Ismch17 - 96 Instructors Solutions Manual for Statistics for Business Economics 5th Edition Chapter 17 Time Series Analysis and Forecasting 17.1

Info iconThis preview shows pages 1–4. Sign up to view the full content.

View Full Document Right Arrow Icon
96 th Edition Chapter 17: Time Series Analysis and Forecasting 17.1 Various answers. A price index of a ‘market basket’ of goods and services could be compiled to measure how prices have changed. Difficulties of measuring prices via a market basket of goods includes the definition of the market basket – the types of goods may have changed (e.g., land-lines vs. wireless communication, mainframe computers to servers & PCs). Items may become obsolete and the quality or technological improvements may create difficulties in capturing solely price changes 17-2 a. e.g., 2 100(35.875/35) 102.5 I = = b. e.g., 1 100(35/34.375) 101.82 I = = Week_17-2 Price Base_Week1 Base_Week4 1 35 100.00 101.82 2 35.875 102.50 104.36 3 34.75 99.29 101.09 4 34.375 98.21 100.00 5 35 100.00 101.82 6 34.875 99.64 101.45 7 35 100.00 101.82 8 34.75 99.29 101.09 9 34.75 99.29 101.09 10 35.25 100.71 102.55 11 38.75 110.71 112.73 12 37.125 106.07 108.00 17-3 a. Unweighted aggregate price index Month Average Index of Average January 6.32 100.00 February 6.34 100.32 March 6.32 99.95 April 6.57 103.90 May 6.62 104.80 June 6.73 106.54 July 6.85 108.33 August 6.90 109.12 September 6.96 110.13 October 7.03 111.23 November 7.13 112.87 December 7.33 116.03
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
97 th Edition b. Laspeyres price index Month 1 o i i q p Laspeyres Index January 3275.58 100.00 February 3259.06 99.50 March 3248.35 99.17 April 3374.70 103.03 May 3406.21 103.99 June 3471.70 105.99 July 3508.62 107.11 August 3543.51 108.18 September 3574.80 109.13 October 3603.47 110.01 November 3660.80 111.76 December 3779.64 115.39 c. Laspeyres quantity index Month 1 0 i i q p Laspeyres Index January 3275.58 100.00 February 3168.09 96.72 March 3414.60 104.24 April 2944.61 89.90 May 3160.73 96.49 June 2815.03 85.94 July 3678.28 81.77 August 3557.50 78.08 September 3512.83 107.24 October 3645.16 111.28 November 3866.05 118.03 December 4197.62 128.15 17-4 a. Unweighted average index Year Average Index of Average 1 11.8 100.00 2 12.43 105.37 3 12.93 109.60 4 13.30 112.71 5 13.63 115.54 6 13.83 117.23
Background image of page 2
Chapter 17: Time Series Analysis and Forecasting 98 b. Laspeyres index Year 1 o i i q p Laspeyres Index 1 1120.4 100.00 2 1174.30 104.81 3 1237.90 110.49 4 1256.40 112.14 5 1296.40 115.71 6 1316.10 117.47 17-5 Spliced index with year 4 as the base: Year 1: 100(100/120.2) = 83.19 Year 2: 100(108.4/120.2) = 90.18 Year 3: 100(114.3/120.2) = 95.09 17.6 A price index for energy is helpful in that it allows us to say something about price movements over time for a group of commodities, namely, energy prices. A weighted index of prices allows one to compare the cost of a group of products
Background image of page 3

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Image of page 4
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 03/25/2009 for the course FIN FIN534 taught by Professor Stevenjordan during the Spring '09 term at Korea Advanced Institute of Science and Technology.

Page1 / 45

Ismch17 - 96 Instructors Solutions Manual for Statistics for Business Economics 5th Edition Chapter 17 Time Series Analysis and Forecasting 17.1

This preview shows document pages 1 - 4. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online