Title: "Economic Impacts of Migration"¶
Analysis of Migration and Remittance Dynamics in Nigeria (2000–2024): Scaling, Correlation, and Policy Efficiency
Nigeria code: 566
UK code: 826
Filtered Nigeria → UK migration (2000–2026) saved at: c:\Users\ZIZIPHO\Desktop\DataScienceLab\nigeria_to_uk_migration_2000_2026.csv
2000.1 2005.1 2010.1 2015.1 2020.1 2024.1 2000.2 2005.2 \
84 298175 426869 536809 722576 947270 1099316 243965 337122
370 144478 184659 211165 292058 353023 392744 111025 141490
597 17467 22308 23844 28607 36440 52288 13837 16128
776 408 378 380 502 471 462 380 331
931 2017 2680 3150 3744 5003 5358 517 648
... ... ... ... ... ... ... ... ...
25881 4525 7580 14990 25136 38980 56121 3557 6314
26093 69664 96515 117513 168524 240635 285451 55839 71206
26239 1113 1565 2741 5060 8212 11262 699 1035
26495 1113 1565 2741 5060 8212 11262 699 1035
26746 1113 1565 2741 5060 8212 11262 699 1035
2010.2 2015.2 2020.2 2024.2
84 441869 636943 821174 994949
370 159046 259308 326701 369686
597 14789 17205 21495 31884
776 271 321 266 258
931 785 1407 2677 3496
... ... ... ... ...
25881 13204 22979 36698 55944
26093 103982 155703 211021 279602
26239 1890 3352 5921 8262
26495 1890 3352 5921 8262
26746 1890 3352 5921 8262
[128 rows x 12 columns]
Year Number of Migrants 0 2000.1 2935764 1 2005.1 4103056 2 2010.1 5058710 3 2015.1 6824936 4 2020.1 8817306 5 2024.1 10177871 6 2000.2 2372601 7 2005.2 3222717 8 2010.2 4085094 9 2015.2 5992138 10 2020.2 7684414 11 2024.2 9192164
Collecting xlrd Using cached xlrd-2.0.2-py2.py3-none-any.whl.metadata (3.5 kB) Using cached xlrd-2.0.2-py2.py3-none-any.whl (96 kB) Installing collected packages: xlrd Successfully installed xlrd-2.0.2
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Columns in dataset:
Index(['Country Name', 'Country Code', 'Indicator Name', 'Indicator Code',
'1960', '1961', '1962', '1963', '1964', '1965', '1966', '1967', '1968',
'1969', '1970', '1971', '1972', '1973', '1974', '1975', '1976', '1977',
'1978', '1979', '1980', '1981', '1982', '1983', '1984', '1985', '1986',
'1987', '1988', '1989', '1990', '1991', '1992', '1993', '1994', '1995',
'1996', '1997', '1998', '1999', '2000', '2001', '2002', '2003', '2004',
'2005', '2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013',
'2014', '2015', '2016', '2017', '2018', '2019', '2020', '2021', '2022',
'2023', '2024', '2025'],
dtype='str')
Nigeria remittances extracted successfully.
Saved to: C:\Users\ZIZIPHO\Desktop\DataScienceLab\nigeria_remittances_2000_2024.csv
Country Name 2000 2001 2002 2003 \
174 Nigeria 1.052142e+06 593358.431196 903977.979981 1.156224e+07
2004 2005 2006 2007 2008 \
174 2.085560e+07 6.803027e+07 1.015608e+08 5.400630e+07 5.814876e+07
... 2015 2016 2017 2018 \
174 ... 1.035451e+09 7.447711e+08 2.753458e+08 6.767628e+07
2019 2020 2021 2022 2023 \
174 9.060008e+07 9.210166e+07 8.254529e+07 8.242428e+07 8.409685e+07
2024
174 9.230130e+07
[1 rows x 26 columns]
Year total_remittances number_of_migrants 0 2000 1.052142e+06 83822 1 2005 6.803027e+07 125003 2 2010 4.747469e+07 189847 3 2015 1.035451e+09 236603 4 2020 9.210166e+07 286251 Index(['Year', 'total_remittances', 'number_of_migrants'], dtype='str') Correlation between Remittances and Migrants: 0.22
The graph shows a weak positive relationship between the number of migrants and total remittances. Each point represents a specific year, plotting migration against remittance inflows. The upward-sloping trend line suggests that remittances tend to increase as migration rises. However, the low correlation coefficient (0.22) indicates that this relationship is not strong. The wide spread of points and the large confidence interval suggest that other factors, beyond migration, significantly influence remittance flows.
Reason for the spike in 2015?
In 2015: Nigeria faced falling oil prices (major income source) and coursed Economic uncertainty. Global evidence shows that low oil prices and economic stress affect remittance behavior. Reference: International Monetary Fund. (2016). IMF Executive Board Concludes 2016 Article IV Consultation with Nigeria. IMF
Year total_remittances number_of_migrants remittances_scaled \ 0 2000 1.052142e+06 83822 0.000000 1 2005 6.803027e+07 125003 0.064751 2 2010 4.747469e+07 189847 0.044879 3 2015 1.035451e+09 236603 1.000000 4 2020 9.210166e+07 286251 0.088022 migrants_scaled Policy_Index 0 0.000000 0.000000 1 0.203434 -0.015705 2 0.523764 -0.125714 3 0.754739 0.473578 4 1.000000 -0.238385
The policy index assigns a weight of 70% to remittances and 30% to migration, reflecting the assumption that economic gains are more important than the costs associated with human migration. The negative sign for migration indicates that higher migration is treated as a loss.
The results show that 2015 achieved the highest policy efficiency, as strong remittance inflows outweighed the costs of migration. In contrast, 2020 recorded the lowest score, indicating that high migration was not matched by sufficient financial returns. Overall, the findings suggest that migration only contributes positively to policy outcomes when it generates substantial economic benefits.
