Version 7.91 Final (December 2nd, 2022)

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You can download IFs Version 7.91 Final at 7.91 Final VB6 version and 7.91 Final NET version.

Model Updates

• Added UNPAIDLABOR.
• Added INCOMELT215LN, INCOMELT365LN, INCOMELT685LN, initialization and Forecast.
• Added POVGAP365, POVGAP685, update on POVGAP using 2017$.
• Added POVRATE365, POVRATE685, update on POVRATE using 2017$.
• Added POVCOUNT365, POVCOUNT685, update on POVCOUNT using 2017$.
• Added POVGNDRATIO365, POVGNDRATIO685, update on POVGNDRATIO using 2017$.
• Added POVSHORT365, POVSHORT685, update on POVSHORT using 2017$.
• Added POVSHORTSEXDIFF365, POVSHORTSEXDIFF685, update on POVSHORTSEXDIFF using 2017$.
• Added POV15PCT365, POV15PCT685, update on POV15PCT using 2017$.
• Added POV25PCT365, POV25PCT685, update on POV25PCT using 2017$.
• Fix for WATSAN5 on Forward linkages, Malnutrition and Mortality
• Added Forecast of MARRIEDFEMSHR and POPFEM15TO24
• Added Forecast of WOMENINLEADERSHIP.

• MARRIEDFEMSHR: for the share of girls/women, 15-19 and 20-24, who are married. The variable is driven by educational attainment of 25 year plus, both sexes combined. The 20-24 rate is computed as the 15-19 rate plus an additional amount added to it. The additional amount, i.e., the difference between the 20-24 rate and the 15-19 rates is the dependent variable of the regression for the 20-24 variable. I have used a cubic function, not only because it has a better fit, but also the patter has an interpretation. With very low ed/dev countries have high earlier (15-19) marriage thus leaving less headroom to add in 20-24. With more education, the 15-19 rate decreases allowing more addition in 20-24. With further progress, 20-24 rates start coming down. The independent variable (edyears25) is bounded between 1 year and 16 years, thus preventing growth/decline explosion at the end of cubic function. I have also save functions of other formats like linear, log etc.
• Same functions are used to estimate missing values when there is no data at all, or extrapolate when the available data is from an year prior to the base year.
  • Historical growth rates are also used as the initial growth rate of projection, converging it to regression model growth rate over a period of 20 years.
  • There is also MARRIEDFEMPOP for the number of girls/women married.
  • Changing rate of marriage: The parameter/multiplier to change the rate/share of marriage is marriedfemshrm.
  • Education impact: In the base case there is no impact of rate of marriage on schooling. When marriage rates change through multiplier, lower and upper secondary graduation rates change. The change is computed as the difference induced by the marriedfemshrm, which is multiplied with the respective parameters - marriageedseclowr and marriageedsecuppr (they are in GlobalParametersMult in IFs.mdb) . The default values are. .5 for 15-19 and 0 for 20-24 for lower sec, and .5 for 15-19 and .05 for 20-24 for upper secondary. A value of .5 means a 1 percentage point reduction in rate of marriage will increase graduation rate by half a percentage point. Some of that growth might be taken away by other drivers of education, like finance.
  • The education variables that need to be checked for immediate impact are - EDSECLOWRGRATE (Female) and EDSECUPPRGRATE (Female)

Data Updates

• 6 new tables of FIES by gender;
  • naming pattern is SeriesFoodInsecPop...FIES
• 1 new UN Women table;
  • SeriesGenderManagersFemaleShare

• 3 new tables of mean nominal monthly earnings;
  • SeriesLaborWageAvgMonthlyFemale, SeriesLaborWageAvgMonthlyMale, SeriesLaborWageAvgMonthly

• 6 new tables of pov and povgap from WDI, adjusted to 2017$ PPP (unvetted version)
• 16 new tables of marriage rates of women (unvetted version)
• 5 new tables of median age and pop by gender (unvetted version)
• 5 Tables inserted & updated
  • Rao GINI series updated, values for Montenegro are now available.

• 8 Tables deleted
  • 8 AoM tables with wrong naming conventions, e.g. "15-49"

• 16 DataDict changes
  • 16 AoM tables, aggregation rules changed to POP