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Working with NSSO Data Using STATA
2020
Lecture 2: This lecture deals with merging ( one to one merge, one to many merge and many to one merge) and calculation of few basic employment and unemployment indicators using PLFS data set
Lecture 1: This lecture deals with extractions , merging , uses of weight part of data work. For the purpose periodic labour force survey (PLFS) 2018-19 is used.
2021
Lecture 1: This lecture is the same as above. The only difference is that it was taken in a different year with a different set of cohorts. The cohort was MA Eco students. It deals mainly with the extraction, merging and use of weights. The PPT file used in this lecture can be found here.
Lecture 2: This lecture deals with merging ( one to one merge, one to many merge and many to one merge) and calculation of a few basic employment and unemployment indicators using PLFS data set. The PPT used in this lecture can be found here.
UPDATES and CORRECTIONS
Correction 1: for estimating annual statistics of labour market indicators, divide the same weight with a number of quarter variables in the data file instead of 4. A proportion of the data set number of quarters is different from 4.
Update 1: for PLFS 2022-23, calculate labour market indicators using the below Stata codes. You can note the changes in the calculation of WPR across state, sector and gender in below mentioned codes.
*** generating employment, unemployment and not in labour force code for PS + SS activity workers.
gen empps=1 if perv_fvv9>=11 & perv_fvv9<=51
replace empps=2 if perv_fvv9==81
replace empps=3 if perv_fvv9>=91 & perv_fvv9<=97
gen empss=1 if perv_fvv20>=11 & perv_fvv19<=51
replace empss=2 if perv_fvv20==81
replace empss=3 if perv_fvv20>=91 & perv_fvv19<=97
gen empsss=1 if empps==1 | empss==1
**** for getting WPR across state, sector and gender
egen dinemp=rowtotal(perv_fvv31 perv_fvv32)
egen tduration=rowtotal(perv_fvv34 dinemp)
gen dninlf=12-tduration
rename perv_fvv34 dunemp
save,replace
gen emp_new=1 if dinemp>=1
**step 1: first get employment distribution across categories
table sg sector [fw=weight1] if emp_new ==1 & age>=15
**Step 2: obtain distribution of total ppulation across categories
table sg sector [fw=weight1] if age>=15
**setep 3: compy and paste the above tables on excel.
** Derive WPR statistics using the WPR formula, here we are required to divide statistics obtained from step 1 by the total population obtained from step 2
** Data is fully matched with the report, pg. no. 9
*** Labour force
gen labourforceps=1 if perv_fvv9>=11 & perv_fvv9<=82
gen labourforcess=1 if perv_fvv20>=11 & perv_fvv20<=82
gen labourforce=1 if labourforceps==1| labourforcess==1
table sg sector [fw=weight1] if labourforce==1 & age>=15
* matched with report, pg. No. 7
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