Evaluating the farmer’s preferences for feedstock supply of cereal straw. Is there a strategic behavior? Giacomo Giannoccaro 1,3, Bernardo De Gennaro 2,

Evaluating the farmer’s preferences for feedstock supply of cereal straw.

Is there a strategic behavior?

Giacomo Giannoccaro 1,3, Bernardo De Gennaro 2, Emilio De Meo 2

Maurizio Prosperi 1,3

1 University of Foggia, Dpt. SAFE2 University of Bari, Dpt. DiSAAT3 STAR* Agro-Energy Group, University of Foggia

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Research motivation

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Research motivation

Cereals straw residue represents an abundant source of biomass therefore might represent a valuable biomass feedstock in the bio-economy

Currently straw has many uses i.e. animal bedding and feeding, as well as sold on market; or end-practices i.e. incorporated in the soil and in-situ burned

Although cereal straw assessment as a feedstock is a pre-requisite in the bio-economy planning , actually there are no official statistics with reference to amount, price or supply delivering neither at national nor at local level

Literature review (1/2)

Ericsson and Nilsson (2006) estimated the agronomic availability of straw

de Wit and Faaij (2010) assessed the biomass availability along with the costs of handling, transporting and storing

Delivand et al. (2015), tooke into account spatial straws availability minimizing the total transportation distance

While the supply costs incurred for collecting and transporting the biomass from the field to the plant are counted, they ignore the interplay with current straws uses (e.g. animal bedding and feeding) and on-farm practices (e.g. chopped and incorporated)

As a whole, all these works assume that straw currently not used will be available without monetary compensation

Literature review (2/2)

Glithero et al., (2013) carried out an estimation of current straw use along with potential availability for second generation biofuels by surveying 249 farmers across England

Findings show that the amount of straws would not be a limiting factor

The main barrier to a bio-energy plant development would be the high price called by farmers for the straw, apart the cost due for baling and transporting

Practically, farmers are not willing to leave it as free of charge

Aim of research

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Research goals

We focuses on farmers with the aim of assessing the supply curve (i.e. amount and price) of cereals straw that farmers would willing to sell on a feedstock market

The objectives are twofold: to investigate the factor which influence the

willingness of farmers to sell straw on the new feedstock market

for the fraction of straw that is not deployed, to identify the level of compensation necessary (if any) for the change of current straw practice associated with its provision

Materials and Methods

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Where we areFoggia, province of Apulia region (South Italy)200 thousands hectares of wheatA quite large combustion power plant (25 MWe) is going to be built, using straw residues as main feedstock.130 Kt d.m. will be intended to fuel the plantCereal area of 110 thousands hectares around the plant will be necessary devoted

Data The research use data from a sample of 203 on-

farm survey carried out in 2014 across 24 municipalities all around the plant site

Cereals land extent, farming practices, straw and grain yields, willingness to enter the alternative market and his/her relative willing to accept (monetary value) selling straw on that market

Farmers were also asked to indicate their level of commitment (% of straws annually produced), participation (length of contract provision) and delivery modality (i.e. sold in-swath or baled)

Methodology We apply an inference procedure to draw the

supply curve of straw for the sampled area Heckman two-steps model is used to estimate

an econometric regression of farmers Willingness to Accept (WTA)

Statistical package STATA (IC.11) has been used to estimate the Heckman model

Results

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How many and who enter the feedstock market

Table 2 – Farm profile of willing and non-willing participants Sample Non

participants Do not know/Other

Willing to partecipate

N 203 63 25 115 Farmer age (median) 55 years 57 years 58 years 54 years Farm size (mean ha) 22.91 16.95 34.70 23.66 Cereal crops (mean ha) 15.33 12.17 19.41 16.22 Pre-dominant farm system Specialist in cereals Mixed arable crops

66.5% 22.7%

71.4% 3.2%

66.7% 20.8%

64.4% 33%

Livestock rearing 10.8% 25.4% 12.5% 2.6% Pre-dominant straw disposal

on-farm use livestock 8.9% 22.2% 8% 1.7% sold (in-swath or baled) 45.3% 47.6% 44% 44.3% chopped & incorporated 20.7% 12.7% 8% 27.8% on-field burning 14.3% 12.7% 28% 12.2% many of previous 10.8% 4.8% 12% 13.9%

the sale in-swath modality is dominant preference

57%

Farmer’s motivation for curren end-practices

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

other

technical harvesting constraintsno economic conveniencesaving in fertilization

soil fertility

timelineless

Variables, meaning, sample meanCode variable meaning of variable mean

Cereals area (ha) cereals area within the farm (hectare) 15.78 (ha)

Production contracts none= without any production contractwholly= all production on the farm is under contract agreement partly=a portion of production is under contract agreement

70% of farms3%27%

Agro Environmental Schemes (AES)

none= no engagement soil fertility= engaged into measure 214 of RDP (100 EUR ha-1 per 300 unit of dray matter year -1)other = engaged into other AES

76% of farms21%

3%Current straws use/practice sold in-swath/baled = already sold in-swath or sold in-bale

chopped and incorporated = incorporated into the soilon-field burnt= burning on the field many = no specific uses/practices

44% of farms9%13%14%

Off-farm employment yes= farm head has off-farm jobno= farm head does not have off-farm job

45% of farms55%

Farm system specialist in cereals= at least 97% of farmland is devoted to cerealsmixed arable crops= more than 3% of farmland is devoted to arable crops (excluding cereals)livestock rearing= farms with livestock

66.5% of farms22.7%

10.8%

Heckman model result: Participation

Code variable β coefficient S.E.

Constant .25** .13

Agro Environmental Schemes (AES) other = -1.48** .64

Farm system mixed arable crops= 1.80***livestock rearing= -1.90***

.51

.50

lambda (λ) = -1.95**(.80)

*Significant at 10%; ** Significant at 5%; ***Significant at 1%;

There is a bias in selection for market participation

Y*= 0.25 – 1.48(other AES) + 1.80 (mixed arable crops) – 1.90 (livestock rearing)

Heckman model result: WTACode variable β coefficient S.E.

Constant 13.71*** .77

Cereals area (ha) .05** .015

Production contracts wholly= 2.73*

1.54

Agro Environmental Schemes (AES) soil fertility= 1.90** .65

Current straws use/practice on-field burnt= 1.76** .77

Off-farm employment yes= 1.12** .49

WTA (EUR ha-1 )y= 13.71 + 0.05 (cereals area)+ + 2.73 (wholly production contract) + + 1.90 (AES soil fertility) + + 1.76 (on-field burnt) + +1.12 (off-farm employment)

*Significant at 10%; ** Significant at 5%; ***Significant at 1%;

Figure 2: Supply curves for straws sold in-swath on the current and feedstock market

Source: our elaboration from data sampled and ISTAT (2010)

Sold in-swath Incorporated or burnt

Discussion

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Discussion In general, despite of the high level of farmer’s

participation the price of straws would go up In our study, straws is not the case of a “zero

value resource”: i) already established markets ; ii) traditional burning; iii) incorporation practice to get public subsidy according to the AES

The value of cereal straws is very similar to the case of natural resources, where the value does not depend on the production costs, but rather on the scarcity of the resource (i.e. on the demand)

So that, farmers are rational and they do not exhibit strategic behavior

Evaluating the farmer’s preferences for feedstock supply of cereal straw.

Is there a strategic behavior?

Giacomo Giannoccaro 1,3, Bernardo De Gennaro 2, Emilio De Meo 2

Maurizio Prosperi 1,3

1 University of Foggia, Dpt. SAFE2 University of Bari, Dpt. DiSAAT3 STAR* Agro-Energy Group, University of Foggia

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