Women carrying firewood in Guatemala
Over two million Guatemalan households use fuelwood as a primary source of energy, however it is becoming increasingly scarce. 
The IEEM model can help policymakers develop the best strategy to increase fuelwood efficiency.

By Onil Banerjee, Inter-American Development Bank
Martin Cicowiez, Universidad Nacional de La Plata, Argentina
Renato Vargas, CHW Guatemala
Mark Horridge, Victoria University, Australia

September 16, 2016 —As international development institutions, it is our mandate to reduce poverty and inequality, to boost shared prosperity, and do so in an environmentally sustainable way. Our cooperation and investments across the globe should reflect these ideals, contributing to current economic well-being and enhancing prospects for future economic growth. Considering that physical, human and natural capital is the foundation of wealth and prosperity, it is an institutional commitment to strengthening this foundation upon which the well-being of future generations is dependent. 

The investments of multilateral development institutions and the advice they provide are subject to economic analysis of their potential impacts on the economy and society. Where public policy and large investments are concerned, economy-wide models are often used to assess the net present value of these interventions which tells us whether or not we will be better off as a result of their implementation, compared with a business as usual scenario. 

There is a critical limitation to the standard ‘ex-ante’ impact analysis approach, though, and this has been described as the ‘economic invisibility of nature’. While our standard impact analytical approaches capture important interactions in an economy and generate results in terms of indicators that reflect changes in gross domestic product (GDP), income and employment, they are silent on how an investment will affect natural capital as one of the three pillars of wealth and prosperity. 

This is all about to change. For over two decades, a multi-disciplinary community of international experts has been developing the first international standard for Environmental Economic Accounting (SEEA). The fact that data organized under the SEEA is compatible with the economy-wide frameworks with which we regularly measure economic performance has enabled the development of IEEM, the Integrated Economic-Environmental Modelling platform

IEEM Presentation in Guatemala

At a workshop in Guatemala City in August 2016, Fernando Quevedo, IADB Guatemala, Onil Banerjee, IADB, and Raúl Maas, Director of IARNA, presented IEEM and provided training on its use togovernment officials, institutional technical staff, think-tank researchers, academics, and the general public.

Developed with support from the Inter-American Development Bank’s BIO Program, IEEM is the first highly disaggregated and regionalized economy-wide model of its kind where users can simulate public policy and investment proposals, with an internally consistent and comprehensive economic-environmental data structure, and evaluate trade-offs in terms of both economic and environmental criteria. While traditional impact analysis models tell us about effects on standard indicators, IEEM goes one step further, capturing impacts on indicators reflecting stocks of environmental resources, environmental quality and wealth such as adjusted net savings.  

IEEM has been developed in such a way that it may be applied to any country with strong national accounts and a SEEA. Since Guatemala has one of the most comprehensive SEEA in the Latin American and Caribbean region, we have developed a first exercise with IEEM for Guatemala and for illustrative purposes, applied it to the critical national issue of fuelwood scarcity and forest degradation. Over two million Guatemalan households use fuelwood as a primary source of energy and it comprises 57 percent of national energy use. Fuelwood, however, is increasingly scarce, with the current deficit of 10 million cubic meters met by deforestation and forest degradation. Inefficient use of fuelwood, primarily in cookstoves, increases the probability of respiratory illnesses by 31%; causes the premature death of over 5,000 people per year, and; results in productivity losses of around 1% of Gross Domestic Product. To address this issue, the government has implemented a National Strategy for Sustainable Production and Efficient Use of Fuelwood.

We applied IEEM to evaluate the impacts of the fuelwood strategy by simulating a 25% increase in the efficiency of household fuelwood use (efficiency scenario), which could be achieved through the use of more efficient fuelwood cookstoves such as the Patsari Cookstove. In a second scenario, we examine the potential health benefits of improved fuelwood use efficiency. Reduced emissions within households would reduce household exposure to particulate, toxic and carcinogenic by-products of fuelwood combustion. These benefits would manifest themselves through improved productivity with household members missing less work or school, and spending less time gathering fuelwood (efficiency + health scenario). 

The power of IEEM comes from its ability to shed light on how policies and investment affect environmental resource use by the economy, the stocks of environmental resources and environmental quality. 

Poorer rural households use more fuelwood than wealthier and urban households and as such, receive a greater share of the benefits with a positive income effect on the order of 0.19% and 0.30% increased income by 2025 in the efficiency and efficiency + health scenarios, respectively. With IEEM, it is possible to evaluate how emissions profiles change as a result of a policy; this includes the emissions profiles of the overall economy (7% decline in CO2 emissions in the fuelwood efficiency scenario), individual industries, and households (13% decline in poor rural household emissions). 

Figure 1 illustrates some of the economic-environmental dimensions captured by IEEM, which would have previously required various models to estimate. The fuelwood efficiency scenario would result in a small decline in agricultural land use with a concomitant increase in forestland use as the pace of deforestation would slow with implementation of the fuelwood strategy. Forestry output would decline, as fuelwood prices fall, whereas water use would remain similar to baseline consumption levels despite the small decline in agricultural output. Total greenhouse gas emissions would fall as a result of the improvements in efficiency.

While GDP measures the component of well-being attributed to the production of goods and services, IEEM for the first time enables ex-ante estimation of indicators that capture the additional dimensions that contribute to well-being and national wealth. One such indicator is adjusted net savings which measures a country’s sustainability, indicating the extent that changes in natural and human capital are balanced by changes in physical capital. In essence, adjusted net savings it provides an indication of the current generation’s bequest to future generations. 

Figure 2 shows a variation of adjusted net savings which is national net savings, less the economic loss/cost of deforestation, reductions in mining assets, and greenhouse gas emissions as a result of both efficiency and efficiency + health scenarios. The greatest increase in savings would occur in the efficiency + health scenario with an increase of over US$66 million in 2040 and a cumulative savings increase of US$415 million, driven by the reduction in deforestation and emissions. With natural capital serving as the basis for future economic growth, the fuelwood strategy is unambiguously wealth-enhancing. 

In this post, we have demonstrated the analytical potential of IEEM which is the first modelling platform to integrate data organized under the SEEA in an economy-wide modelling framework. IEEM represents critical relationships between the environment and the economy and when used for public policy and investment analysis, produces results that could not previously be obtained through a single modelling framework. IEEM generates indicators that capture the multi-dimensionality of wealth and well-being as well as standard indicators that reveal impacts on GDP, income and employment.
Through IEEM we aim to elevate the discussion of policy and investment impacts from a growth-centric perspective to a more holistic understanding of how interventions impact the wealth of nations. It is our goal to promote the development and institutionalization of IEEM in countries around the world in order to tip the policy making paradigm towards one of evidence-based policy design.