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Comparison of GDP among u.s.a and china

Comparison of GDP among u.s.a and china. Matt Mullens Gulsah Gunenc Alex Keyfes Gaoyuan Tian Andrew Booth. Preview of Coming Attractions (Outline). Motivation Background Data sources Models Model Validations Results Conclusions Questions. Motivation.

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Comparison of GDP among u.s.a and china

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  1. Comparison of GDP among u.s.a and china Matt Mullens Gulsah Gunenc Alex Keyfes Gaoyuan Tian Andrew Booth

  2. Preview of Coming Attractions(Outline) • Motivation • Background • Data sources • Models • Model Validations • Results • Conclusions • Questions

  3. Motivation • We wanted to first off see what a forecast of the United States GDP will be for the rest of the year • Thought it was relevant given current economic state • We also wanted to compare the GDP of two dissimilar countries • Compared USA and China

  4. Background • The US is considered to be a long established industrialized country • China is considered to be an emerging or developing nation • We figured that the US and China models would be different.

  5. Data Source: USA • USA data gathered from: • http://www.bea.gov/national/index.htm#gdp

  6. Data Source: China • Chinese data gathered from: • http://www.stats.gov.cn/eNgliSH/statisticaldata/Quarterlydata/

  7. Models:Main US GDP Model • Quarterly data from 1947 first quarter -2009 first quarter

  8. Models:Main US GDP Model • Pre-Whitening Process • Needed to be logged and first differenced

  9. Models:Main US GDP Model • Model Validation • As seen from the correlogram more work is needed

  10. Models:Main US GDP Model • Final ARMA model

  11. Models:Main US GDP Model • Model Validation

  12. Models:Main US GDP Model • More Model Validation • Actual, Fitted, Residuals

  13. Forecast of US Model • Forecast for the rest of 2009

  14. Forecast of US Model • Recoloring of GDP • Recoloring: • Lngdpf=lngdp (2009:1 2009:1) • lngdpf=lngdpf(-1)+dlngdpf (2009:2 2009:4) • gdpf=exp(lngdpf) (2009:2 2009:4)

  15. Results • Possible Forecast Bias • Long time period upward trend • According to our model it will increase, only time will tell

  16. A Closer Look • Examine just the past few years in an attempt to eliminate upward time trend

  17. Model:US Short Term • Data had linear trend • Needed first difference

  18. Model:US Short Term • Model Validation • Looking at the correlogram more work was needed • Try ARMA model

  19. Model:US Short Term • Final ARMA Model

  20. Model:US Short Term • Model Validation • A much better looking model • High P-values for Q-stats

  21. Forecast (US Short Term) • Forecast of the rest of 2009

  22. Forecast (US Short Term) • Recoloring of the model

  23. Results • A better estimation as the long time upward trend is less of a bias • Due to economic changes over the past decades a data set that includes only more recent data is more accurate for forecasting • More relevant to current economy • Reflects current issues without previous bias

  24. China Model • Looking at the past few years of China’s GDP • Highly seasonal due to large economic dependence on seasonal agriculture of 900 million farmers

  25. China Model • Pre-Whitening • Needed both log and seasonal differencing • Also used from 1998-2008 and first differenced

  26. China Model • Model Validation • Correlogram • Needs some work • Try ARMA model

  27. Final ARMA Model

  28. Model Validation • A much better looking model • High P-values for Q-stats • Appears valid

  29. Forecast (China) • Rest of 2009

  30. Forecast (China) • Recoloring Model

  31. Results • China continues with an increasing seasonal trend • This can be accounted for by the large agriculture economy in China

  32. Conclusions • Not surprising that USA and China did not have similar models • USA historic leading economy • China is a recent world economy • Long term upward trends indicate USA economy will improve • Shorter term model is less generous

  33. Fin • Any Questions? • anyone • Any Comments? • anyone

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