Final revision 6-09-2016

Jamaican Agriculture Report: Policy Impacts and Greenhouse Gas EmissionsReport prepared by Tim Josling

This report presents the results of a study that combines data on the emission of greenhouse gasses (GHG measured in CO2 equivalents) from farming activities with the incidence of policy incentives (transfers to the farming sector as measured in the Agrimonitor database) for Jamaican agriculture. The objective of the report is to look at Jamaican agricultural policy from the viewpoint of greenhouse gas emissions in the context of attempts to ensure consistency among policy objectives and nationally established targets related to the current climate change discourse. Specifically: are the products that contribute the most to GHG emissions also those that are more highly protected? Or are incentives arising from policy in accord with objectives to mitigate GHG emissions?

The broader context in which this chapter should be seen is the future pressures that will be imposed on Jamaican agriculture. This has been described by Vosti, et al. as follows:

“The world demand for food will increase by between 50% and 85% from 2009 to 2030. The LAC contains some of the few remaining large areas available in the world that could be converted to agriculture; there will be great pressure on the region to do so to help meet global food needs. Increased demand for animal products in general, and for beef products in particular, will intensify the pressure to expand pasture area in LAC due (in part) to the extensive nature of cattle production systems and relatively low stocking rates in the region. A substantial part of the growth in demand for food will be met by intensifying production activities on existing agricultural lands; this combination of agricultural extensification and intensification will have environmental consequences – our focus here is on greenhouse gas (GHG) emissions.” (Vosti, et al, 2012)

IntroductionThe contribution of agriculture to greenhouse gas emissions is of interest in the context of obligation of the Government of Jamaica (GOJ) to communicate the level of GHG emissions to the United Nations (UN), under the provisions of the UN Framework Convention on Climate Change (UNFCCC). The first such communication took place in 2000, with a second communication in 2011. A study conducted for the third national Communication brings the data up to 2012 (Aether, 2015). This contribution of the farming sector to the “inventory” of GHG emissions is of interest in the debate on ways to mitigate such emissions, and will become

even more significant as comprehensive attempts are made to reduce GHG emissions in the economy as a whole.

The Paris Climate Change Agreement of December 2015 (COP 21) called for “intended nationally determined contributions” (INDC) to be defined by signatories. The levels of INDC for the countries of the Caribbean are reported in a recent IICA study (IICA, 2016). All but one of the Caribbean countries have included agriculture as a relevant sector in terms of GHG emissions and potential for GHG reductions. Jamaica’s participation in this global effort will require some adjustments to be made that will include agriculture. 1

At the same time, the development of agriculture in Jamaica is in itself of importance in the economic and social life of the country. To assess the contribution of policy to the objective of agricultural development a study by FAO and the IDB estimated producer support estimates (PSEs) for the sector, following the methodology used by the OECD in its monitoring of the agricultural policies of its members (IDB/FAO, 2012). This information has been updated to 2014 in the current report and is contained in the IDB Agrimonitor database that has been constructed to cover many of the countries of Latin America and the Caribbean (IDB, 2016).2

An additional study, also conducted by the FAO and the IDB, looked at taxation in agriculture in Jamaica, and calculated the benefits that the sector receives as a result of the tax code (FAO, 2012). A third study from the IDB and FAO collaboration examined the question of the vulnerability of Jamaican agriculture to extreme weather events (IDB/FAO, 2013). Though not limited to events linked to climate change, the results emphasize that Jamaica is a high weather-risk country and that the agricultural sector is particularly vulnerable. This current study builds on the analysis of these earlier studies and brings together the information necessary to examine consistency among objectives. In particular, it focuses on the GHG emissions from the agricultural sector, an issue not covered in the study of the impact of climate change on the agricultural sector. It also attempts to bring the previous analyses of policy incentives up to date by using the most recent data available.

The Aether study and the Agrimonitor database present a welcome opportunity to address the question of the link between commodity policy on the one hand, which provides support for particular sectors, and the environmental impact of those sectors on the other hand as shown by their contribution to GHG emissions. The matching of GHG emission data and policy support is not precise, as emissions are dependent on farming practices and conditions that can vary and the policy incidence depends on the market conditions as well as the details of policy administration. But the evidence from the comparison represents a starting point for more detailed research based on the links between farm and climate change policy.

1 Jamaica is not an Annex 1 country under the current Climate Change agreement and therefore has not so far been required to undertake reductions. However, the nature of the INDC targets are “voluntarily mandatory” in that by signing and ratifying the agreement the countries concerned commit to their targets.2 For more detail on the Agrimonitor database see http://www.iadb.org/en/topics/agriculture/agrimonitor/agrimonitor-pse-agricultural-policy-monitoring-system,8025.html.

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Data and MethodsThe data on GHG emissions was combined with the policy transfer data in a way that focused on the correspondence between commodity policy indicators and climate change measures. Some assumptions were required to make the mapping possible. These involved the allocation of various activities responsible for GHG emissions to individual commodities. The most important of these assumptions are noted here.

The emissions data from the Aether study cover direct GHG release from the farming activity itself. The farms’ use of fuel is also captured along with corresponding data from other sectors (energy, transportation, etc.) in the Jamaica inventory. The focus in the Aether report is on direct emissions from livestock and from crop cultivation. In this study we attempt to include the GHG emissions from the use of fuel and energy inputs into the farming process on the basis of additional information in other parts of the Aether data files. This requires some additional assumptions about the nature of fuel and energy use by crop.

Sequestration of GHG by agricultural crops is not measured in the Aether study. The positive contribution of crops and in particular tree crops made through the absorption of GHG needs to be included in the accounting in order to take into consideration this key aspect of land use. In the UN inventory the category of GHG accounting known as Land Use and Land Use Change and Forestry (LULUCF) was calculated, but was not specifically included in the agricultural inventory. Estimates of sequestration were recorded in the Aether database under the headings of “changes from forestry to other uses.” But In the absence of data on sequestration by agricultural crops such as coffee and sugar some preliminary estimates were incorporated in this current study to cover this informational gap.3

The choice of crops and livestock activities differs between the Aether study and the FAO/IDB estimates incorporated in the Agrimonitor database. Aether groups 56 crops under 13 categories together with eight livestock sectors. Some crops such as cocoa are not considered separately in that commodity list. The Agrimonitor database identifies 10 crop sectors, including cocoa, and five livestock types. It does not include separate support estimates for pulses, condiments, plantain, tubers or sorrel, though there is a category for “other products.” On the livestock side, Agrimonitor does not include support estimates for turkeys, horses, mules, sheep and rabbits. More significantly, goats are not included in the Agrimonitor database (there are no specific goat sector policies) whereas Aether includes them as a class of livestock that is important in the Jamaican livestock sector. In the present study the emphasis is on those products that

3 The sequestration issue remains a cloudy area in the measurement and reporting of GHG emissions. Different countries use different sequestration measures when reporting to the UNFCCC. The UNFCCC does not fully incorporate these data, explaining that “since the communicated amounts by the Parties to the Convention in many cases did not include data on emissions by source and removals by sinks from land use, land-use change and forestry, or when included these emissions by source and removals by sink were estimated using different methodologies, these data were not included”.

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are included in the Agrimonitor database and account for about 70 percent of the value of production in Jamaica. The mapping of the two sets of data is described below.

GHG emissionsThe Aether study collected data on the types of emissions that are shown in Table 1. The calculations of the magnitude of these emissions were achieved by estimating the use (in Gigagrams) of GHG emitting products such as nitrogen fertilizer (synthetic nitrogen and urea) and limestone, and taking into account the hectares in organic farming. The IPCC emissions factors were used to convert these quantities into presumptive emissions of N2O in both direct and indirect emissions from managed soils. Similarly, emissions of CO2 from liming, N2O from urea and corresponding GHG emissions from rice cultivation and biomass burning were derived. Adding up the GHG estimates for these different types of activity and converting to CO2 equivalent enabled Aether to come up with an estimate of the GHG emissions for the soils (and by implication the crops grown in those soils).

The contribution of individual crops to the total is not calculated in the Aether report (see below) though data is given on hectarage and production of many crops. 4 The data on hectarage is however used in that study to estimate the land in three different crop types: nitrogen-fixing crops (such as dry beans), non-nitrogen fixing grain crops (such as corn and rice) and roots and tubers (such as potato). These groups were used to correspond to emission factors identified in the IPCC guidelines (2006).

Table 1: List of categories and emissions (gases) estimated in the Aether study

Soils:Direct emissions from managed soils – N2O (Synthetic; Organic; Grazing Animals; crop residues)Indirect emissions from managed soils – N2O (Soil Depositions; Leaching, runoff)Liming – CO2

Urea application – N2ORice cultivation – CH4

Biomass burning – CO, NOx, N2O, CH4, NMVOCIndirect GHG: NOx and NMVOC

Livestock:Enteric fermentation – CH4

Manure management – CH4 and N2OIndirect emissions from manure management – NMVOC, NOX and CO

Source: Aether (2015), page 1

4 Aether uses the 2006 IPCC Guidelines, both Tier 1 and Tier 2 methods, depending on the availability of data. For emission coefficients the study takes an average of North American and Latin American (intensive and extensive) assumptions.

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The calculations for livestock emissions are given in much more detail in the Aether study. The population numbers are given for the major types of livestock, based on official sources. The coefficients for emission factors were again drawn from those found in the IPCC Guidelines (IPCC 2006). The calculations for livestock emissions by livestock category are dominated by N20 from manure management and CH4 from enteric fermentation.5

The 2006-2014 average calculated emissions from the various categories of activity noted above as estimated in the Aether study are given in Table 2 (annual figures are shown in Annex Table 3). The total GHG emissions from agriculture for 2012 were estimated at 4,336 Gg CO2equivalent. The average for the period 2006 to 2014 as shown was 3,765 Gg CO2 equivalent.6 Of the varied contributions to this total, N2O from manure management accounts for 43 percent of total crop and livestock emissions. Other major contributions came from N2O emissions from organic fertilizer and the leaching of soils.

5 Enteric fermentation refers to the release of methane from the fermentation of feed as a part of the normal digestive process of ruminants. Some methane is released by anaerobic management of manure. N20 is released in the breakdown of nitrogen in manure and urine. 6 This total was obtained by adding each of the individual emission categories in the Aether study. The FAO GHG database indicates a total emission of only 904 Gg CO2e on average for Jamaican agriculture over the period 1990-2012, the total falling from 1,063 Gg in 2003 to 636 Gg in 2012 (FAO, 2014).

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Allocation of Emissions to Agrimonitor CommoditiesThe GHG emissions were allocated to the commodities identified in the Agrimonitor database, using the information updated to 2014.

Allocation of the total emissions estimated for soil management (direct and indirect N2O emissions from fertilizer and crop residues) required several steps. The Aether study gives a

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breakdown of the land area and production (harvested weight) from MOAF data but makes no allocation of the GHG emissions from these individual commodities. To make the comparison with policy incentives it was necessary to make assumptions of the commodity share of their total emissions on the basis of crop areas. The Aether commodity harvested areas are grouped in that study under 13 headings. The mapping of these groups with the Agrimonitor commodities is given in Table 3. These are then used to estimate emissions from soil management by Agrimonitor commodities by scaling the share of that commodity in the Aether group.7

As noted above, the Aether data spreadsheets do include an estimate of the emissions from the use of fuels for farming activities associated with agricultural commodities. This data is not broken down into the emissions from specific activities such as land preparation, fertilizing and weed control and harvesting. In addition, many crops require some first stage processing and some transportation to get them to the market. Each of these activities uses fuel and energy, and thus a full inventory for agriculture would include the GHG emissions from these processes.8 In the absence of such detailed information calculations were made on the use of fuel for field operations as well as energy for harvesting and for processing. In the case of energy usage the national totals were scaled down to correspond to the approximate share of agriculture in total use energy in the Jamaican economy.

The livestock categories included in the Aether report fit more conveniently into the sectors identified in the Agrimonitor database. This allows the estimates of enteric fermentation to be used with minimal reallocation. Similarly, it is possible to allocate (direct and indirect) emissions from manure management and animal grazing to livestock sectors. The emission estimates from the Aether groups of livestock are incorporated in the worksheets based on Agrimonitor livestock products. The levels of emission for livestock are thus based on Aether with little need for modification.

7 The inclusion of an “other products” category in the Agrimonitor database picks up some of the commodities that are included in Aether but not separated out in Agrimonitor.8 The data transmitted to the UNFCCC includes fuel and energy as separate sectors. Allocation to various farming activities is not necessary under the IPCC guidelines for the inventory. The Aether spreadsheets contain detailed allocations on fuels used in sugar and in “agriculture, forestry and fisheries.” Assumptions were made to scale this back to fuels used in agricultural product activities.

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The GHG emissions by Agrimonitor categories of products are presented in Table 4. The total GHG emissions under the two groupings of products are compatible: 3,765 Gg CO2 e in the case of the Aether groups and 3,831 Gg CO2 e for the Agrimonitor categories.

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Once included in the worksheets based on the Agrimonitor commodities the comparison with the policy transfers is straightforward. The appropriate measure from the Agrimonitor database for this purpose is the Producer Commodity Specific Transfers (PCST). This indicator measures the transfers that are specific to a particular commodity, and thus directly influence the incentives to produce that crop or animal product.

Comparison Among SectorsThe contributions of the sectors identified in the Agrimonitor database to total sector GHG emission from agriculture are shown in Table 5. The first three columns of the table show the share of the value of output along with the share of the commodity-specific level of support and of the GHG emissions for the average of the period 2006-2014 (Annex Tables 1, 2, and 4 give the yearly values of these variables). The share in the value of production (column 1) shows the dominance of three products, poultry, yams and sugar as well as a composite group of “other products” mainly vegetables, pulses and condiments. Over one quarter of the value of production in Jamaican agriculture comes from the poultry (broiler) sector. The share of the total transfers by sector (column 2) is a reflection of policy priorities. The single commodity transfers by sector in Jamaica vary significantly and appear to be unrelated to the value of production. The share of transfers to the sugar sector, for instance, is four times the share of that product in the value of production. The poultry sector receives an overwhelming share of

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the commodity transfers, as reported elsewhere (FAO/IDB, 2012). As several commodities have negative transfers (usually because farm prices are well below the reference prices for those commodities) the total support to the poultry sector from Commodity-specific policies is greater than the net total for the whole sector.

Are the sectors that account for most of the value of output also those that cause the greatest emissions of GHG (as shown in column 3)? The relationship is certainly not direct, as some products that have a low profile in terms of the value of production can still contribute significantly to the GHG emissions. The share of bananas in the value of production is less than three percent but the sector accounts for 6 percent of GHG emissions. The poultry sector is responsible for almost forty percent of the GHG emissions, exceeding its high share in the value of production (26 percent). Due to the significance of enteric fermentation by ruminants, the beef sector appears to be responsible for 10 percent of the total GHG emissions from agriculture, though only contributing 3 percent of the value of output. Among other sectors that contribute significantly to GHG emissions are sugar cane that accounts for about 19 percent of total GHG emissions but contributes only 8 percent of the value of agricultural output. Coffee and bananas also contribute significantly to GHG emissions. Sweet potatoes and yams, pineapples and other products (mostly vegetables) contribute less to GHG emissions than would be indicated by their share in the value of production. The implications for policy are discussed below.

The importance of accounting for crop sequestration was mentioned above. For an accounting of the GHG emissions associated with activities the storage of carbon in growing plants and associated soil organic matter (carbon sinks) should be included. Again, data is not available on a consistent and complete basis. As a result, the sequestration amounts for crops were chosen on the basis of limited studies on individual tree crops.9 Sequestration amounts are included in the calculation in the next section on the cost of agricultural carbon emissions by crop: to ignore such benefits would be to bias the estimated against the production of tree crops and sugar cane.10

9 Annual crops also sequester carbon, but this is largely released after harvest and therefore is not relevant for GHG accounting on an annual basis. The use of plant material as fertilizer is included in the GHG inventory under soil management. 10 In the case of sugar cane another important assumption needs to be made. The use of bagasse (a by-product from the sugar mills) as a source of fuel is an important part of the sugar economy. The burning of bagasse releases greenhouse gasses, but the amount of CO2 emitted is generally less than the CO2 absorbed by the sugar cane during the growing stage. So the assumption is made in the tables below that the use of bagasse as a fuel in agriculture has no net GHG emission contribution. In broader terms, as a biofuel bagasse contributes to the reduction in the use of fossil fuels.

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Source: Author’s calculations based on Agrimonitor and Aether

Costing the EmissionsThe intended contribution of this report is to put together the estimates of GHG emissions with those of incentives from agricultural (commodity) policy. Putting the two together is facilitated by using a common unit: the monetary value of GHG emissions and the monetary value of transfers based on commodity output. To use a monetary unit therefore requires a price of carbon, as this allows the cost of GHG emissions to be compared with financial transfers to producers of particular commodities. A price of carbon does not exist as an observable market price in all countries. However, some 44 countries now have carbon markets in the form of exchanges based on tradable permits for CO2 emissions. Thus one can either posit that the Jamaican agricultural sector has to purchase such permits in a carbon marketplace or that the government taxes the sector to offset the cost of carbon emissions. In either case, it is straightforward to apply a price to carbon emissions and so arrive at a financial equivalent of GHG emissions.11

11 The price chosen for a unit of CO2 or equivalent is a key assumption. The figure underlying the tables presented here is US$10 per metric ton of carbon dioxide. The carbon markets in countries in the region show a price that is somewhat lower than this ($5 per ton in Chile and up to $4 in Mexico). However, the carbon price tends to be much higher in other regions: $62 in Switzerland and $16 in France and the UK (IMF sources). Should the carbon price reach the level in Sweden in 1991 ($168 per ton) the ACE would approach two-thirds of the value of agricultural production in Jamaica. At a price of $US255 the ACE would equal the total value of

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The measure used here to represent this financial equivalent is called the Agricultural Carbon Equivalent (ACE) expressed as a value in local currency. The GHG emission data is expressed in terms of J$ and modified to include the value of sequestration. The share of commodities in the total ACE is shown in Table 5 (column 4) for the period 2006-2014. (The annual values are presented in Annex Table 5). The shares are broadly comparable to those of the GHG emissions, as in most cases the sequestration adjustment is not large. However, some products such as sugar cane, bananas, coffee and cocoa show up as contributing less to the ACE than to GHG emissions as a result of the positive financial benefit from sequestration to offset some of the cost of GHG emission.

Net Valuation of CommoditiesPutting GHG emissions in a monetary unit allows for an interesting comparison between GHG policy and farm policy. One step in this direction is to consider the value of production less the carbon emission cost (ACE). The result changes somewhat the order of sectors. Poultry is still the dominant sector, with about 26 percent of the value of production net of externalities. But this is significantly less than the share of poultry in the value of production. Sugar cane also appears less valuable to the agricultural economy when the cost of emissions is taken into account: the sector contributes 20 percent of the value of production but less than 8 percent when emissions costs are included. By contrast yams appear to have a higher weight in the value of production net of emission costs than in gross production value. These relative shares are illustrated in Figures 1 and 2 below: Figure 1 shows the average share of production by commodity for the period 2006-2014 and Figure 2 the share when the costs of GHG emissions is included. (The annual data is shown in Annex Table 6.)

A further step in the examination of the links between policy and GHG emissions is to subtract from the value of production the combined impact of GHG emissions (ACE) and transfers from commodity-specific policy (SCT). This is shown in Figure 3: the annual data are reported in Annex Table 7. This measure shows the value of production net of both the cost of carbon emissions and the transfers through commodity policy. The interpretation of this calculation is that this would be the value of production (assuming no change in hectarage or cattle numbers) if producers had to pay for the GHG emissions and were obliged to forgo the transfers through the commodity-specific programs. This can be considered as a rough approximation of the value of output at world prices with a carbon tax offsetting the GHG externalities. This in turn can be considered as a partial estimate of the net social value (NSV) of the output from the sector.12

Estimating the positive contribution of the Jamaican agricultural sector to the economy (VoP-SCT-ACE) tells a significantly different story about the importance of various crops and livestock products when these adjustments are made. Crops that have relatively little support (or in several cases negative support) and do not have a high ACE value show up as making a more significant contribution to the net benefits of the agricultural sector. Those with significant support and high levels of GHG emissions make up a smaller share of the net benefit of the

production. 12 A full NSV calculation would have to take account of all external costs and benefits from the sector besides GHG emissions and policy actions.

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sector. Thus the contribution of poultry to the NSV of the agricultural sector is only 8.1 percent, that of sugar cane is 4.1 percent, and beef contributes less than three percent to the net social value of production. However sweet potatoes contributes 7.5 percent of net social value (relative to less than two percent of gross value of production) and yams (16 percent) and other products (37 percent) are also more significant when GHG emissions and policy transfers are taken into account. This latter category is mainly vegetables and other annual crops that have no or only limited price support policies, use less inorganic fertilizer and have no issues with manure management.

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Interpretation of ResultsThe main objective of combining GHG emission data with that on policy transfers is to see to what extent the transfers are encouraging or reducing GHG emissions. If the transfers encourage sectors with high GHG emissions then there is a presumption that the climate change and agricultural policies may be at cross-purposes. The dominance of the poultry sector, for instance, is in part due to commodity policy transfers (in this case by high tariffs). This encourages a sector that is responsible for the emission of considerable amounts of GHG. This suggests that the policies of transfer from consumers to producers of poultry are not entirely consistent with the need to reduce GHG emission.

A relationship between sectors with high support levels and those with high GHG emissions is in itself of interest in the context of achieving the targets set in the INDC. But the connection has to be handled with care. On the one hand the high support levels encourage production and this in turn elevates GHG emissions. But some commodities have higher emissions per hectare than others: if the transfer encourages production of a commodity with a lower per hectare GHG emission then this would ameliorate the environmental situation.13 The GHG emissions per hectare can be seen in Table 6, column 1. This shows that sugar cane has the highest per hectare GHG emissions, followed by bananas and yams. Taking account of the sequestration benefits and converting to J$ with the carbon price (i.e. the ACE) gives another picture of the per hectare comparison (column 2) with yams and bananas falling back in the list relative to sugar. In the case of livestock the ACE can best be compared by ton of output rather than by hectare (column 3). This emphasizes the high environmental burden from milk and beef through enteric fermentation and from poultry as a result of manure management.

A further measure relating agricultural policy to GHG emissions is shown in Table 6 (column 4), which calculates the the percentage of the value of production that is offset by the ACE. Milk in particular appears to have environmental costs that are very high (200 percent) relative to the value of production. Beef and pigmeat also show up as sectors that have ACE costs that are a high proportion of their production value. By contrast, the ACE for poultry is only about 3 percent of the market value of the product. The field crops, such as tomatoes, potatoes and yams, and the tree crops such as bananas and coffee, generally have an ACE cost that is only a small share of the value of production. This measure would tend to suggest that a policy to reduce GHG emissions might be focused on a few commodities.

13 A complete solution to this measurement issue would have to come from a multi-market model of Jamaican agriculture, with cross-elasticities of supply included. This would need input from databases such as Agrimonitor but involve considerable additional modeling. Unfortunately, the more realistic the model that is used the more parameter assumptions and model structure decisions will be needed. So the additional definition of the results may come at the cost of credibility.

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Source: Author’s calculations based on Agrimonitor and Aether

The value of production however includes the transfers generated through commodity policy. One more step is needed to indicate the relative value of sectors net of emissions costs. To remove the effect of policy one can compare the “social” value of production (as defined above) with the ACE. The final column in Table 6 shows the ratio between the value of production net of policy transfers (VoP-SCT) and the ACE. Sugar, tomatoes, oranges and “other products” appear to have highly favorable ratios, indicating the greatest value (net of transfers) per unit of environmental cost. The ratio for livestock appears to be relatively low: the social value of output is only 8 times the ACE in the case of poultry and there appears to be no net benefit from milk production once emission costs and transfers are removed. This emphasizes that conclusion that minimizing ACE is not necessarily a sound policy choice: if GHG emissions are being limited then one should get the best value possible subject to this constraint.

Policy ImplicationsWhat implications might these results have for policy makers? As the GOJ implements its INDC commitment to curb emissions of GHG it has a range of agricultural policy actions from which to choose. One would be to reduce the transfers to the highest GHG-emitting sectors – such as poultry, sweet potatoes, yams and beef. It may also be that the high transfers are contributing to higher production levels and consequently higher GHG emissions. But the net effect, as argued above, could result in a shift of resources to other environmentally unfriendly commodities. Another option would be to reduce support to those sectors that have a high ratio of ACE to the value of production (in effect the livestock products) as this would ensure that the GHG emission reduction was being achieved at the lowest cost in terms of farm output. Alternatively one could increase support for those sectors with a low ratio of GHG emission

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costs to the value of production (in effect tree crops and cocoa in particular). Even more preferable would be to support (or at least remove constraints on) sectors that have a high ratio of the value of output net of support to the cost of carbon emissions. Candidates here would include tomatoes, coffee, pineapple and yams. The estimates given here point the way to what might be attempted by policy in an effort to coordinate price incentives with greenhouse gas emission reduction.

An alternative approach, or one that could be considered as complementary to price policy changes, would be to locate the source of the GHG emissions and attempt to change the management techniques used in the high-emitting sectors. Manure management is one area that may need to be addressed, either through regulation or financial incentives (taxes or subsidies). The use of offsets to GHG emissions would fit into this approach, as improved management practices would be encouraged by private incentives. Thus the results shown here may be most useful in guiding policy towards solutions in the area of crop and livestock husbandry. Policy at the commodity level may help, but changes in farming practices could be a very useful complementary step.

The report has focused on GHG emissions in the context of attempts at mitigation of climate change at the global level. The extent to which Jamaica participates in such mitigation will depend on national policy decisions way beyond the considerations of agricultural policy. No amount of mitigation in Jamaica alone is likely to have any measurable impact on Jamaica or its agricultural sector: the vulnerability of Jamaica and Jamaican agriculture to climate change is related to the actions of other countries. However the actions taken by Jamaica in connection with its INDC obligations (once ratified) could have a considerable impact on the agricultural sector. Thus at one level the significance of GHG reductions is separable from the vulnerability of Jamaican agriculture to climate change but in the context of policy decisions the link between GHG emissions and policy incentives is significant.

There is an even more important link between mitigation and adaptation policies relating to climate change that could be crucial for policy-makers. Given that there is a compelling case for Jamaican policy to develop a strategy for adaptation to climate change the more such a strategy can be consistent with mitigation efforts the more mutually supportive can be the two separate policy goals. Efforts at increasing the resilience of agriculture in the face of climate variability could be accompanied by changes necessary to meet mitigation goals. Resilience can also be related to policy transfers. Attempts to make Jamaican agriculture more sustainable could in this way be paired with reduction of GHG emissions. The next step could therefore be to examine, with the help of Agrimonitor, the range of policies that are being used which might impact adaptation and resilience. This report has discussed the link between policy incentives and GHG emissions: the compatibility of Jamaican agricultural policy and climate change adaptation needs to be further explored.

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Annex Tables with annual values of data and calculations reported in text.

Source: Agrimonitor

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Source: Agrimonitor

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FAO/IDB (2012). JAMAICA - Agricultural Sector Support Analysis: Policy Review and Support Estimates

FAO (2014). Jamaica: Review of Agricultural Sector Support and Taxation, FAO Investment Centre, Rome.

FAO (2016). FAOSTAT Agricultural Emissions database (accessed at FAOstat3@fao.org)

IDB (2016). IDB Agrimonitor database (accessed at IADB.org)

IICA (2016). Caribbean Intended Nationally Determined Contributions Where does agriculture fit? http://infoagro.net/archivos_Infoagro/Ambiente/biblioteca/EN_IICA.2016.CaribbeanI.pdf

Ramasamy Selvaraju, Agriculture and Climate Change in Jamaica: Agricultural Sector Support Analysis, FAO Environment and Natural Resources Service Series, No. 20 – FAO, Rome, 2013

GOJ, (2011). Second National Communication to the UN Framework Convention on Climate Change (UNFCCC).

Vosti, Stephen; Msangi, Siwa; Lima, Eirivelthon; Quiroga, Ricardo; Batka, Miroslav; Zanocco, Chad. (2011). Agricultural Greenhouse Gas Emissions in Latin America and the Caribbean: Current Situation, Future Trends and One Policy Experiment, Inter-American Development Bank, Infrastructure and Environment Division Discussion Paper No. IDB-DP-167, January

IPCCC (2006). “Guidelines”, Volume 2, Energy.

CIA World Fact Book (accessed via index mundi website)

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