Using the countries assigned in Question 1, collect data on the quarterly (not seasonally adjusted) consumer price index rate for 2001 – 2020.Provided in screenshots Year Quarter CPI rate Seasonal Index Period De-seasonalized CPI rate (i) Compute the CMAs for the four quarters of 2002 and 2003 manually (Show ALL workings). (ii) Use EXCEL to complete the calculation of the CMAs and the seasonal indices for 2001 - 2020. Provide a table with the de-seasonalized input variables. iii)Using R-Studio, estimate a regression equation to determine the effect of time (period) on the De-Seasonalized CPI rate. Write down the forecast equation. (All codes and regression output should be provided).
Using the countries assigned in Question 1, collect data on the quarterly (not seasonally adjusted) consumer price index rate for 2001 – 2020.Provided in screenshots Year Quarter CPI rate Seasonal Index Period De-seasonalized CPI rate (i) Compute the CMAs for the four quarters of 2002 and 2003 manually (Show ALL workings). (ii) Use EXCEL to complete the calculation of the CMAs and the seasonal indices for 2001 - 2020. Provide a table with the de-seasonalized input variables. iii)Using R-Studio, estimate a regression equation to determine the effect of time (period) on the De-Seasonalized CPI rate. Write down the forecast equation. (All codes and regression output should be provided).
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Using the countries assigned in Question 1, collect data on the quarterly (not seasonally
adjusted) consumer price index rate for 2001 – 2020.Provided in screenshots
| Year | Quarter | CPI rate | Seasonal Index | Period | De-seasonalized CPI rate |
(i) Compute the CMAs for the four quarters of 2002 and 2003 manually (Show ALL
workings).
(ii) Use EXCEL to complete the calculation of the CMAs and the seasonal indices for
2001 - 2020. Provide a table with the de-seasonalized input variables.
iii)Using R-Studio, estimate a regression equation to determine the effect of time
(period) on the De-Seasonalized CPI rate. Write down the forecast equation. (All
codes and regression output should be provided).
first two pictures are screenshots but the last section is pasted here
| 2018-04-01 | 1.0330755668451100 |
| 2018-07-01 | 0.3272675677575110 |
| 2018-10-01 | -0.0574947362577725 |
| 2019-01-01 | 0.3351160342574930 |
| 2019-04-01 | 1.1985132267461000 |
| 2019-07-01 | 0.2741660078433930 |
| 2019-10-01 | 0.2130179974229810 |
| 2020-01-01 | 0.4194274219471020 |
| 2020-04-01 | -0.5400354172367320 |
| 2020-07-01 | 1.1314853746528500 |
| 2020-10-01 | 0.2299502501607060 |
Transcribed Image Text:FRED Graph Observations
Federal Reserve Economic Data
Link: https://fred.stlouis fed.org
Help: https://fredhelp.stlouis fed.org
Economic Research Division
Federal Reserve Bank of St. Louis
CPALTT01USQ657N
Frequency: Quarterly
observation_date
2001-01-01
2001-04-01
2001-07-01
2001-10-01
2002-01-01
2002-04-01
2002-07-01
2002-10-01
2003-01-01
2003-04-01
2003-07-01
2003-10-01
2004-01-01
2004-04-01
2004-07-01
2004-10-01
2005-01-01
2005-04-01
2005-07-01
2005-10-01
2006-01-01
2006-04-01
2006-07-01
2006-10-01
2007-01-01
2007-04-01
2007-07-01
2007-10-01
2008-01-01
Consumer Price Index: All Items: Total for United States, Growth rate previous period, Quarterly, Not Seasonally Adjusted
CPALTT01USQ657N
0.9576709442635600
1.0434452665528300
0.1314307172362030
-0.2812675792237250
0.3572771718691430
1.0867528574105300
0.4263206672845220
0.3137689184200950
1.0119595216191100
0.3642987249544690
0.4900181488203220
0.0180603214737247
0.9028530155290800
1.4316392269148300
0.3528581510232810
0.5977496483825580
0.6291506466270560
1.3372698853768600
1.2167952013710400
0.5079580088046080
0.5390835579514890
1.6923592493297400
0.5602240896358650
-0.8520399803375380
1.0191703850603500
1.9173290885979300
0.2759287111930160
0.7112145553268010
1.1367736418559100
Transcribed Image Text:2008-04-01
2008-07-01
2008-10-01
2009-01-01
2009-04-01
2009-07-01
2009-10-01
2010-01-01
2010-04-01
2010-07-01
2010-10-01
2011-01-01
2011-04-01
2011-07-01
2011-10-01
2012-01-01
2012-04-01
2012-07-01
2012-10-01
2013-01-01
2013-04-01
2013-07-01
2013-10-01
2014-01-01
2014-04-01
2014-07-01
2014-10-01
2015-01-01
2015-04-01
2015-07-01
2015-10-01
2016-01-01
2016-04-01
2016-07-01
2016-10-01
2017-01-01
2017-04-01
2017-07-01
2017-10-01
2018-01-01
2.1953446560668800
1.1630553462407900
-2.8285294292016500
-0.4976330750000650
1.0603023370987900
0.6790719816300370
0.2011885888057600
0.4014150536042500
0.4750721516790430
0.0932504983551205
0.2949163207394540
1.2648223751433300
1.7433108921968100
0.4085179842504890
-0.1520557704649750
0.7956386559205690
0.8275317381384120
0.2193281479826690
0.0360404695392824
0.5903298757558220
0.5409806118647430
0.3779793413259540
-0.2790676461114500
0.7612225296713880
1.1808678137278600
0.1146758444726260
-0.8033517566055490
-0.5431990016883260
1.2055956442996000
0.2626773738433370
-0.4498436877111130
0.0646340658059050
1.1723505565470800
0.3326819410748960
0.2225741971628630
0.7907369629848110
0.5435177057500180
0.3966156913806910
0.3706296362620260
0.8861183797928000
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Step 1: Write the given information.
VIEWStep 2: Determine the CMAs for the four quarters of 2002 and 2003 manually.
VIEWStep 3: Use EXCEL to complete the calculation of the CMAs and the seasonal indices for 2001 - 2020.
VIEWStep 4: Estimate a regression equation to determine effect of time(period) on De-Seasonalized CPI rate.
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