Climate change is more obvious and stable than weather change, but due to many factors affecting climate and great uncertainty, it is impossible to fully quantify its impact on economic development. We can only quantitatively evaluate some of the most stable climatic factors in specific economic sectors such as agriculture. Bok's forecast model is based on the economic data and temperature historical data of 166 countries during the 50 years from 1960 to 20 10. They found that the influence of temperature on economic development is nonlinear, and the annual average temperature 13℃ is a watershed. When the average temperature in that year is lower than 13℃, with the increase of temperature, the economic productivity and economic level will increase. Once it exceeds 13℃, the economic productivity will decrease with the increase of temperature, and the higher the annual average temperature, the faster the economic productivity will decrease. Therefore, the annual average temperature 13℃ is the most suitable "environmental temperature" for economic development.
It can be clearly judged from this paragraph that the way to reach this conclusion is to use statistical correlation analysis. More simply, it is to list a temperature change curve of 1960-20 10, and then list an economic productivity curve of 1960-20 10, and then look at their correlation, and finally get 10. Of course, everyone who plays with big data knows that this can only draw their relevant conclusions, but not that one factor is the cause and effect of another, so I am skeptical about the results of this report. 973 National Key Basic Research Development Plan: Impact of Climate Change on Socio-economic System and Adaptation Strategies China Academy of Sciences. This is a project I participated in when I was at school. At present, CGE model and the model developed by tutors in cooperation with other disciplines are very complicated and involve many parameters.