The I, the T or the Q? Which shing opportunity attributes are associated with sustainable shing?

11 While several prominent studies link the use of individual transferable quotas (ITQs) to 12 sustainable fishing, it remains unclear which attributes of this system (i.e., individual, 13 transferable, or quota), or any other system, lead to sustainable outcomes. To test for a linkage 14 between management systems and sustainable fishing, we systematically classified how fishing 15 opportunities are allocated for 443 fish stocks from 1990 to 2018 to produce the largest 16 database of its kind. Using mixed-effects models and a difference-in-differences approach, we 17 tested the occurrence of system attributes against two metrics of sustainable fishing: mortality 18 (i.e., overfishing) and biomass (i.e., overfished). Our results reveal that quota limits and 19 individual allocation reduce the probability of overfishing, but offer no evidence supporting 20 the transferability of fishing opportunities or the length of time they are held for. These results 21 highlight the importance of considering specific attributes in the design of fisheries 22 management systems.


26
Individual transferable quotas (ITQs), where harvest limits are held individually, for a long 27 duration, and can be freely transferred, are an increasingly used fisheries management system 28 throughout global fisheries 1,2 . While several prominent studies have linked the use of ITQs to 29 sustainable fishing 3,4 , the effect of each ITQ attribute (i.e. the I, the T, and the Q), remains 30 underexplored and the lessons for policy design unclear 5 . 31 For each ITQ attribute, theoretical claims have been made supporting a link to sustainable 32 fishing, but counterclaims have also been raised. Limiting catches through quota has the 33 advantage over limiting fishing effort (e.g. time at sea, number of hooks or pots) that it is more 34 closely tied to fishing mortality 6,7 and more predicable to control 8,9 , although quota limits may 35 be more difficult to enforce and over-quota catches simply discarded at sea 10,11 . Allocating 36 fishing opportunities to individuals empowers fishers to choose when to use them 12 , including 37 during lower impact fishing seasons, however the common-pool aspect of fish stocks and thus 38 the incentive for individuals to fish more remains 10 . Transferability in fishing opportunities 39 will lead to concentration in the hands of the most profitable businesses 6,13 who may be more 40 likely to pay for management 14 of a smaller fleet 15 , but profitability is not synonymous with 41 efficiency given unaccounted for externalities 7,16 , and transferability of fishing opportunities 42 and fleet contraction can still occur through vessel sale if quota trade is prohibited. 43 Beyond these ITQ attributes, there is little literature on the attributes used in alternative 44 allocation systems, such as pooling (i.e. opportunities are fished collectively without allocation 45 to individuals), leasing, rationing throughout the year, and leaving the industry to self-govern 46 (e.g. the allocation of fishing opportunities to a cooperative, not including initial individual 47 allocation that is later grouped by cooperatives 17 ). While we explore these other attributes and 48 their link to fisheries sustainability in this article, we mainly focus on the I, T, Q attributes as 49 this is the domain where theories have been advanced. 50 The allocation of fishing opportunities is closely linked to duration, and several studies have 51 claimed that when the duration of exclusive fishing opportunities is sufficiently long and 52 secure, the long-term sustainability of the fish populations is in the interest of fishers 53 themselves as they will bear the consequences of (un)sustainable behaviour 18,19 . This is 54 disputed, however, as other studies have noted that the common-pool aspect of fish stocks and 55 the incentive to overfish remains, hence the need for enforcement 5 , and long-term property 56 rights in other sectors have still led to unsustainable behaviour 5 . 57 As many of the theoretical claims linking ITQ attributes to sustainable fishing are contested, it 58 is especially important to test the empirical effect of existing fisheries management systems. 59 Unfortunately, much of the existing empirical literature does not distinguish between the 60 different attributes of management systems (Table 1) and some studies have used contested 61 proxies as metrics of sustainable fishing 20 . By ignoring attributes, the control groups used in 62 these studies also suffer as all other management systems, including systems with no 63 management at all, are grouped together. The few empirical studies that analyse system 64 attributes show no conclusive evidence that individual allocation, transferability, or duration 65 are associated with sustainable fishing beyond the benefits of quota management (Table 1). 66 [ Table 1] 67 As there are conflicting theoretical claims and as the empirical evidence on specific attributes 68 is limited and ambiguous, an important research question remains: Which attributes of fisheries 69 management systems, if any, are associated with sustainable fishing? For this purpose, we 70 compiled the largest dataset on fisheries management systems to date, covering 71 and tested different systems and their attributes against two metrics of sustainable fishing: 72 mortality (i.e., whether a fish stock is subjected to overfishing) and biomass (i.e., whether a 73 fish stock is overfished). 74

Fisheries management systems 76
The most frequently observed fisheries management system in our dataset was total effort (TE, 77 number of stocks = 174, Figure 1A), where an input to fishing is managed at the fleet level. 78 The second most observed management system was individual transferable quota (ITQ, n=151) 79 followed closely by total quota pool (TQP, n=112), where a quota cap is set and fished 80 collectively by the fleet until it is exhausted. Individually rationed quota pool (IRQP, a 81 collective quota system where quota is allocated in rationed periods over the year, e.g. a weekly 82 limit for vessels) and individual quota (IQ) were also frequently observed (n=63 and n= 46, 83 respectively, Figure 1A). Other allocation systems were extremely rare: rationed individual 84 quota (RIQ, n= 4, where individual quota is allocated for a shorter term than a full season), 85 self-governed quota pool (SGQP, n=4, where quota is formally allocated to a group such as a 86 cooperative), individual transferable effort (ITE, n=3) and rationed quota pool (RQP=,n=2,87 where quota is allocated to the fleet, for a shorter time than one fishing season). 88 89 [ Figure 1] 90 91 Regarding the duration for which individual quota (IQ, ILQ, ITQ) are held, most individual 92 quota was held with a 'legal ability' to change allocations (e.g. by changes in the fisheries 93 management plan, n=77, Figure 1B). Other durations were all also frequently observed 94 (indefinite, n= 40, multiple seasons, n=35 and for one single season, n=31, Figure 1B). 95

Sustainable fishing indicators 96
We found that overfishing frequently occurred in all management systems and regions . The  97   regions with the highest shares of overfishing were the Mediterranean & Black Sea region and  98   northern Europe with 84 percent and 69 percent of observations, respectively. TE, unregulated,  99 RQP, RIQ, and ITE management regimes had the largest shares of overfishing occurring, 100 ranging between 71 and 100 percent of observations. In contrast, TQP, IRQP, ITQ, and 101 individual leasable quota (ILQ) management regimes had the lowest share of overfishing 102 ranging between 30 and 36 percent of observations ( Figure 2A). 103

104
Of the total sample, a smaller amount of fish stocks, only 32 percent, were in an overfished 105 state. Individual effort (IE) was the management regime with the largest share of fish stocks in 106 an overfished state with 71 percent of observations, followed by TE and unregulated with 45 107 and 44 percent respectively ( Figure 2B). 108 109

Effects of fisheries management systems on sustainable fishing indicators 110
Several fisheries management systems reduced the probability of overfishing and/or being in 111 an overfished state when compared to the control system of TE ( Figure 2C). Strong effects for 112 reducing overfishing were found for individual quota systems (including ITQ, ILQ, and IQ), 113 although the strongest effect was found for SGQP ( Figure 2C). TQP, another form of pooled 114 quota, also significantly reduced the probability of overfishing, although the effect was smaller 115 ( Figure 2C). ILQ and ITE reduced the probability of overfished biomass ( Figure 2C), although 116 there were few of these systems and the confidence intervals are wide. 117 [ Figure 2] 118 Disentangling the effects of the I, the T, and the Q on sustainable fishing 119 Without controlling for other factors (i.e., region, time, fish stock), systems with the attributes 120 of quota limits, individual allocation, and transferability had lower frequencies of overfishing 121 and overfished states, with the largest difference for quota limits (71 percent without versus 40 122 percent with quota limits, Figures 3A and 3B). 123 Association between attributes and sustainable fishing (mixed regression models): Controlling 124 for other factors in the mixed-model analysis, we found a reduced probability for overfishing 125 when fisheries were under quota limits and/or when fishing opportunities were allocated 126 individually ( Figure 3C), with the largest effect found for quota limits. We found that the 127 predicted probabilities of overfishing were, on average, 0.5 without quota versus 0.3 with quota. 128 For individual allocation, the probability of overfishing without individual allocations was, on 129 average, 0.45 versus an average probability of 0.25 for a stock with individual allocations 130 ( Figure B1). However, considerable uncertainty in the random effects resulted in wide 131 prediction confidence intervals ( Figure B1). For transferability, despite a lower occurrence of 132 overfishing ( Figure 3A), no significant effect was found when other factors were accounted for 133 in the mixed-model analysis ( Figure 3C). None of the attributes had a significant effect for 134 stocks being in an overfished state ( Figure 3C). We found no significant difference in the 135 probability of overfishing when systems with longer durations were compared to those 136 allocated for a single season, although there was an increased probability of an overfished state 137 when fishing opportunities were allocated for fixed multiple seasons ( Figure 3D). 138 Difference-in-differences: We found a significant reduction in the probability of overfishing 139 for the addition of Q (fisheries transitioning from IE to IQ) and for the addition of I (TE to IE) 140 ( Figure 4). Where multiple attributes were jointly added to a system, we found a reduced 141 probability of overfishing and the overfished state where pooled quota fisheries transitioned 142 became individual and transferable (i.e. transitioned to ITQ) but found no significant effect for 143 TE managed fisheries that became quota, individual, and transferable (i.e. transitioned to ITQ). 144 This finding may be regionally confounded as 18 of the 20 treatment fisheries that transitioned 145 from TE to ITQ were Australian fisheries in the early 1990s. None of the transitions were 146 associated with a change in the probability of stocks being overfished (Figure 4). 147 Refining the DiD approach to 22 paired treatment and control fisheries, where treatment 148 fisheries transitioned from pooled quota to individually allocated quota revealed no significant 149 change in the probability of overfishing or overfished outcomes (Figure 4). 150

Sensitivity test using mortality and biomass trends 151
The analysis of the trend indicators showed that IE increased the probability of a declining 152 trend in overfishing (Table B2), while these systems were not associated with reduced 153 overfishing using the sustainability threshold ( Figure 2). We found the reverse for ITQ and 154 TQP (i.e. while these systems reduced the probability for overfishing, they reduced the 155 probability of an increasing trend for stocks that were experiencing overfishing). We found no 156 significant change in the probability of an increasing trend in biomass for overfished stocks 157 under any management system (Table B2). We also found no significant change in trends for 158 Q, I, T, or D ( Figure B2 and B3). Using the DiD approach, we found a small effect on the 159 increase in the probability of reduced overfishing when fisheries transitioned from TE to IE 160 (the addition of I) ( Figure B4). 161

Sensitivity test using alternative thresholds for overfishing and overfished 162
Applying alternative sustainability thresholds (high overfishing: F/Fmsy >1.5; highly overfished: 163 B/Bmsy < 0.5) resulted in changes to the significant effects (Table B3). Whereas IRQP, IE, and 164 unregulated fisheries did not have an effect at the original overfishing threshold ( Figure 2C), 165 these systems were associated with a reduced probability of high overfishing (Table B3). IE 166 systems also has a significant effect on biomass at a highly overfished level (Table B3). 167 At the attribute level, the results were largely unchanged when alternative sustainability 168 thresholds were applied (i.e., a reduced probability of high overfishing with individual 169 allocation and quota limits) and the effect sizes increased ( Figure B5). The lack of effect for 170 duration also remained unchanged ( Figure B6). 171 The results from the DiD analysis shifted considerably with alternative sustainability 172 thresholds, with several more transitions reducing the probability of high overfishing ( Figure  173 B7). Adding Q (IE to individual quota; TE to non-individual quota) and adding I (TE to IE; 174 non-individual quota systems to individual quota) resulted in a reduced probability of high 175 overfishing ( Figure B7). Transitioning from non-individual quota to ITQ reduced the 176 probability of a highly overfished state ( Figure B7). In contrast, transitioning from TE to IE 177 increased the probability of a highly overfished state occurring ( Figure B7). 178

179
We set out to understand the degree to which fishery management systems, and in particular 180 systems that include I, T, Q, and/or D, affect sustainable fishing. After classifying management 181 systems used in hundreds of fisheries around the world, we found that management systems 182 using quota limits, particularly those allocated individually (IQ, ILQ, ITQ), reduced the 183 probability of overfishing compared to TE management. ILQ and ITE were the only systems 184 associated with a reduction in the probability of stocks being overfished, with considerable 185 uncertainty. 186 Disentangling the effects of I, T, and Q as system attributes, we found that Q and I were 187 associated with large reductions in the probability of overfishing, and that this effect was 188 stronger when we applied an alternative threshold for overfishing (i.e., high overfishing, F/Fmsy 189 >1.5). These results were only somewhat reflected in biomass indicators; individual allocation 190 increased stock biomass for overfished stocks, but not to a level that prevented the probability 191 of stocks remaining in an overfished state. From these results, we conclude that quota systems 192 tend to outperform effort systems in terms of delivering sustainable fishing, and that individual 193 systems tend to outperform systems with total, pooled limits. The result for individual 194 allocation, however, seems to be largely driven by individual quota systems (I+Q, Figure 2 The reduced probability of overfishing in individual systems could potentially be caused by the 203 elimination of the race to fish in individual systems 12 , which may result in a more targeted 204 fishery and a reduced need to discard fish 14,22,23 . It may also result in catches that are lower 205 compared to total allowable catches 4 . A longer fishing season may aid enforcement (e.g. in a 206 fishery with a very short season it may be more difficult for coastguards to monitor over-quota 207 catches or illegal discarding) 22 , as would the accountability of individual allocations as these 208 are held (and exceeded) by a fisher or a company rather than the entire fleet. 209 We found no effect for either the transferability of fishing opportunities or their duration, which 210 suggests that the casual mechanisms underlying our findings for individual allocation may not 211 be related to secure property rights in fisheries, or the use of market-based systems, as has been 212 suggested in previous literature 3, 12 . 213 Costello et al. (2008) 3 found that 'catch shares' (specifically ITQs) prevented fisheries 214 collapse, defined as landings below 10 percent of historical levels. While the study was the 215 first of its kind, it suffered from several shortcomings. In the study, control fisheries were not 216 classified and the comparison group, all non-ITQ fisheries, included many unregulated 217 fisheries, making it impossible to disentangle the effect of implementing whether a reduced 218 probability of collapse was due to I, T, or Q attributes 5 . In addition, it has been demonstrated 219 that landings data, the proxy used for sustainable fishing, is a poor indicator of stock status 20 . 220 Subsequent studies have nuanced these results. For instance, a subsequent study by the same 221 authors 24 addressed some of the issues by investigating the impact of ITQs on fisheries that 222 already had quota limits in place, and found that effects were still present, although weaker, 223 than in the earlier study (Table 1). Other, more nuanced studies found mixed results for the 224 sustainability benefits of management systems (Table 1). The few studies that have analysed 225 specific system attributes have consistently found that Q improves sustainable fishing, a weak 226 effect for I, and no consistent effect for either T or D (Table 1). Our findings are similar, as we 227 found a reduced probability of overfishing for fisheries managed by Q and I but not for T or D. 228 While our study addresses many of the confounding issues in previous literature, several 229 limitations remain. First, we cannot guarantee that our control and treatment fisheries are 230 similar, for example regional circumstances may differ even for adjacent regions 25 , or that 231 fisheries undergoing management change may undergo transitions due to a current or recent 232 fisheries collapse 15,26 . Second, the scope of this study is limited to governmental policy, and 233 thus in our classification method we relied on the legal definitions of fisheries management 234 systems. Systems may differ from what is described on paper or may develop important 235 attributes in parallel to the governmental system (e.g. producer organisations and fishing co-236 operatives may pool fishing opportunities that were initially individually allocated). Similarly, 237 the legal definitions of duration may differ from the perceived duration of fishing opportunities 238 based on historical precedent. However, our result for duration based on legal definitions aligns 239 with 27 who used perceived duration. Differentiating between systems as defined by policy and 240 systems as they operate in practice is one area for future research and even further nuance in 241 studying fishing opportunities. Third, our approach relies on defined thresholds for overfishing 242 and overfished states and does not allow for comparison with previous work that studied 243 continuous indicators of fish stocks 28,29 . We believe, however, that higher or lower fishing 244 pressure can only be assessed against a defined threshold (i.e., an increase in fishing pressure 245 from a low base could still be sustainable). 246 Based on our methodology and new dataset of fisheries management systems, we found 247 evidence that both Q and I attributes were associated with a reduced probability of overfishing. 248 The effect of different management attributes on sustainable fishing was not ubiquitous, 249 however, as this finding was only slightly reflected in the probability of a stock being 250 overfished and we found no benefit for stocks already under quota transitioning to individual 251 quota or individual transferable quota when we matched these to control fisheries that 252 continued to use pooled quota. Whereas some previous studies have emphasised that market-253 based systems (i.e., the presence of transferability) or those with strong property rights (i.e., a 254 long duration) are associated with sustainable fishing, these benefits disappear with proper 255 controls for other attributes of fisheries management systems. These results highlight the 256 importance of considering specific attributes in the design of fisheries management systems. terms (e.g. analysis of 'catch shares'); however, duration operates as an independent attribute 304 that can vary across all allocation types, as confirmed by the resulting classifications (fishing-305 opportunities-database). We only assessed duration for individual systems, where fishing 306 opportunities were allocated as a separate unit from the fishing licence which may have had its 307 own specified duration. 308

Sustainability definitions 309
To define sustainable fishing, we assessed fish stocks against two metrics (in line with 4,29 ): 310 fishing mortality divided by the fishing mortality needed to achieve maximum sustainable yield 311 (F/Fmsy), and biomass divided by the biomass that can produce maximum sustainable yield 312 (B/Bmsy). We defined a fish stock as subjected to overfishing when the fishing mortality was 313 higher than 1.1 times Fmsy (following 4 ) and a fish stock as overfished when the stock biomass 314 was lower than 0.8 B/Bmsy (following 30 ). We only included stocks from the year that F/Fmsy 315 was at least 0.5 (where data on F/Fmsy was available) to control for fisheries that were not yet 316 developed or of little commercial interest. 317 Sensitivity analyses: Due to a potential delay between management change and sustainable 318 fishing 15 , we included trend indicators for mortality and biomass to assess whether stocks that 319 did not meet sustainable fishing metrics were trending toward the threshold. When a stock was 320 experiencing overfishing (i.e., F/Fmsy >1.1), but the level of F/Fmsy was lower compared to the 321 average of the previous three years, the observation was recorded as decreasing mortality. 322 When a stock was overfished (i.e., B/Bmsy < 0.8), but the level of B/Bmsy was higher compared 323 to the average of the previous three years, the observation was recorded as increasing biomass. 324 As a second sensitivity analysis, we used two alternative thresholds for the definition of 325 overfishing and overfished (both also used in 4 ), for high overfishing (F/Fmsy > 1.5) and highly 326 overfished (B/Bmsy < 0.5). 327

Data analyses 328
To estimate the effect of management systems and their attributes on fisheries sustainability 329 we used two modelling approaches: (1) a set of mixed-effects regressions testing both systems 330 and attributes, and how these were associated to fisheries status; and (2) a difference-in-331 differences (DiD) approach that tested systems where attributes changed (also using mixed 332 effects). 333 The mixed-effects modelling framework allowed for the introduction of random effects for 334 variables where the sustainability indicators were more likely to share a similar response. For 335 example, a response of a stock in one region to a management system was more likely to 336 correlate to the response of another stock in the same region 31 . 337 First, we modelled the sustainable fishing metrics S for region r, stock s, and year t as a function 338 of the fisheries management system (and its multiple attributes): 339 ",$,% = ) ",$,% + " + $ + ",$,% (1) 340 where ",$,% is a dummy variable for the management system in place, " is a random effect 341 dummy variable for the region, $ is a dummy variable for the stock-specific random effect, 342 and ",$,% is the error term. We compared the effects of all management systems against total 343 effort (TE) as a control group as there are very few unregulated fisheries in our dataset. 344 Second, we modelled the sustainable fishing metrics as a function of the attributes I, T, and/or 345 Q reflecting the theoretical literature (Table 1): 346 ",$,% = ) ",$,% + / ",$,% + 1 ",$,% + " + $ + ",$,% (2) 347 The metrics of sustainable fishing was modelled by dummy variables Q (quota), I (individual) 348 and T (transferable). Random effects were the same as in Equation (1). 349 350 We modelled the impact of the duration of fishing opportunities as follows: 351 ",$,% = ) ",$,% + " + $ + ",$,% (3)  352 where ",$,% represents the duration of fishing opportunities in a management system. We 353 compared the effects of duration against single season as a control group. Random effects were 354 the same as for Equations (1) and (2). 355 As a second approach, we employed a DiD analysis for all transitions where a Q, I, or T element 356 was "added", for instance a transition from non-individual effort management to individual 357 effort management (addition of I), or a transition from individual quota to ITQ (addition of T). 358 We also employed DiD for transitions where multiple elements were added, i.e., a transition 359 from non-individual effort to ITQs (addition of Q, I, and T). This second approach is commonly 360 used for analysing time series data where systems that undergo a change (i.e., treatment) are 361 compared to systems that remain the same (i.e., control). A key assumption in this approach is 362 that treatment stocks would have followed a similar trajectory to control fisheries if no change 363 had occurred 32 . DiD modelling was previously employed to study the effects of IQs, ILQs, and 364 ITQs on sustainable fishing (Table 2). 365 Equation 4 represents the DiD approach where treatment stocks were compared to control 366 stocks: 367 ",$,% = ) ",$,% + " + $ + ",$,% (4) 368 The sustainable fishing metrics were modelled by dummy variable Tr (treatment, i.e., addition 369 on I, T, or Q in the treatment fishery, a dummy variable which was coded 1 after the addition 370 of the attribute and coded 0 for control stocks or prior to introduction of the attribute in 371 treatment fisheries). The other variables are the same as Equations (1)-(3). 372 For a subset of stocks (n=22), we matched treatment and control stocks for the same species in 373 the same region or regions closely located to one another (Table A2) Table A1: Management system definitions, for the 12 final management systems and the 4 520 types of duration of harvesting rights. 521

Individual Transferable Quota
A quantity limit on catches/landings is allocated for the exclusive use of a vessel/license and can be sold to a different vessel/license (quota swapping and leasing may also be permitted).

Individual Leasable Quota
A quantity limit on catches/landings is allocated for the exclusive use of a vessel/license and can be sold to a different vessel/license for a fixed time period only (quota swapping may also be permitted but permanent transfer is not).

Individual Quota
A quantity limit on catches/landings is allocated for the exclusive use of a vessel/license and can be swapped for other quota but cannot be leased or permanently sold (i.e. monetary transfers).

Self-Governed Quota Pool(s)
A quantity limit on catches/landings is allocated to a group of vessels/licenses for joint use. The pool is managed by its membership. Fishers have no individual holdings to enter/exit the pool.

Total Quota Pool
A quantity limit on catches/landings is allocated to a group of vessels/licenses for joint use. The pool is managed by the government.

Individually-Rationed Quota Pool
A quantity limit on catches/landings is allocated to a group of vessels/licenses for joint use. These limits are allocated to individual vessels/licenses for exclusive use in multiple time periods within a fishing season (e.g. daily, weekly or monthly limits).

Rationed Quota Pool
A quantity limit on catches/landings is allocated to a group of vessels/licenses for joint use. These limits are administered in multiple time periods within a fishing season (e.g. weekly or monthly vessel limits).

Rationed Individual Quota
A quantity limit on catches/landings is allocated for the exclusive use of a vessel/license. These limits are administered in multiple time periods within a fishing season (e.g. weekly or monthly vessel limits). There is no total quota limit that can be reached, meaning there is no pool and each vessel/license limit is independent.

Individual Transferable Effort
A limit on fisheries inputs (e.g. days at sea, area/territory, vessel capacity) is allocated for the exclusive use of a vessel/license and can be sold to a different vessel/license.

Individual Effort
A limit on fisheries inputs (e.g. days at sea, area/territory, vessel capacity) is allocated for the exclusive use of a vessel/license.

Total Effort
A limit on fisheries inputs (e.g. number of vessels, days at sea, vessel capacity, seasonal closure, spatial closure) is set for the entire fishery.

Unregulated
There is no fisheries legislation limiting the amount of fishing pressure.

Indefinite
In fisheries legislation it is specified that fishing opportunities are held permanently. The size of the fishing opportunity may change as the total changes (e.g. 3% of 100 may become 3% of 150), but fishing opportunity does not change as a relative share of the total. Fishing licenses may be subject to change at a different interval.

Fixed multiple seasons
In fisheries legislation it is specified that fishing opportunities are held for a fixed period that spans multiple fishing seasons (e.g. 10 years) after which the relative shares of fishing opportunities may be revised. Fishing licenses may be subject to change at a different interval.

One season
In fisheries legislation it is specified that fishing opportunities are held for one season (e.g. one year) after which the relative shares of fishing opportunities may be revised. Fisheries legislation requires an active decision each year on allocations (i.e. the default is not necessarily the same allocation as the previous year). Fishing licenses may be subject to change at a different interval.

Legal ability
In fisheries legislation it is specified that the fisheries manager reserves the right to revise the relative shares of fishing opportunities, but as the duration of the fishing opportunities is not specified this can take place at any time. Fisheries legislation does not require an active decision each year on allocations (i.e. the default is the same allocation as the previous year). Fishing licenses may be subject to change at a different interval.
522       1. B). B/Bmsy for all classi ed sheries management systems (dotted line indicates the threshold for over shed, i.e., when B/Bmsy = 0.8). C) Estimates and 95 percent con dence intervals of management systems compared to TE. Negative (blue) values indicate that the management system reduces the probability of the outcome variable, for example IQ reduces the probability of over shing compared to TE. The non-signi cant effect for ITE cannot be displayed in the gure due to wide standard errors (Table B1).  DiD estimates of treatment effects, outcomes for the probability of over shing and over shed outcomes. DiD estimates are indicated for the addition of Q (TE systems transitioning to pooled quota systems, IE systems transitioning to individual quota systems), I (TE systems transitioning to IE, pooled quota systems transitioning to individual (non-transferable) quota systems, T (individual quota systems transitioning to ITQ systems), and multiple attributes simultaneously. Negative (blue) values indicate that the attribute reduced the probability of the outcome variable.