Reviving Cleveland’s commercial corridors: Analyzing the Storefront Renovation Program, 1983–2016

Kinahan, Kelly L.; Ryberg-Webster, Stephanie

doi:10.1080/07352166.2021.1915152

Cited by 2 publications

(1 citation statement)

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“…Shrinking cities are typically characterized by population decline, leading to delayed economic growth, imbalanced industrial structure, reduced investment output, declining enterprise efficiency, and inefficient land use. Slow economic growth [2,37], weak investment [40,41], and relatively unfavorable natural conditions [42,43] are among the primary causes contributing to the emergence of shrinking cities. With the requirements of the panel threshold regression model in mind, this study selects the following factors for regression analysis:…”

Section: Variable Selection and Sourcementioning

confidence: 99%

Exploration of Spatio-Temporal Evolution and Threshold Effect of Shrinking Cities

Song

Jia

2023

Land

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Shrinking cities are a global issue with regional characteristics. This paper focuses on the county-level administrative units in the Three Northeastern Provinces in China to identify and classify shrinking cities using a two-step identification method and explores their spatial-temporal evolution. The paper utilizes the panel threshold regression model for empirical testing. The results indicate the following: (1) The number of shrinking cities in the region is large and deep. Quantitatively, the shrinking cities account for about 50% of the whole; spatially, there are six major shrinking city “groups”, showing the distribution trend around the “Ha-Da” urban corridor. (2) The threshold effect test reveals that GDP is a critical threshold variable influencing the formation of shrinking cities. Moreover, cities are classified into three types based on the threshold values: Type I (GDP > 2,270,731 yuan), Type II (434,832 < GDP ≤ 2,270,731), and Type III (GDP < 434,832). (3) The results of the dual-threshold and grouped regression models show significant variations in the dominant factors of shrinking cities of different scales. Variables such as impervious area, fiscal revenue, and grass area demonstrate relatively stable promoting effects.

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