metadata: authors: 0: author: Amankwah,Akuffo
1: author: Castaing,Pauline
2: author: Owoo,Nkechi Srodah
3: author: Palacios-Lopez,Amparo
count: Ghana,World
docna: 0: docna: Labor Market Participation and Employment
            Choice in Ghana : Do Individual Personality Traits and
            Gender Role Attitudes Matter ?
docty: Policy Research Working Paper
abstracts: cdata!: In addition to the conventional
            determinants of labor market participation and the choice
            between wage employment and self-employment, there is a
            growing interest of the significance of gender role
            attitudes and personality traits. This study uses data from
            the 2022 Ghana Informal Sector Measurement Study to
            investigate the influence of these factors on employment
            outcomes in the Northern and Ashanti regions of Ghana. The
            findings are based on a series of analyses, including
            descriptive, multinomial logistic, and linear probability
            model regressions. The empirical results show the critical
            role played by both gender role attitudes and personality
            traits in shaping individuals' decisions on labor
            market participation and employment choices. Notably,
            personality traits emerge as significant drivers of observed
            employment outcomes. However, the impact of these
            personality traits is often mitigated or even reversed in
            the presence of heightened traditionalism. Furthermore, the
            gender-disaggregated analysis reveals that possessing at
            least a secondary education level is a pivotal factor in the
            selection of men into formal employment, whereas this
            criterion holds less significance for women. Conversely,
            once the decision to participate in the labor market has
            been made, having at least a secondary education becomes
            relevant for securing wage employment, regardless of an
            individual's gender.
display_title: Labor Market Participation and
            Employment Choice in Ghana : Do Individual Personality
            Traits and Gender Role Attitudes Matter ?
listing_relative_url: /research/2024/01/34235906/labor-market-participation-employment-choice-ghana-individual-personality-traits-gender-role-attitudes-matter
topicv3: Gender and Employment m1326451 618,Labor Market Analysis m1582757 4428
publishtoextweb_dt: 2024-01-10T00:00:00Z
dois: 10.1596/1813-9450-10664
origu: Off of Sr VP Dev Econ/Chief Econ (DECVP)
no_of_pages: 52
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model_extractions: Policy Research Working Paper 10664

# Labor Market Participation and Employment Choice in Ghana

Do Individual Personality Traits and Gender Role Attitudes Matter?

_Akuffo Amankwah Pauline Castaing Nkechi S. Owoo Amparo Palacios-Lopez_ Development Economics Development Research Group January 2024 A verified reproducibility package for this paper is available at http://reproducibility.worldbank.org, click **here** for direct access.
Policy Research Working Paper 10664

# **Abstract**

In addition to the conventional determinants of labor market participation and the choice between wage employment and self-employment, there is a growing interest of the significance of gender role attitudes and personality traits. This study uses data from the 2022 Ghana Informal Sector Measurement Study to investigate the influence of these factors on employment outcomes in the Northern and Ashanti regions of Ghana. The findings are based on a series of analyses, including descriptive, multinomial logistic, and linear probability model regressions. The empirical results show the critical role played by both gender role attitudes and personality traits in shaping individuals’ decisions on labor market participation and employment choices.

Notably, personality traits emerge as significant drivers of observed employment outcomes. However, the impact of these personality traits is often mitigated or even reversed in the presence of heightened traditionalism. Furthermore, the gender-disaggregated analysis reveals that possessing at least a secondary education level is a pivotal factor in the selection of men into formal employment, whereas this criterion holds less significance for women. Conversely, once the decision to participate in the labor market has been made, having at least a secondary education becomes relevant for securing wage employment, regardless of an individual’s gender.

This paper is a product of the Development Research Group, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at aamankwah@worldbank.org. A verified reproducibility package for this paper is available at http:// reproducibility.worldbank.org, click **here** for direct access.

<!-- Start of picture text --> TRANSPARENT<br>ANALYSIS<br>G<br>R E<br>N<br>S<br>I P<br>Y E<br>K A<br>C A<br>R P<br>LI R<br>O E<br>O C<br>W R<br>H<br>S<br>P<br><!-- End of picture text --> _The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Labor Market Participation and Employment Choice in Ghana: Do Individual Personality Traits and Gender Role Attitudes Matter?**

Akuffo Amankwah<sup>1</sup> , Pauline Castaing<sup>2</sup> , Nkechi S. Owoo<sup>3</sup> , Amparo Palacios-Lopez<sup>2</sup>

- 1 Corresponding Author – Living Standards Measurement Study, Development Data Group, World Bank, Washington DC, email – aamankwah@worldbank.org.

- 2 Living Standards Measurement Study, Development Data Group, World Bank, Washington DC.

- 3 Department of Economics, University of Ghana, nkechi.owoo@gmail.com

**Keywords:** employment outcomes, self-employment, gender role attitudes, personality traits, Ghana

**<mark>WB Thematic Areas</mark>** <mark>: Gender and Employment; Labor Market diagnostics</mark>
# **1. Introduction**

The drivers of labor market participation and employment outcomes have been well documented in the literature (Baah-Boateng, 2014; Contreas et al., 2010). These determinants range from observed household and individual characteristics (Fadayomi et al., 2014), to the geographic location of an individual (Naudé and Serumaga- Zake, 2010), to the type and distribution of employment options (labor demand) in the local area. In addition, individuals’ cultural setting as well as their inherent traits play a significant role in shaping their decisions regarding labor market participation and employment choices (Reimers, 1985; Attasoy, 2017; Wichert and Pohlmeier, 2010). For instance, wage employment tends to increase with age in Nigeria, but is non-linear, slowing down as workers approach retirement (Aminu, 2010; Anyanwu, 2013).

In Ghana, unemployment rates are higher among women (Baah-Boateng, 2014). Broeck and Kilic (2018), using cross-country data from Ethiopia, Malawi, Nigeria, Tanzania, and Uganda, similarly found that women are underrepresented in wage and self-employment, likely due to local norms that differentially affect their opportunities. Aminu (2010) also identified a positive relationship between and wage employment. Urban residence is associated with greater employment, owing to the larger capacities and job opportunities in these settings (Naudé and Serumaga-Zake, 2010). Male household headship, marital status and household size have all been found to improve employment outcomes (Sackey, 2005; Fadayomi et al., 2014). Giannetti and Andrei (2004) noted that household wealth serves as a positive driver of self-employment, as individuals may encounter fewer liquidity constraints when starting a business.

This study examines the drivers of labor market participation and employment choices, and how individual gender role attitudes and personality traits shape these decisions. We achieve this by pursuing the following specific objectives. First, we explore the gender differences in labor market outcomes. Second, we examine the determinants of labor market participation and employment choice (wage vs. self) in the absence of personality traits and gender role attitudes. Third, the study examines the effect of gender role attitudes and personality traits on these labor market outcomes, both with and without household, individual and geographic controls. Finally, we examine the interactions effects of gender role attitudes and personality traits and how individuals’ gender role attitudes could alter their inherent traits in making labor market participation and employment choices.

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While numerous studies have explored the roles of personality traits and gender role attitudes on labor market outcomes, most of these studies have focused on Western societies, and a few on Asia. However, there is notable absence of such studies in the Ghanaian context, rendering this paper crucial for Ghana and, by extension, Africa. This study explores the respective contributions of gender role attitudes and personality traits to labor market outcomes and examines their interactions within the context of a developing country.

Ghana is an interesting country to study for a number of reasons. Firstly, Ghanaian society is predominantly patriarchal, charactarized by strong cultural influences that govern daily life. Secondly, there are substantial disparities in labor force participation between men and women, with men’s participation being approximately 8 percentage points higher than that of women, largely attributed to cultural and gender role attitudes (DTDA, 2020). Thirdly, women in Ghana are disproportionately engaged in family and own-account work, with 31% of women involved in own-account work compared to 11% of men (GSS, 2014). They often opt for low-productivity jobs that provide flexibility for domestic chores (Owoo & LambonQuayefio, 2022). Lastly, the availability of household-level data, including genderdisaggregated information on labor market indicators, as well as personality traits and gender role attitudes, provides a vital context for this study. This dataset covers two independent regions in Ghana with diverse cultural background and gender perspectives.

We employ both descriptive and econometric approaches to achieve the study’s objectives. To understand the drivers of labor market participation decision, we use the multinomial logit (MNL) model with the dependent variable comprising three mutually exclusive categories: not in the labor force, employed, and unemployed. The choice between wage and self-employment is examined using the linear probability model (LPM).

The empirical results suggest that both gender role attitudes and personality traits significantly influence individuals’ decisions regarding labor market participation and employment choices in Ghana. In most cases, gender role attitudes tend to mask the effect of personality traits. The gender-disaggregated analysis shows that having at least secondary education is critical for selection into employment of a male, but not for females. Once the decision to participate in the labor market has been made, having at least secondary education becomes relevant for securing a wage job, irrespective of the individual’s gender.

The remainder of the paper is structured as follows: Section 2 presents a review of relevant literature, while Section 3 presents the data used in the analyses. In Section 4, we 3
outline the analytical approach, followed by Section 5, which contains a discussion of results encompassing both descriptive and empirical findings. Finally, Section 6 provides concluding remarks and implications of the study.

# **2. Literature review**

Sociologists and economists have recognized the potential effects of individual preferences, social norms, and institutional factors on gender inequality. Recently, the economics literature has witnessed a synthesis of these disciplines in an effort to better understand various economic outcomes. While data limitations and challenges in defining and measuring these concepts have historically hindered access to direct evidence of the relationship between cultural norms, personality traits, and economic outcomes, recent years have seen substantial progress in the operationalization of these concepts and a heightened emphasis on verifying their linkages (Bertrand, 2011). For instance, with respect to the effects of social norms, Giuliano (2004) found that living arrangements of U.S. families were affected by their cultural heritage; Fernandez and Fogli (2005) showed that the work and fertility choices of second-generation American women were affected by their ancestors’ country of origin; and in Italy, Ichino and Maggi (2000) show that job commitment was driven by place of birth, a proxy for cultural background. Other studies have established a clear connection between culture and economic outcomes, encompassing aspects such as savings behaviors (Knowles and Postlewaite, 2004) and labor force participation (Fortin, 2005; Scoppa and Stranges, 2019).

Jayachandran (2015) states that disparities in economic outcomes between men and women can be deeply rooted in cultural and social norms. Similarly, gender disparities in employment outcomes can be traced back to the pre-industrial era when greater body strength necessitated production specialization along gender lines (Boserup, 1970). These historical norms, originating from agrarian systems of the past, continue to exert significant influence in shaping gender roles and perpetuating labor market inequalities in contemporary times (Alesina et al. 2013; Hansen et al. 2015).

Gender role attitudes influence employment outcomes through the construction of an “ideal” family structure in which the allocation of labor and caregiving responsibilities within the family is done along gendered lines (Pfau-Effinger, 2012). These differences in perceived gender roles are an important determinant of gender differences in labor market outcomes (Fortin, 2005; Marianne, 2011). Corrigall and Konrad (2007) found that traditional gender roles 4
tended to reduce women’s working hours but had no effect on men. In some cases, women with or belonging to a household with traditional gender role attitudes opt to either withdraw from the labor market entirely and assume only family functions (Fortin 2015), or reduce their working hours to make room for domestic chores. The consequence of these choices is an expanding income gap between men and women (Stickney and Konard, 2007; Judge and Livingston, 2008).

While much of the early literature has focused on the role of education and cognitive skills on labor market outcomes, there is a growing view that personality traits and noncognitive skills also play an important role in driving these outcomes (Campbell, 2000; Hatak et al., 2015; Hahn et al., 2012; Fay and Frese, 2001). Personal initiative generally refers to employees’ behaviors at work that are characterized by a self-starting nature, a proactive approach, and persistence in overcoming difficulties that arise in the pursuit of objectives (Fay and Frese, 2001). Personality traits directly affect employment outcomes by increasing employees’ performance and determining their positions within workplace social networks. Wichert and Pohlmeier (2010) analyze the role of personality traits in women’s labor market participation in Germany and show that they play an important role, with particular channels of effects dependent on specific traits. They conclude that neglecting the role of non-cognitive skills may inadvertently exaggerate the effect of education and cognitive skills.

Further, Jencks (1979) found that non-cognitive traits are at least as important as cognitive traits in explaining employment success and earnings in the United Kingdom. Heckman et al. (2006) also show that self-esteem and locus of control strongly affect employment status in the United States. Kuhn and Weinberger (2002) also find that leadership skills improved labor market outcomes in the US. Drawing from data in Britain, Carneiro et al. (2007) established that social skills gained by age 11 had positive implications for future employment status. In Germany, Heineck and Anger (2010) showed that people with higher external locus of control (i.e., where they tend to attribute success or failure to external circumstances rather than to individual effort) earned less. Nyhus and Pons (2005) found extraversion and agreeableness traits to be correlated with lower earnings among the Dutch population.

Scholars have suggested that personal initiative has two forms, task- and relationshiporiented personal initiative (Hahn et al., 2012; Bolino and Turnley, 2005; Fay and Frese, 2001). Task-oriented personal initiative encourages workers to obtain task- and job-related knowledge and skills. In contract, relationship-oriented workers are more inclined to leverage social 5
resources to exploit opportunities. They are more capable of network formation and information collection, as well as network contacts monitoring (Shane and Nicolaou, 2015), which facilitates the assessment, procurement, and use of resources, all contributing to entrepreneurial success. In summary, personality traits significantly influence labor market outcomes, and the nature of these traits (i.e., task-oriented versus relationship-oriented) may be important in determining the types of work (i.e., paid work, self-employment) that both men and women engage in.

# **3. Data and descriptive statistics**

# **3.1. Data**

The paper uses data from the Ghana Informal Sector Measurement Study conducted from September to November 2022 by the World Bank and the Institute of Statistical Social and Economic Research (ISSER) of the University of Ghana. The survey contains rich information on household and individual demographics, and economic, social and geographic variables. In addition, the survey includes valuable information on individual gender role attitudes and personality traits, allowing for exploring the drivers of labor market participation and employment choice, and understanding the unique roles that gender role attitudes and personality traits play in shaping these decisions.

The survey adopted a multi-stage sampling approach where the first stage involved the purposive selection of districts within the Ashanti and Northern regions of Ghana. In the Ashanti region, Asokore Mampong, Asokwa, Kumasi Metropolitan Area (Bantama, Manhyia North, Manhyia South, Nhyiaeso and Subin municipals), Kwadaso municipal, Oforikrom, Old Tafo municipal and Oforikrom municipal were selected, while the Sagnerigu, Tamale Central, Tamale South, Central Gonja, North East Gonja, Gushiegu, Kumbungu, Mion, Nanton, Savelugu and Tolon were selected in the Northern region for the study. Following the purposive selection of these districts, the second stage involved the random selection of 134 enumeration areas (EAs) from these districts using probability proportional to size (PPS). All the districts and EAs in Kumasi were urban, while the Northern region covered both urban and rural EAs. The purposive selection of the districts was driven by the study’s objectives, which is to gain insights into informality in general, and rural agribusiness development, particularly in the northen region.

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Following the selection of the EAs, a fresh household listing was conducted, and 15 households were then randomly selected from each EA and interviewed for the study. This gave a total of 2,000 households and over 7,700 individuals. Labor-related data were collected for individuals aged 15 years and older, in accordance with the legal employment age in Ghana. Overall, 4,497 individuals successfully provided this information. Gender role attitudes and personality traits information was collected only from individuals that were available and able to answer for themselves during the survey. Within each household, up to 4 individuals aged 15-64 were randomly selected to provide gender roles attitudes and personality traits information. Given that one of the primary study objectives was to investigate the impact of gender role attitudes and personality traits on labor market participation and employment choices, we further restricted the sample to include only individuals aged 15 years or older who provided complete information on gender role attitudes and personality traits modules. This additional restriction resulted in an analytical sample of 2,478 individuals. In the subsequent analyses and results, the 4,497 individuals constitute the _full survey sample_ , while the 2,478 restricted sample constitutes the _analytical or pooled sample_ .

# **3.2. Definition and construction of analytical variables**

Table 1 outlines the definitions of variables used in the analysis. The demographic variables are those found in the literature to be main drivers of labor market participation and employment choice (Baah-Boateng, 2014; Contreas et al., 2010; Naudé and Serumaga- Zake, 2010). In this section, we provide additional clarity on the construction of some of these variables. An individual (15 years or older) is classified as employed if they worked for at least one hour in the 7 days prior to the day of interview or have been temporarily absent from their job. _Self-employed_ pertains to individuals (> 15 years of age) who either operate their own business or contribute to another household member’s business. _Wage employment_ refers to working for pay as an employee, trainee or intern for someone else outside the household.

Asset-based wealth quintiles were constructed from household ownership of durables including furniture, sewing machine, stove, fridge and freezer, fan, radio, computer, TV, vehicles, among others. A principal component analysis (PCA) technique was used to categorize households into one of five (5) asset-based wealth quintiles- poorest, poorer, middle, richer, richest. This was further reclassified to poor (comprising poorest and poorer quintiles) and non-poor (i.e., middle, richer, richest) households.

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In the survey, up to 4 individuals were randomly selected in each household to answer a total of fourteen (14) questions on gender role attitudes (see Table 1). Response options were strongly disagree-1, disagree- 2, neutral-3, agree-4, or strongly agree-5. An index for gender role attitudes was constructed from these responses following Guiso (2006), Kling et al. (2007), and Friedman et al. (2011). First, all answers were recoded so that higher values correspond to more traditional beliefs. Second, z-scores were generated for each variable entering the index using the mean and standard deviation. Third, the index was created by calculating the means of these z-scores. Finally, the gender role attitudes index was standardized to take on a value between 0 and 100, with higher scores indicating more traditional inclinations.

Like the gender norms variable, the personality traits questions (28 questions in all) use Likert scale response categories. Following Laajaj and Macours (2017), nine personality groups – locus of control, work centrality, tenacity, polychronicity, impulsiveness, achievement, power motivation, organization, and optimism – were constructed from these 28 questions. Each personality group is a simple average of all related traits (see Table 1 for associated personality groups and traits).

# **3.3. Descriptive results**

# **3.3.1. Description of study variables**

Table 2 presents descriptive statistics for the analytic sample for all study variables, i.e., outcome, main explanatory variables and controls (see Table A1 in the appendix for similar results for the pooled sample). The table shows that about two-thirds of the sample is employed, with no significant difference between men and women. About 5% of both men and women are unemployed, while about 27% of individuals are _not in the labor force_ , with slightly higher estimates for men compared to women. There are significant differences in wage and selfemployment between men and women – more women are represented in self-employment, compared to men (52% vs. 33%), while more men are in wage employment, compared to women (35% vs. 15%). The distribution of employment found in this study differs from that of the AHIES (2022), even after restricting the AHIES sample to Ashanti and Northern regions. This could be explained by the differences in sample design and the objectives of the two studies; the current study was designed to provide information on employment and informality in the regions while the AHIES focuses on providing income and expenditure information, with limited emphasis on employment and informality.

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The average age of individuals in the analytic sample is about 37 years. Forty-four percent of the sample is male, and about 61% are either married or cohabiting. About 65% of the sample have at least a secondary education, with a slightly higher percentage for men (69%) compared to women (61%). The table also shows that 71% of the respondents live in maleheaded households, with only about 28% of them living in female-headed households. In addition, 53% of the sample are Muslims, while the remainder are Christians. In almost 60% of cases, individuals’ spouses are present in the household. Using the asset index described earlier, about 32% of individuals in the sample belong to poor households. The average household has about 4 members, and over 80% of individuals reside in urban areas. More respondents were sampled from the Ashanti region (56%), compared to the Northern region (44%).

# **3.2.1. Decomposition of labor market outcomes**

This section presents subgroup decomposition of employment and labor market outcomes by education, gender of respondents, rural/urban residence, regional residence, and household poverty status (Table 3). Using education backgrounds of respondents, a higher proportion of educated workers are employed (72%), compared to the less educated people (61%). A higher percent of educated people are in wage employment (32%). A substantial proportion of less educated individuals are involved in self-employment (40%). Thirty-five percent of the less educated are not in the labor force, compared to 23% of the highly educated. With respect to gender, we do not see much difference in labor market outcomes between men and women. However, women appear to be more represented in self-employment (52% vs. 33%), while men are more likely to engage in wage work (35% vs. 15%).

With respect to residence, more urban residents are employed (71%), compared to their rural counterparts (47%). A larger percentage of both rural and urban respondents are in self-, compared to wage-employment. A higher proportion of rural dwellers are _not in the labor force_ (51%), compared to urban counterparts (23%). Disaggregated by poverty status, employment appears higher in non-poor households (75%), compared to poor households (53%), with a larger percentage of people in poor households not being in the labor force (40%). While both groups are similarly represented in self-employment, only 14% of individuals from poor households are in wage employment. Finally, regional differences are also observed, with employment being higher in the Ashanti region (73%), than in the Northern region (61%).

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Figure A1 in the appendix presents the gender-disaggregated distribution of employment outcomes across the two study regions for the _analytic_ and _main survey_ samples.

The average man in the analytic sample is significantly more traditional than the average woman (Table 4). This is because the average gender role attitudes index for the 1,103 men was 42.75, compared to the average of 40.31 for the 1,375 women questioned on their gender norm perceptions (see Table 1). The table shows the proportion of sampled men and women in the various households who agreed with different statements relating to gender role attitudes. Average gender norm indices are shown in parentheses below the percentages. The last column depicts the significance of differences in responses given by men and women.The table shows in general that both gender agree women should perform household chores, care for children and dependents, while men should manage women workers on the farm (over 95% of both gender agree). That notwithstanding, we see significant differences between men and women with respect to making all important business and financial decisions.

A summary of the answers to the questions on personality traits for men and women in the survey is presented in Figure 1. On average, men tend to show higher averages than women with most traits e.g., enjoyment in planning activities that others do, enjoying having influence over people, etc. The only exceptions are with respect to being organized and an affinity for multitasking, where women report higher preferences than their male counterparts. Women and men display similar traits with respect to planning tasks carefully (92%); enjoyment with improving past performance (86%); as well as expecting the best in uncertain times (77%). About two-thirds of the respondents – men and women – reported a lack of confidence in identifying genuine friendships; were hesitant about trying new things; and disliked juggling different things at the same time.

Table 5 presents the mean difference test for the personality groups as well as gender role attitudes index for the analytic sample. Differences in gender role attitudes between men and women are highly statistically significant, with men being more traditional than women (see Table 3). There are significant differences in personality groups between men and women as well. While men and women show similar levels of impulsiveness and optimism, men have higher measures of work centrality, compared to women. Men are also more tenacious, have a higher desire to achieve, and also have stronger power motivations. Women, on the other hand, demonstrate higher levels of polychronicity, have greater desire for control in their lives and businesses, and also show greater strengths in being organized, compared to their male counterparts.

10
# **4. Empirical approach**

A random utility framework (Greene 2008) is used as the empirical approach to examine the drivers of labor market participation, and the effects of personality traits and gender role attitudes on an individual’s decision to participate in the labor market (i.e., not in the labor force, employed, unemployed) and the type of employment chosen (wage or self). In this approach, two layers of decisions have to be made by the individual – first, participate in the labor market, and then once the employment decision has been made, they will have to decide on the type of employment.

on the type of employment. Let i denote the utility an individual gains from participating in the labor market and i represent the utility of not participating. Let ∗ denote an indicator function that UU ii jj conditions participation such that the individual participates in the labor market if the utility ii UU EE gained from participating is larger than the utility from not participating: ∗ i i > 0 and otherwise if ∗ i i ≤0, for all . Here we denote ii as the base EE = UU − UU category to represent “not in the labor force”, while j = 1,2 represent being in the labor force ii EE = UU − UU jj≠kk kk= 0 as employed (1) or unemployed (2). The actual observed participation decision, conditional on personality traits ( ), gender role attitudes ( ), interactions effects of personality traits and gender role attitudes (ii P ii PP GG ii<sup>)</sup><sup>**,**and other household and individual characteristics (CC</sup> ii<sup>) is:</sup> (1) ii ii ii ii<sup>δδ+ CC</sup> ii<sup>γγ+ εε</sup> ii Once the decision to participate is made, the second stage decision, type of employment (EE = αα+ PP ββ+ GG φφ+ P E ), is similarly modeled as: E (2) ii ii ii ii<sup>ψψ+ CC</sup> ii<sup>φφ+ ee</sup> ii where = μμ+ PP λλ+ GG ΦΦ+ P are parameters to be estimated, and are error terms with binomial distributions, while **,** , P ii ii αα, ββ, φφ, δδ, γγ, μμ , λλ , ΦΦ, ψψ, φφ εε ee ii ii ii<sup>**,**and CC</sup> ii<sup>are as defined above.</sup> Equation 1 is estimated using a multinomial logit model (MNL), with the dependent PP GG variable taking the value of 0 if the individual does not participate in the labor market, 1 if the individual participates and is employed, and 2 if the individual participates and is unemployed. The second equation is estimated using a linear probability model (LPM) where the dependent variable takes the value of 1 if the individual has a wage work, but 0 if self-employed. The second equation is estimated only for individuals that have category 1 in the first-stage decision model.

11
The effects of personality traits on labor market participation and employment type decisions are captured by the parameters and , respectively, while and represent the parameters for gender role attitudes. Interaction terms are also included to explore the ββ λλ φφ ΦΦ moderating effects of personality traits on the link between gender role attitudes and employment outcomes, captured by the parameter and for equations 1 and 2 respectively. Equations 1 and 2 are estimated first for the pooled sample, and then separately for men and δδ ψψ women. The dependent variables in each of the two equations contain mutually exclusive categories.

Although studies of this nature usually require considering endogeneity caused by potential reverse causality, this is not necessarily the case for the present study. This is because individual gender role attitudes and personality traits are shaped in childhood or adolescence as a result of early socialization (Platt and Polavieja, 2016), which occurs prior to labor market engagement. Additionally, gender role attitudes and personality traits may persist over long periods of time (Voigtlander and Voth, 2012). Though not unalterable, most individuals’ gender role attitudes remain remarkably constant through life (Schober and Scott 2012). Given these arguments, it is reasonable to assume that an individual’s gender role and inherent personality traits affect labor market outcomes and not the other way round. Thus, the use of MNL and LPM is enough at examining the drivers of labor market outcomes, including the roles of gender role attitudes and personality traits in shaping these outcomes.

# **5. Empirical results**

This section presents the empirical results from the multinomial logit and the linear probability models. We first estimate the MNL and LPM equations including individual and household characteristics as covariates to understand the drivers of labor market participation and employment choice in the absence of gender role attitudes and personality traits. We then proceed to estimate twelve different specifications (Tables 8-13 ) for both MNL and LPM regressions from equations (1) and (2) presented in the empirical approach. In the first specification, naïve regressions are run to examine the effects of gender role attitudes alone on employment outcomes. In the second specification, the effects of gender role attitudes on employment outcomes are examined once other control variables are included in the regressions. Specification three adds personality traits to the prior specification. In the fourth to twelfth specifications, the full set of controls are included, as well as simultaneous 12
interactions of gender role attitudes with each of the nine (9) personality trait variables. For each specification, separate regressions are run for men and women.

# **5.1. Drivers of labor market participation and employment choice, no gender role attitudes and personality traits**

The MNL and LPM regressions of the determinants of labor market participation and employment choice, excluding personality traits and gender role attitudes, are presented in Tables 6 and 7 respectively. Here we use all individuals in the main sample (4,497) prior to restricting to only those that have information on gender role attitudes and personality traits. In the pooled sample results (Table 6), we see that the odds of employment, compared to not being in the labor force, do not differ significantly between men and women, although the odds of unemployment are lower for men (Glik and Sahn, 1997; Fadayomi et al., 2014; Naudé & Serumaga-Zake, 2010). This means that men are less likely to be unemployed, compared to not being in the labor force. One possible reason could be that fewer job opportunities are available to women. Formal job search channels are often more beneficial to men (Huffman & Torres, 2001), and informal channels contribute to the perpetuation of gender biases (Drentea, 1998; Affum-Osei et al., 2019). Another reason is that men may be taking over more jobs formerly thought to be in women’s domain (e.g., trading), and therefore crowding them out (Overa, 2005). Finally, supply side factors may also lead to higher unemployment among women including domestic responsibilities, own or spouses’ traditional attitudes about work outside the home, as well as culturally conditioned low work/career aspirations (Glick and Sahn, 1997).

The odds of employment are higher with age, though the relationship is non-linear, decreasing after a certain point (Glick and Sahm, 1997). Being married increases the odds of employment, compared to not being in the labor force. According to Glick and Sahn (1997), married women may be better able to secure capital through their husbands to start up small businesses, or use their husband’s connections to obtain wage employment. Marriage may not necessarily be an exogenous determinant of employment for men, as men may have secured employment before marriage. Other factors that are positively correlated with employment include education (Baah-Boateng, 2015) and residing in a household that is headed by a male (Fadayomi et al., 2014; Hussain et al., 2016). The presence of a spouse in the household reduces the odds of employment only among men, with no significant effect in the women sample. Individuals living in poor households have lower odds of being employed (Baah-Boateng, 13
2015); both in the pooled sample and the gender-disaggregated independent samples. Urban residence increases the odds of employment in all samples (Contreras et al., 2011; Naudé & Serumaga-Zake, 2010) although opposite effects have been observed in the literature (Fadayomi et al., 2014). Similarly, residence in the Ashanti, rather than the northern region, is associated with higher odds of employment for the male sample. A closer look at the genderdisaggregated results indicates that men who have at least high school education, and reside in male-headed households are more likely to be employed, which is not the case in the female sample.

With respect to the second stage decision of choosing between self- vs. wageemployment, the probability of the latter are higher among men, compared to women (pooled sample column of Table 7). Other factors that are associated with higher probability of wage employment among both men and women include education and urban residence, while being Muslim (H’madoun, 2010) and residing in a large household lowers the probability in both groups. Residing in a male-headed household increases the likelihood of wage employment among men, while having a spouse present in the household has the reverse effect.

# **5.2. MNL regression results of labor market outcomes and traditionalism, personality and other controls**

The _pooled sample_ results of the effects of gender role attitudes and personality traits on labor market participation decisions are presented in Table 8. The naïve regression of traditionalism on employment indicate a negative correlation (specification 1) that is retained even after controlling for other individual, household and geographic characteristics (specification 2). Results from the interactions between traditionalism and personality traits indicate that among less traditional individuals, traits such as work centrality (5) and high achievement (9) are positively associated with being employed, while high internal locus of control (8) has a negative significant effect on employment. The additional effect of being more traditional, however, masks the significant effects of work centrality and high achievement, and reverses the effects of high locus of control on employment. Although individual personality traits such as power motivation (10) and optimism (12) have no statistically significant effect on a less traditional person being employed, these traits appear to be negatively and positively associated with employment, respectively, among more traditional individuals. In the presence of personality traits and gender role attitudes, the results show 14
further the relevance of education, age, marital status and urban residence in determining an individual’s participation in the labor market as employed. On the contrary, the presence of the spouse in the household and the poverty status of the household limit the employability of an individual.

The MNL model result of the _women sample_ (Table 9) show that females who are more traditional are less likely to be employed, compared to being out of the labor force. Unlike the pooled sample, the inclusion of other control variables does not change the negative sign of traditionalism, but instead, renders it not significant. Among less traditional women, work centrality (5), tenacity (6) and high achievement (9) are positively associated with being employed following participation in the labor force. The importance of these traits, however, dampens with increasing traditionalism. Although a woman’s optimism by itself plays no significant role in their employment outcome (first half of specification 12), it does positively influence their selection into employment when combined with traditionalism. In the presence of traditionalism and personality traits, women who are older and residing in an urban area have higher odds of employment. Residing in a poor household has a reducing effect on the likelihood of a woman being employed.

Table 10 contains the MNL results of the _men sample._ Here again we see the negative effect of increasing traditionalism on the odds of a man being employed compared to them not being in the labor force. The significant association is retained even when other factors are controlled for (2). Results from the interaction of gender role attitudes and personality traits indicate that among less traditional men, a high internal locus of control has a negative significant effect on their likelihood of being employed (8). Traditionalism appears to positively influence a man with high internal locus of control’s selection into employment, all things being equal. As in the female sample, the inclusion of gender role attitudes and personality traits jointly with other control variables indicate that older men who are married, have at least secondary education, and are residing in male-headed households are more likely to be employed. In addition, religion and the geographic location of a male respondent play vital roles in their employment choice; Muslims and urban dwellers have higher odds of employment. Other factors like spousal presence and household poverty status are, however, negatively associated with employment odds.

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# **5.3. LPM results of wage versus self-employment on traditionalism, personality and other controls**

Following the decision to participate in the labor market, Tables 11-13 present the results of the LPM on the type of employment – self or wage – that an individual engages in. Similar to the first stage participation decision, the analysis was conducted first for the pooled sample and then separately for the gender-disaggregated samples. The dependent variable here takes a value of 1 if the individual worked in a wage employment and 0 if they were in selfemployment.

The _pooled sample_ results (Table 11) indicate that gender role attitudes have no significant effect on the probability of an individual being employed in a wage work, which is maintained even after controlling for household, individual, and geographic characteristics. On the personality traits, we find that high achieving and organized individuals are more likely to have a wage job. On the contrary, impulsive individuals are less likely to participate in a wage work. When we control for household, individual, and geographic characteristics as well as high achieving and organized traits, the results show that traditionalism positively influences the individual’s wage employment choice. The interaction of gender role attitudes and personality traits show that traditionalism reverses the directional effect of impulsiveness and being organized; impulsiveness becomes positive while being organized tends to have a negative effect on the wage employment choice. In all specifications that include other control variables, we see that male individuals with at least secondary education, who live in predominantly male-headed households and reside in urban areas are more likely to have a wage job. Conversely, individuals who are Muslims, live in large households, and whose spouses are present in the household are less likely to have a wage job; they are more likely to be engaged in self-employment, instead.

In the naïve model of the _female sample_ in Table 12, we see that traditionalism has a negative significant effect on the probability of a woman’s wage employment. This effect, though maintained after controlling for impulsiveness and other individual and household characteristics, is reversed with the inclusion of the trait of being organized. The results show further that except for impulsivesness that tends to lower the likelihood of a woman’s selection into a wage job, none of the other personality traits by themselves are vital in explaining the wage/self-employment choice. Bringing together gender role attitudes and personality traits show that traditional women who are impulsive and more organized have a lower and higher probability, respectively, of being self-employed, compared to landing a wage job. From the 16
other controls, we observe that women who have at least secondary education and live in urban areas are more likely to work in a wage job, while Muslim women are more likely to be selfemployed.

In Table 13, we present the results of the _male sample_ of the linkage between gender role attitudes and personality traits, and a man’s choice of wage or self-employment. The results show that traditionalism has a negative significant effect on the probability of a man being employed in a wage job. This finding, is not retained after controlling for all personality traits and other covariates, except when we control for a man’s trait of impulsiveness and other covariates (column 11). In the fully controlled model (personality traits, gender role attitudes, and other covariates), men with high work centrality, high internal locus of control, and who are organized are less likely to work in a wage employment, while high achieving men are more likely to do so. In the simultaneous interactions models, we observe that traditional men who have high internal locus of control and are well organized are less likely to have a wage job (column 8 & 11). In the presence of gender role attitudes and other household, individual and geographic characteristics (column 11), men who are well organized are more likely to have a wage job, though traditionalism tends to gravitate them towards self-employment. Finally, the results show that education has a positive significant effect on male wage employment, which is consistent with the results in the female and pooled samples. Additionally, a Muslim man who lives in a large household in which his spouse is present is less likely to be working on a wage job.

Findings that traditionalism is negatively related with labor market participation is consistent with other works that find cultural norms to be barriers, particularly to women’s employment (Jayachandran, 2021; Munoz- Boudet et al., 2013). Traditionalism is also negatively associated with wage employment, compared to self-employment, despite the often lower returns from the latter in the Ghanaian setting (Oyenubi, 2019). For women, this may be because cultural expectations of domestic work and child care may be easier to combine with self-employment, given the greater flexibility. Personality traits also affect labor market participation and employment choices, consistent with existing work (Wichert and Pohlmeier; 2010; Heckman et al., 2006; Heineck and Anger, 2010). Interaction effects from this study indicate that these positive associations are sometimes dampened by higher traditionalism.

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# **6. Conclusions and implications**

The paper explores the determinants of labor force participation (i.e., employed, unemployed, not in the labor force) and employment type choice (wage vs. self), with a focus on the role played by gender role attitudes and personality traits using multi-topic household survey data collected in two regions – Ashanti and Northern – of Ghana. The study uses both descriptive and econometric analytical approaches. The econometric approach employs multinomial logit and linear probability models to examine the drivers of labor market participation and employment choice, respectively.

The descriptive results indicate that employment is higher among educated individuals, and those that live in urban areas and non-poor households. Self-employment is more prevalent than wage employment in the study area, and more common among women than men. The gender disaggregated descriptive comparison shows that men are more traditional, compared to their female counterparts. While some personality traits are more prevalent among men (work centrality, tenacity, achievement and power motivation), others are more dominant among women (i.e., polychronicity, locus of control and organization skills).

The empirical results in general show that the main drivers of labor market participation and employment choice include the age and education level of an individual, geographic location of the household, gender of the head, and poverty status of the household. In terms of the choice between wage and self-employment, the results show that individuals who have at least secondary education who live in male-headed households, and reside in urban areas are more likely to be employed in a wage job. On the contrary, Muslim individuals who live in large-sized households are more likely to be self-employed. In the gender disaggregated analysis, the results show that the education level of an individual is vital in shaping their decisions to be employed in wage jobs, while Muslim men and women are more likely to be self-employed. In addition, women who live in urban areas are more likely to land a wage job than those that live in rural areas. We also find that while the presence of a man’s spouse in the household motivates him to embark on self-employment work, this does not matter in the female sample.

Turning to personality traits and gender role attitudes, the empirical results show that both personality traits and gender role attitudes are vital in explaining labor market participation and the type of employment in the study area. Among the male sample, the results show that men with high locus of control have lower odds of being employed, while for women, 18
having work centrality, tenacity, and optimism traits increase their likelihood of employment. Interactions of gender role attitudes and personality traits, however, make some of these traits lose their significant effects, especially for women deciding on being employed.

The study also found the significant roles played by individual traits in the nature/type of employment (i.e., wage vs. self-employment) that women and men engage in. For men, being organized increases their likelihood of wage employment outcomes, although traditionalism tends to reverse this effect. Among women, impulsiveness appears to reduce their likelihood of of being employed in wage jobs. Like the results for males, traditionalism tends to reverse the direction of impact such that traditional and impulsive women have higher probability of being employed in wage jobs. These results, in general, suggest that while personality traits play an important role in observed employment outcomes, these effects are often dampened or reversed with increasing traditionalism.

Employment policies may need to focus on the development of soft skills in order to improve labor force participation and employment in the Ghanaian settings. Additionally, labor market policies that address certain constraits facing women and other general work should be encouraged. Policies that improve access to education and child care are also recommended.

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**Figure 1.** Differences in Personality Traits by Men and Women, _Pooled_ Sample (weighted)

<!-- Start of picture text --> Experience more good things<br>Complete present task before start another<br>Plan tasks carefully<br>Look forward to work<br>Very competitive<br>Optimistic<br>Organised<br>Complete entire project<br>Enjoy improving past performance<br>Risks equal riches<br>Important things happen at work<br>Work hard despite opposition<br>Persist when others quit<br>Expect the best despite uncertainty<br>Important to outperform others<br>Control over events around me<br>Excel despite low popularity<br>Save regularly<br>Things go my way<br>Make up mind quickly<br>I enjoy planning what others do<br>Good things expected to happen to me<br>I like having influence over people<br>Take lead in planning grp activities<br>Things don’t often go wrong<br>Juggle several activities<br>Try things not sure of<br>Not difficult to know true friends<br>0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1<br>Men Women<br><!-- End of picture text --> 23
**Table 1.** Description of Variables

|**Variable**|**Definition**|
|---|---|
|**_Outcome Variables_**||
|Employed|Individual (>15 years of age) has worked in the past 7 days or temporary absent:<br>•<br>worked for a wage, salary, commission, other pay (incl. in-kind) for someone who is not a member<br>of your household for at least an hour;<br>•<br>managed a non-farm enterprise of any size that belongs to person for one or more hours;<br>•<br>worked in a non-farm enterprise owned by the household for one or more hours;<br>•<br>Worked/helped on a farm owned or rented by a household member for at least an hour?<br>•<br>Products were not (mainly/only) for household use|
|Unemployed|Individual (> 15 years of age) has not worked in the past 7 days, is not temporary absent, but is actively<br>looking for one<br>•<br>During the last four weeks, person did something to find a paid job<br>|
||•<br>During the last four weeks, person tried to start a business|
|Not in the Labor Force|<br>Individual(> 15years of age)has not worked in thepast 7 days and does not activelylook for ajob|
|Self-Employment|Individual (> 15 years of age) whose main activity is self-employed or working for someone else in the<br>household<br>•<br>Main job is in own business or farming activity<br>•<br>In a business or farm operated by a household member|
|Wage Employment|<br>Individual (> 15 years of age) whose main activity is working as an employee, trainee or intern for<br>someone else outside of the household|
|**_Main explanatory variables_**||
|Gender role attitudes Index|A Z score index derived from responses to 14questions ongender role attitudes|
|Personalitytraits|Responses: Stronglyagree/Agree/ Neither agree nor disagree/disagree/ stronglydisagree|
|Impulsiveness|Iplan tasks carefully (_reverse coded_);I make upmymindquickly;I save regularly (_reverse coded_)|
|Work centrality|I look forward to returning to my work when I am away from work;<br>The most important thing that happens in life involves work.|
|Tenacity|I can think of many times when I persisted with work when others quit;<br>I continue to work on hard projects even when others oppose me.|
|Polychronicity|I like to juggle several activities at the same time;<br>I would rather complete an entire project every day than complete parts of several projects (_reverse_<br>_coded_); I believe it is best to complete one task before beginning another (_reverse coded_)|
|Locus of control|It is difficult to know who my real friends are (reverse code); I never try anything that I am not sure of<br>(reverse code); A person can get rich by taking risks.|
|Achievement|It is important for me to do whatever I’m doing as well as I can even if it isn’t popular with people<br>around me; Part of my enjoyment in doing things is improving my past performance; When a group I<br>belong to plans an activity, I would rather direct it myself than just help out and have someone else<br>organize it; I try harder when I’m in competition with other people; It is important to me to perform<br>better than others on a task.|
|Power motivation|I enjoy planning things and deciding what other people should do; I find satisfaction in having influence<br>over others; I like to have a lot of control over the events around me.|
|Organized|Myfamilyand friends would sayI am a veryorganizedperson.|
|Optimism|In uncertain times I usually expect the best; If something can go wrong for me, it will (_reverse coded_);<br>I’m always optimistic about my future; I hardly ever expect things to go my way (r_everse coded_); I<br>rarely count on good things happening to me (_reverse coded_); Overall I expect more good things to<br>happen to me than bad.|
|**_Control variables_**||
|Male|Dummyvariable(=1)if individual is male|
|Age|Age inyears|
|Married/ cohabiting|Married(monogamous/polygynous)or livingwith apartner|
|Secondaryeducation|Has completed at least a secondaryschool education|
|Male household head|Household head is male(as opposed to female)|
|Muslim|Belongs to Muslim religion(as opposed to Christian)|
|Spouse ispresent|Spouse lives in the household|
|Household size|Number of household memberspresent|
|Poor|Belongingto thepoorest andpoorer asset-based wealthquintiles|
|Urban residence|Household is located in urban area(as opposed to rural area)|
|Ashanti region|Household is located in Ashanti region|

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**<u>Table 2.</u>** <u>Descriptive statistics of analytical variables (</u> _<u>weighted</u>_ <u>)</u>

||**Pooled S**<br>**_Mean_**|**ample**<br>**_SD_**|**Women**<br>**_Mean_**|<br>**_SD_**|**Men**<br>**_Mean_**|**_SD_**|**_T-tests_**|
|---|---|---|---|---|---|---|---|
|**_Outcome Variables_**||||||||
|Employed|0.68|0.47|0.68|0.47|0.68|0.47|0.030|
|Unemployed|0.05|0.23|0.06|0.23|0.05|0.21|0.010|
|Not in the labor force|0.27|0.45|0.27|0.44|0.28|0.45|-0.040**|
|Self-employment (self/family)|0.44|0.5|0.52|0.5|0.33|0.47|0.191***|
|Wage employment|0.24|0.43|0.15|0.36|0.35|0.48|-0.167***|
|**_Demographic variables_**||||||||
|Male|0.44|0.5|-|-|-|-|-|
|Age|36.6|12.09|36.63|12.35|36.56|11.75|-0.314|
|Married/ cohabiting|0.61|0.49|0.62|0.49|0.6|0.49|0.019|
|At least secondary education|0.65|0.48|0.61|0.49|0.69|0.46|-0.0921***|
|Male household head|0.72|0.45|0.56|0.5|0.94|0.24|-0.343***|
|Muslim|0.53|0.5|0.49|0.5|0.58|0.49|-0.0757***|
|Spouse is present|0.59|0.49|0.57|0.5|0.62|0.49|-0.0593**|
|Household size|4.1|2.56|4.29|2.46|3.87|2.67|0.342**|
|Poor|0.32|0.47|0.3|0.46|0.35|0.48|-0.0464**|
|Urban residence|0.86|0.35|0.88|0.32|0.83|0.38|0.0635***|
|Ashanti region|0.56|0.5|0.6|0.49|0.52|0.5|0.0788***|
|Observations|2,478||1375||1103|2478||

* p<0.10, ** p<0.05, *** p<0.01

25
**Table 3.** Differences in labor market outcomes by different subgroups ( _weighted_ )

||**Labor Force**|**Participation**|**Proportion of E**|**mployed**||
|---|---|---|---|---|---|
||**Employed**<br>**(%)**|**Unemployed**<br>**(%)**|**Not in Labor**<br>**Force**<br>**(%)**|**Self-**<br>**employment**<br>**(%)**|**Wage**<br>**employment**<br>**(%)**|
|Secondary or higher|72|6|23|40|32|
|Less than secondary|61|4|35|52|10|
|Female|68|6|27|52|15|
|Male|68|5|28|33|35|
|Rural|47|2|51|39|9|
|Urban|71|6|23|45|26|
|Non-poor|75|5|21|46|29|
|Poor|54|6|40|41|14|
|Northern region|61|4|35|44|17|
|Ashanti region|73|7|21|44|29|

26
**Table 4.** Differences in perceptions of gender roles by men and women ( _weighted_ )

||N**Gender role attitudes (Proportion Agreeing with**<br>**Statements)**|**Women**<br>_(Average_<br>_index)_|**Men**<br>_(Average_<br>_Index)_|**Test of**<br>**differences**|
|---|---|---|---|---|
|1.|Only men should work outside the home|0.255<br>(_47.79_)|0.253<br>(_50.60_)|-0.016|
|2.|It is not okay for women to work outside of the home, even if<br>she has young children less than 5 years|0.206<br>(_46.04_)|0.252<br>(_50.10)_|-0.042**|
|3.|Men should not perform household chores|0.291<br>(_47.20)_|0.316<br>(_50.97_)|-0.038**|
|4.|Women should perform household chores|0.977<br>(_40.49_)|0.975<br>(_43.10)_|-0.002|
|5.|Men should not care for children/dependents|0.087<br>(_55.16_)|0.110<br>(_61.06_)|-0.020*|
|6.|Women should care for children/dependents|0.965<br>(_40.66_)|0.941<br>(_43.36_)|0.019**|
|7.|Women are not as capable as men to manage workers.|0.053<br>(_58.85_)|0.126<br>(_60.09)_|-0.066***|
|8.|Women are not as capable (intellectually) as men of being<br>successful|0.065<br>(_58.86_)|0.108<br>(62.64_)_|-0.038***|
|9.|Men should make all the important business and financial|0.368|0.481|-0.113***|
||decisions in the family|(_47.24_)|(_48.67_)||
|10.|Women farmers should focus on growing food for the family|0.280<br>(_47.42_)|0.321<br>(_50.92_)|-0.042**|
|11.|It is not okay for a woman to grow crops for sale in the market|0.047<br>(_57.09)_|0.069<br>(_56.25_)|-0.015|
|12.|Only men should grow crops for sale in the market.|0.243<br>(_47.97)_|0.236<br>(_51.01_)|-0.007|
|13.|It is not okay for a woman to manage men working on her land|0.045<br>(_55.57_)|0.106<br>(_58.39_)|-0.049***|
|14.|It is okay for a man to manage women working on his land|<br>0.949<br>(_40.51_)|<br>0.948<br>(43.09_)_|-0.002|
||Standardized Index|40.31|42.75|-2.50***|
||# Observations|1,375|1,103||

average gender norm index in parenthesis: * p<0.10, ** p<0.05, *** p<0.01 27
**Table 5** . Distribution of gender norm index and personality <u>groups, by men and women (</u> _weighted_ <u>)</u>

||**Pooled S**<br>**_Mean_**|**ample**<br>**_SD_**|**Women**<br>**_Mean_**|<br>**_SD_**|**Men**<br>**_Mean_**|**_SD_**|**_T-tests_**|
|---|---|---|---|---|---|---|---|
|**_Main explanatory variables_**||||||||
|<br>Gender role attitudes index|41.38|11.12|40.31|10.06|42.75|12.22|-2.504***|
|Personality Groups||||||||
|<br>Impulsiveness|2.47|0.56|2.46|0.55|2.47|0.57|0.0095|
|<br>Work centrality|4.14|0.75|4.1|0.78|4.2|0.7|-0.0951***|
|<br>Tenacity|3.91|0.72|3.87|0.74|3.96|0.7|-0.0961***|
|<br>Polychronicity|2.13|0.67|2.15|0.69|2.09|0.64|0.0541**|
|<br>Locus of control|2.88|0.7|2.93|0.7|2.81|0.71|0.104***|
|Achievement|3.75|0.58|3.73|0.59|3.78|0.56|-0.0755***|
|Power motivation|3.35|0.81|3.28|0.83|3.44|0.79|-0.174***|
|Organized person|4.08|0.76|4.11|0.77|4.05|0.75|0.0779**|
|<br>Optimism|3.57|0.52|3.56|0.52|3.59|0.53|-0.0355|
|Observations|2,478||1375||1103|2478||

28
**Table 6.** MNL of employment outcomes, without gender role attitudes and personality traits

||(1)|(2)|(3)|
|---|---|---|---|
||Pooled sample|Women|Men|
|**Employed**<br>||||
|Male|-0.082|-|-|
||(-0.99)|||
|Age|0.321***<br>|0.346***<br>|0.248***<br>|
||(14.62)<br>|(13.13)<br>|(7.87)<br>|
|Age_sq|-0.004***<br>|-0.004***<br>|-0.003***<br>|
||(-14.00)|(-12.18)|(-8.28)|
|Married|0.684***|0.471***|1.410***|
||(5.51)|(3.27)|(5.03)|
|Secondaryeducation|0.429***|0.181|0.703***|
||(3.95)|(1.28)|(4.28)|
|Male head|0.322**|-0.528|1.248***|
||(2.05)|(-1.36)|(4.42)|
|Muslim|-0.001|-0.266|0.319|
||(-0.01)|(-1.36)|(1.57)|
|Spousepresent|-0.681***|-0.029|-0.885***|
||(-3.75)|(-0.07)|(-3.14)|
|Household size|-0.027|0.001|-0.039|
||(-1.52)|(0.07)|(-1.54)|
|Poor|-0.404***|-0.317**|-0.580***|
||(-3.29)|(-1.98)|(-3.67)|
|Urban|0.757***<br>|0.758***<br>|0.753***<br>|
||(4.17)|(3.45)|(3.74)|
|Ashanti(b:Northern)|0.219|0.044|0.496**|
||(1.53)|(0.22)|(2.29)|
|**UNEMPLOYED**||||
|Male|-0.460**|0.000|0.000|
||(-2.40)|(.)|(.)|
|Age|0.177***|0.138***|0.243***|
||(4.62)|(2.84)|(3.87)|
|Age_sq|-0.002***|-0.002***|-0.003***|
||(-4.95)|(-3.13)|(-4.25)|
|Married|0.629***|0.704**|0.490|
||(2.85)|(2.50)|(0.98)|
|Secondaryeducation|0.355|0.071|0.778**|
||(1.63)|(0.27)|(2.20)|
|Male head|0.584**|-0.333|0.475|
||(2.08)|(-0.87)|(1.15)|
|Muslim|0.204|-0.028|0.548|
||(0.64)|(-0.07)|(1.26)|
|Spousepresent|-0.934***|-0.074|-0.884|
||(-3.06)|(-0.18)|(-1.55)|
|Household size|-0.030|0.001|-0.079|
||(-0.72)|(0.02)|(-1.09)|
|Poor|0.117<br>(055)|0.194<br>(075)|0.021<br>(006)|
|Urban|.<br>1.159***|.<br>1.777***|.<br>0.344|
||(2.93)|(4.77)|(0.62)|
|Ashanti(b:Northern)|0.662*|0.579|0.880**|
||(1.85)|(1.28)|(2.03)|
|_N_|4497|2474|2023|
|Odds ratios reported; t statist|ics in parentheses: * p<0.10 **|p<0.05 *** p<0.01; Errors c|lustered at cluster-level. Base|
|<br>category is “Not in the Labor|,<br>Force”|,||

29
**Table 7.** LPM of wage employment, without gender role attitudes and personality traits

||(1)|(2)|(3)|
|---|---|---|---|
||Pooled sample|Women|Men|
|Male|0.182***|-|-|
||(7.92)|||
|Age|-0.003|-0.007|0.003|
||(-0.82)|(-1.53)|(0.38)|
|Age_sq|-0.000|0.000|-0.000|
||(-0.54)|(0.18)|(-1.05)|
|Married|-0.003|-0.029|-0.000|
||(-0.11)|(-0.80)|(-0.00)|
|Secondaryeducation|0.133***|0.142***|0.112***|
||(5.22)|(4.66)|(2.63)|
|Male head|0.160***|0.050|0.169**|
||(4.49)|(0.62)|(2.07)|
|Muslim|-0.120***|-0.120**|-0.120**|
||(-3.82)|(-2.60)|(-2.45)|
|Spousepresent|-0.135***|-0.024|-0.142***|
||(-3.60)|(-0.28)|(-2.65)|
|Household size|-0.009**|-0.007*|-0.013**|
||(-2.57)|(-1.86)|(-2.13)|
|Poor|-0.045|-0.044|-0.044|
||(-1.60)|(-1.50)|(-1.03)|
|Urban|0.076**|0.045*|0.108*|
||(2.37)|(1.88)|(1.94)|
|Ashanti(b:Northern)|-0.039|-0.039|-0.045|
||(-1.21)|(-0.88)|(-0.88)|
|Constant|0.394***|0.514***|0.428**|
||(3.81)|(4.13)|(2.35)|
|_N_|2361|1293|1068|

t statistics in parentheses: * p<0.10, ** p<0.05, *** p<0.01. Errors clustered at cluster-level. Base category is “SelfEmployment” 30
**Table 8.** MNL regressions - effects of gender role attitudes and personality traits on employment outcomes ( _pooled_ sample)

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||_Norms_|_Norms+_<br>_Controls_|_Norms+_<br>_Control+_<br>_Personality_|_Norms+_<br>_Controls+_<br>_Impulsive_|_Norms+_<br>_Controls+_<br>_Work_<br>_Central_|_Norms+_<br>_Controls+_<br>_Tenacity_|_Norms+_<br>_Controls+_<br>_Polychroni_<br>_city_|_Norms+_<br>_Controls+_<br>_Locus of_<br>_Control_|_Norms+_<br>_Control+_<br>_Achievement_|_Norms+_<br>_Control+_<br>_Power_<br>_Motivation_|_Norms+_<br>_Controls+_<br>_Organized_|_Norms+_<br>_Controls+_<br>_Optimism_|
|**EMPLOYED**|||||||||||||
|Traditional|-0.032***|-0.014**|0.002|0.011|0.027|0.009|0.013|-0.086***|0.017|0.023|-0.014|-0.076*|
||(-6.24)|(-2.46)|(0.43)|(0.67)|(1.08)|(0.36)|(0.69)|(-3.72)|(0.57)|(1.11)|(-0.81)|(-1.79)|
|Gender(male=1)||-0.226*|-0.367***|-0.226*|-0.263**|-0.241**|-0.230*|-0.286**|-0.230*|-0.202*|-0.216*|-0.308**|
|||(-1.90)|(-2.77)|(-1.84)|(-2.18)|(-1.99)|(-1.91)|(-2.32)|(-1.91)|(-1.68)|(-1.80)|(-2.50)|
|Age||0.401***|0.403***|0.395***|0.393***|0.397***|0.407***|0.406***|0.401***|0.405***|0.401***|0.417***|
|||(11.46)|(11.52)|(11.33)|(10.95)|(11.34)|(11.67)|(11.47)|(11.34)|(11.62)|(11.38)|(12.22)|
|Age_sq||-0.005***|-0.005***|-0.005***|-0.005***|-0.005***|-0.005***|-0.005***|-0.005***|-0.005***|-0.005***|-0.005***|
|||(-11.04)|(-11.01)|(-10.90)|(-10.56)|(-10.94)|(-11.25)|(-11.04)|(-10.91)|(-11.16)|(-10.98)|(-11.68)|
|Married||0.303*|0.298|0.306*|0.316*|0.322*|0.297*|0.259|0.335**|0.293*|0.305*|0.285|
|||(1.81)|(1.64)|(1.81)|(1.84)|(1.93)|(1.75)|(1.50)|(1.96)|(1.75)|(1.81)|(1.64)|
|At least secondaryschool||0.623***|0.583***|0.588***|0.640***|0.615***|0.616***|0.599***|0.608***|0.619***|0.607***|0.602***|
|||(4.42)|(3.97)|(4.11)|(4.54)|(4.31)|(4.35)|(4.29)|(4.30)|(4.34)|(4.28)|(4.19)|
|Gender of head(male=1)||0.183|0.214|0.202|0.173|0.179|0.181|0.168|0.184|0.165|0.179|0.208|
|||(0.84)|(0.95)|(0.92)|(0.80)|(0.83)|(0.84)|(0.76)|(0.85)|(0.75)|(0.82)|(0.92)|
|Muslim(Christian is base)||0.197|0.163|0.191|0.164|0.172|0.195|0.181|0.171|0.206|0.192|0.232|
|||(0.96)|(0.75)|(0.95)|(0.81)|(0.85)|(0.94)|(0.88)|(0.84)|(0.98)|(0.93)|(1.05)|
|Spousepresent||-0.737***|-0.730***|-0.771***|-0.723***|-0.756***|-0.745***|-0.640***|-0.766***|-0.701***|-0.742***|-0.724***|
|||(-3.20)|(-2.97)|(-3.35)|(-3.11)|(-3.27)|(-3.24)|(-2.70)|(-3.29)|(-3.01)|(-3.22)|(-3.01)|
|Household size||-0.006|-0.011|-0.001|-0.002|-0.003|-0.004|-0.016|-0.004|-0.009|-0.005|-0.017|
|||(-0.22)|(-0.44)|(-0.04)|(-0.07)|(-0.12)|(-0.14)|(-0.63)|(-0.17)|(-0.35)|(-0.22)|(-0.71)|
|Poor||-0.731***|-0.785***|-0.720***|-0.721***|-0.734***|-0.729***|-0.735***|-0.726***|-0.718***|-0.742***|-0.801***|
|||(-4.73)|(-4.94)|(-4.59)|(-4.67)|(-4.70)|(-4.58)|(-4.66)|(-4.68)|(-4.65)|(-4.74)|(-5.22)|
|Urban||0.687***|0.772***|0.696***|0.718***|0.697***|0.693***|0.694***|0.703***|0.691***|0.688***|0.728***|
|||(3.37)|(3.43)|(3.35)|(3.34)|(3.32)|(3.35)|(3.35)|(3.39)|(3.38)|(3.35)|(3.59)|
|Ashanti(Northern is base)||0.256|0.183|0.239|0.235|0.262|0.228|0.240|0.296|0.267|0.251|0.334|
|||(1.28)|(0.85)|(1.21)|(1.19)|(1.32)|(1.11)|(1.16)|(1.50)|(1.32)|(1.24)|(1.54)|
|Impulsive|||-0.242**|0.073|||||||||
||||(-2.35)|(0.25)|||||||||

31
|Work centrality|||0.418***||0.793***||||||
|---|---|---|---|---|---|---|---|---|---|---|
||||(4.12)||(2.71)||||||
|Tenacity|||0.096||0.467||||||
||||(1.19)||(1.63)||||||
|Polychronicity|||-0.169*|||0.243|||||
||||(-1.65)|||(0.72)|||||
|High locus of control|||0.158|||-0.780**|||||
||||(1.62)|||(-2.30)|||||
|Achievement|||0.095||||0.586*||||
||||(0.74)||||(1.66)||||
|Power motivation|||-0.147*|||||0.395|||
||||(-1.75)|||||(1.59)|||
|Organized|||-0.025||||||0.096||
||||(-0.31)||||||(0.44)||
|Optimism|||0.853***|||||||0.041|
||||(6.26)|||||||(0.08)|
|Traditional*Impulsive||||-0.009|||||||
|||||(-1.46)|||||||
|Traditional*Work centrality|||||-0.010||||||
||||||(-1.53)||||||
|Traditional*Tenacity|||||-0.006||||||
||||||(-0.91)||||||
|Traditional*Polychronicity||||||-0.012|||||
|||||||(-1.57)|||||
|Traditional*internal control||||||0.026***|||||
|||||||(3.30)|||||
|Traditional*Achievement|||||||-0.008||||
||||||||(-1.03)||||
|Traditional*Power motiva,||||||||-0.011*|||
|||||||||(-1.83)|||
|Traditional*Organized|||||||||0.000||
||||||||||(0.04)||
|Traditional*Optimism||||||||||0.021*|
|||||||||||(1.66)|
|**UNEMPLOYED**|||||||||||
|Traditional|-0.025**|-0.006|0.006|-0.033|-0.063<br>0.003|0.005<br>-0.068|0.050|0.056*|0.044|-0.070|

32
||(-2.27)|(-0.53)|(0.56)|(-0.90)|(-0.91)|(0.08)|(0.16)|(-1.24)|(0.86)|(1.71)|(1.44)|(-1.01)|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Gender(male=1)||-0.449*|-0.555**|-0.465**|-0.448*|-0.447*|-0.454*|-0.498**|-0.430*|-0.397*|-0.515**|-0.522**|
|||(-1.89)|(-2.38)|(-1.98)|(-1.90)|(-1.87)|(-1.91)|(-2.11)|(-1.79)|(-1.68)|(-2.15)|(-2.17)|
|Age||0.170***|0.190***|0.168***|0.174***|0.170***|0.174***|0.173***|0.169***|0.174***|0.177***|0.182***|
|||(3.18)|(3.47)|(3.09)|(3.21)|(3.19)|(3.23)|(3.18)|(3.17)|(3.25)|(3.27)|(3.43)|
|Agesq||-0.002***|-0.002***|-0.002***|-0.002***|-0.002***|-0.002***|-0.002***|-0.002***|-0.002***|-0.002***|-0.002***|
|_||(-3.31)|(-3.53)|(-3.24)|(-3.31)|(-3.31)|(-3.36)|(-3.29)|(-3.29)|(-3.34)|(-3.37)|(-3.53)|
|Married||0.373|0.333|0.359|0.349|0.366|0.370|0.331|0.357|0.351|0.382|0.369|
|||(1.16)|(1.01)|(1.11)|(1.08)|(1.13)|(1.15)|(1.02)|(1.10)|(1.10)|(1.19)|(1.12)|
|At least secondaryschool||0.661**|0.698**|0.666**|0.664**|0.664**|0.657**|0.638**|0.667**|0.664**|0.714**|0.630**|
|||(2.25)|(2.35)|(2.23)|(2.27)|(2.26)|(2.23)|(2.18)|(2.23)|(2.23)|(2.43)|(2.12)|
|Gender of head(male=1)||0.381|0.456|0.389|0.412|0.373|0.376|0.361|0.372|0.354|0.444|0.404|
|||(1.03)|(1.20)|(1.06)|(1.12)|(1.01)|(1.02)|(0.98)|(1.02)|(0.96)|(1.21)|(1.06)|
|Muslim(Christian is base)||0.321|0.385|0.333|0.293|0.329|0.322|0.305|0.332|0.369|0.366|0.355|
|||(0.95)|(1.20)|(0.98)|(0.89)|(0.97)|(0.95)|(0.92)|(0.98)|(1.10)|(1.12)|(1.05)|
|Spousepresent||-0.745**|-0.755*|-0.744**|-0.770**|-0.734**|-0.749**|-0.654*|-0.717*|-0.675*|-0.744**|-0.748**|
|||(-2.00)|(-1.94)|(-1.97)|(-2.09)|(-1.98)|(-2.00)|(-1.73)|(-1.91)|(-1.82)|(-1.99)|(-2.00)|
|Household size||-0.027|-0.037|-0.027|-0.027|-0.027|-0.026|-0.036|-0.026|-0.033|-0.032|-0.037|
|||(-0.51)|(-0.68)|(-0.49)|(-0.51)|(-0.50)|(-0.49)|(-0.67)|(-0.50)|(-0.63)|(-0.62)|(-0.68)|
|Poor||0.138|0.098|0.148|0.125|0.144|0.142|0.134|0.149|0.171|0.203|0.053|
|||(0.44)|(0.30)|(0.47)|(0.40)|(0.46)|(0.45)|(0.42)|(0.47)|(0.55)|(0.64)|(0.17)|
|Urban||1.268***|1.349***|1.275***|1.265***|1.270***|1.280***|1.282***|1.272***|1.299***|1.285***|1.326***|
|||(3.02)|(3.24)|(3.04)|(3.01)|(3.03)|(3.03)|(3.06)|(3.03)|(3.11)|(3.07)|(3.21)|
|Ashanti(Northern is base)||0.751*|0.716*|0.754*|0.674|0.759*|0.729*|0.736*|0.775*|0.722*|0.787*|0.831*|
|||(1.75)|(1.68)|(1.74)|(1.57)|(1.73)|(1.71)|(1.72)|(1.73)|(1.66)|(1.84)|(1.94)|
|Impulsive|||-0.076|-0.507|||||||||
||||(-0.40)|(-0.87)|||||||||
|Work centrality|||-0.012||-0.700||||||||
||||(-0.07)||(-1.05)||||||||
|Tenacity|||0.039|||0.075|||||||
||||(0.25)|||(0.14)|||||||
|Polychronicity|||-0.259||||-0.007||||||
||||(-1.53)||||(-0.01)||||||
|High internal locus of control|||-0.003|||||-0.676|||||
||||(-0.02)|||||(-0.88)|||||
|Achievement|||0.094||||||0.495||||

33
||||(0.43)||||(0.69)||||
|---|---|---|---|---|---|---|---|---|---|---|
|Power motivation|||-0.237|||||0.511|||
||||(-1.47)|||||(1.09)|||
|Organized|||-0.398***||||||0.315||
||||(-3.22)||||||(0.82)||
|Optimism|||0.902***|||||||-0.006|
||||(3.96)|||||||(-0.01)|
|Traditional*Impulsive||||0.011|||||||
|||||(0.81)|||||||
|Traditional*Work centrality|||||0.015||||||
||||||(0.89)||||||
|Traditional*Tenacity|||||-0.002||||||
||||||(-0.22)||||||
|Traditional*Polychronicity||||||-0.005|||||
|||||||(-0.38)|||||
|Traditional*internal control||||||0.022|||||
|||||||(1.20)|||||
|Traditional*Achievement|||||||-0.015||||
||||||||(-0.94)||||
|Traditional*Power motiv.||||||||-0.019*|||
|||||||||(-1.82)|||
|Traditional*Organized|||||||||-0.014*||
||||||||||(-1.77)||
|Traditional*Optimism||||||||||0.021|
|||||||||||(1.09)|
|_N_|2478|2478|2478|2478|2478<br>2478|2478<br>2478|2478|2478|2478|2478|

Odds ratios reported; t statistics in parentheses: * p<0.10, ** p<0.05, *** p<0.01. Errors clustered at cluster-level. Base category is “Not in the Labor Force” 34
**Table 9.** MNL regressions- effects of gender role attitudes and personality traits on employment outcomes ( _women_ sample)

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||_Norms_|_Norms+_<br>_Controls_|_Norms+_<br>_Control+_<br>_Personality_|_Norms+_<br>_Controls+_<br>_Impulsive_|_Norms+_<br>_Controls+_<br>_Work_<br>_Central_|_Norms+_<br>_Controls+_<br>_Tenacity_|_Norms+_<br>_Controls_<br>_+_<br>_Polychro_<br>_nicity_|_Norms+_<br>_Controls+_<br>_Locus of_<br>_Control_|_Norms+_<br>_Control+_<br>_Achievemen_<br>_t_|_Norms+_<br>_Control+_<br>_Power_<br>_Motivation_|_Norms+_<br>_Controls+_<br>_Organized_|_Norms+_<br>_Controls+_<br>_Optimism_|
|**EMPLOYED**|||||||||||||
|Traditional|-0.028***|-0.011|0.002|0.020|0.040|0.022|0.006|-0.057*|0.046|0.036|-0.023|-0.116**|
||(-4.58)|(-1.57)|(0.22)|(0.84)|(1.10)|(0.71)|(0.21)|(-1.78)|(0.94)|(1.09)|(-0.72)|(-2.22)|
|Age||0.416***|0.418***|0.409***|0.410***|0.413***|0.418***|0.417***|0.420***|0.422***|0.416***|0.429***|
|||(9.75)|(9.63)|(9.51)|(9.57)|(9.67)|(9.74)|(9.70)|(9.76)|(9.81)|(9.76)|(10.08)|
|Age_sq||-0.005***|-0.005***|-0.005***|-0.005***|-0.005***|-<br>0.005***|-0.005***|-0.005***|-0.005***|-0.005***|-0.005***|
|||(-9.11)|(-9.03)|(-8.88)|(-8.95)|(-9.04)|(-9.12)|(-9.08)|(-9.11)|(-9.15)|(-9.12)|(-9.37)|
|Married||-0.031|0.004|-0.015|0.010|-0.014|-0.040|-0.035|0.018|-0.047|-0.037|-0.066|
|||(-0.15)|(0.02)|(-0.07)|(0.05)|(-0.07)|(-0.19)|(-0.17)|(0.08)|(-0.23)|(-0.18)|(-0.31)|
|At least secondarysch||0.295|0.255|0.256|0.294|0.261|0.294|0.286|0.260|0.305|0.291|0.291|
|||(1.55)|(1.29)|(1.35)|(1.51)|(1.35)|(1.56)|(1.49)|(1.36)|(1.56)|(1.51)|(1.50)|
|Gender of head(male=1)||-0.669|-0.497|-0.618|-0.807|-0.754|-0.674|-0.604|-0.816|-0.703|-0.684|-0.412|
|||(-0.94)|(-0.62)|(-0.87)|(-1.09)|(-1.05)|(-0.95)|(-0.87)|(-1.09)|(-0.98)|(-0.96)|(-0.55)|
|Muslim(Christian is base)||-0.109|-0.140|-0.124|-0.126|-0.144|-0.102|-0.102|-0.130|-0.084|-0.111|-0.063|
|||(-0.41)|(-0.50)|(-0.47)|(-0.48)|(-0.55)|(-0.38)|(-0.39)|(-0.50)|(-0.31)|(-0.42)|(-0.22)|
|Spousepresent||-0.049|-0.258|-0.119|0.077|-0.001|-0.045|-0.118|0.054|0.005|-0.034|-0.251|
|||(-0.07)|(-0.32)|(-0.17)|(0.10)|(-0.00)|(-0.06)|(-0.17)|(0.07)|(0.01)|(-0.05)|(-0.33)|
|Household size||0.032|0.033|0.040|0.035|0.036|0.034|0.030|0.033|0.028|0.033|0.025|
|||(1.11)|(1.12)|(1.33)|(1.16)|(1.22)|(1.20)|(1.03)|(1.14)|(0.98)|(1.14)|(0.90)|
|Poor||-0.807***|-0.823***|-0.780***|-0.785***|-0.812***|-<br>0.804***|-0.809***|-0.799***|-0.784***|-0.810***|-0.877***|
|||(-3.58)|(-3.45)|(-3.39)|(-3.48)|(-3.52)|(-3.55)|(-3.58)|(-3.48)|(-3.42)|(-3.57)|(-3.86)|
|Urban||0.445*|0.497*|0.443*|0.477*|0.456*|0.437*|0.434*|0.457*|0.449*|0.445*|0.457*|
|||(1.71)|(1.77)|(1.69)|(1.77)|(1.69)|(1.66)|(1.66)|(1.71)|(1.73)|(1.70)|(1.73)|
|Ashanti(base: Northern)||-0.071|-0.150|-0.095|-0.069|-0.062|-0.072|-0.056|0.017|-0.021|-0.070|-0.022|
|||(-0.25)|(-0.52)|(-0.34)|(-0.25)|(-0.22)|(-0.25)|(-0.20)|(0.06)|(-0.08)|(-0.25)|(-0.08)|
|Impulsive|||-0.333**|0.157|||||||||

35
||(-2.45)|(0.36)||||||||
|---|---|---|---|---|---|---|---|---|---|
|Work centrality|0.428***|0.927**||||||||
||(3.22)|(2.43)||||||||
|Tenacity|0.182*||0.666*|||||||
||(1.69)||(1.80)|||||||
|Polychronicity|-0.076|||0.210||||||
||(-0.56)|||(0.43)||||||
|High locus of control|-0.027||||-0.608|||||
||(-0.25)||||(-1.30)|||||
|Achievement|0.125|||||1.001*||||
||(0.75)|||||(1.81)||||
|Power motivation|-0.148||||||0.611|||
||(-1.40)||||||(1.57)|||
|Organized|-0.122|||||||-0.073||
||(-1.14)|||||||(-0.22)||
|Optimism|0.723***||||||||-0.703|
||(4.35)||||||||(-1.08)|
|Traditional*Impulsive||-0.012||||||||
|||(-1.30)||||||||
|Traditional*Work centrality||-0.013||||||||
|||(-1.42)||||||||
|Traditional*Tenacity|||-0.009|||||||
||||(-1.03)|||||||
|Traditional*Polychronicity||||-0.008||||||
|||||(-0.67)||||||
|Trad*internal control|||||0.016|||||
||||||(1.46)|||||
|Traditional*Achievement||||||-0.016||||
|||||||(-1.19)||||
|Trad*Power motivation|||||||-0.015|||
||||||||(-1.53)|||
|Traditional*Organized||||||||0.003||
|||||||||(0.37)||
|Traditional*Optimism|||||||||0.033**|
||||||||||(2.12)|
|**UNEMPLOYED**||||||||||

36
|Traditional|-0.035**|-0.019|-0.011|-0.073|-0.054|-0.026|-0.056|-0.036|0.041|0.076*|0.028|-0.067|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||(-2.42)|(-1.27)|(-0.73)|(-1.30)|(-0.87)|(-0.51)|(-1.31)|(-0.58)|(0.55)|(1.74)|(0.58)|(-0.58)|
|Age||0.150**|0.171**|0.147**|0.155**|0.151**|0.152**|0.151**|0.147**|0.156**|0.157**|0.158**|
|||(2.13)|(2.30)|(2.00)|(2.13)|(2.12)|(2.13)|(2.14)|(2.10)|(2.25)|(2.23)|(2.25)|
|Age_sq||-0.002**|-0.002**|-0.002**|-0.002**|-0.002**|-0.002**|-0.002**|-0.002**|-0.002**|-0.002**|-0.002**|
|||(-2.34)|(-2.43)|(-2.23)|(-2.30)|(-2.33)|(-2.33)|(-2.34)|(-2.30)|(-2.44)|(-2.41)|(-2.45)|
|Married||0.242|0.185|0.235|0.176|0.222|0.236|0.252|0.215|0.179|0.238|0.225|
|||(0.62)|(0.47)|(0.59)|(0.44)|(0.55)|(0.60)|(0.64)|(0.54)|(0.46)|(0.62)|(0.57)|
|At least secondaryschool||0.105|0.270|0.096|0.106|0.109|0.117|0.115|0.127|0.151|0.271|0.087|
|||(0.29)|(0.75)|(0.26)|(0.29)|(0.30)|(0.32)|(0.31)|(0.35)|(0.41)|(0.74)|(0.24)|
|Gender of head(male=1)||-0.052|0.448|-0.023|0.159|-0.028|-0.066|-0.011|-0.038|0.096|-0.012|0.162|
|||(-0.07)|(0.62)|(-0.03)|(0.21)|(-0.04)|(-0.09)|(-0.01)|(-0.05)|(0.13)|(-0.02)|(0.20)|
|Muslim(Christian is base)||-0.010|0.065|0.007|-0.036|0.006|-0.004|-0.012|0.025|0.138|0.037|0.018|
|||(-0.02)|(0.15)|(0.01)|(-0.08)|(0.01)|(-0.01)|(-0.03)|(0.05)|(0.29)|(0.08)|(0.04)|
|Spousepresent||-0.244|-0.798|-0.272|-0.444|-0.258|-0.225|-0.317|-0.234|-0.304|-0.238|-0.427|
|||(-0.35)|(-1.19)|(-0.39)|(-0.65)|(-0.37)|(-0.32)|(-0.47)|(-0.33)|(-0.42)|(-0.33)|(-0.59)|
|Household size||-0.035|-0.040|-0.034|-0.035|-0.035|-0.036|-0.034|-0.036|-0.048|-0.043|-0.040|
|||(-0.53)|(-0.59)|(-0.49)|(-0.52)|(-0.53)|(-0.54)|(-0.52)|(-0.55)|(-0.75)|(-0.68)|(-0.61)|
|Poor||0.085|0.122|0.099|0.058|0.085|0.079|0.083|0.085|0.181|0.183|0.025|
|||(0.22)|(0.32)|(0.25)|(0.15)|(0.22)|(0.21)|(0.22)|(0.22)|(0.47)|(0.48)|(0.06)|
|Urban||1.496***|1.536***|1.509***|1.474***|1.498***|1.514***|1.484***|1.493***|1.624***|1.502***|1.501***|
|||(2.79)|(2.89)|(2.82)|(2.74)|(2.80)|(2.80)|(2.77)|(2.81)|(3.01)|(2.79)|(2.82)|
|Ashanti(base: Northern)||0.579|0.420|0.608|0.513|0.580|0.586|0.585|0.592|0.546|0.542|0.611|
|||(1.06)|(0.79)|(1.09)|(0.96)|(1.03)|(1.07)|(1.08)|(1.02)|(0.96)|(1.00)|(1.12)|
|Impulsive|||-0.111|-0.897|||||||||
||||(-0.45)|(-1.08)|||||||||
|Work centrality|||-0.216||-0.628||||||||
||||(-1.10)||(-0.90)||||||||
|Tenacity|||0.081|||-0.133|||||||
||||(0.38)|||(-0.19)|||||||
|Polychronicity|||-0.019||||-0.555||||||
||||(-0.09)||||(-0.78)||||||
|High locus of control|||-0.313*|||||-0.317|||||
||||(-1.89)|||||(-0.36)|||||
|Achievement|||0.297||||||0.484||||
||||(1.02)||||||(0.53)||||

37
|Power motivation|||-0.469**|||||0.831|||
|---|---|---|---|---|---|---|---|---|---|---|
||||(-2.12)|||||(1.24)|||
|Organized|||-0.519***||||||0.111||
||||(-3.30)||||||(0.19)||
|Optimism|||0.534*|||||||-0.166|
||||(1.75)|||||||(-0.12)|
|Traditional*Impulsive||||0.021|||||||
|||||(1.08)|||||||
|Traditional*Work centrality||||0.010|||||||
|||||(0.61)|||||||
|Traditional*Tenacity|||||0.002||||||
||||||(0.15)||||||
|Traditional*Polychronicity|||||0.016||||||
||||||(1.00)||||||
|Trad*internal control||||||0.006|||||
|||||||(0.27)|||||
|Traditional*Achievement|||||||-0.016||||
||||||||(-0.79)||||
|Trad*Power motivation||||||||-0.032**|||
|||||||||(-2.01)|||
|Traditional*Organized|||||||||-0.013||
||||||||||(-0.97)||
|Traditional*Optimism||||||||||0.016|
|||||||||||(0.48)|
|N|1375|1375|1375|1375<br>1375|1375<br>1375|1375|1375|1375|1375|1375|

Odds ratios reported; t statistics in parentheses: * p<0.10, ** p<0.05, *** p<0.01. Errors clustered at cluster-level. Base category is “Not in the Labor Force” 38
**Table 10.** MNL regressions- effects of gender role attitudes and personality traits on employment outcomes ( _men_ sample)

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||_Norms_|_Norms+_<br>_Controls_|_Norms+_<br>_Control+_<br>_Personalit_<br>_y_|_Norms+_<br>_Controls+_<br>_Impulsive_|_Norms+_<br>_Controls+_<br>_Work_<br>_Central_|_Norms+_<br>_Controls_<br>_+_<br>_Tenacity_|_Norms+_<br>_Controls+_<br>_Polychroni_<br>_city_|_Norms+_<br>_Controls+_<br>_Locus of_<br>_Control_|_Norms+_<br>_Control+_<br>_Achieveme_<br>_nt_|_Norms+_<br>_Control+_<br>_Power_<br>_Motivation_|_Norms+_<br>_Controls+_<br>_Organized_|_Norms+_<br>_Controls+_<br>_Optimism_|
|**EMPLOYED**|||||||||||||
|Traditional|-0.035***|-0.015**|0.006|0.004|0.011|-0.014|0.009|-0.122***|-0.030|0.003|0.014|-0.024|
||(-5.63)|(-2.17)|(0.82)|(0.15)|(0.31)|(-0.43)|(0.42)|(-3.38)|(-0.85)|(0.11)|(0.57)|(-0.37)|
|Age||0.308***|0.329***|0.304***|0.300***|0.302***|0.313***|0.325***|0.307***|0.308***|0.305***|0.340***|
|||(5.22)|(5.57)|(5.21)|(5.10)|(5.11)|(5.34)|(5.27)|(5.14)|(5.24)|(5.14)|(5.71)|
|Age_sq||-0.004***|-0.004***|-0.004***|-0.004***|-<br>0.004***|-0.004***|-0.004***|-0.004***|-0.004***|-0.004***|-0.004***|
|||(-5.49)|(-5.74)|(-5.47)|(-5.33)|(-5.38)|(-5.60)|(-5.48)|(-5.40)|(-5.50)|(-5.43)|(-5.90)|
|Married||1.320***|1.306***|1.293***|1.222***|1.328***|1.342***|1.163***|1.339***|1.338***|1.354***|1.383***|
|||(3.56)|(3.17)|(3.52)|(3.23)|(3.59)|(3.56)|(3.16)|(3.59)|(3.61)|(3.65)|(3.45)|
|At least secondarysch||0.993***|1.032***|0.967***|1.019***|1.005***|0.988***|0.990***|1.001***|0.978***|0.992***|1.017***|
|||(4.90)|(4.68)|(4.63)|(5.05)|(4.89)|(4.73)|(4.71)|(4.96)|(4.82)|(4.93)|(4.79)|
|Gender of head(male=1)||1.447***|1.056***|1.427***|1.406***|1.433***|1.430***|1.363***|1.431***|1.453***|1.429***|1.203***|
|||(3.70)|(2.66)|(3.62)|(3.60)|(3.63)|(3.73)|(3.21)|(3.61)|(3.70)|(3.66)|(3.06)|
|Muslim(base:Christian)||0.629**|0.510*|0.629**|0.572**|0.613**|0.575**|0.569*|0.619**|0.639**|0.635**|0.629**|
|||(2.24)|(1.77)|(2.24)|(2.04)|(2.21)|(1.99)|(1.91)|(2.20)|(2.25)|(2.20)|(2.17)|
|Spousepresent||-0.959**|-0.852*|-0.954**|-0.870**|-0.961**|-1.000**|-0.656|-0.980**|-0.956**|-0.994**|-0.975**|
|||(-2.35)|(-1.92)|(-2.35)|(-2.11)|(-2.35)|(-2.43)|(-1.60)|(-2.38)|(-2.35)|(-2.46)|(-2.23)|
|Household size||-0.011|-0.037|-0.011|-0.009|-0.009|-0.014|-0.037|-0.012|-0.012|-0.010|-0.030|
|||(-0.28)|(-0.89)|(-0.27)|(-0.23)|(-0.22)|(-0.35)|(-0.92)|(-0.29)|(-0.30)|(-0.26)|(-0.72)|
|Poor||-0.771***|-0.818***|-0.768***|-0.763***|-<br>0.774***|-0.779***|-0.750***|-0.773***|-0.774***|-0.798***|-0.814***|
|||(-4.00)|(-3.91)|(-3.94)|(-4.07)|(-3.99)|(-3.94)|(-3.56)|(-4.01)|(-4.01)|(-4.13)|(-3.82)|
|Urban||0.927***|1.069***|0.942***|0.956***|0.940***|0.961***|0.985***|0.933***|0.917***|0.932***|1.006***|
|||(4.13)|(4.24)|(4.12)|(4.12)|(4.17)|(4.26)|(4.11)|(4.16)|(4.02)|(4.18)|(4.39)|
|Ashanti(base: Northern)||0.843***|0.772***|0.832***|0.798***|0.849***|0.715**|0.782***|0.844***|0.832***|0.820***|1.004***|
|||(3.15)|(2.59)|(3.09)|(3.02)|(3.21)|(2.51)|(2.62)|(3.17)|(3.07)|(2.95)|(3.50)|
|Impulsive|||-0.091|0.043|||||||||
||||(-0.52)|(0.09)|||||||||
|Work centrality|||0.339**||0.586||||||||

39
|||(2.48)||(1.34)||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
|Tenacity||0.044|||0.189|||||||
|||(0.33)|||(0.52)|||||||
|Polychronicity||-0.316**||||-0.052||||||
|||(-2.41)||||(-0.11)||||||
|High locus of control||0.359**|||||-1.029**|||||
|||(2.29)|||||(-1.96)|||||
|Achievement||0.057||||||-0.036||||
|||(0.31)||||||(-0.08)||||
|Power motivation||-0.099|||||||0.104|||
|||(-0.78)|||||||(0.32)|||
|Organized||0.129||||||||0.528||
|||(0.98)||||||||(1.63)||
|Optimism||1.083***|||||||||1.022|
|||(5.40)|||||||||(1.20)|
|Traditional*Impulsive|||-0.006|||||||||
||||(-0.67)|||||||||
|Trad*Work centrality||||-0.006||||||||
|||||(-0.64)||||||||
|Traditional*Tenacity|||||-0.000|||||||
||||||(-0.02)|||||||
|Traditional*Polychronicity||||||-0.010||||||
|||||||(-1.03)||||||
|Trad*internal control|||||||0.038***|||||
||||||||(3.22)|||||
|Traditional*Achievement||||||||0.004||||
|||||||||(0.41)||||
|Trad*Power motivation|||||||||-0.005|||
||||||||||(-0.74)|||
|Traditional*Organized||||||||||-0.007||
|||||||||||(-1.13)||
|Traditional*Optimism|||||||||||0.006|
||||||||||||(0.31)|
|**UNEMPLOYED**||||||||||||
|Traditional|-0.011|0.007<br>0.027*|0.007|-0.021|0.052|0.019|-0.055|0.069|0.058|0.097**|-0.005|
||(-0.81)|(0.49)<br>(1.80)|(0.15)|(-0.19)|(0.79)|(0.55)|(-0.76)|(0.85)|(1.33)|(2.30)|(-0.06)|

40
|Age|0.199**|0.232**|0.197**|0.195**|0.193**|0.201**|0.208**|0.192**|0.198**|0.203**|0.226**|
|---|---|---|---|---|---|---|---|---|---|---|---|
||(2.18)|(2.35)|(2.20)|(2.07)|(2.12)|(2.18)|(2.22)|(2.10)|(2.15)|(2.17)|(2.43)|
|Age_sq|-0.002**|-0.003**|-0.002**|-0.002**|-0.002**|-0.002**|-0.003**|-0.002**|-0.002**|-0.003**|-0.003**|
||(-2.23)|(-2.38)|(-2.26)|(-2.13)|(-2.18)|(-2.25)|(-2.24)|(-2.15)|(-2.19)|(-2.25)|(-2.45)|
|Married|0.677|0.587|0.646|0.614|0.691|0.726|0.534|0.682|0.648|0.707|0.774|
||(1.15)|(0.97)|(1.09)|(1.05)|(1.15)|(1.24)|(0.91)|(1.17)|(1.10)|(1.16)|(1.32)|
|At least secondarysch|1.434***|1.508***|1.432***|1.438***|1.429***|1.458***|1.409***|1.403***|1.415***|1.489***|1.440***|
||(3.09)|(2.99)|(3.00)|(3.03)|(3.11)|(3.13)|(3.05)|(3.05)|(3.02)|(3.03)|(3.00)|
|Gender of head(male=1)|0.497|0.168|0.494|0.495|0.539|0.486|0.397|0.567|0.513|0.613|0.240|
||(0.82)|(0.28)|(0.84)|(0.76)|(0.89)|(0.80)|(0.66)|(0.92)|(0.84)|(1.05)|(0.39)|
|Muslim(base:Christian)|0.833*|0.703|0.831*|0.765|0.810*|0.765|0.769|0.792|0.823*|0.925*|0.813*|
||(1.72)|(1.50)|(1.71)|(1.57)|(1.71)|(1.60)|(1.59)|(1.62)|(1.71)|(1.94)|(1.71)|
|Spousepresent|-1.098|-0.883|-1.079|-1.030|-1.101|-1.178*|-0.810|-1.101*|-1.051|-1.065|-1.131*|
||(-1.64)|(-1.30)|(-1.62)|(-1.56)|(-1.61)|(-1.74)|(-1.22)|(-1.66)|(-1.59)|(-1.56)|(-1.70)|
|Household size|-0.004|-0.035|-0.004|-0.005|-0.003|-0.005|-0.026|-0.000|-0.008|-0.007|-0.022|
||(-0.04)|(-0.35)|(-0.04)|(-0.05)|(-0.03)|(-0.06)|(-0.30)|(-0.00)|(-0.09)|(-0.08)|(-0.23)|
|Poor|0.211|0.208|0.216|0.208|0.210|0.225|0.210|0.229|0.232|0.235|0.143|
||(0.48)|(0.43)|(0.49)|(0.49)|(0.48)|(0.50)|(0.46)|(0.52)|(0.53)|(0.52)|(0.31)|
|Urban|1.044**|1.301***|1.048**|1.066**|1.044**|1.108**|1.100**|1.071**|1.068**|1.066**|1.185**|
||(1.97)|(2.65)|(2.00)|(2.07)|(1.99)|(2.09)|(2.11)|(2.00)|(2.05)|(1.99)|(2.24)|
|Ashanti(base: Northern)|1.099**|1.066*|1.087**|1.008*|1.100**|0.890*|1.030*|1.099**|1.130**|1.173**|1.230**|
||(2.05)|(1.89)|(2.04)|(1.83)|(2.06)|(1.65)|(1.89)|(2.03)|(2.10)|(2.11)|(2.23)|
|Impulsive||-0.046|-0.148|||||||||
|||(-0.15)|(-0.19)|||||||||
|Work centrality||0.286||-0.092||||||||
|||(0.91)||(-0.08)||||||||
|Tenacity||-0.014|||0.606|||||||
|||(-0.05)|||(0.69)|||||||
|Polychronicity||-0.625**||||-0.594||||||
|||(-2.50)||||(-0.85)||||||
|High locus of control||0.385|||||-0.349|||||
|||(1.47)|||||(-0.36)|||||
|Achievement||-0.159||||||0.770||||
|||(-0.56)||||||(0.74)||||
|Power motivation||0.194|||||||0.717|||
|||(0.76)|||||||(1.17)|||

41
|Organized||-0.145||||||||1.087*||
|---|---|---|---|---|---|---|---|---|---|---|---|
|||(-0.66)||||||||(1.80)||
|Optimism||1.275***|||||||||1.099|
|||(3.89)|||||||||(0.97)|
|Traditional*Impulsive|||0.001|||||||||
||||(0.04)|||||||||
|Trad*Work centrality||||0.007||||||||
|||||(0.27)||||||||
|Traditional*Tenacity|||||-0.012|||||||
||||||(-0.68)|||||||
|Traditional*Polychronicity||||||-0.003||||||
|||||||(-0.23)||||||
|Trad*internal control|||||||0.024|||||
||||||||(1.07)|||||
|Traditional*Achievement||||||||-0.017||||
|||||||||(-0.74)||||
|Trad*Power motivation|||||||||-0.015|||
||||||||||(-1.14)|||
|Traditional*Organized||||||||||-0.024**||
|||||||||||(-2.27)||
|Traditional*Optimism|||||||||||0.007|
||||||||||||(0.28)|
|N|1103|1103<br>1103|1103|1103|1103|1103|1103|1103|1103|1103|1103|

Odds ratios reported; t statistics in parentheses: * p<0.10, ** p<0.05, *** p<0.01. Errors clustered at cluster-level. Base category is “Not in the Labor Force” 42
**Table 11.** LPM regressions- effects of norms and personality traits on wage employment  (vs. self-employment) - _pooled_ sample

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||_Norms_|_Norms+_<br>_Controls_|_Norms+_<br>_Controls+P_<br>_ersonality_|_Norms+_<br>_Controls+_<br>_Impulsive_|_Norms+_<br>_Controls+_<br>_Work_<br>_Central_|_Norms+_<br>_Controls+_<br>_Tenacity_|_Norms+_<br>_Controls+_<br>_Polychronici_<br>_ty_|_Norms+_<br>_Controls+_<br>_Locus of_<br>_Control_|_Norms+_<br>_Control+_<br>_Achievement_|_Norms+_<br>_Control+_<br>_Power_<br>_Motivation_|_Norms+_<br>_Controls+_<br>_Organized_|_Norms+_<br>_Controls+_<br>_Optimism_|
|Traditional|-0.002|0.001|-0.000|-0.007|0.003|0.001|0.002|0.006|0.013*|0.002|0.014**|0.014|
||(-1.53)|(0.64)|(-0.10)|(-1.53)|(0.52)|(0.11)|(0.54)|(1.26)|(1.72)|(0.31)|(2.58)|(1.58)|
|Gender(male=1)||0.193***|0.208***|0.189***|0.195***|0.194***|0.193***|0.208***|0.196***|0.194***|0.192***|0.201***|
|||(6.27)|(6.55)|(6.15)|(6.25)|(6.25)|(6.29)|(6.58)|(6.39)|(6.31)|(6.24)|(6.44)|
|Age||-0.002|-0.004|-0.002|-0.002|-0.002|-0.002|-0.004|-0.002|-0.002|-0.002|-0.003|
|||(-0.27)|(-0.58)|(-0.35)|(-0.25)|(-0.26)|(-0.24)|(-0.54)|(-0.29)|(-0.27)|(-0.34)|(-0.39)|
|Age_sq||-0.000|-0.000|-0.000|-0.000|-0.000|-0.000|-0.000|-0.000|-0.000|-0.000|-0.000|
|||(-0.59)|(-0.28)|(-0.52)|(-0.60)|(-0.60)|(-0.61)|(-0.35)|(-0.58)|(-0.60)|(-0.52)|(-0.49)|
|Married||0.013|0.018|0.013|0.013|0.012|0.012|0.016|0.013|0.012|0.016|0.015|
|||(0.31)|(0.46)|(0.33)|(0.31)|(0.30)|(0.30)|(0.39)|(0.33)|(0.31)|(0.40)|(0.38)|
|At least secondaryeducation||0.129***|0.130***|0.132***|0.129***|0.130***|0.130***|0.133***|0.127***|0.129***|0.125***|0.126***|
|||(4.10)|(4.20)|(4.17)|(4.07)|(4.11)|(4.10)|(4.25)|(3.98)|(4.09)|(3.89)|(4.03)|
|Gender of head(male=1)||0.156***|0.157***|0.156***|0.156***|0.156***|0.156***|0.155***|0.154***|0.155***|0.159***|0.153***|
|||(3.54)|(3.57)|(3.57)|(3.51)|(3.53)|(3.54)|(3.52)|(3.52)|(3.53)|(3.63)|(3.49)|
|Muslim(Christian is base)||-0.126***|-0.122***|-0.123***|-0.125***|-0.126***|-0.126***|-0.125***|-0.129***|-0.127***|-0.127***|-0.130***|
|||(-3.82)|(-3.67)|(-3.73)|(-3.78)|(-3.78)|(-3.78)|(-3.88)|(-3.87)|(-3.83)|(-3.90)|(-3.90)|
|Spousepresent in household||-0.150***|-0.164***|-0.150***|-0.150***|-0.150***|-0.150***|-0.160***|-0.149***|-0.150***|-0.152***|-0.152***|
|||(-3.08)|(-3.31)|(-3.10)|(-3.07)|(-3.05)|(-3.08)|(-3.24)|(-3.07)|(-3.09)|(-3.14)|(-3.14)|
|Household size||-0.012**|-0.011**|-0.012**|-0.012**|-0.012**|-0.012**|-0.011**|-0.012**|-0.012**|-0.012**|-0.012**|
|||(-2.28)|(-2.16)|(-2.26)|(-2.29)|(-2.27)|(-2.27)|(-2.20)|(-2.20)|(-2.28)|(-2.29)|(-2.31)|
|Poor||-0.040|-0.037|-0.039|-0.040|-0.039|-0.040|-0.041|-0.039|-0.040|-0.039|-0.036|
|||(-1.18)|(-1.11)|(-1.17)|(-1.21)|(-1.18)|(-1.19)|(-1.23)|(-1.16)|(-1.18)|(-1.16)|(-1.08)|
|Urban||0.069*|0.062*|0.068*|0.070*|0.069*|0.069*|0.063*|0.071*|0.069*|0.071*|0.060*|
|||(1.83)|(1.66)|(1.85)|(1.86)|(1.83)|(1.83)|(1.71)|(1.86)|(1.83)|(1.88)|(1.66)|
|Ashanti(Northern is base)||-0.040|-0.039|-0.039|-0.038|-0.040|-0.041|-0.041|-0.033|-0.040|-0.041|-0.047|
|||(-1.16)|(-1.11)|(-1.13)|(-1.08)|(-1.16)|(-1.16)|(-1.20)|(-0.93)|(-1.12)|(-1.18)|(-1.31)|
|Impulsive|||-0.026|-0.164*|||||||||
||||(-1.32)|(-1.90)|||||||||
|Work centrality|||-0.022||0.009||||||||
||||(-1.39)||(0.16)||||||||

43
|Tenacity|-0.004||-0.004||||
|---|---|---|---|---|---|---|
||(-0.22)||(-0.07)||||
|Polychronicity|-0.007|||0.019|||
||(-0.42)|||(0.29)|||
|High internal locus of control|-0.059***||||0.019||
||(-3.87)||||(0.30)||
|Achievement|0.032||||0.154*||
||(1.22)||||(1.68)||
|Power motivation|-0.008||||0.010||
||(-0.51)||||(0.16)||
|Organized|-0.015||||0.133**||
||(-0.99)||||(2.27)||
|Optimism|-0.025|||||0.121|
||(-1.11)|||||(1.22)|
|Traditional*Impulsive||0.003*|||||
|||(1.72)|||||
|Traditional*Work centrality||-0.000|||||
|||(-0.35)|||||
|Traditional*Tenacity|||0.000||||
||||(0.03)||||
|Traditional*Polychronicity||||-0.001|||
|||||(-0.34)|||
|Traditional*internal control|||||-0.002||
||||||(-1.25)||
|Traditional*Achievement|||||-0.003||
||||||(-1.60)||
|Traditional*Power motivation|||||-0.000||
||||||(-0.15)||
|Traditional*Organized|||||-0.003**||
||||||(-2.55)||
|Traditional*Optimism||||||-0.004|
|||||||(-1.61)|
|_N_<br>1565|1565<br>1565|1565<br>1565|1565|1565|1565<br>1565<br>1565<br>1565|1565|

t statistics in parentheses: * p<0.10, ** p<0.05, *** p<0.01. Errors clustered at cluster-level. Base category is “Self-Employment” 44
**Table 12.** LPM regressions- effects of norms and personality traits on wage employment  (vs. self-employment)- women sample

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||_Norms_|_Norms+_<br>_Controls_|_Norms+_<br>_Controls+_<br>_Personalit_<br>_y_|_Norms+_<br>_Controls+_<br>_Impulsive_|_Norms+_<br>_Controls+_<br>_Work_<br>_Central_|_Norms+_<br>_Controls+_<br>_Tenacity_|_Norms+_<br>_Controls+_<br>_Polychroni_<br>_city_|_Norms+_<br>_Controls+_<br>_Locus of_<br>_Control_|_Norms+_<br>_Control+_<br>_Achievem_<br>_ent_|_Norms+_<br>_Control+_<br>_Power_<br>_Motivation_|_Norms+_<br>_Controls+_<br>_Organized_|_Norms+_<br>_Controls+_<br>_Optimism_|
|Traditional|-0.003*|0.001|0.000|-0.014***|0.001|-0.001|0.005|0.002|0.014|0.009|0.014*|0.001|
||(-1.73)|(0.59)|(0.04)|(-2.81)|(0.09)|(-0.09)|(1.00)|(0.24)|(1.48)|(1.50)|(1.67)|(0.07)|
|Age||-0.002|-0.003|-0.003|-0.002|-0.001|-0.001|-0.002|-0.001|-0.000|-0.002|-0.002|
|||(-0.18)|(-0.29)|(-0.32)|(-0.18)|(-0.16)|(-0.13)|(-0.25)|(-0.11)|(-0.05)|(-0.25)|(-0.25)|
|Age_sq||-0.000|-0.000|-0.000|-0.000|-0.000|-0.000|-0.000|-0.000|-0.000|-0.000|-0.000|
|||(-0.69)|(-0.59)|(-0.55)|(-0.70)|(-0.71)|(-0.75)|(-0.62)|(-0.78)|(-0.82)|(-0.63)|(-0.63)|
|Married||-0.018|-0.018|-0.012|-0.018|-0.019|-0.022|-0.016|-0.020|-0.022|-0.013|-0.016|
|||(-0.42)|(-0.42)|(-0.29)|(-0.43)|(-0.45)|(-0.51)|(-0.37)|(-0.46)|(-0.53)|(-0.30)|(-0.37)|
|At least secondary education||0.125**<br>*|0.131***|0.126***|0.126***|0.127***|0.127***|0.129***|0.125***|0.127***|0.116***|0.126***|
|||<br>(3.30)|(3.49)|(3.36)|(3.30)|(3.42)|(3.33)|(3.40)|(3.32)|(3.39)|(3.05)|(3.31)|
|Gender of head(male=1)||0.049|0.056|0.048|0.047|0.053|0.052|0.046|0.040|0.056|0.060|0.039|
|||(0.56)|(0.62)|(0.56)|(0.53)|(0.60)|(0.58)|(0.51)|(0.45)|(0.61)|(0.67)|(0.44)|
|Muslim(Christian is base)||-0.131**|-0.127**|-0.127**|-0.133**|-0.128**|-0.129**|-0.131**|-0.126**|-0.125**|-0.138**|-0.133**|
|||(-2.37)|(-2.31)|(-2.31)|(-2.40)|(-2.32)|(-2.31)|(-2.35)|(-2.29)|(-2.27)|(-2.48)|(-2.36)|
|Spousepresent in household||-0.036|-0.044|-0.035|-0.034|-0.039|-0.039|-0.038|-0.022|-0.037|-0.046|-0.027|
|||(-0.39)|(-0.47)|(-0.39)|(-0.37)|(-0.42)|(-0.43)|(-0.40)|(-0.24)|(-0.40)|(-0.51)|(-0.29)|
|Household size||-0.009|-0.009|-0.009|-0.009|-0.009|-0.008|-0.009|-0.009|-0.009*|-0.009|-0.009|
|||(-1.58)|(-1.60)|(-1.65)|(-1.53)|(-1.60)|(-1.52)|(-1.60)|(-1.63)|(-1.70)|(-1.61)|(-1.60)|
|Poor||-0.019|-0.013|-0.021|-0.018|-0.019|-0.020|-0.019|-0.022|-0.020|-0.020|-0.014|
|||(-0.52)|(-0.34)|(-0.54)|(-0.48)|(-0.50)|(-0.53)|(-0.52)|(-0.59)|(-0.52)|(-0.52)|(-0.36)|
|Urban||0.056*|0.051|0.055*|0.054*|0.056*|0.057*|0.054*|0.057*|0.056*|0.058*|0.052|
|||(1.72)|(1.52)|(1.67)|(1.71)|(1.71)|(1.73)|(1.66)|(1.77)|(1.70)|(1.77)|(1.64)|
|Ashanti(Northern is base)||-0.029|-0.041|-0.022|-0.031|-0.028|-0.030|-0.032|-0.021|-0.028|-0.031|-0.032|
|||(-0.55)|(-0.77)|(-0.43)|(-0.59)|(-0.54)|(-0.57)|(-0.60)|(-0.41)|(-0.54)|(-0.59)|(-0.61)|
|Impulsive|||-0.020|-0.280***|||||||||
||||(-0.81)|(-2.98)|||||||||
|Work centrality|||0.012||0.008||||||||
||||(0.61)||(0.12)||||||||

45
|Tenacity|-0.010||-0.030|||||||
|---|---|---|---|---|---|---|---|---|---|
||(-0.42)||(-0.36)|||||||
|Polychronicity|-0.007|||0.066||||||
||(-0.38)|||(0.73)||||||
|High internal locus of control|-0.029||||-0.016|||||
||(-1.41)||||(-0.17)|||||
|Achievement|-0.003|||||0.127||||
||(-0.11)|||||(1.20)||||
|Power motivation|-0.024||||||0.074|||
||(-1.09)||||||(1.14)|||
|Organized|0.007|||||||0.134||
||(0.40)|||||||(1.57)||
|Optimism|-0.028||||||||-0.030|
||(-1.03)||||||||(-0.29)|
|Traditional*Impulsive||0.006***||||||||
|||(3.06)||||||||
|Traditional*Work centrality||0.000||||||||
|||(0.05)||||||||
|Traditional*Tenacity|||0.000|||||||
||||(0.21)|||||||
|Traditional*Polychronicity||||-0.002||||||
|||||(-0.88)||||||
|Traditional*internal control|||||-0.000|||||
||||||(-0.18)|||||
|Traditional*Achievement||||||-0.004||||
|||||||(-1.43)||||
|Traditional*Power motivation|||||||-0.002|||
||||||||(-1.51)|||
|Traditional*Organized||||||||-0.003*||
|||||||||(-1.67)||
|Traditional*Optimism|||||||||-0.000|
||||||||||(-0.03)|
|_N_<br>883<br>883|883|883<br>883|883|883|883|883|883|883|883|

t statistics in parentheses: * p<0.10, ** p<0.05, *** p<0.01. Errors clustered at cluster-level. Base category is “Self-Employment” 46
**<u>Table 13.</u>** <u>LPM regressions- effects of norms and personality traits on wage employment  (vs. self-employment)- men sample</u>

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||_Norms_|_Norms+_<br>_Controls_|_Norms+_<br>_Controls+Pe_<br>_rsonality_|_Norms+_<br>_Controls+_<br>_Impulsive_|_Norms+_<br>_Controls+_<br>_Work_<br>_Central_|_Norms+_<br>_Controls+_<br>_Tenacity_|_Norms+_<br>_Controls+_<br>_Polychronici_<br>_ty_|_Norms+_<br>_Controls+_<br>_Locus of_<br>_Control_|_Norms+_<br>_Control+_<br>_Achieve_<br>_ment_|_Norms+_<br>_Control+_<br>_Power_<br>_Motivation_|_Norms+_<br>_Controls+_<br>_Organized_|_Norms+_<br>_Controls_<br>_+_<br>_Optimis_<br>_m_|
|Traditional|-0.004*|0.001|-0.000|0.001|0.003|0.002|0.001|0.012|0.013|-0.006|0.015**|0.030**|
||(-1.78)|(0.55)|(-0.02)|(0.09)|(0.35)|(0.18)|(0.13)|(1.65)|(1.21)|(-0.73)|(2.14)|(2.23)|
|Age||-0.005|-0.011|-0.006|-0.004|-0.006|-0.005|-0.010|-0.009|-0.005|-0.006|-0.007|
|||(-0.45)|(-0.89)|(-0.53)|(-0.30)|(-0.51)|(-0.45)|(-0.87)|(-0.77)|(-0.42)|(-0.48)|(-0.60)|
|Age_sq||0.000|0.000|0.000|0.000|0.000|0.000|0.000|0.000|0.000|0.000|0.000|
|||(0.15)|(0.60)|(0.23)|(0.00)|(0.22)|(0.16)|(0.55)|(0.49)|(0.14)|(0.19)|(0.27)|
|Married||0.055|0.063|0.055|0.055|0.060|0.055|0.067|0.064|0.049|0.055|0.061|
|||(0.74)|(0.88)|(0.75)|(0.74)|(0.80)|(0.74)|(0.91)|(0.88)|(0.66)|(0.75)|(0.85)|
|At least secondaryeducation||0.134**|0.121**|0.133**|0.132**|0.135**|0.134**|0.130**|0.131**|0.136**|0.133**|0.122**|
|||(2.46)|(2.31)|(2.45)|(2.42)|(2.47)|(2.47)|(2.46)|(2.41)|(2.51)|(2.41)|(2.24)|
|Gender of head(male=1)||0.150|0.186|0.152|0.154|0.142|0.151|0.164|0.152|0.147|0.158|0.169|
|||(1.06)|(1.29)|(1.07)|(1.08)|(0.99)|(1.06)|(1.13)|(1.08)|(1.05)|(1.11)|(1.18)|
|Muslim(Christian is base)||-0.121**|-0.110**|-0.118**|-0.118**|-0.122**|-0.121**|-0.112**|-0.132**|-0.119**|-0.115**|-0.120**|
|||(-2.35)|(-2.26)|(-2.30)|(-2.29)|(-2.35)|(-2.35)|(-2.32)|(-2.59)|(-2.32)|(-2.26)|(-2.31)|
|Spousepresent in household||-0.194**|-0.228***|-0.196**|-0.193**|-0.199**|-0.194**|-0.223***|-0.204**|-0.194**|-0.193**|-0.208**|
|||(-2.35)|(-2.80)|(-2.38)|(-2.35)|(-2.41)|(-2.34)|(-2.71)|(-2.53)|(-2.40)|(-2.35)|(-2.57)|
|Household size||-0.017*|-0.014|-0.016*|-0.017*|-0.017*|-0.017*|-0.015|-0.016*|-0.018*|-0.017*|-0.016*|
|||(-1.77)|(-1.50)|(-1.73)|(-1.77)|(-1.75)|(-1.77)|(-1.55)|(-1.67)|(-1.87)|(-1.72)|(-1.70)|
|Poor||-0.061|-0.070|-0.061|-0.064|-0.061|-0.061|-0.067|-0.059|-0.060|-0.059|-0.068|
|||(-1.16)|(-1.38)|(-1.17)|(-1.23)|(-1.17)|(-1.16)|(-1.31)|(-1.12)|(-1.15)|(-1.14)|(-1.35)|
|Urban||0.080|0.069|0.080|0.080|0.082|0.080|0.065|0.085|0.082|0.083|0.060|
|||(1.22)|(1.12)|(1.23)|(1.21)|(1.25)|(1.22)|(0.99)|(1.28)|(1.29)|(1.26)|(0.95)|
|Ashanti(Northern is base)||-0.062|-0.032|-0.062|-0.055|-0.063|-0.061|-0.054|-0.058|-0.057|-0.060|-0.070|
|||(-1.08)|(-0.61)|(-1.08)|(-0.95)|(-1.10)|(-1.06)|(-0.99)|(-0.99)|(-1.00)|(-1.02)|(-1.20)|
|Impulsive|||-0.040|-0.037|||||||||
||||(-1.10)|(-0.28)|||||||||
|Work centrality|||-0.070**||-0.017||||||||
||||(-2.42)||(-0.19)||||||||
|Tenacity|||0.014|||0.028|||||||

47
||||(0.51)||(0.30)||||||
|---|---|---|---|---|---|---|---|---|---|---|
|Polychronicity|||0.002|||-0.002|||||
||||(0.06)|||(-0.02)|||||
|High internal locus of control|||-0.091***||||0.053||||
||||(-3.55)||||(0.58)||||
|Achievement|||0.079**|||||0.198|||
||||(2.02)|||||(1.58)|||
|Power motivation|||0.015||||||-0.041||
||||(0.55)||||||(-0.43)||
|Organized|||-0.047*|||||||0.136*|
||||(-1.92)|||||||(1.76)|
|Optimism|||-0.016|||||||0.292*|
||||(-0.44)|||||||(1.89)|
|Traditional*Impulsive||||0.000|||||||
|||||(0.08)|||||||
|Traditional*Work centrality|||||-0.000||||||
||||||(-0.23)||||||
|Traditional*Tenacity|||||-0.000||||||
||||||(-0.06)||||||
|Traditional*Polychronicity||||||0.000|||||
|||||||(0.07)|||||
|Traditional* internal control|||||||-0.004*||||
||||||||(-1.67)||||
|Traditional*Achievement||||||||-0.003|||
|||||||||(-1.10)|||
|Traditional*Power motivation|||||||||0.002||
||||||||||(0.84)||
|Traditional*Organized||||||||||-0.003**|
|||||||||||(-1.98)|
|Traditional*Optimism||||||||||<br>-0.008**|
|||||||||||(-2.24)|
|_N_|682|682|682|682|682<br>682|682|682|682|682|682<br>682|

t statistics in parentheses: * p<0.10, ** p<0.05, *** p<0.01. Errors clustered at cluster-level. Base category is “Self-Employment” 48