缺失天气变量估计的计量经济模型:坦桑尼亚Shinyanga地区

Kulyakwave P.D, Shiwei Xu, Wen Yu
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摘要

本研究的目的是建立坦桑尼亚辛扬加地区天气变量的计量经济模型。开发的模式用于预测1981年至1987年缺少的天气变量,如日照、最高和最低温度。作者利用1981年至2017年的降雨、日照、最高气温和最低气温等天气时间序列数据,建立了Mbeya和Shinyanga地区变量之间的统计关系。使用的统计方法有:普通最小二乘回归、增强型Dickey-Fuller检验时间序列平稳性的单位根检验、Johansen协整检验和误差修正来建立变量之间的关系。我们建立了新阳加地区缺失日照、最大和最小变量的三个计量模型。日照模式表明,Mbeya地区每增加单位降雨量(mm),新阳加地区的日照增加3.8%,而新阳加地区每增加单位降雨量(mm),日照减少1%。最高温度模型表明,Mbeya降雨量每增加1mm,最高温度降低0.5%,而Shinyanga降雨量每增加1mm,最高温度降低0.7%。对于最低温度模型,Mbeya和Shinyanga地区的降雨量每增加1 mm, Shinyanga地区的最低温度降低0.4%,而Mbeya地区的最低温度每增加1°C, Shinyanga地区的最低温度升高43%。因此,我们通过使用各自构建的模型来估计缺失变量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Econometric Modelling for Missing Weather Variables Estimation: Shinyanga Region of Tanzania
This study was conducted to develop econometric models for weather variables for Shinyanga region of Tanzania. The developed models used to predict missing weather variables such as sunshine, maximum, and minimum temperatures from 1981 to 1987. The authors used weather time series data including rainfall, sunshine, maximum, and minimum temperatures from 1981 to 2017 to establish statistical relationship among variables from Mbeya and Shinyanga regions. Various statistical methods used include Ordinary Least Square regression, Augmented Dickey-Fuller test for Unit root test of time series stationarity, Johansen Cointegration test and error correction to establish relationship among variables. We developed three econometric models for missing sunshine, maximum and minimum variables for Shinyanga region. Sunshine model shows that for each unit rainfall (mm) increase in Mbeya region increased the sunshine for Shinyanga by 3.8%, while for each increase in lmm rainfall in Shinyanga region the sunshine decreases by 1%. Maximum temperature model reveals that increase in rainfall in Mbeya by lmm decreases the maximum temperature by 0.5 % while for each increase by lmm rainfall in Shinyanga leads to a decrease of maximum temperature by 0.7%. For the minimum temperature model, 1 mm increase in both Mbeya and Shinyanga rainfall decreases the minimum temperature for Shinyanga by 0.4 % while increase in 1°C minimum temperature for Mbeya region increases Shinyanga minimum temperature by 43%. Accordingly, we estimated the missing variables by the use of the respective constructed models.
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