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Consider the following time series data:

Week             1                   2                 3                4                 5                     6

-----------------------------------------------------------------------------

Value            18                 13            16               11              17                   14

Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.

A. mean absolute error

B. mean squared error

C. mean absolute percentage error

d. What is the forecast for Week 7?

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Priyanshu Patel
Priyanshu PatelLv10
7 Mar 2021

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Related textbook solutions

Introductory Statistics
OER Edition, 2013
Openstax
ISBN: 9781938168208

Related questions

consider the following time series data

Week 1 2 3 4 5 6
Value 18 13 16 11 17 14
a. Construct a time series plot. What type of pattern exists in the data?
b. develop a three-week moving average for this time series. Compute mSe and a forecast for week 7.
c. use a 5 0.2 to compute the exponential smoothing values for the time series. Compute mSe and a forecast for week 7.
d. Compare the three-week moving average forecast with the exponential smoothing
forecast using a 5 0.2. Which appears to provide the better forecast based on mSe?
explain.
e. use trial and error to find a value of the exponential smoothing coefficient a that
results in a smaller mSe than what you calculated for a 5 0.2.

EX16_XL_CH05_GRADER_CAP_AS - Travel Expenses 1.3

Project Description:

You are the manager of an information technology (IT) team. Your employees go to training workshops and national conferences to keep up-to-date in the field. You created a list of expenses by category for each employee for the last six months. Now you want to subtotal the data to review total costs by employee and then create a PivotTable to look at the data from different perspectives.

Instructions:

For the purpose of grading the project you are required to perform the following tasks:

Step

Instructions

Points Possible

1

Start Excel. Open the downloaded Excel file named exploring_e05_grader_a1_Expenses.xlsx. Save the workbook as exploring_e05_grader_a1_Expenses_LastFirst, replacing LastFirst with your own name.

0.000

2

On the Subtotals worksheet, sort the data by Employee and further sort by Category, both in alphabetical order.

4.000

3

Use the Subtotals feature to insert subtotal rows by Employee to calculate the total expense by employee.

5.000

4

Collapse the Donaldson and Hart sections to show only their totals. Leave the other employees’ individual rows displayed.

5.000

5

Use the Expenses worksheet to create a blank PivotTable on a new worksheet named Summary. Name the PivotTable Categories.

8.000

6

Use the Category and Expense fields, enabling Excel to determine where the fields go in the PivotTable.

5.000

7

Modify the Values field to determine the average expense by category. Change the custom name to Average Expense.

4.000

8

Format the Values field with Accounting number type.

3.000

9

Type Category in cell A3 and change the Grand Totals layout option to On for Rows Only.

5.000

10

Apply Pivot Style Dark 2 and display banded rows.

Note, depending upon the version of Office being used, the style name may be Light Blue, Pivot Style Dark 2.

5.000

11

Insert a slicer for the Employee field, change the slicer height to 2 inches and apply the Slicer Style Dark 5. Move the slicer below the PivotTable.

Note, depending upon the version of Office being used, the style name may be Light Blue, Slicer Style Dark 5.

5.000

12

Use the Expenses worksheet to create another blank PivotTable on a sheet named Totals. Add the Employee to the Rows and add the Expense field to the Values area. Sort the PivotTable from largest to smallest expense.

10.000

13

Change the name for the Expenses column to Totals and format the field with Accounting number format.

4.000

14

Insert a calculated field to subtract 2659.72 from the Expense field. Format the field with the custom name Above or Below Average and apply Accounting number format to the field.

10.000

15

Set 12.25 width for column B and column C, change the row height of row 3 to 30, and apply word wrap to cell C3.

4.000

16

Create a clustered column PivotChart from the PivotTable. Move the PivotChart to a new sheet named Chart. Hide all field buttons in the PivotChart, if necessary.

Note, Mac users, select the range A3:C8 in the PivotTable. On the Insert tab, click Recommended Charts, and then click Clustered Column to make the chart.

10.000

17

Add a chart title above the chart and type Expenses by Employee. Change the chart style to Style 14.

6.000

18

Apply 11 pt font size to the value axis and display vertical axis as Accounting with zero decimal places.

4.000

19

Create a footer on all worksheets with your name in the left section, the sheet name code in the center section, and the file name code in the right section.

3.000

20

Ensure that the worksheets are correctly named and placed in the following order in the workbook: Subtotals, Summary, Chart, Totals, Expenses. Save the workbook. Close the workbook and then exit Excel. Submit the workbook as directed.

0.000
 

Total Points

100.000

https://www.dropbox.com/s/m7falnl85tfazl9/Torres%20DaSilva_exploring_e05_grader_a1_Expenses.xlsx?dl=0

 
 
  1. Let the mortgage rate be the dependent variable and use the unemployment rate, unemployment duration, real GDP, housing starts, and the CPI as explanatory variables. Conduct a multiple regression estimation and discuss your results. Is this a good model? What do the coefficients on the explanatory variables mean and which explanatory variables are important in explaining mortgage rates? Use any level of significance you believe is appropriate in your discussion. What is the multiple regression equation and the goodness of fit measure?
                  
  1. From your work in question 1, eliminate all the explanatory variables that are not statistically important. What is the equation of your new regression model? Discuss the coefficients and the goodness of fit for the new model.
                    
                     
                     
                     
                     
Year Quarter MORTRATE FFUNDS EMPLOY URATE UDUR RGDP HOUSING CPI TREND
1972 1 7.413 4.563 71179.000 5.900 11.233 5097.179 2020.333 40.300 1
1972 2 7.658 5.473 71434.000 6.033 11.633 5139.128 2094.000 40.700 2
1972 3 7.553 4.750 71866.000 5.933 12.033 5151.245 2201.667 41.000 3
1972 4 7.349 3.540 72677.667 5.767 12.267 5245.974 2406.000 41.333 4
1973 1 7.347 4.300 73463.000 5.700 12.367 5365.045 2241.333 41.600 5
1973 2 7.406 4.740 74038.000 5.567 11.900 5415.712 2371.667 41.933 6
1973 3 7.431 5.143 74971.667 5.367 11.500 5506.396 2424.000 42.367 7
1973 4 7.446 6.537 75971.667 4.933 10.700 5642.669 2378.333 43.033 8
1974 1 7.650 7.817 76663.333 4.933 9.900 5704.098 2139.000 43.933 9
1974 2 8.457 10.560 77119.000 4.800 9.600 5674.100 2016.000 44.800 10
1974 3 8.626 9.997 77852.667 4.767 9.867 5727.960 1642.333 45.933 11
1974 4 8.462 9.323 78216.667 5.133 9.600 5678.713 1586.000 47.300 12
1975 1 8.887 11.250 78511.667 5.200 9.700 5692.210 1515.333 48.567 13
1975 2 9.606 12.090 78621.667 5.633 9.767 5638.411 1202.667 49.933 14
1975 3 9.793 9.347 78182.333 6.600 9.867 5616.526 1023.667 51.467 15
1975 4 9.168 6.303 76953.000 8.267 11.400 5548.156 976.333 52.567 16
1976 1 8.875 5.420 76535.000 8.867 13.867 5587.800 1071.000 53.200 17
1976 2 8.984 6.160 77050.333 8.467 15.567 5683.444 1250.000 54.267 18
1976 3 9.161 5.413 77747.333 8.300 16.167 5759.972 1341.667 55.267 19
1976 4 8.873 4.827 78789.000 7.733 16.467 5889.500 1442.000 55.900 20
1977 1 8.777 5.197 79326.667 7.567 15.933 5932.711 1449.667 56.400 21
1977 2 8.968 5.283 79714.333 7.733 15.500 5965.265 1557.000 57.300 22
1977 3 8.847 4.873 80199.667 7.767 15.200 6008.504 1691.333 58.133 23
1977 4 8.693 4.660 81023.000 7.500 14.800 6079.494 1844.333 59.200 24
1978 1 8.808 5.157 82101.333 7.133 14.567 6197.686 1918.667 60.233 25
1978 2 8.925 5.820 83147.000 6.900 14.067 6309.514 2009.000 61.067 26
1978 3 8.937 6.513 84127.667 6.667 13.633 6309.652 2075.333 61.967 27
1978 4 9.127 6.757 85000.667 6.333 12.600 6329.791 1829.333 63.033 28
1979 1 9.558 7.283 86540.333 6.000 12.167 6574.390 2114.000 64.467 29
1979 2 9.760 8.100 87436.000 6.033 11.600 6640.497 2019.333 65.967 30
1979 3 10.122 9.583 88339.333 5.900 11.133 6729.755 2039.667 67.500 31
1979 4 10.409 10.073 89114.000 5.867 11.333 6741.854 1665.667 69.200 32
1980 1 10.764 10.180 89771.333 5.700 10.833 6749.063 1845.667 71.400 33
1980 2 11.157 10.947 90281.333 5.867 10.467 6799.200 1790.000 73.700 34
1980 3 12.485 13.577 90575.333 5.967 10.633 6816.203 1567.667 76.033 35
1980 4 13.680 15.047 90892.333 6.300 10.667 6837.641 1246.000 79.033 36
1981 1 14.419 12.687 90456.667 7.333 11.200 6696.753 1058.000 81.700 37
1981 2 12.643 9.837 90050.667 7.667 12.367 6688.794 1392.000 83.233 38
1981 3 14.226 15.853 90726.667 7.400 13.467 6813.535 1505.000 85.567 39
1981 4 15.127 16.570 91116.000 7.433 14.133 6947.042 1366.333 87.933 40
1982 1 16.239 17.780 91356.333 7.400 13.733 6895.559 1181.667 89.767 41
1982 2 17.380 17.577 91547.667 7.400 13.933 6978.135 964.000 92.267 42
1982 3 17.736 13.587 91148.667 8.233 13.233 6902.105 873.333 93.767 43
1982 4 17.414 14.227 90520.667 8.833 13.867 6794.878 880.000 94.600 44
1983 1 16.766 14.513 90040.667 9.433 15.033 6825.876 948.000 95.967 45
1983 2 16.222 11.007 89355.667 9.900 16.067 6799.781 1118.667 97.633 46
1983 3 14.033 9.287 88821.333 10.667 17.467 6802.497 1282.667 97.933 47
1983 4 13.030 8.653 88999.000 10.367 19.333 6892.144 1630.333 98.000 48
1984 1 12.763 8.803 89676.333 10.133 20.267 7048.982 1660.333 99.133 49
1984 2 13.641 9.460 90604.333 9.367 20.467 7189.896 1801.667 100.100 50
1984 3 13.460 9.430 91875.000 8.533 19.700 7339.893 1729.333 101.100 51
1984 4 13.333 9.687 93086.333 7.867 19.500 7483.371 1940.000 102.533 52
1985 1 14.035 10.557 94123.000 7.433 18.600 7612.668 1822.667 103.500 53
1985 2 14.494 11.390 95055.000 7.433 17.433 7686.059 1672.000 104.400 54
1985 3 13.648 9.267 95906.000 7.300 16.833 7749.151 1630.333 105.300 55
1985 4 13.064 8.477 96572.333 7.233 15.967 7824.247 1714.333 106.267 56
1986 1 12.785 7.923 97269.667 7.300 15.733 7893.136 1725.667 107.233 57
1986 2 12.141 7.900 97844.333 7.200 15.367 8013.674 1701.000 107.900 58
1986 3 11.731 8.103 98428.333 7.033 15.367 8073.239 1824.667 109.000 59
1986 4 10.584 7.827 98837.667 7.033 14.867 8148.603 1898.667 109.567 60
1987 1 10.246 6.920 99174.667 7.167 14.867 8185.303 1878.000 109.033 61
1987 2 10.235 6.207 99665.000 6.967 15.367 8263.639 1758.667 109.700 62
1987 3 9.684 6.267 100312.667 6.833 15.067 8308.021 1712.333 110.467 63
1987 4 9.115 6.220 100920.333 6.600 14.833 8369.930 1761.333 111.800 64
1988 1 10.343 6.650 101709.000 6.267 14.867 8460.233 1612.000 113.067 65
1988 2 10.482 6.843 102438.000 6.000 14.267 8533.635 1625.000 114.267 66
1988 3 10.864 6.917 103390.333 5.833 14.067 8680.162 1523.667 115.333 67
1988 4 10.068 6.663 104152.000 5.700 14.100 8725.006 1425.333 116.233 68
1989 1 10.359 7.157 105006.667 5.467 13.400 8839.641 1490.667 117.567 69
1989 2 10.496 7.983 105745.667 5.467 13.533 8891.435 1484.000 119.000 70
1989 3 10.410 8.470 106597.000 5.333 12.967 9009.913 1551.333 120.300 71
1989 4 10.820 9.443 107403.000 5.200 12.433 9101.508 1489.333 121.667 72
1990 1 10.636 9.727 107910.333 5.233 11.867 9170.977 1355.667 123.633 73
1990 2 10.008 9.083 108186.000 5.233 11.567 9238.923 1346.000 124.600 74
1990 3 9.814 8.613 108688.000 5.367 11.733 9257.128 1337.333 125.867 75
1990 4 10.132 8.250 109425.333 5.300 11.700 9358.289 1425.667 128.033 76
1991 1 10.324 8.243 109794.667 5.333 11.700 9392.251 1212.333 129.300 77
1991 2 10.103 8.160 109653.667 5.700 12.167 9398.499 1132.000 131.533 78
1991 3 9.959 7.743 109249.000 6.133 12.367 9312.937 1042.667 133.767 79
1991 4 9.501 6.427 108789.000 6.600 12.600 9269.367 894.667 134.767 80
1992 1 9.522 5.863 108318.333 6.833 13.367 9341.642 1011.000 135.567 81
1992 2 9.273 5.643 108314.333 6.867 13.900 9388.845 1042.333 136.600 82
1992 3 8.690 4.817 108328.000 7.100 14.867 9421.565 1087.000 137.733 83
1992 4 8.688 4.023 108351.000 7.367 16.633 9534.346 1241.000 138.667 84
1993 1 8.678 3.770 108631.333 7.600 17.800 9637.732 1152.667 139.733 85
1993 2 8.018 3.257 108895.333 7.633 18.067 9732.979 1183.667 140.800 86
1993 3 8.192 3.037 109306.667 7.367 18.600 9834.510 1228.333 142.033 87
1993 4 7.723 3.040 109948.333 7.133 18.033 9850.973 1167.667 143.067 88
1994 1 7.453 3.000 110542.333 7.067 17.633 9908.347 1266.000 144.100 89
1994 2 7.088 3.060 111240.000 6.800 17.933 9955.641 1299.000 144.767 90
1994 3 7.046 2.990 112015.333 6.633 18.333 10091.049 1433.667 145.967 91
1994 4 7.296 3.213 112878.000 6.567 18.867 10188.954 1391.000 146.700 92
1995 1 8.428 3.940 113920.667 6.200 19.100 10327.019 1466.667 147.533 93
1995 2 8.594 4.487 114922.000 6.000 18.833 10387.382 1454.333 148.900 94
1995 3 9.105 5.167 115837.000 5.633 18.367 10506.372 1472.000 149.767 95
1995 4 8.785 5.810 116707.667 5.467 17.133 10543.644 1324.000 150.867 96
1996 1 7.918 6.020 117141.667 5.667 16.833 10575.100 1287.333 152.100 97
1996 2 7.696 5.797 117636.333 5.667 16.300 10665.060 1415.333 152.867 98
1996 3 7.339 5.720 118182.667 5.567 16.233 10737.478 1417.333 153.700 99
1996 4 7.272 5.363 118689.333 5.533 16.600 10817.896 1460.667 155.067 100
1997 1 8.102 5.243 119480.667 5.500 17.400 10998.322 1495.667 156.400 101
1997 2 8.147 5.307 120215.000 5.267 16.933 11096.976 1501.333 157.300 102
1997 3 7.703 5.280 120931.667 5.333 15.933 11212.205 1417.000 158.667 103
1997 4 7.793 5.277 121684.333 5.233 15.767 11284.587 1432.667 159.633 104
1998 1 7.927 5.523 122559.333 5.000 15.500 11472.137 1476.000 160.000 105
1998 2 7.470 5.533 123270.667 4.867 16.100 11615.636 1457.667 160.800 106
1998 3 7.205 5.507 124248.333 4.667 15.800 11715.393 1532.000 161.667 107
1998 4 7.050 5.520 125007.000 4.633 15.167 11832.486 1558.667 162.000 108
1999 1 7.098 5.500 125798.333 4.400 14.500 11942.032 1572.333 162.533 109
1999 2 6.872 5.533 126509.333 4.533 14.067 12091.614 1631.333 163.367 110
1999 3 6.764 4.860 127272.667 4.433 14.200 12287.000 1722.333 164.133 111
1999 4 6.878 4.733 128027.667 4.300 13.533 12403.293 1709.333 164.733 112
2000 1 7.182 4.747 128843.667 4.267 13.667 12498.694 1574.333 165.967 113
2000 2 7.786 5.093 129592.333 4.233 13.267 12662.385 1650.667 167.200 114
2000 3 7.841 5.307 130485.000 4.067 13.033 12877.593 1654.667 168.433 115
2000 4 8.257 5.677 131255.000 4.033 12.800 12924.179 1659.000 170.100 116
2001 1 8.316 6.273 132032.333 3.933 12.433 13160.842 1586.667 171.433 117
2001 2 8.020 6.520 132283.667 4.000 12.833 13178.419 1503.667 173.000 118
2001 3 7.621 6.473 132552.333 3.900 12.533 13260.506 1544.000 174.233 119
2001 4 7.007 5.593 132759.000 4.233 12.767 13222.690 1605.000 175.900 120
2002 1 7.130 4.327 132404.333 4.400 12.400 13299.984 1630.000 177.133 121
2002 2 6.964 3.497 132007.000 4.833 13.133 13244.784 1599.667 177.633 122
2002 3 6.771 2.133 131207.667 5.500 14.033 13280.859 1570.000 177.500 123
2002 4 6.972 1.733 130784.000 5.700 15.033 13397.002 1723.000 178.067 124
2003 1 6.813 1.750 130659.333 5.833 16.667 13478.152 1691.000 179.467 125
2003 2 6.289 1.740 130577.000 5.733 17.000 13538.072 1697.333 180.433 126
2003 3 6.075 1.443 130587.667 5.867 17.967 13559.032 1729.667 181.500 127
2003 4 5.841 1.250 130434.333 5.867 18.367 13634.253 1736.000 183.367 128
2004 1 5.507 1.247 130204.333 6.133 19.433 13751.543 1753.667 183.067 129
2004 2 6.034 1.017 130217.667 6.133 19.467 13985.073 1889.667 184.433 130
2004 3 5.919 0.997 130522.667 5.833 19.667 14145.645 2035.667 185.133 131
2004 4 5.598 1.003 130929.000 5.700 19.933 14221.147 1918.333 186.700 132
2005 1 6.106 1.010 131647.667 5.600 19.967 14329.523 1937.333 188.167 133
2005 2 5.894 1.433 131977.000 5.433 19.000 14464.984 1977.000 189.367 134
2005 3 5.736 1.950 132543.667 5.433 19.533 14609.876 1965.333 191.400 135
2005 4 5.768 2.470 133004.333 5.300 19.367 14771.602 2071.667 192.367 136
2006 1 5.708 2.943 133733.000 5.100 18.700 14839.782 2051.333 193.667 137
2006 2 5.764 3.460 134471.333 4.967 17.967 14972.054 2100.000 196.600 138
2006 3 6.226 3.980 134951.000 4.967 17.633 15066.597 2068.667 198.433 139
2006 4 6.247 4.457 135754.000 4.733 17.267 15267.026 2120.333 199.467 140
2007 1 6.602 4.907 136274.667 4.633 16.800 15302.705 1855.000 201.267 141
2007 2 6.560 5.247 136703.667 4.633 17.100 15326.368 1702.333 203.167 142
2007 3 6.244 5.247 137073.333 4.433 16.200 15456.928 1570.000 202.333 143
2007 4 6.215 5.257 137625.333 4.500 16.933 15493.328 1461.333 204.317 144
2008 1 6.358 5.250 137986.667 4.500 16.667 15582.085 1451.000 206.631 145
2008 2 6.552 5.073 138067.000 4.667 16.833 15666.738 1289.000 207.939 146
2008 3 6.225 4.497 138299.333 4.800 16.967 15761.967 1166.000 210.490 147
2008 4 5.872 3.177 138351.333 5.000 16.967 15671.383 1064.000 212.770 148
2009 1 6.087 2.087 137878.000 5.333 16.867 15752.308 1010.667 215.538 149
2009 2 6.322 1.940 137168.667 6.000 17.767 15667.032 862.333 218.861 150
2009 3 5.841 0.507 135568.667 6.867 19.567 15328.027 663.000 213.849 151
2009 4 5.060 0.183 133311.667 8.267 20.300 15155.940 525.667 212.378 152
2010 1 5.012 0.180 131450.667 9.300 22.667 15134.117 534.333 213.507 153
2010 2 5.162 0.157 130481.667 9.633 25.667 15189.222 588.333 215.344 154
2010 3 4.922 0.120 129979.333 9.933 28.700 15356.058 567.667 217.030 155
2010 4 4.996 0.133 129805.667 9.833 30.567 15415.145 618.000 217.374 156
2011 1 4.922 0.193 130442.667 9.633 33.933 15557.277 602.000 217.297 157
2011 2 4.447 0.187 130417.333 9.467 33.667 15671.967 579.667 217.934 158
2011 3 4.436 0.187 130748.667 9.500 34.200 15750.625 542.333 219.699 159
2011 4 4.847 0.157 131078.333 9.033 37.900 15712.754 582.333 222.044 160
2012 1 4.651 0.093 131766.667 9.067 39.400 15825.096 574.333 224.568 161
2012 2 4.292 0.083 132176.000 9.000 40.533 15820.700 619.333 226.033 162
2012 3 4.002 0.073 132734.000 8.633 39.767 16004.107 671.667 227.047 163
2012 4 3.922 0.103 133523.000 8.267 39.733 16129.418 707.333 228.326 164
2013 1 3.795 0.153 133942.000 8.200 39.700 16198.807 739.333 228.808 165
2013 2 3.554 0.143 134352.333 8.033 39.567 16220.667 780.333 229.841 166
2013 3 3.359 0.160 134877.333 7.800 38.733 16239.138 908.000 231.369 167
2013 4 3.497 0.143 135514.333 7.733 36.333 16382.964 953.333 232.299 168
2014 1 3.672 0.117 136099.667 7.533 36.567 16403.180 868.000 232.045 169
2014 2 4.440 0.083 136624.333 7.233 37.433 16531.685 882.333 233.300 170
2014 3 4.293 0.087 137256.333 6.933 36.067 16663.649 1009.000 234.163 171
2014 4 4.365 0.073 137762.333 6.667 35.633 16621.696 934.000 235.621 172
2015 1 4.228 0.093 138567.333 6.200 34.400 16830.111 987.000 236.872 173
2015 2 4.135 0.090 139313.000 6.067 32.200 17033.572 1030.667 237.478 174
2015 3 3.964 0.100 140121.333 5.700 32.567 17113.945 1049.333 236.888 175
2015 4 3.717 0.110 140800.000 5.533 31.200 17254.744 980.667 235.320 176
2016 1 3.819 0.123 141503.333 5.433 30.000 17397.029 1157.000 236.938 177
2016 2 3.955 0.137 142141.667 5.100 27.467 17438.802 1161.667 237.862 178
2016 3 3.898 0.160 142860.000 5.033 27.733 17456.225 1129.333 237.871 179
2016 4 3.738 0.360 143447.667 4.933 28.867 17523.374 1145.667 237.780 180
2017 1 3.589 0.373 143996.000 4.900 27.733 17622.486 1160.667 239.486 181
2017 2 3.446 0.397 144705.000 4.900 27.333 17706.705 1151.333 240.601 182
2017 3 3.842 0.450 145243.000 4.767 26.100 17784.185 1254.000 242.164 183
2017 4 4.173 0.700 145831.333 4.600 25.233 17863.023 1230.667 243.830 184
2018 1 3.980 0.950 146337.667 4.367 24.833 17995.150 1169.333 244.065 185
2018 2 3.884 1.153 146867.667 4.300 25.200 18120.843 1175.333 245.368 186
2018 3 3.922 1.203 147406.667 4.133 24.800 18223.758 1259.667 247.273 187
2018 4 4.282 1.447 148047.667 4.067 23.667 18323.963 1320.667 249.250 188
2019 1 4.545 1.737 148742.333 3.900 21.833 18511.576 1259.667 250.579 189
2019 2 4.567 1.923 149409.000 3.800 23.267 18664.973 1233.000 251.829 190
2019 3 4.785 2.220 150058.333 3.800 21.967 18765.256 1185.000 252.759 191
2019 4 4.374 2.403 150675.333 3.867 21.467 18910.332 1213.000 253.311 192
                     
                     
                     
MORTRATE 30-Year Fixed Mortgage Rate              
FFUNDS Federal Funds Rate                
EMPLOY Non-Farm Employment (Thousands)              
URATE Unemployment Rate                
UDUR Average Unemployment Duration (Weeks)            
RGDP Real GDP (Billions of dollars)              
HOUSING Housing Starts (Thousands)                
CPI Consumer Price Index                
TREND Linear trend                  

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