| Title: | Data Sets from "Lectures on Econometrics" by Chirok Han |
|---|---|
| Description: | Data sets for Chirok Han (2022, ISBN:979-11-303-1497-6, "Lectures on Econometrics"). Students, teachers, and self-learners will find the data sets essential for replicating the results in the book. |
| Authors: | Chirok Han [aut, cre, cph] |
| Maintainer: | Chirok Han <[email protected]> |
| License: | GPL-3 |
| Version: | 1.0.1 |
| Built: | 2024-11-07 06:30:24 UTC |
| Source: | CRAN |
Robert Boyle's data set
data(Boyle)data(Boyle)
A data frame with 25 rows and 2 variables:
the number of equal spaces in the shorter leg, that contained the same parcel of air diversely extended
the pressure sustained by the included air
Chirok Han [aut, cre, cph]
https://www.chemteam.info/GasLaw/Gas-Boyle-Data.html
Death rate and related variables for Korean districts for 2008-2010
data(Death)data(Death)
A data frame with 258 rows and 9 variables:
region ID
year
registered population (end of year)
number of registered deaths
percentage of drinkers (more than once in a month)
percentage of smokers (smoker = has smoked 100+ cigarettes and currently smoking)
percentage of those aged 65 and over
number of vehicles per person
= death/regpop*1000
Chirok Han [aut, cre, cph]
Statistics Korea
CO2 emissions per capita and GDP per capita in 2005
data(Ekc)data(Ekc)
A data frame with 183 rows and 4 variables:
country code
country name
GDP per capital, ppp adjusted (USD)
CO2 emissions per capita (ton)
Chirok Han [aut, cre, cph]
Card and Krueger (1994) fastfood data set
data(Fastfood)data(Fastfood)
A data frame with 820 rows and 35 variables:
ID of fastfood restaurant [+]
sheet number (unique store id)
1 if second interview [+]
chain 1=bk; 2=kfc; 3=roys; 4=wendys
1 if company owned
1 if NJ; 0 if Pa
1 if in southern NJ
1 if in central NJ
1 if in northern NJ
1 if in PA, northeast suburbs of Philadelphia
1 if in PA, Easton etc
1 if on NJ shore
type 2nd interview 1=phone; 2=personal
status of second interview; see details
date of second interview MMDDYY format
number of call-backs*
# full-time employees
# part-time employees
# managers/assistant managers
full time equivalent, FTE = empft + nmgrs + 0-.5*emppt [+]
FTE for after - FTE for before [+]
starting wage ($/hr)
months to usual first raise
usual amount of first raise ($/hr)
1 if cash bounty for new workers
% employees affected by new minimum
free/reduced price code (see details)
hour of opening
number hrs open per day
price of medium soda, including tax
price of small fries, including tax
price of entree, including tax
number of cash registers in store
number of registers open at 11:00 am
1 if empft, nmgrs and emppt observed both periods [+]
See attr(Fastfood, "desc"). [+] are added by Chirok Han.
Chirok Han [aut, cre, cph]
https://davidcard.berkeley.edu/data_sets.html
Card, D., and A. Krueger (1994). Minimum Wages and Employment: A Case Study of the Fast Food Industry in New Jersey and Pennsylvania, American Economic Review 84, 772-793.
Korean firm data for 2018 in KOSPI and KOSDAQ
data(Firmdata)data(Firmdata)
A data frame with 2073 rows and 24 variables:
Firm code
"KOSPI" or "KOSDAQ"
=1 if KOSPI
=1 if KOSDAQ
industry code
one of A, C, GHI, DEF, JK, and Others
A, B, ..., U (top SIC categories)
2-digit SIC
3-digit SIC
establishment date in yyyymmdd
establishment year
=2018-estyear
=1 if the firm operates in Korea
="000" if firm information is available
number of employees
total annual salary paid (sum)
average tenure in years
=totsal/nemp
CFS or OFS
="000" if account information is available
sales in KRW
operating profit in KRW
net income in KRW
Chirok Han [aut, cre, cph]
opendart.fss.or.kr
Parent-level version of Galton's family data
data(Galtonpar)data(Galtonpar)
A data frame with 205 rows of 10 variables:
parent ID, a factor with levels 001-204
height of father
height of mother
mid-parent height, calculated as father + 1.08*mother)/2
number of children
number of sons
number of daughters
average height of children
average height of sons
average height of daughters
Chirok Han [aut, cre, cph]
GaltonFamilies data in HistData package
HistData::GaltonFamilies
Household consumption shares of communication and recreation sector in Korean Household Income and Expenditure Survey 2014
data(Hcons)data(Hcons)
A data frame with 6723 rows of 3 variables:
age of household head
share of consumption for communication in %
share of consumption for recreation in %
Chirok Han [aut, cre, cph]
Korea Household Income and Expenditure Survey 2014 http://kostat.go.kr/portal/eng/surveyOutline/6/1/index.static
A subset (30 <= age <= 39) of Korea Household Income and Expenditure Survey 2016
data(Hies)data(Hies)
A data frame with 1368 rows of 26 variables:
year of survey, =2016
number of family members
number of employed members
age of household head
1 if head is employed
1 if own house
cross sectional weight
household monthly income
1 if has income from properties
household total monthly expenditure
household monthly consumption
household monthly consumption in section 01
household monthly consumption in section 02
household monthly consumption in section 03
household monthly consumption in section 04
household monthly consumption in section 05
household monthly consumption in section 06
household monthly consumption in section 07
household monthly consumption in section 08
household monthly consumption in section 09
household monthly consumption in section 10
household monthly consumption in section 11
household monthly consumption in section 12
propensity to consume (=cons/inc)
years of head's education
1 if head is female
Chirok Han [aut, cre, cph]
http://kostat.go.kr/portal/eng/surveyOutline/6/1/index.static
The Boston HMDA data set in the Ecdat package, with yes/no converted to 1/0
data(Hmda)data(Hmda)
A data frame with 2381 rows of 13 variables:
debt payments to total income ratio
housing expenses to income ratio
ratio of size of loan to assessed value of propensity
consumer credit score from 1 to 6 (a low value being a good score)
mortgage credit score from 1 to 4 (a low value being a good score)
1 if public bad credit score
1 if denied mortgage insurance
1 if self employed
1 if the applicant is single
1989 Massachusetts unemployment rate in the applicant's industry
1 if unit is a condominium
1 if the applicant is black
1 if mortgage application denied
Chirok Han [aut, cre, cph]
Hmda data in the Ecdat package
Artificial data for studying IV estimation
data(Ivdata)data(Ivdata)
A data frame with 100 rows of 5 variables:
y variable
x1 variable
x2 variable
z2a variable
z2b variable
Chirok Han [aut, cre, cph]
Subset (30 <= age <= 39, nonzero income, 9 <= educ < 20) of 2011 KLIPS
data(Klips)data(Klips)
A data frame with 646 rows of 8 variables:
age
years of education
tenure
1 if regular, 0 if irregular
hours worked per week
monthly earning in 10,000 KRW
annual labor income after tax
1 if married
Chirok Han [aut, cre, cph]
Korea Labor Institute https://www.kli.re.kr/klips/index.do
Korea Longitudinal Study of Aging wave 4 (2012)
data(Klosa)data(Klosa)
A data frame with 2153 rows of 45 variables:
personal ID
= (year-2006)/2 + 1
1 if male
years of education
age
1 if married, 0 otherwise
number of children
number of housemates
region type, one of "big city", "small city", and "town"
type of residential facility, either "dwelling" or "apartment"
1 if has religion
1 if in religious meeting groups
1 if in social gathering groups
1 if in leisure/sports groups, etc.
1 if in union/fraternity groups, etc.
1 if in volunteer service groups
1 if in political/civic/interest groups
health conditions, one of "excellent",
"above average", "average", "below average", and "poor"
1=poor, 2=below average, 3=average, 4=above average, 5=excellent
1=health above average, 0=average, -1=below average
height in cm
weight in kg
period of regular exercise; 0=do not regularly exercise, 1=0~3mo, 2=4~6mo, 3=7mo~1yr, 4=1~2yr, 5=3~4yr, 6=5~6yr, 7=7+yr
BMI
# of cigarettes smoked per day
1 if working
job type; one of waged employee, self-employed, unemployed, unpaid family worker
1 if seeking a job
amount received from children last year (10k KRW)
amount given to children last year (10k KRW)
regular pocket money received from children (10k KRW)
satisfaction about health conditions
satisfaction about economic conditions
satisfaction about relationship with spouse
satisfaction about relationship with children
satisfaction in comparison to others in the same age group (out of 100)
number of travels last year
expenditure on travel (10k KRW)
number of cultural activities
expenditure on cultural activities
hours for hobbies, per month
expenditure on hobbies (10k KRW)
hours for self development, per month
expenditure on self development (10k KRW)
hours of volunteer service
Goeun Lee, Chirok Han [aut, cre, cph]
https://survey.keis.or.kr/klosa/klosa01.jsp
Average salary for Korean firms in 2012
data(Ksalary)data(Ksalary)
A data frame with 1636 rows and 10 variables:
sequential number
"kospi" or "kosdaq"
sales in Bil. KRW
profit in Bil. KRW
sector (character)
number of employees
average salary in Mil. KRW
average years of tenure
=1 if KOSPI
=1 if KOSDAQ
Chirok Han [aut, cre, cph]
https://blog.naver.com/naamoo01/130185489128
This package contains data sets for Lectures on Econometrics by Chirok Han
Chirok Han [aut, cre, cph]
help(package="loedata")
Korean regional public servants and financial independence in 2010
data(Pubserv)data(Pubserv)
A data frame with 86 rows of 3 variables:
name of gun
number of public servants per 1000 pop
financial independence index, = (local tax + other income)/budget * 100
Chirok Han [aut, cre, cph]
Korean regional data for 2014-2016 average
data(Regko)data(Regko)
A data frame with 264 rows of 23 variables:
ID of region
Metropolitan region name (metro cities and provinces)
Region name
1=si (non-metropolitan cities), 2=gun, 3=gu in metro cities and provinces
gross regional GDP
population
population growth
the EQ-5D health index
number of registered deaths
% of drinkers
% of high-risk drinkers
% of smokers
% of aged 65 and over
# of divorces per 1000 pop
# of medical beds per 1000 pop
gender composition # men / 100 women
# of vehicles per person
# of accidents per 1000 vehicles
waste dump per person, kg/day
# of students per teacher
# of deaths per 100,000 pop
=gcmp/(gcomp+100)*100, % of male
=vehipc*accpv, # of accidents per 1000 pop
Chirok Han [aut, cre, cph]
Korean regional panel data (2014-2016)
data(RegkoPanel)data(RegkoPanel)
A data frame with 792 rows of 24 variables:
ID of region
Metropolitan region name (metro cities and provinces)
Region name
1=si (non-metropolitan cities), 2=gun, 3=gu in metro cities and provinces
Year
gross regional GDP
population
population growth (=100*(regpop/regpop[-1]-1))
the EQ-5D health index
number of deaths
% of drinkers
% of high-risk drinkers
% of smokers
% of aged 65 and over
# of divorces per 1000 pop
# of medical beds per 1000 pop
gender composition # men / 100 women
# of vehicles per person
# of accidents per 1000 vehicles
waste dump per person, kg/day
# of students per teacher
# of deaths per 100,000 pop
=gcmp/(gcomp+100)*100, % of male
=vehipc*accpv, # of accidents per 1000 pop
Chirok Han [aut, cre, cph]