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Subsidies are a widely criticized policy instrument in fisheries management. The critique argues that by artificially increasing fishing profits, subsidies promote global fishing capacity growth and overharvesting. Scientists worldwide have thus called for a ban on subsidies, resulting in the recent agreement among members of the World Trade Organization to eliminate harmful subsidies. But is the solution so simple? The argument for banning harmful subsidies relies on the assumption that fishing can be made unprofitable by eliminating subsidies, incentivizing some fishermen to exit and others to refrain from entering. These mechanisms are logical under open-access fishing where entry has driven profits to zero. Yet many modern-day fisheries are conducted under limited-access regimes that limit capacity and maintain economic profits, even without subsidies. In these settings, subsidy removal might simply reduce profits, without any effect on capacity. Importantly, until now, there have been no empirical studies of subsidy reductions to inform us about their likely quantitative impacts. In this paper, we evaluate a policy reform that reduced fisheries subsidies in China. We find that China's subsidy reductions accelerated the rate at which fishermen scrapped their vessels , resulting in reduced fleet capacity, particularly among older and smaller vessels. 1 Notably, the reduction of harmful subsidies was only partly responsible for reducing fleet capacity; an increase in vessel retirement subsidies was also a necessary driver of capacity reduction. Our study demonstrates that the efficacy of subsidy reductions depends upon the policy environment in which removals occur.
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Fisheries Subsidies Reform in China
Kaiwen Wang1
, Matthew N. Reimer1
, James E. Wilen1
1Department of Agricultural & Resource Economics, University of California, Davis
December 18, 2022
Abstract
Subsidies are a widely criticized policy instrument in fisheries management. The cri-
tique argues that by artificially increasing fishing profits, subsidies promote global
fishing capacity growth and overharvesting. Scientists worldwide have thus called for a
ban on subsidies, resulting in the recent agreement among members of the World Trade
Organization to eliminate harmful subsidies. But is the solution so simple? The argu-
ment for banning harmful subsidies relies on the assumption that fishing can be made
unprofitable by eliminating subsidies, incentivizing some fishermen to exit and others
to refrain from entering. These mechanisms are logical under open-access fishing where
entry has driven profits to zero. Yet many modern-day fisheries are conducted under
limited-access regimes that limit capacity and maintain economic profits, even without
subsidies. In these settings, subsidy removal might simply reduce profits, without any
effect on capacity. Importantly, until now, there have been no empirical studies of
subsidy reductions to inform us about their likely quantitative impacts. In this paper,
we evaluate a policy reform that reduced fisheries subsidies in China. We find that
China’s subsidy reductions accelerated the rate at which fishermen scrapped their ves-
sels, resulting in reduced fleet capacity, particularly among older and smaller vessels.
Corresponding Author. Ph.D. candidate. Email: kvnwang@ucdavis.edu
Associate Professor. Email: mnreimer@ucdavis.edu
Professor Emeritus. Email: wilen@primal.ucdavis.edu
1
Notably, the reduction of harmful subsidies was only partly responsible for reducing
fleet capacity; an increase in vessel retirement subsidies was also a necessary driver
of capacity reduction. Our study demonstrates that the efficacy of subsidy reductions
depends upon the policy environment in which removals occur.
Keywords: Fisheries subsidies; China; buyback program; sustainable fisheries.
Introduction
Fisheries worldwide have experienced a vast transformation in governance in the decades
since the U.N. Convention on the Law of the Sea (LOS) negotiations were adopted in 1982.
Many coastal nations have implemented management institutions and practices that have
been instrumental in reversing overfishing and creating economic wealth (Grafton et al.,
2006; Worm et al., 2009; Costello and Ovando, 2019). Indeed, most fisheries with strong
management institutions and science-based stock assessments are currently rebuilding or
harvested at sustainable levels (Melnychuk et al., 2017; Hilborn et al., 2020).
Despite these successes, several perceived threats to fisheries sustainability remain. Fore-
most among these threats is the widespread use of capacity-enhancing, or so-called “harm-
ful”, subsidies that artificially increase the profitability of fishing, putting undue pressure on
fish stocks (Sumaila et al., 2008). By one estimate, approximately US$22 billion in harmful
subsidies were distributed to fishers worldwide in 2018 (Sumaila et al., 2019), represent-
ing nearly 15% of global fisheries revenue (FAO, 2020). Empirical and theoretical evidence
demonstrates that such subsidies lead to overcapacity, are inefficient, and, in the absence of
sound biological controls, can result in overfishing (Clark et al., 2005; Sakai, 2017; Smith,
2019; Sakai et al., 2019). To make matters worse, harmful subsidies are also overly rep-
resented in fisheries with weaker management institutions that lack complete control over
fishing pressure, thereby heightening the threat of overfished stocks (Costello et al., 2021).
In response, scientists worldwide have called for a complete ban on all harmful fisheries sub-
sidies (Sumaila et al., 2021), a plea that culminated in such a ban being adopted recently
amongst members of the World Trade Organization (Cisneros-Montemayor et al., 2022).
At the heart of this policy recommendation is the expectation that reducing harmful
subsidies can be an effective tool for controlling fleet capacity. This belief relies on the as-
sumption that removing subsidies will make marginal units of fishing capital unprofitable,
thereby reducing fleet capacity as marginal units of capital are incentivized to leave the fish-
ery. This argument is theoretically consistent with mechanisms we would expect to operate
in open-access fisheries (Munro and Sumaila, 2002), an apt description of the institutional
conditions that led to fisheries becoming overcapitalized in the decades leading up to the
1982 LOS agreement (Finley, 2017). However, many modern-day fisheries are no longer open
access, as nation-states have since instituted additional controls, such as limits on entry or
fishing effort, to curb overfishing concerns (Reimer and Wilen, 2013). It is well known that
such limits have the potential to generate positive marginal economic profits, even if they
are not set at their optimal levels (Anderson, 1985; Campbell and Lindner, 1990; Deacon
et al., 2011). In these arguably common cases, marginal units of fishing capital may still earn
positive economic profits after the removal of subsidies, leaving fleet capacity unchanged. In
practice, there have been few instances of actual subsidy reductions since the LOS agreement
that can provide guidance on the potential effectiveness of a subsidy ban.
In this paper, we examine a recent fisheries policy reform in China that actually reduced
harmful subsidies. This case study is important for its novelty, the complexity of the policy
context, the quality of the data, and the importance of China as a fishing nation-state.
China is the world’s largest seafood producer. Its rise to dominance began soon after the LOS
negotiations concluded, as price controls on aquatic products were lifted and the Communist
Party of China (CPC) promoted the full development of domestic and distant water fleets.
Under new incentives to invest, the Chinese coastal marine fleet grew precipitously to 250,000
vessels and domestic marine catch grew at almost 12% per year. By 1992, China had become
the world’s most productive fishing nation, reaching over 13 MMT (18% of global catch) by
1998 (Cao et al., 2017). But as the decade of the 1990s came to a close, broad signs of
overexploitation began to emerge, prompting an abrupt about-face in fisheries management
objectives (Cao et al., 2017; Su et al., 2020). In 2000, the CPC announced a “negative
growth” strategy, essentially signaling an end to the decade of rapid growth and development.
Today, China remains the world’s largest fish-producing nation (FAO, 2020), prosecuted by
the world’s largest domestic marine capture fleet (Rousseau et al., 2019).
China is also the largest user of harmful fishing subsidies (Hopewell and Margulis, 2022).
The subsidies we investigate were conceived in 2006 to cushion the impact of rising diesel
prices as China deregulated domestic fuel prices to conform to higher global prices. The
complex system of fuel rebates began paying out subsidies that depended on a vessel’s engine
power, the type of gear used, and the global price of fuel each year. As diesel prices rose
throughout the 2006-2015 period, these fuel subsidies became important to fishing profits
4
(Zhong et al., 2012). During 2006-2014, the central government paid 148 billion RMB (23
billion USD) for fuel subsidies (MOF, 2015), amounting to one-fifth of the total value added
by the marine capture industry (MOAFAB, 2012, 2016).
By 2014, Chinese fisheries managers found themselves juggling multiple objectives in the
face of a large domestic fleet, declines in abundance of major target species, and fluctuating
fuel and fish prices. As the CPC promoted the “Ecological Civilization” objective for the
2016-2020 Five-Year Plan, Chinese fisheries policymakers were compelled to confront the fact
that subsidizing fuel conflicted with other new ecological goals, particularly those focused on
reducing the fleet size and harmful gear use in the East China Sea fleet. As a result, in 2016,
China implemented a wide-ranging fuel subsidy reform as part of its 13th Five-year Plan (Cao
et al., 2017). The reform reduced subsidies broadly, committed to a gradual reduction over
the upcoming five-year period, and targeted specific harmful gear by enhancing incentives to
exit. We take advantage of this policy reform and utilize the break from pre-reform subsidy
levels as a quasi-experiment to examine the quantitative impact of subsidy reductions.
We investigate the impact of China’s fisheries fuel subsidy reform on fleet capacity using
a unique administrative dataset of trawl vessels in China’s Zhejiang Province, the largest
fishing fleet in the East China Sea. Our policy setting offers several advantages for under-
standing the potential impacts of harmful subsidy reductions. First, fuel subsidy reductions
were allocated across vessels in a relatively ad hoc manner, allowing us to identify the re-
form’s effect on fleet capacity using standard quasi-experimental designs. Second, China’s
fuel subsidy reform took place within an institutional setting that embodies the complexity
of the policy environments in which many future subsidy reforms are likely to take place.
In particular, fuel subsidies were just one policy instrument among many others, including
a cap-and-trade program for engine power, a buyback program to encourage exit and fleet
capacity reduction, gear regulations, and open-season restrictions. As we show, these other
elements conditioned the effect of fuel subsidy reductions in complex but understandable
ways that provide insights into how banning subsidies might work globally.
5
Fisheries Management and Subsidy Reform in China
In the early 1980s, the Ministry of Agriculture (MOA) instituted a vessel licensing system
requiring vessels to be registered, inspected, and licensed to fish each year. The licensing
system tracks vessel power, measured by kilowatts (kW) of engine power, as well as gear
fished and vessel attributes. This facilitated management by a “dual control” system whereby
the MOA could set local county/provincial targets for vessel numbers and aggregate fleet
engine power in order to bring fleet capacity and biological productivity into balance. The
licensing system essentially created a cap-and-trade program in engine power whereby new
vessels could only be constructed by acquiring power quota from fishers exiting the fleet and
scrapping their vessels (MOA, 2018).
In the early 2000s, local leaders were directed to reduce vessel numbers and fleet power,
reduce catch targets, and implement input controls such as a summer moratorium on fishing
(Su et al., 2020). Fleet reduction was facilitated with a vessel buyback system introduced
in 2002, which served as a vessel retirement subsidy program by providing compensation to
fishers willing to exit and surrender their engine power quota, in addition to retraining funds
designed to help transition to other non-fishing occupations.
The Fuel Subsidy Program: 2006-2015
As oil prices surged in the early 2000s, the CPC concluded China could no longer afford to
insulate its economy from international markets to stimulate development with low-priced
fossil fuel energy. In 2006, the CPC lifted domestic fuel price controls in order to expose the
Chinese economy to global fuel prices. Officials were aware that shocks in fuel prices could
cause political instability and hence initiated a fuel subsidy plan to ease the transition in
the agriculture, public transportation, and fishing sectors (MOF, 2015).
In the fishing sector, managers conducted surveys to determine vessel fuel consumption
by gear type, engine power, and annual average operation time. These were used to compute
average fuel consumption “subsidy coefficients”, measured in metric tons (MT) of fuel per
kW of engine power, for each type of fishing gear. The MOA then formalized a national
standard for fuel subsidies in 2009 (MOF and MOA, 2009), where annual subsidy payments
6
for each legally licensed vessel were computed as
Subsidy = fuel price standard (RMB/MT)
×engine power (kW) ×subsidy coefficient (MT/kW),
where the fuel price standard was adjusted annually to reflect global diesel prices. In the face
of declining biomass and abundance, declining market value of catch, and tighter restrictions
on the fishing season, these fuel subsidies soon became an important component of fishing
revenues, particularly for less efficient vessels (Shen and Chen, 2022).
The fuel subsidy program achieved its primary intended goal, which was to ease the tran-
sition to global fuel prices and minimize political fallout from price shocks. Nevertheless,
subsidizing fuel costs conflicted with other management goals, particularly those associated
with reducing fleet capacity to bring catch into balance with biological productivity (Zhong
et al., 2012). The mechanisms by which fleet reduction goals were compromised were subtle
and intricate. For instance, the licensing system capped aggregate fleet engine power and re-
quired power-for-power quota transfers for new vessel construction. Prior to the introduction
of fuel subsidies, the market price of engine power quota transfers was below the buyback
price of engine power, and hence exiting fishermen chose to surrender their quota through
the buyback program rather than sell to a new entrant. But as fuel subsidies were intro-
duced, engine power quota prices rose to reflect the capitalized value of anticipated future
payments (Wang and Pan, 2016). For example, in 2006, reported quota prices for trawlers
were around 600 RMB/kW. But by 2014, they had increased to 8,000-10,000 RMB/kW, re-
flecting the present value of the flow of future subsidy payments for the average trawler (SI
Appendix Table 2 ). The value of subsidies thus became embedded in quota transfer prices,
causing transfer prices to exceed the buyback price. This in turn choked off incentives for
exiting fishermen to surrender their quota to the buyback program. Indeed, during the four
years leading up to the fuel subsidy reform, no vessels in our sample surrendered their engine
power quota to the buyback program (Table 1).
7
The Fuel Subsidy Program: 2016-2020
In 2016, the MOA implemented a nationwide reform to its fuel subsidy program, in part
due to the CPC’s embrace of marine ecosystem protection in its new agenda for “Ecological
Civilization” (Su et al., 2020), as well as intense international pressure to reform its fisheries
subsidies out of overfishing concerns (Yang et al., 2017; Hopewell and Margulis, 2022). Re-
forms to the fuel subsidy program were designed to address several issues that compromised
capacity reduction and resource conservation objectives, including (i) fuel subsidies propped
up revenues of marginal fishermen, incentivizing them to remain in the fleet; (ii) fuel subsi-
dies became capitalized into power quota prices, inhibiting the effectiveness of the buyback
program; and (iii) fuel subsidies kept ecologically harmful gear types (e.g., trawlers) in the
fishery, impeding rebuilding plans (MOF and MOA, 2015).
In contrast to its original design, the reformed fuel subsidy program decoupled subsidy
payments from fuel consumption. Rather than basing subsidy coefficients on estimated an-
nual fuel consumption, the coefficients were revised to reflect fishery managers’ judgments
about the ecological harm done by each gear type, so that fishing operations regarded as
ecologically harmful were assigned lower subsidy coefficients. In addition, subsidies were
no longer determined by a vessel’s registered engine power; instead, vessels were assigned to
vessel classifications based on their fishing gear and length, and the average engine power of a
vessel class was used as the basis for fuel subsidy payments. Finally, rather than adjusting the
fuel subsidy standard to reflect prevailing diesel prices, it was set to the 2014 fuel price stan-
dard and then further reduced by 18% annually so that subsidy payments would be decreased
by 60% by the end of the Five-year Plan (Zhejiang Province Ocean and Fisheries Bureau,
2016a).
In addition to revising fuel subsidy payments, the MOA made two other complementary
reforms to promote its capacity reduction and resource conservation objectives. First, the
MOA announced that new construction of vessels using ecologically harmful gears, such as
double-otter trawlers, would be prohibited in 2017 (the ban was expanded to general trawl
vessels in 2019) MOA (2017, 2018). Second, the MOA enhanced the buyback program by
raising buyback prices from 2,500 to 5,000 RMB/kW, made possible by diverting the savings
8
from reforming fuel subsidies into the buyback program. Further, the province of Zhejiang
added 2,500 RMB/KW to the buyback price to meet its own target of reducing its fleet size
by 2,580 fishing vessels by 2020 (Zhejiang Province Ocean and Fisheries Bureau, 2016b).
The reformed fuel subsidy program had immediate implications for fishermen, particu-
larly those experiencing sharp reductions in subsidy coefficients associated with vessel oper-
ations classified as being harmful (e.g., trawlers). Indeed, fuel subsidy payments decreased
dramatically in the first year of the reform, and continued to decrease thereafter as the fuel
subsidy standard was adjusted downward annually (Figure 1). In turn, the reduction of
expected future fuel subsidy payments brought about decreases in quota prices for engine
power (SI Appendix, Table S2 ). Together with the revised buyback prices, surrendering
engine power quota through the buyback program began to look more attractive to fishers
(China National Radio, 2016).
The reformed fuel subsidy program also has important implications for our evaluation of
its impact. As discussed, reformed fuel subsidy payments were based on vessel classes deter-
mined by vessel-length thresholds. For example, vessels just below the 30-meter threshold
received fuel subsidy payments that were approximately 25% lower than vessels just above the
30-meter threshold in the post-reform years, despite receiving nearly the same fuel subsidy
payments in the pre-reform years (Figure 2). Such sharp local discontinuities yield quasi-
experimental variation in the assignment of fuel subsidy reductions across vessels, which we
use to identify changes in vessel exiting decisions that are solely attributable to the reform
itself.
Results
To evaluate the impact of China’s fuel subsidy reform, we assemble a vessel-level longitudinal
database of nearly all large trawlers (24 meters) registered in 2011 (7,685 vessels) in
China’s Zhejiang Province, the largest fishing fleet in the East China Sea (Zhang et al.,
2016). The database includes information on a vessel’s age, length, tonnage, and engine
power. Most importantly, we are able to determine whether a vessel exits the fishery in
any year, either retired through the buyback program or acquired through the engine power
9
quota market. We supplement these vessel registry databases with county-level data on fuel
subsidy payment records.
A before-and-after comparison of vessel activity suggests that vessel exit and construction
decisions were substantively affected by the reformed fuel subsidy program (Table 1). In the
four years following the reform, the number of large trawling vessels in the Zhejiang Province
decreased by 22%, compared to 2% in the four years before the reform. The decrease in the
number of vessels was due to both an increase in the number of vessels exiting the fishery—
the annual exit rate increased from 3.9% in the pre-reform years to 7.1% in the post-reform
years—and a decrease in the number of new vessels being constructed. Most notably, 54%
of the vessels that exited the fishery in the post-reform years surrendered their engine power
quota through the buyback program, a considerable increase over 0% in the four years
preceding the fuel subsidy reform.
To evaluate changes in vessel exiting decisions attributable to the reform alone, we
estimate the relationship between fuel subsidy reductions and the hazard rate of exiting
the fishery using two quasi-experimental approaches. First, we use a continuous-treatment
difference-in-differences (DD) design that is based on the reform’s differential treatment of
fuel subsidy reductions across all vessels. Second, we use a regression discontinuity difference-
in-differences (RD-DD) design that focuses on a discontinuity in the exposure to fuel subsidy
reductions created by the assignment of vessels to discrete classes in the post-reform years.
Both approaches estimate the marginal effect of a persistent reduction in fuel subsidies
brought about by the reform on a vessel’s probability of exiting the fishery in any given
year; however, the DD design utilizes variation in fuel subsidy reductions across all vessel
classes while the RD-DD design only utilizes local variation around a particular vessel-length
threshold (30m).
Using the DD approach, we find that a one-percent reform-induced reduction in a vessel’s
annual fuel subsidy is associated with a 0.153 percentage-point increase in the probability of
exiting the fishery on an annual basis, or a 0.350 percentage-point increase in the probability
of exiting the fishery anytime during the post-reform period (Table 2). Given that the
reform was responsible for decreasing average annual fuel subsidies by 20.6% (SI Appendix,
Table S5 ), this equates to increasing the probability of exiting the fishery during the post-
10
reform years by 7.2 percentage points, which is an approximately 50 percent increase over
the observed exiting rate during the pre-reform period. The marginal effect of fuel subsidy
reductions on the annual rate of exit is relatively constant and persistent during the post-
reform years after the initial transition period in 2016: the percentage-point increase in the
annual exit rate associated with a one-percent lower annual subsidy payment is around 0.20
in the years proceeding the reform (Figure 3).
Our RD-DD approach confirms the effect of fuel subsidy reductions on vessel exit deci-
sions. Before the reform, fuel subsidy payments were smoothly allocated to vessels across
vessel length, with no discontinuities at the post-reform 30m vessel-length threshold; ac-
cordingly, there was no difference in the probability of exiting on either side of the threshold
(Figure 2). In contrast, the difference in fuel subsidy payments at the vessel-length threshold
in the post-reform years corresponds with a significant difference in the probability of exit-
ing on either side of the threshold. Combining the reform’s first-stage effect on fuel subsidy
payments with its reduced-form effect on vessel exiting decisions, we find that a one-percent
reduction in fuel subsidy payments is associated with a 0.158 percentage-point increase in
the probability of exiting on an annual basis (SI Appendix, Table S4), which is virtually
identical to our estimate using the DD approach.
The subsidy reform significantly increased the rate at which vessels exited the fishery.
But an exiting vessel can either be retired through the buyback program or purchased for
its engine power quota, which is then transferred to a new vessel. Fleet capacity is thus
only reduced by exit through the buyback program as the engine power quota associated
with retired vessels is removed from the aggregate supply of quota. Determining the effect of
the subsidy reform on fleet capacity, therefore, requires us to distinguish between these two
forms of exit. We find that nearly half of the reform’s effect on vessel exit rates is driven by
vessels retiring through the buyback program: a one-percent reform-induced reduction in a
vessel’s annual fuel subsidy is associated with a 0.065 percentage-point increase in the annual
probability of participating in the buyback program, or a 0.156 percentage-point increase in
the probability of a buyback anytime during the post-reform period (Table 2, SI Appendix).
The subsidy reform therefore induced a decrease in the aggregate supply of engine power
available to the fishery.
11
To explore the heterogeneous exit decisions of fishermen in response to the subsidy reform,
we allow the marginal effects on exit and buyback rates from our DD design to vary over
observed vessel characteristics, such as vessel size, vintage, engine power, and gear type.
We find that the subsidy reform had a meaningful impact on the structure of the fleet.
For a constant percentage reduction in fuel subsidy payments, double-otter trawlers were
more likely to exit the fishery in the post-reform years relative to single-otter and beam
trawlers (Figure 4). Given that they also received the largest reduction in payments under
the reformed fuel subsidy program, exiting double-otter trawl vessels were disproportionately
responsible for the overall increase in vessel exiting rates. We also find that smaller and older
vessels were more responsive to the reduced fuel subsidy payments than larger and newer
vessels, which experienced negligible impacts from the reform. This heterogeneity is echoed
in the marginal effects of subsidy reductions for buyback decisions. Notably, smaller and
older exiting vessels were more likely to surrender their engine power quota through the
buyback program than larger and newer vessels. Altogether, the fuel subsidy reform led to
an acceleration of exit and buyback rates in smaller and older vessels, thereby shifting the
structure of the remaining fleet to newer and bigger trawling vessels.
The subsidy reform simultaneously decreased fuel subsidy payments to fishermen and
increased the buyback price offered for retiring vessels. We can use our DD model to de-
compose the separate contributions of each reform to the total impact on fleet capacity by
predicting the exit and buyback rates for the post-reform years after replacing the observed
fuel subsidies with the hypothetical fuel subsidies that would have existed had they been
determined using the pre-reform rule. These predictions estimate the counterfactual exit
and buyback rates that would have existed if only the buyback subsidy had been raised (SI
Appendix). We find that raising the buyback price alone would have resulted in a four-year
exit rate of 19.4% in the post-reform years, compared to 15.4% in the pre-reform years (SI
Appendix, Table S5 ). The higher exit rate can be largely explained by the corresponding
higher four-year buyback rate: 9.7% in the post-reform years compared to 0% in the pre-
reform years. Increasing the buyback price alone would not only have induced additional
vessels to exit, but also converted would-be exiters to retire their quota through the buyback
program since the post-reform buyback price of 7,500 RMB/kW was above the prevailing
12
post-reform market price of engine power quota, which various estimates place at 6,000-9,000
RMB/kW (SI Appendix, Table S2 ). We find that of the 1080 fishermen retiring their quota
in the post-reform years, 640 would have been induced to exit and retire their quota if fuel
subsidies had not been reduced but buyback prices alone increased, suggesting the remaining
440 were induced to retire because of fuel subsidy reductions.
Discussion
A synthesis of the marine science literature would suggest that eliminating harmful fishing
subsidies is the foremost solution to addressing many of the threats to fisheries sustainability
worldwide. While there is logic behind this suggestion, a difficulty is that there have been
very few cases where subsidies have actually been reduced, and virtually no empirical studies
that unravel how removing subsidies impacts fisheries. In this paper, we utilize an unprece-
dented dataset and a unique natural experiment where subsidies were actually reduced to
estimate how subsidy reductions affected the trawl fleet in China’s Zhejiang province. Our
study suggests that the relationship between subsidies and sustainable fisheries is nuanced
rather than simple, and worthy of continued discussion.
Our main empirical results show that removing subsidies increases the probability that
a given vessel owner will decide to exit the fishery, particularly for owners of smaller and
older vessels. This result is consistent with economic theory and suggests that the economic
profits of marginal fishermen were largely comprised of fuel subsidy payments, as indicated
by a survey of trawling vessel owners (Shen and Chen, 2022). The decision to exit fishing,
however, is only the first part of the mechanism leading to fleet capacity reductions. In a
limited entry fishery, like our example in China, whether an exit decision ultimately leads
to reduced fleet size depends on the existence of institutional design features that deny
exiting fishing capital from re-entering the fishery. For example, one design feature of a
limited entry program that would translate exit decisions immediately into fleet reduction
would be a design that mandated retiring fishermen to fully surrender their quota upon exit.
This was not done when Chinese management authorities set up the limited-entry licensing
scheme in the early 1980s. Instead, China followed the precedent of most other limited
13
entry programs by licensing vessels and engine power on each vessel, and then allowing that
licensed power quota to be bought and sold by entrants and exiters, respectively. In such
a regulatory setting, it is important to realize that there will be no change in fleet capacity
when subsidies are reduced without some other institutional design features that purposefully
and permanently retire quota from exiters.
In the case we examine here, the specific institutional design feature that ultimately
fostered fleet reduction was a buyback program. The buyback program was introduced by
Chinese authorities not to reduce fleet capacity per se, but to ease the transition of the
thousands of fishermen removed from foreign fishing grounds as part of the renegotiation of
marine boundaries associated with LOS. But as managers reversed the growth focus of the
1980s and implemented negative growth targets, fleet capacity reduction became possible by
re-invoking and enhancing the vessel buyback program. This was made possible by diverting
the savings from reduced fuel subsidies into the buyback program, essentially repurposing
the subsidies to incentivize vessel exit while aiding fishermen in transitioning to non-fishing
occupations. In doing so, Chinese authorities not only enabled a mechanism for reducing
fleet capacity but also addressed one of the largest hurdles to subsidy reforms, namely the
short-run cost imposed on fishermen from reducing subsidy payments (Costello et al., 2021).
In our natural experiment, the simultaneous reduction in fuel subsidies and increase in
buyback prices led to an increase in the exit rate of vessels. During the four pre-reform
years, approximately 15% of the fishermen in our sample exited by selling their power quota
to new entrants. During the four post-reform years, the exit rate increased to approximately
30%, and most of the increase in the exit rate went into the buyback program. Changes in
both fuel subsidies and the buyback price played roles in motivating the observed reduction
in fleet capacity: the former decreased the annual returns to owning a vessel and the market
value of engine power quota, while the latter increased the opportunity cost of not retiring
a vessel. The contribution of each of these changes to fleet capacity reduction is confirmed
by our counterfactual estimates, suggesting that reducing fuel subsidies has the potential to
induce vessel owners to leave fishing, as proponents expect.
But perhaps the more important observation is that without the buyback program, vessel
exit decisions would not have likely translated into any fleet capacity reduction. Indeed,
14
even with the buyback program in place, if buyback prices had remained at their pre-reform
level, there would have been no post-reform capacity reduction. This is because pre-reform
buyback prices (2,500 RMB/kW) had been set below the prevailing post-reform power quota
prices of 6,000-9,000 RMB/kW. Under these circumstances, if buyback prices had not been
raised to 7,500 RMB/kW, exiting vessels would have preferred selling their power quota
on the market to potential entrants rather than surrendering it to authorities through the
buyback program. This is important because it implies subsidy reductions alone are not likely
to have any effect on fleet capacity in limited entry fisheries unless they are accompanied by
complementary policies that ensure that exit decisions translate into fleet capacity reduction
actions.
Removing subsidies is only a first step towards sustainable fisheries. But subsidy removal
may be neither necessary nor essential for sustainability. The end goal of subsidy removal is
surely to reduce fishing mortality in overharvested fisheries. But as argued above, subsidy
removal alone does not guarantee capacity reduction. Moreover, fishing capacity, as measured
by vessel numbers or total engine power, is only one of many factors determining fishing
mortality, such as fishing time, number of fishers, and the technical efficiency of vessels. If
the desire is to rebuild fisheries and/or hold them at sustainable levels, managers must either
control fishing mortality directly (e.g., through a total allowable catch) or control all factors
in the harvest production process. Indeed, a cross-country empirical investigation found no
effect of fisheries subsidies on the status of fish stocks in countries with individual quota-
based fisheries management systems, which often have rigorous monitoring and enforcement
requirements for controlling fishing mortality (Sakai, 2017).
In China’s case, it is not immediately clear how reduced fleet capacity will translate into
harvests and the status of fish stocks. On the one hand, conservation gains from reduced fleet
capacity could be eroded by the transition to a fleet of newer, bigger, and more technically
efficient vessels. On the other hand, prohibiting the construction of vessels with trawling
gear, which tend to be more productive and indiscriminate in their harvests, could result
in a fleet of vessels with lower CPUE harvesting technology and drastically different catch
compositions of species. All of this must also be considered within the historical context
of China’s persistent high fishery catches, despite the perception of overfishing for decades
15
(Costello, 2017; Szuwalski et al., 2017).
In general, as the preceding discussion demonstrates, the use of subsidy removals and
buyback programs can be effective tools for fleet capacity reduction, provided that they
are tailored to the policy context at hand; however, they should not be viewed as long-
term solutions to sustainability challenges for fisheries. Importantly, simply reducing fleet
capacity does not address the underlying incentives of remaining vessel owners to over-
invest in unregulated dimensions of the harvesting production process, and without direct
control over fishing mortality, overfishing can persist Homans and Wilen (1997); Holland
et al. (1999); Weninger and McConnell (2000); Squires (2010). At best, such tools should
be viewed as short-term aids in transitioning to a more sustainable governance system that
addresses the root of overfishing concerns, rather than the symptoms. It remains to be seen
how the management of China’s post-reform fisheries will evolve and how complementary
policies will foster the “ecological economy” goals of a sustainable fishery.
Methods
Data
Individual-level information on fishing vessels primarily comes from the records of the Marine
Fishing Vessel Dynamic Management System provided by the Zhejiang government. This
administrative platform comprises five modules corresponding to each section of the vessel
management activities: engine power quota, vessel name, vessel inspection, vessel registra-
tion, and fishing license. Each module is responsible for documenting the acquisition and
cancellation of respective certificates for fishing vessels in the double-control system. We
compile a dataset for all exiting vessels in the archives, identify the time at which each vessel
exited, and identify each vessel who exited through the buyback program. With construc-
tion and exit time identified for each trawler in our compiled dataset, we can recover the
dynamic fleet capacity of trawlers in the Zhejiang Province. Fuel subsidy payment records
are available through public county-level databases. More details on the assembly of our
dataset can be found in the SI Appendix.
16
Baseline Empirical Model
We use a difference-in-differences (DD) design with a continuous treatment to measure the
exit (or buyback) elasticity with respect to fuel subsidy reductions for all vessels. We model
the decision to exit (or buyback) using the following linear transition probability model:
yit =βiIt+λait +ci+γt+νtXi+uit,(1)
where yit is a binary variable indicating whether vessel iexited (or participated in the
buyback program) in year t,ciand γtare fixed effects for vessels and years, respectively, λait
captures the baseline hazard at age ait, and uit is the idiosyncratic component of the exit
(buyback) decision. The variable It=1{t2016}indicates the post-reform period. The
linear transition probability model in Eq. 1 is motivated as a linear approximation of the
discrete-time conditional hazard function for a duration model of vessel life (SI Appendix).
We supplement the DD model with a regression-discontinuity difference-in-differences (RD-
DD) approach, which directly exploits the variation in fuel subsidy payments created by the
vessel-length thresholds in the post-reform years. The details of this approach are discussed
in the SI Appendix.
Our treatment variable iis defined as the reduction rate in the average annual post-
reform fuel subsidy relative to the pre-reform period for vessel i:
i= log ¯spre
i
¯spost
i,(2)
where ¯spre
iand ¯spost
iare the average fuel subsidy payments during the pre- and post-reform
periods, respectively. Since the year fixed effects γtabsorb the common annual adjustments
in fuel subsidy payments across vessels, the subsidy reduction rate iindicates vessel i’s
persistent treatment exposure to the subsidy reform (SI Appendix). Our parameter of inter-
est is β, which represents the marginal effect of a persistent reduction rate in fuel subsidies
on the probability of exit (or buyback), conditional on not exiting prior to year t.
The vessel characteristics that determine the subsidy assignment imay intrinsically
correlate with exiting and buyback decisions, as well as unobserved time-varying factors
17
such as fuel prices, buyback prices, sea conditions, and fishery stocks. To purge out omitted
variable bias associated with vessel characteristics, we further introduce the interactive fixed
effects νtXito capture characteristic-specific common trends, where νtare factor loadings
and Xiis a vector of vessel characteristics allowed to influence the exit (buyback) decision
differently across years. In the baseline specification, Xiincludes engine power, vessel length,
total tonnage, and a categorical variable representing fishing operation (gear). After the
absorption of νtXi, the exogenous variation in iremaining for identification primarily
comes from the discontinuities in the post-reform subsidy assignments generated by the
multiple eligibility thresholds (Figure 1).
Additional Specifications
We modify our baseline model Eq. 1 in several ways. First, to investigate time-varying
treatment effects across years, we replace βiItwith βjiIj
tfor j= 2012, ..., 2019, where
Ij
t=1{t=j}. This produces the event-study plot in Figure 3. Second, to investigate
heterogeneous treatment effects, we replace βiItwith βmVm
iiItfor m= 1, ..., M , where
Vm
i=1{vessel classi=m}is a binary variable indicating whether vessel iis in a particular
vessel class m, based on quantiles (or categories) associated with vessel characteristics in
X. This produces the heterogeneous treatment effects in Figure 4. Finally, to estimate the
marginal effect of subsidy reform on exit (or buyback) decisions over the entire four-year
post-reform period, we estimate an aggregated two-period pre- and post-reform version of
Eq. 1. These produce the quadrennial marginal effects reported in columns (2) and (4) in
Table 2.
Validation and Robustness Checks
We perform various validation and robustness checks for our DD and RD-DD estimation
models. A subset of these robustness checks can be seen in SI Appendix Tables S3 and S4. A
more detailed discussion of these robustness checks, as well as the identification assumption
underlying the DD and RD-DD approaches, can be found in the SI Appendix.
18
Supporting Information
Supporting information can be found here.
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Tables
Table 1: Fleet and Fishery Dynamics for Trawling Vessels in China’s Zhejiang Province
Fleet Avg. Vessel Vessel Vessels Fuel Fuel Buyback
Size Power Exits Buybacks Constructed Subsidy Price Price CPUE
Year (No.) (kW) (No.) (No.) (No.) (RMB/kW)a(RMB/MT) (RMB/kW) (MT/kW)b
2012 7646 262 247 0 208 1681 7765 2500 0.90
2013 7613 267 439 0 406 1831 7651 2500 0.89
2014 7533 271 386 0 306 1774 7315 2500 0.94
2015 7515 272 113 0 95 1608 5706 2500 0.99
2016 7252 275 357 182 94 1148 5380 7500 1.01
2017 6506 280 808 585 62 950 6195 7500 1.02
2018 6151 284 467 148 112 786 7455 7000 0.93
2019 5860 287 338 165 47 645 6924 7000 0.92
Fleet capacity dynamics are summarized from the sample of large trawlers compiled from the Zhejiang fishing vessel management
system, where fleet size is measured at the end of the year.
aFuel subsidy is calculated as the annual average payments per power.
bCatch per unit effort (CPUE) is calculated from the aggregated statistics for trawling fisheries in Zhejiang, reported by the China
Fisheries Yearbook.
Table 2: Marginal Effect of Fuel Subsidy Reduction on Vessel Exit and Buyback
Exit Buyback
Annual Quadrennial Annual Quadrennial
(1) (2) (3) (4)
Fuel Subsidy 0.153∗∗∗ 0.350∗∗∗ 0.0651∗∗∗ 0.156∗∗∗
Reduction (0.0185) (0.0408) (0.0140) (0.0350)
R20.168 0.509 0.136 0.303
¯
Y0.0610 0.222 0.0207 0.0751
Observations 50,984 14,016 50,984 14,016
Standard errors in parentheses
p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001
25
Figures
Figure 1: Fuel subsidy payments per kW of engine power for all large trawling vessels (24
meters) in the Province of Zhejiang. Boxes represent the 25th, 50th, and 75th percentiles,
while whiskers extend to 1.5 times the interquartile range (IQR).
26
Figure 2: Average fuel subsidies (left) and vessel exit rates (right) as a function of vessel
length (meters), before (top) and after (bottom) the fuel subsidy reform. The vertical line
denotes the vessel-length threshold for determining vessel classes. Blue dots denote sample
means in evenly-spaced bins of vessel length with 95% confidence intervals (Calonico et al.,
2015). Red lines are fitted by cubic regressions on either side of the threshold.
27
Figure 3: Year-specific marginal treatment effects of a one-percent reduction in fuel subsidy
payments on the probability of exiting, relative to the baseline year 2015. Estimates from
the difference-in-difference model. The shaded area represents 95% confidence intervals.
28
Figure 4: Estimates of heterogeneous treatment effects of a one-percent fuel subsidy reduction
on quadrennial post-reform exit and buyback probabilities across vessel characteristics with
95% confident intervals.
29
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