RDP 2009-07: Estimating Marginal Propensities to Consume in Australia Using Micro Data 2. Related Literature

Most estimates of the MPC are by-products of tests of the excess sensitivity of consumption to changes in predictable income, in other words of tests of the permanent income hypothesis (PIH). Historically, these tests were conducted using the time-series properties of the consumption Euler equation (as in Hall 1982, and in the Australian context in McKibbin and Richards 1988). However, there are difficulties in estimating the causal effect of a change in income on consumption, in part reflecting the difficulty distinguishing between income changes and other macroeconomic factors. This has led to a greater focus on the use of micro data to both test the PIH and estimate MPCs. Micro data has also allowed analysis of heterogeneity in households' responses, particularly in response to liquidity constraints.

A series of recent studies use the detailed data available in the US Consumer Expenditure Survey (CEX) in order to estimate the effect on consumption of predicted changes in income (see, for example, Souleles 2002 and Johnson et al 2006). The CEX is well suited to such a task; the survey contains comprehensive expenditure data, it is conducted monthly and, although households move in and out of the survey, they are interviewed every three months for up to a year. These studies focus on the effect of anticipated fiscal policies on expenditure at the time when households receive additional income. Souleles (2002) examines the effect of the Reagan tax cuts in the United States in the early 1980s and finds that household expenditure increased in the quarter after taxes were actually cut even though these tax cuts had been pre-announced, with an MPC of between 0.6 and 0.9. Johnson et al (2006) exploit the random timing of the distribution of the 2001 tax rebates and find that households, on average, had an MPC of 0.2 to 0.4 out of the rebate income. The authors also find an important role for liquidity constraints; households with low income or low assets spent a significantly greater share of their rebates.

While each of the above studies formally reject the PIH, the results are consistent with consumers treating temporary and permanent shocks differently: consuming more out of permanent than out of transitory changes. These studies also shed light on how different income changes affect different types of expenditure. Souleles (1999) finds that lump-sum increases in income are largely spent on durable purchases, while Parker (1999) shows that a large share of (permanent) changes in net pay received continuously is spent on non-durables.

Using a noticeably different data source (which complicates a direct comparison of the results to those of the US studies), this paper applies some of these same techniques to the Australian context. We examine the effect of both tax cuts and specific lump-sum transfers – the Baby Bonus and the Carer Bonus – on consumption, and explore the role of liquidity and financial constraints.[1] In order to provide some insights into how MPCs might potentially change across the economic cycle, we also explore how differences in perceptions of risks to income across households affect MPCs.


With the exception of Johnson et al (2006), which relies on the random timing of the delivery of the tax rebates, all of the above studies assume that the income change is uncorrelated with unobserved determinants of consumption. While this may be a reasonable assumption when the fiscal policies affect a broad cross-section of the population, it is less likely to hold when fiscal policies are targeted towards specific groups in the population, since it will be difficult to distinguish between the effect of the unobserved characteristics of these groups on consumption and the effect of fiscal policies. Hence, for the Carer Bonus we use propensity score matching (see, for example, Brzozowski 2007) to identify a control group that did not receive the payment but otherwise had similar characteristics. [1]