International Review of Applied Economics,
Vol. 20, No. 4, 469–490, September 2006
Impact of the Minimum Wage on Expected Profits
GAIL PACHECO* & VIC NAIKER**
*Auckland University of Technology, Auckland, New Zealand; **The University of Auckland,
Auckland, New Zealand
International
10.1080/02692170600874077
CIRA_A_187335.sgm
0269-2171
Original
Taylor
402006
20
[email protected]
GailPacheco
00000September
and
&
Article
Francis
(print)/1465-3486
Francis
Review
2004
Ltd
of Applied
(online)
Economics
ABSTRACT This paper investigates the impact of a significant reform to the youth
minimum wage in New Zealand in 2001, on the expectations of low wage employers’
profits. In March 2001, the eligibility for adult minimum wage rates was lowered from 20
to 18 years while the youth minimum wage for 16–17 year olds was also increased from 60
to 70% of the adult minimum wage. We construct a descriptive profile of minimum wage
workers in New Zealand and their industry membership. We find that most minimum
wage workers in New Zealand predominantly work in the four industry sectors; (1)
Retail, (2) Textile and apparel, (3) Accommodation, cafes and restaurants, and (4) Agriculture, forestry, and fishing. Next using an event study methodology we examine the
economic impact of the substantial increase in youth minimum wage rates on employers
in industries with high concentrations of minimum wage workers. Surprisingly, all
conclusions point to there being an insignificant impact on profit expectations for low
wage employers by investors.
KEY WORDS: minimum wage, shareholder wealth, event study.
JEL CLASSIFICATION: J0; J38
1. Introduction and Overview
What is the expected impact of minimum wage legislation on employer’s profits?
Past minimum wage research usually focuses on the consequences of minimum
wage increases on workers and their employment levels, but there has been little
emphasis on the impact of minimum wage increases on employers. The general
economic argument is that a higher minimum wage increases the labour costs,
resulting in lower profits for businesses that employ a large amount of low wage
workers.
To consider the impact of the minimum wage on employers’ profitability, one
option posed by finance theory is to conduct an event study that analyses the
Correspondence Address: Vic Naiker, Department of Accounting and Finance, The University of
Auckland, Private Bag 92019, Auckland, New Zealand. Email: [email protected]
ISSN 0269-2171 print; ISSN 1465-3486 online/06/040469-22 © 2006 Taylor & Francis
DOI: 10.1080/02692170600874077
470
G. Pacheco & V. Naiker
impact of important minimum wage news on the stock market value of the firm.
The stock market value of the firm represents investors’ forecast of the net present
discounted value of the firms’ future profitability (Horsky & Swyngedouw, 1987).
The main assumption underlying this proposition is that capital markets are efficient in evaluating the impact of new information on expected future profits of the
firms. The benefit of using an event study is that the effects on minimum wage can
be observed quickly and empirically using share price information over a relatively
short period.
This study examines the reaction of investors to a significant minimum wage
reform that took place in the youth labour market in New Zealand (hereafter
NZ). In March 2001, the eligibility for the adult minimum wage was lowered
from 20 to 18 years. Previously, an adult minimum wage had existed for workers aged 20 or over, and a youth minimum wage had existed since March 1994
for workers aged 16–19.1 Along with the reduction in age eligibility for the adult
minimum in March 2001, the youth minimum wage, applying to 16–17 year
olds, was also increased from 60 to 70% of the adult minimum, with a clear
intention of increasing it further to 80% of the adult minimum in another year
(Hyslop & Stillman, 2004). In the lead up to this reform, news began to hit the
labour market in late 1999, as the incoming government made initial promises
concerning this reform. They later reneged on their promises and put the issue
on the ‘backburner’ for a while before finally meeting their promise in early
December 2000.
The contribution of this study is twofold. First we present the industry
membership of minimum wage workers in NZ. Such descriptive information on
the industry membership of minimum wage workers in NZ has not been empirically examined in prior research. We find that over half of the minimum wage
workers in NZ are predominantly employed in four industries; (1) Retail, (2)
Textile and apparel, (3) Accommodation, cafes and restaurants, and (4) Agriculture, forestry, and fishing. Second, we contribute to the relatively scant stream of
literature on investors’ perception of an increase in minimum wage rates.2 Using
an event study methodology, we find that shareholders of firms operating in
industries with high levels of minimum wage workers do not react strongly to
major events that were deemed to provide surprising news relating to changes in
minimum wage rates. This finding remains robust to several sensitivity tests
including combining the economic effects of events providing similar news,
expanding the event windows, using an alternative ‘price reversal’ methodology
and using accounting measures of firm profitability. Possible explanations for
the lack of a significant impact could include investors’ belief that the increase in
labour cost would be easily absorbed (through an increase in product prices
and/or an increase in production efficiencies) and/or that minimum wage is not
effectively policed in NZ.
The remainder of this paper is organised as follows. Section 2 presents a brief
background to the level of minimum wage rates in NZ, along with a description of
the 2001 reform to the youth rates. Section 3 discusses prior research on the industry membership of minimum wage workers and investor reaction to changes in
minimum wage rates. Section 4 discusses the data collection. The industry
memberships of minimum wage workers in NZ are presented in Section 5. Section
6 discusses the event study methodology employed in this study. The results from
the event study are presented in Section 7 and Section 8 summarizes and
concludes.
Minimum Wage Impact on Expected Profits 471
2. 2001 Reform of Minimum Wage Rates
In NZ, the 1983 Minimum Wage Act prescribes the minimum rates of wages
payable to workers in particular age groupings. Initially, the Act set a binding
wage only for workers aged 20 years and above. Then in March 1994, a youth minimum wage was introduced for teenagers aged 16–19 years. The following four
years witnessed small annual increments in the minimum wage of all workers
until March 1997 after which there was a period of three years during which there
were no changes in minimum wage rates.
The next review of minimum wage rates largely precipitated from the election
of a centre-left government in 1999. In the lead-up to the 1999 elections both the
Labour and the Alliance parties made strong promises to review the minimum
wage rates. In fact the Alliance party explicitly stated that it would push for an
hourly increase of NZ$0.50 if it had a role to play in the new government. The election of a Labour–Alliance coalition government on 29 November 1999 further
increased the probability of large changes in minimum wage rates. Shortly after
the election, the Labour party hesitated in their plan to substantially increase
minimum wage rates for youth, indicating it was not a decision to be rushed into.
However on 21 December 1999 the cabinet finally agreed to increase the minimum
wage for adults and youths.
In the following year the Alliance party engaged in a vigorous campaign to
lower the adult minimum wage threshold from 20 to 18 years of age. As a result of
this pressure, on 4 April 2000 the cabinet agreed in principle to lower the adult
minimum wage threshold. Shortly afterwards the pay plan was axed in a government retreat as the Labour party attempted to shed an anti-business perception of
its policies. This was largely as a result of a business backlash against the policies
of the coalition government. Using arguments related to economic growth and
rising confidence, the Alliance party soon exerted fresh pressure on its coalition
partner to resurrect these policies. Finally, on 3 December 2000 the cabinet
approved a rise in the youth minimum wage rate that would take effect from
March 2001.
The major implication of this minimum wage reform (hereafter 2001 reform)
was that the youth minimum wage rate was now only applicable to 16–17 year
olds, as 18–19 year olds became eligible for the adult minimum wage rate. Further,
the minimum wage rate for 16–17 year olds increased from 60 to 70% of the adult
minimum wage rate, with an expected increase to 80% in March of the following
year.
Table 1 provides a summary of all the changes to the statutory minimum wage
that have occurred since 1983, dependent on three age subgroups: 16–17 year olds,
18–19 year olds and lastly 20 year olds and over.
As evident from Table 1, the subgroup most ‘affected’ by the 2001 reform are
those aged 18–19 years. Workers in this particular age subgroup experienced huge
increases in their statutory minimum wage. Their nominal minimum wage
jumped 69% from 2000 to 2001, in comparison to the workers in the 20 years and
older subgroup who experienced an increase of only 2% in their nominal minimum wage over the same period.
Workers in the 16–17 year old subgroup also experienced large rises in their statutory minimum. The cumulative effect of increasing the youth minimum wage
from 60 to 70% in March 2001, and further to 80% in March 2002, was equivalent
to a 41% increase in the nominal minimum wage for workers in this subgroup.
472
G. Pacheco & V. Naiker
Table 1. Nominal hourly minimum wage rates and changes since 1983
(Gross NZ$/hour)
Age groups
Pre February 1985
February 1985
September 1985
February 1987
February 1988
May 1989
September 1990
March 1994
March 1995
March 1996
March 1997
March 2000
March 2001*
March 2002*
March 2003
March 2004
16–17 years
18–19 years
20 years +
No minimum applies
No minimum applies
3.68
3.75 (1.9)
3.83 (2.1)
4.20 (9.7)
4.55 (8.3)
5.40 (18.7)
6.40 (18.5)
6.80 (6.3)
7.20 (5.9)
3.68
3.75 (1.9)
3.83 (2.1)
4.20 (9.7)
4.55 (8.3)
7.70 (69.2)
8.00 (3.9)
8.50 (6.3)
9.00 (5.6)
2.500
2.800 (12.0)
4.250 (51.8)
5.250 (23.5)
5.625 (7.1)
5.875 (4.4)
6.125 (4.3)
6.125 (−)
6.250 (2.0)
6.375 (2.0)
7.000 (9.8)
7.550 (7.9)
7.700 (2.0)
8.000 (3.9)
8.500 (6.3)
9.000 (5.6)
Percentage increases are reported in brackets.
*Reform to youth minimum wage implemented (March 2001 and 2002).
Information supplied by the labour market policy group.
Consequently, the 2001 reform, presents a unique opportunity to analyse the
impact of the minimum wage increases on investors’ profit expectations in industries with high concentrations of youth minimum wage workers (aged 16–19
years).
The motivation for investigating impacts of the minimum wage in NZ during
this period is further illustrated in Figure 1 where the real minimum wage for the
three main age categories is displayed for the time period 1984–2004. The figure
displays a common trend in the real minimum wage, where legislated increases in
the minimum wage rates are quickly eroded by inflation until the next increase—
causing a ratchet effect. The leap in the real minimum for both 16–17 and 18–19
year olds introduced by the 2001 reform appears to be substantial, relative to the
adult minimum increase during the same time period.
Figure 1. The real minimum wage for adults since 1984 and youth since 1994.
3. Prior Research
Investigating the effects of the 2001 reform on firms’ expected profitability requires
isolating the industries that are the most vulnerable when the minimum wage is
increased. US evidence on this front points to a high concentration of minimum
wage workers in the retail industry and female dominated occupations (e.g. cashiers), firms with low levels of union representation, the fast food industry (Card &
Krueger, 1994; Wimmer, 1996; Gissy 1998) and firms with proportionately more
young and less skilled workers (Neumark, 1999). However many of these studies
focus on the types of workers receiving minimum wage rates and hence have
inevitably used an indirect approach to determine the industry membership of
Minimum Wage Impact on Expected Profits 473
8.50
8.00
real minimum wage ($)
7.50
7.00
6.50
6.00
5.50
5.00
4.50
4.00
real min wage (adult: 20 + years)
Jun. 2004
Sep. 2003
Dec. 2002
Jun. 2001
Mar. 2002
Sep. 2000
Dec. 1999
Jun. 1998
real min wage (youth:16-17 years)
Mar. 1999
Sep. 1997
Dec. 1996
Jun. 1995
Mar. 1996
Sep. 1994
Dec. 1993
Jun. 1992
Mar. 1993
Sep. 1991
Dec. 1990
Jun. 1989
Mar. 1990
Sep. 1988
Dec. 1987
Jun. 1986
Mar. 1987
Sep. 1985
Dec. 1984
3.50
real min wage (18-19 years)
Note: Nominal adult minimum wages over the period 1984:4ñ2004:2 and nominal youth minimum wages over
the period 1994:1ñ2004:2 are deflated by the consumer price index, with a base year of 1999:2.
Figure 1.
The real minimum wage for adults since 1984 and youth since 1994
minimum wage workers. This is due to the fact that most prior studies isolate the
types of workers likely to be earning the minimum wage, so as to isolate employment effects of minimum wage changes on these workers.
Luke (2000) states that research on the industry membership of minimum wage
workers in NZ has been scant. There is some informal evidence to suggest that NZ
employers/industries that are most at risk from increases in minimum wage rates
include the retail sector,3 the textile industry (Luke, 2000), small and rural businesses,4 and firms with a relatively large proportion of young, Maori and unskilled
workforce.
The lack of NZ literature on the industry membership of minimum wage workers presents difficulties for researchers trying to isolate industries that are most
sensitive to changes in the minimum wage. We overcome this gap in NZ literature
by constructing a detailed profile of minimum wage workers and their industry
membership in NZ. Having compiled this profile, we use it to examine shareholder reaction in the sensitive industries, to the 2001 reform.
With respect to the consequences of changes in minimum wage rates, Card &
Krueger (1995) is, to our knowledge, the only study thus far to have employed an
event study methodology to investigate the impact of minimum wage changes on
investors’ evaluations of employers’ profits. They investigate 23 prominent
events in the USA between early 1987 and mid 1989 that eventually lead to
minimum wage increases in 1990 and 1991. They find that firms most affected5 by
the 1990 minimum wage increase consisted of small establishments and firms
operating in the restaurant, hotel, grocery store, variety merchandise store and
department store industries.6 Overall, they find inconclusive evidence, and a
minimal relationship, if any, between news of a minimum wage increase and
changes in shareholder wealth.
474
G. Pacheco & V. Naiker
By re-examining the value relevance of changes in minimum wage rates under
an alternative setting in NZ and through a series of alternative tests, our study
provides an additional insight on the economical impact of changes in minimum
wage rates on firms.
4. Data
Data used to construct the industry memberships of minimum wage workers in
NZ is derived from two sources, namely, the Household Labour Force Survey
(hereafter HLFS) and the Income Survey (hereafter IS), both provided to us by
Statistics NZ.
The HLFS is a quarterly data source that began in December 1985, and consists
of a sample of between 16,000 and 32,000 households over that time. This data set
is ongoing and includes a wide array of information on the working age population in NZ.7 Specifically, the HLFS contains individualised information on labour
force states, as well as a raft of other variables such as educational status, demographic variables, region, household statistics, and most importantly for the
purposes of this study—industry affiliation.
The IS is an annual survey that commenced in 1997 and is conducted in the June
quarter to supplement the HLFS with information on wage or non-categorical
income. This extensive and detailed supplemental questionnaire collects information on wages and salaries, government transfers, other transfers such as private
superannuation or pension schemes, pre-tax income from self-employment and
income from investments (from 2002). For the purpose of this study, it allows us to
isolate workers earning the minimum wage or close to it.
Industry classifications of the NZ firms listed on the share market are
obtained from the New Zealand Investment Yearbook 2001. Finally, share prices of
firms and market index details used to measure the economic effect of the
increase in minimum wage rates are obtained from the Investment Research
Group (Datex).
5. Industry Profile of Minimum Wage Workers in New Zealand
The HLFS and IS data is combined over the period 1997–2004, since the IS supplemental questionnaire only began in June 1997. Specifically, this study combines the
wage information from the unit record data within the IS (to classify which workers are earning close to the minimum wage)8 with industry affiliation information
on these individual workers from the HLFS. The combination of the two data
sources allows us to measure the concentration of minimum wage workers in
various NZ industries.
5.1. Construction of Minimum Wage Categories
We commence by trimming the combined HLFS and IS data sample to remove
outliers, individuals with missing information, etc.9 The resulting data sample is
then divided into three subgroups based on workers’ hourly wage. Although the
IS provides individually obtained or survey computed values for hourly wage,
these are inclusive of overtime earnings. Consequently, weekly data on both
total and overtime hours and earnings from the IS is used to derive hourly earnings, exclusive of overtime. This derivation gives a more accurate picture of each
Minimum Wage Impact on Expected Profits 475
individual’s regular hourly wages and hence whether he/she truly belongs in
the minimum wage workers’ group in NZ.
The regular hourly wage can be derived for both actual wage (i.e. the regular
hourly wage the individual was paid in their latest pay before the survey was
taken) and usual wage (i.e. the regular hourly wage the individual is usually paid)
using IS data. The advantage of actual wage is that it refers to a particular reference
week and therefore reflects a single standard. While, usual wage is open to interpretation, this wage can possibly be seen as a better average of the individual’s
wages, if the reference week was not the usual for any particular reason. Additionally, usual wages is the standard used in most US research.10 It was also observed
that usual wage information for each year tended to have less outliers and missing
observations in our data sample.
Consequently, individuals are assigned into three groups based on each individual’s regular usual hourly wages. These three groups are named the sub-minimum
wage workers (hereafter SMW), current minimum wage workers (hereafter CMW)
and other workers (hereafter OTHER). Specifically, the SMW group includes individuals earning below the current minimum wage rate, the CMW group includes
individuals earning a more than or equal to the current minimum wage but less
than 10% above that minimum, and the OTHER group contains the remaining
individuals. Individuals in the CMW group are deemed to be directly affected
because they are directly at risk of losing their job when there is a rise in the
minimum wage.
The three wage groups are constructed for each year from 1997 to 2004. The
group that an individual gets assigned to therefore depends on the particular year
and their age. Table 1 summarises the minimum wage levels applicable to each age
group over this time period. The information by wage category is then combined
across all eight years, as averages across the merged data provide a more consistent and robust picture, rather than individual year snapshot estimates. Next, the
industry affiliation of each worker within the three wage groups is identified using
the HLFS data.
Table 2 summarises the industry affiliations of all workers used in our sample
and workers assigned into the SMW, CMW and OTHER groups. All summary
statistics are weighted using the sampling weights Statistics NZ provided to
increase the representativeness of the sample. This is done in order to take account
of sample frame, non-random survey response and individual attrition.
Panel A of Table 2 shows that a significant number of workers are affected by
the minimum wage. The SMW and CMW groups together amount to 5.92% of the
total sample of workers. Also, employed teens (16–19 year olds) account for close
to a quarter of minimum wage workers (23.41%), while only constituting 4.55% of
the data sample. This is as expected, given the large increases in nominal and real
minimum wage teens have undergone in this sample period, as a result of the 2001
reform.11
Panel B of Table 2 presents the industry affiliation of low wage employers.
Several industries stand out as having high concentrations of minimum wage
workers. More than 40% of workers in the CMW group are employed in the retail
trade or accommodation, cafes and restaurants industries. The next largest grouping of workers in the CMW group is located in the manufacturing industry
(12.48%). However, this figure is lower than the proportion of total workers that
work in the manufacturing industry (17.61%). We decompose this group further to
identify which particular sector(s) of the manufacturing industry contain(s) the
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G. Pacheco & V. Naiker
Table 2. Industry affiliations of workers: June 1997–June 2004
Full sample
of workers
SMW Group
Panel A: Wages of all workers and teenage workers
Total sample size
99,091
2960
(%)
(100)
(2.99)
Percentage of teenagers in each wage
4.55
18.29
category
Panel B: Industry affiliations of all workers from each wage category
Agriculture, forestry and fishing
5.37
12.99
Manufacturing
17.61
9.45
Construction
5.19
3.62
Wholesale trade
4.91
2.53
Retail trade
12.07
18.65
Accommodation, cafes and
4.42
7.83
restaurants
Transport and storage
4.19
3.54
Finance and insurance and
5.05
3.08
communication services
Property and business services
8.33
8.05
Education
9.93
7.52
Health and community services
10.26
9.98
Cultural and recreational services
1.92
2.85
Personal and other services
3.94
7.44
Other services
6.38
2.29
CMW Group
OTHER Group
2904
(2.93)
23.41
93,227
(94.08)
3.54
10.6
12.48
2.76
2.22
28.71
13.11
4.97
18.02
5.32
5.07
11.34
4.04
1.74
1.55
4.29
5.22
4.67
5.53
9.6
1.76
3.83
1.2
8.46
10.14
10.29
1.91
3.84
6.67
Source: HLFS and IS.
Note: The SMW group included individuals earning below the current minimum wage rate, the CMW
group included individuals earning more than or equal to the current minimum wage but less than 10%
above that minimum, and the OTHER group contained the remaining individuals.
largest proportion of minimum wage workers. The results (not reported) from this
breakdown analysis of the manufacturing industry find the textile and apparel
sector to contain the bulk of minimum wage workers within the manufacturing
industry. This finding is supported by the informal evidence present in NZ
concerning research into the collective contracts in the textile industry.
The only other industry sector that appears to be relevant is the agriculture, fishing and forestry sector. Just over 5% of the total workers were employed in this
industry, while they make up 12.99% of workers in the SMW group, and 10.6% of
workers in the CMW group. This finding is not surprising as our study also finds
(results not reported) that minimum wage workers are more likely to live in a rural
area in comparison to other workers.
In summary we find that over half of the minimum wage workers in NZ work
in the four industries; (1) Retail trade, (2) Accommodation, cafes and restaurants,
(3) Textile and apparel, and (4) Agriculture, forestry and fishing
We next perform several checks to test the robustness of our results on the industry affiliation of minimum wage workers. First, while Table 2 presents the industry
affiliations of all minimum wage workers in the sample between 1997 and 2004,
the same employer profile by wage category emerges when only 16–19 year olds
are focussed on. This is a necessary point to make given the focus of this study is
investigating the impact of the youth minimum wage 2001 reform.
Minimum Wage Impact on Expected Profits 477
Next, we measure the industry affiliations of all minimum wage workers in two
time periods, 1997–1999 (before the events leading up to the minimum wage
reform started to take place) and 2002–2004 (post implementation of the reform).
The results are once again qualitatively similar to those reported in Table 2.
A final check for robustness of our results is performed by changing the criteria
used to assign workers into the SMW, CMW and OTHER groups. Specifically, the
definition of minimum wage workers is changed to include workers earning
between 10% below and 10% above the relevant minimum wage. This overlapping
definition is tried, in case measurement error present in the weekly earnings and
hours information by individuals incorrectly enlarges the SMW group and reduces
the CMW group. While this procedure decreases the number of workers assigned
to the SMW group down to 1896 workers and increases the membership in the
CMW group to 3968 workers, the industry affiliations of the groups did not change
(results not reported) in comparison to those reported in Table 2.
5.2. Industries and Sector Classifications in the New Zealand Stock Exchange
The next step in our analysis is to match the four industry sectors with high
concentrations of minimum wage workers (identified using HLFS data) to the
industry affiliation of firms listed on the New Zealand Stock Exchange (hereafter
NZX). The NZX provides information relating to six group sectors and 13 additional single sectors. A list of all sectors is presented in Appendix A. Several NZX
industry sectors match very well with the four HLFS industry sectors with a high
concentration of minimum wage workers. More specifically NZX sectors G01A01
and G01A03 provide a match for agriculture, fishing and forestry, sector G03A07
for textile and apparel, sector G05A13 for retail trade while sector G05A12
provides a good proxy for the accommodation, cafes and restaurants category.12
The New Zealand Investment Yearbook 2001 contains a listing of public firms that
operate in the matching five NZX sectors. Using this information we extract an
initial sample of 35 firms operating in the five NZX sectors. To conduct our event
study we require each of the sample firms to have share price data available on
Datex. This process eliminates three firms resulting in our final sample of 32 firms.
We use industry segment data from the annual reports of the firms in the final
sample to measure their degree of industry diversification. We find that the average number of industries that the sample firms identify themselves in is 1.15,
suggesting that the sample firms are highly specialised in their respective sectors.
This confirms that the 32 firms chosen in our final sample match well to the sector
they are assigned into by the NZX and hence to sectors that are likely to be most
vulnerable to minimum wage increases.
Further, although there is no firm specific wage data, there are examples in news
sources and firm announcements that firms within this sample pay the minimum
wage. For example, Simon (1997) finds evidence of Sanford (a firm in the G01A01
sector) paying the minimum wage. Also, Restaurant brands (a firm in the G05A13
sector, which owns several fast food chains in this country) included in its directors report to shareholders in April 2005 that there was a significant escalation in
labour costs because of changes in minimum wage and holiday pay legislation.
In addition to this evidence, we would further expect the firms in this sample to
be affected by the minimum wage as a result of a ‘spillover effect’. Most low wage
firms often use the minimum wage to set up their entire wage structure (Card &
Krueger, 1995) and prior research has shown that as the minimum wage increases,
478
G. Pacheco & V. Naiker
the entire wage distribution may shift rightwards as well, owing to this spillover
effect (Katz & Krueger, 1992). Various other studies have also found that because
of this effect, individuals earning just above the minimum (and in fact as much as
20–25% above the minimum) also benefit in their wage levels after a minimum
wage increase (Spriggs & Klein, 1994). We find that workers earning just above the
minimum are also highly concentrated in the same four sectors that have a high
proportion of minimum wage workers.13
Overall, our examination of the annual reports, news sources, firm announcements and industry membership of workers earning just above the minimum
wage re-assures us that the firms chosen from the five NZX sectors for our final
sample are representative of firms that are more likely to be affected by minimum
wage rises in NZ.
6. Event Study Methodology
Having identified the 32 firms operating in industry sectors that are most vulnerable to minimum wage increases, the remainder of this study focuses on examining the impact of changes in minimum wage polices on the market value of these
firms. Given that the focus of our study is the 2001 reform, we seek to identify the
important news events that hit the labour market in the year long lead up to
the 2001 reform. To reduce the likelihood of measurement error in instances where
the capital market anticipates the effect of the news events before they occur, we
follow the Schipper & Thompson (1983) strategy of only considering news events
that significantly influence investor’s expectations about the minimum wage
increase.
Published news sources of minimum wage events concerning the reform under
study are available from the Newztext and Newzindex online databases in NZ.
These sources contain published news from all major newspapers and business
magazines in NZ (including the NZ Herald, The Dominion, The Independent, The
National Business Review and The Evening Post). In a similar fashion, Card &
Krueger (1995) used the Wall Street Journal as their main source.14 The 10 events
used for this study are detailed in Table 3. In each case, the description of the event
(news summary) reads close in line with the title of the newspaper article and/or
introduction of the article.
We expect that investors will view news of a minimum wage increase negatively
and news of a back down of an upcoming minimum wage increase positively. The
intuition behind this expectation arises from the general agreement amongst economists that if minimum wage increases, and other factors are held constant, costs
faced by the employer will increase. This inevitably results in a fall in firm profits
unless the firm is either able to raise prices and pass all of the extra costs onto
consumers in the form of higher prices or able to increase production efficiencies
to counteract the effect of the higher costs faced. In the context of this study, the
reform to minimum wage rates is substantially large enough to suggest that
neither of these alternatives are expected to completely counteract the increased
employer costs from the minimum wage, ex ante.
The third column of Table 3 presents the predicted impact of each event on
investor’s expectations with respect to future firm profits. An event with a negative predicted impact is termed an increasing event as it increases the likelihood of
a minimum wage increase. News of these events are expected to be negatively
received by investors as it increases the likelihood of a fall in firm profits.
Minimum Wage Impact on Expected Profits 479
Table 3. Summary of major minimum-wage related events
Predicted
impact News summary
Event
Published date
1
5 November 1999
−
2
29 November 1999
−
3
2 December 1999
+
4
21 December 1999
−
5
21 January 2000
−
6
7
6 March 2000
4 April 2000
−
−
8
2 June 2000
+
9
28 June 2000
−
10
3 December 2000
−
Labour and Alliance parties announce plans to increase
minimum wage for the young
News confirmed that Labour–Alliance coalition to govern
New Zealand
Prime Minister says she is not going to be rushed into a
decision on the minimum wage rise
Cabinet agrees to increase minimum wage for adults and
youth
Axing youth rates announced as top priority for youth affairs
minister
Rise in adult and youth minimum wages takes effect*
Cabinet agrees in principle to lower the adult minimum wage
threshold
Pay plan axed as the government retreat on the impending
reform
Alliance exerts fresh pressure to resurrect policies on youth
minimum wage reform
Alliance wins rise for the young. Cabinet expected to approve
it on the next day
Note: A negative predicted impact on employers’ future profits indicates the increased likelihood that
there will be an increase in the minimum wage rates. Hence, events with a negative predicted impact
are termed increasing events. While a positive predicted impact signifies the decreased likelihood of
an increase in the minimum wage rates and are termed decreasing events.
*This rise in minimum wage for both adults and youth was planned well before the series of events
under investigation in this study. However, news of its implementation bought the debate about minimum wage effects back to the forefront of the media’s attention and also acted as a signal of the further
rises under planning in the 2001 reform.
Conversely an event with a positive predicted impact is termed a decreasing event
as it contains news that decreases the likelihood of a minimum wage increase
(expected to have a positive effect on firm value).
The abnormal returns around the events are computed using the standard event
study approach pioneered by Fama et al. (1969) which has been commonly
employed in the finance and economic literature (Card & Krueger, 1995). In examining the markets reaction to the ten events, we eliminate the overall effect of
market-wide factors by estimating the following firm level market model:
Rit = α i + β i Rmt + ε it
where Rit is the stock return of firm i on day t, Rmt is the return on the NZX index
on day t, and αi and βi are the parameters of the market model. We estimate the
market model for each event using daily stock and market return data over a
period of 250 days through to 10 days before each event.15 We exclude 5-day
windows around prior events when estimating the market model for subsequent
events. Firm abnormal returns (ARit), also known as prediction errors, are
computed for each firm on an event date by:
480
G. Pacheco & V. Naiker
ARit = Rit − (αˆ i + βˆ i Rmt )
where α̂ i and β̂ i are the estimates of αi and βi from the estimation market model
corresponding to an event.16 As well as examining the daily abnormal returns on
each event date, we also examine cumulative abnormal returns around each event,
using 3- and 5-day windows. We then use the computed abnormal returns to test
the hypothesis that news of possible changes in minimum wage rates is value
relevant to investors.
7. Results
7.1. Abnormal Returns
Table 4 reports the average 1-day, 3-day and 5-day abnormal returns around the
eight increasing and two decreasing events.
The average 1-day abnormal returns for the two events (events 2 and 10, both
increasing events) with the highest levels statistical significance are positive,
suggesting that shareholders and investors reacted positively to the news of an
increase in the likelihood of a minimum wage increase. The average 1-day
abnormal returns of the two remaining events (events 4 and 5, both increasing
Table 4. One-day, three-day and five-day average cumulative abnormal returns
in response to events
Predicted
impact
Event
Published date
1
5 November 1999
−
2
29 November 1999
−
3
2 December 1999
+
4
21 December 1999
−
5
21 January 2000
−
6
6 March 2000
−
7
4 April 2000
−
8
2 June 2000
+
9
28 June 2000
−
10
3 December 2000
−
One-day
average
abnormal return
(t-statistic)
Three-day
average
abnormal return
(t-statistic)
Five-day
average
abnormal return
(t-statistic)
−0.0040
(−1.024)
0.0182
*(2.144)
−0.0041
(−0.424)
−0.0059
*(−1.792)
−0.0098
*(1.753)
0.0025
(0.539)
0.0018
(0.243)
−0.0079
(−1.936)
−0.0040
(−0.805)
0.0076
**(2.205)
−0.0049
(−0.924)
0.0109
(0.978)
0.0021
(0.344)
−0.0033
(−0.314)
−0.0017
(−0.161)
−0.0162
*(−1.768)
0.0111
(0.845)
−0.0041
(−0.940)
−0.0060
(−0.604)
−0.0015
(−0.177)
−0.0213
*(−1.780)
0.0091
(0.883)
−0.0076
(−0.700)
−0.0043
(−0.313)
0.0032
(0.213)
−0.0234
**(−2.587)
0.0167
(1.027)
−0.0095
(−1.011)
−0.0193
(−1.776)
0.0015
(0.143)
Note: A negative predicted impact on employers’ future profits indicates the increased likelihood that
there will be an increase in the minimum wage rates. While a positive predicted impact signifies the
decreased likelihood of an increase in the minimum wage rates.
** and * denote significance at the 5% and 10% level, respectively using two-tailed tests.
Minimum Wage Impact on Expected Profits 481
events) are negative and moderately significant at a 5% level. This suggests that
shareholders and investors reacted negatively to news that increased the
likelihood of an increase in minimum wage rates. Overall, the results from average
1-day abnormal returns yield no obvious conclusions on the impact of an increase
in minimum wage on firm value.
Given the possibility that there may have been some leakage of news revealed
on our event days and the added possibility of the share market not fully capturing
the economical impact of the news revealed on the event day itself, we also examine average cumulative abnormal returns using a 3- and 5-day window around
each event. We only find evidence of weakly significant negative average abnormal returns for event 1 around a 5-day window (at a 10% level), and moderately
significant negative abnormal returns for event 6, around both the 3-day (10%
level) and 5-day windows (5% level). Because both events 1 and 6 are increasing
events, the results suggest negative shareholder reaction to news that increases the
likelihood of a rise in minimum wage rates. Overall, the conflicting and largely
insignificant results from the examination of abnormal returns around the 10
events do not provide strong evidence to indicate that minimum wage policies
affect shareholder wealth.
7.2. Price Reversal Tests
Given the inconclusive results from examination of abnormal returns around each
event, we employ an alternative methodology to test for any shareholder reaction
in response to the 10 events. This ‘price reversal’ methodology has been employed
in previous event studies (e.g. Ali & Kallapur, 2001) and has the advantage of not
requiring an ex ante specification of the direction of abnormal price reaction to an
event. Suppose the stock prices of some firms are expected to be affected by an
event that increases the likelihood of an increase in minimum wage rates. It is
likely that firms positively (negatively) affected by this event would be negatively
(positively) affected by an event that decreases the likelihood of an increase in
minimum wage rates. Hence a priori, if minimum wage changes are value-relevant
to investors, we should expect a negative correlation between the abnormal
returns of our sample firms from an increasing and a decreasing event. Conversely
we would expect a positive correlation between the abnormal returns experienced
by our sample firms on two increasing events (and similarly on the two decreasing
events).
Table 5 reports the Pearson correlation coefficients amongst the 1-day abnormal
returns of our sample firms from the 10 events. We find that only seven of the 36
correlation coefficients are significant (at a 10% level or better). Four of the seven
significant coefficients are in the direction (event 1 vs event 2, event 3 vs event 8,
event 2 vs event 9 and event 7 vs event 10) weakly supporting the conjecture that
investors reacting positively (negatively) to events that increases the likelihood of
an increase in minimum wage rates react negatively (positively) to events that
decreases the likelihood of an increase in minimum wage rates. However the three
remaining significant coefficients (event 1 vs event 5, event 2 vs event 5 and event
3 vs event 6) are in a direction suggesting that news that increases or decreases the
likelihood of a hike in minimum wage rates are irrelevant to investors and shareholders. As a robustness test of the reported correlation coefficients, we report
alternative p-values to control for the normal level of correlation between 1-day
abnormal returns during the sample period.17 Even after controlling for the normal
Increasing
Increasing
Decreasing
Increasing
Increasing
Increasing
Increasing
Decreasing
Increasing
Increasing
1
2
3
4
5
6
7
8
9
10
1.00
1
1.00
0.373
*(0.051)
*[0.083]
2
0.226
(0.256)
[0.206]
0.130
(0.520)
[0.327]
1.00
3
5
−0.454
**(0.017)
**[0.037]
−0.358
*(0.067)
*[0.078]
−0.144
(0.474)
[0.275]
0.066
(0.744)
[0.418]
1.00
4
−0.080
(0.687)
[0.362]
−0.090
(0.650)
[0.348]
0.039
(0.840)
[0.459]
1.00
0.095
(0.624)
[0.376]
0.185
(0.347)
[0.254]
0.324
*(0.099)
[0.116]
−0.049
(0.804)
[0.407]
0.060
(0.766)
[0.427]
1.00
6
−0.045
(0.819)
[0.413]
−0.085
(0.666)
[0.355]
0.056
(0.772)
[0.433]
0.231
(0.227)
[0.201]
0.094
(0.640)
[0.377]
−0.194
(0.324)
[0.215]
1.00
7
−0.111
(0.571)
[0.318]
−0.175
(0.372)
[0.237]
−0.378
**(0.048)
*[0.067]
0.018
(0.927)
[0.491]
0.044
(0.826)
[0.452]
−0.116
(0.549)
[0.312]
−0.082
(0.673)
[0.359]
1.00
8
−0.001
(0.996)
[0.480]
0.565
***(0.002)
**[0.017]
0.082
(0.678)
[0.395]
−0.186
(0.333)
[0.224]
0.217
(0.276)
[0.216]
0.122
(0.536)
[0.337]
0.039
(0.839)
[0.459]
−0.160
(0.408)
[0.255]
1.00
9
0.040
(0.843)
[0.458]
0.076
(0.708)
[0.403]
−0.189
(0.344)
[0.220]
−0.136
(0.489)
[0.285]
−0.326
(0.104)
*[0.097]
−0.247
(0.214)
[0.160]
0.323
*(0.094)
[0.117]
−0.189
(0.335)
[0.220]
−0.246
(0.206)
[0.161]
1.00
10
Cells report the Pearson correlation coefficient, standard p-values in ( ), and Noreen and Sepe p-values in [ ]. ** and * denote significance at the 5% and 10% level.
Note: Increasing events are events that increase the likelihood that there will be an increase in the minimum wage rates. Decreasing events are events that decrease the
likelihood that there will be an increase in the minimum wage rates.
Event type
Event No.
Table 5. Correlation between the event abnormal returns
482
G. Pacheco & V. Naiker
Minimum Wage Impact on Expected Profits 483
level of correlation the results are conflicting. We find significant correlations for
only six of the 36 correlation coefficients. Three of the six significant coefficients
remain significant in the direction suggesting that changes in minimum wage rates
are value relevant to shareholders (event 1 vs event 2, event 3 vs event 8, event 2 vs
event 9), while the three remaining significant correlations are in a direction,
suggesting that changes in minimum wage rates are irrelevant to investors (event
1 vs event 5, event 2 vs event 5 and event 5 vs event 10). Overall the results from
our ‘price reversal’ tests offer no strong support for the notion that investors react
to news that increase or decrease the likelihood of an increase in minimum wage
rates.
7.3. Combined Abnormal Returns of Increasing and Decreasing Events
Given our conflicting and relatively insignificant results thus far, perhaps some
impression of the impact of minimum wage rate changes can be obtained by aggregating and examining the abnormal returns of all eight (two) increasing (decreasing) events. Accordingly we report the average combined abnormal returns for our
sample firms around a 1-day, 3-day and 5-day window. The results are reported
in Panel A of Table 6. Once again the results are inconclusive. We find weakly
significant (at a 10% level) negative abnormal returns for our sample firms in a
combined 5-day window around the eight increasing events, suggesting that a
possible increase in minimum wage rates will be detrimental to shareholders.
However we also find presence of negative, albeit moderately significant (at a 5%
level) abnormal returns in a combined 1-day window around the two decreasing
events suggesting that shareholders reacted negatively even to events that
decreased the likelihood of an increase in minimum wage. Parametric and nonparametric two-sample tests in all windows reveal no significant differences
between the combined abnormal returns experienced by the sample firms on the
two groupings of events.
7.4. Control Sample
To further evaluate the impact of minimum wage rate changes on our sample firms
we next employ the use of a control sample. The set of firms chosen for inclusion
in this control sample operate in the building and construction, media and telecommunications, finance and other services, and investment industries. These
industries have a low concentration of minimum wage workers (see Table 2) and
hence any increase in minimum wage rates is unlikely to affect firms operating in
these industries. While we expect an increase in minimum wage not to affect firms
in our control sample, we examine the combined abnormal returns of these firms
in order to investigate whether we can differentiate the share price reaction of our
sample firms from the share price reaction of the control sample firms around the
combined increasing and decreasing events. Panel B of Table 6 shows that the
control firms experience no significant abnormal returns in all windows around
the two groupings of events. Similar to the test sample, two-sample tests in all
windows again yield no significant differences between the abnormal returns of
the control firms from the combined increasing and decreasing events.
While our abnormal returns from the combined events result in insignificant
results for both our test and control sample, we next examine whether abnormal
returns of our sample firms are more negative (positive) than the abnormal returns
Predicted impact
Two sample tests:
t-statistic
(Wilcoxon score)
Control firms
No impact
Panel C: Increasing events 1, 2, 4, 5, 6, 7, 9 & 10
Sample firms
−
Panel B: Combined abnormal returns for control firms
Combined increasing events
No impact
1, 2, 4, 5, 6, 7, 9 & 10
Combined decreasing events
No impact
3&8
Two sample tests:
t-statistic
(Wilcoxon Score)
Panel A: Combined abnormal returns for sample firms
Combined increasing events
−
1, 2, 4, 5, 6, 7, 9 & 10
Combined decreasing events
+
3&8
Two sample tests:
t-statistic
(Wilcoxon score)
Event
0.0054
(0.362)
−0.0139
(−0.693)
−0.77
(0.00)
−0.0139
(−0.693)
0.0011
(0.109)
0.67
(0.26)
0.0054
(0.362)
−0.0089
**(−2.089)
−0.92
(−0.44)
One-day average abnormal
return (t-statistic)
−0.0092
(−0.478)
0.0132
(0.350)
0.53
(1.20)
0.0132
(0.350)
−0.0010
(−1.060)
−0.59
(−1.44)
−0.0092
(−0.478)
−0.0016
(−0.227)
0.37
(0.47)
Three-day average abnormal
return (t-statistic)
−0.0338
*(−1.828)
0.0002
(0.004)
0.53
**(2.05)
0.0002
(0.004)
0.0263
(1.188)
0.40
(−0.45)
−0.0338
*(−1.828)
−0.0161
(−1.053)
0.74
(0.36)
Five-day average abnormal
return (t-statistic)
Table 6. Combined one-day, three-day and five-day average abnormal returns in response to events for sample and control firms
484
G. Pacheco & V. Naiker
No impact
+
Predicted impact
−0.0089
**(−2.089)
0.0011
(0.109)
0.92
(0.87)
One-day average abnormal
return (t-statistic)
−0.0016
(−0.227)
−0.0010
(−1.060)
−0.71
(−0.60)
Three-day average abnormal
return (t-statistic)
−0.0161
(−1.053)
0.0263
(1.188)
1.58
(1.38)
Five-day average abnormal
return (t-statistic)
Note: Increasing events are events that increase the likelihood that there will be an increase in the minimum wage rates. Decreasing events are events that decrease the
likelihood that there will be an increase in the minimum wage rates.
** and * denote significance at the 5% and 10% level, respectively using two tailed tests.
Two sample tests:
t-statistic
(Wilcoxon Score)
Control firms
Panel D: Decreasing events 3 & 8
Sample firms
Event
Table 6. Continued
Minimum Wage Impact on Expected Profits 485
486
G. Pacheco & V. Naiker
of our control sample around the combined increasing (decreasing) events. Panel
C (D) of Table 6 reports the abnormal returns of the test and control sample firms
in all three windows around the increasing (decreasing) events. The two-sample
tests reported in Panel C of Table 6 shows some evidence to suggest that the
combined 5-day abnormal returns experienced by our test sample were significantly more negative (at a 5% level) than the combined 5-day abnormal returns of
our control sample around the combined increasing events. Similar two-sample
tests performed using a 1-day and 3-day window reveal no significant differences
between the abnormal returns of the two samples. However, the two-sample tests
reported in Panel D of Table 6 show no significant differences between the abnormal returns of the test and control sample firms around the combined decreasing
events.
In general, the above results do not provide strong evidence to suggest that
changes in minimum wage rates are value relevant to shareholders and investors
as abnormal changes in the firm value of our sample firms appears to be indistinguishable from the abnormal changes in the firm value of a sample of firms who
are unlikely to be affected by any changes in minimum wage rates.
7.5. Long Run Cumulative Abnormal Returns
Cumulative Average Abnormal Returns
As an additional check, we cumulate and report the 1-day abnormal returns for the
sample firms around the combined increasing and decreasing events starting from
10 days prior to each event. The objective of this commonly employed examination
(e.g. Bittlingmayer & Hazlett, 2000) is to visually inspect for any sharp movements
in the abnormal returns of our sample firms on days immediately prior to, on, or
immediately after, the event dates. The presence of such behaviour will support
the notion that changes in minimum wage policies are value relevant to investors.
Figure 2 shows that sample firms start experiencing negative abnormal returns
10 days prior to the combined increasing events and continue to experience
0.05
0
-10
-0.05
-9
-8
-7
-6
-5
-4
-3
-2
-1
0
1
2
3
4
5
6
7
8
9
10
-0.1
-0.15
-0.2
-0.25
-0.3
Days
Increasing Events
Decreasing Events
Note: Increasing events are events that increase the likelihood that there will be an increase in the minimum
wage rates. Decreasing events are events that decrease the likelihood that there will be an increase in the
minimum wage rates.
Figure 2.
Cumulative average abnormal returns for eight increasing and two decreasing events
Minimum Wage Impact on Expected Profits 487
negative abnormal returns throughout the 21 following days, resulting in large
negative cumulative abnormal returns at the end of the period examined. More
importantly, Figure 2 does not depict any significant acceleration in the accumulation of negative cumulative abnormal returns immediately around the event dates
of the combined increasing events. Similarly while Figure 2 reports relatively more
positive cumulative abnormal returns for the sample firms around the combined
decreasing events, there are no sharp changes in the pattern of cumulative abnormal returns nearer to the event dates. The lack of any radical changes in the
patterns of cumulative abnormal returns around the events are consistent with our
earlier results and strongly support the conjecture that changes in minimum wage
rates are not value-relevant to investors and shareholders.
Figure 2. Cumulative average abnormal returns for eight increasing and two decreasing events.
7.6. Impact on Accounting Profitability
Our analyses so far have concentrated on investors’ perception of how minimum
wage changes affect firm profitability. To test the robustness of our results we also
consider the impact of the minimum wage reform on accounting measures of profitability.18 We use a cross-sectional regression model utilising panel data during
the period 1997–2002 to implement this sensitivity analysis. Our dependent variable is, return on equity (ROE), a commonly employed accounting measure of firm
profitability. We include as explanatory variables, firm and industry conditions
that have been previously linked to firm profitability. These include firm size,
leverage, market share, capital intensity, export intensity, growth rate, advertising
intensity, industry concentration and industry dummies. We add to these explanatory variables a dummy variable (PERIOD) that equals one for observations from
years ending after 5 November 2000 (a year after our first event), and zero otherwise. The sign and significance of PERIOD would provide evidence of any shift in
profitability following the minimum wage reform. Our results (not reported)
indicate that the parameter estimate of PERIOD is positive and insignificant. This
finding remains after using alternative measures of firm profitability (e.g. return
on assets and return on sales), and alternative definitions of PERIOD (e.g. defining
PERIOD as one for observations from years ending after 3 December 2001, a year
after our last event, and zero otherwise. These findings confirm our earlier results
by suggesting that our sample firms do not experience any significant changes in
accounting profitability following the minimum wage reform.
8. Conclusions
This study investigates the industry membership of minimum wage workers in
NZ and examines the impact of a significant change in minimum wage policies on
firms operating in industries with a high concentration of minimum wage workers. We find that minimum wage workers in NZ are predominantly employed in
four industries; (1) Retail, (2) Textile and apparel, (3) Accommodation, cafes and
restaurants, and (4) Agriculture, forestry, and fishing. These findings are insensitive to different age groups and time periods examined and are also insensitive to
the use of an alternative definition of minimum wage workers.
Having determined the industry concentrations of minimum wage workers the
study goes on to examine whether a higher minimum wage results in a transfer of
wealth from the shareholders of affected businesses to low wage employees. Our
results indicate an inconclusive and mostly insignificant effect on investors’ profit
488
G. Pacheco & V. Naiker
expectations of low wage firms in reaction to news about the minimum wage
rising. This is surprising given the significant minimum wage reform that was the
subject of our investigation.
The insignificant findings suggest the possibility of employers passing on the
incremental increase in wage costs onto consumers through higher prices and/or
employers increasing production efficiencies (i.e. the shock argument) to offset the
higher labour costs. Another possibility is that investors believed that the
economic growth NZ experienced from 2000 onwards had a larger impact on
industries employing low wage workers than the rest of the industry sectors in
NZ. If this was so, the future expected economic growth to some extent compensated for the higher employers’ costs faced by the increase in minimum wage rates.
As a final possibility, investors may have believed minimum wage policies to be
ineffective in NZ. This needs to be considered as there is evidence to support the
fact that compliance to the minimum wage is not full. For example, the finding that
between 1.92 and 2.96% of the data sample were earning under the minimum wage
over the period 1997–2004, depending on the definition of the category for those
earning the minimum wage.
While the above possibilities may have some offsetting effects it seems unlikely
that they would have completely outweighed the downward expectation for the
share prices of low wage employers. However, the number of tests and robustness
checks performed in this study all point to the same conclusion, implying that
some weight should be given to the argument that investors simply find changes
in minimum wage value irrelevant.
Acknowledgements
This paper is based in part on my doctoral work at the University of Auckland. We
are grateful to David Card, Malcolm Sawyer, Farshid Navissi, Graham Brownlow
and an anonymous referee for their useful feedback and suggestions on this paper.
Access to the data used in this study was provided by Statistics New Zealand in a
secure environment designed to give effect to the confidentiality provisions of the
Statistics Act 1975. The results presented in this study are the work of the authors,
not Statistics New Zealand.
Notes
1. There is almost full coverage of the minimum wage in the NZ labour market. The few exemptions
there are to being paid the minimum are that it does not apply to those who hold under rate permits
as a result of a significant disability, or are undergoing particular training recognised under the
Industry Training Act. Another allowance under the Minimum Wage Act is that if the employee is
given board and lodging, a deduction of 15 and 5% can be made respectively.
2. To our knowledge, only one study by Card & Krueger (1995) conducted this type of investigation.
3. The National Distribution Union that represents this retail and manufacture’s group stated in 2000
that some employers in the retail industry do use the legal minimum to undercut competitor
employers ((2000, December 16) Retail staff tipped to benefit from wage rises, The Dominion).
4. For example, in Timaru (a small rural NZ town), the town’s Chamber of Commerce stated in March
2000 that most small businesses in that region ‘don’t pay above the minimum rate because the money
simply isn’t there’ ((2000, March 10) Wage levels could mean fewer jobs, The Timaru Herald, p. 2).
5. This group of affected workers were those earning between the current minimum wage (NZ$3.35
per hour) and the new minimum wage (NZ$4.24 per hour).
6. See Card & Krueger (1995), Table 9.1, p. 282, for more details.
7. The target population is the civilian non-institutionalised and usually resident NZ population aged
15 and over.
Minimum Wage Impact on Expected Profits 489
8. One limitation with the IS data is that it does not observe true wages for those individuals who are
on salary. Someone with hourly earnings below the minimum wage may still be legally paid above
it. This may be because the individual has worked and reported higher hours than they are paid
for, or they have overestimated their hours. The result is then an underestimation of hourly earnings.
9. For example, individuals who responded to having a disability in the HLFS questionnaire were
removed from this analysis, as this is one of the few exceptions under which a worker can legally
be employed with a sub-minimum wage.
10. Data on usual earnings are collected as part of the CPS, a nationwide sample survey of households
in which respondents are asked, among other things, how much each wage and salary worker
usually earns.
11. 18–19 year olds for example underwent a 64% (69%) increase in their real (nominal) minimum wage
from 2000 to 2001.
12. G01A01 Food and Beverages was not chosen because it consisted of only multinational companies
involved in alcoholic beverages such as beer and wine, rather than restaurants. Restaurants fall
under the consumer category G05A13 along with retail trade.
13. This indicates that current estimates of the proportion of workers expected to be affected by minimum wage rises in these sectors (e.g. approximately half the workers in the retail sector) are most
likely underestimates.
14. However, Card & Krueger (1995) encounter difficulties in identifying unambiguous events in the
lead up to the 1990 and 1991 minimum wage increases in the USA.
15. Hence we run a total of 320 regressions in computing the abnormal returns around our events (32
sample firms × 10 events). Prior studies verify that their sample firms have sufficient daily share
price observations to provide more accuracy when estimating the parameters of the market model.
For example Chang (1998) requires firms in his sample to possess at least 100 days of share price
data on the CRSP database when estimating the market model. Similarly we confirm that all firmlevel market model regressions run in this study comprise of at least 100 days of firm and market
returns data from the Datex database.
16. Alternatively we compute abnormal returns using another methodology that has also been
commonly employed in prior literature (Bittlingmayer & Hazlett, 2000). Specifically we compute
abnormal returns using the following model:
ARit = Rit − (α i + β i Rmt ) + ∑ c i ,t + k Dik + ε it
k
where Dit is defined as a [0,1] variable that equals 1 if a given event occurs on day t and 0 otherwise.
Estimates of the coefficients ci,t+k are similar to the abnormal returns obtained form the market
model where the sign and significance of the coefficients would indicate how firms react to events
(positively or negatively) and the statistical significance of the reactions. The results after employing this alternative methodology are qualitatively similar to those reported in this study.
17. This was achieved by examining the correlation between 298 trading days covering the sample
period between 18 October 1999 and 8 December 2000. A correlation matrix was then computed
amongst the abnormal returns of all 298 days resulting in 41,905 correlation coefficients. Using
the Kolmogorov–Smirnov one-sample test we cannot reject the hypothesis that the observed
correlation is normally distributed with a mean correlation of 0.012 with a standard deviation of
0.261. Hence we report alternative p-values based on the assumption that the correlations
amongst our 10 events are drawn from a normal population with a mean of 0.012 and a standard
deviation of 0.261.
18. We thank an anonymous referee for this suggestion.
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Appendix A
Table A1. Industry sector classifications
Code
Sector
G01
PRIMARY
–
–
–
–
A01
A02
A03
A04
G02
G03
–
–
–
–
ENERGY
GOODS
– A06
– A07
– A08
G04
G05
– Food and beverages
– Textile and apparel
– Intermediate and durables
PROPERTY
SERVICES
–
–
–
–
–
–
G06
Agriculture and fishing
Mining
Forestry and forest products
Building materials and construction
A10
A11
A12
A13
A14
A15
–
–
–
–
–
–
INVESTMENT
Source: New Zealand Investment Yearbook 2001
Transport
Ports
Leisure and tourism
Consumer
Media and telecommunications
Finance and other services