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Forecasting population movement trends is crucial for implementing effective policies to regulate labor force growth and understand demographic changes. Combining migration theory expertise and neural network technology can bring a fresh perspective to international migration forecasting research.

This study proposes a conditional generative adversarial neural network model incorporating the migration knowledge – conditional generative adversarial network (MK-CGAN). By using the migration knowledge to design the parameters, MK-CGAN can effectively address the limited data problem, thereby enhancing the accuracy of migration forecasts.

The model was tested by forecasting migration flows between different countries and had good generalizability and validity. The results are robust as the proposed solutions can achieve lesser mean absolute error, mean squared error, root mean square error, mean absolute percentage error and R² values, reaching 0.9855 compared to long short-term memory (LSTM), gated recurrent unit, generative adversarial network (GAN) and the traditional gravity model.

This study is significant because it demonstrates a highly effective technique for predicting international migration using conditional GANs. By incorporating migration knowledge into our models, we can achieve prediction accuracy, gaining valuable insights into the differences between various model characteristics. We used SHapley Additive exPlanations to enhance our understanding of these differences and provide clear and concise explanations for our model predictions. The results demonstrated the theoretical significance and practical value of the MK-CGAN model in predicting international migration.

Within the labor-intensive construction industry characterized by distinctly structural shortages in the labor force worldwide, efficient and effective migration of construction workers across regions is critical for the smooth operation of construction activities. This study aims to investigate how the interregional migration patterns of construction workers are impacted by the disparities in both employment opportunities and environment amenities between the origin and destination provinces.

Drawing on the push and pull theory and the archival data on 13,728 migrant construction workers in China, descriptive analyses are first performed to characterize the interregional migration patterns of the investigated construction workers. Combining regional data in the National Bureau of Statistics of China, this study uses hierarchical regression modeling techniques to empirically test the relative importance of the employment-related and environment-related factors in driving the interregional migration of construction workers after controlling for the effects of related economic and geographic factors.

The results provide evidence that the interregional migration of construction workers is principally driven by the disparities in employment opportunities while disparities in environment amenities (including climate comfort disparity, medical service disparity and educational service disparity) generally play much fewer substantive roles. With regard to the impacts of employment opportunities, the results provide evidence that compared with the disparity in job market size, the disparities in job income and industry development level are more significantly relevant factors, which positively pull and adversely push the interregional migration flows, respectively.

This study contributes to a deepened understanding of how workers specifically balance their employment and amenity needs to make temporary migration decisions in the “laggard” labor-intensive construction industry. This study also adds to the literature on population migration by characterizing the specific characteristics of construction workers and the temporary nature of the workers' migration activities. The findings hold important practical implications for construction organizations and policymakers for effectively managing the mobility of migrant construction workers.

The extant literature on migrant construction workers has primarily focused on the consequences of international migration and the generalization of empirical findings on population migration mechanisms in other domains to the construction industry is substantially limited by the specific characteristics of construction workers and the temporary nature of their migration activities. In addressing this gap, this study represents an exploratory effort to quantitatively characterize the interregional migration patterns of construction workers in the labor-intensive construction industry and examines the roles of employment opportunity and environmental amenity in driving interregional migration.

This study aims to quantify the influence of urbanization on housing prices at the district-based level, while also investigating the heterogeneous impacts across different quantiles of housing prices.

The study uses remote-sensed spectral images from the Landsat 7 ETM+ satellite to measure urbanization, replacing prior reliance solely on urban population metrics. Subsequently, the two-step system generalized method of moments is used to evaluate how urbanization influences district-based housing prices through three spectrometries: Urban Index (UI), Normalized Difference Built-up Index (NDBI) and Built-Up Index (BUI). Finally, this study examines the heterogeneous impacts across various housing price quantiles through Dynamic Panel Quantile Regression with non-additive fixed effects under Markov Chain Monte Carlo simulation.

The study demonstrates that urbanization leads to an increase in regional housing prices. However, these impact magnitudes vary across housing price quantiles. Specifically, the impact exhibits an inverse V-shaped curve, with urbanization exerting a more pronounced influence on the 60th percentile of housing prices, while its effect on the 10th and 90th percentiles is comparatively weaker.

This study uses a novel method of remote sensing to measure urbanization and investigates its effects on housing prices. Furthermore, it provides an empirical application of non-additive fixed effect quantile regression for analyzing heterogeneity.

By analyzing the mechanisms by which rural infrastructure resilience (RIR) impacted population loss in Longxi County, this study proposes measures to improve RIR, which provides a practical reference for realizing China's rural revitalization strategy, besides providing ideas for alleviating population loss in similar regions around the world.

This study considered 213 administrative villages in Longxi County in the Longzhong loess hilly region as the evaluation unit. Based on the construction of a multidimensional RIR evaluation system, the spatial spillover effect of RIR on population loss was determined using the spatial Durbin model (SDM).

The average resilience of each subsystem of rural infrastructure in Longxi County was low, and there were large differences in the spatial distribution. The mean RIR index value was 0.2258, with obvious spatial directivity and agglomeration characteristics. The population loss index of Longxi County had a value of 0.1759, with 26.29 of villages having a high loss level. The population loss was relatively serious and was correlated with the spatial distribution of RIR. The villages with larger RIR index values had lower population loss. The RIR had a significant spatial spillover effect on population loss. Productive infrastructure resilience and living infrastructure resilience (LIR) had negative spillover effects on population loss, and social service infrastructure resilience (SSIR) had a positive spillover effect on population loss.

By analyzing the mechanisms by which RIR impacted on population loss in Longxi County, this study proposes measures to improve RIR, which provides a practical reference for realizing China's rural revitalization strategy, besides providing ideas for alleviating population loss in similar regions around the world.

This study aims to contribute to the literature on migration by examining the nexus between migration-related fears and housing affordability in France, Germany, the UK and the USA using new datasets for migration-related fears.

This study adopts the feasible quasi-generalized least squares approach wherein a predictor can be isolated in the estimation process. Thus, rather than specifying a multi-predictor model that may also lead to parameter proliferation, a single-predictor model (for the predictor of interest) is formulated while also accounting for other salient features resulting from suppressing other important factors that may not be of interest to the current study. Such salient features include persistence, endogeneity and conditional heteroscedasticity issues.

Overall, the results show heterogeneous responses of housing affordability to migration fears across the four developed countries, as the latter deteriorates housing affordability in Germany and the USA and improves it in France and the UK. Similarly, the GFC makes housing less affordable in all four countries as low interest rate passes the mediation test in the nexus. The results, especially for low interest rates, are robust to different uncertainty measures.

As is often the case with economic phenomena, no single model can capture all the factors influencing an economic variable. Thus, besides examining the nexus between migration fears and housing affordability, the authors also account for the role of GDP per capita, given the influence of population and income dynamics on housing affordability. However, incorporating GDP per capita alone does not substantially enhance the model’s ability to predict housing affordability. Future research should explore additional macroeconomic and social factors, such as human capital development, to further enhance this subject.

The findings have significant implications for policymakers regarding the use of low interest rates to counteract the adverse effects of migration-related fear on housing affordability. Specifically, to mitigate the potential negative impact of migration and the associated fear on housing affordability, monetary authorities could adopt a more accommodative stance on mortgages. By allowing real estate investors to obtain loans at lower rates, this approach would help increase housing supply and reduce the housing gap exacerbated by migration influx.

The values of this study lie in its examination of housing affordability in relation to migration fears from both the demand and supply sides of the market. Furthermore, the analyses are conducted to cover out-of-sample forecast evaluation as in-sample predictability may not guarantee out-of-sample prediction.

The purpose of this study is to explore the impacts of aid in the form of food, cash, and agricultural inputs on internal migration following a series of cyclones in the southern coastal areas of Bangladesh. The impacts of sources of aid, such as institutional or social network sources, were also analysed. With the increasing frequency of extreme climatic events, it becomes crucial to understand the impacts of different post-cyclonic aid on human mobility.

A total of 472 households across 16 blocks (moujas) in the Patharghata sub-district of Barguna district were selected for participation using a stratified sampling strategy. Data were captured via a survey which included individual and household-level demographics, migration and aid-receipt following cyclones. Data were analysed using a mixture of descriptive and inferential statistical methods.

The analysis revealed that migration was significantly higher among households which did not receive institutional food aid. More specifically, non-receipt of food aid and cash aid after a cyclone, different sources of income, non-availability of alternative sources of income, lack of land ownership and severity of cyclones up to a certain level increased migration among the households where a minority of household members migrated. In contrast, the absence of food aid and the severity of cyclones were found to be significant factors in increasing migration among the households where a majority of household members migrated. The authors argue that the decision to migrate from the households where most members migrated increased with the rise in cyclone severity.

The contribution of this research in the field of aid and migration is unique. To the best of the authors’ knowledge, no research was conducted before on the impacts of distribution and type of aid on internal migration following a cyclone.

The purpose of this paper is to explore the factors that influence migrant workers' household registration transfer willingness at both individual and urban levels and to provide empirical evidence on adjusting the household registration system to accommodate economic development and migrant workers' imbalances.

This paper adopts a hierarchical nonlinear model and examines individual and urban influencing factors of migrant workers' household registration transfer willingness, based on the data from China Migrants Dynamic Survey (CMDS) and the Urban Statistical Yearbooks.

This paper shows that: (1) multi-factors, such as age, education, marital status, household demographics, industry and migrant workers' contract coverage, have significant effects on migrant workers' household registration transfer willingness; (2) The urban public service equalization indicators, such as regional economic, educational resources, medical care and ecological quality, have significant effects on migrant workers' willingness to transfer household registration; (3) The heterogeneity of migrant workers' willingness to transfer household registration is significant in central, eastern and western China.

The authors provide a fresh perspective on population migration research in China and other countries worldwide based on the pull–push migration theory, which incorporates both individual and macro (urban) factors, enabling a comprehensive examination of the factors influencing household registration transfer willingness. This hierarchical ideology and approach (hierarchical nonlinear model) could be extended to investigate the influencing factors of various other human intentions and behaviors.

Micro approaches (individual perspective) have dominated existing studies examining the factors influencing migrant workers' household registration transfer willingness. The authors combine individual and urban perspectives and adopt a more comprehensive hierarchical nonlinear model to extend the empirical evidence and provide theoretical explanations for the above issues.

Sub-Saharan forced migration in recent decades has reached alarming levels, significantly increasing the risk to develop mental health vulnerabilities due to traumatic events and postmigration stressors. Research gaps persist within this population, necessitating culturally sensitive studies within a socioecological framework. This pilot exploratory mixed-method study aims to investigate the quality of life and subjective well-being among African displaced individuals in Niger.

In total, 119 African displaced adults (M = 26; SD = ±7.8) were administered WHOQOL-BREF to assess the quality of life (objective well-being) and Perma profiler and SWLS to assess subjective well-being, and 20 (M = 30.8; SD = ±7.4) of the previously assessed participants were in-depth interviewed to record their life stories, and transcripts were analyzed throughout thematic content analysis.

Quantitative results showed that all domains of quality of life, subjective well-being and life satisfaction scored below the African normative population levels. Particularly, environment, positive emotions and accomplishments in life were consistently below the normative mean score. The most affected dimension was life satisfaction. Qualitative findings revealed three main themes: potentially stressful or traumatic events that occurred to migrants and refugees, well-being as a continuum and the multiple meanings of forced migration, explaining the multiple burdens and resources that displaced people, affecting their subjective and objective well-being.

This study contributes to addressing mental health gaps among sub-Saharan forced migrants through a unique combination of quantitative and qualitative analysis, offering insights into their experiences within the context of forced migration and resettlement.

This study aims to investigate the relationship between Kosovo remittances, migration and labor force participation and seeks to uncover how migration and remittances, often considered separately, interact to shape labor market outcomes across gender, age and education groups.

To analyze the relationship between remittances, migration and labor force participation, this study leverages multivariate probit (mvprobit) to rectify the endogeneity issue intrinsic from remittances and migration. Utilizing this robust methodological approach allows us to circumvent the limitations traditionally associated with biprobit analysis. The research is grounded in empirical evidence from the Millennium Century Corporation survey in Kosovo.

The findings indicate that remittances and migration are pivotal determinants in shaping the contours of labor force participation, particularly influencing disparities across gender, age and educational attainment. Further, this study unearthed intriguing evidence suggesting the disincentivizing effect of remittances on labor force participation, alongside the potentially disruptive influence of prospective migration plans.

The novelty of this work lies not only in the context-specific insights it provides into the socio-economic fabric of Kosovo—an area that has hitherto received limited scholarly attention—but also in its methodological innovation. The simultaneous application of mvprobit technique provides a nuanced approach to tackle the inherent endogeneity issue, thereby pushing the methodological frontiers of the field.

Countries have implemented various migration policies targeting the migrants' economic and political integration and social inclusion. However, little is known about the impact of migration policies on migrants' participation in socio-cultural activities and their link with well-being. The first aim of this study is to explore the effect of the Migration Act of 2000 in Germany on participation in socio-cultural activities of first-generation migrants. The second aim is to examine the impact of socio-cultural activities on subjective well-being (SWB), measured by life satisfaction, and how it is compared between first-generation immigrants and natives.

The Migration Act of 2000 was extended in 2005 to provide permanent residence permits to high-skilled migrants and deliver cultural orientation and German language courses. The author will implement a Difference-in-Differences (DiD) methodology comparing the relationship between socio-cultural participation and SWB of first-generation immigrants and natives.

The results show that while first-generation immigrants participate less frequently in the socio-cultural activities explored, they experience an increase in participation after the implementation of the 2000 Migration Act. Furthermore, migrants report lower levels of SWB than natives, but their life satisfaction significantly improves with the increase in socio-cultural participation.

The findings of this study have implications for researchers and policymakers, such as income, education and employment promoting migrant integration. Providing employment opportunities and a permanent residence permit, cultural participation, and thus, the integration of migrants can be successfully achieved.

While there is a long debate about the effectiveness of migration integration policies, this is the first study investigating the effect of the Migration Act of 2000 on migrants' socio-cultural participation and well-being.