# **I. Introduction**

According to recent estimates by the International Energy Agency, global energy demand will rebound to its pre-Covid-19 level sometime between 2023 and 2025, and then grow by 9 percent on average each year until 2030 (IEA 2020). Since the demand in most advanced economies is on a declining trend, almost all this increase will come from developing and emerging market economies, driven by factors such as industrial development, demographic change, and changes in consumer behavior. Given limited resources and the costs associated with increasing energy generation capacity, energy efficiency (EE)<sup>1</sup> projects are increasingly seen by policy makers around the world as a critical tool to help meet the rapid growth in energy demand.<sup>2</sup> In addition, improvements in EE are often argued to be a key channel to reduce greenhouse gas emissions and achieve the ambitious 2°C stabilization target in the Copenhagen Consensus (World Bank, 2010). In fact, improving EE has been called `` _the cheapest, fastest, and most environmentally friendly way to meet a significant portion of the world’s energy needs_ ’’ (Kaygusuz 2012). Moreover, EE projects are generally believed to provide important socio-economic benefits, including reducing countries’ dependence on fossil fuels (thus enhancing energy security), easing infrastructure bottlenecks and impacts of temporary power shortfalls, improving industrial and commercial competitiveness through reduced operating costs (Sarkar and Singh 2010), and facilitating the expansion of energy access (Can et al. 2018).

Despite these benefits, achieving significant and sustained gains in EE continues to be a challenge across countries, especially in many developing economies. An important factor in this context is the scarce empirical evidence of the impacts of EE projects in developing economies, whose energy systems and associated challenges often differ fundamentally from those in advanced economies (Urban et al 2007; Ouedraogo 2017). Recent studies on low and middle income countries (LMIC) find preliminary evidence that investments focused on more efficient lighting can be cost-efficient (Iimi et al. 2019; Carranza and Meeks 2021). For example, transitioning from kerosene lighting to solar lighting reduces energy expenditures by 42 percent in rural households in Kenya (Rom and Günther 2019). There is, however, at best mixed evidence in the literature as to whether these interventions cause energy savings,<sup>3</sup> and most of the existing evidence is based on small-scale interventions with unknown external validity and potential for scaling up. As noted by Fowlie and Meeks (2021), there is “ _tremendous value in ex post evaluations of these interventions. Empirical research that objectively evaluates the impacts of these and other programs can inform the course of future policy initiatives aimed at improving energy efficiency._ ” This paper contributes to addressing this gap in the literature by providing quasi-experimental evidence on the impacts of a large-scale EE project in Malawi which was supported by the World Bank between 2015 and 2018. Our estimation strategy is based on a difference-in-differences (DiD) approach using a combination of remote-sensing data from satellite images and data from national household surveys. The estimation strategy takes advantage of the geographical variation in the implementation of different project components, including variation across districts, subdistricts (cities), and individual households. Various project components were implemented in different areas across the country,

> 1 In this paper, EE refers to reductions in the amount of energy required to provide the same output or level of service. For example, such reduction can result from the adoption of improved technologies or practices that help to save energy or reduce energy losses.

> 2 For example, the IEA (2017) estimates that, without the improvements in EE achieved since 2000, the world would have needed to generate 12% more energy in 2016.

> 3 On the one hand, studies have found that replacing traditional cooking stoves in Senegal with more fuel-efficient versions causes a decrease in firewood consumption by 30 percent (Bensch and Peters 2015), and that upgrading to more efficient cookstoves in Kenya delivered, on average, 40 percent decrease in charcoal expenditures (Berkouwer and Dean 2020). On the other hand, energy savings have been found to be either negligible or negative on investments in LMIC replacing refrigerators, air conditioners, and building insulation with more energy efficient alternatives (Davis et al. 2014; Davis et al. 2018; Ryan 2018). One factor that could help explain these findings is an energy rebound effect; that is, an efficiency-induced reduction in the cost of this service triggering an increase in energy consumption. The existing literature on energy rebound effects focuses mostly on high income countries, but there is incipient research that suggests that rebound effects could be higher in LMIC than in high income countries (Ouyang et al., 2010; Davis et al., 2014).

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