| dc.contributor | 政治系 | en_US |
| dc.creator (作者) | 蔡宗漢 | zh_TW |
| dc.date (日期) | 2011.09 | en_US |
| dc.date.accessioned | 7-Jan-2014 14:13:19 (UTC+8) | - |
| dc.date.available | 7-Jan-2014 14:13:19 (UTC+8) | - |
| dc.date.issued (上傳時間) | 7-Jan-2014 14:13:19 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/63317 | - |
| dc.description.abstract (摘要) | The time-invariant and/or rarely changing explanatory variables are of interest to political scientists, including both their short- and long-run effects. However, estimating these effects in the analysis of time-series cross-sectional (TSCS) data by the conventional estimators may be problematic when unit effects are included in the model. This paper discusses the advantages of using Bayesian multilevel modeling to estimate the dynamic effects of these slowly changing explanatory variables in the analysis of TSCS data and applies a Bayesian dynamic multilevel model to analyzing the effects of political regime on social spending in Latin America. | en_US |
| dc.format.extent | 1365642 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.language.iso | en_US | - |
| dc.relation (關聯) | 2011 American Political Science Association Annual Meeting, American Political Science Association | en_US |
| dc.subject (關鍵詞) | Bayesian inference; multilevel modeling; dynamic panel models; time-invariant variables; social spending; Latin America working papers series | en_US |
| dc.title (題名) | Bayesian Inference for Dynamics of Slowly Changing Variables in Time-Series Cross-Sectional Data Analyses | en_US |
| dc.type (資料類型) | conference | en |
