Sensitivity analyses of industrial economic output to weather variability in Beijing
Based on 12 years (2002-2013) of economic data and historical weather observations,we analyzed the sensitivity of the industry economy to changes in meteorological factors.By improving an econometric model,Cobb-Douglas (C-D) production function,a quantitative causal relationship is established between meteorological factors and industry economy.Ridge regression modeling was employed to analyze meteorological factors and the industry economy of Beijing.Sensitivity ranking of Beijing economic industry was obtained,three among which are hypersensitive:construction industry,wholesale and retail trade,and financial industry.Agriculture is the least sensitive.The sensitivity ranking,from highest to lowest was:construction industry (0.499 5),wholesale and retail trade (0.417 6),financial industry (0.293 3),transportation,warehousing and postal services (0.280 6),industry (0.279 9),accommodation and catering industry (0.271 O),health and social security and welfare (0.269 1),cultural and sports and entertainment industry (0.260 7),and agriculture (0.253 7).Sensitivity analysis is helpful to the government of Beijing when conducting the industrial restructuring and optimization of resource patterns.This research indicates ridge regression is more in keeping with local economic development in Beijing.
econometric modelmeteorological factorssensitive industriesridge regressionBeijing City
NETL
NSTL
万方数据
维普
