A) Perform the plots of import/export versus yearly & apply the moving average technique to smooth...
A) Perform the plots of import/export versus yearly & apply the moving average technique to smooth them out using PHSTATS.
B) Please select one of the appropriate forecasting method to predict the import & export (use the data from 1985 to 2018 and try to predict the import/export number of 2019)
| year | Import (Mil$) | Export (Year) |
| 1985 | 3861.7 | 3855.7 |
| 1986 | 4771 | 3106.3 |
| 1987 | 6293.6 | 3497.3 |
| 1988 | 8510.9 | 5021.6 |
| 1989 | 11989.7 | 5755.4 |
| 1990 | 15237.4 | 4806.4 |
| 1991 | 18969.2 | 6278.2 |
| 1992 | 25727.5 | 7418.5 |
| 1993 | 31539.9 | 8762.9 |
| 1994 | 38786.8 | 9281.7 |
| 1995 | 45543.2 | 11753.7 |
| 1996 | 51512.8 | 11992.6 |
| 1997 | 62557.7 | 12862.2 |
| 1998 | 71168.6 | 14241.2 |
| 1999 | 81788.2 | 13111.1 |
| 2000 | 100018.2 | 16185.2 |
| 2001 | 102278.4 | 19182.3 |
| 2002 | 125192.6 | 22127.7 |
| 2003 | 152436.0969 | 28367.94286 |
| 2004 | 196682.0339 | 34427.77246 |
| 2005 | 243470.1048 | 41192.01012 |
| 2006 | 287774.3526 | 53673.00834 |
| 2007 | 321442.8669 | 62936.89158 |
| 2008 | 337772.6278 | 69732.83754 |
| 2009 | 296373.8835 | 69496.67861 |
| 2010 | 364952.6336 | 91911.08094 |
| 2011 | 399371.2326 | 104121.5236 |
| 2012 | 425619.0826 | 110516.6157 |
| 2013 | 440430.0196 | 121746.1886 |
| 2014 | 468474.8949 | 123657.2034 |
| 2015 | 483201.6554 | 115873.3653 |
| 2016 | 462419.9916 | 115594.7845 |
| 2017 | 505220.2333 | 129797.5872 |
| 2018 | 539675.5908 | 120148.1411 |
Homework Answers
A) PLOTS of import/ export versus year -
Using moving average of order 3 for both import and export -
| Year | Import (Mil$) | Export (Year) | MA Import | MA Export |
| 1985 | 3,861.70 | 3,855.70 | ||
| 1986 | 4,771.00 | 3,106.30 | ||
| 1987 | 6,293.60 | 3,497.30 | 4,975.43 | 3,486.43 |
| 1988 | 8,510.90 | 5,021.60 | 6,525.17 | 3,875.07 |
| 1989 | 11,989.70 | 5,755.40 | 8,931.40 | 4,758.10 |
| 1990 | 15,237.40 | 4,806.40 | 11,912.67 | 5,194.47 |
| 1991 | 18,969.20 | 6,278.20 | 15,398.77 | 5,613.33 |
| 1992 | 25,727.50 | 7,418.50 | 19,978.03 | 6,167.70 |
| 1993 | 31,539.90 | 8,762.90 | 25,412.20 | 7,486.53 |
| 1994 | 38,786.80 | 9,281.70 | 32,018.07 | 8,487.70 |
| 1995 | 45,543.20 | 11,753.70 | 38,623.30 | 9,932.77 |
| 1996 | 51,512.80 | 11,992.60 | 45,280.93 | 11,009.33 |
| 1997 | 62,557.70 | 12,862.20 | 53,204.57 | 12,202.83 |
| 1998 | 71,168.60 | 14,241.20 | 61,746.37 | 13,032.00 |
| 1999 | 81,788.20 | 13,111.10 | 71,838.17 | 13,404.83 |
| 2000 | 1,00,018.20 | 16,185.20 | 84,325.00 | 14,512.50 |
| 2001 | 1,02,278.40 | 19,182.30 | 94,694.93 | 16,159.53 |
| 2002 | 1,25,192.60 | 22,127.70 | 1,09,163.07 | 19,165.07 |
| 2003 | 1,52,436.10 | 28,367.94 | 1,26,635.70 | 23,225.98 |
| 2004 | 1,96,682.03 | 34,427.77 | 1,58,103.58 | 28,307.81 |
| 2005 | 2,43,470.10 | 41,192.01 | 1,97,529.41 | 34,662.58 |
| 2006 | 2,87,774.35 | 53,673.01 | 2,42,642.16 | 43,097.60 |
| 2007 | 3,21,442.87 | 62,936.89 | 2,84,229.11 | 52,600.64 |
| 2008 | 3,37,772.63 | 69,732.84 | 3,15,663.28 | 62,114.25 |
| 2009 | 2,96,373.88 | 69,496.68 | 3,18,529.79 | 67,388.80 |
| 2010 | 3,64,952.63 | 91,911.08 | 3,33,033.05 | 77,046.87 |
| 2011 | 3,99,371.23 | 1,04,121.52 | 3,53,565.92 | 88,509.76 |
| 2012 | 4,25,619.08 | 1,10,516.62 | 3,96,647.65 | 1,02,183.07 |
| 2013 | 4,40,430.02 | 1,21,746.19 | 4,21,806.78 | 1,12,128.11 |
| 2014 | 4,68,474.89 | 1,23,657.20 | 4,44,841.33 | 1,18,640.00 |
| 2015 | 4,83,201.66 | 1,15,873.37 | 4,64,035.52 | 1,20,425.59 |
| 2016 | 4,62,419.99 | 1,15,594.78 | 4,71,365.51 | 1,18,375.12 |
| 2017 | 5,05,220.23 | 1,29,797.59 | 4,83,613.96 | 1,20,421.91 |
| 2018 | 5,39,675.59 | 1,20,148.14 | 5,02,438.61 | 1,21,846.84 |
B) From the above plots, it is evident that exponential smoothing method of forecasting will be most suitable. The exponential smooth results with dampening factor 0.9 and forecast for 2019 are shown below.
| Year | Import (Mil$) | Export (Year) | Exponential Smoothing Import | Exponential Smoothing Export |
| 1985 | 3,861.70 | 3,855.70 | ||
| 1986 | 4,771.00 | 3,106.30 | 3,861.70 | 3,855.70 |
| 1987 | 6,293.60 | 3,497.30 | 4,680.07 | 3,181.24 |
| 1988 | 8,510.90 | 5,021.60 | 6,132.25 | 3,465.69 |
| 1989 | 11,989.70 | 5,755.40 | 8,273.03 | 4,866.01 |
| 1990 | 15,237.40 | 4,806.40 | 11,618.03 | 5,666.46 |
| 1991 | 18,969.20 | 6,278.20 | 14,875.46 | 4,892.41 |
| 1992 | 25,727.50 | 7,418.50 | 18,559.83 | 6,139.62 |
| 1993 | 31,539.90 | 8,762.90 | 25,010.73 | 7,290.61 |
| 1994 | 38,786.80 | 9,281.70 | 30,886.98 | 8,615.67 |
| 1995 | 45,543.20 | 11,753.70 | 37,996.82 | 9,215.10 |
| 1996 | 51,512.80 | 11,992.60 | 44,788.56 | 11,499.84 |
| 1997 | 62,557.70 | 12,862.20 | 50,840.38 | 11,943.32 |
| 1998 | 71,168.60 | 14,241.20 | 61,385.97 | 12,770.31 |
| 1999 | 81,788.20 | 13,111.10 | 70,190.34 | 14,094.11 |
| 2000 | 1,00,018.20 | 16,185.20 | 80,628.41 | 13,209.40 |
| 2001 | 1,02,278.40 | 19,182.30 | 98,079.22 | 15,887.62 |
| 2002 | 1,25,192.60 | 22,127.70 | 1,01,858.48 | 18,852.83 |
| 2003 | 1,52,436.10 | 28,367.94 | 1,22,859.19 | 21,800.21 |
| 2004 | 1,96,682.03 | 34,427.77 | 1,49,478.41 | 27,711.17 |
| 2005 | 2,43,470.10 | 41,192.01 | 1,91,961.67 | 33,756.11 |
| 2006 | 2,87,774.35 | 53,673.01 | 2,38,319.26 | 40,448.42 |
| 2007 | 3,21,442.87 | 62,936.89 | 2,82,828.84 | 52,350.55 |
| 2008 | 3,37,772.63 | 69,732.84 | 3,17,581.46 | 61,878.26 |
| 2009 | 2,96,373.88 | 69,496.68 | 3,35,753.51 | 68,947.38 |
| 2010 | 3,64,952.63 | 91,911.08 | 3,00,311.85 | 69,441.75 |
| 2011 | 3,99,371.23 | 1,04,121.52 | 3,58,488.55 | 89,664.15 |
| 2012 | 4,25,619.08 | 1,10,516.62 | 3,95,282.96 | 1,02,675.79 |
| 2013 | 4,40,430.02 | 1,21,746.19 | 4,22,585.47 | 1,09,732.53 |
| 2014 | 4,68,474.89 | 1,23,657.20 | 4,38,645.56 | 1,20,544.82 |
| 2015 | 4,83,201.66 | 1,15,873.37 | 4,65,491.96 | 1,23,345.97 |
| 2016 | 4,62,419.99 | 1,15,594.78 | 4,81,430.69 | 1,16,620.63 |
| 2017 | 5,05,220.23 | 1,29,797.59 | 4,64,321.06 | 1,15,697.37 |
| 2018 | 5,39,675.59 | 1,20,148.14 | 5,01,130.32 | 1,28,387.57 |
| 2019 | 5,35,821.06 | 1,20,972.08 |
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