income Tax The Data – Corporate Tax

Forecast: SD2LNTOTAL, 2008:1 – 2008: :105:306:106:307:107:308:108:3 SD2LNTOTAL FORECASTOT FORECASTOT+2*SEFOT FORECASTOT-2*SEFOT RECOLOR SD2LNTOTAL Sample: 2007: :04 Genr lntotalf = lntotal Sample: 2007: :04 Genr lntotalf = forecastot + lntotalf(-2) (undo seasonal difference) Genr totalforecast = exp(lntotalf) (undo natural logarithm)

The Results Four quarter forecast, with historical data

The Conclusions The model provides a satisfactory account for the increasing tax revenues of the United States government over the past twenty years. Increasing variation is not significant and simply represents the various fluctuations from a number of tax revenue generating sources. The spike in revenues following the economic downturn can be explained by the economic growth led by corporate expansion attributed to the cutbacks in capital gains tax as well as the corporate tax rate.