For this exercise, you will need to download quarterly Personal Consumption Expenditures: Chain-type Price Index (PCECTPI) from FRED. The variable PCECTPI is the price index for personalconsumption expenditures from the U.S. National Income and Product Accounts. In this exercise, you will construct forecasting models for the rate of inflation based on PCECTPI. For the analysis, youwill use the sample period 1963:Q1-2019:Q4, but data before 1963 may be used, as necessary, as initial values for lags in regressions.a. Compute the inflation rate, Infl, = 400 x [In(PCECTPI) - In(PCECTPI-1)]. What are the units of Infl? (Is Infl measured in dollars, percentage points, percentage per quarter, percentageper year, or something else? Explain.)b. Compute the first four autocorrelations of AInfl. Estimate an AR(2) model for AInfl. Present you results.c. Forecast AInfl2020:Q1, the change in inflation from 2020:Q1 to 2019:Q4.d. Forecast Infl2020:02, the change in inflation from 2020:Q2 to 2020:Q1 (Use an iterated forecast).e. Forecast Infl2020:22. the rate of inflation in 2020:Q2.

a. Compute the inflation rate, InflThe inflation rate is calculated as the quarterly change in the…

Answered: For this exercise, you will need to…

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

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Question 2 a) Sketch two separate time series on two different axes with the following features: i. The first time series should violate only one out of the three requirements for stationarity. ii. The second should violate at least two of the three requirements for stationarity. State each violation mathematically and explain it conceptually. Label your graphs appropriately and explain exactly how these violations are being depicted in your time series plots. b) Can you forecast either of these time series variables using the AR models you studied in this course? Explain in detail how you would do this and outline any limitations or drawbacks of this approach. c) Can you regress one of these time series variables on the other? What kind of results will you get if you do so? Give a well-thought-out answer based on everything you have learnt about this topic in this course.
The number of pending corporate fraud cases in federal court stood at 545 at the beginning of 2008 (t = 0). The number of cases had grown to 726 at the beginning of 2012. Assume the growth has been approximately linear. Develop the equation of the line that describes this linear growth. Then use that linear equation to estimate the number of cases pending at the beginning of 2014, assuming that the linear growth continues at the same rate.
Hand written solutions are strictly prohibited
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The following equation
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