Economics of a Light Bulb: Experimental Evidence on CFLs and End-User Behavior
Last registered on August 14, 2014


Trial Information
General Information
Economics of a Light Bulb: Experimental Evidence on CFLs and End-User Behavior
Initial registration date
August 14, 2014
Last updated
August 14, 2014 2:31 PM EDT
Primary Investigator
World Bank
Other Primary Investigator(s)
PI Affiliation
Harvard University
PI Affiliation
University of Michigan
Additional Trial Information
On going
Start date
End date
Secondary IDs
In developing countries, residential access to modern energy and lighting improves living standards and productivity (World Bank, 2006). Yet due to electricity constraints, blackouts and high prices are not uncommon. Because lighting is a major component of electricity consumption, energy efficient technologies such as compact fluorescent lamps (CFLs) can reduce electricity demand and help energy-constrained countries to meet conservation goals. Using a randomized study design, we examine the adoption, utilization, and diffusion of CFLs in Kyrgyzstan. We find that energy efficient light bulbs have a significant impact on electricity use, that there is evidence of a rebound in electricity use, and that the behavioral response differs between households that received CFL bulbs for free vs. for a positive price. Moving forward, we continue to evaluate reasons for these differential responses.
External Link(s)
Registration Citation
Carranza, Eliana, Robyn Meeks and Sendhil Mullainathan. 2014. "Economics of a Light Bulb: Experimental Evidence on CFLs and End-User Behavior." AEA RCT Registry. August 14.
Former Citation
Carranza, Eliana et al. 2014. "Economics of a Light Bulb: Experimental Evidence on CFLs and End-User Behavior." AEA RCT Registry. August 14.
Experimental Details
Our intervention is the deployment of compact fluorescent lamps (CFLs) at a free or reduced price in Kyrgyzstan. We vary the intensity of the intervention at a regional level, in order to elicit information on network effects related to CFL usage.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Key outcomes variables include household-reported willingness to pay (WTP) measures, rebound effects, and electricity usage reports from the meter logs.
Primary Outcomes (explanation)
Our narrow definition of "rebound effect" excludes indirect cross price and income effects. The energy use of lighting (E), measured in kW, is defined to be the product of the energy intensity of such service (I) in kw/hour, and the household consumption of hours of lighting (A): E = I*A. Households determine their consumption A(T) based on the price per hour of lighting (T) rather than the price per kW used to produce lighting (P). The relationship between the prices is T = EP/A.

We are interested in improving energy efficiency, i.e., what happens when "I" falls. We differentiate E with respect to energy efficiency (y = 1/I) to determine the rebound (the electricity consumed for services, taking into account the electricity elasticity of consumption costs).
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
To better understand the adoption, use, and diffusion process of CFL technology, we use a randomized trial in Kyrgzstan to inspect: (1) the "rebound" effects, i.e., behavioral responses that boost consumption and offset potential electricity savings of CFLs and (2) the role of peer networks in diffusing information. We elicit measures of willingness to pay (WTP) to study these effects, as this metric will affect treatment adoption.

The two-stage randomization works as follows: first, villages in Kyrgyzstan are selected based on accessibility. Next, we randomize transformer groups (TGs) within these villages into groups of treatment intensity: control (0% treated), low-intensity (60% treated), and high-intensity (80% treated). Finally, we randomly select 20 percent of households in each TG for survey. These households are randomized into three groups: control (no CFL offer), T1 (free CFLs), and T2 (reduced-price CFLs).

In terms of site selection, all regions in the study must be low-income, have high rates of electrification, and have relatively substantial household expenditure on energy. Participating households must have formal connections to electrical grid, have household-specific meters for electricity consumption, and pay for electricity based on actual electricity consumption rather than a fixed charge.
Experimental Design Details
Randomization Method
We run a computer-based randomization.
Randomization Unit
We have two levels of randomization. First, we randomize transformer groups into different treatment intensities. Next, we randomize at the household level into free CFLs, reduced-price CFLs, and no CFLs (i.e., control).
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
We selected 124 transformer groups (TGs).
Sample size: planned number of observations
1,000 households
Sample size (or number of clusters) by treatment arms
39 TGs control, 45 low-intensity, 40 high intensity.
Within these groups:
Control TGs:
Control: 200 households

Low-intensity TGs:
Control: 186 households
Free: 143 households
Buy: 134 households

High intensity TGs:
Control: 71 households
Free: 136 households
Buy: 134 households
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB Name
Harvard University Committee on the Use of Human Subjects in Research
IRB Approval Date
IRB Approval Number
Post Trial Information
Study Withdrawal
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Is data collection complete?
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports and Papers
Preliminary Reports
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