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U.S. Tax Revenues and Policy Implications A Time Series Approach

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.

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U.S. Tax Revenues and Policy Implications A Time Series Approach

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

  2. Outline • The Objectives • The Data • The Technique • The Results • The Conclusions

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

  4. The Data – Total Revenue Quarterly data from 1988 – 2007

  5. The Data – Total Revenue Histogram for Total Revenue

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

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

  8. Final Estimated Model

  9. Correlogram of Final Model

  10. Government Revenue • Growth in revenue partly from cuts in: • Top marginal income tax • Capital gains tax • Corporate tax

  11. 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.

  12. The Data – Corporate Tax Trace for Corporate Income Tax

  13. The Data – Corporate Tax Histogram for Corporate Income Tax

  14. The Data – Corporate Tax Correlogram for Corporate Income Tax

  15. 0.3 0.2 0.1 0.0 -0.1 -0.2 05:1 05:3 06:1 06:3 07:1 07:3 08:1 08:3 SD2LNTOTAL FORECASTOT+2*SEFOT FORECASTOT FORECASTOT-2*SEFOT Forecast: SD2LNTOTAL, 2008:1 – 2008:4 RECOLOR SD2LNTOTAL Sample: 2007:03 2007:04 Genr lntotalf = lntotal Sample: 2007:03 2008:04 Genr lntotalf = forecastot + lntotalf(-2) (undo seasonal difference) Genr totalforecast = exp(lntotalf) (undo natural logarithm)

  16. The Results Four quarter forecast, with historical data

  17. 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 2001-02 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.

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