Report Typology WAW: France3 2. Approach and methods used 2.1. Team The team working on the French case is composed of: Magali Aubert (INRA MOISA); Jean-François Bélières (CIRAD

Report Typology WAW: France

A World Agricultures Watch report

Report Typology WAW: France

A World Agricultures Watch report

prepared by

INRA - CIRAD

June 2014

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1. Glossary and definitions

GAEC (Groupement agricole d’exploitation en commun): legal structure (moral person) specific to the agricultural sector in France that recognizes two or more individuals as associates in the management and responsibility of an agricultural holding. OTEX (Orientation technico-économique des exploitations agricoles) : defines the specialization of agricultural holdings, based on the calculation of the SGM. SGM (standard gross margin) : measures the production or economic dimension of an agricultural holding. Activities are weighted according to a standardized coefficient (according to geography and technical orientation). The sum represents the profit to be realized at the farm level under normal conditions. UAA (utilised agricultural area): includes arable land; permanent grassland; permanent crops; other agricultural land such as kitchen gardens. AWU (annual work unit): corresponds to the work performed by one person who is occupied on an agricultural holding on a full-time basis.

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2. Approach and methods used

2.1. Team

The team working on the French case is composed of: Magali Aubert (INRA MOISA); Jean-François Bélières (CIRAD ArtDev); Céline Bignebat (INRA MOISA); Pierre-Marie Bosc

(CIRAD MOISA); Sawsane Bouadjil (internship IAMM-UM3); Rocard-Amèvi Kouwoaye (internship University of Auvergne); Philippe Perrier-Cornet (INRA MOISA); Isabelle Piot-Lepetit (INRA MOISA)1. 2.2 Data

The French Agricultural Census 2000 was used (the test can be easily translated to the French Census 2010 when locally available). The data provide a large range of characteristics of agricultural holdings. In this Census, an agricultural holding is defined as an independent entity:

- that operates more than 1 hectare of land - or more than 0.2 hectare of specialized crops of animals (in particular, orchards,

horticulture, vineyard) - or a sufficient activity in agricultural production measured in number of livestock

or production volume, for instance 10 beehives or 10 mother rabbits.

The original data base entails 663,807 holdings. When removing suspicious data reporting a Standard Gross Margin2 (SGM) equal to zero, revealing no agricultural activity for this year: we end up with 663,041 valid observations. 2.3. Involvement of stakeholders along the research process

The construction of the typology was discussed during the period July to September 2013 with stakeholders and resource persons of the Region Languedoc Roussillon (South of France) engaged in a large variety of productions: perennial crops (wine, fruits), livestock and dairy and crop-livestock farming systems. (Appendix 1 for a description). We built on local capacities to test and improve the typology. Field work involved 13 interviews of recognized experts in the Languedoc Roussillon region that could bring light on the recent evolution of the agricultural productive structure. They were selected according to their functions (past or present), but above all because of their expert knowledge taking into account the diversity of the production systems even if wine growing, wine making together with horticulture and fruits dominate in 4 out of 5 departments of the region (the exception being Lozère where livestock based systems dominate). An open 1 In bold, the authors of this specific document.

2 The SGM measures the economic dimension of the farm.

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interview guide organized three themes gathering 40 questions s was implemented. After a few introductory questions regarding the experts’ experiences and skills, the three themes were: (i) production dynamics; (ii) holding dynamics and (iii) the labor situation and evolution at holding and global level in the region. About the interview methodology, one should note that the labor based typology was never mentioned directly but the questions used and their organization were designed in order to test the relevance of using labor as the main entry point to initially classify holdings, opening the way for further deepening the analysis including other variable (but this was not part of this initial round of interviews). The experts implicitly validate the typology based on labor through their own words that lead to distinguish « family based holding” relying on family labor; they differentiate these holdings from those family holding that could transform and that now rely on permanent hired labor working together with the family members. Their size appears to be generally larger than for family farms. Family farms seem to be closely linked to pluriactivity at household level. On the other hand, experts draw attention on what they call “capitalist holdings” where means of production belong to investors that rely on hired labor including that of managers (often called contremaître). Further contacts are in construction with the region of Britany where dairy, poultry and hog production are much more present. We expected to present and discuss our preliminary results with the French Ministry of Agriculture - MAAF officers in Paris during spring 2014. 2.4. Definition of the variables related to the three variables selected

2.4.1. Labour The data available in the census in Annual Work Unit – AWU: family labour (permanent and seasonal separately), wage labour (permanent and seasonal separately). The quality of the data was proven in many studies, expect moonlighting or informal labour arrangements which are only partially captured for reporting reasons, particularly when the practices are not legal. The variable related to familial and wage labour use was broken down into 3 categories (see appendix 6 for a graph). Three categories of labour composition employed by farm holdings are distinguished: (i) corporate farms where wage labour only is engaged; (ii) Patronal farms

where permanent non familial labour is employed or where the amount of wage labour is high relatively to total labour; (iii) Family farms that rely heavily on family labour. On French data the categories were defined as follows: 1) Corporate (or entrepreneurial) farms were empirically defined in the French Census as those farms that report no family labour and a clear disconnection between the owners of the capital (means of production) and the labour engaged in productive activities including

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managerial one. More than 95% of wage (familial and non-familial) labour compared to total labour has been chosen as a statistical threshold. This threshold of 95% was chosen as a confidence interval because of the potential misreporting of some data: in particular some holdings are reporting no familial labour whereas the total amount of labour is higher than the amount wage labour. The confidence interval of 95% adds 1,772 holdings to those who report zero family labour. Among these 1,772 holding, 1,423 report more than 99% of wage labour so that a confidence interval of 1% wouldn’t have been much different.

2) Patronal farms are defined as holdings (i) that reported more than one AWU of permanent wage labor (familial and non-familial) are classified as or (ii) that report a very high proportion of seasonal wage labour. In fact, according to our knowledge those wage workers are perfect substitutes to permanent workers: as the cost of seasonal workers is less than that of permanent workers, farmers get round the law and use strategically seasonal contracts (Darpeix et al., 2014). We decided to split the sample with no permanent workers into two samples in order to assess the fact that some farms are actually employing a large amount of hired wage labour relatively to the amount of family labour. We used the k-mean method to find a threshold above which we can consider the amount of wage labour relatively high enough to the total amount of labour (in AWU): this technique enables to minimize the variance of holdings belonging to the same group (regarding labour composition) whereas it maximizes the variance of holdings across groups: the threshold of 81.5% of family labor in total labor emerged for our study. The results turned out to be robust when using k-median instead of k-mean, that is when the median point of the sub-sample was used instead of the mean. 3) 3) Accordingly family farms are farms with no permanent wage workers and more than 81.5% of family labor in total labor. See appendix 1 for a graphic description of the method.

2.4.2. Commercialization

The second selected variable is related to the type of commercialization the holding is engaged in, with a particular focus on the integration in marketing channels. However, no variable directly related to commercialization/self-subsistence is available in the French Census 2000. This is obviously due to the fact that the question of self-subsistence is not particularly relevant for the French case. Therefore we chose to define a variable standing for the type of commercialization or type of integration in the market. Due to the structure of the information available and the existing dynamics of agricultural systems in France, we chose to differentiate holdings according to the presence or absence of a direct link between the farm and the final consumer. This choice makes sense in the French context because of: (i) their relation with the type of agricultural practices in both cases; (ii) the added-value and overall income coming from agricultural activities that may be different.

1) When this link with the final consumer exists, the term “Direct final marketing relationships” has been used to qualify it: this identifies all farms that develop a direct commercial relation with the consumers (i.e. direct sales of raw or processed products, housing and on-farm restaurant services, production and sales of handicrafts or any

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diversification product). Those relationships relate directly to the consolidation of the employment structure of the holding (Agreste Primeur, 2012). Furthermore, they are found to improve the viability of the holdings for some agricultural sub-sectors like vineyard and wine production (Aubert and Perrier-Cornet, 2012).

2) When not, we define the commercialisation type as “Indirect marketing relationship”: in this case, the holdings do not report any kind of activities in relation to final consumers. Those holding are found in indirect marketing channels: they are selling their produce through intermediaries, brokers or producers’ organisations such as cooperatives or producers’ groups.

For the next steps, further results will be extracted from the Agricultural Census 2010 as a variable related to self-consumption is available – indicating the farm households that consume more than the half of their own production. However, only a very few number of farms are concerned, and mostly family farms (around 4% of the smallest farms in terms of size). For the other types of farms the number turned out to be marginal (far less than 1%) which is more than expected due to the weight of the economic dimension. 2.4.3. Management type We identified the variable related to the legal status of farms as being the most relevant for interpreting the type management which is at work on the French holdings. We built therefore on previous studies on the topic (Bathélémy and Dussol, 2002 among others) that show that the legal status is related to the size of the holding. The national census considers 8 categories of legal status. For the purpose of this report, we had to reconsider the original categories into larger groups. The Census questionnaire for 2000 distinguishes between “individual farmers” and 7 other types of legal status. What is relevant here is an aggregate of different meaningful status in three categories:

(i) Individual farm, that represents farms that are run by a single manager who is considered as a juridical person.

(ii) Agricultural Company status: this category encompasses “collective” types of farm management (such as GAEC) and company status which are specific to the agricultural sector (EARL, for instance). The term “collective” is used in the sense that their management brings together at least two individuals.

(iii) Generic company status, i.e. Limited liability companies or public liability companies.

See appendix 3 for the descriptive statistics of each variables.

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3. Results

3.1. Results on the labour criteria

Tables 1.1 and 1.2 summarize some of the statistics related to the variable related to family or wage labour. The analysis of those tables is displayed below.

Table 1.1. Summary statistics, labour, overall distribution across farm types

Number (%) AWU distribution

total

Familial AWU

distribution total

Wage Labour AWU

distribution total

SGM in total

Family farms 540,933 (81.6%) 60.1% 79.7% 7.5% 56.5%

Patronal farms 113,996 (17.2%) 32.3% 20.2% 64.8% 37.7%

Corporate farms 8,112 (1.2%) 7.6% 0.1% 27.7% 5.8%

Table 1.2. Further insight on statistics, labour

UAA (ha) * SGM (1000 €)* AWU (total)*

AWU per ha* SGM per ha*

Family farms 36,9 (137%) 36,1 (124%) 1,1 (78%) 0,23 (953%) 3,91 (1163%)

Patronal farms 64,7 (131%) 114,4 (109%) 2,7 (97%) 0,42 (732%) 10,70 (697%)

Corporate agriculture 62,1 (125%) 246,9 (253%) 8,9 (201%) 2,04 (512%) 55,72 (622%)

Total sample 42 (177%) 102,17 (195%) 1,4 (180%) 0,28 (922%) 5,71 (1128%)

* In parentheses standardized standard deviation (percentage of variation around the mean)

Analysis of the distribution of farms according to farm types (Tables 1.1 and 1.2)

Family farms as defined here largely predominate in the sample (representing 81,6%) and patronal farms reach 17,2% of the total sample: this makes an overwhelming share of family owned farms and leaves only 1,2% or corporate farming. Interesting is the weight of patronal farms. This latter figure is however far from negligible in the French agricultural landscape. It represents a large part of the AWU engaged on farms (20.2%) and is even more represented in the case of wage labour (with 64.8% of the AWU registered in patronal farms). Furthermore, patronal farms accounts for more than 37.7% of the total SGM, whereas they represent only 17.2% of the number of farms. In family farms the share of familial labour relatively to total labour is nearly 100% (97.4%) which is explained by the methodological background we used as to select the category of family farms: in fact, they are considered in this study as farms with no permanent wage workers or with an amount of seasonal wage labour statistically low enough to consider them as family farms. The amount of family labour is around 25% more important for patronal

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farms (1,4 vs 1,1) than for family farms. It is worth mentioning that these patronal farms employ more family labour and “produce” more than their equivalent in jobs through wage labour recruitment. Family farms with less than 1 familial AWU represent 44,2% of the sample (among them 42% report that the household head is retired); this proportion is less for patronal farms but not negligible as 32,1% of the farms have less than 1 familial AWU (among them 22% with a retired household head). This proportion drops when considering the threshold of 0,5 AWU (32% and 17.9% for family and patronal farms respectively).

Analysis of size for the different categories (Table 1.2)

Family farms are on average smaller with 36,9 ha, 1.1 AWU and 36 120 € of SGM against 64,7 ha, 2.7 AWU and 114400€ for patronal farms and 62,1 ha, 8.9 AWU and 246 900€ for corporate farms (table 1.2). This results hides however a very large heterogeneity of the categories and will be also investigated further against categories.

- In terms of hectares, namely one of the measures of holdings’ size that is predominantly used, we believe that the statistical results are difficult to exploit: areas (number of hectares) are in fact highly related to the technical orientation of the cropping patterns. The types of crops engaging large holdings turn out to be cereals. The presence of vineyards for smaller units is important as well.

- However, we can learn from the next results that are expressed in terms of total SGM. We can expressively see an inversed U-shape for every categories of holding. Individual farms exhibit a SGM below the one of farms with a legal status specific to the agricultural sector. However, farms working under a generic company status seem to be less profitable on average. This result opens further research questions and discussion to understand

- Last, the difference in farm types (family, patronal and corporate farms) is

insightful regarding their legal status: the variance related to the earnings of family farms is higher than the one of other types. Family farms seem to gain to be engaged legal status specific to agriculture.

Categories and productivity of labour

When the difference is brought per AWU, family farms seem to have less return but it is likely to be connected to very different OTEX (in Appendix 5, we see that vineyards and fruit and vegetables are especially represented in patronal and corporate farms). This impact can also be seen in the difference categories exhibit as regards SGM per ha (table 1.2): SGM per ha is 3 and 14 times higher respectively for patronal and corporate farms than for family farms. Similarly, labor productivity (AWU/ha, table 1.2) on patronal farms is twice that of family farms; this gap is far higher for corporate farms that exhibit an average labour productivity as high as 10 times that of family farms. On this side, it is interesting to see that as a result, despite very high difference per hectare (namely, SGM / AWU) is far less important between patronal and

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corporate farms (around 30% to 50% difference). Further analyses are required within homogeneous OTEX but it may corroborate a higher productivity of family labour, as it is likely to be the scarcer factor. Such result may be opposite than results obtained in countries where opportunity for work is low and family farms may keep family labour under-employed in the farm (see section 4).

The development of services is also a way to cope with labor requirements when labor on the farm is scarce. But observations from the Census show a very limited development of this type external supply (labor and machinery provided by external companies or cooperative for the collective use of machineries or “hiring family labor” as a financial arrangement within the family) – so called CUMA, Coopératives d’utilisation de matériel agricole.

Categories and OTEX

Appendix 4 gives the distribution of categories against OTEX. Compared to the overall sample (last column), (i) we can see that especially vineyards, then fruit and vegetables and perennial crops are the sectors which are the overrepresented in the categories of patronal and corporate farms; (ii) the distribution of the column “family farms” is not extremely different from that of the total sample, in fact family farms represent more than 80% of the sample and are thus driving the distribution; (iii) However, looking at the row distribution (per OTEX), we see that family farms account for more than 90% of OTEX “livestock and dairy” and “goats and sheep” whereas they represent only the half of the OTEX “fruit and vegetables”. This result should be further investigated in the next sections of this report displaying the results; this should be furthermore taken into account as a research path for further studies which could break down the categories into OTEX and replicate the methodology on specific production sectors (section 4).

Key discriminating factors of the labor based categories

We run a descriptive analysis of the correlation of the categories of labour as endogenous variable (Familial, patronal, corporate), taking into account as explanatory variables: (i) mode of commercialization (ii) legal status. We control for specific effects of further variables: technical orientation, economic size, in particular. We used a multinomial logit regression to understand the characteristics of the holding belonging to the labour categories (Familial, patronal, corporate). We conclude (Appendix 5) that the variables related to labour, commercialization and legal status are correlated to the categories that were chosen and should be considered altogether. First, commercial companies with a generic legal status (LLC, PLC …) are more likely to be observed in the categories of patronal or corporate farms than to family farms. It shows, however, that companies with a status specific to agriculture are not much present in the category of patronal agriculture. This may be due to the fact that status specific to agriculture entails corporate organizations (GAEC) that encompass co-workers (section 4. For

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recommendations for further research). Second, patronal and corporate farms are more likely to be engaged in direct marketing than family farms. Third, the importance of technical orientation (OTEX) is high.

3.2. Results combining the factors

3.2.1. Overall view

When crossing the three variables presented above, we end up with the following distribution into the categories.

Table 2: Distribution of the holdings

Direct market relationships Conventional commercialisation

Total

Individual farm

Agricultural farms status

Commercial

company status

Individual farm


Commercial

company status

Family farms

77647 (77,4%) (14,4%)

10657 (39,8%) (2,0%)

1106 (25,7%) (0,2%)

389737 (89,2%) (72,0%)

58454 (66,5%) (10,8%)

3332 (46,8%) (0,6%)

540933 (81,6%) (100%)

Patronal farms

22358 (22,2%) (19,6%)

14656 (54,7%) (12,9%)

1404 (32,6%) (1,2%)

46485 (10,6%) (40,8%)

27559 (31,3%) (24,2%)

1534 (21,5%) (1,3%)

113996 (17,2%) (100%)

Corporate farms

292 (0,2%) (3,6%)

1464 (5,4%)

(18,0%)

1790 (41,6%) (22,1%)

467 (0,1%) (5,8%)

1843 (2,1%)

(22,7%)

2256 (31,7%) (27,8%)

8112 (1,2%) (100%)

Total sample

100297 (100%) (15,1%)

26777 (100%) (4,0%)

4300 (100%) (0,6%)

436689 (100%) (65,9%)

87856 (100%) (13,3%)

7112 (100%) (1,1%)

663041 (100%) (100%)

General comments

The distribution (table 2) of family / patronal and corporate farms is uneven according to the variables describing commercialization and type of management. Differences across farms types related to labour are important, in particular as regards farm status (individual farm, agricultural farm status or generic company status). Moreover, we can see that the weight of farms reporting a conventional (indirect) way of marketing their product is the highest, whatever the farm type in terms of labour, even though we shall see that this difference varies across farm types.

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Corporate farms are mostly found for farms with commercial company status (22.1% of the total number of corporate farms for the case of direct market relationships; 27.8% for the case of indirect relationships). However, the weight of farms relying on an agricultural farm status is far for being negligible for corporate farms. In that respect they are very similar to patronal farms.

Breaking down this general distribution, we will focus on 5 results:

- First steps: the first result is related to the type of commercialisation,(result 1) the second on the influence of management (result 2): this analyses allow us to finally propose to aggregate some of the categories.

- On this basis, the second step proposes to compare the typology with the ones usually used (results 3 and 4) and give some insight on performance indicators (result 5)

3.2.2. Combining labour with other key-variables

Result 1 combining labour and commercialization: Family farms are not specifically engaged in “Direct final marketing relation” (direct sales to consumers, transformation and value-adding to the produce including on-farm through catering), contrarily to the common knowledge (table 3). On the contrary, a higher share of patronal farms and even corporate farms belong to such category – see below for a tentative explanation.

Table 3: Farm types and type of marketing channels

Direct marketing Indirect marketing Total

Family farms 89410 (16,5%) 451523 (83,5%) 540933 (100%)

Patronal farms 38418 (33,7%) 75578 (66,3%) 113996 (100%)

Corporate farms 3546 (43.7%) 4566 (56,3%) 8112 (100%)

Total sample 131374 (19,8%) 531657 (80,1%) 663031 (100%)

Family farms under individual farms status are more probable to be observed in “conventional” or indirect marketing,: they represent 83,5% family farms whereas only 66,3% of patronal farms and even less (56,3%) for corporate farms. When looking at family farms that are in direct marketing and do not belong to the individual farm status, we can draw the following conclusions (table 3):

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- The presence of family farms registered as individual farms and that are engaged in “Indirect marketing” are mostly engaged in “livestock and dairy” or “cereals”. The description of the statistics related to OTEX are in appendix 4).

- The difference in the age of the farmer is to be noticed too: the average age of the farmers who decided to engage in activities such as products processing is 48. If not, the average age is 54.

- The differences in the distributions of observations according to the categories “family farms”, “patronal farms” and “corporate farms ?” between the two types of marketing in the case of “company status” is striking as we may have thought that family farms were the ones that try to find ways to diversify their revenues and invest in value –adding production in order to cope with the difficulties they actually face within the agricultural sector.

This result corroborates previous research on small farms that showed that they are less engaged in direct commercialization than larger farms are (Aubert and Perrier-Cornet, 2009).

The presence of corporate agriculture working under a legal status specific to the agricultural sector is higher for farms engaged in ”Direct final marketing relationships” (5,4% of the total) than for regular commercialization (2,1%). This result is highly correlated to vineyards (more than 25% of the sub-sample for farms engaged in ”Direct final marketing relationships” ). Integration of wine making seems to be the main reason for this result (Aubert and Perrier-Cornet, 2012).

Result 2: combining labour and status The generic company legal status is not the exclusivity of corporate farms as their weight in the total number of farms with a generic company status is respectively 35.5% (table 4).

Table 4: Farm types and type of legal status

Individual farm Agricultural farms

status Generic company

status Total

Family farms 467,384 (87%) 69,111 (60.3%) 4,438 (38.9%) 540,933

(81.6%)

Patronal farms 68,843 (12.8%) 42,215 (36.8%) 2,938 (25.7%) 113,996

(17.2%) Corporate

farms 759 (0.1%) 3,307 (2.9%) 4,046 (35.5%) 8,112 (1.2%)

Total sample 536,986 (100%) 114,633 (100%) 11,412 (100%) 663,031 (100%)

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- The major part of the farms engaged in patronal farms with a generic company status for is in wine production regardless the type of commercialization. Companies with a generic status are found in particular in cereal production and wine production with a significant over-representation of those productions relatively to the whole patronal farm sample.

- Family farms with a generic company status are found in livestock and dairy production (for 23% of them) and in cereal production (20% of them), regardless the type of commercialization. But their distribution across productive orientation is not difference from that of the total family farms sample.

- Last, corporate farms that are registered as generic companies are relatively evenly

distributed across technical orientations. However, compared to the total sample of corporate farms, vineyards are over-represented and fruit and vegetables under-represented (10% level)

However, we should notice (table 2) that the major part of corporate farms are registered as generic companies (49,9%), whereas only a small proportion of family and patronal farms are generic companies (respectively 0,8% and 2,6%). Nevertheless, we see that a large proportion of patronal farms decided to adopt a status specific to the agricultural sector (37%).

3.2.3. Conclusion: aggregation of the categories

The motivation for this aggregation is to bring back the number of categories into a reasonable number in order to facilitate the readability of the proposal. Two criteria were used:

- The number of observations in each category. - The importance of the discriminating variable in understanding the rationale of the

category. This choice was made relatively to the results presented in the previous (section 3.2.2)

Table 5 highlights the categories that are merged by signalling them in the same colour, namely:

- For family farms (green) and patronal farms (orange), we considered only the status of generic company regardless to type of commercialisation

- For corporate farms, we believe that only the distinction between agricultural types of status (individual farms included) and generic types of status is relevant. Furthermore, we did not find any evidence of differences according to the type of commercialisation for farms with agricultural status.

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Table 5. Aggregation of the categories

Direct market relationships Indirect market relationships Total

Individual farm


Generic company

status

Individual farm


Generic company

status

Family farms 77647

(14.4%) 10657 (2%)

1106 (0.2%)

389737 (72%)

58454 (10.8%)

3332 (0.6%)

540933 (100%)

Patronal farms 22358

(19.6%) 14656

(12.9%) 1404

(1.2%) 46485

(40.8%) 27559

(24.2%) 1534

(1.3%) 113996 (100%)

Corporate farms

292 (3.6%)

1464 (18%) 1790

(22.1%) 467

(5.8%) 1843

(22.7%) 2256

(27.8%) 8112

(100%)

Total sample 100297 (15.1%)

26777 (4%) 4300

(0.6%) 436689 (65.9%)

87856 (13.3%)

7112 (1.1%)

663031 (100%)

Table 6 summarizes the characteristics of the different categories. It presents results on (i) the frequency of each category; (ii) the share of family labour in total labour;

The first column gives the category that is concerned:

- First (blue): Labour: “Familial” for family farms, “Patronal” for Patronal farm, “Corporate” for corporate farms.

- Second (orange): Legal status “Indiv” for individual farms, “Agr status” for company status specific to agriculture, “Enterprise” for farms with a generic company status.

- Third – if any (black): commercialization “Market” for market relationships, “Regular” if not

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3.3. Comparison with traditional typologies

Table 6. Frequency of the categories and percentage of family labour in total labour (AWU)

Number

(% of total) % family labor

Familial/Indiv/Market 77647 (11,7%) 97.5%

Familial/Agr status/Market 10657 (1,6%) 92.9%

Familial/Indiv/Regular 389737 (58,8%) 97.4%

Familial/Agr status/Regular 58454 (8,8%) 95%

Familial/Enterprise 4438 (0,67%) 97.9%

Patronal/Indiv/Market 22358 (3,4%) 55.5%

Patronal/Agr status/Market 14656 (2,21%) 46.7%

Patronal/Indiv/Regular 46485 (7%) 59.7%

Patronal/Agr status/Regular 27559 (4,2%) 54.1%

Patronal/Enterprise 2938 (0,44%) 40.3%

Corporate/Enterprise/Market 1790 (0,27%) 0.3%

Corporate/Enterprise/Regular 2256 (0,34%) 0.3%

Corporate/Indiv & Agr status 4066 (0,6%) 0.3%

Total 663031 (100%) 89.1%

Result 3: Weight of family labour The weight of family labour is uneven according to farm types. (table 6)

- Obviously, holdings engaged in family farms present a high level of family labour relatively to total labour: the level is quite homogenous across categories, ranging from 92.9% to 97.9%. It seems that most family farms with more than one family member involved choose a generic company status (“Enterprise”), which may slightly modify the type of management as well as the overall assets as such farm are likely to be larger with more assets (also requiring agricultural status). The category Family/Enterprise does not differ from the entire sample in terms of OTEX.

- Patronal farms exhibit a relatively high level of family labour that represents about the half of the total amount of labour. However, we see that this level is sensitive to the legal status of the farm when going from an individual (more than 55% of family labour) to a specific agricultural status (around 50% of family labour) and then to a generic enterprise (40% of family labour).

- Moreover, corporate farms do not exhibit specific features with a very low level of family labour across status and marketing strategy. The level of family labour is

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slightly higher than zero due to the confidence interval we used when building the categories.

Table 7. Statistics according to the different categories

UAA (ha)

SGM (1000€)

AWU (total)

AWU

per ha

SGM

per ha

SGM

per

AWU

Familial/Indiv/Market 22,3 26554 1,07 0,63 7,9 24,6

Familial/Agr status/Market 79,9 94911 2,37 0,25 5,7 43,3

Familial/Indiv/Regular 28,8 26165 0,86 0,17 3,1 28,3

Familial/Agr status/Regular 102,5 104517 2,11 0,06 3,3 55,5

Familial/Enterprise 37,8 35792 1,37 0,42 8,4 29,7

Patronal/Indiv/Market 31,0 89463 2,53 0,76 13,3 37,9

Patronal/Agr status/Market 59,5 179826 4,46 0,48 12,4 45,1

Patronal/Indiv/Regular 52,3 72574 1,74 0,28 8,3 48,5

Patronal/Agr status/Regular 118,1 168821 3,37 0,22 10,0 60,1

Patronal/Enterprise 44,4 127654 4,21 1,54 27,1 36,3

Corporate/Enterprise/Market 42,4 299020 10,94 2,79 59,2 29,5

Corporate/Enterprise/Regular 50,5 193474 9,09 4,38 107,3 35,5

Corporate/Indiv & Agr status 77,3 253621 7,95 1,16 25,6 50,0

Total 42,1 52125 1,44 0,29 5,7 34.2

Result 4: Comparison with traditional measurement of farm size – utilized agricultural

area (UAA) and economic dimension (SGM). We saw in the previous section that family farms are on average smaller with 36,9 ha and 36 120 € of SGM against 64,7 ha and 114400€ for patronal farms and 62,1 ha and 246 900€ for corporate farms. This results hides however a very large heterogeneity of the categories (appendix 6 summarizes the averages of the diverse indicators – UAA, SGM …- two by two).

- In terms of hectares, that is one of the measures of holdings’ size that is predominantly used, we believe that the statistical results are difficult to exploit: areas (number of hectares) are in fact highly related to the technical orientation of the cropping patterns. The types of crops engaging large holdings turn out to be cereals. The presence of vineyards for smaller units is important as well.

- However, we can learn from the next results that are expressed in terms of total SGM. We can expressively see an inversed U-shape for every categories of holding. Individual farms exhibit a SGM below the one of farms with a legal status specific to the agricultural sector. However, farms working under a generic commercial status seem to be less profitable on average. This result opens further research questions and discussion to understand

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- Last, the difference in farm types (family, patronal and corporate farms) is insightful regarding their legal status: the variance related to the earnings of family farms is higher than the one of other types. Family farms seem to gain, at the farm level, to be engaged legal status specific to agriculture. Moreover, the SGM per AWU is higher for patronal farm than for any other type of legal status. However, it could be interesting to differentiate family labour from wage labour in order to better capture the rationale beyond farms with agricultural status, in particular the potential presence of family associates.

Result 5: Labour intensity and economic results across types (table 7)

- We should first put forward that the following remarks are drawn from observations that are not related to OTEX. Appendix 7 shows however that the distribution of holdings across categories is different according to OTEX. We take the examples of “vineyards”, “crops” and “livestock and dairy” in order to highlight those differences. Conclusions are reported in appendix.

- Labour intensity: family farms exhibit lower AWU per ha (from 0,06 to 0,63 for family farms with individual status and direct market relationships) than patronal farms (from 0,22 to 1,54 for those with a generic company status even though farms with individual status and direct market relationships exhibit a high level of labour intensity as well). Corporate farms show very different AWU per ha against status, the generic company having the highest AWU per ha (around 3 AWU per ha on average) whereas the other status have results closer to the patronal farm. Such may connect directly to very different OTEX.

- It is quite striking that such combination change much some of the previous results per category. The patronal and family farms with agricultural status and around 2 AWU family have the highest SGM / AWU (very close around 52-54 per AWU), whereas family farms with individual farm status reach two times less SGM per AWU.

- Finally, SGM per ha is relatively the same across status for patronal and family farms, much higher for patronal ones (between 9 and 11 against around 4 for family farms) with indirect market relationships leading to lower levels of SGM per ha, especially for family farms.

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4. Recommendations for the next steps

In the case of France, this study confirms that the global typology shows the importance of family farming but at the same time it provides an opportunity to focus on patronal farms as they show an interesting level of employment (see section 3). It shows as well that the correlation of those types with other categories – in this case, legal status and type of market relationships- is relevant in order to understand the rationale at stake. We can also think about drawing more attention to the level and nature of family labor on “family farms” since according to our quantitative data this quantity of labor is rather reduced and hence the pressure on it is high. By comparing both types (family and patronal) it can bring light on the conditions that could favour employment strategies.

- For family farming, the interest would be to analyse the family labor with the following insights (Sourisseau et al, 2012): the quantitative distribution of family farming in relation with several other key variables: - (i) the level and share (time and income) of off-farm labor at household level;

this path, for a further proposal, seems to be tractable on the Census data we used.

- (ii) an estimate of the level of capital at farm level and an assessment of its productivity; however, this variable may be rather difficult to capture on the basis of the Census. Perhaps, a further discussion about the use of other data sets may be useful to build on this idea, especially with FADN data sets.

- (iii) the amount of “non-market” labor available on farm [elders, children...] that provide free labor, especially retired household heads for the French case (20% of the household heads of farms categorized as family farms report to be retired for the Census 2000). We believe however that the trend towards increased wage labour use is partly due to the fact that those unpaid categories of labour working on family farms are decreasing in weight.

- For patronal farms:

- (i) it should be interesting to characterize both the nature of the 45% extra family labor compared to family farms labor and the nature of hired labor - which should imply to disaggregate by type of technical orientation (OTEX).

- (ii) the presence of co-workers, or associates, (in French co-exploitants) seem also to be decisive and do not totally overlap with the variable related to legal status.

- For corporate farms:

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- (i) Corporate farms tuned out to be few in number but not negligible: the analysis of the Census 2010 may reveal some strong evolutions of this category of farms which seems to be not that much investigated as a research topic.

- (ii) the analysis can further specifically investigate the type of management which is at work in those holdings.

Those propositions of research paths call for deepening the analysis in a dynamic perspective with the 2010 Census. At this stage, we believe that the analysis for France can’t avoid the need also to be developed within each “technical orientation” which requires specific labour needs intensity. Then, within each broad category as defined through labour we will need to deepen the structural analysis by including the level of assets engaged in farming. More generally we would also suggest the need to present these results and their follow-up to relevant stakeholders (Farmers’ unions, at regional and national levels; ministry officers, other researchers...).

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Conclusion:

In the general framework of the WAW initiative, the study led on the case study “France” exhibits some key-features:

In terms of the categories that were designed regarding the three variables (labour, management type, commercialization/self-subsistence):

- We conclude on the tractability of the approach as the data that are available match the requirements of the project – with the constraint that we had to adapt the proposal to the specific case of France (the variable “commercialization” being perhaps the most meaningful example).

- Further investigations should be put on patronal farms; their importance in terms of added-value and, even more, in terms of agricultural wage employment is very large. Those farms should be more precisely characterised and their evolution taken into account on a dynamic point of view (Census 2000 + 2010).

- The ongoing decline of family farms (in terms of number) raises the question the transition of some of the holdings from the category “family farms” to “patronal farms”.

- Last, the characterization of corporate farms should be assessed: they are few in number but their type of management should be further studied.

All those conclusions legitimate a more precise analysis of the cases which were presented in this report. Going beyond the objective of the international typology, those are the ideas we want to put forward:

In terms of variables that should be further investigated:

- The diversification of activities (off-farm) and the generated income is not taken into account at this stage.

- For the variable “type of management”: the presence of family associates (co-

exploitants) is not specifically addressed, even though the legal status of the holding encompasses much of the information about the presence of family associates.

- Last, the interpretation of our results couldn’t bypass the fact that farms are engaged in different types of technical orientation (OTEX).

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5. Appendix

Appendix 1: stakeholders engaged in discussing the construction of the typology

- Administrator of ADEAR 34 (installation aid for farming), producer of wine and breeder of sheep and goats as well.

- Conseil Général Pyrénées Orientales – Head of the division “Agriculture, Forestry and Rural areas”

- Chambre d’agriculture Gard – Head of the division - President of the observatory for wine Conseil Général Hérault - President of the comité de bassin des Cévennes - Manager Terracoopa (cooperative for the installation in environment-friendly agriculture),

vice-president of RENATA (Network for rural development) - Facilitator at FD CIVAM 34 (Association promoting agriculture and rural areas)

- Appendix 2: labour classification

-

-

Total number of holdings

663041

Family labour present

654,929 holdings

Family farms

540,933 holdings

patronal farms

113,996 holdings

More than 95% of wage labour

8,112 holdings

Corporate (or entrepreneurial)

agriculture

8,112 holdings

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Appendix 3: descriptive statistics of the three variables

Appendix. 3.1. Labour

Labour Total

Family farms 540933 (81,6%)

Patronal farms 113996 (17,2%)

Corporate farms 8112 (1,2%)

Total 663041 (100%)

Appendix. 3.2 Legal status (3 categories)

Legal status Total

Individual farm 536986 (81%) Company status specific to agriculture (GAEC ; EARL, etc.)

114633 (17,29%)

General company status (LLR for instance.) 11422 (1,72%)

Total 663041 (100%)

Appendix. 3.3. Commercialization types3

Commercialization type Total Market relationships 131374 (19,8%) Indirect market relationships 531667 (80,2%) Total 663041 (100%)

3 direct sales, restoration ; transformation considered as innovative and called market relationships directly

linked to the consumer.

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Appendix 4: Description by technical orientation (OTEX)

OTEX Family farms Patronal farms Corporate farms Total Crop 107105 (19,8%)

(80%)

25665 (22,5%) (19%)

1243 (15,3%) (1%)

134391 (20,2%) (100%)

Fruits and vegetables

8114 (1,5%) (51,8%)

6530 (5,7%) (41,3%)

1087 (13,4%) (6,9%)

15784 (2,3%) (100%)

Vineyard 55716 (10,3%) (60,9%)

33723 (29,5%) (36,5%)

2385 (29,4%) (2,6%)

92304 (13,9%) (100%)

Fruits and other permanent crops

15687 (2,9%) (62,6%)

8616 (7,5%) (34,1%)

827 (10,1%) (3,3%)

25305 (3,8%) (100%)

Livestock and dairy

150379 (27,8%) (91,6%)

13311 (11,6%) (8,1%)

565 (6,9%) (0,3%)

164732 (24,8%) (100%)

Goats and sheep 76272 (14,1%) (92,6%)

5539 (4,8%) (6,7%)

606 (7,4%) (0,7%)

82456 (12,4%) (100%)

Poultry/hog 9196 (1,7%) (70,2%)

3305 (2,9%) (25,3%)

593 (7,3%) (4,5%)

13104 (1,9%) (100%)

Polyculture 116896 (21,6%) (86,6%)

17266 (15,1%) (12,8%)

806 (9,9%) (0,6%)

134965 (20,3%) (100%)

Total 540933 (100%) (100%)

113966 (100%) (100%)

8112 (100%) (100%)

633041 (100%)

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Appendix 5: Probability to belong to the categories (multinomial logit)

We use a multinomial logit regression with the categories as endogeneous variable and the variables presented in the previous section as exogenous variables. We performed a Hausman test for the assumption of independence of irrelevant alternatives. We accept the independence but only weakly (10% risk) in the case of corporate agriculture.

The relative risk ratios (RRR) are reported in table 8 where the category of “family farms” is chosen as the reference category. As we consider a logistic regression, the odd of success is ��(��|)

��(��|)= �� = � . If the coefficient affected to one variable x is more than 1 for a

category j, then the variable has a positive effect on the probability to belong to j relatively to k (the reference category). Moreover the odds of belonging to the category j is α times as large as belonging to category k.

Patronal farms Corporate farms Family farms Crop 13+14 1.734*** 1.839*** Reference Fruit and vegetables 28+29 6.951*** 11.097*** Vineyard 37+38 5.977*** 7.325*** Fruits and other permanent crops 39 6.345*** 8.096***

Livestock and dairy 41+42+43 Reference Reference

Goats and sheeps 44 1.461*** 3.488*** Poultry 50 2.294*** 4.137*** Polyculture 60+71+72+81+82 1.222*** 1.095***

Diversified holding (a) 1.699*** 1.769*** Individual farm Reference Reference Company status specific to agriculture (b) 1.359*** 9.646***

General company status (c) 3.541*** 375.574***

Age 0.997*** 1.001

UUA (ha) 1.000*** 0.998*** Economic dimension (1000 €) 1.016*** 1.018***

N 663 041

Pseudo R2 0,274

LR chi2(22) 190088,5 Prob > chi2 0.0000

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Appendix 6: comparison to farm size in terms of UAA and SGM

Appendix. 6.1. Key characteristics and performance: combined categories Labour / legal

status

Combined categories Number Family labour (%)

UAA (ha)

SGM (1000€)

AWU (total)

AWU Family

AWU

per ha

SGM

per ha

SGM per

AWU

Familial/Indiv 467 384 97,9 27,7 26229,4 0,9 0,9 0,2 3,9 27,7

Familial/Agr status 69 111 94,7 99,0 103035,8 2,1 2,0 0,1 3,7 53,6

Familial/Enterprise 4 438 95,1 37,8 35792,4 1,4 1,3 0,4 8,4 29,7

Patronal/Indiv 68 843 58,4 45,4 78059,1 2,0 1,0 0,4 9,9 45,0

Patronal/Agr status 42 215 51,5 97,7 172641,8 3,7 1,6 0,3 10,8 54,9

Patronal/Enterprise 2 938 35,8 44,4 127653,8 4,2 1,1 1,5 27,1 36,3

Corporate/Indiv 759 1,3 46,3 132432,8 5,0 0,1 0,6 8,8 37,8

Corporate/ Agr status 3 307 0,7 84,4 281435,5 8,6 0,1 0,4 29,5 52,8

Corporate/Enterprise 4 046 0,3 46,9 240168,7 9,9 0,0 3,7 86,0 32,9

Appendix 6.2 Key characteristics and performance: combined categories Labour /

Commercialization

Combined categories Number Family labor

UAA (ha)

SGM (1000€)

AWU (total)

AWU Family

AWU

per ha

SGM

per ha

SGM per

AWU

Familial/Market 451 523 97,5 38,5 36382,7 1,0 1,0 0,2 3,2 31,9

Familial/Regular 8941 96,9 29,2 34798,6 1,2 1,2 0,6 7,7 26,8

Patronal/Market 75 578 57,3 76,4 108502,7 2,4 1,1 0,3 9,3 52,6

Patronal/Regular 38 418 51,3 41,8 125892,1 3,4 1,4 0,7 13,4 40,4

Corporate/Market 4 566 0,5 70,8 199125,8 7,9 0,01 2,4 69,0 45,8

Corporate/Regular 3 546 0,6 50,9 308442,8 10,3 0,01 1,6 38,6 35,9

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Appendix 7: distribution of holdings into the categories according to the OTEX

Crop: distribution (number and percentage)

Number

(% of total)

Familial/Indiv/Market 1036 7,7

Familial/Agr status/Market 2103 1,6

Familial/Indiv/Regular 78539 58,4

Familial/Agr status/Regular 1554 11,6

Familial/Enterprise 929 0,7

Patronal/Indiv/Market 2312 1,7

Patronal/Agr status/Market 1725 1,3

Patronal/Indiv/Regular 1172 8,7

Patronal/Agr status/Regular 9521 7,1

Patronal/Enterprise 399 0,3

Corporate/Enterprise/Market 67 0,1

Corporate/Enterprise/Regular 365 0,3

Corporate/Indiv & Agr status 811 0,6

Total 134391 100%

Conclusions: no large difference between this distribution and that of the whole sample can be noticed.

Vineyard: distribution (number and percentage)

Number

(% of total)














Total 92304 100.00

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Conclusions: (i) A large number of patronal farms relatively to the total number and less familial farms; (ii) The difference is more pronounced for the regular way of commercialization with a lower increase (in percentage) of the presence of patronal farms and a larger decrease of the presence of family farms. This may confirm the importance of transformation activities and direct sales in this OTEX; (iii) The overrepresentation of corporate farms is not negligible as they account respectively for 37% and 39% of the total number of holdings in categories Corporate/Enterprise/Market and Corporate/Indiv & Agr status; furthermore vineyard farms represent only 5% of the category Corporate/Enterprise/Regular, a statement that reinforces the previous result about the importance of direct final marketing relationships in the sector. Livestock and dairy: distribution (number and percentage)

Number

(% of total)














Total 164732 100

Conclusions: in this case the presence of family farms is particularly high, but only in the case of regular (indirect) market relationships. The weight of patronal farms is lower than in the whole sample and the decrease is less pronounced for regular (indirect) market relationships.

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REFERENCES

AUBERT M., PERRIER-CORNET P. 2009, “Is there a future for small farms in developed countries? Evidence from the French case”, Agricultural Economics, 40 (s1): 773-787.

AUBERT M., PERRIER-CORNET P. 2012, “La diversification des activités dans les exploitations viticoles françaises”, Economies et Sociétés, 10-11: 1969-1996.

AGRESTE PRIMEUR, 2012, “Un producteur sur cinq vend en circuit court”, n° 275.

BARTHÉLÉMY D., DUSSOL A.M., 2002,, “Sociétés agricoles : entre modernité et tradition”, AGRESTE - Cahiers n° 2 CAPT D., DUSSOL A.M., 2002, “Exploitations diversifiées : un contenu en emploi plus élevé”, AGRESTE - Cahiers n° 2 DARPEIX A., BIGNEBAT C, PERRIER-CORNET P., 2014, “Demand for seasonal wage labour in agriculture: what does family farming hide? ”, Journal of Agricultural Economics, 65(1): 257–272. SOURISSEAU JM, BOSC PM, FREGUIN-GRESH , BELIERES JF, BONNAL P, LE COQ JF, WARD A., DURY S., 2012,. “Les modèles familiaux de production agricole en question.

Quelle méthode pour analyser leur diversité ? ” Autrepart (62): 159-181

Report Typology WAW: FranceA World Agricultures Watch Report

The typology of agricultural holdings (AHs) aims to characterise different types of production structures and assess their relative importance. The dynamics of these different types allow the transformation of agriculture to be monitored over time to design pertinent support policies for agricultural production units. This paper presents the results of a typology of agricultural holdings in France that was carried out with a methodology discussed in the WAW initiative. It validates a typology based on labor.

Documents

Report Typology WAW: France3 2. Approach and methods used 2.1. Team The team working on the French case is composed of: Magali Aubert (INRA MOISA); Jean-François Bélières (CIRAD