Question: Although you should not expect a perfectly fitting model for any time-series data, you can consider the first differences, second differences, and percentage differences for

Although you should not expect a perfectly fitting model for any time-series data, you can consider the first differences, second differences, and percentage differences for a given series as guides in choosing an appropriate model.

YearSeries ISeries IISeries III
200510.030.060.0
200615.133.167.9
200724.036.476.1
200836.739.984.0
200953.843.992.2
201074.848.2100.0
2011100.053.2108.0
2012129.258.2115.8
2013162.464.5124.1
2014199.070.7132.0
2015239.377.1140.0
2016283.583.9147.8

For this problem, use each of the time series presented in the table above and stored in TSModel1:

a. Determine the most appropriate model.

b. Compute the forecasting equation.

c. Forecast the value for 2017 .

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