The unit root can lead to major problems in economic time series analyses. I obtain the asymptotic distributions of the ordinary least squares (OLS) estimator when the true model is trend stationary for the following ...The unit root can lead to major problems in economic time series analyses. I obtain the asymptotic distributions of the ordinary least squares (OLS) estimator when the true model is trend stationary for the following three cases: 1) the null model is a random walk without drift, and the auxiliary regression model does not contain a constant;2) the null model is a random walk with drift, and the auxiliary regression model contains a constant;and 3) the null model is a random walk with drift, and the auxiliary regression model contains both a constant and a time trend. In the third case, the asymptotic distribution of the OLS estimator is determined by the first order of the autocorrelation, and we can distinguish between the random walk and trend stationary models, unlike in previous studies. Based on these results, the real US gross domestic product is analyzed. A time trend model with autoregressive error terms is chosen. The results suggest that the impacts of a shock can become larger than the original shock in some periods and then gradually decline. However, the impacts continue for a long period, and policy makers should account for this to design better economic policies.展开更多
为了分析像素级社会经济活动的空间分布状况,以Landsat8和NPP-VIIRS夜间灯光影像为数据源,分别对北京市第一产业和第二、三产业GDP进行空间化操作。利用分类回归树(classification and regression tree,CART)算法,通过Landsat8影像生成...为了分析像素级社会经济活动的空间分布状况,以Landsat8和NPP-VIIRS夜间灯光影像为数据源,分别对北京市第一产业和第二、三产业GDP进行空间化操作。利用分类回归树(classification and regression tree,CART)算法,通过Landsat8影像生成北京市的土地利用图,在分析第一产业GDP与土地利用类型面积相关性的基础上,构建了第一产业GDP与耕地面积的线性回归模型。建立了5种灯光指标与第二、三产业GDP的数学关系,通过相关性和回归分析确定第二、三产业GDP与综合灯光指数呈明显的幂函数关系。根据以上2种模型分别生成对应2类产业的像素级GDP密度图,再分别对其进行线性纠正并求和后制作出北京市500 m格网尺寸的GDP密度图。误差分析发现,第一产业GDP、第二、三产业GDP和GDP总量与实际统计值的平均相对误差分别为0.86%,0.61%和1.37%。结果表明,结合土地利用数据的NPP-VIIRS夜间灯光GDP空间化方法可以精确估算北京市GDP产值,反映北京市经济空间分布特征。展开更多
文摘The unit root can lead to major problems in economic time series analyses. I obtain the asymptotic distributions of the ordinary least squares (OLS) estimator when the true model is trend stationary for the following three cases: 1) the null model is a random walk without drift, and the auxiliary regression model does not contain a constant;2) the null model is a random walk with drift, and the auxiliary regression model contains a constant;and 3) the null model is a random walk with drift, and the auxiliary regression model contains both a constant and a time trend. In the third case, the asymptotic distribution of the OLS estimator is determined by the first order of the autocorrelation, and we can distinguish between the random walk and trend stationary models, unlike in previous studies. Based on these results, the real US gross domestic product is analyzed. A time trend model with autoregressive error terms is chosen. The results suggest that the impacts of a shock can become larger than the original shock in some periods and then gradually decline. However, the impacts continue for a long period, and policy makers should account for this to design better economic policies.
文摘为了分析像素级社会经济活动的空间分布状况,以Landsat8和NPP-VIIRS夜间灯光影像为数据源,分别对北京市第一产业和第二、三产业GDP进行空间化操作。利用分类回归树(classification and regression tree,CART)算法,通过Landsat8影像生成北京市的土地利用图,在分析第一产业GDP与土地利用类型面积相关性的基础上,构建了第一产业GDP与耕地面积的线性回归模型。建立了5种灯光指标与第二、三产业GDP的数学关系,通过相关性和回归分析确定第二、三产业GDP与综合灯光指数呈明显的幂函数关系。根据以上2种模型分别生成对应2类产业的像素级GDP密度图,再分别对其进行线性纠正并求和后制作出北京市500 m格网尺寸的GDP密度图。误差分析发现,第一产业GDP、第二、三产业GDP和GDP总量与实际统计值的平均相对误差分别为0.86%,0.61%和1.37%。结果表明,结合土地利用数据的NPP-VIIRS夜间灯光GDP空间化方法可以精确估算北京市GDP产值,反映北京市经济空间分布特征。
