QUESTION 1 Which of the following is NOT a time-series model? a. Moving averages b. Exponential smoothing c. Linear regression d. Naïve approach
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- A company wants to use regression analysis to forecast the demand for the next quarter.In such a regression model, demand would be the independent variable. True or false?a. Trueb. FalseUsing Y as the dependent variable and X1, X2, X3, X4 and X5 as the explanatoryvariables, formulate an econometric model for data that is (i) time series data (ii)cross-sectional data and (iii) panel data – (Hint: please specify the specific model herenot its general form).1.In what cases is the logit/probit model used? example? 2. In what cases is the ordered logit/probit model used? Example? Please provide detail answer, i need it to review for my test. Thank you in advanced!
- (2)What would the consequence be for a regression model if theerrors were not homoscedastic?Q. Rubax, a U.S. manufacturer of athletic shoes, estimates the following linear trend model for show sales: Qt = a + bt + c1D1 + c2D2 + c3D3 Qt = sales of athletic shoes in the tth quarter t = 1, 2,..., 28 [2014(I), 2014(II),....,2020[IV)] D1 = 1 if t is quarter I (winter); 0 otherwiseD2 = 1 if t is quarter II (spring); 0 otherwiseD3 = 1 if t is quarter III (summer); 0 otherwise The regression analysis produces the following results: a. Is there sufficient statistical evidence of an upward trend in shoe sales? b. Do these data indicate a statistically significant seasonal pattern of sales of Rubax shoes? If so, what is the seasonal pattern exhibited by the data? c. Using the estimated forecast equation, forecast sales of Rubax shoes for 2021(III) and 2022(II). d. How might you improve this forecast equation? Thank you!Q2B. Which of the following are limitations of using Impulse Response Functions(IRFs) in time series analysis?i. IRFs are only valid for linear time series models.ii. IRFs assume that the underlying time series is stationary.iii. IRFs can provide information about the short-term dynamics of the relationshipbetween variables, but they do not capture longer-term effects or otherimportant aspects of the relationship.iv. IRFs depend on the specification of the model used to estimate the relationshipbetween variables.
- Run the Multiple Linear Regression using Fatalities as the dependentvariable and Licensed drivers, registered vehicles, and GDP per capita as independentvariables. Submit Excel FileCalculate the following:a- Interpret the R-squareb-Find the equation of the fitted linec- Which variable has the strongest relationship with number of fatalities?d- Identify which variables are significant/non-significant using alpha = 0.05? Fatalities Licensed Drivers Registered Vehicles GDP per Capita (measured) 953 3999057 5300199 40598 80 536033 803684 71996 1010 5284970 5806313 43464 516 2145334 2817145 38919 3563 27039400 31022328 68970 632 4244713 5356018 59885 294 2605612 2879802 68555 111 786504 1008468 64895 31 527731 351933 176498 3133 15368695 17496002 43423 1504 7168733 8512550 50288 117 948417 1267385 58185 231 1252535 1879670 40189 1031 8714788 10588910 60419 858 4589405 6190736 49209 318 2260271 3691892 54520 404 2149430 2684010 53094 724…What is a circular flow modelClassify each one of the following variables as either measurable (continuous) or categorical. If a variable is categorical, further classify it as either nominal or ordinal. Justify your answer (Note that no marks will be awarded without a justification). I. The manufacturer of a car (brands), II. The amount of money in a bank account, III. The Gross Domestic Product (GDP) of a country, IV. The rating of a hotel according to the number of stars it has