Subsidizing Fuel Efficient Cars
| Titel: | Subsidizing Fuel Efficient Cars : Evidence from China's Automobile Industry / Chia-Wen Chen, Wei-Min Hu, Christopher R. Knittel |
|---|---|
| Verfasser: | |
| Beteiligt: | ; |
| Veröffentlicht: | Cambridge, Mass. : National Bureau of Economic Research, 2017 |
| Umfang: | 1 Online Ressource |
| Format: | E-Book |
| Sprache: | Englisch |
| Mehrbändiges Werk: |
NBER working paper series ; no. w23045 |
X
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[Tp3] $915999151X 033A $pCambridge, Mass. $nNational Bureau of Economic Research 034D $a1 Online Ressource 036E $aNBER working paper series $lno. w23045 045E $c330 047I $aThe Chinese automobile market is the largest in the world with annual sales exceeding 20 million vehicles. The tremendous growth in sales---over 200 percent from 2008 to 2015---and concerns over local air quality have prompted China's policy makers to incentivize the adoption of more fuel efficient vehicles. We examine the response of vehicle purchase behavior to China's largest national subsidy program for fuel efficient vehicles during 2010 and 2011. Using variation from the program's eligibility cutoffs, we find that the program boosted sales for subsidized vehicle models, but that the program also created a substitution effect within highly fuel efficient vehicles and most subsidies went to inframarginal consumers. This substitution effect greatly reduces the cost effectiveness of the program. We calculate that the average cost per ton of carbon dioxide saved is over 82 USD, well above the social cost of carbon used in U.S. regulatory filings. Using the framework in Boomhower and Davis (2014) and accounting for local pollution benefits, we show that ignoring the substitution effect would lead one to conclude that the program is welfare enhancing, whereas in fact the marginal cost of the program exceeds the marginal benefit by almost as much as 300 percent. We also show that the program was not well-targeted; the effect of the subsidy on sales of fuel efficient vehicles was smaller in areas where consumers were more likely to purchase fuel inefficient models or were lower educated. lok: 43806533 3 101B $031-10-18 $t10:01:24.000 101C $031-10-18 101U $0utf8 145S/01 $a008 exp: 43806533 3 1 #EPN 201B/01 $026-01-26 $t16:27:46.000 201C/01 $029-10-18 201U/01 $0utf8 203@/01 $01031535780 204P/01 $010.3386/w23045 $S0 208@/01 $a29-10-18 $bl lok: 43806533 5 exp: 43806533 5 1 #EPN 201B/01 $002-01-20 $t22:24:46.455 201C/01 $002-01-20 201U/01 $0utf8 203@/01 $01073784274 204P/01 $010.3386/w23045 $S0 208@/01 $a02-01-20 $bl lok: 43806533 8 exp: 43806533 8 1 #EPN 201B/01 $002-01-20 $t22:24:46.433 201C/01 $029-10-18 201U/01 $0utf8 203@/01 $01031535799 204P/01 $010.3386/w23045 $S0 208@/01 $a29-10-18 $bl lok: 43806533 10 exp: 43806533 10 1 #EPN 201B/01 $002-01-20 $t22:24:46.459 201C/01 $002-01-20 201U/01 $0utf8 203@/01 $01073784282 204P/01 $010.3386/w23045 $S0 208@/01 $a02-01-20 $bl lok: 43806533 11 exp: 43806533 11 1 #EPN 201B/01 $002-01-20 $t22:24:46.462 201C/01 $002-01-20 201U/01 $0utf8 203@/01 $01073784290 204P/01 $010.3386/w23045 $S0 208@/01 $a02-01-20 $bl lok: 43806533 20 exp: 43806533 20 1 #EPN 201B/01 $002-01-20 $t22:24:46.466 201C/01 $002-01-20 201U/01 $0utf8 203@/01 $01073784304 204P/01 $010.3386/w23045 $S0 208@/01 $a02-01-20 $bl lok: 43806533 21 exp: 43806533 21 1 #EPN 201B/01 $002-01-20 $t22:24:46.469 201C/01 $002-01-20 201U/01 $0utf8 203@/01 $01073784312 204P/01 $010.3386/w23045 $S0 208@/01 $a02-01-20 $bl lok: 43806533 23 exp: 43806533 23 1 #EPN 201B/01 $002-01-20 $t22:24:46.438 201C/01 $029-10-18 201U/01 $0utf8 203@/01 $01031535802 204P/01 $010.3386/w23045 $S0 208@/01 $a29-10-18 $bl lok: 43806533 25 exp: 43806533 25 1 #EPN 201B/01 $002-01-20 $t22:24:46.444 201C/01 $029-10-18 201U/01 $0utf8 203@/01 $01031535810 204P/01 $010.3386/w23045 $S0 208@/01 $a29-10-18 $bl lok: 43806533 49 exp: 43806533 49 1 #EPN 201B/01 $002-01-20 $t22:24:46.472 201C/01 $002-01-20 201U/01 $0utf8 203@/01 $01073784320 204P/01 $010.3386/w23045 $S0 208@/01 $a02-01-20 $bl lok: 43806533 54 exp: 43806533 54 1 #EPN 201B/01 $002-01-20 $t22:24:46.476 201C/01 $002-01-20 201U/01 $0utf8 203@/01 $01073784339 204P/01 $010.3386/w23045 $S0 208@/01 $a02-01-20 $bl lok: 43806533 108 exp: 43806533 108 1 #EPN 201B/01 $002-01-20 $t22:24:46.483 201C/01 $002-01-20 201U/01 $0utf8 203@/01 $01073784355 204P/01 $010.3386/w23045 $S0 208@/01 $a02-01-20 $bl lok: 43806533 204 exp: 43806533 204 1 #EPN 201B/01 $002-01-20 $t22:24:46.447 201C/01 $029-10-18 201U/01 $0utf8 203@/01 $01031535829 204P/01 $010.3386/w23045 $S0 208@/01 $a29-10-18 $bl lok: 43806533 205 exp: 43806533 205 1 #EPN 201B/01 $002-01-20 $t22:24:46.451 201C/01 $029-10-18 201U/01 $0utf8 203@/01 $01031535837 204P/01 $010.3386/w23045 $S0 208@/01 $a29-10-18 $bl
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| 520 | |a The Chinese automobile market is the largest in the world with annual sales exceeding 20 million vehicles. The tremendous growth in sales---over 200 percent from 2008 to 2015---and concerns over local air quality have prompted China's policy makers to incentivize the adoption of more fuel efficient vehicles. We examine the response of vehicle purchase behavior to China's largest national subsidy program for fuel efficient vehicles during 2010 and 2011. Using variation from the program's eligibility cutoffs, we find that the program boosted sales for subsidized vehicle models, but that the program also created a substitution effect within highly fuel efficient vehicles and most subsidies went to inframarginal consumers. This substitution effect greatly reduces the cost effectiveness of the program. We calculate that the average cost per ton of carbon dioxide saved is over 82 USD, well above the social cost of carbon used in U.S. regulatory filings. Using the framework in Boomhower and Davis (2014) and accounting for local pollution benefits, we show that ignoring the substitution effect would lead one to conclude that the program is welfare enhancing, whereas in fact the marginal cost of the program exceeds the marginal benefit by almost as much as 300 percent. We also show that the program was not well-targeted; the effect of the subsidy on sales of fuel efficient vehicles was smaller in areas where consumers were more likely to purchase fuel inefficient models or were lower educated. | ||
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