Impact of LPG promotion program in Ghana: The role ofdistance to refill
Kwame Adjei-Mantey
Kenji TakeuchiPeter Quartey
August , 2021
Discussion Paper No.2120

GRADUATE SCHOOL OF ECONOMICS
KOBE UNIVERSITYROKKO, KOBE, JAPANImpact of LPG promotion program in Ghana:
The role of distance to refill
Kwame Adjei-Mantey*
Graduate School of Economics, Kobe University

Kenji Takeuchi
Graduate School of Economics, Kobe University

Peter Quartey
Institute of Statistical, Social & Economic Research (ISSER), University of Ghana

Abstract
This study investigates the impact of a clean cooking intervention on primary fuel choice and on
households’ willingness to pay for an improved LPG distribution model in Ghana. Using dataobtained via a survey of 904 households in two beneficiary districts, we found that the intervention
led to higher LPG usage. The program increases the probability of households choosing LPG as a
primary cooking fuel by 24% and the rate of use of LPG among households by 33%. Furthermore,an analysis of willingness to pay shows that delivery preference is not statistically different
between beneficiary and control groups. The distance to refill the cylinder significantly affects
LPG usage and willingness to pay. A policy that brings LPG refill closer to households and reduces
the time and money cost of accessing a refill station is key to increasing the adoption of LPG as
the primary cooking fuel.

Keywords: LPG; refill station; willingness to pay; distance; Ghana; RLPGPP*Corresponding author. kwamemantey@gmail.com

11. Introduction
Cooking with solid fuels, such as firewood and charcoal, is still common in many developing
countries. It is a major cause of household air pollution and leads to numerous health risks andmortality. An estimated death toll of more than 3 million annually can be linked to indoor air
pollution (WHO, 2018). Research has shown that household air pollution from cooking with solid
fuels has health implications, such as acute respiratory infections and cancer (Lim et al., 2013).
The dangers associated with the use of such fuels have prompted governments and policymakers
to enhance the uptake and adoption of improved and cleaner cooking practices.
Liquefied petroleum gas (LPG) is one of the cleaner cooking fuels strongly promoted in many
countries. Interventions to promote LPG have taken various forms, ranging from providing
equipment for free to households (Abdulai et al., 2018) to financial incentives such as subsidies
on purchases (Calzada and Sanz, 2018). These interventions, including the provision of free LPG,
have yielded mixed outcomes among different countries. A growing body of literature has
examined the impact of programs to promote clean cooking (Carrion et al., 2018; Quinn et al.,2018; Troncoso and da Silva, 2017). While some studies suggest positive effects of such programs(Andadari, 2014; Calzada and Sanz, 2018; Kimemia and Annegarn, 2016), analyses in other areas
show that these programs were ineffective (Abdulai et al., 2018; Adjei-Mantey and Takeuchi,
2019; Asante et al., 2018). Therefore, it is essential to evaluate the effects of clean cooking
interventions to guide future programs.
In Ghana, the Rural LPG Promotion Program (RLPGPP) was rolled out in 2013 and continued
for four years. The RLPGPP aimed to make LPG the primary cooking fuel for rural residents. The
RLPGPP distributed free LPG cylinders, cookstoves, and accessories to rural households as theytransitioned from firewood and charcoal to LPG, thus removing the initial cost barrier (Ministryof Energy, 2018). According to the Ghana Living Standards Survey (GLSS VII) data collected in2017, LPG is the primary cooking fuel for 18.4% of households.2 While the use of LPG among
urban households is as high as 34.9%, only 6% of rural households use LPG as their primarycooking fuel. Ghana’s 2012 Sustainable Energy for All Action Plan targeted a 50% household
LPG access rate by 2020 (Energy Commission, 2012), and programs such as the RLPGPP were2

It slightly increased from the share of 16.9% in 2013 (GLSS VI). The proportions of Ghana households that use
firewood and charcoal as primary cooking fuel stand 46.5% and 28.2%, respectively.

2

part of interventions to achieve the target. Documents provided by Ghana’s Ministry of Energy,
the implementing agency for the RLPGPP, show that 149,500 cylinders and 118,360 cookstoves
with accessories were distributed in a third of districts nationwide from 2013 to 2017. RLPGPP
has since been discontinued, but the effect of the program remains to be measured3. Concerning
other LPG programs, the government of Ghana in 2017 proposed replacing the current LPG
distribution system with a new one known as the LPG cylinder recirculation model. However, thisprogram has not been implemented, and the existing distribution system has not been replaced.
This study contributes to the literature in three ways. First, we focus on the distance to refill
stations as a key to promoting LPG usage. While several researchers evaluated the impact of clean
cooking programs (Andadari, 2014; Calzada and Sanz, 2018; Kimemia and Annegarn, 2016), they
did not thoroughly consider the impact of distance to obtain LPG on use. Because access to refill
stations represents a considerable cost for rural households, it is crucial to examine their effect onfuel usage. Second, this study examines the treatment effect of a clean cooking intervention that
reduces only the initial cost of use by providing free equipment. Although earlier studies haveconducted similar impact evaluations in other countries, the interventions are mostly subsidies orcontain a price support mechanism. For example, Calzada and Sanz (2018) explored Peru’s
program, which offers monthly vouchers to treated households to be exchanged for LPG. Kimemia
and Annegarn (2016) examined South Africa’s policy to control the maximum retail price of LPG.
In both cases, the interventions included a subsidy or a price support mechanism, which continued
over a long period, whereas the Ghanaian program provided one-time free LPG equipment. It is
crucial to ascertain whether this marked difference relative to price leads to differences in thetreatment effects. Initial setup costs are known to limit LPG usage, and hence the removal of thesecosts could represent a significant push towards a transition to clean cooking fuel. Furthermore,since affordability has been noted in the literature to be significantly related to LPG use (Karimu
et al., 2016), a policy with continuous subsidies and price support systems is expected to have agood response from households. Previous evaluations of the RLPGPP in Ghana used a descriptive
approach (Asante et al., 2018) or evaluated spillover effects at the district level (Adjei-Mantey and
Takeuchi, 2019). This study differs from these studies in that it collects original survey data and3

Asante et al. (2018) found that the RLPGPP did not demonstrate an effective change in indoor air pollution while
Kaali et al. (2019) documented that a similar cookstove intervention for pregnant women in Ghana reduced indoor
air pollution.

3

uses micro-econometric analysis at the household level. Third, this study investigates thewillingness to pay (WTP) for an improved LPG delivery system. By using the stated preferencetechnique, studies such as Chindarkar et al. (2021), Zahno et al. (2020), and Jeuland et al. (2015)
examined WTP to use LPG and improved cookstoves. Our study complements the above literatureby focusing on the WTP for the delivery system as a practical and operational step of LPG use.
The remainder of this paper is structured as follows: Section 2 reviews the relevant literature,
while Section 3 describes the data and the strategies to collect them. Section 4 explains themethodology adopted for analyzing the treatment effect, and the results are discussed in Section 5.
Section 6 explores the WTP for LPG delivery services and their determinants, and Section 7
concludes the study with policy recommendations.

2. Literature Review
Several studies have investigated the impact of clean-cooking interventions. These intervention
schemes take various forms across different countries. Calzada and Sanz (2018) evaluated Peru’s
program to substitute LPG for traditional stoves among low-income households. The beneficiaries
received monthly discount vouchers under the program, which amounted to half the cost of an
LPG cylinder. By applying matching techniques, the researchers observed that beneficiaryhouseholds used LPG to cook 33%–38% more than non-beneficiaries. Additionally, they found noevidence that the use of LPG reduced respiratory problems in beneficiary households. Pollard etal. (2018) evaluated the same program in Peru using data from a different province. In addition toreporting a greater likelihood of LPG usage among beneficiaries, thus confirming Calzada andSanz’s (2018) findings, the study finds that kitchen concentrations of PM2.5, were lower for
program beneficiaries, hence lower exposure to household air pollution among this group.
Kimemia and Annegarn (2016) evaluated the LPG intervention program in 2006 in Atteridgeville,
South Africa. In 2010, the government followed up on the initial intervention by controlling the
maximum retail price of LPG to boost uptake. The study reported that the program led to LPG
substitution for combustion fuels among beneficiary households, making LPG the second most
preferred cooking fuel after electricity, which was the most preferred possibly due to monthly

4subsidies. They further observed that 67% of respondents maintained regular use of LPG for
cooking or heating seven years after the program was implemented.
The Indonesian government embarked on a fuel conversion program that involved removing
subsidies on kerosene and reallocating them to LPG. Imelda (2020) evaluated the impact of the
program on fuel choice and infant mortality. Overall, she found that the program increased thenumber of households that used LPG as primary fuel by 350%–900% while reducing total
kerosene consumption by over 80% in four years. The study also found that the program reduced
infant mortality by a conservative estimate of 25%, possibly through the channel of improved
indoor air quality associated with LPG use. Andadari et al. (2014) also found that LPG
consumption increased after the program, with a significant shift from kerosene usage across large
sections of the population. This shift was due to the increased prices of kerosene because of subsidy
removal. The study found that the program helped alleviate extreme energy poverty in Indonesia
by substantially increasing LPG usage. Both evaluations of the Indonesian fuel conversion
program confirmed the effectiveness of the program in promoting LPG use.
Few studies have been conducted on Ghana’s RLPGPP. Asante et al. (2018) examined theprogram’s effect in the Nkoranza North District of Ghana and observed that LPG usage was low
among beneficiary households. After 18 months of program implementation, less than 10% of
respondents still used LPG, and all respondents used firewood or charcoal as their primary fuel.
Further analysis showed that the program did not yield significant changes in personal exposure
to carbon monoxide. A study by Abdulai et al. (2018) in the same district found that financial
constraints hampered the sustained use of LPG among beneficiaries by limiting their ability toafford the cost of fuel itself and that of commuting over long distances to refill their cylinders.
They also found that factors promoting LPG use included quicker cooking time and reduced
burden of firewood collection. Adjei-Mantey and Takeuchi (2019) examined the program’s
spillover effects at the district level using nationwide survey data. The study found no evidence ofthe program’s significant impact in choosing LPG over fuelwood in beneficiary districts. The study,
however, found that the RLPGG contributed to poverty alleviation in beneficiary districts. The
potential channel was through the increased number of LPG refill stations established inbeneficiary districts throughout the program’s implementation. Apart from national level programs,
Kaali et al. (2019) conducted a study in Kintampo municipality in Ghana to examine the effects of5

prenatal household air pollution on mitochondrial function and how clean cooking interventions
could reverse the effect. The study found that children born in households that benefited from arandomized LPG intervention had higher mitochondrial DNA copy number (a biomarker used formany diseases) than children born in households that used efficiency biomass stove or traditional
3-stone fire stoves. This suggests that LPG intervention potentially reverses the effects of exposure
to household air pollution.

In contrast to studies revealing the effectiveness of clean cooking interventions, studies in Ghana
have not supported this narrative so far. The limitations of these studies can be summarized asfollows. First, Asante et al. (2018) and Abdulai et al. (2018) did not compare beneficiaries to nonbeneficiary households to measure program impact. Their studies either focused on the reach,
effectiveness, adoption, implementation, and maintenance (REAIM) framework or used focus
group discussions to reveal factors that enabled or inhibited LPG use and were both based solely
on beneficiary households. This study contributes by comparing beneficiaries to non-beneficiaries
under a quantitative framework to measure impact. Second, Adjei-Mantey and Takeuchi (2019)
examined the program’s spillover impacts at the district level, even though the program targeted
selected households. Thus, there is a possibility that fuel choice changes at the household level
were not large enough to impact the district level significantly. Therefore, an evaluation at thehousehold level is necessary to ascertain the results in more detail. Finally, the other countries’
programs used price support for consumers, such as subsidies and discount vouchers. Instead,Ghana’s RLPGPP reduced the initial cost of introduction but did not include support forcontinuous usage, thereby not protecting consumers from high fuel costs. Because the downstream
petroleum sector has been deregulated in Ghana, prices are not controlled and fluctuate due tomarket conditions. Examining the impact under this condition allows us to enrich the literature
concerning program implementation.
Other clean cooking interventions involved the use of improved cookstoves (ICSs). ICSs require
a lower amount of biomass fuel than traditional cookstoves and hence emit fewer pollutants.
Empirical studies on ICS use have shown that interventions often led to increased adoption of
cookstoves to improve clean cooking (Bensch and Peters, 2015; Bonan et al., 2021; Levine et al.,2018; Miller and Mobarak, 2014). Although there is a common feature with the current study, the6evaluation of LPG intervention has a particular implication for understanding the policy that
substantially reduces indoor air pollution.
Our study also relates to the strand of research that examined WTP for clean cooking. For
example, Zahno et al. (2020) examined the role of health awareness on households’ WTP for LPG
and actual LPG consumption. The study found that WTP for LPG use increased when healthinformation was provided. The distance to obtain LPG lowered the WTP, but this was notstatistically significant. A related study by Chindarkar et al. (2021) examined the WTP to use LPG
exclusively in rural India by employing a dichotomous choice approach. They also found thatknowledge about the health benefits of LPG was a significant positive predictor of WTP.
In contrast to these studies, Beltramo et al. (2015) found that marketing information on the healthimproving features of ICSs did not increase WTP for fuel-efficient cookstoves in Uganda.
However, they also found that WTP was 40% higher when the payment due was over four weeks
than within a week. The result highlighted the importance of liquidity or affordability barriers thathouseholds face when adopting ICSs. Similarly, Jeuland et al. (2015) used a discrete choice
experiment to elicit WTP for improved cookstoves in India. They found that WTP was highest forthe smoke-reducing attribute of the improved cookstoves, followed by the convenience of
cookstoves and the reduction in fuel requirement. These findings suggest that households have ahigher WTP to reduce smoke emissions, and LPG fits well into this cooking mode. While thesestudies are an important precedent of investigations on household preferences for clean cooking,they did not consider the WTP for a system that assures a constant supply of these fuels. Our study
fills this gap by examining the WTP for LPG delivery to reduce access to further adoption barriers.

3. Data
3.1 Data Collection
We collected data by conducting face-to-face interviews in the Ga South4 and Ada West districtsof Ghana. The important factor in selecting these study areas was the availability of the list of
beneficiary households of RLPGPP to identify treatment groups in the districts. Among the few

4

Ga South is officially identified as a municipality. However, we refer to both Ga South and Ada West as districts
throughout this study for simplicity.

7

districts for which Ghana’s Ministry of Energy provided the list of households that benefitted fromthe program, the Ga South and Ada West districts’ lists were complete, as they contained thecontact information of each household. In both districts, 1,000 households benefitted from the
RLPGPP, which was implemented in these districts in 2017.
According to estimates from the most recent population census conducted in 2010, Ada West has
11,642 households and a total population of 59,124, with 70.3% being rural residents, while Ga
South has 100,701 households and a population of 411,377 with a 10% rural population (GSS,
2014a; GSS, 2014b). A larger proportion of Ada West settlements can be found in the coastal area,
while Ga South has a relatively larger proportion of inland residents. The number of active refill
stations operating in these districts at the time of the survey was seven for Ada West and 12 for
Ga South.
We used electoral areas within the districts as enumeration areas (EAs) for the survey. In Ghana,electoral areas are geographical demarcations in each district for political administration anddecentralized governance. The distribution of LPG equipment under the RLPGPP was done at theelectoral area level, with lists of beneficiaries available for each district’s electoral areas. Ada Westhas 15 electoral areas, and Ga South has 23 electoral areas. Considering the geographical balance,
we sampled seven electoral areas in Ada West and 13 electoral areas from Ga South as EAs forthe survey5. Following stratification of households on an electoral area basis, random sampling
was employed to sample treated households using the beneficiary list information. We used asnowball sampling strategy to complement simple random sampling to select non-beneficiary
respondents within the same EA to serve as a control group. The number of candidates forrespondents in each EA was proportional to the number of households that benefited from theprogram in that EA. When candidates were unavailable due to relocation from the community,
travel, non-cooperation, or unreachability, we replaced them with other households from the same
EA.
The field survey was conducted using computer-assisted personal interviews (CAPI) from August
3rd to 31st, 2020. The exercise began with a training program for survey enumerators, after whicha pilot survey was conducted to check whether the questionnaires were suitable and understandable

5

A list of sampled EAs is provided in Appendix A.

8to the respondents. The pilot survey also provided enumerators an opportunity to practice with thesurvey instrument ahead of the main exercise. After revisions of the instrument based on the pilot
exercise’s feedback, the main field survey was conducted by 14 enumerators. The total number ofsuccessful interviews was 904, of which 448 were conducted in Ada West and 456 in Ga South.

3.2 Data Description
Table 1 presents summary statistics of the data. The data showed that 45% of the sample
benefitted from RLPGPP. As mentioned in the above section, the percentage is higher than theactual share of beneficiaries in each district, approximately 8.5% in Ada West and 1% in Ga South.
The proportion of households that used LPG as their main fuel stood at 43%, while about 40%
used LPG comparably more than other fuels in the seven days preceding the interview day. LPG
usage rate is calculated as frequency of LPG usage in a day as a ratio of frequency of cooking in aday.6 The mean LPG usage rate was 52%; on average, households used LPG once out of every
two cooking times. Regarding occupation, 28% of the sample worked in the agricultural sector.
On average, a round-trip to the nearest LPG refill station took 42 minutes (travel time only).
Table 1: Summary statistics of household characteristics and cooking fuel use variables
VariableObs
Mean
Std. Dev.
Min
Max
Treatment
904
0.45
0.5
0
1
Distance to refill station (mins)
836
41.6
29.3
1
240
LPG is main fuel
904
0.43
0.5
0
1
LPG in past 7 days
904
0.44
0.5
0
1
LPG usage rate
866
0.52
0.45
0
1
Education (years)
904
7.4
4.5
0
16
Occupation (1 = agriculture)
904
0.3
0.45
0
1
Access to information
904
0.84
0.36
0
1
Access to financial services
904
0.66
0.48
0
1
Rural
904
0.77
0.42
0
1
Risk averse
904
0.77
0.42
0
1
District (1 = Ga South)
904
0.5
0.50
0
1
*
WTP (cedis)
904
6.97
3.69
2
20
Household income (cedis)
904
1781.31697.7022600* Approximately, 1 Ghana cedi is equal to 0.17 US dollars.

6

For example, if a household cooks thrice a day and uses LPG twice a day, this household's LPG usage rate
becomes 0.67.

94. Empirical Methodology – LPG Usage
We employed a random utility framework to examine the factors that influenced household LPG
usage. The framework assumes that the utility associated with a particular choice alternative isexpressed as a function of observable and non-observable (stochastic) components. A household ichooses its main fuel from cooking fuel options j that includes LPG and other fuels (firewood andcharcoal). The household chooses LPG as its main cooking fuel if the utility derived from using
LPG, ULPG, exceeds the utility from other fuels, Uothers i.e.,

Pr! (𝐿𝑃𝐺) = Pr)𝑈!,#$% > 𝑈!,&'()*+ , .

(1)

Based on the framework above, we specified a model that describes the probability of choosing
LPG as the main fuel in the household, as follows:

Pr! (𝐿𝑃𝐺) = 𝛽, + 𝛽- 𝑇! + 𝛽. 𝐷! + 𝛽/ 𝐴! + 𝛽0 𝑋! + 𝜀! ,(2)

where T is a treatment indicator and took 1 if the household was the beneficiary of the RLPGPP.
We expected the beneficiaries to have higher LPG usage because the intervention reduced the
upfront costs and eased the burden of transitioning to LPG. D represents the round-trip distance tothe nearest refill station. When the LPG in a cylinder is used up, households in Ghana must go to
the station to refill them. Therefore, a longer distance to the station would reduce the probabilityof LPG usage. A indicates the occupation of the household head, whether an agricultural worker
or not. We assume that it is easier for agricultural workers to obtain wood and biomass residuals
as cooking fuel sources. They could also collect firewood on their usual commute to the farms andmay have a lower time cost for firewood collection than non-agricultural workers. X is a vector ofother factors that might affect household choices, such as income, education, and location. We
used a probit model to estimate equation (2) and reported the marginal effects evaluated at the10means. We further conducted heterogeneous analyses for different subgroups of the sample toexplore which groups responded to the treatment. There was no strong correlation between any ofthe explanatory variables.
As a robustness check, we used two outcome indicators as alternative dependent variables: (1)
LPG used more in the past seven days preceding the survey or otherwise, and (2) the LPG usagerate. Since households typically have multiple fuel types, the survey asked which fuel they used
the most over the seven days preceding the survey. We limited the period to seven days for easeof recall. The LPG usage frequency rate also indicated whether LPG was often used in households.
Both variables were used to confirm and check whether the regression results were robust to the
choice of outcome indicator.
The above approach assumes that the Ministry of Energy randomly chose the beneficiaries of the
RLPGPP. In the actual implementation of the program, there were no criteria for household
selection in beneficiary districts. The field data showed that some beneficiaries owned LPG
equipment before the program implementation and still benefitted from this program 7 . Thisaffirmed the randomness in the beneficiary selection since all households stood the chance ofbenefiting from the program regardless of whether they owned LPG or not. Furthermore, giventhat households had nothing to lose if they opted out of the program, a randomly selected
beneficiary household’s chances to self-select themselves out of the program were meager. On thisbasis, the treatment was deemed exogenously determined; hence, the chosen approach isappropriate for estimating treatment effects. This notwithstanding, we considered potential biases
in selecting households in some areas beyond the supervising authority’s control. As an additional
analysis, we used matching techniques to mitigate against potential bias from the possibility thatsome beneficiary households may not have been selected randomly. Based on the baseline
covariates that were likely to affect the treatment selection, beneficiary households were matchedwith non-beneficiary households. Because treated and control households were matched oncommon characteristics, any differences in the outcome variables between treated and control
households could be attributed to the treatment.

7

Among the sample of treated households, 27.6% owned LPG before benefiting from the RLPGPP. We conducted a
sub-sample analysis that excludes this group of treated households. The results are discussed in Section 5.

11

We used Mahalanobis distance matching (MDM) and propensity score matching (PSM)
estimators. For every treated observation, the MDM calculates the distance between its covariates
and those of control households and matches treated households with the control households withthe shortest distance in covariates. Meanwhile, PSM allows us to estimate the probability of ahousehold being treated (the so-called propensity score) based on its characteristics (Rosenbaumand Rubin, 1983). Each treated household is then matched with a control household that had
similar propensity scores. In both cases, the matching was done on the following covariates:
occupation, distance to the nearest refill station, access to financial services, access to information,
education, location, and income.8

5. Results and Discussion
5.1 Treatment effect and determinants of LPG usage

Table 2: Main results: dependent variable = LPG is the main fuel (LPG = 1; otherwise, 0)
VARIABLES(1)
Probit(2)
Probit(3)
Probit

(4)
MDM

(5)
PSM

Treatment

0.262***(0.032)

0.218***(0.034)-0.0037***(0.00065)

0.235***(0.036)-0.0025***(0.0007)0.223***(0.040)0.203***(0.044)

No
Yes
836

Yes
Yes
836

814

814

Distance to refill
Other control variables No
District effects
Yes
Observations
904

Note: Coefficients are marginal effects evaluated at the mean. Standard errors are shown in parentheses. *** p<0.01,** p<0.05, * p<0.1.

Columns (1-3) of Table 2 show the probit estimation results on the factors that influenced the
choice of LPG as the primary cooking fuel for the household. Columns (4-5) present the resultsfrom the matching estimators. The results shown in Table 2 indicate a positive and statistically

8

Tables in Appendix B summarize the balancing properties of covariates for both matching estimators.

12

significant effect of the program. Treated households were more likely to choose LPG as theirprimary fuel by 23.5% compared to non-treated households (column 3). This finding suggests thatthe program contributed to increased LPG usage among the households that benefited from theprogram. The results from the MDM and PSM, shown in columns (4) and (5), confirm the positive
impact of the program on LPG use, and the magnitude of the effect is consistent. Treatedhouseholds increased LPG use as their main fuel by 20% to 22% compared to non-treatedhouseholds. The coefficients’ sizes were comparable to the estimates from the main results, as
shown in (2) and (3).
The result is consistent with those of other studies on clean cooking interventions. The size of thetreatment effect found in our study was smaller than that found in the Peruvian study by Calzada
and Sanz (2018). This difference might be a result of the different features of the interventions.
Beneficiaries in Peru receive a monthly voucher for LPG. However, this continuous LPG subsidy
is not present in the RLPGPP in Ghana, and could lower the treatment effect. Our findings wereinconsistent with those of Adjei-Mantey and Takeuchi (2019), who found no significant increasein LPG use. This result can be attributed to the differences in the study’s focus. Adjei-Mantey and
Takeuchi (2019) examined the district-level impact using data from official statistical surveys andfound that the program did not yield significant spillover effects. In contrast, the current study
examined the impact at the household level, which is the actual unit for treatment. The closer focusof the analysis in this study could account for the difference in results from the previous study.
The coefficient for the distance to the nearest LPG refill station was negative and statisticallysignificant, suggesting that LPG usage decreases with distance. We found that for every minuteincrease in the travel time to access a refill station, the probability of choosing LPG as the main
fuel reduced by 0.25%. A longer distance to a refill station represents higher monetary and time
costs and reduces the choice of LPG as the primary cooking fuel. The result highlights theimportance of providing an LPG distribution service that refills cylinders more conveniently withless time and travel costs. Dendup and Arimura (2019) noted that distance to the nearest market
negatively affected the choice of LPG, while Dalaba et al. (2018) found no significant association
between distance to a refill station and LPG ownership in northern Ghana.
To check the robustness of our choice of outcome indicator, we replaced LPG as the primary fuelwith other dependent variables and compared the effect of treatment. Table 3 summarizes the13results of the regressions with the alternative dependent variables. The marginal effects on the
recent LPG usage (LPG in the past 7 days) and the LPG usage rate (ratio of LPG use to the total
number of times of cooking in a day) are reported in columns (2) and (3), along with the main
result (1), which is already indicated in column (3) of Table 2. Model (2) was estimated using
probit and (3) by fractional probit regression.
The estimated coefficients for treatment in Table 3 are positive and statistically significant,suggesting a positive impact of the program on LPG choice. The chances of using LPG more thanother fuels and usage rate of LPG were higher for treated households than for others by about 20%
and 33%, respectively. These results are consistent with the main results from Table 2, whichsuggest a positive impact of the program on LPG use as the primary fuel. The significant effect ofthe distance to the nearest LPG refill station was also confirmed. An additional minute to a refill
station reduces the probability of using LPG more than other fuels and LPG usage frequency by
0.3% and 0.4%, respectively.

Table 3: Other dependent variables

VARIABLES
Treatment
Distance to refill
Agricultural worker
IncomeEducation
Risk averse
Rural
District effects
Observations(1)
LPG is main fuelProbit(2)
LPG in past 7 days
Probit(3)
LPG usage rate
Fractional Probit

0.235***(0.036)-0.0025***(0.0007)-0.085*(0.044)0.0039***(0.0012)0.030***(0.0044)-0.066(0.046)-0.28***(0.051)0.195***(0.036)-0.0027***(0.0007)
0.017(0.044)0.0038***(0.0011)0.029***(0.0043)-0.122***(0.045)-0.279***(0.052)0.333***(0.029)-0.0043***(0.00082)-0.023(0.039)0.0039***(0.0012)0.020***(0.0035)-0.092**(0.037)-0.29***(0.042)

Yes
836

Yes
836

Yes
798

Note: Coefficients are marginal effects evaluated at the mean. Standard errors are shown in parentheses. *** p<0.01,** p<0.05, * p<0.1.

14

The estimated coefficients for the other control variables are also in line with expectations.
Agricultural workers chose LPG as their primary cooking fuel at an 8.5% lower likelihood than
non-agricultural workers in model (1). This result is consistent with the findings of Saksena et al.
(2018). Farmers typically have easier access to wood and agricultural waste as a primary fuel,discouraging them from choosing LPG as their main fuel. Furthermore, it is a regular practice forfarmers in Ghana to collect firewood on their usual commute to their farms. Hence, the time costassociated with gathering firewood might be lower for them. Jagger and Jumbe (2016) found thathouseholds that used crop residue as cooking fuel were more likely to adopt improved cookstoves(ICS). In that respect, their results differed from our findings. However, they examined theadoption of ICS while we examine the adoption of LPG. Transition to ICSs reduces the demandfor biomass fuels but still requires it. Furthermore, the adoption of LPG implies that farmers cannot
use such fuels. In line with previous studies (Choumert-Nkolo et al., 2019; Karimu et al., 2016;
Muller and Yan, 2018), we found statistically significant and expected signs for other covariates,
such as income, education, and rural location.
Table 4 presents results that exclude households that owned LPG before benefitting from the
RLPGPP. The results can be regarded as a lower bound estimate because it measures the program’s
impact on treated households who became first-time owners of LPG equipment under the program
without considering the program’s impact on other beneficiary households. A positive andstatistically significant impact of the program is observed among the sub-sample. Compared to themain results, the estimated treatment effects on LPG usage were lower. This is because households
who own multiple LPG equipment will use LPG even more than households with single LPG
equipment. While one cylinder is in use, another cylinder could be filled with LPG and be readyto substitute should the active cylinder run out of gas. Households with only one cylinder do nothave this advantage. Therefore, if they run out of gas during cooking or when it is inconvenient tocommute to refill their cylinders, they are likely to use firewood or charcoal as temporal substitutes.

15

Table 4: Exclusion of households that owned LPG before treatment

VARIABLES
Treatment
Distance to refill
Agricultural
worker
IncomeEducation
Risk averse
Rural

(1)
LPG is main fuelProbit(2)
LPG in past 7 days
Probit(3)
LPG usage rate
Fractional probit

0.162***(0.039)-0.0021***(0.00071)-0.0630.118***(0.039)-0.0021***(0.00069)
0.021

0.314***(0.032)-0.0041***(0.00086)-0.0088(0.045)0.0035***(0.0012)0.029***(0.0050)-0.053(0.049)-0.29***(0.057)(0.045)0.0030**(0.0012)0.028***(0.0044)-0.097**(0.049)-0.28***(0.057)(0.042)0.0046***(0.0014)0.022***(0.0038)-0.12***(0.041)-0.30***(0.048)

Yes
723

Yes
724

Yes
692

District effects
Observations

Note: Coefficients are marginal effects evaluated at the mean. Standard errors are shown in parentheses. *** p<0.01,** p<0.05, * p<0.1.

5.2 Heterogeneous effects
This section investigates the heterogeneity in treatment effects, with the main purpose of deriving
policy implications for similar interventions in developing countries. Based on the earlier findings,
we considered three sub-groups: households that live closer or far from refill stations, agriculturalor non-agricultural workers, and lower or higher income groups. We divided the distance bywhether the round-trip travel exceeded 30 minutes. Income groups were divided by medianhousehold income in the sample.

16

Table 5: Heterogeneous effects; probability of choosing LPG as household’s main cooking fuel
(1)
(2)
(3)
(4)
(5)
(6)
VARIABLES
Shorter
LongerAgricultural Non-agric.
Lower
Higherdistance
distance
workerworkerincomeincomeTreatment

0.21***(0.055)0.25***(0.047)0.073(0.066)-0.0017*(0.00098)

0.316***(0.042)-0.0022**(0.00095)-0.12*(0.067)0.0070***(0.0024)0.034***(0.0069)-0.063(0.074)-0.27***(0.066)-0.055(0.055)0.0023*(0.0013)0.024***(0.0056)-0.088(0.057)-0.31***(0.087)0.0017(0.0019)0.018**(0.0083)-0.175*(0.099)0.011(0.152)

Yes
384

Yes
452

Yes
227

Distance to refill
Agricultural worker
IncomeEducation
Risk averse
Rural
District effects
Observations

0.308***(0.047)-0.0024***(0.00093)-0.089*(0.054)0.154***(0.050)-0.0016(0.00096)-0.077(0.064)0.0050***(0.0016)
0.036***(0.0053)-0.016(0.053)-0.29***(0.058)0.026***(0.0060)-0.018(0.065)-0.16*(0.091)0.029***(0.0059)-0.077(0.058)-0.29***(0.065)

Yes
609

Yes
404

Yes
432

Note: Standard errors are shown in parentheses. *** p<0.01, ** p<0.05, * p<0.1

Table 5 summarizes the results. Models (1) and (2) show that the treatment had a slightly higher
effect on households who lived farther from refill stations. The result suggests that theintervention’s impact was more substantial for families living longer distances from a refill station.
The importance of distance to access a refill station is crucial in households’ decisions to use LPG
and confirms the findings in earlier sections. In models (3) and (4), the treatment effect is not
significant among agricultural workers but is significant among non-agricultural workers. Among
non-agricultural workers, treated households were 32% more likely to use LPG as their main fuelthan non-treated households. For agricultural workers, treated households were not likely to use
LPG significantly more than non-treated households. For this subgroup, the treatment did not
matter in terms of usage. As previously mentioned, the abundant supply of wood fuel andagricultural waste for agricultural workers provides a strong disincentive to use LPG. Saksena etal. (2018) also found that Vietnam’s agricultural households had a positive and significant use ofwood fuel. In models (5) and (6), the treatment effect was twice as potent in the lower-income
group than in the higher-income group. These results agreed with those of Calzada and Sanz (2018)17

and Troncoso and da Silva (2017), who found similar conclusions in their study of cooking fuelinterventions. This result suggests that a minimum level of income may be sufficient to induce
LPG usage.

6. Willingness to pay for LPG delivery
This section explores the WTP for LPG delivery to assess households’ preferences for an LPG
distribution system. The current LPG distribution system in Ghana requires households to go torefill stations with their LPG cylinders when they run out. Refill stations may not necessarily belocated close to a household’s location, and the travel costs to a refill station increase households’
difficulties in adopting LPG. We provided a hypothetical scenario in which LPG was delivered tothe household upon a phone call in exchange for their empty cylinder. This system means thathouseholds do not have to worry about time costs or the inconvenience of carrying their cylinder
to a refill station. They can also arrange for the cylinder to be delivered at a time convenient tothem and hence do not have to alter their daily schedules. The exact text for the explanation in thesurvey questionnaire is as follows:

Let’s assume for a moment that there is a service which is akin to refilling your LPG
cylinder at your home. This service brings you a cylinder which is similar to your cylinder
in every way, filled with gas in exchange for your empty cylinder so that you do not haveto make any trips to a refill station to refill your cylinder whenever your gas runs out. The
service is prompt, reliable, and your gas will be delivered once a phone call is madewithout any hassle. The cost of the gas itself remains the same as what pertains at therefill stations. In addition, however, you may need to pay an extra amount as a fee fordelivery of this service.

Following this explanation, we asked the maximum amount per delivery (aside from the gas price)
the respondent was willing to pay as a choice from the list of fee options. The listed fees varied
from 0 to more than ȼ20 and increased by ȼ2. This method was adopted to avoid biases associated18

with using a starting bid and a subsequent iterative bidding process to elicit WTP values whileallowing for economically reasonable fees for the service based on the price of LPG and costs ofcommuting to refill stations. Box plots are used to analyze the data, and they show the distribution

10
0

5

WTP (cedis)

15

20

across different subgroups.

Not treated Treated

Not treated Treated

Not treated Treated

Up to 30 mins

31-60 mins

More than 60 mins

Figure 1: Distribution of willingness to pay

Figure 1 shows the distribution of WTP across treatment groups and the distance to refill stations.
There appeared to be no significant differences in WTP between the treatment and control groups.
The mean WTP for treated and control groups were ȼ7.01 and ȼ6.94, respectively, while the total
mean was ȼ6.97 ($1.20). This amount is about 22% of the average cost of refilling a 6 kg LPG
cylinder at the time of the survey (ȼ31.14), which was the size of cylinders distributed under the
RLPGPP. The distribution showed that households that live farthest from refill stations (more than
60 minutes round trip) had higher WTP than households that live closest to refill stations. The
results aligned with expectations because households that live closer to refill stations are likely toincur lower money and time costs to travel to refill stations than households that lived farther.

19

In addition, we examined the factors that are likely to influence households’ WTP by specifying
the following model:

WTP = 𝛼, + 𝛼- 𝑇! + 𝛼. 𝐷! + 𝛼/ 𝐴! + 𝛼0 𝑋! + 𝜀!

(3)where 𝛼i are coefficients to be estimated, and T, D, A, and X are as previously explained in (2).
Ordinary least squares (OLS) was used to estimate equation 3.

Table 6: Determinants of willingness to pay (WTP) for new LPG distribution system
Dependent variable: WTP amount (in Ghana cedis)
VARIABLES
Treatment
Distance to refill
Agricultural worker
IncomeEducation
Risk averse
Rural
Constant
District effectObservations
R-squared(1)
Full sample(2)
Treated(3)
Not treated

0.101(0.24)
0.040***(0.0044)0.046(0.29)
0.0039(0.0070)0.079***(0.027)0.283(0.29)-0.32(0.35)
5.223***(0.52)

0.047***(0.0058)
0.14(0.40)
0.0036(0.0082)
0.13***(0.039)0.20(0.40)-0.56(0.49)
5.02***(0.71)

0.030***(0.0067)-0.15(0.42)
0.0038(0.013)0.029(0.038)0.36(0.43)-0.0081(0.51)
5.57***(0.76)

Yes
837
0.132

Yes
408
0.214

Yes
429
0.066

Note: Standard errors are shown in parentheses. *** p<0.01, ** p<0.05, * p<0.1

Table 6 presents the results from OLS estimation on the drivers of WTP. Regression results from
Table 6 confirmed that the treatment had no significant effect on households’ WTP for the20

proposed distribution system. However, distance to the refill station was positive and significantly
associated with WTP. An increase in the travel time by 10 minutes increases WTP by ȼ0.4 ($0.07)
to access this service. Sub-sample analysis in columns (2) and (3) suggests that the effect of
distance is stronger for treated households than for untreated households. Thus, the WTP of treatedhouseholds was more sensitive than non-treated households. The results confirm the opportunity
to implement the cylinder circulation model of LPG distribution, especially for communities
located far from refill stations. Larsen et al. (2020) estimated that such a system has cost reduction
potential of about 28% for rural households in Ghana and could increase rural LPG consumption
by about 37%. Education was also found to increase WTP, similar to the findings of Chindarkar
et al. (2021) and Zahno et al. (2020) that exposure to health awareness increases WTP for LPG in
India.

7. Conclusions and Policy Implications
This study investigated the impact of the LPG promotion program in two districts of Ghana. We
found that the program successfully increased the likelihood of choosing LPG as the household’s
primary cooking fuel, and the results were robust across different specifications. The distance torefill stations played a significant role in the decision to use LPG. Households that lived far fromrefill stations were less disposed to use LPG because of the obvious inconvenience and costs ofcommuting to refill stations. These households also had a positive and significant association with
WTP for the proposed LPG delivery. This distribution model is similar to the LPG cylinder
recirculation model proposed by the government of Ghana.
Based on our findings, we conclude that the distance to refill is crucial for successful clean
cooking interventions. The construction of refill stations and providing stable services will increase
the effectiveness of programs to promote LPG. In areas without refill stations nearby, the cylinder
recirculation model that delivers an LPG cylinder to individual households will further assist the
program’s impact. The distribution system will make it easier and more convenient to use LPG,
particularly for households far from refill stations. Furthermore, our findings indicate lower
effectiveness of the program for particular subgroups of the population, such as agricultural
workers. It may require a different form of support to encourage LPG usage among this sub-groupof the population.
21

Acknowledgments
This research was supported by the Grant for Environmental Research Projects from the Sumitomo
Foundation (Grant Number 193278) and Kobe University Center for Social Systems Innovation.

22

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26Appendix A: Sampled EAs
Ada West

Ga SouthAfiadenyigba

Paanor

Kofi Kwei

Goi

Kokrobitey

Tuba

Wokumagbe

Weija

New Weija

Koluedor

Danchira

GbemomoSege/Koni

Obom

Honi Ofadjator

Anyaman

HorborJei Krodua

Addokope

Bortianor

27

Appendix B: Covariate balance summary
The tables below show the differences between the treated and control households before andafter matching for both estimators. After matching, the differences were significantly reduced for
all covariates in both the MDM and PSM. For example, a difference before matching of 0.19
between treated and control concerning access to information reduces to an absolute difference of
0.008 after matching. These results show that matching makes the treated and control households
more similar than the absence of matching.
Table B1: Balance before and after the matching(A) Mahalanobis distance matching (MDM).

VARIABLES
Access to
information
Access to financial
services
Distance to refill
stationAgricultural worker
Education
IncomeRural

Standardized differences
Unmatched
MatchedVariance ratio
Unmatched Matched

0.19-0.0079

0.68

1.02

0.21

-0.016

0.86

1.02

-0.16

0

1.01

1.04

0.10
0.089
0.14
-0.0076

0.016
0.023
0.060
0

1.11
0.85
2.39
1.01

1.02
1.05
1.19
1

(B) Propensity score matching (PSM)

VARIABLES
Access to
information
Access to financial
services
Distance to refill
stationAgricultural worker
Education
IncomeRural

Standardized differences
Unmatched
MatchedVariance ratio
Unmatched Matched

0.19

0.0079

0.68

0.98

0.21

-0.055

0.86

1.060

-0.16

0.036

1.01

1.12

0.10
0.089
0.14
-0.0076

0.082
0.024
0.077
-0.040

1.11
0.85
2.39
1.01

1.09
0.89
1.64
1.05
28