Bruno Lanfranco

In a collaborative effort with private agents of the oilseed industry, INIA conducted a research study to determine the feasibility of framing soybean production in Uruguay into a sustainable development pathway. A spatial model based on land suitability analysis and the imposition of other soil restrictions (risk erosion, current regulations, and permanent soil uses) was adopted to estimate potential soybean yields and the most suitable cropping areas in the country. Assuming a national average production cost for soybeans, total costs were calculated by adding location-specific logistics and land rent costs. Crop economic margins were estimated using a combination of price, technology, and climate-change scenarios. Only areas exhibiting non-negative margins were considered suitable for sustainable cultivation. With all restrictions imposed, the potential soybean area on rotation with other crops and pastures in Uruguay would range between 2.1 and 2.9 million hectares, depending on the prevailing producer price level. Climate change effects did not show significant differences on their own. This ad-hoc approach can be useful for private and public decision-makers. It can be applied to any crop situation or region where the objective is to define how far it is possible to expand and intensify production sustainably, without compromising the environment.

For years, livestock production has been accused of having a supposed impact on global warming. This message permeated broad sectors of public opinion. Recently, questions have arisen about the metrics used to determine the potential contribution of different greenhouse gases. The differences between the atmospheric decays of short- and long-lived climate forcers (SLCFs and LLCFs) and the inadequacy of single-pulse metrics, such as the global warming potential (GWP), to describe sustained emission sources over time, prompted the development of new estimators to compare the warming potential of gases other than CO2. Alternatives such as GWP* show a considerable reduction in the contribution of SLCFs compared to GWP100. This article assesses the differential warming contribution of enteric methane emissions from Uruguayan cattle from 1900 to 2023 using GWP and GWP* and their potential usefulness in negotiating future emission reduction commitments. Data on livestock population and feed were used to calculate annual feed intake and methane emissions. The total cumulative emissions, as calculated using the GWP* method, represented 56% of the CO2-equivalent value estimated using the traditional metric (1,139 versus 2,027 Mt CO2e). Furthermore, the downward trend in annual CO2 warming-equivalent emissions over the past three decades (-60.6%) has been accompanied by a significant reduction in emissions intensity (-13.0%). Considering GWP* as an additional metric can contribute to Uruguay's positioning for future commitments and provide evidence of its compliance.

A series of non-spatial and spatial hedonic models of feeding and replacement cattle prices at video auctions in Uruguay (2002 to 2009) were specified with predictors measuring marketing conditions (e.g., steer price), cattle characteristics (e.g., breed) and agro-ecological factors (e.g., soil productivity, water characteristics, pasture condition, season). Results indicated that cattle prices produced under extensive production systems were influenced by all of predictor categories, confirming that found previously. Although many of the agro-ecological predictors were inherently spatial in nature, the incorporation of spatial effects into the estimation of the hedonic model itself, through either a spatially-autocorrelated error term or allowing the regression coefficients to vary spatially and at different scales, was able to provide greater insight into the cattle price process. Through the latter extension, using a multiscale geographically weighted regression, which was the most informative and most accurate model, relationships between cattle price and predictors operated at a mixture of global, regional, local and highly local spatial scales. This result is considered a key advance, where uncovering, interpreting, and utilizing such rich spatial information can help improve the geographical provenance of Uruguayan beef and is critically important for maintaining Uruguay’s status as a key exporter of beef with respect to the health and safety benefits of natural, open-sky, grass-fed production systems.

Purpose: The purpose of this paper is to present an economic evaluation of Uruguay’s beef industry competitiveness to quantify the effects of public policies (taxes, subsidies, social charges) on the various links constituting the beef export chain and estimate the impact of transfers of resources between the beef industry and other sectors of the economy. Design/methodology/approach: The Policy Analysis Matrix (PAM) techniques were employed to quantify the effects of public policies on the competitiveness of Uruguay’s beef industry. A series of PAM coefficients were calculated to assess the competitiveness of the beef export chain in 2010 and 2013 with comparison between the two years to make policy recommendations. Findings: Beef sector returns captured by private agents decreased from 30 percent in 2010 to 10 percent in 2013. Competitiveness of the beef export chain deteriorated between 2010 and 2013 due primarily to higher prices paid for live cattle by the beef slaughtering, manufacturing, and packing sector. Uruguay’s beef industry transfers resources to the larger economy via social security payments and is penalized as a result of high capital costs. Research limitations/implications: Although three different sources of resource transfers were identified, more effort is needed to improve the precision of estimations. Originality/value: The competitiveness of export chains is critical to the economic and social wellbeing of small-economy countries. They must be efficient producing for the international markets at the time they constitute pillars of the whole economy.

The objective of this research is to determine the impact of the CONEAT productivity index over farmland prices in Uruguay. The CONEAT index attempts to express the relationship between land productivity, measured in terms of meat and wool production, and the type of soils present in the land. The advantage of this index is that is easily understood by all agents operating in the agricultural sector. The main critic is that it considers exclusively parameters from livestock production, which may be questioned when applied to the comparison of land for other productive uses. In spite of this pitfall, the CONEAT index is widely used to value farmlands in Uruguay, as well as to compare productivity among rural lands. In order to asses the implicit money values that land traders assign to CONEAT productivity index, a hedonic price model was estimated. This study analyzes 1,407 land transactions, representing almost 2 million hectares, carried out between December 1993 and January 2005. The findings reveal that the CONEAT index has a nonlinear positive relationship with the price per hectare. Along with productive aptitude, farm location, and market conditions, these are all relevant characteristics for farmland price formation in Uruguay.