RDP 2009-07: Estimating Marginal Propensities to Consume in Australia Using Micro Data 6. The Response of Expenditure to Lump-sum Payments

The MPC for the Baby Bonus is estimated using Equation (2) and the results are shown in Tables 5 and 6.[25] As before, we report the results for both fixed effects and first differences. However, unlike with the tax cuts, we estimate a variant of the model without time effects because they are highly correlated with the policy variable. The coefficient on the amount of the Baby Bonus provides an estimate of the MPC.

Table 5: Non-durable Expenditure (in $100) – Baby Bonus Regressions
Fixed effects First differences
Bonus size ($100) 0.30 0.70***   0.29* 0.53***
Wave 5 dummy −59.50***   −59.33***
Wave 6 dummy −22.50***   −23.88***
First child 3.68 11.25   8.29 13.66
No of adults 30.76** 45.53***   30.50* 42.72**
House value ($10,000) 0.30 0.72***   0.27 0.54**
R2-within 0.31 0.13  
R2-between 0.27 0.28  
R2-adjusted   0.21 0.10
Notes: ***, ** and * denote statistical significance at the 1, 5 and 10 per cent levels respectively. There are 470 observations (161 households) in the fixed-effect specification and 310 observations in the first-differences equation.
Table 6: Strictly Non-durable Expenditure (in $100) – Baby Bonus Regressions
Fixed effects First differences
Bonus size ($100) 0.25 0.54***   0.23 0.42***
Wave 5 dummy −40.50***   −41.55***
Wave 6 dummy −13.94**   −14.94**
First child 3.20 8.83   5.21 9.83
No of adults 25.68* 35.75**   27.11* 35.83**
House value ($10,000) 0.27 0.54***   0.18 0.36*
R2-within 0.24 0.11  
R2-between 0.29 0.29  
R2-adjusted   0.15 0.07
Notes: ***, ** and * denote statistical significance at the 1, 5 and 10 per cent levels respectively. There are 472 observations (161 households) in the fixed-effect specification and 311 observations in the first-differences equation. Expenditure excludes education, clothing and footwear, and motor vehicle repairs and maintenance.

We find that the estimates of the MPC out of the Baby Bonus for non-durable expenditure range from around 0.3 to 0.7, while the MPC for strictly non-durable expenditure is slightly lower, ranging from 0.2 to 0.5. The estimated MPCs on both non-durable and strictly non-durable expenditure rise noticeably when the time variables are excluded from the regression (Models (II) and (IV)). While ideally we would want to control for the time variation, the coefficients on both of the time dummies are implausibly large, implying that expenditure grows by up to 12.5 per cent per year. The difficulty is that with little variation in bonus payments, the time variables are highly correlated with the size of the bonus received and whether or not the household had a baby that year. It is likely that these large coefficients are picking up some of the Baby Bonus effect and the effect of having a baby. However, not accounting for time variables is likely to overstate the effect of the bonus payment on consumption. This suggests that the true effect lies somewhere between the range of estimates shown.

The range of estimated MPCs for the lump-sum Baby Bonus payment is lower than that for the tax cuts. There are two possible explanations for this. First, since the Baby Bonus amounts were announced prior to the beginning of our sample, there may have been more of an expectation that households would receive the bonus than there was for the tax cuts, even accounting for the uncertainties surrounding conception or adoption. The expectation of the bonus would have allowed some households to adjust expenditure prior to actually receiving it, lessening the increase in expenditure on receipt. Second, compared with the tax cuts, the bonus payments were more likely to have been perceived by the households as temporary. According to the PIH, non-liquidity-constrained households would thus have smoothed consumption over time, lowering the estimated MPC for more temporary payments. However, direct comparisons between tax cuts and lump-sum transfers are difficult since a lump-sum transfer is unlikely to be spent evenly across a year, so the reported expenditure of the household at the time it is surveyed may not be a good estimate of the annual average expenditure of the household (on average, seven months pass between when households are assumed to receive the bonus and the survey date). Tax cuts, in contrast, are received continuously, so their effect should be more evenly distributed.

Caution should be exercised in interpreting the Baby Bonus MPCs as an indication of the MPC out of all lump-sum transfers. There are two main reasons for this. First, and probably more importantly, the Baby Bonus is received during a time of large personal and financial adjustment for a household, including expenditure on many new consumption goods and services (particularly if it is a household's first child). In such an environment, a household might spend more out of a lump-sum transfer than usual. Second, we found it very difficult to control for the separate effects of having a baby and receiving the bonus, given that we had to assume that these events coincided. While variation in the magnitude of the Baby Bonus itself separates these effects, the Baby Bonus and new baby variable are highly correlated. Hence no baby born variable was included in the regression. In short, combined with the multicollinearity problem of the time variables, there is considerable uncertainty surrounding the estimates of the MPC out of the Baby Bonus, with estimates ranging between 0.25 and 0.7 for non-durable expenditure.

Unfortunately the Carer Bonus results are not reliable. This is because it is very difficult to find appropriate matches for carer households – the selection equations tend not to meet the balancing property across all three years.[26] In addition, the estimates are very sensitive to the variables included in the selection equation, implying that small changes in specification lead to quite different matches. As summarised in Table 7, these problems lead to varied and statistically insignificant estimates of the MPCs across the three years and across the different expenditure classifications.

Table 7: MPC Out of the Carer Bonus
Bonus Non-durable Strictly non-durable No of carers/Non-carers(a)
Carer Bonus 2005 −0.01 −0.29 117/4492
Carer Bonus 2006 0.49 0.52 130/4675
Carer Bonus 2007 0.10 −0.29 140/4680
Notes: ***, ** and * denote statistical significance at the 1, 5 and 10 per cent levels respectively.
(a) These are the pre-matched sample sizes. After the matching, the number of non-carers in the control group is the same as the number of carers.


Heteroskedacity does not appear to be a problem in this specification. We do not correct for it because the sample size is small. [25]

The balancing property is satisfied when there is no statistically significant difference between the mean of the estimated propensity score in both groups, Carer Bonus recipients and non-recipients. [26]