Application of decision tree model for prediction of immigration policy in different countries of the world
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Author(s)Viktoriia ApalkovaLink to ORCID Index: https://orcid.org/0000-0001-5185-7571
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Sergiy TsyganovLink to ORCID Index: https://orcid.org/0000-0002-9032-7829
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Nataliia MeshkoLink to ORCID Index: https://orcid.org/0000-0002-0075-3825
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Nadiia TsyganovaLink to ORCID Index: https://orcid.org/0000-0002-5186-8884
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Serhii ApalkovLink to ORCID Index: https://orcid.org/0000-0003-1465-7794
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DOIhttp://dx.doi.org/10.21511/ppm.19(3).2021.42
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Article InfoVolume 19 2021, Issue #3, pp. 513-532
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245 Downloads
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Creative Commons Attribution 4.0 International License
In the past few decades, the ever-increasing dynamics of international migration flows can be observed. At this stage, the governments of major countries in the world are striving to balance the needs of their citizens and the support of immigrants. The paper analyzes factors that affect the immigration policies of various countries and determines the role of ecological factors (such as environmental conditions). The objective of the study is to predict the immigration policies of different countries of the world based on the analysis of the influencing factors, including environmental performance. The research method is based on the use of the RapidMiner software package to build two decision tree models and a static index database of more than 150 countries around the world. The results show that in most cases, the immigration policies of various countries will focus on maintaining the current level of immigration and increasing the number of skilled workers. At the same time, one of the key decision-making factors will be the country’s current immigration level, environmental performance, GDP per capita, and the Education index. One of the main conclusions is that the country’s environmental indicators have begun to become one of the priority values that determine the state immigration policy. This can be explained by the rising global community interest in the challenges of climate change.
- Keywords
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JEL Classification (Paper profile tab)F22, Q56
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References33
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Tables2
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Figures4
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- Figure 1. Classification of the main types of immigration policies based on the UN approach
- Figure 2. General view of 1st and 2nd classification models
- Figure 3. Decision tree for classification of policy on immigration
- Figure 4. Decision tree for classification of immigration policy on highly skilled workers
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- Table 1. Key indicators for calculating the model
- Table A1. Data set for 1st Model “Decision tree for classification of policy on immigration” and 2nd Model “Decision tree for classification of policy on immigration”
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- Adisa, O., & McSharry, P. E. (2020). Female enrollment, child mortality and corruption are good predictors of a country’s UN Education Index (Thesis). Child Mortality and Corruption Are Good Predictors of a Country’s UN Education Index Project.
- Aleksynska, M., & Tritah, A. (2015). The heterogeneity of immigrants, host countries’income and productivity: a channel accounting approach. Economic Inquiry, 53(1), 150-172.
- Anderson, B. (2010). Migration, immigration controls and the fashioning of precarious workers. Work, employment and society, 24(2), 300-317.
- Barnett, J. (2003). Security and climate change. Global environmental change, 13(1), 7-17.
- Bernardini, E. (2019). The highly skilled migrant in contemporary society: a conceptual analysis. Conference Proceedings of the Third International Symposium Od Diaspore Italiane, 29-33. Genova, Italy.
- Cangiano, A. (2012). Immigration policy and migrant labour market outcomes in the European Union: New evidence from the EU Labour Force Survey (Working Paper).
- Chandrasekar, P., Qian, K., Shahriar, H., & Bhattacharya, P. (2017). Improving the prediction accuracy of decision tree mining with data preprocessing. 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC), 481-484.
- d’Albis, H., Boubtane, E., & Coulibaly, D. (2018). Macroeconomic evidence suggests that asylum seekers are not a “burden” for Western European countries. Science advances, 4(6), eaaq0883.
- Détang-Dessendre, C., Partridge, M. D., & Piguet, V. (2016). Local labor market flexibility in a perceived low migration country: The case of French labor markets. Regional science and urban economics, 58, 89-103.
- Dustmann, C., Hatton, T., & Preston, I. (2005). The labour market effects of immigration. The Economic Journal, 115(507), F297-F299.
- Feng, S., Krueger, A. B., & Oppenheimer, M. (2010). Linkages among climate change, crop yields and Mexico–US cross-border migration. Proceedings of the national academy of sciences, 107(32), 14257-14262.
- Friedrich-Ebert-Stiftung, Global Future, & International Organization for Migration. (2017). Tomorrow’s World of Migration. Geneva, Switzerland: FES, Global Future, IOM.
- Gabriel, C., & Pellerin, H. (2012). Governing International Labour Migration: Current Issues, Challenges and Dilemmas. Routledge.
- Ghimis, A. (2016). The EU’s Labour Migration Policy: Recent Developments and What More is Needed. IEMed Mediterranean.
- International Organization for Migration. (2019). World Migration Report 2020.
- Johnson, I. I. (2011). Immigration as a Response Variable to Climate Change from Mexico into the United States. Journal of Alternative Perspectives in the Social Sciences, 3(3).
- Kalra, V., & Aggarwal, R. (2017). Importance of Text Data Preprocessing & Implementation in RapidMiner. Proceedings of the 2017 International Conference on Information Technology and Knowledge Management, 71-75.
- Lacroix, T. (2012). Designing a structure/agency approach to transnationalism (Working Paper). University of Oxford.
- Laffineur, C., Moreno-Galbis, E., Tanguy, J., & Tritah, A. (2017). Are immigrants’ skills priced differently? Evidence from France.
- McAuliffe, M., & Khadria, B. (2019). Report overview: Providing perspective on migration and mobility in increasingly uncertain times (World Migration Report 2020).
- Migration Policy Institute. (n.d.). Total Immigrant and Emigrant Populations by Country.
- Ndiaye, P. O. (2018). Migration d’étude, migration de travail: deux faces indissociables d’une même réalité? Géo-Regards, (10), 109-121. (In French).
- Patel, H. H., & Prajapati, P. (2018). Study and analysis of decision tree based classification algorithms. International Journal of Computer Sciences and Engineering, 6(10), 74-78.
- Prieur, F., & Schumacher, I. (2016). The role of conflict for optimal climate and immigration policy (TSE Working Paper 16-663). Toulouse School of Economics.
- Ries, L. (2020, October 21). President Trump and Joe Biden: Comparing Immigration Policies. The Heritage Foundation.
- Stakanov, R.D. (2014). Osoblyvosti mihratsiinoi polityky rozvynenykh krain svitu v XXI st [Peculiarities of developed countries migration policies in the twenty-first century]. Investytsii: praktyka ta dosvid – Investments: practice and experience, 15, 11-15. (In Ukrainian).
- Timmer, A. S., & Williams, J. G. (1998). Immigration policy prior to the 1930s: Labor markets, policy interactions, and globalization backlash. Population and Development Review, 24(4), 739-771.
- United Nations. (2017). International Migration Policies: Data Booklet.
- United Nations. (2020). Human Development Report 2020 – Education Index 2020.
- United Nations. (n.d.). Human Development Data Center.
- Wendling, Z. A., Emerson, J. W., de Sherbinin, A., Esty, D. C., Hoving, K., Ospina, C., Murray, J.-M., Gunn, L., Ferrato, M., Schreck, M., Jacob, M., Dahl, N., & Gordon, A. (2020). 2020 Environmental Performance Index. New Haven, CT: Yale Center for Environmental Law & Policy.
- World Bank Data. (n.d.a). GDP per capita (current US$).
- World Bank Data. (n.d.b). Population, total.
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Existing situation and prospects of green economy: evidence from Bangladesh
Environmental Economics Volume 9, 2018 Issue #2 pp. 7-21 Views: 2229 Downloads: 185 TO CITE АНОТАЦІЯEconomy for green is currently becoming a “buzz word” among producers, suppliers and consumers, which is also receiving impetus in Bangladesh. Based on the literature review, a number of theoretical relationships were empirically tested. An investigative query is: to what extent the green economy is flourishing with a via to extend sustainability of the state with competitive advantage? Structured questionnaire was deliberated in order to find the relationships between the demographic variables and the green ecosystem. Time period of the research was October 1, 2017 to March 31, 2018. It was empirically observed that the relationship between the respondents of both genders and usability of green production in the country exists; the connection between business type and sensitivity of any green product is easily obtainable; the linkage between business type and awareness of any green product is accessible in the market; the linkage between type of institution and encouraging goods and services of any “Green Product” in Bangladesh occurs; the relationship between different types of institutes and use of Green Product consumption is applicable in the country. Economy for Green can possibly reduce the magnitude of the worst shock of natural disasters which increasingly occur as regular variation in addition to severe problems on human being and non-human assets. Consumers and producers are essential by conscious of green concept. Green Investment Bank in Bangladesh may be established to accomplish a broad range of economic support for innovative green projects and technologies leading to increasing capacity and sustainable connections.
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Business angels as an alternative to financial support at the early stages of small businesses’ life cycle
Nataliya Pedchenko ,
Victoria Strilec ,
Galina M. Kolisnyk ,
Mariia Dykha ,
Serhiy Frolov
doi: http://dx.doi.org/10.21511/imfi.15(1).2018.15
Investment Management and Financial Innovations Volume 15, 2018 Issue #1 pp. 166-179 Views: 1693 Downloads: 375 TO CITE АНОТАЦІЯIn the process of small business establishment and development, it is very important to understand both the financial needs of entrepreneurs and the main obstacles and difficulties arising in the way of financing. Alternative sources of financial support, along with traditional ones, create opportunities to increase funds, but the solution to the issue of their attraction should be based on modern effective methods and decision- making technologies. The article uses the decision tree method to determine the optimal alternative to financial support of small business at the early stages of the life cycle. The results highlight the importance of alternative source of resources for small business entities, namely business angels’ means. The empirical and statistical analysis confirms that access to alternative sources of financing for small businesses in EU countries is improving, while in Ukraine, informal financing is a rather new and underdeveloped area. Based on the analysis of the advantages of using the business angels’ funds, it was concluded that they need to implement their potential in small business of Ukraine. The results show that the decision tree method is an effective tool for deciding on the prioritization of a financial alternative to the small business, and is characterized by ease of use, forecast precision and problems solution novelty.
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Green bonds of supranational financial institutions: On the road to sustainable development
Nataliia Versal ,
Antonina Sholoiko
doi: http://dx.doi.org/10.21511/imfi.19(1).2022.07
Investment Management and Financial Innovations Volume 19, 2022 Issue #1 pp. 91-105 Views: 1526 Downloads: 440 TO CITE АНОТАЦІЯThe move to sustainable development and building a carbon-low economy needs funding. In this regard, a new direction in finance – green (sustainable) finance – has emerged. One of the green finance instruments is green bonds, first issued by supranational financial institutions. This paper aims to identify the features of green bond issues and implemented green projects by the World Bank (the WB) and the European Bank for Reconstruction and Development (the EBRD). Data were obtained from databases and reports of the WB, the EBRD, and the Climate Bonds Initiative. Data analysis was provided using statistical methods, particularly descriptive and comparative statistics. A positive trend in the issue of green bonds in the volumes and timing of the WB and the EBRD was revealed, despite the shift in emphasis caused by COVID-19. Renewable energy, energy efficiency, and clean transportation remain the primary directions of the WB, and the EBRD green projects amounted to more than 60% of total projects funding. The geography of green projects financed through the WB and the EBRD green bonds indicates that green projects are receiving significant funding from countries facing environmental challenges and demonstrating intent to green transition (the WB – China and India, the EBRD – Turkey, Poland, and Egypt). Supranational financial institutions were the first to come to the forefront of sustainable development funding and are now spearheading the creation of new financial instruments aimed at financing both green and social projects, leading to the emergence of sustainability bonds.
Acknowledgment(s)
The authors would like to thank the participants of the 1st International Conference on Sustainable Development (SDL 2021) for providing the valuable remarks and a fruitful discussion. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
