The World Bank Economic Review, 31(3), 2017, 631–649 doi: 10.1093/wber/lhw052 Advance Access Publication Date: October 20, 2016 Article Downloaded from https://academic.oup.com/wber/article-abstract/31/3/631/2433616 by Joint Bank-Fund Library user on 08 August 2019 A First Step up the Energy Ladder? Low Cost Solar Kits and Household’s Welfare in Rural Rwanda ¨ rg Peters, and Maximiliane Sievert Michael Grimm, Anicet Munyehirwe, Jo Abstract More than 1.1 billion people in developing countries are lacking access to electricity. Based on the assumption that electricity is a prerequisite for human development, the United Nations has proclaimed the goal of provid- ing electricity to all by 2030. In recent years, Pico-Photovoltaic kits have become a low-cost alternative to investment intensive grid electrification. Using a randomized controlled trial, we examine uptake and impacts of a simple Pico-Photovoltaic kit that barely exceeds the modern energy benchmark defined by the United Nations. We find significant positive effects on household energy expenditures and some indication for effects on health, domestic productivity, and on the environment. Since only parts of these effects are internalized, underinvestment into the technology is likely. In addition, our data show that adoption will be impeded by affordability, suggesting that policy would have to consider more direct promotion strategies such as subsidies or financing schemes to reach the UN goal. JEL classification: D13, H23, H43, I31, O13, O18, Q41 More than 1.1 billion people in developing countries lack access to electricity. Some 590 million of them live in Africa, where the rural electrification rate is only 14 percent (SE4All 2015). Providing access to electricity is an explicit goal of the sustainable development goals (SDGs) and frequently considered a precondition for economic and social development (UN 2005). Based on such assumptions, the United Nations aims for universal access to electricity by 2030 via its initiative Sustainable Energy for All (SE4All; see also UN 2010). The investment requirements to achieve this target are enormous, estimated by the International Energy Agency (IEA) (2011) to be about 640 billion US Dollars. Michael Grimm is a Professor of Development Economics at University of Passau. He is also affiliated with Erasmus University Rotterdam and IZA, Bonn; his email address is michael.grimm@uni-passau.de. Anicet Munyehirwe is director of IB&C Rwanda; his email address is munyehirwe@gmail.com. Jo ¨ rg Peters is heading the research group “Climate Change in Developing Countries” at RWI, Germany. He is Visiting Associate Professor at the University of the Witwatersrand, Johannesburg, South Africa; his email address is joerg.peters@rwi-essen.de. Maximiliane Sievert (corresponding author) is a Research Fellow at RWI, Germany; her email address is maximiliane.sievert@rwi-essen.de. We thank two anonymous refer- ees and the editor for very valuable comments. We also thank conference participants in Mu ¨ nster (VfS 2015), in Oxford (CSAE 2015), in Kiel (VfS Development Economics 2015), Copenhagen (PEGNET 2013) and Du ¨ sseldorf (IAEE 2013) as well as participants at research seminars at the University of Bonn (ZEF), the Kiel Institute for the World Economy, and the University of Groningen. The data underlying this research was collected for an impact evaluation commissioned by the Policy and Evaluation Department of the Ministry of Foreign Affairs of the Netherlands (IOB). This work was supported by the German Federal Ministry for Economic Affairs and Energy and the Ministry of Innovation, Science, and Research of the State of North Rhine-Westphalia [Sondertatbestand – special grant] to JP and MS. A supplemental appendix to this article is available at https://academic.oup.com/wber. C The Author 2016. Published by Oxford University Press on behalf of the International Bank for Reconstruction and Development / THE WORLD BANK. V All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com 632 Grimm et al. In recent years, so-called Pico-Photovoltaic (Pico-PV) kits have become a low-cost alternative to exist- ing electrification technologies thanks to a substantial cost decrease of photovoltaic and battery systems as well as energy saving LED lamps. Different Pico-PV kits exist that provide basic energy services like lighting, mobile phone charging, and radio usage. In the SE4All initiative’s multi-tier definition of what is considered as modern energy, the Pico-PV technology constitutes the Tier 1 and thus the first step on Downloaded from https://academic.oup.com/wber/article-abstract/31/3/631/2433616 by Joint Bank-Fund Library user on 08 August 2019 the metaphoric energy ladder. Investment costs for Pico-PV kits are far lower than for the provision of on-grid electricity or higher tier PV systems. This paper investigates usage behavior and the changes in people’s living conditions when households make this first step toward modern energy based on a randomized controlled trial (RCT) that we imple- mented in rural Rwanda. The kit, which we randomly assigned free of charge to 150 out of 300 house- holds in 15 remote villages, consists of a 1 Watt solar panel, a 40 lumen lamp, a telephone charger, and a radio—and thereby just barely reaches the benchmark of what qualifies as modern energy access in the SE4All framework. The market price of the full Pico-PV kit is at around 30 USD. Our study population is the main target group of the Pico-PV technology, that is, the bottom-of-the-pyramid living in a coun- try’s periphery who will not be reached by the electricity grid in the years to come and who will have problems to afford higher tier PV systems. We investigate the adoption of the Pico-PV kit at both the extensive and the intensive margin. At the extensive margin, we examine whether households actually use the Pico-PV kit. This is not obvious given that we distribute the kit for free and the technology is new for the households. There is an intense debate in the development community about usage intensity of freely distributed goods (see, e.g., Dupas 2014). At the intensive margin, so conditional on households using the kit, we examine the effects of Pico-PV usage on three types of outcomes: energy expenditures, health and environment, and productiv- ity in domestic work. The amplitude of effects heavily depends on usage behavior: is the kit used in addi- tion or as a substitute to traditional lighting sources like kerosene? Which household member uses the kit and for which purposes? Do households expand their activities that require lighting into evening hours, or do they just shift activities from daytime to nighttime? Does the total time awake of household members change? Nonelectrified rural households in Africa are increasingly using LED lamps that run on dry-cell batteries. Since these batteries are not disposed of appropriately and potentially harm the local environment, Pico-PV usage might also induce environmental benefits. We also analyze whether potential productivity gains in domestic work release time that can now be dedicated to income generat- ing activities. Our paper complements the seminal work of Furukawa (2014) who studies the effects of Pico-PV lamps on children’s learning outcomes in rural Uganda. We extend the scope by examining the effects of Pico-PV kits on various in-house activities of all household members, not only those of school children. We find that households use the kits intensively in spite of the zero price and the novelty of the product. Furthermore, the kit considerably reduces consumption of kerosene, candles, and dry-cell batteries and, in consequence, energy expenditures. The reduction of kerosene improves household air quality and the reduction of dry-cell battery consumption plausibly leads to environmental benefits. Moreover, we find that children shift part of their homework into the evening hours. Primary school boys even increase their total study time. While parts of these effects are clearly internalized benefits, other parts are impor- tant externalities, which may provide the cause for public subsidies, in particular if it turns out that households are simply too poor to raise the upfront costs alone. The role of public policy in the promotion of Pico-PV technology is not defined so far. The expecta- tion of the World Bank’s Lighting Global program, for example, as well as other donors is that Pico-PV kits make inroads to African households via commercial markets, implying that end users pay cost-covering prices (see Lighting Global 2016). This might in fact work out for the relatively well-off strata in rural areas but is much more uncertain for the rural poor. In fact, the major target group of The World Bank Economic Review 633 Pico-PV kits within the SE4All endeavor is located beyond the reach of the grid in remoter areas. These households are short on cash, credit constrained, and might have more essential priorities to spend their money on. If these groups in the periphery of the developing world shall be reached by the SE4All initia- tive, direct subsidies or even a free distribution might be required. This is indeed the policy intervention we mimic in our study. From a welfare economics point of view this would be justified if the usage of Downloaded from https://academic.oup.com/wber/article-abstract/31/3/631/2433616 by Joint Bank-Fund Library user on 08 August 2019 Pico-PV kits generates private and social returns that outweigh the investment cost. Our paper provides empirical substance to this debate. So far, only very little evidence exists on the take-up and impacts of Pico-PV lamps. To our knowl- edge, the only published study is Furukawa (2014), who concentrates on educational outcomes alone. Furukawa randomized Pico-PV lamps among 155 primary school students in Uganda who at baseline used kerosene wick lamps as the main lighting source at home. Although Furukawa (2014) finds that children’s study hours clearly increased among Pico-PV lamp owners, he curiously observes decreasing test scores. Furukawa tests different explanations of this “unexpected result”. Without having the data at hand to obtain a robust answer, he hypothesizes that the low power of the lamps and the inadequate recharging behavior could have led to flickering light, which eventually worsened studying conditions. Based on this experience, we will therefore carefully check the lighting quality and users’ satisfaction in our experiment. Much more evidence exists on the socioeconomic effects of classical rural electrification programs using higher tier technologies, mostly the extension of the electricity grid. These interventions differ from our randomized solar kit to the extent that much higher effect sizes can be expected, but also much higher costs are incurred. Nonetheless, this literature constitutes an important background of our work, in particular those studies that explore the effects of electricity usage on similar outcomes. Van de Walle et al. (2016) for instance find that in rural India electrification led to a significant increase in households’ expenditures. For the case of a grid extension program in El Salvador, Barron and Torero (2014, 2015) find reductions in kerosene consumption, in particulate matter exposure, and respiratory disease prevalence as well as an increase in study hours among children. The latter finding is confirmed in a grid extension program in Bangladesh (Khandker et al. 2012) but not in a previous study in Rwanda on the effects of mini-grid electrification (Bensch et al. 2011). For South Africa and Nicaragua, respectively, Dinkelman (2011) and Grogan and Sadanand (2013) provide evi- dence that the use of electricity saves women’s time in household chores and leads to increased labor supply of women.1 In SE4All’s multi-tier framework solar home systems are the intermediate step between Pico-PV and grid electricity. Samad et al. (2013) evaluate a solar home system program in Bangladesh and find increases in evening study hours of school children, TV usage, and female decision-making power. They also find reduced kerosene consumption and some moderate evidence for positive health effects. Bensch et al. (2013) confirm positive effects of solar home system usage on children’s studying hours in Senegal. It is the aim of our paper to extend the scope of this literature to the bottom step of the energy ladder. Hence, these findings are important to classify our observations, although of course the cost-related and technological differences between on-grid electricity, 50 Watt solar home systems and our 1 Watt Pico- PV kit have to be borne in mind. The remainder of the paper is organized as follows: Section I gives the policy and country back- ground. Section II provides theoretical considerations that will guide our empirical analysis. Section III presents our experimental design. Section IV discusses all results, and Section V concludes. 1 Further studies exist that examine whether on-grid rural electrification programs can spur income generation and eco- nomic growth (see, e.g., Bensch et al. 2011; Dinkelman 2011; Bernard 2012; Khandker et al. 2012, 2013; Grogan and Sadanand 2013; Lipscom et al. 2013; Barron and Torero 2014; Lenz et al. 2016; Peters and Sievert 2016). As discussed above, we do not expect the Pico-PV systems to affect such outcomes. 634 Grimm et al. I. Background Policy Background In the absence of electricity, people in rural Sub-Saharan Africa light their homes using traditional lighting sources—candles or kerosene driven wick lamps and hurricane lamps. In recent years, dry-cell battery driven Downloaded from https://academic.oup.com/wber/article-abstract/31/3/631/2433616 by Joint Bank-Fund Library user on 08 August 2019 LED-lamps have become available in almost every rural shop and are increasingly used (see Bensch et al. 2015). The most common ones are small LED-torches and mobile LED-lamps that exist in various versions (see fig. 1). In addition, many rural households use hand-crafted LED lamps, that is, LED-lamps that are removed from torches and installed somewhere in the house or on a stick that can be carried around. For rural households in Africa, expenditures for both traditional lighting sources and dry-cell batteries constitute a considerable part of their total expenditures. In very remote and poor areas, people who are cash con- strained generally use very little artificial lighting and sometimes even only resort to the lighting that the cooking fire emits. For this stratum, the day inevitably ends after sunset. Figure 1. Traditional Lighting Devices Source: Own illustration Obviously, this lighting constraint restricts people in many regards. Activities after nightfall are liter- ally expensive but also difficult and tiring because of the low quality of the lighting (see Section II for more information on lighting quality). At the same time, it becomes evident that modern energy is not a binary situation. Rather, there are several steps between a candle and an incandescent light bulb. This continuum has sometimes been referred to as the energy ladder. In fact, SE4All has defined different tiers of modern energy access within its Global Tracking Framework (SE4All 2013) according to the electric- ity supply that is made available. For example, a regular connection to the national grid qualifies as Tier 3, because it allows for using general lighting, a television, and a fan the whole day. A solar home system would qualify for Tier 1 or 2 (depending on its capacity). Tier 1 requires having access to a peak capacity of at least 1 Watt and basic energy services comprising a task light and a radio or a phone charger for four hours per day. The spread between the service qualities of the different tiers is also reflected in the required investment costs: the retail price of the Pico-PV kit used in this study is at around 30 USD. The World Bank (2009) esti- mates a cost range for on-grid electrification in rural areas of 730 to 1450 USD per connection.2 The promotion of Pico-PV kits is most prominently pursued by the World Bank program Lighting Global. Based on the assumption that the market a quality certificate for Pico-PV systems is threatened by a lack of information and information asymmetries, it provides technical assistance to governments, conducts market research, facilitates access to finance to market players, and has introduced a quality 2 The investment requirements calculated by IEA (2011) of additional 640 billion USD to achieve universal access to elec- tricity are based on electricity connections that provide a minimum level of electricity of 250 kWh per year. This roughly corresponds to a Tier 2 electricity source. The World Bank Economic Review 635 certificate. The objective of Lighting Global’s initiative in the region, Lighting Africa, is to provide access to certificated Pico-PV kits to 250 million people by 2030. The Pico-PV lantern and the panel used for the present study were certified by Lighting Africa.3 Downloaded from https://academic.oup.com/wber/article-abstract/31/3/631/2433616 by Joint Bank-Fund Library user on 08 August 2019 Country Background Rwanda’s energy sector is undergoing an extensive transition with access to electricity playing a domi- nating role. The Government of Rwanda’s goal is to increase the electrification rate to 70 percent of the population by 2017/2018 and to full coverage by 2020. The key policy instrument clearly is the huge Electricity Access Roll-Out Program (EARP) that since 2009 quintuplicated the national connection rate to 24 percent country wide. Three further programs exist that have not been implemented so far, though. First, the Government plans to establish a mechanism to provide the poorest households (categorized as Ubudehe 1 according to the national poverty scale) with a basic solar system corresponding to Tier 1 electricity access. Second, a risk mitigation facility shall be established to encourage the private sector to increase sales of solar products and services. Third, mini-grids shall be developed by the private sector (MININFRA 2016). These programs are complemented by the so-called Bye Bye Agatadowa initiative that aims at eliminating kerosene lamps completely from the country. In the absence of public promotion schemes, few private firms that sell Lighting Africa verified Pico- PV kits were active in the country at the time of the study implementation. They operate mostly in the Rwandan capital Kigali and other cities. In rural areas, Pico-PV kits are sometimes available, but their retail price is much higher compared to lower quality dry-cell battery driven LED-lamps that can be bought in rural shops all over the country. These devices are not quality verified, but cost only between 500 FRW (0.82 USD4) for hand-crafted LED lamps and 3000 FRW (4.95 USD) for an LED hurricane lamp. The battery costs to run an LED hurricane lamp for one hour are around 0.01 USD. This is cheaper than running a kerosene driven wick lamp (around 0.03 USD per hour) and the lighting quality is slightly better, which is why many households are now using such ready-made or hand-crafted LED- lamps. Compared to both battery-driven LED lamps and kerosene lamps, Pico-PV kits provide higher quality lighting (depending on the number of LED diodes) at zero operating costs. Assuming that a household uses the lamp for four hours per day, the investment into the Pico-PV lamp used for this study amortizes after 10 months if a ready-made LED lamp is replaced and after less than 5 months if it repla- ces a kerosene wick lamp. II. Theoretical Considerations Based on the literature on rural electrification presented in the Introduction, we assume that the Pico-PV treatment affects three dimensions of living conditions: First, the budget effect which arises because households with access to a Pico-PV kit experience a change in the price of energy, while no (substantial) investment costs occur as long as we assume that the Pico-PV treatment is subsidized or distributed for free. Second, health and environmental effects occur whenever Pico-PV kits replace kerosene lamps, can- dles, and dry-cell batteries. A decrease in kerosene and candles consumption reduces household air pollu- tion with potential effects on health (see Lam et al. 2012; WHO 2016). Environmental benefits arise due to inappropriate dry-cell battery disposal (see Bensch et al. 2015) that is reduced if dry-cell battery con- sumption goes down. Third, we analyze the productivity of domestic production, that is, production not intended to be traded on competitive markets. This we refer to as domestic productivity effect in what follows. The reason for only focusing on domestic production is that income in such remote rural areas 3 At the point of the Pico-PV kit’s certification, Lighting Africa did not yet issue certificates for mobile phone charging and other services. 4 Exchange rate as of November 2011: 1 USD ¼ 607 FRW. 636 Grimm et al. is virtually only generated by subsistence agriculture. The Pico-PV kit, in turn, is too small to affect agricul- tural production. For non agricultural products, access to markets is very limited and, hence, local nonagri- cultural labor markets are nonexistent. At baseline, only seven percent of head of household’s main occupation and one percent of spouse’s main occupation was a non-agricultural activity. Yet, since in theory the Pico-PV kit could liberate time from domestic labor and extend the time awake of household members, Downloaded from https://academic.oup.com/wber/article-abstract/31/3/631/2433616 by Joint Bank-Fund Library user on 08 August 2019 we examine at least the time dedicated to any income generating activity (agricultural and non-agricultural activities). Labor demand in such rural regions is too low, though, to absorb increases in labor supply, and therefore measurable effects on nonagricultural income cannot be expected. The mechanism leading to the budget and health and environmental effects are quite intuitive, whereas the transmission channel for the domestic productivity effect might be less obvious. Productive activities at home include cooking, cleaning, and making and repairing of household goods as well as studying and charging a cell phone. Since the visual performance of humans strongly increases with the lighting level (Brainard et al. 2001), we assume that the productivity in performing these activities increases with the quantity and quality of light. Productivity in fine assembly work for instance has been shown to increase by 28 percent as the lighting level increases from 500 to 1500 lumen (lm) (Lange 1999). But even increasing the lighting level from much lower levels comes with significant productivity effects. Evidence comes for instance from weaving mills (Lange 1999).5 The literature attributes good quality lighting to devices that provide sufficient, nonglaring, nonflickering and uniform light, balanced luminous distribution throughout the room, good color rendering and appropriate light color (Lange 1999). Along all these criteria, the Pico-PV kits perform better than other traditional lighting devices such as kerosene lamps and candles, but also compared to smaller hand-crafted LED lamps. Our Pico- PV lamp emits 40 lm, while a candle only emits around 12 lm, a hurricane lamp used at full capacity around 32 lm and large mobile LED lamps can reach levels around 100 lm (O’Sullivan and Barnes 2006). The LED lamps used in poor and remote areas are less luminous, though. Lumen levels emitted by hand-crafted LED lamps vary substantially depending on the number and quality of diodes and bat- teries used. Two to three diode-lamps connected to a battery package emit about 10 lm.6 One additional effect associated with a possible increase in radio usage is better access to information, which in turn may have productivity effects if the information relates to market data or can affect norms, such as gender norms for instance, and preferences (Bertrand et al. 2006; Jensen and Oster 2009; La Ferrara et al. 2012; Sievert 2015). Although we analyze whether radios are used with the Pico-PV kit and display radio ownership and usage in the supplemental appendix (see Appendix S5, available at https://academic.oup.com/wber), we do not further investigate any of these effects as most households use the Pico-PV kit only for lighting. III. Research Approach and Data Our identification strategy relies on the randomized assignment of Pico-PV kits after the baseline survey. The intention-to-treat effect (ITT) in our case is almost identical to the average treatment effect on the treated (ATT) because of the high compliance rate in the treatment group and no treatment 5 More evidence exists also on softer impacts such as a positive linkage between lighting and work mood (Kuller and Wetterberg 1993; Boyce et al. 1997; Partonen and Lo ¨ nnqvist 2000), fatigue (Daurat et al. 1993; Grunberger et al. 1993; Begemann et al. 1997), and eye strain and headache (Wilkins et al. 1989, Kuller and Laike 1998) that can be assumed to improve working performance. For a detailed presentation of the evidence for productivity effects associated with light, see the supplemental appendix. 6 Since lumen numbers for these hand-crafted lamps do not exist, we tested the two most widely used structures (a two diode-lamp and a three diode-lamp structure) in a laboratory at University of Ulm, Germany, using standard lumen emission test procedures. According to these tests, the level of emitted lumens by hand-crafted LED lamps is at around 10 lm. The World Bank Economic Review 637 contamination in the control group. Since all results are robust with regard to both ways of estimating impacts, we show only the more conservative ITT results. Treatment Downloaded from https://academic.oup.com/wber/article-abstract/31/3/631/2433616 by Joint Bank-Fund Library user on 08 August 2019 The randomized kits include a 1 Watt panel, a rechargeable 4-LED-diodes lamp (40 lumen maximum) includ- ing an installed battery, a mobile phone charger, a radio including a charger, and a back-up battery package (see fig. 2).7 There are different options to use the panel. First, it can be used to directly charge the lamp’s bat- tery. After one day of solar charging it is fully charged. The lamp can be used in three dimming levels and— fully charged—provides lighting for between 6 and 30 hours depending on the chosen intensity level. Second, the kit can be connected directly to the mobile phone connector plug and the radio connector to charge mobile phones or the radio. Third, the kit can be used to charge the back-up battery package that can then be used to charge the other devices without sunlight. The complete kit costs around 30 USD, the smallest version with only the solar panel and an LED lamp including an installed battery costs around 16.50 USD. Figure 2. The Pico-PV Kit Source: Own illustration Impact Indicators As a precondition for the three effects on budget, health, and environment, and domestic productivity the households’ usage behavior is our first matter of interest. We look at usage and charging patterns of the Pico-PV kit and analyze which of the different energy services—lighting, radio operation, and mobile phone charging—households use most. Since the kit is mostly used for lighting (see below), we focus in particular on this service. For budget effects, we first look at changes in the price of the energy service. We calculate the price per lighting hour and price per lumen hour the households effectively pay. Second, we analyze whether price effects translate into a change in lighting consumption. Here, we look at the average amount of 7 The kit used in our experiment provides more energy services than the solar lantern used by Furukawa (2014), but the panel is also twice as large (1 Watt compared to 0.5 Watt). 638 Grimm et al. lighting hours consumed per day and lumen hours consumed per day. Lighting hours are calculated as the sum of usage time of all lamps used during a typical day (including candles and ready-made torches). The price per lighting hour is calculated by dividing expenditures on lighting fuels by the number of lighting hours consumed. For calculating lumen hours, we multiply the lamp specific lighting hours with the amount of lumen emitted per lamp. Downloaded from https://academic.oup.com/wber/article-abstract/31/3/631/2433616 by Joint Bank-Fund Library user on 08 August 2019 Finally, we look at changes in total energy expenditures and in the expenditures for the different energy sources kerosene, batteries, and candles. For health and environmental effects, we first explore reductions in kerosene and candle consumption and to what extent this leads to a perceived improvement of air quality, measured by the subjective assess- ment of the respondents. Also for measuring the household members’ health status, we rely on self-reported information on whether any household member suffers from respiratory diseases and eye problems. We dis- tinguish between male and female adults as well as primary, and secondary school children. We did not measure air quality or undertake any medical exams. For environmental effects, we analyze reductions in dry-cell battery consumption and the way how households dispose of dry-cell batteries. In order to investigate domestic productivity effects, we look at the main users’ domestic labor activ- ities exercised when using the Pico-PV lamp. The main domestic labor activity for adults is housework; children use the lamp mainly for studying. We assess the increase of domestic productivity by analyzing the lighting source used for these respective activities. Based on the evidence from the literature presented in Section II and the supplemental appendix, we assume that households become more productive when they switch from a lower quality lighting source or no artificial lighting to the Pico-PV lamp. This seems reasonable since even at day time, the typical dwelling in rural Rwanda is quite dark. Windows are small in order to keep the rain and the heat out of the inner of the dwelling. To analyze lamp switching, we enumerated all lamps in each household interview and asked respondents to name all users for each lamp and the respective purpose of using it. The information on time spent on different activities was eli- cited in the interviews through an activity profile for each household member. If a certain activity pur- sued by the household is not associated with one of the employed lamps, we assume that no specific lighting device is used for this activity, and it is either exercised using daylight, or using indirect lighting from the fireplace or lamps used for other household tasks. In order to analyze whether the higher productivity also leads to an increase in total domestic labor input, we analyze the total amount of time dedicated to domestic labor per day. We furthermore examine whether total time household members are awake changes due to increased lighting availability and whether time dedicated to income generating activities changes as a result of time savings in domestic production. RCT Implementation The key facts of the implementation are presented in table 1. A detailed description of the implementa- tion including a map of the survey area and a figure illustrating the participant flow can be found in the supplemental appendix. A discussion of the external validity of our results is also presented in the supplemental appendix. IV. Results Balance of Socioeconomic Characteristics of Participating Households This section examines the balancing between treatment and control group and, at the same time, portrays the socioeconomic conditions in the study areas. Baseline values of the households’ socioeconomic character- istics show that the randomization process was successful in producing two balanced groups (see table 2). The surveyed households are mainly subsistence farmers that live in very modest conditions. The edu- cational level of the head of household is low and households own only a few durable consumption The World Bank Economic Review 639 Table 1. Key Facts on RCT Implementation Baseline survey November 2011 Delivery of Pico-PV kits December 2011 Follow-up survey June 2012 Study population 15 nonadjoined communities in four rural districts of Rwanda located in the Downloaded from https://academic.oup.com/wber/article-abstract/31/3/631/2433616 by Joint Bank-Fund Library user on 08 August 2019 Northern, Western and Southern Province. No Pico-PV kits available on the market $5.5 hours of sunlight per day (which is similar to country average) Sample 300 randomly sampled households Randomization Stratified randomization and additional re-randomization using minmax t-stat method at the household level; random assignment of 150 Pico-PV kits Stratification criteria Consumed lighting hours per day, usage of mobile phones (binary), radio usage (binary), and district Re-randomization Balancing criteria are marked in Table 2 and Table 3 Compensation for control households One bottle of palm oil and a 5 kg sack of rice worth around 7 USD Attrition rate < 1% Compliance rate 87% (18 households declared their Pico-PV kit to be sold, lost or stolen; One household received kit only during follow-up) Source: Household data set 2011/2012. goods. The households in our sample have cash expenditures of on average 0.45 USD (1.12 USD PPP) a day per person with the lower 25%-stratum having only 0.07 USD (0.18 USD PPP). Even the upper quartile has cash expenditures of 1.14 USD (2.86 USD PPP) only. By any standard, the sampled house- holds qualify as extremely poor. Also energy consumption patterns illustrate the precarious situation of most households (see table 3). They consume on average only around three hours of artificial lighting per day which is mainly provided through kerosene wick lamps or battery-driven small hand-crafted LED lamps. Around 11 percent of households even do not use any artificial lighting devices and rely only on lighting from the fireplace after nightfall. For the baseline values, we calculate lighting hours as the sum of lighting usage per day across all used lamps, excluding candles and torches, for which we did not elicit usage hours at the baseline stage. Almost 65 percent of the household own a radio, around 40 percent have a cell phone. If we look at the small group of non-compliers, who declared their kit to be sold, lost or stolen, we see that they are generally poorer than complying households: They have more children, own less land, have less cows and goats, and have less radios and cell phones. Impact Assessment Take-Up and Lighting Usage. Among the 131 households that still have a Pico-PV kit when interviewed in the follow-up survey, usage rates are very high (see table 4). In sum, 86 percent use the kit at least once per day, primarily for lighting. Radio and especially cell phone charging usage rates are rather low. Most households report that both the radio and the cell phone charger were very difficult to use with the kit, which was confirmed by technical inspectors involved in testing the kit for Lighting Africa. The major reason for this seems to be the low capacity of the panel, which only allows for charging all devices com- pletely within one day if the daily sunlight is exploited at a maximum. In practice, households used the charging capacities mainly for the lighting device. Given this preference for lighting, too little capacity is left for the other two services. For cell phone charging, noncompatibility of the solar charger with some of the widely used cell phone types in rural Rwanda posed additional problems. In line with these techni- cal deficiencies and the households’ expressed priorities for lighting, charging patterns are dominated by 640 Grimm et al. Table 2. Balance of Socioeconomic Characteristics between Treatment and Control Group (Baseline Values) Treatment Control total (SD) t-test/chi- 2-test (total treated vs. total (SD) noncompliant (SD) control p-values) Downloaded from https://academic.oup.com/wber/article-abstract/31/3/631/2433616 by Joint Bank-Fund Library user on 08 August 2019 Household size1 4.85 (2.0) 5.5 (1.5) 5.0 (2.0) 0.491 HH’s composition (%) Share children 0–15 years 39 (24) 51 (16) 38 (23) 0.680 Share elderly 65þ 7 (20) 2 (6) 5 (16) 0.389 HH’s head male (%) 76 84 76 0.892 Age of the HH’s head 47 (15) 45 (17) 48 (15) 0.795 Education of HH head (%)1 None 35 53 35 0.857 Primary education 61 42 60 Secondary education and more 4 5 5 Cultivation of arable land (%)1 99 100 98 0.314 Ownership of arable land (%)1 95 90 95 0.791 Ownership of cows (%)1 No cow 63 84 69 0.542 One cow 22 11 19 More than one cow 15 5 12 Ownership of goats (%)1 No goat 68 79 74 0.476 One goat 16 5 14 More than one goat 16 16 12 Material of the walls (%)1 Higher value than wood, mud, or clay 14 11 14 1.000 Material of the floor (%)1 Higher value than earth or dung 12 5 11 0.854 District (%)2 Gicumbi 19 16 20 0.997 Gisagara 26 32 27 Huye 28 26 27 Rusizi 27 26 26 Number of observations 148 19 148 Note: 1Used for re-randomization; 2used for stratification. Source: Household data set 2011. the lamp: most of the time, the kit is used to charge the lamp (26 hours per week), followed by operating the radio (20 hours). It is hardly used to charge a cell phone (only two hours8). Due to the technical drawbacks of the Pico-PV kit, we will concentrate in the following on effects related to the usage of improved lighting service. Virtually all kit owning households predominantly use it for lighting.9 Some details on radio usage, preferred programs and other information sources are shown in the supplemental appendix.10 The Pico-PV lamps are mainly used by female adults, followed by male adults (see table 4). Children use the lamps less frequently. 8 The share of households using the kit for cell phone charging is very low at less than ten percent. Those households that do charge their phone with the kit charge it 19 hours per week. 9 The only exceptions are four households that reported to have technical problems with the lamp and cannot use it for this reason. 10 It can be seen that radio usage significantly increased in the treatment group, on average and across all types of house- hold members. Adults listen above all to news on the radio, while children listen to music. Consequently, radio is The World Bank Economic Review 641 Table 3. Balance of Outcome Related Characteristic between Treatment and Control Group (Baseline Values) Treatment Control total (SD) t-test/chi-2-test (total treated vs. Total (SD) Non-compliant (SD) control p-values) Downloaded from https://academic.oup.com/wber/article-abstract/31/3/631/2433616 by Joint Bank-Fund Library user on 08 August 2019 Lighting hours, categorized2 (%) 19 26 19 No lamps or candles Less or equal 3h/day 51 42 51 More than 3h/day 30 32 30 1.000 Lighting hours per day, continuous1 3.1 2.7 3.2 0.910 Usage of hand-crafted LED1 (%) 37 26 35 0.628 Usage of mobile LED1 (%) 4 5 3 0.520 Consumption of candles1 (pieces per month) 1.25 2.32 1.76 0.356 Usage of wick lamps (%) 49 47 47 0.727 Usage of no artificial lighting (%) 12 16 11 0.715 Consumption of kerosene for 0.46 0.35 0.54 0.372 lighting1 (in liter per month) Radio ownership2 (%) 64 32 64 1.000 Mobile phone ownership2 (%) 36 32 36 1.000 Number of mobile phones1 0.49 0.21 0.47 0.876 N 148 19 148 Note: 1used for re-randomization; 2used for stratification. Source: Household data set 2011. Table 4. Usage of Pico-PV Kits (Share of Treatment Households in Percent) Share of treatment households (in parentheses: only compliant households) % Pico-PV lamp is mainly used by . . . % using the kit at least once a day 86 (95) Female adult >17 years old 49 . . . using the kit for lighting 85 (97) Male adult >17 years old 23 . . . using the kit for listening to the radio 68 (79) Female between 12 and 17 years old 10 . . . using the kit for charging mobile phones 10 (11) Male between 12 and 17 years old 7 . . . use the battery pack 65 (71) Collectively used by whole family 6 Children between six and 11 years old 5 Source: Household data set 2012. Traditional lamp usage goes down substantially, with 47 percent of the treatment group using exclu- sively the Pico-PV lamp for lighting purposes.11 While treatment group households use on average 0.8 traditional lamps (any type, including candles), control group households use 1.4 traditional lamps implying that the Pico-PV lamps have replaced half of the traditional lighting sources. Treatment house- holds use above all significantly less wick lamps and hand-crafted LED lamps, but also less ready-made torches, hurricane lamps, and mobile LED lamps. The share of households that do not use any artificial lighting source, amounting to nine percent in the control group, still reaches five percent among treat- ment households. They either belong to the group of non-compliers or to the households with technical problems with the Pico-PV lamp. substantially more often the main source of information for treatment households. In the control group community gatherings constitute typically a more important source of information. 11 Table S6.1 in the supplemental appendix shows a comprehensive presentation of lamp usage in the treatment and the control group. 642 Grimm et al. Most lamp users are satisfied with the lighting quality of the lamp. More than 70 percent of all lamp users report they are “always” or “often” satisfied with the lighting quality. Only 22 percent report to be satisfied only seldom and six percent are never satisfied. Satisfaction levels with traditional lamps are substantially lower. For wick lamps and hand-crafted LED lamps, 94 percent and 91 percent, respec- tively, report to be satisfied seldom or never. Downloaded from https://academic.oup.com/wber/article-abstract/31/3/631/2433616 by Joint Bank-Fund Library user on 08 August 2019 Since both treatment and control households are located within the same communities, spill-over effects might occur. Especially children often meet and play with friends and there might be positive spill-over effects on other households’ children. If among these ‘other’ households are households from our control group, it may even downward bias our impact estimates. Yet we did not find any evidence for spill-overs. For instance, in the control group the share of children studying outside their home did not increase and is negligible at less than one percent. More generally, the qualitative interviews we con- ducted did not provide any indication for joint activities using the kits and hence spill-overs of that sort. Budget Effects and Kerosene Consumption. Looking at the price per consumed lighting hour and the price per consumed lumen hour (table 5), households in the control group pay approximately five times as much per lighting hour as households in the treatment group (950 FRW vs. 180 FRW; 1.56 USD vs. 0.30 USD). The difference is obviously even more pronounced for the price per lumen hour: A household in the control group pays seven times more per lumen hour than a household in the treatment group (70 FRW vs. 9 FRW; 0.12 USD vs. 0.02 USD). Table 5. Price and Consumption of Lighting Energy Treatment Control ITT p-value Cost per lighting hour (in FRW per 100 hours) 176 950 À702 .000 Cost per lumen hour (in FRW per 100 hours) 9 70 À57 .000 Lighting hours consumed per day 4.43 3.85 0.59 .074 Lumen hours consumed per day 142 61 78 .000 Note: The ITT depicts the difference in means at the follow-up stage between the whole treatment and control group, including also non-complying households. We control for all stratification and re-randomization characteristics. Detailed estimation results can be found in the supplemental appendix. Exchange rate as of November 2011: 1 USD ¼ 607 FRW. Source: Household data set 2011/2012. This reduction in lighting costs effectively translates into a strong increase in the amount of lumen hours consumed per day in treated households, which is more than two times as high as in control-group households (see table 5)—reflecting the very poor lighting quality of traditional lighting sources. Yet, also without accounting for the improved quality of lighting, the Pico-PV kit leads to an increase in light- ing consumption. The amount of lighting hours consumed per day is significantly higher in the treatment group after having received the Pico-PV lamp. Looking at total energy expenditure (table 6), we observe that households spend around five percent of their overall expenditures on kerosene, candles, and dry-cell batteries. In treated households we expect a significant decrease of expenditures for kerosene, candles and dry-cell batteries. In fact, we observe a significant and considerable drop of kerosene expenditures by almost 70 percent. Two types of dry-cell batteries are used in our sample, big (Type D) and small (Type AA) batteries. While more than 90 per- cent of small batteries are used for lighting, more than three-fourths of big batteries are used for radios. As a consequence, we observe a significant reduction in expenditures for small batteries, but not for the larger batteries since households use their Pico-PV kit predominantly for lighting but only very seldom to run their radio. The consumption of candles is also significantly reduced. In addition, we find a mod- erate reduction in expenditures on cell phone charging, although the difference is not significant. The World Bank Economic Review 643 Table 6. Expenditures per Month per Category (in FRW) Treatment Control ITT p-value Candles 42 109 À20 .339 Kerosene for lighting 155 609 À418 .000 Downloaded from https://academic.oup.com/wber/article-abstract/31/3/631/2433616 by Joint Bank-Fund Library user on 08 August 2019 Big batteries (Type D) 358 352 À9 .750 Small batteries (Type AA) 30 72 À43 .003 Mobile phone charging 407 520 À68 .407 Total traditional energy sources (without cooking energy) 993 1,662 À557 .000 Total expendituresa 37,971 31,334 7,249 .276 Share of energy expenditure on total expenditures 0.04 0.07 À0.03 .001 Note: The ITT depicts the difference in means at the follow-up stage between the whole treatment and control group, including also non-complying households. We control for all stratification and re-randomization characteristics. Detailed estimation results can be found in the supplemental appendix. Exchange rate as of November 2011: 1 USD ¼ 607 FRW). Source: Household data set 2011/2012. a This difference seems not to be driven by the treatment. The (nonsignificant) difference in total expenditures had already existed at baseline. Moreover, the differ- ent subcategories of expenditures do not show any significant changes over time neither. Estimating an ATT only among mobile phone users by employing the random treatment assignment as an instrument shows a statistically significant reduction of costs for phone charging of 1,662 FRW (2.74 USD). The average household that pays for charging the mobile phone pays 1,400 FRW per month (2.31 USD). In total, energy expenditures without cooking energy are 557 FRW (0.92 USD PPP) lower in the treat- ment group. This difference is statistically significant. If we compare this to the total household expendi- tures it shows the importance of energy expenditures for the household budget: The share of energy expenditures without cooking decreases by three percentage points from seven percent to four percent. Health and Environmental Effects. The combustion of kerosene is associated with harmful emissions that can lead to respiratory diseases (WHO 2016). Although the relative contribution of kerosene lamps to household air pollution is rather low compared to firewood and charcoal usage for cooking purposes, it is the immediate exposure of people sitting next to a wick lamp for a specific task (e.g., studying), that makes kerosene a substantial health threat (Lam et al. 2012). Indeed, in our sample kerosene lamps are above all used by children for studying and by women for cooking. In qualitative in-depth interviews preceding the baseline survey many households complained about sooty kerosene lamps leading to recurring eye problems and kids having black nasal mucus. We therefore examined the extent to which the decrease in kerosene lamp usage translates into a perceived improvement of air quality and, potentially, into a decrease in respiratory disease symptoms and eye problems. At the baseline stage the judgement of most households (around 67 percent in both groups) was that air quality in their houses was good, in the follow-up survey 45 percent of treated households and only three percent of control households say that the air quality in their homes has improved in com- parison to the baseline period. In an open question, virtually all treated households ascribe this improve- ment to the Pico-PV lamp. Looking at self-reported health indicators, though, we cannot confirm that this improved air quality leads to a better health status of the household members, which is not surpris- ing given that cooking fuels are still the dominating source of household air pollution.12 Households in nonelectrified areas in Africa are increasingly using dry-cell batteries and LED lamps to light their homes. Therefore, a potential reduction in dry-cell batteries deserves special attention because they might contain harmful materials and a proper collection system does not exist. In fact, in our sample 95 percent of households throw discharged batteries into their pit latrines, that is, nonsealed 12 See supplemental appendix, table S6.2, for more detailed results. 644 Grimm et al. 3–4 meter holes in their backyard. Two percent of the households collect them with their garbage, and three percent throw them away somewhere in their backyard. Hence, potentially toxic substances can be expected to enter the groundwater. The extent to which this poses a threat to people’s health is unclear, as little is known about this process, neither in Rwanda nor elsewhere (see also Bensch et al. 2015). Downloaded from https://academic.oup.com/wber/article-abstract/31/3/631/2433616 by Joint Bank-Fund Library user on 08 August 2019 Domestic Productivity Effects. Building on the substantial usage of the Pico-PV lamp we examine the extent to which this induces a potential gain in domestic productivity. For this purpose, we look at the main users’ activ- ities exercised when using the Pico-PV lamp and—in order to assess the extent of the quality improvement— which lighting sources are used among households in the control group for the respective activity. The most frequent users of the Pico-PV lamp are female adults, of which 87 percent use the lamp mainly for housework (see table 7). Housework done by women refers above all to cooking but also includes, for example, child caring, preparing the beds before going to sleep, and repairing clothes. The Pico-PV lamp replaces above all wick lamps and is used by female adults that had not been using any particular lighting device before.13 Male adults also use the lamp mostly for housework, although these are more diverse activities than for women. For male adults, the Pico-PV lamp replaces wick lamps, ready-made torches, and hand-crafted LEDs and is also used by men who had not used any artificial lighting device before for housework activities. Table 7. Activity Using Pico-PV Lamp, Adults and Children in Treatment Households (%) First Activity Second Activity Third Activity Female adult >17 years old N ¼ 149 Housework 87 Study 5 Eat 4 Male adult >17 years old N ¼ 60 Housework 71 Recreation 10 Study 10 Children 6 to 17 years old N ¼ 56 Study 75 Housework 16 Recreation 4 Note: Information on activities stem from an open question among treatment households at follow-up, asking for the main activities the different lamp users are exercising while using the lamp. Source: Household data set 2011/2012. Table 8 shows that housework is done primarily during daytime, also in the treatment group, and the total time dedicated to domestic work per day does not change significantly. The total time household members are awake per day does not change significantly, either. This reveals that the Pico-PV lamp is also used during daytime for housework activities, which is in line with observations made during quali- tative interviews: the typical Rwandan dwelling is quite dark even during the daytime and people some- times use artificial lighting in their homes. To the extent the Pico-PV lamp replaces a traditional lighting source for their daytime housework activity, lighting quality clearly improves. Yet, people might also relocate outside activities indoors and replace natural daylight by the Pico-PV lamp. In this case, lighting quality would probably not improve, but still it demonstrates the higher flexibility people have in organ- izing their daily tasks. Moreover, table 8 probes into the question whether time dedicated to any income generating activity increases, which might happen because the higher domestic productivity could set free time for other purposes. We concentrate our analysis on subsistence farmers that constitute 86 percent of household heads and 85 percent of spouses at baseline.14 Both the head of household and the spouse slightly 13 We analyse lamp switching by comparing lamps used for the corresponding activities by treatment and control house- holds. Detailed results of the analysis can be found in the supplemental appendix, table S6.3. 14 We distinguish as income generating activities between subsistence farmers, governmental employees, independent occupations, and other dependent occupations. The group sizes of the latter three are small at n ¼ 2, n ¼ 1, and n ¼ 2 for spouses and n ¼ 4, n ¼ 11, and n ¼ 9 for head of households. Therefore, these groups are very unbalanced across The World Bank Economic Review 645 Table 8. Daily Time Awake, Time Spent on Domestic Labor and Any Income Generating Activity Treatment Control ITT p-value Time awake Head of household 14h28 14h27 0h05 .739 Downloaded from https://academic.oup.com/wber/article-abstract/31/3/631/2433616 by Joint Bank-Fund Library user on 08 August 2019 Spouse 14h46 14h36 0h11 .378 Domestic labor Head of household, total 2h08 2h10 -0h01 .950 Head of household, after nightfall 0h16 0h12 0h04 .542 Spouse, total 2h48 2h30 0h16 .333 Spouse, after nightfall 0h32 0h31 0h02 .779 Any income generating activity of subsistence farmers Head of household, total 5h37 5h29 0h21 .215 Head of household, after nightfall 0h01 0h01 0h00 .823 Spouse, total 5h37 5h25 0h10 .354 Spouse, after nightfall 0h00 0h01 0h00 .462 Note: The ITT depicts the difference in means at the follow-up stage between the whole treatment and control group, including also non-complying households. We control for stratum dummies and re-randomization characteristics. Detailed estimation results can be found in the supplemental appendix. Source: Household data set 2011/2012. increase the time they dedicate to income generation (by six and three percent, respectively), but this dif- ference is not statistically significant. The third most important user group are children between six and 17 years. They use the Pico-PV lamp mainly for studying (see table 7). In order to understand changes in the productivity of studying at home, we first need to analyze children’s study patterns and how they divide their study time between daylight time and evening. As can be seen in table 9, in around one-third of the households with children at school age, children do not study after school. There is no significant difference between households in the control and treatment groups. The share of children studying after nightfall, though, is significantly higher in the treated group. The total study time, that is, after nightfall and during daytime, increases only for male primary school children. Female primary school children just shift their study time from afternoon hours to the evening leading to an increase in study time after nightfall. For secondary school children we do not observe any significant changes. Hence, the Pico-PV kits benefit primarily younger children. Besides the increase of total study time for primary school boys, it seems to increase the flexibility in girl’s time allocation, although we do not detect whether they use the freed time during the day for domestic work or recreation. In any case, at least for those children who used wick lamps before, the lighting and air quality increases. Altogether, we observe an effect of Pico-PV kit ownership on time dedicated to domestic activities only in the case of study time of primary school boys. For other Pico-PV users, we only observe a higher flexibility in organizing their domestic duties. Moreover, it is plausible to expect that the improved light- ing also increases the effectiveness of the tasks it is used for. Quantifying this effect is beyond the scope of our study, though. At least for the case of students’ school test-scores the Furukawa (2014) results advise some caution in making hasty statements about improving learning outcomes based on longer study times and better light.15 treatment and control households at baseline (see table S6.4 in the supplemental appendix). When estimating effects on time dedicated to income generation including these occupation groups, we find a significant postive effect for overall income generation time for spouses. This difference is driven, however, by these non-balanced sub-groups and can thus not be interpreted as an effect. 15 Remember that Furukawa (2014) observes even a decline of school children’s test scores in spite of an increase in study time in an RCT using solar lanterns in Uganda. One explanation for this puzzling outcome he provides is the potentially bad lighting quality of the solar lamp. In our case, we have no indication for such a bad lighting quality and we believe 646 Grimm et al. Table 9. Study Pattern (Only HH with Children at School Age; 6–17 years) N Treatment Control ITT p-value Share of HH with children studying after school 209 67 61 5 .369 Share of HH with children studying after nightfall 209 26 14 14 .006 Downloaded from https://academic.oup.com/wber/article-abstract/31/3/631/2433616 by Joint Bank-Fund Library user on 08 August 2019 Daily study time after school (in minutes) male children 6-11, total 100 0h37 0h26 0h13 .009 male children 6-11, after nightfall 100 0h29 0h12 0h12 .045 female children 6-11, total 92 0h51 0h30 0h12 .533 female children 6-11, after nightfall 92 0h27 0h11 0h11 .090 male children 12-17, total 89 1h01 0h54 0h21 .191 male children 12-17, after nightfall 89 0h50 0h32 0h14 .382 female children 12-17, total 94 1h02 0h58 0h10 .327 female children 12-17, after nightfall 94 0h44 0h37 0h10 .191 Note: The ITT depicts the difference in means at the follow-up stage between the whole treatment and control group, including also non-complying households. We control for all stratification and re-randomization characteristics. Detailed estimation results can be found in the supplemental appendix. Source: Household data set 2011/2012. V. Conclusion Our results show that simple but quality verified Pico-PV kits in fact constitute an improvement com- pared to the baseline energy sources, mostly dry-cell batteries and kerosene. Given the small size of the panel, the charging capacity is obviously not abundantly available, and many households did not man- age to use the panel for charging the radio and mobile phones; lighting turned out to be the most often used service. In these remote and poor areas, lighting is a scarce good and the lamp was indeed inten- sively used by virtually all treatment group households leading to increases in both the quality and the quantity of lighting usage. The most important finding of our study is that total energy expenditures and expenditures for dry- cell batteries and kerosene go down considerably. This shows that beneficiaries substitute traditional energy sources instead of just increasing their energy consumption. Beyond the direct effect this has on household welfare, the usage of the lamp also implies social returns. It induces advantages for people’s health because kerosene usage is associated with harmful smoke emissions and the environment because dry-cell batteries are usually disposed of in unprotected latrines or in the landscape. Since households in rural Sub-Saharan Africa are rapidly switching from kerosene or candles to LED-lamps that run on dry- cell batteries this finding deserves particular attention. In addition, we find that beneficiaries use the kit for various domestic production activities like cook- ing or studying. Although we cannot quantify the benefits, evidence from the literature strongly suggests that the solar lamp allows doing these activities better and faster than with traditional lighting sources, which plausibly results in an overall increase in domestic output. The solar lamp also enables households to allocate their time more freely and to shift activities toward the evening hours. School children, for example, find better and more flexible studying conditions thanks to the improved lighting source. Even if this does not lead to an immediate measurable increase in domestic output, pursuing the activities with better light and in a more flexible way will at least reduce the effort that is needed to undertake house- hold chores. This would still be an important improvement of household’s living conditions. While ultimate poverty impacts on, for example, income or educational investments might be small compared to productivity gains associated with bigger infrastructure interventions, these effects are still considerable from the poor’s perspective, particularly having in mind the low investment costs of the intervention at 30 USD per kit. this would have been disclosed in the various qualitative interviews we conducted (in which many other problems were discussed pretty openly, see Section IV). The World Bank Economic Review 647 Our results hence substantiate the Tier-1-threshold of modern energy access in the SE4All Global Tracking Framework. The Pico-PV kits can in fact meet the need for basic energy services in poor areas where energy consumption is still at a very low level. Yet, comparing our findings to more advanced regions and larger interventions, such as grid extension, it also becomes evident that Pico-PV kits cannot satisfy the whole portfolio of energy demand (Lenz et al. 2016). Hence, in many not so remote areas Pico-PV kits can Downloaded from https://academic.oup.com/wber/article-abstract/31/3/631/2433616 by Joint Bank-Fund Library user on 08 August 2019 be considered as either a complement to a grid connection for backup purposes or as a bridging technology toward a grid connection at a later point in time. For very poor areas in the periphery of a country as studied in this paper, in contrast, Pico-PV is in many cases the only option to obtain modern energy because, first, these regions are beyond the reach of the electricity grid for many years to come and, second, other off-grid solutions such as larger solar home systems are too expensive. We therefore argue that households in such remote areas are the major target group of Tier 1 energy systems within the SE4All initiative. What is crucial for the acceptance of this new technology is the proper functioning and ease in usage of the kit—in particular if the objective is to set up a market as pursued by programs like Lighting Africa. It has turned out that a relatively mature product such as the Pico-PV kit used in this study, of which the principal components had been tested and certified by Lighting Africa as well as massively sold in other countries, might still exhibit technical problems under real usage conditions. This is in line with findings of Furukawa (2014) who observes that insufficient charging under real usage conditions led to flickering light quality. Testing and certification procedures as well as the development of compre- hensible usage guidelines should therefore encompass a strong component of field tests and not only lab- oratory examinations. This is particularly important in the light of the rapid penetration of rural Africa with non-branded LED lamps that has occurred in recent years (see Bensch et al. 2015). In terms of light- ing quality, these dry-cell battery-run lamps are on a par with Pico-PV kits. Nonetheless, Pico-PV kits that meet quality standards in terms of usability and lifetime are a worth- while investment. If kerosene or dry-cell batteries are replaced, households with consumption patterns as observed in our research economize on average 0.95 USD PPP per month, which is around two percent of monthly household expenditures. The investment into the Pico-PV kit then pays off after 18 months, which is less than its life-span of 2–3 years, but the interplay of cash and credit constraints, the lack of information, and high discount rates will make most households forego this investment. This claim points at a dilemma of Lighting Africa and other donor and governmental interventions, which intend to disseminate Pico-PV kits via sustainable markets as a contribution to SE4All: The major target population will hardly be able to bring up the required investment. Financing schemes might in some regions be an obvious solution. But given the long pay-off period for the bottom of the income dis- tribution and noninternalized advantages, such financing schemes are probably not effective. At the same time, if it is clearly the political will both in national governments and among the international community to provide electricity also to the very poor, one should consider more direct promotion options. Subsidized or even free distribution of kits might then be an alternative to reach the poorest of the poor. While many development practitioners are opposed to a free distribution policy and it would be in stark contrast to the strategies pursued by ongoing dissemination programs, the empirical literature provides evidence from other field experiments that supports such an approach (Kremer and Miguel 2007; Cohen and Dupas 2010; Tarozzi et al. 2014; Bensch and Peters 2015). As a matter of course, a subsidized distribution policy would require establishing institutions that maintain the subsidy scheme including an effective system for maintenance and replacement of broken kits in order to ensure long- term sustainability. Moreover, since subsidies would require public funds, the priority of the SE4All goal would obviously need to be pondered against other development objectives. Having said this, it is also clear that further experimental studies that can examine the mechanisms behind take-up behavior, such as the households’ willingness-to-pay for electric energy, the role of credit 648 Grimm et al. constraints, and information are certainly useful. Such research efforts would help to design appropriate least-cost strategies to achieve the modern “energy-for-all-goals” of the international community. References Downloaded from https://academic.oup.com/wber/article-abstract/31/3/631/2433616 by Joint Bank-Fund Library user on 08 August 2019 Barron, M., and M. Torero. 2014. “Electrification and Time Allocation: Experimental Evidence from Northern El Salvador.” MPRA Paper 63782, University Library of Munich, Germany. ———. 2015. “Household Electrification and Indoor Air Pollution.” MPRA Paper 61424, University Library of Munich, Germany. Begemann, S.H.A., G.J. van den Beld, and A.D. Tenner. 1997. “Daylight, Artificial Light and People in an Office Environment, Overview of Visual and Biological Responses.” International Journal of Industrial Ergonomics 3: 231–39. Bensch, G., and J. Peters. 2015. “The Intensive Margin of Technology Adoption: Experimental Evidence on Improved Cooking Stoves in Rural Senegal.” Journal of Health Economics 42: 44–63. Bensch, G., J. Peters, and M. Sievert. 2013. “Fear of the Dark? How Aaccess to Electric Lighting Affects Security Attitudes and Nighttime Activities in Rural Senegal.” Journal of Rural and Community Development 8 (1): 1–19. ———. 2015. “The Lighting Transition in Africa: From Kerosene to LED and the Emerging Dry-Cell Battery Problem.” (No. 579). Essen: Ruhr Economic Papers. Bensch, G., J. Kluve, and J. Peters. 2011. “Impacts of Rural Electrification in Rwanda.” Journal of Development Effectiveness 3 (4): 567–88. Bernard, Tanguy. 2012. “Impact Analysis of Rural Electrification Projects in Sub-Saharan Africa.” World Bank Research Observer 27 (1): 33–51. Bertrand, J. T., K. O’Reilly, J. Denison, R. Anhang, and M. Sweat. 2006. “Systematic Review of the Effectiveness of Mass Communication Programs to Change HIV/AIDS-related Behaviors in Developing Countries.” Health Education Research 21 (4): 567–97. Boyce, P.R., J.W. Beckstead, N.H. Eklund, R.W. Strobel, and M.S. Rea. 1997. “Lighting the Graveyard Shift: The Influence of a Daylight-Simulating Skylight on the Task Pperformance and Mood of Night Shift Workers.” Lighting Research and Technology 29 (3): 105–34. Brainard, G.C., J.P. Hanifin, J.M. Greeson, B. Byrne, G. Glickman, E. Gerner, and M.D. Rollag. 2001. “Action Spectrum for Melatonin Regulation in Humans: Evidence for a Novel Circadian Photoreceptor.” Journal of Neuroscience 21 (16): 6405–6412. Cohen, J., and P. Dupas. 2010. “Free Distribution or Cost-Sharing? Evidence from a Randomized Malaria Prevention Experiment.” Quarterly Journal of Economics 125 (1): 1–45. Daurat A., A. Aguirre, J. Foret, P. Gonnet, A. Keromes, and O. Benoit. 1993. “Bright Light Affects Alertness and Performance Rhythms during a 24-hour Constant Routine.” Physics and Behaviour 53 (5):929–36. Dinkelman, T. 2011. “The Effects of Rural Electrification on Employment: New Evidence from South Africa.” American Economic Review 101 (7): 3078–108. Dupas, P 2014. “Short-Run Subsidies and Long-Run Adoption of New Health Products: Evidence from a Field Experiment.” Econometrica 82 (1): 197–228. Furukawa, C. 2014. “Do Solar Lamps Help Children Study? Contrary Evidence from a Pilot Study in Uganda.” Journal of Development Studies 50 (2): 319–41. Grogan, L., and A. Sadanand. 2013. “Rural Electrification and Employment in Poor Countries: Evidence from Nicaragua.” World Development 43: 252–65. Grunberger, J., L. Linzmayer , M. Dietzel, and B. Saletu. 1993. “The Effect of Biologically Active Light on the Noo- and Thymopsyche on Psycho-physiological Variables in Healthy Volunteers.” International Journal of Psychophysiology 15 (1): 27–37. IEA. 2011. World Energy Outlook 2011. Paris. Jensen, R., and E. Oster. 2009. “The Power of TV: Cable Television and Women’s Status in India.” Quarterly Journal of Economics 124 (3): 1057–94. Khandker, Shahidur R., Douglas F. Barnes, and Hussain A. Samad. 2012. “The Welfare Impacts of Rural Electrification in Bangladesh.” Energy Journal 33 (1): 187–206. The World Bank Economic Review 649 ———. 2013. “Welfare Impacts of Rural Electrification: A Panel Data Analysis from Vietnam.” Economic Development and Cultural Change 61 (3): 659–92. Kremer, M., and E. Miguel. 2007. “The Illusion of Sustainability.” Quarterly Journal of Economics 122 (3): 1007–65. Kuller, R., and T. Laike. 1998. “The Impact of Flicker from Fluorescent Lighting on Well-Being, Performance and Downloaded from https://academic.oup.com/wber/article-abstract/31/3/631/2433616 by Joint Bank-Fund Library user on 08 August 2019 Physiological Arousal.” Journal of Ergonomics 41 (4): 433–47. Kuller, R., and L. Wetterberg. 1993. “Melatonin, Cortisol, EEG, ECG and Subjective Comfort in Healthy Humans: Impact of Two Fluorescent Lamp Types at Two Light Intensities.” Lighting Research and Technology 25 (2): 71–80. Lenz, L., A. Munyehirwe, J. Peters, and M. Sievert. 2016. “Does Large Scale Infrastructure Investment Alleviate Poverty? Impacts of Rwanda’s Electricity Access Roll-Out Program.” World Development, forthcoming. La Ferrara, E., A. Chong, and S. Duryea. 2012. “Soap Operas and Fertility: Evidence from Brazil.” American Economic Journal: Applied Economics 4 (4): 1–31. Lam, N. L., K. R. Smith, A. Gauthier, and M. N. Bates. 2012. “Kerosene: A Review of Household Uses and Their Hazards in Low- and Middle-Income Countries.” Journal of Toxicology and Environmental Health, Part B 15 (6): 396–432. Lange, H. 1999. Handbuch fu ¨ r Beleuchtung, SLG, LiTG, LTG, NSVV, 5. Auflage, ecomed SICHERHEIT. Landsberg am Lech. Lighting Global. 2016. Off-Grid Solar Market Trends Report 2016, Bloomberg New Energy Finance and Lighting Global in cooperation with the Global Off-Grid Lighting Association (GOGLA). Lipscom M., M. Mobarak, and T. Barham. 2013. “Development Effects of Electrification: Evidence from the Topographic Placement of Hydropower Plants in Brazil.” American Economic Journal: Applied Economics 5 (2): 200–231. MININFRA. 2016. Rural Electrification Strategy. April 2016. Ministry of Infrastructure, Republic of Rwanda. Kigali. O’Sullivan, K., and D. F. Barnes. 2006. “Energy Policies and Multitopic Household Surveys. Guidelines for Questionnaire Design in Living Standards Measurement Studies.” Energy and Mining Sector Board Discussion Paper (17). Partonen, T., and J. Lo ¨ nnqvist. 2000. “Bright Light Improves Vitality and Alleviates Distress in Healthy People.” Journal of Affective Disorders 57 (1–3): 55–61. Peters, J., and M. Sievert. 2016. “Impacts of Rural Electrification Revisited: The African Context.” Journal of Development Effectiveness 8 (3): 327–45. Samad, Hussain A., Shahidur R. Khandker, M. Asaduzzaman, and M. Yunus. 2013. “The Benefits of Solar Home Systems: An Analysis from Bangladesh.” World Bank Policy Research Working Paper No. 6724, World Bank, Washington D.C. Sievert, M. 2015. “Rural Electrification and Domestic Violence in Sub-Saharan Africa.” Ruhr Economic Papers #570. RWI Working Paper No. 570. Sustainable Energy for All (SE4All). 2013. Sustainable Energy for All Global Tracking Framework Consultation Document. http://www.se4all.org/tracking-progress/ [Accessed September 10, 2014]. Sustainable Energy for All (SE4All). 2015. Sustainable Energy for All Global Tracking Framework Consultation Document. Retrieved from: http://www.se4all.org/tracking-progress/. Tarozzi, A., A. Mahajan, B. Blackburn, D. Kopf, L. Krishnan, and J. Yoong. 2014. “Micro-loans, Insecticide-Treated Bednets, and Malaria: Evidence from a Randomized Controlled Trial in Orissa, India.” American Economic Review 104 (7): 1909–41. United Nations. 2005. The Energy Challenge for Achieving the Millennium Development Goals. New York. ———. 2010. Energy for a Sustainable Future. Report and Recommendations. New York. van de Walle, D., M. Ravallion, V. Mendiratta, and G. Koolwal. 2016. “Long-Term Gains from Electrification in Rural India.” World Bank Economic Review, forthcoming. WHO. 2016. Burning Opportunity: Clean Household Energy for Health, Sustainable Development, and Wellbeing of Women and Children. Washington, D.C.: World Health Organization. Wilkins, A.J., I. Nimmo-Smith, A. Slater, L. Bedocs. 1989. “Fluorescent Lighting, Headaches and Eyestrain.” Lighting Research and Technology 21 (1): 11–18. World Bank. 2009. “Unit Costs of Infrastructure Projects in Sub-Saharan Africa.” Africa Infrastructure Country Diagnostic, Background Paper No. 11, World Bank, Washington D.C.