The team meeting will be held in 3 days from the date of the assignment and because of the limitation oftime the Chief economist has given you the following guidelines:(a) Is there a trend in total accidents?(b) Is there seasonality in total accidents?(c) Consider the following change in the time series model: y; = P1yt-1 + utwhere ut follows a white noise process. What is the condition we need to impose on p1 in orderfor the series yt to be weakly stationary? Why?(d) Consider the following change in the time series model: y; = Bo + B1x1-1+ B2xt-2 + uwhere y, is some outcome variable of interest, and x-1 and x-2 are strictly exogenousexplanatory variables. How would you test for the presence of serial correlation in the residualuz?(e) Briefly explain how you would carry out econometric analysis of the model in (d) if u, is found tobe stationary, but positively serially correlated.

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Answered: The team meeting will be held in 3 days…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The quarterly sales data (number of copies sold) for a college textbook over the past three years follow. a) Construct a time series plot. What type of pattern exists in the data? b) Use a regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. Qtr1=1 if Quarter 1, 0 otherwise; Qtr2=1 if Quarter 2, 0 otherwise; Qtr3=1 if Quarter 3, 0 otherwise. c) Compute the quarterly forecasts for next year. d) Let t=1 to refer to the observation in quarter 1 of year 1; t=2 to refer to the observation in quarter 2 of year 1; ...; and t=12 to refer to the observation in quarter 4 of year 3. Using the dummy variables defined in part (b) and also using t, develop an equation to account for seasonal effects and any linear trend in the time series. Based upon the seasonal effects in the data and linear trend, compute the quarterly forecasts for next year.
What is the MA3 forecast for Year 4, Q1? What is the weighted MA3 forecast for Year 4, Q1 with weights of 0.5, 0.33, and 0.17? What is the Exponential Smoothing forecast for Year 4, Q1 using alpha = 0.3? What is the Adjusted Exponential Smoothing forecast for Year 4, Q1 using alpha = 0.3 and beta = 0.5?
(b) Develop a three-month moving average for this time series. Compute MSE and a forecast for month 8. If required, round your answers to two decimal places. Do not round intermediate calculation. MSE The forecast for month 8: (c) Use a 0.2 to compute the exponential smoothing values for the time series. Compute MSE and a forecast for month R. If required, round your answers to two decimal places. Do not round intermediate calculation. MSE: The forecast for month 8: (d) Compare the three-month moving average forecast with the exponential smoothing forecast using a 0.2. Which appears to provide the better forecast based on MSE? Select your answer- (e) Use trial and error to find a value of the exponential smoothing coefficient a that results in the smallest MSE. Do not round intermediate calculations. Use a two-decimal digit precision for the exponential smoothing coefficient. Check Mv Wnrk
Please answer part b and c
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The following table gives the millions of metric tons of carbon dioxide emissions in a certain country for selected years from 2010 and projected to 2032. 2012 2014 2016 2018 2020 CO2 Emissions 338.5 364.5 397.1 423.8 452.1 498.4 Year 2010 Year 2022 2024 2026 2028 2030 CO2 Emissions 557.2 592.9 628.7 662.1 707.1 (a) Create a linear function that models these data, with x as the number of years past 2010 and y as the millions of metric tons of carbon dioxide emissions. (Round all numerical values to two decimal places.) y(x) = 2032 741.7 (b) Find the model's estimate for the 2024 data point. (Round your answer to two decimal places.) million metric tons Interpret the slope of the linear model. For each year since ---Select--- (c) Find the slope of the linear model. (Round your answer to two decimal places.) , carbon dioxide emissions in the U.S. are expected to change by million metric tons.
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12) The following results are an autoregression for US Exports to Mexico where the dependent variable is the lagged value of US Exports. a) Fill in the table b)Based on these regression results, what is your forecast of US Exports to Mexico for March 2005? c) Which of the two forecasts do you think is more accurate? Explain.

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