Year	Quarter	Expenditure
1950	1	599
1950	2	583
1950	3	448
1950	4	451
1951	1	596
1951	2	573
1951	3	468
1951	4	485
1952	1	557
1952	2	575
1952	3	547
1952	4	485
1953	1	612
1953	2	713
1953	3	566
1953	4	571
1954	1	697
1954	2	664
1954	3	572
1954	4	562
1955	1	641
1955	2	702
1955	3	582
1955	4	568
1956	1	689
1956	2	746
1956	3	610
1956	4	652
1957	1	724
1957	2	734
1957	3	611
1957	4	623
1958	1	747
1958	2	755
1958	3	671
1958	4	656
1959	1	783
1959	2	821
1959	3	781
1959	4	697
1960	1	830
1960	2	840
1960	3	812
1960	4	767
1961	1	852
1961	2	844
1961	3	794
1961	4	738
1962	1	862
1962	2	887
1962	3	750
1962	4	863
1963	1	946
1963	2	961
1963	3	868
1963	4	923
1964	1	977
1964	2	982
1964	3	829
1964	4	855
1965	1	1038
1965	2	1059
1965	3	958
1965	4	959
1966	1	1015
1966	2	1031
1966	3	914
1966	4	892
1967	1	1039
1967	2	1085
1967	3	1018
1967	4	1031
1968	1	1154
1968	2	1134
1968	3	1111
1968	4	1108
1969	1	1132
1969	2	1177
1969	3	1122
1969	4	1149
1970	1	1286
1970	2	1305
1970	3	1165
1970	4	1174
1971	1	1363
1971	2	1359
1971	3	1167
1971	4	1212
1972	1	1363
1972	2	1325
1972	3	1187
1972	4	1265
1973	1	1368
1973	2	1411
1973	3	1368
1973	4	1326
1974	1	1453
1974	2	1462
1974	3	1342
1974	4	1360
1975	1	1539
1975	2	1566
1975	3	1405
1975	4	1485
1976	1	1546
1976	2	1525
1976	3	1466
1976	4	1496
1977	1	1640
1977	2	1677
1977	3	1572
1977	4	1533
1978	1	1734
1978	2	1749
1978	3	1675
1978	4	1667
1979	1	1761
1979	2	1773
1979	3	1774
1979	4	1789
1980	1	1844
1980	2	1896
1980	3	1812
1980	4	1875
1981	1	1999
1981	2	1959
1981	3	1906
1981	4	1891
1982	1	1991
1982	2	2041
1982	3	1999
1982	4	1970
1983	1	2159
1983	2	2103
1983	3	2058
1983	4	2125
1984	1	2215
1984	2	2203
1984	3	2161
1984	4	2196
1985	1	2255
1985	2	2368
1985	3	2244
1985	4	2198
1986	1	2417
1986	2	2470
1986	3	2361
1986	4	2374
1987	1	2505
1987	2	2585
1987	3	2505
1987	4	2486
1988	1	2598
1988	2	2630
1988	3	2573
1988	4	2586
1989	1	2724
1989	2	2707
1989	3	2688
1989	4	2691
1990	1	2821
1990	2	2941
1990	3	2841
1990	4	2868
1991	1	2978
1991	2	3060
1991	3	2916
1991	4	2933
1992	1	3045
1992	2	3124
1992	3	2998
1992	4	3067
1993	1	3207
1993	2	3243
1993	3	3200
1993	4	3211
1994	1	3363
1994	2	3381
1994	3	3363
1994	4	3340
1995	1	3509
1995	2	3547
1995	3	3557
1995	4	3524
1996	1	3634
1996	2	3761
1996	3	3655
1996	4	3686
1997	1	3864
1997	2	3898
1997	3	3820
1997	4	3872
1998	1	3997
1998	2	4048
1998	3	3942
1998	4	3967
1999	1	4206
1999	2	4234
1999	3	4158
1999	4	4164
2000	1	4310
2000	2	4407
2000	3	4279
2000	4	4309
2001	1	4528
2001	2	4553
2001	3	4556
2001	4	4575
2002	1	4752
2002	2	4817
2002	3	4754
2002	4	4756
2003	1	4945
2003	2	4947
2003	3	4885
2003	4	4914
2004	1	5106
2004	2	5197
2004	3	5165
2004	4	5219
2005	1	5387
2005	2	5429
2005	3	5447
2005	4	5431
2006	1	5596
2006	2	5633
2006	3	5608
2006	4	5742
2007	1	5825
2007	2	5903
2007	3	5875
2007	4	5943
2008	1	6122
2008	2	6151
2008	3	6092
2008	4	6148
2009	1	6310
2009	2	6431
2009	3	6404
2009	4	6424
2010	1	6579
2010	2	6751
2010	3	6685
2010	4	6751
2011	1	6894
2011	2	7002
2011	3	7004
2011	4	7068
2012	1	7241
2012	2	7303
2012	3	7270
2012	4	7334
2013	1	7571
2013	2	7620
2013	3	7636
2013	4	7664
2014	1	7861
2014	2	7983
2014	3	7922
2014	4	8027
2015	1	8196
2015	2	8326
2015	3	8294
2015	4	8373
2016	1	8596
2016	2	8703
2016	3	8632
2016	4	8780
2017	1	8957
2017	2	9056
2017	3	9041
2017	4	9126
2018	1	9339
2018	2	9440
2018	3	9445
2018	4	9496
2019	1	9802
2019	2	9845
2019	3	9846
2019	4	9976
2020	1	10181
2020	2	10285
2020	3	10300
2020	4	10403

Part A: Visualization 1. Plot the series using a line chart. Briefly describe what you see: Is it a positive or negative trend? Is the trend increasing? What kind of short term fluctuations do you observe? 2. Answer the previous question using the log-scale. Can you tell if the growth rate is increasing or decreasing on average over the period? 3. To better see how the growth rate evolves through time, plot the annualized growth rate of consumption expenditure. Describe what you see. Is it constant on average? Part A already complete here is the answers and charts from that. I just need part B. Part A: Visualization Line chart 12100 10100 8100 ) 6100 4100 2100 100 1. This is a positive trend in expenditure since 1950. The trend is increasing. In the 1950s and 60s the growth seemed to have been rather slow, picking up steam properly towards the late 60s and early 70s. Therefore, an exponential, increasing trend in the long run, with seasonal fluctuations in the short run (oscillations along the trend).Line chart - log scale 30000 3000 Wwwwwwww 300 2010 2013 2007 2. The log-scale graph looks like a line, so the trend is mostly constant. Annualized growth rate () -10 - 3. 1951 1358 1965 1972 1979 1985 1939 2000 2007 2014 The growth rate oscillates around an average value of 5%. This oscillation was stronger in the 1950's and is very small in the 21st century. Here is Part B questions which I need. It can be done in excel by copying and pasting the data provided. Part B: Time Series Decomposition 1. Fit a linear and quadratic trends to your series. Then, create a line chart with your original series and the two trends. Which trend seems to best fit the series? Explain. 2. Fit a linear and quadratic trends to the log of your series. Then, create a line chart with the log of your series and the two trends. Which trend seems to best fit the series? Do you see a difference between the best trend in this question and in the previous one? Explain.Part B: Time Series Decomposition 1. Overall Plotted Series 10000 8000 6000 Expenditure 4000 2000 1940 1960 1980 2000 2020 Year\fQuadratic Trend 2000 4000 6000 8000 10000 1940 1960 1980 2000 2020 Year . Expenditure Fitted values Based on the visuals the quadratic trend seems to fit the data more appropriately. 2. Log of plotted series logexpediture 1940 1960 1980 2000 2020 YearLinear Trend 1940 1960 1960 2000 2020 Year . logexpediture Fitted values Quadratic Trend 1940 1960 1980 2000 2020 Year . logexpediture Fitted values I took the log of the expenditure and then plotted the scatter plot, linear trends, and quadratic trends. When log transformation is considered, the data gets normalized. This may be the reason that with log value, the quadratic trend got eliminated and it seems linear trends fit the data more precisely.Part B: Time Series Decomposition 1. Fit a linear and quadratic trends to your series. Then, create a line chart with your original series and the two trends. Which trend seems to best fit the series? Explain. 2. Fit a linear and quadratic trends to the log of your series. Then, create a line chart with the log of your series and the two trends. Which trend seems to best fit the series? Do you see a difference between the best trend in this question and in the previous one? Explain. Answer the following questions using the log of your series and the trends computed in question 2. 3. Plot the detrended series using the trend that best fit the series. Briefly describe what you see: Do you better detect short term fluctuations? 4. Using a moving average of order 5, compute the cyclical component of your series. Then, plot the cycle and briefly describe what you see: interpret the values of some peaks and troughs. 5. Plot the low frequency of your series and briefly describe what you see. 6. Compute the seasonal component and represent it on a bar chart (only the 4 quarters). Interpret the four seasonal values. Part C: Comovement For this part, select any other series in the file assignmentl.zip and answer the following questions: . Create a scatter plot of your series expressed in logs against the selected series also expressed in logs. . Using the log of the selected series, compute its cyclical component. Then create a scatter plot of this cycle with the cycle of your series computed in Part B. Econ 102 Assignment 1 Page 1 of 2 . Looking at the two scatter plots, what can you say about the type of comovement between the two series