我国城镇登记失业率的影响因素分析及预测

Forecast and Factors Analysis on Chinese Registered Urban Unemployment Rate

失业是市场经济运行中的难题,把失业率控制在社会可承受的范围内,是很多国家的重要目标。失业率要受各种经济和社会因素的影响,利用我国的一些宏观经济指标和城镇登记失业率建立贝叶斯向量自回归模型(BVAR),并做脉冲响应分析,通过对比向量自回归(VAR)和贝叶斯向量自回归模型(BVAR)所做的失业率预测,发现BVAR比VAR得出的预测结果更好。

Unemployment is a difficult problem in the market economy,and it is an important objective for many countries to control the unemployment rate in the affordable range.Unemployment rate is affected by various economical and social factors.In this paper,we establish Bayesian vector Autoregression（BVAR） model by using macro-economic variables and the registered urban unemployment rate.In addition,we make impulse response analysis to study the variables＇ effects on the unemployment rate in phrase one and multi-phase period.By comparing effects on unemployment forecasting made by the vector autoregressive（VAR） and Bayesian vector autoregression（BVAR）,we conclude that BVAR forecasts better than VAR.