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Agrociencia
versión On-line ISSN 2521-9766versión impresa ISSN 1405-3195
Agrociencia vol.50 no.3 Texcoco abr./may. 2016
Water-Soils-Climate
Simulation of a CO 2 e tax to mitigate impacts from Chilean agriculture and livestock sector on climate change
1Departamento de Ingeniería Industrial, Universidad de Concepción, Concepción, chile. (tmunoz@udec.cl).
2Departamento de Ingeniería Industrial, Universidad de Concepción, Concepción, Chile.
In Chile, the agriculture and livestock sector contributes 40.6 % of total CO2e emissions. The aim of this study was to use an environmental extension of the Leontief price model to simulate the economic and environmental effects that the application of a tax would have on CO2e emissions from this sector. We used the methodology of the input-output table and the pricing model of Leontief to characterize the current price structure of the sectors of the Chilean economy; then we introduced several simulations rates of environmental tax on CO2e emissions in the agriculture and livestock sector, which affects the production costs of this and other sectors, generating impact on prices, consumer price index, private welfare, tax collection and emission reductions. The results showed that the application of environmental taxes in the agriculture and livestock sector does not significantly reduce emissions in Chile. In countries that have implemented this tax, a low tax of US$1 per Mg of CO2e reduces emissions by 0.2 %, an average tax of US$30 per Mg of CO2e reduces emissions by 4.0 %, a high tax of US$130 per Mg of CO2e only low emissions by 12.2 %. In the latter more restrictive scenario, the price of agriculture and livestock products would rise by 66.1 %, as well as the prices of forestry, food processing, aquaculture, wood industry, among other sectors, which will eventually result in an increase of 4.7 % of the consumer price index.
Keywords: Leontief price model; environmental taxes; CO2e emissions
En Chile, el sector agropecuario contribuye 40.6 % al total de emisiones de CO2e. El objetivo de este estudio fue usar el modelo de precios de Leontief para simular los efectos económicos y ambientales que tendría la aplicación de un impuesto a las emisiones de CO2e de este sector. La metodología fue utilizar la matriz insumo-producto y el modelo de precios de Leontief para caracterizar la estructura actual de precios de los sectores de la economía chilena, luego se introdujeron otras simulaciones de tasas de impuesto ambiental a las emisiones de CO2e del sector agropecuario, lo cual afecta los costos de producción de éste y de otros sectores, generando efectos en los precios, índice de precios al consumidor, el bienestar privado, la recaudación fiscal y la reducción de emisiones. Los resultados mostraron que la aplicación de impuestos ambientales al sector agropecuario no reduce significativamente las emisiones chilenas. En países que han implementado este tributo un impuesto bajo de US$1 por Mg de CO2e reduce las emisiones 0.2 %, un impuesto medio de US$ 30 por Mg de CO2e reduce las emisiones 4.0 %, y un impuesto alto, de US$130 por Mg de CO2e, reduce solo las emisiones 12.2 %. En este último escenario más restrictivo aumentaría el precio de los productos agropecuarios en 66.1 %, y también elevaría los precios de los sectores silvícola, industria de alimentos, acuícola, industria de la madera, entre otros, lo cual se traduciría finalmente en un aumento de 4.7 % en el índice de precios al consumidor.
Palabras clave: Modelo de precios de Leontief; impuestos ambientales; emisiones de CO2e
Introduction
In recent decades, climate change has increased global warming as a result of the increased emissions of carbon dioxide and other greenhouse gases. These gases are part of the planet’s nature and allow a temperature warm enough for the development of life. However, their emissions have increased due to human activity, mainly through the burning of fossil fuels in industrial processes, transportation, livestock and constant changes in land use for agriculture, so the warming process is perceived accelerated. According to FAO (2014) agricultural crops and livestock emitted 5-3 billion Mg of CO2 equivalent3 (CO2e) in 2011, increasing by 14 % since 2001. The increase occurred primarily in developing countries by the expansion of agriculture and livestock production. Chile's contribution to greenhouse gases generated by agriculture and livestock activity in the world is low (0.7 %), but Chilean emissions from this sector represent 40.6 % of the national total CO2e emissions4. Moreover, in the climate change summit in 2009 in Copenhagen, Chile pledged to reduce its greenhouse gas emissions (GHGs) by 20 %.
In several economic studies the Leontief inputoutput model is used to identify the direct and indirect emissions from the production chain (Alcantara and Padilla, 2006; Linping and Bin, 2010; Su etai2013), but in few of them the Leontief price model is used to analyze the impact of a tax on emissions.
Alcantara and Padilla (2008) evaluated the CO2 emissions associated with the set of productive branches of the service sector in Spain, and refuted the idea that a service economy is necessarily a cleaner economy. In Thailand, Limmeechokchai and Suksuntornsiri (2007) estimated the direct greenhouse gas (GHG) emissions in final energy consumption using national GHG inventories and also calculated the indirect energy and indirect emissions by using a Leontief input-output model. According to their findings, the electricity sector mobilized more energy flows and used mainly fossil fuels, but the highest total GHG emitter was the cement industry, whose main sources of emissions are industrial processes and the burning of fossil fuels.
In Brazil, Wachsmann et al. (2009) used an inputoutput model and showed that the contemporary trend towards a more service-oriented economy does not necessarily lead to a decrease in energy use in the country. In Spain, Gemechu et al. (2014) used a Leontief price model and showed that applying a CO2 tax on the most polluting sectors induces a minor increase in the consumer prices index, reduces emissions by 2 % and negatively affects private economic welfare.
In the literature review we found no studies about the introduction of taxes on agricultural emissions. Therefore, the objective of this study was to use the Leontief price model to simulate the economic and environmental effects that the implementation of a tax on emissions of CO2e of the agriculture and livestock sector would have under the hypothesis that the change in prices will negatively affect production generating a decrease in emissions. This model is an alternative to assess the direct and indirect effects of the new environmental tax on prices.
There are other more complex intersectoral methodological alternatives to assess the impact of a tax on CO2e emissions of the agriculture and livestock sector. For example, using an environmentally extended social accounting matrix (ESAM), which provides more comprehensive and complete information than the Input-Output Table on describing the relationships between economic activities, the circular flow of income and pollutant emissions (Xie, 2000), although it requires to integrate and reconcile a greater data set from various sources of information (Gallardo and Mardones, 2013) .
Another option is to use an ESAM as a database to calibrate a Computable General Equilibrium (CGE) model, which would allow to generate simulations of taxes on CO2e of the agriculture and livestock sector making behavioral assumptions for economic agents and the economic structure of countries (Liu and Lu, 2015; Guo et al, 2014.Mahmood and Marpaung, 2014) . However, a CGE model involves a complex computer modeling, increased requirement data for calibration, and less possibilities of replicating the results obtained, regarding the methodology chosen in this research.
Materials and Methods
The development of the Leontief price model used a set of data from an Input-Output Table of the Chilean economy (Central Bank of Chile, 2013), and the economic models required for the development of the Leontief model are described below in the context of a tax on CO2e emissions of the agriculture and livestock sector in Chile.
Input-output model
From the structure of the input-output table of a country it is possible to develop a highly simplified model of the economy, which helps explain the structural interdependence between the various economic sectors.
Assuming a Leontief production function, the level of production that the 2th sector sells to jth (X ij ) is a constant proportion of the production level of the jth sector (X j ):
Therefore, the technical coefficients record the need for input of each sector to produce one unit of output in this sector.
Assuming that X j and X ij , (1≤ i ≤ n, 1 ≤ j ≤n) are the n+n 2 endogenous variables, while the components of final demand net imports (y i ) including consumption, investment, government spending and exports are ո exogenous variables. Thus, the model for all sectors of the economy can be represented in matrix form as:
where A is called the matrix of direct requirements, as its matrix elements indicate the rate at which input per unit of product are demanded. Then, with matrix algebra we obtain the expression of the Leontief input-output model:
Where
Environmental extension of the input-output model
The CO2e emission intensity of an economic sector is defined as the total CO2e emissions per unit of production in this sector. Since CO2e emissions for most sectors come mainly from fossil fuels, there is a direct relationship between energy use and emissions of CO2e. However, the agriculture and livestock sector and forestry sector are an exception since most of their emissions come from other sources, not fuel use. In the agriculture and livestock sector those standing out are enteric fermentation, manure management, rice cultivation, agricultural land use, burning of agricultural waste, among other activities.
The forestry sector generates capture of CO2e emissions, so the value of such emissions is negative.
The CO2e emissions generated by the production of an economic sector consist of direct emissions from that sector, plus indirect emissions due to the production of goods and services by other sectors, but required by this sector. The direct emission intensity g is a vector of emissions in which each element represents the amount of direct CO2e emissions released per unit produced in sector i5. So you can get vector m, the vector of intensities of direct and indirect emissions:
On the other hand, the vector of environmental tax on production є is calculated by multiplying the emission intensity of each sector by a (φ) pollutant price, expressed in US $/t emitted (Gemechu et al., 2014).
Environmental extension of the Leontief price model
The input-output model also provides a framework for analyzing the structure of the prices of the various products of the economy. If p i , are the unit prices of the sector ith-, then the cost (in terms of inputs) of a product unit of sector j is: Assuming that sectoral prices are equal to the average cost of production, the unit normalized price of production in each sector j, p j . can be expressed as the total cost of intermediate inputs and expenditures on the total value added as follows (Llop, 2008):
where t j . is the ad ty on imports in sector j, p j m is the price of imports, and m. is the import coefficient.
The impact of the introduction of an environmental tax rate (ɛ j ) on the cost structure of sector j is evaluated by the following equation:
When defining the value added (wages, benefits) and the domestic value of the imported product, both per unit of product j as v j , the above equation can be rewritten as:
Which in matrix form can be written as follows:
where A* is the new matrix of technical coefficients that incorporates both ad valorem taxes and environmental taxes, and v is the vector of value added per unit of production which includes wages, payment to capital, and includes imported inputs. Thus, producer prices shall be determined according to the following matrix operation:
The environmental tax also affects the consumer price index (CPI) which increases from IPC to IPC
ɛ
, where p
j
. and
The impact of the tax on private real income from the change in consumer spending goods of sector j (C j ), can be evaluated by the expression:
This indicator can be interpreted as the change in the economic welfare of consumers after tax; any negative value reflects a situation in which there is a loss of welfare, since it indicates an increase in spending.
Changes in sectoral prices induced by the environmental tax could also be reflected in the total production. These effects can be evaluated under the assumption that the monetary values of sectoral output before and after the introduction of the tax will remain constant at the original levels6. Therefore, the new sectoral production of sector j after the environmental tax (
By taking into account that prices on the benchmark equilibrium are normalized equal to 1 (that is, p
j
=1) and using the proportionality assumption of the input-output model, in which the total emissions of CO2e of each sector are directly linked to the total output of this sector, we can approximate the new sectoral emissions (
Finally, the tax collection (R) is evaluated as:
Economic data used
This research used data from the statistical yearbook "Cuentas Nacionales de Chile 2008-2012" (National Accounts of Chile 2008-2012), Central Bank of Chile, and specifically the Input-Output Table 2010 (IOT 2010) was used. To make information manageable 111 economic activities of the IOT 2010 in 34 sectors were added, resulting in a square matrix of a 34x34 dimension.
The sectors used are: Agriculture and Livestock, Forestry, Aquaculture, Fisheries, Coal, Oil and Gas, Copper, Rest of Mining, Food Industry, Textiles and Leather, Wood, Pulp, Fuel, Chemical Industry, Non-Metallic Mining, Basic Metals Industry, Metalworking Industry, Furniture, Other industries, Electricity, Water, Construction, Trade and Hotels, Passenger Transport, Transportation, Telecommunications, Financial Services, Services, Public Administration, Public Education, Private Education, Public Health, Private Health and Other Services (Anex).
Environmental emission data
CO2e is a measure used to indicate the possibility of global warming associated with each of GHGs, ie, in addition to CO2, it also includes the effects of methane (CH4), nitrous oxide (N O) and other long life GHG compared to a reference gas, usually CO2. The Global Warming Potential (GWP) of these gases can be calculated for periods of 20, 100 or 500 years and 100 years is the most frequent value. For example, the 100-year GWP of CH4 is 25 and ΝΟχ is 298; that is, the emission of 1 million Mg of methane is equivalent to emitting 25 million Mg CO2e (World Bank, 2014).
Due to the variability and unreliability of official data reported by the Pollutant Release and Transfer Register (PRTR) in Chile, emissions were estimated using other sources of information. Thus, CO2 and CO2e emissions for the 34 sectors were obtained with data of fuels used and extracted from various sources such as industrial survey ENIA and National Energy Balance (BNE).
To transform fuel consumption data into CO2 emissions we used emission factors (EPA, 2014). Then to calculate CO2e emissions the procedure was similar, but also emissions multiplied by a conversion GWP factor for CO2, CH4 and N20 using a horizon of 100 years (United Nations Convention Framework on Climate change, 2014).
For the agriculture and livestock sector and forestry sector, data for CO2 emissions were estimated from fuel use and emissions data of CO2e were obtained from the report "Complementos у actualización del inventario de Gases de Efecto Invernadero (GEI) para Chile en los sectores de Agropecuario, uso del suelo, cambio de uso del suelo y silvicultura, y residuos antrópicos" (Accessories and updated inventory of Greenhouse Gases (GHG) for Chile in the sector of agriculture, land use, land use change and forestry, and anthropic waste) prepared by the Institute of Agricultural Research INIA (2010). Within CO2e emission data we took into account the capture of emissions obtained from the source "Suelos forestales y plantaciones forestales" (Forest soils and forest plantations), presented in the report. The CO2e emissions associated with livestock were estimated from the information extracted from the report "Producción Pecuaria, Periodo 2008-2013 y Primer Semestre 2014" (Livestock Production, 2008-2013 and First Half 2014) (Instituto Nacional de Estadística, 2014/National Institute of Statistics, 2014). To estimate emissions from this sector average GHG emission intensities for beef, small ruminants, pig, chicken, milk and egg were used, obtained from the report "Enfrentando el Cambio climático a través de la Ganadería" (Confronting climate change through Livestock) prepared by FAO (2013).
For the validation of estimates of CO2e there is no official figure available for comparison. However, according to World Bank statistics emissions for 2010 in Chile were 72.2 million Mg of CO2, very close to the value of the emission estimates made in this study of 72.0 million Mg of CO2.
Results and Discussion
Direct and indirect emissions of CO 2 e
In a scenario in which the final demand of sectors experienced an increase of one million dollars, for example, if the agriculture and livestock sector has an increase in its final demand of one million dollars (equivalent to 0.0126 % of agriculture and livestock GDP), the direct and indirect effects on all productive sectors would result in an increase of 3429 t of CO2e (2872 direct t and 557 indirect t).
Regarding CO2e emissions, the sectors that produce a greater direct impact are: Agriculture and Livestock (2872 Mg), Electricity (1741 Mg), Oil and Natural Gas (1641 Mg), Passenger Transport and Transport (1620 Mg). Those who produce a greater indirect impact are: Forestry (2065 Mg), Electricity (1287 Mg), Water (1193 Mg), Food Industry (892 Mg) and Aquaculture (635 Mg). The sectors with the greatest overall impact of CO2e emissions are: Agriculture and Livestock (3429 Mg), Electricity (3028 Mg), Passenger Transport (1773 Mg), Oil and Gas (1734 Mg) and Water (1200 Mg).
Direct emissions from the forestry sector have a negative value because the capture of GHG is greater than the direct emissions from fuel use and indirect emissions, creating a favorable balance capture. The wood sector has a negative value of indirect and total emissions, since this sector is an important consumer of the forestry sector inputs and emits directly only 23 t.
Simulation of tax rates on CO 2 e
The environmental extension of the Leontief price model allows assessment of environmental taxes, as the total effect of emissions is reflected in the cost of production of all the sectors involved.
![](/img/revistas/agro/v50n3//1405-3195-agro-50-03-271-gf2.png)
Figure 1 Environmental indicators of direct and indirect emissions of CO2e by the increase in the final demand of one million dollars. (Cuentas Nacionales de Chile 2008-2012 Banco Central de Chile, 2013).
While the agriculture and livestock sector receives the tax burden directly, other sectors are also affected indirectly as a result of sectoral interactions due to input demand.
Five tax values were simulated on emissions of CO2 and CO2e , US$l/Mg, US$5/Mg, US$10/ Mg, US$30/Mg (close to the world average value of CO2 tax) [1] and US$130/Mg (close to the world maximum values of the CO2 tax). These values are used to estimate the rate of environmental tax associated with the intensity of CO2e emissions in the agriculture and livestock sector which correspond respectively to 0.40 %, 1.99 %, 3.98 %, 11.94 % and 51.75 % of the products prices of this sector (Table 1).
Table 1 Changes in production prices due to tax payment on emissions of CO2e in the agriculture and livestock sector.
![](/img/revistas/agro/v50n3//1405-3195-agro-50-03-271-gt3.png)
Data obtained from Cuentas Nacionales de chile 2008-2012 (Banco Central de Chile, 2013).
The agriculture and livestock sector has the largest variation in prices because it is the sector where the tax is applied directly. For example, the price increases by 4.68 % for a tax of US$10/Mg of CO2e and 66.12 % for a tax of US$130/t of CO2e, ie approximately 0.48 % per dollar of tax.
In addition, there is a change in the sectoral prices of forestry [1], food industry, wood and aquaculture because an environmental tax in the agricultural sector affects the cost of inputs demanded by these sectors (which have not undergone direct taxation from CO2e).
Other economic and environmental indicators that can be obtained with the model correspond to the CPI variation, the increase in spending, total revenue and variation in CO2e emissions associated with changes in production.
Taxing the agriculture and livestock sector in Chile seems reasonable as it is the sector that emits more CO2e Mg. However, the results showed that it would generate small reductions of emissions in various tax scenarios. Although tax revenue increases, the private economic welfare would be diminished by the rise in the price of goods consumed (Table 2). In addition, we observed that the effects on the CPI are not negligible for higher taxes, a result explained by the share of agriculture and livestock products in the consumer basket (3-1 % fraction of expenditure according to the data of Final Consumption reported in National Accounts).
Table 2 Economic and environmental variables under the new tax on CO2e emissions.
![](/img/revistas/agro/v50n3//1405-3195-agro-50-03-271-gt4.png)
Data from Cuentas Nacionales de chile 2008-2012 (Banco Central de Chile, 2013).
The results obtained showed that an environmental tax of US$30 on CO2e emissions in the agriculture and livestock sector (value close to the average in countries that have implemented a CO2 tax) would lead to an increase in the consumer price index (CPI) of 1.01 %, an increase in spending of US$1282.4 million, a total tax revenue of US$1473-6 million and a reduction in CO2e emissions associated with a variation in the production of only 4.04 %. In addition, production of the agriculture and livestock sector and the total output of the economy would be reduced by 0.61 % and 0.03 %, respectively.
Conclusions
The simulation implemented in this study uses the environmental extension of the Leontief price model to investigate the economic and environmental impact of a CO2e tax on Chilean agriculture and livestock sector. The model showed that a restricted reduction of Chilean CO2e emissions would be achieved if a tax is applied to the agriculture and livestock sector per t of CO2e emitted, with an average decrease of 0.15% per dollar of tax.
But this economic policy would raise the prices of agriculture and livestock products, on average 0.48% per dollar of tax. As a result of the production chain, sectoral prices of forestry, food processing, aquaculture, wood industry would also raise, among others. Thus, the level of prices measured by the CPI would rise on average 0.03% per dollar of tax, reflecting the inevitable increase in spending for consumers, and consequently the loss of economic welfare.
Therefore, we concluded that the application of environmental taxes in the Chilean agriculture and livestock sector does not guarantee a significant reduction in emissions. As an example, a tax of US$130 per Mg emitted (high globally) would only reduce emissions of CO2e by 12.2% in Chile, whereas the agricultural sector emits 40.6% of the country's total emissions.
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3It is a metric used to compare the emissions from various greenhouse gases based on their global warming potential.
6This assumption is restrictive and assumes a unitary elasticity; for other less restrictive assumptions the use of a CGE model would be required
7La ecuación (4) permite obtener la tasa de impuesto ambiental de cada sector, la cual se usa para determinar el shock en los precios sectoriales, y finalmente sobre la producción. Así, la ecuación (14) solo estima las emisiones directas una vez que la producción sectorial ha cambiado
Received: March 01, 2015; Accepted: November 01, 2015