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Do better entrepreneurial and economic outcomes stem from an increase in the share of migrant populations? Please use evidence from the UK.
The aim of this chapter is to develop an optimal research strategy that aims at achieving the desired results through the use of empirical tradition. The chapter makes use of the “research onion” framework to achieve overall scope of this investigation.
Research methodology has been defined as the overall mechanics adopted by the investigator to achieve the desired outcomes of the research (Bryman & Bell, 2015). According to Zikmund et al (2013), the research methodology is considered as one of the critical areas for the achievement of authenticity, reliability and authenticity. This degree of importance of the research methodology has led to significant attention given by the academic as well practitioners in its development. There is a school of thought within the literature that has pointed out that adoption of a framework or model can facilitate novice investigators to develop optimal research strategy rather than use their personal biases in selection of research methods. These factors have led to the adoption of “research onion” framework that has led to the development of research strategy aligned with this investigation. According to Saunders (2011), research onion is a step-by-step model, where the decisions made in the outer layers of the framework have significant implications in the inner layers of the framework. This is the reason that the rest of the structure of this investigation has been based on the use of “research onion” framework, which is summarised as follows:
Fig: Research Onion Framework (Saunders, 2011)
The outer layers of the research onion framework are related with the research philosophy and research approach related with the investigation. Drawing upon Blumberg et al (2014), epistemological underpinnings of any investigation are correlational with the research philosophy of that investigation and therefore an appropriate selection is required for achieving the overall positive outcomes of the investigation. It is noted that the overall feasible paradigms are seen between the natural and social sciences. The natural science has led to the development of paradigm of realism, which suggests that high degree of objectivity can be used in the understanding of any natural event. On the other hand, the social science has led to the development of paradigm of interpretivism, which suggests that the behaviour of humans can only be recorded through subjective measures (Sreejesh et al, 2014).
The research has also pointed out that there is also the development of middle path between realism and interpretivism, which suggests that human behaviour can also be objectively defined through the adoption of appropriate methods, which is referred to as positivism (Bajpai, 2011). The review of the aim and objectives of this investigation has highlighted that the study falls within exploratory investigation, where the focus is to critically appraise and analyse the relationship between overall share of migrant population and entrepreneurial and economic outcomes within the UK national economy. It is noted that there are number of models and frameworks that have been developed within the literature that are focused on objectively defining the core variables that have been presented within this study. These factors have led to the selection of positivism research philosophy for the purpose of this investigation.
The review of the literature has pointed out that the choice of research philosophy highlights the underlying epistemological factors and therefore has implications on the choice of the research approach. According to Blumberg et al (2014), there are broadly two types of research approaches that are: induction and deduction. Induction operates from observations and develops into a theory, which is the reason it is also referred to as bottom-up approach. On the other hand, deduction operates from the theory towards its use within a certain types of observation, which is the reason it is also referred to as the top-down approach. In the light of the aim and objectives of this investigation, it can be argued that the research falls within the domain of exploratory investigations and therefore is aligned with the research strategy of induction. According to Saunders (2011), rich insights into complex topics are lost, if these topics are reduced to law like generalisations.
The aim of this investigation is to critically appraise and analyse the relationship between overall share of migrant population and entrepreneurial and economic outcomes within the UK national economy. The research objectives are: to critically appraise the impact of size of migrant population on the degree of innovation and business knowledge creation within the context of the UK economy. ; to highlight the channels through which entrepreneurs add value to the entrepreneurship outcomes within the UK economy; and to understand the overall link between entrepreneurial outcomes and the economic development within the context of the UK national economy.
In order to achieve the overall research scope of this investigation that is to appraise and analyse the relationship between overall share of migrant population and entrepreneurial and economic outcomes within the UK national economy, the researcher has adopted qualitative data analysis in the light of the research philosophy adoption of positivism and induction.
The review of the academic literature surrounding data collection has highlighted the importance of objectively defined datasets. The use of quantitative data for the purpose of this investigation has been noted to have three major advantages, which include: (a) the data is audited and peer-reviewed for its use of the migrant implication on the economic outcomes; (b) triangulation of data can be achieved through the collection of data from multiple sources; and (c) diversity of the research objectives can be achieved through the adoption of multiple different datasets (Zikmund et al, 2013).
The quantitative data that has been selected for the purpose of conducting the desired analysis for this investigation has been collected from the quarterly Labour Force Survey (QLFS). The data has been collected by the Office of National Statistics (ONS) and therefore has a reputation of high degree of representability of the UK residents. It is important to note that the quarterly survey is a cross-sectional of the UK population, where the years between 1992 and 2010 have been included within this investigation. The use of LFS data has also number of limitations as it includes a sample of population that consistent of adults, elderly and children, who are residing in the UK at the time of the survey. Furthermore, it is also an important limitation of the survey that the population size in the UK that in included in the survey was only 150,000 respondents in the early 1990s, which has now been reduced to only 100,000 respondents in the 2000s. Although the overall percentage of the immigrants that have been interviewed as part of the LFS has increased from 6.82% in 1992 to 10.41% in 2010, therefore highlighting the overall growth in the immigration population.
Although LFS is a good starting point for understanding the overall changes in the labour force and their implications on the UK economy, which also included the adoption of self-employment and entrepreneurial work. However, there are number of criticisms that have been noted within the literature. According to Blumberg et al (2014), it is noted that LFS surveys inherently can include a higher proportion of native population as large proportion of student accommodations are not included into the survey, where a large number of potential immigrant population is resident. Furthermore, it is also argued by Sreejesh et al (2014) that as LFS is a volunteer arrangement for the collection of data from the population, there can be lower level of immigrants that are willing to participate in the survey, which therefore would not be represented within the survey.
However, in contrast with other datasets available, the researcher has selected the use of LFS survey data between 1992 and 2010, where the key variables that are relevant with the scope of this investigation. The research questions that have developed the overall scope of this investigation have been summarised as follows:
- Do migrant inflows and the size of migrant community affect the process of innovation and business (instead of scientific) knowledge creation?
- Through which channels does immigration enhance entrepreneurial function?
- Do better entrepreneurial outcomes result in faster economic growth?
//Please add the analytical equation here and also highlight the key hypotheses that you have noted from the equation//
In the light of the discussion provided, it can be argued that positivism research philosophy is selected in conjunction with inductive research approach, which are translated into the adoption of quantitative data collection based on LFS datasets between 1996 and 2010. In order to provide the analytical underpinnings for this investigation, the researcher has developed two regression equations comprising of the most important variables relevant to the scope of this investigation. The first equation is focused on highlighting fraction of migrant population in the region effect on business births; while the second equation is focused on highlighting number of national insurance migrant registrations in the region effect on business birth.
The aim of this chapter is to provide empirical research surrounding the scope of this investigation. The focus of this chapter will be towards answering the core questions that have been presented within this investigation.
The aim of this investigation is to critically appraise and analyse the relationship between overall share of migrant population and entrepreneurial and economic outcomes within the UK national economy. In order to achieve this desired outcome, the research scope has been developed with the help of number of research objectives that include: (a) to critically appraise the impact of size of migrant population on the degree of innovation and business knowledge creation within the context of the UK economy; (b) to highlight the channels through which entrepreneurs add value to the entrepreneurship outcomes within the UK economy; and (c) to understand the overall link between entrepreneurial outcomes and the economic development within the context of the UK national economy.
In order to provide the analytical underpinnings for this investigation, the researcher has developed two regression equations comprising of the most important variables relevant to the scope of this investigation. The first equation is focused on highlighting fraction of migrant population in the region effect on business births; while the second equation is focused on highlighting number of national insurance migrant registrations in the region effect on business birth.
The results of the two regression analyses have been summarised as follows:
Fig: Fraction of migrant population in the region effect on Business Births
Fig: Number of National Insurance migrant registrations in the region effect on Business Births
In the light of the analysis conducted, it can be highlighted that the researcher has conducted both ordinary OLS and fixed effect regressions to find differing results. It is noted that the share of migration population is significant at 99%, even when the population and year dummies are used as control variables. However, the fixed effect regression has pointed out that as analysis controls for fixed factors among regions, the share of migrant coefficient loses its significance. Furthermore, it is of importance to note that as both population and year dummies are added in specification for fixed effect analysis FE3, the coefficient on Share of Migrants becomes negative. On the other hand, the migrants number of national insurance registrations in the region effect on business birth remains positive with more than 99% significance level in both ordinary and fixed effect regression analysis.
The aim of this chapter is to provide discussion surrounding the key findings of this investigation within the context of the popular schools of thoughts that have been developed within the topic of immigration, entrepreneurship and economic development.
The aim of this investigation is to critically appraise and analyse the relationship between overall share of migrant population and entrepreneurial and economic outcomes within the UK national economy. In order to achieve the aim of this investigation, the researcher has developed the following set of objectives that defines the overall scope of the investigation: (a) to critically appraise the impact of size of migrant population on the degree of innovation and business knowledge creation within the context of the UK economy; (b) to highlight the channels through which entrepreneurs add value to the entrepreneurship outcomes within the UK economy; (c) to understand the overall link between entrepreneurial outcomes and the economic development within the context of the UK national economy.
The results of the regression analysis has highlighted that there is positive correlation between the migrant population and entrepreneurship. It is noted that all three types of ordinary OLS analysis have controlled for population and year dummies as control variables have shown a positive correlation that is significant with more than 99% significance level. This conclusion can be interpreted in the light of analysis undertaken by Jiang et al (2016) that has pointed out that the underlying reason for this overall high level of entrepreneurship within the migrant population is the result of lack of opportunities within the labour markets for the migrants as compared to that of the natives. This can further be suggested from the observation made by Kushnirovich et al (2017) that has argued that there is aa higher overall motivation among the entrepreneurs to succeed financially in a new national economy as they lack support from their personal networks.
The results of the study has highlighted when analysed for fixed effects regression, which controls for fixed factors among regions, the Share of Migrants coefficient loses its significance. Moreover, when the researcher added both populations and year dummies in specification fixed factor analysis (FE3), the coefficient on share of migrants becomes negative. This is an interesting finding that can be explained from a diverse range of areas that have been noted by the researcher and the review of the popular literature. The research has noted that there are two types of migration within the UK, which are: the controlled; and the uncontrolled (Yasuda, 2016). The controlled migration tend to be focused on the highly skilled or areas of acute skilled shortage in the country. These migrants have a higher degree of scope to be assimilated within the multinationals and local firms that requires these higher or specialised skills (DeLancey, 2014). However, the uncontrolled immigration results in the unskilled migrants to enter the labour force, who tend to have lower degree of acceptance in traditional professional careers due to their immigrant status and lack of skills. It is this segment of the migrant population that tend to move away from the economic hubs due to the cost of living and tend to result in sub-optimal outcome within entrepreneurial careers (Peroni et al, 2016). Furthermore, it is also noted by Lofstrom (2015) that highly skilled migrants tend to have a positive overall assimilation within the cultural change and have a higher overall communication skills and knowledge of the English language. However, the unskilled immigrants that tend to resort to traditional entrepreneurial industries tend to lack to the general interpersonal and English language skills, therefore resulting in sub-optimal outcomes as presented by this investigation.
The review of the research methodology adopted for the purpose of this analysis has highlighted that this investigation has made use of the exploratory nature of the investigation and therefore has adopted positivist philosophy and inductive research approach that has underpinned the overall development of the theoretical and analytical research strategy. Drawing upon Saunders (2011), rich insights into complex topics are lost, if these topics are reduced to law like generalisations, however the critics have argued that such studies are likely to have lower level of applicability to a changing overall situation or a different datasets (Bajpai, 2011). Therefore, in order to achieve higher level of applicability, reliability and authenticity of findings of this investigation, the researcher has recommended that future investigations should use the key findings surrounding migrant population and their implication on the entrepreneurial landscape within the UK and adopt an empirical investigation using primary and secondary datasets. The use of LFS was undertaken within this investigation, however, in further other datasets can be used for a further elaboration of the patterns that have been identified within this investigation. The overall higher level of understanding of the underlying factors surrounding the role played by migrant entrepreneurs would ensure that policymakers are better equipped in developing effective and efficient policymakers to maximise the positive impact of the migration on the development of entrepreneurs that have a positive overall impact on the UK economic development.
In the light of the discussion provided, it can be summarised that the research has pointed out that there is a strong correlation between the percentage of the migrants that become entrepreneurs, however when controlling the fixed factors among regions, the Share of migrants coefficient loses its significance. Furthermore, when the researcher has added both population and year dummies in specification FE3, the coefficient on Share of Migrants becomes negative. The discussion has provided a number of explanations for these results in the context of the popular literature suggesting that highly skilled migrants enter the labour market to become employed by the larger multinationals and local businesses in sectors with skill shortage; however the lower skilled immigrants are likely to choose entrepreneurship. Furthermore, the higher overall cost of living also pushes the lower skilled migrants to peripheral geographic regions therefore having a negative overall implication to their adoption of entrepreneurial careers.
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