xiaodong gong, natsem at university of canberra robert breunig, australian national university

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Estimating Net Child Care Price Elasticity Of Partnered Women With Preschool Children Using Discrete Structural Labour Supply-child Care Model Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University

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Estimating Net Child Care Price Elasticity Of Partnered Women With Preschool Children Using Discrete Structural Labour Supply-child Care Model. Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University. Purposes of the paper:. - PowerPoint PPT Presentation

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Page 1: Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University

Estimating Net Child Care Price Elasticity Of Partnered Women With Preschool Children

Using Discrete Structural Labour Supply-child Care Model

Xiaodong Gong, NATSEM at University of Canberra

Robert Breunig, Australian National University

Page 2: Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University

2

Purposes of the paper:

● To construct and estimate a joint discrete structural model of labour supply and child care demand with a quantity constraint;

● Using simulations, to estimate the labour supply and child care demand elasticities with respect to the gross and net child care costs;

● To get an idea whether and how labour supply and child care demand respond differently across demographic groups to the child care prices.

Page 3: Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University

3

Structure of the talk

● A joint discrete structural model of labour supply and child care demand;

● Data;

● Results;

- Model estimates;

- Elasticities obtained using simulations

● Conclusions.

Page 4: Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University

4

Figure 1. Difference between hours worked by mothers and child care hours of preschool children

0

200

400

600

800

1000

1200

-50 -40 -30 -20 -10 0 10 20 30 40 50 More

Difference in the hours of worked by the mother and the formal child care hours

Fre

qu

ency

Frequency

Page 5: Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University

5

Specification of the econometric model

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Page 6: Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University

6

Specification of the econometric model (2)● h and cf are assumed to be chosen from the following discret sets:

● An i.i.d. random disturbance μj (of Type I extreme value) is added to

the utility:

where 48 is the total number of the alternatives.

● Thus, conditional upon ε, X, and w, the probability that j is chosen is given by

(7) }60,...,20,10,0{ ,(6) }56,...,16,8,0{ fcandh

(8) )48,...,0( )( jvUU jjj

(9) ))(exp(

))(exp(] allfor [ 48

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ii

jij

vU

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Page 7: Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University

7

Specification of the econometric model (3)

. variablesexgoenous of vector a is )',...,(

(5) )3,2( ,

and matrices,parameter are )13( and )33( where

1

1

kT

kk

T

t

pkktktk

k

k

xxx

kxb

bA

Page 8: Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University

8

Specification of the econometric model (4)

● In addition, a wage equation:

● And an equation for fixed cost of working:

are jointly estimated with the model.

● The model is estimated using Simulated Maximum likelihood (with Halton draws).

(10) 'log wzw

(11) 'tFB

Page 9: Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University

9

Data

● Married women and their pre-school children drawn from the Waves 2005, 2006, and 2007 of the ‘in-confidence’ HILDA data

● Gross child care price are constructed using detailed information on the type and the usage of child care for each child, and the costs for each type of child care.

Page 10: Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University

10

Construction of gross child care prices

● Child Care benefit (CCB) is estimated from the observed hours and the net costs of each child care type, using the rules and the information on family taxable income, and family structure;

● The gross costs of each type are calculated by adding CCB back to the net costs and allocated to each child according to their usage;

● The gross child care price is calculated as the per hour gross costs of the formal care;

● The median gross child care price for each age group of children is calculated for each Labour Force Survey Region (LFSR) and is used for the analysis.

Page 11: Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University

11

Variables Mean (Std. dev.)

Hours worked per week by the working mothers 24.79 (13.7)

Average hours of formal child care 18.77 (12.9)

Proportion of families using care 0.43

Wage rate of the mother (at June 2005 price) $25.31 (22.5)

Unearned private income of the mother (including partners’

earnings, at June 2005 price)

$1237.86 (1242.0)

Mean median child care prices (at June 2005 price) 4.67 (0.9)

Mean age of preschool children 1.90 (1.4)

No. of preschool children 1.35 (0.6)

Table 1. Sample statistics of some key variables

Page 12: Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University

12

Estimation results: Table 3. coefficients of b’s of the utility'b s

2b 3b

Constant -0.854[-0.66] 2.952[1.55] Age of the mother 0.333**[2.20] 0.397**[2.90] The mother speaks a language other than English -0.925**[-2.67] 0.004[0.02] The mother is an Aboriginal and Torres islander -1.365[-1.33] 1.372[1.29] The mother was not born but educated in Australia 0.025[0.08] The mother was neither born nor educated in Australia -0.012[-0.03] Age of the youngest child 0.406**[5.62] 0.048[0.25] No. of children aged 0 to 4 0.857**[5.08] 0.331[1.44] No. of children aged 5 to 12 -0.184*[-1.76] 0.078[0.91] No. of children aged 13 to 15 0.248[1.17] -0.646**[-2.80] Presence of extra female adult 0.135[0.31] 0.468[1.05 ] Father received higher edu. -0.219[-0.78] -0.154[-0.68] Father received vocational edu. -0.038[-0.15] 0.027[0.13 ] Father did not finished Year 12 -0.176[-0.60] -0.126[-0.51] The mother and the father were not born but educated in Australia -0.006[-0.04] Neither the mother nor the father born or educated in Australia -0.458**[-2.00] Presence of children older than 12 0.172[1.45 ] Mean age of pre-school children -0.180[-0.92] % of child care staff w/t exp. (state avg.) -0.039**[-1.96] % of child care staff w/t qual. (state avg.) -0.009[-0.39] Dummy: working hours larger than formal childcare hours 0.113[1.54] Variance of the unobserved preference for leisure ( 2

p ) 0.014[0.05] 0.160**[3.62]

Cov. of the unobserved preference for leisure with wage (wp ) 0.038 [0.93] 0.149**[6.05]

Page 13: Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University

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Estimation results: Table 4. fixed costs of workingFixed benefit equation constant 1.168**[7.25] Age of the mother -0.207**[-5.17] The mother speaks a language other than English 0.230**[2.95] The mother is an Aboriginal and Torres islander -0.075[-0.44] The mother was not born but educated in Australia 0.051[0.84] The mother was neither born nor educated in Australia 0.148*[1.79] Age of the youngest child -0.081**[-4.79] No. of children aged 0 to 4 0.017[0.46] No. of children aged 5 to 12 0.101**[3.48] No. of children aged 13 to 15 0.280**[3.72] presence of extra female adult 0.003[0.03 ] Father received higher edu. -0.010[-0.16] Father received vocational edu. -0.043[-0.73] Father did not finished Year 12 0.076[1.09 ] Dummy, wave 6 0.026[0.72 ] Dummy, wave 7 0.058[1.56 ] Likelihood -3347.96 Obs. 2,023 t-values are in the brackets. * Significant at 10% level. ** Significant at 5% level.

Page 14: Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University

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Elasticity estimates

Table 5. Estimated elasticities for the whole sample

Labour supply elasticity Child care demand elasticity With respect to Hours employment Hours of formal care Use of formal care

Gross child care price -0.106** (0.03) -0.070** (0.02) -0.294** (0.05) -0.166** (0.03) Net child care price -0.096** (0.03) -0.059** (0.01) -0.246** (0.04) -0.132** (0.02) Wage 0.427** (0.08) 0.274** (0.05) 0.281** (0.06) 0.176** (0.03) Income -0.092* (0.05) -0.048 (0.04) -0.036 (0.04) -0.036* (0.02)

Standard errors are in the parentheses. ** Significant at 5 % level. * Significant at 10% level.

Page 15: Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University

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Elasticity estimates (2): Table 6. Gross price elasticities for sub-samples

Labour supply elasticity Child care demand elasticity With respect to Hours employment Hours of formal

care Use of formal

care Gross child care price of preschool children By mother’s education With tertiary education Without tertiary education

-0.094**(0.03) -0.125**(0.04)

-0.061**(0.01) -0.083**(0.02)

-0.283**(0.04) -0.310**(0.05)

-0.161**(0.03) -0.174**(0.03)

By father’s education With tertiary education Without tertiary education

-0.095** (0.03) -0.132** (0.04)

-0.062** (0.01) -0.089** (0.02)

-0.279** (0.04) -0.328** (0.05)

-0.158** (0.03) -0.185** (0.03)

By number of children One pre-school child Multiple pre-school children

-0.079** (0.02) -0.158** (0.05)

-0.052** (0.01) -0.105** (0.03)

-0.225** (0.03) -0.427** (0.07)

-0.130** (0.02) -0.236** (0.04)

By mother’s non-labour income

Above median Below median

-0.077**(0.02) -0.136**(0.04)

-0.050**(0.01) -0.090**(0.02)

-0.236**(0.04) -0.353**(0.05)

-0.138**(0.02) -0.194**(0.03)

Page 16: Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University

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Elasticity estimates (3): Table 7. Net price elasticities for sub-samples

Labour supply elasticity Child care demand elasticity With respect to Hours employment Hours of formal

care Use of formal

care Net child care price By mother’s education With tertiary education Without tertiary education

-0.088** (0.02) -0.106** (0.03)

-0.054** (0.01) -0.066** (0.02)

-0.243** (0.04) -0.250** (0.04)

-0.130** (0.02) -0.133** (0.02)

By father’s education With tertiary education Without tertiary education

-0.089** (0.02) -0.110** (0.03)

-0.054** (0.01) -0.071** (0.02)

-0.240** (0.04) -0.260** (0.04)

-0.128** (0.02) -0.139** (0.02)

By number of children One pre-school child Multiple pre-school children

-0.077** (0.02) -0.131** (0.04)

-0.047** (0.01) -0.082** (0.02)

-0.206** (0.03) -0.332** (0.05)

-0.112** (0.02) -0.169** (0.03)

By mother’s non-labour income

Above median Below median

-0.080**(0.02) -0.109**(0.03)

-0.051**(0.01) -0.073**(0.02)

-0.242**(0.05) -0.353**(0.05)

-0.143**(0.03) -0.194**(0.03)

Page 17: Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University

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Conclusions

● We constructed and estimated a discrete structural model of labour supply and child care demand for partnered women with preschool children;

● Using simulations, we find statistically significant gross and net child care price elasticities of labour supply for partnered women with young children. In particular the net child care price elasticity of hours of work and employment are about -0.10 and 0.06, respectively. This again confirms that labour supply of married women is responsive to child care costs;

● The extent of the labour supply response to child care prices varies across demographic groups. Labour supply and child care demand responses to child care price changes are highest amongst women with lower education, lower household income, and more children.

Page 18: Xiaodong Gong, NATSEM at University of Canberra Robert Breunig, Australian National University

www.natsem.canberra.edu.au