Economics gretl: graph 1 0.8 0.6 0.4 0.2 0 -0.2 -0.4 -0.6 -0.8 T y = x 08 Q-Q plot for uhat1 1 -1 -1 -0.8 -0.6 -0.4 -0.2 0 1 0.2 Normal quantiles Please interpret the graph 1 0.4 1 0.6 1 0.8 1
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- Savings-Mart (a chain of discount department stores) sells patio and lawn furniture. Sales are seasonal, with higher sales during the spring and summer quarters and lower sales during the fall and winter quarters. The company developed the following quarterly sales forecasting model: Y t=8.25+0.125t2.75D1t+3.50D3t where Y t=predictedsales(million)inquartert 8.25=quarterlysales(million)whent=0 t=timeperiod(quarter)wherethefourthquarterof2002=0,firstquarterof2003=1,secondquarterof2003=2,... D1t={1forfirst-quarterobservations0otherwiseD2t={1forsecond-quarterobservations0otherwiseD3t={1forthird-quarterobservations0otherwise Forecast Savings-Marts sales of patio and lawn furniture for each quarter of 2010.Plot the logarithm of arrivals for each transportation mode against time, all on the same graph. Which now appears to be growing the fastest?A researcher has a sample of 6 annual observations {94, 104, 102, 99, 111 and 107} for the CPI in country Z for the period 2015 to 2020, and wants to forecast CPI for the years 2021, 2022 and 2023. The researcher uses 3 different forecasting models: A, B and C. Model A is an AR(1) model with no drift and with an estimated autoregressive coefficient = 0.7. Model B is a MA(1) model with no constant and with an estimated MA coefficient = -0.4 (note the minus !). Model C is a random walk model with no drift. The error terms over the 2015-2020 period were estimated to have the values: {3, -1, 2, 4, -3, 1}. a. Compute the 2021, 2022 and 2023 forecasted values for the consumer price index based on the three models. Show the formulas and the details of your calculations, and explain all the related symbols. b. Suppose that the actual values of the CPI over the 2021, 2022 and 2023 were {108, 114, 105}. Calculate the Root mean square error of the three model forecasts over the 2021-2023…
- Suppose that you work for a U.S. senator who is contemplating writing a bill that would put a national sales tax in place. Because the tax would be levied on the sales revenue of retail stores, the senator has asked you to prepare a forecast of retail store sales for year 8, based on data from year 1 through year 7. The data are: (c1p2) Year Retail Store Sales 1 $1,225 2 1,285 3 1,359 4 1,392 5 1,443 6 1,474 7 1,467 54 Chapter One a. Use the first naive forecasting model presented in this chapter to prepare a forecast of retail store sales for each year from 2 through 8. b. Prepare a time-series graph of the actual and forecast values of retail store sales for the entire period. (You will not have a forecast for year 1 or an actual value for year 8.) c. Calculate the root-mean-squared error for your forecast series using the values for year 2 through year 7. 3. Use the second naive forecasting model presented in this chapter to answer parts (a) through (c) of Exercise 2. Use P 0.2 in…Consider the following numerical example of the IS-LM model: C= 100 + 0.3Yd ; I = 150 + 0.2Y – 1000 i ; G = 200 ; T = 100. Derive the IS relation. I've got the answer written down as =400+0.5Y-500i can someone please provide solutions as to how it is this.With respect to a given product, describe the connection that exists between equalibrium/disequalibrium and prediction. cite an unique example
- The use of quarterly data to develop the forecasting model Yt = a +bYt-1 is an example of which forecasting technique?The type of economic indicator that can best be used for business forecasting is the:Based on annual data from 2000-2010, the Gadget Company estimates that sales are growing according to a linear trend: Q = 50,000 + 200t where t is time and t = 0 in 2000. a. Forecast sales for 2013. b. Do you see any problems with this forecasting method?