دانلود مقاله ISI انگلیسی شماره 97928
ترجمه فارسی عنوان مقاله

روش های آماری فضایی برای مدل برآورد توزیع انرژی برزیل در سال 2015: حسابداری برای تعیین کننده های نامطلوب ناکارآمدی

عنوان انگلیسی
Spatial statistical methods applied to the 2015 Brazilian energy distribution benchmarking model: Accounting for unobserved determinants of inefficiencies
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
97928 2017 26 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Energy Economics, Volume 64, May 2017, Pages 373-383

ترجمه کلمات کلیدی
تحلیل پوششی داده ها، تجزیه و تحلیل مرحله دوم، آمار فضایی، تجزیه و تحلیل بیزی،
کلمات کلیدی انگلیسی
Data envelopment analysis; Second stage analysis; Spatial statistics; Bayesian analysis;
پیش نمایش مقاله
پیش نمایش مقاله  روش های آماری فضایی برای مدل برآورد توزیع انرژی برزیل در سال 2015: حسابداری برای تعیین کننده های نامطلوب ناکارآمدی

چکیده انگلیسی

In 2015 the Brazilian regulator presented a DEA benchmarking model to set the regulatory operational cost goals, to be reached in four years for 61 electricity distribution utilities. The DEA model uses: adjusted operational cost as the input variable, seven output variables and weight restrictions. Although non-discretionary variables or environmental variables are available in the dataset, the regulator argued that no statistically significant correlation was found between the DEA efficiency scores and the non-discretionary variables. This study evaluates the statistical correlation between the DEA efficiency scores and the available environmental variables. Spatial statistic methods are used to show that the efficiency scores are geographically correlated. Furthermore, due to Brazil's environmental diversity and large territory it is unlikely that only one environmental component is sufficient to adjust inefficiencies across the Brazilian territory. Thus, a new combined environmental variable is proposed. Finally, a second stage model using the proposed environmental variable and accounting for a spatial latent structure is presented. Results show major differences between original and corrected efficiency scores, mainly for utilities located in harsh environments and which originally achieved lower efficiency scores.