Assignment:
Section 1. Computation of Indices
Below is information on food items for the years 2000 and 2004. [Due Day 4]
|
Item
|
2000
|
2004
|
|
Price
|
Quantity
|
Price
|
Quantity
|
|
Margarine (pound)
|
$0.81
|
18
|
$0.89
|
27
|
|
Shortening (pound)
|
0.81
|
5
|
0.94
|
9
|
|
Milk (½ gallon)
|
1.44
|
70
|
1.43
|
65
|
|
Potato chips
|
2.91
|
27
|
3.07
|
33
|
A. Compute a simple price index for each of the four items. Use 2000 as the base period.
B. Compute a simple aggregate price index. Use 2000 as the base period.
C. Compute Laspeyres’ price index for 2004 using 2000 as the base period.
D. Compute Paasche’s index for 2004 using 2000 as the base period.
E. Determine Fisher’s ideal index using the values for the Laspeyres and Paasche indexes computed in the two previous problems.
F. Determine a value index for 2004 using 2000 as the base period.
Section 2. Convert Price Data to Indices
The following historical data obtained from the U.S Department of Energy (https://www.eia.doe.gov/oil_gas/petroleum/data_publications/wrgp/mogas_history.html) shows the yearly average regular conventional retail gasoline Price (US$ per Gallon) for the period 1990-2010.
|
Year
|
Code
|
Av. Regular Retail Gasoline Prices (US$ per Gallon)
|
|
1990
|
1
|
1.30
|
|
|
1991
|
2
|
1.10
|
|
|
1992
|
3
|
1.09
|
|
|
1993
|
4
|
1.07
|
|
|
1994
|
5
|
1.07
|
|
|
1995
|
6
|
1.10
|
|
|
1996
|
7
|
1.19
|
|
|
1997
|
8
|
1.19
|
|
|
1998
|
9
|
1.02
|
|
|
1999
|
10
|
1.12
|
|
|
2000
|
11
|
1.46
|
|
|
2001
|
12
|
1.38
|
|
|
2002
|
13
|
1.31
|
|
|
2003
|
14
|
1.52
|
|
|
2004
|
15
|
1.81
|
|
|
2005
|
16
|
2.24
|
|
|
2006
|
17
|
2.53
|
|
|
2007
|
18
|
2.77
|
|
|
2008
|
19
|
3.21
|
|
|
2009
|
20
|
2.31
|
|
|
2010
|
21
|
2.72
|
|
Q1. Determine the linear regression equation for the gasoline retail price (1990-2010).Using the equation, forecast the gasoline price for 2012, which is year 23 (1990 = Year 1).
Q2. Compute the gasoline retail price data to a moving average series using a 5-year interval. Draw the trendline for the moving average series. Explain the trend.
To compute the moving average, first, insert the original series in Excel Column A. Use Excel, Data Analysis, Moving Average function. Show the input range. Insert 5 for interval, show the output range next to the original series in column B. Check chart output box. You may also use Megastat, Time Series/Forecasting function, to compute the moving average.
Q3. Convert the gasoline retail price to a price index using the year 1990 as a base year (1990 = 100). Graph the data in line chart. What do the indices suggest about the rate of price inflation? Has the rate of inflation increased, decreased, or remained unchanged during 1990-2010?
Provide complete and step by step solution for the question and show calculations and use formulas.