دانلود رایگان مقاله مقایسه اثرات اشتغال بهره وری انرژی و سوخت فسیلی

Abstract

Global carbon emissions have reached unsustainable levels, and transforming the energy sector by increasing efficiency and use of renewables is one of the primary strategies to reduce emissions. Policy makers need to understand both the environmental and economic impacts of fiscal and regulatory policies regarding the energy sector. Transitioning to lower-carbon energy will entail a contraction of the fossil fuel sector, along with a loss of jobs. An important question is whether clean energy will create more jobs than will be lost in fossil fuels. This article presents a method of using Input-Output (I-O) tables to create “synthetic” industries – namely clean energy industries that do not currently exist in I-O tables. This approach allows researchers to evaluate public and private spending in clean energy and compare it to the effects of spending on fossil fuels. Here we focus on employment impacts in the short-to-medium term, and leave aside the long-term comparison of operations and maintenance employment. We find that on average, 2.65 full-time-equivalent (FTE) jobs are created from $1 million spending in fossil fuels, while that same amount of spending would create 7.49 or 7.72 FTE jobs in renewables or energy efficiency. Thus each $1 million shifted from brown to green energy will create a net increase of 5 jobs.

4. Conclusion

In this article I have presented a method to estimate employment multipliers for industries that are not explicitly identified in inputoutput tables, termed “synthetic industries.” Specifically, I have estimated employment multipliers for clean energy industries including wind, solar, bioenergy, geothermal, hydropower, building weatherization, mass transit & freight rail, industrial EE, and Smart Grid. These clean energy industries are not identified as such in national accounts or in input-output tables, yet the various materials and services of which these EERE industries are composed do already exist in the tables. By creating “synthetic industries” we enable policy evaluation of green versus brown industries, or more precisely, we are able to estimate the number of jobs created by public or private spending for clean energy in comparison to spending the same amount on oil, gas, or coal production. In order to estimate these employment multipliers, I used data on the cost structure of each clean energy industry to generate a vector of demand for the output of that industry. Using survey data, databases, and other sources of data collected by various agencies and organizations, I assigned weights to the various industries in the I-O tables that represent the component costs of the clean energy industries. I also recreated the vectors from Garrett-Peltier (2011) and Pollin et al. (2015) in order to provide a comparison with the new estimates provided in this article and to update these earlier findings with newer data.