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The following results are an autoregression for US Exports to Mexico where the dependent variable is the lagged value of US Exports. a) Fill in the table b)Based on these regression results, what is your forecast of US Exports to Mexico for March 2005? c) Which of the two forecasts do you think is more accurate? Explai

The following results are an autoregression for US Exports to Mexico where the dependent variable is the lagged value of US Exports. a) Fill in the table b)Based on these regression results, what is your forecast of US Exports to Mexico for March 2005? c) Which of the two forecasts do you think is more accurate? Explai

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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12) The following results are an autoregression for US Exports to Mexico where the dependent variable is the lagged value of US Exports. a) Fill in the table b)Based on these regression results, what is your forecast of US Exports to Mexico for March 2005? c) Which of the two forecasts do you think is more accurate? Explain.
Forecasting Forecasting.. 12) The following results are an autoregression for US Exports to Mexico where the dependent variable is the lagged value of US Exports. LN ld bo A SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R lt Square Standard Error Observations 0.558 0.311 o o b A ee o lo o t 0.296 1299 48 YRAMMUS TUSTUO ANOVA Significance df MS Regression Residual Total F 210 BE8.0 FRelotu 3.827E-05aupe a eupe A bolmubA Yona bsbnat2 enotovieedO 35017027 77583215 35017027 46 1686592 47 112600242 SET Standard Error 1778 0.124 Upper Lower 95%AV 95% 9879 0.812 Coefficients t Stat P-value Interceptnoigle 6300 Lagged Exports 3.54 0.0009192 2721 0.563 4.56 3.827E-05 0.315 1888S08A 1888S8 esasa ublass Based on these regression results, what is your forecast of US Exports to Mexico for March 2005? bnebneta rae 1owo ainololiteo fgeavatnl bna T Which of the two forecasts do you think is more accurate? Explain. a.ca 0.0 se 0 d bluow doirlw) c00s donM 1o) ootzaM ol nog 2U to aool oy ai rfW (d (on moi do
Transcribed Image Text:Forecasting Forecasting.. 12) The following results are an autoregression for US Exports to Mexico where the dependent variable is the lagged value of US Exports. LN ld bo A SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R lt Square Standard Error Observations 0.558 0.311 o o b A ee o lo o t 0.296 1299 48 YRAMMUS TUSTUO ANOVA Significance df MS Regression Residual Total F 210 BE8.0 FRelotu 3.827E-05aupe a eupe A bolmubA Yona bsbnat2 enotovieedO 35017027 77583215 35017027 46 1686592 47 112600242 SET Standard Error 1778 0.124 Upper Lower 95%AV 95% 9879 0.812 Coefficients t Stat P-value Interceptnoigle 6300 Lagged Exports 3.54 0.0009192 2721 0.563 4.56 3.827E-05 0.315 1888S08A 1888S8 esasa ublass Based on these regression results, what is your forecast of US Exports to Mexico for March 2005? bnebneta rae 1owo ainololiteo fgeavatnl bna T Which of the two forecasts do you think is more accurate? Explain. a.ca 0.0 se 0 d bluow doirlw) c00s donM 1o) ootzaM ol nog 2U to aool oy ai rfW (d (on moi do
Trend Seasonally Adjusted Ratio of Adjusted Forecast Original Projection 12-month Original to Seasonal Seasonal Month Series MA MA Index Index Series DATE VALUE Feb-01 Mar-01 13356.8 11959.6 97.6 136853 12253.7 15523.7 12322.1 13892.7 3 112.7 13768.7 Apr-01 May-01 14403.0 12390.5 13349.2 15108.0 13368.6 124588 13800.3 Jun-01 15051.0 110.8 6. 13772.3 12527.2 136903 Jul-01 11700.0 109.3 112405 Fof Aug-01 13764.0 89.2 13110.5 Sep-01 12664.0 12908 12423.0 101.9 13503.0 9 Oct-01 13895.0 104.6 11873.1 127324 Forecasting 10 Nov-01 13214.0 110.6 12567.2 12800.8 14153.2 11 Dec-01 11319.0 105.1 12567.9 12869.1 135307 12 Jan-02 12061.5 13484.9 96.4 11740.1 12937.5 12473.5 13 Feb-02 89.4 94.0 94.0 12837.8 13005.9 122194 12368.2 14 Mar-02 92.3 97.6 97.6 12672.4 13074.3 12760.4 13954.0 13271.7 105.1 15 Apr-02 112.7 112.7 12376.4 13142.7 14817.9 14113.0 13247.6 16 Маy-02 107.7 107.7 13099.4 13211.0 14586.0 13204.1 14233.3 110.5 17 Jun-02 14214.0 110.8 13168.1 13279.4 14709.3 13134.3 108.2 18 Jul-02 109.3 109.3 13006.4 13347.8 14587.1 11607.0 13126.6 19 Aug-02 88.4 89.2 89.2 13006.3 11972.8 13416.2 13913.0 13139.0 20 Sep-02 105.9 101.9 101.9 13649.2 13334.0 13214.9 13484.6 13745.2 21 Oct-02 100.9 104.6 104.6 12743.8 13552.9 14180.7 14702.0 13282.1 22 Nov-02 110.7 110.6 110.6 13297.1 13621.3 15060.4 13908.0 13340.0 A105.1 23 Dec-02 104.3 105.1 13228.0 13689.7 14393.5 12161.0 13410.1 90.7 96.4 96.4 12613.4 13758.1 13264.6 24 Jan-03 12889.7 13479.2 95.6 94.0 13719.3 13826.5 12990.4 25 Feb-03 13292.6 13556.2 98.1 97.6 13619.5 13894.8 13561.3 26 Mar-03 15359.6 13673.3 112.3 112.7 13623.1 13963.2 15743.1 27 Apr-03 14646.4 13717.8 106.8 107.7 13594.5 14031.6 15117.3 28 Мay-03 15208.0 13769.6 110.4 110.8 13729.7 14100.0 15618.2 29 Jun-03 15003.2 13835.4 108.4 109.3 13728.6 14168.4 15483.8 30 Jul-03 12029.5 13870.6 86.7 89.2 13479.7 14236.7 12705.1 31 Aug-03 12989.7 13793.6 94.2 101.9 12743.4 14305.1 14581.6 32 Sep-03 Oct-03 14518.1 13892.3 104.5 104.6 13875.4 14373.5 15039.2 33 15554.6 13963.4 111.4 110.6 14068.3 14441.9 15967.7 34 Nov-03 14598.2 14020.9 104.1 105.1 13884.4 14510.3 15256.2 35 Dec-03 13834.0 14160.3 97.7 96.4 14348.6 14578.6 14055.7 36 Jan-04 13290.8 14193.7 93.6 94.0 14146.2 14647.0 13761.3 37 Feb-04 14341.7 14281.2 100.4 97.6 14694,4 14715.4 14362.2 38 Mar-04 17458.0 14456.0 120.8 112.7 15484.3 14783.8 16668.2 39 Apr-04 16014.0 14570.0 109.9 107.7 14863.9 14852.2 16001.4 40 Мay-04 16334.0 14663.8 111.4 110.8 14746.2 14920.5 16527.1 41 Jun-04 16438.0 14783.4 111.2 109.3 15041.5 14988.9 16380.6 42 Jul-04 13824.0 14932.9 92.6 89.2 15490.6 15057.3 13437.4 43 Аug-04 16060.0 15188.8 105.7 101.9 15755.5 15125.7 15418.1 16673.0 108.5 104.6 15934.9 15194.1 15897.8 Sep-04 Oct-04 44 15368.4 45 16975.0 15486.7 109.6 110.6 15352.9 15262.5 16875.0 Nov-04 16772.0 15667.9 107.0 105.1 15951.9 15330.8 16119.0 46 15983.1 15847.0 100.9 96.4 16577.7 15399.2 14846.9 47 Dec-04 Jan-05 16037.1 97.1 94.0 16574.6 15467.6 14532.3 48 15572.3 16185.9 99.6 97.6 16523.6 15536.0 15163.0 49 Feb-05 16127.0 SUMMARY OUTPUT AVOWA Regression Statistics Multiple R R Square 3 Adjusted R Square Standard Error Observations 0.803 0,645 bie e 0.638 732 to 49 Significance n F ANOVA SS 45823881 25186924 71010805 MS 45823881 535892 df 86 3.76219E-12 1 Regression Residual Total 47 48 Standard Error 212.4 P- value 0.0 Lower 95% 11758.0 53.5 Upper 95% 12612.6 83.3 Coefficients 12185.3 t Stat 57.4 Intercept 9.2 0.0 68.4 7.4 Trend
Transcribed Image Text:Trend Seasonally Adjusted Ratio of Adjusted Forecast Original Projection 12-month Original to Seasonal Seasonal Month Series MA MA Index Index Series DATE VALUE Feb-01 Mar-01 13356.8 11959.6 97.6 136853 12253.7 15523.7 12322.1 13892.7 3 112.7 13768.7 Apr-01 May-01 14403.0 12390.5 13349.2 15108.0 13368.6 124588 13800.3 Jun-01 15051.0 110.8 6. 13772.3 12527.2 136903 Jul-01 11700.0 109.3 112405 Fof Aug-01 13764.0 89.2 13110.5 Sep-01 12664.0 12908 12423.0 101.9 13503.0 9 Oct-01 13895.0 104.6 11873.1 127324 Forecasting 10 Nov-01 13214.0 110.6 12567.2 12800.8 14153.2 11 Dec-01 11319.0 105.1 12567.9 12869.1 135307 12 Jan-02 12061.5 13484.9 96.4 11740.1 12937.5 12473.5 13 Feb-02 89.4 94.0 94.0 12837.8 13005.9 122194 12368.2 14 Mar-02 92.3 97.6 97.6 12672.4 13074.3 12760.4 13954.0 13271.7 105.1 15 Apr-02 112.7 112.7 12376.4 13142.7 14817.9 14113.0 13247.6 16 Маy-02 107.7 107.7 13099.4 13211.0 14586.0 13204.1 14233.3 110.5 17 Jun-02 14214.0 110.8 13168.1 13279.4 14709.3 13134.3 108.2 18 Jul-02 109.3 109.3 13006.4 13347.8 14587.1 11607.0 13126.6 19 Aug-02 88.4 89.2 89.2 13006.3 11972.8 13416.2 13913.0 13139.0 20 Sep-02 105.9 101.9 101.9 13649.2 13334.0 13214.9 13484.6 13745.2 21 Oct-02 100.9 104.6 104.6 12743.8 13552.9 14180.7 14702.0 13282.1 22 Nov-02 110.7 110.6 110.6 13297.1 13621.3 15060.4 13908.0 13340.0 A105.1 23 Dec-02 104.3 105.1 13228.0 13689.7 14393.5 12161.0 13410.1 90.7 96.4 96.4 12613.4 13758.1 13264.6 24 Jan-03 12889.7 13479.2 95.6 94.0 13719.3 13826.5 12990.4 25 Feb-03 13292.6 13556.2 98.1 97.6 13619.5 13894.8 13561.3 26 Mar-03 15359.6 13673.3 112.3 112.7 13623.1 13963.2 15743.1 27 Apr-03 14646.4 13717.8 106.8 107.7 13594.5 14031.6 15117.3 28 Мay-03 15208.0 13769.6 110.4 110.8 13729.7 14100.0 15618.2 29 Jun-03 15003.2 13835.4 108.4 109.3 13728.6 14168.4 15483.8 30 Jul-03 12029.5 13870.6 86.7 89.2 13479.7 14236.7 12705.1 31 Aug-03 12989.7 13793.6 94.2 101.9 12743.4 14305.1 14581.6 32 Sep-03 Oct-03 14518.1 13892.3 104.5 104.6 13875.4 14373.5 15039.2 33 15554.6 13963.4 111.4 110.6 14068.3 14441.9 15967.7 34 Nov-03 14598.2 14020.9 104.1 105.1 13884.4 14510.3 15256.2 35 Dec-03 13834.0 14160.3 97.7 96.4 14348.6 14578.6 14055.7 36 Jan-04 13290.8 14193.7 93.6 94.0 14146.2 14647.0 13761.3 37 Feb-04 14341.7 14281.2 100.4 97.6 14694,4 14715.4 14362.2 38 Mar-04 17458.0 14456.0 120.8 112.7 15484.3 14783.8 16668.2 39 Apr-04 16014.0 14570.0 109.9 107.7 14863.9 14852.2 16001.4 40 Мay-04 16334.0 14663.8 111.4 110.8 14746.2 14920.5 16527.1 41 Jun-04 16438.0 14783.4 111.2 109.3 15041.5 14988.9 16380.6 42 Jul-04 13824.0 14932.9 92.6 89.2 15490.6 15057.3 13437.4 43 Аug-04 16060.0 15188.8 105.7 101.9 15755.5 15125.7 15418.1 16673.0 108.5 104.6 15934.9 15194.1 15897.8 Sep-04 Oct-04 44 15368.4 45 16975.0 15486.7 109.6 110.6 15352.9 15262.5 16875.0 Nov-04 16772.0 15667.9 107.0 105.1 15951.9 15330.8 16119.0 46 15983.1 15847.0 100.9 96.4 16577.7 15399.2 14846.9 47 Dec-04 Jan-05 16037.1 97.1 94.0 16574.6 15467.6 14532.3 48 15572.3 16185.9 99.6 97.6 16523.6 15536.0 15163.0 49 Feb-05 16127.0 SUMMARY OUTPUT AVOWA Regression Statistics Multiple R R Square 3 Adjusted R Square Standard Error Observations 0.803 0,645 bie e 0.638 732 to 49 Significance n F ANOVA SS 45823881 25186924 71010805 MS 45823881 535892 df 86 3.76219E-12 1 Regression Residual Total 47 48 Standard Error 212.4 P- value 0.0 Lower 95% 11758.0 53.5 Upper 95% 12612.6 83.3 Coefficients 12185.3 t Stat 57.4 Intercept 9.2 0.0 68.4 7.4 Trend
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