This document discusses the history of variance in minimum wage laws across US states from 1980 to 2010. It provides an overview of the conflicting views on the economic effects of minimum wages and reviews previous literature on the driving forces behind minimum wage laws. The document then presents current minimum wage rates and political indicators by state. Finally, it outlines the methodology to be used, which will involve regressing state-level panel data from 1980-2010 to analyze the political and economic factors influencing states' minimum wage laws over time. The analysis aims to determine if states responded to economic conditions or political preferences in setting their minimum wage rates.

1. Explaining the History of Minimum Wage Law
Variance Across States
Corey Kozak
December 2014
Abstract
In recent years the variance in minimum wage laws across states, as well as the deviation
from the minimum wage set by the Federal government has been increasing in both nominal and
real terms. All the while the economic effects of wage floors remains a source of heavy debate.
Given this uncertainty it is unclear what would motivate some states to maintain minimum wage
rates that differ from the federal rate as well as from one another. This paper aims to identify the
political and economic drivers behind the minimum wage law variance among states throughout
recent history in an attempt to determine whether states have responded to economic conditions
with wage legislation, or if such laws are simply a result of political preferences and special
interest groups.

2. 1
Introduction
The effects that minimum wage laws have on poverty levels, income inequality, and
unemployment have long been a source of heavy debate. Since the Fair Labor Standards Act of
1938 first set the nationwide minimum wage at $0.25, economists have attempted to analyze the
impact that changes to minimum wage policies have had on the labor market. Over time, States
have gradually adopted minimum wage laws of their own that regularly exceed the rates set by
the Federal government. According to the Department of Labor, in 1980 there were only three
states that enforced wage floors higher than the federal rate. By 1990 the number of states had
increased to nine, and by the turn of the century this number had risen to 13. All the while the
monetary amount that states deviated from the federal minimum and from each other (in both
nominal and real wage terms) steadily increased as well. Today there are 29 states with minimum
wage rates set higher than the federal minimum wage, which currently range from the federal
minimum at $7.25 up to $9.47 in Washington (DOL 2015).
While thorough research in the past few decades has been performed to examine the
effects that these minimum wage rates have had on the economy, evidence for the reasoning
behind this variance of wage laws from state to state is largely missing from the literature. The
fact that the research regarding the effects of minimum wage laws has shown mixed effects on
the labor market and the economy further motivates the need to understand states’ reasoning for
choosing their particular minimum wage. Particularly, have states’ minimum wage laws
historically been driven by economic factors such as poverty and income inequality, or has this
variance in wage floors simply been the result of political preferences and interest groups?
Similarly, why have some states historically been content with the wage laws set by the Federal
government while others have tended to regularly surpass these rates in favor of their own laws?

3. 2
Conflicting Views of the Effects of Minimum Wage Laws
To better understand the economics behind whether or not a government should choose
to impose and/or increase a minimum wage law, the two sides of the argument should first be
identified. Proponents of minimum wage laws suggest that a higher minimum wage reduces
income inequality via income redistribution (Levin-Waldman 2001). The objective of these
minimum wage laws is therefore to improve the living standards of those who earn the lowest
wages and consequently reduce poverty among these individuals (West and McKee 1980).
According to Bluestone and Harrison (2001), setting a higher standard for wages
increases the earnings of the lowest paid workers, therefore promoting a more equitable
distribution of wages and income. Thomas Volscho (2005) finds quantitative evidence that
reinforces this institutional economist argument. Through the analysis of decennial state level
data from 1960-2000, Volscho tests the hypothesis that states with higher minimum wages have
lower levels of family income inequality. Using the Gini coefficient as a measure of income
inequality, Volscho finds that increasing the state minimum wage is a potential method for states
to reduce family income inequality. He finds that this effect is non-linear, and that minimum
wages are ineffective at reducing inequality unless they are set sufficiently high in terms of real
wage rates.
On the other side of the debate, many economists believe that minimum wage laws, and
subsequent increases to minimum wages are detrimental to low wage workers due to the
potential reductions in employment and output that follow. A simple explanation for this is
founded by basic principles of microeconomics. An increase to the minimum wage rates
increases the cost of labor to low-wage employers, without increasing the productivity of the
workers. Therefore, firms will choose to utilize additional capital at the expense of labor in order

4. 3
to maximize their profitability. This substitution effect will result in low-wage laborers being laid
off, fired, or having their working hours reduced.
In addition to this effect, Brown (1940) points out that this increase in cost of production
would result in increased prices, which would then reduce demand for goods. This would lower
the demand for leading to even higher levels of unemployment. In an empirical analysis of these
employment effects, Neumark and Wascher (1992) use state-level panel data from 1973-1989 to
reevaluate the evidence of the effects that state minimum wages have on employment. From their
analysis, they determine that “a 10% increase in the minimum wage leads to a decline of 1-2% in
employment among teenagers, and a decline of 1.5-2% in employment for young adults”
(Neumark and Wascher 1992).
These results of these conclusions suggest that while minimum wage laws may indeed
decrease income inequality and poverty levels for those who are lucky enough to keep their jobs,
the policies also result in crowding out of low-wage workers resulting in higher unemployment
rates and potentially reductions in output. In light of these conflicting effects it comes of utmost
importance to determine whether these policies are developed in response to particularly high
levels of poverty and income inequality, or if they are instead the result of self-interest and
political motivations.
Literature Review of Driving Forces Behind Minimum Wage Laws
As was previously stated, most research involving the history of minimum wage laws has
examined the effects that such laws have had on the labor market and the economy. However, a
small amount of literature has attempted to identify some of the causal effects of minimum wage
law variances within a country. Specifically, Cox and Oaxaca (1982) look at labor unions and

5. 4
employer organizations within the states in particular in order to determine whether or not these
groups have significant impacts on minimum wage legislation. Using a median legislator utility
maximization model, Cox and Oaxaca provide the conclusion that an increase in organized labor
participation increases the probability that a state would establish a minimum wage.
Furthermore, they determine that the expected value of the minimum wage would be higher in
states with greater a greater extent of organized labor (Cox and Oaxaca 1982). Zavodny (1996)
examined state minimum wage laws as well, utilizing a multiple regression model that included
both economic and political variables. Her results show that Democratic Party strength has a
significant effect on whether or not a state increased its minimum wage in a given year.
Unfortunately, no other firm conclusions were able to be drawn.
Looking outside of the U.S. due to the usefulness of the methodologies involved in their
studies, Blais, Cousineau, and McRoberts (1989) draw upon Cox and Oaxaca’s findings when
examining the determinants of minimum wage rates in the Canadian provinces. Stating that Cox
and Oaxaca’s study was partially flawed due to its confined approach of using only a few
potential factors, Blais, Cousineau, and McRoberts develop a more comprehensive model which
examines the effects of women, youth, small business, and unions across nine Canadian
provinces from 1975-1982. Their conclusions suggest that minimum wage in the Canadian
provinces is higher when there are fewer women and young people in the labor force, where
there are less small businesses, when unemployment is low, and where the wage in the province
is below Canada’s average wage. They also point out that in the case of Canada as compared to
Cox and Oaxaca’s findings within the U.S., “organized pressure groups do not control policy
outputs. On the other hand, politicians do respond to the demands and needs of the constituents”
(Blais, Cousineau, McRoberts 1989, p.20)

6. 5
In a contrasting approach to the determinants of state minimum wage rates, Waltman and
Pittman (2002) develop a public policy approach within the states where they analyze the impact
of relative wealth, the strength of the Democratic Party, and the “ideological propensities” of the
public. Their model consists of a logistic regression where the dependent variable represents
whether or not a state in 1999 had a minimum wage that was higher than the federal minimum.
From this they are able to conclude that the citizens’ political ideologies have the most influence
on minimum wage rates, whereas relative wealth and the strength of the Democratic Party are
insignificant.
Finally, in what is arguably the most involved and comprehensive study on the topic to
date, Arnaud (2005) takes another approach toward analyzing provincial minimum wage laws
across Canada. Drawing upon insights from previous studies performed in both the U.S. and the
Canadian provinces, Arnaud develops a series of time-series cross-sectional analyses from 1976-
2003 in ten provinces to determine how political interest groups and the preferences of
policymakers affect the minimum wage rate.
After constructing a static model to examine the variance in minimum wage rates, he
determines that a dynamic model which captures the change in minimum wage laws across time
is the optimal approach, and thus develops a series of dynamic models to analyze the
determinants of the real minimum wage. His confounding conclusion is that union density
actually has a negative effect on provincial wage rates, which he then explains by stating “it is
possible that when labor movements are strong, their focus is on the collective agreement with
the employer but when labor movements are weak, their energy is dispensed in the political
arena” (Arnaud 2005, p.25).

7. 6
Present-Day Wage Conditions
Before delving into a detailed analysis of wage law variances across states, it is beneficial
to first gain an understanding of the current minimum wage conditions in the U.S. Table 1 below
breaks down the minimum wage rates by state and also includes political indicators that have
been suspected to drive minimum wage rates in previous study (Arnaud 2005). The political
indicators shown include the percentage of the workforce who are members of unions (as
reported by the Bureau of Labor Statistics), and the partisan control of the state’s legislature
(Democratic, Republican, or split) according to the National Conference of State Legislatures.
Additionally, this table includes an indicator specifying whether or not the state’s minimum
wage rate exceeded the federal minimum of $7.25 in 2014. An overview and discussion of this
data provides the present-day baseline from which further analysis and testing of hypotheses may
be performed.

8. 7
Table 1 – 2014MinimumWage Rates and Selected Political Indicators by State
State Abbr.
% of employed who
are members of
unions
2014 Nominal
Minimum Wage
Above Federal
Minimum
Partisan Comp. of State
Legislature
Alabama AL 10.8 7.25 NO Rep
Alaska AK 22.8 8.75 YES Rep
Arizona AZ 5.3 8.05 YES Rep
Arkansas AR 4.7 7.5 YES Rep
California CA 16.3 9 YES Dem
Colorado CO 9.5 8.23 YES Dem
Connecticut CT 14.8 9.15 YES Dem
Delaware DE 9.9 7.75 YES Dem
Florida FL 5.7 8.05 YES Rep
Georgia GA 4.3 7.25 NO Rep
Hawaii HI 21.8 7.75 YES Dem
Idaho ID 5.3 7.25 NO Rep
Illinois IL 15.1 8.25 YES Dem
Indiana IN 10.7 7.25 NO Rep
Iowa IA 10.7 7.25 NO Split
Kansas KS 7.4 7.25 NO Rep
Kentucky KY 11 7.25 NO Split
Louisiana LA 5.2 7.25 NO Rep
Maine ME 11 7.5 YES Dem
Maryland MD 11.9 8 YES Dem
Massachusetts MA 13.7 9 YES Dem
Michigan MI 14.5 8.15 YES Rep
Minnesota MN 14.2 8 YES Dem
Mississippi MS 3.7 7.25 NO Rep
Missouri MO 8.4 7.65 YES Rep
Montana MT 12.7 8.05 YES Rep
Nebraska NE 7.3 8 YES N/A
Nevada NV 14.4 8.25 YES Dem
New Hampshire NH 9.9 7.25 NO Split
New Jersey NJ 16.5 8.38 YES Dem
New Mexico NM 5.7 7.5 YES Dem
New York NY 24.6 8.75 YES Dem
North Carolina NC 1.9 7.25 NO Rep
North Dakota ND 5 7.25 NO Rep
Ohio OH 12.4 8.1 YES Rep
Oklahoma OK 6 7.25 NO Rep
Oregon OR 15.6 9.25 YES Dem
Pennsylvania PA 12.7 7.25 NO Rep
Rhode Island RI 15.1 9 YES Dem
South Carolina SC 2.2 7.25 NO Rep
South Dakota SD 4.9 8.5 YES Rep
Tennessee TN 5 7.25 NO Rep
Texas TX 4.8 7.25 NO Rep
Utah UT 3.7 7.25 NO Rep
Vermont VT 11.1 9.15 YES Dem
Virginia VA 4.9 7.25 NO Split
Washington WA 16.8 9.47 YES Dem
West Virginia WV 10.6 8 YES Dem
Wisconsin WI 11.7 7.25 NO Rep
Wyoming WY 6.7 7.25 NO Rep

9. 8
As can be seen in Table 1, there is a moderate level of variation between the minimum
wage laws amongst states. 29 of the 50 states have minimum wage rates set higher than the
federal minimum of $7.25, ranging up to $9.47 in Washington. Regarding the political
conditions of the states in 2014, 19 of the 50 states had Democratic partisan control of their
legislature, 26 had Republican control, and 5 were split. Speaking toward union membership
rates, average unionization across the states was 10.2% ranging from 2.2% in South Carolina to
22.8% in Alaska.
Simple analysis of these present-day conditions generates some very interesting results.
One of the most striking relationships to this static view of state minimum wage laws is that
100% of states with Democratic legislatures have minimum wages that are set higher than the
federal minimum wage. Additionally, analyzing union membership rates, 20 of the 29 states with
minimum wages higher than the federal minimum had unionization rates that exceeded the
10.2% interstate average. Both of these initial findings point toward a relationship between
minimum wage laws and political preferences or interest groups within the states.
However, while this view is useful for establishing the current condition of wages and
their relationship to political factors across states, it is important to note that this disregards the
relevant aspect of time. One cannot accurately assess these relationships without considering the
historical conditions of these states and their tendencies to set higher minimum wage rates.
Therefore, the remainder of this analysis will integrate the interstate variation of minimum wage
laws with political and economic conditions across a significant timeframe.

10. 9
Chart1
In a transition from the present day view to a dynamic view of wage law trends over time,
Chart 1 above compares the historical federal minimum wage rates to those of the States from
1980 to 2010. Comparing the federal minimum (in bold) to the state-specific trends it is clear
that the instances and magnitude of states adopting minimum wage laws that are higher than the
federal wage floor have been increasing over the years. From this graph it is also apparent that
the stagnant federal minimum wage of $5.15 from 1997 to 2006 caused many states to abandon
the federal law in favor of a higher minimum wage of their own in the latter years. However, the
driving factors behind specific states’ decisions to abandon the federal rate at these points in time
remain unclear. Therefore, the tendencies of states to adopt higher minimum wages than those
set by the Federal government, along with the variance amongst the states themselves merits
further empirical investigation.
*Federal minimum wagein bold

11. 10
Methodology
The framework for the empirical analysis of the political and economic factors that
influence state minimum wage laws involves regressions of state-level panel data from 1980 to
2010. This date range was chosen due to limitations on the availability of annual state level data,
and also due to a lack of significant state deviation from the federal minimum before this time.
As per Arnaud’s (2005) discussion involving the correctness of using the real minimum wage
over the relative minimum wage, the real minimum wage is the dependent variable involved in
the model specifications. The real minimum wage is calculated for each state in time period t
from 1980 to 2010 by dividing the nominal wage during that time period by the consumer price
index, obtained from the Department of Labor and U.S. Census Bureau respectively.
It should be noted that some states conceptually do not have a minimum a wage law of
their own. However, since the federal minimum wage supersedes the state minimum in states
with wage laws lower than the federal wage, the federal minimum wage in time t will act as the
baseline for such states. Another possible issue arises from the fact that since the minimum wage
is actually voted on a year before it goes into effect, the economic and political conditions must
be lagged by one time period. For simplicity and consistency all of the independent variables in
time period t-1 will be used to determine their effect on the state’s minimum wage law in time
period t.
Model 1
The first specification to the model involves OLS regression using the state real
minimum wage as the endogenous variable. Since we are particularly interested in understanding
why minimum wages vary across states throughout history (and less interested in the intrastate

12. 11
trends of these wages), the regression model contains time series fixed-effects. The technical
methodology behind these fixed-effects is the standardization of both the endogenous and
exogenous variables around their respective inter-state means within each time period. This
enables comparison of political and economic conditions between states while controlling for
overarching trends across time.
The first independent variable of interest is captured by the union membership rate as a
percentage of the labor force within the state and time observed, as is obtained from the
Department of Labor. If state minimum wage laws are motivated by self-interest groups, union
membership rates would most likely reflect this to the greatest extent. Since typical union
members are skilled/high-wage workers, a raise in the minimum wage would indirectly increase
the demand for union labor by increasing the cost of low wage labor (Cox and Oaxaca 1982).
Therefore, these organized labor groups are likely to lobby for higher wages in order to benefit
their own groups indirectly. Similarly, large businesses are likely to lobby for higher minimum
wages as well, since they tend to be owners of a greater portion of capital to labor than do small
businesses (Cox and Oaxaca 1982). Whereas higher minimum wages may increase the costs to
large businesses, their smaller competitors will be hit much harder due to their tendency to be
labor-dependent. Therefore, the percent of firms that have over 500 employees within each state
in period t-1 is included in the regression. Since both unions and large firms are expected to
lobby for higher minimum wages out of their own self-interest, union membership rates and the
number of large firms as a percentage of total firms is expected to be positively correlated with
the real wage within each state. If state minimum wage laws are influenced by these interest
groups, this will be captured by positive and significant coefficients for unions and large firms.

13. 12
Consequently, since small businesses are most likely to incur the highest costs of
minimum wage increases, one may expect to see states with a relatively high proportion of small
businesses lobbying against minimum wage increases. However, one might make an intuitive
argument against this case. First, small businesses may be less likely to organize and lobby than
large firms due to the disproportionately high transaction costs of doing so. Furthermore,
lobbying against minimum wage increases could severely damage the public image of the
businesses that partake in such practices. The public may make the assumption that the
businesses are refusing to pay their employees a higher wage, making them appear cheap or
untrustworthy. Knowing this, small businesses may be deterred from lobbying against wage
increases in order to maintain their public image. For the sake of completeness nonetheless, the
percentage of small firms within each state in period t-1 is included in the model. Small firms are
defined in this analysis in accordance with the Bureau of Labor Statistics definition, which
includes all firms with less than 20 employees.
In order to avoid collinearity between the exogenous indicators for firm size, the
categorization of ‘medium-sized’ firms, or firms with 20-500 people, will be excluded. It is
assumed that fluctuations in the percentage of average sized firms will have less of an impact on
state minimum wage rates than the relative proportion of small or large firms.
Next, to determine whether or not a state’s political stance in time period t-1 affects the
state’s minimum wage law in time t, an indicator representing Democratic control of the state
legislature in time period t-1 is included. Building on Zavodny’s (1996) method of assigning
variables to determine the state’s political stance at a particular time, a binary variable is used to
indicate whether or not there was a Democratic partisan composition within a state legislature by
year. If political ideology is an important determinant of state minimum wage laws, one would

14. 13
predict that there will be a positive correlation for the Democratic dummy variable, implying
higher minimum wage laws for states with Democratic majority in legislature.
Additionally, in order to analyze the potential economic determinants of state minimum
wage laws, the state-specific poverty rates for time period t-1 are included. If the true objective
of minimum wage law legislation is to help reduce poverty and income inequality then it should
follow that states with relatively high poverty rates and income inequality in previous periods
would adopt higher minimum wage laws than other states. As such, it is expected that there will
be a positive correlation between state minimum wage rates and poverty levels, as represented by
a positive and significant beta coefficient.
Due to the fact that each state’s wage in time period t builds upon their wage in t-1, a
lagged dependent variable is included in the regression (Arnaud, 2005). This will ensure that this
trend is captured in what will almost certainly be a highly significant and positive beta
coefficient.
Potential Endogeneity
It should be noted that this model is potentially subject to simultaneity bias if the
institutional economists’ argument regarding the effects of minimum wage laws on poverty and
income inequality holds true. If this is the case, the passage of a higher minimum wage in a state
within a particular time period will result in lower poverty levels and reduced income inequality
in a future time period. This decreased poverty and income inequality could then result in a
lower minimum wage increase in subsequent periods if states truly use higher minimum wages
as a tool to respond to high levels of income inequality and poverty. In this case, the observed
beta coefficients of poverty and the Gini values will be smaller in absolute value than in reality.

15. 14
Consequently, the unemployment rate variable is subject to a similar, but opposite effect.
States may choose to keep minimum wages low in period t if they see that unemployment is high
in t-1. While states will not technically set period t’s minimum wage lower than their wage in t-
1, choosing to keep their wage at the same rate actually results in a decrease to the real minimum
wage, since this means that wages are not keeping up with inflation. This decrease in real wage
in period t (the independent variable) may lead to a decrease in unemployment in future periods,
which would result in higher minimum wages in subsequent periods. As was the case with
poverty and income inequality, the beta coefficient will be smaller in absolute value within the
model than it is in reality due to simultaneity bias in this scenario.
These issues would need to be addressed using two-stage least squares regression to
correct for the endogeneity. The three instrumental variables involved need to be correlated with
changes in poverty, income inequality, and unemployment respectively, but uncorrelated with
the error term in the model. In other words, these variables will be correlated with said
independent variables, but will have no direct impact on the change in minimum wage laws over
time. Particular econometric tests would have to be performed in order to determine whether or
not the particular instrumental variables are a good fit for the model, but some instrumental
variables may be educational attainment, state spending, or proportion of the state population
that is African American.
Unfortunately, the true impact that minimum wage laws have on poverty rates remains a
source of complex debate. Therefore, further exploration of endogeneity between state wage
laws and poverty will remain a source for future study.

16. 15
Model 2
An additional specification of the dependent variable is run in the form of a logistic
regression. This involves a binary dependent variable which takes on a value of 1 if the state
passed a minimum wage law increase in a given year and 0 if its minimum remained constant.
As stated previously some states may not have technically had minimum wage laws during
certain years, but since the federal minimum wage supersedes the state wage in these cases, this
binary regression will suffice. This logistic regression will provide a look into the economic and
political conditions that raise or lower the probability of a state passing legislature for higher
minimum wages in any given year.
The same political and economic exogenous variables used in the first model
specification are also applied to this iteration. These include state level measures of union
participation, poverty rates, proportions of large and small firms, and an indicator for Democratic
majority of the state’s legislature. However, since this model aims to examine the factors that
have historically influenced the probability of a state adopting a higher minimum wage, the
state’s wage rate in period t-1 is excluded. In lieu of this variable is an indicator which reflects
whether or not the federal wage had been increased in the same year. It is assumed that there will
be an extremely strong correlation between this variable and the probability that the state wage
will increase. This is because an increase in the federal minimum will result in a direct increase
for any states that maintained a wage equal to the federal minimum wage. Therefore, the
inclusion of a dummy variable for years in which the federal rate was raised is essential for
capturing this effect.
Additionally, to accommodate for fixed effects within this model while maintaining
interpretability, both the endogenous and exogenous variables are standardized around their

17. 16
mean within each time period. As with the first model specification, this enables comparison
between states while controlling for overarching trends across time.
Empirical Results
Model 1
Table 2 : OLS Regression with Fixed Effects on State Real Minimum
Wages (1980-2010)
IndependentVariable Coefficient T-Statistic
(P-Value)
Correlation
Democraticlegislature(dummy) 0.0282 2.2523** Positive
(0.0245)
Proportionof firmswith> 500 employees 0.0116 1.4018 Positive
(0.1612)
Povertyrate -0.0052 -0.8825 Negative
(0.4109)
Proportionof firmswith< 20 employees 0.0137 1.6782* Positive
(0.09350)
Unionmembershiprate 0.0286 4.2233** Positive
(0.0002)
Real wage inpreviousyear(control) 0.8426 61.47** Positive
(0.0000)
1) * α ≤ 0.10; ** α ≤ 0.05
2) All explanatory variables were lagged oneperiodto moreaccurately reflectthecausalrelationship betweentheindicators andstatewage
laws.
3) Explanatory variables (excluding binary for Democratic legislature) werestandardizedaround their mean within each timeperiod.
Therefore, the coefficient measures thechange inthe realwage rate per one standard deviation increasein the explanatory variable.
First, the results from the OLS regression with fixed effects will be examined. These
results show the significance and direction of impact that the explanatory variables of interest
have against the states’ minimum wage rates. In order to accurately interpret the results from
table 2, emphasis must be placed upon the methodology behind the standardization of the
relevant explanatory variables and the implications for the model. Since these variables were
standardized across all states within each of the time periods, they reflect the difference from the
national mean for any given year. Standardization of these variables enables comparison of

18. 17
characteristics across states, while accounting for trends over time. Each state was given an equal
weight in their contribution to the averages across states.
It can be seen in table 2 above that the indicator for Democratic majority of a state’s
legislature is significant with a positive correlation. This suggests that part of the minimum wage
variance between states can be explained by the partisan control of their state legislature. These
results imply that states with a Democratic majority exhibit higher minimum wage laws than
those with Republican or split partisan control. Specifically, states that have Democratic control
of their legislature in the previous period have historically set minimum wage laws
approximately $0.03 higher (in real wage terms) than those with Republican or split partisan
control.
Furthermore, union membership rates were also found to be significant and positively
correlated with states’ minimum wages. States with union membership rates that are one
standard deviation higher than the mean for all of the states within a given time period set real
minimum wages $0.03 higher than those with average union membership rates. This suggests
that heightened labor union participation within a state does in fact lead to higher minimum wage
laws, albeit with small nominal impact. As organized labor groups have historically lobbied for
higher wages, these results could imply that greater union participation within a state leads to
more effective lobbying efforts. These lobbying efforts in turn may lead states to adopt higher
minimum wage laws than those with lower union participation rates.
Surprisingly this regression method found no statistically meaningful relationship
between minimum wage and the poverty level within a state. Although the implied driver for
state minimum wage laws is the reduction of poverty, these results suggest that states with

19. 18
relatively higher poverty rates are no more likely than others to adopt higher minimum wage
laws.
With regards to the prominence of large and small firms (identified in table 1 as
proportion of large firms and proportion of small firms respectively) it appears that large firms
have no significant impact on states’ minimum wages. This lack of significance may imply that
large firms are unlikely to devote time and resources toward lobbying for or against minimum
wage increases. However, an unsuspected finding resides in the fact that states’ proportion of
firms with less than 20 employees were found to be positively correlated with state minimum
wage laws at α ≤ 0.10.
As it is highly unlikely that small firms would lobby for higher minimum wage rates, this
suggests there is an underlying contributing factor that remains unseen. A potential explanation
is that, despite the exclusion of the proportion of mid-sized firms, collinearity still exists between
the proportion of large firms and proportion of small firms. To test this hypothesis the regression
was remodeled twice; once with the exclusion of the large firms group, and once with the
exclusion of the small firms group. As was expected, in both scenarios the explanatory variable
for proportion of large/small firms that remained in the model became statistically insignificant.

20. 19
Model 2
Table 3 : Logistic Regression with Fixed Effects – Probability of State minimum
wage increase in a given year (1980-2010)
IndependentVariable Pr > ChiSq Odds Ratio Estimate
Democraticlegislature(dummy) 0.0202** 1.577
Proportion of large firms (Standardized) 0.2447 1.167
Povertyrate (Standardized) 0.0137** 0.760
Proportionof small firms (Standardized) 0.1128 1.289
Unionmembershiprate (Standardized) 0.0312** 1.246
Federal wage Increase Year(control dummy) 0.0000** 133.137
1) * α ≤ 0.10; ** α ≤ 0.05
2) All explanatory variables were lagged oneperiodto moreaccurately reflectthecausalrelationship betweentheindicators andstatewage
laws. Furthermore, explanatory variables arestandardized about themean across states within each time period where applicable.
The results of the logistic regression involving the probability that a state will increase
their minimum wage in a given month will now be examined. The most striking, but also
intuitively sound result from this regression can easily be appointed to the indicator for whether
or not the federal minimum wage was increased in a given year. The Wald Chi-Squared statistic,
which was used as the test of significance of a coefficient, showed that the null hypothesis was to
be rejected with a staggeringly high level of confidence. As was specified previously, the federal
minimum is recognized as the baseline for any state minimum wage. Therefore, if the federal
minimum wage increases then any states that set their wages to the federal rate will see an
increase in their wage floor as well.
As was true with the OLS regression method, union membership rates again show high
levels of significance. With an odds ratio estimate of 1.25, this implies that higher union

21. 20
membership rates within a state within a given year (when compared against other states) will
make the state more likely to adopt a higher minimum wage than if the union participation within
that state was at the national average. Specifically, if a state exhibits union participation rates that
are one standard deviation greater than the mean across all states within a given period, that state
will be 1.25 times more likely than average to adopt a higher minimum wage in that year.
Similarly, the indicator for Democratic majority of a state’s legislature is also significant
within this model. According to the odds ratio estimate, states with Democratic legislatures are
1.5 times more likely to pass higher minimum wage laws than those with Republican or split
partisan control of their legislature. This again follows the intuition that lobbying by political
parties has a strong influence on minimum wage law decisions.
Finally, in contrast with the OLS regression method, the logistic regression found that the
standardized poverty rates were statistically significant with a high degree of confidence.
Furthermore, these results actually suggest an inverse relationship between poverty rates and the
probability that the state will pass a law to increase the minimum wage. Specifically, if a state’s
poverty levels are one standard deviation above the mean then their odds of increasing their
minimum wage fall to 0.760 times of what they would be otherwise. While this fails to follow
intuition for the motivation of minimum wage law increases, this may be partially explained by
the endogeneity issues that were outlined previously.
Conclusion
In spite of long-lasting economic debate, state governments across the country have
continued to increase minimum wage laws at rates exceeding those set by the Federal
government. Could it be that state governments have carefully weighed the possibilities of

22. 21
reduced employment against the opportunity for reducing poverty and income inequality in
determining minimum wage laws? Or could other factors be driving such decisions? While these
questions will undoubtedly remain difficult to answer concretely, this paper has attempted to
expand upon the progress made by previous economists.
Using the logistic specification of the model previously described, one should be able to
obtain a better understanding of the economic and political conditions that have historically
driven states to adopt higher minimum wage laws within a given period. Adding to this, the
regressions utilizing real minimum wage rates as the dependent variable help to explain how the
same conditions have impacted the variance of wage floors between states. If the states truly use
minimum wage laws as a responsive tool to fight high poverty and income inequality, these
economic indicators should have prevailed as driving forces for the variance in wage laws
amongst states.
However, these models suggest that as with many other areas of politics, higher
minimum wage laws could simply be the result of self-interested unions and political groups.
This provides reinforcement to the literature thus far that has found political motivations behind
U.S. state minimum wage laws, and would also explain why states continue to disregard the
possibility that higher minimum wages may cause higher unemployment (Cox and Oaxaca 1982;
Seltzer 1995; Zavodny 1996).
Finally, as variances in state minimum wage laws are apparently significantly correlated
with political and interest-group determinants as was anticipated, it may then be interesting to
consider why results from the previously referenced studies in the Canadian provinces have
come to a different conclusion altogether about their country (Blais, Cousineau and McRoberts
1989; Arnaud 2005). Could it be that state governments have simply been subject to greater

23. 22
political pressures than their northern counterparts when it comes to minimum wage laws? Has
the influence of politics and interest groups between the states and provinces varied in other
areas of legislation as well? Such determinations would undoubtedly involve an expansive
comparative study between the standards for setting minimum wage laws across countries.

24. 23
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