Modelling and forecasting immigration processes in the united kingdom using endogenous pull factors

This study focuses on the econometric modelling of immigration processes in the United Kingdom (UK) using endogenous pull factors. The study aims to investigate the impact of economic, social, housing and labour indicators on immigration inflows to the UK. In the article a regression model is employed, covering the period from 2000 to 2021 to estimate the relationship between the endogenous pull factors in the UK and immigra-tion processes. The endogenous pull factors considered in this study include economic factors such as GDP per capita, the number of new businesses per year, budget spend-ing per student and the average salary per year; social factors such as population den-sity, level of urbanization, and crime rate; housing factors such as the number of new residential buildings built; labour factors the unemployment and the employment rates. The results of the study show that key factors like GDP per capita, unemployment rate, newly registered businesses, and government spending per student have a significant influence on immigration inflows. In contrast, it was found that crime rate, average salary and population indicators don't affect international migration to the UK as much. The findings of this article have important implications for policymakers and researchers interested in understanding the dynamics of immigration processes in the UK. By iden-tifying the key endogenous pull factors driving immigration and using them to create forecasts such as the one in this study, policymakers can develop more effective immi-gration policies and better allocate resources to support immigrants and their integration into UK society.