Table 4: Selected variables in proposed formula and coefficient signs

The variables selected in the proposed model and their positive or negative contributions are reported in Table 4, whereas the full set of variables and coefficients of the proposed new model are reported in Annex B (Table B1.1).

Table 4: Selected variables in proposed formula and coefficient signs

Variables

Demographic variables

Income related Tbilisi

Dummies for household size (+, but nonlinear) Whether there are disabled members (-) Higher education by age (<32, 32–49, 50+) (+, nonlinear)

Income from hired employment (+), property (+), other income (+) Number of members working Individual hot water systema (+) Car/minibus/tru ck (+)

Large cities

Dummies for household size (+, but nonlinear) Higher education by age (<32, 32–49, 50+) (+, nonlinear) Income from hired employment (+), self-employment (+), other income (+) Electricity expenditure (+) Individual hot water systema (+) Other dwelling/summer house (+) Car/minibus/truc k (+) Satellitea (+)

Other urban

Dummies for household size (+, but nonlinear) HH members abroad (+) Higher education by age (<50, 50+)

(+, nonlinear) Income from hired employment (+), self-employment (+), agriculture (+), other income (+) No. of HH members working (+) HH members whose employer pay SI

Housing

Assets

contributions (+) Electricity expenditure (+) No. of rooms (+) Parquet floor (+) Individual hot water systema (+) Other dwelling/summer house (+)

Car/minibus/truck (+) Fridgea (+) Washing machinea

Villages

Dummies for household size (+, but nonlinear) Whether there are disabled members (-) Higher education (+)

Income from hired employment (+), selfemployment (+), agriculture (+), property (+), other income (+) No. of HH members working (+) HH members whose employer pay SI contributions (+)

Electricity expenditure (+) Individual heating systema (+) Individual hot water systema (+) Dwelling area (+)

Land area owned (+) Livestock index = cows + buffaloes + young cattle* +

Variables Tbilisi Large cities Other urban Villages

form. horsesa+ 0.1 (goatsa +sheepa +pigs) (+) Car/minibus/tru ck (+) Fridgea (+) Satellitea (+)

Geographical • Samegrelo/Zemo • Racha Lechkhumi • Guria (-) Svaneti (-) and Zvemo • Samegrelo/Zem Svaneti (-) o Svaneti (-) • Kakheti (-) • Racha Lechkhumi and Zvemo Svaneti (-) • MtskhetaSource: Authors’ analysis of HIES 2018 data. Note: HH = Household; SI = Social insurance. a. New variables for which there is no information in the declaration Mtianeti (-)

The choice of the final model was based on its performance and ability to predict the distribution of the ‘true welfare’ with a specific focus on the bottom deciles. The model’s robustness was further tested by assessing its ability to predict the welfare distribution in different groups (see Annex C) and by comparing its statistical fitness (measured by the R squared) to that observed in comparable contexts. The preferred model for the estimate of the PMT formula has R2 between 0.58 and 0.65 depending on the geographical subset of the sample that is used. This is a good performance compared to Albania (0.47), Bangladesh (0.57), 28 Mongolia (0.50 to 0.69 depending on the subsample used for the estimate), Sri Lanka (0.56), 29 and Pakistan (0.53). 30

The proposed model was estimated as follows:

��������(��������������������ℎ��������������������������������������������������������−��������������������������������������������������������������������������������)=��������+����,

where utilities expenditure includes electricity, natural gas, water supply, and cleaning services. Xstands for the different explanatory variables, β is the coefficient associated to each explanatory variable, and ɛ is the error term.

The estimated welfare indicator is the computed as follows:

�������������+ ����2 2 �+��������������������������������������������������������������������������������−������������������������������������������������ ,��������������������ℎ��������������������������������

where ����2 is the variance of the error term.

28 Sharif 2009. 29 Narayan, Viswanath, and Yoshida 2005. 30 Hou 2008.