As an Econometrics student, you have just been hired by the new Zambian government to evaluate the relationship between monetary policy rate and economic growth. (1) Derive the OLS estimator for the intercept and slope to test the relationship between monetary policy rate and economic growth. (1I) What are the properties of these estimators? (III) What steps will you undertake to obtain empirical evidence of the relationship between monetary policy and economic growth as well as be able to comment on the decision?
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- A firm experienced the demand shown in the following table. *Unkown future value to be forecast Fill in the table by preparing forecasts based on a five-year moving average, a three-year moving average, and exponential smoothing (with a w=0.9 and a w=0.3). Note The exponential smoothing forecasts may be begun by assuming Y t+1=Yt. Using the forecasts from 2005 through 2009, compare the accuracy of each of the forecasting methods based on the RMSE criterion. Which forecast would you have used for 2010? Why?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…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.
- An attempt was made to evaluate the inflation rate as a predictor of the spot rate in the German treasury bill market. For a sample of 79 quarterly observations, the estimated linear regressionŷ = 0.0027 + 0.7916xwas obtained, wherey = actual change in the spot ratex = change in the spot rate predicted by the inflation rateThe coefficient of determination was 0.097, and the estimated standard deviation of the estimator of the slope of the population regression line was 0.2759.a. Interpret the slope of the estimated regression line.b. Interpret the coefficient of determination.c. Test the null hypothesis that the slope of the population regression line is 0 against the alternative that the true slope is positive, and interpret your result.d. Test, against a two-sided alternative, the null hypothesis that the slope of the population regression line is 1, and interpret your result.Hello, please help me to solve the question (c) and (d) below.Consider this regression model (1) : Yt = β0 + β1 Ut + β2 Vt + β3 Wt + β4 Xt + εt ; where t= 1, ..., 75.We use OLS to estimate the parameters, producing the following model:Ŷt = 1.115 + 0.790 Ut − 0.327 Vt + 0.763 Wt + 0.456 Xt (0.405) (0.178) (0.088) (0.274) (0.017) Given that:R2 = 0.941; Durbin Watson stat DW = 1.907; RSS = 0.0757.(To answer the question, use the 5% level of significance, state clearly H0 and H1 that are tested, the test statistics that are used, and interpret the decisions.) (a) Describe the concepts of unbiasedness and efficiency. State the conditions required of regression (1) in order that the OLS estimators of the model parameters possess these properties. (b) Perform the following tests on the parameters of regression (1): (i) test whether the parameters β1, β2, β3 and β4 are individually statistically significant; (ii) test the overall significance of the regression model;…4- The manager of Collins Import Autos believes the number of cars sold in a day(Q) depends on two factors: (1) the number of hours the dealership is open (H) and (2) the number of salespersons working that day (S ). After collecting data for two months (53 days), the manager estimates the following log-linear model: Q = aHbSc ----- a. Explain how to transform this log-linear model into a linear form that can be estimated using multiple regression analysis. b. How do you interpret coefficients b and c? If the dealership increases the number of salespersons by 20 percent, what will be the percentage increase in daily sales? c. Test the overall model for statistical significance at the 5 percent significance level.
- 21. Consider a firm subject to quarter-to-quarter variation in its sales. Suppose that the following equation was estimated using quarterly data for the period 2011–2018 (the time variable goes from 1 to 32). The variables D1, D2, and D3 are, respectively, dummy variables for the first, second, and third quarters (e.g., D1 is equal to 1 in the first quarter and 0 otherwise). Qt =a+bt+c1D1+c2D2+c3D3 The results of the estimation are presented here: a. Calculate the intercept in each of the four quarters. What do these values imply? b. Use this estimated equation to forecast sales in the fourth quarter of 2019.Use the IS Equation, S(y) + M(y) = I(r) + X, to derive the slope of the IS curve. Describe the significance of points to the left and right of this schedule. Please type out the correct answer ASAP with proper explanation within 40 min. Thank you .Hello. May I ask how did you get the values? Were those only assumed values? Can you also explain how did you make the normal form thoroughly?
- Please refer to the table “Pet Owners’ Behavior during Recession,” which shows results of a survey in themidst of the recession in 2008. Now that there hasbeen some economic recovery, the results may differ.a. Perform a survey of modern-day pet ownersasking the same questions. Compare andcontrast your results with those from 2008.b. Record the generation for your respondents andperform a cross-tab analysis based on those data.c. Record household life-cycle stage and perform across-tab analysis based on those data.There has been coherent effort by various national agencies to educate and encourage reduction in energy consumption among Singapore household over the years. As part of your social science school project, you have chosen to research on whether such campaign has found success among households living in 1-room and 2-room HDB flats. You have downloaded the latest town gas consumption data for further analysis.Comment on the underlying pattern in the average quarterly household town gas consumptions over 2010 Q1 – 2021 Q2. Assume that today is 1st August 2021.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.