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Climbing the ladders of job satisfaction and employee organizational commitment: cross-country evidence using a semi-nonparametric approach

Climbing the ladders of job satisfaction and employee organizational commitment: cross-country... JOURNAL OF APPLIED ECONOMICS 2023, VOL. 26, NO. 1, 2163581 https://doi.org/10.1080/15140326.2022.2163581 RESEARCH ARTICLE Climbing the ladders of job satisfaction and employee organizational commitment: cross-country evidence using a semi-nonparametric approach a a a José A. C. Vieira , Francisco J. F. Silva , João C. A. Teixeira , a b António J. V. F. G. Menezes and Sancha N. B. de Azevedo School of Business and Economics and Centre of Applied Economics Studies of the Atlantic, University of the Azores, Ponta Delgada, Portugal; School of Business and Economics, University of the Azores, Ponta Delgada, Portugal ABSTRACT ARTICLE HISTORY Received 23 November 2021 Satisfied and committed employees play a major positive role in Accepted 23 December 2022 business performance in today’s globalized and competitive land- scape. This paper contributes to the literature on the empirical KEYWORDS determinants of job satisfaction and organizational commitment, Job satisfaction; employee drawing on a rich micro dataset for 36 countries, using a flexible organizational commitment; semi-nonparametric approach, which nests and outperforms the cross-country differences; standard ordered probit model. The findings indicate that job great resignation satisfaction and organizational commitment can be fostered by instruments which can be controlled by management. Our results shed timely light on how managers can improve job satisfaction and organizational commitment and address implications of the Great Resignation. However, despite the ever-increasing pace of globalization and expanding role of multinationals across the globe in shaping work environments, our results uncover that significant cross-country differences in job satisfaction and organi- zational commitment do exist, even after controlling for a plethora of job-and-workplace manageable attributes and individual (includ- ing religious dimensions) related characteristics. 1. Introduction In today’s competitive landscape, human resources are increasingly recognized as the most valuable assets to any organization (Fulmer & Ployhart, 2014). Consequently, strategic human resources management plays a fundamental role in increasing employ- ees’ job satisfaction and organizational commitment and consequently business perfor- mance (Brown et al., 2011). Within this context, researchers and human resource practitioners consider employees’ satisfaction as a critical goal to be achieved, which influences their commitment and other positive behavioral attitudes towards the orga- nization (Brown et al., 2011). CONTACT António J. V. F. G. Menezes antonio.jv.menezes@uac.pt School of Business and Economics and Centre of Applied Economics Studies of the Atlantic, University of the Azores, Ponta Delgada, Portugal Supplemental data for this article can be accessed online at https://doi.org/10.1080/15140326.2022.2163581 © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/ licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 2 J. A. C. VIEIRA ET AL. Therefore, there is a growing body of empirical literature on the determinants of employees’ job satisfaction within human resource management and organizational behavior literature or, more broadly, in economics, psychology, and sociology (Belfield & Harris, 2002; Borjas, 1979; Clark, Oswald, 1996; Idson, 1990; Johnson & Johnson, 2002; Judge & Hulin, 1993; Judge et al., 2002; King & Williamson, 2005; Souza-Poza & Souza- Poza, 2003; Vieira, 2005; Westover & Taylor, 2010) and how such satisfaction relates to employees’ level of organizational commitment (Harter et al., 2002; Rayton, 2006; Saridakis et al., 2018; Valaei & Rezaei, 2016) and organizational performance (e.g., Harter et al., 2002; Koys, 2001). This paper adds novel empirical evidence to the literature on job satisfaction and employee organizational commitment and its managerial implications. In order to achieve this objective, we address the following questions. First, we inquire if there are specific job satisfaction enhancing variables at managers’ disposal, or if job-satisfaction is intrinsic to workers (e.g., their demographics or religious beliefs). Second, we evaluate the extent to which employee organizational commitment is explained by job satisfaction. To answer these questions, we analyze a vast, detailed, rich sample of employees for a large number of countries − 36 – using a robust yet flexible semi-nonparametric model, of which the ordered probit model is a particular, restricted case. We focus on cross-country differences, as the data allow to isolate cross-country differences, after controlling for a rich plethora of job and workplace-related characteristics, in addition to individual related characteristics, including religious beliefs and practices. The results indicate that the conventional ordered probit model, which needs a distributional assumption about the error term, is rejected in favor of the proposed more flexible semi-nonparametric alternative, validating, thus, our approach. Moreover, the findings suggest that while not all determinants of workers’ job satisfaction can be influenced by management, it is most interesting to note that indeed some instruments that increase job satisfaction are available to managers and controlled by managers. The results also indicate that increas- ing job satisfaction increases employees’ organizational commitment. In addition, certain determinants of job satisfaction also exert a direct (not only indirect) effect on employee organizational commitment. Quite interestingly, there are striking cross-country differ- ences on the determinants of job satisfaction and employee organizational commitment even after controlling for a rich plethora of job, workplace, and individual characteristics (including cultural and religious beliefs), which researchers and human resources man- agers alike ought to consider. The paper is organized as follows. Section 2 reviews the literature on job satisfaction and employee organizational commitment. Section 3 presents the conceptual framework, the hypotheses to be tested, the data set collected, and the statistical and micro-econometric model used. Section 4 presents the estimation results and discusses the findings. Finally, Section 5 contains the main conclusions and directions for further research. 2. Literature review 2.1. Job satisfaction In general, in the literature the concept of job satisfaction expresses the degree to which one feels positively or negatively about his or her job and involves a subjective evaluation JOURNAL OF APPLIED ECONOMICS 3 of many work-specific factors such as pay, work autonomy, occupational prestige, super- vision, promotional opportunities, and workplace relations (Clark, Oswald, 1996; Rayton, 2006; Saridakis et al., 2018; Wood & Ogbonnaya, 2018). For instance, Newstorm (2007) summarizes it as “a set of favorable or unfavorable feelings and emotions with which employees view their work.” Other definitions can be found in Spector (1997), Judge and Kammeyer-Mueller (2012), and Frederici and Skaalvik (2012). There is also a debate on how one can measure job satisfaction (Judge & Kammeyer- Mueller, 2012; van Saane et al., 2003). Regardless of the exact definition of job satisfac- tion, it has long been found in the literature that employees’ reported feelings towards their job do convey useful managerial information on individual behavior and organiza- tional performance (Akerlof et al., 1988; Harter et al., 2002; Hellman, 1997; Rayton, 2006; Saridakis et al., 2018; Shields & Price, 2002). Several motivational theories have been used to address job satisfaction, including the needs hierarchy theory (Maslow, 1943), two-factor theory (Herzberg et al., 1959), X and Y theory (McGregor, 1960), needs achievement theory (McClelland, 1961), equity theory (Adams, 1963), expectancy theory (Vroom, 1964), goal setting theory (Locke, 1968), and job characteristics theory (Hackman & Oldham, 1976). These theoretical frameworks have guided empirical work on the determinants and outcomes of job satisfaction. At the empirical level, some studies have examined overall job satisfaction, while others have focused on satisfaction with a specific aspect of the job (Saridakis et al., 2018). There is evidence that one’s job satisfaction relates to a diversity of job-related characteristics, although the findings are not completely consistent across studies, such as pay (Clark, Oswald, 1996; Heywood & Wei, 2006; Pouliakas & Ioannis, 2010), hours of work (Clark, Oswald, et al., 1996), job security (Artz & Kaya, 2014), promotion oppor- tunities (Clark, 1998), job stress (Wang et al., 2014), work autonomy (Ross & Reskin, 1992), workplace relations with co-workers and management (Westover & Taylor, 2010), job-skill use (Allen & van der Velden, 2001; Amador & Vila, 2013; Belfield & Harris, 2002; Johnson & Johnson, 2002; Vieira, 2005), and job-life interference (Anderson et al., 2002; Scandura & Lankau, 1997). Several authors have also examined the role of socio-demographic characteristics as explanatory variables for job satisfaction, such as gender (Clark, 1997; Linz, 2003; Souza- Poza & Souza-Poza, 2003; Witt & Neal, 1992), age (Chaudhuri et al., 2015; Clark, Oswald, et al., 1996; Linz, 2003; Saner & Eyüpoğlu, 2012), education (Clark, Oswald, 1996; Clark, Oswald, et al., 1996; Idson, 1990; Linz, 2003; Ross & Reskin, 1992; Vila & García mora, 2005), marital status (Clark, Oswald, et al., 1996; Linz, 2003; Saner & Eyüpoğlu, 2013), region or country (Borooah, 2009; Bozionelos & Kostopoulos, 2010; Díaz-Serrano & Vieira, 2005; Jones & Sloane, 2009; Mysíková & Večerník, 2013), union membership (Borjas, 1979; Clark, Oswald, et al., 1996; García-Serrano, 2008; Hammer & Avgar, 2005; Renaud, 2002), religious beliefs (King & Williamson, 2005), and public service versus private-sector employment (Top et al., 2015). 2.2. Organizational commitment It is widely recognized that employees’ organizational commitment plays an important role in any organization, linked to important competitive advantages, such as employee turnover, absenteeism, and performance (Brown et al., 2011; Mowday et al., 1979; 4 J. A. C. VIEIRA ET AL. Walton, 1985). Price (1997) defined organizational commitment as loyalty to a social unit. Others refer to it as the strength of identification and involvement with an organization (Mowday et al., 1979). Mowday et al. (1979) identified the following three components of organizational commitment: a strong belief in the organization’s goals and values, a willingness to exert considerable effort on behalf of it, and a strong intent to remain employed by the organization. Meyer and Allen (1991, 1997) refer to one’s organizational commitment as a psychological state that has at least three separable components: affective commitment (a desire), continuance commitment (a need), and normative commitment (an obligation) to maintain employment in an organization. Affective commitment is an attitudinal process that involves employees’ identification with, attachment to, and involvement in the organization’s efforts to share its values and goals. Continuance commitment relates to employees’ awareness of the costs associated with leaving the organization. Normative commitment reflects the feeling of obligation towards the organization based on their personal values and beliefs. In general, commit- ment captures the worker-employer ties or attachment. Several studies have examined the determinants of organizational commitment, although the findings are not completely consistent across different studies. Such research has addressed the explanatory role of variables including rewards or compensa- tion (Paik et al., 2007), job–life balance (Azeem & Akhtar, 2014) and demographic characteristics such as gender (Mathieu & Zajac, 1990), age (Allen & Meyer, 1993; Suliman & Lies, 2000; Yucel & Bektas, 2012), and education (González et al., 2016). A close reading of empirical studies suggests that many determinants of job satisfaction also impact organizational commitment. The extent to which their effect on organiza- tional commitment is direct, indirect (via the mediating effect of job satisfaction), or both is an important empirical issue in the literature. This study contributes to the literature in this regard. 2.3. Connecting job satisfaction and organizational commitment The existing empirical evidence on job satisfaction and organizational commitment still reflects a lack of unanimity on the causal ordering between these constructs (Saridakis et al., 2018). A vast majority of studies have evidenced that job satisfaction is an antecedent of organizational commitment (Chan & Qiu, 2011; Elangovan, 2001; Top & Gider, 2013; Top et al., 2015). However, others have proposed that organizational commitment shapes job satisfaction (Bateman & Strasser, 1984; Paik et al., 2007; Vandenberg & Lance, 1992), while some authors also view these constructs as potentially reciprocally related (Farkas & Tetrick, 1989; Huang & Hsiao, 2007; Lance, 1991; Saridakis et al., 2018). 3. Methodology, data, and the statistical model 3.1. Methodology Figure 1 displays the conceptual framework for empirical examination, which includes the following hypotheses: JOURNAL OF APPLIED ECONOMICS 5 Figure 1. The conceptual model. Note: This figure depicts our proposed conceptual model to be used for empirical purposes and the corresponding hypotheses to be tested. The model considers that employee and job/workplace attributes influence job satisfaction and organizational commitment. As job satisfaction might also influence organizational commitment, this means that employee and job/ workplace attributes may impact organizational commitment directly and/or also indirectly due to their effect on satisfaction. It can, however, also be the case that some attributes have no impact on organizational commitment or eventually act only through one of the channels instead of both. H1 - Employee characteristics influence job satisfaction.a H2 - Job or workplace characteristics influence job satisfaction. H3 - Job satisfaction influences organizational commitment. To investigate H1, we test the effect of workers’ characteristics on job satisfaction, controlling for confounding effects arising via observed job or workplace characteristics. If job attributes were not controlled for them, employee attributes regression coefficients could also capture the effect of those attributes due to the correlation between both variables. In H2, we test the influence of job or workplace characteristics on job satisfac- tion, controlling for the influence of workers’ observed attributes. Despite the lack of consensus in the literature regarding the causal ordering between these two variables, we entertain in H3 job satisfaction as a determinant (even if partially) of organizational commitment, while we also consider the possibility that job satisfaction is endogenously determined with organizational commitment via an instrument variable approach. Two additional hypotheses are necessary to close the model: H4 - Employee characteristics have a direct impact on organizational commitment. H5 - Job or workplace characteristics have a direct impact on organizational commitment. In order to test H4, one must control for the effect of job satisfaction and job or workplace characteristics on organizational commitment. To test H5, we must control 6 J. A. C. VIEIRA ET AL. for the influence of job satisfaction and employees’ characteristics on organizational commitment. Therefore, the present framework allows to examine the extent to which the effect of employee and job-and-workplace characteristics on organizational commitment runs directly is mediated by job satisfaction, or both. For instance, if such an effect is totally mediated via job satisfaction, then there is no room for any direct effect of these variables on the organizational commitment equation (otherwise, those variables will also have a direct impact). 3.2. Data The present study uses data from the 2015 Work Orientation module of International Social Survey Program (ISSP) survey, which was implemented in 2015–2016 in a large number of countries. The national surveys include random samples of the population and include questions regarding the general and working populations. We only use data on working respondents. The final sample, after eliminating missing values on relevant variables, includes 14,437 working respondents. A similar procedure has been used by other researchers (e.g., Saridakis et al., 2018). The survey collected information on respondents, in this case employees, includ- ing characteristics such as age, gender, education, marital status, trade union membership, religious beliefs, religious services attendance, and country of employ- ment. The survey also includes questions on job or workplace characteristics, namely number of weekly hours worked, type of organization (public or private employer), whether the respondent supervises other workers or not in the work- place, whether the employee has recently received any training to improve skills at the workplace or elsewhere (which can be viewed as the extent to which the job provides or allows training opportunities to improve skills), perceived professional use of past experience and skills, perceived work–life balance, perceived relations in the workplace (between management and employees and between colleagues), per- ceived incidence of stress at work, and, finally, respondents’ evaluation of their job on a five-point scale ranging from strongly disagree to strongly agree. These responses are given to statements such as a) My job is secure, b) My income is high, c) My opportunities of advancement are high, d) My job is interesting, e) I can work independently, f) In my job I can help other people, g) My job is useful to society, and h) In my job I have personal contact with other people. Table 1 presents the summary of descriptive statistics on employee and job-related characteristics, along with a description of other independent variables to be used in the regression analysis. The survey also asked the following question: How satisfied are you in your (main) job? The level of satisfaction had to be reported on a seven-point scale ranging from completely dissatisfied to completely satisfied (see Table 2). Moreover, respondents were asked the extent to which they agreed or disagreed with the following three statements: a) I am willing to work harder than I have to in order to help the firm or organization for succeed, b) I am proud to be working for my firm or organization, and c) I would turn down another job that offered quite a bit more pay in order to stay with this organization. The levels of agreement to these JOURNAL OF APPLIED ECONOMICS 7 Table 1. Data and variables description. Variable Description Mean S. Dev. Age Reported age (years) 42.192 11.954 Age /100 Reported age squared 1923.0 1016.1 Female 1 if a female worker, 0 otherwise 0.5421 Years of education Reported education (in years) 14.618 10.051 Living in steady partnership 1 if the worker lives in steady partnership, 0 otherwise 0.6281 Unionized worker 1 if the worker is unionized, 0 otherwise 0.2616 Catholic 1 if affiliated with the Catholic religion, 0 otherwise 0.3008 Protestant 1 if affiliated with the Protestant religion, 0 otherwise 0.1930 Orthodox 1 if affiliated with the Orthodox religion, 0 otherwise 0.0616 Other Christian religions 1 if affiliated with other Christian religions, otherwise 0.0470 Jewish 1 if affiliated with the Jewish religion, 0 otherwise 0.0219 Islamic 1 if affiliated the Islamic religion, 0 otherwise 0.0231 Buddhist 1 if affiliated with the Buddhist religion, 0 otherwise 0.0175 Hindu 1 if affiliated with the Hindu religion, 0 otherwise 0.0149 Other Asian religions 1 if affiliated with other Asian religions, 0 otherwise 0.0329 Other religions 1 if affiliated with other religions, 0 otherwise 0.0096 Attendance of religious 1 if attends religious services at least once a week, 0 otherwise 0.1076 services Australia 1 if the survey was conducted in Australia, 0 otherwise 0.0268 Austria 1 if the survey was conducted in Austria, 0 otherwise 0.0255 Belgium 1 if the survey was conducted in Belgium, 0 otherwise 0.0479 Chile 1 if the survey was conducted in Chile, 0 otherwise 0.0240 China 1 if the survey was conducted in China, 0 otherwise 0.0166 Croatia 1 if the survey was conducted in Croatia, 0 otherwise 0.0252 Czech Republic 1 if the survey was conducted in Czech Republic, 0 otherwise 0.0320 Estonia 1 if the survey was conducted in Estonia, 0 otherwise 0.0315 Finland 1 if the survey was conducted in Finland, 0 otherwise 0.0280 France 1 if the survey was conducted in France, 0 otherwise 0.0272 Georgia 1 if the survey was conducted in Georgia, 0 otherwise 0.0109 Germany 1 if the survey was conducted in Germany, 0 otherwise 0.0444 Hungary 1 if the survey was conducted in Hungary, 0 otherwise 0.0258 Iceland 1 if the survey was conducted in Iceland, 0 otherwise 0.0298 India 1 if the survey was conducted in India, 0 otherwise 0.0109 Israel 1 if the survey was conducted in Israel, 0 otherwise 0.0265 Japan 1 if the survey was conducted in Japan, 0 otherwise 0.0262 Latvia 1 if the survey was conducted in Latvia, 0 otherwise 0.0263 Lithuania 1 if the survey was conducted in Lithuania, 0 otherwise 0.0181 Mexico 1 if the survey was conducted in Mexico, 0 otherwise 0.0171 New Zealand 1 if the survey was conducted in New Zealand, 0 otherwise 0.0109 Norway 1 if the survey was conducted in Norway, 0 otherwise 0.0431 Philippines 1 if the survey was conducted in Philippines, 0 otherwise 0.0240 Poland 1 if the survey was conducted in Poland, 0 otherwise 0.0189 Russia 1 if the survey was conducted in Russia, 0 otherwise 0.0362 Slovak Republic 1 if the survey was conducted in Slovak Republic, 0 otherwise 0.0265 Slovenia 1 if the survey was conducted in Slovenia, 0 otherwise 0.0229 South Africa 1 if the survey was conducted in South Africa, 0 otherwise 0.0321 Spain 1 if the survey was conducted in Spain, 0 otherwise 0.0380 Suriname 1 if the survey was conducted in Suriname, 0 otherwise 0.0177 Sweden 1 if the survey was conducted in Sweden, 0 otherwise 0.0353 Switzerland 1 if the survey was conducted in Switzerland, 0 otherwise 0.0384 Taiwan 1 if the survey was conducted in Taiwan, 0 otherwise 0.0497 United Kingdom 1 if the survey was conducted in United Kingdom, 0 otherwise 0.0290 Venezuela 1 if the survey was conducted in Venezuela, 0 otherwise 0.0172 Supervising other workers 1 if the respondent supervises other employees, 0 otherwise 0.2505 Public servant 1 if the respondent works for a public employer, 0 otherwise 0.3303 High income job 1 if respondent agrees or strongly agrees that has a high-income 0.2854 job, 0 otherwise Secure job 1 if respondent agrees or strongly agrees that has a secure job, 0 0.7204 otherwise Job with high opportunities 1 if respondent agrees or strongly agrees that his job has high 0.2942 for advancement opportunities for advancement, 0 otherwise (Continued) 8 J. A. C. VIEIRA ET AL. Table 1. (Continued). Variable Description Mean S. Dev. Received training to 1 if the worker received training to improve skills over the last 12 0.4763 improve job skills months, 0 other. Interesting job 1 if respondent agrees or strongly agrees that his job is interesting, 0.7252 0 otherwise Useful job to society 1 if respondent agrees or strongly agrees that his job is useful to 0.9205 society, 0 otherwise Job can help other people 1 if respondent agrees or strongly agrees that in his job he can help 0.8914 other people, 0 otherwise Job allows personal contact 1 if respondent agrees or strongly agrees that his job has personal 0.9553 with other people contact with other people, 0 otherwise Can work independently 1 if respondent agrees or strongly agrees that can work 0.7140 independently in his job, 0 otherwise Easy to take time off during 1 if respondent considers that it is not too difficult or not difficult at 0.6086 working hours all to take time off during working hours, 0 otherwise Nonstressful work 1 if respondent hardly ever or never finds to have a stressful work, 0 0.2186 otherwise Hours worked weekly Number of hours worked per week 37.085 8.921 Good relations between 1 if respondent considers that relations between workmates or 0.8634 workmates or colleagues colleagues are quite good or very good, 0 otherwise Good relations between 1 if respondent considers that relations between management and 0.7316 manag. and employees employees are quite good or very good, 0 otherwise Job does use of past work 1 if respondent considers that job does a lot or almost all use of 0.6233 exper. and skills past work experience and skills, 0 otherwise Job demands do not 1 if respondent considers that job demands hardly ever or never 0.5863 interfere with family life interfere with the family life, 0 otherwise 1. This table describes some variables to be used as explanatory in the regression analysis and reports the corresponding sample mean and standard deviation; 2. Standard deviations were computed only for continuous variables; 3. For each binary variable the mean matches its sample proportion. Table 2. Job satisfaction and organizational commitment description. Level of Job Satisfaction: 1-Completely dissatisfied 1.7 2-Very dissatisfied 2.2 3-Dissatisfied 4.8 4-Neither satisfied nor dissatisfied 10.1 5-Satisfied 35.9 6-Very satisfied 30.2 7-Completely satisfied 14.7 Level of Organizational Commitment: a)I am willing to work harder than I have to in order to help firm or organization for succeed 1-Strongly disagree 5.3 2-Disagree 12.8 3-Neither agree nor disagree 21.8 4-Agree 42.6 5-Strongly agree 17.5 b)I am proud to be working for my firm or organization 1-Strongly disagree 2.6 2-Disagree 7.6 3-Neither agree nor disagree 23.2 4-Agree 45.7 5-Strongly agree 21.0 c) I would turn down another job that offered quite a bit more pay in order to stay with this organization 1-Strongly disagree 16.1 2-Disagree 28.5 3-Neither agree nor disagree 23.3 4-Agree 20.0 5-Strongly agree 12.1 % indicates the percentage in the sample. JOURNAL OF APPLIED ECONOMICS 9 statements were reported on a five-point scale ranging from strongly disagree to strongly agree. These three items naturally correspond to our measures of organiza- tional commitment to the extent that they capture workers’ levels of involvement, affection, attachment, or dedication to the firm or organization. 3.3. The statistical model The constructs to be explained in this paper are the level of job satisfaction and the level of organizational commitment. For the empirical analysis and following the conceptual framework previously described, the determinants of job satisfaction include both employee and job or workplace-related characteristics. These are also considered deter- minants of organizational commitment together with job satisfaction. For this purpose, we estimate separate equations for job satisfaction and organizational commitment: a common procedure in the literature. Due to the ordinal nature of the dependent variables, a linear regression approach is not suitable. Instead, an ordered probit type model may be used. Another common alternative in the literature is to assume that the error term follows a logistic pattern, which yields the so-called ordered logit model (Greene, 2018). Consider that the dependent variable (job satisfaction or organizational commitment) for respondent i is determined by the following stochastic process: y ¼ βx þ ε i ¼ 1; . . . ; N (1) i i where y is a latent variable, x is a set of explanatory variables, β is the vector of parameters to be estimated, andε stands for a random term. However, in the data, we do not observe y but an indicator variable y , which indicates the level of satisfaction or the level of organizational commitment, depending on the case under scrutiny, to which the respondent belongs, such that: y ¼ j if μ < y � μ j ¼ 1; . . . ; J (2) j 1 j The thresholds µ are unknown and cut the assumed distribution for the error term into segments, being that µ <µ . Assuming that the error terms, ε , are independent and j-1 j i follow a standard normal distribution, the probability that respondent i belongs to each alternative j is given by: � � � � 0 0 Pðy ¼ jÞ ¼ Φ μ β x Φ μ β x if j ¼ 1; . . . ; J (3) i i i j j 1 The log-likelihood function to be maximized is given by: N n � � � �o X X 0 0 LogL ¼ λ log Φ μ β x Φ μ β x (4) ij i i j j 1 i¼1 j¼1 where λ ¼ 1 if y ¼ j ij i λ ¼ 0 if y � j i ¼ 1; . . . ; N j ¼ 1; . . . ; J ij i 10 J. A. C. VIEIRA ET AL. Identification in this model is achieved by excluding the constant term and by fixing one of the µ (Stewart, 2004). Another alternative would be a simple normalization that keeps the constant term but fixes µ equal to zero (Greene, 2018). The ordered probit model, although widely used to examine ordinal data, depends on a strong assumption about the error term. Our estimation model uses, as a robust yet flexible alternative approach to the stringent assumption associated with the standard ordered probit model, a semi-nonparametric estimator of an unknown density, proposed by Gallant and Nychka (1987). This procedure can be written as the product of a squared polynomial and a normal density. It is noteworthy to mention that the resulting model nests the standard ordered probit model, thus allowing for hypothesis testing in order to choose the appropriate model. The semi-nonparametric approach approximates the unknown density as: γ ε ϕðεÞ k¼0 k f ðεÞ ¼ (5) K � 1 2 ∫ γ ε ϕðεÞdε 1 k¼0 k The required distribution function is specified as: � � ∫ γ ε ϕðεÞdε 1 k¼0 k F ðεÞ ¼ (6) K � 1 2 ∫ γ ε ϕðεÞdε 1 k¼0 k Equation (5) defines a family of semi-nonparametric distributions for increasing values of K, and the unknown density can be closely approximated by this Hermite series by increasing the choice of K – the degree of the polynomial -, provided that it satisfies certain smoothness conditions (Gallant & Nychka, 1987; Stewart, 2004). Following Gallant and Nychka (1987), the model parameters can be consistently estimated by maximizing a pseudo-likelihood function which replaces in Equation (4) the standard normal cumulative distribution by the one defined in (6). The model requires a location normalization for identification. One way of doing this is to fix the first threshold (µ ) to its ordered probit estimate by using (4), which closely resembles the procedure used by Melenberg and van Soest (1996) in the context of a probit model. It is also worth noting that when K = 0, K = 1, and K = 2, the model is equivalent to the conventional ordered probit model. The choice of K is part of the model selection procedure by testing between different alternatives. In this paper, model estimation and further testing rely on Stewart (2004). 4. Results and discussion 4.1. Results We start by noting that likelihood-ratio tests, included in Table 3, regarding the explana- tion of job satisfaction for different values of K from 3 to 5 reject the standard ordered probit model against the semi-nonparametric alternative in all cases. Moreover, like- lihood-ratio tests for K against K-1 reject the null hypothesis at significance levels of 10% or less for K ≤ 4 but not for K above this limit, suggesting the selection of a K = 4 model. JOURNAL OF APPLIED ECONOMICS 11 Table 3. Job satisfaction: LRT tests for model choice. LR-test LR-Test K Log-L of OP DF p-value of K-1 DF p-value OP −18088.0 K = 3 −18044.4 87.15 1 0.000 87.15 1 0.000 K = 4 −17999.8 176.46 2 0.000 89.30 1 0.000 K = 5 −17999.0 178.02 3 0.000 1.56 1 0.211 1. This table reports two likelihood-ratio tests for model choice such as suggest by Stewart (2004): a) LR-test of OP which tests the standard ordered probit model (null hypothesis) against three semi-nonparametric alternatives for K = 3, K = 4, and K = 5 (in the K = 1 and K = 2 cases the model is equivalent to the standard ordered probit) and b) LR-test of K-1 which tests the alternative K-1 (null hypothesis) against the alternative K; 2. LR-test of OP is computed as −2(Log-L – OP Log-L ) with j = 3, 4, or 5 (degrees of freedom and the test p-values of a chi-square distribution are Columns 4 and 5, K=j respectively); 3. LR-test of K-1 is computed as −2(Log-L – Log-L ) with K = 3, 4, 5 (degrees of freedom and the test K-1 K p-values of a chi-square distribution are Columns 7 and 8, respectively); 4. K, Log-L, OP, and DF denote the order of the Hermite polynomial, the value of the Log-L function evaluated at the parameters estimated values, standard ordered probit model, and degrees of freedom, respectively. Estimation results for the K = 4 semi-nonparametric ordered probit model are pre- sented in Table 4, in which workers’ reported level of job satisfaction is explained through two sets of employee and job-related characteristics. The null hypotheses that each of these sets of variables does not explain workers’ job satisfaction are rejected at conven- tional significance levels using the likelihood-ratio tests included in Table 5. These results validate hypotheses H1 and H2. However, it is worth noting that not all variables included in those sets have explana- tory power, such is the case of individual characteristics like age, gender, and whether or not the employee is a union member (Table 4). Other attributes such as education, religious beliefs, and country of residence explain job satisfaction. For instance, as education increases, the likelihood of being completely satisfied decreases, and that of being completely dissatisfied increases. In terms of religious beliefs, Buddhists show the highest probability of being completely satisfied with their jobs. Most interestingly, there are significant differences in job satisfaction by country. Out of 36 countries included in the regression and after controlling for the effect of a large number of other individual and job-related characteristics, Georgia and India occupy the two extremes. That is, the highest likelihood of being completely satisfied is found in India and is the lowest in Georgia, all else equal. Compared with the United States, which corresponds to the reference category in the regression, the probability of a worker being completely satisfied is higher, and the probability of being completely unsatisfied is lower, for countries such as India, Mexico, Venezuela, Spain, Russia, Israel, Croatia, Chile, Austria, and the Czech Republic. The reverse (i.e., the probability of being completely satisfied is lower and that of being completely unsatisfied is higher, as compared with the United States) is true in Georgia, Taiwan, China, Japan, Lithuania, Suriname, Sweden, Australia, Germany, and Slovenia. There is no statistical difference in those probabilities between the United States and the remaining 15 countries used in the analysis, all else equal. The heterogeneity in job satisfaction across countries is in some cases quite striking, such as the finding that Venezuelans had a higher probability of reporting (high) job satisfaction compared to Americans, while Germans had in turn a lower probability. There is no clear-cut explanation for these differences, but one can note that Germany is known as a strong labor market, while Venezuela has been experiencing an economic 12 J. A. C. VIEIRA ET AL. Table 4. The determinants of employees’ job satisfaction. Coef. S. Error 1.Employee Characteristics Age −0.0039 0.0044 Age /100 0.0001 0.0001 Female 0.0191 0.0187 Years of education −0.0021 0.0009 ** Living in steady partnership 0.0636 0.0204 *** Unionized worker −0.0320 0.0242 Catholic 0.0701 0.0290 ** Protestant 0.0653 0.0309 ** Orthodox 0.1018 0.0595 * Other Christian religions −0.0541 0.0474 Jewish −0.2228 0.1334 * Islamic 0.1544 0.0685 ** Buddhist 0.2111 0.0806 *** Hindu 0.0524 0.1140 Other Asian religions 0.1991 0.0888 ** Other religions −0.0689 0.0972 Attendance of religious services 0.0617 0.0321 * Australia −0.1875 0.0718 *** Austria 0.2461 0.0742 *** Belgium 0.0361 0.0614 Chile 0.2477 0.0767 *** China −0.3392 0.0850 *** Croatia 0.2706 0.0759 *** Czech Republic 0.1483 0.0685 ** Estonia −0.0347 0.0698 Finland 0.1113 0.0707 France −0.0068 0.0707 Georgia −0.5382 0.1178 *** Germany −0.1776 0.0621 *** Hungary −0.0281 0.0739 Iceland 0.0290 0.0714 India 0.7481 0.1444 *** Israel 0.2793 0.1291 ** Japan −0.2662 0.0776 *** Latvia −0.0653 0.0746 Lithuania −0.2314 0.0827 *** Mexico 0.5825 0.0876 *** New Zealand −0.0936 0.0981 Norway −0.0201 0.0631 Philippines 0.1285 0.0795 Poland 0.0472 0.0802 Russia 0.2801 0.0827 *** Slovak Republic 0.0350 0.0724 Slovenia −0.1633 0.0760 ** South Africa 0.0614 0.0698 Spain 0.3421 0.0673 *** Suriname −0.2016 0.0871 ** Sweden −0.1976 0.0681 *** Switzerland 0.0708 0.0629 Taiwan −0.3906 0.0906 *** United Kingdom 0.0014 0.0705 Venezuela 0.4452 0.0859 *** 2.Job or Workplace Characteristics Supervising other workers 0.0348 0.0220 Public servant 0.0702 0.0210 *** High income job 0.2660 0.0253 *** Secure job 0.2303 0.0239 *** Job with high opportunities for advancement 0.2395 0.0252 *** Received training to improve job skills 0.0800 0.0197 *** Interesting job 0.7409 0.0395 *** (Continued) JOURNAL OF APPLIED ECONOMICS 13 Table 4. (Continued). Coef. S. Error Useful job to society 0.1692 0.0370 *** Job can help other people 0.1514 0.0331 *** Job allows personal contact with other people 0.1150 0.0452 ** Can work independently 0.1379 0.0234 *** Easy to take time off during working hours 0.1285 0.0202 *** Nonstressful work 0.2687 0.0256 *** Hours worked weekly −0.0011 0.0011 Good relations between workmates or colleagues 0.2575 0.0308 *** Good relations between management and employees 0.6294 0.0368 *** Job does use of past work experience and skills 0.1287 0.0206 *** Job demands do not interfere with family life 0.3238 0.0238 *** Thresholds: µ −0.7807 Fixed µ −0.1382 0.0514 *** µ 0.6368 0.0762 *** µ 1.4071 0.1039 *** µ 2.8463 0.1596 *** µ 4.0023 0.2069 *** Polynomial: 1 0.0029 0.0089 *** 2 −0.0980 0.0194 *** 3 0.0054 0.0022 *** 4 0.0169 0.0014 *** Log-L −17999 Wald chi-square (70) 546.1 Number of observations 14437 1. This table reports the estimates of a semi-nonparametric ordered probit model for job satisfaction (dependent variable) with K = 4; 2. ***, **, and * denote significance at the 1%, 5%, and 10% levels, respectively. Table 5. Job satisfaction hypothesis testing. Null hypotheses LRT DF p-value 1.Employee characteristics do not influence job satisfaction, 654 52 0.0000 all else equal 2.Job or workplace characteristics do not influence job 5585 18 0.0000 satisfaction, all else equal LRT, DF, and p-value denote the likelihood ratio test, degrees of freedom (equal to the number of restrictions imposed to the model), and the test p-value (for a chi-square distribution), respectively. crisis. Consequently, it could be the case that due to the well-known dual vocational education and training system in Germany, once one starts a career in a specific field it is quite difficult to change careers. Moreover, increased unemployment experienced by Venezuelans during the time of the survey could make workers in Venezuela happy to have a job at all. In order to evaluate this argumentation, we included a new explanatory variable based on the following 5-point scale ordinal question from the survey How difficult or easy do you think it would be for you to find a job at least as good as your current one?. This new variable assumes a value equal to 1 for responses of the type very difficult and fairly difficult and 0 in the other situations and undoubtedly captures the worker’s perceptions of both macro-general and micro-idiosyncratic factors that impact his or her perceived desirability of his or her circumstances. However, including this variable as a regressor does not eliminate the existence of significant cross-county differences. 14 J. A. C. VIEIRA ET AL. Job-and-workplace characteristics matter for employees’ level of job satisfaction in most cases. The aspects of being a public servant, feeling of security in a job which brings a high income, having many opportunities for advancement, accessing training to improve skills, feeling interested in one’s job, feeling useful to society, helping other people, and having the ease of taking time off during working hours positively impact reported job satisfaction. The same is valid for those who feel they have non-stressful work, good relations among workmates, good relations between management and employees, application of past experience and skills, and no interference with family life. Some of these attributes and, therefore, workers’ level of job satisfaction can be controlled by management. In other words, managers have at their disposal some instruments that can be used in order to foster employees’ satisfaction with the job. The likelihood ratio tests included in Table 6 suggest the use of a K = 4 semi- nonparametric ordered probit model to explain employees’ organizational commitment, whose estimation results are included in Table 7. Moreover, based on the information included in Table 8, the null hypothesis that workers’ job satisfaction does not influence organizational commitment is rejected, thus supporting H3. The regression results predict that higher levels of job satisfaction imply higher levels of organizational commit- ment. However, a word of caution is worth since job satisfaction might be endogenous namely due to omitted variables that affect organizational commitment and are corre- lated with job satisfaction (Saridakis et al., 2018), which we address subsequently. A commonly proposed technique for correcting the potential bias arising from such a problem is the use of instrumental variables (IV) techniques. This requires the existence of at least one observable variable which influences job satisfaction but does not affect employee’s organizational commitment. By inspection of the estimated results included in Tables 4 and 7, we conclude that having a non-stressful work exerts a (positive) direct impact in job satisfaction but does not directly explain organizational commitment. Indeed, ample support for this mediatory role of job satisfaction in the effect of occupa- tional stress on organizational commitment has already been reported by Aghdasi et al. (2011). In order to address the robustness of our previous results, the following two-step strategy has been implemented within our semi-nonparametric approach. From the Table 6. Organizational commitment: LRT tests for model choice. Log-L LR-Test of OP DF p-value LR-Test of K-1 DF p-value I am willing to work harder than I have to in order to help the firm or organization for succeed OP −17916.1 K = 3 −17862.5 107.12 1 0.000 107.12 1 0.000 K = 4 −17824.0 184.27 2 0.000 77.15 1 0.000 K = 5 −17823.7 184.74 3 0.000 0.46 1 0.497 I am proud to be working for my firm or organization OP −15078.5 K = 3 −15010.5 135.94 1 0.000 135.94 1 0.000 K = 4 −14940.8 275.42 2 0.000 139.49 1 0.000 K = 5 −14940.8 275.43 3 0.000 0.01 1 0.938 I would turn down another job that offered quite a bit more pay in order to stay with this organization OP −19394.5 K = 3 −19374.8 39.52 1 0.000 39.52 1 0.000 K = 4 −19308.5 172.03 2 0.000 132.51 1 0.000 K = 5 −19307.8 173.47 3 0.000 1.45 1 0.229 See notes at the bottom of Table 3, which also apply to this table. JOURNAL OF APPLIED ECONOMICS 15 Table 7. The determinants of employees’ organizational commitment. Turn down another Work harder in order job that offered quite to help the firm or Proud to be working a bit more pay to organization for for the firm or stay in the firm or succeed. organization. organization. Coef. S. Error Coef. S. Error Coef. S. Error 1.Employee Characteristics: Age 0.0041 0.0048 0.0138 0.0043 *** 0.0111 0.0043 *** Age /100 −0.0001 0.0001 −0.0001 0.0001 *** 0.0000 0.0001 Female −0.0849 0.0196 *** 0.0022 0.0170 −0.0189 0.0164 Years of education −0.0004 0.0009 −0.0011 0.0008 −0.0003 0.0008 Living in steady partnership 0.0183 0.0199 0.0587 0.0183 *** 0.0153 0.0179 Unionized worker −0.0689 0.0243 *** 0.0260 0.0220 0.0263 0.0212 Catholic 0.0798 0.0293 *** 0.0712 0.0264 *** 0.0240 0.0254 Protestant 0.0375 0.0306 0.0734 0.0283 *** −0.0141 0.0269 Orthodox −0.0778 0.0570 0.0805 0.0532 −0.0460 0.0516 Other Christian religions 0.0007 0.0469 0.1093 0.0435 ** 0.0754 0.0420 * Jewish −0.2291 0.1256 * 0.0554 0.1125 −0.0722 0.1066 Islamic 0.1016 0.0669 0.2213 0.0613 *** 0.0251 0.0586 Buddhist −0.0400 0.0798 0.0963 0.0747 0.1466 0.0716 ** Hindu 0.5009 0.1199 *** 0.2667 0.1034 *** 0.1241 0.1006 Other Asian religions 0.0611 0.0852 0.1705 0.0804 ** 0.0447 0.0747 Other religions 0.1061 0.0924 −0.0180 0.0841 −0.0300 0.0835 Attendance of religious services 0.0201 0.0320 0.0648 0.0292 ** 0.0819 0.0288 *** Australia −0.4012 0.0751 *** −0.3194 0.0656 *** −0.0045 0.0616 Austria −0.6998 0.0893 *** −0.5266 0.0720 *** 0.2398 0.0672 *** Belgium −0.8982 0.0879 *** −0.3205 0.0576 *** 0.1778 0.0540 *** Chile −1.0765 0.1040 *** −0.6323 0.0714 *** 0.0817 0.0643 China −0.1426 0.0812 * −0.3091 0.0775 *** 0.6040 0.0793 *** Croatia −0.7129 0.0901 *** −0.3385 0.0688 *** 0.0307 0.0642 Czech Republic −0.4934 0.0760 *** −0.5862 0.0663 *** 0.4630 0.0645 *** Estonia −0.8941 0.0916 *** −0.7392 0.0690 *** 0.0887 0.0602 Finland −1.0019 0.1002 *** −0.5950 0.0691 *** 0.4438 0.0672 *** France −1.2416 0.1104 *** −0.2787 0.0661 *** 0.0285 0.0622 Georgia 0.0173 0.1133 −0.1824 0.1037 * 0.2403 0.1003 ** Germany −0.8027 0.0828 *** −0.5789 0.0604 *** 0.2818 0.0561 *** Hungary −0.4875 0.0786 *** −0.3495 0.0674 *** 0.0601 0.0641 Iceland −0.0289 0.0714 −0.0791 0.0656 −0.1615 0.0629 *** India −0.3348 0.1372 ** −0.4549 0.1282 *** 0.3549 0.1275 *** Israel −0.1414 0.1220 −0.2211 0.1098 ** 0.5507 0.1105 *** Japan −0.3071 0.0787 *** −0.2565 0.0709 *** 0.6795 0.0782 *** Latvia −1.0476 0.1047 *** −0.4924 0.0702 *** 0.5164 0.0712 *** Lithuania −1.0255 0.1078 *** −0.7497 0.0789 *** 0.3905 0.0771 *** Mexico −0.2719 0.0871 *** −0.1625 0.0775 ** 0.3003 0.0797 *** New Zealand −0.1319 0.0964 −0.1243 0.0895 0.1655 0.0820 ** Norway −0.3502 0.0666 *** −0.1772 0.0580 *** 0.2635 0.0566 *** Philippines −0.3433 0.0788 *** −0.3261 0.0724 *** 0.5307 0.0754 *** Poland −0.9971 0.1056 *** −0.6108 0.0768 *** 0.1652 0.0708 ** Russia −0.8942 0.1032 *** −0.8741 0.0821 *** 0.3350 0.0744 *** Slovak Republic −0.6141 0.0827 *** −0.5256 0.0679 *** 0.2512 0.0633 *** Slovenia −0.7299 0.0894 *** −0.2735 0.0693 *** 0.1889 0.0666 *** South Africa 0.0616 0.0677 −0.1480 0.0633 ** 0.2192 0.0618 *** Spain −0.6312 0.0850 *** 0.0345 0.0612 −0.0567 0.0622 Suriname −0.4209 0.0920 *** −0.1564 0.0776 ** 0.5227 0.0858 *** Sweden −0.6641 0.0827 *** −0.5185 0.0649 *** −0.0896 0.0605 Switzerland −0.4233 0.0698 *** −0.3586 0.0597 *** 0.3468 0.0577 *** Taiwan −0.1209 0.0853 −0.4728 0.0808 *** 0.1659 0.0753 ** United Kingdom −0.3073 0.0721 *** −0.3066 0.0644 *** 0.1602 0.0606 *** Venezuela 0.4025 0.0923 *** 0.3982 0.0837 *** 0.1268 0.1158 2.Job or Workplace Characteristics Supervising other workers 0.1893 0.0257 *** 0.0962 0.0204 *** 0.0861 0.0200 *** (Continued) 16 J. A. C. VIEIRA ET AL. Table 7. (Continued). Turn down another Work harder in order job that offered quite to help the firm or Proud to be working a bit more pay to organization for for the firm or stay in the firm or succeed. organization. organization. Coef. S. Error Coef. S. Error Coef. S. Error Public servant −0.0730 0.0208 *** 0.0118 0.0189 −0.0199 0.0181 High income job 0.0533 0.0222 ** 0.0268 0.0202 0.0938 0.0201 *** Secure job −0.0280 0.0210 0.0941 0.0197 *** 0.0868 0.0194 *** Job with high opportunities for 0.1140 0.0237 *** 0.1607 0.0219 *** 0.1329 0.0215 *** advancement Received training to improve job 0.0884 0.0200 *** 0.1145 0.0181 *** 0.0137 0.0169 skills Interesting job 0.1539 0.0256 *** 0.3496 0.0265 *** 0.1401 0.0230 *** Useful job to society 0.0369 0.0357 0.1602 0.0331 *** 0.1155 0.0334 *** Job can help other people 0.0710 0.0323 ** 0.1014 0.0296 *** 0.1754 0.0313 *** Job allows personal contact with 0.0971 0.0447 ** 0.0331 0.0406 0.0744 0.0412 * other people Can work independently 0.1243 0.0236 *** 0.0991 0.0208 *** 0.0407 0.0200 ** Easy to take time off during 0.1190 0.0207 *** 0.0752 0.0181 *** 0.0813 0.0181 *** working hours Nonstressful work −0.0310 0.0229 −0.0041 0.0210 0.0216 0.0203 Hours worked weekly 0.0016 0.0011 −0.0006 0.0010 −0.0018 0.0009 * Good relations between −0.0063 0.0286 0.0031 0.0264 0.0552 0.0260 ** workmates or colleag. Good relations between manag. 0.2772 0.0305 *** 0.3432 0.0261 *** 0.1747 0.0239 *** and employees Job does use of past work exper. 0.0524 0.0195 *** 0.0356 0.0180 ** 0.0310 0.0173 * and skills Job demands do not interfere with 0.0904 0.0200 *** −0.0151 0.0178 0.0075 0.0171 family life 3.Job satisfaction Very dissatisfied 0.3045 0.1291 ** 0.5479 0.1161 *** 0.7190 0.1215 *** Fairly dissatisfied 0.5518 0.1164 *** 0.8523 0.1036 *** 0.7480 0.1048 *** Neither satisfied nor dissatisfied 0.6530 0.1135 *** 1.1206 0.1027 *** 1.0872 0.1086 *** Fairly satisfied 0.8342 0.1185 *** 1.4219 0.1071 *** 1.3008 0.1136 *** Very satisfied 1.0407 0.1270 *** 1.8337 0.1156 *** 1.6521 0.1272 *** Completely satisfied 1.5128 0.1485 *** 2.3296 0.1283 *** 1.9538 0.1413 *** Thresholds: µ −0.9924 Fixed −0.0626 Fixed 1.3602 Fixed *** µ 0.0278 0.0065 *** 0.9205 0.0530 *** 2.3099 0.0641 *** µ 0.8152 0.1293 *** 2.0067 0.0942 *** 2.9433 0.1027 *** µ 2.2040 0.2215 *** 3.4561 0.1477 *** 3.7003 0.1488 *** Polynomial: 1 −0.1040 0.0774 −0.2179 0.0560 *** −0.1430 0.0692 ** 2 −0.1400 0.0315 *** −0.1850 0.0197 *** −0.1987 0.0415 *** 3 0.0063 0.0013 *** 0.0289 0.0076 *** 0.0076 0.0028 *** 4 0.0237 0.0025 *** 0.0259 0.0019 *** 0.0289 0.0034 *** Log-L −17824 −14940 −19308 Wald chi-square (76) 272.5 759.3 358.2 Number of observations 14437 14437 14437 1. This table reports the estimates of three semi-nonparametric ordered probit models (one for each organizational commitment construct) with K = 4; 2. ***, **, and * denote significance at the 1%, 5%, and 10% levels, respectively. coefficients of the estimated job satisfaction equation included in Table 4 which include a dummy for having a non-stressful work among the covariates, we calculated in a first step the corresponding predicted values for the job satisfaction index y (see Equation (1)). In a second step, we estimated a semi-nonparametric ordered probit (K = 4) for the organizational commitment constructs, which includes this predicted index among the JOURNAL OF APPLIED ECONOMICS 17 Table 8. Organizational commitment hypothesis testing. 1.Job satisfaction does not influence organizational commitment, all else equal LRT DF p-value 1.1 I am willing to work harder than I have . . . 778 6 0.0000 1.2 I am proud to be working for firm or organization 1632 6 0.0000 1.3 I would turn down another job . . . 1048 6 0.0000 2. Employee characteristics do not directly influence organizational commitment, all else equal 2.1 I am willing to work harder than I have . . . 1721 52 0.0000 2.2 I am proud to be working for firm or organization 919 52 0.0000 2.3 I would turn down another job . . . 799 52 0.0000 3. Job characteristics do not directly influence organizational commitment, all else equal 3.1 I am willing to work harder than I have . . . 710 18 0.0000 3.2 I am proud to be working for firm or organization 2141 18 0.0000 3.3 I would turn down another job . . . 528 18 0.0000 See note at the bottom of Table 5, which also applies to this table. covariates. Other explanatory variables included in the organizational commitment equations are the same as in Tables 8, except the work stress indicator which has been removed. The estimated coefficient associated with the satisfaction index is positive and significant at the 5% level for all the organizational commitment constructs, thus con- firming that job satisfaction explains and exerts a positive effect on employee’s organiza- tional commitment. Estimated values for this coefficient across organizational commitment constructs are as follows: I am willing to work harder than I have to in order to help firm or organization for succeed (coef. = 0.0874, s.e. = 0.0383), I am proud to be working for my firm or organization (coef. = 0.2967, s.e. 0.0850) and I would turn down another job that offered quite a bit more pay in order to stay with this organization (coef. = 0.2502, s.e. 0.0971), where reported standard errors are robust and based on the Huber- White sandwich estimator of variance. In addition to this exercise, we also carried out further analysis by estimating a parametric ordered probit model for organizational commitment which treats job satisfaction as potentially endogenously determined and where the change in work stress is used once again as the instrument (performed by using the extended regression command eoprobit from the STATA statistical package). This approach implied a maximum likelihood joint estimation of two ordered probit models for job satisfaction and organizational commitment which allows for the correlation between the errors of these two equations. Such as before, the results indicated a positive and statistically significant role of job satisfaction to the determination of organizational commitment. Moreover, the null hypothesis of zero correlation between error terms of the two equations is not rejected at the 1% of significance across the three organizational commitment constructs, being the estimated results as follows: I am willing to work harder than I have to in order to help firm or organization for succeed (corr. = 0.1227, s.e. = 0.3131), I am proud to be working for my firm or organization (corr. = 0.0621, s.e. 0.1073) and I would turn down another job that offered quite a bit more pay in order to stay with this organization (corr = −0.1272, s.e. 0.1704). Therefore, we cannot reject the hypothesis of exogeneity of job satisfaction in the organizational commitment equations. In sum, the previously reported positive impact of job satisfaction on organizational commitment is robust and not undermined by the endogeneity issues. 18 J. A. C. VIEIRA ET AL. The null hypotheses that employee characteristics and job characteristics do not directly influence organizational commitment are rejected at conventional levels of significance, thus validating H4 and H5, respectively (Table 8). This implies that job and worker attributes do not determine organizational commitment only indirectly via their effect on job satisfaction, but also directly. In such a case, organizational commit- ment varies within each level of job satisfaction, depending on the values of those attributes. Nevertheless, some particularities can be isolated when examining the set as a whole and investigating the role of specific variables. Only a few cases will be mentioned below, although others can be easily identified within the estimated results included in Tables 4 and 7. For instance, although gender has no visible effect on job satisfaction, it directly impacts the degree of agreement on the willingness to work harder in order to help the firm or organization succeed. In this case, women are less likely to strongly agree and more likely to strongly disagree, compared to men. However, gender has no visible effects on other organizational commitment indicators such as the pride of working for the firm or the willingness to turn down another job that offers quite a bit more pay in order to stay with the organization. The same is valid for union membership, whose coefficient is not statistically different from zero in the satisfaction equation. However, unionized workers are more unwilling to work harder in order to help the firm succeed than their non-unionized counterparts, but do not differ from these with respect to the pride of working for the firm or the willingness to stay in the job. There are substantial heterogeneous outcomes regarding the impact of religious beliefs on organizational commitment. Hindus and Catholics are apparently more available to work harder to promote the success of the firm or organization. Hindus, Islamic, Protestants, and Catholics are more likely to be proud to work for a firm or organization. Buddhists are more probable to turn down another job in order to stay in the firm or organization. Years of completed education exert no direct effect on organizational commitment but only indirectly through their influence on job satisfaction. There is also significant heterogeneity regarding the influence of country of residence on organizational commitment, which varies within a specific construct as well as across constructs (Table 9). Regarding the statement concerning their willingness to work harder in order to help a firm succeed, workers in Venezuela had the highest probability of strongly agreeing and the lowest probability of strongly disagreeing, all else equal, with the other extreme of the ranking occupied by France. The United States ranked fourth, although the difference was not statistically different from the second and the third (South Africa and Georgia, respectively). With respect to being proud of working for the firm or organization, Venezuela also led, while the other extreme of the ranking was found in Russia. In this case, the United States ranked third but was not statistically different from the second in the ranking (Spain), and France occupied a middle position. Despite some visible differences in these two rankings, such as the position of France, a Spearman rank correlation equals 0.606 (P = 0.000), indicating the positive significant association between them, therefore suggesting a proximity of type of organizational commitment captured by these two variables. However, substantial differences emerge when these rankings are compared with that of the willingness to turn down another job that offered quite a bit more pay in order to stay in the firm or organization. In this case, workers in Japan were the ones with the highest probability of strongly agreeing and the JOURNAL OF APPLIED ECONOMICS 19 Table 9. Regression coefficients ranking by country and Spearman rank correlation by organizational commitment constructs. Turn down another job that offered quite Work harder in order to help the Proud to be working for a bit more pay to stay in the firm or firm or organization for succeed. the firm or organization. organization. 1 Venezuela Venezuela Japan 2 South Africa Spain China 3 Georgia United States Israel 4 United States Iceland Philippines 5 Iceland New Zealand Suriname 6 Taiwan South Africa Latvia 7 New Zealand Suriname Czech Republic 8 Israel Mexico Finland 9 China Norway Lithuania 10 Mexico Georgia India 11 Japan Israel Switzerland 12 United Kingdom Japan Russia 13 India Slovenia Mexico 14 Philippines France Germany 15 Norway United Kingdom Norway 16 Australia China Slovak Republic 17 Suriname Australia Georgia 18 Switzerland Belgium Austria 19 Hungary Philippines South Africa 20 Czech Republic Croatia Slovenia 21 Slovak Republic Hungary Belgium 22 Spain Switzerland Taiwan 23 Sweden India New Zealand 24 Austria Taiwan Poland 25 Croatia Latvia United Kingdom 26 Slovenia Sweden Venezuela 27 Germany Slovak Republic Estonia 28 Estonia Austria Chile 29 Russia Germany Hungary 30 Belgium Czech Republic Croatia 31 Poland Finland France 32 Finland Poland United States 33 Lithuania Chile Australia 34 Latvia Estonia Spain 35 Chile Lithuania Sweden 36 France Russia Iceland Work . . . - 0.606 (p = 0.000) 0.021 (p = 0.902) Proud . . . - 0.004 (p = 0.983) 1. The first panel (rows numbered 1 to 36) of this table reports the ranking of the organizational commitment constructs regression coefficients from the most committed country (#1) to the least (# 36); 2. The second panel includes the Spearman rank correlation across organizational commitment constructs and the corresponding p-value test for the null hypothesis of zero correlation. lowest probability of strongly disagreeing, followed by China, Israel, and the Philippines (Table 9). The other extreme is occupied by Iceland, and the United States ranks thirty- second out of 36 countries. Employees in Venezuela, which occupied the top of the ranking in the former constructs, now occupy the twenty-sixth position. A Spearman rank correlation coefficient included at the bottom of Table 9 does not support any significant association between this ranking and the two previously examined. This finding suggests that the type of organizational commitment captured by this variable and the former ones are quite different, as it is likely closer to some sort of continuance commitment. Employees with high levels of continuance commitment remain in the 20 J. A. C. VIEIRA ET AL. organization because they need to stay until they find a more suitable opportunity elsewhere (Meyer & Allen, 1997). 4.2. Discussion Job satisfaction, organizational commitment, and the relationship between them have been debated in several scientific areas. The present study contributes to this empirical literature by evaluating the determinants of these two constructs using a semi- nonparametric estimation of separate ordered probit models, with the benefit of not imposing ex ante stringent distributional assumptions regarding the error term. For this purpose, we consider a conceptual framework where job satisfaction may act as an antecedent of organizational commitment. Empirical testing revealed interesting results. The results support our empirical estimation strategy, as the simple ordinary probit model – a specific case of our more general, more flexible non-parametric model – is rejected in favor of the general form we herein propose. Job satisfaction depends on certain employees’ characteristics and job- related attributes, in line with the literature. Furthermore, job satisfaction significantly influences organizational commitment but does not fully explain such organizational commitment behavior. Finally, organizational commitment depends directly and indir- ectly (via job satisfaction) on employees and job-related attributes. These outcomes have several managerial implications. It has been argued that organizational commitment contributes to business success, and our results indicate that management may foster organizational commitment to a certain extent. In fact, certain variables that directly and/or indirectly determine organizational commitment are not readily under the management’s control, such as, and for instance, gender, religious beliefs and practices, public versus private sector work, country of residence. However, many instruments can be used by management in order to directly and/or indirectly enhance organizational commitment, including creating conditions to reduce stress in the workplace (due to its indirect impact on organizational commitment via job satisfaction) and promoting good relations between workmates and with management. Whenever possible, enabling an employee to take time off during working time and improving the coordination between job and family life also seems important in order to achieve that goal, which points to the role of flexible workplace arrangements and practices for individuals, teams, and organizations (Anderson et al., 2002; Scandura & Lankau, 1997). Recruiting workers with previous experience and skills to be used at work or providing training to improve workers’ skills in order to avoid job- skill mismatch can help promote satisfaction and commitment. Other instruments relate to the development of practices that promote employees’ positive feelings about job aspects such as pay, security, or autonomy and provide opportunities for job career development. Our results are useful for managers to address perils of the Great Resignation of late 2021 and early 2022, with high number of resignations and high labour market tightness in labour markets such as the USA and associated potential for non-optimal job turnover and wage-growth induced inflation. In fact, the information herein uncovered may be used for managers to design human resource policies and practices that foster job satisfaction and organizational commitment, thus potentially avoiding excessive job turnover in a win–win manner for workers and organizations. JOURNAL OF APPLIED ECONOMICS 21 Finally, country-specific factors play a significant role in job satisfaction and organiza- tional commitment. Indeed, job satisfaction varies substantially according to country of residence, after controlling for a large set of personal and job or workplace-related attributes. The same is true regarding organizational commitment. Moreover, the impact of country of residence on the explanation for the likelihood of turning down another job that offered quite a bit more pay in order to stay at the firm and the explanation for the other two organizational commitment constructs differs substantially. These results suggest that, despite the convergence in workplaces and workforces in many aspects due to globalization and the expanding role of multinationals, managers and human resources professionals alike must be aware that substantial differences still exist across countries (even after controlling for religious dimensions). 5. Conclusions and future research directions This paper examined job satisfaction and organizational commitment using a sizeable, rich, micro data set for a large number of working respondents in 36 countries. Due to the ordered nature of the dependent variables, we estimate ordered probit equations using a semi-nonparametric approach, which revealed itself to be far superior to the conventional ordered probit model thus validating our proposed empirical strategy. The results indicate that employee and job-related attributes directly and indirectly (through job satisfaction) affect organizational commitment. However, within each of those sets, not all variables play the same role or are equally controllable for managerial purposes. Our empirical results do uncover a set of workplace-related variables which managers can leverage to significantly foster organizational commitment. A very interesting result is that despite the ubiquitous and inexorable globalization process, job satisfaction and organizational commitment differ significantly across countries, even after a large set of controls for individual and job-workplace related characteristics is considered. Managers ought to consider said micro determinants of job satisfaction and organizational com- mitment and cross-country differences to design well-informed human resources poli- cies that aim to foster job satisfaction and organizational commitment, which could help address job resignations that contribute negatively to optimal job turnover; an economic problem acutely felt in certain labour markets experiencing the present day so-called Great Resignation. The semi-nonparametric approach does not address some aspects which could be explored in future research, such as a potential reciprocity between the organizational commitment and job satisfaction, which could be relevant (Saridakis et al., 2018). Moreover, a replication of the methodology applied to different countries separately could add to the understanding of cross-country differences or similarities in the determinants of job satisfaction and organizational commitment as well as the relation- ship between these two constructs. Disclosure statement No potential conflict of interest was reported by the author(s). 22 J. A. C. VIEIRA ET AL. Funding This paper/research is financed by Portuguese national funds through FCT – Fundação para a Ciência e a Tecnologia, I.P., project number UIDB/00685/2020. Notes on contributors José A. C. Vieira is a Professor of Economics at the School of Business and Economics of the University of the Azores, in Portugal. He holds a Ph.D. in Economics from the University of Amsterdam, in Netherlands. His main research areas include tourism and labour economics. He is a member of the editorial board of Tourism Economics. Francisco J. F. Silva is an Assistant Professor of Operations Research at the School of Business and Economics of the University of the Azores, in Portugal. He holds a Ph.D. in Management from the University Pompeu Fabra, in Spain. His main research areas include operations research and tourism economics. João C. A. Teixeira is an Assistant Professor of Finance at the School of Business and Economics of the University of the Azores, in Portugal. He holds a Ph.D. in Finance from Lancaster University, in the United Kingdom. His main research areas include banking and corporate finance. António J. V. F. G. Menezes is an Associate Professor of Economics at the School of Business and Economics of the University of the Azores, in Portugal. He holds a Ph.D. in Economics from Boston College, in the U.S.A. His main research areas include labor economics and transportation economics. Sancha N. B. de Azevedo is a manager in the marketing area. She holds a MSc in Economics and Business Sciences and an undergraduate degree in Economics at the School of Business and Economics of the University of the Azores, in Portugal. ORCID José A. C. Vieira http://orcid.org/0000-0003-1422-1288 Francisco J. F. Silva http://orcid.org/0000-0002-3893-6029 João C. A. Teixeira http://orcid.org/0000-0003-4774-0236 António J. V. F. G. Menezes http://orcid.org/0000-0002-2001-1589 Sancha N. B. de Azevedo http://orcid.org/0000-0002-5407-3569 Information on rights and permissions The authors hereby knowingly accept the rules and practices regarding the reproduction of copyright material in their articles. Submission declaration statement The authors hereby solemnly declare that this manuscript is not under consideration for publica- tion elsewhere and that it has not already been published and that it will also not be submitted for publication elsewhere without the agreement of the Managing Editor. JOURNAL OF APPLIED ECONOMICS 23 References Adams, J. 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Climbing the ladders of job satisfaction and employee organizational commitment: cross-country evidence using a semi-nonparametric approach

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Climbing the ladders of job satisfaction and employee organizational commitment: cross-country evidence using a semi-nonparametric approach

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Satisfied and committed employees play a major positive role in business performance in today’s globalized and competitive landscape. This paper contributes to the literature on the empirical determinants of job satisfaction and organizational commitment, drawing on a rich micro dataset for 36 countries, using a flexible semi-nonparametric approach, which nests and outperforms the standard ordered probit model. The findings indicate that job satisfaction and organizational commitment...
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10.1080/15140326.2022.2163581
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JOURNAL OF APPLIED ECONOMICS 2023, VOL. 26, NO. 1, 2163581 https://doi.org/10.1080/15140326.2022.2163581 RESEARCH ARTICLE Climbing the ladders of job satisfaction and employee organizational commitment: cross-country evidence using a semi-nonparametric approach a a a José A. C. Vieira , Francisco J. F. Silva , João C. A. Teixeira , a b António J. V. F. G. Menezes and Sancha N. B. de Azevedo School of Business and Economics and Centre of Applied Economics Studies of the Atlantic, University of the Azores, Ponta Delgada, Portugal; School of Business and Economics, University of the Azores, Ponta Delgada, Portugal ABSTRACT ARTICLE HISTORY Received 23 November 2021 Satisfied and committed employees play a major positive role in Accepted 23 December 2022 business performance in today’s globalized and competitive land- scape. This paper contributes to the literature on the empirical KEYWORDS determinants of job satisfaction and organizational commitment, Job satisfaction; employee drawing on a rich micro dataset for 36 countries, using a flexible organizational commitment; semi-nonparametric approach, which nests and outperforms the cross-country differences; standard ordered probit model. The findings indicate that job great resignation satisfaction and organizational commitment can be fostered by instruments which can be controlled by management. Our results shed timely light on how managers can improve job satisfaction and organizational commitment and address implications of the Great Resignation. However, despite the ever-increasing pace of globalization and expanding role of multinationals across the globe in shaping work environments, our results uncover that significant cross-country differences in job satisfaction and organi- zational commitment do exist, even after controlling for a plethora of job-and-workplace manageable attributes and individual (includ- ing religious dimensions) related characteristics. 1. Introduction In today’s competitive landscape, human resources are increasingly recognized as the most valuable assets to any organization (Fulmer & Ployhart, 2014). Consequently, strategic human resources management plays a fundamental role in increasing employ- ees’ job satisfaction and organizational commitment and consequently business perfor- mance (Brown et al., 2011). Within this context, researchers and human resource practitioners consider employees’ satisfaction as a critical goal to be achieved, which influences their commitment and other positive behavioral attitudes towards the orga- nization (Brown et al., 2011). CONTACT António J. V. F. G. Menezes antonio.jv.menezes@uac.pt School of Business and Economics and Centre of Applied Economics Studies of the Atlantic, University of the Azores, Ponta Delgada, Portugal Supplemental data for this article can be accessed online at https://doi.org/10.1080/15140326.2022.2163581 © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/ licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 2 J. A. C. VIEIRA ET AL. Therefore, there is a growing body of empirical literature on the determinants of employees’ job satisfaction within human resource management and organizational behavior literature or, more broadly, in economics, psychology, and sociology (Belfield & Harris, 2002; Borjas, 1979; Clark, Oswald, 1996; Idson, 1990; Johnson & Johnson, 2002; Judge & Hulin, 1993; Judge et al., 2002; King & Williamson, 2005; Souza-Poza & Souza- Poza, 2003; Vieira, 2005; Westover & Taylor, 2010) and how such satisfaction relates to employees’ level of organizational commitment (Harter et al., 2002; Rayton, 2006; Saridakis et al., 2018; Valaei & Rezaei, 2016) and organizational performance (e.g., Harter et al., 2002; Koys, 2001). This paper adds novel empirical evidence to the literature on job satisfaction and employee organizational commitment and its managerial implications. In order to achieve this objective, we address the following questions. First, we inquire if there are specific job satisfaction enhancing variables at managers’ disposal, or if job-satisfaction is intrinsic to workers (e.g., their demographics or religious beliefs). Second, we evaluate the extent to which employee organizational commitment is explained by job satisfaction. To answer these questions, we analyze a vast, detailed, rich sample of employees for a large number of countries − 36 – using a robust yet flexible semi-nonparametric model, of which the ordered probit model is a particular, restricted case. We focus on cross-country differences, as the data allow to isolate cross-country differences, after controlling for a rich plethora of job and workplace-related characteristics, in addition to individual related characteristics, including religious beliefs and practices. The results indicate that the conventional ordered probit model, which needs a distributional assumption about the error term, is rejected in favor of the proposed more flexible semi-nonparametric alternative, validating, thus, our approach. Moreover, the findings suggest that while not all determinants of workers’ job satisfaction can be influenced by management, it is most interesting to note that indeed some instruments that increase job satisfaction are available to managers and controlled by managers. The results also indicate that increas- ing job satisfaction increases employees’ organizational commitment. In addition, certain determinants of job satisfaction also exert a direct (not only indirect) effect on employee organizational commitment. Quite interestingly, there are striking cross-country differ- ences on the determinants of job satisfaction and employee organizational commitment even after controlling for a rich plethora of job, workplace, and individual characteristics (including cultural and religious beliefs), which researchers and human resources man- agers alike ought to consider. The paper is organized as follows. Section 2 reviews the literature on job satisfaction and employee organizational commitment. Section 3 presents the conceptual framework, the hypotheses to be tested, the data set collected, and the statistical and micro-econometric model used. Section 4 presents the estimation results and discusses the findings. Finally, Section 5 contains the main conclusions and directions for further research. 2. Literature review 2.1. Job satisfaction In general, in the literature the concept of job satisfaction expresses the degree to which one feels positively or negatively about his or her job and involves a subjective evaluation JOURNAL OF APPLIED ECONOMICS 3 of many work-specific factors such as pay, work autonomy, occupational prestige, super- vision, promotional opportunities, and workplace relations (Clark, Oswald, 1996; Rayton, 2006; Saridakis et al., 2018; Wood & Ogbonnaya, 2018). For instance, Newstorm (2007) summarizes it as “a set of favorable or unfavorable feelings and emotions with which employees view their work.” Other definitions can be found in Spector (1997), Judge and Kammeyer-Mueller (2012), and Frederici and Skaalvik (2012). There is also a debate on how one can measure job satisfaction (Judge & Kammeyer- Mueller, 2012; van Saane et al., 2003). Regardless of the exact definition of job satisfac- tion, it has long been found in the literature that employees’ reported feelings towards their job do convey useful managerial information on individual behavior and organiza- tional performance (Akerlof et al., 1988; Harter et al., 2002; Hellman, 1997; Rayton, 2006; Saridakis et al., 2018; Shields & Price, 2002). Several motivational theories have been used to address job satisfaction, including the needs hierarchy theory (Maslow, 1943), two-factor theory (Herzberg et al., 1959), X and Y theory (McGregor, 1960), needs achievement theory (McClelland, 1961), equity theory (Adams, 1963), expectancy theory (Vroom, 1964), goal setting theory (Locke, 1968), and job characteristics theory (Hackman & Oldham, 1976). These theoretical frameworks have guided empirical work on the determinants and outcomes of job satisfaction. At the empirical level, some studies have examined overall job satisfaction, while others have focused on satisfaction with a specific aspect of the job (Saridakis et al., 2018). There is evidence that one’s job satisfaction relates to a diversity of job-related characteristics, although the findings are not completely consistent across studies, such as pay (Clark, Oswald, 1996; Heywood & Wei, 2006; Pouliakas & Ioannis, 2010), hours of work (Clark, Oswald, et al., 1996), job security (Artz & Kaya, 2014), promotion oppor- tunities (Clark, 1998), job stress (Wang et al., 2014), work autonomy (Ross & Reskin, 1992), workplace relations with co-workers and management (Westover & Taylor, 2010), job-skill use (Allen & van der Velden, 2001; Amador & Vila, 2013; Belfield & Harris, 2002; Johnson & Johnson, 2002; Vieira, 2005), and job-life interference (Anderson et al., 2002; Scandura & Lankau, 1997). Several authors have also examined the role of socio-demographic characteristics as explanatory variables for job satisfaction, such as gender (Clark, 1997; Linz, 2003; Souza- Poza & Souza-Poza, 2003; Witt & Neal, 1992), age (Chaudhuri et al., 2015; Clark, Oswald, et al., 1996; Linz, 2003; Saner & Eyüpoğlu, 2012), education (Clark, Oswald, 1996; Clark, Oswald, et al., 1996; Idson, 1990; Linz, 2003; Ross & Reskin, 1992; Vila & García mora, 2005), marital status (Clark, Oswald, et al., 1996; Linz, 2003; Saner & Eyüpoğlu, 2013), region or country (Borooah, 2009; Bozionelos & Kostopoulos, 2010; Díaz-Serrano & Vieira, 2005; Jones & Sloane, 2009; Mysíková & Večerník, 2013), union membership (Borjas, 1979; Clark, Oswald, et al., 1996; García-Serrano, 2008; Hammer & Avgar, 2005; Renaud, 2002), religious beliefs (King & Williamson, 2005), and public service versus private-sector employment (Top et al., 2015). 2.2. Organizational commitment It is widely recognized that employees’ organizational commitment plays an important role in any organization, linked to important competitive advantages, such as employee turnover, absenteeism, and performance (Brown et al., 2011; Mowday et al., 1979; 4 J. A. C. VIEIRA ET AL. Walton, 1985). Price (1997) defined organizational commitment as loyalty to a social unit. Others refer to it as the strength of identification and involvement with an organization (Mowday et al., 1979). Mowday et al. (1979) identified the following three components of organizational commitment: a strong belief in the organization’s goals and values, a willingness to exert considerable effort on behalf of it, and a strong intent to remain employed by the organization. Meyer and Allen (1991, 1997) refer to one’s organizational commitment as a psychological state that has at least three separable components: affective commitment (a desire), continuance commitment (a need), and normative commitment (an obligation) to maintain employment in an organization. Affective commitment is an attitudinal process that involves employees’ identification with, attachment to, and involvement in the organization’s efforts to share its values and goals. Continuance commitment relates to employees’ awareness of the costs associated with leaving the organization. Normative commitment reflects the feeling of obligation towards the organization based on their personal values and beliefs. In general, commit- ment captures the worker-employer ties or attachment. Several studies have examined the determinants of organizational commitment, although the findings are not completely consistent across different studies. Such research has addressed the explanatory role of variables including rewards or compensa- tion (Paik et al., 2007), job–life balance (Azeem & Akhtar, 2014) and demographic characteristics such as gender (Mathieu & Zajac, 1990), age (Allen & Meyer, 1993; Suliman & Lies, 2000; Yucel & Bektas, 2012), and education (González et al., 2016). A close reading of empirical studies suggests that many determinants of job satisfaction also impact organizational commitment. The extent to which their effect on organiza- tional commitment is direct, indirect (via the mediating effect of job satisfaction), or both is an important empirical issue in the literature. This study contributes to the literature in this regard. 2.3. Connecting job satisfaction and organizational commitment The existing empirical evidence on job satisfaction and organizational commitment still reflects a lack of unanimity on the causal ordering between these constructs (Saridakis et al., 2018). A vast majority of studies have evidenced that job satisfaction is an antecedent of organizational commitment (Chan & Qiu, 2011; Elangovan, 2001; Top & Gider, 2013; Top et al., 2015). However, others have proposed that organizational commitment shapes job satisfaction (Bateman & Strasser, 1984; Paik et al., 2007; Vandenberg & Lance, 1992), while some authors also view these constructs as potentially reciprocally related (Farkas & Tetrick, 1989; Huang & Hsiao, 2007; Lance, 1991; Saridakis et al., 2018). 3. Methodology, data, and the statistical model 3.1. Methodology Figure 1 displays the conceptual framework for empirical examination, which includes the following hypotheses: JOURNAL OF APPLIED ECONOMICS 5 Figure 1. The conceptual model. Note: This figure depicts our proposed conceptual model to be used for empirical purposes and the corresponding hypotheses to be tested. The model considers that employee and job/workplace attributes influence job satisfaction and organizational commitment. As job satisfaction might also influence organizational commitment, this means that employee and job/ workplace attributes may impact organizational commitment directly and/or also indirectly due to their effect on satisfaction. It can, however, also be the case that some attributes have no impact on organizational commitment or eventually act only through one of the channels instead of both. H1 - Employee characteristics influence job satisfaction.a H2 - Job or workplace characteristics influence job satisfaction. H3 - Job satisfaction influences organizational commitment. To investigate H1, we test the effect of workers’ characteristics on job satisfaction, controlling for confounding effects arising via observed job or workplace characteristics. If job attributes were not controlled for them, employee attributes regression coefficients could also capture the effect of those attributes due to the correlation between both variables. In H2, we test the influence of job or workplace characteristics on job satisfac- tion, controlling for the influence of workers’ observed attributes. Despite the lack of consensus in the literature regarding the causal ordering between these two variables, we entertain in H3 job satisfaction as a determinant (even if partially) of organizational commitment, while we also consider the possibility that job satisfaction is endogenously determined with organizational commitment via an instrument variable approach. Two additional hypotheses are necessary to close the model: H4 - Employee characteristics have a direct impact on organizational commitment. H5 - Job or workplace characteristics have a direct impact on organizational commitment. In order to test H4, one must control for the effect of job satisfaction and job or workplace characteristics on organizational commitment. To test H5, we must control 6 J. A. C. VIEIRA ET AL. for the influence of job satisfaction and employees’ characteristics on organizational commitment. Therefore, the present framework allows to examine the extent to which the effect of employee and job-and-workplace characteristics on organizational commitment runs directly is mediated by job satisfaction, or both. For instance, if such an effect is totally mediated via job satisfaction, then there is no room for any direct effect of these variables on the organizational commitment equation (otherwise, those variables will also have a direct impact). 3.2. Data The present study uses data from the 2015 Work Orientation module of International Social Survey Program (ISSP) survey, which was implemented in 2015–2016 in a large number of countries. The national surveys include random samples of the population and include questions regarding the general and working populations. We only use data on working respondents. The final sample, after eliminating missing values on relevant variables, includes 14,437 working respondents. A similar procedure has been used by other researchers (e.g., Saridakis et al., 2018). The survey collected information on respondents, in this case employees, includ- ing characteristics such as age, gender, education, marital status, trade union membership, religious beliefs, religious services attendance, and country of employ- ment. The survey also includes questions on job or workplace characteristics, namely number of weekly hours worked, type of organization (public or private employer), whether the respondent supervises other workers or not in the work- place, whether the employee has recently received any training to improve skills at the workplace or elsewhere (which can be viewed as the extent to which the job provides or allows training opportunities to improve skills), perceived professional use of past experience and skills, perceived work–life balance, perceived relations in the workplace (between management and employees and between colleagues), per- ceived incidence of stress at work, and, finally, respondents’ evaluation of their job on a five-point scale ranging from strongly disagree to strongly agree. These responses are given to statements such as a) My job is secure, b) My income is high, c) My opportunities of advancement are high, d) My job is interesting, e) I can work independently, f) In my job I can help other people, g) My job is useful to society, and h) In my job I have personal contact with other people. Table 1 presents the summary of descriptive statistics on employee and job-related characteristics, along with a description of other independent variables to be used in the regression analysis. The survey also asked the following question: How satisfied are you in your (main) job? The level of satisfaction had to be reported on a seven-point scale ranging from completely dissatisfied to completely satisfied (see Table 2). Moreover, respondents were asked the extent to which they agreed or disagreed with the following three statements: a) I am willing to work harder than I have to in order to help the firm or organization for succeed, b) I am proud to be working for my firm or organization, and c) I would turn down another job that offered quite a bit more pay in order to stay with this organization. The levels of agreement to these JOURNAL OF APPLIED ECONOMICS 7 Table 1. Data and variables description. Variable Description Mean S. Dev. Age Reported age (years) 42.192 11.954 Age /100 Reported age squared 1923.0 1016.1 Female 1 if a female worker, 0 otherwise 0.5421 Years of education Reported education (in years) 14.618 10.051 Living in steady partnership 1 if the worker lives in steady partnership, 0 otherwise 0.6281 Unionized worker 1 if the worker is unionized, 0 otherwise 0.2616 Catholic 1 if affiliated with the Catholic religion, 0 otherwise 0.3008 Protestant 1 if affiliated with the Protestant religion, 0 otherwise 0.1930 Orthodox 1 if affiliated with the Orthodox religion, 0 otherwise 0.0616 Other Christian religions 1 if affiliated with other Christian religions, otherwise 0.0470 Jewish 1 if affiliated with the Jewish religion, 0 otherwise 0.0219 Islamic 1 if affiliated the Islamic religion, 0 otherwise 0.0231 Buddhist 1 if affiliated with the Buddhist religion, 0 otherwise 0.0175 Hindu 1 if affiliated with the Hindu religion, 0 otherwise 0.0149 Other Asian religions 1 if affiliated with other Asian religions, 0 otherwise 0.0329 Other religions 1 if affiliated with other religions, 0 otherwise 0.0096 Attendance of religious 1 if attends religious services at least once a week, 0 otherwise 0.1076 services Australia 1 if the survey was conducted in Australia, 0 otherwise 0.0268 Austria 1 if the survey was conducted in Austria, 0 otherwise 0.0255 Belgium 1 if the survey was conducted in Belgium, 0 otherwise 0.0479 Chile 1 if the survey was conducted in Chile, 0 otherwise 0.0240 China 1 if the survey was conducted in China, 0 otherwise 0.0166 Croatia 1 if the survey was conducted in Croatia, 0 otherwise 0.0252 Czech Republic 1 if the survey was conducted in Czech Republic, 0 otherwise 0.0320 Estonia 1 if the survey was conducted in Estonia, 0 otherwise 0.0315 Finland 1 if the survey was conducted in Finland, 0 otherwise 0.0280 France 1 if the survey was conducted in France, 0 otherwise 0.0272 Georgia 1 if the survey was conducted in Georgia, 0 otherwise 0.0109 Germany 1 if the survey was conducted in Germany, 0 otherwise 0.0444 Hungary 1 if the survey was conducted in Hungary, 0 otherwise 0.0258 Iceland 1 if the survey was conducted in Iceland, 0 otherwise 0.0298 India 1 if the survey was conducted in India, 0 otherwise 0.0109 Israel 1 if the survey was conducted in Israel, 0 otherwise 0.0265 Japan 1 if the survey was conducted in Japan, 0 otherwise 0.0262 Latvia 1 if the survey was conducted in Latvia, 0 otherwise 0.0263 Lithuania 1 if the survey was conducted in Lithuania, 0 otherwise 0.0181 Mexico 1 if the survey was conducted in Mexico, 0 otherwise 0.0171 New Zealand 1 if the survey was conducted in New Zealand, 0 otherwise 0.0109 Norway 1 if the survey was conducted in Norway, 0 otherwise 0.0431 Philippines 1 if the survey was conducted in Philippines, 0 otherwise 0.0240 Poland 1 if the survey was conducted in Poland, 0 otherwise 0.0189 Russia 1 if the survey was conducted in Russia, 0 otherwise 0.0362 Slovak Republic 1 if the survey was conducted in Slovak Republic, 0 otherwise 0.0265 Slovenia 1 if the survey was conducted in Slovenia, 0 otherwise 0.0229 South Africa 1 if the survey was conducted in South Africa, 0 otherwise 0.0321 Spain 1 if the survey was conducted in Spain, 0 otherwise 0.0380 Suriname 1 if the survey was conducted in Suriname, 0 otherwise 0.0177 Sweden 1 if the survey was conducted in Sweden, 0 otherwise 0.0353 Switzerland 1 if the survey was conducted in Switzerland, 0 otherwise 0.0384 Taiwan 1 if the survey was conducted in Taiwan, 0 otherwise 0.0497 United Kingdom 1 if the survey was conducted in United Kingdom, 0 otherwise 0.0290 Venezuela 1 if the survey was conducted in Venezuela, 0 otherwise 0.0172 Supervising other workers 1 if the respondent supervises other employees, 0 otherwise 0.2505 Public servant 1 if the respondent works for a public employer, 0 otherwise 0.3303 High income job 1 if respondent agrees or strongly agrees that has a high-income 0.2854 job, 0 otherwise Secure job 1 if respondent agrees or strongly agrees that has a secure job, 0 0.7204 otherwise Job with high opportunities 1 if respondent agrees or strongly agrees that his job has high 0.2942 for advancement opportunities for advancement, 0 otherwise (Continued) 8 J. A. C. VIEIRA ET AL. Table 1. (Continued). Variable Description Mean S. Dev. Received training to 1 if the worker received training to improve skills over the last 12 0.4763 improve job skills months, 0 other. Interesting job 1 if respondent agrees or strongly agrees that his job is interesting, 0.7252 0 otherwise Useful job to society 1 if respondent agrees or strongly agrees that his job is useful to 0.9205 society, 0 otherwise Job can help other people 1 if respondent agrees or strongly agrees that in his job he can help 0.8914 other people, 0 otherwise Job allows personal contact 1 if respondent agrees or strongly agrees that his job has personal 0.9553 with other people contact with other people, 0 otherwise Can work independently 1 if respondent agrees or strongly agrees that can work 0.7140 independently in his job, 0 otherwise Easy to take time off during 1 if respondent considers that it is not too difficult or not difficult at 0.6086 working hours all to take time off during working hours, 0 otherwise Nonstressful work 1 if respondent hardly ever or never finds to have a stressful work, 0 0.2186 otherwise Hours worked weekly Number of hours worked per week 37.085 8.921 Good relations between 1 if respondent considers that relations between workmates or 0.8634 workmates or colleagues colleagues are quite good or very good, 0 otherwise Good relations between 1 if respondent considers that relations between management and 0.7316 manag. and employees employees are quite good or very good, 0 otherwise Job does use of past work 1 if respondent considers that job does a lot or almost all use of 0.6233 exper. and skills past work experience and skills, 0 otherwise Job demands do not 1 if respondent considers that job demands hardly ever or never 0.5863 interfere with family life interfere with the family life, 0 otherwise 1. This table describes some variables to be used as explanatory in the regression analysis and reports the corresponding sample mean and standard deviation; 2. Standard deviations were computed only for continuous variables; 3. For each binary variable the mean matches its sample proportion. Table 2. Job satisfaction and organizational commitment description. Level of Job Satisfaction: 1-Completely dissatisfied 1.7 2-Very dissatisfied 2.2 3-Dissatisfied 4.8 4-Neither satisfied nor dissatisfied 10.1 5-Satisfied 35.9 6-Very satisfied 30.2 7-Completely satisfied 14.7 Level of Organizational Commitment: a)I am willing to work harder than I have to in order to help firm or organization for succeed 1-Strongly disagree 5.3 2-Disagree 12.8 3-Neither agree nor disagree 21.8 4-Agree 42.6 5-Strongly agree 17.5 b)I am proud to be working for my firm or organization 1-Strongly disagree 2.6 2-Disagree 7.6 3-Neither agree nor disagree 23.2 4-Agree 45.7 5-Strongly agree 21.0 c) I would turn down another job that offered quite a bit more pay in order to stay with this organization 1-Strongly disagree 16.1 2-Disagree 28.5 3-Neither agree nor disagree 23.3 4-Agree 20.0 5-Strongly agree 12.1 % indicates the percentage in the sample. JOURNAL OF APPLIED ECONOMICS 9 statements were reported on a five-point scale ranging from strongly disagree to strongly agree. These three items naturally correspond to our measures of organiza- tional commitment to the extent that they capture workers’ levels of involvement, affection, attachment, or dedication to the firm or organization. 3.3. The statistical model The constructs to be explained in this paper are the level of job satisfaction and the level of organizational commitment. For the empirical analysis and following the conceptual framework previously described, the determinants of job satisfaction include both employee and job or workplace-related characteristics. These are also considered deter- minants of organizational commitment together with job satisfaction. For this purpose, we estimate separate equations for job satisfaction and organizational commitment: a common procedure in the literature. Due to the ordinal nature of the dependent variables, a linear regression approach is not suitable. Instead, an ordered probit type model may be used. Another common alternative in the literature is to assume that the error term follows a logistic pattern, which yields the so-called ordered logit model (Greene, 2018). Consider that the dependent variable (job satisfaction or organizational commitment) for respondent i is determined by the following stochastic process: y ¼ βx þ ε i ¼ 1; . . . ; N (1) i i where y is a latent variable, x is a set of explanatory variables, β is the vector of parameters to be estimated, andε stands for a random term. However, in the data, we do not observe y but an indicator variable y , which indicates the level of satisfaction or the level of organizational commitment, depending on the case under scrutiny, to which the respondent belongs, such that: y ¼ j if μ < y � μ j ¼ 1; . . . ; J (2) j 1 j The thresholds µ are unknown and cut the assumed distribution for the error term into segments, being that µ <µ . Assuming that the error terms, ε , are independent and j-1 j i follow a standard normal distribution, the probability that respondent i belongs to each alternative j is given by: � � � � 0 0 Pðy ¼ jÞ ¼ Φ μ β x Φ μ β x if j ¼ 1; . . . ; J (3) i i i j j 1 The log-likelihood function to be maximized is given by: N n � � � �o X X 0 0 LogL ¼ λ log Φ μ β x Φ μ β x (4) ij i i j j 1 i¼1 j¼1 where λ ¼ 1 if y ¼ j ij i λ ¼ 0 if y � j i ¼ 1; . . . ; N j ¼ 1; . . . ; J ij i 10 J. A. C. VIEIRA ET AL. Identification in this model is achieved by excluding the constant term and by fixing one of the µ (Stewart, 2004). Another alternative would be a simple normalization that keeps the constant term but fixes µ equal to zero (Greene, 2018). The ordered probit model, although widely used to examine ordinal data, depends on a strong assumption about the error term. Our estimation model uses, as a robust yet flexible alternative approach to the stringent assumption associated with the standard ordered probit model, a semi-nonparametric estimator of an unknown density, proposed by Gallant and Nychka (1987). This procedure can be written as the product of a squared polynomial and a normal density. It is noteworthy to mention that the resulting model nests the standard ordered probit model, thus allowing for hypothesis testing in order to choose the appropriate model. The semi-nonparametric approach approximates the unknown density as: γ ε ϕðεÞ k¼0 k f ðεÞ ¼ (5) K � 1 2 ∫ γ ε ϕðεÞdε 1 k¼0 k The required distribution function is specified as: � � ∫ γ ε ϕðεÞdε 1 k¼0 k F ðεÞ ¼ (6) K � 1 2 ∫ γ ε ϕðεÞdε 1 k¼0 k Equation (5) defines a family of semi-nonparametric distributions for increasing values of K, and the unknown density can be closely approximated by this Hermite series by increasing the choice of K – the degree of the polynomial -, provided that it satisfies certain smoothness conditions (Gallant & Nychka, 1987; Stewart, 2004). Following Gallant and Nychka (1987), the model parameters can be consistently estimated by maximizing a pseudo-likelihood function which replaces in Equation (4) the standard normal cumulative distribution by the one defined in (6). The model requires a location normalization for identification. One way of doing this is to fix the first threshold (µ ) to its ordered probit estimate by using (4), which closely resembles the procedure used by Melenberg and van Soest (1996) in the context of a probit model. It is also worth noting that when K = 0, K = 1, and K = 2, the model is equivalent to the conventional ordered probit model. The choice of K is part of the model selection procedure by testing between different alternatives. In this paper, model estimation and further testing rely on Stewart (2004). 4. Results and discussion 4.1. Results We start by noting that likelihood-ratio tests, included in Table 3, regarding the explana- tion of job satisfaction for different values of K from 3 to 5 reject the standard ordered probit model against the semi-nonparametric alternative in all cases. Moreover, like- lihood-ratio tests for K against K-1 reject the null hypothesis at significance levels of 10% or less for K ≤ 4 but not for K above this limit, suggesting the selection of a K = 4 model. JOURNAL OF APPLIED ECONOMICS 11 Table 3. Job satisfaction: LRT tests for model choice. LR-test LR-Test K Log-L of OP DF p-value of K-1 DF p-value OP −18088.0 K = 3 −18044.4 87.15 1 0.000 87.15 1 0.000 K = 4 −17999.8 176.46 2 0.000 89.30 1 0.000 K = 5 −17999.0 178.02 3 0.000 1.56 1 0.211 1. This table reports two likelihood-ratio tests for model choice such as suggest by Stewart (2004): a) LR-test of OP which tests the standard ordered probit model (null hypothesis) against three semi-nonparametric alternatives for K = 3, K = 4, and K = 5 (in the K = 1 and K = 2 cases the model is equivalent to the standard ordered probit) and b) LR-test of K-1 which tests the alternative K-1 (null hypothesis) against the alternative K; 2. LR-test of OP is computed as −2(Log-L – OP Log-L ) with j = 3, 4, or 5 (degrees of freedom and the test p-values of a chi-square distribution are Columns 4 and 5, K=j respectively); 3. LR-test of K-1 is computed as −2(Log-L – Log-L ) with K = 3, 4, 5 (degrees of freedom and the test K-1 K p-values of a chi-square distribution are Columns 7 and 8, respectively); 4. K, Log-L, OP, and DF denote the order of the Hermite polynomial, the value of the Log-L function evaluated at the parameters estimated values, standard ordered probit model, and degrees of freedom, respectively. Estimation results for the K = 4 semi-nonparametric ordered probit model are pre- sented in Table 4, in which workers’ reported level of job satisfaction is explained through two sets of employee and job-related characteristics. The null hypotheses that each of these sets of variables does not explain workers’ job satisfaction are rejected at conven- tional significance levels using the likelihood-ratio tests included in Table 5. These results validate hypotheses H1 and H2. However, it is worth noting that not all variables included in those sets have explana- tory power, such is the case of individual characteristics like age, gender, and whether or not the employee is a union member (Table 4). Other attributes such as education, religious beliefs, and country of residence explain job satisfaction. For instance, as education increases, the likelihood of being completely satisfied decreases, and that of being completely dissatisfied increases. In terms of religious beliefs, Buddhists show the highest probability of being completely satisfied with their jobs. Most interestingly, there are significant differences in job satisfaction by country. Out of 36 countries included in the regression and after controlling for the effect of a large number of other individual and job-related characteristics, Georgia and India occupy the two extremes. That is, the highest likelihood of being completely satisfied is found in India and is the lowest in Georgia, all else equal. Compared with the United States, which corresponds to the reference category in the regression, the probability of a worker being completely satisfied is higher, and the probability of being completely unsatisfied is lower, for countries such as India, Mexico, Venezuela, Spain, Russia, Israel, Croatia, Chile, Austria, and the Czech Republic. The reverse (i.e., the probability of being completely satisfied is lower and that of being completely unsatisfied is higher, as compared with the United States) is true in Georgia, Taiwan, China, Japan, Lithuania, Suriname, Sweden, Australia, Germany, and Slovenia. There is no statistical difference in those probabilities between the United States and the remaining 15 countries used in the analysis, all else equal. The heterogeneity in job satisfaction across countries is in some cases quite striking, such as the finding that Venezuelans had a higher probability of reporting (high) job satisfaction compared to Americans, while Germans had in turn a lower probability. There is no clear-cut explanation for these differences, but one can note that Germany is known as a strong labor market, while Venezuela has been experiencing an economic 12 J. A. C. VIEIRA ET AL. Table 4. The determinants of employees’ job satisfaction. Coef. S. Error 1.Employee Characteristics Age −0.0039 0.0044 Age /100 0.0001 0.0001 Female 0.0191 0.0187 Years of education −0.0021 0.0009 ** Living in steady partnership 0.0636 0.0204 *** Unionized worker −0.0320 0.0242 Catholic 0.0701 0.0290 ** Protestant 0.0653 0.0309 ** Orthodox 0.1018 0.0595 * Other Christian religions −0.0541 0.0474 Jewish −0.2228 0.1334 * Islamic 0.1544 0.0685 ** Buddhist 0.2111 0.0806 *** Hindu 0.0524 0.1140 Other Asian religions 0.1991 0.0888 ** Other religions −0.0689 0.0972 Attendance of religious services 0.0617 0.0321 * Australia −0.1875 0.0718 *** Austria 0.2461 0.0742 *** Belgium 0.0361 0.0614 Chile 0.2477 0.0767 *** China −0.3392 0.0850 *** Croatia 0.2706 0.0759 *** Czech Republic 0.1483 0.0685 ** Estonia −0.0347 0.0698 Finland 0.1113 0.0707 France −0.0068 0.0707 Georgia −0.5382 0.1178 *** Germany −0.1776 0.0621 *** Hungary −0.0281 0.0739 Iceland 0.0290 0.0714 India 0.7481 0.1444 *** Israel 0.2793 0.1291 ** Japan −0.2662 0.0776 *** Latvia −0.0653 0.0746 Lithuania −0.2314 0.0827 *** Mexico 0.5825 0.0876 *** New Zealand −0.0936 0.0981 Norway −0.0201 0.0631 Philippines 0.1285 0.0795 Poland 0.0472 0.0802 Russia 0.2801 0.0827 *** Slovak Republic 0.0350 0.0724 Slovenia −0.1633 0.0760 ** South Africa 0.0614 0.0698 Spain 0.3421 0.0673 *** Suriname −0.2016 0.0871 ** Sweden −0.1976 0.0681 *** Switzerland 0.0708 0.0629 Taiwan −0.3906 0.0906 *** United Kingdom 0.0014 0.0705 Venezuela 0.4452 0.0859 *** 2.Job or Workplace Characteristics Supervising other workers 0.0348 0.0220 Public servant 0.0702 0.0210 *** High income job 0.2660 0.0253 *** Secure job 0.2303 0.0239 *** Job with high opportunities for advancement 0.2395 0.0252 *** Received training to improve job skills 0.0800 0.0197 *** Interesting job 0.7409 0.0395 *** (Continued) JOURNAL OF APPLIED ECONOMICS 13 Table 4. (Continued). Coef. S. Error Useful job to society 0.1692 0.0370 *** Job can help other people 0.1514 0.0331 *** Job allows personal contact with other people 0.1150 0.0452 ** Can work independently 0.1379 0.0234 *** Easy to take time off during working hours 0.1285 0.0202 *** Nonstressful work 0.2687 0.0256 *** Hours worked weekly −0.0011 0.0011 Good relations between workmates or colleagues 0.2575 0.0308 *** Good relations between management and employees 0.6294 0.0368 *** Job does use of past work experience and skills 0.1287 0.0206 *** Job demands do not interfere with family life 0.3238 0.0238 *** Thresholds: µ −0.7807 Fixed µ −0.1382 0.0514 *** µ 0.6368 0.0762 *** µ 1.4071 0.1039 *** µ 2.8463 0.1596 *** µ 4.0023 0.2069 *** Polynomial: 1 0.0029 0.0089 *** 2 −0.0980 0.0194 *** 3 0.0054 0.0022 *** 4 0.0169 0.0014 *** Log-L −17999 Wald chi-square (70) 546.1 Number of observations 14437 1. This table reports the estimates of a semi-nonparametric ordered probit model for job satisfaction (dependent variable) with K = 4; 2. ***, **, and * denote significance at the 1%, 5%, and 10% levels, respectively. Table 5. Job satisfaction hypothesis testing. Null hypotheses LRT DF p-value 1.Employee characteristics do not influence job satisfaction, 654 52 0.0000 all else equal 2.Job or workplace characteristics do not influence job 5585 18 0.0000 satisfaction, all else equal LRT, DF, and p-value denote the likelihood ratio test, degrees of freedom (equal to the number of restrictions imposed to the model), and the test p-value (for a chi-square distribution), respectively. crisis. Consequently, it could be the case that due to the well-known dual vocational education and training system in Germany, once one starts a career in a specific field it is quite difficult to change careers. Moreover, increased unemployment experienced by Venezuelans during the time of the survey could make workers in Venezuela happy to have a job at all. In order to evaluate this argumentation, we included a new explanatory variable based on the following 5-point scale ordinal question from the survey How difficult or easy do you think it would be for you to find a job at least as good as your current one?. This new variable assumes a value equal to 1 for responses of the type very difficult and fairly difficult and 0 in the other situations and undoubtedly captures the worker’s perceptions of both macro-general and micro-idiosyncratic factors that impact his or her perceived desirability of his or her circumstances. However, including this variable as a regressor does not eliminate the existence of significant cross-county differences. 14 J. A. C. VIEIRA ET AL. Job-and-workplace characteristics matter for employees’ level of job satisfaction in most cases. The aspects of being a public servant, feeling of security in a job which brings a high income, having many opportunities for advancement, accessing training to improve skills, feeling interested in one’s job, feeling useful to society, helping other people, and having the ease of taking time off during working hours positively impact reported job satisfaction. The same is valid for those who feel they have non-stressful work, good relations among workmates, good relations between management and employees, application of past experience and skills, and no interference with family life. Some of these attributes and, therefore, workers’ level of job satisfaction can be controlled by management. In other words, managers have at their disposal some instruments that can be used in order to foster employees’ satisfaction with the job. The likelihood ratio tests included in Table 6 suggest the use of a K = 4 semi- nonparametric ordered probit model to explain employees’ organizational commitment, whose estimation results are included in Table 7. Moreover, based on the information included in Table 8, the null hypothesis that workers’ job satisfaction does not influence organizational commitment is rejected, thus supporting H3. The regression results predict that higher levels of job satisfaction imply higher levels of organizational commit- ment. However, a word of caution is worth since job satisfaction might be endogenous namely due to omitted variables that affect organizational commitment and are corre- lated with job satisfaction (Saridakis et al., 2018), which we address subsequently. A commonly proposed technique for correcting the potential bias arising from such a problem is the use of instrumental variables (IV) techniques. This requires the existence of at least one observable variable which influences job satisfaction but does not affect employee’s organizational commitment. By inspection of the estimated results included in Tables 4 and 7, we conclude that having a non-stressful work exerts a (positive) direct impact in job satisfaction but does not directly explain organizational commitment. Indeed, ample support for this mediatory role of job satisfaction in the effect of occupa- tional stress on organizational commitment has already been reported by Aghdasi et al. (2011). In order to address the robustness of our previous results, the following two-step strategy has been implemented within our semi-nonparametric approach. From the Table 6. Organizational commitment: LRT tests for model choice. Log-L LR-Test of OP DF p-value LR-Test of K-1 DF p-value I am willing to work harder than I have to in order to help the firm or organization for succeed OP −17916.1 K = 3 −17862.5 107.12 1 0.000 107.12 1 0.000 K = 4 −17824.0 184.27 2 0.000 77.15 1 0.000 K = 5 −17823.7 184.74 3 0.000 0.46 1 0.497 I am proud to be working for my firm or organization OP −15078.5 K = 3 −15010.5 135.94 1 0.000 135.94 1 0.000 K = 4 −14940.8 275.42 2 0.000 139.49 1 0.000 K = 5 −14940.8 275.43 3 0.000 0.01 1 0.938 I would turn down another job that offered quite a bit more pay in order to stay with this organization OP −19394.5 K = 3 −19374.8 39.52 1 0.000 39.52 1 0.000 K = 4 −19308.5 172.03 2 0.000 132.51 1 0.000 K = 5 −19307.8 173.47 3 0.000 1.45 1 0.229 See notes at the bottom of Table 3, which also apply to this table. JOURNAL OF APPLIED ECONOMICS 15 Table 7. The determinants of employees’ organizational commitment. Turn down another Work harder in order job that offered quite to help the firm or Proud to be working a bit more pay to organization for for the firm or stay in the firm or succeed. organization. organization. Coef. S. Error Coef. S. Error Coef. S. Error 1.Employee Characteristics: Age 0.0041 0.0048 0.0138 0.0043 *** 0.0111 0.0043 *** Age /100 −0.0001 0.0001 −0.0001 0.0001 *** 0.0000 0.0001 Female −0.0849 0.0196 *** 0.0022 0.0170 −0.0189 0.0164 Years of education −0.0004 0.0009 −0.0011 0.0008 −0.0003 0.0008 Living in steady partnership 0.0183 0.0199 0.0587 0.0183 *** 0.0153 0.0179 Unionized worker −0.0689 0.0243 *** 0.0260 0.0220 0.0263 0.0212 Catholic 0.0798 0.0293 *** 0.0712 0.0264 *** 0.0240 0.0254 Protestant 0.0375 0.0306 0.0734 0.0283 *** −0.0141 0.0269 Orthodox −0.0778 0.0570 0.0805 0.0532 −0.0460 0.0516 Other Christian religions 0.0007 0.0469 0.1093 0.0435 ** 0.0754 0.0420 * Jewish −0.2291 0.1256 * 0.0554 0.1125 −0.0722 0.1066 Islamic 0.1016 0.0669 0.2213 0.0613 *** 0.0251 0.0586 Buddhist −0.0400 0.0798 0.0963 0.0747 0.1466 0.0716 ** Hindu 0.5009 0.1199 *** 0.2667 0.1034 *** 0.1241 0.1006 Other Asian religions 0.0611 0.0852 0.1705 0.0804 ** 0.0447 0.0747 Other religions 0.1061 0.0924 −0.0180 0.0841 −0.0300 0.0835 Attendance of religious services 0.0201 0.0320 0.0648 0.0292 ** 0.0819 0.0288 *** Australia −0.4012 0.0751 *** −0.3194 0.0656 *** −0.0045 0.0616 Austria −0.6998 0.0893 *** −0.5266 0.0720 *** 0.2398 0.0672 *** Belgium −0.8982 0.0879 *** −0.3205 0.0576 *** 0.1778 0.0540 *** Chile −1.0765 0.1040 *** −0.6323 0.0714 *** 0.0817 0.0643 China −0.1426 0.0812 * −0.3091 0.0775 *** 0.6040 0.0793 *** Croatia −0.7129 0.0901 *** −0.3385 0.0688 *** 0.0307 0.0642 Czech Republic −0.4934 0.0760 *** −0.5862 0.0663 *** 0.4630 0.0645 *** Estonia −0.8941 0.0916 *** −0.7392 0.0690 *** 0.0887 0.0602 Finland −1.0019 0.1002 *** −0.5950 0.0691 *** 0.4438 0.0672 *** France −1.2416 0.1104 *** −0.2787 0.0661 *** 0.0285 0.0622 Georgia 0.0173 0.1133 −0.1824 0.1037 * 0.2403 0.1003 ** Germany −0.8027 0.0828 *** −0.5789 0.0604 *** 0.2818 0.0561 *** Hungary −0.4875 0.0786 *** −0.3495 0.0674 *** 0.0601 0.0641 Iceland −0.0289 0.0714 −0.0791 0.0656 −0.1615 0.0629 *** India −0.3348 0.1372 ** −0.4549 0.1282 *** 0.3549 0.1275 *** Israel −0.1414 0.1220 −0.2211 0.1098 ** 0.5507 0.1105 *** Japan −0.3071 0.0787 *** −0.2565 0.0709 *** 0.6795 0.0782 *** Latvia −1.0476 0.1047 *** −0.4924 0.0702 *** 0.5164 0.0712 *** Lithuania −1.0255 0.1078 *** −0.7497 0.0789 *** 0.3905 0.0771 *** Mexico −0.2719 0.0871 *** −0.1625 0.0775 ** 0.3003 0.0797 *** New Zealand −0.1319 0.0964 −0.1243 0.0895 0.1655 0.0820 ** Norway −0.3502 0.0666 *** −0.1772 0.0580 *** 0.2635 0.0566 *** Philippines −0.3433 0.0788 *** −0.3261 0.0724 *** 0.5307 0.0754 *** Poland −0.9971 0.1056 *** −0.6108 0.0768 *** 0.1652 0.0708 ** Russia −0.8942 0.1032 *** −0.8741 0.0821 *** 0.3350 0.0744 *** Slovak Republic −0.6141 0.0827 *** −0.5256 0.0679 *** 0.2512 0.0633 *** Slovenia −0.7299 0.0894 *** −0.2735 0.0693 *** 0.1889 0.0666 *** South Africa 0.0616 0.0677 −0.1480 0.0633 ** 0.2192 0.0618 *** Spain −0.6312 0.0850 *** 0.0345 0.0612 −0.0567 0.0622 Suriname −0.4209 0.0920 *** −0.1564 0.0776 ** 0.5227 0.0858 *** Sweden −0.6641 0.0827 *** −0.5185 0.0649 *** −0.0896 0.0605 Switzerland −0.4233 0.0698 *** −0.3586 0.0597 *** 0.3468 0.0577 *** Taiwan −0.1209 0.0853 −0.4728 0.0808 *** 0.1659 0.0753 ** United Kingdom −0.3073 0.0721 *** −0.3066 0.0644 *** 0.1602 0.0606 *** Venezuela 0.4025 0.0923 *** 0.3982 0.0837 *** 0.1268 0.1158 2.Job or Workplace Characteristics Supervising other workers 0.1893 0.0257 *** 0.0962 0.0204 *** 0.0861 0.0200 *** (Continued) 16 J. A. C. VIEIRA ET AL. Table 7. (Continued). Turn down another Work harder in order job that offered quite to help the firm or Proud to be working a bit more pay to organization for for the firm or stay in the firm or succeed. organization. organization. Coef. S. Error Coef. S. Error Coef. S. Error Public servant −0.0730 0.0208 *** 0.0118 0.0189 −0.0199 0.0181 High income job 0.0533 0.0222 ** 0.0268 0.0202 0.0938 0.0201 *** Secure job −0.0280 0.0210 0.0941 0.0197 *** 0.0868 0.0194 *** Job with high opportunities for 0.1140 0.0237 *** 0.1607 0.0219 *** 0.1329 0.0215 *** advancement Received training to improve job 0.0884 0.0200 *** 0.1145 0.0181 *** 0.0137 0.0169 skills Interesting job 0.1539 0.0256 *** 0.3496 0.0265 *** 0.1401 0.0230 *** Useful job to society 0.0369 0.0357 0.1602 0.0331 *** 0.1155 0.0334 *** Job can help other people 0.0710 0.0323 ** 0.1014 0.0296 *** 0.1754 0.0313 *** Job allows personal contact with 0.0971 0.0447 ** 0.0331 0.0406 0.0744 0.0412 * other people Can work independently 0.1243 0.0236 *** 0.0991 0.0208 *** 0.0407 0.0200 ** Easy to take time off during 0.1190 0.0207 *** 0.0752 0.0181 *** 0.0813 0.0181 *** working hours Nonstressful work −0.0310 0.0229 −0.0041 0.0210 0.0216 0.0203 Hours worked weekly 0.0016 0.0011 −0.0006 0.0010 −0.0018 0.0009 * Good relations between −0.0063 0.0286 0.0031 0.0264 0.0552 0.0260 ** workmates or colleag. Good relations between manag. 0.2772 0.0305 *** 0.3432 0.0261 *** 0.1747 0.0239 *** and employees Job does use of past work exper. 0.0524 0.0195 *** 0.0356 0.0180 ** 0.0310 0.0173 * and skills Job demands do not interfere with 0.0904 0.0200 *** −0.0151 0.0178 0.0075 0.0171 family life 3.Job satisfaction Very dissatisfied 0.3045 0.1291 ** 0.5479 0.1161 *** 0.7190 0.1215 *** Fairly dissatisfied 0.5518 0.1164 *** 0.8523 0.1036 *** 0.7480 0.1048 *** Neither satisfied nor dissatisfied 0.6530 0.1135 *** 1.1206 0.1027 *** 1.0872 0.1086 *** Fairly satisfied 0.8342 0.1185 *** 1.4219 0.1071 *** 1.3008 0.1136 *** Very satisfied 1.0407 0.1270 *** 1.8337 0.1156 *** 1.6521 0.1272 *** Completely satisfied 1.5128 0.1485 *** 2.3296 0.1283 *** 1.9538 0.1413 *** Thresholds: µ −0.9924 Fixed −0.0626 Fixed 1.3602 Fixed *** µ 0.0278 0.0065 *** 0.9205 0.0530 *** 2.3099 0.0641 *** µ 0.8152 0.1293 *** 2.0067 0.0942 *** 2.9433 0.1027 *** µ 2.2040 0.2215 *** 3.4561 0.1477 *** 3.7003 0.1488 *** Polynomial: 1 −0.1040 0.0774 −0.2179 0.0560 *** −0.1430 0.0692 ** 2 −0.1400 0.0315 *** −0.1850 0.0197 *** −0.1987 0.0415 *** 3 0.0063 0.0013 *** 0.0289 0.0076 *** 0.0076 0.0028 *** 4 0.0237 0.0025 *** 0.0259 0.0019 *** 0.0289 0.0034 *** Log-L −17824 −14940 −19308 Wald chi-square (76) 272.5 759.3 358.2 Number of observations 14437 14437 14437 1. This table reports the estimates of three semi-nonparametric ordered probit models (one for each organizational commitment construct) with K = 4; 2. ***, **, and * denote significance at the 1%, 5%, and 10% levels, respectively. coefficients of the estimated job satisfaction equation included in Table 4 which include a dummy for having a non-stressful work among the covariates, we calculated in a first step the corresponding predicted values for the job satisfaction index y (see Equation (1)). In a second step, we estimated a semi-nonparametric ordered probit (K = 4) for the organizational commitment constructs, which includes this predicted index among the JOURNAL OF APPLIED ECONOMICS 17 Table 8. Organizational commitment hypothesis testing. 1.Job satisfaction does not influence organizational commitment, all else equal LRT DF p-value 1.1 I am willing to work harder than I have . . . 778 6 0.0000 1.2 I am proud to be working for firm or organization 1632 6 0.0000 1.3 I would turn down another job . . . 1048 6 0.0000 2. Employee characteristics do not directly influence organizational commitment, all else equal 2.1 I am willing to work harder than I have . . . 1721 52 0.0000 2.2 I am proud to be working for firm or organization 919 52 0.0000 2.3 I would turn down another job . . . 799 52 0.0000 3. Job characteristics do not directly influence organizational commitment, all else equal 3.1 I am willing to work harder than I have . . . 710 18 0.0000 3.2 I am proud to be working for firm or organization 2141 18 0.0000 3.3 I would turn down another job . . . 528 18 0.0000 See note at the bottom of Table 5, which also applies to this table. covariates. Other explanatory variables included in the organizational commitment equations are the same as in Tables 8, except the work stress indicator which has been removed. The estimated coefficient associated with the satisfaction index is positive and significant at the 5% level for all the organizational commitment constructs, thus con- firming that job satisfaction explains and exerts a positive effect on employee’s organiza- tional commitment. Estimated values for this coefficient across organizational commitment constructs are as follows: I am willing to work harder than I have to in order to help firm or organization for succeed (coef. = 0.0874, s.e. = 0.0383), I am proud to be working for my firm or organization (coef. = 0.2967, s.e. 0.0850) and I would turn down another job that offered quite a bit more pay in order to stay with this organization (coef. = 0.2502, s.e. 0.0971), where reported standard errors are robust and based on the Huber- White sandwich estimator of variance. In addition to this exercise, we also carried out further analysis by estimating a parametric ordered probit model for organizational commitment which treats job satisfaction as potentially endogenously determined and where the change in work stress is used once again as the instrument (performed by using the extended regression command eoprobit from the STATA statistical package). This approach implied a maximum likelihood joint estimation of two ordered probit models for job satisfaction and organizational commitment which allows for the correlation between the errors of these two equations. Such as before, the results indicated a positive and statistically significant role of job satisfaction to the determination of organizational commitment. Moreover, the null hypothesis of zero correlation between error terms of the two equations is not rejected at the 1% of significance across the three organizational commitment constructs, being the estimated results as follows: I am willing to work harder than I have to in order to help firm or organization for succeed (corr. = 0.1227, s.e. = 0.3131), I am proud to be working for my firm or organization (corr. = 0.0621, s.e. 0.1073) and I would turn down another job that offered quite a bit more pay in order to stay with this organization (corr = −0.1272, s.e. 0.1704). Therefore, we cannot reject the hypothesis of exogeneity of job satisfaction in the organizational commitment equations. In sum, the previously reported positive impact of job satisfaction on organizational commitment is robust and not undermined by the endogeneity issues. 18 J. A. C. VIEIRA ET AL. The null hypotheses that employee characteristics and job characteristics do not directly influence organizational commitment are rejected at conventional levels of significance, thus validating H4 and H5, respectively (Table 8). This implies that job and worker attributes do not determine organizational commitment only indirectly via their effect on job satisfaction, but also directly. In such a case, organizational commit- ment varies within each level of job satisfaction, depending on the values of those attributes. Nevertheless, some particularities can be isolated when examining the set as a whole and investigating the role of specific variables. Only a few cases will be mentioned below, although others can be easily identified within the estimated results included in Tables 4 and 7. For instance, although gender has no visible effect on job satisfaction, it directly impacts the degree of agreement on the willingness to work harder in order to help the firm or organization succeed. In this case, women are less likely to strongly agree and more likely to strongly disagree, compared to men. However, gender has no visible effects on other organizational commitment indicators such as the pride of working for the firm or the willingness to turn down another job that offers quite a bit more pay in order to stay with the organization. The same is valid for union membership, whose coefficient is not statistically different from zero in the satisfaction equation. However, unionized workers are more unwilling to work harder in order to help the firm succeed than their non-unionized counterparts, but do not differ from these with respect to the pride of working for the firm or the willingness to stay in the job. There are substantial heterogeneous outcomes regarding the impact of religious beliefs on organizational commitment. Hindus and Catholics are apparently more available to work harder to promote the success of the firm or organization. Hindus, Islamic, Protestants, and Catholics are more likely to be proud to work for a firm or organization. Buddhists are more probable to turn down another job in order to stay in the firm or organization. Years of completed education exert no direct effect on organizational commitment but only indirectly through their influence on job satisfaction. There is also significant heterogeneity regarding the influence of country of residence on organizational commitment, which varies within a specific construct as well as across constructs (Table 9). Regarding the statement concerning their willingness to work harder in order to help a firm succeed, workers in Venezuela had the highest probability of strongly agreeing and the lowest probability of strongly disagreeing, all else equal, with the other extreme of the ranking occupied by France. The United States ranked fourth, although the difference was not statistically different from the second and the third (South Africa and Georgia, respectively). With respect to being proud of working for the firm or organization, Venezuela also led, while the other extreme of the ranking was found in Russia. In this case, the United States ranked third but was not statistically different from the second in the ranking (Spain), and France occupied a middle position. Despite some visible differences in these two rankings, such as the position of France, a Spearman rank correlation equals 0.606 (P = 0.000), indicating the positive significant association between them, therefore suggesting a proximity of type of organizational commitment captured by these two variables. However, substantial differences emerge when these rankings are compared with that of the willingness to turn down another job that offered quite a bit more pay in order to stay in the firm or organization. In this case, workers in Japan were the ones with the highest probability of strongly agreeing and the JOURNAL OF APPLIED ECONOMICS 19 Table 9. Regression coefficients ranking by country and Spearman rank correlation by organizational commitment constructs. Turn down another job that offered quite Work harder in order to help the Proud to be working for a bit more pay to stay in the firm or firm or organization for succeed. the firm or organization. organization. 1 Venezuela Venezuela Japan 2 South Africa Spain China 3 Georgia United States Israel 4 United States Iceland Philippines 5 Iceland New Zealand Suriname 6 Taiwan South Africa Latvia 7 New Zealand Suriname Czech Republic 8 Israel Mexico Finland 9 China Norway Lithuania 10 Mexico Georgia India 11 Japan Israel Switzerland 12 United Kingdom Japan Russia 13 India Slovenia Mexico 14 Philippines France Germany 15 Norway United Kingdom Norway 16 Australia China Slovak Republic 17 Suriname Australia Georgia 18 Switzerland Belgium Austria 19 Hungary Philippines South Africa 20 Czech Republic Croatia Slovenia 21 Slovak Republic Hungary Belgium 22 Spain Switzerland Taiwan 23 Sweden India New Zealand 24 Austria Taiwan Poland 25 Croatia Latvia United Kingdom 26 Slovenia Sweden Venezuela 27 Germany Slovak Republic Estonia 28 Estonia Austria Chile 29 Russia Germany Hungary 30 Belgium Czech Republic Croatia 31 Poland Finland France 32 Finland Poland United States 33 Lithuania Chile Australia 34 Latvia Estonia Spain 35 Chile Lithuania Sweden 36 France Russia Iceland Work . . . - 0.606 (p = 0.000) 0.021 (p = 0.902) Proud . . . - 0.004 (p = 0.983) 1. The first panel (rows numbered 1 to 36) of this table reports the ranking of the organizational commitment constructs regression coefficients from the most committed country (#1) to the least (# 36); 2. The second panel includes the Spearman rank correlation across organizational commitment constructs and the corresponding p-value test for the null hypothesis of zero correlation. lowest probability of strongly disagreeing, followed by China, Israel, and the Philippines (Table 9). The other extreme is occupied by Iceland, and the United States ranks thirty- second out of 36 countries. Employees in Venezuela, which occupied the top of the ranking in the former constructs, now occupy the twenty-sixth position. A Spearman rank correlation coefficient included at the bottom of Table 9 does not support any significant association between this ranking and the two previously examined. This finding suggests that the type of organizational commitment captured by this variable and the former ones are quite different, as it is likely closer to some sort of continuance commitment. Employees with high levels of continuance commitment remain in the 20 J. A. C. VIEIRA ET AL. organization because they need to stay until they find a more suitable opportunity elsewhere (Meyer & Allen, 1997). 4.2. Discussion Job satisfaction, organizational commitment, and the relationship between them have been debated in several scientific areas. The present study contributes to this empirical literature by evaluating the determinants of these two constructs using a semi- nonparametric estimation of separate ordered probit models, with the benefit of not imposing ex ante stringent distributional assumptions regarding the error term. For this purpose, we consider a conceptual framework where job satisfaction may act as an antecedent of organizational commitment. Empirical testing revealed interesting results. The results support our empirical estimation strategy, as the simple ordinary probit model – a specific case of our more general, more flexible non-parametric model – is rejected in favor of the general form we herein propose. Job satisfaction depends on certain employees’ characteristics and job- related attributes, in line with the literature. Furthermore, job satisfaction significantly influences organizational commitment but does not fully explain such organizational commitment behavior. Finally, organizational commitment depends directly and indir- ectly (via job satisfaction) on employees and job-related attributes. These outcomes have several managerial implications. It has been argued that organizational commitment contributes to business success, and our results indicate that management may foster organizational commitment to a certain extent. In fact, certain variables that directly and/or indirectly determine organizational commitment are not readily under the management’s control, such as, and for instance, gender, religious beliefs and practices, public versus private sector work, country of residence. However, many instruments can be used by management in order to directly and/or indirectly enhance organizational commitment, including creating conditions to reduce stress in the workplace (due to its indirect impact on organizational commitment via job satisfaction) and promoting good relations between workmates and with management. Whenever possible, enabling an employee to take time off during working time and improving the coordination between job and family life also seems important in order to achieve that goal, which points to the role of flexible workplace arrangements and practices for individuals, teams, and organizations (Anderson et al., 2002; Scandura & Lankau, 1997). Recruiting workers with previous experience and skills to be used at work or providing training to improve workers’ skills in order to avoid job- skill mismatch can help promote satisfaction and commitment. Other instruments relate to the development of practices that promote employees’ positive feelings about job aspects such as pay, security, or autonomy and provide opportunities for job career development. Our results are useful for managers to address perils of the Great Resignation of late 2021 and early 2022, with high number of resignations and high labour market tightness in labour markets such as the USA and associated potential for non-optimal job turnover and wage-growth induced inflation. In fact, the information herein uncovered may be used for managers to design human resource policies and practices that foster job satisfaction and organizational commitment, thus potentially avoiding excessive job turnover in a win–win manner for workers and organizations. JOURNAL OF APPLIED ECONOMICS 21 Finally, country-specific factors play a significant role in job satisfaction and organiza- tional commitment. Indeed, job satisfaction varies substantially according to country of residence, after controlling for a large set of personal and job or workplace-related attributes. The same is true regarding organizational commitment. Moreover, the impact of country of residence on the explanation for the likelihood of turning down another job that offered quite a bit more pay in order to stay at the firm and the explanation for the other two organizational commitment constructs differs substantially. These results suggest that, despite the convergence in workplaces and workforces in many aspects due to globalization and the expanding role of multinationals, managers and human resources professionals alike must be aware that substantial differences still exist across countries (even after controlling for religious dimensions). 5. Conclusions and future research directions This paper examined job satisfaction and organizational commitment using a sizeable, rich, micro data set for a large number of working respondents in 36 countries. Due to the ordered nature of the dependent variables, we estimate ordered probit equations using a semi-nonparametric approach, which revealed itself to be far superior to the conventional ordered probit model thus validating our proposed empirical strategy. The results indicate that employee and job-related attributes directly and indirectly (through job satisfaction) affect organizational commitment. However, within each of those sets, not all variables play the same role or are equally controllable for managerial purposes. Our empirical results do uncover a set of workplace-related variables which managers can leverage to significantly foster organizational commitment. A very interesting result is that despite the ubiquitous and inexorable globalization process, job satisfaction and organizational commitment differ significantly across countries, even after a large set of controls for individual and job-workplace related characteristics is considered. Managers ought to consider said micro determinants of job satisfaction and organizational com- mitment and cross-country differences to design well-informed human resources poli- cies that aim to foster job satisfaction and organizational commitment, which could help address job resignations that contribute negatively to optimal job turnover; an economic problem acutely felt in certain labour markets experiencing the present day so-called Great Resignation. The semi-nonparametric approach does not address some aspects which could be explored in future research, such as a potential reciprocity between the organizational commitment and job satisfaction, which could be relevant (Saridakis et al., 2018). Moreover, a replication of the methodology applied to different countries separately could add to the understanding of cross-country differences or similarities in the determinants of job satisfaction and organizational commitment as well as the relation- ship between these two constructs. Disclosure statement No potential conflict of interest was reported by the author(s). 22 J. A. C. VIEIRA ET AL. Funding This paper/research is financed by Portuguese national funds through FCT – Fundação para a Ciência e a Tecnologia, I.P., project number UIDB/00685/2020. Notes on contributors José A. C. Vieira is a Professor of Economics at the School of Business and Economics of the University of the Azores, in Portugal. He holds a Ph.D. in Economics from the University of Amsterdam, in Netherlands. His main research areas include tourism and labour economics. He is a member of the editorial board of Tourism Economics. Francisco J. F. Silva is an Assistant Professor of Operations Research at the School of Business and Economics of the University of the Azores, in Portugal. He holds a Ph.D. in Management from the University Pompeu Fabra, in Spain. His main research areas include operations research and tourism economics. João C. A. Teixeira is an Assistant Professor of Finance at the School of Business and Economics of the University of the Azores, in Portugal. He holds a Ph.D. in Finance from Lancaster University, in the United Kingdom. His main research areas include banking and corporate finance. António J. V. F. G. Menezes is an Associate Professor of Economics at the School of Business and Economics of the University of the Azores, in Portugal. He holds a Ph.D. in Economics from Boston College, in the U.S.A. His main research areas include labor economics and transportation economics. Sancha N. B. de Azevedo is a manager in the marketing area. She holds a MSc in Economics and Business Sciences and an undergraduate degree in Economics at the School of Business and Economics of the University of the Azores, in Portugal. ORCID José A. C. Vieira http://orcid.org/0000-0003-1422-1288 Francisco J. F. Silva http://orcid.org/0000-0002-3893-6029 João C. A. Teixeira http://orcid.org/0000-0003-4774-0236 António J. V. F. G. Menezes http://orcid.org/0000-0002-2001-1589 Sancha N. B. de Azevedo http://orcid.org/0000-0002-5407-3569 Information on rights and permissions The authors hereby knowingly accept the rules and practices regarding the reproduction of copyright material in their articles. Submission declaration statement The authors hereby solemnly declare that this manuscript is not under consideration for publica- tion elsewhere and that it has not already been published and that it will also not be submitted for publication elsewhere without the agreement of the Managing Editor. JOURNAL OF APPLIED ECONOMICS 23 References Adams, J. 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Journal

Journal of Applied Economics – Taylor & Francis

Published: Dec 31, 2023

Keywords: Job satisfaction; employee organizational commitment; cross-country differences; great resignation

References

  • Toward an understanding of inequity
  • Emotional intelligence and organizational commitment: Testing the mediatory role of occupational stress and job satisfaction
  • Job switching and job satisfaction in the US labor market
  • Organizational commitment: Evidence from career stage effects
  • Educational mismatches versus skill mismatches: Effects on wages, job satisfaction and on-the-job search
  • Education and skill mismatches: Wage and job satisfaction consequences
  • Formal organizational initiatives and informal workplace practices: Links to work-family conflict and job-related outcomes
  • The impact of job security on job satisfaction in economic contractions versus expansions
  • The influence of work life balance and job satisfaction on organizational commitment of healthcare employees
  • A longitudinal analysis of the antecedents of organizational commitment
  • How well do theories of job matching explain variation in job satisfaction across education levels? Evidence for U.K. graduates
  • Job satisfaction, wages and unions
  • Comparing levels of job satisfaction in the countries of Western and Eastern Europe
  • What accounts for job satisfaction differences across countries?
  • Workplace performance, worker commitment and loyalty
  • Loneliness, job satisfaction, and organizational commitment of migrant workers: Empirical evidence from China
  • Job satisfaction, age and tenure: A generalized dynamic random effects model
  • Job satisfaction and gender: Why are women so happy at work?
  • Satisfaction and comparison income
  • Is job satisfaction U-shaped in age?
  • Causal ordering of stress, satisfaction and commitment, and intention to quit: A structural equations analysis
  • A three-wave longitudinal analysis of the causal ordering of satisfaction and commitment on turnover decisions
  • Principal self-efficacy: Relations with burnout, job satisfaction and motivation to quit
  • Our most important asset: A multidisciplinary/multilevel review of human capital valuation for research and practice
  • Semi-nonparametric maximum likelihood estimation
  • Job satisfaction, union membership and collective bargaining
  • The effect of educational level on job satisfaction and organizational commitment: A case study in hospitality
  • Motivation through the design of work: Test of a theory
  • The impact of unions on job satisfaction, organizational commitment, and turnover
  • Business-unit-level relationship between employee satisfaction, employee engagement, and business outcomes: A meta-analysis
  • Job satisfaction and intent to leave
  • Performance pay and job satisfaction
  • The causal relationship between job satisfaction and organizational commitment
  • Establishment size, job satisfaction and the structure of work
  • Perceived over-qualification and dimensions of job satisfaction: A longitudinal analysis
  • Regional differences in job satisfaction
  • Five-factor model of personality and job satisfaction: A meta-analysis
  • Job satisfaction as a reflection of disposition: A multiple-source causal analysis
  • Job attitudes
  • Workplace religious expression, religiosity and job satisfaction: Clarifying a relationship
  • The effects of employee satisfaction, organizational citizenship behavior, and turnover on organizational effectiveness: A unit-level, longitudinal study
  • Evaluation of a structural model relating job satisfaction, organizational commitment, and precursors to voluntary turnover
  • Job satisfaction among Russian workers
  • Toward a theory of task motivation and incentives
  • A theory of human motivation
  • A review and meta-analysis of the antecedents, correlates, and consequences of organizational commitment
  • Measuring the costs of children: Parametric and semiparametric estimators
  • A three-component conceptualization of organizational commitment
  • The measurement of organizational commitment
  • Job satisfaction across Europe: Differences between and within regions
  • The relationship between perceived compensation, organizational commitment and job satisfaction: The case of Mexican workers in the Korean Maquiladoras
  • Differences in the job satisfaction of high-paid and low-paid workers across Europe
  • Handbook of organizational measurement
  • Examining the interconnection of job satisfaction and organizational commitment: An application of the bivariate probit model
  • Rethinking the union membership/job satisfaction relationship: Some empirical evidence in Canada
  • Education, control at work, and job satisfaction
  • The age and job satisfaction relationship in higher education
  • The gender-marital status job satisfaction relationship of academics
  • Exploring the relationship between job satisfaction and organizational commitment: An instrumental variable approach
  • Relationships of gender, family responsibility and flexible work hours to organizational commitment and job satisfaction
  • Racial harassment, job satisfaction and intentions to quit: Evidence from the British nursing profession
  • Gender differences in job satisfaction in Great Britain, 1991–2000: Permanent or transitory?
  • Semi-nonparametric estimation of extended ordered probit models
  • Is continuance commitment beneficial to organizations? Commitment performance relationship: A new look
  • Examining transformational leadership, job satisfaction, organizational commitment and organizational trust in Turkish hospitals: Public servants versus private sector employees
  • Interaction of organizational commitment and job satisfaction of nurses and medical secretaries in Turkey
  • Job satisfaction and organizational commitment
  • Examining the causal order of job satisfaction and organizational commitment
  • Reliability and validity of instruments measuring job satisfaction: A systematic review
  • Skill mismatches and job satisfaction
  • Education and the determinants of job satisfaction
  • From control to commitment in the workplace
  • Stress, burnout, and job satisfaction: Case of police force in China
  • International differences in job satisfaction: The effects of public service motivation, rewards and work relations
  • Gender and the relationship between perceived fairness of pay or promotion and job satisfaction
  • High-involvement management, economic recession, well-being, and organizational performance
  • Job satisfaction, organizational commitment and demographic characteristics among teachers in Turkey: Young is better?