Economic Locus of Control and Occupational Choices: Evidence from Faisalabad

Pakistan Journal of Social Sciences, Vol. 45(3) 2025, 243-250 243 ©2025 PJSS, Bahauddin Zakariya University Multan Pakistan Economic Locus of Control and Occupational Choices: Evidence from Faisalabad a Maryam Ejaz, b Imran Qaiser, c Anam Shehzadi, d Sadia Ali a M.Phil. Scholar, Department of Economics, Government College University Faisalabad, Pakistan Email: maryam.ijaz77[email protected]m b Assistant Professor, Department of Economics, Government College University Faisalabad, Pakistan Email: [email protected] c Lecturer, Department of Economics, Government College University Faisalabad, Pakistan E-mail: [email protected] d Assistant Professor, Department of Economics, Government College University Faisalabad, Pakistan E-mail: sadiaa[email protected].pk ARTICLE DETAILS ABSTRACT History: Accepted: 16 September, 2025 Available Online: 30 September, 2025 Purpose: Selecting a job has a multidimensional effect of employees’ personal, household, social, and economic sphere. This study intends to estimate the effect of economic locus of control on occupational choices. Design/Methodology/Approach: For this study data is gathered through questionnaire survey from 201 respondents from Faisalabad, Pakistan. Logistic regression models were used to estimate the relationship between variables Findings: The results reveal that the respondents with an internal economic locus of control are more likely to choose government job rather than their own business as compared to the respondents with an external economic locus of control. Implications/Originality/Value: Economic locus of control has significantly negative impact on occupational choices. The respondents with an internal economic locus of control are more likely to choose job either government or private as compared to the respondents with an external economic locus of control. Economic locus of control has significantly positive impact on self-employment. The respondents with an internal economic locus of control are more likely to choose a job with more salary but with less security. © 2025 The authors. Published by PJSS, BZU. This is an open-access research paper under the Creative Commons Attribution-Non-Commercial 4.0 Keywords: Economic Locus of Control Occupational Choices Self-Employment Risk Attitude Recommended Citation: Ejaz, M., Qaiser, I., Shehzadi, A. & Ali, S. (2025). Economic Locus of Control and Occupational Choices: Evidence from Faisalabad. Pakistan Journal of Social Sciences, 45(3), 243-251. DOI: 10.5281/zenodo.17356161 *Corresponding Author’s email address: [email protected] 1. Introduction Choosing a job has significant effects on employees' health because they can either improve or worsen their health (Kelly et al., 2014). People tended to select occupations whose values matched more closely with their own values (Judge & Bretz 1992). The global labor force's skill heterogeneity has a beneficial impact on welfare gains. When individuals have the option to select between wage labor and management job, the global labor market increases output more in countries that are wealthy and developing and less in middle-income nations (Eeckhout & Jovanovic (2012). The self-concept implementation theory of occupational choice (Super, 1957, 1963) states that an individual Pakistan Journal of Social Sciences ISSN (E) 2708-4175 ISSN (P) 2074-2061 Volume 45: Issue 3 September 2025 Journal homepage: https://pjss.bzu.edu.pk Pakistan Journal of Social Sciences, Vol. 45(3) 2025, 243-250 244 chooses the career path that best fits his self-concept out of a range of options. Making an occupational decision is a multi-year developmental process. A conceptual framework relates the various, varied aspects impacting an individual's choice of career (Balu et al., 1956). A significant increase in the percentage of the population employed in professional and management roles occurred throughout the second half of the 20th century, marking a significant shift in occupational status. However, along with this increase in absolute mobility, there was little change in the relative mobility of individuals with varying occupational backgrounds (Croll, 2008). The students who have an internal LOC are impacted by external factors while choosing their careers, whereas students who have an external LOC are influenced by external factors (Denga, 1984). John & Thomsen, (2014) proves that locus of control is an important determinant of occupational choices. Uhlendorff et al., (2010) show that the people with an internal locus of control search more for jobs rather than the people with an external locus of control and as the people’s locus of control becomes more internal, it increases the reservation wage while people with an external LOC have low reservation wage. Ahn, (2015) find that locus of control plays a crucial role to determines a job mobility of worker and labor market attachment. Cobb-Clark, (2015) concludes that individuals’ decisions to look for new challenges, work hard, and acquire human capital all have been linked to the locus of control so; the LOC must be carefully taken into account by governments and businesses when creating incentive contracts, laws, and campaigns to encourage employee behavior. A mental concept that expresses people's opinions regarding the causality of occurrences in their lives and their own behavior (Cobb-Clark et al., 2016). LOC a broad mindset, expectation, or belief about the nature of the causal connection between one's own actions and the results (Rotter, 1966). Individuals possessing an internal locus of control believe that their choices influence their lives, while those with an external locus of control blame their outcomes to outside factors such as destiny, fortuity, or chance. The propensity to think that internal rather than external variables determine economic growth is known as the economic locus of control (Sakalaki et al, 2009). Individuals with an internal locus of control are individuals who perceive their actions as determining the path of events in their life, whereas those who think luck, chance, or outside forces influence their lives are considered to have an external locus of control (Phares et al., 1968). The main objective of this study is to estimate the effect of economic locus of control on occupational choices. Some other determinants of occupational choices used in this research are personality traits (Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism), resilience, emotion (fear, anger, sadness, and pessimism), social influence, and other demographical factors. 2. Data and Methodology 2.1 Data A questionnaire survey by using cluster sampling technique is used to gather data for this study from 201 individuals from Faisalabad. One hundred and sixty-four, or eighty-two percent, of the individuals in this study are from rural areas; the remaining subjects are from urban regions. The people who make money from any source are the study's subject. There are 61 female respondents and 140 male respondents. 52 responders are between the age of 51 and 77, 73 are between the age of 31 and 50, and 76 are between the age of 18 and 30. 52 respondents work in the public sector, 74 in the commercial sector, and 75 are independent contractors. 48 respondents are matriculated or less educated, 28 have an intermediate level of education, 20 have a BA/BSc level of education, 71 have a master's level of education, 22 have an MPhil level of education, and 12 have a PhD level of education. The respondents' educational backgrounds vary widely. 2.2 Measurement of Variables Economic locus of control is derived in response to ten questions 9 are adopted from Furnham (1986) and 1 is adopted from Rasheed et al. (2018). Occupational choices, job preferences, and self-employment are the dependent Pakistan Journal of Social Sciences, Vol. 45(3) 2025, 243-250 245 variables while economic locus of control is an independent variable. One question is used to measure occupational choices which is “If you are to choose which one will you prefer?” and the given options from respondent choses one are “government job; private job and self-employed”. One question is used to measure job preferences which is “If you have two options of employment which one will you prefer?” and the given options from respondent choses one are “a long term/permanent contract with the pay of Rs 100000 and retirement benefits and a job with short term contract likely to be extended with the pay of Rs 250000 but no retirement benefits”. One question is used to measure self-employment which is “If you are to choose which one will you prefer” and the given options from respondent choses one are “government job or private job and self-employed” 2.3 Factor Analysis Factor analysis is a subset of multivariate analysis that was first created by psychologists, with Spearman, Thomson, Thurstone, and Bur being the most notable innovators (Lawley & Maxwell, 1962). Factor analysis is a genetic term for a collection of data processing methods that are rather undefined and are primarily used in the social and biological sciences. These methods are designed to analyze the relationships between several measurements taken on multiple measurable items (McDonald, 2014). Factor analysis is a group of techniques used to interpret correlations between variables in terms of factors, which are more basic entities. It originated from the finding that variables from a well-constructed domain, such intelligence tests or assessments of interpersonal functioning, frequently show correlations with one another (Cudeck, 2000). 2.4 Multinomial Logistic Regression (MLR) The MLR model is a crucial technique for analyzing categorical data. This model focuses on single nominal or ordinal response variable that has more than two categories. This model has been used to analyze data in a variety of fields, including social, behavioral, health, and education (El-Habil, 2012). An extension of a binary logistic regression is called a multinomial logistic regression. when there are more than two levels in the categorical dependent outcome (Chan, 2005). Without selecting variables, all feature space subsets that are mutually exclusive can be used with the multinomial logit model. Because it integrates many models, the proposed method can handle a sizable database without the limitations necessary for researching high-dimensional data, and by reducing correlation between base classifiers, the random partition can improve prediction accuracy (lee et al., 2013). Multinomial Logistic Regression Model: OC = α0 + α1 (ELOC) + α2 (PT) + α3 (CV) + µ1 Where: OC denote as occupational choices, ELOC denote as economic locus of control, PT denote as personality trait (openness to experience, neuroticism and conscientiousness), CV denote control variable such as gender, resilience, family type, qualification, and emotional weakness. 2.5 Binary Logistic Regression Logistic regression models are used to examine how predictor factors affect categorical outcomes. When the outcome is frequently binary, such the presence or absence of a disease, a binary logistic model is employed. Simple logistic regression is a term given to the logistic regression model when there is just one predictor variable. When several predictors (such risk factors and treatments) are present, the model uses both continuous and categorical data as predictors is known as a multiple or multivariable logistic regression (Nick & Campbell, 2007). Binary or dichotomous outcomes with two mutually exclusive levels can be analyzed using logistic regression. On the other hand, logistic regression has the ability to account for a variety of parameters and allows the use of categorical or continuous predictors. Therefore, when correcting to reduce any possible bias caused by differences between the groups being compared, logistic regression is particularly advantageous for the analysis of observational data (LaValley, 2008). Pakistan Journal of Social Sciences, Vol. 45(3) 2025, 243-250 246 Binary logistic regression model: JB = α0 + α1 (ELOC) + α2 (PT) + α3 (CV) + µ1 SE = β0 + β1 (ELOC) + β2 (E) + β3 (CV) + µ2 Where: JB denote as job preference, ELOC denote as economic locus of control, SE denotes self-employment, E denotes as emotion (fear, anger, and pessimism), PT denote as personality trait (openness to experience, agreeableness and conscientiousness), CV denote control variable such as age, gender, family type, and emotional weakness. Table 1 Descriptive Analysis of Continues Variables Mean Median Sd. Skewness Kurtosis Max. Min. ELOC 0.0000 0.1412 0.7846 -0.3057 2.7320 1.6947 -2.1180 Neuroticism 0.0000 -0.0658 0.7610 -0.1394 -0.1394 1.5006 -1.7065 Extraversion 0.0000 0.0322 0.7820 -0.3796 3.0852 1.4042 -2.4794 Openness to experience 0.0000 0.0235 0.7276 -0.2982 2.8050 1.4147 -1.8429 Agreeableness 0.0000 -0.1322 0.7578 0.6946 3.6915 3.0478 -1.4546 Conscientiousness 0.0000 0.1174 0.6967 -0.7601 3.9668 1.1889 -2.4935 Attitude toward financial risk 0.0000 0.1928 0.7632 -0.4945 3.4866 1.6724 -2.6524 Resilience 0.0000 -0.1393 0.5005 -0.2755 2.8051 1.1777 -1.4880 Fear 0.0000 0.1147 0.7343 0.2577 2.4656 1.6303 -1.3578 Anger 0.0000 0.0430 0.8153 0.1097 2.1226 1.6175 -1.4272 Pessimism 0.0000 -0.1425 0.7045 0.3382 2.4923 1.7309 -1.2466 Sadness 0.0000 -0.0095 0.5907 -0.1009 2.6353 1.2394 -1.2585 Herding effect 0.0000 -0 .0293 0.8354 -0.2879 2.4174 1.9315 -2.5075 Long term goal 0.0000 -0.0276 0.4891 -0.2143 3.3297 1.3292 -1.6001 Authors’ compilation As the results reveals in the above table a slim majority of the respondents have either neutral or a behavior characterized by an internal ELOC. There are few respondents who have either neutral or a behavior characterized by neuroticism. The results also show that slim majority of the respondents have either neutral or an extravert behavior. A small majority of respondents are traditional, which is defined as having an interest in knowledge, appreciating the arts, and being sensitive to aesthetics. There are fractions of people who are not agreeable to others or put others need before their own. A fraction of the respondents does not think of other needs before themselves. A fraction of the respondents has either neutral behavior or are disciplined and to prefer planned rather than spontaneous behavior. There is a slim majority of the respondents are either risk neutral or are risk lovers or willing to take risk. A small fraction of the respondents has either neutral or resilient behavior. A slim majority of the respondents have either neutral behavior or do not have a fear of other’s or a fear what other think about them. A small fraction of the respondents has either neutral behavior or do not get angry easily. A slim majority of the respondents have either neutral or hopeful behavior or a respondent who do not lose hope easily. There are a few respondents who become sad easily because of others. A small fraction of the respondents has either neutral or herd behavior or a respondent whose investment decision effects because of other investor’s decisions. A slim majority of the respondents have long term goals or who plans their future with their present. Pakistan Journal of Social Sciences, Vol. 45(3) 2025, 243-250 247 Table 2 Multinomial Logistic Regression Results Occupational choices Coefficient Std. Error Z-statistics P>|z| Government job Gender -0.8879008 0.3527415 -2.52 0.012 ELOC -0.4376093 0.2122707 -2.06 0.039 Qualification 0.0509041 0.0385939 1.32 0.187 Family type 0.7448455 0.3485673 2.14 0.033 Neuroticism -0.1459628 0.2229751 -0.65 0.513 OTE 0.1640606 0.2309112 0.71 0.477 Conscientiousness 0.0990285 0.2402283 0.41 0.680 Resilience -0.5249752 0.3301211 -1.59 0.112 Emotional weakness 0.2539385 0.2042174 1.24 0.214 Private job Gender -0.5146601 0.8331596 -0.62 0.537 ELOC 0.4409698 0.5486969 -0.80 0.422 Qualification 0.0378795 0.0907109 0.42 0.676 Family type 1.253757 0.9764963 1.28 0.199 Neuroticism -0.8650422 0.5529451 -1.56 0.118 OTE -0.0095055 0.5280289 -0.02 0.986 Conscientiousness -1.159401 0.5031406 -2.30 0.021 Resilience 0.652607 0.8950241 0.73 0.466 Emotional weakness -0.1690949 0.4885317 -0.35 0.729 Self Employed Base outcome Authors’ compilation Results in the above table show that the respondents with an internal ELOC are more likely to choose government job rather than their own business as compared to the respondents with an external ELOC. ELOC has significantly negative impact on occupational choices. Male respondents are more willing to choose government job rather than their own business as compared to the female respondents. Gender has significantly negative impact on occupational choices. Respondents from join families are more likely to choose government job rather than their own business as compared to the respondents from nuclear-type of families. Family type has significantly positive impact on occupational choices. While other independent variables such as qualification, personality trait (Neuroticism, conscientiousness, and openness to experience), resilience and emotional weakness have insignificant effects on Table 3 Logistic Regression Results Job Preferences Coefficient Std. Error Z-statistics P>|z| ELOC 0.5140003 0.2521878 2.04 0.042 Gender 0.5890849 0.4169426 1.41 0.158 Middle age 0.3117396 0.4089019 0.76 0.446 Old age -0.5103002 .4924552 -1.04 0.300 Family type -0.7224311 0.3662846 -1.97 0.049 Agreeableness 0.2381055 0.2500859 0.95 0.341 Conscientiousness -0.5089528 0.2781312 -1.83 0.067 Emotional weakness 0.2814137 0.2057454 1.37 0.171 Constant -1.124989 0.4778538 -2.35 0.019 Authors’ compilation Pakistan Journal of Social Sciences, Vol. 45(3) 2025, 243-250 248 Results in the above table show that the respondents with an internal ELOC are more likely to choose a job with more salary but with less security ELOC has a significant and positive effect on job preference, the study of Luck, (2004) are in the line of our result. Nuclear-type families are more likely to choose permanent jobs with low salaries but high security, family type has a significantly negative effect on job preference. Respondents with a conscientious personality are more likely to choose permanent jobs with low salaries but high security or with employment benefits, conscientiousness significantly negative effect on job preference. While other independent variables such as gender, age, agreeableness (personality trait), and emotional weakness have insignificant effects on job preferences. Table 4 Logistic Regression Results Self-employed Coefficient Std. Error Z-statistics P>|z| ELOC 0.4316591 0.2052351 2.10 0.035 Gender 0.8138496 0.3448215 2.36 0.018 Qualification -0.0607726 0.0376509 -1.61 0.107 Family size -0.0336528 0.0575482 -0.58 0.559 Family type -0.7409204 0.3457817 -2.14 0.032 OTE -0.1222419 0.2204669 -0.55 0.579 Fear 0.0916173 0.2222784 0.41 0.680 Anger -0.1115387 0.2225611 -0.50 0.616 Pessimism -0.0448534 0.2718421 -0.16 0.869 Authors’ compilation Results in the above table show that the respondents with an internal ELOC are more likely to choose job either government or private job as compared to the respondents with an external ELOC. ELOC has significantly positive impact on self-employment. Female respondents are more likely to choose a job than male respondents. Gander has significantly positive impact on self-employment. Nuclear-type families are more likely to choose job rather than their own business family type has a significantly negative effect on self-employment. While other independent variables such as qualification, family size, openness to experience (personality trait), and emotion (fear, anger and pessimism) have insignificant effects on self-employment. 3. Summary and Conclusion The main objective of this study is to estimate the effect of economic locus of control on occupational choices by using the data collected through questionnaire survey from 201 subjects from Faisalabad, Pakistan. In this study three models have been drawn to estimate the relationship between dependent and independent variables, there are numerous independent variables have been used in this study such as personality traits (neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness), social influence, herding effect, long term goals, emotions, basic financial literacy, resilience, and other demographic factors but the key regress or is economic locus of control while occupational choices, self-employment, and job preferences are dependent variables. The results of this study reveal that the respondents with an internal ELOC are more likely to choose government job rather than their own business as compared to the respondents with an external ELOC. ELOC has significantly negative impact on occupational choices. The respondents with an internal ELOC are more likely to choose job either government or private job as compared to the respondents with an external ELOC. ELOC has significantly positive impact on self-employment. The respondents with an internal ELOC are more likely to choose a job with more salary but with less security ELOC has a significant and positive effect on job preference, the study of Luck, (2004) are in the line of our result. Pakistan Journal of Social Sciences, Vol. 45(3) 2025, 243-250 249 References Ahn, T. (2015). Locus of control and job turnover. Economic Inquiry, 53(2), 1350-1365. Blau, P. M., Gustad, J. W., Jessor, R., Parnes, H. S., & Wilcock, R. C. (1956). Occupational choice: A conceptual framework. ILR Review, 9(4), 531-543. Chan, Y. H. (2005). Biostatistics 305. Multinomial logistic regression. Singapore medical journal, 46(6), 259. Cobb-Clark, D. A. (2015). Locus of control and the labor market. Locus of control and the labor market, 4, 1-19. Cobb-Clark, D. A., Kassenboehmer, S. C., & Sinning, M. G. (2016). Locus of control and savings. Journal of Banking & Finance, 73, 113-130. Croll, P. (2008). Occupational choice, socio‐economic status and educational attainment: a study of the occupational choices and destinations of young people in the British Household Panel Survey. Research papers in Education, 23(3), 243-268. Cudeck, R. (2000). Exploratory factor analysis. In Handbook of applied multivariate statistics and mathematical modeling (pp. 265-296). Academic Press. Denga, D. I. (1984). Locus of control and its relationship to occupational choice behaviour. Applied Psychology, 33(3), 371-379. Eeckhout, J., & Jovanovic, B. (2012). Occupational choice and development. Journal of Economic Theory, 147(2), 657-683. El-Habil, A. M. (2012). An application on multinomial logistic regression model. Pakistan journal of statistics and operation research, 271-291. John, K., & Thomsen, S. L. (2014). Heterogeneous returns to personality: the role of occupational choice. Empirical Economics, 47, 553-592. Judge, T. A., & Bretz, R. D. (1992). Effects of work values on job choice decisions. Journal of applied psychology, 77(3), 261. Kelly, I. R., Dave, D. M., Sindelar, J. L., & Gallo, W. T. (2014). The impact of early occupational choice on health behaviors. Review of Economics of the Household, 12, 737-770. LaValley, M. P. (2008). Logistic regression. Circulation, 117(18), 2395-2399. Lawley, D. N., & Maxwell, A. E. (1962). Factor analysis as a statistical method. Journal of the Royal Statistical Society. Series D (The Statistician), 12(3), 209-229. Lee, K., Ahn, H., Moon, H., Kodell, R. L., & Chen, J. J. (2013). Multinomial logistic regression ensembles. Journal of Biopharmaceutical Statistics, 23(3), 681-694. McDonald, R. P. (2014). Factor analysis and related methods. Psychology Press. Nick, T. G., & Campbell, K. M. (2007). Logistic regression. Topics in biostatistics, 273-301. Phares, J. E., Ritchie, E. D., & Davis, W. L. (1968). Internal-external control and reaction to threat. Journal of Personality and Social Psychology, 10(4), 402. Rotter, J. B. (1966). Generalized expectancies for internal versus external control of reinforcement. Psychological monographs: General and applied, 80(1), 1. Sakalaki, M., Kanellaki, S., & Richardson, C. (2009). Is a manipulator's externality paradoxical? The relationship between Machiavellianism, economic opportunism, and economic locus of control. Journal of Applied Social Psychology, 39(11), 2591-2603. Super, D. E. (1957). Psychology of Careers, New York, NY: Harper and Brothers. Super, D. E. (1963). Self-concepts in vocational development. Career development: Self-concept theory, 1-16. Uhlendorff, A., Caliendo, M., & Cobb-Clark, D. A. (2010). Locus of Control and Job Search Strategies. Acknowledgments The authors are grateful for comments from two anonymous referees. Disclosure statement No potential conflict of interest was reported by the author(s). Disclaimer Pakistan Journal of Social Sciences, Vol. 45(3) 2025, 243-250 250 The views and opinions expressed in this paper are those of the authors alone and do not necessarily reflect the views of any institution. Mariam Ijaz is a student at Department of Economics, Government College University Faisalabad, Pakistan. She got her Master of Philosophy degree in Economics from the Government College University Faisalabad, Pakistan. Imran Qaiser is an assistant professor at Department of Economics, Government College University Faisalabad, Pakistan. He got his Master of Philosophy degree in Economics from the Government College University Lahore, Pakistan and PhD degree in Economics from the Frei University Berlin, Germany. His research focuses on Econometrics, Microeconomics and Macroeconomics. Anam Shezadi is a lecturer at Department of Economics, Government College University Faisalabad, Pakistan. She got her Master of Philosophy degree in economics from the Government College University Lahore, Pakistan and PhD degree in Economics from the University of Kassel, Germany. Her research focuses on Energy Economics Development Economics and Macroeconomics. Sadia Ali is an assistant professor at Department of Economics, Government College University Faisalabad, Pakistan. She got her Master of Philosophy degree in Economics from the Government College University Lahore, Pakistan and PhD degree in Economics from the Government College University Faisalabad, Pakistan. ORCID: 0000-0002-8847-8409