# The 95% upper and lower forecast confidence interval for each of the forecasted months…. 1 answer below »

Using Stata, use the seasonal multiplicative Holt-Winters method to develop a forecast for the non-seasonally adjusted monthly Total: New Privately Owned Housing Units Started (HOUSTNSA) for January through December 2013. Note: the data is scaled in thousands of units.
Task: Use the tssmooth command with the multiplicative seasonal Holt-Winters method to create a forecast of monthly housing starts for January through December 2013, a monthly seasonal index, the 95% forecast confidence interval, a graph of the results, goodness-of-fit measurements, and a chart of the forecast vs. actual values with upper and lower 95% forecast intervals, all using stata and stata graphs and output screenshots.
Directions: Using the multiplicative Holt-Winters method discussed in class and the non-seasonally adjusted monthly Total: New Privately Owned Housing Units Started (HOUSTNSA) series from the Federal Reserve FRED Economic Data and make a forecast for the next 12 months and provide the following information:
(1) The forecast for each of the 12 months from January 2013 through December 2013.
(2) Be sure to to address the following in your write-up:

Don't use plagiarized sources. Get Your Custom Essay on
The 95% upper and lower forecast confidence interval for each of the forecasted months…. 1 answer below »
Just from \$13/Page
• The 95% upper and lower forecast confidence interval for each of the forecasted months.
• The seasonal index for each of the 12 seasonal periods (months).
• The mean squared error, root mean squared error (mean absolute deviation), and percentage error of the in-sample forecast error.
• The number and percentage of forecast observations that fall outside of the upper and lower 95% forecast intervals.
• A chart of the actual vs. forecasted results including the upper and lower 95% forecast intervals

Document Preview:

Using Stata, use the seasonal multiplicative Holt-Winters method to develop a forecast for the non-seasonally adjusted monthly Total: New Privately Owned Housing Units Started (HOUSTNSA) for January through December 2013. Note: the data is scaled in thousands of units.
Task: Use the tssmooth command with the multiplicative seasonal Holt-Winters method to create a forecast of monthly housing starts for January through December 2013, a monthly seasonal index, the 95% forecast confidence interval, a graph of the results, goodness-of-fit measurements, and a chart of the forecast vs. actual values with upper and lower 95% forecast intervals, all using stata and stata graphs and output screenshots.
Directions: Using the multiplicative Holt-Winters method discussed in class and the non-seasonally adjusted monthly Total: New Privately Owned Housing Units Started (HOUSTNSA) series from the Federal Reserve FRED Economic Data and make a forecast for the next 12 months and provide the following information:
(1) The forecast for each of the 12 months from January 2013 through December 2013.
(2) Be sure to to address the following in your write-up:
The 95% upper and lower forecast confidence interval for each of the forecasted months.
The seasonal index for each of the 12 seasonal periods (months).
The mean squared error, root mean squared error (mean absolute deviation), and percentage error of the in-sample forecast error.
The number and percentage of forecast observations that fall outside of the upper and lower 95% forecast intervals.
A chart of the actual vs. forecasted results including the upper and lower 95% forecast intervals