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Exam 15: Time-Series Forecasting and Index Numbers

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Question 21

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Fitting a linear trend to 36 monthly data points (January 2011 = 1, February 2011 =2, March 2011 = 3, etc.) produced the following tables. The projected trend value for January 2014 is ________.

A) 231.39
B) 555.71
C) 339.50
D) 447.76
E) 355.71

F) A) and B)
G) A) and C)

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Question 22

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Jim Royo, Manager of Billings Building Supply (BBS) , wants to develop a model to forecast BBS's monthly sales (in $1,000's) .He selects the dollar value of residential building permits (in $10,000) as the predictor variable.An analysis of the data yielded the following tables. Jim's calculated value for the Durbin-Watson statistic is 1.14.Using $\alpha$ = 0.05, the appropriate decision is: _________.

A) do not reject H₀: $\rho$ = 0
B) reject H₀: $\rho$ = 0
C) do not reject H₀: $\rho$$\neq$ 0
D) the test is inconclusive
E) reject H₀: $\rho$ ≠ 0

F) A) and C)
G) A) and B)

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Question 23

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If the seasonal index values for four consecutive quarters are 86.3, 105.6, 99.2, and 100, respectively, then which quarter has the most activity compared with the base quarter?

Although seasonal effects can confound a trend analysis, a regression model is robust to these effects and the researcher does not need to adjust for seasonality prior to using a regression model to analyze trends.

Analysis of data for an autoregressive forecasting model produced the following tables. The actual values of this time series, y, were 228, 54, and 191 for May, June, and July, respectively.The forecast value predicted by the model for July is __________.

A time series with forecast values is presented in the following table: $\begin{array} { | r | r | r | } \hline \text { Month } & \text { Actual } & \text { Forcast } \\\hline \text { Jan } & 1 & \\\hline \text { Mar } & 1.2 & * \\\hline \text { May } & 1.15 & * \\\hline \text { Jul } & 1.25 & * \\\hline \text { Sep } & 1.3 & * \\\hline \text { Nov } & 1.275 & x \\\hline\end{array}$ If the mean absolute deviation (MAD) until September is 0.06, and the overall MAD is 0.05, Then x = ______.

If the trend equation is quadratic in time t=1….T, the forecast value for the next time period, T+1, depends on time T.

Using 2000 as the base year, the 1990 value of the Paasche Price Index is ______.(Quantities are averages for the student body.)

The ratios of "actuals to moving averages" (seasonal indexes) for a time series are presented in the following table as percentages. $\begin{array} { | r | r | r | r | r | r | } \hline & 2008 & 2009 & 2010 & 2011 & 2012 \\\hline Q _ { 1 } & & 112.22 & 110.78 & 111.22 & 111.87 \\\hline Q _ { 2 } & & 100.65 & 108.68 & 103.78 & 101.95 \\\hline Q _ { 3 } & 97.76 & 99.08 & 97.68 & 97.61 & \\\hline Q _ { 4 } & 86.61 & 95.00 & 94.64 & 92.92 & \\\hline\end{array}$ The final (completely adjusted) estimate of the seasonal index for Q₁ is __________.

Using 2010 as the base year, the 2012 value of a simple price index for the following price data is _____________. $\begin{array} { | c | c | c | c | c | c | c | } \hline \text { Year} & 2008 & 2009 & 2010 & 2011 & 2012 & 2013 \\\hline \text { Price } & 29,88 & 32.69 & 42.04 & 46.18 & 47,98 & 48.32 \\\hline\end{array}$

Often, index numbers are expressed as ____________.

The table below shows the prices in $ and quantities (thousands) for five specialized electronic components for 2000 and 2016. The Laspeyres price index for 2016 using 2000 as base year is ______.

If a researcher is using exponential smoothing and determines that the forecast for the next period (F_{t + 1}) coincides with the weighted average of the actual value for the previous period (X_t) and the forecast value for the previous period (F_t) , with weights of p and q respectively.If p = 2, then q = ______.

The city golf course is interested in starting a junior golf program.The golf pro has collected data on the number of youths under 13 that have played golf during the last 4 months.Using a three-month moving average (with weights of 5, 3, and 1 for the most current value, next most current value and oldest value, respectively) , the forecast value for October made at the end of September in the following time series would be __________. $\begin{array} { | c | r | } \hline \text { Joly } & 28 \\\hline \text { Ang } & 27 \\\hline \text { Sept } & 17 \\\hline \text { Oct } & 19 \\\hline\end{array}$

When a trucking firm uses the number of shipments for January of the previous year as the forecast for January next year, it is using a naïve forecasting model.

If a researcher is using exponential smoothing and determines that the forecast for the next period (F_{t + 1}) is the average of the actual value for the previous period (X_t) and the forecast value for the previous period (F_t) , then α = ______.

Index numbers facilitate comparison of ____________.

If the Year_t Quarter_q actual value is 9,885 and the corresponding Year_t Quarter_q seasonal index is 97.75, then the Year_t Quarter_q deseasonalized value is ______.

A small value of the Durbin-Watson statistic indicates that successive error terms are positively correlated.

A simple index number is the ratio of the base period divided by the period of interest, multiplied by 100.