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worldbank / ESG_gaps_research

See draft publication here: https://worldbank.github.io/ESG_gaps_research/
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Assignment of expl_g #9

Closed tgherzog closed 4 years ago

tgherzog commented 4 years ago

Many discrepancies in expl_g between the values and the analysis on which it is supposed to be based. See attachment.

ESG Data Comparison Matrix-2019b.xlsx

tgherzog commented 4 years ago

We need a separate conversation on which of these indicators should be switched from 1 to 0 for expl_g but we first need to fix the problem above.

andreiilas commented 4 years ago

I corrected this issue and pushed it to the rep on GitKraken

tgherzog commented 4 years ago

I'm reopening this issue.

First, in the spreadsheet above I count 42 countries that should nominally be coded 1 for EXP_G, but there are only 30 in the latest database. 3 of those 12 countries have EXP_B=1 which leaves 9 remaining:

IC.FRM.OUTG.ZS
IP.PAT.RESD
MS.MIL.XPND.GD.ZS
NY.ADJ.DFOR.GN.ZS
NY.ADJ.DPEM.GN.ZS
SH.DTH.COMM.ZS
SH.STA.MMRT
SN.ITK.DEFC.ZS
TX.MNF.TECH.ZS.UN

Let's discuss at our 2pm meeting today. I first want to make sure there's not an error on my part.

tgherzog commented 4 years ago

For discussion: here is a list of indicators where we're missing 80%+ of HIC countries:

CETSID Description
DT.ODA.ODAT.CD Net official development assistance received (current US$)
SH.MLR.INCD.P3 Incidence of malaria (per 1,000 population at risk)
SI.POV.NAHC Poverty headcount ratio at national poverty lines (% of population)
SL.TLF.0714.ZS Children in employment, total (% of children ages 7-14)
SP.UWT.TFRT Unmet need for contraception (% of married women ages 15-49)

Except for possibly SI.POV.NAHC I'm fine to apply EXP_G to all of these on the basis that the values are not interesting for HICs.

Here is the same list for low-population countries (POP<100,000), and I've marked the ones I think are still relevant to small economies (i.e., EXP_G should be changed to 0):

CETSID Description Relevant?
EG.ELC.COAL.ZS Electricity production from coal sources (% of total)  
EG.ELC.NUCL.ZS Electricity production from nuclear sources (% of total)
EG.IMP.CONS.ZS Energy imports, net (% of energy use)  
EN.CLC.GHGR.MT.CE GHG net emissions/removals by LUCF (Mt of CO2 equivalent)
EN.CLC.MDAT.ZS Droughts, floods, extreme temperatures (% of population, average 1990-2009) 1
ER.H2O.FWTL.ZS Annual freshwater withdrawals, total (% of internal resources)
GFDD.DM.06 Outstanding international public debt securities to GDP (%)
IC.FRM.OUTG.ZS Value lost due to electrical outages (% of sales for affected firms) 1
IP.PAT.RESD Patent applications, residents  
MS.MIL.XPND.GD.ZS Military expenditure (% of GDP)  
NY.ADJ.DFOR.GN.ZS Adjusted savings: net forest depletion (% of GNI)  
NY.ADJ.DPEM.GN.ZS Adjusted savings: particulate emission damage (% of GNI)
NY.ADJ.DRES.GN.ZS Adjusted savings: natural resources depletion (% of GNI)
SH.DTH.COMM.ZS Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions (% of total) 1
SH.DYN.AIDS.ZS Prevalence of HIV, total (% of population ages 15-49) 1
SH.MLR.INCD.P3 Incidence of malaria (per 1,000 population at risk) 1
SH.STA.MMRT Maternal mortality ratio (modeled estimate, per 100,000 live births) 1
SI.DST.FRST.20 Income share held by lowest 20% 1
SI.POV.DDAY Poverty headcount ratio at $1.90 a day (2011 PPP) (% of population) 1
SI.POV.GINI GINI index (World Bank estimate) 1
SI.POV.NAHC Poverty headcount ratio at national poverty lines (% of population) 1
SI.SPR.PCAP.ZG Annualized average growth rate in per capita real survey mean consumption or income, total population (%) 1
SL.EMP.1524.SP.ZS Employment to population ratio, ages 15-24, total (%) (modeled ILO estimate) 1
SL.EMP.VULN.ZS Vulnerable employment, total (% of total employment) (modeled ILO estimate) 1
SL.TLF.0714.ZS Children in employment, total (% of children ages 7-14) 1
SL.TLF.ACTI.ZS Labor force participation rate, total (% of total population ages 15-64) (modeled ILO estimate) 1
SL.TLF.CACT.FM.ZS Ratio of female to male labor force participation rate (%) (modeled ILO estimate) 1
SL.UEM.1524.ZS Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) 1
SL.UEM.TOTL.FE.ZS Unemployment, female (% of female labor force) (modeled ILO estimate) 1
SL.UEM.TOTL.ZS Unemployment, total (% of total labor force) (modeled ILO estimate) 1
SM.POP.NETM Net migration  
SN.ITK.DEFC.ZS Prevalence of undernourishment (% of population) 1
SP.POP.65UP.TO.ZS Population ages 65 and above (% of total population) 1
SP.POP.SCIE.RD.P6 Researchers in R&D (per million people) 1
SP.POP.TECH.RD.P6 Technicians in R&D (per million people) 1
SP.UWT.TFRT Unmet need for contraception (% of married women ages 15-49) 1
TX.MNF.TECH.ZS.UN Medium and high-tech exports (% manufactured exports)
andreiilas commented 4 years ago

ESG.Data.Comparison.Matrix-2019b (3).xlsx

The problem came from a faulty selection in excel when I sorted by color. It would keep the cetsid constant while changing the other variables.

In total there are 41 indicators with G, from which I deleted 6 that were coded B due to MRV 2014 or earlier.

tgherzog commented 4 years ago

@andreiilas - you should have 42 indicators less 6 coded B for a total of 36. Don't forget the Retirement Age indicator (WBL) should also be coded G as discussed on #9

andreiilas commented 4 years ago

thanks Tim. I updated it.

tgherzog commented 4 years ago

This is an update to this comment but with the small economy threshold set to 120,000 population as we discussed. The net effect was to flag 6 HIC countries and 30 small economy countries (excluding those that had already been flagged EXP_A or EXP_B).

HIC countries are as follows:

ID DESCRIPTION
DT.ODA.ODAT.CD Net official development assistance received (current US$)
SH.MLR.INCD.P3 Incidence of malaria (per 1,000 population at risk)
SI.POV.NAHC Poverty headcount ratio at national poverty lines (% of population)
SL.TLF.0714.ZS Children in employment, total (% of children ages 7-14)
SP.UWT.TFRT Unmet need for contraception (% of married women ages 15-49)
WBL Retirement Age

Let's have a quick discussion about these; the two I can imagine being non-trivial for HICs are SI.POV.NAHC, SP.UWT.TFRT and possibly "Retirement Age"

The small economy indicators look like this . The ones where I've put "1" in column 3 are the ones that I'm suggesting may be "false positives," that is, they are non-trivial for small economies. Column 4 shows which indicators are being flagged as possibly trivial for HIC countries.

ID DESCRIPTION NON-TRIVIAL IS_RICH
EG.ELC.COAL.ZS Electricity production from coal sources (% of total) 0  
EG.ELC.NUCL.ZS Electricity production from nuclear sources (% of total) 0  
EG.IMP.CONS.ZS Energy imports, net (% of energy use) 0  
GFDD.DM.06 Outstanding international public debt securities to GDP (%) 0  
IP.PAT.RESD Patent applications, residents 0  
MS.MIL.XPND.GD.ZS Military expenditure (% of GDP) 0  
NY.ADJ.DPEM.GN.ZS Adjusted savings: particulate emission damage (% of GNI) 0  
NY.ADJ.DRES.GN.ZS Adjusted savings: natural resources depletion (% of GNI) 0  
SH.DYN.AIDS.ZS Prevalence of HIV, total (% of population ages 15-49) 1  
SH.MLR.INCD.P3 Incidence of malaria (per 1,000 population at risk) 1 1
SH.STA.SMSS.ZS People using safely managed sanitation services (% of population) 1  
SI.DST.FRST.20 Income share held by lowest 20% 1  
SI.POV.DDAY Poverty headcount ratio at $1.90 a day (2011 PPP) (% of population) 1  
SI.POV.GINI GINI index (World Bank estimate) 1  
SI.POV.NAHC Poverty headcount ratio at national poverty lines (% of population) 1 1
SI.SPR.PCAP.ZG Annualized average growth rate in per capita real survey mean consumption or income, total population (%) 1  
SL.EMP.1524.SP.ZS Employment to population ratio, ages 15-24, total (%) (modeled ILO estimate) 1  
SL.EMP.VULN.ZS Vulnerable employment, total (% of total employment) (modeled ILO estimate) 1  
SL.TLF.0714.ZS Children in employment, total (% of children ages 7-14) 1 1
SL.TLF.ACTI.ZS Labor force participation rate, total (% of total population ages 15-64) (modeled ILO estimate) 1  
SL.TLF.CACT.FM.ZS Ratio of female to male labor force participation rate (%) (modeled ILO estimate) 1  
SL.UEM.1524.ZS Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) 1  
SL.UEM.TOTL.FE.ZS Unemployment, female (% of female labor force) (modeled ILO estimate) 1  
SL.UEM.TOTL.ZS Unemployment, total (% of total labor force) (modeled ILO estimate) 1  
SN.ITK.DEFC.ZS Prevalence of undernourishment (% of population) 1  
SP.POP.SCIE.RD.P6 Researchers in R&D (per million people) 0  
SP.POP.TECH.RD.P6 Technicians in R&D (per million people) 0  
SP.UWT.TFRT Unmet need for contraception (% of married women ages 15-49) 1 1
TX.MNF.TECH.ZS.UN Medium and high-tech exports (% manufactured exports) 1  
WBL Retirement Age 1 1
tgherzog commented 4 years ago

I've committed the changes from our 11/26 discussion to the metadata file, so I'm closing this.

HirokoMaeda commented 4 years ago

This is to follow up on the trivial vs non-trivial discussion for high-income countries here.

  1. SH.MLR.INCD.P3 | Incidence of malaria (per 1,000 population at risk) Malaria is less relevant in high income countries, since most of the them are located in malaria free climate (e.g. Europe, North America). The incidence of high income countries with malaria climate (e.g. South Korea, Saudi Arabia, and Singapore) can be considered zero in general.

  2. SL.TLF.0714.ZS | Children in employment, total (% of children ages 7-14) Child labor is trivial. They exist in high-income countries, but the size is small (1 percent of the total number of child labors).

  3. WBL | Retirement Age | 1 | 1 There aren’t laws that set mandatory retirement age in many high-income countries such as USA. The data source will move toward a pension-based question: the statutory retirement age for a woman/man to receive a full old-age pension.

tgherzog commented 4 years ago

This is to follow up on the trivial vs non-trivial discussion for high-income countries here.

Thanks, @HirokoMaeda this confirms the values already in the spreadsheet