Metropolitan, Urban, and Rural Regions: How Regional Differences Affect Elementary School Students in Germany

Oct 15, 2026

Uploaded by Pentious

Using PIRLS 2016 data, this study analyzes how regional differences in Germany shape elementary students’ educational tracking, enjoyment of school, and reading interest. The sample includes 3,959 fourth-grade students, modeled through bootstrapping, multiple imputation, principal component analysis, and LASSO. Students from rural and metropolitan areas show higher probabilities of receiving academic track recommendations and slightly greater reading-related well-being and interest compared with urban peers.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages26

Reading Time1 h 6 min

AccessFree to download

Introduction

Regional differences and student outcomes

German education system and early tracking

Data and analytic approach

Key variables and modeling strategy

AERA Open January-December 2025, Vol. 11, No. 1, pp. 1–26 DOI: 10. 1177/23328584251331453 Article reuse guidelines: [sagepub.com/journals-permissions](sagepub.com/journals-permissions)[ ](sagepub.com/journals-permissions)© The Author(s) 2025. [https://journals.sagepub.com/home/ero](https://journals.sagepub.com/home/ero) Metropolitan, Urban, and Rural Regions: How Regional Differences Affect Elementary School Students in Germany Jakob Schwerter TU Dortmund University Johannes Bleher University of Hohenheim Philipp Doebler Nele McElvany TU Dortmund University This study examined how regional differences affect elementary school students using the representative German Progress in International Reading Literacy Study (PIRLS) 2016 data (N = 3,959 fourth-grade students; M_ {Age} = 10.34 years; 49% girls; 71% from a nonimmigrant background) by combining bootstrapping, multiple imputations, principal component analysis, and the least absolute shrinkage and selection operator (LASSO). Grouping regions into rural,(sub-)urban, and metropolitan, we found that students from rural and metropolitan areas are 10.9% and 15.1% more likely, respectively, to receive an academic track recommendation than their urban counterparts. Similarly, rural and metropolitan students are 0.2 to 0.3 standard deviations more likely to enjoy school and be interested in reading than their urban counterparts. Aside from students’ backgrounds and skills, many of the characteristics explaining this regional difference are structural, directly affected by policy decisions. Variables directly and indirectly influenced by policy help explain regional differences, but nonpolicy variables reduce regional differences in academic track recommendations the most. Keywords: regional differences, school resources, teacher distribution, academic achievement, well-being, interest, elementary school, fourth grade school students, machine learning application, Progress in International Reading Literacy Study (PIRLS) 2016 Introduction Even slight differences in early-life conditions can produce significant social inequalities by establishing pathdependent trajectories (DiPrete & Eirich, 2006; Elder et al., 2003; Kosse et al., 2020; Organisation for Economic Co-operation and Development [OECD], 2017) . This underscores the importance of ensuring the equal quality of students’ institutional environments because growing up ina region with “better” characteristics improves students’educational trajectories (Chetty et al., 2016) as well as labor market outcomes (Abramitzky et al., 2021; Lavy, 2021) . In particular, being part of an effective institutional learning environment during elementary school relates to educational attainment later in life (Tymms et al., 2018) . Thus, whether children growing up in different regions within a country experience equal opportunities in their institutional environment along their educational pathway is a fundamental question when it comes to designing and evaluating educational policies. Children are inevitably influenced by the regional characteristics of their surroundings—especially local educational institutions, which they cannot choose (Mayer & Koinzer, 2020) .1 Furthermore, a school’s resources affect health and academic outcomes. Better-resourced schools can provide, for example, a healthier breakfast and lunch, which increases students’ health (Rothbart et al., 2023). Additionally, the little residential mobility that occurs in Germany is mainly related to changes in parents’ jobs, meaning that school choice is determined endogenously (Krabel & Flöther, 2014; Sánchez & Andrews, 2011) . This is particularly relevant for elementary school students, who are too young to commute to a distant school and given that no school busing is provided in Germany. In addition, students in Germany must Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License ([h

FAQs

What data and sample does the study use?

The study uses PIRLS 2016 data with 3,959 German fourth-grade students (N = 3,959).

How do rural and metropolitan students differ from urban students?

Students from rural and metropolitan areas are more likely than urban students to receive an academic track recommendation, and they also show greater enjoyment of school and interest in reading.

What explains regional differences according to the study?

Regional differences are linked to both policy-influenced structural variables and nonpolicy factors; policy-related variables help explain differences, while nonpolicy variables most reduce differences in academic track recommendations.

Oct 15, 2026

Uploaded by Pentious