The entries in each column show the structure of the purchases made by the agents identified in the column heading. Each of the 'C' commodity rows identified in the model can be sourced locally or imported from overseas.
Creation of an investment matrix
Thus, column 1 of the aggregate investment matrix (agriculture) matches the first two IO industry columns of the 118x75 use matrix with buyer prices ('agriculture' and 'forestry'). The combined intermediate usage of these two IO columns in each of the 118 rows is summed together.
Disaggregation of basic values, margins and taxes into Domestic, EU and non- EU routes
In the case of the export columns, all taxes are assigned to the domestic matrix. One must use the domestic row shares in the GDFCF column of the domestic and import duty matrix AND the import tariffs in the GDFCF column of the tariff matrix calculated in section 9.
Disaggregation and re-representation of tariffs in the 2000 data
Similarly, EU and non-EU indirect taxation (margin) investment matrices are derived by using the GDFCF columns of the EU and non-EU taxation (margin) matrix. To the base values of the non-EU investment import matrix, we add the import duty on the investment matrix, which in accordance with ORANI gives the cif PLUS tariff values.
Subdivision of labour into different occupations
From the scaled 10x75 matrix of total employed labor, we calculate a 10x75 matrix component for paid labor using the share of paid labor (of total industrial labor) from the IO Spanish data for each of the 75 industries. Using the full-time share data for each industry, full-time workers by occupation are derived for each of the 75 industries.
Disaggregation of agricultural land and remaining value added components Since the focus of the study is on the agricultural sectors, more effort has been
This matrix is subsequently adjusted to correspond to column sums of the Spanish IO data by industry (i.e. total number of employed persons (paid and unpaid). The paid work matrix is then split into full-time and part-time paid work. the remainder (i.e. total paid work minus full-time paid work) is the part-time job header matrix.
Using data from INE, it is possible to access average (gross) salaries for the 10 occupational types for both full-time and part-time labour. This procedure gives a part-time and full-time 10x75 matrix of wage bills, which when added together gives the total wage bill for the 10 occupations across 75 industries. An additional approach to apportion value-added components (besides labor wages given) was through the use of the 'Red Contable Agraria Nacional'. RECAN, 2002) provided by the Ministerio de Medio Ambiente y Medio Rural y Marino for the year 2000.
Creating ‘Inbound’ Tourism accounts
In addition, detailed data on land use (irrigated and non-irrigated) by agricultural activity are also available in the 'Anuario de Estadistica Agroalimentaria' (MARM, 2009b). Furthermore, if we compare the total inward base expenditure on foreign tourism in the satellite accounts (€32,641 million) (excluding margins) with the IO accounts (€32,738 million), the numbers are close, but do not match. In the case of services, the mappings are one-to-one, as the breakdown of satellite accounts is relatively detailed.
In the case of restaurants, hotels, travel agency services, rentals, and cultural and recreational services, domestic and foreign tourism expenditures from the satellite account are removed from the domestic private household expenditure account (non-domestic private household row values are zero and the export account row values are also zero in the underlying IO data). In the case of tourism demand for 'goods' (as opposed to 'services'), domestic and foreign expenditure is systematically removed from the private household accounts. In the agricultural aggregate, we thus mapped arable, livestock and fish rows from the IO table.
Disaggregating the private household account by income sub-groups
So if 10% of a private household's consumption of domestically produced crops is now spent on domestic tourism, then the 10% margin and tax for that cell is now collected at the expense of domestic tourism. Thus, we assume that the tax rate and margin per item line are constant per user (column). Once the 118x2 matrices for domestic and foreign tourism base prices, taxation and margins have been calculated, the expenditure base values in the private households and export columns (transport rows only) must be reduced by the appropriate amounts so that the database remains balanced.
So if the domestic purchases of arable products make up 3% of the household expenditure of 'food and drink' of private households, then this share is uniformly applied to the domestic purchases of 'arable farming' of all 8 households. The tax and margin matrices for each of the households are broken down using spending shares in basic prices. We thus again assume that the margin and tax rate are constant for each good/service in all households.
Disaggregation of agro-food related commodities (rows) and activities (columns)
In addition, additional columns in the basic, tax, and marginal investment in food submatrices use the same use shares as in intermediate input equivalents. 25 In the RECAN database, intermediate cost categories are divided into: seeds and plants; fertilizer; Production values for the four industries in 2000 are taken from Chapter 31 (‘food industry’) of the Anuario de estadistica agroalimentaria (MARM, 2009b).
Moreover, the additional columns in the basic food investment, tax, and margin submatrices use the same use shares as in the intermediate input equivalents. In the EU and non-EU import intermediate matrices, agricultural and food purchases are subdivided using DATACOMEX import trade data from the Ministerio de. In the EU and non-EU import matrices, the private households and tourism agriculture and food purchases are also broken down using DATACOMEX import trade data.
Creation of Bio-fuels row and column accounts
For example, the share of domestic energy consumption in biodiesel is the same as in the vegetable oil and grease anchor industry, from which biodiesel is removed. For example, in the case of the industry columns, the biodiesel taxes and margins items are split from the vegetable oils and fats taxes and margins column, while the biodiesel row taxes and margins are split from the 'refined fuels' row taxes and margins. To complete the primary agricultural component of the MAKE matrix, the remaining columns (industries) producing field and livestock goods in the original MAKE matrix are 'forestry', 'wholesale trade', 'retail trade', 'public administration' and 'not - market-related activities'.
In the case of the 'other foodstuffs' sector in the standard IO Spanish data, we have to split 'vegetable oils and fats', 'process sugar', 'animal feeds' and 'other foodstuffs'. Since the 'vegetable oils and fats' and 'animal feed' rows are already split in the standard IO Spanish tables, it is only necessary to split sugar processing products from 'other food products' in all user industries. As in the USE tables, the MAKE matrix divides biodiesel production into 'vegetable oils and fats'; 'bio-ethanol1' is separated from 'other food processing'; and bioethanol2 has been spun off from the “chemical” industry.
Creating a 2005 database
In the case of bioethanol1 (cereal-based ethanol), imports of undenatured and denatured ethanol (TARIC codes 220710 and 220720) are used, which are broken down by EU and non-EU routes. Total industry cost targets (column) are taken directly from the Spanish MAKE IO 2005 matrix in the non-agricultural and biofuel sectors. Thus, each of these individual cell entries in the Spanish IO accounts for 2005 is used to update the domestic intermediate consumption of non-agricultural products.
Information on the production of investment goods in the Spanish IO accounts for 2005 is limited to a single column. In the modernization process, this coordination is carried out with the additional help of the COICOP classification system. The export columns in the Spanish IO accounts for 2005 are already split according to EU and non-EU use.
Additional data flows for the Dynamic Investment module
Elasticity parameters and Agricultural Policy parameters 1 Elasticity parameters
Thus, in the upper layer of the land nest, the CET between permanent pasture and composite livestock and land use for cereals/oilseeds42 is very inelastic (0.125). In the bottom layer of the nest, the CET between grains, oilseeds, forages, textiles and primary sugar is 0.5 (identical to that of the standard GTAP model). Given Engel's law, poor households show a higher income elasticity than wealthier households, reflecting the larger consumption share of 'necessities' in the consumption bundle.
In the tourism accounts, total (ie foreign and domestic) tourism expenditure is Leontius' aggregate of goods expenditure. In the case of milk, the rent estimate was taken from Jongeneel and Tonini (2008), which is based on When examining the agricultural sectors, intervention prices are used in the cereals (except rye), rice and sugar sectors, but not in the production of oilseeds and pulses (peas, beans, lupins).
Description of the CGE database
The quota rent (€ 660 million) corresponds with our estimate of the value of the milk quota rent in the reference year.49. A closer look at the trade data is provided in Table 7 below for a stylized aggregation of commodities. For example, the agriculture and fisheries sector (i_Agrfish) produces €38,321 million (or 99%) of the total domestic sales of agricultural and fish products (€38,681 million).
By convention, the total cost in each of the industry columns is equal to the disaggregated breakdown of costs in the first four columns of the absorption matrix. This accounts for the majority of Common Agricultural Policy (CAP) payments for the sector (see sections 14.4 and 17.10). Finally, in the investment and final demands columns of the absorption matrix, the breakdowns of the expenditure aggregates of GDP (in Table 6) are presented.
Brief Conclusions
MARM (2009a) Ministerio de Medio Ambiente y Medio Rural y Asuntos Marítimos, Servicio de Estadística, http://www.mapa.es/es/estadistica/infoestad.html, Encuesta de Precios del Suelo (2000 y 2005), Gobierno de España. MARM (2009b) Ministerio de Medio Ambiente y Medio Rural y Marítimo, Servicio de Estadística, http://www.mapa.es/es/estadistica/infoestad.html, Anuario Estadístico Agroalimentario (2000 y 2005), Gobierno de España. MARM (2009c) Ministerio de Medio Ambiente y Medio Rural y Marítimo, Fondo Español de Garantía Agraria (FEGA), Gobierno de España, http://www.fega.es/PwfGcp/es/el_fega/presupuesto/index.jsp. 2003) El modelo IMAGE: herramienta de toma de decisiones para la industria alimentaria, Departamento de Economía, Trinity College, Dublín.
Ministerio de Industria, Comercio y Turismo (2005) Plan de Energias Renovables http://www.mityc.es/desarrollo/seccion/energiarenovable/plan, Gobierno de España. Sugar beet Oils and fats Textiles Vehicle maintenance Non-market rail transport services Market sanitary services Oilseeds Processed sugar Carrying clothes Railway products Non-market other land transport services Non-market sanitary services Textile crops Livestock feeds Leather Aviation and aircraft products Air transport services Market veterinary services Other Indian crops Other food Leather products Other transport materials Other services related to transport Market social services Fodder crops Alcoholic beverages Wood Furniture products Non-market services related to transport Non-market social services Grapes for wine Non-alcoholic beverages Paper and card Other manufacturing articles Travel agent services Market industrial cleaning services Olives for oil Paper and card products Residential construction Non-market travel agent services Non-market industrial cleaning services. Resources - 9 Pharmaceutical products Insurance and pension services Non-market news, drama and arts services Table grapes Forestry Other chemical products Financial intermediation accessories Cultural and sporting activities.