Drakopoulos, S., & Grimani, K. (2017). Labor earnings reductions, happiness levels and needs hierarchy. International Journal of Wellbeing, 7(1), 23-39. doi:10.5502/ijw.v7i1.540 Stavros Drakopoulos National and Kapodistrian University of Athens sdrakop@uoa.gr Copyright belongs to the author(s) www.internationaljournalofwellbeing.org 23 ARTICLE Labor earnings reductions, happiness levels and needs hierarchy Stavros Drakopoulos · Katerina Grimani Abstract: One of the main economic outcomes of the recent Great Recession has been the decrease of labor earnings in many countries. The relevant literature indicates that earnings and other socioeconomic predictors can influence levels of happiness. This paper tests the effect of pay cuts on happiness levels based on the psychological model of hierarchical needs. The basic idea of hierarchy is that the most important needs must be satisfied first before the secondary needs come into the picture. In a happiness research framework, this implies that for higher income levels, the effect of pay cuts on reported happiness levels becomes much weaker, given that the satisfaction of non-basic needs becomes important. The data used in this paper was drawn from the 5th European Survey on Working Conditions, which focuses on European countries. Two different disaggregation methods were performed, based on absolute nominal income threshold and relative income threshold, respectively. The methods for analyzing the data are the ordinary least- squares (OLS) regression model, and the Wald chi-square test. The pay cuts are a stronger predictor of happiness for low/middle income individuals than for high income individuals when it comes to disaggregation based on absolute threshold. The regression coefficients of pay cuts for the low/middle income group were not significantly different from those for the high income group regarding disaggregation based on relative threshold. The results seem to depend on the disaggregation method, implying the need for further research and discussion. Keywords: pay cuts, happiness, subjective wellbeing, Maslow’s Hierarchy of Needs 1. Introduction One of the main characteristics of the Great Recession of 2008 was the reduction of labor earnings in many countries for a substantial number of employees (Jenkins et al., 2013). Apart from the obvious effects of pay cuts on the purchasing power and living standards of individuals and households, falling labor earnings must also affect happiness levels, given that rising income has been shown to have a positive relationship to happiness (Sloane & Williams, 2000; Helliwell, 2003; Gasper, 2005; Clark et al., 2008; Stutzer & Frey, 2010). Happiness (or life satisfaction) has been defined as a combination of feeling good (hedonic perspective) and functioning effectively (eudemonic perspective). The hedonic component is concerned with subjective experiences of pleasure, while the eudemonic component is concerned with fulfillment and the realization of human potential and actualization (Deci & Ryan, 2008; Steptoe et al., 2008; Huppert, 2009). Understanding the happiness (or job satisfaction) of employees is important because work exhibits a substantial psychological dimension for self-identity and sense of purpose, given that adults spend an average of about 33.6 hours per week at work (Kahneman et al., 2004; Tay & Harter, 2013). Improving the happiness levels of the workforce has important social and economic effects, since it brings benefits for both the employees and the organization, and http://creativecommons.org/licenses/by-nc-nd/3.0/ The effect of labor earnings reductions on happiness Drakopoulos & Grimani www.internationaljournalofwellbeing.org 24 influences an individual’s social behavior, employment relations and productive performance in the workplace (Danna & Griffin, 1999; Lyubomirsky et al., 2005; Grant et al., 2007; Panos & Theodossiou, 2007; Wesarat et al., 2015). High levels of psychological wellbeing at the workplace allow employees to flourish and achieve their full potential for the benefit of themselves and their organization (Grant et al., 2007; Wesarat et al., 2015). In empirical work, reported subjective wellbeing is taken as a proxy measure for individual welfare and individual happiness (see Stutzer & Frey, 2010). In this study, the terms life satisfaction, subjective wellbeing, and happiness are used interchangeably, as is the usual practice in most recent studies (see also the discussion in La Placa et al., 2013). The paper examines the relatively under-researched topic of labor earnings reductions and its relationship to happiness levels. Based on Maslow’s psychological theory of hierarchical needs (Maslow, 1954), the paper argues that labor earnings are very important for happiness up to a certain level of income. The incorporation of the needs hierarchy into a happiness framework implies that individuals have a priority approach to happiness in relation to income. The crucial point here is that the most important needs must be satisfied first before the secondary needs come into the picture. It follows that forra higher income levels the effect of pay cuts on reported happiness levels becomes much weaker, given that the satisfaction of non-basic needs becomes important. In this work, the above idea is tested by employing data drawn from the 5th European Survey on Working Conditions (2010). The structure is as follows: Section 2 will present a literature survey concerning happiness and its relationship to labor earning changes. It will also discuss the incorporation of Maslow’s needs hierarchy approach into the framework of happiness research. The following sections will concentrate on the data and the empirical methodology, as well as the main research findings. A conclusion will close the paper. 2. Literature review 2.1 Happiness and labor earning changes Aristotle has been cited as the first written source of the idea that all human action is implicitly motivated by a desire to increase individuals’ subjective wellbeing or eudemonia, which referred to specific psychological experiences that were seen as the essence of a good life (Deci & Ryan, 2008). Modern rational choice theory suggests that revealed preferences imply motivation which means that individuals who strive for money believe (at some conscious or unconscious level) that it will increase their happiness (Ahuvia, 2008).1 Accordingly, the existing empirical research reveals that the richer countries declare higher levels of happiness compared to poorer countries, and within each country, the richer members of society are happier than the poor. In particular, several studies have suggested that higher income is associated with greater life satisfaction (see for instance: Easterlin, 1995; Helliwell, 2003; Liu et al., 2010). On the other hand, time-series analyses show that higher per capita incomes have failed to generate any noticeable improvement in happiness levels in most developed countries (e.g., Blanchflower & Oswald, 2004; Easterlin & Angelescu, 2012). Although within a country at a given time those with higher incomes are, on average, happier, many studies have found that raising the incomes of all does not increase the happiness of all. This presents researchers with a paradox, termed usually as the happiness or the Easterlin paradox (Easterlin, 1995; 2001; Cummins, 2000; Mentzakis & Moro, 2009; Diener et al., 2013). 1 Similarly, recent evidence from psychology suggests that high levels of income are also associated with lower levels of psychopathology (e.g., Wood et al. 2012). The effect of labor earnings reductions on happiness Drakopoulos & Grimani www.internationaljournalofwellbeing.org 25 With these findings in mind, it is reasonable to assume that wage cuts would have the opposite effects on happiness levels. In fact, the effect might be stronger than pay rises, according to the notion of loss aversion, which implies that “losses loom larger than gains.” This concept originated in the work of Kahneman and Tversky (1979), and has since been shown to be useful in a range of real-world contexts (for example, Camerer, 2000). In particular, under experimental conditions, a loss is typically estimated to have twice the influence on decisions as equivalent gains (Novemsky & Kahneman, 2005). However, there is not much relevant work examining the effects of wage cuts on happiness levels. One plausible explanation for this might be that until the Great Recession of 2008, nominal wage cuts was a rare and rather isolated phenomenon in most Western countries. One of the few papers that has employed this idea in the subjective wellbeing framework found that experienced drops in income have a larger impact on wellbeing than equivalent income gains (Boyce et al., 2013). Similarly, a recent working paper found that measures of life satisfaction and affect are more than twice as sensitive to negative economic growth as compared to positive growth (De Neve et al., 2015). However, another recent paper reported mixed results concerning the presence of loss aversion, and suggested that the relationship between pay growth and job satisfaction is less steep for cuts than for raises (Smith, 2015). Furthermore, according to Drakopoulos and Grimani (2015), pay cuts have a highly significant negative effect on psychological wellbeing and job satisfaction. This work aims to provide some additional insights into these relationships. 2.2 Labor earning changes and hierarchical behaviour Hierarchical choice consists of two interconnected central ideas: the first is that human needs are of varying importance, and the second is that human needs must be satisfied in a specific order. These two ideas imply that there are primary needs and secondary needs that cannot be substituted. According to Maslow (1954), primary needs refer mainly to physical needs like the need for food, clothing and shelter, while secondary needs refer to intellectual or non-material needs (for a discussion of the definition of primary and secondary needs, see Drakopoulos, 1994; Max-Neef, 1995; Gasper, 2005). The hierarchical approach predicts that when income is very low, a very high percentage of it would be spent on food, since food satisfies a basic need. This is in line with the hypothesis that consumption evolves along a hierarchical order as income increases. The hierarchical model has been applied to a wide array of economic issues (see for instance, Lluch et al., 1977; Canterbery, 1979; Jackson & Marks, 1999; Thiele & Weiss, 2003; Canova et al., 2005; Chattopadhyay et al., 2009). However, the application of hierarchical choice to happiness research has not received much attention. In our framework, hierarchy implies that once a level of labor earnings that satisfies the basic needs has been reached, further changes of labor earnings do not provide analogous changes on happiness levels because secondary needs come into the picture (Clark & Oswald, 1996; Drakopoulos & Theodossiou, 1997; Drakopoulos, 2013). Taking into account the notion of earnings that satisfy basic needs, an employee’s happiness level can be written as: H = H(LE, LE∗, X) (1) where H is happiness, LE is the level of labor earnings, LE* is the level of labor earnings which satisfies basic needs, and X is a vector of characteristics comprising variables that affect happiness. The inclusion of the threshold level of labor earnings LE* in equation (1) reflects the The effect of labor earnings reductions on happiness Drakopoulos & Grimani www.internationaljournalofwellbeing.org 26 essence of hierarchy. 2 The other variables (X) satisfy secondary needs and are taken into consideration only when LE reaches a satisfactory level or target LE*. (For a discussion concerning the determination of LE*, see Ferrer-i-Carbonell 2005.) We can incorporate all the above by taking a two-part function: H(LE, X) = {HL(LE, X),HH(LE,X)} (2) where H(LE, X) = HL for LE ≤ LE* and H(LE, X) = HH for LE > LE∗ with the following conditions (which are also our hypotheses to be tested in the empirical part of the paper): , and (3) The conditions provide the essence of the hierarchical approach to happiness levels. The first two conditions imply that labor earnings have a positive effect on happiness levels. The last condition infers that labor earnings do not provide the same rate of happiness levels once a given level (LE*) has been reached, suggesting that other factors start playing a role with regard to the level of happiness. Thus, falling labor earnings affect significantly and in a negative manner the happiness levels of the group of lower/middle income workers, while for the group of higher income workers, the effect of pay cuts on reported happiness levels becomes much weaker. In other words, falling earnings have an asymmetric effect on happiness, depending on the category of income. In the following sections of this paper, we will test this idea by using a large European dataset. 3. Empirical analysis 3.1 Data and participants The data used in this paper was drawn from the 5th European Survey on Working Conditions,3 which aimed to provide a comprehensive picture of the everyday reality of men and women at work. The research was conducted in the first half of 2010 (face-to-face interviews in people’s homes in the national language(s) of the country) and contains data from 33 European countries and Turkey. Given our focus in this paper, the timing of the survey was two years after the financial crisis of 2008, when the phenomenon of nominal pay cuts became much more widespread in many European countries. Thus, the 5th wave of 2010 captures very well the substantial occurrence of pay cuts in contrast to pre-2008 waves. The target sample size of 1,000 interviews was set for most countries. The participants were aged 15 or older, were in employment at the time of the survey, and were selected by the method of multi-stage stratified random sampling. They responded to a questionnaire of about 44 minutes’ duration, comprising 89 questions relating to issues such as work time duration, work organization, learning and training, physical and psychosocial risk factors, health and safety, 2 The inclusion of LE* and the two-part function implies a kink at LE*, and this is the main difference from the standard diminishing marginal utility approach, which gives one smooth function. 3 Further information on the project can be found at www.eurofound.europa.eu/surveys/ewcs/index.htm. The effect of labor earnings reductions on happiness Drakopoulos & Grimani www.internationaljournalofwellbeing.org 27 work-life balance, worker participation, earnings and financial security. A number of questions were included to capture the effect of the economic downturn on working conditions. The questionnaire data of interest included happiness and labor earning changes variables. It also included type of occupation (four dummy variables: high skilled clerical, low skilled clerical, high skilled manual, low skilled manual), previous occupational status (seven dummy variables: employed with an indefinite contract, employed with a fixed-term contract, employed with a temporary employment agency contract, employed, unemployed, in education or training, other), and working hours per week. The participants were working adults aged 18 to 65. In terms of countries, the sample consisted of 34 dummy variables: Albania, Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Kosovo, Latvia, Lithuania, Luxembourg, Former Yugoslav Republic of Macedonia (FYROM), Malta, Montenegro, the Netherlands, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, Turkey, and the United Kingdom. Finally, the data contained personal variables such as age and age squared, gender and educational level (three dummy variables: none and primary education, secondary, including lower, upper and post-secondary education, and tertiary, including advanced level of tertiary education). The happiness variable covers five positively worded items related to positive mood (good spirits, relaxation), vitality (being active and waking up fresh and rested) and general interests (being interested in things), all experienced over the previous two weeks. This five-item World Health Organization Well-Being Index (WHO-5) is among the most widely used questionnaires assessing subjective psychological wellbeing with high clinimetric validity. Since its first publication in 1998, the WHO-5 has been translated into more than 30 languages and has been applied successfully across a wide range of study fields (see, for instance Topp et al., 2015; Schutte et al., 2014; Sisak et al., 2008; Gill & Feinstein, 1994). The WHO-5 was derived from the WHO-10, which in turn was derived from a 28-item rating scale (selected from the Zung scales for depression, distress and anxiety, as well as from the General Health Questionnaire and the Psychological General Well-Being Scale), on the basis of a non-parametric item response theory analysis. The new version identified the 10 most valid items from the original 28-item scale (Bech, 1993). Each of the five items is rated on a 6-point Likert scale from 1 (= at no time) to 6 (= all of the time). In addition, the five scores created an index, which was linearized by using z-scores transformation. The negative values of the z-scores were transformed into positive and the natural logarithm (ln) was estimated. Reliability and validity estimations were conducted prior to index variable construction. The internal consistency approach (Cronbach’s alpha) was employed in order to assess the reliability of the scale. According to the results, the Cronbach’s alpha of the Psychological General Well-Being Scale was 0.8814. This suggests that the internal reliability of the scale is high, since an instrument with an internal consistency coefficient of 0.80 (scale total) or higher is considered to be adequate (Cronbach, 1951; Nunnaly, 1978). The validity of the scale was assessed by construct validity, using factor analysis. The results are considered to be satisfactory, since the loadings were far from 0 and the uniqueness was less than 0.50. The labor earning changes variable was assessed, reporting a change in their salary, comparing their current situation with that of a year ago (three dummy variables: pay cuts (decrease in labor earnings), no change in labor earnings, increase in labor earnings, see Table 1 below). The theoretical model that we follow implies that the sample has to be disaggregated into two categories: low/middle and high income. There is no standard definition of high income threshold in the relevant literature. Absolute nominal thresholds and relative thresholds are the two main methods found in most works on income levels (see Murphy et al., 2007). Both the “relative threshold cutoff,” based on median or mean income, and absolute nominal income threshold are widely used approaches (e.g., Morissette & Zhang, 2006; Murphy et al., 2007). The effect of labor earnings reductions on happiness Drakopoulos & Grimani www.internationaljournalofwellbeing.org 28 Table 1. Definitions of variables Variables/Definitions Ln Happiness levels France = 1, otherwise = 0 Ireland = 1, otherwise = 0 Males = 1, Females = 0 Italy = 1, otherwise = 0 Age (18 – 65 years) Luxembourg = 1, otherwise = 0 Age2 Netherlands = 1, otherwise = 0 Primary education = 1, otherwise = 0 UK = 1, otherwise = 0 Secondary education = 1, otherwise = 0 Bulgaria = 1, otherwise = 0 Tertiary education = 1, otherwise = 0 Cyprus = 1, otherwise = 0 Low skilled manual = 1, otherwise = 0 Czech Republic = 1, otherwise = 0 Low skilled clerical = 1, otherwise = 0 Estonia = 1, otherwise = 0 High skilled manual = 1, otherwise = 0 Hungary = 1, otherwise = 0 High skilled clerical = 1, otherwise = 0 Latvia = 1, otherwise = 0 Working hours per week (1 – 84) Lithuania = 1, otherwise = 0 Pay cuts (decrease labor earnings) = 1, otherwise = 0 Malta = 1, otherwise = 0 No change labor earnings = 1, otherwise = 0 Poland = 1, otherwise = 0 Increase labor earnings = 1, otherwise = 0 Romania = 1, otherwise = 0 Belgium =1, otherwise = 0 Slovakia = 1, otherwise = 0 Denmark =1, otherwise = 0 Slovenia = 1, otherwise = 0 Germany =1, otherwise = 0 Turkey = 1, otherwise = 0 Spain = 1, otherwise = 0 Croatia = 1, otherwise = 0 Finland = 1, otherwise = 0 Norway = 1, otherwise = 0 Austria = 1, otherwise = 0 FYROM =1, otherwise = 0 Portugal = 1, otherwise = 0 Albania = 1, otherwise = 0 Greece = 1, otherwise = 0 Kosovo = 1, otherwise = 0 Sweden = 1, otherwise = 0 Montenegro = 1, otherwise = 0 In this work, the relative threshold cutoff approach identifies as high income those who earn above two times the median income. This is also consistent with empirical work indicating that above this level, individuals tend to save a considerable percentage of their income, something which implies that they can comfortably cover their basic needs (Huggett & Ventura, 2000). The application of this method gave 28,965 low/middle income individuals and 4,131 high income individuals. The disaggregation was based on the Eurostat map data of European countries of median income for the year 2010. For the three following countries: Albania, Kosovo, and Montenegro, the disaggregation was based on the Trading Economics map data for year 2010. The split performed for low/middle and high income groups is appropriate, given that the Kolmogorov-Smirnov test indicated that the income distributions are different (see Table 2a below). An additional disaggregation, based on absolute nominal income threshold, was also conducted. The data was drawn from the World Bank map data of European countries by GDP per capita for the year 2010. The low/middle income sample contains 29,239 individuals, while the high income sample contains 3,857 individuals. We determined a threshold value for each country that was based on each country’s per capita gross domestic product. The effect of labor earnings reductions on happiness Drakopoulos & Grimani www.internationaljournalofwellbeing.org 29 Table 2a. Summary statistics of variables (after disaggregation by relative threshold) Variables Low/middle income levels High income levels 000Mean 0SD 000Mean 0SD Ln Happiness levels 0001.040 000.533 0001.082 000.466 Pay cuts (decrease labor earnings) 0000.201 000.400 0000.191 000.393 No change labor earnings 0000.541 000.498 0000.502 000.500 Males 0000.482 000.499 0000.718 000.449 Age 0041.044 011.460 0041.321 010.884 Age2 1815.975 947.533 1825.854 920.091 Primary education 0000.057 000.232 0000.059 000.235 Secondary education 0000.675 000.468 0000.433 000.495 Working hours 0038.415 011.652 0045.446 012.552 Low skilled manual 0000.193 000.395 0000.091 000.286 Low skilled clerical 0000.447 000.497 0000.307 000.461 High skilled manual 0000.159 000.366 0000.137 000.344 Belgium 0000.089 000.285 0000.028 000.165 Bulgaria 0000.023 000.153 0000.014 000.119 Czech Republic 0000.022 000.149 0000.021 000.143 Denmark 0000.029 000.168 0000.027 000.163 Germany 0000.058 000.234 0000.015 000.121 Estonia 0000.021 000.141 0000.035 000.184 Spain 0000.024 000.155 0000.026 000.160 France 0000.023 000.151 0000.012 000.111 Ireland 0000.081 000.272 0000.024 000.155 Italy 0000.022 000.147 0000.035 000.185 Cyprus 0000.031 000.172 0000.008 000.089 Latvia 0000.024 000.154 0000.020 000.141 Lithuania 0000.023 000.151 0000.023 000.152 Luxemburg 0000.021 000.144 0000.019 000.139 Hungary 0000.017 000.131 0000.029 000.167 Malta 0000.026 000.160 0000.022 000.146 Netherlands 0000.022 000.149 0000.023 000.151 Austria 0000.026 000.160 0000.023 000.149 Poland 0000.022 000.148 0000.004 000.064 Portugal 0000.025 000.156 0000.055 000.228 Romania 0000.017 000.131 0000.056 000.229 Slovenia 0000.039 000.194 0000.013 000.113 Slovakia 0000.025 000.156 0000.016 000.127 Finland 0000.029 000.168 0000.005 000.067 Sweden 0000.025 000.156 0000.027 000.162 UK 0000.028 000.167 0000.031 000.175 Croatia 0000.022 000.148 0000.059 000.235 FYROM 0000.028 000.166 0000.007 000.089 Turkey 0000.025 000.157 0000.231 000.421 Norway 0000.028 000.164 0000.024 000.155 Albania 0000.023 000.150 0000.017 000.131 Kosovo 0000.025 000.156 0000.014 000.118 Montenegro 0000.023 000.151 0000.008 000.091 Observations 28965 4131 The income above the given threshold value for each country has been considered as high, while the income below the given threshold value for each country has been considered as low/middle. The split performed for low/middle and high income groups is also appropriate, according to the Kolmogorov-Smirnov test (see Table 2b below). The effect of labor earnings reductions on happiness Drakopoulos & Grimani www.internationaljournalofwellbeing.org 30 Table 2b. Summary statistics of variables (after disaggregation by absolute nominal threshold) Variables Low/middle income levels High income levels 000Mean 0SD 000Mean 0SD Ln Happiness levels 0001.031 000.542 0001.151 000.354 Pay cuts (decrease labor earnings) 0000.206 000.404 0000.151 000.358 No change labor earnings 0000.546 000.497 0000.458 000.498 Males 0000.486 000.499 0000.704 000.456 Age 0040.649 011.474 0044.337 010.156 Age2 1784.004 945.019 2068.919 898.533 Primary education 0000.063 000.243 0000.015 000.124 Secondary education 0000.679 000.466 0000.385 000.486 Working hours 0038.784 012.036 0043.152 010.931 Low skilled manual 0000.195 000.396 0000.069 000.253 Low skilled clerical 0000.446 000.497 0000.309 000.462 High skilled manual 0000.165 000.371 0000.096 000.295 Belgium 0000.080 000.271 0000.096 000.295 Bulgaria 0000.025 000.157 0000.003 000.057 Czech Republic 0000.025 000.156 0000.003 000.060 Denmark 0000.018 000.134 0000.111 000.314 Germany 0000.052 000.223 0000.057 000.231 Estonia 0000.024 000.154 0000.007 000.083 Spain 0000.024 000.155 0000.028 000.165 France 0000.022 000.148 0000.019 000.138 Ireland 0000.073 000.260 0000.080 000.271 Italy 0000.019 000.137 0000.058 000.234 Cyprus 0000.028 000.167 0000.018 000.133 Latvia 0000.021 000.145 0000.040 000.197 Lithuania 0000.025 000.158 0000.006 000.080 Luxemburg 0000.023 000.151 0000.002 000.050 Hungary 0000.017 000.131 0000.031 000.173 Malta 0000.028 000.166 0000.004 000.068 Netherlands 0000.022 000.148 0000.024 000.155 Austria 0000.024 000.155 0000.034 000.182 Poland 0000.021 000.143 0000.015 000.124 Portugal 0000.031 000.174 0000.010 000.101 Romania 0000.024 000.155 0000.002 000.045 Slovenia 0000.038 000.191 0000.021 000.143 Slovakia 0000.026 000.160 0000.006 000.080 Finland 0000.024 000.153 0000.042 000.201 Sweden 0000.021 000.143 0000.057 000.232 UK 0000.026 000.161 0000.046 000.210 Croatia 0000.027 000.164 0000.020 000.142 FYROM 0000.028 000.165 0000.011 000.107 Turkey 0000.054 000.227 0000.021 000.144 Norway 0000.024 000.155 0000.047 000.213 Albania 0000.022 000.147 0000.023 000.151 Kosovo 0000.024 000.155 0000.015 000.122 Montenegro 0000.022 000.146 0000.018 000.134 Observations 29239 3857 4. Empirical methodology In the econometric specification of this paper, happiness will be the dependent variable. The variable is determined by a number of factors, including labor earning changes. The methods for analyzing psychological wellbeing data is the ordinary least-squares (OLS) regression and the Wald chi-square test (Williams, 2008; Green & Hensher, 2010; Greene, 2012). The effect of labor earnings reductions on happiness Drakopoulos & Grimani www.internationaljournalofwellbeing.org 31 Before we proceed to the report of the results, we should also mention a limitation of the present study that needs to be acknowledged. The limitation concerns the survey instrument employed, which was a self-reporting measure of happiness. This suggests that the information presented by the participants is based upon their subjective perceptions. Although participants were assured of confidentiality, it is possible that they either over- or underreported their level of happiness. However, self-reporting measures are widely used in many similar contemporary empirical studies (for instance, see Fordyce, 1988; Danna & Griffin, 1999; Charness & Grosskopf, 2001; Senik, 2005; Kahneman & Krueger, 2006). 5. Results In line with the theoretical part and with our discussion of the empirical methodology section, our equation of interest for the low/middle income group is: (4) whereas for the high income group it is: (5) It is assumed that employees’ happiness is determined by a variety of factors. These factors are the following: LE is the labor earning changes (three dummy variables: pay cuts (decrease in labor earnings), no change in labor earnings, increase in labor earnings), which is the basic independent variable; X is a vector of other individual socioeconomic variables, such as age, age2, gender, education level, type of occupation, hours of work, and country dummy variables, assumed to influence happiness levels (Ferrer-i-Carbonell, 2005; Panos & Theodossiou, 2007; Dolan et al., 2008). The α and b are the associated coefficients, and εi is a normally distributed error term. The results of the OLS regression models (with robust standard errors – Table 3a below), which are similar for both groups, reveal a statistically significant negative effect of pay cuts (decrease in labor earnings) on subjective wellbeing. After the simultaneous estimation of the results for both regression models, the Wald chi-square test was employed in order to examine whether coefficients differ across groups (Greene, 2012). Initially, there was a comparison of all of the coefficients from the two regression models. The results indicated that one or more of the coefficients significantly differ across groups (x2 (44) = 89.84, p < .01). Subsequently, the significance of the independent dummy variable was tested separately. The results indicated that the regression coefficients of the independent dummy variable for low/middle income group are not significantly different from those for high income group. Analogous results regarding the additional disaggregation based on absolute nominal income threshold are presented in Table 3b below. One or more of the coefficients also significantly differ across groups (x2 (44) = 183.88, p < .01). However, the regression coefficients of the independent dummy variables for low/middle income group are significantly different from those for high income group (x2 (1) = 4.15, p<.05), suggesting that labor earning changes is a stronger predictor of happiness for the first group than for the latter. The effect of labor earnings reductions on happiness Drakopoulos & Grimani www.internationaljournalofwellbeing.org 32 Table 3a. Dependent variable - Ln Happiness levels: Simultaneous results for regression models (after disaggregation by relative threshold) Variables Low/middle income group High income group Pay cuts (decrease labor earnings) -0.106 (-10.60)** -0.095 (-4.18)** No change -0.005 (0.73) -0.009 (0.55) Males -0.070 (10.47)** -0.053 (3.24)** Age -0.009 (-5.24)** -0.012 (-2.36)* Age2 -0.000 (3.73)** -0.000 (2.23)* Primary education -0.079 (-4.80)** -0.112 (-3.09)** Secondary education -0.003 (-0.38) -0.012 (0.68) Working hours -0.001 (-2.86)** -0.003 (-4.68)** Low skilled manual -0.112 (-9.97)** -0.071 (-2.47)* Low skilled clerical -0.028 (-3.17)** -0.032 (-1.78) High skilled manual -0.044 (-3.74)** -0.005 (0.19) Belgium -0.065 (2.72)** -0.063 (0.93) Bulgaria -0.082 (-2.77)** -0.005 (-0.07) Czech Republic -0.114 (-3.86)** -0.085 (-1.19) Denmark -0.194 (6.88)** -0.178 (2.63)** Germany -0.086 (3.43)** -0.060 (0.77) Estonia -0.057 (1.86) -0.055 (0.86) Spain -0.072 (2.50)* -0.093 (1.37) France -0.197 (6.78)** -0.117 (1.43) Ireland -0.041 (1.71) -0.052 (0.75) Italy -0.219 (7.29)** -0.092 (1.43) Cyprus -0.036 (-1.32) -0.077 (0.82) Latvia -0.012 (-0.42) -0.033 (0.46) Lithuania -0.048 (-1.62) -0.006 (-0.10) Luxemburg -0.102 (-3.33)** -0.113 (-1.55) Hungary -0.055 (1.78) -0.005 (-0.09) Malta -0.074 (-2.60)** -0.088 (-1.24) Netherlands -0.131 (4.45)** -0.098 (1.41) Austria -0.114 (3.97)** -0.096 (1.37) Poland -0.055 (1.86) -0.105 (0.86) Portugal -0.025 (-0.87) -0.005 (-0.09) Romania -0.006 (-0.21) -0.052 (0.86) Slovenia -0.026 (-0.99) -0.016 (0.21) Slovakia -0.001 (-0.05) -0.075 (0.98) Finland -0.142 (5.07)** -0.031 (0.27) Sweden -0.152 (5.20)** -0.063 (0.93) UK -0.017 (0.62) -0.018 (0.29) Croatia -0.057 (-1.95) -0.046 (-0.77) FYROM -0.049 (1.77) -0.103 (1.09) Turkey -0.201 (-7.09)** -0.122 (-2.23)* Norway -0.139 (4.91)** -0.103 (1.50) Albania -0.078 (-2.66)** -0.101 (-1.34) Kosovo -0.162 (5.54)** -0.020 (0.26) Montenegro -0.039 (1.33) -0.016 (-0.18) Constant -1.320 (29.45)** -1.469 (12.03)** Observations 28965 4131 R2 0.061 0.066 Note: Robust z-statistics in parentheses. *Significant at 5%; **significant at 1%. The effect of labor earnings reductions on happiness Drakopoulos & Grimani www.internationaljournalofwellbeing.org 33 Table 3b. Dependent variable - Ln Happiness levels: Simultaneous results for regression models (after disaggregation by absolute nominal threshold) Variables Low/middle income group High income group Pay cuts (decrease labor earnings) -0.112 (-10.10)** -0.065 (-3.24)** No change 0.004 (0.51) 0.012 (0.99) Males 0.074 (10.68)** 0.049 (3.56)** Age -0.008 (-4.44)** -0.021 (-4.47)** Age2 0.000 (2.88)** 0.000 (4.50)** Primary education -0.092 (-4.69)** -0.005 (-0.09) Secondary education -0.007 (-0.91) 0.015 (1.02) Working hours -0.001 (-3.80)** -0.001 (-1.07) Low skilled manual -0.118 (-9.66)** -0.049 (-1.87) Low skilled clerical -0.033 (-3.82)** -0.017 (-1.25) High skilled manual -0.048 (-4.09)** 0.016 (0.66) Belgium 0.054 (2.24)* 0.075 (1.08) Bulgaria -0.077 (-2.25)* -0.151 (-1.01) Czech Republic -0.116 (-3.90)** 0.098 (0.99) Denmark 0.175 (7.01)** 0.207 (3.06)** Germany 0.075 (3.04)** 0.090 (1.24) Estonia 0.061 (2.12)* 0.097 (1.02) Spain 0.064 (2.43)* 0.131 (1.72) France 0.188 (7.35)** 0.187 (2.57)** Ireland 0.025 (1.06) 0.101 (1.44) Italy 0.212 (7.16)** 0.153 (2.17)* Cyprus -0.051 (-1.72) 0.071 (0.90) Latvia -0.036 (-1.03) 0.107 (1.45) Lithuania -0.046 (-1.53) 0.069 (0.68) Luxemburg -0.105 (-3.35)** 0.071 (0.69) Hungary 0.045 (1.48) 0.064 (0.85) Malta -0.083 (-2.89)** 0.165 (1.82) Netherlands 0.121 (4.46)** 0.149 (2.05)* Austria 0.098 (3.40)** 0.158 (2.28)* Poland 0.038 (1.36) 0.134 (1.80) Portugal -0.015 (-0.53) 0.014 (0.15) Romania 0.026 (0.87) 0.211 (2.54)* Slovenia -0.034 (-1.22) 0.027 (0.35) Slovakia 0.001 (0.05) 0.047 (0.52) Finland 0.135 (5.63)** 0.111 (1.59) Sweden 0.137 (5.38)** 0.139 (2.00)* UK 0.004 (0.15) 0.064 (0.88) Croatia -0.044 (-1.57) -0.024 (-0.29) FYROM 0.038 (1.23) 0.181 (2.21)* Turkey -0.156 (-5.43)** 0.148 (1.99)* Norway 0.121 (4.49)** 0.168 (2.39)* Albania -0.086 (-2.77)** -0.094 (-0.99) Kosovo 0.151 (5.29)** 0.070 (0.79) Montenegro 0.028 (1.01) 0.073 (0.91) Constant 1.323 (29.22)** 1.501 (11.95)** Observations 29239 3857 R2 0.058 0.052 Note: Robust z-statistics in parentheses. *Significant at 5%; **significant at 1%. Most of the predictors exhibited a significant relationship to (ln) happiness at 1% or 5% level. The predicted value is higher for males, which implies that women’s happiness is less than that of men. With regards to age, a negative relationship to happiness is revealed. In addition, individuals with a high skilled clerical occupation and tertiary education have higher happiness The effect of labor earnings reductions on happiness Drakopoulos & Grimani www.internationaljournalofwellbeing.org 34 levels. Moreover, longer working hours are associated with a decrease in the levels of happiness. Greece, being the omitted country, seems to have lower happiness levels than the Nordic countries, Kosovo and the Former Yugoslav Republic of Macedonia, while it seems to have higher happiness levels than the rest of the Balkan countries. Thus, the results provide a strong indication for the validity of the theoretical discussion concerning hierarchical needs, income levels and reported happiness. At this point, it has to be noted that other factors might have played a role in determining the happiness level of Europeans, and may confound the pay cuts estimates. In particular, the aftermath of the Great Recession witnessed the Eurozone crisis, with large bailouts of countries and banks, and austerity policies. Apart from public service cuts, all these developments implied distrust towards national and European governments and institutions, and a general feeling of uncertainty and fear (Blanchflower & Shadforth, 2009; Ehrmann et al., 2013). It can be argued that these negative effects might have been stronger for low income groups, thus strengthening the negative pay cuts effects of our study. However, given that our data is from 2010, the public service cuts effects took a relatively long period to be instituted and implemented, and therefore their effect exhibits a considerable lag compared to the pay cut effects. Although the relevant literature on this topic is not very extensive, some prior empirical research on happiness in general provides some insights regarding the main variables (see Smith, 2015; Boyce et al., 2013). Our results indicate that males demonstrated higher levels of happiness than females. Previous evidence on gender differences and their associations with happiness has been inconsistent. The 2009 study by Stevenson and Wolfers showed that measures of subjective wellbeing suggest that women’s happiness has declined both absolutely and relative to men, although a few studies report no gender differences (for instance, Louis & Zhao, 2002; Liu et al., 2010). One of the main explanations for these results might be that women may simply find the complexity and increased pressure in their modern lives to have come at the cost of happiness (see also Ferber & Green, 2003). Furthermore, our findings point to a negative relationship between age and psychological wellbeing, which is consistent with other studies such as Van Praag et al. (2003) and Drakopoulos and Grimani (2013a). Many papers on the determinants of happiness and wellbeing, suggest a U-shaped relationship between age and wellbeing, where the youngest and the oldest are happiest, while the middle age groups are the least happy (see for instance: Blanchflower & Oswald, 2008; Frijters & Beatton, 2012; Drakopoulos & Grimani, 2013b). One explanation here has to do with the higher expectations of the younger age group compared to older individuals (Clark & Oswald, 1994; Gerdtham & Johannesson, 2001). In addition, tertiary education and high skilled clerical employees were reporting the highest happiness levels (see for instance: Tsou & Liu, 2001; Blanchflower & Oswald, 2004; Drakopoulos & Grimani, 2013a). A negative relationship was also found between working hours and happiness, suggesting that individuals who have longer work hours report lower happiness levels. The evidence is consistent with other empirical work, such as in Galay (2007). Finally, happiness is higher for Nordic countries and lower for southern contiguous countries compared to Greece (Huppert & So, 2013; Drakopoulos & Grimani, 2013b). Our results can also be connected to research indicating that income is a very important happiness determinant for lower income groups (e.g., Layard et al., 2010). Furthermore, Corazzini et al. (2012) focused on the differences between high and low income countries regarding the strength of relative concerns. Their findings support the presence of relative concerns in the perception of wellbeing, with the strength of relativism being higher for respondents in high income countries. The effect of labor earnings reductions on happiness Drakopoulos & Grimani www.internationaljournalofwellbeing.org 35 6. Conclusions Falling labor earnings have been observed in many countries since the Great Recession. Given that there is not much work on this important issue, the main aim of this paper was to investigate the relationship between falling labor earnings and workers’ happiness. The paper employed the psychological theory of hierarchical needs which has been applied to many economic contexts. The hierarchical structure of needs implies that the most important needs must be satisfied first before the secondary needs are considered. In the framework of the income-happiness relationship, the theory would predict that income is very important for happiness up to a certain level of income. For higher levels of income, income is still important but much less so, given that other factors affecting happiness come into the picture. The paper utilized a large sample to test the above relationships by using data from 33 European countries and Turkey. In particular, the results indicate that pay cuts have a highly significant negative effect on the happiness levels of workers with low and middle income, implying that pay cuts reduce workers’ happiness compared to those whose pay does not change or increase. The effect becomes much weaker for the workers belonging to higher income group when it comes to the disaggregation based on absolute nominal threshold. The main empirical findings reveal different results between the two disaggregation methods. Disaggregation based on absolute nominal threshold supports the notion of the needs hierarchy and its relation to labor earnings. Labor earning changes seem to be more important for happiness for low and middle income group workers. Moreover, it seems that labor earning changes lose their importance for the high income workers’ group, and this is consistent with the incorporation of the needs hierarchy into the context of happiness research. Furthermore, the above empirical findings link psychological wellbeing issues to financial loss, and this is consistent with other relevant studies. There is a large literature pointing out the importance of subjective wellbeing for labor productivity, organizational performance, absenteeism, and health and longevity (for a recent survey, see De Neve et al. 2013 and references therein). Our results provide additional insights to the above, given that low and middle income workers are likely to suffer more in terms of happiness loss when nominal wage cuts are applied. The fall of happiness of low income groups may have stronger adverse effects on their productivity, work performance, absenteeism and health levels. Nevertheless, there is a need for further research on understanding the above relationships, given that the relative threshold method did not provide the same support to the previous points. Authors Stavros Drakopoulos National and Kapodistrian University of Athens sdrakop@uoa.gr Katerina Grimani National and Kapodistrian University of Athens Publishing Timeline Received 22 June 2016 Accepted 27 February 2017 Published 9 June 2017 The effect of labor earnings reductions on happiness Drakopoulos & Grimani www.internationaljournalofwellbeing.org 36 References Ahuvia, A. (2008). If money doesn’t make us happy, why do we act as if it does? Journal of Economic Psychology, 29(4), 491-507. https://doi.org/10.1016/j.joep.2007.11.005 Bech, P. (1993). Rating scales for psychopathology, health status and quality of life: A compendium on documentation in accordance with the DSM-III-R and WHO systems. 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