Abstract
Since 2006 English Local Authorities (LA) have had discretionary powers to implement a type of landlord licensing scheme, Selective Licensing (SL), in the private rental sector. The scheme is intended to improve housing standards in areas marked by antisocial behaviour, poor housing conditions, low housing demand, and high levels of migration, deprivation, and crime. Yet up to 2019, only 15% of LA had adopted SL.
We examine temporal, socio-economic, and geographical factors associated with SL adoption between 2006 and 2019, focusing on: A) overall temporal trends in adoption, B) socio-economic factors in adoption on their own; and in relation to C) regional diffusion processes. To examine these factors, we applied cumulative adoption rate, logit, and spatial autoregressive logit (SAL) models considering 1st and 2nd order LA neighbours. The influence of socio-economic factors was studied using multiple variables and by coding the LA with the Census 2011 LA classification.
The adoption curve showed that the policy has only been adopted at a slow rate. The adoption rate did however increase slightly at the point when the justifiable reasons for implementing SL were expanded. The logit and SAL models showed that higher proportions of the population receiving Income Support was a powerful determinant, while spatial spillovers were not statistically significant. The same was true in SAL with Census classification exposure showing stronger associations with larger urban areas than with spatial spillovers. We note that SL is absent from large parts of Mid- and South-England, so even without evidence of regional diffusion on a local scale it may still exist on a larger scale.
We conclude that SL adoption has been slow, regionally patchy, and more correlated with socio-economic factors than with regional diffusion processes. Resource and staffing constraints as well as internal organisational/political and policy-related factors are likely barriers to adoption. More qualitative evidence is needed from local areas including from those that never adopted SL.
We examine temporal, socio-economic, and geographical factors associated with SL adoption between 2006 and 2019, focusing on: A) overall temporal trends in adoption, B) socio-economic factors in adoption on their own; and in relation to C) regional diffusion processes. To examine these factors, we applied cumulative adoption rate, logit, and spatial autoregressive logit (SAL) models considering 1st and 2nd order LA neighbours. The influence of socio-economic factors was studied using multiple variables and by coding the LA with the Census 2011 LA classification.
The adoption curve showed that the policy has only been adopted at a slow rate. The adoption rate did however increase slightly at the point when the justifiable reasons for implementing SL were expanded. The logit and SAL models showed that higher proportions of the population receiving Income Support was a powerful determinant, while spatial spillovers were not statistically significant. The same was true in SAL with Census classification exposure showing stronger associations with larger urban areas than with spatial spillovers. We note that SL is absent from large parts of Mid- and South-England, so even without evidence of regional diffusion on a local scale it may still exist on a larger scale.
We conclude that SL adoption has been slow, regionally patchy, and more correlated with socio-economic factors than with regional diffusion processes. Resource and staffing constraints as well as internal organisational/political and policy-related factors are likely barriers to adoption. More qualitative evidence is needed from local areas including from those that never adopted SL.
| Original language | English |
|---|---|
| Article number | 23998083251411371 |
| Number of pages | 17 |
| Journal | Environment and Planning B: Urban Analytics and City Science |
| Early online date | 6 Jan 2026 |
| DOIs | |
| Publication status | E-pub ahead of print - 6 Jan 2026 |
Bibliographical note
Publisher Copyright:© The Author(s) 2026. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).