Question: In this exercise, we are going to work with the housing market data. Data in file Housing_Market.xls provides quarterly data of the number
In this exercise, we are going to work with the housing market data. Data in file "Housing_Market.xls" provides quarterly data of the number of housing starts in Texas from 1998 to 2011. Housing starts reflects the number of privately owned new houses on which construction has been started in a given period. The dataset includes information data on the unemployment rate, real gross state product (GSP), GSP growth, sales of lumber, sheet goods, and miscellaneous hardware.
1.Construct a time series plot of housing starts. Do you see a pattern in the data?
2.Use exponential smoothing with =0.4 to develop a forecast of housing starts for the first quarter of 2012.
3.Compute the accuracy of your forecast using all three measures discussed in the class?
4.Applying the forecast accuracy measures, would you prefer a smoothing constant of =0.2, =0.3, or =0.4 for the housing start time series? Are the conclusions the same regardless of the choice of the forecast accuracy measure?
5.Compute four-quarter and five-quarter moving averages for the housing starts time series.
6.Compute the forecast accuracy of the four-quarter and five-quarter moving averages.
7.Do you think moving average and exponential smoothing are appropriate forecasting methods for Housing starts time series? Why?
| state | Year | Quarter | Unemployment rate | Housing starts |
| TX | 1998 | 1 | 4.97 | 22859 |
| TX | 1998 | 2 | 4.90 | 24001 |
| TX | 1998 | 3 | 5.00 | 25140 |
| TX | 1998 | 4 | 4.90 | 25812 |
| TX | 1999 | 1 | 4.70 | 25253 |
| TX | 1999 | 2 | 4.73 | 24736 |
| TX | 1999 | 3 | 4.80 | 25253 |
| TX | 1999 | 4 | 4.67 | 24262 |
| TX | 2000 | 1 | 4.57 | 27173 |
| TX | 2000 | 2 | 4.47 | 25036 |
| TX | 2000 | 3 | 4.30 | 26111 |
| TX | 2000 | 4 | 4.20 | 27271 |
| TX | 2001 | 1 | 4.30 | 27520 |
| TX | 2001 | 2 | 4.73 | 27886 |
| TX | 2001 | 3 | 5.23 | 26738 |
| TX | 2001 | 4 | 5.80 | 27553 |
| TX | 2002 | 1 | 6.20 | 28418 |
| TX | 2002 | 2 | 6.37 | 30297 |
| TX | 2002 | 3 | 6.40 | 30468 |
| TX | 2002 | 4 | 6.53 | 31291 |
| TX | 2003 | 1 | 6.67 | 30741 |
| TX | 2003 | 2 | 6.83 | 31882 |
| TX | 2003 | 3 | 6.80 | 35414 |
| TX | 2003 | 4 | 6.50 | 33715 |
| TX | 2004 | 1 | 6.23 | 35268 |
| TX | 2004 | 2 | 6.07 | 35494 |
| TX | 2004 | 3 | 5.93 | 35854 |
| TX | 2004 | 4 | 5.83 | 35898 |
| TX | 2005 | 1 | 5.60 | 37776 |
| TX | 2005 | 2 | 5.40 | 39176 |
| TX | 2005 | 3 | 5.30 | 41906 |
| TX | 2005 | 4 | 5.20 | 45821 |
| TX | 2006 | 1 | 5.10 | 43965 |
| TX | 2006 | 2 | 5.07 | 41509 |
| TX | 2006 | 3 | 4.90 | 37650 |
| TX | 2006 | 4 | 4.60 | 35797 |
| TX | 2007 | 1 | 4.40 | 33977 |
| TX | 2007 | 2 | 4.30 | 30134 |
| TX | 2007 | 3 | 4.30 | 27351 |
| TX | 2007 | 4 | 4.40 | 24693 |
| TX | 2008 | 1 | 4.37 | 22366 |
| TX | 2008 | 2 | 4.57 | 21449 |
| TX | 2008 | 3 | 5.07 | 18949 |
| TX | 2008 | 4 | 5.73 | 14586 |
| TX | 2009 | 1 | 6.57 | 13817 |
| TX | 2009 | 2 | 7.37 | 15732 |
| TX | 2009 | 3 | 7.93 | 18630 |
| TX | 2009 | 4 | 8.13 | 18024 |
| TX | 2010 | 1 | 8.20 | 18634 |
| TX | 2010 | 2 | 8.17 | 16717 |
| TX | 2010 | 3 | 8.13 | 14619 |
| TX | 2010 | 4 | 8.20 | 15265 |
| TX | 2011 | 1 | 8.03 | 14991 |
| TX | 2011 | 2 | 8.07 | 15584 |
| TX | 2011 | 3 | 8.03 | 16223 |
| TX | 2011 | 4 | 7.60 | 17201 |
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