Forecasting the Integration of Immigrants

TL;DR

This paper introduces a simple, accurate, and robust quantitative framework for forecasting immigrant integration based solely on immigrant density, providing timely predictions with minimal error.

Contribution

It presents a novel, straightforward model that effectively predicts immigrant integration over several years using only immigrant density as a key driver.

Findings

Forecasts are available shortly after data collection.

Predictions have a small relative error.

The model accurately predicts long-term integration trends.

Abstract

This paper presents a quantitative framework for forecasting immigrant integration using immigrant density as the single driver. By comparing forecasted integration estimates based on data collected up to specific periods in time, with observed integration quantities beyond the specified period, we show that: Our forecasts are prompt-readily available after a short period of time, accurate-with a small relative error-and finally robust-able to predict integration correctly for several years to come. The research reported here proves that the proposed model of integration and its forecast framework are simple and effective tools to reduce uncertainties about how integration phenomena emerge and how they are likely to develop in response to increased migration levels in the future.