The index of industrial production (IP) is a monthly time series that measures the quantity of industrial commoditiesproduced in a given month. This problem uses data on this index for the United States. All regressions are estimated overthe sample period 1986:M1 to 2017:M12 (that is, January 1986 through December 2017). Let Ye=1200 x In(IP/IP-1).Suppose that a forecaster estimates the following AR(4) model for YeŶ=0.749 +0.071Y1 + 0.170Y 2 + 0.216Y 3 + 0.167Y(-4(0.488) (0.088)(0.053)(0.078)(0.064)The forecaster wants to use this AR(4) to forecast the value of Ye in January 2018, using the following values of IP forJuly 2017 through December 2017:DateIP2017:M7 2017:M8 2017:M9 2017:M10 2017:M11 2017:M12105.01 104.56 104.82 106.58 106.86107.30The forecast value isa.The forecast value can not be computed with the given values.O b.4.1046.485Od.0.787

To forecast the value of Y_t for January 2018 using the AR(4) model, we use the following…

Answered: The index of industrial production (IP)…

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

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You are interested in how the number of hours a high school student has to work in an outside job has on their GPA. In your regression you want to control for high school standing and so you run the following regression: GPA = 3.4 0.03 * HrsWrk - 0.7 * Frosh - 0.3 * Soph +0.1 * Junior (1.1) (0.013) (0.23) (0.14) (0.08) where HrsWrk is the number of hours the student works per week, and Frosh, Soph, and Junior are dummy variables for the student's class standing. a) If you include a dummy variable for seniors, that would cause a Hint: type one word in each blank. For the rest of questions, type a number in one decimal place. b) The expected GPA of a Sophomore who works 10 hours per week is c) The expected GPA of a Senior who works 10 hours per week is d) If Dom and Sarah work the same number of hours per week, but Dom is a Junior and Sarah is a Freshman. Dom is expected to have a higher GPA than Sarah. e) Suppose you rewrite the regression as: problem. GPA = ₁HrsWrk + ß2Frosh + B2Soph +…
Assignment-log linear model with dummy variable regressor A least squares regression model explaining the sample variation of LOGEARN,, the logarithm of reported weekly earnings for individual i, yields the estimated Bivariate Regression Model LOGEARN = 5.99+ .383 gender, + U₁ where gender, is a dummy variable which is, in this case, one for females and zero for males. The issue of how to evaluate the precision of the parameter estimates in a model such as this will be discussed in Chapters 6 and 7: you may ignore these issues in answering this question. a. What interpretation can be given to this estimated coefficient on the variable gender,? In particular, what can one say about how the expected value of the logarithm of weekly earnings depends on gender? b. What can one say about how the expected value of household earnings itself depends on gender? c. Suppose that it becomes apparent that females are, on average, better educated than males. Presuming that well-educated individuals…
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Suppose in a static or distributed lag time series regression, you are able to use n =280 quarterly observations.What would be some reasonable values for the lag g in the Newey-West estimator?
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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…
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Econometrics: Given the following regressions: yt = 1.2yt-1 + Et and xt = 1.3xt-1 - 0.4xt-2 + Ct 1) Find he homogeneous equation and assess the implications of the roots.
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