Inflationary effect of coal price change on the Chinese economy

This study investigates the pass-through effect induced by coal price fluctuations on the Chinese economy 2007–2011 based on a non-competitive input–output model. Three scenarios with different domestic tariff regulation alternatives, i.e., Actual Regulation (AR), No Regulation (NR), and Strong Regu...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Chen, Zhan-Ming [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2013

Schlagwörter:	Chinese economy Energy price Inflation Input–output model

Übergeordnetes Werk:	Enthalten in: Applied energy - Amsterdam [u.a.] : Elsevier Science, 1975, 114, Seite 301-309
Übergeordnetes Werk:	volume:114 ; pages:301-309

DOI / URN:	10.1016/j.apenergy.2013.09.068

Katalog-ID:	ELV002512602

Internformat


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520			\|a This study investigates the pass-through effect induced by coal price fluctuations on the Chinese economy 2007–2011 based on a non-competitive input–output model. Three scenarios with different domestic tariff regulation alternatives, i.e., Actual Regulation (AR), No Regulation (NR), and Strong Regulation (SR), are simulated to reflect the effectiveness of different policies. At the sectoral scale, the Coking sector has the largest price variation under all scenarios while agriculture sectors and services sectors are the least sensitive. Nation-level impacts are examined by the weighted price changes of commodities used for different purposes. With the government regulation in reality, about 5% of the GDP deflator and CPI changes as well as 25% of the PPI change over the research period are attributed to coal price increase. Comparison shows the AR scenario brings more stable fluctuations but higher inflation than the NR scenario. The SR scenario confirms that authorities can remarkably relieve short-run inflation by controlling domestic electricity and heat tariffs. The induced inflationary expense sums up to between 0.03% and 0.97% of China’s GDP, around three quarters of which are burdened by investors and foreigners. The quantitative effect investigated in this study can serve as empirical evidence for policy makers regarding inflation control in China.
650		4	\|a Chinese economy
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allfields	10.1016/j.apenergy.2013.09.068 doi (DE-627)ELV002512602 (ELSEVIER)S0306-2619(13)00815-5 DE-627 ger DE-627 rda eng 620 DE-600 52.50 bkl Chen, Zhan-Ming verfasserin (orcid)0000-0001-5239-6332 aut Inflationary effect of coal price change on the Chinese economy 2013 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This study investigates the pass-through effect induced by coal price fluctuations on the Chinese economy 2007–2011 based on a non-competitive input–output model. Three scenarios with different domestic tariff regulation alternatives, i.e., Actual Regulation (AR), No Regulation (NR), and Strong Regulation (SR), are simulated to reflect the effectiveness of different policies. At the sectoral scale, the Coking sector has the largest price variation under all scenarios while agriculture sectors and services sectors are the least sensitive. Nation-level impacts are examined by the weighted price changes of commodities used for different purposes. With the government regulation in reality, about 5% of the GDP deflator and CPI changes as well as 25% of the PPI change over the research period are attributed to coal price increase. Comparison shows the AR scenario brings more stable fluctuations but higher inflation than the NR scenario. The SR scenario confirms that authorities can remarkably relieve short-run inflation by controlling domestic electricity and heat tariffs. The induced inflationary expense sums up to between 0.03% and 0.97% of China’s GDP, around three quarters of which are burdened by investors and foreigners. The quantitative effect investigated in this study can serve as empirical evidence for policy makers regarding inflation control in China. Chinese economy Energy price Inflation Input–output model Enthalten in Applied energy Amsterdam [u.a.] : Elsevier Science, 1975 114, Seite 301-309 Online-Ressource (DE-627)320406709 (DE-600)2000772-3 (DE-576)256140251 1872-9118 nnns volume:114 pages:301-309 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_34 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 52.50 Energietechnik: Allgemeines AR 114 301-309
spelling	10.1016/j.apenergy.2013.09.068 doi (DE-627)ELV002512602 (ELSEVIER)S0306-2619(13)00815-5 DE-627 ger DE-627 rda eng 620 DE-600 52.50 bkl Chen, Zhan-Ming verfasserin (orcid)0000-0001-5239-6332 aut Inflationary effect of coal price change on the Chinese economy 2013 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This study investigates the pass-through effect induced by coal price fluctuations on the Chinese economy 2007–2011 based on a non-competitive input–output model. Three scenarios with different domestic tariff regulation alternatives, i.e., Actual Regulation (AR), No Regulation (NR), and Strong Regulation (SR), are simulated to reflect the effectiveness of different policies. At the sectoral scale, the Coking sector has the largest price variation under all scenarios while agriculture sectors and services sectors are the least sensitive. Nation-level impacts are examined by the weighted price changes of commodities used for different purposes. With the government regulation in reality, about 5% of the GDP deflator and CPI changes as well as 25% of the PPI change over the research period are attributed to coal price increase. Comparison shows the AR scenario brings more stable fluctuations but higher inflation than the NR scenario. The SR scenario confirms that authorities can remarkably relieve short-run inflation by controlling domestic electricity and heat tariffs. The induced inflationary expense sums up to between 0.03% and 0.97% of China’s GDP, around three quarters of which are burdened by investors and foreigners. The quantitative effect investigated in this study can serve as empirical evidence for policy makers regarding inflation control in China. Chinese economy Energy price Inflation Input–output model Enthalten in Applied energy Amsterdam [u.a.] : Elsevier Science, 1975 114, Seite 301-309 Online-Ressource (DE-627)320406709 (DE-600)2000772-3 (DE-576)256140251 1872-9118 nnns volume:114 pages:301-309 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_34 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 52.50 Energietechnik: Allgemeines AR 114 301-309
allfields_unstemmed	10.1016/j.apenergy.2013.09.068 doi (DE-627)ELV002512602 (ELSEVIER)S0306-2619(13)00815-5 DE-627 ger DE-627 rda eng 620 DE-600 52.50 bkl Chen, Zhan-Ming verfasserin (orcid)0000-0001-5239-6332 aut Inflationary effect of coal price change on the Chinese economy 2013 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This study investigates the pass-through effect induced by coal price fluctuations on the Chinese economy 2007–2011 based on a non-competitive input–output model. Three scenarios with different domestic tariff regulation alternatives, i.e., Actual Regulation (AR), No Regulation (NR), and Strong Regulation (SR), are simulated to reflect the effectiveness of different policies. At the sectoral scale, the Coking sector has the largest price variation under all scenarios while agriculture sectors and services sectors are the least sensitive. Nation-level impacts are examined by the weighted price changes of commodities used for different purposes. With the government regulation in reality, about 5% of the GDP deflator and CPI changes as well as 25% of the PPI change over the research period are attributed to coal price increase. Comparison shows the AR scenario brings more stable fluctuations but higher inflation than the NR scenario. The SR scenario confirms that authorities can remarkably relieve short-run inflation by controlling domestic electricity and heat tariffs. The induced inflationary expense sums up to between 0.03% and 0.97% of China’s GDP, around three quarters of which are burdened by investors and foreigners. The quantitative effect investigated in this study can serve as empirical evidence for policy makers regarding inflation control in China. Chinese economy Energy price Inflation Input–output model Enthalten in Applied energy Amsterdam [u.a.] : Elsevier Science, 1975 114, Seite 301-309 Online-Ressource (DE-627)320406709 (DE-600)2000772-3 (DE-576)256140251 1872-9118 nnns volume:114 pages:301-309 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_34 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 52.50 Energietechnik: Allgemeines AR 114 301-309
allfieldsGer	10.1016/j.apenergy.2013.09.068 doi (DE-627)ELV002512602 (ELSEVIER)S0306-2619(13)00815-5 DE-627 ger DE-627 rda eng 620 DE-600 52.50 bkl Chen, Zhan-Ming verfasserin (orcid)0000-0001-5239-6332 aut Inflationary effect of coal price change on the Chinese economy 2013 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This study investigates the pass-through effect induced by coal price fluctuations on the Chinese economy 2007–2011 based on a non-competitive input–output model. Three scenarios with different domestic tariff regulation alternatives, i.e., Actual Regulation (AR), No Regulation (NR), and Strong Regulation (SR), are simulated to reflect the effectiveness of different policies. At the sectoral scale, the Coking sector has the largest price variation under all scenarios while agriculture sectors and services sectors are the least sensitive. Nation-level impacts are examined by the weighted price changes of commodities used for different purposes. With the government regulation in reality, about 5% of the GDP deflator and CPI changes as well as 25% of the PPI change over the research period are attributed to coal price increase. Comparison shows the AR scenario brings more stable fluctuations but higher inflation than the NR scenario. The SR scenario confirms that authorities can remarkably relieve short-run inflation by controlling domestic electricity and heat tariffs. The induced inflationary expense sums up to between 0.03% and 0.97% of China’s GDP, around three quarters of which are burdened by investors and foreigners. The quantitative effect investigated in this study can serve as empirical evidence for policy makers regarding inflation control in China. Chinese economy Energy price Inflation Input–output model Enthalten in Applied energy Amsterdam [u.a.] : Elsevier Science, 1975 114, Seite 301-309 Online-Ressource (DE-627)320406709 (DE-600)2000772-3 (DE-576)256140251 1872-9118 nnns volume:114 pages:301-309 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_34 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 52.50 Energietechnik: Allgemeines AR 114 301-309
allfieldsSound	10.1016/j.apenergy.2013.09.068 doi (DE-627)ELV002512602 (ELSEVIER)S0306-2619(13)00815-5 DE-627 ger DE-627 rda eng 620 DE-600 52.50 bkl Chen, Zhan-Ming verfasserin (orcid)0000-0001-5239-6332 aut Inflationary effect of coal price change on the Chinese economy 2013 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This study investigates the pass-through effect induced by coal price fluctuations on the Chinese economy 2007–2011 based on a non-competitive input–output model. Three scenarios with different domestic tariff regulation alternatives, i.e., Actual Regulation (AR), No Regulation (NR), and Strong Regulation (SR), are simulated to reflect the effectiveness of different policies. At the sectoral scale, the Coking sector has the largest price variation under all scenarios while agriculture sectors and services sectors are the least sensitive. Nation-level impacts are examined by the weighted price changes of commodities used for different purposes. With the government regulation in reality, about 5% of the GDP deflator and CPI changes as well as 25% of the PPI change over the research period are attributed to coal price increase. Comparison shows the AR scenario brings more stable fluctuations but higher inflation than the NR scenario. The SR scenario confirms that authorities can remarkably relieve short-run inflation by controlling domestic electricity and heat tariffs. The induced inflationary expense sums up to between 0.03% and 0.97% of China’s GDP, around three quarters of which are burdened by investors and foreigners. The quantitative effect investigated in this study can serve as empirical evidence for policy makers regarding inflation control in China. Chinese economy Energy price Inflation Input–output model Enthalten in Applied energy Amsterdam [u.a.] : Elsevier Science, 1975 114, Seite 301-309 Online-Ressource (DE-627)320406709 (DE-600)2000772-3 (DE-576)256140251 1872-9118 nnns volume:114 pages:301-309 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_34 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 52.50 Energietechnik: Allgemeines AR 114 301-309
language	English
source	Enthalten in Applied energy 114, Seite 301-309 volume:114 pages:301-309
sourceStr	Enthalten in Applied energy 114, Seite 301-309 volume:114 pages:301-309
format_phy_str_mv	Article
bklname	Energietechnik: Allgemeines
institution	findex.gbv.de
topic_facet	Chinese economy Energy price Inflation Input–output model
dewey-raw	620
isfreeaccess_bool	false
container_title	Applied energy
authorswithroles_txt_mv	Chen, Zhan-Ming @@aut@@
publishDateDaySort_date	2013-01-01T00:00:00Z
hierarchy_top_id	320406709
dewey-sort	3620
id	ELV002512602
language_de	englisch
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV002512602</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230524133212.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230429s2013 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.apenergy.2013.09.068</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV002512602</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0306-2619(13)00815-5</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">620</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">52.50</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Chen, Zhan-Ming</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0001-5239-6332</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Inflationary effect of coal price change on the Chinese economy</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2013</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This study investigates the pass-through effect induced by coal price fluctuations on the Chinese economy 2007–2011 based on a non-competitive input–output model. Three scenarios with different domestic tariff regulation alternatives, i.e., Actual Regulation (AR), No Regulation (NR), and Strong Regulation (SR), are simulated to reflect the effectiveness of different policies. At the sectoral scale, the Coking sector has the largest price variation under all scenarios while agriculture sectors and services sectors are the least sensitive. Nation-level impacts are examined by the weighted price changes of commodities used for different purposes. With the government regulation in reality, about 5% of the GDP deflator and CPI changes as well as 25% of the PPI change over the research period are attributed to coal price increase. Comparison shows the AR scenario brings more stable fluctuations but higher inflation than the NR scenario. The SR scenario confirms that authorities can remarkably relieve short-run inflation by controlling domestic electricity and heat tariffs. The induced inflationary expense sums up to between 0.03% and 0.97% of China’s GDP, around three quarters of which are burdened by investors and foreigners. 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author	Chen, Zhan-Ming
spellingShingle	Chen, Zhan-Ming ddc 620 bkl 52.50 misc Chinese economy misc Energy price misc Inflation misc Input–output model Inflationary effect of coal price change on the Chinese economy
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topic_title	620 DE-600 52.50 bkl Inflationary effect of coal price change on the Chinese economy Chinese economy Energy price Inflation Input–output model
topic	ddc 620 bkl 52.50 misc Chinese economy misc Energy price misc Inflation misc Input–output model
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title	Inflationary effect of coal price change on the Chinese economy
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title_full	Inflationary effect of coal price change on the Chinese economy
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title_sort	inflationary effect of coal price change on the chinese economy
title_auth	Inflationary effect of coal price change on the Chinese economy
abstract	This study investigates the pass-through effect induced by coal price fluctuations on the Chinese economy 2007–2011 based on a non-competitive input–output model. Three scenarios with different domestic tariff regulation alternatives, i.e., Actual Regulation (AR), No Regulation (NR), and Strong Regulation (SR), are simulated to reflect the effectiveness of different policies. At the sectoral scale, the Coking sector has the largest price variation under all scenarios while agriculture sectors and services sectors are the least sensitive. Nation-level impacts are examined by the weighted price changes of commodities used for different purposes. With the government regulation in reality, about 5% of the GDP deflator and CPI changes as well as 25% of the PPI change over the research period are attributed to coal price increase. Comparison shows the AR scenario brings more stable fluctuations but higher inflation than the NR scenario. The SR scenario confirms that authorities can remarkably relieve short-run inflation by controlling domestic electricity and heat tariffs. The induced inflationary expense sums up to between 0.03% and 0.97% of China’s GDP, around three quarters of which are burdened by investors and foreigners. The quantitative effect investigated in this study can serve as empirical evidence for policy makers regarding inflation control in China.
abstractGer	This study investigates the pass-through effect induced by coal price fluctuations on the Chinese economy 2007–2011 based on a non-competitive input–output model. Three scenarios with different domestic tariff regulation alternatives, i.e., Actual Regulation (AR), No Regulation (NR), and Strong Regulation (SR), are simulated to reflect the effectiveness of different policies. At the sectoral scale, the Coking sector has the largest price variation under all scenarios while agriculture sectors and services sectors are the least sensitive. Nation-level impacts are examined by the weighted price changes of commodities used for different purposes. With the government regulation in reality, about 5% of the GDP deflator and CPI changes as well as 25% of the PPI change over the research period are attributed to coal price increase. Comparison shows the AR scenario brings more stable fluctuations but higher inflation than the NR scenario. The SR scenario confirms that authorities can remarkably relieve short-run inflation by controlling domestic electricity and heat tariffs. The induced inflationary expense sums up to between 0.03% and 0.97% of China’s GDP, around three quarters of which are burdened by investors and foreigners. The quantitative effect investigated in this study can serve as empirical evidence for policy makers regarding inflation control in China.
abstract_unstemmed	This study investigates the pass-through effect induced by coal price fluctuations on the Chinese economy 2007–2011 based on a non-competitive input–output model. Three scenarios with different domestic tariff regulation alternatives, i.e., Actual Regulation (AR), No Regulation (NR), and Strong Regulation (SR), are simulated to reflect the effectiveness of different policies. At the sectoral scale, the Coking sector has the largest price variation under all scenarios while agriculture sectors and services sectors are the least sensitive. Nation-level impacts are examined by the weighted price changes of commodities used for different purposes. With the government regulation in reality, about 5% of the GDP deflator and CPI changes as well as 25% of the PPI change over the research period are attributed to coal price increase. Comparison shows the AR scenario brings more stable fluctuations but higher inflation than the NR scenario. The SR scenario confirms that authorities can remarkably relieve short-run inflation by controlling domestic electricity and heat tariffs. The induced inflationary expense sums up to between 0.03% and 0.97% of China’s GDP, around three quarters of which are burdened by investors and foreigners. The quantitative effect investigated in this study can serve as empirical evidence for policy makers regarding inflation control in China.
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title_short	Inflationary effect of coal price change on the Chinese economy
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Inflationary effect of coal price change on the Chinese economy

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