Low-Carbon City Initiatives and Analyst Behaviour: A Quasi-Natural Experiment
This paper investigates how environmental regulation and action affect analyst behaviour. Exploiting staggered enactment of low carbon city (LCC) initiatives in a difference-in-differences (DiD) setting, we observe that analyst forecast accuracy (dispersion) is significantly lower (greater) for clie...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
2022
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| Online Access: | http://hdl.handle.net/20.500.11937/88981 |
| _version_ | 1848765129956524032 |
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| author | Cao, June Li, W. Bilokha, A. |
| author_facet | Cao, June Li, W. Bilokha, A. |
| author_sort | Cao, June |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This paper investigates how environmental regulation and action affect analyst behaviour. Exploiting staggered enactment of low carbon city (LCC) initiatives in a difference-in-differences (DiD) setting, we observe that analyst forecast accuracy (dispersion) is significantly lower (greater) for client firms headquartered in cities covered by the LCC pilot programme, especially among firms with a low-quality information environment. The LCC effort affects analyst behaviour via increased firm risk and reduced earnings predictability, causing enhanced site visits and coverage. The results are stronger in cities with more rigorous enforcement and regulation intensity, for private firms with high business complexity and in heavily polluting industries. Results are robust to DiD models with entropy balancing matching, placebo tests, parallel trend tests, and a battery of fixed effects. Collectively, they reveal that environmental regulation has real impacts on analyst forecast behaviour. |
| first_indexed | 2025-11-14T11:30:21Z |
| format | Journal Article |
| id | curtin-20.500.11937-88981 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:30:21Z |
| publishDate | 2022 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-889812022-08-15T03:56:02Z Low-Carbon City Initiatives and Analyst Behaviour: A Quasi-Natural Experiment Cao, June Li, W. Bilokha, A. This paper investigates how environmental regulation and action affect analyst behaviour. Exploiting staggered enactment of low carbon city (LCC) initiatives in a difference-in-differences (DiD) setting, we observe that analyst forecast accuracy (dispersion) is significantly lower (greater) for client firms headquartered in cities covered by the LCC pilot programme, especially among firms with a low-quality information environment. The LCC effort affects analyst behaviour via increased firm risk and reduced earnings predictability, causing enhanced site visits and coverage. The results are stronger in cities with more rigorous enforcement and regulation intensity, for private firms with high business complexity and in heavily polluting industries. Results are robust to DiD models with entropy balancing matching, placebo tests, parallel trend tests, and a battery of fixed effects. Collectively, they reveal that environmental regulation has real impacts on analyst forecast behaviour. 2022 Journal Article http://hdl.handle.net/20.500.11937/88981 10.1016/j.jfs.2022.101042 restricted |
| spellingShingle | Cao, June Li, W. Bilokha, A. Low-Carbon City Initiatives and Analyst Behaviour: A Quasi-Natural Experiment |
| title | Low-Carbon City Initiatives and Analyst Behaviour: A Quasi-Natural Experiment |
| title_full | Low-Carbon City Initiatives and Analyst Behaviour: A Quasi-Natural Experiment |
| title_fullStr | Low-Carbon City Initiatives and Analyst Behaviour: A Quasi-Natural Experiment |
| title_full_unstemmed | Low-Carbon City Initiatives and Analyst Behaviour: A Quasi-Natural Experiment |
| title_short | Low-Carbon City Initiatives and Analyst Behaviour: A Quasi-Natural Experiment |
| title_sort | low-carbon city initiatives and analyst behaviour: a quasi-natural experiment |
| url | http://hdl.handle.net/20.500.11937/88981 |