Discussion Paper
China’s Vehicle Trade-In
Subsidy: Impact,
Cost-Effectiveness,
and Barriers to Electric
Vehicle Purchase
Rubal Dua
August 2025 Doi: 10.30573/KS--2025-DP39
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China’s Vehicle Trade-In Subsidy: Impact, Cost-Eectiveness, and Barriers to Electric Vehicle Purchase 3
Abstract
In 2024, China introduced a vehicle trade-in subsidy to stimulate
automotive demand and promote renewal of the national vehicle fleet.
This study presents the first evaluation of the subsidy’s effectiveness in
encouraging additional vehicle trade-ins, accelerating fleet turnover, and
shaping consumerpreferences between internal combustion engine
vehicles (ICEVs) and plug-in electric vehicles (PEVs). Using survey data from
programparticipants, we assess the subsidy’s additionality – the proportion
of trade-ins that would not have occurred in its absence – and analyze its
cost-effectiveness. Results indicate that approximately 44% of respondent
trade-ins were directly attributable to the subsidy, with a greater impact
observed among lower-income consumers. On average, the subsidy
advanced vehicle replacement by 1.2 years, with stronger effects in lower-
income groups. More than half of the surveyed recipients chose ICEVs,
underscoring persistent barriers to PEV adoption, including high upfront costs,
limited charging infrastructure, and range anxiety.
China’s Vehicle Trade-In Subsidy: Impact, Cost-Eectiveness, and Barriers to Electric Vehicle Purchase 4
Introduction
Governments around the world are promoting fuel-efficient vehicles, not
only to address energy, climate, and environmental challenges, but also to
strengthen their position in the global vehicle manufacturing sector (Su,Shen,
and Yuan 2025; Dua 2024; Tahir, El-Ferik, and Tayyab 2025; Dua, Almutairi,
and Bansal 2024). A range of policy tools is being employed, including
market-based measures such as taxes, subsidies, and feebates, as well
as regulatory approaches such as fuel economy and carbon emissions
standards, zero-emission vehicle (ZEV) mandates, and restrictions on the sale
of new internal combustion engine vehicles (Anilan and Vij 2024; Du, Zhao,
and Li 2023; Sheldon and Dua 2020b; Wu, Xie, and Lyu 2022; Das and Bhat
2022; Lin, Wu, and Xiong 2021; Yadav et al. 2024).
A growing body of research highlights the potential of
vehicle retirement programs (Dill 2004; Spitzley et al.
2005; Hsu and Sperling 1994; Sahil, Sarmah, and Nayak
2024; Mishra et al. 2024). In China, the trade-in program
has recently gained traction as a key instrument for
stimulating demand and supporting vehicle fleet renewal
(Zhang et al. 2024; Mi, O’Donovan, and Soulopoulos
2024; He et al. 2017; Wei 2024; Yuyin and Jian 2023).
In April 2024, China introduced a nationwide vehicle
trade-in subsidy, jointly administered by seven ministries.
The program offered fixed incentives to private vehicle
owners replacing older vehicles with newer, more fuel-
efficient ones – including battery electric vehicles (BEVs),
plug-in hybrids (PHEVs), and modern internal combustion
engine vehicles (ICEVs). Initially set at ¥10,000 ($1,380)
for plug-in electric vehicle (PEV) buyers and ¥7,000
($966) for ICEV buyers, the subsidy was later increased
to ¥20,000 ($2,760) and ¥15,000 ($2,070), respectively,
with retroactive applicability. To qualify, ICEVs had to be
registered before June 30, 2011, and PEVs before April 30,
2018 (Mi, O’Donovan, and Soulopoulos 2024).
Despite its scale and ambitious goals, a central question
persists: How many of these trade-ins were truly induced
by the subsidy, and to what extent did they accelerate
vehicle turnover rather than merely subsidize purchases
that would have occurred anyway?
This study examines the effectiveness of China’s 2024
vehicle trade-in policy in inducing additional vehicle
trade-ins, expediting fleet turnover, and shaping
consumer decisions. Using a survey of randomly selected
respondents who participated in the subsidy program, we
assess the extent to which the policy influenced consumer
behavior. Specifically, we measure (i) the proportion of
trade-ins that would not have occurred in the absence
of the subsidy (additionality), (ii) how much sooner
consumers replaced their vehicles due to the subsidy,
and (iii) how these effects vary across income groups.
Furthermore, given that many consumers who benefited
from the subsidy still opted for new ICEVs rather than
PEVs, we investigate the barriers that prevented them
from transitioning to electric mobility. While prior studies
have explored the role of financial incentives in promoting
electric vehicle adoption using stated- and revealed-
preference surveys as well as aggregate data (Tal and
Nicholas 2016; Hoogland et al. 2023; Sheldon, Dua, and
Alharbi 2023; Sheldon and Dua 2024), limited research
China’s Vehicle Trade-In Subsidy: Impact, Cost-Eectiveness, and Barriers to Electric Vehicle Purchase 5
has assessed the broader impacts of trade-in policies
(Chen, Hu, and Knittel 2021; Li, Linn, and Spiller 2013) –
and none, to the best of our knowledge, in the context of
China’s 2024 vehicle trade-in policy.
Understanding the real impact of the trade-in policy
is critical for optimizing future subsidy programs. If a
significant share of vehicle replacements would have
occurred even without the subsidy, the cost-effectiveness
of the policy could be called into question. Additionally,
if the program disproportionately benefits higher-income
consumers, adjustments may be needed to better align
with China’s long-term equity, energy, and environmental
objectives. By addressing these gaps, this research
provides insights into the trade-offs and policy design
considerations necessary for maximizing both economic
and environmental benefits.
China’s Vehicle Trade-In Subsidy: Impact, Cost-Eectiveness, and Barriers to Electric Vehicle Purchase 6
Regarding the vehicles being traded in, the vast majority
(96%) were ICEVs. The average fuel economy of the
traded-in vehicles was ~9 km per liter equivalent, whereas
the newly purchased vehicles had an average fuel
economy of ~25 km per liter equivalent. The median
annual vehicle kilometers traveled (VKT) for the traded-in
vehicles fell within the 10,000-15,000 km range. Notably,
about 94% of respondents expected their annual VKT
for the new vehicle to remain within the same range.
For context, Sheldon and Dua (2020a) reported that the
average annual VKT for new car buyers in China was
between 13,800 and 14,400 km. Additionally, the median
income of survey respondents was in the RMB 10,000-
20,000 range, which is comparable to the RMB 16,000
median income reported by Sheldon and Dua (2020a) for
new car buyers in China.
To assess how the subsidy influenced additional vehicle
trade-ins – that is, trade-ins that would not have occurred
without the subsidy – respondents were asked how
much longer they would have kept their old vehicle if
the subsidy had not been available. The extra years they
would have retained their older vehicle are shown in
Figure 1. On average, the trade-in subsidy accelerated
vehicle disposal by about 1.2 years across all respondents.
However, the impact varied by income level: for those in
the below-median income group, the subsidy led to an
earlier trade-in by roughly 1.9 years, whereas for those in
the above-median income group, the effect was around
0.5 years.
Table 1.Summary statistics for the respondent group.
Old car
traded-in
BEV 3%
PHEV 1%
ICEV 96%
Average fuel economy
(km per liter equivalent)
8.8
Median annual vehicle
kilometers travelled
10,000-15,000 km
New car
bought
BEV 28%
PHEV 20%
ICEV 52%
Average fuel economy
(km per liter equivalent)
24.9
Median expected annual
vehicle kilometers travelled
10,000-15,000 km
Median income RM 10,000-20,000
Data and Methods
Participants who had traded in their old vehicle – either an ICEV registered
before 2011 or a PEV registered before 2018 – to purchase a new ICEV or
PEV became eligible for a vehicle trade-in subsidy. As shown in Table 1,
28% of respondents were new BEV buyers, 20% were PHEV buyers, and
approximately 52% purchased a new ICEV among the 1,223 respondents.
These proportions are roughly aligned with the fuel-type distribution of new
car sales in China during the relevant period (Bloomberg Intelligence 2024).
China’s Vehicle Trade-In Subsidy: Impact, Cost-Eectiveness, and Barriers to Electric Vehicle Purchase 7
Figure 1.Acceleration in vehicle replacement due to the trade-in subsidy, measured in years.
Note: The figure shows the additional years older vehicles would have been retained without the subsidy, comparing below- and
above-median income groups.
Source: Author.
When asked about the type of vehicle they would have
eventually purchased, approximately 95% of respondents
indicated they would have chosen a new vehicle with
fuel economy similar to the one they actually acquired.
Based on this, we assume that in a counterfactual scenario
without the trade-in subsidy, respondents would have
held onto their older vehicle for the additional years they
reported before replacing it with a vehicle of comparable
fuel economy to the one they purchased in 2024.
Additionality
To assess the impact of the subsidy on vehicle trade-ins,
we use respondents’ answers about whether they would
have traded in their old vehicle and purchased a new
one in 2024. From this, we calculate Additionality, which
represents the proportion of trade-ins that were directly
driven by the subsidy. This metric is determined using the
following formula (Sheldon, Dua, and Alharbi 2023):
Additionality (%) 5 Trade_ins subsidy
2
Trade_ins No subsidy
Trade_ins subsidy
* 100%, (1)
where
Trade_ins subsidy: The total number of respondents who
traded in their vehicle under the subsidy scenario in 2024.
Trade_ins No subsidy: The number of respondents who would
have traded in their vehicle even without the subsidy in
2024.
This calculation helps isolate the effect of the subsidy
by identifying the share of trade-ins that would not have
occurred without financial incentives.
Cost-Effectiveness
We assess the cost-effectiveness of the vehicle trade-in
subsidy using two key metrics: the cost per additional
vehicle traded in and the cost per additional liter of
gasoline equivalent avoided. The first metric – cost per
additional trade-in – represents the expenditure required
to induce one extra vehicle trade-in. This is calculated
by dividing the total subsidy outlay by the number of
additional trade-ins, as shown in Equation 2 (Sheldon, Dua,
and Alharbi 2023).
China’s Vehicle Trade-In Subsidy: Impact, Cost-Eectiveness, and Barriers to Electric Vehicle Purchase 8
To refine this measure, we express both the numerator
and the denominator as proportions of total trade-ins
under the subsidy program. This transformation shows
that cost-effectiveness equals the average subsidy per
trade-in divided by the percentage increase in trade-ins
attributable to the subsidy. In practical terms, when the
per-vehicle subsidy remains fixed – as it does in this
case– the program’s cost-effectiveness is inversely
related to the percentage of additional trade-ins.
Cost per additional vehical traded 2 in 5
Trade_ins with subsidy * Sub
Trade_ins subsidy 2 Trade_ins No subsidy 5 100 * Sub
Additionality (%) (2)
where
Sub : Average vehicle trade-in subsidy
Trade_ins subsidy : The number of respondents who traded in
their vehicles under the subsidy in 2024
Trade_ins No subsidy : The number of respondents who
wouldhave traded in their vehicles even without the
subsidy in 2024
The spending per additional liter of gasoline equivalent
avoided represents the cost of conserving one extra
liter of fuel. It is calculated by dividing the total subsidy
expenditure by the total gasoline-equivalent fuel savings
(Sheldon, Dua, and Alharbi 2023). These savings are
determined by comparing fuel consumption under the
vehicle trade-in subsidy program to a counterfactual
scenario without the subsidy (Sheldon, Dua, and
Alharbi2023).
The formula for this calculation is:
Cost per additional liter of gasoline equivalent avoided
5 Trade_ins subsidy * Sub
FC No subsidy 2 FC subsidy (3)
FC No subsidy 2 FC subsidy 5 ^ VKT * ExtraYears
FE Old_vehicle
2
VKT * ExtraYears
FE New_vehicle
(4)
Respondents
where
Sub: Average vehicle trade-in subsidy
Trade_ins subsidy: Respondents who traded-in under the
subsidy scenario in year 2024
FC: Fuel consumption
VKT: Annual vehicle kilometers traveled1
ExtraYears: Extra years represent the additional years
a respondent would have kept their old vehicle if the
subsidy had not been available.
FE: Vehicle fuel economy
To clarify, Trade_ins subsidy represents all the respondents
in the survey across all new vehicle types – ICEV, BEV,
and PHEV, as they reported trading in their old vehicle
and purchasing a new one in 2024 under the subsidy
program. The average subsidy per trade-in (Sub) is
estimated by taking a weighted average of the official
subsidy amounts for each vehicle type (¥20,000 for
BEVs and PHEVs; ¥15,000 for ICEVs), weighted by their
observed shares in the sample. For subgroup analyses
– such as cost-effectiveness estimates by vehicle type
(BEV, PHEV, ICEV) – we use the respective fixed subsidy
amount for each category. That is, we assign ¥20,000 for
BEV and PHEV trade-ins and ¥15,000 for ICEV trade-ins.
This disaggregated approach enables a more precise
evaluation of cost-effectiveness by vehicle type.
This approach provides a clear way to assess the cost-
effectiveness of the subsidy program in reducing fuel
consumption.
China’s Vehicle Trade-In Subsidy: Impact, Cost-Eectiveness, and Barriers to Electric Vehicle Purchase 9
Results and
Discussion
Figure 2 illustrates four key aspects of the subsidy: (i) the subsidy amount,
(ii) the additional vehicle trade-ins resulting from the subsidy, (iii) the subsidy’s
cost-effectiveness, and (iv) the cost per additional liter of gasoline equivalent
avoided due to the subsidy. These metrics are presented for below-median
and above-median income groups,2 as well as for all survey respondents,
disaggregated by the fuel type of vehicles purchased under the subsidy
program.
Overall, considering all survey respondents and all three
fuel types, the estimated additionality is around 44%.
In other words, 44% of respondents who utilized the
subsidy would not have traded in their old vehicle and
purchased a new one if the trade-in subsidy policy had
not been available. This effect is particularly pronounced
for BEVs and PHEVs, where the additionality rate is 59%–
roughly double that of ICEVs. For context, a 2018 J.D.
Power survey found that, had the NEV subsidies not been
available, 41% of consumers in 2018 indicated they would
not have chosen a PEV. As another point of comparison,
Li, Linn, and Spiller (2013) estimated that about 55%
of vehicle purchases under the 2009 U.S. “Cash-for-
Clunkers” program were truly additional – that is, they
would not have occurred without the program.
On average, the subsidy per vehicle across all fuel types is
around $2,400. Given that 44% of these trade-ins are truly
additional (i.e., they would not have happened without the
subsidy), the cost per extra vehicle traded in is roughly
$5,400. For BEVs and PHEVs, the cost per additional
vehicle is about $4,600, whereas for ICEVs, it is higher at
around $6,800. For comparison, Sheldon and Dua (2020a)
estimated that in 2017, the subsidy cost per additional PEV
sold in China was about $24,500. This higher cost was
partly due to the larger average subsidy per PEV at the
time, which was around $8,500.
When examining the subsidy cost per additional liter of
gasoline equivalent avoided, the figure averages around
~$2 per liter across all fuel types and income groups. For
context, Sheldon and Dua (2020a) estimated that the PEV
subsidy cost per additional liter of gasoline equivalent
avoided in China in 2017 was $1.9. Among respondents
who purchased a PEV, the subsidy cost is approximately
~$1.5 per additional liter, whereas for those who bought an
ICEV, it is significantly higher – around $3 per additional
liter. This disparity arises because new PHEVs and BEVs
are generally more fuel-efficient than new ICEVs in terms
of kilometers per liter equivalent, resulting in a lower
subsidy cost per additional liter of gasoline equivalent
avoided.
Regarding income groups, the results align with
expectations. Consumers in the below-median income
group tend to be more responsive to subsidies, as
reflected in their higher additionality. This responsiveness
translates into a lower subsidy cost per additional PEV
sold and a lower cost per additional liter of gasoline
avoided. These findings are consistent with previous
studies suggesting that the cost-effectiveness of PEV
subsidies can be enhanced by incorporating income-
based caps into their design (Sheldon and Dua 2019; Xing,
Leard, and Li 2019).
China’s Vehicle Trade-In Subsidy: Impact, Cost-Eectiveness, and Barriers to Electric Vehicle Purchase 10
Figure 2.Impact of China’s 2024 vehicle trade-in subsidy on additional vehicle trade-ins and its cost-effectiveness.
Note: Displayed are the subsidy amounts (light blue columns), additional trade-ins induced (% data labels), and the subsidy cost
per additional vehicle traded-in (dark blue columns) and liter of additional gasoline equivalent avoided (purple line with markers),
differentiated by income groups and vehicle types.
Source: Author.
When respondents who purchased an ICEV were asked
to identify and rank the five most significant barriers
preventing them from buying a PEV, the results –
presented in Figure 3 – highlighted several key concerns.
The findings are reported for the full sample, as well as
separately for below- and above-median income groups.
Among cost-related barriers, the higher upfront price of
PEVs, concerns about battery replacement costs, and
uncertainty about resale value were consistently ranked
among the top 10 barriers. Charging-related challenges–
including the lack of public charging infrastructure,
long recharging times, and limited access to home or
workplace charging – also remained prominent. Notably,
these barriers persisted even as PEVs accounted for
approximately 50% of new car sales in the second half
of 2024. Beyond cost and charging, range anxiety was
consistently among the top three concerns cited by ICEV
buyers. Other frequently mentioned issues included
the limited availability of PEV models, concerns about
reliability, and the perception that the EV market is still not
mature.
Most of these concerns were shared across income
groups. T-test results show no statistically significant
differences in the majority of responses. However,
above-median income respondents placed greater
emphasis on having more PEV model options and better
features, such as longer range and faster charging. In
contrast, below-median income respondents were more
likely to cite a lack of awareness about available purchase
incentives and the perception that PEVs are less suitable
for non-urban users.3
China’s Vehicle Trade-In Subsidy: Impact, Cost-Eectiveness, and Barriers to Electric Vehicle Purchase 11
Figure 3.Barriers preventing PEV purchase, as identified by survey respondents who traded in their old car for a
newICEV.
Note: The p-values from t- test 4 are presented to assess the statistical significance of each barrier’s impact across the two income
groups. Significance levels are denoted as follows: [0, 0.001): ***, [0.001–0.05): **, [0.05–0.1): *
Source: Author.
China’s Vehicle Trade-In Subsidy: Impact, Cost-Eectiveness, and Barriers to Electric Vehicle Purchase 12
Conclusion
This study assessed the impact of China’s 2024 vehicle trade-in subsidy
on inducing additional trade-ins, accelerating fleet turnover, and influencing
consumer vehicle choices. The findings indicate that approximately
44% of vehicle trade-ins would not have occurred in the absence of the
subsidy, reflecting a moderate level of additionality. Notably, the subsidy
had a stronger impact on lower-income consumers, accelerating vehicle
replacement by an average of 1.9 years, compared to 0.5 years for higher-
income groups. Despite these incentives, a substantial share of consumers
still chose ICEVs over PEVs, highlighting persistent barriers to electric
vehicle adoption. These include high upfront costs, insufficient charging
infrastructure, and range anxiety. Overall, the results suggest that while
trade-in subsidies can effectively stimulate fleet renewal and improve vehicle
efficiency, their capacity to advance transport electrification remains limited
without complementary policy measures.
This study has several limitations worth noting. First, the
reliance on self-reported survey data introduces the
potential for response bias, particularly when assessing
counterfactual purchasing behaviors. Although stated
preference surveys are widely used, actual consumer
decisions may diverge from reported intentions. Second,
the analysis does not account for broader macroeconomic
factors that may have influenced vehicle purchasing
decisions independently of the subsidy. Third, variations
in regional policy implementation and local incentives
were not explicitly controlled for, which may limit the
generalizability of the findings. Fourth, the study does
not capture long-term behavioral shifts that may occur
beyond the immediate subsidy period, such as repeat
PEV purchases or changes in vehicle usage patterns.
Finally, detailed data on the purchase prices of new
vehicles acquired under the subsidy program were not
collected. While the income-based subgroup analysis
partially reflects differences in consumers’ purchasing
capacity, incorporating price variation could provide
greater granularity in understanding how long consumers
would have otherwise retained their older vehicles.
Future research could expand on this by examining the
interaction between new vehicle purchase price and
trade-in timing.
Future research should also employ natural experiments
or econometric modeling techniques to better isolate the
causal impact of trade-in subsidies from other external
economic influences. Lastly, cross-national comparisons
could provide valuable insight into how trade-in incentives
function across diverse policy and market contexts.
This study contributes to the literature on vehicle trade-in
policies by providing the first evaluation of China’s 2024
vehicle trade-in subsidy program. By quantifying the
policy’s additionality and identifying continued barriers
to PEV adoption – even as PEVs approached a 50%
market share – the findings offer actionable insights
for policymakers. They underscore the importance
of designing subsidies that maximize both economic
efficiency and environmental benefit, particularly by
aligning with broader decarbonization and equity
objectives. Finally, the results highlight the need for
integrated policy frameworks that address both financial
and infrastructural barriers to PEV uptake. As China
continues refining its electrification strategy, these findings
can inform more effective and equitable policy design
in support of a cleaner, more sustainable transportation
future.
China’s Vehicle Trade-In Subsidy: Impact, Cost-Eectiveness, and Barriers to Electric Vehicle Purchase 13
Endnotes
1 While factors such as fuel type and charging convenience may influence VKT, about 94% of surveyed respondents expected their
annual VKT with the new vehicle to remain within the same range. Thus, Eq. (3) assumes constant VKT across vehicle replacement.
2 Following similar practice in other policy evaluation studies, such as Sheldon and Dua (2020); Sheldon, Dua, and Alharbi (2023),
weuse a median split of respondent-reported income to define below- and above-median groups. This approach provides a
balanced division of the sample and preserves statistical power for subgroup analysis. While alternative methods could oer
additional nuance, given our sample size and our goal of illustrating the improved cost-eectiveness of income-targeted subsidy
designs, we adopt the median income split in this study.
3 Below-median income respondents may live in or frequently travel to rural or remote areas and therefore perceive EVs as less
suitable for such contexts relative to ICEVs. They also tend to be less concerned about range anxiety than their above-median
income counterparts. In contrast, abovemedian income respondents are more likely to reside in urban areas or have access to
multiple vehicles, which mitigates concerns about using EVs for travel to remote areas. At the same time, they likely have higher
overall expectations for vehicle performance, making driving range a more salient concern – both in comparison to ICEVs and
relative to below-median income respondents.
4 To evaluate whether the responses from the two sub-samples are statistically dierent, we use p-values from a two-sided t-test.
China’s Vehicle Trade-In Subsidy: Impact, Cost-Eectiveness, and Barriers to Electric Vehicle Purchase 14
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China’s Vehicle Trade-In Subsidy: Impact, Cost-Eectiveness, and Barriers to Electric Vehicle Purchase 16
About the Author
Rubal Dua
Rubal Dua, a Principal Fellow at KAPSARC, is actively engaged in exploring emerging
challenges and priorities in sectors that critically influence transportation and infrastructure,
viewed through the lens of energy economics, policy, and sustainability. Rubal holds a Ph.D.
from KAUST, Saudi Arabia, an M.Sc. from the University of Pennsylvania, U.S., and a B.Tech.
from the Indian Institute of Technology (IIT) Roorkee.
China’s Vehicle Trade-In Subsidy: Impact, Cost-Eectiveness, and Barriers to Electric Vehicle Purchase 17
About the Project
Theproject seeks to explore current challenges, opportunities, and priorities
in the transport sector. It focuses on identifying emerging trends and
translating them into research questions and insights that can inform policy.
