A first estimate of LCD by gender (Uruguay)

Marisa BucheliCecilia González

dECON, FCS, Udelar

• In Uruguay we are doing NTA by SES

• We have estimations of labor income, consumption, LCD and public transfers

• We have preliminary estimations of RA and private transfers

• We recently began to think of doing estimations by gender

• We have not worked on unpaid activities

NTA by SES groups

• To my best knowledge, in the Latin American team we used (at least at the beginning) different procedures for estimation

• In our case, we have estimations basead on two differente procedures (the one we used at the beginning and the proposed late by CELADE)

• But we have not compared the sensitivity of the results to the procedures

First procedure

• We estimate the profiles (mean and smooth mean) as usual but for each SES group separately

• Note that all members of the hh belong to the same group so the only challenge is define groups with a “good” size in all ages

• We estimate the aggregated value (AV) of each group (g) and age (a), where P is the population and XS is the smooth microdata value:

• The Total AV is the sum of the Total AV of groups

First procedure

• In order to calculate the formula, we need to know the population of each age-group

• We estimate it using its proportion in the survey

• Note: in the definition of the classification, we took into account (¿?) the size of the age-group population in the survey

Second procedure

• We estimate the total AV of each group using the weight of the group in the microdata

• We estimate the total AV of the age-group using the weight of the age-group in the microdata (X is the mean value in the microdata):

• We estimate the mean value as AV of the age-group / Population in the age-group

• In the analysis of the data we work with five-year-age group

Up to now…

• We have a complete NTA estimation (though a preliminary version particularly of private transfers and RA) following the first procedure (using the “educational level of the hh adults” as the proxy of SES)

• Many challenges: 1) ¿inter-hh transfers?; 2) public RA; ….

• We have estimations of labor income, consumption and public transfers following the second procedure (using the “educational level of the hh head 2” as the proxy of SES)

NTA by gender

• Our first idea was to follow the first procedure to estimate NTA by gender

• Two differences:

• In the gender classification we know the population of each age-group. We used it

• In the SES classification, all the members of a hh belong to the same group. In the classification by sex, it is possible that members of the same hh belong to a different group

• This issue is not important in the estimation of accounts for which we have individual information in the surveys: labor income, some components of private consumption, public inflows and some public outflows

0,E+00

5,E+04

1,E+05

2,E+05

2,E+05

3,E+05

3,E+05

4,E+05

0 3 6 9 121518212427303336394245485154576063666972757881848790

Labor income (smooth mean)

women

men

0,E+00

1,E+06

2,E+06

3,E+06

4,E+06

5,E+06

6,E+06

7,E+06

0 3 6 9 121518212427303336394245485154576063666972757881848790

Labor income (aggregate value)

women

men

0,E+00

5,E+03

1,E+04

2,E+04

2,E+04

3,E+04

3,E+04

4,E+04

0 3 6 9 121518212427303336394245485154576063666972757881848790

Public consumption (smooth mean)

women

men

0,E+00

1,E+05

2,E+05

3,E+05

4,E+05

5,E+05

6,E+05

7,E+05

8,E+05

9,E+05

1,E+06

0 3 6 9 121518212427303336394245485154576063666972757881848790

Public consumption (aggregate value)

women

men

0

2.000

4.000

6.000

8.000

10.000

12.000

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89

Public health (smooth mean)

women

men

0,E+00

5,E+03

1,E+04

2,E+04

2,E+04

3,E+04

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34

Public education (smooth mean)

women

men

But if the information is given at household-level …

• Private education: we follow exactly the same procedure than in NTA:

– In the survey, we identify the students (and their level of education) that attend private school. We assign to each one the amount of the tuitions paid by the hh.

– In the case other spending (books, courses of language, computation, etc.) we use the method proposed by NTA

• We classify the persons by age and sex in order to calculate mean and smooth mean values

0

5.000

10.000

15.000

20.000

25.000

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35

Private education (smooth mean)

women

men

0

5.000

10.000

15.000

20.000

25.000

30.000

35.000

40.000

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35

Education (smooth mean)

women

men

The difference is due to spending not related to attendance (apparently, to “enseñanza no curricular” -language, computation, special teachers, etc.-)

¿Is it the method? ¿Should we take into account the sex-composition of the hh when we have to assign spending informed at hh level?

But if the information is given at household-level …

• This is the case of most of the private consumption and indirect taxes

But if the information is given at household-level …

• Private health: we follow exactly the same procedure than in NTA:

– In the survey, we identify the persons who were ill. We assign to each one the amount of the spending related to be ill.

– In the case other spending we use the method proposed by NTA

• We classify the persons by age and sex in order to calculate mean and smooth mean values

0

5.000

10.000

15.000

20.000

25.000

30.000

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89

Private health (smooth mean)

women

men

0

5.000

10.000

15.000

20.000

25.000

30.000

35.000

40.000

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89

Health (smooth mean)

women

men

We do not know which components explain the increasing gap

We should explore if it is due to a component assigned to an individual through an indirect method (not an ill-related component)

But if the information is given at household-level …

• Rest of private consumption: we follow exactly the same procedure than in NTA:

– We used an equivalence scale to calculate the rest of private consumption per hh member

– We assigned to each individual of the hh the same amount

• We classify the persons by age and sex in order to calculate mean and smooth mean values

0100002000030000400005000060000700008000090000

100000

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89

Rest of private consumption (smooth mean)

women

men

0

20.000

40.000

60.000

80.000

100.000

120.000

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89

Private consumption (smooth mean)

women

men

0,E+00

2,E+04

4,E+04

6,E+04

8,E+04

1,E+05

1,E+05

1,E+05

0 3 6 9 121518212427303336394245485154576063666972757881848790

Consumption (smooth mean)

women

men

0,E+00

5,E+05

1,E+06

2,E+06

2,E+06

3,E+06

3,E+06

0 3 6 9 121518212427303336394245485154576063666972757881848790

Consumption (aggregate value)

women

men

-3,E+05

-2,E+05

-2,E+05

-1,E+05

-5,E+04

0,E+00

5,E+04

1,E+05

2,E+05

0 3 6 9 121518212427303336394245485154576063666972757881848790

LCD (smooth)

women

men

-5,E+06

-4,E+06

-3,E+06

-2,E+06

-1,E+06

0,E+00

1,E+06

2,E+06

3,E+06

4,E+06

0 3 6 9 121518212427303336394245485154576063666972757881848790

LCD (aggregate value)

women

men

Some questions

• We would like to know more about the gender difference in the private health and private education.

• Are they sensitive to the method of allocation of spending informed at household level?

• If there is a gender difference in private / health education, should we use the traditional method of imputation of the rest of private consumption?

• Another challenge: private transfers

Unpaid work

• We have not worked in this issue in the last year

• In the past, we performed some estimations of the value of unpaid activities in which we imputed a wage to unpaid work: – Results quite sensitive to use the opportunity cost criteria or

replacement criteria– Also sensitive to consider specialist / non-specialist wage in the

replacement criteria

• There is a new survey (2009) but we had not worked with it yet