Ingrid E Van Putten
email: ingrid.vanputten@csiro.aue.quillérou

Emmanuelle Quillérou
email: emmanuelle.quillerou@unu.edu

Olivier Guyader
email: olivier.guyader@ifremer.fr

How constrained? Entry into the French Atlantic fishery through secondhand vessel purchase

Keywords: Entry into fishery, network analysis, logit model, second-hand trade, market analysis, fishing vessels, French Atlantic fisheries

published or not. The documents may come     How constrained? Entry into the French Atlantic fishery through second-hand vessel purchase

Introduction

The French Atlantic fishery comprises a considerable fleet of 3,300 vessels that make up 70 percent of the overall French mainland fleet 1 . Most vessels in the French Atlantic fleet are trawlers, and like in many fisheries around the world, the size of the fleet has fallen in conjunction with decreased resource abundance. Over the past decades several management policies aimed at actively encouraging capacity reduction in the French fishing fleet have been implemented. The first of these policies was the introduction of a compulsory access licence for all fishing operations in France in 1988 (Decision 1.88 of the Comité Central des Pêches Maritimes of September 22, 1988). Access licences limit the total number of vessels operating in the fleet and the additional entry restrictions limit fleet power and tonnage. As the access rights are tied to the vessel, entry to the fishery could, from then on, only be gained through the purchase of a new or secondhand vessel. In addition, fisheries that faced reduced resource abundance are introducing fishing rights. Fishing rights are however not well documented in France as they are managed at the local level by producer organisations.

Since 1992, entry of new vessels into the fishery has been increasingly difficult. A new vessel can enter only if another vessel with greater capacity leaves the fleet, so that an overall set reduction in national fleet capacity can be achieved. For the purpose of reducing capacity, a series of decommissioning schemes were established from 1991 [START_REF] Cueff | A Case Study of Fishing Vessel Capacity Management Public Buyout Schemes: Community Experience through the Multi-Annual Guidance Programmes and Ways Forward[END_REF]) mostly targeted at declining fisheries following the 2002 Common Fishery Policy Reform [START_REF] Guyader | Decommisioning schemes and capacity adjustement : A preliminary analysis if the French experience[END_REF]. Decommissioning has been implemented continuously since 1991, with the rent created by the scheme captured in vessel prices.

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3 At the same time as the decommissioning scheme a seemingly contradictory policy to help fleet renewal was also implemented with the government offering some subsidies to construct new vessels [START_REF] Mesnil | Public-aided crises in the French fishing sector[END_REF]). However, this programme was conditional on meeting the overall capacity reduction target. Between 1992 and 2010, a total of 833 new vessels were constructed (with or without subsidy) for 1,891 scrapped vessels (with or without subsidy).

Overall, the size of the French Atlantic fleet was reduced by 35% (1,736 vessels) between 1992 and 2010. Many fisheries have moved towards significantly smaller fishing fleets. In the French Atlantic fishery this is evidenced by the 34 percent decrease in the number of vessels less than 10 meters and 51 percent decrease for vessels over 40 meters. The smaller size fleet is characterised by increases in harvest and economic efficiency [START_REF] Guyader | Second Hand Market for fishing vessels and implicit price of fishing rights[END_REF]. There are few new vessel constructions (with access rights) because of the limited entry system, but also because capital investments for new vessels are generally very high. This high capital demand could constitute a barrier to entry for more capital-constrained potential first-time owners into the fishery sector who are typically also younger.

Because of capital constraints and limited new vessel entry, second-hand vessel markets have become a crucial entry point for first-time owners to the French Atlantic fishery [START_REF] Guyader | Second Hand Market for fishing vessels and implicit price of fishing rights[END_REF]. This was most obvious from 1996 to 2002 with an increase in the number of owners exchanging vessels on the second-hand market [START_REF] Quillérou | Analyse statistique du fonctionnement du marché des navires d'occasion et de la dynamique associée des flottilles[END_REF]. Around 280 vessels were traded every year on the Atlantic second-hand vessel market between 1992 and 1995 rising to around 400 vessels a year between 1996 and 2001. In the latter period increasing prices per kW were also observed on the secondhand market. Greater profitability following reduction in the fleet numbers may have Trades in second-hand vessels are higher within defined geographical areas [START_REF] Quillérou | Analyse statistique du fonctionnement du marché des navires d'occasion et de la dynamique associée des flottilles[END_REF]. Buyers and sellers find one another mostly through local information channels such as direct contact, through other fishers, newspapers, fishers associations, producer organisations, and accounting centres. Internet websites have recently become popular for advertising sales. Contrary to smaller vessels, bigger (more expensive) vessels tend to be traded through intermediaries (brokers) 3 . Although most trades are within certain geographic areas, there has been some redistribution of the fleet towards Aquitaine and Northern France over the time period considered (Quillérou, Roudaut, and Guyader in review).

Due to the importance of second-hand vessel markets to capital constrained first-time owners in different fisheries, these markets have been the subject of price formation investigation. Prices of second-hand vessels are the result of both demand and supply characteristics. Demand typically depends on the age of buyers and future profit expectations. Supply depends on level of natural, physical, human, immaterial capital investment, and depreciation.

To establish the relationship between supply and demand for second-hand vessels various econometric techniques have been applied to empirical vessel trade data. For instance, hedonic regressions, a revealed preference approach used to estimate demand on the basis of constituent characteristics of a good, has been used to determine how much second-hand vessel prices change with different vessel attributes such as length,

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5 age, and engine power, fleet segment, the type of hull and the maritime district of registration (e.g. [START_REF] Daurès | Estimating capital value and depreciation of fishing fleets: application to French fisheries[END_REF][START_REF] Kirkley | A limited information approach for determining capital stock and investment in a fishery[END_REF]. Even though the second-hand vessel market is characterised by market segmentation [START_REF] Tsolakis | Econometric modelling of second-hand ship prices[END_REF][START_REF] Quillérou | Analyse statistique du fonctionnement du marché des navires d'occasion et de la dynamique associée des flottilles[END_REF], if the vessel price is sufficiently independent from supply-side variables, it could be used as proxy for buyer's capital constraints.

This paper is structured as follows. Section 2 details the materials and methods for logit estimation and social networks. Section 3 details our results which are discussed in Section 4 followed by our conclusions in section 5.

Materials and methods

Models of fisher entry

As mentioned in the introduction, over the past decades much fisheries research has focussed on reducing fishing capacity for sustainability as well as economic reasons and entry into fisheries has largely been ignored. Some authors have indicated concern over the lack of focus on industry renewal, entry and investment, particularly in quota managed fisheries (Putten van and Gardner 2010). The theoretical literature and applied models of entry or investment behaviour make up only a small proportion of the fisher decision-making literature (Putten van et al. 2011). The models generally indicate that entry, stay, and exit decisions in open access fisheries are correlated to the profitability of the vessels [START_REF] Ward | Vessel entry-exit behaviour in the Gulf of Mexico shrimp fishery[END_REF][START_REF] Pradhan | Modeling trip choice behavior of the longline fishers in Hawaii[END_REF][START_REF] Mardle | Empirical analysis of fishing fleet dynamics: entry, stay and exit choices in selected fisheries[END_REF], the availability of technology, and technology uptake [START_REF] Fissel | Exogenous Productivity Shocks and Capital Investment in Common-pool Resources[END_REF].

Entry decisions are sometimes seen as analogous to investment decisions. However, explanatory variables for entry decisions often explicitly include non-monetary drivers.

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6 Most entry and investment models have been theoretical in nature [START_REF] Clark | The optimal exploitation of renewable resource stocks: problems of irreversible investment[END_REF][START_REF] Boyce | Optimal capital accumulation in a fishery: A nonlinear irreversible investment model[END_REF][START_REF] Sandal | Irreversible Investments Revisited[END_REF], but some applied investment models have shed light on how vessels might adjust their level of capital in response to changes in long term prices and stock conditions, assuming profit maximizing behaviour [START_REF] Squires | Long run profit functions of multiproduct firms[END_REF][START_REF] Asche | Fisher's behaviour with individual vessel quotas--Over-capacity and potential rent: Five case studies[END_REF][START_REF] Nøstbakken | Fisheries law enforcement-A survey of the economic literature[END_REF].

Understanding of fisher investment behaviour is still considered low [START_REF] Garcia | Gloom and doom? The future of marine capture fisheries[END_REF] but this is slowly improving. A few studies outline that a range of fisher characteristics may affect observed entry (and exit) decisions [START_REF] Anderson | Necessary components of economic surplus in fisheries economics[END_REF][START_REF] Smith | Satisfaction bonus from salmon fishing: Implications for management[END_REF][START_REF] Binkley | Risks, Dangers and Rewards in the Nova Scotia Offshore Fishery[END_REF][START_REF] Pollnac | Fishery policy and job satisfaction in three southeast Asian fisheries[END_REF][START_REF] Pollnac | Job satisfaction in the fishery in two Southeast Alaskan towns[END_REF].

Recent studies of micro-scale individual fishers investment decisions within a given firm however showed that production level, debt, interest rates and capital stocks are primary determinants of investments, and investment in vessels being governed by oneyear lagged variables (Nøstbakken forthcoming;[START_REF] Jensen | Investment behaviour in individual nontransferable quota systems[END_REF]. [START_REF] Tidd | Exit and entry of fishing vessels: an evaluation of factors affecting investment decisions in the North Sea English beam trawl fleet[END_REF] show that investment is affected by vessel age and size, future revenue, operating cost, stock status of the main target species, impact of management measures, and total fleet size (proxy for congestion). Between firm differences in investment levels is often linked to geographical location and whether it is a family operation (Nøstbakken forthcoming). Studies of economic models of investment and capacity development, however, remain scarce in practice [START_REF] Nøstbakken | Investment Behaviour and Capacity Adjustment in Fisheries: A Survey of the Literature[END_REF].

Trade in the second-hand vessel market has the potential to reduce capital constraints faced by owners because second-hand vessels have lower prices compared to new vessels due to depreciation. Also, social networks exist in most markets [START_REF] Uzzi | The sources and consequences of embeddedness for the economic performance of organizations: The network effect[END_REF][START_REF] Eguíluz | Transmission of Information and Herd Behavior: An Application to Financial Markets[END_REF][START_REF] Podolny | Networks as Pipes and Prisms of the Market[END_REF][START_REF] Jackson | Social and economic networks[END_REF]. The presence of social

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or family connections between a young first-time buyer and the seller may decrease prices paid for fishing vessels compared to the market prices, or better vessel quality for the same price. For instance, fathers may charge their sons a price slightly less than the market price to help them enter the fishing sector. Also, working relationships such as between an owner and an existing crew member could reduce market prices paid because the buyer has perfect information when buying the vessel they are working on.

Second-hand vessel trade with greater levels of kinship-or social networks may thus reduce capital constraints. On the other hand, capital constraint could increase due to increased demand in second-hand fishing vessels under limited entry. It is thus not theoretically clear that second-hand trade removes capital contraints on first-time owners completely.

In this current study we test whether first-time owners are effectively capital constrained compared to second-hand vessel buyers already in the fishery. We shift from dynamic models of entry and exit of vessels to focus on fisher entry. We focus on within-firm investment but not on-between firm investments. In particular, we focus on first-time fishery owners, who embody renewal of owners operating in the French Atlantic fishery and are hypothesised to high levels of capital constraints. These first entry owners represent the majority (about 90%) of owner entries in the French Atlantic fleet whilst owners entering for the second time or more represent a minority (Quillérou and Guyader, 2012, Tables 2 &3). This study is complementary to the description of the French fleet vessel and owner movements by [START_REF] Quillérou | What Is Behind Fleet Evolution: A Framework for Flow Analysis and Application to the French Atlantic Fleet[END_REF] and the study of second-hand market trade flows along the French coastline by Quillérou, Roudaut, and Guyader (in review).

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We develop a logit model using 20 years of second-hand vessel trade data. As a novel approach we supplement our entry model with indicators of the first-time owner's place in a vessel trade network and use network statistics as explanatory variables in our entry model. We hypothesize that the lack of integration into a second-hand trade network and increased capital constraint explain first time entry through the second-hand vessel market. By better understanding the potential role of trade networks and the capital constraints placed on first-time owners into the fishing sector through the second-hand vessel market, we can suggest policy reforms and alternative measures to encourage entry of fishers into the sector.

Theory and methodology

We use a utility maximisation framework to explain the economic behaviour of firsttime owners in the second-hand vessel market and consequently the French Atlantic fisheries. It is theorised that first-time second-hand vessel buyers seek to maximise utility with respect to entering the fishery. In our model the utility derived from entering the fishery through the second-hand vessel market can be explained by attributes of the vessel purchase, attributes specific to the individual decision maker, and their 'place' in the trade network.

A stochastic utility model of entry choice can be developed where the utility of the choice alternatives (i which run from 1-n) depend on the characteristics of the purchase and the attributes of the buyer (k) including their place in the trade network. We apply a logit analysis to estimate the probability of k choosing alternative j. The logistic distribution is given by [START_REF] Mcfadden | Conditional logit analysis of qualitative choice behaviour[END_REF]:

)] ( exp[ )] ( exp[ i k j k k j x v x v P = (1) M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT 9
The binary logit model predicts probabilities that fall between zero and one by using an S-shaped cumulative density function (CDF) to transform the dichotomous 0-1 dependent variable. The cumulative logistic probability function is specified as:

i Z i e P - + = 1 1 (2)
where e is the base of natural logarithms and Z i = α + βX, α and β are the estimated parameters of the logit model and X is a vector of explanatory variables. The dependent variable in the regression equation is the natural logarithm of the odds that the secondhand vessel buyer is a first-time owner and the right hand side of the regression is linear in the parameters of the model.

Our model is developed using data available from Ifremer's Fisheries Information System (IFREMER 2010) including European fleet register data, vessel activity, and fleet segment. For the second-hand vessel transaction prices and owner and buyer information we use information for vessels registered in the French Atlantic from 1992 to 2010. We estimate what determines the probability that an owner buying a vessel on the second-hand market is a first-time owner. We consider measures of capacity (vessel characteristics and fleet segments as proxy for gear), prices, network integration and family connections, and geographic region. Network integration refers to integration into the second-hand market: first-time owners are typically not integrated with integration increasing with the number of second-hand trade transactions for a given owner. Family connections refer to a shared family name between buyer and seller. In buyer and seller is not available and this type of buyer-seller connection is not included in our study. Regional and time dummies are included to control for spatial and time patterns in capital constraints. Depreciation is captured by vessel age and starts immediately because of the stochasticity of natural resource stock [START_REF] Singh | Fisheries management with stock growth uncertainty and costly capital adjustment[END_REF]. All these determinants relate to the physical and some immaterial capital constraint on fishers for investment into means of production (as defined by

Nøstbakken, Thébaud, and Sørensen 2011). Additionally, constant vessel prices can also capture some of capital constraint faced by fishers as shown in [START_REF] Daurès | Estimating capital value and depreciation of fishing fleets: application to French fisheries[END_REF] and [START_REF] Guyader | Decommisioning schemes and capacity adjustement : A preliminary analysis if the French experience[END_REF]. Capital constraint is typically greater for first entry owners. We thus assume greater capital constraints on first entry fishers for greater capacities and prices, lower network integration and no family connections to the seller. We use R (version 2.8.1) to format the data and perform simple statistical analyses, and use Systat (version 8.0) to develop our logit model.

As mentioned above, in our vector of explanatory variables we include statistical indicators of each first entry vessel buyers place in the trade network. We use a network analysis approach to calculate statistical indicators for each individual trader in the second-hand vessel market. Network analysis is an area of research originating in the biological sciences but made famous by analysis of human social systems (e.g. [START_REF] Milgram | The small world problem[END_REF]). Network theory and associated analysis explains the characteristics of a system of connected individuals and the implications of these connections, providing insight into different social processes (e.g. [START_REF] Glaeser | Crime and social interaction[END_REF][START_REF] Burk | Beyond dyadic interdependence: Actor-oriented models for co-evolving social networks and individual behaviors[END_REF][START_REF] Oetting | Primary Socialization Theory: the Etiology of Drug Use and Deviance[END_REF][START_REF] Barabási | Evolution of the social network of scientific collaborations[END_REF]. The connections between individuals (also referred to as actors or nodes) in a

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network can be many things including a market exchanges and trade (e.g. [START_REF] Cook | Two approaches to social structure: Exchange theory and network analysis[END_REF][START_REF] Jackson | Social and economic networks[END_REF]. Social networks where shown to affect trade in the Marseille fish market [START_REF] Kirman | Market organization and individual behaviour: Evidence from fish markets[END_REF][START_REF] Weisbuch | Market organization[END_REF]. When demand outstripped supply it was beneficial for a buyer to establish a relationship with just one (large) seller to ensure supply. At other times, when the catch was large and shopping around resulted in a better price, buyer loyalty to one particular seller was not so evident. Predictability was therefore central to the fish market's repeat relationships [START_REF] Weisbuch | Market organization[END_REF].

In our study we map the second-hand vessel trades between market participants for the French Atlantic fishing fleet. Statistical indicators for each market trader (Table 1) in the network are generated using Cytoscape (version 2.6.2). For instance, edge count (connectivity) indicates the number of connections of an individual to the rest of the network. The greater the value, the more connected an individual is.

<< Table 1 approximately here >>

We include the statistical network indicators [START_REF] Freeman | Centrality in social networks: ii. Experimental results[END_REF][START_REF] Putten Van | Network analysis of a rock lobster quota lease market[END_REF]NetworkAnalyser 2009;[START_REF] Brandes | A faster algorithm for betweenness centrality[END_REF][START_REF] Watts | Collective dynamics of small world networks[END_REF][START_REF] Barabási | Emergence of scaling in random networks[END_REF], shown above, as it is theoretically recognised that social context is an important determinant of economic behaviour in markets [START_REF] Fligstein | The sociology of markets[END_REF]. 'Social exchange theory', provides the theoretical foundation for social network analysis of markets. Social exchange theory focuses on phenomena that economic exchange theory treats as indeterminate, such as power relationships and equity [START_REF] Cook | Power, Equity and Commitment in Exchange Networks[END_REF]. In traditional neoclassical 'economic exchange theory', markets are rational and perfectly competitive, which means that exchange partners have no commitment to each other. However, often a variety of observed

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12 phenomena cannot easily be explained by simply applying the principles of 'economic exchange theory' [START_REF] Jackson | Social and economic networks[END_REF]. Since [START_REF] Granovetter | Economic Action and Social Structure: The Problem of Embeddedness[END_REF] many studies have looked at the moderating effect of relationships among agents in market exchanges [START_REF] Rauch | Networks and markets: Concepts for bridging disciplines[END_REF] and used social exchange theory to help predict the effect of loyalties or longitudinal commitments on market exchanges [START_REF] Cook | Power, Equity and Commitment in Exchange Networks[END_REF][START_REF] Myers | The dynamics of a labor market[END_REF][START_REF] Rees | Workers in an urban labor market[END_REF][START_REF] Kim | Networks, information transfer, and status conferral: The role of social capital in income stratification among lawyers[END_REF][START_REF] Katz | Personal Influence: The Part Played by People in the Flow of Mass Communication[END_REF]. Social and ethnographic patterns in fisheries suggest that tight social networks exist (e.g. [START_REF] Gatewood | Cooperation, competition, and synergy: Information-sharing groups among southeast Alaskan salmon seiners[END_REF][START_REF] Palmer | Kin-selection, reciprocal altruism, and information sharing among Maine Lobstermen[END_REF]. 'Social exchange theory' predicts that these social networks may extend to influence trade in associated markets.

Data

A general description of the French Atlantic fishery fleet and owners can be found in [START_REF] Quillérou | What Is Behind Fleet Evolution: A Framework for Flow Analysis and Application to the French Atlantic Fleet[END_REF]. As the access licence in this fleet is tied to the vessel, we are able to model fishery entry by virtue of vessel trade data. A total number of 4,238 second-hand vessels were traded between 1992 and 2010. There were 4,923 individuals who participated in the second-hand vessel trade 4 . Consistent with the findings of [START_REF] Quillérou | Analyse statistique du fonctionnement du marché des navires d'occasion et de la dynamique associée des flottilles[END_REF], three relatively distinct time periods between 1992 and 2010 can be identified, each characterised by either a policy change or other significant external event. For instance, between 1992 and 1997 the fisheries are recovering from the 1993 "fishing crisis" [START_REF] Mesnil | Public-aided crises in the French fishing sector[END_REF]). In the next period (between 1998 and 2004) we observe the surge in confidence after the fishing crisis. This period is characterised by an increase in average second-hand vessel prices (Figure 1). The last period between 2005 and 2010 is characterised by a downward trend in prices and a decrease in the number of exchanges on the second-hand market, especially for vessels over 18 meters.

<< Figure 1 approximately here >>

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The average transaction value between 1992 and 2010 was €144,199 (median €76,747) per second-hand vessel, and the average price per engine power was €932.77/kW (median €957.62) 5 . The average value of traded vessels starts to rise around 2001 and peaks around 2004 increasing by more than 50%.

There are more small vessels than larger vessels traded, which is consistent with the fleet composition (14% of the Atlantic fleet is made of vessels longer than 18 meters).

The patterns for larger vessels (longer than 18 meters), that make up 7.3 percent of the total trade (308), is a little different. After an initial decline in second-hand vessel value after 1992, there was a subsequent but temporary increase of the value of larger vessels, declining again to 1992 levels by 2010. As expected, the average price at which these larger vessels are traded is significantly higher (average €504,830, median €495,136).

Vessel sale prices are a function of vessel length and engine power (see [START_REF] Daurès | Estimating capital value and depreciation of fishing fleets: application to French fisheries[END_REF] 6 . However, for vessels longer than 18 meters this relationship is not so obvious, with a correlation of 0.3421 between price and vessels length and 0.4168 between price and engine power. This is because bigger vessels have become less profitable (rising fuel costs and decreases in fish stocks). The average age of traded vessels has increased in a linear fashion (at 5.6% per annum, R 2 = 0.948) and buyers of second-hand vessels are now paying relatively more than before for older vessels, a result also found in other studies [START_REF] Adland | Ship valuation using cross-sectional sales data: A multivariate non-parametric approach[END_REF][START_REF] Quillérou | Analyse statistique du fonctionnement du marché des navires d'occasion et de la dynamique associée des flottilles[END_REF]. This suggests that rising costs and lower harvests have been offset by the decrease in overcapacity making individual vessels more profitable.

Besides information on the sale price and vessel characteristics we also have information on the buyers and sellers which shows that trade is mainly concentrated in South and North Bretagne (45% of all trade) 7 . The majority of second-hand vessel trade

M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT 14 (66%
) is between buyers and seller registered in the same region 8 . As a group, traders in second-hand vessels are getting older by 0.381 years per annum (R 2 = 0.859) on average. As expected, the buyers of second-hand vessels are younger than the sellers by an average of 6.61 years 9 .

There is little regional variation in the proportion of first entry buyers in relation to the total number of traders in the respective regions 10 . The number of first entry buyers varies between 44 in 2010 and 171 in 1997 and appears to be an exponentially declining (y = 178.49e -0.0447x , R 2 = 0.5296, n=2,277). The decline in first entry buyers seems to be at an even faster rate in the trade in large vessel (y = 23.551e -0.0899x , R 2 = 0.5867, n=210).

Even though there are relatively few fishers in the younger age bracket of up to 30 years (making up 12% of the total), they are more active participants in second-hand vessel trade as a higher proportion of these individual in this age bracket not only buy vessels but later also sell them and buy new ones again. Also, fishers have to retire by law when they are 54 years old.

We use the following variables in the first-time fisher entry model through purchase of second-hand vessels for the French Atlantic fisheries (Table 2).

<< Table 2 approximately here >> These variables have been chosen as available proxies of capital levels and values.

We also enter network statistics for all individuals who buy second-hand vessels between 1992 and 2010 as independent variables in our model (Table 3).

<< Table 3 approximately here >>

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Results

We use a stepwise process (Systat 8.0) to determine the significant variables in our firsttime entry model. The first-time entry model is significant at the 5% level and entry behaviour can be explained by a combination of buyer, geographic, vessel, price, and trade network variables (Table 4).

<< Table 4 approximately here >>

McFadden's Rho-Squared, a transformation of the LR statistic intended to mimic an Rsquared, is 0.370. A value between 0.20 and 0.40 is considered satisfactory [START_REF] Hensher | Système d'Informations Halieutiques (SIH)[END_REF]. The model correctly predicts 71.9 percent of the first-time entry choices in the second-hand vessel market. Of the cases where first-time entry is made 73.4% (1,566) are predicted correctly. Of those cases where there is no first-time entry,

Discussion

Our model shows that first-time owners pay significantly lower prices for the secondhand vessels they purchase. This suggests that capital constraints exist for first entry fishers in the Atlantic fishery and that capital is therefore not perfectly malleable [START_REF] Clark | The optimal exploitation of renewable resource stocks: problems of irreversible investment[END_REF][START_REF] Boyce | Optimal capital accumulation in a fishery: A nonlinear irreversible investment model[END_REF].

Contrary to prior expectations, capital constraints for first-time owners are not significantly reduced by the first-time owner's family connections to the seller.

Moreover, our model suggests that the first-time owner's connections in the market place for second-hand vessels have a significant effect on the probability of entry. Firsttime owners do not seem strongly included in a vessel trade network when they enter the fishing sector in contrast to other buyers. This is consistent with the development in time of a personal social network [START_REF] Lorenz | Neither friends nor strangers: Informal networks of subcontracting in French industries[END_REF][START_REF] Knoke | Network analysis: Basic concepts[END_REF]. The lack of trade connections for first-time owners, as determined by the network variables included in our model, also indicate no significant reduction in capital constraints. Firsttime owners are however more likely to buy a vessel from a seller who is resident in the same region. This suggests that first-time entry of owners occurs through access to more information at the more local level rather than by means of integration into a trading network or explicitly through family connections.

Like any other capital investment fishing vessels are subject to depreciation. Secondhand vessels are therefore, on the whole, lower priced than new vessels. Cheaper There are some regional implications from the characteristics of second-hand vessel trades and consequent industry renewal. Our model shows that renewal in the French Atlantic fishery tends to be concentrated in one particular region, which is North Bretagne. This result is confirmed by [START_REF] Quillérou | Analyse statistique du fonctionnement du marché des navires d'occasion et de la dynamique associée des flottilles[END_REF] support increased interaction between second-hand vessel buyers and sellers, facilitate first-time owners integration into the network, and thus decrease capital constraints for first-time buyers. However, removing decommissioning subsidies might be more costeffective in terms of public spending than subsidising first-time owners because of the reduction in the rent captured from decommissioning schemes [START_REF] Guyader | Decommisioning schemes and capacity adjustement : A preliminary analysis if the French experience[END_REF].

Conclusions

Fisheries research in the past decades has focused mainly on developing incentives and management approaches to reduce fishing capacity. Increasingly, concerns are raised in relation to a lack of renewal in the fishing sector of both vessels and owners. It is suggested that capital investment including fishing vessels purchase, or quota in the case of ITQ managed fisheries, is perceived to be prohibitively high and discouraging first-time owners into fisheries.

We find evidence that first-time owners buying vessels on the second-hand market for entry in the fishing sector are more capital constrained than fishers already trading on the second-hand market. Capital constraints are reduced by geographical proximity and increased integration into a trading network. Access to information on vessels and fishing is key in the decision to enter the fishing sector for the first time. Financial support for set up of (formal or informal) forums that support increased interaction between second-hand vessel buyers and sellers and facilitate first-time owners integration into the network could also help reduce the capital constraint of firsttime buyers. However, removing decommissioning subsidies might be more costeffective in terms of public spending than subsidising first-time owners. Removing these decommissioning subsidies removes the rent from decommissioning schemes captured into second-hand market prices. Removing these price distortions would therefore be more economically efficient as well as help first-time buyers buy their first fishing vessel.

One of the limitations of this study is that we do not have information about the actual relationship between first-time owners and the sellers of vessels other than through second-hand market trade. Although we do know that kinship relations did not explain first-time entry into the second-hand vessel market in our model some other relationships could exist that are not captured here, for example between a former crew member and an existing owner. Extending this current research and to map the effects of the largely unknown 'working relationships' in vessel trades, will be necessary to fully understand renewal in fisheries.

  for these price increases 2 . Since 2002 both the number of vessels exchanged on the second-hand vessel market and the number of owners exchanging second-hand vessels have decreased. However, since 2002 the price per kW has doubled despite the reduction in the number of vessel exchanges taking place.

France, wives take

  the name of their husband as their family name and children take the last name of their father. Testing for trade based on common family names would capture father-son trades or trade between male cousins or uncle-nephew (or with . Information on working relationship connections between

  70.2%(1,338) are predicted correctly 11 .The success indicator signifies the improvement the model shows over a purely random model that assigned the same probability of first-time entry in the second-hand vessel market to every observation in the data. The model produces a gain of 0.205 over the random model for responses and 0.230 for reference cases. The odds of the response are given by p/(1-p), where p is the probability of response, and the odds ratio is the multiplicative factor by which the odds change when the independent variable increases by one unit. For example, the buyer and seller being in the same geographic (B_S_SAME_REG) region increases the odds of a first-time entry into the second-hand vessel market by multiplicative factor of 1.545, with lower and upper confidence bounds of 1.297 and 1.840 respectively. , the probability that the owner enters into the fishing sector for the first-time significantly decreases with lower owner age (B_AGE) and with less time spent in the industry (B_YRININDUST). Older fishers who have been in the industry for longer are less likely to enter for the first-time in the fishing sector with a second-hand vessel. We also tested for the influence of family relationships i.e. o whether buyer and seller share the same last name (B_FAM_TRADE). Contrary to prior expectations; family relations did not have a significant effect on first-time entry. The characteristics of the seller of the vessels, for instance the fact that they were exiting the fishery (S_PERM-EXIT), did not have any explanatory power in our model 12 . First-time owners are more likely to purchase an older vessel (VESSEL_AGE) for a lower price (PR_EUR000_DE). The horsepower of the vessel (VESSEL_kW) was not significant in our model and did not explain first entry into the fishery. The probability of entering the fishery increases if the buyer is in North Bretagne and decreases if the buyer is in Aquitaine or Pays de la Loire. Three of the seven network statistics were significant in explaining first-time entry into the French Atlantic fisheries through purchase of a second-hand vessel. As expected, first-time owners had lower closeness centrality (B_NW_ClC), eccentricity (B_NW_ECC), and edge count (B_NW_EDG). All network statistics significant in our model indicate that first-time owners are less connected and less 'embedded' in the trade network for second-hand vessels. The inclusion of network statistics improved the predictive accuracy of our model with a McFadden's Rho-Squared of 0

  second-hand vessels are an important point of entry into a fishery. This is particularly true as our study shows that first-time owners are typically younger and are more restricted in obtaining investment capital. As illustrated, first-time owners are more older (cheaper) vessels. This typically reflects the lower potential access to capital and investment opportunities of first-time owners[START_REF] Martin | Résultats économiques des flottilles artisanales bretonnes: une vue synthétique à partir des données de l'observatoire économique régional des pêches[END_REF].

  buy vessels could help new owners to enter the fishing industry.

  and Quillérou, Roudaut, and Guyader (in review) suggesting both vessel and owner renewal in this region through the operation of the second-hand vessel market. North Bretagne is also the most profitable fishing region[START_REF] Floch | Une évaluation des performances économiques de la pêche côtière : le cas de la région Bretagne[END_REF][START_REF] Martin | Résultats économiques des flottilles artisanales bretonnes: une vue synthétique à partir des données de l'observatoire économique régional des pêches[END_REF] and is an area that obviously attracts first-time owners who bring second-hand vessels into the area that they may have purchased elsewhere. Also, Bretagne has historically been associated with small fishing vessels and small fishing harbours. This image is still very strong in the public mind. The region has thus set up policies to actively encourage sector renewal. This is most prominent in North Bretagne as South Bretagne has developed other economic activities (e.g. recreational boating). There are fewer firsttime owners in Aquitaine and Pays de la Loire which are both to the South of Bretagne. be established as part of the 2013 European Union Fishery Policy reform. Alternatively, subsidies could help set up (formal or informal) forums that

		ACCEPTED MANUSCRIPT
	fishery communities which are highly dependent on fishing and with limited alternative
	economic activities (Commission of the European Communities 2009, section 5.1;
	European Commission 2011, sections 2.2 & 2.3). Targeted subsidies for first-time
	vessel buyers could	M A N U S C R I P T
	Even though Aquitaine is a region that attracts second-hand fishing vessels (Quillérou et al. 2011) and is a profitable fishing region, it tends to favour higher levels of foreign (Spanish) investment into the French vessels rather than entry of first-time owners into the sector 13 . Fisheries organisations and government institutions have suggested that financial A C C E P T E D
	support to buy vessels could help new owners to enter the fishing industry. Our findings
	that first-time owners are capital constrained suggest that this policy initiative should
	assist in achieving industry renewal. This would be particularly important in small scale
		19

Acknowledgements

We are grateful to the three anonymous reviewers for their constructive suggestions. We would like to thank Dr Katia Frangoudes, Dr Rémi Mongruel and the rest of the AMURE team for their critical insights into French fisheries, as well as Michèle

2 Causal relationships are difficult to derive here. 3 It is not possible to quantify this more specifically because of the lack of specific data. 4 The number of participants is greater than the number of trade interactions because if the trade is simply between two people, this is counted as one trade interaction and two trade participants. 5 All values are in Euro and have been deflated to 2010 values. 6 The correlation is 0.7561 between price and length and 0.7613 between price and engine power.

Obviously there is also a relationship between length and engine power (correlation of 0.9211 for all vessels and 0.7332 for larger vessels).

7 Some geographic information prior to 2004 is missing. 8 There is a slight overestimation as some buyers are also sellers of second-hand vessels in subsequent years. 9 Correlation between the average age of sellers and buyers time series is 0.867. 10 We find that for vessels greater than 18 meters there are a relatively higher number of first entry buyers (0.68% as opposed to 0.54% of the total number of buyers) but in terms of age distribution these buyers of larger vessels do not appear different to the overall sample.

11 This includes where an owner enters the market for a second (or more) time.

12 None of the seller characteristics, such as seller age and time in the fishery, were significant at the 5 percent level. 13 New owners might enter into the Aquitaine fishing sector by buying newly built fishing vessels, but this would need to be tested separately.


Emmanuelle Quillérou
email: emmanuelle_quillerou@yahoo.fr

Olivier Guyader

What is behind fleet evolution: a framework for flow analysis and application to the French Atlantic fleet

Keywords: capacity dynamics, capacity reduction, fishery management, owner flows, policy targeting, vessel flows

The study of fishery dynamics considers national-level fleet evolution. It has, however, failed to consider the flows behind fleet evolution as well as the impact of the dynamics of owners of invested capital on fleet evolution. This paper establishes a general conceptual framework which identifies different vessel and owner flows behind fleet evolution and some relationships between these flows. This descriptive conceptual framework aims to change the current focus on drivers of fleet evolution to drivers of the flows behind fleet evolution. We identify a direct impact of vessel flows on the fleet size and nature, and an indirect impact of the movements of capital owners on the fleet evolution (size and nature). This conceptual framework is illustrated using French Atlantic fleet data over a 15-year period (1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008). It is shown that the identified flows vary in size and nature and therefore impact differently on the fleet evolution. This description also shows some dependence of vessel flows on owner dynamics. This relationship should be better taken into account for more effective capacity management.

3/35 1. INTRODUCTION

Current shortfalls in fisheries management suggest there is a need to better understand fleet dynamics [START_REF] Fulton | Human behaviour: the key source of uncertainty in fisheries management[END_REF]. If the study of fisheries dynamics increasingly seeks to take into account the evolution of fishing fleets and their pressure on ecosystems, the main mechanisms behind fleet evolution at the local, national or international levels are often not studied or only partially studied [START_REF] Salas | The behavioural dynamics of fishers: management implications[END_REF][START_REF] Garcia | Gloom and Doom? The Future of Marine Capture Fisheries[END_REF], FAO, 2010). This largely stems from a lack of data availability on fleet evolution for most fisheries as well as the lack of a complete and explicitly defined framework for analysis. This paper focuses on the latter.

Most developed country fleets are monitored following overcapacity concerns. In particular, open access fisheries are typically characterised by only partly used vessels and this unused potential effort constitutes overcapacity. Even when fleets are managed with the objective of preserving fish stocks, using a Total Allowable Catch and quota system, fleet dynamics remain a concern for resource rent maximisation and more economically optimal fishery management. Overcapacity reduces the economic rent extracted by each vessel operating in the fleet and has been identified as a major factor leading to overfishing (FAO, 2010). An International Plan of Action for the Management of Fishing Capacity has been implemented since 1999 (FAO, 1999).

Fishing capacity should, in theory, be measured as the maximum output potentially produced from given inputs in the fishery (as recommended by [START_REF] Gréboval | Managing Fishing Capacity: Selected Papers on Underlying Concepts and Issues[END_REF]. In practice however, the number of inputs (e.g. number of vessels, their tonnage and engine power) is largely used by policy-makers as a measure for capacity (Pascoe, 4/35 2007). This capacity input-approach has so far inspired the design of many fleet monitoring tools, e.g. the Fleet Register of the European Common Fisheries Policy [START_REF] Cueff | A Case Study of Fishing Vessel Capacity Management Public Buyout Schemes: Community Experience Through the Multi-Annual Guidance Programmes and Ways Forward[END_REF]. These fleet monitoring tools record simple measures of fleet evolution through the number of vessels and their characteristics (length, power, tonnage). This descriptive data is viewed as less politically sensitive and is more easily made publicly available.

Parallel to fleet monitoring, policies targeting fishing capacity reduction typically restrict vessel entry in the fishery whilst targeting an increase in vessel exits. Barriers to entry have been implemented through mandatory access right or permits to fish (licences) complemented by input-control measures such gear restrictions, area limitations, seasonal closures [START_REF] Wilen | Limited Entry Licensing: A Retrospective Assessment[END_REF][START_REF] Townsend | Entry Restrictions in the Fishery: A Survey of the Evidence[END_REF]. In parallel, decommissioning schemes (or buyback programmes) have provided financial incentives for voluntary vessel exit [START_REF] Curtis | Fisheries Buybacks[END_REF]. These capacity management policies have however been shown to be cost-ineffective for fleet capacity reduction [START_REF] Guyader | Simulating the effect of regulatory systems in a fishery -An application to the French driftnet albacore fleet[END_REF][START_REF] Reid | An analysis of fishing capacity in the western and central Pacific Ocean tuna fishery and management implications[END_REF][START_REF] Kirkley | Deterministic and Stochastic Capacity Estimation for Fishery Capacity Reduction[END_REF], Lindebo, 2005a[START_REF] Tingley | Eliminating Excess Capacity: Implications for the Scottish Fishing Industry[END_REF][START_REF] Van Hoof | Capacity Assessment of the Dutch Beam-trawler Fleet using Data Envelopment Analysis (DEA)[END_REF][START_REF] Hoff | Optimal Vessel Quotas and Capacity of a Danish Trawler Fleet Segment: A Dual Approach[END_REF][START_REF] Villasante | Global assessment of the European Union fishing fleet: An update[END_REF]. This limited effectiveness of capacity management programmes has been partly caused by the provision of conflicting subsidy programmes, along with poorly defined policy objectives and institutional weaknesses [START_REF] Caddy | A review of fisheries management past and present and some future perspectives for the third millennium[END_REF]. For example, vessel buyback programmes have been undermined by the parallel provision of subsidies for the construction or modernisation of vessels (Lindebo, 2005b[START_REF] Sumaila | The world trade organization and global fisheries sustainability[END_REF][START_REF] Mesnil | Public-aided crises in the French fishing sector[END_REF].

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Also, and more importantly, entry and exit policies are based on incentives to change the size of established flows of capital (increase exit flows and decrease entry flow).

The underlying incentive structure for investment decision is thus left relatively unchanged by current entry and exit policies, and has been identified as the major cause for overcapitalisation [START_REF] Wilen | Limited Entry Licensing: A Retrospective Assessment[END_REF][START_REF] Townsend | Entry Restrictions in the Fishery: A Survey of the Evidence[END_REF][START_REF] Espino | Capacity and Capacity Utilization of the "Voracera" Fleet in the Strait of Gibraltar[END_REF][START_REF] Grafton | Incentive-based approaches to sustainable fisheries[END_REF][START_REF] Anderson | Does Capacity Analysis Help us Meet Fishery Policy and Management Objectives? Comments[END_REF][START_REF] Asche | Capacity Measurement in Fisheries: What Can We Learn?[END_REF][START_REF] Cox | Capacity Analysis and Fisheries Management: Is the Tail Wagging the Dog?[END_REF][START_REF] Wilen | Thoughts on Capacity Analysis: Is Capacity Analysis Giving Policy Makers Information they Need?[END_REF]. The incentive instruments advocated in the literature as successfully changing capital investment incentives by better aligning them with harvesting decisions so far have been either

Individual Transferable Quotas (ITQ) or taxes [START_REF] Jensen | Investment behavior and tax policy[END_REF][START_REF] Asche | Fisher's behaviour with individual vessel quotas -Over-capacity and potential rent: Five case studies[END_REF][START_REF] Squires | Controlling excess capacity in common-pool resource industries: the transition from input to output controls[END_REF]. These incentive instruments might, however, not always be sufficient in fully reducing overcapacity depending on the broader context, transaction costs of implementation, and the time horizon considered [START_REF] Whitmarsh | The Fisheries Treadmill[END_REF][START_REF] Asche | Fisher's behaviour with individual vessel quotas -Over-capacity and potential rent: Five case studies[END_REF][START_REF] Townsend | Transactions costs as an obstacle to fisheries self-governance in New Zealand[END_REF]. These economic instruments have so far, not been formally implemented under a nationally uniform and transparent system in France.

Conceptual studies of capital dynamics in fisheries have aimed to determine either optimal investment paths towards desirable levels of capital or changes in investment behaviour because of incentives created by economic and regulatory circumstances [START_REF] Nostbakken | Investment Behaviour and Capacity Adjustment in Fisheries: A Survey of the Literature[END_REF]. Fishers are decision-makers in relation to investments into fishing capital and are therefore sensitive to incentives. These incentives encompass incentives for keeping or removing their vessels from the fleet, but also their own entry or exit into the fishing sector. Fishers' behaviour is a key source of uncertainty in fisheries management [START_REF] Fulton | Human behaviour: the key source of uncertainty in fisheries management[END_REF]. It is however rarely analysed in operational decision-making tools for fisheries management support. The academic literature on 6/35 investment in fisheries or entry-exit models has so far focused on vessels only. Several decision-making models of vessel entries and exits have been established in the literature. These models show that vessel entry and exit decisions depend on potential profitability, alternative fishery, crowding externality, resource abundance, some vessel characteristics such as age and size, and less often on the availability of decommissioning scheme [START_REF] Bjorndal | Capital Dynamics in the North Sea Herring Fishery[END_REF][START_REF] Pradhan | Modeling entry, stay, and exit decisions of the longline fishers in Hawaii[END_REF][START_REF] Mardle | Empirical analysis of fishing fleet dynamics: entry, stay and exit choices in selected fisheries Bioecon conference[END_REF][START_REF] Tidd | Exit and entry of fishing vessels: an evaluation of factors affecting investment decisions in the North Sea English beam trawl fleet[END_REF]. Vessel entry-exit models are however limited.

They have allowed to characterise the direction of change (qualitative) rather than its magnitude (quantitative) (TECTAC, 2005, p110, 114-116). They have considered some owner's characteristics such as age but failed to explicitly consider the owners' own entries and exits from the fishing sector as a determinant of the decision to enter or exit vessels, which in turn impacts on the fleet size and structure. The implication is that considering owner movements might help improve predictions of models of entry and exit of vessels from the fleet.

Within the fleet, fishers can also trade their vessels on the second-hand market. These transactions are very often associated with investment in upgrading existing vessel capacity. These capacity changes are most obvious when leading to vessels changing in fleet segments. In France, second-hand markets are geographically limited, although they have allowed some redistribution of the fleet towards Aquitaine and Northern France between 1992 and 2009 [START_REF] Quillérou | Managing fleet capacity: national policies and regional market redistribution[END_REF]. Buyers and sellers find one another mostly through local channels of information such as direct contact, through other fishers, newspapers, fishers associations, producer organisations, accounting centres. Internet websites have recently become popular for advertising sales. Contrary

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to smaller vessels, bigger (more expensive) vessels tend to be traded through intermediaries (brokers). It is not possible to quantify this more specifically in France because of the lack of specific data.

In relation to the shortfalls of the current capacity management policies and incentive structure provided, there is a need for a better description of what is happening below the fleet level considered by national policies. This more complete approach to capacity analysis considers both vessels and owners flows. This approach sets the scene for improved assessment of what drives investment into fishing capacity taking an owner's point of view. It also provides a simple framework for operational decision-making tools for fisheries management support and assessing the fleet's economic efficiency. It could also help better evaluate different capacity management measures and better inform the design of public policies.

The aim of this paper is consequently to establish an integrated framework to decompose the evolution of fleet capacity. This framework adopts a very generic approach by considering a group of vessels as the evolving fleet (here within a common geographical area) and a generic unit of capacity (vessel numbers, power, or tonnage).

This framework can be used to describe different fleet evolutions in different management contexts as data on vessels and their owners is publicly available in most fleet registers.

The integrated framework identifies the vessel and owner flows underlying the evolution of fleet capacity (in size and nature) and is designed for a given group of 8/35 vessels (here within the same geographical unit for illustration purposes). For illustration purposes, fleet capacity is measured by vessel numbers in this paper. This framework is based on the consideration of both direct and indirect impacts on fleet capacity from vessel flows and owners' flows. This framework outlines the need to consider the owner's decision-making for vessels entry and exits, but also behind their own entry into and exit from the fishing sector. These flows are further decomposed along different types of entries and exits. This framework is detailed using French Atlantic fleet data, with each flow type characterised by its size and nature. This framework is general enough to characterise any fleet capacity evolution, and not only in a context of overcapacity.

Supply of second-hand vessels depends on the size of entry flows relative to exit flows, as well as on the number of owners leaving the fleet. Demand in vessels depends on fishery productivity and owners' entries into the fishing sector. The different vessel and owners' flows will impact vessel supply and demand, with asymmetric impacts on entry, exit and the second-hand market. The analysis of both direct and indirect impacts could thus help derive a better understanding of what determines vessel entry, exit and market exchange. This framework aims to allow a simple approach for preliminary economic analysis of fleets that are not yet subject to systematic capacity monitoring. This framework should help to better understand fleet capacity dynamics, improve policy evaluations and inform policy design for more effective capacity management. It is applied on the French fishing vessel fleet as data on vessel and owners flows was available.

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In the introduction we described the general policy context, identified the shortfalls of the current literature, and detailed the approach taken in this paper. The next section details the proposed conceptual framework for fleet evolution analysis for a given group of vessels (Method). The section that follows details the French policy context, the data used in the empirical analysis and the evolutions of vessels and owners numbers observed between 1994 and 2008 (Material). The fourth and fifth sections detail the empirical application of the conceptual framework (Results). They illustrate respectively the vessel and owner flows identified in the conceptual framework. These flows are characterised both by their magnitude (number of vessels or owners) and nature (types of vessel or owners). The section on indirect impacts also describes the vessel flows associated to each owner's flow. The last section discusses implications from our results and concludes.

CONCEPTUAL FRAMEWORK TO ESTABLISH A TYPOLOGY OF VESSEL AND OWNER FLOWS IN RELATION TO FLEET

EVOLUTION

This descriptive analysis is based on a novel conceptualisation of a measure of vessel capacity and number of owners (population), graphically represented in Figure 1. The conceptual framework of this paper provides the basis for deriving a typology for both vessel and owner flows. These flows will in particular impact on the size and nature of the fleet for a given unit of reference.

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This conceptual framework is established for a given perfectly defined group of vessels as the reference unit of interest. For description purposes, we take this group of vessels to belong to the same geographical unit of analysis. This geographical unit is defined according to the analysis scale of interest, e.g. a fishing harbour, district, administrative region or country. It should be noted that the empirical section of this paper uses a landbased geographical unit i.e. it is not related to the actual fishing area but to the place of vessel registration. This conceptual framework could similarly be used to describe capacity movements for given fishing grounds or fishing stocks and is therefore not restricted to land-based units. This analysis attempts to identify the flows behind the fleet changes within this given geographical unit. This framework does, however, not attempt to describe the flows between two specific geographical units, nor identify the drivers behind the identified flows. Also, the empirical part of this paper considers vessel numbers as measure of fishing capacity. This framework could be applied to other measures of fishing capacity (power, tonnage or investment flows) depending on data availability and research question of interest.

In a fleet context, two types of evolutions can be considered: the evolution of of fishing vessels (fleet) and that of the owners of the fishing vessels (clear ellipses in Figure 1).

The fleet considered is contained in the geographical unit of analysis (rectangle on Figure 1). This fishing fleet can be further decomposed into fleet segments. A given fishing segment is relatively homogenous and characterised by a specific vessel length and gear combination (e.g. trawler, seine purse). The dotted-frontier darker ellipsis on 11/35 Flows also arise within the geographical unit (e.g. second-hand trade within the unit), as well as to (entry) and from (exit) the geographical unit. Vessel flows are typically associated with vessel entry (arrow 1 in Figure 1) and vessel exit (arrow 2 in Figure 1). Vessels entering the geographical unit can be decomposed into new builds, vessels imported from other geographical units, and the vessels changing from a non-

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commercial fishing to a fishing activity or vessels resuming their fishing activity after a period of inactivity (Figure 1). Vessels exits from the geographical unit can be decomposed into vessel destructions (subsidised or not), vessels exports to other geographical units or vessels suspending their activity for some time (Figure 1).

In addition, vessel flows within the geographical unit arise with their exchange on the second-hand market (arrow 3 in Figure 1). This exchange will be subject to the supply and demand for second-hand vessels (and their associated fishing entry licences).

Following an exchange on the second-hand market, vessels can change segments, thus affecting the nature of the fleet, or exit the geographical unit (e.g. exported to other geographical units). In some fisheries, fishery licences can also be traded or leased separately from fishing vessels. This separate trade or leasing could also induce changes in fishing capacity and could be associated to different owners' dynamics. This however is not allowed in France and is therefore not further detailed in this paper.

For conceptual simplicity and following the definition of the geographical unit in this paper, all vessels traded on the second-hand market are considered as part of the same geographical unit. This implies that all vessels traded in the second-hand market of a given geographical unit have entered the geographical unit (i.e. as part of the entry flow) before being sold on the second-hand market (where they become part of the exchange flow). The second-hand market trade in a given geographical unit thus does not impact on the overall size of the fleet but can impact on the nature of the fleet by impacting on the vessel allocation between fishing segments.

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To sum up, vessels flows can be categorised as follows within the geographical unit of analysis of interest: entry flows (arrow 1 in Figure 1), exit flows (arrow 2 in Figure 1), and exchange flows (through the second-hand vessel market, arrow 3 in Figure 1). All these flows will affect the size and nature of the fleet across time (total numbers and proportions of each fishing segment), within the considered geographical unit.

Parallel to these vessel flows, the population of owners is also subject to changes because of owner flows. Owners can enter the geographical unit (arrow 4 in Figure 1). It can be a First entry or, if they leave the geographical unit and come back, a Second entry or more (depending on the number of times they appear in the fleet register).

Owners can leave the geographical unit (arrow 5 in Figure 1), Permanently (e.g. when retiring or moving to another geographical unit) or Temporarily (i.e. when they come back to the area at a later date). They can also remain in the same geographical unit and trade on the second-hand market (arrow 8 in Figure 1). These owner and vessel flows are often associated, but do not overlap completely. An owner can enter the geographical unit with the entry of a vessel (new builds, imports or resumed vessel activity). In this case, vessel entries are linked to entry of owners into the geographical unit (arrow 6 in Figure 1). Alternatively, an owner can enter the geographical unit after buying a vessel on the second-hand market of the geographical unit (arrow 7 in Figure 1). In this case, the entry of an owner is not linked to the entry of a vessel, and the fleet does not change within the considered geographical unit. Owners can also change fishing segments by exchanging vessels on the second-hand market (arrow 8 in Figure 1). In this case, there is no entry of owner or vessel in the 14/35 geographical unit, but rather internal changes to the vessel and owner population allocation between segments within the geographical unit. Similarly, an owner can leave the geographical unit through selling a vessel on the second-hand market (arrow 9 in Figure 1). In this case, the exit of an owner is not linked to the exit of a vessel, and the fleet does not change. An owner can exit the geographical unit with the exit of a vessel (destructions, exports or suspended vessel activity). In this context, vessel exits are thus linked to the exit of owners from the geographical unit (arrow 10 in Figure 1). Because of these associations between vessel and owner flows, owners' flows can thus indirectly impact on the fleet. The degree to which vessel flows are linked to owners' flows and the types of vessel and owner flows associated would help refine and extend current models of investment and associated vessel entries/exits. An obvious consequence of the above is that the second-hand market vessel trade is influenced by the number and types of vessels within the geographical unit (arrow 3 in Figure 1), the entry or exit of owners associated with second-hand market transactions (arrows 7 and 9 in Figure 1), or the second-hand trade between owners within the same geographical unit and for the same overall fleet (arrow 8 in Figure 1). The weight of entries and exits relative to the second-hand market trade depends on the geographical scale of analysis: entries and exit flows are likely to dominate smaller geographical units of analysis with a reduced second-hand market. Neighbouring effects between geographical units might also arise for smaller units of analysis, thereby impacting entry and exit (as defined in this paper).

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The above conceptual framework identifies, for a given land-based geographical area, impacts of vessel flows and owner flows on the fleet evolution (size and nature). Direct impact refers to changes in the fleet induced by (direct) vessel flows, and indirect impact refers to changes in the fleet associated with owners flows (indirect impact of owner flows on the fleet). This framework also suggests that vessels flows are not independent from owner flows whilst not being necessarily fully correlated.

The following Sections illustrate the above conceptual framework by taking the French Atlantic fleet as a case study.

POLICY CONTEXT, VESSELS AND OWNER POPULATION IN THE FRENCH ATLANTIC FLEET

To illustrate our conceptual framework, the group of vessels of interest considered here is registered in the French Atlantic. This area is relatively well monitored and has therefore good available data. Vessel numbers are taken as a measure of capacity available across the whole time-period considered.

Fishery policy has been set from the 1970s into the Common Fishery Policy (CFP), a common European framework. Each European Member State is responsible for implementing this common framework. In France, the fishing capacity reduction policies implemented within the Common Fishery Policy have relied on the combination of limited entry and decommissioning schemes. A permit to fish ("Permis de Mise en Exploitation", P.M.E.) has been required from 1988 for fishing vessels to operate (Decision of the "Comité Central des Pêches Maritimes", 22 September 1988).

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This permit to fish is attached to the vessel and cannot be traded separately (as determined by a 1852 decree on maritime fishing practice, "Décret du 9 janvier 1852 sur l'exercice de la pêche maritime"). It is very likely that most vessel scrapping is subsidised by decommissioning schemes, but this was not quantifiable in this study because of the available data.

The geographical unit of analysis is the French Atlantic which covers all land-based maritime districts of the Western French coast i.e. on the North Sea, the English Channel and the Atlantic Ocean.

The data used in this analysis have been collected by Ifremer's Fisheries Observatory from the French Fleet Register. In particular, the data include vessel characteristics [START_REF] Van Iseghem | Ensuring representative economic data: survey data-collection methods in France for implementing the Common Fisheries Policy[END_REF]. Deducting the fuel costs and variable costs from the gross revenue and dividing them by the number of crew members leads to rough estimates of crew remuneration (Euro/full-time equivalent crew member). These estimates are around 20,000 Euro for small vessel segments (<10m), and much higher for larger vessels. Smaller vessels hardly remunerate the fishers compared to unemployment benefits. Economic behaviour for entry and exit of these vessels might differ from larger vessels. This paper considers overall entry and exits regardless of fleet segments.

The summary statistics used in the following Sections to illustrate the conceptual framework have been produced from this specific dataset.

EMPIRICAL APPLICATION: DIRECT IMPACT OF VESSEL FLOWS ON THE FRENCH ATLANTIC FLEET

In this paper, the fleet considered is measured in terms of vessel numbers to illustrate the conceptual framework, from 1994 to 2008.

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From 1994 to 2008, a total number of 1,415 vessels entered the French Atlantic fleet of which 718 (51%) were constructed, 600 (42%) resumed their activity and 97 (7%) were imported (from other oceans or countries). In the same period, a total number of 2,814 vessels left the French Atlantic fleet of which 1,464 (52%) were scrapped, 1,183 (42%) suspended their activity and 167 (6%) were exported (to other oceans or countries).

These numbers are represented in Figure 3. A total of 2,940 vessels have been exchanged over 1994-2008 on the Atlantic fleet second-hand market. All these figures are subject to annual variations. Average characteristics of the vessels are summed up for each type of flow in Table 1.

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A net total of 1,399 vessels left the French Atlantic from 1994 to 2008 from this analysis, which corresponds to 97% of the overall decrease in fleet size described in the previous section. The other 3% correspond to missing data on the types of vessel entry or exit. There are some marked differences in the vessel flow size and vessel characteristics across the different vessel flows. The fleet evolution (size and nature)

would thus depend relative size of the different vessel entries and exits from the geographical area. The structural changes within the fleet could be reinforced by the operation of the second-hand market leading to changes in fleet segments.

These trends are consistent with previous analyses of fleet structure and evolution,

showing an overall decrease in fleet sizes (see for instance the Danish and Dutch fleet analyses by [START_REF] Frost | An appraisal of the effects of the decommissioning scheme in the case of Denmark and the Netherlands[END_REF] the different case studies in [START_REF] Curtis | Fisheries Buybacks[END_REF]. This analysis however identifies different characteristics varying across the flow types. The analysis also shows varying characteristics of fleet activity flows (i.e.

resumed or suspended vessel activity) and of fleet renewal flows (i.e. constructions and destructions). Fleet activity changes do not involve any permanent decision but a temporary suspension of activity and can constitute fleet size adaptations on a relatively short time horizon. Fleet renewal flows however involve new investments and would relate to decisions on the longer run. Fleet segments differ across flows, suggesting technological differences are important determinants for the types of entry and exit [START_REF] Sampson | Fishing Technology and Fleet Dynamics: Predictions from a Bioeconomic Model[END_REF].

Quillérou and Guyader

What Is Behind Fleet Evolution: A Framework for Flow Analysis and Application to the French Atlantic Fleet 22/35

EMPIRICAL APPLICATION: INDIRECT IMPACT OF OWNER FLOWS ON THE FRENCH ATLANTIC FLEET

As shown in Figure 2, and parrallel to the decrease in vessel numbers, the number of owners in the fleet register has decreased less substantially from 3,510 in 1993 to 3,216 in 2008 (by 10%), with the highest number of owners (3,823) in 1999. There was an average increase of 53 owners per year (R 2 =0.96) before 1999, and an average decrease of 68 owners per year (R 2 =0.98) after 1999. Despite the 1993 "fishing crisis" [START_REF] Mesnil | Public-aided crises in the French fishing sector[END_REF], fishers were attracted to the Atlantic fishery then seen as one of the most productive French fisheries. Fishing capital was concentrated after 1999, with more vessels per owner in the fleet on average. This decrease in owners' numbers is mostly due to natural aging of the French population.

From 1994 to 2008, a total number of 3,550 owners have entered the French Atlantic. A huge majority (87%) of these owners have never operated there beforehand (First entry). Over the same period of time, a total number of 3,879 owners have left the French Atlantic, 90% of whom were never to return (Permanent exit). These numbers are represented in Figure 3. All these figures and the owner's average age have been summed up in Table 2.

Quillérou and Guyader

What Is Behind Fleet Evolution: A Framework for Flow Analysis and Application to the French Atlantic Fleet The analysis of entries and exits of owners leads to a net total of 329 owners leaving the French Atlantic between 1994 and 2008, which corresponds to 112% of the decrease observed in Figure 2. This discrepancy arises because of multiple entries and temporary exits. As expected entrants are on average 12.3 years younger than the owners leaving the French Atlantic (Table 2). This suggests a renewal of the owner population thanks to these younger entrants. However, this average hides some marked variations across the owner entry and exit flows combined to specific vessel flows. Models of vessel entries and exits often use owner's age as a dependent variable, with younger vessel owners entering vessels and less young vessel owners more likely to scrap their vessels. Table 3 however shows that vessel destructions (exit) can arise for owners (38.3 year old for those leaving the fishing sector temporarily) younger than owners entering with a newly built vessel (39.6 year old for those entering the fishing sector for the second time or more). The owner's age, unless related to a specific type of vessel movement and its owner behaviour, does therefore not constitute a perfect proxy for vessel entry and exit as used in previous models of vessel entries and exits.

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The decomposition of the flows of owners and the owner's average age have been summed up in Table 3. All these figures show that the majority (91%) of first entry owners have entered with second-hand vessels. 75% of Permanent exit owners sold their vessels on the second hand market. This is the same for owners for whom this is not the first entry or who temporary exit the fishery. 3.

In summary, there are some marked differences in the owner characteristics for each owner flow and across vessel flow types for a given owner flow. Sellers' (buyers') age will typically impact on supply (demand) of second-hand vessels, with older owners more likely to leave the fishing sector and increase supply of second-hand vessels. The vessel owner's age, as an underlying determinant for their own behaviours (entry and exit) and choices of vessel entry and exit, would consequently influence the vessel trade.

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MANAGEMENT

Following the shortfalls of recent capacity management policies, a more complete framework needed to be derived to better understand fleet dynamics and increase the fisheries economic efficiency. The framework described is based on an analysis of flows impacting fleet for a given geographical area. This framework allows to exhaustively identify and quantify the impact on the fleet of different types of flows.

This framework has allowed to identify a combination of direct impacts of vessel flows on the fleet and indirect impacts of owners' flows. This analysis showed marked differences in the size and nature of entry and exit flows of vessels and owners.

Data for the French Atlantic over 1994-2008 have been used to illustrate both types of impacts. This analysis outlined that the evolution of the French fleet is described very well by the analysis of the vessel entry and exit flows. Scrapped vessels are the main flow of vessel exit whilst, despite the limited entry system in place, New builts constitute the main flow of vessel entry. Both vessel destructions and constructions are investment-related decisions, with introduction or removal of capital from the fishing sector. This suggests that fleet renewal is an important factor of fleet evolution and structural changes. This is consistent with the targeting of these flows by public capacity management policies over the time-period considered. However, resuming and suspending the vessel activity is comparable in size to these fleet renewal flows. This flexibility in the use of the current fleet does not involve any investment into new capital but rather decision on the use of existing capital. This suggests that the flexibility in the use of the current fleet is, in addition fleet renewal and decision on 27/35 capital investments, an important factor of fleet evolution. The number of vessel entries through resuming or suspending the vessel activity however decreased in time (not captured by aggregation for the whole time period). This suggests fleet renewal as the main flow behind fleet evolution. This analysis also outlined the second-hand market as the main vessel source for owner entry into the Atlantic. The data suggests some renewal of owners, with entrants younger than leavers in the Atlantic.

French fleet dynamics have been shown to be influenced by both owners and vessel flows, with both these flows not fully independent. Vessel entry/exit models could be easily refined by considering the type of owner flow associated to a vessel flow. Our results also showed that the second-hand market is the most prominent flow in relation to owner entries and exits, despite the subsidies for early retirement and vessel destructions provided during the studies time period. Our study shows that these notoriously inefficient types of subsidies would also have had a limited effectiveness in reducing fleet and owner numbers.

Management policies to this date typically target vessel characteristics without considering the associated owners' behaviours (i.e. owner's entry and exit). Also, these policies do not consider the types of entries and exits (e.g. fleet usage). This framework has outlined the need to take owners' behaviours (i.e. owner's entry and exit) into consideration as well as vessel flows (policy-induced or not) for effective capacity management and improvement of current vessel entry and exit models. These are crucial for better assessing, targeting and designing more effective overcapacity reduction policies.

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The same type of analysis could be undertaken over various time-periods and geographical scales. The data used is part of the EU Fleet Register data, and the same type of analysis could easily be conducted at the European level or for other European Member States. A decrease in vessel numbers seems in some cases compensated by an increase in the average engine power per vessel, or associated to owners leaving the fleet on a permanent basis. Capacity measures other than vessel numbers could be used to further study fleet capacity evolution and corresponding flows. Further research could look into economic issues arising with asymmetric information between vessel owners and policy makers.

This suggests that improved capacity management policies would need to be designed as a combination of incentive for owner's entry and exit as well as better consideration of all types of vessel flows. In particular, the flows linked to changes in the fleet activity would need to be considered in addition to the flows behind fleet capital renewal. The reform of the Common Fisheries Policy (European Commission, 2009) currently considers the provision of incentives to owners through tradable quotas for adjustment of fleet capacity, which should encompass fleet activity flows as well as the constructions and destructions flows. The impact of this new management system on changes in both vessel and owner flows would however need to be assessed more specifically. This type of analysis could also be included to refine fisheries bioeconomic models for improved assessment. This data is relatively accessible and not too costly to obtain so this approach could also be implemented for preliminary assessment of fishing capacity dynamics in fisheries where capacity management is limited. The capacity management policies and owner's behaviours could also lead to distortions in the second-hand market, which would also need to be studied more specifically.

Our framework provides a good basis for improved analysis of capacity dynamics in

Figure 1

 1 Figure 1 represents the vessels traded on the second-hand vessel market within the

Figure 1 :

 1 Figure 1: Conceptualisation, for a given unit of analysis (rectangle), of the impact of vessel (owner) flows (single arrows) on vessel (owners) numbers (ellipses), and of the impact of possible associations between owners and vessel flows (double arrows) on the fleet. Vessel entries (arrow 1)are made of new builts, imports from outside the vessel group of interest (e.g., from other geographical zones) and vessels resuming their activity. Vessel exits (arrow 2) include destructions, exports and suspensions of vessel activity. Owners can enter the vessel group considered for the first time or more (arrow 4), and leave the group permanently (e.g. when they leave the fishing sector and do not come back) or temporarily (arrow 5). Owners trade vessels on the second hand market (arrow 8) which can lead to changes in fleet segments (arrow 3). Vessel and owners entries are not independent as represented by arrows 6, 7, 9 10.

(

  size, fishing segment, age) and owner characteristics (age) from 1994 to 2008, which are used for this analysis. Data on fleet segments are available from 2000 only. The fleet segments used in this paper correspond to the ones defined in the Data Collection Framework (Commission Regulation (EC) No. 665/2008 of the 14 July 2008). The data have been collected on the overall fleet every calendar year on December 31st. Flow indicators (entry, exit and change of owner or fleet segment) are derived by comparing the national fleet composition between two consecutive years. Indicators of change based on comparison of fleet composition at lower time scales (e.g. month) will show greater temporary movements of vessels (resumed/suspended activity) and owners (temporary entry/exit) compared to the yearly time csale chosen here. The time scale does not affect the import/export flows and new builts/scrapped vessel flows, nor the first entry/permanent exit of owners. All fleet segments are considered together here, 17/35 but the same analysis could be conducted for a given fleet segment. Economic indicators on the French fishing fleet have been collected every year since 2001. The sampling plan is detailed in Van Iseghem et al. (2011) and allows valid and reliable extrapolations to the whole fishing fleet. Economic indicators for 2007 are detailed in

Figure 2 :

 2 Figure 2: Vessel fleet and owner population

Figure

  Figure 3: Vessel and owner flow sizes (1994-2008)

  Fleet Evolution: A Framework for Flow Analysis and Application to the French Atlantic Fleet 29/35

  relation to capital investment flows, capital usage flows and owners' dynamics. It is however descriptive and does not provide any identified economic drivers of fleet evolution nor causal relation between the changes and flows. An analytical model could however be built based on our conceptual framework for further analysis. Another limitation is due to the temporary movements of owners in and out of the French fishing sector, leading to double counting of owners in the fleet when combined to vessel flows over the time period considered. A smaller timeframe could reduce this problem.

Table 1 : Size and nature of the different vessel flows (1994-2008)

 1 Fleet segments are not available for the entire period chosen in this paper. The most populated fleet segment is however representative of the overall fleet.

	Number of vessels	Length (m) GT (UMS)	kW	Age	Most populated segment *

*

Table 2 : Size and average owner age for each owners flow (1994-2008) ENTRIES Number of

 2

			Age of		Number	Age of
			Owner	EXITS	of	Owner
		Owners	(yrs)		Owners	(yrs)
	First entry	3,094	33.4	Permanent exit	3,490	47.7
	Second or more entry	456	41.0	Temporary exit	389	38.2
	TOTAL OWNER ENTRY	3,550	34.4	TOTAL OWNER EXIT 3,879	46.7

Table 3

 3 decomposition of owner entry flows per vessel flow types in covers 92% of First entry owners in Table 2 (i.e. a sum of 2,845 across all vessel entry types divided by 3,094 First entry owners) and 86% of Second or more entry owners. The decomposition of owner exit flows per vessel flow types covers 99.7% of Permanent exit owners and 102% of Second or more entry owners. The percentage is greater than 100% for Temporary exit owners because they can leave the fleet several times with different associated vessel exits. They are counted only once in Table 2 but as many times as different vessel exits in Table

Table 3 : Size of the different owners flows and the average owner age, decomposed along their associated vessel flows (1994-2008)

 3

	ENTRIES	Number of Owners	Age of Owner (yrs)	EXITS	Number of Owners	Age of Owner (yrs)
	Total number of first entry owners	2,845	33.1	Total number of permanent exit owners	3,479	47.7
	New builds	96	32.2	Scrapped	399	47.9
	Imports (other countries)	2	NaN	Exports (other countries)	35	45.5
	Imports (other oceans)	32	34.3	Exports (other oceans)	1	NaN
	Resumed activity	132	35.5	Suspended activity	419	47.3
	Second-hand market trade (change of owner)	2,583	32.9	Second-hand market trade (change of owner)	2,625	47.8
	Total number of second or more entry owners	391	41.3	Total number of temporary exit owners	397	38.3
	New builds	22	39.6	Scrapped	20	34.7
	Imports (other countries)	1	NaN	Exports (other countries)	2	40.0
	Imports (other oceans)	6	45.6	Exports (other oceans)	2	46.0
	Resumed activity	49	41.0	Suspended activity	37	37.5
	Second-hand market trade (change of owner)	313	41.4	Second-hand market trade (change of owner)	336	38.6

ACKNOWLEDGEMENTS

We are extremely grateful to the Editor of the ICES Journal of Marine Science, Sarah Kraak, and two anonymous reviewers for their helpful suggestions on previous versions of this paper. This paper is based on work initiated at Ifremer by Patrick Berthou. The authors are particularly grateful to Michèle Jézéquel, Fabienne Daurès, Emilie Leblond, Samuel Le Blond, and Damaris Phélippé for their expertise on the data and exchanges on the paper, and to Christelle Le Grand, Manuel Bellanger and Mathieu Merzéréaud for their valuable help with programming in R. This research was conducted whilst Emmanuelle Quillérou was a post-doctoral researcher at Ifremer.