This paper proposes a new time-varying parameter distributed lag(DL)model.In contrast to the existing methods,which assume parameters to be random walks or regime shifts,our method allows time-varying coefficients of ...This paper proposes a new time-varying parameter distributed lag(DL)model.In contrast to the existing methods,which assume parameters to be random walks or regime shifts,our method allows time-varying coefficients of lagged explanatory variables to be conditional on past information.Furthermore,a test for constant-parameter DL model is introduced.The model is then applied to examine time-varying causal effect of inventory on crude oil price and forecast weekly crude oil price.Time-varying causal effect of US commercial crude oil inventory on crude oil price return is presented.In particular,the causal effect of inventory is occasionally positive,which is contrary to some previous research.It’s also shown that the proposed model yields the best in and out-of-sample performances compared to seven alternative models including RW,ARMA,VAR,DL,autoregressive-distributed lag(ADL),time-varying parameter ADL(TVP-ADL)and DCB(dynamic conditional beta)models.展开更多
风速性质直接影响风力发电的功率,确定性预测在很多方面无法满足当前需要,而概率性预测比较符合实际,具有更强的实用性.采用以当前时段实测风速和下一时段预报风速为联合条件的离散预报误差概率统计模型(forecast error probability dis...风速性质直接影响风力发电的功率,确定性预测在很多方面无法满足当前需要,而概率性预测比较符合实际,具有更强的实用性.采用以当前时段实测风速和下一时段预报风速为联合条件的离散预报误差概率统计模型(forecast error probability distribution,FEPD),从而预测短时(功率预测前几小时)风速,通过得到风速数据,在短时时段覆盖内,就能够预测风力发电的功率.实例证明,以风速为基础从而预测风力发电功率是一种有效的方法.展开更多
基金National Natural Science Foundation of China(71871213)。
文摘This paper proposes a new time-varying parameter distributed lag(DL)model.In contrast to the existing methods,which assume parameters to be random walks or regime shifts,our method allows time-varying coefficients of lagged explanatory variables to be conditional on past information.Furthermore,a test for constant-parameter DL model is introduced.The model is then applied to examine time-varying causal effect of inventory on crude oil price and forecast weekly crude oil price.Time-varying causal effect of US commercial crude oil inventory on crude oil price return is presented.In particular,the causal effect of inventory is occasionally positive,which is contrary to some previous research.It’s also shown that the proposed model yields the best in and out-of-sample performances compared to seven alternative models including RW,ARMA,VAR,DL,autoregressive-distributed lag(ADL),time-varying parameter ADL(TVP-ADL)and DCB(dynamic conditional beta)models.
文摘风速性质直接影响风力发电的功率,确定性预测在很多方面无法满足当前需要,而概率性预测比较符合实际,具有更强的实用性.采用以当前时段实测风速和下一时段预报风速为联合条件的离散预报误差概率统计模型(forecast error probability distribution,FEPD),从而预测短时(功率预测前几小时)风速,通过得到风速数据,在短时时段覆盖内,就能够预测风力发电的功率.实例证明,以风速为基础从而预测风力发电功率是一种有效的方法.
