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5. Describe the process of “de-trending” in time series regression analysis. Why do we
need to “de-trend”?
6. Describe the nature of omitted variable bias as it relates to time series? In what cases
does controlling for trend variables solve the omitted variable bias?
7. Event studies.
a. Describe the six steps to conduct a financial event study.
b. What is the relationship between the
use of financial event studies for causal inference?
Step by step
Solved in 3 steps
- 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.d. If the director used these 4 weeks of data to create a linear regression, what does that linear regression formula suggest for this week's forecast of employee appointments? What does the regression analysis suggest in general about employee appointments for Director Very Busy?The following table represents sales data for milk (in hundred liters) sold by a grocery.Do the computations to fill out the table and answer the following questions:1. Using MAD as the criterion, which of the following models would you use for thegiven time series data? Why?A. Naïve approach;B. 5-month SMA model;C. WMA model with weights 0.1, 0.3, and 0.6; orD. ES model with α = 0.5 and a forecast of 3,500 liters in the first month. NOTE: In answering Item 1, mention the whole description of the model; i.e., not just“SMA model”, but “SMA model with n = ...”; not just “WMA model”, but “WMA modelwith weights ...”; not just “ES model”, but “ES model with α = ...”. 2. Interpret the MAD of the most accurate among the forecasting models above.3. Based on your decision in Item 1, what should be the forecast for Month 11?
- Explain the relationship that economic variables can have with businesscycles. These have both direction and timing. Give an example economicvariable of each combination of direction timing. Of these two attributes, ifyou had exclusive access to a reliable variable, which relationships wouldyou want this variable to have for forecasting purposes3. Write the theoretical model speciation of a logit model?UESTION 5 Suppose the parameters of the Romer model take the following values: A=10, 7 =0.01, 7=1/500, and L= 100,000. what is the growth rate of this country's economy? OA. 0.2 percent O B.2 percent OC. 200 percent O D.20 percent LC 100ml U R - Eter G H D Look B N M rol Alt Al Contral Ann
- This is a Business Forecasting Question. I know the 3 stages for the evolution of forecasting are 1. Times Series Model 2. Demand Planning Model 3. Predictive Analytics Models I have questions in my homeworks about these stages, but they don't call them what I was given. I have the answer choices: Judgemental, Big Data, Quantitative, and Time Series. Obviously Time Series is one, but what are the other 2 Called. I am not putting the specifics of the questions because that's not what I'm asking. I'm just hoping that someone can clarify these 3 stages for me. I realize that I listed 4 things which means that one is not a stage. I think Big Data isn't a stage, but please correct me if I'm wrong.Suppose you regress the annual percentage stock price returns on Russell 2000 small cap index for on a the percentage annual returns for a market index. Use the following output from this linear regression to answer questions a. - f. a. What is the formula for the Russell 2000's characteristic line? b. You forecast a market return of 6% next year. According to the market model, what is next year's expected return for the Russell 2000 index? c. What is the correlation between the return on the Russell 2000 and the return on the market Index? d. How much of the variation in the Russell 2000's returns are explained by the model? e. Based on these regression results, the Russell 2000 index would be considered what kind of an investment, defensive, aggressive, or market neutral? f. Does this regression have much explanatory power? Why or why not?Economics You own a restaurant near the beach. Business has been growing each year, but obviously spikes during the summer months. A regression produces the following equation: M = 30,000 + 500t + 1,000S Where M is monthly sales, t is years past 2010, and S is a dummy variable for the summer months. If the month is June, July, or August, insert a "1". If not, the value for S is zero. What are the predicted sales for July 2020? Enter as a value.
- 4. Relate cycles, seasonality and trends in time series forecasting. What is their relevance in such type of forecasting? 5. Illustrate one example/scenario when judgmental forecast is utilized.Which trend would you choose to forecast the 2013 value of Bob's beer can collection? Dollars Market Value of Bob's Beer Can Collection, 1989-2009 300 250 200 150 100 50 0 -50 -100 1989 1991 1993- 1995- ye-10.23x+229.84 R=0.7036 6002 2011- 2013- O Linear model is preferred. O. Neither model is appropriate. Either model works-they are equivalent. Exponential model is preferred. Dollars Market Value of Bob's Beer Can Collection, 1989-2009 300 250 200 150 100 50 0 1989 1991 1993- 1995- Y-241.72e-0083 R²=0.675 1997 1999- 2001 2003 2005 2007 6002 2011- 2013-Suppose, as an economist, you are asked to analyze an issue unlike anything you have ever done before. Also, suppose you do not have a specific model for analyzing that issue. What should you do? Hint: What would a carpenter do in a similar situation?
