Regko

Korean regional data for 2014-2016 average

datasets

Data sets for Chirok Han (2024, ISBN:979-11-303-1964-3,
"Lectures on Econometrics"). Students, teachers, and self-learners will
find the data sets essential for replicating the results in the book.

Chirok Han

loedata

Data Sets from "Lectures on Econometrics" by Chirok Han

Regko function

A data frame with 264 rows of 23 variables:<dl>
 <dt>id</dt>
<dd>ID of region</dd> <dt>metro</dt>
<dd>Metropolitan region name (metro cities and provinces)</dd> <dt>region</dt>
<dd>Region name</dd> <dt>type</dt>
<dd>1=si (non-metropolitan cities), 2=gun, 3=gu in metro cities and provinces</dd> <dt>grdp</dt>
<dd>gross regional GDP</dd> <dt>regpop</dt>
<dd>registered population (end of year, by registration record, excl. foreigners)</dd> <dt>popgrowth</dt>
<dd>population growth</dd> <dt>eq5d</dt>
<dd>the EQ-5D health index</dd> <dt>deaths</dt>
<dd>number of registered deaths</dd> <dt>drink</dt>
<dd>% of drinkers</dd> <dt>hdrink</dt>
<dd>% of high-risk drinkers</dd> <dt>smoke</dt>
<dd>% of smokers</dd> <dt>aged</dt>
<dd>% of aged 65 and over</dd> <dt>divorce</dt>
<dd># of divorces per 1000 pop</dd> <dt>medrate</dt>
<dd># of medical beds per 1000 pop</dd> <dt>gcomp</dt>
<dd>gender composition # men / 100 women</dd> <dt>vehipc</dt>
<dd># of vehicles per person</dd> <dt>accpv</dt>
<dd># of accidents per 1000 vehicles</dd> <dt>dumppc</dt>
<dd>waste dump per person, kg/day</dd> <dt>stratio</dt>
<dd># of students per teacher</dd> <dt>deathrate</dt>
<dd># of deaths per 100,000 mid-year population (note: not equal to deaths/regpop*1e5)</dd> <dt>nbirth</dt>
<dd># of births</dd> <dt>cbrate</dt>
<dd>Crude birth rate (per 1,000 pop)</dd> <dt>tfrate</dt>
<dd>Total fertility rate</dd> <dt>pctmale</dt>
<dd>=gcomp/(gcomp+100)*100, % of male</dd> <dt>accpc</dt>
<dd>=vehipc*accpv, # of accidents per 1000 pop</dd>
</dl>

Format

Korean regional data (2014-2016 averages) — Regko

A data frame with 264 rows of 23 variables:<dl>
 <dt>id</dt>
<dd>ID of region</dd>

 <dt>metro</dt>
<dd>Metropolitan region name (metro cities and provinces)</dd>

 <dt>region</dt>
<dd>Region name</dd>

 <dt>type</dt>
<dd>1=si (non-metropolitan cities), 2=gun, 3=gu in metro cities and provinces</dd>

 <dt>grdp</dt>
<dd>gross regional GDP</dd>

 <dt>regpop</dt>
<dd>registered population (end of year, by registration record, excl. foreigners)</dd>

 <dt>popgrowth</dt>
<dd>population growth</dd>

 <dt>eq5d</dt>
<dd>the EQ-5D health index</dd>

 <dt>deaths</dt>
<dd>number of registered deaths</dd>

 <dt>drink</dt>
<dd>% of drinkers</dd>

 <dt>hdrink</dt>
<dd>% of high-risk drinkers</dd>

 <dt>smoke</dt>
<dd>% of smokers</dd>

 <dt>aged</dt>
<dd>% of aged 65 and over</dd>

 <dt>divorce</dt>
<dd># of divorces per 1000 pop</dd>

 <dt>medrate</dt>
<dd># of medical beds per 1000 pop</dd>

 <dt>gcomp</dt>
<dd>gender composition # men / 100 women</dd>

 <dt>vehipc</dt>
<dd># of vehicles per person</dd>

 <dt>accpv</dt>
<dd># of accidents per 1000 vehicles</dd>

 <dt>dumppc</dt>
<dd>waste dump per person, kg/day</dd>

 <dt>stratio</dt>
<dd># of students per teacher</dd>

 <dt>deathrate</dt>
<dd># of deaths per 100,000 mid-year population (note: not equal to deaths/regpop*1e5)</dd>

 <dt>nbirth</dt>
<dd># of births</dd>

 <dt>cbrate</dt>
<dd>Crude birth rate (per 1,000 pop)</dd>

 <dt>tfrate</dt>
<dd>Total fertility rate</dd>

 <dt>pctmale</dt>
<dd>=gcomp/(gcomp+100)*100, % of male</dd>

 <dt>accpc</dt>
<dd>=vehipc*accpv, # of accidents per 1000 pop</dd>


</dl>

Regko: Korean regional data (2014-2016 averages)

Description

Usage

Arguments

Format

See Also