Letter to Editor Illiteracy and Cognition in Older Adults Sir, The article “Cognitive dysfunction in normally aging urban older adults” by Tripathi and Tiwari (2011) which appeared in volume 33 (2)[1] is interesting and has raised important issues regarding cognitive assessment in the elderly population. In this study the sample comprised of 89 community‑dwelling normal elderly and most of the subjects (68.5%) had education below primary school level. Further, their results indicated that normal elderly had dysfunction in the domains of orientation and concentration. However, the findings of the article raise several questions for further examination. Here we have provided our observations in brief. To the best of our knowledge no age and education adjusted cut off value is available on MMSE or HMSE to call someone ‘normal’ in Indian context. Moreover the cut off scores on these screening tools are meant to indicate probable impairment rather than determination of “normal aging” Secondly, it would have been useful if authors had provided more detailed information on education levels in terms of illiteracy and functional illiteracy, as it affects the performance on neuropsychological assessment and interpretation of the result. In clinical settings it is often observed that some elderly, although educated upto primary level, become functionally illiterate when they do not utilize their reading and writing skills. These skills may be redundant for their lifestyle or occupation, which is often the case in rural setting. Further it has been demonstrated that the ability to read and write itself reinforces and modifies our cognitive abilities.[2] In Tripathi and Tiwari’s study the majority of the sample had education below 5 years. Several studies have demonstrated that low education levels adversely affect the performance on neuropsychological tests.[3,4] This could be due to lack of exposure to psychological test and testing situation itself. Therefore, the poor performance on a particular test may not reflect the true cognitive ability on the tested domain, particularly when the tests are not culturally appropriate. Hence, we would be cautious in using the term “cognitive dysfunction” in the current study context. Based on the performance on serial subtraction, orientation to time, month and date the authors have interpreted that normal elderly have cognitive impairment in the domains of orientation and concentration. It is well documented that subtests such as serial subtraction, orientation to time, month and date are influenced by education.[5,6] Also the elderly with low levels of education may perform poorly on a 406 particular test even when they do not have deficit in that particular cognitive domain. Poor performance in individuals with low education could be attributed to various reasons such as task familiarity and appropriateness of the test for given population, anxiety‑related to testing situation, test taking attitude, lack of ecological validity of the test for population of individuals with low levels of education. It is therefore imperative to use ecologically valid and culturally appropriate tests in order to make definitive comments on the true cognitive status of a particular individual. Ravikesh Tripathi, Keshav Kumar Department of Clinical Psychology, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, Karnataka, India Address for correspondence: Dr. Keshav Kumar, Department of Clinical Psychology, NIMHANS, Bangalore‑560029, Karnataka, India. E‑mail: keshavjkapp@gmail.com References 1. 2. 3. 4. 5. 6. Tripathi RK, Tiwari SC. Cognitive dysfunction in normally aging urban older adults: A community‑based study. Indian J Psychol Med 2011;33:177‑81. Ardila A, Bertolucci PH, Braga LW, Castro‑Caldas A, Judd T, Kosmidis MH, et al. Illiteracy: The neuropsychology of cognition without reading. Arch Clin Neuropsychol 2010;25:689‑712. Ardila A, Rosselli M, Rosas P. Neuropsychological assessment in illiterates: Visuospatial and memoryabilities. Brain Cogn 1989;11:147‑66. Ostrosky‑Solis F, Ardila A, Rosselli M, Lopez‑Arango G, Uriel‑Mendoza V. Neuropsychological test performance in illiterate subjects. Arch Clin Neuropsychol 1998;13:645‑60. Ganguli M, Ratcliff G, Chandra V, Sharma S, Gilby J, Pandav R, et al. A Hindi version of the MMSE: The development of a cognitive screening instrument for a largely illiterate rural elderly population in India. Int J Geriatr Psychiatry 1995;10:367‑77. Mathuranath PS, Cherian JP, Mathew R, George A, Alexander A, Sarma SP. Mini mental state examination and the Addenbrooke’s cognitive examination: Effect of education and norms for a multicultural population. Neurol India 2007;55:106‑10. Access this article online Quick Response Code Website: www.ijpm.info DOI: 10.4103/0253-7176.108238 Indian Journal of Psychological Medicine | Oct - Dec 2012 | Vol 34 | Issue 4 Copyright of Indian Journal of Psychological Medicine is the property of Medknow Publications & Media Pvt. Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. APPLIED ECONOMICS LETTERS, 2016 VOL. 23, NO. 11, 765–767 http://dx.doi.org/10.1080/13504851.2015.1105917 The effect of education on the minimum wage Christos Pargianas University of Scranton, Scranton, PA, USA Downloaded by [EBSCO Publishing Distribution 2010], [Paige Riordan] at 21:08 20 May 2016 ABSTRACT This research shows for the first time that the level of education has a causal, negative effect on the minimum wage. I use 2SLS, with historical educational data as an instrument for the level of education in 2010, and I find that across the US states a one percentage point greater proportion of college graduates is associated with a real minimum wage that is lower by 1.5%–1.6%. Also, in order to control for state-level omitted variables, I regress the change in the minimum wage on the change in education and I find again a negative, and significantly at the 1% level, effect. Minimum wage is a policy that is chosen by governments according to voters’ preferences. The results of this research imply that when the level of education increases voters prefer a lower minimum wage. I. Introduction This research is related to political economy papers that examine how education affects the economy through institutions and policies.1 Glaeser and Saks (2005) show that an increase in education reduces corruption, and Glaeser, Ponzetto, and Shleifer (2007) argue that an increase in education leads to more democracy. This research shows that an increase in education reduces the minimum wage. Pargianas (2015; Forthcoming) explain theoretically how education affects institutions and policies and, therefore, they provide theoretical support for Glaeser and Saks (2005) and this research. More specifically, they argue that college graduates and unskilled individuals prefer different policies and governments choose the policies that benefit the group with the greater political power. An increase in the proportion of college graduates increases their political power and, therefore, policies change in their favour. College graduates do not earn the minimum wage and this means that they do not lose when the minimum wage decreases. On the other hand, they are either entrepreneurs who employ unskilled workers and pay to them the minimum wage or employees who could receive a pay rise if their employer’s profit increases after a decrease in KEYWORDS Education; minimum wage; 2SLS regressions; voter preferences JEL CLASSIFICATION H00; I28; H27 the minimum wage that reduces the unskilled labour cost. As a result, a decrease in the minimum wage is a policy they prefer. Several papers have examined how a change in the minimum wage affects wage inequality. More specifically, DiNardo, Fortin, and Lemieux (1996) and Lee (1999) find that during the 1980s, the decline in the real value of the minimum wage explains 20%–50% of the rise in wage dispersion, 80% of the growth in within-group wage inequality and about 15% of the change in the return to schooling. This evidence suggests that the minimum wage significantly affects economic outcomes and so the question ‘what determines the minimum wage’ is of great importance. This research shows for the first time that the level of education has a causal negative effect on the minimum wage. II. Empirical evidence Data description The analysis in this section uses minimum wage data from the Bureau of Labor Statistics Monthly Labor Review, January Issues. In every state, the minimum wage value that is used is the largest between the federal minimum wage and the state minimum wage CONTACT Christos Pargianas christos.pargianas@scranton.edu 1 Earlier research has argued that education affects the economy, first, because human capital is a factor in the production of final output, and, second, because it increases innovation and imitation rates. See, for example, Mankiw, Romer, and Weil (1992). In addition, Galor (2005) argues that education affects people’s ability to adapt and remain productive in an economy that changes rapidly because of technological progress. © 2015 Taylor & Francis 766 C. PARGIANAS Downloaded by [EBSCO Publishing Distribution 2010], [Paige Riordan] at 21:08 20 May 2016 in the January of each year. For the construction of the real minimum wage I follow Lee (1999), and I divide the minimum wage by the median income for each state. The source for the median income, the Gini index, the percentage of blacks and Latinos, the composition of the four US regions, and the education data across states, is the US Census Bureau. The measure that is used for education is the fraction of individuals 25 or older with at least a bachelor’s degree. The coefficients in the four specifications I use are –.011 and –.012, and imply that a one percentage point increase in the proportion of college graduates decreases the real value of the minimum wage by 1.1%–1.2%. None of the control variables is statistically significant. The problem with OLS is, first, that there might be omitted variables that affect both education and the minimum wage and, second, that there might be reverse causality. The identification strategy I use in order to address these issues is the same as the one used by Glaeser and Saks (2005) and Barro and Lee (2010). More specifically, I use the 2SLS method with historical educational data as an instrument.3 The only potential issue that remains is that the instrument may depend on state-specific omitted variables which do not change over time and which are the true determinants of the minimum wage. I capture most of them, but not all, by including region dummies in the regressions. The best way to avoid all the bias from omitted state-level variables is to estimate regressions with state fixed effects which asks whether changes in education predict changes in the minimum wage. I report the results of these regressions in Table 2. Both the 2SLS and the fixed- Results Table 1 presents the results of a simple OLS regression of the 2010 log real minimum wage on the proportion of college graduates and other controls in 2000.2 The controls I use are, first, the dummies of the US regions, which control for region specific characteristics, second, the proportion of blacks and Latinos, which capture racial dissimilarity and, third, the Gini index, which captures economic dissimilarity. In all cases, we can see that states with higher proportion of college graduates are associated with lower real minimum wage and that this effect is large and always statistically significant at the 1% level. Table 1. OLS and 2SLS regressions of the real minimum wage on the proportion of college graduates. OLS Dependent variable: log real minimum wage in 2010 Proportion of college graduates in 2000 Northeast South West (1) −.012*** (.0019) .020 (.0213) .018 (.0128) .034 (.0205) Blacks 2000 Latinos 2000 (2) −.012*** (.0021) .021 (.0217) .018 (.0162) .037 (.0240) .000 (.0008) .000 (.0009) Gini 2000 Constant R2 1st stage F # Obs. 2SLS (3) −.012*** (.0018) .010 (.0254) .003 (.0183) .026 (.0216) (4) (5) (6) (7) (8) −.011*** −.016*** −.016*** −.016*** −.015*** (.0019) (.0020) (.0022) (.0018) (.0022) −.005 .040* .041** .032 .021 (.0276) (.0236) (.0235) (.0268) (.0297) .002 .010 .005 −.004 −.005 (.0179) (.0097) (.0155) (.0145) (.0159) .031 .040* .040 .033 .036 (.0220) (.0218) (.0249) (.0232) (.0234) −.001 .000 −.001 (.0010) (.0007) (.0010) −.002 .000 −.001 (.0012) (.0008) (.0011) 1.017** .382 .717 (.4597) (.3171) (.4539) −3.98*** −3.47*** −3.47*** −3.61*** −3.76*** (.1910) (.0422) (.0445) (.1346) (.2009) −3.57*** (.0428) −3.57*** (.0450) .402 (.3411) −3.73*** (.1369) .61 .61 .62 .65 50 50 50 50 .55 29.73 50 .55 20.07 50 .56 27.27 50 .60 18.09 50 Note: Robust standard errors appear in brackets. *, ** and *** denote statistical significance at the 10%, 5% and 1% level, respectively. In 2SLS regressions, the instrument is the proportion of college graduates in 1960. 2 I use year 2000 independent variables because according to the theory (see the Introduction section to this paper), education affects the minimum wage through the political process which is slow. Thus, it takes time to see the political effect of a change in the level of education. The results do not change if I use year 2010 independent variables. 3 I use education data of year 1960 because is the earliest year with available data for all the states. The earliest data are from year 1940 but in 1940’s data two values are missing (Alaska and Hawaii). The results do not change if I use year 1940 education as an instrument but in this case the instrument turns out to be weak in some specifications. APPLIED ECONOMICS LETTERS Table 2. OLS regressions of the change in the real minimum wage on the change in the proportion of college graduates. Downloaded by [EBSCO Publishing Distribution 2010], [Paige Riordan] at 21:08 20 May 2016 Dependent variable: difference in log real minimum wage 1980–2010 Difference in the proportion of college graduates in 1970–2000 Difference in Share Black 1970–2000 Difference in Share Latino 1970–2000 Difference in Gini 1970–2000 constant R2 # Obs. OLS (1) −.007*** (.0016) (2) −.007*** (.0018) (3) −.009*** (.0016) (4) −.009*** (.0017) .745*** (.2470) −.034* (.0193) −.001 (.0026) −.002 (.0013) .984*** (.2998) −.036* (.0212) .002 (.0037) .001 (.0010) −.024 (.0202) .21 50 −.022 (.0229) .22 50 .36 50 .38 50 Note: Robust standard errors appear in brackets. *, ** and *** denote statistical significance at the 10%, 5% and 1% level, respectively. effects methods confirm the significant negative effect of education on the minimum wage. More specifically, Table 1 also presents the results of the 2SLS regressions. I use the same specifications as in the OLS regressions and, again, states with higher proportion of college graduates are associated with lower real minimum wage. This effect is larger in the 2SLS than in the OLS regressions, the coefficients of the 2SLS regressions are between –.015 and –.016, and always statistically significant at the 1% level. The variable ‘northeast’ is significant in two of the four specifications and the variable ‘west’ in one. The variables that capture economic and racial dissimilarity are always insignificant. Also, the instrument is not weak as we can see from the first stage F-values, which are always sufficiently high. Finally, in Table 2, I present the results of the regressions of the difference in the minimum wage on the difference in the proportion of college graduates and the difference in other controls, in order to avoid the bias from statespecific omitted variables. The main coefficient is a little smaller, in absolute value, than in the OLS and 2SLS regressions but always significant at the 1% level. Also, the coefficient of the change in the Gini index is positive and significant. III. Conclusions This research shows that education has a causal effect on the minimum wage in the USA. More specifically, a one percentage point increase in the proportion of college graduates decreases the 767 minimum wage by 0.7%–1.6%. A very interesting topic for future research would be to examine the effect of education on other economic policies like the level of taxation, government spending, labour market regulations, etc. Also, it would be interesting to examine whether there are other variables that predict the minimum wage and other policies. In order to identify these variables, we need to have in mind that policies change when the political power of the different groups changes. As a result, variables that affect the balance of the political power are probably the best candidates. Disclosure statement No potential conflict of interest was reported by the author. References Barro, R. J., and J. Lee. 2010. “A New Data Set of Educational Attainment in the World, 1950-2010.” NBER Working Paper No. 15902, doi:10.3386/w15902. DiNardo, J., N. M. Fortin, and T. Lemieux. 1996. “Labor Market Institutions and the Distribution of Wages, 1973-1992: A Semiparametric Approach.” Econometrica 64: 1001–1044. doi:10.2307/2171954. Galor, O. 2005. “From Stagnation to Growth: Unified Growth Theory.” In Handbook of Economic Growth, edited by Philippe Aghion and Steven Durlauf, 1: 171–293. doi:10.1016/S1574-0684(05)01004-X. Glaeser, E. L., G. A. M. Ponzetto, and A. Shleifer. 2007. “Why Does Democracy Need Education?” Journal of Economic Growth 12: 77–99. doi:10.1007/s10887-0079015-1. Glaeser, E. L., and R. E. Saks. 2005. “Corruption in America.” Journal of Public Economics 90: 1053–1072. doi:10.1016/j. jpubeco.2005.08.007. Lee, D. S. 1999. “Wage Inequality in the United States During the 1980s: Rising Dispersion or Falling Minimum Wage?” The Quarterly Journal of Economics 114: 977– 1023. doi:10.1162/003355399556197. Mankiw, N. G., D. Romer, and D. N. Weil. 1992. “A Contribution to the Empirics of Economic Growth.” The Quarterly Journal of Economics 107: 407–437. doi:10.2307/ 2118477. Pargianas, C. 2015. “Endogenous Economic Institutions and Persistent Income Differences among High Income Countries.” Open Economies Review 1–24. doi:10.1007/ s11079-015-9363-y. May 2015. Pargianas, C. Forthcoming. “Endogenous Political Institutions, Wage Inequality, and Economic Growth.” Macroeconomic Dynamics. Advance online publication. doi:10.1017/S1365100515000449. Copyright of Applied Economics Letters is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. The Minimum Wage and Poverty among Full-Time Workers RICHARD VEDDER and LOWELL GALLAWAY Ohio University, Athens, OH 45701 I. Introduction When the federal minimum wage was established, the nation had suffered eight consecutive years of double-digit unemployment rates, and about one-half of Americans were below the poverty level as currently defined by the federal government (Patterson, 1994, p. 79). The elimination of poverty was the major objective of that legislation. Proponents of the minimum wage believed that the higher-than-market wages mandated by the Fair Labor Standards Act would bring some persons above the poverty line and improve their standard of living. The implicit assumption of the proponents of mandated minimum wages is that the "income effect" arising from higher worker compensation among those working would be greater than the "substitution effect" arising from employers substituting other resources for labor as a consequence of the increased employee costs. The unemployment effects of minimum wages were either ignored or assumed to be small. A number of facts are relevant in evaluating the relationship between minimum wages and poverty. First, the long-run trend in the overall rate of poverty (using the official Census Bureau definition) was downward prior to 1973, falling from 26.2 percent in 1953 to 11.1 percent in 1973, but essentially near-stationary since that date — the 1999 rate of 11.8 percent was actually slightly higher than the rate for 1973. Second, poverty rates are strongly negatively correlated with employment. In 1999, the poverty rate among full-time, year-round workers over 16 was 2.6 percent, compared to 19.9 percent for those over 16 not working at all. Fewer than 12 percent of the poor over the age of 16 worked full-time year-round (U.S. Bureau of the Census, 2000, p. 18). Third, the minimum wage adjusted for inflation in general showed an upward trend in the 1950s and 1960s, but a downward trend since, using the CPIU as the price deflator. For example, from 1953 to 1968, the real wage in 1982-1984 dollars rose from $2.81 to $4.54, but from 1968 to 1999 it fell over 30 percent to $3.09. This no doubt overstates the decline, both because of the growing consensus that the CPI-U overstates inflation and because of expanding minimum wage coverage. Nonetheless, casually "eyeballing" the descriptive statistics might lead one to believe that minimum wages do reduce poverty, since poverty rates declined during the era of rising real minimum wages in the 1950s and 1960s, but failed to maintain the downward trend during the era since 1968 when minimum wages stopped rising. JOURNAL OF LABOR RESEARCH Volume XXIII, Number 1 Winter 2002 JOURNAL OF LABOR RESEARCH A fourth fact, however, calls that into question. Everyone agrees that the minimum wage is designed to raise incomes and reduce poverty for workers. Yet in the years 1966-1968, when the hourly real minimum wage in 1982-1984 dollars was never less than $3,86, the poverty rate among full-time, year-round workers was never less than 4,0 percent. In the period 1984-1999, by contrast, the hourly real minimum wage was never greater than $3.22, but the same poverty rate never exceeded 2.9 percent. Over time, the real minimum wage fell, but so did worker poverty. What does more elaborate empirical research suggest? Again, recent studies tend to refute the notion that minimum wages reduce the rate of poverty (Neumark and Wascher, 1997; Neumark et al„ 1998; Vedder and Gallaway, 2001), Even Card and Krueger (1995), whose findings that minimum wages have little unemployment impact have been severely criticized (Neumark and Wascher, 2000), observe generally very weak relationships between measurements of the minimum wage and poverty. To illustrate, in our study we ran literally hundreds of regressions relating varying definitions of poverty rates to the real federal minimum wage, changes in that wage, or to state minimum wages. In the overwhelming majority of regressions, there was no statistically significant relationship between the poverty rate (however defined) and the real minimum wage (however defined). For example, consider just one rather representative regression for the years 1953 through 1998 for the aggregate rate of poverty (POVFRTY) as officially denned by the U.S. Bureau of the Census. We regressed POVFRTY against the minimum wage deflated by the CPI-U (RWAGF), the unemployment rate for civilian workers (UNFM), and the amount of federal transfer payments as a percent of GDP (TRAN): POVFRTY =\0.156-Q.AIO (5.00) (0.69) RWAGF +0.635 (5,75) UNFM - 0.00\ TRAN, (0,27) (1) /?2 = .980, D-W = 1,89, /^= 392.02, ARIMA (1,1), where the numbers in parentheses are i-statistics. While the relationship between POVFRTY and RWAGF is negative, it is statistically insignificant, in contrast to the robust expected positive relationship between unemployment rates and the rate of poverty. As indicated above, scores of variations of the model using different definitions of poverty (e.g., for various age, gender, and racial groups, different income thresholds, different geographic regions), alternative independent variables, and even cross-sectional (state) data, show similar results, with nearly one-third of the regressions actually showing a positive relationship between POVFRTY and RWAGF, and almost none showing a statistically significant negative one. n. The Minimum Wage and Poverty among Full-Time Workers The economic theory relating to minimum wages leads us to be unsurprised by the results observed above, since the higher than equilibrium price for labor implied by effective minimum wage legislation should create some unemployment or forestall RICHARD VEDDER and LOWELL GALLAWAY 43 some job creation, offsetting the income effects of higher compensation for those working. These unemployment effects are among the most thoroughly researched phenomena in labor economics (Brown et al., 1982; Deere et al., 1995; Neumark and Wascher, 1999; Neumark, 1999). Yet there is one group for whom minimum wage increases might be expected a priori to have negative effects on the incidence of poverty, namely full-time, year-round workers. These individuals, by definition, do not lose their jobs as a consequence of minimum wage hikes, so the substitution effect is presumably small or non-existent, allowing the income effect to dominate. Yet even full-time workers can face negative consequences of increases in the minimum wage. First, they may benefit from less on-the-job training, reducing their productivity and thus their income growth over time (Rosen, 1972; Feldstein, 1973; Welch, 1978; Hashimoto, 1982; Neumark and Wascher, 1998). Second, they may have a reduction in hours worked, going from, say, a 45-hour week where they collect substantial overtime pay to, say, a 36-hour week where they collect none. The decline in hours might completely offset the increase in compensation per hour. If this effect is large, the substitution effect might offset the income effect even for those workers who do not lose their jobs as a consequence of increases in the statutory wage minimum. Poverty data for full-time, year-round workers were provided by the Census Bureau to the National Conference Board (Barrington, 2000). We used those data to ascertain whether any relationship existed between poverty rates and the real minimum wage, introducing five additional independent variables into the model for control purposes. The results are shown in Table 1. The observed relationship between the poverty Table 1 Explaining Poverty Rates for Full-Time, Year-Round Workers, 1966-1998 Variable or Statistic Coefficient or Value /-Statistic Constant 4.120 3.572 Real Minimum Wage 0.053 0.398 Unemployment Rate 0.431 9.590 % Growth, Real GDP 0.005 0.348 Real GDP per Capita 0.000 5.843 -0.012* 15.746 2.72E-06* 14.845 Real Domestic Transfers per Capita Real Transfers per Capita^ R^ Durbin-Watson Statistic .932 2.195 *Nole: Coefficients are small due to the small unit of measurement. 44 JOURNAL OF LABOR RESEARCH rate for full-time workers and the real minimum wage, while insignificant, is nonetheless positive — higher minimum wage, higher poverty. The hypothesis that higher minimum wages mean lower poverty for the working poor is rejected. It is interesting that there are strong statistical relationships between poverty and several of the other independent variables. Noteworthy is the evidence of what we have elsewhere (Vedder and Gallaway, 1986) called the Poverty-Welfare curve: Small amounts of transfer payments tend to reduce the rate of poverty, but larger amounts tend to increase it. We subjected the results in Table 1 to nine different econometric tests. We examined for problems in model specification, model stability, serial correlation, heteroskedasticity, and nonstationarity. The results passed all nine tests at conventional threshold levels. Also, the relationship in Table 1 is maintained with different versions of the model, including expressing the variables in first-difference form, using alternative independent variables, and even using alternative-worker cohorts in defining poverty. Regarding the last point, we re-estimated the model using data for four broad Census regions: Northeast, South, Midwest, and West. The results (Table 2) again reject the hypothesis of a negative relationship between the real minimum wage and worker poverty. Indeed, the only statistically significant relationship, for the Northeast, is pos- Table 2 Poverty Rates and the Minimum Wage: Full-time Workers by Regions* Variable, Statistic Northeast South Midwest West Constant -0.379 (0.279) 12.487 (4.298) 3.452 (1.716) 1.824 (1.303) Real Minimum Wage 0.361 (2.286) -0.175 (0.516) -0.229 (0.986) 0.013 (0.077) Unemploment Rate 0.344 (6.395) 0.427 (3.724) 0.679 (8.774) 0.356 (6.528) % Growth, Real GDP 0.022 (1.310) 0.008 (0.231) 0.056 (2.195) -0.045 (2.461) Real GDP per Capita 0.000 (4.136) 0.000 (2.032) 0.000 (4.901) 0.000 (4.632) Real Domestic Transfers per Capita -0.008 (8.579) -0.018 (9.783) -0.014 (9.209) -0.008 (9.362) 1.79E-06 (8.221) 4.05E-06 (9.697) 2.98E-06 (7.893) 2.07E-06 (9.320) R2 0.799 0.930 0.821 0.865 ARIMA (0,1) (0,1) (1,0) (0,0) Real Domestic Transfers per Capita'^ *Note: Numbers in parentheses below regression coefficients are i-statistics. 45 RICHARD VEDDER atid LOWELL GALLAWAY Table 3 Results for Nonwhite, Full-Time, Year-Round Workers, by Census Regions'* United States Northeast South Midwe.st West Constant 17.144 (2.515) -3.772 (1.917) 51.570 (4.529) -2.364 (0.336) 13.170 (3.509) Real Minimum Wage 0.215 (0.316) 1.563 (6.773) -1.420 (1.074) 0.268 (0.312) -0.867 (1.973) Unemployment Rate 0.648 (2.624) 1.014 (16.320) 1.096 (2.420) 0.796 (2.684) 0.449 (3.250) % Growth, Real GDP 0.087 (1.506) 0.092 (2.257) 0.242 (1.788) -0.073 (0.871) 0.101 (1.812) Real GDP per Capita 0.000 (1.644) 0.001 (13.642) 0.000 (0.771) 0.001 (3.170) 6.25E-05 (0.419) Real Domestic Transfers per Capita -0.029 (4.378) -0.028 (22.234) -0.062 (8.399) -0.020 (3.271) -0.014 (5.718) Real Domestic Tranfers per Capita^ 7.07E-06 (4.141) 6.39E-06 (18.143) I.61E-05 (8.671) 3.64E-06 (2.336) 3.65E-06 (6.021) 0.939 0.927 0.943 0.572 0.608 (1,0) (0,1) (0,1) (1,0) (1,0) Variable, Stat. ARIMA *Noie: Numbers in parentheses below regression coefficients are /-statistics. itive; there is some evidence that the minimum wage increased poverty among fulltime workers in the Northeast. As before, there is a strong indication that transfer payments beyond some point tend to have positive, not negative, effects on poverty. As with the minimum wage, apparently the substitution effect (substituting leisure for work) is at least as great as the income effect. Finally, we looked at the behavior of nonwhite, full-time, year-round workers. Unlike for the total population, where the poverty rate from 1966 to 1998 varied between 2.0 and 4.8 percent with virtually no time trend, the nonwhite poverty rate varied between 3.87 percent in 1978 and 17.60 percent in 1966, although with relatively little trend over the past 20 years. Whereas in the late 1960s, the nonwhite-tototal (largely white) poverty rate ratio for full-time, year-round workers was three or more to one, since then that ratio has stabilized at between 1.5 and 2.0, reflecting a greater decline in poverty among nonwhites. Table 3 looks at the same model for nonwhites, both nationally and for the four Census regions. The results mirror those for the total population. In three of the five regressions, the observed relationship between the real minimum wage and the poverty rate is positive, and in one instance, that for the Northeast, it is statistically significantly so at the one percent level. Neither of the two negative relationships is significant at 46 JOURNAL OF LABOR RESEARCH the five pereent level, although one is at the 10 percent level. We certainly reject the hypothesis that the real minimum wage reduced poverty among nonwhite, full-time, year-round workers. By contrast, the two terms making up a quadratic relationship between transfers and poverty consistently work as indicated above, typically at the one percent level of statistical significance. Using alternative model specifications (e.g., using the change in the poverty rate instead of the level of the rate) makes little difference in the findings. The results suggest that increases in the real minimum wage do not reduce worker poverty. in. Minimum Wages and Hours Worked By definition, full-time, year-round workers are employed at least 35 hours per week for at least 50 weeks per year. Therefore the analysis above is confined to persons who were working at least 1,750 hours per year. Thus, we are limiting our analysis to a group of workers who by definition did not suffer severe unemployment effects of rising minimum wages. Yet even for that group, increases in the minimum wage did not reduce the incidence of poverty. As indicated above, one possible explanation is that this group reduced their hours of work, although to not below 1,750 hours per year. For example, suppose a worker was earning the minimum wage of $5.15 per hour and working 2,200 hours per year, 200 of them at time-and-a-half pay. Total annual compensation would equal $11,845. Suppose the minimum wage were raised by $1 per hour,- to $6.15, but our hypothetical worker had his/her hours reduced to 35 per week, or 1,750 per year. Annual compensation would actually fall by over $ 1,000 to $ 10,762 — perhaps drawing our hypothetical worker into poverty. To examine this possibility empirically, we turned to two Bureau of Labor Statistics time series, one on hours worked in manufacturing and the second for hours for all private, nonagricultural industries. Each data set has advantages. The manufacturing data involve relatively homogeneous forms of employment and show little time trend, mitigating econometric problems of nonstationarity. Moreover, not only are total weekly hours reported, but also overtime hours, typically compensated at 50 percent premium pay. The total private, nonagricultural industry data encompass a larger proportion of total employment, but show a noticeable downward trend in hours, presumably in part reflecting compositional changes in the labor force such as a rise in the relative importance of females and the increasing importance of the service industries. Data encompass the 41-year period 1959 through 1999 (Economic Report, 2000 p. 360). Table 4 presents OLS results for the hours data. The data for hours in the total private nonagricultural sector are expressed in first-difference form to avoid the stationarity problem indicated above (from 1959 to 1999, average hours declined rather steadily from 39 to 34.5 hours per week). There is a statistically significant negative relationship (at the one percent level, in the case of manufacturing hours) between hours worked or overtime hours worked and the real minimum wage, controlling for cyclical fluctuations by use of the unemployment rate and the percent growth of real GDP. RICHARD VEDDER and LOWELL GALLAWAY 47 Table 4 ÖLS Results: Impact of Minimum Wages on Hours Worked, 1959-1999* Change, Total Hours Manufact. Hours Overtime, Manuf. Constant -0.148 (0.693) 44.180 (64.792) 5.887 (9.194) Real Minimum Wage -0.131 (2.922) -0.816 (5.070) -0.349 (2.059) Unemployment Rate 0.040 (2.433) -0.188 (3.912) -0.190 (5.619) % Change, Real GDP 0.074 (6.486) 0.125 (6.404) 0.077 (6.368) «2 0.587 0.896 0.933 ARIMA (0.0) (0,2) (1,0) Variable, Statistic *Note: Numbers in parentheses below regression coefficients are (-statistics. Tbe results are statistically highly robust, witb tbe models exhibiting high overall explanatory power. The evidence strongly supports the conclusion that the substitution effect of higher minimum wages is strong even among full-time, year-round workers, strong enough to nullify any positive impact that the income effect has in eradicating poverty, IV. Lost Income Implications of Minimum Wages: Some Conjectural Estimates Our findings suggest that conventional estimates of the impact of minimum wages on labor force involvement may be understated. Estimates traditionally measure unemployment effects, implicitly assuming that there are two categories of workers, "employed" and "unemployed." The hours results above suggest that many officially "employed" workers actually do less work after minimum wages are increased, so the true "unemployment effects" of minimum wages may be understated in conventional estimations. How significant is this factor? To get some quantitative feel for this question, we asked the question, "What would be the impact on total hours worked if the federal minimum wage in 2000 had been raised from $5.15 to $6.15?" Using the change in total hours regression from Table 4, that implies a decrease in average hours in the private nonagricultural economy of about 0.08 per week (the minimum wage in 1982-1984 dollars would have risen about 60 cents. $.60 x .131 = about .08). This may be an understatement, since tbe larger coefficients on the alternative regressions suggest the impact may be much larger (e.g., 0.40 hours a week or more in manufacturing alone). Since average hours per week are currently less than 35, the 0.08 estimate 48 JOURNAL OF LABOR RESEARCH suggests that total hours in the private nonagricultural economy may be reduced by somewhere between 0.2 and 0.3 percent (say 0.25 percent for calculation purposes). Additionally, because of job layoffs or sluggish job creation, other studies are consistent with the notion that such a minimum wage increase could easily reduce the number employed by 0.4 or 0.5 percent (say 0.45 percent for calculation purposes) for the economy as a whole (and a much larger percent for younger and less skilled workers) (Deere et al., 1995; Neumark, 1999). Assuming these losses are additive, the total lost hours may approximate 0.7 percent of the amount existing in 2000 (0.25 plus 0.45). Making further assumptions, we can calculate a rough estimate of the income or output loss to the American economy of such a minimum wage increase. Suppose that the productivity of the lost labor is, on average, 35 percent of that of employed workers as a whole (roughly the ratio of the minimum wage to the average wage). This would imply a loss of labor input in standardized units of about 0.25 percent (0.7 x 0.35). If the elasticity of output with respect to labor input is about 0.70, as factor share national income data would suggest under normal neoclassical assumptions, the total national income would be reduced by about 0.175 percent (0.25 percent x 0.70). Using a national income of $8 trillion for 2000, this implies an income loss of $14 billion (using GDP, the estimate is closer to $17 billion). This calculation is similar to what one obtains by multiplying the lost labor in full-time-worker equivalents (approximately one million workers) by an annual wage, including fringes, of say, $13,000 a year. Whether the elimination of the minimum wage would yield comparable income gains for society depends, of course, on the extent to which the minimum wage on average leads to compensation levels above the market-clearing wage. With plausible assumptions, however, it is easy to estimate at least the equal of the above estimates of income lost from raising the minimum wage by one dollar. V. Conclusions The empirical evidence is strong that minimum wages have had little or no effect on poverty in the U.S. Indeed, the evidence is stronger that minimum wages occasionally increase poverty. It also suggests that the minimum wage does not even lower poverty for the one group that, almost by definition, one would expect to be helped: full-time, year-round workers. While the empirical results suggest minimum wages do not achieve what is ostensibly their primary goal — relieving poverty among the working poor — minimum wages do seem to impose a real cost on society in terms of lost income and output. The empirical evidence on work hours suggests that a $1 increase in the minimum wage, far from being almost costless, could conceivably impose income losses to American workers in the $ 12-15 billion range per year — an amount equal to the "income deficit" of millions of persons counted as poor by the U.S. Bureau of the Census. RICHARD VEDDER and LOWELL GALLAWAY 49 REFERENCES Barrington Linda. "Does a Rising Tide Lift All Boats? America's Full-Time Working Poor Reap Limited Gains in the New Economy." Research Report 1271-00-RR. New York: Conference Board, 2000. Brown, Charles, Curtis Gilroy, and Andrew Kohen. "The Effect of the Minimum Wage on Employment and Unemployment." Journal of Economic Literature 20 (June 1982): 487-528. Card, David and Alan B. Krueger. Myth and Measurement: The New Economics of the Minimum Wage. Princeton: Princeton University Press, 1995. Deere, Donald, Kevin M. Murphy, and Finis Welch. "Employment and the 1990-1991 Minimum Wage Hike." American Economic Review 85 (May 1995): 232-37. Economic Report of the President 2000. Washington, D.C: Government Printing Office, 2000. Feldstein, Martin. "The Economics of the New Unemployment." Public Interest 33 (Fall 1973): 3-42. Hashimoto, Masanori. "Minimum Wage Effects of Training on the Job." American Economic Review 72 (December 1982): 1070-87. Neumark, David. "The Employment Effects of Recent Minimum Wage Increases: Evidence from a Pre-specified Research Design." Cambridge, Mass.: National Bureau of Economic Research Working Paper W7171, June 1999. , Mark Schweitzer, and William Wascher. "Order from Chaos? The Effects of Early Market Experiences on Adult Labor Market Outcomes." Industrial and Labor Relations Review 51 (January 1998): 299-322. and William Wascher. "Do Minimum Wages Fight Poverty?" Cambridge, Mass.: National Bureau of Economic Research Working Paper W6127, August 1997. . "Minimum Wages and Training Revisited." Cambridge, Mass.: National Bureau of Economic Research Working Paper W6651, July 1998. _. "A Cross-National Analysis of the Effects of Minimum Wages on Youth Employment." Cambridge, Mass.: National Bureau of Economic Research Working Paper No. W7171, June 1999. _. "Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania: Comment." American Economic Review 90 (December 2000): 1362-96. Patterson, James T. America's Struggle Against Poverty, 1900-1994. Cambridge, Mass.: Harvard University Press, 1994. Rosen, Sherwin. "Learning and Experience in the Labor Market." Journal of Human Resources 1 (Summer 1972): 326-42. U.S. Bureau of the Census. Current Population Reports, P60-210. Poverty in the United States: 1999. Washington, D.C: U.S. Government Printing Office, 2000. Vedder, Richard and Lowell Gallaway. Poverty, Income Distribution, the Family and Public Policy. Study, Joint Economic Committee of Congress. Washington, D.C: U.S. Government Printing Office, 1986. . "Does the Minimum Wage Reduce Poverty?" Study, Washington, D.C: Employment Policies Institute, 2001. Welch, Finis. "The Rising Impact of Minimum Wages." Regulation 1 (November/December 1978): 28-37. Copyright of Journal of Labor Research is the property of Springer Science & Business Media B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. 47 The Delta Kappa Gamma Bulletin Special Contributions Illiteracy as a Life-Threatening Disease Maria Consoii Toulas I bis article explains the steps the author took in applying for a 2004 Diamond Jubilee Stipend and outlines how the cash award is being used. It shows how networking community services can enlighten and enrich the life of the volunteer, the community, and the members being served. The author provides some suggestion for prospective community volunteers. "H ope sees the Invisible, feels the Intanand achieves the hnpossihie" was an inspirational saying printed on a Cancer Foundation Christmas card I received last year. It seemed to confirm my need of supporting those efforts aimed at eradicating life-threatening ills like cancer, poverty and illiteracy. Educators are hopeful people, but at limes we can become overwhelmed by all that needs to be done. Overcoming the overwhelming thought of eradicating cancer. 1 did something. I hate cancer! So in 1991. afier losing a number of my family members to that dreadful disease. I became a hospital volunteer in the cancer unit ofa local hospital. Maria Consoii Toulas, Alpha Phi Chapter. New York. IS a rccipieni of one of ihe 2(X14 75th Anniversary Sli]iends. She has submitlcd this special report on how she has used her stipend. Perhaps we do not think of illiteracy as life threatening. To a person who is unable to provide for family members because of illiteracy, the pain and stress can be as disruptive as a life-threatening disease. In Nassau County. New York, one of the most altluent areas in America, hundreds of foreign-born people are illiterate in cither their native tongue or English, or both. As a way to do something about thi.s intolerable situation. 1 began to network my volunteer activities by connecting my community services. This past year my volunteer choices and community services converged, providing me with a comfort zone of purposeful retirement. After I retired from teaching social studies in the Bellmore-Merrick High School District (1966-1998). I took advantage of all the free course work offered by Catholic Charities to prepare for advocacy work on 48 behalf of the "working poor." One of these courses introduced me to the Workplace Project in Hempstead. Long Island. It is a place where immigrants go to be advised of their rights in the workplace. For example, if you are un immigrant day laborer cleaning an oflice or home, working on the roof of a building or mowing lawns, and at the end of the day you do not get paid, what do you do? You will go to the Workplace Project, and they will track down the employer and get you your pay. I asked the clients there what they needed mosi. They responded that the ability to communicate in English was primary. They e.xplained that they work long hours and rarely have the time or money to go to formal English classes. Wilhout basic English, these immigrants have difliculty finding or keeping a job. using public transportation, seeking proper medical attention, filling out forms or helping a child with school work. Once I became aware of this situation, I began to search out ways to eradicate illiteracy, one person at a time. Years ago, illiterate factory workers and immigrants in upstate New York cxpcrieni:etl problems associated wilh illiteracy. In 1972, Literacy Volunteers of America (LVA Inc.) was founded by Ruth Colvin to combat illiteracy among adults and teens in her own community of Syracuse. New York. Working with reading experts, she developed a training workshop that would equip a volunteer to tutor adults and teens in basic reading and writing. Later. In response to the increased needs of the thousands of foreign-born adults. English as a Second Language (ESL) tutoring workshops were added. In 1978, LVANassau County (LVA NC), a .5OI(c)(3) not-for-profit, became an affiliate of LVA Inc. Adults in need of literacy services and tutors were recruited, oriented, trained and assessed. In 1999. after completing a mandatory 24-hour workshop. I became a tutor. My first assignment was a senior profes- Spring 2005 sional couple who had immigrated to the United Stales from Iraq when, as a result of the Gulf War in 1991. their pensions were stopped. They wanted me to help them pass the American Citizenship test. They knew all the answers to the civic questions, but felt uncomfortable speaking English. We visited malls, parks, beaches and flea markets, and spoke about ordinary things. The following year we had a joyful celebration the day they were swom in as American citizens. Once ihcy became Americans they sought and received Social Security, which restored their dignity and some level of economic independence. Next. I tutored an immigrant from Mexico. Her ambition wa.s to get one good job instead of working two part-time jobs. We worked together in a local library, between her jobs. Eventually, she dropped out because of physical exhaustion. In the meantime, the Korean owners of Grace Nails, where I was a customer, asked me to help them with their conver.sationai English. They worked in their own .store twelve hours a day, six days a week. 1 tutored them every Monday morning, about an hour before the shop got bu.sy. Although they were high school graduates with knowledge of written English. Ihey wanted me to help them correctly pronounce words used in their trade. In lime, as they gained confidence, they would ask me questions about paying bills, going to the doctor and the education of ihcir child. By 2(K)3. the Iraqi f'amily moved to New Jersey, and ihc nail shop owners last their business when Grace became ill. Each experience reinforced my awareness that the specific needs of working immigrant adult learners is best served in the workplace. Knowing my enthusiasm for tutoring in the workplace, the dircctor of LVA-NC asked me to tutor a class in Basic English at a King Kullen Supcnnarket, located in Glen Cove, about 25 miles from my home. The The DeUa Kappa Gamma Bulletin manager, desperate to train and keep help, established a policy of paying his non-English speaking employees for the time they spend learning English in the store. I started with seven students in January 2003, and Ihe attendance liuctuates depending on their work schedule. Wc meet in the basement of the store for 90 minutes of formal instruction, and then we go into the supermarket and practice using the vocabulary associated with various departments. At Thanksgiving we watched the store deli-chef prepare and cook a Thanksgiving meal. He enjoyed being the instructor, lamiliarizing the adult learners with the vocabulary associated with that American holiday. The next week one student explained that she did not have a working oven in which to cook a turkey, so she had beans and rice on Thanksgiving Day. At one point, a student wanted to quit because another employee ridiculed her efforts at learning English. Her manager spoke to her in Spanish and explained how she. too. was once in a similar situation, and how because she was patient with herself she succeeded. In one year, this employee has excelled so much that she has been promoted from bagging groceries to the bakery. Another student's ability to communicate in English has improved so much that she has taken on two more part-time jobs, one cleaning the home of a store patron on Sundays and the other cleaning office buildings in the evening. The store manager is happy with the increased communication beiwfen his customers and employees, and the employees arc happy and comfortable working in the stoR'. All of this gives me great satisfaction. A colleague of mine at LVA-NC tutors four factory workers at another workforce project where immigrants make electronic connectors. Here they are paid to take one hour of Basic English after work one day a week. LVA-NC has been a.sked to do more of this type of tutoring, but it is difficult to 49 find volunteer tutors for group instruction. Networking Volunteer Activities Since retirement. I find myself navigating through a network of volunteer activities. 1 realized the potential available to enrich my workforce project at King KulIcn Supermarket when The Delta Kappa Gamma Society International publicized its intention of awarding stipends for educational projects. The director of our LVA-NC board. Anne DuPrey, was delighied when I suggested that 1 apply for a Delta Kappa Gamma 2004 75th Anniversary Stipend. I printed the application from Delta Kappa Gamma's website, typed the necessary information on the computer and attached it to the printed application form. Most of this information outlined my literacy project and itemized how I intended to spend the money. The director of LVA-NC. Anne DuPrey, and the 2002-2004 president of Alpha Phi Chapter. Betty Andrews-Tobias, provided letters of recommendation that I needed to complete the application. I attended English as a Second Other Language fESOL) Conferences at Molloy College in Rockville Centre, where I collected samples of Basic English programs. After trying out a number of programs, I decided that the Saslow Program for Preliterate Adults suited the needs of my students. At discount stores. I purchased a personal audiocassette player, some batteries, wrist watches and key locks for each student. When I was notified that 1 a recipient of one of the $1000 stipends. 1 directed Delta Kappa Gamma to make the check payable to LVA-NC. Wc ordered Saslow Workbooks A and B, flashcards. audiocassettes. Spanish/English dictionaries, and a picture reader for each student and one copy of the Teacher Workbooks A and B. with CDs for me. Some of my on-going expenses include scissors, pens, markers, crayons, color charts, alphabet lists and cal- 50 endars. I will continue to buy supplies on LVA-NC's account at Staple's as long as there is stipend money left. In this way no taxes are levied on my purchases. I have been an active member of the Public Policy Education Network (PPEN) of Catholic Charities since 1998. We study recent social legislation and then seek ways to educate the public and the legislatures about social issues. As a result of my comtnitmcnt to the hard-working, highly-motivated, working-poor adults at King Kuilcn, 1 lobby for the working poor and literacy projects, with great conviction, when visiting my congresswutnen. state senator., state assemblyman or county representative. Government allocation of funds for educational initiatives is in flux, and it is imperative that educators be vigilant about how their tax money is being spent. Through my contacts with non-English speaking parents. I became aware Uiat many lorcign-born carcgivers are confused as to how our school system works. I engaged my fellow Alpha Phi Chapter sisters in putting together a seminar entitled "Navigating Through the Public School System," aimed at teaching foreign-bum parents or caretakers the terminology consistent with public education. We presented this tutor/parent workshop in the East Meadow Library in 2002 and were asked to give it again in 2(X)4 and 2(H)3. Since 2004 I have been on the Speakers Bureau of LVA-NC and have been a member of the LVA-NC Board of Directors. Tutor training courses and workshops have a nominal regi.stration fee. As an active member of the Bellmore-Merrick Retited Teachers Association (BMRTA). I felt comfortable asking the retired teachers to allow me to raffle off a gift-basket of international foods at their 2004 spring luncheon. The proceeds ($180) were presented to LVANC to help defray the cost of tutor training. The biggest fundraiser for LVA-NC is the annual {Un)Scrabble Challenge, held each Spring 2005 spring in the ballroom ofa large hotel. After dinner, champagne and dessert, teams compete in three rounds of modified Scrabble. This was the forth year that ten Alpha Phi Chapter members and their friends made up a Delta Kappa Gamma table. The BellmoreMerrick United Teachers Association and the retired teachers are presently getting a table together for the 200.') {Un)Scrabble Challenge. I have assured them that it will be a '"fun" evening for a good cause. All these endeavors are aimed at raising the awareness of Long Islanders to the needs of adult-lcamcrs in their own communities. Poverty, Partnerships and Peace LVA Inc. underwent a name change in 2004 when it merged with Laubach Literacy and became ProLiteracy/World Wide. In order lo remain afliliiited with ProLiteracy/Arnerica and ProLiteracy/New York. LVA-NC is in the process of changing its name to Literacy/Nassau (L/N). The mission atid commitment to use volunteers to educate adult learners is stronger than ever. Our efforts will continue to be successful because of the cooperation of numerous sectors of the community, working in partnership to help L/N achieve its mission. Not all adult learners are among the working poor, but those that are do not have the time or money to travel to the Hempstead office to use the computers and library resources available to them, Kvcry effort is made to accommodate tutors and learners by local villages, churches and libraries. They often provide the space, time and talent for teacher-tutor training workshops and student tutoring. Each year adult learners and their volunteer tutors celebrate their achievements at the award's celebration held at the East Meadow Synagogue in June, A journal containing the written work of ESOL students is published and learning certificates of achievement arc presented. The Corporate Advisory Council, made up of local I he Delta Kappa Gamma Bulletin business-people, volunteer their expertise in marketing, managing and fundraising activities. Housewives, firemen, po.stmen. teachers, doctors, working and retired, will continue to volunteer hundreds ol' hours a year to make L/N a successful community service to adult-learners. At the 20(M conference, entitled '"Poverty and Partnerships and Peace," the Committee for Teaching Ahout the United Nations (CTAUN) advocated the type of cooperation explained above as "a true remedy for eradicating poverty and bringing about peace in our communities." Networking the activities of Public Policy Education Network. Bellmore-Merrick Retired Teachers Association. Alpha Phi Chapter of The Delta Kappa Gamma Society International, and Literacy/Nassau, in order to eradicate illiteracy for 2. 3. 4... people at a time, has indeed provided me with a purposeful retirement. 1 enjoy a certain delight in my endeavors and am grateful to these organizations for providing me with an opportunity to fill my life with so the many hidden rewards. Suggestions for Entering Community Service The following are some suggestions for those educators thinking about engaging in voluntary community service. This effort will give an educated woman a chance to use her expertise and may even open the door to a second career. 51 1. Family first! Sometimes it is more important to take eare of a child or sick family member than it is to volunteer outside the home. This experience may be valuable when you are free to serve in your community. 2. Know yourself and choose a service that suits your personality. 3. It is perfectly okay to try different things until you find what suits you best. You must feel comfortable. 4. The training that is offered is important to your suecess. Take it seriously. 5. Schedule your volunteer activity on your day planner and try your best to keep the eommitment. 6. You never know what the hidden rewards for your volunteer service will be. So, stay alert —it will sneak up on you! 7. Think of creative ways you can link your activity to other activities in your community— it will open new doors. 8. Educate others about the service you finally choose to do, so you can inspire them to step out and do their small pan. 9. Keep an eye out for opportunities to get your chapter members involved. 10. The people you will associate witli in community service are often the "best" the human race has to offer—clients and volunteers. A Educational Gerontology, 30: 79–93, 2004 Copyright # Taylor & Francis Inc. ISSN: 0360-1277 print/1521-0472 online DOI: 10.1080/03601270490266257 ILLITERACY AND OLDER ADULTS: INDIVIDUAL AND SOCIETAL IMPLICATIONS Sarah Poff Roman Scripps Gerontology Center, Miami University, Oxford, Ohio, USA Literacy has become an important predictor of well being in old age. Being literate in today’s society demands a myriad of functional abilities, which, when absent, can have dramatic health, economic, and social consequences. The purpose of this study was to develop a framework for defining literacy within an increasingly technological society, and to explore the experience of illiteracy among older adults. To examine these issues, qualitative data were gathered from an adult literacy program in Hamilton, Ohio. Data collected through these interactions suggest that the devastating effects of illiteracy are exacerbated throughout the lifecourse, resulting in significant disadvantage for older adults. In this time of rapid technological advancement, opportunities abound for innovation and the generation of knowledge. This so-called ‘‘age of information’’ has revolutionized every facet of society, including the medical, industrial, and educational fields. Although this has resulted in the proliferation of valuable data and technologies, the benefits of these advancements are unevenly dispersed. In the wake of this surge in innovation, a considerable portion of our population is being left behind due to literacy issues. Disproportionately from lower socioeconomic and minority groups, this country’s illiterate population is secluded from the aforementioned tools of innovation. As a result, The author thanks Dr. Lisa Groger for her assistance in the preparation of this paper. Address correspondence to Sarah Poff Roman, Miami University, Scripps Gerontology Center, Oxford, Ohio 45056. E-mail: romansa@muohio.edu 79 80 S. P. Roman illiterate adults experience poorer health outcomes, less financial security, and lower life expectancies compared to the overall population. Literacy, which conceptually encompasses far more than the ability to read, has become increasingly important as our society becomes ever more dependent on technology. The purpose of this study was to explore the effects that adult illiteracy has on both the individual and society. First, a framework for developing a contemporary definition of literacy is presented. Then, the demographic prevalence of illiteracy in America is illustrated through the use of national literacy data sets. To identify the consequences of these statistics, the individual and societal implications of illiteracy are explored within the context of a case study from an adult literacy center in Hamilton, Ohio. Finally, recommendations for addressing this social problem through policy and program development are offered. DEFINING LITERACY Literacy is a socially constructed concept whose definition varies according to cultural and historical context (Center for Educational Research and Innovation [CERI], 1992). In this sense, literacy is not a state of being, but a reflection of the relative fit between the individual’s various competencies and the social and historical environment. Literacy has not always held this holistic connotation. Until relatively recently, literacy was defined according to easily quantifiable measures, such as the ability to sign one’s name, and the number of grades completed in school (CERI, 1992). Now referred to as basic or conventional, this traditional definition of literacy involves the ability to read written words, but says nothing about the understanding of those words (Rassool, 1999). Literacy by this definition was actually the exception, rather than the rule in early American society. Very few individuals possessed basic literacy skills, because reading and writing were not necessary in early industrial and agricultural occupations (Costa, 1988). Because literacy was uncommon, illiteracy was not viewed as a social problem. This began to change as public education became standard and society became increasingly industrialized. As a result of these important developments, a gap began to develop between the educated and non-educated with regard to income, occupational security, and health (CERI, 1992). Once education became the norm, literacy began to be defined according to grade level attainment (CERI, 1992). Because this type of data is readily available in most countries, this definition facilitated the collection of easily quantifiable and cross-cultural data on literacy rates. Contemporary research has shown, however, that grade level attainment is not always a good Illiteracy and Older Adults 81 indicator of one’s ability levels. The number of years completed in school does not reflect the amount of education received, but rather the amount of education attempted (Baker, Parker, Williams, Clark, & Nurss, 1997). Although there is an uncontestable relationship between educational attainment and literacy, education by itself is not a proxy for ability level. To illustrate, it is not uncommon for poorly educated people to score high on literacy tests, and for highly educated individuals to rank poorly on the literacy scales. Thus, literacy seems to be a product of both educational attainment and life experience. Functional Literacy Recognizing the underlying complexity of individual literacy, contemporary researchers have struggled to develop more appropriate definitions of this multi-faceted concept. Our understanding of what true literacy entails has changed significantly since the days when signing your name was the only prerequisite. Today, the definition of literacy is based on what is called functional literacy. That is, someone is literate if they are able to function properly within society (Rassool, 1999). This definition can include (but is not limited to) possessing skills in reading and writing. In other words, literacy is no longer viewed as a well-defined set of technical skills, but as a multidimensional concept that is linked to one’s ability to process and generate information from his or her surroundings (Rassool, 1999). Today, literacy is defined as ‘‘the ability to read, write and speak English proficiently, to compute and solve problems, and to use technology in order to become a life-long learner and to be effective in the family, in the workplace and in the community’’ (Literacy Volunteers of America [LVA], no date, para. 1). The concept of functional literacy has made the definition of literacy infinitely more complicated. Primarily, because functional literacy involves utilizing a diverse array of skills in various combinations, literacy is not an ‘‘all or nothing’’ attribute (CERI, 1992). Rather, literacy is commonly described as a continuum. This has made the assessment of literacy skills much more challenging for adult educational centers because there are no absolute stages of literacy. However, this conceptualization also has had positive effects in that it has led to the development of highly effective and individualized tutoring approaches. Health Literacy The definition of literacy also has expanded to include what is commonly called health literacy. This concept refers to one’s ability to read 82 S. P. Roman and understand materials encountered in the health care setting and to obtain knowledge necessary for positive health outcomes (Nurss, 1998). This concept has emerged as a critical component of functional literacy with arguably the most severe consequences for both the individual and society. MEASURING LITERACY As illiteracy has become an issue of concern to society at large, various techniques for measuring its prevalence have been developed. Generally, these techniques can be categorized as tools for measuring either individual or population literacy. Individual Literacy Tools for measuring individual literacy are used primarily by educators and the health care community to gauge comprehension and reading skills. Most of these systems categorize respondents into multiple levels of literacy according to cumulative scores on a variety of skill tests. Examples of tools for assessing individual literacy include the Test of Adult Basic Education (TABE), the Adult Basic Literacy Examination (ABLE), the Wide Range Achievement TestRevised (WRAT-R), and the Test of English as a Foreign Language (TOEFL) (Nurss, 1998). These tests, although highly used by adult education centers, have been criticized for being inadequate at testing functional literacy skills. The focus of these tests is on reading ability, with little to no attention on comprehension or practical utility (Nurss, 1998). Various tools have been developed to address these shortcomings and approach literacy assessment from a functional perspective. Two of the most widely used tools are the Test of Functional Health Literacy in Adults (TOFHLA) and the Rapid Estimate of Adult Literacy in Medicine (REALM) (Nurss, 1998). Although designed for use in health care settings, both tests have been found to have wider applicability because of their focus on functional literacy. Population Literacy The primary mechanism used to measure population literacy in this country is the National Adult Literacy Survey (NALS), which is funded by the U.S. Department of Education and administered by the Educational Testing Service (Kirsch, Jungeblut, Jenkins, & Kolstad, 2001). This survey, which was last conducted in 1992, elicits a wide range of data on literacy rates including ethnic background, Illiteracy and Older Adults 83 socioeconomic status, work history, family trends, age ranges, and gender composition of the population. Rather than focusing on educational attainment as a measure of literacy, the NALS tests people according to their performance on tasks relating to everyday life. The structure of this survey involves three main categories of testing (prose, document, and quantitative literacy) that are used to garner a cumulative score (Kirsch et al., 2001). This cumulative score places the individual in one of five literacy levels, one being the lowest, and five being the highest. Level one includes those with minimal reading skills who cannot complete simple literacy tasks such as filling out an application, reading a food label, or reading a children’s book (LVA, no date). The second level of adult literacy includes the ability to compare, contrast, and integrate small chunks of information, but excludes the ability to complete more complex problem-solving tasks (LVA, no date). This is the level that Steve, the case study who is presented in a following section, tested into during a preliminary literacy assessment. The last three literacy levels (levels three through five) are characterized by an increasing ability to solve ever more complex tasks (LVA, no date). DEMOGRAPHIC PREVALENCE Findings of the NALS According to the results of the NALS, 23% of adults in this country are functioning at the lowest level of literacy. This translates into roughly 44 million adults who lack the basic skills to function and thrive (Weiss & Coyne, 1997). Of this population, 62% did not complete high school; more than 30% were over the age of 65; 25% were immigrants; and 26% had physical, mental, or other debilitating health conditions (Kirsch et al., 2001). The study also revealed that 25–28% of the adult population (or 45–50 million individuals) have level two literacy skills. Taken together, this means that more than half of the adults in America have reading skills well below the 8th grade level (Weiss & Coyne, 1997). Perhaps most striking are the findings reported on the highest literacy levels. In 1992, only 3% of adults surveyed exhibited level five literacy skills (Kirsch et al., 2001). While these figures are generally accepted, the ambiguous definition of literacy has resulted in numerous contested estimates of the magnitude of our national literacy crisis. Some statistics place the rate of illiteracy in this country much higher than the NALS, depending on the definition of literacy employed. For example, estimates offered by the Laubach Literacy 84 S. P. Roman Organization suggest that as many as 90 million Americans suffer from limited literacy skills (Byers, 1993). Although the statistics generated through the NALS have been contested, the results have provided invaluable insight into the characteristics of the illiterate population. Several predictors or variables related to literacy have been identified, including age, ethnicity, and socioeconomic status. Older Adults Age seems to be highly correlated to literacy among the American population. As a group, older adults have higher rates of illiteracy than any other age bracket. Data collected through the NALS classified 44% of adults over the age of 65 as functionally illiterate (Baker et al., 2002). It is likely that this predominance in the older population is a cohort effect rather than age-related. Because these cohorts grew up in a time when literacy was not a common value, many older adults lack the functional skills that have become necessary in today’s society. On average, adults over the age of 65 test a full level below adults aged 40–54 years old (Kirsch et al., 2001). Ethnic Background Largely a product of economic, social, and educational inequalities, literacy rates in America follow distinct demographic trends. Although illiteracy is present in every demographic group, African Americans exhibit the highest prevalence of illiteracy, followed by Hispanics, Native Americans, and Whites of lower socioeconomic status (Sissel, 1996). Although the rates of illiteracy are highest among African American and Hispanic populations, the numerical majority of illiterate adults are white (Weiss & Coyne, 1997). The incidence of illiteracy also seems to vary according to geographic location, with the highest prevalence of literacy problems occurring in rural communities. While rural residents only make up about 28% of the U.S. population, they account for some 42% of all functionally illiterate adults (Byers, 1993). Challenges in Recognizing Illiteracy One of the greatest challenges in fighting illiteracy is recognizing it. Identifying literacy problems among older adults is a difficult task because many of them hide their illiteracy and have a lifetime of practice in doing so (Weiss & Coyne, 1997). One older gentleman who sought literacy training at the site for this study had kept his illiteracy Illiteracy and Older Adults 85 a secret from everyone, including his wife of 50 years. Studies have found that up to 70% of illiterate adults have not told their spouse and over 50% have not told their children about their literacy problems (Nurss, 1998). This poses a significant challenge with regard to addressing our literacy crisis. INDIVIDUAL IMPLICATIONS OF ILLITERACY My goal’s in life first get my GED learn computers and spend time with my keds. Little do they know they are my strenth. Also give more time to God. Give him all thanks and prays (Steve, Journal entry, March 1, 2002). Shame and Frustration I began tutoring Steve twice a week through the local YWCA’s adult literacy program (all names have been changed). Consistent with demographic trends, Steve is an African American who dropped out of high school due to the birth of his first son. Now, his illiteracy has begun to jeopardize his career. This has motivated him to try again for his GED. When we first met, I was immediately struck by his enveloping sense of embarrassment and frustration. As he struggled to tell me why he had sought tutoring and what he hoped to achieve, he expressed shame towards his past and doubt towards his future. Steve’s story illustrates that illiteracy affects the individual on numerous levels, including at the workplace, as a consumer, as a parent, and in social situations (Heathington, 1987). Poverty and Unemployment One of the most serious implications of illiteracy for the individual is the inability to obtain employment and receive competitive wages. Researchers have found that there is a positive relationship between literacy level and employment stability and income. As workers, illiterate adults are at a serious disadvantage in today’s workplace. It is estimated that 75% of adults who are unemployed have limited literacy skills (Family Literacy, no date). Not only do illiterate adults have trouble with the application and interview processes, but their employment status is often jeopardized by changes in company policies and regulations (Heathington, 1987). Steve is a prime example of how problems with literacy can pose challenges to securing and maintaining employment. Steve was driven to the program at the YWCA out of necessity when he was disqualified for a promotion due to his technological illiteracy. Although he was given the chance to take a 86 S. P. Roman computer course that would qualify him for the position, Steve’s course application was denied due to his lack of a high school degree. Unfortunately, Steve’s story is not uncommon; adults with low literacy skills are frequently unemployed, work fewer weeks annually, and earn lower wages than individuals with high literacy skills (Kirsch et al., 2001). According to the NALS, average incomes among adults scoring at the lowest levels were less than one-third of the average incomes of those scoring at the highest level on the literacy scale. Adults with level one literacy skills earned an average of $240 per week, compared to $681 for those at the highest level (National Institute for Literacy [NIL], 1998). Almost half of the adults who scored in the lowest level were living in poverty, compared to only 4–8% of those in the two highest levels (NIL, 1998). Health Outcomes As consumers, adults with low literacy struggle to obtain health services, buy groceries, take medications, and pay bills, among numerous other daily tasks (Heathington, 1987). Perhaps the most serious implication of illiteracy is the barrier that is created between illiterate adults and the health care community. Studies have found that adults with literacy problems have poorer health, are more likely to take medications incorrectly or not at all, are less likely to have regular medical examinations, are more likely to work in hazardous occupations, have poor health habits, and are more likely to lack health insurance (Baker et al., 1997; Sissel, 1996). The link between health and literacy is of particular concern with regard to the older population. Not only does this population have the highest rates of illiteracy, it also has the highest rates of chronic disease and health-related complications (Baker et al., 2002). The implications of this are evident in data gathered through the Robert Wood Johnson Literacy and Health Care Project (Preston, 1995). Results of this study found that among older patients, 41.6% could not read instructions on how to take medications, 26% could not read or understand when their next appointment was scheduled, 59.5% could not understand a standard consent form, and 36.9% could not understand the application forms for the Medicaid program (Preston, 1995). Studies have also found that literacy offers some protective effects against memory decline in old age. The most well-known of these studies is David Snowdon’s longitudinal ‘‘nun study,’’ in which he analyzed the thought processes of a group of nuns throughout their life course. He discovered that the women who exhibited the most simple writing patterns in early adulthood were the most likely to develop Alzheimer’s disease in old Illiteracy and Older Adults 87 age (Fotuhi, 2003). Similar results were found in a collaborative study of the Rush Alzheimer’s Disease Center (Chicago), and the University of Pennsylvania. This study found that highly educated individuals have heightened resistance to the progression of Alzheimer’s disease. Highly educated people showed little to no sign of memory loss at time of death, despite high densities of plaques and tangles in their brain tissue, while less educated individuals showed significant memory loss with far fewer plaques and tangles present (Fotuhi, 2003). As a result of the barriers between illiterate adults and the health care community, they are more likely to find themselves needing hospital-level care. Because protocols for health maintenance and prevention strategies are often misunderstood by this population, the hospital is often the first line of health care, which is not only costly but often too little too late. A study of Medicare managed care enrollees found that those with inadequate literacy skills had a significantly higher risk of hospitalization than those with adequate literacy skills (Baker et al., 2002). Even when adjustments are made for other sociodemographic variables (age, income, and self-reported health), adults with the lowest literacy are more likely to be admitted to a hospital, have higher healthcare costs, and poorer overall health than those with adequate literacy (Baker et al., 2002; Weiss & Coyne, 1997). SOCIETAL IMPLICATIONS OF ILLITERACY The Bigger Picture of Illiteracy While illiteracy poses significant threats to the individual, there also are numerous societal implications. Illiteracy has adverse effects on families, the economy, and society at large. It has long been recognized that illiteracy is an intergenerational trend that is passed on from parent to child (Costa, 1988). Children whose parents did not complete school or have trouble with literacy skills are more likely to be illiterate themselves, and are more than five times as likely to drop out of high school as other children (Pages, no date). Illiteracy also imposes a considerable burden on the family or support system of the individual in question, as illiterate adults are highly dependent on others to function and survive. Family members often must do the grocery shopping, pay the bills, fill out forms and documents, and manage the financial affairs of illiterate relatives (Costa, 1988). Economic Impact Illiteracy also affects society at large through the financial burden that it imposes via lost productivity and increased taxes for welfare 88 S. P. Roman programs, prisons, and crime prevention programs (Pages, no date). Almost 50% of adults on welfare do not have a high school diploma or their GED (Pages, no date). Not only is this population more likely to need welfare, but they are often dependent for longer periods of time. There also seems to be a link between literacy levels and incarceration. Studies have found that seven out of 10 inmates perform in the lowest two literacy levels (NIL, 1998). Over half of these individuals cannot read or write at all and have not graduated from high school. Nowhere is the economic impact of illiteracy greater than on the health care system. As illustrated in the previous section, low literacy is associated with poor health, poverty, and a heightened risk of hospitalization. Because the hospital is often the first line of health care for individuals with literacy issues, and the majority are impoverished and uninsured, there is a significant strain on the healthcare system (Baker et al., 2002). People with low literacy skills are more likely to receive health care through public services, and the cost is often much higher. A study of Medicaid patients found that those who read at a 3rd grade level or less had average health care costs four times higher than the overall Medicaid population (Center for Health Care Strategies [CFHCS], no date). Considering the prevalence of illiteracy among the older population, and the impending growth in this segment of our society, the financial implications are astounding. It is estimated that the price tag of illiteracy in America is in the billions as a result of health care costs, low productivity in the workplace, and strains on the welfare system (Baker et al., 1997). DISCUSSION AND RECOMMENDATIONS As uncovered in the current study, there are several areas that warrant further research and development. Significant strides towards eradicating illiteracy and diminishing its effects could be made by changing our definition of literacy, the way we teach adult learners, and the standard of communication between the health care system and consumers. Individualized Instruction To make instruction in adult literacy more effective, more personalized or consumer-oriented materials are needed (Literacy Research Centers [LRC], 2001). Steve made frequent reference to his former tutor’s teaching methods that, according to Steve, would have made him take ‘‘ten years to get [his] GED.’’ This instructor had simply followed the Illiteracy and Older Adults 89 manual produced by the literacy center, and took no initiative to respond to Steve’s personal interests and goals. Tutoring needs to be made relevant to the individual student, and should be presented in a manner consistent with his or her learning style. In fairness to the preceding tutor, there are several programmatic issues that need to be addressed. Specific program limitations include a lack of resources, continuity of instruction, and as addressed earlier, antiquated definitions of literacy. Also, more efficient methods for teaching adult learners are needed to ensure that those who need help receive it. This involves improving the funding and organization of services to make them more stable, and thus reliable, resources to the illiterate population (LRC, 2001). Continuity seems to be the key: After receiving almost three years of tutoring at the YWCA, Steve feels as though he’s been running backwards because of the unreliability and limited tenure of all of his previous tutors. Programmatic Reform Innovation also is a primary need in the area of adult literacy training. In order to address individual needs and to ensure proficiency amidst rapidly evolving technology, innovative programs are a must (LRC, 2001). Efforts should be made to ensure that adult literacy students have access to the same technologies that are afforded public schools. Computers have introduced exciting potential into the world of adult literacy training. Computer-based learning has several advantages for the adult student. First and most apparent, interaction with a computer helps to introduce the student to a skill that has become necessary in the workplace (Askov & Clark, 1991). Second, computers allow for individualized instruction. Literacy software lets students work at their own pace and focus on material of interest to them. A number of software programs for adult literacy tutoring have been developed. A good source for comparing these programs is the Adult Literacy and Technology Project, which offers annual software evaluation guides (Askov & Clark, 1991). Additionally, the American Literacy Council (ALC) has dedicated its efforts to the development of literacy software. The goal of the Council is to produce literacy software and other technological aids that adults can use in the home, library, or school setting (ALC, no date). Because Steve is interested in ‘‘learning computer,’’ I decided to use one of these programs as the core of his curriculum. As completion of the GED is his ultimate goal, I wanted to find a tutorial that focused on the necessary skill sets. The National Council on Literacy has developed an on-line GED literacy kit hosted on the Public Broadcasting Service’s (PBS) website. 90 S. P. Roman The content of the site is divided into lessons in different skill areas, including reading, writing, comprehension, and mathematics. Students’ work is saved on their personal (and free) account, accessible only with a user name and password. Students are able to work ahead or complete homework assignments from remote locations, and tutors are able to access the student account in the same manner. This system has already improved Steve’s functional literacy after spending only three sessions on the program. Whereas he was initially afraid to touch the computer for fear that he would irreparably damage it, he can now turn on the machine, access the Internet and type in a web address. Because the software is relatively new, it was developed with the concept of functional literacy in mind. In preparing students for the GED, this tutorial gives students practice in everyday literacy activities. For example, one lesson required that the student access an on-line newspaper, locate a story of interest, and answer a series of essay questions regarding the content. Not only did this exercise help Steve improve his writing and reading skills, but it also helped him to become familiar with using the Internet and reading newspapers. Improve Communication in the Healthcare Setting Throughout the literature that explores the issue of health literacy, there is agreement that there is need for widespread simplification of health care and health-related materials. Because universal literacy is unlikely to occur, the health care system must be tailored to meet the needs and protect the interests of people with a wide range of literacy skills. Studies have found that basic medical paperwork (i.e., medical forms, treatment regiments, prescription labels, and insurance forms) are generally written at a 10th grade level or higher (Weiss & Coyne, 1997). To serve the population with limited literacy skills, health literature and instructions need to be re-written into simpler texts, ideally with graphic representations to reach a wider population (Baker et al., 2002). In addition to rethinking written materials, the use of non-written materials has great potential for reducing the incidence of miscommunication with illiterate patients (Weiss & Coyne, 1997). Examples of effective approaches include diagrams and pictures, audiotaped instructions, videotapes, and interactive computer programs (CFHCS, no date). In a study of older patients, those who received a simplified graphic version of a fluvaccination pamphlet were five times more likely to get the vaccine than those who were given the standard text-only version (CFHCS, no date). Studies also have found that patients with low literacy levels Illiteracy and Older Adults 91 can have difficulty understanding oral instruction due to limited vocabulary and poor problem solving skills (Baker et al., 2002). To address this reality, health care workers need to be trained to identify patients with literacy issues, and work with them to ensure comprehension (Nurss, 1998). Innovation: Who is Leading the Way? Several volunteer organizations have helped to reduce the prevalence of illiteracy through the development of tutoring programs for adult learners. The most well-known of these efforts are the Literacy Volunteers of America and Laubach Literacy Action (Davis, 1991). Another organization that has helped to make information about adult literacy and educational programs readily available is the National Institute for Literacy. This organization maintains a directory of state resources with links to every state’s adult education office, each state’s plan for addressing adult illiteracy, and the state literacy resource center (NIL, 1998). Several groups have also stepped up as advocates for adults with literacy issues in the health care setting. For example, the Joint Commission on the Accreditation of Healthcare Organizations (JCAHO) now requires that accredited providers take measures to ensure that all patients understand the information they receive (Weiss & Coyne, 1997). CONCLUSION Solving the problem of adult literacy is not as simple as developing more effective educational approaches. Over 90% of adults who fall into the lowest levels of literacy perceive their abilities as sufficient or even above average (Byers, 1993). If the majority of these adults do not recognize that they have a problem, they are unlikely to seek any sort of training. Addressing the issue of illiteracy among older adults will involve significant restructuring of programs that are targeted to this population. In addition to educational measures, steps must be taken to ensure that the needs of illiterate adults are met through public programs, businesses, and the health care industry. This may involve redesigning materials to accommodate the needs of those with limited literacy skills and training professionals to recognize literacy issues. Unless the technologies that are becoming commonplace in society are incorporated into these advances, illiteracy will have heightened consequences as the definition of literacy continues to evolve. 92 S. P. Roman REFERENCES American Literacy Council. (no date). Literacy figures. Retrieved September 10, 2003, from http://www.americanliteracy.com/literacyfigures.htm Askov, E., & Clark, C. (1991). Using computers in adult literacy instruction. In M. Radencich (Ed.), A compendium of articles from the Journal of Reading, (pp. 164–170). Delaware: International Reading Association. Baker, D., Gazmararian, J. A., Williams, M. V., Scott, T., Parker, R. M., Green, D., Ren, J., & Peel, J. (2002). Functional health literacy and the risk of hospital admission among Medicare managed care enrollees. 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