Consider the data on new orders for computers and electronic products and the M1
ID: 472569 • Letter: C
Question
Consider the data on new orders for computers and electronic products and the M1 money supply for the years 2011 through 2014.
Year
Month
New Orders for Computers and Electronic Products
M-1 Money Supply
2011
1
19222
1855.6
2011
2
20727
1874.7
2011
3
24893
1892.0
2011
4
19375
1897.8
2011
5
20152
1934.3
2011
6
25075
1947.0
2011
7
18615
2001.5
2011
8
21289
2112.9
2011
9
27014
2126.0
2011
10
22179
2137.4
2011
11
20761
2172.0
2011
12
27818
2168.2
2012
1
19447
2202.3
2012
2
23043
2212.2
2012
3
26734
2228.7
2012
4
21897
2245.3
2012
5
22403
2251.0
2012
6
24942
2262.3
2012
7
19365
2314.6
2012
8
20240
2346.5
2012
9
25478
2383.6
2012
10
20790
2415.5
2012
11
20362
2423.2
2012
12
27841
2457.7
2013
1
17393
2467.6
2013
2
18725
2470.4
2013
3
22919
2474.8
2013
4
19560
2511.0
2013
5
20333
2522.0
2013
6
24619
2517.9
2013
7
18065
2545.6
2013
8
18487
2557.3
2013
9
24877
2578.8
2013
10
20410
2620.2
2013
11
20194
2622.2
2013
12
24955
2654.5
1.Using the same data, develop exponential smoothing forecasts with an alpha () of 0.85 and 0.15. Assume the first month forecast is the same as the actual data
Year
Month
New Orders for Computers and Electronic Products
M-1 Money Supply
2011
1
19222
1855.6
2011
2
20727
1874.7
2011
3
24893
1892.0
2011
4
19375
1897.8
2011
5
20152
1934.3
2011
6
25075
1947.0
2011
7
18615
2001.5
2011
8
21289
2112.9
2011
9
27014
2126.0
2011
10
22179
2137.4
2011
11
20761
2172.0
2011
12
27818
2168.2
2012
1
19447
2202.3
2012
2
23043
2212.2
2012
3
26734
2228.7
2012
4
21897
2245.3
2012
5
22403
2251.0
2012
6
24942
2262.3
2012
7
19365
2314.6
2012
8
20240
2346.5
2012
9
25478
2383.6
2012
10
20790
2415.5
2012
11
20362
2423.2
2012
12
27841
2457.7
2013
1
17393
2467.6
2013
2
18725
2470.4
2013
3
22919
2474.8
2013
4
19560
2511.0
2013
5
20333
2522.0
2013
6
24619
2517.9
2013
7
18065
2545.6
2013
8
18487
2557.3
2013
9
24877
2578.8
2013
10
20410
2620.2
2013
11
20194
2622.2
2013
12
24955
2654.5
Explanation / Answer
Exponential smoothing forecasts uses a simple formula as given below
Forecasted value of current period = Forecasted value of previous period + alpha times the difference between the actual and forecasted values of previous period
One can use scientific calculator or excel to make use of the above mentioned formula repeatedly to get the forecasts.
Alpha .85 Alpha .85 Alpha .15 Alpha .15 Actual Actual Forecasted Forecasted Forecasted Forecasted Year Month New Orders for Computers and Electronic Products M-1 Money Supply New Orders for Computers and Electronic Products M-1 Money Supply New Orders for Computers and Electronic Products M-1 Money Supply 2011 1 19222 1855.6 19222 1855.6 19222 1855.6 2011 2 20727 1874.7 19222 1855.6 19222 1855.6 2011 3 24893 1892 20501.25 1871.835 19447.75 1858.465 2011 4 19375 1897.8 24234.2375 1888.97525 20264.5375 1863.49525 2011 5 20152 1934.3 20103.88563 1896.476288 20131.10688 1868.640963 2011 6 25075 1947 20144.78284 1928.626443 20134.24084 1878.489818 2011 7 18615 2001.5 24335.46743 1944.243966 20875.35472 1888.766345 2011 8 21289 2112.9 19473.07011 1992.911595 20536.30151 1905.676394 2011 9 27014 2126 21016.61052 2094.901739 20649.20628 1936.759935 2011 10 22179 2137.4 26114.39158 2121.335261 21603.92534 1965.145944 2011 11 20761 2172 22769.30874 2134.990289 21690.18654 1990.984053 2011 12 27818 2168.2 21062.24631 2166.448543 21550.80856 2018.136445 2012 1 19447 2202.3 26804.63695 2167.937282 22490.88727 2040.645978 2012 2 23043 2212.2 20550.64554 2197.145592 22034.30418 2064.894081 2012 3 26734 2228.7 22669.14683 2209.941839 22185.60856 2086.989969 2012 4 21897 2245.3 26124.27202 2225.886276 22867.86727 2108.246474 2012 5 22403 2251 22531.0908 2242.387941 22722.23718 2128.804503 2012 6 24942 2262.3 22422.21362 2249.708191 22674.3516 2147.133827 2012 7 19365 2314.6 24564.03204 2260.411229 23014.49886 2164.408753 2012 8 20240 2346.5 20144.85481 2306.471684 22467.07403 2186.93744 2012 9 25478 2383.6 20225.72822 2340.495753 22133.01293 2210.871824 2012 10 20790 2415.5 24690.15923 2377.134363 22634.76099 2236.781051 2012 11 20362 2423.2 21375.02388 2409.745154 22358.04684 2263.588893 2012 12 27841 2457.7 20513.95358 2421.181773 22058.63982 2287.530559 2013 1 17393 2467.6 26741.94304 2452.222266 22925.99384 2313.055975 2013 2 18725 2470.4 18795.34146 2465.29334 22096.04477 2336.237579 2013 3 22919 2474.8 18735.55122 2469.634001 21590.38805 2356.361942 2013 4 19560 2511 22291.48268 2474.0251 21789.67984 2374.127651 2013 5 20333 2522 19969.7224 2505.453765 21455.22787 2394.658503 2013 6 24619 2517.9 20278.50836 2519.518065 21286.89369 2413.759728 2013 7 18065 2545.6 23967.92625 2518.14271 21786.70963 2429.380769 2013 8 18487 2557.3 18950.43894 2541.481406 21228.45319 2446.813653 2013 9 24877 2578.8 18556.51584 2554.927211 20817.23521 2463.386605 2013 10 20410 2620.2 23928.92738 2575.219082 21426.19993 2480.698614 2013 11 20194 2622.2 20937.83911 2613.452862 21273.76994 2501.623822 2013 12 24955 2654.5 20305.57587 2620.887929 21111.80445 2519.710249