The Impact of Minimum Wage Indexing: Employment and Wage Evidence from Oregon and Washington more

THE IMPACT OF MINIMUM Eric Fruits, Ph.D. Economics International Corp. WAGE INDEXING: Employment and Wage Evidence from Oregon and Washington Electronic copy available at: http://ssrn.com/abstract=1461764 T he Employment Policies Institute (EPI) is a nonprofit research organization dedicated to studying public policy issues surrounding employment growth. In particular, EPI research focuses on issues that affect entry-level THE IMPACT OF MINIMUM from Oregon and Washington employment. Among other issues, EPI research has quantified the impact of new labor costs on job creation, explored the connection between entry-level employment and welfare reform, and analyzed the demographic distribution of mandated benefits. EPI sponsors nonpartisan research that is conducted by independent economists at major universities around the country. WAGEandINDEXING: Employment Wage Evidence Dr. Eric Fruits is an economist specializing in quantitative analysis market and policy issues. He is president of Economics International Corp. and an adjunct professor at Portland State University. Dr. Fruits has worked on a wide range of projects covering a variety of public policy issues. He has evaluated the economic impacts of state public employee retirement system reforms and provided testimony to the Oregon Supreme Court. Dr. Fruits has been invited to testify before legislative bodies on the economics of climate change legislation, education tax credits, health care and health insurance policies, and state revenue programs. Dr. Fruits has published peer-reviewed papers on a wide range of topics in economics, nance, and regulation. His op-eds and letters have been published in a variety of places, including e Economist. In addition to consulting, he has been a professor at Portland State University, the University of Southern California, Indiana University, and the Claremont Colleges, where he has taught business, economics, nance, and statistics courses. Eric Fruits, Ph.D. Economics International Corp. 1090 Vermont Avenue, NW Suite 800 Washington, DC 20005 Electronic copy available at: http://ssrn.com/abstract=1461764 THE IMPACT OF MINIMUM from Oregon and Washington Eric Fruits, Ph.D. Economics International Corp. WAGEandINDEXING: Employment Wage Evidence Table of Contents Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Impact of Minimum Wage Indexing on Employment and Wages. . . . . . . . . . . . . . . . . . . . . . . 5 Background and Previous Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Oregon and Washington . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Hypothesis and an Empirical Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Model and Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 THE IMPACT OF MINIMUM from Oregon and Washington WAGEandINDEXING: Employment Wage Evidence formation covers the period in which both Oregon and Washington have indexed their minimum wages. e data provide su cient detail for individuals in Oregon, Washington, and other states; thus, di erences in and changes to the wage and employment distribution can be tested statistically. e model used in this study accounts for the possibility that factors a ecting whether an individual is employed also a ect the hourly wage earned. Rather than assuming that younger individuals are di erentially affected by the minimum wage and minimum wage indexing, this study tests and quanti es minimum wage impacts by age. Executive Summary M inimum wage increases are a hot-button issue in many states. On the one hand, the minimum wage is o en cited as a textbook example of how price oors create surpluses in which too many workers chase too few jobs, especially among those applicants with the fewest skills. On the other hand, proponents of raising the minimum wage suggest that increases are virtually painless. Because minimum wage increases can be politically challenging to implement, many states have introduced minimum wage indexing. With indexing, the minimum wage increases automatically each year based on some measure of in ation. e goal of this research is to evaluate quantitatively the economic e ects of minimum wage indexing, with a focus on Oregon and Washington’s experience. Impacts are quanti ed by how they a ect (1) employment and (2) hourly wages for hourly workers. e project uses wage data from the annual March Current Population Surveys (CPS) covering the period 2003–2008 for Oregon, Washington, and their neighboring states (California, Idaho, and Nevada). is in- Key Findings Higher minimum wages in Oregon and Washington are associated with reduced employment: Regression results indicate that Oregon and Washington’s higher minimum wages are associated with a statistically signi cant reduced probability of being employed. Younger members of the labor force are more likely to be adversely a ected by increases in the minimum wage and minimum wage indexing: Oregon and Wash- The Impact of Minimum Wage Indexing Employment Policies Institute 3 ington’s indexing policy produces annual increases in the minimum wage that, in turn, are likely to increase unemployment, especially among the young. Higher minimum wages have no statistically signi cant impact on wages of Oregon and Washington hourly wage earners: Regression results indicate that, controlling for employment impacts, increasing minimum wages has no statistically or economically signi cant impact on income. us, minimum wage indexing imposes employment costs with no measurable income bene ts. Employment Policies Institute Impact of Minimum Wage Indexing on Employment and Wages: Evidence from Oregon and Washington Minimum wage increases are a contentious issue in many states. Because minimum wage increases can be politically challenging to implement, many states have introduced minimum wage indexing. With indexing, the minimum wage increases automatically each year based on some measure of in ation. Washington voters were the rst to adopt an indexing provision, voting in 1998 to increase the state’s minimum wage to $6.50 per hour by January 1, 2000. Starting in 2001, the state’s Department of Labor and Industries began making annual adjustments to the minimum wage each year based on the federal Consumer Price Index (CPI). In January 2009, Washington’s minimum wage increased to $8.55 an hour, or $2.00 more than the federal minimum wage of $6.55. In November 2002, Oregon voters passed Measure 25, which increased Oregon’s minimum wage to $6.90 per hour e ective January 1, 2003. In addition to the increase, the ballot measure requires the State’s Bureau of Labor and Industries to annually adjust the minimum wage for in ation based on a rise in the CPI. e annual adjustment is to be calculated every September, rounded to the nearest ve cents, and becomes e ective the following January. In January 2009, Oregon’s minimum wage increased to $8.40 an hour, or $1.85 more than the federal minimum wage. In addition to Washington and Oregon, eight other states increase the minimum wage in line with some measure of in ation: Arizona, Colorado, Florida, Missouri, Montana, Nevada, Ohio, and Vermont. e cities of San Francisco, California, and Santa Fe, New Mexico, also have minimum wage indexing. Neoclassical economists cite the minimum wage as a textbook example of how price oors create surpluses in which too many workers chase too few jobs. ese job impacts chie y a ect younger and less skilled applicants. Signaling theory suggests that high or increasing minimum wages send signals to business that a state may have other regulations that are unfavorable to businesses. In this way, even employers who do not hire low-wage workers would prefer to locate or expand in states with more favorable minimum wages and other business regulations. In contrast, proponents of raising the minimum wage suggest that increases are virtually painless. Proponents argue that businesses may exert market power in labor or product markets or that increased labor costs are costlessly passed on to consumers or other businesses. e goal of this research is to evaluate quantitatively the economic e ects of minimum wage indexing, with a focus on Oregon and Washington’s experiences. Impacts are quanti ed by how they a ect (1) employment and (2) hourly wages for hourly workers. e project uses wage data from the annual March Current Population Surveys (CPS) covering the period 2003–2008 for Oregon, Washington, and their neighboring states (California, Idaho, and Nevada). is information covers the period in which Oregon and Washington both indexed their minimum wage rates. e data provide su cient detail for individuals in Oregon, Washington, and other states that di erences in and changes to the wage and employment distribution can be tested statistically. Minimum wages for California, 1 Idaho’s minimum wage is equal to the federal rate; Nevada began indexing in November 2006. The Impact of Minimum Wage Indexing Employment Policies Institute 4 Employment Policies Institute The Impact of Minimum Wage Indexing 5 Figure 1: Minimum Wage Rates, California, Oregon, Washington, and Federal, 2000–2008 8.50 8.00 Minimum Wage ($/hour) 7.50 7.00 6.50 6.00 5.50 5.00 Low wage workers make up a relatively small portion of employment in the Paci c Northwest. For example, in Oregon, approximately 25 percent of the workforce are employed in a “low-wage” job, and less than 5 percent of the workforce have “low-wage” jobs as their only employment.2 Oregon and Washington have persistently had high unemployment rates. In many of the past 30 years, Oregon and Washington have ranked in the top 10 states for unemployment. In addition to the states’ high and annually increasing minimum wages, several other factors explain these states higher and persistent unemployment. For example, both Oregon and Washington have relatively “generous” unemployment bene ts. In addition, Oregon and Washington have relatively high rates of in-migration, adding to competition for employment opportunities. Oregon has a reputation for rigid employment laws and health insurance mandates that add to rms’ costs of growing their workforces. Studies focusing on teenage employment are relatively consistent in nding that a 10 percent increase in the minimum wage would be associated with a 1 percent to 4 percent decrease in teenage employment.4 Research suggests that minimum wage impacts may take a year to a ect employment. For example, Currie and Fallick (1996) nd that employed individuals who were a ected by an increase in the minimum wage are less likely to be employed a year later, even a er accounting for the fact that workers employed at the minimum wage may di er from their peers in unobservable ways. Some studies nd little evidence of employment losses.5 In fact, in contrast to the predictions of neoclassical economic theory, some studies nd that employment increases as the minimum wage increases. For example, all seven of the studies in Card and Krueger (1995) nd that higher minimum wages lead to increase employment, but in only two of the studies are the increases statistically signi cant.6 Typically, these studies rely on ad hoc theories that assume employers exercise market power in the labor market or the product market. In other words, as noted by Neuberg (1997), the approach taken by Card and Krueger (1995) assumes that employers have the power to set wages or prices in a relatively uncompetitive market rather than a theory that assuming that employers take wages and prices as given in a relatively competitive market. Federal California Oregon Washington Oregon, and Washington, and the federal rate are shown incomes occur without any counterbalancing increase in in Figure 1.1 the number of people entirely unemployed or employed less advantageously than they otherwise would be. For e model used in this study accounts for the possibility example, Lester (1946) hypothesizes that it would be that factors a ecting whether an individual is employed possible that a higher minimum wage would not have also a ect the hourly wage earned. the negative employment consequences predicted by neoclassical economics. Background and Previous Research Friedman (1953) suggests that debates on the minimum wage are based on di erences in predictions or beliefs about how well a minimum wage would help attain a particular income or employment goal. He notes that those in favor of increasing minimum wages believe that the increases reduces poverty by raising the incomes of those receiving less than the increased minimum wage. In many cases, proponents also believe that some workers receiving the minimum wage also may experience increased incomes. Proponents believe that the increased 6 Employment Policies Institute The Impact of Minimum Wage Indexing Friedman (1953) notes that opponents of increasing minimum wages believe that doing so would increase poverty by increasing the number of people who are unemployed or employed less advantageously and that this more than o sets any favorable e ect on the wages of those who remain employed. For example, Stigler (1946) hypothesizes that if a minimum wage is e ective, one of the potential e ects is that workers whose services are worth less than the minimum wage are discharged and are unemployed or, retired, or enter unregulated elds of employment (the “shadow economy”). Much of the earlier empirical research supports the hypothesis that increasing minimum wages are associated with reduced employment. For example, Peterson (1957) is one of the rst empirical studies of the minimum wage. He found that in each of the three industries evaluated (sawmills, men’s cotton garments, and seamless hosiery) minimum wages reduced employment. Peterson (1959, 1960) nds that in retail, laundry, and dry cleaning industries, higher retail wages for women are associated with reduced employment of women. Gallasch (1975) and Gardner (1981) nd some evidence that the agricultural Recent studies are more consistent with the neoclassical minimum wage causes negative employment and positive theory that increasing minimum wages tend to be associated with decreased employment. Neumark and wage e ects.3 Moore and Peniston (2005) consider anyone who earned less than $8 an hour in 2003 to be a “low wage” worker. Adilov (2008) provides an overview of several key empirical studies on the e ects of the minimum wage on employment and discusses the controversy related to the empirical methods and the ndings. 4 See, for example, Brown (1988); Neumark and Wascher (1992, 1994, 2000, 2008); Kim and Taylor (1995); Williams (1993). For international comparisons, see Abowd et al. (2000); Neumark et al. (2004). 5 See, for example, Katz and Krueger (1992); Card (1992a,b). 6 See also Card (1992b); Katz and Krueger (1992); Card and Krueger (1994) for earlier versions of the studies provided in Card and Krueger (1995). 2 3 The Impact of Minimum Wage Indexing Employment Policies Institute 7 Wascher (2006) review more than 90 empirical studies on the employment e ects of minimum wages that was spurred by the “new minimum wage research” of Card, Katz, and Krueger. Neumark and Wascher nd that the overwhelming majority of the studies surveyed give a relatively consistent—although not always statistically signi cant—indication of the negative employment e ects of minimum wages. Moreover, among the studies providing the most credible evidence, almost all indicate negative employment e ects. More recently, Wessels (2007) applied one of the models outlined in Card and Krueger (1995) to the 1996–1997 federal minimum wage increase and found that increases in the minimum wage signi cantly lowered teenage employment rates. female employment was not counterbalanced by increases in wages to the remaining working women. Singell and Terborg (2007) note that Oregon and Washington voter initiatives raised the minimum wage over three successive years by approximately 37 percent in both states. Using monthly Bureau of Labor Statistics (BLS) wage data, Singell and Terborg (2007) nd that Oregon and Washington’s successive minimum wage increases lowered employment growth in Oregon and Washington. Eating and drinking establishments experienced more signi cant impacts than the hotel and lodging industry. Earlier studies note that employment e ects of the minimum wage are sensitive to the wage distribution in the industry prior to the introduction of the minimum wage (Neumark et al., 2004; Yuen, 2003). Because wages in eating and drinking establishments typically are lower than in the hotel and lodging industry, Singell and Terborg’s (2007) ndings are consistent with these earlier studies. All Observations Hourly wage Labor force Unemployed Age Black Never married High school or higher Bachelor’s degree or higher Graduate degree Food occupation Retail occupation California Idaho Nevada Oregon Washington Workers With Hourly Wage > 0 Hourly wage Age Black Never married High school or higher Bachelor’s degree or higher Graduate degree Food occupation Retail occupation California Idaho Nevada Oregon Washington Table 1: Descriptive Statistics Mean 1.00 0.50 0.04 32.88 0.05 0.48 0.56 0.17 0.05 0.03 0.02 0.59 0.08 0.12 0.09 0.12 14.63 37.92 0.05 0.33 0.82 0.17 0.03 0.08 0.06 0.52 0.10 0.13 0.10 0.15 Std. Dev. 4.38 0.50 0.20 21.32 0.22 0.50 0.50 0.38 0.22 0.16 0.15 0.49 0.28 0.32 0.29 0.32 9.00 13.26 0.22 0.47 0.39 0.37 0.18 0.27 0.24 0.50 0.30 0.34 0.30 0.35 Obs. 115,483 186,285 186,285 186,285 186,285 186,285 186,285 186,285 186,285 186,285 186,285 186,285 186,285 186,285 186,285 186,285 7,885 7,885 7,885 7,885 7,885 7,885 7,885 7,885 7,885 7,885 7,885 7,885 7,885 7,885 Some studies hypothesize that the impacts of minimum wage increases are passed through to consumers via higher prices. For example, Aaronson and French (2006) nd that food prices at limited service restaurants increase in the two months following a minimum wage increase. In contrast, other studies, such as Katz and Krueger (1992) nd no relationship between output prices and minimum In addition to the BLS wage data, Singell and Terborg wage increases. (2007) evaluate want ads collected from the Portland Oregonian and the Seattle Times for speci c eating and drinking and hotel and lodging jobs over the same period Oregon and Washington as the employment data. Want-ad regressions indicate Peterson (1959) revisits one of the rst studies of the that the minimum wage initiatives reduced the number impact of minimum wage on employment, a study of of job vacancies (and related hiring e orts), particularly Oregon retail stores in 1913–1915. Minimum wage rates for those jobs for which the minimum wage is relatively for females employed in Oregon retail stores became binding. e ective between October 1913 and February 1914. e minimum wage di ered by age, level of experience, and location. Women over 18 or with more experience had a Hypothesis and an Empirical Test e approach taken in this study is to test two related higher minimum wage than younger and inexperienced women. Women in the City of Portland had a higher hypotheses regarding the impact of increasing minimum e primary minimum wage than women working elsewhere in the wages on employment and wages. state. Peterson (1959) nds that female retail employment innovations that are o ered in the current study are to declined in the wake of the minimum wage law and that evaluate the impacts of indexing the minimum wage female payrolls declined. In other words, the decline in to some measure of in ation and the use of statistical controls to simultaneously account for employment and wage impacts. e null hypotheses are as follows: 1. ere is a negative relationship between the minimum wage and employment. In other words, As noted earlier, several published studies have found increases in the minimum wage are associated that increasing minimum wages are associated with with decreases in employment. The Impact of Minimum Wage Indexing Employment Policies Institute 2. A er accounting for employment e ects, there is a positive relationship between the minimum wage and hourly workers’ hourly wages. 8 Employment Policies Institute The Impact of Minimum Wage Indexing 9 Figure 2: Age and Unemployment Rates, Ages 15–65, 2003–2008 20.00 50% Figure 3: Age and Hourly Wage Rates, Ages 15–65, 2003–2008 18.00 16.00 Average Wage Rate ($/hour) 40% Unemployment Rate 14.00 12.00 10.00 8.00 6.00 4.00 2.00 30% 20% 10% 0% 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 California, Idaho, Nevada, Oregon, Washington California, Idaho, Nevada, Oregon, Washington decreased employment and increased wages for those who are employed. e approach in this study is an extension of these earlier studies (Brown, 1988; Neumark and Wascher, 1992, 1994, 2000; Kim and Taylor, 1995; Williams, 1993; Currie and Fallick, 1996). e following sections describe data used and a two-step procedure described by Heckman (1979), Maddala (1983), and Amemiya (1985) that rst examines the employment impacts and then examines the factors determining the hourly wage for hourly workers. Speci cally, the following are examined: e project uses wage data from the annual March Current Population Surveys (CPS) covering the period 2003– 2008 for Oregon, Washington, and their neighboring states (California, Idaho, and Nevada). is information covers the period in which Oregon and Washington both indexed their minimum wage rates. e data provide su cient detail for individuals in Oregon, Washington, and other states; thus, di erences in and changes to the wage and employment distribution can be tested statistically. e data include variables measuring individual 1. Whether the probability that an individual is demographic and employment characteristics. Descriptive employed is a function of individual and statestatistics are provided in Table 1. e variables used in speci c characteristics. this analysis are described in the appendix. 2. e extent to which the minimum wage a ects hourly wages a er controlling for the Hourly wage is the dependent variable of interest and is interdependence between employment and wages. the dependent variable in the impact regression. Whether an individual is employed is a dependent variable in the selection regression and an independent variable in the impact regression. Both employment and wages are a function of several factors. To evaluate the relationships between the minimum wage and employment and hourly wages, it is important to control for other factors that may explain employment and wages. For example, age is widely cited as a factor that determines both employment (Figure 2) and wages (Figure 3),7 as minimum wage workers tend to be young. In the U.S., workers under age 25 represent only about one- h of hourly-paid workers and make up half of those paid the federal minimum wage or less.8 us, youth is an indicator variable to control for the di erential impacts of age on younger workers. Oregon’s employment department has similarly concluded that 7 8 “undoubtedly, many of the state’s low-wage workers are also young” (Moore and Peniston, 2005). Similarly, senior is an indicator variable to control for the di erential impacts of age on older workers. Female workers are more likely to earn the minimum wage. While the percentage of workers earning the minimum wage does not vary much across the major race and ethnicity groups, many researchers believe race to be an important factor a ecting employment and wages, and whether an individual earns the minimum wage. Education is positively related to wages and employment. Never married workers, who tend to be young, are more likely than married workers to earn the federal minimum wage or less. is variable controls for both age and for See the appendix for a discussion of employment and unemployment as used in this study. See Bureau of Labor Statistics (2009a) for information on U.S. workers. 10 Employment Policies Institute The Impact of Minimum Wage Indexing The Impact of Minimum Wage Indexing Employment Policies Institute 11 other unobservable characteristics that may a ect employment and wages. By major occupation, the highest proportion of workers earning at or below the federal minimum wage is in service occupations, especially food preparation and service and retail. e data used include control variables to take into account unobservable state factors; year accounts for year-to-changes in the economy that are independent of changes to the minimum wage. While such measures are imperfect, Burkhauser et al. (2000) suggest that alternative variables such as macroeconomic factors are inappropriate. Model and Results e model used in this study accounts for the possibility that factors a ecting whether an individual is employed also a ect the hourly wage earned. First, a probit model explaining the employment status is estimated, and the tted values from the probit model are included in the wage equation using ordinary least squares as follows. Results are presented in Table 2.9 As predicted by neoclassical theory, Oregon and Washington’s relatively high minimum wages disproportionately a ect younger workers (under 25 the probit with the following equation: years of age). e high minimum wage rates triggered EMPLOYED = X1 β1 + MINWAGE β2 + u1 (1) by annual indexing result in an unintended dilemma for these lower skilled applicants: eir inexperience makes the ordinary least squares regression, where FIT them unemployable at the higher minimum wage, but they cannot get experience to justify the higher wage. denotes the tted values from Step 1. WAGE = X3 β3 + FIT β4 + MINWAGE β5 + u2 (2) signi cant reduced probability of being employed, but they do not have a signi cant impact on hourly wages. To illustrate the magnitude of the employment impacts, the tted value of the probit model is recalculated under the assumption that every state is subject to the federal minimum wage, which is no higher than any of the state minimum wages in the study. Figure 4 shows that if Oregon and Washington were subject to the lower federal minimum wage, the unemployment rate (as measured in this study) would be more than 2 percentage points lower. Over the period 2003–2008, Oregon’s average employment rate was 9.0 percent; if Oregon’s minimum had been equal to the lower federal minimum wage rate, then the state’s unemployment rate would have been 6.2 percent. Similarly, over the same period, Washington’s average employment rate was 8.4 percent; if Washington’s minimum had been equal to the lower federal minimum wage rate, then the state’s unemployment rate would have been 5.6 percent. Table 2: Regression Results Dependent Variable: Employed Method: ML - Binary Probit (Quadratic hill climbing) Included observations: 93816 Variable Coefficient Intercept -112.061 Year 0.057 Female -0.110 Black -0.310 Never married -0.190 High school 0.298 Bachelor’s degree 0.186 Graduate 0.139 Youth -2.037 Senior 1.829 Age 0.001 Youth * Age 0.087 Senior * Age -0.032 California 0.039 Idaho 0.028 Nevada 0.018 Washington 0.055 Minimum wage -0.102 McFadden R-squared S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter. LR statistic Prob(LR statistic) Obs with Dep=0 Obs with Dep=1 0.07 0.27 0.52 0.52 0.52 3529.42 0.00 7541 86275 Std. Error 13.566 0.007 0.012 0.025 0.017 0.016 0.019 0.032 0.110 0.286 0.001 0.005 0.004 0.023 0.062 0.055 0.026 0.026 z-Statistic -8.260 8.307 -8.895 -12.274 -11.219 18.931 9.829 4.327 -18.518 6.400 1.072 16.457 -7.513 1.717 0.445 0.330 2.087 -3.961 0.92 0.27 6592.13 -24475.47 -26240.18 -0.26 93816 Prob. 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.28 0.00 0.00 0.09 0.66 0.74 0.04 0.00 Mean dependent var S.E. of regression Sum squared resid Log likelihood Restr. log likelihood Avg. log likelihood Total obs Table 3 illustrates the impacts of indexing on youth unemployment over time. As Oregon and Washington’s minimum wages increase over time relative to the federal minimum, the states’ youth unemployment increases Discussion e e probit regression presented in Table 2 indicates that relative to what it would have been otherwise. higher minimum wages are associated with a statistically exception to the increasing di erential in unemployment 9 is in 2008, when the federal minimum wage increased to focus on Oregon and Washington’s experience. Impacts are quanti ed by how they a ect (1) employment and (2) $5.85 an hour. hourly wages for hourly workers. is study employs two methods. One method incorporates the tted values from the probit model in the hourly wage model; these results are presented in Figure 4. e second method calculates the inverse Mill’s ratio, which is incorporated in the hourly wage model. e results for both methods are virtually identical, and only the results from the rst method are reported. Results from the second method are available from the author. Conclusion e project uses wage data from the annual March e goal of this research is to evaluate quantitatively the Current Population Surveys for Oregon, Washington, economic e ects of minimum wage indexing, with a and their neighboring states and covers the period in The Impact of Minimum Wage Indexing Employment Policies Institute 12 Employment Policies Institute The Impact of Minimum Wage Indexing 13 Table 2: Regression Results Dependent Variable: LOG(Hourly Wage) Method: Least Squares Included observations: 7885 Variable Coefficient Intercept -106.597 Fitted value from probit -3.076 Year 0.055 Female -0.206 Black -0.202 Never married -0.149 High school 0.445 Bachelor’s degree 0.289 Graduate 0.234 Food -0.355 Retail -0.244 Youth -4.196 Senior 9.005 LN(Age) 0.227 Youth * LN(Age) 1.288 Senior * LN(Age) -2.244 California 0.080 Idaho -0.046 Nevada 0.072 Washington 0.101 LN(Minimum wage) -0.139 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.35 0.34 0.41 1323.33 -4151.73 207.76 0.00 Figure 4: Unemployment Impacts of Minimum Wage Above Federal Minimum Wage, Oregon and Washington, 2003–2008 Std. Error 11.832 0.447 0.006 0.012 0.032 0.018 0.027 0.017 0.029 0.017 0.020 0.727 1.483 0.023 0.232 0.357 0.017 0.049 0.045 0.019 0.140 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat t-Statistic -9.009 -6.876 9.050 -17.219 -6.342 -8.513 16.408 17.287 8.088 -20.326 -12.204 -5.775 6.072 9.786 5.548 -6.291 4.618 -0.922 1.613 5.218 -0.995 Prob. 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.36 0.11 0.00 0.32 2.54 0.51 1.06 1.08 1.06 1.56 0.09 0.08 Difference in Unemployment (%) 0.07 0.06 0.05 0.04 0.03 0.02 0.01 0 Oregon Washington Table 3: Unemployment Impacts of Minimum Wage Indexing on Workers Under Age 25, Oregon and Washington, 2003–2008 Oregon Unemployment Rate 20.7% 21.0% 20.0% 18.9% 18.9% 16.4% 19.5% Unemployment Rate if State Minimum = Federal Minimum 16.3% 16.2% 14.9% 13.5% 12.8% 11.9% 14.5% Washington Unemployment Rate if State Unemployment Minimum = Difference Rate Federal Minimum 21.0% 16.3% 4.7% 19.5% 14.7% 4.8% 18.5% 13.4% 5.0% 18.9% 13.2% 5.7% 17.7% 11.6% 6.0% 17.1% 12.3% 4.8% 18.8% 13.7% 5.2% Year Difference which Oregon and Washington both indexed their respective minimum wage rates. e regression models used in this study account for the possibility that factors a ecting whether an individual is employed also a ect the hourly wage earned. Regression results indicate that higher minimum wages are associated with a statistically signi cant reduced probability of being employed. Indexing the minimum wage produces annual increases in the minimum wage that, in turn, are likely to increase unemployment, especially among the young. In addition, regression 2003 2004 2005 2006 2007 2008* 2003-08 Average 4.4% 4.8% 5.1% 5.4% 6.0% 4.4% 5.0% 14 Employment Policies Institute The Impact of Minimum Wage Indexing The Impact of Minimum Wage Indexing Employment Policies Institute 15 results indicate that, controlling for employment impacts, increasing minimum wages have no statistically or economically signi cant impact on wages. It is clear that the costs of reduced employment associated with minimum wage indexing are not o set by higher wages throughout the wage distribution. us, minimum wage indexing imposes employment costs with no measurable income bene ts. Appendix e data in this study include the following variables measuring individual demographic and employment characteristics. Hourly wage Hourly earnings individual’s current job (hourly workers only). Labor force Dummy variable equal to 1 for individual in the labor force, 0 otherwise. Employed Dummy variable equal to 1 for individual in the civilian labor force who is not unemployed, 0 otherwise; an individual is considered to be unemployed if he or she is in the civilian labor force and has either (1) lost a job or (2) stated that he or she wants a regular job now. Note that these de nitions di er slightly from those used by the Bureau of Labor Statistics (2009b); thus, employment and unemployment in this study are not directly comparable to the statistics reported by the Bureau of Labor Statistics. Age Age, in years, of the individual. Youth Dummy variable equal to 1 for individual younger than 25 years of age, 0 otherwise. Senior Dummy variable equal to 1 for individual older than 60 years of age, 0 otherwise. Female Dummy variable equal to 1 for female individual, 0 otherwise. Black Dummy variable equal to 1 for black individual, 0 otherwise. Never married Dummy variable equal to 1 for never married individual, 0 otherwise. High school Dummy variable equal to 1 for individual completing high school or higher education, 0 otherwise. College Dummy variable equal to 1 for individual completing bachelor’s degree or higher education, 0 otherwise. Graduate Dummy variable equal to 1 for individual completing a graduate degree, 0 otherwise. Occupation Dummy variables equal to 1 for individual employed in speci c occupation, 0 otherwise. Occupations: (1) food preparation or food services, (2) retail. tate Dummy variables equal to 1 for individual’s state of residence, 0 otherwise. States: Oregon, California, Washington, Idaho, Nevada. 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(2003). “ e E ect of Minimum Wages on Youth Employment in Canada: A Panel Study.” Journal of Human Resources, 38(3):647–672. 18 Employment Policies Institute The Impact of Minimum Wage Indexing The Impact of Minimum Wage Indexing Employment Policies Institute 19 Notes Notes 20 Employment Policies Institute The Impact of Minimum Wage Indexing The Impact of Minimum Wage Indexing Employment Policies Institute 21 Notes SELECTED PUBLICATIONS Who are the Uninsured? An Analysis of America’s Massachusetts Healthcare Reform: e View from One Uninsured Population, eir Characteristics and eir Year Out, by Jonathan Gruber, Massachusetts Institute of Health, by June E. and David M. O’Neill, Baruch College, Technology, September 2007. City University of New York, June 2009. 2007 EPI Minimum Wage Survey of Labor Economists, Indexing the Minimum Wage: A Vise on Entry- by e Survey Center—University of New Hampshire, Level Wages, by the Employment Policies Institute, July 2007. April 2009. Paid Sick Leave: Putting Legislative Preferences before Congressional Minimum Wage Support: e Role Individual Preferences, by the Employment Policies of Background and Economic Education, by J. Brian Institute, May 2007. O’Roark, Robert Morris University, and William C. Wood, James Madison University, October 2008. Comparing e E ects of Health Insurance Reform Proposals: Employer Mandates, Medicaid Expansions, Minimum Wages and Poverty: Will the Obama and Tax Credits, by Ellen Meara, Meredith Rosenthal, Proposal Help the Working Poor? by Joseph J. Sabia, and Anna Sinaiko, Harvard University, February 2007. American University, and Richard V. Burkhauser, Cornell University, September 2008. Minimum Wage E ects in the Post-welfare Reform Era, by David Neumark, University of California, Irvine, Examining E ects of Minimum Wages on Single January 2007. Mothers’ Exits from Welfare, by Peter D. Brandon, Brown University, July 2008. e E ects of the Proposed Arizona Minimum Wage Increase, by David Macpherson, Florida State Good Intentions Are Not Enough: Why Raising New University, September 2006. York’s Minimum Wage Continues to be a Poor Way to Help the Working Poor, by Joseph J. Sabia, University of e E ects of the Proposed Missouri Minimum Wage Georgia, and Richard V. Burkhauser, Cornell University, Increase, by David A. Macpherson, August 2006. January 2008. Output Prices and the Minimum Wage, by Daniel Helping Low-wage Americans: e Earned Income Aaronson and Eric French, June 2006. Tax Credit, by the Employment Policies Institute, September 2007. e E ect of Minimum Wage Increases on Retail and Small Business Employment, by Joseph J. Sabia, e Impact of Minimum Wage Increases on Single University of Georgia, May 2006. Mothers, by Joseph J. Sabia, University of Georgia, September 2007. e “Fair Share for Healthcare Act” and New York’s Labor Market, by Dr. Aaron Yelowitz, University of Employer Health Insurance Mandates and the Risk Kentucky, April 2006. of Unemployment, by Helen Levy, University of Michigan, and Katherine Baicker, Harvard University, e E ect of Increase in Health Insurance Premiums on Labor Market Outcomes, by Katherine Baicker, September 2007. University of California at Los Angeles, and Amitabh Who Gets What from Employer “Pay or Play”, by Chandra, Harvard University, October 2005. Richard Burkhauser and Kosali Simon, Cornell University, September 2007. 22 Employment Policies Institute The Impact of Minimum Wage Indexing 1090 Vermont Avenue, NW Suite 800 Washington, DC 20005 www.EPIonline.org Tel: 202.463.7650 Fax: 202.463.7107