Case study and Household selection

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4.3.2 Productivity indicators

We use different energy productivity indicators, depending on the output and the inputs analysed. Although all the productivities are measured in energy terms (mainly GJ in ECB terms;

GJECB), we will not indicate it in every moment in order to avoid repetition. First we analyse the productivities with respect to the Final Produce in Equivalent Consumption Baskets (FPECB), and we relate it with the major two inputs, land (measured in hectares of farmland) and labour (measured in agricultural working days). Thus, we obtain the Final Productivity of Land (FPLan) and the Final Productivity of Labour (FPLab). Second, we calculate an indicator to assess the whole labour effort required to maintain the productive capacity of the agroecosystem, which would include not only the agricultural tasks to maintain soil fertility and livestock, but also to reproduce the human workforce.

In this case, we maintain FPECB as the output, and include both agricultural and Domestic and Family Work (DFW) as inputs. This is labelled Total Productivity of Labour (TPLab).

4.3.3 Case study and Household selection

Given the complexity of the methodology presented, in this initial attempt we propose a first application to five representative households of a local case study located in the Barcelona province (Sentmenat municipality, Vallès County, Catalonia, c.1850). Thanks to the availability of historical sources and cadastral maps, and the long lasting historical research made on four municipalities of the Vallès County (Serra 1988; Cussó et al. 2006a and 2006b; Garrabou et al. 2001, 2010, 2012;

Olarieta et al. 2008; Tello et al. 2008, 2016; Marull et al. 2016, Galán et al. 2016), our research project has been using them as a test bench to develop and apply a socio-metabolic scanning of farm systems before and after the Green Revolution. Previous research show land use analyses (Olarieta et al. 2008), energy balances (see Chapter 3; Padró et al. 2017; Galán et al. 2016; Tello et al. 2016) and nutrient balances (Tello et al. 2012). In the current work we develop our proposed methodology only for one of these municipalities (Sentmenat).

On the basis of the sources detailed in the methodological annex (the Cadastre of 1841, the Municipal Census of 1855, and the Amillaramiento of 1850—a list of plots and their ownership) we have resampled the size and composition of the funds (farmland and livestock) owned by 193 agricultural HHs, which means 86% of the ones that appear as farm labourers in the Municipal Census of 1857. To those numbers we must add 51 registered agricultural HHs with no access to land or livestock. We must note some aspects about the time point selected in both Chapters 4 and 5.

Although we will generally refer to 1850, given that the main historical sources used to account landownership and land uses were closer to this date, other historical records only provide us other type of data for later dates that range from 1850 to 1880. This is especially relevant for cash flows, as most of its sources date from 1870-1880 (see Table 4.J). Despite this, only changes in relative prices would deeply affect our results, specially those between wages and prices of agricultural

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products. Indeed, the prices and wages used are coherent among them as all of them are refered to the mid-1870. In doing so, we are assuming that landownership distribution and farmland uses had a high inertia, with only small and slow changes from 1850 to 1880. This also means that the results are refered to this whole period. Indeed, they are more aimed at revealing some structural functionings of this epoch, than some short-term historical changes.

Our sample then comprises 244 HHs, which covered 63% of the total area (see Section 4.A.1). To establish the different subgroups in the sample we used the threshold of minimum access to the necessary land for the reproduction defined by Padró et al. (forthcoming) for that agroecosystem. By means of a linear programming model this work simulates the dynamics established between the household composition of fund-elements (needs/capabilities) and the biophysical conditionings. In this case study we have established through technical coefficients and consumption standards that the average household c.1850 (5 people; 2 dependent persons) needed 4.36 hectares of total surface (including crops, grasslands and forest) to cover its basic needs and replenish the soil fertility and animal feeding cycles. From this reference farmland area, we have categorised HHs into five groups: (i) the ones that had no land (21% of the total); (ii) the ones that had up to 2.18 ha (26%); (iii) between 2.18 and 4.36 ha (23%); (iv) between 4.36 and 8.72 (18%) and (v) more than 8.72 ha (12%). Figure 4.3 describes the cumulative area according to the land uses as the different subgroups are incorporated.

Given that the HH size and composition affected many of the main flows analysed (Domestic and Family Work [DFW], availability of labour, food consumption and clothing expenses), we isolated the effect of the different HH models so as to be able to analyse the effect of inequality in access to farmland. To that end, we defined a representative HH model and selected a HH with those characteristics per each group (see Section 4.A.2). All the chosen HHs (Figure 4.4) were formed by 4 members, two of them active and two dependents, except for HH5 because in this subgroup there was not a HH with those characteristics. In that subgroup, we selected the HH with the most similar size and dependency ratio. The different HHs respectively owned 0, 1.5, 3.2, 7.9 and 34.2 hectares of farmland (Figure 4.4). Vine cultivation prevailed in HH2 and HH3, while the share of rainfed and/or irrigated cereals and woodland increased in larger HH. In a similar way, livestock density increased as the size of the land possessed did: 0.09, 0.09, 0.17, 1.34 and 5.54 Livestock Units of a standard weight of 500 kg (LU500), respectively.

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Figure 4.3 Distribution of access to land and livestock¹⁹

Source: Own elaboration, from the sources mentioned in the text. Legend refers to Irrigated (IRR), Rainfed (RF), Vineyard (VIN), Olive groves (OLIV), Woodland (WOOD), Pasture (PAST).

Figure 4.4 Features of funds of the selected Households

Source: Own elaboration, from the sources mentioned in the text.

19 Figure 4.3 will be analysed in detail in Chapter 5.

0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 80 90 100

Funds cumualtive percentage

HH cumulative percentage

AGR LAB

VIN

LIV OLIV

RF

PAST

IRR

WOOD

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4.4 Results