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| 1 |
ID:
161809
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| Summary/Abstract |
In China energy-saving mandates issued by the central government can trigger a trade-off between faithful implementation and kinds of strategic responses at the local level. This paper examines the biased data revision pattern of Chinese provinces under incentives created by energy-saving mandates. The data revisions conducted by provinces in the treatment group are evaluated against those carried out by their counterparts in the control group. Empirical evidence is provided that some provinces in the treatment group conducted biased data revisions by taking advantage of benchmark revisions of historical data following the 2008 Economic Census. These provinces adjusted their base-year energy consumption figure upward in seeking to reach the 2010 energy intensity reduction targets numerically. In institutional terms, strong political incentives are formed by assigning energy-saving indicators a veto power in cadre performance assessment. In a self-reported statistical regime, checks and balances are particularly weak regarding benchmark revisions of historical data. The findings of this paper suggest that the data quality of associated official statistics at the local level is undermined by energy-saving mandates. To improve the data quality of the official statistics, new checks and balances should be installed for local statistics.
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| 2 |
ID:
132594
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| Publication |
2014.
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| Summary/Abstract |
Whereas the technical feasibility of solar water heaters (SWHs) has long been established, the economic feasibility of SWHs in regional China remains to be examined. This paper constructs cost models to calculate costs per unit energy saving of SWHs in 27 Chinese provincial capital cities. The cost effectiveness of SWHs is examined at the national level. At a micro level, we analyze the financial attractiveness of consumers' investment in SWHs. A panel data model is employed to evaluate the effectiveness of a subsidy program in rural China. The results show that SWH costs, ranging from 0.305 to 0.744 CNY/kW h, are much lower than those of other major renewable energies across China. This finding indicates that the diffusion of SWHs is a cost-effective way to reach China's renewable energy target. For consumers, incentive programs for SWHs are needed to improve the financial attractiveness of the devices in China. Existing subsidy policies for rural China have failed to significantly enhance the deployment of SWHs. The causes of the failure are examined and a new incentive program is suggested for rural areas of the country.
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| 3 |
ID:
134874
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| Summary/Abstract |
This paper examines sectoral contributions to discrepancies between China's national aggregate statistical values and the sum of provincial figures. In institutional terms, the paper then explores the sources of principally sectoral discrepancies. We find that the industrial sector has been the major contributor to discrepancies in both gross domestic product (GDP) and total energy consumption in recent years. Technical aspects such as statistical coverage, data collection method, and double-counting cannot explain the discrepancy. For the industrial sector, limited data accessibility undermines external checks and balances from the general public. As the primary bodies in collecting industrial data, the Provincial Bureaus of Statistics (PBSs) are not subject to effective internal checks and balances from other governmental divisions. To out-compete counterparts and get promoted, provincial leaders have explicit incentives to overstate provincial GDP, with industrial added value being the first statistic to be affected. This dynamic further extends to industrial energy consumption, which is over-reported as well
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| 4 |
ID:
187854
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| Summary/Abstract |
National energy consumption data are typically adjusted upward and provincial revision downward based on the Third Economic Census, thus substantially reducing energy statistical discrepancy between China and its provinces. Examining revision effects can facilitate better understanding whether and how the revision process eliminated the fundamental roots of the discrepancy. Through multiple index decomposition methods, this study traced the overall discrepancy to raw coal consumption by energy source, coal washing by transforming process and industrial consumption by economic sector. The reduction of the discrepancy was primarily based on improvements in the data consistency for raw coal, including the input by coal washing and industrial raw coal consumption. At provincial level, unexpected operations were detected during benchmark revisions, particularly inner-provincial inconsistency and inter-provincial incoordination. We conclude that the data discrepancy was institutionally rooted and cannot be solved by benchmark revision alone. Shifting the statistical system from a hierarchical regime to a more centralized one, which would allow greater coordination during energy data accounting and revisions, can help resolve this issue fundamentally.
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