Introduction
In recent decades, achieving sustainable employment has become one of the main goals of economic policies. As a result, a large amount of research has been carried out in order to determine the most influential variables on the increase of employment in order to make a suitable economic policy. In this research, variables such as human capital (Kapelras et al., 2019), government spending (Doi et al., 2018), income distribution (Neos et al., 2016) and institutions (Galindo Martin et al., 2021 and Urbano et al., 2019)) have been effective factors in increasing the level of employment. However, important factors can potentially provide a significant portion of new jobs. Therefore, entrepreneurship can be another effective factor in increasing the employment rate.
Over the years, entrepreneurship has been proposed not only as a policy and strategy priority for economic growth (Adertesh, 2018 and Pepra and Adekoya, 2020), but also as an engine for creating employment and poverty alleviation (Desai and Hessels, 2008, Adosi, 2016 and Folster, 2000). In other words, the existing literature has proven that entrepreneurship ensures the welfare, productivity and efficiency of the economy (Bamol, 1990) and acts as a main driving force for promoting innovation, achieving new business ideas and changing economic structures(Adretsch et al., 2002; Fritsch, 2008 and Gomes et al., 2022). Furthermore, entrepreneurial activities in an economy have been proven to contribute to resilient economic performance by introducing innovations, implementing change, promoting and improving competitiveness (Wang et al., 2005). The organizational policy of the European Union also confirms the importance of entrepreneurship as a core competency for employment, growth and personal fulfillment (EC, 2004).
Methodology
In spatial econometrics, spatial effects are added to the performance of periodic or complex regression models (panels). Therefore, in spatial econometrics, sample information has a spatial component. When data has a spatial component, two issues can be raised: (1) Spatial dependence, and (2) Spatial heterogeneity. Before estimating spatial panel models, we need to perform spatial dependence tests and to check the existence of autocorrelation between disturbance terms. The existence of spatial coherence between observations and spatial autocorrelation between disturbance terms indicates the need to use spatial panel models. To do this, Moran, Jerry C, and Jetis Ord J tests are used. The Moran test examines the assumption of spatial autocorrelation between disturbance terms. In spatial econometric models, to model spatial reactions, it is necessary to select the numerical value of spatial directions. For this purpose, we have two sources of assumptions: (1) Position on the coordinate plane, which is expressed by latitude and longitude, so that the distance of any point in the location, or distance of any observation located at any point relative to fixed or central points or observations can be calculated. (2) The source of spatial information is neighborhood, and which expresses the relative location in the space of an observed peripheral unit, compared to other such scales.
Findings
The aim of the current research was to analyze the effect of entrepreneurship on employment in the provinces of Iran during 2013-2020 with a spatial econometric approach. First, in order to check the diagnosis of spatial dependence, the spatial dependence of the provinces was confirmed by Moran's test and based on the significance of the above test and according to the statistical coefficient of the Lagrange test, the research was evaluated in the framework of the spatial Durbin model. According to the results of the research, the entrepreneurship index has positive and significant effect on the employment rate of the target and neighboring provinces (overflow), and this result is coompatible with the findings of other researches, including Zu et al. 2022), Levin and Rubinstein (2018), Ataf and Al Balushi (2015), Miriam and Sandi (2015), Amini et al. (2013), Khoda Muradpour et al. (2018) and Khorsand et al. The research questions were confirmed. In addition, the variables of price index and wage rate have negative and significant effects on the employment rate of the target and neighboring provinces, while the gross domestic product has a positive and significant effect on the employment rate of the target provinces.
Discussion and Conclusion
Based on the results, the suggestions of the present research in order to increase the employment are as follows:
- Financial support for provincial entrepreneurs through the removal of production barriers, the use of up-to-date global technologies in order to create competition with international entrepreneurs and reduce capital risk.
- Presenting specialized trainings in the field of entrepreneurship with the approach of better understanding of investment opportunities, familiarity with different regions and provinces in terms of relative advantages.
- Supporting small and medium enterprises in provincial development programs through incentives, tax exemptions, and government subsidies.
- Stabilizing the price level in order to create a safe environment for encouraging entrepreneurs.
- Adoption of policies to create small and medium industries in rural areas and small towns.
- Establishing provincial meetings between top entrepreneurs for consultation, transfer of experiences, and awareness of existing problems in this field.
- Improving various infrastructures in deprived areas to attract more entrepreneurs.
