Determinants of Urban Shrinkage in Small-Sized Cities: A Path Analysis of Demographic Decline in Harsin, Iran

Abstract Urban shrinkage has emerged as a relevant theme in recent urban scholarship, with growing intellectual interest since the start of the twenty-first century. The process, characterized by concomitant population decline and economic downturn, is driven by global and local forces such as economic globalization, deindustrialization, suburbanization, and political–institutional reform. While extensive research in developed countries has explored its causes and consequences, studies in developing contexts, particularly in small cities, remain limited. This study examines urban shrinkage in the small Iranian town of Harsin (Iran) that experienced a loss of roughly 20% of its population over two decades with the aim of identifying dominant drivers through direct and indirect causal relationships and proposing mitigation strategies. In this study, spatial and descriptive analyses were carried out on 15 social, economic, physical, and infrastructural indicators at the neighborhood scale, using GIS-based overlay techniques. To further examine the mechanisms underlying population decline, path analysis with a backward elimination regression procedure was employed to trace both the direct and indirect determinants of urban shrinkage in Harsin (Iran) during the period 2011–2016. Four direct predictors include (1) homeownership rates, (2) unemployment, (3) rental housing share, and (4) property values, while seven indirect factors, such as aging populations (more than 65 years old), male labor participation, employment status, small-sized housing (less than 75 m 2 ), building age, nonreinforced construction materials, and net migration, operate through mediating variables. Unemployment emerged as the strongest direct predictor (coefficient = 4.491), whereas property values showed the weakest association (coefficient = 0.290). The combined-effects model underscores unemployment’s dominant role (total coefficient = −5.87), with high-unemployment neighborhoods experiencing acute population loss. These findings highlight the urgency of targeted policy interventions, particularly in employment and housing, to address urban shrinkage in small cities. Finally, based on these findings, a set of goals, objectives, strategies, and policies is proposed to mitigate urban shrinkage, with implications for urban planning in similar small-scale cities in developing countries.

Authors

Institutions

Publication Details

Journal
Journal of Urban Planning and Development
Published
2026-08-25
DOI
https://doi.org/10.1061/jupddm.upeng-6456
Primary Topic
Urbanization and City Planning
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Determinants of Urban Shrinkage in Small-Sized Cities: A Path Analysis of Demographic Decline in Harsin, Iran

Mohammadreza Gholami Gowhareh
Journal of Urban Planning and Development
Urbanization and City Planning
article

Determinants of Urban Shrinkage in Small-Sized Cities: A Path Analysis of Demographic Decline in Harsin, Iran

Mohammadreza Gholami Gowhareh
article en

Abstract

Abstract Urban shrinkage has emerged as a relevant theme in recent urban scholarship, with growing intellectual interest since the start of the twenty-first century. The process, characterized by concomitant population decline and economic downturn, is driven by global and local forces such as economic globalization, deindustrialization, suburbanization, and political–institutional reform. While extensive research in developed countries has explored its causes and consequences, studies in developing contexts, particularly in small cities, remain limited. This study examines urban shrinkage in the small Iranian town of Harsin (Iran) that experienced a loss of roughly 20% of its population over two decades with the aim of identifying dominant drivers through direct and indirect causal relationships and proposing mitigation strategies. In this study, spatial and descriptive analyses were carried out on 15 social, economic, physical, and infrastructural indicators at the neighborhood scale, using GIS-based overlay techniques. To further examine the mechanisms underlying population decline, path analysis with a backward elimination regression procedure was employed to trace both the direct and indirect determinants of urban shrinkage in Harsin (Iran) during the period 2011–2016. Four direct predictors include (1) homeownership rates, (2) unemployment, (3) rental housing share, and (4) property values, while seven indirect factors, such as aging populations (more than 65 years old), male labor participation, employment status, small-sized housing (less than 75 m 2 ), building age, nonreinforced construction materials, and net migration, operate through mediating variables. Unemployment emerged as the strongest direct predictor (coefficient = 4.491), whereas property values showed the weakest association (coefficient = 0.290). The combined-effects model underscores unemployment’s dominant role (total coefficient = −5.87), with high-unemployment neighborhoods experiencing acute population loss. These findings highlight the urgency of targeted policy interventions, particularly in employment and housing, to address urban shrinkage in small cities. Finally, based on these findings, a set of goals, objectives, strategies, and policies is proposed to mitigate urban shrinkage, with implications for urban planning in similar small-scale cities in developing countries.

Journal of Urban Planning and DevelopmentVol. 152(4)
Northern Illinois University (US)
Openalex Percentile: Top 3%
Urbanization and City Planning
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.