zwages1\u201d
\nHomework #1
\nA hard copy is due in class on Tuesday, February 9, 2016Thursday February 11, 2016. Late homeworks are not accepted. If you cannot make it to lecture, you should arrange to hand in your homework ahead of time. For data, you must use the August 2015 CPS data set.<\/p>\n
Several questions refer to the Basic Sample: persons whose age is in the 21-27 (inclusive) range, who are working at least 40 hours per week.
\n1. Consider the Basic Sample only. Create standardizations (z-scores) of for the variables: wages, age, education, and hours. Display the resulting histograms and statistics next to the unstandardized versions. Describe the main ways the pairs of graphs are similar, and the main ways they are different.
\n2. Start with the entire data set and construct the variable \u201czwages1\u201d by (i) restricting your sample to the Basic Sample, and then (ii) forming the z-scores of the wages. Now start with the entire data set and construct \u201czwages2\u201d by (i) forming the z-scores of the wages, and then (ii) restricting your sample to the Basic Sample. Compare the resulting histogram and statistics, and compare the first observation in the two cases. Explain the differences.
\n3. Determine the following proportions of persons in the Basic Sample:
\na. Women;
\nb. Persons making over 50k;
\nc. Persons who are women making over 50k;
\nd. Persons who are women or who make over 50k;
\ne. The proportion of women among the persons making over 50k;
\nf. The proportion of women who make over 50k;
\n[Hint:Construct the relevant binary (indicator) variables, and them both, and then use N-way tabulation. Intuitively, you will be calculating Pr[A], Pr[B], Pr[A and B], Pr[A or B], Pr[A|B], and Pr[B|A].]
\n4. The 2016 federal poverty level for family of size 1 (i.e., just you living alone) is $11,770. For a family of size 2 or 3 it is $15,930 and $20,090 respectively. Construct a graph that displays the breakdown of people\u2019s wages (ignoring other possible sources of income) in terms of positive and negative percentages (or proportions) above or below the poverty level for a family of size 1. Assuming that each individual is the sole earner for their family, do the same for families of size 2 and 3 (i.e., assume each individual is the sole earner for a family of the appropriate size). Repeat this, but for the Basic Sample only.
\n5. Restrict your sample to people working at least 40 hours per week (no other constraints). Construct and compare the \u201chistogram and statistics\u201d of wages of 20-25 year olds, 26-35 year olds, 36-45 year olds, 46 \u2013 55 year olds, 56 \u2013 65 year olds, 66 \u2013 70 year olds, and 71+ year olds. What do you notice about wages Give a short explanation of what you think accounts for the differences in wages. [Copy and paste your histograms and statistics onto a single sheet of paper.]<\/p>\n
#################################
\n2015 AUGUST CPS CODE BOOK
\n#################################
\nSTATE
\nGeography-FIPS state code<\/p>\n
With the following Ranges:
\n1 AL
\n2 AK
\n4 AZ
\n5 AR
\n6 CA
\n8 CO
\n9 CT
\n10 DE
\n11 DC
\n12 FL
\n13 GA
\n15 HI
\n16 ID
\n17 IL
\n18 IN
\n19 IA
\n20 KS
\n21 KY
\n22 LA
\n23 ME
\n24 MD
\n25 MA
\n26 MI
\n27 MN
\n28 MS
\n29 MO
\n30 MT
\n31 NE
\n32 NV
\n33 NH
\n34 NJ
\n35 NM
\n36 NY
\n37 NC
\n38 ND
\n39 OH
\n40 OK
\n41 OR
\n42 PA
\n44 RI
\n45 SC
\n46 SD
\n47 TN
\n48 TX
\n49 UT
\n50 VT
\n51 VA
\n53 WA
\n54 WV
\n55 WI
\n56 WY<\/p>\n
METROSIZE
\nMetropolitan Statistical Area Size<\/p>\n
With the following Ranges:
\n0 Not Identified or NonMetropolitan
\n2 100,000 \u2013 249,999
\n3 250,000 \u2013 499,999
\n4 500,000 \u2013 999,999
\n5 1,000,000 \u2013 2,499,999
\n6 2,500,000 \u2013 4,999,999
\n7 5,000,000+<\/p>\n
METROAREA
\nCombined Statistical Area FIPS Code<\/p>\n
With the following Ranges:
\n000 Nonmetropolitan or Not Identified
\n118 Appleton-Oshkosh-Neenah, WI
\n176 Chicago-Naperville-Michigan City, IL-IN-WI (part)
\n178 Cincinnati-Middletown-Wilmington, OH-KY-IN (part)
\n184 Cleveland-Akron-Elyria, OH (part)
\n206 Dallas-Fort Worth, TX (part)
\n212 Dayton-Springfield-Greenville, OH (Part)
\n216 Denver-Aurora-Boulder, CO
\n220 Detroit-Warren-Flint, MI
\n260 Fresno-Madera, CA
\n266 Grand Rapids-Muskegon-Holland, MI (part)
\n268 Greensboro-Winston-Salem-High Point, NC (part)
\n272 Greenville-Anderson-Seneca, SC (part)
\n288 Houston-Baytown-Huntsville, TX (part)
\n290 Huntsville-Decatur, AL
\n294 Indianapolis-Anderson-Columbus, IN (part)
\n304 Johnson City-Kingsport-Bristol, TN-VA (part)
\n348 Los Angeles-Long Beach-Riverside, CA
\n356 Macon-Warner-Robins-Fort Valley, GA (part)
\n376 Milwaukee-Racine-Waukesha, WI
\n378 Minneapolis-St. Paul-St. Cloud, MN-WI (part)
\n408 New York-Newark-Bridgeport, NY-NJ-CT-PA (part)
\n428 Philadelphia-Camden-Vineland, PA-NJ-DE-MD (part)
\n450 Raleigh-Durham-Cary, NC (part)
\n472 Sacramento\u2013Arden-Arcade\u2013Truckee, CA-NV (part)
\n482 Salt Lake City-Ogden-Clearfield, UT (part)
\n488 San Jose-San Francisco-Oakland, CA
\n500 Seattle-Tacoma-Olympia, WA
\n548 Washington-Baltimore-Northern Virginia, DC-MD-VA-WV (part)
\n715 Boston-Worchester-Manchester, MS-NH-CT-ME (part)
\n720 Bridgeport-New Haven-Stamford, CT<\/p>\n
HOUSEHOLD
\nHousehold-total # of members<\/p>\n
With the following Ranges:
\n0:16 Range<\/p>\n
EDUCATION
\nDemographics-highest level of school completed<\/p>\n
With the following Ranges:
\n-1 Not in Universe
\n31 Less Than 1st Grade
\n32 1st,2nd,3rd Or 4th Grade
\n33 5th Or 6th Grade
\n34 7th Or 8th Grade
\n35 9th Grade
\n36 10th Grade
\n37 11th Grade
\n38 12th Grade No Diploma
\n39 High School Grad-Diploma Or Equiv (ged)
\n40 Some College But No Degree
\n41 Associate Degree-Occupational\/Vocationl
\n42 Associate Deg.-Academic Program
\n43 Bachelor\u2019s Degree(ex:ba,ab,bs)
\n44 MASTER\u2019S DEGREE(EX:MA,MS,MEng,MEd,MSW)
\n45 Professional School Deg(ex:md,dds,dvm)
\n46 DOCTORATE DEGREE(EX:PhD,EdD)<\/p>\n
HOURS
\nLabor Force-# hours actually worked at all jobs<\/p>\n
With the following Ranges:
\n-1 Not in Universe
\n0:198 Range<\/p>\n
HISPANIC
\nDemographics- hispanic\/non-hispanic origin<\/p>\n
With the following Ranges:
\n1 Hispanic
\n2 Non-Hispanic<\/p>\n
MARITAL
\nDemographics-marital status<\/p>\n
With the following Ranges:
\n-1 Not in Universe
\n1 Married \u2013 Spouse Present
\n2 Married-Spouse Absent
\n3 Widowed
\n4 Divorced
\n5 Separated
\n6 Never Married<\/p>\n
SEX
\nDemographics-sex<\/p>\n
With the following Ranges:
\n1 Male
\n2 Female<\/p>\n
ASIAN
\nDemographics Detailed Asian Subgroup<\/p>\n
With the following Ranges:
\n-1 Not in Universe
\n1 Asian Indian
\n2 Chinese
\n3 Filipino
\n4 Japanese
\n5 Korean
\n6 Vietnamese
\n7 Other Asian<\/p>\n
AGE
\nDemographics \u2013 age topcoded at 85, 90 or 80 (see full description)<\/p>\n
With the following Ranges:
\n0:90 Range<\/p>\n
RACE
\nDemographics- race of respondent<\/p>\n
With the following Ranges:
\n01 White only
\n02 Black only
\n03 American Indian, Alaskan Native Only
\n04 Asian only
\n05 Hawaiian\/Pacific Islander Only
\n06 White-Black
\n07 White-AI
\n08 White-Asian
\n09 White-HP
\n10 Black-AI
\n11 Black-Asian
\n12 Black-HP
\n13 AI-Asian
\n14 AI-HP
\n15 Asian-HP
\n16 W-B-AI
\n17 W-B-A
\n18 W-B-HP
\n19 W-AI-A
\n20 W-AI-HP
\n21 W-A-HP
\n22 B-AI-A
\n23 W-B-AI-A
\n24 W-AI-A-HP
\n25 Other 3 Race Combinations
\n26 Other 4 and 5 Race Combinations<\/p>\n
WEEKLYWAGES
\nEarnings-weekly earnings,amount-recode<\/p>\n
With the following Ranges:
\n-1 In Universe, Met No Conditions To Assign
\n0.0:2884.61 Range<\/p>\n","protected":false},"excerpt":{"rendered":"
zwages1\u201d Homework #1 A hard copy is due in class on Tuesday, February 9, 2016Thursday February 11, 2016. Late homeworks are not accepted. If you cannot make it to lecture, you should arrange to hand in your homework ahead of Read More …<\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-93787","post","type-post","status-publish","format-standard","hentry"],"_links":{"self":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/posts\/93787","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/comments?post=93787"}],"version-history":[{"count":0,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/posts\/93787\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/media?parent=93787"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/categories?post=93787"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/tags?post=93787"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}