RDP 2016-10: The Effect of Consumer Sentiment on Consumption 3. Data

We study the effect of consumer sentiment on consumption using individual- and postcode-level consumption data. On an individual level, we match reported spending intentions to reported economic beliefs. Our study is novel because it also uses actual spending data at a postcode level, the most disaggregated level at which an annual or higher frequency consumption proxy is available. We measure consumption using the number of new motor vehicle purchases in a postcode. In particular, we match the share of votes for each of the major parties by postcode with postcode-level motor vehicle purchase data to see if postcodes with a greater fraction of voters for the incoming government purchased relatively more motor vehicles.

3.1 Individual-level Data

We proxy consumption at the individual level using spending intentions data from the consumer sentiment survey. In particular, we use the response to the question on whether it is a good time to purchase a major household item. Responses are classified as positive, unchanged/don't know, or negative. Using other questions in the survey, we can match an individual's stated spending intentions to their sentiment, political preferences and a range of economic and demographic characteristics. The data are available on a monthly basis and span the changes in government in March 1996, November 2007 and September 2013.

3.2 Postcode-level Data

3.2.1 Vote shares

Australia has a parliamentary political system, with either the ALP or the Liberal/National party holding government since World War II. Voting is compulsory, with failure to vote resulting in a fine. This has ensured turnout rates of at least 93 per cent at each election in the post-War period. This is important because it minimises the possibility of mismeasurement of local-area partisanship, which would arise with voluntary voting if those who choose to vote have different political preferences from those who do not vote. By contrast, turnout in the United States has varied between 49 and 63 per cent since 1960.[4]

We measure partisanship at the postcode level as the share of votes going to the ALP in a federal election using the Australian Electoral Commission's two-party preferred measure.[5] There are currently 150 federal electorates (equivalent to US Congressional districts) in Australia, with electorate boundaries set by an independent non-partisan commission. Voting occurs at more than 8,000 polling places. We aggregate these polling place results to the 2,738 postcodes in Australia.

Political opinion polling data indicate that a change of government for the two elections in our sample could have been anticipated in advance of the election (Figure 6). Despite this, consumer sentiment moves precisely when the government changes hands, rather than in advance based on polling data.[6] One possible explanation is that a majority of voters do not pay attention to polling data. Reinforcing this, in a Newspoll survey conducted between just four and six days prior to the 2007 Federal election, 45 per cent of Liberal/National supporters said they believed their party would win the election, despite polling evidence to the contrary and widespread media coverage of opinion polls leading up to the election.

Figure 6: Political Opinion Polling
Newspoll survey
Figure 6: Political Opinion Polling

Notes: Shows ALP and LNP two-party preferred vote shares from the generally fortnightly Newspoll survey; dots indicate actual vote shares at the November 2007, September 2010 and September 2013 Federal elections; vertical lines show dates when government changed hands

Source: Newspoll

3.2.2 Consumption

We use the number of motor vehicle sales as our postcode-level consumption measure. We think that motor vehicle purchases are a good metric of consumption because it represents an important spending decision for households. Between 1995 and 2013, the consumer sentiment survey included a question asking whether it is a good time to buy a motor vehicle. Using the methodology outlined in Section 2.3, we construct the difference in responses between ALP and Liberal/National voters to this question conditional on an individual's economic and demographic characteristics. There is a very close relationship between attitudes toward buying a motor vehicle and self-reported spending intentions for a major household item, indicating that motor vehicle sales is a good measure of consumption to map to sentiment (Figure 7).

Figure 7: Spending Intentions – Good Time to Buy a Motor Vehicle
Conditional, ALP minus Liberal/National voters
Figure 7: Spending Intentions – Good Time to Buy a Motor Vehicle

Notes: Shows the effect of changes of government on spending intentions for motor vehicles; index is constructed from individual response data and conditions on respondents' economic and demographic characteristics (see notes to Figure 5); consumers asked whether now is a good time to buy a motor vehicle and responses are either good, neutral, or bad; the motor vehicles question was asked on a quarterly basis from 1995–2006, then monthly until January 2014, when it was discontinued; we show the index on a quarterly basis, together with the analogous index of spending intentions on a major household item

Sources: Authors' calculations; Westpac and Melbourne Institute

Motor vehicle sales data are sourced from VFACTS. These are administrative data covering the universe of motor vehicle sales. The data record the postcode of the owner, not the location of the dealership where the motor vehicle was purchased. One benefit of the VFACTS sales data is disaggregation by buyer type. We use only motor vehicle sales to households (and exclude sales to businesses and governments) because this corresponds most closely to the sample underlying the consumer sentiment survey.[7] The data span the November 2007 and the September 2013 changes in government.

To control for differences in population growth across postcodes we measure motor vehicle sales in per capita terms. Population data are sourced from the five-yearly Socio-Economic Indexes for Areas census. We linearly interpolate the data to get population estimates between Census dates.[8]

3.2.3 Control variables

The federal government's tax and transfer policies could differentially affect different groups of voters. We use a range of postcode-level variables to control for these differences. We use average taxable income data from the Australian Taxation Office. The Census provides a range of postcode-level economic variables every five years: the share of people with a tertiary education, average age, the unemployment rate, the share of people who rent, and the share of employed people in white-collar professions. We also collect postcode-level information on the share of employment by industry. Industries are grouped according to the NAICS classification. We also collect information on the geographic location of a postcode. Postcodes are classified in increasing order of remoteness – as being in either a major city, inner regional, outer regional, remote or very remote. These data are sourced from the Australian Statistical Geography Standard. Throughout the paper, we exclude postcodes in the Australian Capital Territory (ACT), where the federal public service is located. Changes of government may have an immediate effect on the incomes of federal public servants, through hiring or redundancies. Hence, consumption for those people can be affected by other channels rather than via sentiment effects.

3.2.4 Summary statistics

Table 1 reports postcode-level summary statistics by population-weighted quintiles of ALP vote share at the 2007 and 2013 Federal elections. Demographic and employment-by-industry data reported in Table 1 are sourced from the Census closest in time to each election: the 2006 Census for the 2007 election and the 2011 Census for the 2013 election.

Our analysis is able to exploit large differences in vote shares across postcodes, with the fifth quintile having a 36 percentage point higher ALP vote share at the 2007 and 2013 elections than the first quintile. Income is decreasing in ALP vote share, and so is the mean level of motor vehicle purchases. Postcodes with a higher ALP vote share also tend to have a lower share of white-collar employment, a higher unemployment rate, and a higher share of renters. However, differences in educational attainment and average age are relatively minor. By industry, the main differences are the relatively high share of manufacturing employment and low share of agricultural employment in high ALP vote share postcodes. By geographic location, 88 per cent of postcodes in the top quintile of ALP vote share are in metropolitan areas, compared with 50 per cent of postcodes in the bottom quintile.

Table 1: Means
By quintile of ALP vote share
  Total population Quintiles
1 2 3 4 5
November 2007 election: ALP victory
ALP vote share 53.4 36.3 46.0 52.9 60.1 71.7
Motor vehicle purchases per capita 0.025 0.027 0.027 0.025 0.024 0.020
Income ($) 50,317 57,132 51,330 49,552 48,243 45,319
Average age (yrs) 37 38 38 37 37 36
Share with tertiary education 13.9 14.5 14.0 14.1 13.4 13.4
Share who rent 27.6 22.8 25.1 26.7 29.6 33.8
Unemployment rate 5.5 4.3 4.8 5.0 5.6 7.7
Share in white-collar profession 32.7 39.0 33.8 32.7 30.1 27.6
Industry share of employment:
Agriculture 3.2 9.0 2.9 2.4 1.2 0.8
Mining and construction 10.3 10.0 11.2 10.8 10.5 9.1
Manufacturing 11.1 8.9 10.0 10.3 12.1 14.3
Retail and wholesale trade 21.2 19.9 20.8 21.3 21.8 22.5
Services 17.2 16.9 17.2 17.3 17.2 17.6
Health and education 18.6 18.7 19.4 19.4 18.5 17.1
Arts and accommodation 8.0 7.6 8.2 7.9 7.8 8.3
Public sector 6.4 5.4 6.4 6.8 7.1 6.4
Other 3.8 3.6 3.9 3.9 3.9 3.9
September 2013 election: Liberal/National victory
ALP vote share 47.2 30.1 39.8 46.6 53.9 65.7
Motor vehicle purchases per capita 0.026 0.028 0.027 0.026 0.026 0.021
Income ($) 68,424 77,614 70,192 67,501 65,831 60,969
Average age (yrs) 38 39 38 38 37 36
Share with tertiary education 16.5 16.8 16.0 16.3 16.9 16.6
Share who rent 30.1 26.4 29.1 29.2 30.7 35.4
Unemployment rate 5.8 4.7 5.5 5.5 5.8 7.4
Share in white-collar profession 33.8 39.2 34.0 33.3 32.7 30.0
Industry share of employment:
Agriculture 2.6 7.6 2.4 1.6 0.9 0.6
Mining and construction 11.4 11.6 12.7 12.2 11.0 9.6
Manufacturing 9.5 7.7 8.6 9.1 9.9 12.3
Retail and wholesale trade 20.1 18.8 19.7 20.1 20.6 21.4
Services 17.5 17.4 17.2 17.2 17.8 18.0
Health and education 20.1 20.0 20.7 20.7 20.2 19.0
Arts and accommodation 8.2 7.6 8.4 8.2 8.0 8.7
Public sector 6.6 5.5 6.3 6.9 7.7 6.4
Other 3.9 3.7 3.9 4.0 3.9 3.9

Notes: Reports population-weighted means for each variable by quintile of the ALP vote share and for the total population; postcode characteristics data are taken from the Census that is the closest in time to the change in government; the 2006 Census for the 2007 Federal election and the 2011 Census for the 2013 Federal election; income data are taxable income for 2006/07 and 2012/13; motor vehicles data are total per capita purchases for 2007 and 2013; postcodes in the ACT are excluded

Sources: ABS; Australian Electoral Commission; Authors' calculations; VFACTS

Footnotes

Data on Australian voter turnout is sourced from the Australian Electoral Commission. US data is from the International Institute for Democracy and Electoral Assistance. [4]

We use vote shares for elections to the House of Representatives (lower house). In all but a few electorates, the two candidates remaining at the end of the vote count are from the ALP or the Liberal/National party. For the few electorates where an independent or minor party either won or came second, we use a two-party preferred measure constructed such that the top two candidates are from each of the major parties. [5]

Unlike in the United States, the government changes hands as soon as the election result is known. [6]

Sales to businesses and governments account for around 55 per cent of total annual motor vehicle sales. [7]

For the period after 2011, the most recently available Census, we assume postcode-level population growth continues at its rate over the period 2006–11. [8]