Shifts in the Boot: Understanding Inequality’s Impact on Interregional Migration Patterns in Italy
Abstract
:1. Introduction
2. Literature Review
2.1. Historical Context
2.2. Gravity Models in Regional Economics
2.3. Effects of Income Inequality on Interregional Mobility
2.4. The Economic Crisis of 2008 as a Trigger for Interregional Immigration
3. Methodology
- MFijt: Bilateral Gross Migration Flows, from region I to j, at time t;
- MFijt−1: Bilateral Gross Migration Flows from region I to j, at time t − 1;
- Inequalityt−1: The three different indexes of inequality used in the paper, at time t − 1;
- Demogr.t−1: The one-year lagged demographic explanatory variables listed above, at time t − 1;
- Distanceij: Distance between origin and destination region;
- Cinema: Inequality instrument encompassing people who can afford an inexpensive cinema ticket;
- Theater: Inequality instrument encompassing people who can afford an expensive theater ticket.
4. Results
4.1. Gini Index
4.2. Relative Poverty
4.3. Income Ratio
5. Conclusions
5.1. Theoretical Implications
5.2. Policy Implications
- Economic Development Programs
- 2.
- Investment in Education and Infrastructure
- 3.
- Social Cohesion Programs
- 4.
- Incentives for High-Skilled Workers
- 5.
- Combating Organized Crime
- 6.
- Supporting Innovation and Creative Economies
- 7.
- Universal Basic Income (UBI)
Author Contributions
Funding
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Independent Variables | Migration Flows | Migration Flows | Migration Flows |
---|---|---|---|
Two Lags Migration Flows | 0.967 *** (254.7) | 0.967 *** (257.1) | 0.968 *** (257.8) |
Two Lags Gini Origin | 6108.8 ** | ||
(2.16) | |||
Two Lags Gini Destination | 819.1 | ||
(0.86) | |||
Two Lags Relative Poverty Origin | 16.29 *** | ||
(3.12) | |||
Two Lags Relative Poverty Destination | −8.123 ** | ||
(−2.18) | |||
Two Lags Income Ratio Origin | −160.2 *** | ||
(−4.09) | |||
Two Lags Income Ratio Destination | 116.0 *** | ||
(4.54) | |||
Distance | −2.048 *** | −2.112 *** | −2.114 *** |
(−13.16) | (−13.73) | (−13.53) | |
Distance2 | 0.001 *** | 0.001 *** | 0.001 *** |
(12.97) | (13.73) | (13.63) | |
Two Lags Unemployed Origin | 7.941 | 2.809 | −8.021 |
(0.87) | (0.37) | (−0.99) | |
Two Lags Unemployed Destination | −31.28 *** | −18.63 *** | −6.100 |
(−6.01) | (−3.01) | (−0.97) | |
Two Lags Population Origin | 0.000 *** | 0.000 *** | 0.000 *** |
(19.85) | (28.71) | (28.30) | |
Two Lags Population Destination | 0.000 *** | 0.000 *** | 0.000 *** |
(35.26) | (35.15) | (33.81) | |
Two Lags Education Level Origin | 12,982.7 | 19,825.5 * | −121.9 |
(1.24) | (2.48) | (−0.02) | |
Two Lags Education Level Destination | 52,869.4 *** | 46,846.7 *** | 62,232.9 *** |
(5.05) | (4.43) | (5.86) | |
Two Lags Crime Origin | 16.71 *** | 19.41 *** | 19.71 *** |
(5.05) | (6.40) | (6.46) | |
Two Lags Crime Destination | −5.948 * | −6.703 ** | −6.952 ** |
(−1.87) | (−1.62) | (−1.82) | |
Constant | −2137.4 *** | −471.0 *** | −308.7 ** |
(−3.26) | (−4.43) | (−2.14) | |
Region Fixed Effects | Yes | Yes | Yes |
Period Fixed Effects | Yes | Yes | Yes |
R-squared | 0.721 | 0.727 | 0.724 |
Observations | 3038 | 3038 | 3038 |
Underidentification test | 230.552 | 1450.932 | 1201.297 |
Chi-sq(2) p-value | 0.000 | 0.000 | 0.000 |
Weak identification test | 124.183 | 1385.212 | 990.623 |
Sargan statistics | 0.014 | 0.821 | 0.063 |
Chi-sq(1) p-value | 0.907 | 0.365 | 0.805 |
Number of regions | 20 | 20 | 20 |
Independent Variables | Migration Flows | Migration Flows | Migration Flows |
---|---|---|---|
Five Lags Migration Flows | 0.967 *** (254.7) | 0.967 *** (257.1) | 0.968 *** (257.8) |
Five Lags Gini Origin | 20,469.2 ** | ||
(2.13) | |||
Five Lags Gini Destination | 2103.4 | ||
(1.37) | |||
Five Lags Relative Poverty Origin | 18.85 ** | ||
(2.30) | |||
Five Lags Relative Poverty Destination | −1.850 | ||
(−0.39) | |||
Five Lags Income Ratio Origin | −234.2 *** | ||
(−2.64) | |||
Five Lags Income Ratio Destination | 87.80 ** | ||
(2.56) | |||
Distance | −1.872 *** | −2.134 *** | −2.168 *** |
(−7.72) | (−10.73) | (−10.76) | |
Distance2 | 0.001 *** | 0.001 *** | 0.001 *** |
(7.71) | (10.81) | (10.87) | |
Five Lags Unemployed Origin | −61.35 | −6.199 | −38.01 |
(−1.52) | (−0.44) | (−1.61) | |
Five Lags Unemployed Destination | −52.57 *** | −39.13 *** | −17.71 * |
(−6.08) | (−4.16) | (−1.66) | |
Five Lags Population Origin | 0.000 *** | 0.000 *** | 0.000 *** |
(7.99) | (19.33) | (18.97) | |
Five Lags Population Destination | 0.000 *** | 0.000 *** | 0.000 *** |
(25.12) | (26.03) | (26.31) | |
Five Lags Education Level Origin | 18,517.8 | 24,914.3 * | −3868.6 |
(1.39) | (1.92) | (−0.25) | |
Five Lags Education Level Destination | 47,312.3 *** | 44,995.7 *** | 56,598.1 *** |
(3.57) | (3.56) | (4.36) | |
Five Lags Crime Origin | 16.13 *** | 22.38 *** | 26.77 *** |
(2.83) | (5.69) | (6.76) | |
Five Lags Crime Destination | 1.437 | 1.336 | −0.471 |
(0.34) | (0.34) | (−0.12) | |
Constant | 5790.1 ** | −481.7 *** | 65.72 |
(−2.43) | (−3.71) | (0.19) | |
Region Fixed Effects | Yes | Yes | Yes |
Period Fixed Effects | Yes | Yes | Yes |
R-squared | 0.692 | 0.729 | 0.723 |
Observations | 3038 | 3038 | 3038 |
Underidentification test | 35.332 | 649.978 | 292.874 |
Chi-sq(2) p-value | 0.000 | 0.000 | 0.000 |
Weak identification test | 17.868 | 491.133 | 171.958 |
Sargan statistics | 0.001 | 0.450 | 0.383 |
Chi-sq(1) p-value | 0.976 | 0.502 | 0.536 |
Number of regions | 20 | 20 | 20 |
References
- Accetturo, Antonio, Francesco Manaresi, Sauro Mocetti, and Elisabetta Olivieri. 2014. Don’t Stand so close to me: The urban impact of immigration. Regional Science and Urban Economics 45: 45–56. [Google Scholar] [CrossRef]
- Angelucci, Manuela. 2012. Conditional cash transfer programs, credit constraints, and migration. Labour 26: 124–36. [Google Scholar] [CrossRef]
- Ashby, Nathan J. 2007. Economic freedom and migration flows between US states. Southern Economic Journal 73: 677–97. [Google Scholar] [CrossRef]
- Azarnert, Leonid V. 2012. Guest-worker migration, human capital and fertility. Review of Development Economics 16: 318–30. [Google Scholar] [CrossRef]
- Bai, Janjun, Wenjin Jin, and Xiaoxiao Shi. 2019. Technology, e-commerce, and labor market institutions. Review of Economic Dynamics 33: 251–73. [Google Scholar]
- Bailey, Zinzi D., Nancy Krieger, Madina Agénor, Jasmine Graves, Natalia Linos, and Mary T. Bassett. 2017. Structural racism and health inequities in the USA: Evidence and interventions. Lancet 389: 1453–63. [Google Scholar] [CrossRef]
- Bartolucci, Cristian, Claudia Villosio, and Mathis Wagner. 2018. Who migrates and why? Evidence from Italian administrative data. Journal of Labor Economics 36: 551–88. [Google Scholar] [CrossRef]
- Benassi, Federico, Corrado Bonifazi, Frank Heins, Francesca Licari, and Enrico Tucci. 2019. Population Change and International and Internal Migration in Italy, 2002–2017: Ravenstein Revisited. Comparative Population Studies 44: 497–532. [Google Scholar] [CrossRef]
- Biagi, Bianca, Alessandra Faggian, and Philip McCann. 2011. Long and short distance migration in Italy: The role of economic, social and environmental characteristics. Spatial Economic Analysis 6: 111–31. [Google Scholar] [CrossRef]
- Blomquist, Glenn C., Mark C. Berger, and John P. Hoehn. 1988. New estimates of quality of life in urban areas. The American Economic Review 78: 89–107. [Google Scholar]
- Bonifazi, Corrado, Frank Heins, and Enrico Tucci. 2017. Italy: Internal migration in a low-mobility country. In Internal Migration in the Developed World. London: Routledge, pp. 242–62. [Google Scholar]
- Borjas, George J. 1987. Self-Selection and the Earnings of Immigrants. American Economic Review 77: 531–53. [Google Scholar]
- Borjas, George J. 1989. Immigrant and Emigrant Earnings: A Longitudinal Study. Economic Inquiry 27: 21–37. [Google Scholar] [CrossRef]
- Borjas, George J. 1995. The Economic Benefits from Immigration. Journal of Economic Perspectives 9: 3–22. [Google Scholar] [CrossRef]
- Boschini, Anne D., Jan Pettersson, and Jesper Roine. 2007. Resource curse or not: A question of appropriability. Scandinavian Journal of Economics 109: 593–617. [Google Scholar] [CrossRef]
- Cannari, Luigi, Francesco Nucci, and Paolo Sestito. 2000. Geographic labour mobility and the cost of housing: Evidence from Italy. Applied Economics 32: 1899–906. [Google Scholar] [CrossRef]
- Ceriani, Lidia, and Paolo Verme. 2012. The origins of the Gini index: Extracts from Variabilità e Mutabilità (1912) by Corrado Gini. The Journal of Economic Inequality 10: 421–43. [Google Scholar] [CrossRef]
- Ciccarelli, Carlo, Cosimo Magazzino, and Edoardo Marcucci. 2021. Early development of Italian railways and industrial growth: A regional analysis. Research in Transportation Economics 88: 100916. [Google Scholar] [CrossRef]
- Corrigall-Brown, Caroline, and Mabel Ho. 2015. How the state shapes social movements. Protest and Politics: The Promise of Social Movement Societies, 101–17. Available online: https://books.google.com.sg/books?hl=en&lr=&id=dKJeCAAAQBAJ&oi=fnd&pg=PA101&dq=How+the+state+shapes+social+movements&ots=LDPxb_xwzV&sig=DK7JwA95ZyBGAo_e3YdEdmd4OmI&redir_esc=y#v=onepage&q=How%20the%20state%20shapes%20social%20movements&f=false (accessed on 17 November 2024).
- Coulter, Rory, and Jacqueline Scott. 2015. What motivates residential mobility? Re-examining self-reported reasons for desiring and making residential moves. Population, Space and Place 21: 354–71. [Google Scholar] [CrossRef]
- Cullen, Julie Berry, and Steven D. Levitt. 1999. Crime, Urban Flight, and the Consequences for Cities. The Review of Economics and Statistics 81: 159–69. [Google Scholar] [CrossRef]
- Cushing, Brian, and Jacques Poot. 2004. Crossing boundaries and borders: Regional science advances in migration modelling. Papers in Regional Science 83: 317–38. [Google Scholar] [CrossRef]
- Di Quirico, Roberto. 2010. Italy and the global economic crisis. Bulletin of Italian Politics 2: 3–19. [Google Scholar]
- Epstein, Gil S., and Ira N. Gang. 2006. Ethnic networks and international trade. In Labor Mobility and the World Economy. Berlin and Heidelberg: Springer, pp. 85–103. [Google Scholar]
- Etzo, Ivan. 2011. The determinants of the recent interregional migration flows in Italy: A panel data analysis. Journal of Regional Science 51: 948–66. [Google Scholar] [CrossRef]
- Felice, Emanuele. 2018. The socio-institutional divide: Explaining Italy’s long-term regional differences. Journal of Interdisciplinary History 49: 43–70. [Google Scholar] [CrossRef]
- Felice, Emanuele, and Michelangelo Vasta. 2015. Passive modernization? The new human development index and its components in Italy’s regions (1871–2007). European Review of Economic History 19: 44–66. [Google Scholar] [CrossRef]
- Forman, Chris, Avi Goldfarb, and Shane Greenstein. 2005. How did location affect adoption of the commercial internet? Global village vs. urban leadership. Journal of Urban Economics 58: 389–420. [Google Scholar] [CrossRef]
- Freedman, Matthew, and Emily G. Owens. 2011. Low-income housing development and crime. Journal of Urban Economics 70: 115–31. [Google Scholar] [CrossRef]
- Gagliardi, Luisa, and Marco Percoco. 2011. Regional disparities in Italy over the long run: The role of human capital and trade policy. Région et Développement 33: 81–105. [Google Scholar]
- García, Ana Isabel López. 2018. Economic remittances, temporary migration and voter turnout in Mexico. Migration Studies 6: 20–52. [Google Scholar] [CrossRef]
- Gastil, Raymond Duncan. 1990. The comparative survey of freedom: Experiences and suggestions. Studies in Comparative International Development 25: 25–50. [Google Scholar] [CrossRef]
- Glaeser, Edward L., Matt Resseger, and Kristina Tobio. 2009. Inequality in cities. Journal of Regional Science 49: 617–46. [Google Scholar] [CrossRef]
- Graves, Philip E. 1976. A reexamination of migration, economic opportunity, and the quality of life. Journal of Regional Science 16: 107–12. [Google Scholar] [CrossRef]
- Greenwood, Michael J. 1975. Research on internal migration in the United States: A survey. Journal of Economic Literature 13: 397–433. [Google Scholar]
- Greenwood, Michael J. 1997. Internal Migration in Developed Countries. In Handbook of Population and Family Economics. Amsterdam: Elsevier, vol. 1, pp. 647–720. [Google Scholar]
- Harris, John R., and Michael P. Todaro. 1970. Migration, unemployment and development: A two-sector analysis. The American Economic Review 60: 126–42. [Google Scholar]
- Hausman, Jerry A., Whitney K. Newey, Tiemen Woutersen, John C. Chao, and Norman R. Swanson. 2012. Instrumental variable estimation with heteroskedasticity and many instruments. Quantitative Economics 3: 211–55. [Google Scholar] [CrossRef]
- Henry, LaVaughn M. 2014. Income Inequality and Income-Class Consumption Patterns. In Economic Commentary. Cleveland: Federal Reserve Bank of Cleveland. [Google Scholar]
- Jargowsky, Paul A. 2015. The Architecture of Segregation: Civil Unrest, the Concentration of Poverty, and Public Policy. The Century Foundation, August 7. [Google Scholar]
- Juarez, Juan Pablo. 2000. Analysis of interregional labor migration in Spain using gross flows. Journal of Regional Science 40: 377–99. [Google Scholar] [CrossRef]
- Katz-Gerro, Tally. 2002. Highbrow Cultural Consumption and Class Distinction in Italy, Israel, West Germany, Sweden, and the United States. Social Forces 81: 207–29. [Google Scholar] [CrossRef]
- Katz-Gerro, Tally. 2006. Comparative evidence of inequality in cultural preferences: Gender, class, and family status. Sociological Spectrum 26: 63–83. [Google Scholar] [CrossRef]
- Kolko, Jed. 2012. Broadband and local growth. Journal of Urban Economics 71: 100–13. [Google Scholar] [CrossRef]
- LeSage, James P., and R. Kelley Pace. 2008. Spatial econometric modeling of origin-destination flows. Journal of Regional Science 48: 941–67. [Google Scholar] [CrossRef]
- Lisciandra, Maurizio, Riccardo Milani, and Emanuele Millemaci. 2022. A corruption risk indicator for public procurement. European Journal of Political Economy 73: 102141. [Google Scholar] [CrossRef]
- Manioudis, Manolis, and Antonios Angelakis. 2023. Creative economy and sustainable regional growth: Lessons from the implementation of entrepreneurial discovery process at the regional level. Sustainability 15: 7681. [Google Scholar] [CrossRef]
- Molloy, Raven, Christopher L. Smith, and Abigail Wozniak. 2017. Job Changing and the Decline in Long-Distance Migration in the United States. Demography 54: 631–53. [Google Scholar] [CrossRef] [PubMed]
- Monras, Joan. 2018. Economic Shocks and Internal Migration. CEPR Discussion Paper No. DP12977. London: Centre for Economic Policy Research (CEPR). [Google Scholar]
- Musolino, Dario. 2018. The north-south divide in Italy: Reality or perception? European Spatial Research and Policy 25: 29–53. [Google Scholar] [CrossRef]
- Mussida, Chiara, and Maria Laura Parisi. 2016. The Effect of Economic Crisis on Regional Income Inequality in Italy. Regional Studies 50: 1869–89. [Google Scholar]
- Odoardi, Iacopo, and Fabrizio Muratore. 2019. The north–south divergence in Italy during the great recession. The Manchester School 87: 1–23. [Google Scholar] [CrossRef]
- Panichella, Nazareno. 2012. Le migrazioni interne nel secolo scorso: Vecchie e nuove forme a confronto. Stato e Mercato 32: 255–82. [Google Scholar]
- Percoco, Marco. 2018. Wealth inequality, redistribution and local development: The case of land reform in Italy. Environment and Planning C: Politics and Space 36: 181–200. [Google Scholar] [CrossRef]
- Perez-Villadoniga, Maria J., and Sara Suarez-Fernandez. 2019. Education, income and cultural participation across Europe. Cuadernos Económicos de ICE 98: 89–103. [Google Scholar] [CrossRef]
- Piras, Romano. 2020. Internal Migration in Italy: The Role of Migration Networks. Italian Economic Journal 6: 157–95. [Google Scholar] [CrossRef]
- Putnam, Robert D. 2000. Bowling Alone: The Collapse and Revival of American Community. New York: Simon and Schuster. [Google Scholar]
- Reardon, Sean F., and Kendra Bischoff. 2011. Income inequality and income segregation. American Journal of Sociology 116: 1092–153. [Google Scholar] [CrossRef]
- Roback, Jennifer. 1982. Wages, rents, and the quality of life. Journal of Political Economy 90: 1257–78. [Google Scholar] [CrossRef]
- Sanfilippo, Matteo. 2016. The Debate on Personal Sources for the History of Italian Emigration. In From the Records of My Deepest Memory: Personal Sources and the Study of European Migration, 18th–20th Centuries. Bilbao: Universidad del País Vasco, Euskal Herriko Unibertsitatea, pp. 123–36. [Google Scholar]
- Schwartz, Amy Ellen, Scott Susin, and Ioan Voicu. 2003. Has falling crime driven New York City’s real estate boom? Journal of Housing Research 14: 101–35. [Google Scholar]
- Sharkey, Patrick, and Robert J. Sampson. 2010. Destination effects: Residential mobility and trajectories of adolescent violence in a stratified metropolis. Criminology 48: 639–81. [Google Scholar] [CrossRef] [PubMed]
- Simpson, Nicole B. 2017. Demographic and economic determinants of migration. IZA World of Labor 2022: 373. [Google Scholar] [CrossRef]
- Standing, Guy. 2017. Basic Income: And How We Can Make It Happen. London: Pelican. [Google Scholar]
- Widerquist, Karl. 2018. A Critical Analysis of Basic Income Experiments for Researchers, Policymakers, and Citizens. Cham: Springer. [Google Scholar]
- Zamagni, Vera. 1993. The Economic History of Italy 1860–1990. Oxford: Clarendon Press. [Google Scholar]
- Zamagni, Vittorio. 2008. Introduzione Alla Storia Economica. Italy: Il Mulino. [Google Scholar]
- Zhang, Qi, Richard E. Bilsborrow, Conghe Song, Shiqi Tao, and Qingfeng Huang. 2019. Rural household income distribution and inequality in China: Effects of payments for ecosystem services policies and other factors. Ecological Economics 160: 114–27. [Google Scholar] [CrossRef]
Variable | Description |
---|---|
Gini Index | Statistical measure of income distribution. The |
coefficient ranges from 0 (or 0%) to 1 (or 100%), | |
with 0 representing perfect equality and 1 | |
representing perfect inequality. | |
Relative Poverty Index | Statistical measure describing economic struggle to |
use goods and services in specific geographic areas, | |
in relation to the average economic level of the same | |
geographic areas. | |
Top 20% Income/Bottom 20% Income | Index describing the amount of people in the top |
20% of the income level scale in a specific | |
geographic area, compared to the amount of people | |
in the bottom 20% of the income level scale, in the | |
same geographic area. |
Instrument | Description | Correlation with Gini | Correlation with Rel. Pov. | Correlation with Income Ratio | Mean | Std. Deviation | Min. | Max. |
---|---|---|---|---|---|---|---|---|
Theater/Cinema | People who can afford theater/people who can afford cinema. | 0.322 | 0.568 | 0.605 | 0.766 | 0.056 | 0.603 | 0.946 |
Internet Purchase/Internet Access | People who make online purchases/people with just internet access. | 0.444 | 0.666 | 0.646 | 0.744 | 0.064 | 0.546 | 0.882 |
Estimator | Description |
---|---|
LIML | Linear combination of the OLS and 2SLS estimate (with the weights depending on the data). Absence of the 2SLS bias. Very precise under homoskedasticity. Inconsistent under heteroskedasticity and many instruments. |
FULL | IV estimator with lower bias than LIML, due to the smaller number of outliers. Very precise under homoskedasticity. Inconsistent with heteroskedasticity and many instruments. |
HLIM | Updated version of LIML, developed by Hausman et al. (2012). Consistent under heteroskedasticity and has many instrument-robust versions. |
HFUL | Updated version of FULL, developed by Hausman et al. (2012). Consistent under heteroskedasticity and has many instrument-robust versions. |
Independent Variables | Migration Flows | Migration Flows | Migration Flows |
---|---|---|---|
Lagged Migration Flows | 0.967 *** (254.69) | 0.967 *** (257.09) | 0.968 *** (257.80) |
Lagged Gini Origin | 380.27 ** | ||
(2.08) | |||
Lagged Gini Destination | 705.3 *** | ||
(2.09) | |||
Lagged Relative Poverty Origin | 0.752 | ||
(0.56) | |||
Lagged Relative Poverty Destination | −0.81 | ||
(−0.53) | |||
Lagged Income Ratio Origin | −37.62 *** | ||
(−3.76) | |||
Lagged Income Ratio Destination | −3.921 | ||
(−0.41) | |||
Distance | −9.934 * | −10.33 * | −11.97 ** |
(−1.48) | (−1.59) | (−2.21) | |
Distance2 | 0.02 * | 0.02 * | 0.021 ** |
(1.64) | (1.71) | (1.85) | |
Lagged Unemployed Origin | −8.04 *** | −8.732 *** | −8.176 *** |
(−3.08) | (−3.51) | (−3.15) | |
Lagged Unemployed Destination | 2.531 | 2.902 | 1.145 |
(116) | (1.20) | (0.52) | |
Lagged Population Origin | −0.000 *** | −0.001 *** | −0.001 *** |
(−3.69) | (−5.07) | (−5.30) | |
Lagged Population Destination | −0.000 *** | −0.001 *** | −0.001 *** |
(−2.76) | (−2.92) | (−2.95) | |
Lagged Education Level Origin | −14,398.25 ** | −17,141.7 ** | −20,908.52 *** |
(−1.99) | (−2.29) | (−1.32) | |
Lagged Education Level Destination | 34,315.0 *** | 32,680.12 *** | 33,299.1 *** |
(3.55) | (3.26) | (3.33) | |
Lagged Crime Origin | 0.159 | −0.038 | 0.256 |
(0.15) | (−0.04) | (0.25) | |
Lagged Crime Destination | 1.044 | 1.434 | 0.323 |
(0.88) | (1.26) | (0.29) | |
Constant | −1336.939 | −905.01 | −276.63 |
(−0.73) | (−0.49) | (−0.16) | |
Region Fixed Effects | Yes | Yes | Yes |
Period Fixed Effects | Yes | Yes | Yes |
R-squared | 0.023 | 0.021 | 0.021 |
Observations | 3038 | 3038 | 3038 |
Number of Regions | 20 | 20 | 20 |
Independent Variables | Migration Flows | Migration Flows | Migration Flows |
---|---|---|---|
Lagged Migration Flows | 0.967 *** (254.69) | 0.967 *** (257.09) | 0.968 *** (257.80) |
Lagged Gini Origin | 10,805.9 *** | ||
(2.94) | |||
Lagged Gini Destination | 166.5 | ||
(0.17) | |||
Lagged Relative Poverty Origin | 19.93 *** | ||
(3.48) | |||
Lagged Relative Poverty Destination | −5.501 | ||
(−1.45) | |||
Lagged Income Ratio Origin | −190.9 *** | ||
(−4.50) | |||
Lagged Income Ratio Destination | 107.6 *** | ||
(4.08) | |||
Distance | −1.995 *** | −2.099 *** | −2.132 *** |
(−12.41) | (−13.60) | (−13.59) | |
Distance2 | 0.001 *** | 0.001 *** | 0.001 *** |
(12.29) | (13.74) | (13.77) | |
Lagged Unemployed Origin | −8.538 | 0.105 | −12.76 |
(−0.74) | (0.01) | (−1.68) | |
Lagged Unemployed Destination | −26.98 *** | −21.46 *** | −8.056 |
(−5.15) | (−3.52) | (−1.33) | |
Lagged Population Origin | 0.000 *** | 0.000 *** | 0.000 *** |
(15.08) | (29.76) | (29.08) | |
Lagged Population Destination | 0.000 *** | 0.000 *** | 0.000 *** |
(34.31) | (35.40) | (33.53) | |
Lagged Education Level Origin | 21,016.1 | 28,922.1 ** | −1478.939 |
(1.84) | (2.48) | (−0.14) | |
Lagged Education Level Destination | 61,253.3 *** | 56,741.5 *** | 70,417.2 *** |
(5.44) | (5.05) | (6.29) | |
Lagged Crime Origin | 14.47 *** | 19.92 *** | 20.30 *** |
(4.25) | (5.99) | (6.48) | |
Lagged Crime Destination | −4.000 | −5.005 | −5.656 * |
(−1.24) | (−1.62) | (−1.82) | |
Constant | −3181.9 *** | −571.0 *** | −277.4 * |
(−3.73) | (−5.13) | (−1.92) | |
Region Fixed Effects | Yes | Yes | Yes |
Period Fixed Effects | Yes | Yes | Yes |
R-squared | 0.709 | 0.726 | 0.722 |
Observations | 3038 | 3038 | 3038 |
Underidentification Test | 140.258 | 1284.983 | 1097.769 |
KP-F Statistics | 18.500 | 17.353 | 14.228 |
Weak Identification Test | 72.850 | 1108.580 | 808.171 |
Sargan Statistics | 0.517 | 0.817 | 0.162 |
Chi-sq(1) p-value | 0.419 | 0.366 | 0.687 |
Number of Regions | 20 | 20 | 20 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Di Pasquale, G.; Parazzi, E. Shifts in the Boot: Understanding Inequality’s Impact on Interregional Migration Patterns in Italy. Economies 2024, 12, 317. https://doi.org/10.3390/economies12120317
Di Pasquale G, Parazzi E. Shifts in the Boot: Understanding Inequality’s Impact on Interregional Migration Patterns in Italy. Economies. 2024; 12(12):317. https://doi.org/10.3390/economies12120317
Chicago/Turabian StyleDi Pasquale, Giacomo, and Elisa Parazzi. 2024. "Shifts in the Boot: Understanding Inequality’s Impact on Interregional Migration Patterns in Italy" Economies 12, no. 12: 317. https://doi.org/10.3390/economies12120317
APA StyleDi Pasquale, G., & Parazzi, E. (2024). Shifts in the Boot: Understanding Inequality’s Impact on Interregional Migration Patterns in Italy. Economies, 12(12), 317. https://doi.org/10.3390/economies12120317