RDP 2009-07: Estimating Marginal Propensities to Consume in Australia Using Micro Data 3. Data

3.1 The HILDA Survey

The HILDA Survey, which is conducted annually, collects income, expenditure and other demographic information about a panel of Australian households. While the first wave was gathered in 2001/02, comprehensive expenditure data are currently only available for Waves 5–7. Thus our sample starts in the 2005/06 financial year (Wave 5) and ends in the 2007/08 financial year (Wave 7). The balanced panel for Waves 5–7 consists of 6,392 households and 10,023 individuals. The vast majority of the households (90 per cent) are surveyed between August and October, while the remaining 10 per cent are surveyed before March of the following year.

Following other studies (such as Johnson et al 2006) we focus on non-durable expenditure (for a precise definition see below). Provided consumption of non-durables and durables are additively separable in the utility function, this will provide an accurate measure of the MPC on non-durables. We examine two classifications of non-durable expenditure.^[2] The first is a broad measure, which we call ‘non-durables’ (see Table A1). The second measure, ‘strictly non-durable’ expenditure, excludes the semi-durable categories of clothing and footwear, education, and motor vehicle repairs and maintenance following Lusardi (1996) (Column (I) of Table A1).

The HILDA expenditure data are collected using a self-completion recall survey. HILDA respondents are asked ‘on average how much do you usually spend on’ various expenditure categories, with the reference period varying from one week to a whole year depending on the expenditure category. In general, the expenditure categories that are more non-durable in nature have a reference period of one week, with the reference period increasing the more durable the good or service. These estimates are then converted into an annual estimate of expenditure for each category. The nature of the expenditure questions are thus substantially different to those in other expenditure surveys, most notably the CEX, where actual expenditures are recorded. This difference makes our results a little more difficult to interpret, and makes it hard to compare our results directly to others in the literature. By asking about ‘usual’ rather than actual expenditure over a given period, households may be more likely to omit spending out of temporary transfers or more recent spending from their responses. By itself, this is likely to lead to an underestimate of the true effect of temporary transfers on consumption.

The frequency of the HILDA Survey also has important implications for the interpretation of our results. The annual frequency of the survey makes it almost impossible for our tax cut results to be interpreted as a test of the permanent income hypothesis. Other studies test the PIH by examining whether consumption responds to predicted changes in income. For example, Johnson et al (2006) and Souleles (2002) use data that capture the increase in consumption at the time of the actual increase in current income (and so can be used to test the PIH which predicts no change in consumption at the time, in the absence of liquidity constraints). However, the tax cuts we examine are announced and implemented between surveys, which implies that our estimates of the MPC are capturing the full effect of a policy change on consumption. In contrast, the Baby Bonus changes are announced prior to the beginning of our sample period. We thus only capture the response of consumption to an actual change in current income, enabling the Baby Bonus estimation to be used as a test of the PIH.

Each year, the HILDA Survey collects two different types of income data for each individual, in both gross and net terms. These are substantially different in terms of their scope and timing. The first type is a comprehensive measure of income received over the previous financial year. The second type is more limited in scope and is intended to measure current income as at the time of the survey (although the exact reference period is chosen by the respondents). We use previous financial year income (that is, for example, the 2006/07 financial year income collected in interviews conducted during 2007/08) to estimate the size of tax reductions. This more comprehensive measure is likely to be a better measure of annual income.^[3] The financial year income is the sum of wages and salaries, government transfers, and investment and business income. Figure 1 shows the periods when the HILDA Surveys were conducted and the financial year income available from each wave.

3.2 Income Tax Changes

Between 2005/06 and 2007/08, the Federal Government introduced changes to the personal income tax scale, lifting selected income thresholds and lowering marginal tax rates. The majority of the tax cuts in our sample were announced in May of the year they were introduced.^[4] However, given the recent history of tax cuts and the economic environment at the time, it is possible that some form of tax cuts were anticipated prior to their announcement. The changes were part of a run of consecutive tax cuts from 2003/04 to 2009/10 following fiscal surpluses from 2002/03 to 2007/08 and the retirement of Federal Government debt (net public debt was around zero in 2006). These economic factors are likely to have created an expectation that the tax changes were persistent, if not permanent.^[5] The tax rates relevant to our sample period are shown in Table 1 with the changes marked in bold.

Table 1: Personal Income Tax Scale

	Income range Dollars	Marginal tax rate
2004/05	0–6,000	0.00
	6,001–21,600	0.17
	21,601–58,000	0.30
	58,001–70,000	0.42
	70,001 and over	0.47
2005/06	0–6,000	0.00
	6,001–21,600	0.15
	21,601–63,000	0.30
	63,001–95,000	0.42
	95,001 and over	0.47
2006/07	0–6,000	0.00
	6,001–25,000	0.15
	25,001–75,000	0.30
	75,001–150,000	0.40
	150,001 and over	0.45
2007/08	0–6,000	0.00
	6,001–30,000	0.15
	30,001–75,000	0.30
	75,001–150,000	0.40
	150,001 and over	0.45
Source: Australian Taxation Office

We estimate the change in the amount of tax paid by applying the change in the tax rate to the amount of gross income the household was earning in the previous financial year. We use this measure for two reasons. First, we want to get a pure measure of the effect of the tax cuts, abstracting from any changes in household labour supply (which itself might respond to the tax changes). Second, the timing of the tax cuts relative to the survey (the tax year begins on the 1st of July while the survey is largely conducted between August and October) makes it difficult to determine which annual income measure is the most appropriate. Figure 2 illustrates a timeline of the data available in Wave 6 to assess the impact of the new tax rates coming into effect on 1 July 2006. Although information about income as reported at the time of the survey is available, as already mentioned it tends to be a poor proxy for financial year income.^[6] Instead, we assume that the annual income of the previous financial year is a good approximation of the income households perceive as usual at the time that the survey is conducted, which for most households is around three months after the end of the financial year.

The amount of the tax change is calculated for each individual, then aggregated on a household basis. These changes across time can then be used to create a measure of the level of tax paid for the regression analysis described in Section 4.1 below.

While most households are estimated to have received some tax cuts (according to our approach), the amount varies across the years and across different income groups. At the household level, the average estimated size of the tax cuts (again, according to our specific approach) across the three sample years were $731, $1,543 and $956, respectively.^[7] This represents around 1 to 3 per cent of average household disposable income. Figures 3, 4 and 5 show the distributions of the tax cuts in each financial year at the household level. The tax reduction was the largest and most dispersed in 2006/07.

3.3 Lump-sum Transfers

We examine the MPC out of two lump-sum transfers: the Baby Bonus and the Carer Bonus. These transfers were introduced in 2004 and covered small subsets of the population based on strict qualifying criteria.

The Baby Bonus was introduced in the 2004 Australian Federal Budget. It was a non-means-tested lump-sum payment, initially of $3,000 designed to assist with the costs of having a child. The primary carer of a newborn baby, adopted child under the age of two, or mother of a stillborn baby could make a claim for the bonus within 26 weeks of birth or adoption.^[8]

In 2004, the basic rates of payment were announced for the next four years. There were two increases of $1,000 that were announced for 1 July 2006 and 1 July 2008. In addition, it was announced that the payment would be indexed to CPI inflation with increases being made biannually in March and September. Table 2 shows the rates of payments from 2005/06 to 2007/08 and the number of households in the survey that had a baby when each rate applied. While the pre-announcement of the policy enables the Baby Bonus to be used as a test of the PIH (abstracting from uncertainty associated with the CPI adjustment), this also creates a potential source of bias. With the policy changes announced so far in advance, some families may have delayed conception in response to the increase in the bonus.^[9] Alternatively, when the birth date can be chosen (for example, through elective caesarean), some families might delay the birth of their child to qualify for the higher payment. The unobserved characteristics of the households that delayed conception or birth would thus be correlated with the transfer received, leading to inconsistent estimates of the MPC. In their study on the effect of the introduction of the Baby Bonus in 2004 and the increase in 2006, Gans and Leigh (2009) do not find evidence of households delaying conception as a result of the transfer, but find strong evidence of delays in elective birth procedures. While this is an important caveat to our results, we estimate that it would affect at most 1 per cent of our sample and thus we abstract from the issue.^[10]

Table 2: Baby Bonus Rates and Recipients in HILDA

Date rate applies	Amount	No of households
20/03/2005	$3,079	63
20/09/2005	$3,119	89
20/03/2006	$3,166	71
01/07/2006	$4,000	46
20/09/2006	$4,100	85
20/03/2007	$4,133	124
20/09/2007	$4,187	–
20/03/2008	$4,258	–
Notes: Wave 7 was collected towards the end of 2007, thus data on births for the last two transfer rates will be available in Wave 8, which has not been released yet. Sources: FaHCSIA (2008); HILDA Release 7.0 (in-confidence version)

Unfortunately, the HILDA Survey does not ask whether a household received the Baby Bonus and, if it did, when the payment was received. Given that a household can receive the bonus up to 26 weeks after the birth or adoption of a child, those households in our sample that are interviewed less than 26 weeks after the birth of the baby may not have received their payment at the time of interview. However, given the size of bonus and the substantial cost of having a baby, we assume that all households that qualified for the bonus received it and that they either claimed the bonus immediately or were liquid enough to be able to adjust their expenditure with the knowledge that they would receive the bonus. When examining the role of liquidity constraints on the MPC out of the Baby Bonus, this will be an important caveat to the results.

We use the July 2006 change in the Baby Bonus to estimate the MPC. The 106 households who received the bonus nine months prior to this change are compared to the 55 households who received it in the subsequent nine months. Due to the incremental adjustments to account for inflation, the average difference in the size of the bonus the two groups received was $922.

To complement the estimates of the MPC out of the Baby Bonus we also analyse the MPC out of the Carer Bonus. This was a one-off lump-sum payment made to persons eligible for the Carer Payment or the Carer Allowance.^[11] These transfers are made to people who provide unpaid care for a person in a private residence who has a disability, severe medical condition or is frail due to age.^[12] The Carer Allowance is a universal payment, while the Carer Payment is an additional means-tested pension for people whose workforce participation is limited due to caring responsibilities. Someone can receive a larger Carer Allowance if they are caring for more than one person; a claim can be made for the care of up to two adults and for an unlimited number of children. The bonuses were announced each year in the Federal Budget in May and were distributed within one month of announcement. This was done each year from 2004 to 2007. Like the Baby Bonus, the HILDA Survey does not directly ask people whether or not they received the Carer Bonus. We infer households' transfers based on the broader category of the amount of the Carer Payment and Carer Allowance they received each year. Because recipients of the Carer Allowance can receive many bonuses, we exclude households from the sample where the amount of allowance reported is inconsistent with the amount they would have received if they were caring for either one or two people.

Table 3 shows the schedule of transfers and the number of recipients in our sample. In all three years, people eligible for the Carer Payment received a bonus of $1,000. Those eligible for the Carer Allowance were given $600 for each person that qualified them for the transfer. Those who were eligible for both received a minimum of $1,600. In 2006 and 2007, persons who received the Carer Allowance and the Wife Pension or the Department of Veterans' Affairs Partner Service Pension were eligible for an additional $1,000, making their total transfer at least $1,600. As discussed below, we estimate the MPC out of the Carer Bonus by comparing expenditure of those that received this bonus with expenditure of households which are otherwise similar, but did not receive the Carer Bonus.

Footnotes

There are 14 broad non-durable expenditure categories available in the HILDA Survey across all three waves (for details see Table A1). A similar set of non-durable categories represent around half of the value of total household consumption in the national accounts. [2]

Current income measures (for example, 2006/07 income collected in Wave 6) tend to be a poor proxy for the financial year income of that same year reported in the following year's survey (for 2006/07 financial year income collected in 2007/08). [3]

The changes to the income thresholds in 2005/06, however, were announced in the year prior. [4]

The fiscal surpluses partly reflected the high terms of trade during this period. If this was a temporary phenomenon, then fully rational households would have expected that the tax cuts were also temporary. However, we think that expectations of persistent or permanent tax cuts are probably realistic at the individual household level on average given the uncertainty around the shift in the terms of trade. [5]

HILDA provides an estimate of the amount of tax paid over the new financial year using income earned as reported at the time of the survey. However, as discussed, this is not a reliable measure of income. [6]

This approach overstates the share of the population that actually pays tax because we are unable to take into account various deductions and tax offsets. These estimates are broadly consistent with, although somewhat higher than, the averages implied by the estimated cost to government revenue, provided in the annual budget papers (Australian Government 2005, 2006 and 2007). HILDA attempts to take these various factors into consideration in its measure of tax. Our results are robust to limiting the sample to households for which HILDA imputes a positive amount of tax paid. [7]

The payment could be split between multiple people if they could all make a substantiated claim to be the child's primary carer for the first 13 weeks. [8]

They may also have increased consumption prior to having the baby in anticipation of the Baby Bonus. In addition, if some households adjusted their expenditure according to expectations of having a baby and these were unrealised, then our estimated coefficient would underestimate the aggregate effect of the policy on consumption [9]

Gans and Leigh estimate that around 4 per cent of births were delayed from June to July in 2006, because of the increase in the Baby Bonus. We use this estimate to infer the number of households with a baby born in July 2006 who may have delayed birth. [10]

Where there are multiple people who provide care to the same person, the payment is apportioned between them. [11]

See Centrelink <www.centrelink.gov.au> for further details on welfare eligibility. [12]