7.1 The LIS_data repository

In order to work with the LIS data you need to clone the repository PovcalNet-Team/LIS/_data. You will find in there three folders, 00.LIS_output, 01.programs, and 02.data.

7.2 Interacting with LISSY

Opening an account in LISSY:

To interact with the LIS data you need to first register here, by first completing the LIS microdata User Registration Form, and then submitting it through the same website using your institutional e-mail account. Within a couple of days, you will receive an e-mail from LIS containing your username and password.

Interacting with LISSY:

To get acquainted with LISSY’s interface, coding structure, database naming and variables available, and learn how to compute estimates within LISSY we highly recommend taking some time to review the tutorials and self-teaching materials. However, in order to update the 400 bins twice a year, Stata codes have been previously written, so you simply need to follow the 5 steps in the next section.

7.3 Getting the 400 bins from LISSY

1. To log in, go to LIS main page, scroll down and click on the lock icon

2. Feed the three drop-down menus on top of the platform with the following information:

• Project: LIS

• Package: Stata

• Subject: (Choose a name Ex: “Bins #1 - Dec 2020”)

#####################################################
  Your job has been killed and will be not executed  
#####################################################

3. Copy and paste the entire content of 01.LIS_400bins.do file into the the main large command window and update the locals in lines 23-24 with the LIS 2-letter acronyms of the group of 5-6 countries in each round.

local silc   "at be cz"
local nosilc "au br"

4. Click on the green arrow icon to submit your project. You will get an e-mail within some minutes with your output. If the system kills your project, your group of countries was probably too large. Remove one country and try again.

5. Copy the entire text in the output e-mail you receive for each round, open your notepad and paste. Save each round in the \00.LIS_output folder. Save each text file with the name LISSY_Dec202@_#.txt, [where @ is the year and # the round]. Consistency with this naming format is important for the next step (02.LIS_organize_output.do file)

7.4 From Text file to datalibweb structure

We now need to convert the the text files generated by the LISSY system to actual data suitable for datalibweb. This structure is suggested by the International Household Survey Network (IHSN). Once the data is saved in folder 00.LIS_output you need to execute the file 02.LIS_organize_output.do. This file created to be executed in just one go. However, it could be ran in sections taking advantage of the different frames along the code.

Before you execute this code, you need to ensure a few things,

cap which rcall
if (_rc) {
    cap which github
    if (_rc) {
        net install github, from("https://haghish.github.io/github/")
    }
    github install haghish/rcall, stable
}

if (lower("`c(username)'") == "wbxxxxx") {
    local dir "c:/Users/wbxxxxx/OneDrive - WBG/WorldBank/DECDG/PovcalNet Team/LIS_data"
}

global update_surveynames = 1 // 1 to update survey names.
global replace            = 0 // 1 to replace data in memory even if it has not changed
global p_drive_output_dir = 0 // 1 to use default Vintage_control folder

7.5 Compare new LIS data to Datalibweb inventory

To identify what data is new and what data has changed with respect to the one available in datalibweb, you need to execute do-file 03.LIS_compare_dlw.do. Again, this do-file is intended to be executed in one run, but you can do it in parts taking advantage of the different frames. At the end of the execution the file 02.data/comparison_results.dta is created. This file contains three important variables wf, wt, and gn, which correspond to the ration of welfare means, weight means, and Gini coefficient between the data in datalibweb and the data in the folder, p:/01.PovcalNet/03.QA/06.LIS/03.Vintage_control.

You should only send to the Poverty GP those surveys for which at least one of these three variables is different to 1.

7.6 The Excel file LIS datasets.xlsx

With each LIS data update performed, we must first identify from LIS the new surveys (countries and/or years) they had recently added. LIS send users e-mails informing about new datasets added, and also releases newsletters with this information.

Inside the 02.data folder of your LIS_data GIT repository you will find a _aux sub folder, and the LIS datasets.xlsx file placed in there. We must manually update the tab LIS_survname tab adding new rows to the sheet. All necessary information to fill up this metadata (household size, currency, etc.) can be found in METIS.

Finally, while the survey names in METIS are in English, some of the acronyms in parenthesis are still in the original language. In those cases we translated them to English. For instance, the survey name “Household Budget Survey (BdF) (France)” from METIS was changed to “Household Budget Survey (HBS) (France)” in the column surveyname of the excel.

7.7 Prepare data for the Poverty GP

Finally, the do-file 04.Append_new_LIS_bases.do prepares the data to be shared with the Poverty GP. Note that this do-file ONLY appends the 400 bins data of surveys that are new and those where welfare changed, which are identified in the previous step /comparison_results.dta as those gn != 1.

Before running the code, make sure to change the output file name to the date of your update (last one saved was “LIS_bins_Dec_21_2020.dta”). The output is saved in P:\01.PovcalNet\03.QA\06.LIS\04.Share_with_GP.

Finally, quickly prepare a short .dta file importing the metadata already created in the LIS_survname tab from the Excel, keeping ONLY the surveys of the append output you just run and send both files to Minh Cong Nguyen <mnguyen3@worldbank.org> from the Poverty GP.