Explaining the History of Minimum Wage Law Variance Across States

Corey KozakDecember 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.

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?

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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

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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

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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)

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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).

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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.

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Table 1 – 2014 Minimum Wage Rates and Selected Political Indicators by State

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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 RepAlaska AK 22.8 8.75 YES RepArizona AZ 5.3 8.05 YES RepArkansas AR 4.7 7.5 YES RepCalifornia CA 16.3 9 YES DemColorado CO 9.5 8.23 YES DemConnecticut CT 14.8 9.15 YES DemDelaware DE 9.9 7.75 YES DemFlorida FL 5.7 8.05 YES RepGeorgia GA 4.3 7.25 NO RepHawaii HI 21.8 7.75 YES DemIdaho ID 5.3 7.25 NO RepIll inois IL 15.1 8.25 YES DemIndiana IN 10.7 7.25 NO RepIowa IA 10.7 7.25 NO SplitKansas KS 7.4 7.25 NO RepKentucky KY 11 7.25 NO SplitLouisiana LA 5.2 7.25 NO RepMaine ME 11 7.5 YES DemMaryland MD 11.9 8 YES DemMassachusetts MA 13.7 9 YES DemMichigan MI 14.5 8.15 YES RepMinnesota MN 14.2 8 YES DemMississippi MS 3.7 7.25 NO RepMissouri MO 8.4 7.65 YES RepMontana MT 12.7 8.05 YES RepNebraska NE 7.3 8 YES N/ANevada NV 14.4 8.25 YES DemNew Hampshire NH 9.9 7.25 NO SplitNew Jersey NJ 16.5 8.38 YES DemNew Mexico NM 5.7 7.5 YES DemNew York NY 24.6 8.75 YES DemNorth Carolina NC 1.9 7.25 NO RepNorth Dakota ND 5 7.25 NO RepOhio OH 12.4 8.1 YES RepOklahoma OK 6 7.25 NO RepOregon OR 15.6 9.25 YES DemPennsylvania PA 12.7 7.25 NO RepRhode Island RI 15.1 9 YES DemSouth Carolina SC 2.2 7.25 NO RepSouth Dakota SD 4.9 8.5 YES RepTennessee TN 5 7.25 NO RepTexas TX 4.8 7.25 NO RepUtah UT 3.7 7.25 NO RepVermont VT 11.1 9.15 YES DemVirginia VA 4.9 7.25 NO SplitWashington WA 16.8 9.47 YES DemWest Virginia WV 10.6 8 YES DemWisconsin WI 11.7 7.25 NO RepWyoming WY 6.7 7.25 NO Rep

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.

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Chart 1

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

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*Federal minimum wage in bold

set by the Federal government, along with the variance amongst the states themselves merits

further empirical investigation.

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

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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

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

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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.

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

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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

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

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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.

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.

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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.

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Additionally, to accommodate for fixed effects within this model while maintaining

interpretability, both the endogenous and exogenous variables are standardized around their

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)

Independent Variable Coefficient T-Statistic (P-Value)

Correlation

Democratic legislature (dummy) 0.0282 2.2523** Positive(0.0245)

Proportion of firms with > 500 employees 0.0116 1.4018 Positive(0.1612)

Poverty rate -0.0052 -0.8825 Negative(0.4109)

Proportion of firms with < 20 employees 0.0137 1.6782* Positive(0.09350)

Union membership rate 0.0286 4.2233** Positive(0.0002)

Real wage in previous year (control) 0.8426 61.47** Positive(0.0000)

1) * α ≤ 0.10; ** α ≤ 0.052) All explanatory variables were lagged one period to more accurately reflect the causal relationship between the indicators and state wage laws.3) Explanatory variables (excluding binary for Democratic legislature) were standardized around their mean within each time period. Therefore, the coefficient measures the change in the real wage rate per one standard deviation increase in 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

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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

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

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state minimum wage laws is the reduction of poverty, these results suggest that states with

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.

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Model 2

Table 3 : Logistic Regression with Fixed Effects – Probability of State minimum wage increase in a given year (1980-2010)

Independent Variable Pr > ChiSq Odds Ratio EstimateDemocratic legislature (dummy) 0.0202** 1.577

Proportion of large firms (Standardized) 0.2447 1.167

Poverty rate (Standardized) 0.0137** 0.760

Proportion of small firms (Standardized) 0.1128 1.289

Union membership rate (Standardized) 0.0312** 1.246

Federal wage Increase Year (control dummy) 0.0000** 133.137

1) * α ≤ 0.10; ** α ≤ 0.052) All explanatory variables were lagged one period to more accurately reflect the causal relationship between the indicators and state wage laws. Furthermore, explanatory variables are standardized about the mean 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.

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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

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

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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

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

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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

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.

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References

Arnaud, S. (2005) “The Rise and Fall of provincial Minimum Wages: Labor Movements,

Business Interests and Partisan Theory.” Paper presented at the 2005 Annual

Conference of the Research Committee on Poverty, Social Welfare and Social Policy.

International Sociological Association, Northwestern University, Chicago, Illinois

Blais, A., Cousineau, J., and McRoberts, K. (1989) “The Determinants of Minimum Wage

Rates.” Public Choice, 62, 15-24.

Brown, W. M. (1940). “Some effects of the minimum wage upon on the economy as a whole.”

The American Economic Review, 30, 98-107.

Cox, J., and Oaxaca, R. (1982) “The Political Economy of Minimum Wage Legislation.”

Economic Inquiry, 20, 533-555.

Frank, M. (2008) "A New State-Level Panel of Annual Inequality Measures Over the Period 1

916-2005." Working Papers 0802, Sam Houston State University, Department of

Economics and International Business.

Neumark, D., and Wascher, W. (1992) “Employment Effects of Minimum and Subminimum

Wages: Panel Data on State minimum Wage Laws.” Industrial and Labor Relations

Review, 46, 55-81.

Seltzer, A. (1995) “The Political Economy of the Fair Labor Standards Act of 1938.,” Journal of

Political Economy, 103, 1302-41.

United States Department of Labor. (2015) “Changes in Basic Minimum Wages in Non-Farm

Employment Under State Law: Selected Years 1968 to 2013.” Prepared by Office of

Communications, Wage and Hour Division. Available online: [www.dol.gov].

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Waltman, J., and Pittman S. (2002) “The Determinants of State Minimum Wage Rates: A Public

Policy Approach.,” Journal of Labor Research, 23, 51-6.

West, E.G., and McKee, M. (1980). “Minimum Wages: The New Issues in Throey, Evidence,

Policy, and Politics.” Ottawa: Economic Council of Canada.

Volscho, T. (2002) “Minimum Wages and Income Inequality in the American States, 1960-

2000.” Research in Social Stratification and Mobility, 23, 343-368

Zavodny, M. (1996) “The Minimum Wage: Maximum Controversy over a Minimum Effect?”

PhD. Dissertation, Massachusetts Institute of Technology.

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