# Introduction romoting entrepreneurial activities are important strategies for sustainable economic development. Entrepreneurship is argued to be a viable alternative to industrial recruitment and an economically sustainable development strategy (Petrin, 1994). Moreover, entrepreneurial activity has been found to have strong effects on economic growth and job creation (Gartner, Shaver and Reynolds2004; Marshall and Samal, 2006). For instance, Geaeser, Rosenthal and Strange (2009) suggest that if Henry Ford and Alfred Sloan do not exist, the economic history of Detroit, MI would not have occurred. Therefore, it is important to understand how to support and motivate entrepreneurship. To develop programs that can provide effective support and promote entrepreneurship, it is important to understand what drives entrepreneurial intents, actions and successes. However, there is no coherent theory of entrepreneurship. Rich entrepreneurial literature focuses on analysis of correlations between socio-economic individual and environmental factors as well as entrepreneurial intents, actions and successes. Also, the majority of data are collected using urban samples. Among the most well known data are the Panel Study of Entrepreneurial Dynamics (PSED) and the Global Entrepreneurship Monitor (GEM). The recommendations for entrepreneurial educational and support programs are being developed mostly based on the results of the analysis of urban samples. This neglect of rural entrepreneurs leads to the following two questions: one "is rural entrepreneurship different from urban entrepreneurship?" Second, "if so, then how are entrepreneurial programs that target rural areas different from the programs that target urban areas?" Few studies have looked at rural entrepreneurship. Scorsone (2003) said rurality is the influential entrepreneurial resources which can provide both opportunities and constraints for rural entrepreneurs. They studied the rurality characteristics as an entrepreneurial milieu in Europe. Dabson (2001) noted the importance of rural entrepreneurship and suggested rural entrepreneurs on the map in the aspect of physical infrastructure and farm support. However, many studies on rural entrepreneurship lack access to data and empirical analyses. Most data suggest that the rate of entrepreneurship in rural regions is consistently lower than the rate of entrepreneurship in urban regions (e.g. Marshall and Samal, 2006;Eurobarometer, 2007). However, it is not clear why this difference occurs between rural and urban areas. Literature has suggested two potential explanations one possible explanation is that urban areas offer more social and economic resources. Therefore they create a better environment for entrepreneurial intentions and actions (Raphael Dar-el and Daniel Felsenstein, 1990; Li Yu, Peter and Robert, 2009). The other possible explanation of economic inequality between rural and urban areas is cultural differences. Cultural effects are geographicalspecific identities and most likely can help explain the different rates of entrepreneurs between rural and urban areas (Edward J. Malecki, 1993). A clear understanding of the driving forces behind the entrepreneurial intentions and actions in rural and urban settings has important implications for entrepreneurial education and support programs. If the resources are primarily responsible for the urban-rural gap in entrepreneurial activities, then the main recommendation for the support programs would be to focus on providing more resources to rural regions. Whereas, if the inherent cultural differences are primarily responsible for the urban-rural gap in entrepreneurial activities, then the programs that target rural entrepreneurs need to be designed differently from the programs that target urban entrepreneurs. The focus of the analysis in this paper is on determinants of entrepreneurial intentions (i.e. on characteristics of nascent entrepreneurs) for the following two reasons. First, it has been found that the only consistent predictor of entrepreneurial actions is entrepreneurial intentions (Krueger, 1999). Second, by comparing characteristics of nascent and active entrepreneurs, it is possible to identify the group of nascent entrepreneurs that never progressed from intentions to actions, and investigate the particular barriers they face in order to design a more effective support programs that will work against these barriers. # II. # Literature Review The creation of new businesses is encouraged because of a thought that entrepreneurs and small businesses reinvigorate markets (Gartner et al., 2004). Many studies have identified factors that are thought to be essential and effective in motivating the establishment of new firms. # III. # Entrepreneurship Supports for Economic Growth Entrepreneurs are thought to be proactive because they utilize resources effectively in the market, and as a result spur economic development. Many studies have explored the positive effects of entrepreneurship on economic development. Westhead and Wright, (2005) showed positive relationship between entrepreneurs and economic growth and studied the impact of different kinds of entrepreneurship on economic growth. As a result, among the four types of new business creation behaviours, high growth entrepreneurship showed a significant impact on the economic growth. Schmitz (1989) fostered Romer's macroeconomic model (1986) which focuses on the number of firms and outputs. The results suggested that both endogenous entrepreneurship and external effects from the entrepreneurs are key factors of economic growth. Wennekers et al. (2005) examined that there are u-shaped relationships between the rate of nascent entrepreneurs and economic development. Moreover, Wennekers et al. (2005) found that an increase in the rate of entrepreneurship (number of business owners per labor force) leads to lower levels of unemployment in 23 OECD countries in the period 1984 through 1994. # IV. Determinants of Entrepreneurship in Urban Samples An important factor of entrepreneurial behaviour is the individual characteristics, specifically human capital, especially work experience and educational background (Gartner et al, 2004) and push and pull effects providing motivations for people who are considering start a new business. # a) Push and pull effects One of the most critical factors in entrepreneurship is motivation. Push and pull effects on entrepreneurship spur the creation of nascent entrepreneurs. Starting a new business does not happen by chance (Wennekers et al. 2005). When people choose to begin their own businesses, they compare the expected profits from the new enterprise with their stream of current incomes. Even if an individual is gainfully employed, he/she might be interested in the potential for higher earnings. These are pull effects. When someone feels that the current situation is unfruitful or an individual cannot fund gainful employment, this is a push effects. The push and pull effects are strong motivators for starting firms as well as continuing enterprises (Shapero and Sokol, 1982). If the current economic conditions are good, the pull effects are typically larger than the push effects (Carrasco, 1999). The push and pull effects differ with location: urban entrepreneurs are more likely to start a business due to disagreements with colleagues and management compared to rural entrepreneurs (K. Nielsen and L.C. Freire-Gibb, 2010). In addition, urban entrepreneurs are more likely to start new businesses because of their networking opportunities. We can assume that disagreements with colleagues and management are push factors because these factors curb to continue current employment, and spur people to create new businesses. Wennekers et al. (2005) studied the relationship between job satisfaction and the decision to become an entrepreneur. Predictably, their results showed that people who are more unsatisfied in their previous workplace are more likely to establish a new business. And the main examples of push factors are workplace distress, anxiety of losing a job, unemployment rate and market condition (Wennekers et al., 2005;Gartner et al, 2004). The main examples of pull factors are expectation of life satisfaction and population growth (Gartner et al 2004). # b) Personal background characteristics It is important to review other factors that determine entrepreneurship as well. Although entrepreneurship has been found to provide many positive benefits, very little is known about the entrepreneurial process. How and why do new research programs such as the Panel Study of Entrepreneurial Dynamics (PSED) and the Global Entrepreneurship Monitor (GEM), have provided some important information about individuals who are involved in starting new entrepreneurial ventures and the key features of the business creation process. An important note to consider is that no comprehensive theory of entrepreneurship exists; rather, scholars have focused their efforts on understanding different components of the phenomenon. One important line of research has focused on the determinants of entrepreneurial intentions which have been found to be the single best predictor of entrepreneurial actions and eventual successes (Katz and Carter 1988). Studies have identified two groups of factors that significantly affect entrepreneurial intentions: individual (personal) and contextual (surroundings) characteristics. Among individual characteristics, researchers have primarily worked with the concept of entrepreneurial self-efficacy. Self-efficacy refers to a personal belief that one can successfully deal with various challenges associated with starting and operating a new business (Bandura, 1989). Chen Greene and Crick (1998) found that entrepreneurial selfefficacy increases with one's intention to establish a business and that business founders had higher selfefficacy with respect to innovation and risk taking than non-founders. Other individual characteristics are demographic factors. Some of the demographic factors: gender, age, education level, marital status and ethnicity are repeatedly reported to strongly correlate with selfemployment and modulate the effect on determinants of entrepreneurial intentions and actions (Wilson, Kickul and Marlino 2007). For example, according to Carter and Brush (2004), women (4.2%) are less likely to be involved in the workforce than men (7.6%). There is a negative association between income and the likelihood of becoming an entrepreneur (Reynolds S. Camp and Bygrane 2001). Evans and Leighton (1989) studied that low-wage people are likely to start a new business. Green and Owen (2004) reported that the decline in family size and in marriage duration provide an increased motivation for female labour force participation. However, the presence of children influences the employment rates of women and men in opposite directions (OECD, 2002) -parenthood negatively influences female employment while positively influencing male employment. Mothers are less likely to be full-time employees than women without children. Marital status is significantly different between start-up entrepreneurs and other groups. The married rate is 58.6% in nascent entrepreneurs and 51.6% in comparison control group (not involved with a business start-up) (Brush and Manolova;. As for tenure (amount of time living in the present location) among the nascent entrepreneurs, 16.3% have resided in rural areas for 30 years more, however, in case of the comparison group 26.8% have lived in rural areas for 30 years more. The most nascent entrepreneurs are established residents in the place where they began a new business (Reynolds, 2004). # V. Comparison of Economic and Social Characteristics of Rural and Urban Regions Contextual researchers have differentiated between objectively available economic resources and individual perception about the availability of necessary resources. Baum and Oliver (1992) quoted that in regions with high population density, there are more opportunities to gain effective knowledge and create extensive social networks, but there is also intense competition. During demographic transition, if population growth initially accelerates, the economy experiences faster consumption growth, productivity growth, and entry during this initial period (Peretto, 1998). Carree, Thurick and Surley (2002) reported that the nascent entrepreneurship shows a U-shape relationship per capita income as compared to 23 Organization for Economic Co-operation and Development (OECD) countries during 1976-1996. Evans and Jovanovic (1989) and Blanchflower and Meyer (1994) suggest that increased unemployment leads to an increase in startup activity, since the opportunity cost of not starting a firm has decreased (Push effect). Economic resources, education, government support programs and local networks may exist in a community, but they might be ineffective tools for helping individuals starting new businesses. Therefore, the availability of resources is not necessarily the key factor to assist entrepreneurs, but the individual's perception of the usefulness and available resources influences individual entrepreneurial intent. # VI. Determinants of Rural Entrepreneurship and Comparison them with Determinants of Urban Entrepreneurship Individuals can be easily influenced by contextual environments. Geographic location dictates input costs such as rent, labour, and capital, scale of market, and regulations and taxes. Thus, an individual decision to start a new business would vary depending on location. Studies of urban entrepreneurs are more prevalent than those on rural entrepreneurs. In contrast to urban areas where there are arrays of different types of self-employed businesses, in rural areas, self employed farm businesses tend to dominate (Gladwin et al., 1990). Peretto, (1998) found distinguishing factors between founders and non-founders of enterprises and differences between rural and urban entrepreneurs using 1987 data from North Florida and New England. They adopted a probit model to understand the different decision making strategies between rural and urban areas. As a result of discriminating factors between founders and non-founders, psychological variables are not significantly different for entrepreneurs starting new businesses in rural as opposed to urban areas. However, prior experience in starting firms and the proportion of currently owned firms have a positive effect, while education and management period have a negative effect on the start of new businesses. The largest effect on the probability of having starting a new business is previously owned other businesses. Generally, the authors found that rural areas tend to be more personal, peaceful, clannish, and have a smaller number of consumers than urban areas therefore community and financial management information is useful to start new businesses. Marshall and Samal (2006) compared human and financial capital of start-up entrepreneurs between rural and urban areas. They collected data from the 2004-2005 Indiana start-up entrepreneurs' workshop. They used a logistic regression -the dependent variable was the binary for whether to start-up a business or not, and the independent variables were the personal demographics, human capital, financial capital, and location. They implied that higher net worth (more than $50,000) and residence in cities were positive effects on the start of a new business, while home ownership is a negative effect on the establishment of new firms. Analyzing the combined effects, they estimated the probabilities of a female homeowner, employed during the last six months, having retail chain, graduate degree, greater than net worth $50,000; living in cities had 99.14% probability starting new businesses. And a female homeowner, employed during the last six months, not having retail chain, bachelor's degree, less than net worth $50,000, living in country sides had 18.60% probability starting new businesses. They determined that the critical factors to participate in new enterprises are net worth and residential places. Nielsen and Freire-Gibb (2010) studied the behaviour of female entrepreneurs in rural and urban areas. They found that urban women had more education, higher socio-economic status, and middle level of investment than rural women in Bangalore. They categorized the factors which were effective on the creation of new businesses into three aspects: personal characteristics, socio-economic characteristics and enterprise-related variables. For personal characteristics, education, marital status, birth order, and family support were positively related to the start of new businesses; however, age and family dependency ratios were negatively related to new firm development in both rural and urban areas. The socio-economic characteristics included socio-economic status, sociopolitical participation, and mass-media participation was positively related with entrepreneurial behaviour. In enterprise related variables, ownership of enterprise, extent of investment, and training received are significantly related to participation in enterprises in both rural and urban areas. However, institutional support only affected the urban areas, and financial assistance was not related to either rural or urban areas. Nielsen and Freire-Gibb (2010) studied how rural and urban areas influence the identity and network of entrepreneurs and non-entrepreneurs in Denmark. They used logistic regression analysis and data from the Integrated Database for Labour Market Research (IDA), as well as a questionnaire survey on Danish wageearner and entrepreneurs in 2008. The independent variables were categorized by demographics, identity, start-up motivation, and network. The results were that there were no highly significant differences in geographic effects and in the case of identity such as intrinsic values score, extrinsic values score, convenience, finances, co-workers, career, entrepreneurial traits score, risk seeking score, tolerance of ambiguity, need for achievement, locus of control, desire for independence, optimism, and creativity between rural and urban areas, the entrepreneurial traits were not significantly different between rural and urban areas. However, urban entrepreneurs are more creative, less motivated by the financial side of work, more encouraged by the career side of work, and more likely to start a new business. Start-up motivations such as a new product/service, becoming one's own employer, new work challenges, higher earnings, control work tasks and hours, and the ability to support family/friends were also not significantly different across the two areas. However, rural entrepreneurs were more likely to start a new business by converting a hobby into their career. Urban entrepreneurs were more likely to contact former schoolmates, use professionals, and contact other entrepreneurial friends, but less likely to contact former colleagues, who were influenced by family entrepreneurs rather than rural entrepreneurs. # VII. # Research Methodology Data were collected from a sample of people to determine the relationship between decision to start a new business (the dependent variable) individual and contextual resources (the independent variable). The theoretical population of the study consists of the entire entrepreneurs in the country. However, the study was restricted to plateau state. A simple random sampling technique was used in this study. The primary data consists of a number of items in well-structured nondisguised questionnaire that was administered to and completed by the respondents. The decision to structure the questionnaire is predicated on the need to reduce variability in the meanings possessed by the questions as a way of ensuring comparability of responses. The return rate of completed questionnaire was 80% as we were able to get back 48 out of 60 questionnaires given to our respondents. Thus, only 48 questionnaires were used for final analysis in this study. Data collected from the questionnaire were analysed, summarised and interpreted according with the aid of descriptive statistical techniques such as total score and simple percentage. T-tests were used to compare means between two different groups with the help of statistical packages for social science (spss). The trends, and patterns and relationship among data were identified and interpreted. # VIII. # Testing of Hypothesis and Interpretation of Results Hypothesis 1: The gap in rural and urban entrepreneurship is due to a difference in individual and contextual resources. The individual resources include demographic characteristics and entrepreneurial self-efficacy. To be specific, we investigate how gender, age, employment status, income, education, residence (tenure), household size, presence of children and marital status differ across rural and urban settings. Contextual resources include social resources and economic resources. As a proxy for social resources, this study adopted the perceived level of community support. When businesses start, community support should be considered as well as one's own resources or economic resources. The community is a society which has common interests -new entrepreneurs get information as well as financing opportunities from the community. The considerable economic resources are income per capita, and unemployment rate. Moreover, we include population density and population growth as economic resources. If income per capita is high, then purchasing power is increased and the place is good for beginning a business. Because urban areas have higher living costs and prices compared to rural areas, and there are better chances of getting a higher salary than in rural areas income per capita in urban areas might be higher than in rural areas. If the unemployment rate is high, then the economy is not vivid and the purchasing power would decrease even though the unemployment rate could spur making their businesses. Because of diversity in job opportunities, unemployment rates of cities are less than rural areas. IX. # Description of Variables The dependent variable is the decision to start a new business-this is a binary variable: if the answer is "yes" then the code is "1", otherwise it is "0". Individual characteristics include gender, age, ethnicity, unemployment status education, tenure, number of household members and children, marital status, and entrepreneurial self-efficacy. Gender is a dummy variable: if the respondent is "male" then the code is "1", if not it is "0". In age, the reference group is 45-64 years old, and the other two age groups are people under 44 years old and people older than 65 years old. The unemployment status code is "1", and employment (full time, part time, or temporary) is "0". For income, the reference group is under ?100,000, so less than ?100,000 is coded as "1"; all income of ?100,000 and above is coded as "0". The middle education group is the reference group, so the low and high education groups are included in the analysis. If a person lived in their place of residence for more than 5 years, then the code is "1"; those who lived 5 years or less in their place of residence are coded "0". The household members and number of children are coded to numbers. If the respondents are married, then the code is "1". If they are not, it is "0". Factor analysis with varimax rotation was used to reduce the number of variables in the analytic model by creating single variables to represent highly correlated statements. The varimax rotation in factor analysis maximizes the sum of the variances of the squared loadings; if there are high correlations the number of factors is decreased. The cronbach alpha statistic of reliability was used to evaluate possible composite variables. Two variables, entrepreneurial selfefficacy and perceived community support were derived for highly correlated statements, as shown in Table 2. In entrepreneurial self-efficacy, the original questions included four statements; "If I work hard, I can successfully start a new business," "Overall, my skills and abilities will help me start a business," "My past experience will be very valuable in starting a business," and "I am confident I can put in the effort needed to start a business." The possible responses are ranged from 1 ("strongly disagree") to 5 ("strongly agree"). These four statements are highly correlated and can be reduced to one common factor. As a result of factor analysis using varimax rotation, the scale is reduced to one factor which represents the entrepreneurial self-efficacy. The eigenvalue is 2.407, and the explanation power of variance is 60%. Since the Cronbach alpha showing reliability is 0.772, we can use this factor. In perceived community support, the original questionnaire consisted of five statements: "Young people are encouraged to start their own businesses in my community," "State and local governments provide good support for people starting new businesses in my community," "Bankers and investors go out of their way to help new businesses get started in my community," "Other community groups provide good support for and can be people starting new businesses in my community," and "The local media does a good job of covering local business news in my community." These are highly correlated and these are reduced to one common factor. The eigenvalue is 2.423 and the variance is 48%. The cronbach alpha is 0.726, so we can use this factor. other community groups provide good support for .729 X. # Summary of Research Findings As the determinants of entrepreneurship, we referred to the previous studies and compared two aspects: individual resources and contextual resources. Using these independent factors, we conducted T-tests to compare different resources in rural and urban areas. Then we studied the motivation of rural and urban entrepreneurs and assumed rural entrepreneurs have higher push effects than urban areas, urban entrepreneurs have higher pull effects than rural areas. # XI. T-Test Results (Resource Differences) T-tests are useful when comparing means between two different groups. Using calculated weights, we conducted the weighted T-test. The last column in table 1, we have results of the weighted T-test. As expected, the plan to start a business rate is higher in urban areas than in rural areas. Urban entrepreneurs tend to higher income, education, income per capita, and population density than rural entrepreneurs. These results are consistent with our hypothesis; it is because cities tend to more markets, job opportunities, and schools, so the people who live in cities are more likely to start a new business receiving a higher income and education. Low income, low education, tenure, and unemployment rate factors are more significant and influential in rural areas than in urban areas. These results support our hypotheses. Rural areas show long tenure, which means that rural areas are static and conservative. Rural areas do not have many universities, so the educational opportunities are fewer than in urban areas. This means that rural residents tend to earn a lower income than their urban counterparts. Unemployment rates are also higher in rural areas than in urban areas because there are fewer job opportunities. These results show that the entrepreneurs who live in cities tend to be competitive and more employable. The entrepreneurs who live in rural areas have a propensity to continue living their secure lifestyles -they don't move frequently from their location. Nevertheless, household numbers in rural areas are lower than in cities. This result differs from the hypothesis, perhaps because in rural areas, there is lack of young people and the elderly live without their children, so the number of household members is lower than in urban areas. In contrast to what was proposed in the hypothesis, expected self efficacy, the perceived community support, age, gender, number of children, and marital status are not significantly different between urban and rural areas. These results differ from the study by Marshall (2006) which showed that the female in urban areas is more likely to start a business than the female in rural areas. According to these results, there is not big difference in individual characteristics and social networks between urban and rural areas. It appears that environment does affect infrastructure such as available education and job market resources though. Overall, urban areas have more vitality than rural areas since they have attractions for entrepreneurs looking to start a new business, such as individual and economic resources. This comparison is a superficial analysis of the two different locations. # XII. # Conclusions and Implications We investigated the rate of rural and urban entrepreneurship and analyzed what made the difference between rural and urban settings. When we compared the rural and urban areas, the main gap seemed to be in resources. In rural areas, there are fewer economic resources and education or job opportunities; however, it has fruitful potential. Rural areas have lower production and labour costs, as well as good environmental resources. In urban areas, even though there is great demand, easy-to-find financial and labour resources, and good promotion programs, there are some problems--such as high competition and low environmental quality. As we expected, urban areas have fluid economic resources. Economic resources are important when starting a new business. But, the individual resources are also crucial variables. Such individuals including men, younger, less tenure, married people who are more likely to start a new business. Moreover, innate characteristics are more important than community or contextual resources. Self-efficacy is the most representative variable among innate characteristics; if someone has high self-efficacy, he/she is more likely to create a new business. This is a good motivation and pull effect, even when the novice entrepreneurs run into trouble, those with this self-efficacy factor suffer less harshly and are wiser than other people. This term is not unfamiliar in economics; however, it is closer to the practical model and world, demonstrating that these physical factors should be considered. # XIII. # Policy Implications Entrepreneurs play a pivotal role in business activities and spur economic growth. Although entrepreneurs are highly proactive and self-motivated, if policy makers create favourable business environments, then the start-up businesses would be invigorated and have greater longevity. This study analyzed the behaviour of nascent entrepreneurs with individual, community and economic environment characteristics in rural and urban areas. Most entrepreneurs programs focus on the small entrepreneurs to support their existence or to protect from the closing. This study analyzed the differences between rural and urban entrepreneurs in terms of two aspects: individual/contextual resources, and cultural effects. In accordance with these results, the policies or the related programs can be designed for rural and urban areas. First, after comparing individual and contextual resources in rural and urban areas, as we expected, resources are more abundant in urban areas than in rural areas. Rural areas are dominantly the male, female, old, married people, have long tenure, unemployment status and high population growth rate than urban areas. Urban areas have more young, the low and high income; have short tenure, household number, having children, self-efficacy, income per capita, vulnerability index and population density than rural areas. To reduce the differences between rural and urban areas and to make better places for start-up businesses, rural policy makers should focus on promoting rural areas to be more active, vivid and diverse places. Because rural areas tend to show stationary environments, if the policies or programs are for designed, for more flexible, for movement and communication, then the community will be invigorated and the people living in rural areas get more information to achieve their goals. In the case of urban areas, where young and diverse people live, the motivation for building a new business is higher than in rural areas. However in cities, there are some sorts of negative byproducts accompanied with higher incomes: a high vulnerability index and a high population density. So the policies in urban areas should concentrate on the alleviation of negative effects with development rather than on the stimulation of enthusiasm of individuals. Secondly, we found different cultural effects between rural and urban areas. In rural areas, the people who are male and older, have a lower income, and live for shorter periods in their current residence are more likely to participate in new businesses. These people tend to be weak and vulnerable, having less experience, capital or information. Thus, rural policymakers should provide a way to manage risks for new entrants. In urban areas, the individuals who are young or have high self-efficacy are more likely to establish new firms. However, the perceived community support has a negative effect on a new business. This shows that those in cities believe that it is important to embrace risks, but dependence on other people or programs such as community support are obstacles when opening new enterprises. Even if self-efficacy is a good determinant which highly increases the probabilities of achieving a goal and continues motivation for new frontiers, it is intriguing that this factor is only significant in urban areas. Therefore, urban policy makers should focus on a design to boost self-efficacy for entrepreneurs; however, the specific programs are unclear. We are able to start at this point, casting a tolerant eye over previous experiences or mistakes in psychology, and we can move to more visual and practical programs. Besides, a number of households and having children have a different effect on start-up businesses in rural and urban areas. In rural areas, having fewer household members and having children are good for creating new businesses, while in urban areas having more household members and fewer children is favourable for participants in new businesses. These results imply that in rural areas, smaller families and shorter tenure tend to start new things. Thus, rural policy makers should support the education of children, while providing the adults opportunity to enter consultant programs. On the other hand, in urban areas, new entrepreneurs receive help from their household members, but the effectiveness of children is minor. In cities, the expense for raising children is high, so having children makes parents abandon their new plans or risks Urban policy makers should thus provide financial incentives and risk management for parents starting new businesses. 1t-test1. 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