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Day 2: Labour Market Participation and Income Earning Activities

Day 2: Labour Market Participation and Income Earning Activities. Department of Economics Trinity College Dublin, Ireland. Road map. New commands Exercise 1 HH members working and earning income Exercise 2 Activities by gender and consumption quintiles Exercise 3

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Day 2: Labour Market Participation and Income Earning Activities

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  1. Day 2: Labour Market Participation and Income Earning Activities Department of Economics Trinity College Dublin, Ireland

  2. Road map • New commands • Exercise 1 • HH members working and earning income • Exercise 2 • Activities by gender and consumption quintiles • Exercise 3 • Diversification of income activities • Income shares from income earning activities

  3. Today’s commands • egenname=stat(var1) : adds some summary statistic of var1 to the data as a variable. This command can be used with the ‘by’ command to generate this statistic for different categories. • For example, ‘egen var1=sum(var2), by(var3)’ generates a variable called var1 which is the sum of var2 for different categories given by var3. • See help egen for more details • collapse (stat) list : collapses the data into statistics of the variables given in list.  This command can be use with the ‘by’ command to collapse the dataset into statistics for different categories. • For example, ‘collapse (mean) var1var2, by(var3)’ will collapse the dataset into the mean of var1 and var2 for each of the categories given by var3 • See help collapse for more details

  4. Getting Started Open the do-file “day2.do” stored in “C:\Data” Write your name and the date in the title box Clear all data from Stata’s memory Set Stata up so that 200 megabytes of RAM is allocated to store the data Set the path to “C:\Data” Open a new log file called “day2.log”

  5. Exercise 1 • Open the data file “day2_1.dta” • ‘count’ the number of observations in the data set • Use the ‘describe’ command to review the data in memory • Sort by individual

  6. 5 types of occupations • Working for wage/salary outside the household • Participating in Household production related to agriculture/forestry/aquaculture • Non-farm, non-wage activities, not housework (trading, services, transportations, other business) • Using common property resources to generate income for the household (fishing, hunting, gathering honey and berries) • Doing housework or chores

  7. Exercise 1 • Run the command lines in the do-file that create and label the following variables • hh_active : Total number of HH members of active age • hh_wage : Total number of HH members working for a wage outside of household • hh_wage_prop: Proportion of active HH members working for a wage outside the household • hh_hhprod: Total number of HH members working in the farm household enterprise • hh_hhprod_prop: Proportion of active HH members working in the farm household enterprise

  8. Exercise 1 • Generate and label the following variables: • hh_hhbus: Total number of HH members working in non-farm, non-wage activities, not housework • hh_hhbus_prop: Proportion of active HH members working in non-farm, non-wage activities, not housework • hh_hhprod: Total number of HH members working in the farm household enterprise • hh_hhprod_prop: Proportion of active HH members working in the farm household enterprise • hh_common: Total number of HH members engaged in common property use work • hh_common_prop: Proportion of active HH members engaged in common property use work • hh_house: Total number of HH members doing housework or chores • hh_house_prop: Proportion of active HH members doing housework or chores

  9. Exercise 1 • Run the command lines in the do-file that create and label the following variables • income : Individual HH member earning income • hh_income: Total number of HH members earning income • hh_income_prop: Proportion of active HH members earning income • work: Individual HH member earning income • hh_work: Total number of HH members working • hh_work_prop: Proportion of active HH members working • Collapse hhsizehh_workhh_income wt9 by household • Replicate Figure 2.1 from the 2006 report using the 2008 data (Hints: don’t forget to use weights)

  10. Exercise 2 • Open the data file “day2_2.dta” • Use the ‘describe’ command to review the data in memory • Sort by individual • Run the command lines in the do-file that create and label the following variables • work_male: Dummy variable “male working” • hh_workmal: Total number of male HH members working • hh_workmal_prop: Proportion of male active HH members working • income_male: Dummy variable “male earning income” • hh_incomemal: Total number of male HH members earning income • hh_incomemal_prop: Proportion of male active HH members earning income • wage_male: Male working for wage outside the household • hh_wagemal: Total number of male HH members working for a wage outside of household • hh_wagemal_prop: Proportion of male active HH members working for a wage outside of household

  11. Exercise 2 • Run the command lines in the do-file that create and label the following variables • hhprod_male: Male working in the farm household enterprise • hh_hhprodmal: Total number of male HH members working in the farm household enterprise • hh_hhprodmal_prop: Proportion of male active HH members working in the farm household enterprise

  12. Exercise 2 • Generate and label the following variables: • work_fem: Dummy variable “female working“ • hh_workfem: Total number of female HH members working • hh_workfem_prop: Proportion of female active HH members working for a wage outside of household" • income_fem: Dummy variable “female earning income” • hh_incomefem: Total number of female HH members earning income • hh_incomefem:_prop: Proportion of femaleearning income • wage_fem: Female working for wage outside the household • hh_wagefem: Total number of female HH members working for a wage outside of household • hh_wagefem_prop: Proportion of female active HH members working for a wage outside of household • hhprod_fem: Male working in the farm household enterprise • hh_hhprodfem: Total number of female HH members working in the farm household enterprise • hh_hhprodfem_prop: Proportion of female active HH members working in the farm household enterprise

  13. Exercise 2 • Collapse hh_workfem_prop hh,_workmal_prop, hh_incomefem_prop, hh_incomemal_prop, hh_wagefem_prop, hh_wagemal_prop, hh_hhprodfem_prop, hh_hhprodmal_prop, hh_work_prop, hh_income_prop, fdpcquint, and wt9 by household • Replicate Column 1-4 Table 2.1 from the 2006 report using the 2008 data (Hint: don’t forget to use weights) • Replicate Graph a), b) of Figure 2.2 from the 2006 Report using the 2008 data (Hint: don’t forget to use weights)

  14. Exercise 3 • Open the data file “day2_3.dta” • Use the ‘describe’ command to review the data in memory • Count observations • Sort by household level • Run the command lines in the do-file that create and label the following variable • hhdivers: number of activity types HH is involved in • Replicate Table 2.3 from the 2006 report using the 2008 data (Hint: don’t forget to use weights)

  15. Exercise 3 • A number of variables have to be created for Table 2.5. • totinc: HH Total Income • wageinc: HH Wage Income • agroinc: HH Income from agricultural activities • hhbusinc: HH Income from nonfarm/non-wage activities • compropinc: HH Income from common property resources • other: HH Other Income • iwagesh: HH wage income as a share of total income • iagrosh: HH income from agricultural activities as a share of total income • ihhbussh: HH income from nonfarm/non-wage activities as a share of total income • icompropsh: HH income from common property resources as a share of total income • iothersh: HH other income as a share of total income • A number of prompts and hints are given in the do-file

  16. Exercise 3 • Replicate Table 2.5 from the 2006 report using the 2008 data – Labor Income Share only (Hint: don’t forget to use weights) • Replicate Figure 2.5 from the 2006 report using the 2008 data (Hint: don’t forget to use weights) • Close the log file

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