Legal Immigration to the United States: A Time Series Analysis

D. Akoto, R. N. A. Akoto (), B. K. Mussey and L. Atepor
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D. Akoto: Villanova University
R. N. A. Akoto: University of Professional Studies
B. K. Mussey: Takoradi Technical University
L. Atepor: Cape Coast Technical University

A chapter in Sustainable Education and Development – Sustainable Industrialization and Innovation, 2023, pp 190-201 from Springer

Abstract: Abstract Purpose: This study aims to identify trends in America’s immigration levels, predict the number of immigrants arriving in the United States for the next ten years, and use a regression model to explain variations in the total number of annual U.S. Naturalizations. Design/Methodology/Approach: This study utilizes time series data for legal permanent residents published by the Department of Homeland Security (DHS) from 1820 to 2020. Annual time series data for the number of naturalization applications filed, the annual data on the number of applications denied, and the yearly total number of naturalizations were merged to build a regression model. Time series analysis plots were used to identify trends in annual immigration. Estimating parameters and forecasting immigration numbers for the next ten years was done using the maximum likelihood method (ARIMA). Also, a regression model with ARMA errors was used to explain variations in the total number of U.S Naturalizations. Findings: The time series analysis plots showed an increasing trend for immigration levels. The forecasted values showed a continued increasing trend for number of U.S immigrants in the next ten years. The final regression model with ARMA errors revealed that the yearly number of applications filed and denied are significant in explaining the total of U.S Naturalizations annually. Research Limitations: The time series data on the Department of Homeland Security (DHS) is not timely, hence making it difficult to get the most recent data on immigration. Social Implications: This may be an indicator for law and policy decision makers to adjust future programs and policies to cater for the increasing number of immigrations to track sustainable development and industrialization. Originality: The uniqueness of this study lies in the methodology employed to identify trends, perform forecasts and regression modelling techniques.

Keywords: Immigration; Legal; Naturalization; Time series; USA (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-25998-2_15

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DOI: 10.1007/978-3-031-25998-2_15

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