text:
Does Size Matter in Australia?*
THE ECONOMIC RECORD, VOL. 86, NO. 272, MARCH, 2010, 71–83 Does Size Matter in Australia?* ANDREW LEIGH Economics Program, Research School of Social S...
Author: Collin Anthony Hodge
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THE ECONOMIC RECORD, VOL. 86, NO. 272, MARCH, 2010, 71–83
Does Size Matter in Australia?* ANDREW LEIGH Economics Program, Research School of Social Sciences, Australian National University, Australia
MICHAEL KORTT School of Public Health, University of Sydney, Sydney, Australia
We estimate the relationship between hourly wages and two aspects of body size: height and body mass index (BMI). We observe a height premium, with an additional 10 cm of height being associated with a 3 per cent increase in hourly wages for men. However, workers with higher BMI scores do not seem to earn lower wages. These results are largely unaffected by controlling for physical health, or (in the case of BMI) instrumenting with the BMI of biological family members. A survey of previous instrumental variables studies shows little indication of systematic biases, suggesting that OLS may provide a reasonable estimate of the causal impact of BMI on wages.
for a variety of countries, we are not aware of any articles that have analysed the relationship between body size and wages in the Australian labour market. The issue is particularly salient given the well-documented rise in average body mass indices (BMIs) over recent decades. Between 1989–90 and 2004–05, the age-standardised proportion of overweight or obese Australian adults increased from 38 to 53 per cent (ABS, 2008).1 In this article, we exploit newly available data from the Household, Income and Labour Dynamics in Australia (HILDA) survey to analyse the relationship between height and wages and between overweight and wages for Australia. As well as providing the first results for Australia, we also take advantage of the fact that HILDA contains detailed questions on the health status of the respondent. This allows us to ask the question:
I Introduction Over recent decades, a substantial literature has arisen on the relationship between body size and wages, focusing particularly on height and overweight. Although this issue has been studied
* This article uses unit record data from the Household, Income and Labour Dynamics in Australia (HILDA) survey. The HILDA Project was initiated and is funded by the Australian Government Department of Families, Housing, Community Services and Indigenous Affairs (FaHCSIA) and is managed by the Melbourne Institute of Applied Economic and Social Research (MIAESR). The findings and views reported in this article, however, are those of the authors and should not be attributed to either FaHCSIA or the MIAESR. Susanne Schmidt provided outstanding research assistance. We are grateful to Giorgio Brunello, John Cawley, Paul Frijters, Steven Haider, Petter Lundborg, Satoru Shimokawa, Aydogan Ulker, Roger Wilkins, two anonymous referees and editor Paul Miller for valuable comments on earlier drafts. None of these people should be assumed to agree with the contents of this article, responsibility for which lies solely with the authors. JEL classifications: I10, J31, J71 Correspondence: Andrew Leigh, Economics Program, Research School of Social Sciences, Australian National University. Email: [email protected]
1 The increase was most striking among obese adults, with the proportion doubling from 9 to 18 per cent. The proportion of men classified as overweight or obese increased from 45 to 62 per cent, whereas the share of women who were overweight or obese rose from 32 to 45 per cent (ABS, 2008).
71  2009 The Economic Society of Australia doi: 10.1111/j.1475-4932.2009.00566.x
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controlling for self-reported physical health, do taller and slimmer workers earn more? In a companion article (Kortt & Leigh, 2009), we look at the socio-economic correlates of height and weight. From a theoretical standpoint, why should body size affect wages? One possibility is that for particular jobs, body size has a direct productive payoff. For example, a taller shop assistant may be able to reach the top shelf without needing a ladder, whereas a slimmer construction worker may be able to move more rapidly around the building site. It is also possible that body size has an indirect impact on productivity. For example, taller and slimmer workers might exude greater confidence in dealing with customers and co-workers, perhaps because others have treated them more favourably in the past. The final possibility is that shorter and more overweight workers might be subject to discrimination from customers, co-workers, or employers. Empirically, there is evidence from other countries that body size matters. Studies on overweight have found statistically significant relationships between BMI and wages in the USA (Register & Williams, 1990; Averett & Korenman, 1996; Pagan & Davila, 1997; Baum & Ford, 2004; Cawley, 2004; Han et al., 2009), the UK (Sargent & Blanchflower, 1994; Morris, 2006; Lindeboom et al., 2009), and other European countries (Sarlio-Lahteenkorva & Lahelma, 1999; Cawley et al., 2005; Brunello & D'Hombres, 2007; Lundborg et al., 2007; Garcia Villar & QuintanaDomeque, 2009). Studies on height and wages have found a positive relationship in Brazil (Thomas & Strauss, 1997), the UK (Harper, 2000; Case & Paxson, 2008; Case et al., 2009), and the USA (Loh, 1993; Persico et al., 2004; Case & Paxson, 2008). To preview our findings, we observe a height premium, which is larger for men than for women. We find no BMI penalty for Australian adults. These results are largely unaffected by controlling for physical health, or (in the case of BMI) instrumenting with the BMI of co-resident biological family members.
survey. For a detailed discussion of the quality of the height and weight data in HILDA, see Wooden et al. (2008). We are cognisant of the limitations of BMI as a measure of 'fatness' (for an excellent discussion, see Burkhauser & Cawley, 2008), but are not aware of better Australian datasets for our purposes at this time. We restrict our sample to respondents aged 25–54, dropping those respondents who are not employed, self-employed, enrolled in full-time education, or who did not answer the SF-36 health survey. We also drop pregnant women from the sample. Wage observations below half the federal minimum wage are dropped, since we regard these as implausibly low. 2 Our sample comprises about one-fifth of the respondents in the 2006 and 2007 waves of the HILDA survey. The dependent variable is log hourly wages. We control for a quadratic in age, indicator variables for whether the respondent was born overseas and whether the respondent is Indigenous, and the occupational status of the respondent's father at the time when he or she was aged 14. In the 2006 wave, occupations are coded using the four-digit Australian Standard Classification of Occupations (ASCO 1997), whereas in the 2007 wave, occupations are coded using the four-digit Australian and New Zealand Standard Classification of Occupations (ANZSCO 2006). The father's occupational status scale, developed by researchers at the Australian National University, ranges from 0 (lowest-status occupations) to 100 (highest-status occupations). The scale takes account of the average education and income levels in an occupation (for more detail on the methodology, see Ganzeboom et al., 1992; Jones & McMillan, 2001). We use this as a proxy for the individual's socio-economic background. There is some disagreement in the literature over whether one should also control for experience and education in a context such as this one. Although some studies looking at height have not controlled for these variables (see, e.g. Persico et al., 2004), studies focusing on BMI have typically
II Data and Empirical Strategy The data used in this article comes from the 2006 and 2007 waves of the HILDA survey, which are the only waves to have collected selfreported height and weight data. The major advantage of using HILDA is that it is one of the largest surveys in Australia to have detailed information on wages and body size as well as health status, as measured by the SF-36 health
2 In 2006, most respondents were interviewed between August and November 2006, when the federal minimum wage for workers aged 21 and over was $12.70 per hour, so we drop those earning less than half the minimum wage ($6.35). In 2007, most respondents were interviewed between August and November 2007, when the federal minimum wage for workers aged 21 and over was $13.47 per hour, so we drop those earning less than $6.75.
 2009 The Economic Society of Australia
DOES SIZE MATTER IN AUSTRALIA?
included them as covariates (see, e.g. Cawley, 2004). The central question is whether experience and education are a channel through which body size affects earnings (in which case one would not wish to control for them), or whether they are confounding variables that happen to be correlated with both body size and wages (in which case one would wish to control for them). 3 Here, we opt to control for experience and education, since this approach largely follows the previous literature; more readily permitting a comparison of our results with those from other countries.4 Since previous studies have sometimes observed differences in the effect of body size on the wages of men and women, we show pooled results and specifications that are estimated separately for men and women. All summary statistics and regression results are population-weighted. As measures of body size, we use self-reported height (in centimetres) and BMI (self-reported weight in kilograms divided by self-reported height in metres squared). To account for the possibility that underweight and overweight people may both be penalised in the labour market, we run regressions with BMI as a continuous variable and as a categorical variable. For the categorical measure of BMI, indicator variables were included for underweight (BMI < 18.5), overweight (25 £ BMI < 30), and obese (BMI ‡ 30). The reference group are respondents with a normal-range BMI score (18.5 £ BMI < 25).5 In some specifications, we also control for selfreported health status, measured through the SF-36 health survey. This 36-item survey is used to evaluate patients' health status across eight separate dimensions (Ware et al., 1993; Ohsawa et al., 2003). 3 Neal and Johnson (1996) argue strongly that when looking at labour market discrimination, one should not control for education and experience (on this point, see also Heckman, 1998). However, both those studies have the advantage of being able to control for a measure of cognitive ability, which is not available in the HILDA dataset. 4 There is some evidence from an Australian twin study that education has a causal effect on body size (Webbink et al., 2008), rather than the other way around. Consistent with this, the coefficient on the BMI score is negative and statistically significant in most specifications if we omit education from our regressions. 5 The collection of anthropometric data by self-report has often been shown to be subject to error (Spencer et al., 2002). One possibility is to adjust for this error, using the equations proposed in Hayes et al. (2008). Doing this has very little impact on our results.
We focus here on four physical health dimensions: physical functioning, role–physical, bodily pain, and general health. Our most extensive model (i.e. the specification shown in Table 3) is: Wi ¼ a þ b0 Si þ c0 Xi þ k0 Hi þ ei
ð1Þ
In Equation (1), W is the respondent's log hourly wage, S is a vector of body size measures, X is a vector of exogenous demographic controls (gender, age, age 2, born overseas, Indigenous, father's occupational status, experience, and education, plus a wave indicator), H is a vector of health status measures, and e is an i.i.d. error term. 6 All results are estimated using ordinary least squares (OLS). Since we observe the same individuals over multiple waves, standard errors are clustered at the person level to account for within-person serial correlation. (We also experimented with using lagged body size or average body size, and found that this made little difference to our results.) In Table 1, we report the summary statistics for the 3357 women and 3465 men in our sample. Among the women in our sample, 49 per cent are overweight or obese. Among men, 67 per cent are overweight or obese. These figures are slightly higher than the ABS estimates from the 2004–05 National Health Survey (ABS, 2008), though it should be borne in mind that our sample excludes individuals aged 18–24 and those who are not in employment. III Associations between Body Size and Wages In Table 2, we report the estimated association between log hourly wages and body size. To aid interpretation, we divide both height and BMI by 10, so the coefficients represent the marginal effect of a 10 cm increase in height, or a 10-point increase in BMI. For height (column 1), we observe results that are quite large, particularly for men. For women, each additional 10 cm of height is associated with a 2 per cent increase in hourly wages (statistically insignificant). For men, each additional 10 cm of height is associated with a 3 per cent increase in hourly wages. These effects are virtually unchanged when BMI is 6 We code years of education as the highest year of completed schooling if the respondent has no post-school qualifications (less than 8 years is coded as 8 years). Post-school qualifications are coded into years as follows: masters/doctorate ¼ 17 years; graduate diploma/certificate ¼ 16 years; bachelor degree ¼ 15 years; diploma ¼ 12 years; and certificate ¼ 12 years.
T ABLE 1 Summary Statistics Persons
Height (cm) BMI Underweight Normal weight Overweight Obese Log hourly wage
171.45 26.67 0.01 0.41 0.36 0.22 3.18
10.38 5.18 0.11 0.49 0.48 0.41 0.41
7.71 5.74 0.14 0.50 0.45 0.4 0.38
7.67 4.56 0.07 0.47 0.50 0.42 0.42
Note: Sample size is 3357 women and 3465 men. All statistics are population-weighted.
T ABLE 2 Wages and Body Size Dependent variable is log hourly wage [1] Panel A: Persons Height (cm)/10 BMI score/10 Underweight Overweight Obese Observations R2 Panel B: Women Height (cm)/10 BMI score/10 Underweight Overweight Obese Observations R2 Panel C: Men Height (cm)/10 BMI score/10 Underweight Overweight Obese Observations R2
0.001 [0.011]
0.022 [0.008]*** 0.004 [0.011]
0.022 [0.008]***
–0.032 [0.059] 0.025 [0.014]* –0.001 [0.015] 6822 0.22
0.015 [0.011] –0.003 [0.014]
0.001 [0.071] –0.01 [0.017] 0.025 [0.021] 3357 0.22
0.028 [0.011]** 0.008 [0.018]
–0.175 [0.064]*** 0.045 [0.021]** –0.023 [0.023] 3465 0.2
Note: Heteroskedasticity-robust standard errors, clustered at the person level, in brackets. ***, **, and * denote statistical significance at the 1, 5, and 10 per cent levels, respectively. All estimates are population-weighted. All regressions control for age, age 2 , indicator variables for whether the respondent was born overseas and whether the respondent is Indigenous, the ANU occupational status of the respondent's father at the time when he or she was aged 14, an indicator for whether the occupational status variable is missing, years of actual experience, and years of education. Panel A also includes an indicator variable for the respondent's gender.
added to the model (column 4). To put this into context, the average height of men in our sample is 178 cm (5 feet 10 inches). A male who is 183 cm (6 feet) tall is at the 75th percentile of the height distribution, and would be expected to earn a wage premium of 1.5 per cent. The average annual earnings of men in our sample is $63 200, so at the mean, another 5 cm of additional height is worth $948 per year. For BMI categories (column 2), the effects are close to zero and mostly statistically insignificant. Pooling men and women, overweight workers earn 3 per cent more (only statistically significant at the 10 per cent level), whereas the coefficients on underweight and obese are insignificant in the persons specification. For women, the coefficients for overweight and obesity are close to zero and statistically insignificant. Surprisingly, we find that overweight men receive a wage premium of 5 per cent. (Below, we analyse the possibility that this may reflect socio-economic biases.) We also find that underweight men suffer an extremely large wage penalty (18 per cent). The underweight estimate, however, should be regarded with some caution, since only 22 of the 3465 male observations in our sample fall into the underweight category. Perhaps to the disappointment of Wallis Simpson, 7 we do not observe any significant impact of being underweight on the hourly wages of women. In column 3 of Table 2, we allow BMI to enter linearly, and find that the coefficient on the BMI score is always statistically insignificant, and the point estimates are very close to zero. Importantly, the standard errors on our BMI score estimates are sufficiently small that we can reject (at the 95 per cent level) the hypothesis that a 10-point increase in BMI is associated with a wage rise of more than 4 per cent or a wage drop of more than 3 per cent. Graphical comparisons of a linear fit with a locally weighted regression (available upon request) show divergence only for very low or high BMI scores. Accordingly, we are inclined to prefer the null result from the linear BMI specification, and regard the statistically significant underweight and overweight coefficients for men in the BMI indicators specification (column 2) as potentially spurious. Lastly, we also include both height and BMI score in the regression (column 4), and find that the coefficients are very similar to the specifications in which the two variables enter separately. 7
Wallis Simpson, the Duchess of Windsor, famously noted that, 'A woman cannot be too rich or too thin.'
Although the R 2 statistics are around 0.2, very little of this is due to the inclusion of height and BMI. In all specifications shown in Table 2, the partial R 2 on the body size variables is less than 0.01, indicating that body size can explain less than 1 per cent of the wage variation between adults of the same gender, age, and ethnicity. As noted above, a number of previous studies that have looked at the relationship between hourly wages and BMI scores have found a statistically significant relationship for women (although the evidence for men is weaker and mixed). This raises the puzzle as to why there appears to be no association for men or women in Australia. One possibility is that there is no discrimination in the Australian labour market against overweight workers. Another possibility is that being overweight is so common that it has ceased to carry a wage penalty (this theory suggests that the wage penalty should also have attenuated in other countries). It is also conceivable that BMI is a less accurate measure of fatness in Australia than in other countries (on this point, see Burkhauser & Cawley, 2008), perhaps because Australians are more muscular than people from other countries. 8 A final possibility is that overweight Australian workers do suffer a wage penalty, but that this causal effect is cancelled out by high-wage workers also being more likely to become overweight (e.g. due to longer hours or because they eat richer foods). We address this possibility in Section IV below. Much of the public health literature on body size has focused on the relationship between obesity and health risks. Being overweight or obese is a risk factor for many medical conditions, including Type 2 diabetes, hypertension, coronary heart disease, elevated cholesterol levels, depression, musculoskeletal disorders, gallbladder disease, and several cancers (Bray, 1992; Pi-Sunyer, 1996). It is therefore useful to consider the extent to which health status affects the relationship between body size and wages. To measure health, we include four summary measures of physical health status derived from the self-reported SF-36 health survey (the physical functioning, role-physical, bodily pain, and general health indices). These regressions effectively allow us to ask the question: holding physical health constant, how much do height and BMI affect wages? 8
We are grateful to John Cawley for this flattering suggestion.
T ABLE 3 Wages and Body Size, Controlling for Health Status Dependent variable is log hourly wage [1] Panel A: Persons Height (cm)/10 BMI score/10 Underweight Overweight Obese Observations R2 Panel B: Women Height (cm)/10 BMI score/10 Underweight Overweight Obese Observations R2 Panel C: Men Height (cm)/10 BMI score/10 Underweight Overweight Obese Observations R2
–0.032 [0.059] 0.028 [0.013]** 0.005 [0.016] 6822 0.23
0.016 [0.011] 0 [0.014]
–0.001 [0.071] –0.008 [0.017] 0.03 [0.021] 3357 0.22
–0.183 [0.064]*** 0.048 [0.020]** –0.018 [0.023] 3465 0.21
Note: Heteroskedasticity-robust standard errors, clustered at the person level, in brackets. ***, **, and * denote statistical significance at the 1, 5, and 10 per cent levels, respectively. All estimates are population-weighted. All regressions control for age, age2, indicator variables for whether the respondent was born overseas and whether the respondent is Indigenous, the ANU occupational status of the respondent's father at the time when he or she was aged 14, an indicator for whether the occupational status variable is missing, years of actual experience, and years of education. Panel A also includes an indicator variable for the respondent's gender. Physical health status is proxied by four SF-36 indices: physical functioning, role-physical, bodily pain, and general health.
Table 3 shows the results of this specification. In all specifications, the coefficients in Tables 2 and 3 are very similar, indicating that there is very little evidence that self-reported health affects the returns to height or weight. (Even the positive coefficient on overweight men and the negative coefficient on underweight men are of similar size in both tables.) Taken together, these results suggest that to the extent that body size is associated with wages, most of the effect is not occurring via the impact of body size on physical health (at least as measured by the self-reported health status data available to us). This leaves open the possibility that shorter workers are subject to labour market discrimination. Our findings, however, are also consistent with other hypotheses,
such as the teen socialisation theory that Persico et al. (2004) proposed in the case of height and wages. 9 IV Addressing Potential Endogeneity To what extent should these associations be interpreted as the causal impact of height and BMI on wages? The two major concerns are: reverse causality (i.e. body size might itself be a 9
Persico et al. (2004) found that an individual's height in his or her teen years essentially determines the returns to height. They observed that about half of the wage differential due to height was accounted for by participation in school-sponsored non-academic activities, such as sporting activities and other clubs.
T ABLE 4 Sensitivity Test: Omitting Father's Occupational Status Dependent variable is log hourly wage
Height (cm)/10 BMI score/10 Observations R2
[1] With father's occupational status
[2] Without father's occupational status
0.022 [0.008]*** 0.004 [0.011] 6822 0.22
[3] Ratio [2]/[1] 1.2 0.8
Note: Heteroskedasticity-robust standard errors, clustered at the person level, in brackets. ***, **, and * denote statistical significance at the 1, 5, and 10 per cent levels, respectively. All estimates are population-weighted and include both males and females. All regressions control for respondent's gender, age, age2, indicator variables for whether the respondent was born overseas and whether the respondent is Indigenous, years of actual experience, and years of education. Specification in column 1 also controls for the ANU occupational status of the respondent's father at the time when he or she was aged 14, and an indicator for whether the occupational status variable is missing (the results are identical to those shown in column 4 of Table 2).
function of wages) and bias from unobservables (i.e. both body size and wages are affected by some other factor, such as socio-economic status or genetic attributes). These issues are of more concern in the case of BMI than height, but could potentially apply to both variables. 10 As noted in the previous section, even though we find no significant relationship between BMI and wages, it is possible that this null result reflects offsetting effects, in which higher BMI scores reduce wages, but higher wages also increase BMI. In this article, we address endogeneity concerns in three ways. Our first approach – which is primarily relevant for understanding the causal impact of height on wages – focuses on the concern that unobservable factors may be affecting both body size and wages. One way of gauging how large such unobservables would have to be is to see the impact on the body size coefficients of omitting the observable control for family background: the
10 In particular, reverse causality is unlikely in the case of height, which is fixed from an early age. According to Roche and Davila (1972), the median age at which growth in stature ceases is 21 for men and 17 for women. From ages 18–21, the median height increase in males is just 1 cm. Because most adults have stopped growing in height at a time when they have little or no labour market experience, it is improbable that wages have an impact on height. (From age 40 onwards, individuals tend to shrink in height very slightly, but we know of no evidence that this is related to wages.)
father's occupational status.11 Table 4 re-estimates the regressions without this control. When father's occupational status is omitted, the height coefficient increases by 20 per cent, whereas the weight coefficient drops by 20 per cent. This implies that adding father's occupational status to the regression reduces the impact of height on wages by one-fifth. Assuming that the omitted unobservables are uncorrelated with father's occupational status, this analysis suggests that they would need to have an impact five times larger than father's occupational status in order for them to entirely account for the observed association between height and wages. Our second strategy for addressing endogeneity – which is relevant to understanding the impact of BMI on wages – is to instrument the respondent's BMI with the average BMI of their biological family members. This approach, which is similar to the use of sibling BMI by Cawley (2004), has previously been implemented by Atella et al. (2008) and Brunello & D'Hombres (2007). Its purpose is to allow us to identify a source of variation in BMI that is primarily due to an individual's genetic propensity to become overweight. To the extent that biological family members share some of the respondent's genes, the BMI of biological family members provides a proxy for the genetic component of BMI.
11 The idea that the amount of selection on the observed variables provides a guide to the amount of selection on the unobservables is formalised in Altonji et al. (2005). We do not apply their approach here, due to the non-binary nature of the selection problem.
T ABLE 5 Instrumental Variable Results Dependent variable is log hourly wage
Panel A: Persons BMI score/10 Observations R 2 (centred R 2 in IV specification) F-statistic on excluded instrument Panel B: Women BMI score/10 Observations R 2 (centred R 2 in IV specification) F-statistic on excluded instrument Panel C: Men BMI score/10 Observations R 2 (centred R 2 in IV specification) F-statistic on excluded instrument
[1] OLS – full sample
[2] OLS – restricted sample
[3] IV
0.001 [0.011] 6822 0.22
–0.052 [0.070] 1996 0.23 57.36 (P < 0.01)
0.030 [0.032] 881 0.22
–0.184 [0.152] 881 0.17 15.08 (P < 0.01)
Note: Heteroskedasticity-robust standard errors, clustered at the person level, in brackets. ***, **, and * denote statistical significance at the 1, 5, and 10 per cent levels, respectively. All estimates are population-weighted and include both males and females. All regressions control for respondent's gender, age, age2, indicator variables for whether the respondent was born overseas and whether the respondent is Indigenous, the ANU occupational status of the respondent's father at the time when he or she was aged 14, an indicator for whether the occupational status variable is missing, years of actual experience, and years of education. Specifications in column 1 are the same as those in column 3 of Table 2. In column 3, respondent BMI is instrumented using the average BMI of biological family members who resided with the respondent in one or more waves of the HILDA survey.
If the results in Tables 2 and 3 reflect the offsetting impacts of BMI on wages and vice versa, then using plausibly exogenous variation in BMI should provide an unbiased (or at least less biased) estimate of the impact of BMI on wages. A good instrument should be correlated with the endogenous variable of interest (in this case, BMI), but uncorrelated with any other determinant of the dependent variable (in this case, wages). The latter condition is known as the exclusion restriction. One can imagine instances in which our instrument would fail to satisfy the exclusion restriction. For example, the HILDA survey does not contain a measure of ability. If ability is genetic, and if ability causes people to have higher wages and lower BMI scores, then the BMI of biological family members will not satisfy the exclusion restriction.12 However, 12 Previous researchers have sought to test this hypothesis in various ways. For example, Cawley (2004) found reassuringly little correlation of sibling BMI with ability-related outcomes such as years of education and IQ, whereas Lindeboom et al. (2009) observed a lower correlation between parent obesity and child obesity among adopted children (suggesting that the channel is mostly genetic rather than environmental).
other instruments for BMI also have their limitations. For example, child BMI will fail the exclusion restriction if low wages cause parents to feed their children fattier foods; family structure will fail the exclusion restriction if birth order and sibling gender have a direct impact on life outcomes; genetic markers will fail the exclusion restriction if they are correlated with genes that influence wages; and regional food prices may fail the exclusion restriction if they are driven by demand rather than supply. (Below, we compare the OLS and IV estimates obtained using these various approaches.) Table 5 shows the results from our IV strategy. Since the BMI of biological family members is only available for about one-quarter of respondents, we first estimate the OLS specification on this sub-sample (column 2) and compare it with the results for the full sample (column 1, which is the same as the results in column 3 of Table 2). The BMI coefficient is quite similar in both specifications. We then run an IV regression, using the average BMI of biological family members as the instrument. Although the F-statistic on the excluded instrument is high, the BMI results remain statistically insignificant for women, men, and in
the pooled specification. This result suggests that even the component of BMI variation which is most likely to come from genes does not have a significant impact on wages. A drawback of IV approaches for dealing with endogeneity is that they are most useful for analysing the relationship between continuous BMI score and wages, and are less well-suited to estimating the effect of BMI indicators (underweight, normal weight, overweight, and obese). 13 This leaves open the question of how we should interpret the significant coefficients on underweight and overweight for men. As noted above, graphical comparisons suggest that the relationship between BMI and wages for men is approximately linear across most of the data. Accordingly, our inclination is to place more weight on the null result from the BMI score regression than on the regression using BMI indicators. A third way of addressing endogeneity concerns – which is relevant to understanding the impact of BMI on wages – is to review what is known about the extent of OLS bias in other IV studies. If our failure to find a relationship between BMI score and wages is due to offsetting biases, then this may manifest itself in a systematic relationship between OLS and IV coefficients in previous studies. Table 6 sets out 28 point estimates from nine articles (including the present study) that have used instrumental variables to test the impact of BMI on wages or earnings. For each of these studies, we can observe the degree of bias in the OLS estimate by observing the ratio and difference of the BMI coefficients in the OLS and IV specifications. Of the 28 point estimates, 4 of the OLS estimates are smaller than their comparable IV estimates, whereas 24 are larger. The disparities between the estimates are sometimes very large, with the IV estimate occasionally being of a different sign, and sometimes an order of magnitude larger or smaller. As well as the biases having little systematic pattern, the IV estimates also tend to have much larger standard errors than the OLS estimates. Discussing this issue, Cawley (2004; 465–468) concludes: 'A Hausman test indicates that the 13
With a single instrument, we can only focus on one endogenous variable at a time. Thus while we could in theory use the BMI of biological family members to instrument for one of the four BMI categories, such an approach would require us to assume that the other three BMI categories were exogenously determined. (This critique also applies to the approach in Lundborg et al., 2007; Atella et al., 2008; Lindeboom et al., 2009.)
hypothesis that OLS and IV coefficients are equal cannot be rejected for any of the six race-gender groups. In other words, any endogeneity of weight does not appreciably affect the OLS estimates and OLS should be preferred to IV since OLS results in lower standard errors.' When we tabulate the results from Cawley (2004) and eight subsequent IV studies of BMI and wages, his conclusion seems to have stood up well. In our view, the preferred estimates from our article should be the OLS estimates, whose standard errors are considerably tighter than the IV estimates. As in the case of estimating the wage returns to schooling, it appears that the 'naı¨ve' OLS estimate is quite close to the truth.14 V Conclusion To answer the question posed by our title, body size does indeed seem to matter in the Australian labour market. We find that taller workers earn significant wage premiums, with the results being strongest for men. However, we find no significant relationship between BMI score and wages. Our results are very similar when controlling for a detailed set of selfreported physical health measures. The height premium we observe in Australia is smaller than in the USA and the UK. For women, we estimate that another 10 cm of height is associated with a 2 per cent increase in hourly wages. This is approximately equivalent to the wage returns from an additional third of a year of education, or another 4 years of labour market experience.15 By contrast, Case & Paxson (2008) find that women in the UK and the USA gain a wage premium of 5–8 per cent for each additional 10 cm of height. For men, we estimate that another 10 cm of height is associated with a 3 per cent increase in hourly wages (equivalent to half a year of education or 2 years of experience). By contrast, Case & Paxson (2008) estimate that UK and US men who are 10 cm taller receive a 4–10 per cent hourly wage premium (see also Persico et al., 2004, who find similar results for white men in the UK and the USA). 14 For surveys of the literature on IV and OLS returns to schooling, see e.g. Ashenfelter et al. (1999); Card (1999); Krueger and Lindahl (2001). 15 In the specifications shown in Table 2, column 4, we estimate that an additional year of education raises hourly wages by 7.3 per cent for women and 8.2 per cent for men, while an additional year of experience raises hourly wages by 0.6 per cent for women and 1.6 per cent for men.
T ABLE 6 Estimating OLS Bias from Various IV Studies of BMI and Wages Each coefficient is from a separate regression of log wages/earnings on BMI divided by 10 (or a dummy for overweight/obese if indicated)
b OLS
b IV
OLS Bias: b (IV) / b (OLS)
OLS Bias: b (IV) – b (OLS)
Is OLS < IV?
Atella et al. (2008) Instrument: Average BMI of biological family members European women – obese –0.050*** –0.065* European women – overweight –0.030*** –0.186* European men – obese 0.000 –0.337** European men – overweight 0.020*** –0.061
1.300 6.200 N/A –3.050
No No No No
Brunello & D'Hombres (2007) Instrument: Average BMI of biological family members European women –0.03*** –0.08** European men 0.04*** –0.13***
Cawley (2004) Instrument: Sibling BMI US white women US white men US black women US black men US Hispanic women US Hispanic men
–0.170*** –0.130 –0.020 –0.030 –0.120 –0.090
1.700 13.000 0.667 –0.500 2.000 1.500
–0.070 –0.120 0.010 –0.090 –0.060 –0.030
–0.802*** 0.310
Kortt & Leigh (this study) Instrument: Average BMI of biological family members Australian women –0.004 0.024 Australian men 0.008 –0.184
Lindeboom et al. (2009) Instrument: Parents' obesity status UK women – obese UK men – obese
–0.100*** –0.010 –0.030** 0.060** –0.060** –0.060**
Cawley et al. (2005) Instrument: Parents' and children's BMI US women –0.118*** US men 0.081*** Instrument: Parents' BMI German women –0.133*** German men –0.033
Lundborg et al. (2007) Instrument: Whether or not the respondent had only sisters European women – obese –0.090** –0.120 Instrument: Whether or not the respondent was an only child European men – obese –0.020 –0.860
Norton & Han (2008) Instruments: Sibling BMI and genetic markers US women 0.046 US men 0.012
T ABLE 6 (Continued) Each coefficient is from a separate regression of log wages/earnings on BMI divided by 10 (or a dummy for overweight/obese if indicated)
Study Shimokawa (2008) Instrument: Food prices Chinese women Chinese men Instrument: Children's weight Chinese women Chinese men Mean (excluding overweight/obese) Median (excluding overweight/obese)
–0.173 0.289 –0.155 –0.105 1.084 –0.078 Number of studies in which OLS < IV: Number of studies in which OLS > IV:
–0.163 –0.869*
Note: BMI coefficients reported in this table represent the coefficient on BMI/10 (i.e. the marginal effect on log wages of a 10-point increase in BMI), whereas coefficients for Atella et al. (2008), Lindeboom et al. (2009), and Lundborg et al. (2007) represent the effect on log wages of being overweight/obese. Mean and median estimates are unweighted, and only use the 20 BMI coefficients, not the 8 overweight/obese coefficients. The above numbers can be found in the following tables: Atella et al. (2008), Tables 2, 3, and 9; Brunello & D'Hombres (2007), Table 3 and A2; Cawley (2004), Tables 5 and 6; Cawley et al. (2005), Table 2; Kortt & Leigh (this study), Table 5; Lindeboom et al. (2009), Tables 2 and 5 (respondents aged 42); Lundborg et al. (2007), Tables 9 and 10; Norton & Han (2008), Tables V and VI; Shimokawa (2008), Tables 4 and 5.
Our finding that higher BMI scores are not systematically related to lower wages is at odds with the results for most other countries. For men, women, and in a pooled specification, a 10-point increase in BMI is always associated with less than a 1 per cent change in hourly wages, and the coefficient is never statistically significant. In an OLS specification, pooling men and women, we can reject (at the 95 per cent level) the hypothesis that a 10-point increase in BMI is associated with a wage change larger than ±2 per cent. By contrast, Cawley (2004) finds that among white men and women in the USA in 1981–2000, a 10-point increase in BMI is associated with a 1–10 per cent wage penalty in the OLS specification, and a 13–17 per cent wage penalty in the IV specification. For German respondents observed in 2002, Cawley et al. (2005) estimate that a 10-point increase in BMI is associated with a 3–13 per cent wage penalty in the OLS specification, and a 2–12 per cent wage penalty in the IV specification.16
16 We regard Cawley (2004) as the leading study of BMI and wages for the USA, and Cawley et al. (2005) as the leading study of BMI and wages for Germany. However, a few other estimates have found a positive association between BMI and wages (see Table 6).
We account for potential endogeneity in three ways. The first strategy is primarily aimed at the observed relationship between height and wages. Here, we explore the impact on our results of dropping a key observable variable – father's occupational status. Under the assumption that the unobservables are not correlated with this variable, this exercise provides some sense of how large the unobservables bias would have to be in order to entirely account for our observed effects. This suggests that unobservables would have to have about five times as large an effect on the height coefficient as father's occupational status in order for the unobservables bias to fully explain the association between height and wages. The second and third endogeneity exercises are focused on better understanding the absence of a relationship between BMI and wages. We instrument the respondent's BMI with the BMI of their biological family members as a way of identifying that portion of BMI variation that is driven by genetics. As in the OLS specification, we find coefficients on BMI that are insignificant and mostly close to zero. We then analyse nine IV studies (including the present study) of BMI and wages and find considerable variation in the difference between comparable OLS and IV estimates. Assuming that these results can be applied to
modern-day Australia, they suggest that our null result for BMI is unlikely to be driven by offsetting effects. This provides us with further reassurance that while there are wage returns to height in Australia, there are no systematic wage penalties to having a higher BMI. REFERENCES Altonji, J.G., Elder, T.E. and Taber, C.R. (2005), 'Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools', Journal of Political Economy, 113, 151–84. Ashenfelter, O., Harmon, C. and Oosterbeek, H. (1999), 'A Review of Estimates of the Schooling/Earnings Relationship, with Tests for Publication bias', Labour Economics, 6, 453–70. Atella, V., Pace, N. and Vuri, D. (2008), 'Are Employers Discriminating with Respect to Weight? European Evidence using Quantile Regression', Economics and Human Biology, 6, 305–29. Australian Bureau of Statistics (ABS) (2008), Overweight and Obesity in Adults 2004–05. Australian Bureau of Statistics, Cat no. 4719.0, Canberra. Averett, S. and Korenman, S. (1996), The Economic Reality of the Beauty Myth', Journal of Human Resources, 31, 304–30. Baum, C.L. and Ford, W.F. (2004), 'The Wage Effects of Obesity: A Longitudinal Study', Health Economics, 13, 885–99. Bray, G.A. (1992), 'Pathophysiology of Obesity', American Journal of Clinical Nutrition, 55, 488S–494S. Brunello, G. and D'Hombres, B. (2007), 'Does Body Weight Affect Wages? Evidence from Europe', Economics and Human Biology, 5, 1–19. Burkhauser, R.V. and Cawley, J. (2008), 'Beyond BMI: The Value of More Accurate Measures of Fatness and Obesity in Social Science Research', Journal of Health Economics, 27, 519–29. Card, D. (1999), 'The Causal Effect of Education on Earnings', in Ashenfelter, O. and Card, D. (eds), Handbook of Labor Economics. Elsevier, Amsterdam, Vol. 3A, 1801–63. Case, A. and Paxson, C. (2008), 'Stature and Status: Height, Ability, and Labor Market Outcomes', Journal of Political Economy, 116, 499–532. Case, A., Paxson, C. and Islam, M. (2009), 'Making Sense of the Labour Market Height Premium: Evidence from the British Household Panel Survey', Economics Letters, 102, 174–6. Cawley, J. (2004), 'The Impact of Obesity on Wages', Journal of Human Resources, 39, 451–74. Cawley, J., Grabka, M.M. and Lillard, D.R.A. (2005), 'A Comparison of the Relationship between Obesity and Earnings in the US and Germany', Schmollers Jahrbuch: Zeitschrift fu¨r Wirtschafts- und Sozialwissenschaften Journal of Applied Social Science Studies, 125, 119–29.
Ganzeboom, H.B.G., DeGraaf, P.M. and Treiman, D.J. (1992), 'A Standard International Socio-Economic IndexofOccupationalStatus',Social Science Research, 21, 1–56. Garcia Villar, J. and Quintana-Domeque, C. (2009), 'Income and Body Mass Index in Europe', Economics and Human Biology, 7, 73–83. Han, E., Norton, E.C. and Stearns, S.C. (2009), 'Weight and Wages: Fat Versus Lean Paychecks', Health Economics, 18, 535–48. Harper, B. (2000), 'Beauty, Stature and the Labour Market: A British Cohort Study', Oxford Bulletin of Economics and Statistics, 62, 771–800. Hayes, A.J., Kortt, M.A., Clarke, P.M. and Brandrup, J.D. (2008), 'Estimating Equations to Correct for Reporting Error in Height and Weight: Implications for Prevalence of Overweight and Obesity in Australia', Australian and New Zealand Journal of Public Health, 32, 542–5. Heckman, J.J. (1998), 'Detecting Discrimination', Journal of Economic Perspectives, 12, 101–16. Jones, F.L. and McMillan, J. (2001), 'Scoring Occupational Categories for Social Research: A Review of Current Practice, with Australian Examples', Work, Employment and Society, 15, 539–63. Kortt, M. and Leigh, A. (2009), 'Socioeconomic Correlates of Body Size Among Australian Adults', in Wilkins, R., Warren, D. and Hahn, M. (eds), Families, Incomes and Jobs, Volume 4: A Statistical Report on Waves 1 to 6 of the HILDA Survey. Melbourne Institute, Melbourne; 180–87. Krueger, A.B. and Lindahl, M. (2001), 'Education for Growth: Why and For Whom?', Journal of Economic Literature, 39, 1101–36. Lindeboom, M., Lundborg, P. and van der Klaauw, B. (2009), 'Obesity and Labor Market Outcomes: Evidence from the British NCDS', IZA Discussion Paper 4099, IZA, Bonn. Loh, E.S. (1993), 'The Economic Effects of Physical Appearance', Social Science Quarterly, 74, 420–38. Lundborg, P., Bolin, K., Ho¨ jga˚ rd, S. and Lindgren, B. (2007), 'Obesity and Occupation Attainment among the 50+ of Europe', in Bolin, K. and Cawley, J. (eds), Advances in Health Economics and Health Services Research Volume 17, The Economics of Obesity. Elsevier, New York. 219–52. Morris, S. (2006), 'Body Mass Index and Occupational Attainment', Journal of Health Economics, 25, 347–64. Neal, D.A. and Johnson, W.R. (1996), 'The Role of Premarket Factors in Black-White Wage Differences', Journal of Political Economy, 104, 869–95. Norton, E.C. and Han, E. (2008), 'Genetic Information, Obesity, and Labor Market Outcomes', Health Economics, 17, 1089–104. Ohsawa, I., Ishida, T., Oshida, Y., Yamanouchi, K. and Sato, Y. (2003), 'Subjective Health Values of Individuals with Diabetes in Japan: Comparison of Utility Values with the SF-36 Scores', Diabetes Research and Clinical Practice, 62, 9–16.
Pagan, J.A. and Davila, A. (1997), 'Obesity, Occupational Attainment and Earnings', Social Science Quarterly, 78, 756–71. Persico, N., Postlewaite, A. and Silverman, D. (2004), 'The Effect of Adolescent Experience on Labor Market Outcomes: The Case of Height', Journal of Political Economy, 112, 1019–53. Pi-Sunyer, F.X. (1996), 'A Review of Long-Term Studies Evaluating the Efficacy of Weight Loss in Ameliorating Disorders Associated with Obesity', Clinical Therapeutics, 18, 1006–35. Register, C.A. and Williams, D.R. (1990), 'Wage Effects of Obesity among Young Workers', Social Science Quarterly, 71, 130–41. Roche, A.F. and Davila, G.H. (1972), 'Late Adolescent Growth in Stature', Pediatrics, 50, 874–80. Sargent, J.D. and Blanchflower, D.G. (1994), 'Obesity and Stature in Adolescence and Earnings in Young Adulthood. Analysis of a British Birth Cohort', Archives of Pediatrics and Adolescent Medicine, 148, 681–7. Sarlio-Lahteenkorva, S. and Lahelma, E. (1999), 'The Association Of Body Mass Index with Social and Economic Disadvantage in Women and Men', International Journal of Epidemiology, 28, 445–9.
Shimokawa, S. (2008), 'The Labour Market Impact of Body Weight in China: A Semiparametric Analysis', Applied Economics, 40, 949–68. Spencer, E.A., Appleby, P.N., Davey, G.K. and Key, T.J. (2002), 'Validity of Self-Reported Height and Weight in 4808 EPIC-Oxford Participants', Public Health Nutrition, 5, 561–5. Thomas, D. and Strauss, J. (1997), 'Health and Wages: Evidence on Men and Women in Urban Brazil', Journal of Econometrics, 77, 159–85. Ware, J.E., Snow, K.K., Kosinski, M. and Gandek, B. (1993), SF-36 Health Survey. Manual and Interpretation Guide. The Health Institute, New England Medical Center, Boston, MA. Webbink, D., Martin, N.G. and Visscher, P.M. (2008), 'Does Education Reduce the Probability of Being Overweight?', CPB Discussion Paper 102. CPB Netherlands Bureau for Economic Policy Analysis, The Hague, the Netherlands. Wooden, M., Watson, N., Aguis, P. and Freidin, S. (2008), 'Assessing the Quality of the Height and Weight Data in the HILDA Survey', HILDA Project Technical Paper Series No. 1/08. Melbourne Institute of Applied Economic and Social Research, University of Melbourne.
Report "Does Size Matter in Australia?*"


text:
Report: Facebook considering its own bitcoin for payments
FILE – In this March 29, 2018, file photo, the logo for Facebook appears on screens in New York's Times Square. Facebook's effort to establish a service that provides its users with local news and information is being hindered by the lack of outlets where the company's technicians can find original reporting. The service, launched […]
The Wall Street Journal reports that Facebook plans a cryptocurrency-based payment system that it could launch for billions of users worldwide.
The system would use a digital coin similar to bitcoin, but different in that Facebook would aim to keep the coin's value stable. Bitcoin and similar cryptocurrencies have been susceptible to wild fluctuations in value.
It could reportedly undermine credit cards by sidestepping the processing fees that generate much of their revenue.
Related: Facebook to be fined $3 to $5 billion for privacy issues by FTC
The Journal report cited unidentified people familiar with the matter. It said Facebook is recruiting dozens of financial firms and online merchants to launch the network. Facebook's plans may include ways to financially reward users who interact with ads or other features.
Facebook says only that it is exploring many different applications for cryptocurrency technology.
More Technology Stories
Face App concerns: how to protect yourself and your data
by Suzie Hunter / Jul 17, 2019
(WTNH)--The FaceApp trend is taking selfies by storm -- no doubt, you've seen your friends' aged photos across social media. It's even caught on in our own newsroom.
But, when you download the app, do you know where your information is going?
Trending online: Photo editing app shows aging effect
by Vanessa Wojtusiak / Jul 18, 2019
(WTNH) -- Making rounds online through Facebook, Twitter and Instagram newsfeeds are photos of elderly-looking friends.
Those friends are experimenting with an app that has been around since 2017, but this self-proclaimed "state of the art photo-editor powered by AI" app has released new fun features; including one that allows you to meet your future self.
Feds skeptical of Facebook's cryptocurrency
by Raquel Martin / Jul 16, 2019
WASHINGTON (NEXSTAR) — Facebook wants to get into the money business, announcing last month that it plans to create its own cryptocurrency, but the idea is getting a lot of pushback on Capitol Hill.
"What could possibly go wrong?" a sarcastic Sen. John Kennedy, R-La., asked.

redpajama_set_name: RedPajamaCommonCrawl


text:
Former Analyst
Tim Crawford
CIO Strategic Adviser, AVOA
@tcrawford
Tim is a CIO and a member of a number of CIO organizations including the Wall Street Journal's CIO Network. Over the past 20+ years, Tim has served as CIO and other IT leadership roles for organizations such as All Covered/ Konica Minolta, Stanford University, Knight Ridder, Philips Electronics and National Semiconductor.
Tim is an internationally renowned CIO thought leader in the areas of IT transformation, Cloud Computing, Data Analytics and Internet of Things (IoT). Tim Crawford is ranked as one of the Top 100 Most Social CIOs (#7), Top 20 People Most Retweeted by IT Leaders (#5) and Top 100 Cloud Experts and Influencers. Tim is a strategic CIO & advisor to CIOs of large global enterprise organizations across a number of industries including financial services, healthcare, high-tech and major airlines. Tim's work differentiates and catapults organizations in transformative ways through the use of technology as a strategic lever.
Tim's extensive experience includes strategic planning, organizational development, governance, program and portfolio management that aligns with business strategy. Additional experience includes mergers and acquisitions, business development, strategic sourcing, compliance, information security and risk management.
Buyer's Lens
IT Maturity: The Key to Enterprise Cloud Adoption
CIO Report: Enterprise Data Protection
Navigating the Value of Hybrid and Multi-Cloud Strategies in the Enterprise
Introduction to Cloud Computing: A Primer to Understanding the Key Value and Opportunities from Cloud Computing for Government-based Organizations
Practical Approaches to Move Artificial Intelligence from a Black Box to a Strategic Asset
Gigaom Research + Cloudability AWS re:Invent re:Cap
Strategies for Simplifying Modern Work Management: Leveraging Artificial Intelligence to Simplify the Complexity of Today's Digital Work
Paul Stringfellow
Paul has over 25 Years of experience in the IT industry helping organizations to use technology to deliver business outcomes. Today that…	More
Michael Delzer
Michael is a visionary global leader who offers over 20 years of experience. Delivering competitive advantages from Start-Up ventures to Fortune-100 Corporations…	More
Matt Leib
After a long career as an enterprise engineer, Matthew endeavored into a new phase of his career, as a pre-sales architect. At…	More
Tim Crawford Oct 9, 2018 - 9:09 AM CDT
Tim Crawford Oct 30, 2018 - 9:00 AM CDT
The difference between Hybrid and Multi-Cloud for the Enterprise
Tim Crawford Oct 19, 2017 - 1:10 PM CDT


text:
Q: Which class is needed to specify encodeByte() method? I want to import my data from a csv file to hbase in java.  But I can't find the encodeByte method  in the Base64 class.  In the below line:
Base64.encodeByte(actualSeparator.getBytes())

I get an error.
Can you tell me which class needs to be imported or which file jar I need to inset in my library?

A: If you can use Apache-Commons Base64 Codec is really easy:

import org.apache.commons.codec.binary.Base64;

and using this line of code:

byte[] encoded = Base64.encodeBase64(actualSeparator.getBytes());

Main page of project and download page

redpajama_set_name: RedPajamaStackExchange


text:
Q: Regex Replace is not Working after adding another Variable I am trying to replace text in a div with the variable tagName. I had it working before but I added something and it stopped working. There is nothing wrong with the code so far as the console shows. Here is my replace function (tagName is the word in the replace that we are trying to get back to, and Color is the background-color given by a button).
function removeMark (tagName, Color) {
var tagNameC = tagName.toUpperCase();
var IndAry = tags.indexOf(tagNameC);
tags.splice(IndAry, 1);
var Notes = document.getElementById("NoteHolder").innerHTML;
var MarkBack = new RegExp("(\\b + tagName + \\b)", "gim");
var ColorT = '"' + Color + '"';
var MarkBackTo = "" + MarkBack + ""
var AfterRep = Notes.replace(MarkBackTo, "$1");
document.getElementById("NoteHolder").innerHTML = AfterRep;
var list = document.getElementById("myList");
var idmarker = "MarkID" + tagName;
var ElementID = document.getElementById(idmarker);
MarkList.removeChild(ElementID);
}

An example of what I am trying to replace is Test and I am trying to get it back to Test (test is tagName) Before I added the class to mark it worked perfectly but now it wont remove the mark!

A: I have a doubt in this code here. lets assume Color = 'YelBoxCol'; --> string variable
var ColorT = '"' + Color + '"';
// output is "YelBoxCol"; --> string variable but with double quotes in the string as well so something like '"YelBoxCol"'
var MarkBackTo = "" + MarkBack + ""
//output "yourRegex" --> you can see the double quotes in your class name.

That is the reason that your regex is breaking as it is not able to find the element with the class name "YelBoxCol" but there is a class name YelBoxCol , Not the difference in the quotes.
So change your code var ColorT = '"' + Color + '"'; To
var ColorT = Color;

OR
change the code var MarkBackTo = "" + MarkBack + "" to
var MarkBackTo = "" + MarkBack + ""

If this doesn't solve the problem then I sugget you to debug the code line by line, inspect the values in it and I am sure you will find out the issue, it is something small nothing major problem is seen in your code.

A: I don't know JavaScript very well, but I think it does not match because the class uses "" to mark it's name, but you're slapping extra '' in your regex.
Try
var MarkBackTo = "" + MarkBack + ""

A: I feel the way you build the RegExp is not right. Please try:
function removeMark(tagName, Color) {
  var tagNameC = tagName.toUpperCase();
  var IndAry = tags.indexOf(tagNameC);
  tags.splice(IndAry, 1);
  var Notes = document.getElementById("NoteHolder").innerHTML;
  var MarkBack = "(\\b + tagName + \\b)";
  var ColorT = '"' + Color + '"';
  var MarkBackTo = "" + MarkBack + ""
  var AfterRep = Notes.replace(new RegExp(MarkBackTo, "gim"), "$1", );
  document.getElementById("NoteHolder").innerHTML = AfterRep;
  var list = document.getElementById("myList");
  var idmarker = "MarkID" + tagName;
  var ElementID = document.getElementById(idmarker);
  MarkList.removeChild(ElementID);
}


text:
Vatican official flogs "secularized charity"
Archbishop Paul Josef Cordes is the president of the Pontifical Council "Cor Unum," which coordinates the Catholic Church's charitable institutions. ZENIT reports on a speech the prelate delivered at a Catholic university in Italy. Continue Reading...
'The look of love'
If I may, I'd like to highlight one more section from the Holy Father's new encyclical that has particular relevance to the work here at Acton (although, I agree wholeheartedly with Kishore below: one really must read the whole thing–it's fantastic): Love of neighbour is thus shown to be possible in the way proclaimed by the Bible, by Jesus. Continue Reading...
Pope Benedict on limited government
Pope Benedict's long-awaited first encyclical letter, Deus Caritas Est, was published this morning in Rome. The English translation of it can be found on the Vatican website by clicking here. Continue Reading...
A Catholic alternative to Europe's 'third way'
Proponents of social democracies claim that a large role for the state is important in tempering the profit motive of capitalism and creating a more humane and cultured state. Free markets, they argue, result in an inhumane and disintegrated society, while the social democracy models of Europe protect the weak and create social cohesion. Continue Reading...
Pope's address to World Alliance of Reformed Churches
It took place this morning in the Vatican. Click here for the text from the Vatican's website. Continue Reading...
Who is Pope Benedict XVI?
Despite his many writings, scholarly expertise and long service to the Church as Prefect of Congregation of the Doctrine of the Faith as Cardinal Joseph Ratzinger, there's still much of an unknown quality surrounding Pope Benedict XVI. Continue Reading...
George Weigel at Calvin College
On Jan. 6, Rev. Robert Sirico, president of the Acton Institute, will introduce author George Weigel at the Calvin College January Series in Grand Rapids, Mich. Weigel's topic will be "Revolutionary Papacies: John Paul II, Benedict XVI, and the Future of the Catholic Church." Continue Reading...
To counter social ills…
The separation of church and state–that slippery topic–was dealt with recently with simplicity by the Holy Father. In speaking to the US Ambassador to the Vatican regarding ethics in politics, he said: "The disturbing spread of social disorder, war, injustice and violence in our world can ultimately be countered only by renewed appreciation and respect for the universal moral law whose principles derive from the Creator himself." Continue Reading...
German thought and the Vatican
In today's Times of London, William Rees-Mogg writes about the Vatican and its apparent rejection of intelligent design. Rees-Mogg also makes this provocative claim about Pope Benedict and some possible surprises from this new pontificate: His critics had expected him to be more conservative than his predecessor. Continue Reading...
New site for Catholic social doctrine
The Verona-based Van Thuan Observatory has recently launched its website, reports the Zenit news service. The Observatory's namesake, the late Cardinal Van Thuan, was the recipient of the the Acton Institute Faith and Freedom Award in 2002. Continue Reading...
< Previous 1 … 35 36 37 38 39 … 41 Next >


text:
OwnInvestGiveCollectExperience
https://www.barrons.com/articles/designer-vivienne-tam-bridges-the-gap-51576263600
Designer Vivienne Tam Bridges the Gap
Joseph V. Amodio
Dec. 13, 2019 2:00 pm ET
Photograph by Nicholas Hunt/Getty Images
They say you can never go home again, but don't tell that to Vivienne Tam.
The Chinese-American luxury womenswear designer—born in Guangzhou, China, and raised in Hong Kong—first made a name for herself in the 1990s, with her culture-bridging dresses embroidered with Chinese motifs, or splashed with quirky (and controversial, at the time) faces of Mao Zedong. She based her business in New York, and gained a reputation for bringing an Eastern sensibility to the West.
Now she seems to have flipped that on its head, bringing her collections—which are China-inspired but infused with a fresh, free-wheeling Western sensibility—back East.
Tam, who is in her early 60s, recently made concerted efforts to expand her influence into China, selling her brand's Chinese operations to the apparel giant Shenzhen Ellassay Fashion in 2017 for 37 million Chinese yuan (about US$5.5 million). She has since opened 13 stores in China, which join her six shops in Hong Kong, and 22 in Japan, Thailand, Singapore, and the Philippines.
Over the years, Tam has maintained a commitment to tech-y collaborations, from flower-print laptops designed for Hewlett-Packard in 2008, to this year's line of phone cases and watchbands for Huawei's Honor smartphone brand.
And, as Penta learned when we recently checked in with her, she has also kept up her philanthropic efforts, supporting groups as varied as the Coalition for Asian American Children and Families, the Friends of China Beauty Charity Fund, and a Save the Panda fashion auction sponsored by Elle magazine.
Penta: Given the vast number of charities out there, how do you decide, as a business owner, which to support?
Vivienne Tam: I let my heart guide me. I think that's quite important. Recently, I'm focused on women's empowerment. I worked with Women Helping Women [a nonprofit group fighting gender-based violence]. I also did a fashion show with LEAP [the Hong Kong–based Life Education Activity Programme] to raise money and awareness about drug abuse. And I do the T-shirts promoting AIDS Walk in Hong Kong every year. I like to use my design skill to help. I design special dresses or products, or hold fashion shows that raise money.
Rather than just writing a check.
That's very dry. The other is more emotional, more…I don't really know how to say it.
More soulful?
" Fashion, art, music—all these things can bridge cultures and minds." "
From my own soul, my desire. But different people have different ways of helping. This is my way.
You're also known for your collaborations with tech companies. Are you a tech junkie?
No, I'm not at all. [She laughs.] Totally not. Technology for me is so cold and dull. Just gray and black. Fashion gives it more color, more personality. You remember the HP peony-print computer? You put that on your desk [and it's] like you're sitting in a garden.
Collaborations are huge in the fashion industry now—but usually it's two fashion brands joining forces. Neither side has to reinvent the wheel. How tough is it for you to work with a tech firm? Do you feel out of your element?
There was a big challenge, doing that first computer with so many colors in the peony design. It took a long time for them to [figure out how to] print that on the surface. They had to find different materials, different factories—they'd never worked with that many colors. It's always a challenge, working with another company, especially when it's not in my comfort zone. [We both learned] a lot about the limitations, materialwise, and the possibilities. And the people—I meet such interesting people that become friends. That's what I love.
You've often said that fashion, as an industry, is unique in that it can bridge cultures. Are you still optimistic about that?
Oh, definitely. It has that power. Fashion, art, music—all these things can bridge cultures and minds. The thing about fashion is everybody needs it. I mean, every day we need to wear something. [She laughs.] Fashion has the power to connect people, to define a sense of identity for a generation. When you wear clothes [you like], you're happy. That's important. It's very interesting now. In fashion, you see a mix of cultures.
Like with your line.
It's much more inclusive. There's a sense of freedom to wear what you like. And I think sustainability—how we connect to the environment—is really important now, too. As a fashion designer, this is our responsibility.
Can sustainability unify us? In these divisive times, it seems we need a common goal.
If you want to do it, your staff, your team, has to cooperate. We have to work together in order for it to be successful. Even the pins we use a lot, they drop so much on the floor. I told [my staff] there's so much waste, and this is part of it. It's just pins, right? But we've got to stop being lazy and pick them up. [She laughs again.] That means sometimes I'm the one that has to pick 'em up.


Our project started out great then something went wrong at the office and our project manager vanished. Since then the company has blamed me and my wife for the job not getting done. They dont even know what the job is. This am I was told it wasnt done because our hail damage insurance claim didnt cover it. We dont have a hail damage claim. Someone elses job. I gave a bad review on social media and was offered a $500 discount only if I remove my social media complaints. I have now gone to the BBB and put a formal complaint. See the last paragraph below. He later said its wasnt a bribe.
Contacted Roof Hospital to inspect and repair bathroom roof vent which began leaking after the recent heavy rain storm. Emailed for a quote on a Wednesday night which was followed up with a phone call by the company the next morning with a repair estimate. Based on the foregoing booked a service call for the following morning. Adam the representative was on time and performed the required repair in addition to repairing some other areas where he noticed could cause leaking problems in the future. Bottom the overall service was excellent and I will not hesitate to recommend the company to anyone requiring future roof repairs.
We called the Roof Hospital on a Sunday evening and by Monday morning 9am our issue was fixed. Amazing service. Can not say enough good things anout this company. I hope we don't have any roof issues again, but if we do, we know we will be using the Roof Hospital again.
I called the Roof Hospital to check out moisture issues we were having with our roof. The roof on our house is a bit higher than normal - so I was only interested in hiring experienced roofers. A lot of the other companies I had contacted said that they wouldn't be able to help because of the height of our roof. Not an issue for this company. They came right out, and I had my leak issue fixed right a way. The guys that came out were friendly and knowledgeable. Would definitely recommend this company.
From the initial consult to the final bill things were good. There were some slight damages that the owner of the company came out and fixed promptly. I would use them again with no concerns at all. I only gave 4 stars as I am really picky about service and product. Great job done by roof hospital.
I contacted Roof Hospital to inspect my roof before putting the house on the market for sale. Nigel was very prompt and professional. He performed a thorough inspection inside and out. He found a problem with the flashing on the main chimney stack, took extensive pictures to show me and repaired the flashing. He left our house neat and clean, even had his own vacuum to clean up the bits of attic insulation that fell out when he was inspecting the attic. I would highly recommend Roof Hospital for any future roof work.
Nigel at Roof Hospital was open & honest when giving a quote for the work. Once we had chosen to go ahead with it, it was done quickly & photos were provided to show before & after since We couldn't easily examine the work. It was a pleasure to work with Nigel & I would recommend the Roof Hospital to friends & family.
very good they did what I was expected and beyond, for sure I recommend to any body that need to change the roof .
Replace the shingles on roof that the Roof Hospital guaranteed for life. The crew that can did a good job and the supervisor came after job was done to check the job with me.
Roof Hospital has not added any photos.
The Roof Hospital is a Calgary roofing contractor company specializing in roof repairs, roof replacements, siding, soffit, facia and eaves troughs. We work with asphalt shingles, skylights, rubber roofing, vinyl and hardie board siding, metal roofing, cladding etc.


Hoda Al-Helaissi, female Saudi academic and member of the Shura—the Kingdom's Consultative Assembly—looks at the transformation of her country with a decidedly optimistic eye. In this interview, she ponders over her country's economic and societal progress, a nation that yearns for balance between modernity and conservatism.
How is the role of women in Saudi Arabia changing?
Hoda – We are in the process of changing and evolving. It's largely thanks to our youth. Women's roles are also changing, because we are not stagnant.
Through education, we have seen that a lot of women want to hold higher and higher positions of power, and also want to be a part of the decision-making process. Making nation-wide decisions on the policy-, society-, or the family-level…There's an ongoing evolution, which can be witnessed, and it is very important for women.
Hoda – It's a city full of change, and motion. It's a modern city, with a typically Saudi identity, where the locals represent an older Saudi Arabia. This is important because I believe that, even with our modernity, we shouldn't change who we are. We respect our laws. We respect our identity. We respect our religion and who we are, our roots.
It's very important for young people to understand this. Living in a modern society that is globalized, does not mean forgetting what was important to the generations before us, and those ahead of us as well.
This change, how is it coming around?
Hoda – The past 10 years have brought about big changes. That's for sure. But over the past 3 or 4 years the changes have been unbelievable, especially because the young people are pushing the changes forward.
The activities, events, and all that is quite commonplace in Europe or the West, have started to make big waves in our country. And it's interesting because practically in all sectors, we find quick adoption by the youth.
How can modernity and religion coexist?
Hoda – I think it's very important to understand that religion is a part of our identity. It's not something that will prevent us from evolving, changing, and being modern. I believe that it's completely feasible. Especially when you understand that our religion is not an extremist one. If we find a middle ground, we can adapt and succeed.
Tell us about the three priorities of Vision 2030.
Hoda – Women, the youth, and the economy. I believe those are the three keywords that will change Saudi Arabia. But it will take time. It will take as long as it takes to reach a certain goal, or move in a certain direction. The youth, because 60% of our country is under 30 years old. Women because they are growing steadily stronger, more capable, and more skilled. In particular, 52% of those enrolled in higher education are women.
And the economy, simply because we can no longer live in the luxury that existed before. And so, women must work. And the economy will push people to become entrepreneurs or to become more involved in their field of work.
What issues is the Shura tackling?
Hoda – Mentalities are changing, that's for sure. Issues related to women's rights—of course—will take a little longer, like the issue of women driving. It will come. It's coming, for sure.
But we must adapt and understand the importance of tradition in the typical mindset, not only in the country but also that of those working in the Shura. It is important to understand that it's up to these people; whether or not to effect change. So, it's a matter of time, but societal change is speeding up.
How have stereotypes of the Saudi women evolved over time?
Hoda – I believe the most difficult and the most dangerous thing in the world today is to live by stereotypes. Unfortunately, that is a part of human nature. I remember in the 60s, Eastern women were considered exotic: there was an American show called "I Dream of Jeannie" where women wore multicolored headscarves. Quite the little magician.
Over time, this image has been replaced by a very dark image of the Eastern woman. In a black veil, with her abaya.
Obviously voiceless. Abused, unable to go out, or work, or to do anything. These stereotypes are dangerous to us, because they don't reflect reality.
Sure, there are some traditional, super-religious women who prefer to stay in this limited framework. But the majority, and especially the young people, flat-out refuse this kind of life.


She was married to Lowell Rudolph Nelson. Said to later have married to man last name Clair. Some records show she also used last name of Cutler. When she died her last name was Foley.
I'm looking for information about her husbands/partners and where she is buried. Looking for more information about her daughter, Dorrene Clair Lamb.
She was born in Minnesota. Died in California. Last address was Yuma, Yuma, Arizona.
Any information about these people would be greatly appreciated.
Here is an extract from an obituary. Maybe you can find the full obit in the Grand Rapids Herald-Review in March 2000.
"United States, GenealogyBank Obituaries, 1980-2014," database with images, FamilySearch (https://familysearch.org/ark:/61903/1:1:QKGW-NZWF : 26 October 2016), Dorothy Hart Nelson Clair Foley, Minnesota, United States, 19 Mar 2000; from "Recent Newspaper Obituaries (1977 - Today)," database, GenealogyBank.com (http://www.genealogybank.com : 2014); citing Grand Rapids Herald-Review, born-digital text.
This seems to be Dorothy's family in the 1930 census.
"United States Census, 1930," database with images, FamilySearch(https://familysearch.org/ark:/61903/1:1:X389-K5F : accessed 29 January 2017), Lowell Nelson, Bovey, Itasca, Minnesota, United States; citing enumeration district (ED) ED 12, sheet 13A, line 44, family , NARA microfilm publication T626 (Washington D.C.: National Archives and Records Administration, 2002), roll 1102; FHL microfilm 2,340,837.
Thank you. Yes, very little information is coming up from searches. She moved around alot and had several partners/husbands.
Is anyone familiar with the Clair or Snider side of my family to know if they were Native American ethnicity?
Mary (Barnard ??) King Cutler. Maiden name?
Advice before editing this pre-1700 Cutler profile?
ABSALOM CUTLER born 1855 nfld ,does naybody know who he married,ended up ih halifax ns 1905.
looking for information about Cutler family in Ann Arbor or Detroit MI around 1900.
Allan Benjamin Cutler, Born Oct 13 1919, My Father in Law, I'd like to know all I can about him.
Looking for the parents of Raymond Joseph Foley Sr. b. NY, 31 Aug 1899, son of John and Mary, d. Manhattan Apr 1966.


Growth of a biofilm of the bacteria Bacillis subtilis over four days.
When energetic protons enter tissue, they release most of their energy as they come to rest. Damage to nearby organs and structures can be minimized.
A population of slime-mold cells forms an aggregate in response to a signaling molecule.
At the center of a cyclotron, a charged particle travels through a magnetic field that curves its path into a spiral and out of the cyclotron at a high speed.
Random motion of gas molecules—bottom up.
Rotational entropy is related to the number of possible ways particles can be arranged in a structure. The greater the number, the greater the entropy.
There are different kinds of entropy. Vibrational entropy describes the number of ways that a structure can flex or vibrate without breaking.
In some viruses the capsid appears to be completely self-assembled. Understanding capsid self-assembly could present new ways to fight disease.
The left panel shows the projected image of students and professors who participated in the project, and the right panel shows the bacterial photo.
Rainbow images showing individual neurons fluorescing in different colors. By tracking the neurons through stacks of slices, we can follow each neuron's complex branching structure to create the treelike structures.
The variation in Galapagos finches inspired Charles Darwin's thinking on evolution, but may evolve too fast for his theory.
A chicken egg. Is it alive or dead?
In 1848, a steel rod shot through the left cheek the Phineas Gage and exited through the top of his head. Gage never lost consciousness and lived another 13 years.
As a glass cools, the viscosity increases so rapidly that the atoms get frozen in a disordered state.
As polarized light passes through corn syrup, which is full of right-handed sugar molecules, its plane of polarization is rotated.
A Rubik's Cube is a familiar example of a hierarchical distribution of states.
Cartilage from the fin of the Mako shark.
Colored smoke marks the hydrodynamic flow around an aircraft, an emergent phenomenon.
This sequence logo is a compact way of displaying information contained in a piece of genetic material.
A schematic view of what constitutes a complex adaptive system.
Schematic of a modern digital computer.
The DNA double helix, in three of its possible configurations.
Here, we see two possible paths across an energy landscape strewn with local minima.
The enzyme on the left has a much easier time reading DNA than the enzyme on the right due to structural details that are difficult to predict from first principles.
Natural selection can be viewed as movement on a fitness landscape.
This simple system of three spins is frustrated, and has no clear ground state.
The structure of myoglobin (left) and the form it actually takes in space (right).
Sewall Wright sketched the path different populations might take on the fitness landscape.
Two possible conformations of a prion protein: on the left as a beta sheet; on the right as an alpha helix.
A schematic of how minimizing the free energy of a molecule could lead to protein folding.
The circuit diagram (top), bacterial population (center), and plot of the dynamics (bottom) of the repressilator, an example of a simple synthetic biological network.
The chemical structure of RNA (left), and the form the folded molecule takes (right).
Molecules of life: RNA (left) and DNA (right).
An optimal travelling salesman problem (TSP) tour through Germany's 15 largest cities. It is the shortest among 43,589,145,600 possible tours visiting each city exactly once.
Player C is trying to determine which player—A or B—is a computer and which is a human.


To the surprise of some friends who hold the coffee bean as an elixir of religious proportions, on most days I wait to get to the office for my first cup of morning coffee. But on Saturdays I enjoy one of life's uncomplicated rituals of brewing a pot and easing into the weekend.
The society most of us live in affords us these simple pleasures as well as some that aren't so simple. Especially in the U.S., we embrace the right to expect a reward for our hard work and the prizes that come from the fruits of our work. The expectation of this quid pro quo doesn't exist everywhere, especially in many places outside the U.S.
The magnitude of these global challenges, beginning with population growth, energy, and water, makes the notion of putting even a minor dent in them seem daunting.
Positive reviews of Abundance—The Future is Better Than You Think, co-written by the founder of the X Prize Foundation, Peter H. Diamandis, last year cited the book for its optimistic vision of our own ability to help improve the world.
Diamandis and his co-author, Steven Kotler, make the point that we're now living in a world of information and communication abundance. For example, a Masai warrior with a cell phone, they say, has a better mobile phone than the president of the United States did 25 years ago.
It is encouraging to believe that it is within our own ability to create change. For me, Abundance is not so much inspirational as it is reinforcing. But I'm lucky. I've got a first-hand view of our own ability to move the needle on a macro scale. A focus on curating the intellectual capital of engineers, designers, and other important stakeholders has turned ASME into one of those global change agents, and has empowered those of us close to the organization to make a difference.
He believes that the world's growing population will have the power to solve many of the problems in front of them, and that everyone deserves to expect the fruits of their work—now that's inspirational.


Digital Foundry – Batman: The TellTale Series Analysis – 3WIREL!
Digital Foundry takes a look at how both the PS4 and Xbox One versions of TellTale's Batman series and they have poor performance. Low resolutions on both platforms and unstable frame rates being the big issues. This is running on a new engine for TellTale, so one would think these issues would not be present, considering this new version of the Telltale engine was made to avoid these issues from past titles they made.