Data Exercise 2

This document provides answers to questions related to unemployment and inflation in Data Exercise 2. It discusses the unemployment rates, factors affecting unemployment, and the impact of inflation on the economy. The document also includes tables and graphs for better understanding.

Running head: DATA EXERCISE 2 1
Data Exercise 2
Student’s name
Institution Affiliation
Date

DATA EXERCISE 2 2
1.What month (and year) is summarized? What was the unemployment rate for that
month? How does that rate compare with the rate in the previous month?
The employment situation in March is reported to have increased by more than 196000,
and the rate of unemployment rate remains unchanged at 3.8% as per the statistics released by
the U.S. Bureau of Labour. It is reported that labor gains were reported in sectors such as
healthcare and services involving professional and technical aspects.
2.What were the unemployment rates for adult women, teenagers, blacks, Hispanics, and
whites? How did these rates compare with those a month earlier?
The number of people unemployed remained stagnant approximated to be more than 6
million. The main worker segments that were unemployed entailed adult women who recorded a
3.3%, teenagers were the highest with 12.8%, blacks 6.7%, Hispanics 4.7% and whites at 3.7%.
The number of people classified as long-term unemployed remained unchanged; that is, they
were reported to be more than 1.3 million and represented 21% of the unemployed (Bureau of
Labor Statistics, 2019). Also, part-time employees commonly knowns as involuntary part-time
employees remained slightly unchanged and were reported to be 4.5 million individuals as of
March.
3.What factors make it difficult to determine the unemployment rate?
The process of measuring the unemployment rate entails identifying individuals who are
eligible and available to work. Based on demographic statistics, the total population of the US is
segmented into three distinct niches. The first group is composed of individuals under the age of
16 and others who are institutionalized (Tejvan, 2019). The other group is dubbed as not belong
in the labor force are adults who are categorized as individuals with the potential to work but due
to unavoidable circumstances such as school or social ties are unable to seek work. The last
group is the labor force and comprises individuals who are employed and unemployed but

DATA EXERCISE 2 3
actively finding employment opportunities. It is thus not an easy task to differentiate between
such three types and due to the certain changing thresholds determining frictional and structural
unemployment and also due to the evolving nature associated with such kind of unemployment.
It has also been confirmed that it is a challenge when it comes to establishing the rate of both
full-employment and unemployment (Simpson, 2019). A good illustration is when an individual
resigns from a job in the quest for a better one such a person will be considered to be under
frictional unemployment. However, when the previous post disappears due to a declining
industry that makes it hard to make money, such an individual will be considered under
structural unemployment. Considering a scenario where the economy slips into recession making
it difficult for a worker to find a job then such an individual will be categorized to be cyclically
unemployed.
4.Why is unemployment an economic problem?
Unemployment is an economic problem due to several implications it draws on the economy,
for instance, it adds up to social and economic costs such as loss of income, loss of government
revenue with regards to tax, social evils, and a decline in GDP. The higher the rate of
unemployment, the less the level of tax income collected as only a few individuals can pay the
income tax and also use less of their disposable income. The state is also compelled to spend
more of its resources on unemployment packages and other associated benefits (Simpson, 2019).
The government is not only forced to pay unemployment benefit but also a family that has been
affected by unemployment as it is probable that such a family will be entitled to housing benefit
and income boost (Tejvan, 2019).
5.What are the noneconomic effects of unemployment?

DATA EXERCISE 2 4
Unemployment has been associated with yielding personal demoralization which impacts
negatively on families. Unemployed individuals have lower standards of living, and this may be
related to relationship breakdowns evidenced in most cases as instances of unhappiness erodes
family ties. The rise of crimes is also associated with increases in levels of unemployment
compounding communities with much fear.
6.Who loses from unemployment?
A high rate of unemployment translates to a reduced level of investment and business
operations which means less revenue for the government with regards to tax income. People and
communities suffering from unemployment are characterized by dilapidated houses and
devaluing of their property values. Families and people also suffer due to broken relationships
that result from unemployment.
7.Significance of the data
The survey entails statistics collected from two months. The household survey requires
evaluating labor force status with regards to unemployment based on demographic features
(Bureau of Labor Statistics, 2019). On the other hand, the establishment survey assesses nonfarm
unemployment, income based on different industries and hours of work. High unemployment
rates are also an indicator that the country’s economy is operating below the optimal capacity
thus being inefficient and this translates to lower output and level of incomes. The unemployed
are adversely affected such that they are unable to purchase the required level of commodities
needed to boost the economy leading to lower spending and output. Unemployment on the rise is
associated with a negative multiplier impact.

DATA EXERCISE 2 5
Part 2: Inflation
1.What month (and year) is summarized? What was CPIU for that month?
The consumer price index as per March stood at 0.4% which is an increase with regards to all
urban consumers. It was adjusted seasonally as in February it was recorded as 0.2% according to
the data by Bureau of Labor Statistics (Bureau of Labor Statistics, 2019). Also, in the past year,
it was observed that the index of all commodities rose by 1.9% before adjustments were made.
2.Two goods that had the greatest price increase
One is gasoline whose index rose to 6.5% in March after being recorded as 1.5% in
February. The other item is energy commodities which as at February were recorded at 1.5%,
however, as of March they were recorded at 6.2% (Bureau of Labor Statistics, 2019).
3.Two categories of goods that had the lowest price increase
Apparel as per February was recorded at 0.3%. However, in March they declined and
were recorded at -1.9% which is the smallest price increase of all commodities (Bureau of Labor
Statistics, 2019). The other product is used cars and trucks as at February it was marked as -0.7%
but only increased slightly to -0.4%.
4.Who loses from inflation?
Inflation impacts negatively on the entire population because the prices of consumer
commodities increase assuming that the purchasing power remains constant. Specifically,
individuals with no assets are susceptible as they lack other assets that can be liquefied to be
used for purposes of consumption. The worst possible scenario is that of retirees who have
exhausted their practice that they could depend on to substitute for inflation.
Manufacturers and other service providers also suffer as they are consumers of inputs
used in the production of goods and services. Thus, they are forced to purchase such inputs at

DATA EXERCISE 2 6
higher prices which makes the prices for commodities high making a demand by consumers fall
or the consumers turn to lower-cost competitors or seek for substitute commodities.
The other group that suffers from inflation entail financing and lending institutions such
as banks. It is common practice to fix the amount lent and the rate of interest to be charged based
on a contract. However, with inflation creeping in, the value of the whole loan gets reduced and
this especially with the long-term loan. The case for fixed interests is even dire as it works
against long-term investors who find it hard to cancel their contracts without being charged
termination fees for early canceling of their contracts. Banks and lenders act by raising the
interest rates which subsequently affects borrowers who end up being losers.
5.Unemployment Data by Labor Force Groups and Duration
Tables
Civilian unemployment
Tables
Civilian unemployment
Year or
month
All
civilian
workers
By sex and age
Men
20
years
and
over
Women
20
years
and
over
Both
sexes
16–19
2000. 4.0 3.3 3.6 13.1
2001. 4.7 4.2 4.1 14.7
2002. 5.8 5.3 5.1 16.5
2003. 6.0 5.6 5.1 17.5
2004. 5.5 5.0 4.9 17.0
2005. 5.1 4.4 4.6 16.6
2006. 4.6 4.0 4.1 15.4
2007. 4.6 4.1 4.0 15.7
2008. 5.8 5.4 4.9 18.7
2009. 9.3 9.6 7.5 24.3
2010. 9.6 9.8 8.0 25.9
2011. 8.9 8.7 7.9 24.4
2012. 8.1 7.5 7.3 24.0

DATA EXERCISE 2 7
2013. 7.4 7.0 6.5 22.9
2014. 6.2 5.7 5.6 19.6
2015. 5.3 4.9 4.8 16.9
2016. 4.9 4.5 4.4 15.7
2017. 4.4 4.0 4.0 14.0
2018. 3.9 3.6 3.5 12.9
2017:
Jan. 4.7 4.3 4.4 14.7
Feb. 4.7 4.3 4.2 14.7
Mar. 4.4 4.2 3.9 13.7
Apr. 4.4 3.9 4.1 14.8
May. 4.4 3.9 4.1 14.1
June. 4.3 4.0 4.0 13.4
July. 4.3 4.0 4.0 13.3
Aug. 4.4 4.1 4.0 13.9
Sept. 4.2 3.9 3.9 13.0
Oct. 4.1 3.8 3.7 13.8
Nov. 4.2 3.8 3.7 15.8
Dec. 4.1 3.8 3.7 13.6
2018:
Jan. 4.1 3.9 3.6 13.9
Feb. 4.1 3.7 3.8 14.4
Mar. 4.0 3.7 3.6 13.4
Apr. 3.9 3.7 3.5 13.0
May. 3.8 3.6 3.3 12.7
June. 4.0 3.7 3.7 12.6
July. 3.9 3.4 3.6 13.1
Aug. 3.8 3.5 3.5 12.7
Sept. 3.7 3.4 3.3 12.6
Oct. 3.8 3.5 3.4 12.0
Nov. 3.7 3.3 3.4 12.0
Dec. 3.9 3.6 3.5 12.5

DATA EXERCISE 2 8
2000.
2002.
2004.
2006.
2008.
2010.
2012.
2014.
2016.
2018.
Feb.
Apr.
June.
Aug.
Oct.
Dec.
Feb.
Apr.
June.
Aug.
Oct.
Dec.
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
Unemployment by duration
Duration of unemployment Less than 5 weeks
Duration of unemployment 5–14 weeks
Duration of unemployment 15–26 weeks
Duration of unemployment 27 weeks and over
2000.
2002.
2004.
2006.
2008.
2010.
2012.
2014.
2016.
2018.
Feb.
Apr.
June.
Aug.
Oct.
Dec.
Feb.
Apr.
June.
Aug.
Oct.
Dec.
0.0
5.0
10.0
15.0
20.0
25.0
30.0
Civilian unemploymenent rate
By sex and age Men 20 years and over
By sex and age Women 20 years and over
By sex and age Both sexes 16–19
Year
or
month
Duration of unemployment
Less than 5
weeks
5–14
weeks
15–26
weeks
27 weeks
and over2000. 2,558 1,815 669 649
2001. 2,853 2,196 951 801
2002. 2,893 2,580 1,369 1,535
2003. 2,785 2,612 1,442 1,936
2004. 2,696 2,382 1,293 1,779
2005. 2,667 2,304 1,130 1,490
2006. 2,614 2,121 1,031 1,235
2007. 2,542 2,232 1,061 1,243
2008. 2,932 2,804 1,427 1,761
2009. 3,165 3,828 2,775 4,496

DATA EXERCISE 2 9
2010. 2,771 3,267 2,371 6,415
2011. 2,677 2,993 2,061 6,016
2012. 2,644 2,866 1,859 5,136
2013. 2,584 2,759 1,807 4,310
2014. 2,471 2,432 1,497 3,218
2015. 2,399 2,302 1,267 2,328
2016. 2,362 2,226 1,158 2,005
2017. 2,270 2,008 1,017 1,687
2018. 2,170 1,876 917 1,350
2017:
Jan. 2,427 2,076 1,186 1,834
Feb. 2,507 2,128 1,049 1,772
Mar. 2,272 2,047 1,091 1,677
Apr. 2,332 2,076 1,067 1,650
May. 2,159 1,935 1,113 1,680
June. 2,269 1,943 934 1,708
July. 2,181 2,020 1,001 1,739
Aug. 2,202 2,028 1,065 1,722
Sept. 2,256 1,931 964 1,720
Oct. 2,162 1,957 866 1,628
Nov. 2,248 1,919 970 1,597
Dec. 2,230 1,984 892 1,511
2018:
Jan. 2,271 1,927 959 1,428
Feb. 2,458 1,900 933 1,403
Mar. 2,266 1,976 900 1,337
Apr. 2,121 1,975 1,018 1,311
May. 2,019 1,906 967 1,197
June. 2,218 1,865 862 1,467
July. 2,092 1,818 959 1,418
Aug. 2,199 1,722 927 1,320
Sept. 2,065 1,751 861 1,379
Oct. 2,062 1,845 859 1,370
Nov. 2,128 1,842 865 1,259
Dec. 2,126 2,027 897 1,306
Year
or
month
Reason for unemployment
Job losers 3 Job
leavers
Reentrant
s
New
entrantsTotal On Other

DATA EXERCISE 2 10
layoff
2000. 2,517 852 1,664 780 1,961 434
2001. 3,476 1,067 2,409 835 2,031 459
2002. 4,607 1,124 3,483 866 2,368 536
2003. 4,838 1,121 3,717 818 2,477 641
2004. 4,197 998 3,199 858 2,408 686
2005. 3,667 933 2,734 872 2,386 666
2006. 3,321 921 2,400 827 2,237 616
2007. 3,515 976 2,539 793 2,142 627
2008. 4,789 1,176 3,614 896 2,472 766
2009. 9,160 1,630 7,530 882 3,187 1,035
2010. 9,250 1,431 7,819 889 3,466 1,220
2011. 8,106 1,230 6,876 956 3,401 1,284
2012. 6,877 1,183 5,694 967 3,345 1,316
2013. 6,073 1,136 4,937 932 3,207 1,247
2014. 4,878 1,007 3,871 824 2,829 1,086
2015. 4,063 974 3,089 819 2,535 879
2016. 3,740 966 2,774 858 2,330 823
2017. 3,434 956 2,479 778 2,079 690
2018. 2,990 852 2,138 794 1,928 602
2017:
Jan. 3,650 1,043 2,607 873 2,158 786
Feb. 3,651 970 2,682 813 2,210 750
Mar. 3,501 959 2,541 785 2,061 796
Apr. 3,538 953 2,584 779 2,022 703
May. 3,428 872 2,556 782 2,103 674
June. 3,422 879 2,544 809 2,038 682
July. 3,329 1,009 2,320 744 2,096 696
Aug. 3,519 1,017 2,502 785 2,148 653
Sept. 3,356 909 2,446 748 2,073 663
Oct. 3,236 872 2,365 746 1,998 622
Nov. 3,175 928 2,248 751 2,035 708
Dec. 3,249 923 2,326 726 1,985 568
2018:
Jan. 3,243 908 2,335 724 1,959 638
Feb. 3,227 871 2,356 784 1,954 703
Mar. 3,107 865 2,242 860 1,966 615

DATA EXERCISE 2 11
Apr. 2,965 865 2,100 812 2,001 615
May. 2,882 829 2,054 844 1,868 569
June. 3,055 901 2,154 801 2,078 579
July. 2,996 879 2,117 835 1,804 592
Aug. 2,868 855 2,013 866 1,864 586
Sept. 2,796 812 1,984 739 1,889 588
Oct. 2,858 793 2,066 731 1,914 605
Nov. 2,842 804 2,038 697 1,880 577
Dec. 2,903 762 2,141 839 1,958 588
2000.
2002.
2004.
2006.
2008.
2010.
2012.
2014.
2016.
2018.
Feb.
Apr.
June.
Aug.
Oct.
Dec.
Feb.
Apr.
June.
Aug.
Oct.
Dec.
0
5000
10000
15000
20000
25000
30000
unemployment by reason
Reason for unemployment Job losers 3
Reason for unemployment Job losers 3
Reason for unemployment Job losers 3
Reason for unemployment Job leavers
Reason for unemployment Reentrants
Reason for unemployment New entrants
Men above 20 compared to 16-19 for both sexes in 2000
13.1/3.3=3.97
Women above 20 compared to 16-19 for both cases in 2000
13.1/3.6=3.64
Men above 20 compared to 16-19 for both sexes in 2010
25.9/9.8=2.64
Women above 20 compared to 16-19 for both cases in 2010

DATA EXERCISE 2 12
25.9/8=3.24
1.Years that had the highest and lowest unemployment rate
The highest unemployment rate using 2000 as the base year was recorded in 2010 where it was
9.6%, and more than 14,250,000 were unemployed (Bureau of Labor Statistics, 2019). However,
the lowest rate was in 2018 for all the groups where only 5,692,000 were unemployed presenting
a 4% rate of unemployment (Bureau of Labor Statistics, 2019).
How the rates compare among the groups
For the group comprising of 16-19 years as per both males and females are triple
compared to males and females above the age of 20 years. It is a fact that for people between 16-
19 years, most of them are engaged in studies or are unemployed as they are in window period
expecting their first job.
Year or
month
By sex and age
Men
20
years
and
over
Women
20
years
and
over
Both
sexes
16–19
2000. 3.3 3.6 13.1
2010. 9.8 8.0 25.9
Men above 20 compared to 16-19 for both sexes in 2000
13.1/3.3=3.97
Women above 20 compared to 16-19 for both cases in 2000
13.1/3.6=3.64
Men above 20 compared to 16-19 for both sexes in 2010
25.9/9.8=2.64
Women above 20 compared to 16-19 for both cases in 2000
25.9/8=3.24

DATA EXERCISE 2 13
2.Distribution by unemployment by duration (the highest and lowest unemployment
duration)
The lowest unemployment for any particular term was recorded in 2000 that lasted for 27
weeks and over and the number of unemployed was more than 649,000 (Bureau of Labor
Statistics, 2019). However, the highest unemployment was in 2010 for the same period of 27
weeks and recorded more than 6,415,000.
Relationship found
It is imperative to note that for both the lowest and highest unemployment, the time frame
is the same that is 27 weeks and above which is the most extended duration (Bureau of Labor
Statistics, 2019). In great times and seasons, many individuals get employed sooner; thus, few
are unemployed in the most extended duration. However, during bad times, most of the
unemployed remain unemployed for the longest period.
3Demographic studies reveal that the proportion of teenagers and minorities in the U.S.
population is likely to increase soon. In your opinion, what implications, if any, will this
trend have on the natural rate of unemployment
The ramifications of having a significant proportion of the economy to have a majority of
the teenagers and minorities will depend on the state of the economy at a specific moment. For
instance, if the economy is buoyant, then it is clear that there will be many jobs for an
undergraduate that are both full time and part-time available. Thus, many teenagers will be
limited by the fact that they will not have completed their studies while the minority groups may
be hindered by lower-level English blocking them from higher jobs. However, when the
economy is good, most start-ups would be more than willing to hire lower qualified yet skilled
individuals.

DATA EXERCISE 2 14
4.Significance of the data
The data is important as it depicts that an economy on a downturn will experience an
increase in the level of unemployment with the rise in the number of teenagers and minority
groups. With the rise in the need for diversity among many companies, different standards will
be set for accommodating the various ethnic groups. However, some employers will offer lower
wages, and some of the individuals from minority groups will accept such wages.
References

DATA EXERCISE 2 15
Bureau of Labor Statistics. (2019, April 10). Consumer Price Index Summary. Retrieved April
13, 2019, from https://www.bls.gov/news.release/cpi.nr0.htm
Bureau of Labor Statistics. (2019, April 5). Employment Situation Summary. Retrieved April 13,
2019, from https://www.bls.gov/news.release/empsit.nr0.htm
Bureau of Labor Statistics. (2019, April 10). TABLE B–24. Unemployment by sex, age, and
demographic characteristic, 1975–2018. Retrieved April 13, 2019, from
https://www.govinfo.gov/app/details/ERP-2019/ERP-2019-appendixB/context
Bureau of Labor Statistics. (2019, April 10). TABLE B–28. Unemployment by duration and
reason, 1975–2018. Retrieved April 13, 2019, from
https://www.govinfo.gov/app/details/ERP-2019/ERP-2019-appendixB/context
Simpson, S. D. (2019, April 10). The Cost of Unemployment to the Economy. Retrieved April 13,
2019, from https://www.investopedia.com/financial-edge/0811/the-cost-of-
unemployment-to-the-economy.aspx
Tejvan. (2019). Economic costs of unemployment. Retrieved April 13, 2019, from
https://www.economicshelp.org/macroeconomics/unemployment/costs/