کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5115991 1485116 2017 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Long-term economic growth projections in the Shared Socioeconomic Pathways
ترجمه فارسی عنوان
پیش بینی های رشد اقتصادی درازمدت در مسیرهای اجتماعی-اقتصادی مشترک
کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم محیط زیست علوم زیست محیطی (عمومی)
چکیده انگلیسی
Long-term economic scenarios (up to 2100) are needed as a basis to explore possible different futures for major environmental challenges, including climate change. Given the high level of uncertainty involved, such scenarios would need to span a wide range of possible growth trajectories. The recently developed storylines of the Shared Socioeconomic Pathways (SSPs) provide a basis for making such projections. This paper describes a consistent methodology to derive (per capita) GDP trend pathways on a country basis. The methodology is based on a convergence process and places emphasis on the key drivers of economic growth in the long run: population, total factor productivity, physical capital, employment and human capital, and energy and fossil fuel resources (specifically oil and gas). The paper uses this methodology to derive country-level economic growth projections for 184 countries. The paper also investigates the influence of short-term growth rate estimates on the long-term income levels in various countries. It does so by comparing long-term projections based on short-term forecasts from 2011 with the projections based on forecasts from 2013. This highlights the effects of the recent economic crisis and uncertainty in short term developments on longer term growth trends. The projections are subject to large uncertainties, particularly for the later decades, and disregard a wide range of country-specific drivers of economic growth that are outside the narrow economic framework, such as external shocks, governance barriers and feedbacks from environmental damage. Hence, they should be interpreted with sufficient care and not be treated as predictions.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Global Environmental Change - Volume 42, January 2017, Pages 200-214
نویسندگان
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