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

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 2

3. Today’s commands egen name=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) var1 var2, 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 3

4. Getting Started 1.Open the do-file “day2.do” stored in “C:\Data” 2.Write your name and the date in the title box 3.Clear all data from Stata’s memory 4.Set Stata up so that 200 megabytes of RAM is allocated to store the data 5.Set the path to “C:\Data” 6.Open a new log file called “day2.log” 4

5. Exercise 1 1.Open the data file “day2_1.dta” 2.‘count’ the number of observations in the data set 3.Use the ‘describe’ command to review the data in memory 4.Sort by individual 5

6. 1.Working for wage/salary outside the household 2.Participating in Household production related to agriculture/forestry/aquaculture 3.Non-farm, non-wage activities, not housework (trading, services, transportations, other business) 4.Using common property resources to generate income for the household (fishing, hunting, gathering honey and berries) 5.Doing housework or chores 5 types of occupations 6

7. Exercise 1 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 7

8. Exercise 1 2.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 8

9. Exercise 1 3.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 4.Collapse hhsize hh_work hh_income wt9 by household 5.Replicate Figure 2.1 from the 2006 report using the 2008 data (Hints: don’t forget to use weights) 9

10. Exercise 2 1.Open the data file “day2_2.dta” 2.Use the ‘describe’ command to review the data in memory 3.Sort by individual 4.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 10

11. Exercise 2 5.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 11

12. Exercise 2 6.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 female earning 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 12

13. Exercise 2 7.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 8.Replicate Column 1-4 Table 2.1 from the 2006 report using the 2008 data (Hint: don’t forget to use weights) 9.Replicate Graph a), b) of Figure 2.2 from the 2006 Report using the 2008 data (Hint: don’t forget to use weights) 13

14. Exercise 3 1.Open the data file “day2_3.dta” 2.Use the ‘describe’ command to review the data in memory 3.Count observations 4.Sort by household level 1.Run the command lines in the do-file that create and label the following variable hhdivers: number of activity types HH is involved in 5.Replicate Table 2.3 from the 2006 report using the 2008 data (Hint: don’t forget to use weights) 14

15. Exercise 3 6.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 15

16. Exercise 3 7.Replicate Table 2.5 from the 2006 report using the 2008 data – Labor Income Share only (Hint: don’t forget to use weights) 8.Replicate Figure 2.5 from the 2006 report using the 2008 data (Hint: don’t forget to use weights) 9.Close the log file 16