dc.contributor | 經濟系 | |
dc.creator (作者) | 林馨怡 | |
dc.creator (作者) | Lin, Hsin-Yi;Hsiao, Yu-Hsiang;Hsu, Yu-Chin | |
dc.date (日期) | 2024-04 | |
dc.date.accessioned | 24-May-2024 10:49:20 (UTC+8) | - |
dc.date.available | 24-May-2024 10:49:20 (UTC+8) | - |
dc.date.issued (上傳時間) | 24-May-2024 10:49:20 (UTC+8) | - |
dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/151207 | - |
dc.description.abstract (摘要) | To assess the dynamic distributional impacts of macroeconomic policy, we propose quantile policy effects to quantify disparities between the quantiles of potential outcomes under different policies. We first identify quantile policy effects under the unconfoundedness assumption and propose an inverse probability weighting estimator. We then examine the asymptotic behavior of the proposed estimator in a time series framework and suggest a blockwise bootstrap method for inference. Applying this method, we investigate the effectiveness of U.S. macroprudential actions on bank credit growth from 1948 to 2019. Empirically, we find that the effects of macroprudential policy on credit growth are asymmetric and depend on the quantiles of credit growth. The tightening of macroprudential actions fails to rein in high credit growth, whereas easing policies do not effectively stimulate bank credit growth during low-growth periods. These findings suggest that U.S. macroprudential policies might not sufficiently address the challenges of soaring bank credit or ensure overarching financial stability. | |
dc.format.extent | 109 bytes | - |
dc.format.mimetype | text/html | - |
dc.relation (關聯) | Journal of Business & Economic Statistics, pp.1-17 | |
dc.subject (關鍵詞) | Causal effects; Impulse response functions; Macroprudential policy; Propensity score; Quantile functions | |
dc.title (題名) | Quantile Policy Effects: An Application to U.S. Macroprudential Policy | |
dc.type (資料類型) | article | |
dc.identifier.doi (DOI) | 10.1080/07350015.2024.2326140 | |
dc.doi.uri (DOI) | https://doi.org/10.1080/07350015.2024.2326140 | |