دانلود مقاله ISI انگلیسی شماره 105446
کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
105446 2017 13 صفحه PDF سفارش دهید 9395 کلمه
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عنوان انگلیسی
The accuracy of toll road traffic forecasts: An econometric evaluation
منبع

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

Journal : Transportation Research Part A: Policy and Practice, Volume 101, July 2017, Pages 73-85

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چکیده انگلیسی

This study assesses the accuracy of toll road traffic forecasts in Norway. This study contributes to extant literature regarding transportation economics and policy because few studies have analyzed the accuracy of toll road traffic forecasts and current studies on this topic do not use a succinct econometric framework to infer the forecast’s bias and efficiency, which are determinants of the accuracy of forecasts. The data for this study include 68 toll road projects where forecasts and actual out-turns were available. All projects that are included in this study were opened for traffic during 1975–2014. Transport models were made mandatory for forecasting toll traffic in 2006. The results of this study reveal the following: (i) Norwegian toll road traffic forecasts are underestimated but are close to accurate because the mean percentage error is a mere 4%. This result sharply contrasts international studies that resulted in large overestimations at more than −20%. (ii) The accuracy of forecasts has not improved since transport models became mandatory. (iii) The Norwegian toll road traffic forecasts are unbiased, which implies that they do not tend to be one-sided. (iv) Norwegian forecasts are efficient, which implies that available information is used adequately when making forecasts. Our conclusion is that the toll traffic forecasts in Norway perform fairly well compared to the forecasts of other countries. In addition, we recommend that the assessment of forecasts in the transportation sector should be based on succinct econometric frameworks; otherwise, the conclusions may lack important information regarding the bias and efficiency of the forecasts.

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