1. Matt Mullens Gulsah Gunenc Alex Keyfes Gaoyuan Tian Andrew Booth

2.  Motivation  Background  Data sources  Models  Model Validations  Results  Conclusions  Questions

3.  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.  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.  USA data gathered from:  http://www.bea.gov/national/index.htm#gdp http://www.bea.gov/national/index.htm#gdp

6.  Chinese data gathered from:  http://www.stats.gov.cn/eNgliSH/statisticaldata/Quarterlydata/

7.  Quarterly data from 1947 first quarter -2009 first quarter

8.  Pre-Whitening Process  Needed to be logged and first differenced

9.  Model Validation  As seen from the correlogram more work is needed

10.  Final ARMA model Dependent Variable: DLNGDP Method: Least Squares Date: 05/29/09 Time: 15:28 Sample(adjusted): 1947:3 2009:1 Included observations: 247 after adjusting endpoints Convergence achieved after 10 iterations Backcast: 1942:3 1947:2 VariableCoefficientStd. Errort-StatisticProb. C0.0158090.0019847.9695830.0000 AR(1)0.3838380.0643845.9616590.0000 MA(2)0.1718060.0587022.9267450.0038 MA(5)-0.1623380.056908-2.8526440.0047 MA(9)0.0477660.0556520.8582920.3916 MA(10)0.1512260.0548372.7577250.0063 MA(11)0.1247310.0570342.1869810.0297 MA(16)0.2133110.0592703.5989730.0004 MA(18)0.2084130.0585423.5600540.0004 MA(20)0.3434910.0563356.0972990.0000 R-squared0.375007 Mean dependent var0.016476 Adjusted R-squared0.351273 S.D. dependent var0.011296 S.E. of regression0.009098 Akaike info criterion-6.521832 Sum squared resid0.019618 Schwarz criterion-6.379752 Log likelihood815.4463 F-statistic15.80045 Durbin-Watson stat1.958212 Prob(F-statistic)0.000000 Inverted AR Roots.38 Inverted MA Roots.97 -.18i.97+.18i.83+.44i.83 -.44i.60+.71i.60 -.71i.43+.82i.43 -.82i.15+.96i.15 -.96i -.13+.92i -.13 -.92i -.43+.82i -.43 -.82i -.63+.69i -.63 -.69i -.84 -.48i -.84+.48i -.95 -.17i -.95+.17i

11.  Model Validation

12.  More Model Validation  Actual, Fitted, Residuals

13.  Forecast for the rest of 2009

14.  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.  Possible Forecast Bias  Long time period upward trend  According to our model it will increase, only time will tell

16.  Examine just the past few years in an attempt to eliminate upward time trend

17.  Data had linear trend  Needed first difference

18.  Model Validation  Looking at the correlogram more work was needed  Try ARMA model

19.  Final ARMA Model

20.  Model Validation  A much better looking model  High P-values for Q- stats

21.  Forecast of the rest of 2009

22.  Recoloring of the model

23.  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.  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.  Pre-Whitening  Needed both log and seasonal differencing  Also used from 1998-2008 and first differenced

26.  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.  Rest of 2009

30.  Recoloring Model

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

32.  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.  Any Questions?  anyone  Any Comments?  anyone