基于贝叶斯向量自回归的区域经济预测模型:以青海为例
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引用本文:王飞.基于贝叶斯向量自回归的区域经济预测模型:以青海为例[J].经济数学,2011,(2):95-100
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作者单位
王飞 (中央民族大学经济学院北京100081) 
中文摘要:由于缺乏足够的观测数据等原因,常规的区域经济预测模型在我国难以获得预期的预测效果.而贝叶斯向量自回归(BVAR)模型将变量的统计性质作为参数的先验分布引入到传统的VAR模型中,能够克服自由度过少的问题.以青海为例,本文建立了一个BVAR模型,并引入了全国GDP和中央政府转移支付作为外生变量以描述国民经济与区域经济的联系.样本内和样本外的预测误差比较以及青海经济增长转折点的准确预测都表明BVAR区域经济预测模型优于其他预测模型.
中文关键词:BVAR  预测  区域经济增长  青海
 
Regional Economic Forecasting Model Based on the Bayesian Vector Autoregrssion:Evidence from Qinghai Province
Abstract:Because of insufficient data observations and other reasons, in China, the traditional regional economic forecasting models can not achieve the expected forecasting results. The Bayesian Vector Autoregrssion (BVAR) model introduces variables’ statistical properties as parameter’s prior distribution in the traditional VAR model, solving the problem of lacking degree of freedom. Based on Qinghai province’s empirical data, this paper illustrated the application of BVAR model, in which national GDP and transfer payment from central authority were introduced as exogenous variables to reflect the economic linkage between national economy and regional economy. In sample and out of sample forecasting error comparison and accurate forecast of the turn point of Qinghai economic growth show that the BVAR forecasting model outperforms other alternative models.
keywords:BVAR  forecast  regional economic growth  Qinghai
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