The Lao People’s Democratic Republic (Lao PDR) is a sparsely populated nation in Southeast Asia where agricultural production usually occurs on farms that are less than two hectares, and where populations have tended to be spread out in a way that gives farmers limited access to processing industries and markets [1
]. Smallholder farmers have traditionally been subsistence farmers; dependent on cultivatable land for rice and livestock production with an array of non-timber forest and river products used as supplementary food sources and marketable goods [3
]. More recently, Lao PDR is experiencing agrarian transitional changes that are also occurring elsewhere in Southeast Asia. These transitions are intricate and may cause social change and have considerable impacts on resource management practices as well as a fundamental change of landscapes [6
]. Agrarian transition has been described by [7
] p. 286: “as the transformation of societies from primarily non-urban populations dependent upon agricultural production and organized through rural social structures, to predominantly urbanized, industrialized and market-based societies”. The changes that are happening in Lao PDR include intensified production, the territorial expansion of large actors, market integration, including urbanization of the population, rapid industrialization, increased movement of the population as well as a series of regulatory and environmental dilemmas [7
]. Lao farmers are also contributing to a bigger picture of regional agrarian transition [12
]. In this context, to improve rural livelihoods, the Lao government is trying to shift farmers to commercial agricultural production through interconnected strategies that aim to (a) guarantee food security, (b) deliver comparative and competitive agricultural commodities, (c) expand clean, safe and sustainable agriculture, and (d) deliver a modernized, resilient and productive agricultural economy that contributes substantially to the national economy [13
]. International aid organizations are also helping with the agrarian transition that is aimed for by the Government of Laos [14
What this means for smallholder farmer households in Lao PDR is that many are shifting from traditional low-yield, subsistence-oriented activities towards diversified livelihood strategies by attempting to maximize the income-generating potential of available labour within the family [19
]. As part of this trend, more non-traditional off-farm and non-farming activities have become integral to the way that households generate income.
It is becoming clear that there is an important gender perspective associated with this evolving socio-cultural system, with the changing roles of men and women, described as the “feminization of agriculture” [22
]. In this rapidly changing context, there is a need to understand the trends in gender roles, social norms, as well as the roles of members and heads of households and whole communities as they are increasingly afforded international aid to encourage and support the intensification of agricultural production [24
]. It is argued that, as part of the introduction of new technologies by aid agencies, the gendered roles and social norms, acceptable behaviour and agency that are prescribed according to ethnicity, must also be taken into account [25
With this in mind, we use data from a previous research project to explore differences in what men and women aim to achieve in the agrarian transition, any gendered differences in livelihood strategies, and if there are any gender-based differences in the capacity to engage with modern technologies or farming markets. Specifically, this paper explores, in the context of agrarian transition amongst smallholder farmers in southern Lao PDR:
What are the differences, if any, between how men and women choose to adopt new technology?
What are the differences between men and women, if any, in strategies and attitudes to farming and related activities?
What are the differences between men and women, if any, in the ability to generate income and engage with farming markets?
Exploring these questions using our data contributes to an improved understanding of gender dynamics—strategic thinking, farming attitudes and decision-making—in agrarian transitions. The findings also carry implications for better targeting of gender-sensitive agricultural research. Furthermore, if there is a gender difference in priorities and decision making at this time of transition, then the gender perspective may provide useful information about the multiple directions of agrarian change in Lao PDR.
To explore these questions, we draw primarily on the analysis of quantitative data from 293 female and 452 male farmers surveyed in 2016 in 18 villages in Southern Lao [26
]. We further use the qualitative and other research data, i.e., from interviews and focus groups, key informant insights, and field observations, to provide plausible explanations and to, as best as available primary and secondary data permit, validate our interpretations of what is causing the quantitative results.
2. Gendered Economic Transition in Lao PDR
Rapid and uneven economic growth occurring in Southeast Asian countries over the last few decades has resulted in new and challenging inequities between social groups and for men and women [28
]. In Lao PDR, the New Economic Mechanism introduced in 1986 has seen the government move from a planned economy towards an open-market economy [32
Phouxay and Tollefsen [31
] have argued that the different results for men and women during the agricultural transition can be observed in migration patterns and changes in urban labour markets, where young female migrants in many cases end up in precarious work and/or doing hard manual labour in Southeast Asian cities. There are many examples of young men and women migrating for wages and remittances [31
]. The number of women working in Vientiane, the capital of Lao PDR, has increased, particularly young rural women employed in textile factories, which has influenced women’s roles and status as industrial workers both inside and outside the workplace [31
]. The Mekong Commons [37
] indicate that many Lao people are illegally employed as undocumented workers in Thailand, gaining benefits by contributing remittances but also being exposed to risks.
Women are an important part of the agriculture sector in Lao PDR, contributing to every part of agricultural production [25
]. However, men and women typically have different roles and responsibilities in the household [38
]. Gendered roles in rural areas in Lao PDR are similar to other countries in Southeast Asia [28
] and can be conceptualized as ‘loose patriarchies’ where women’s rights, mobility and labour participation are higher than in other places [40
]. The head of the household, however, is typically a man who is also the key agricultural production decision-maker [42
]. Women tend to have less power in negotiations than men and more limited decision-making opportunities [43
]. Interestingly, women can take responsibility for saving income, while decisions to spend income is usually made by the man in the household [44
]. However, [44
] has noted that gender status can change with commercial agricultural opportunities. Furthermore, changes to gender status can drive further changes and improvements to socio-economic situations [44
It is important to consider the multiple roles of women as mothers, wives, farmers, entrepreneurs and agents as they play a significant role in main crop production, livestock production, horticulture, post-harvesting operations, agro-social forestry and fishing [45
]. Women’s duties are often directed towards household caretaking with significant domestic and reproductive responsibilities [43
]. In Lao PDR, it is well-known that there are differences between households headed by women rather than men. However, it is not very well known what the roles and contributions of rural women are within male-headed households, nor the decision-making and levels of informal and formal control that occur in the households [47
This article primarily draws on quantitative data collected using farmer surveys [26
] whilst also drawing on qualitative data from focus group discussions and interviews designed to validate interpretations of the statistical analysis. For greater explanatory power, we have also drawn from the literature review, Bayesian network findings and outcomes of serious games that explored gender differences in a hypothetical situation of rice production in a game setting.
A farmer survey was carried out as part of a study commissioned by the Australian Centre for International Agricultural Research (ACIAR) (ASEM/2014/052 “Smallholder farmer decision-making and technology adoption in southern Lao PDR: opportunities and constraints”), designed to understand conditions that influence farming households’ decisions to adopt or not adopt innovative farming practices [48
]. The study included a literature review [50
], focus group discussions, interviews, farmer surveys [26
], as well as the application of Q methodology [48
], serious gaming [52
] and Bayesian network (BN) analysis [20
]. The research team used a mixed-methods approach for synthesizing qualitative and quantitative data. Publicly available reports and papers are on an online repository (https://sites.google.com/view/acrtechnologyadoption/project-reports
3.1. Survey Data
A review of the literature was undertaken to explore the factors that influence the adoption of technologies, drawing on adoption literature and literature from the fields of organizational change, supply chains and project management. Based on the review, an exploratory survey instrument was developed and, following a piloting process, finalized to 39 questions. The survey questions can be found in the relevant project report [27
] and explored demographic and socio-economic factors, technology understanding and attractiveness, as well as perceived technology benefits, support, risk and uncertainty, etc [26
]. The survey included a series of questions with dichotomous or a multiple item scales (1–7 Likert scale).
The survey-generated data explored farmers’ perceptions of factors that are relevant for their agricultural decisions. Understanding such factors will influence the success of agricultural research because it can be used to unlock opportunities for farmers. Details of the survey design and analysis can be found in the relevant project report [27
]. The questionnaire explored demographics, technology attributes and attractiveness, as well as benefits, levels of support, risk, uncertainty and costs associated with a change of production systems [20
3.2. Choice of Participants and Survey Administration
Households drawn from 18 villages in Savannakhet and Champasak Provinces in Southern Lao PDR were chosen for the survey using a purposive sampling frame. The villages selected were predominantly characterized by their use of lowland rice-growing agricultural systems with a history of involvement and/or were currently involved in development projects. Villages were at different levels of elevation, soil profiles, access to water supplies and presence or absence of irrigation. The selection procedure also considered additional factors such as the level of access to markets, credit or finance and areas where the production of two crops per year was possible.
The survey was delivered using electronic voting technology. To reduce the risk of misunderstanding, the survey was extensively tested, with iterations of translations of questions from English to the Lao language. There was considerable effort to ensure that clear and non-ambiguous terminology and phrasing were used. Farmers were asked about activities that their household had been involved in, making it difficult to discern the experiences of individual technology types. Instead, the survey aimed to elicit a systems-view of their experiences. A total of 745 farmers participated in an electronic voting exercise; 427 from nine villages in the Province of Savannakhet and 318 from nine villages in the Province of Champasak [27
]. The data collection methods were approved by the Human Ethics Research Committee at James Cook University (H6109).
Interview data indicated that the surveyed villages had a variety of ethnic and language groups [48
] including Lao Loum, Phouthai, Makong, Lao Theung Kmuk, Lao Kang, Suay and Thoy ethnic participants. Lao was the predominantly spoken language, with Lao Theung, Phouthai, and Makong languages also spoken. Villages ranged in size from 121 to 302 households per village, and with an average household size of 6 people. The main income source was from rice production and livestock husbandry, with income also from crops, vegetables and fruit. It was also found that households reported off-farm income from remittances, wages and other activities. Fewer women than men reported that they generated income, although women did make small contributions through livestock raising, wages, remittances and other activities. Families generally worked together to generate income. Reported sources of off-farm income included: house building, handicrafts, weaving, collecting non-timber forest products (such as frogs or cardamom), selling fish, snails, chicken or ducks, wages from offspring working outside of Laos, and wage labour jobs, such as unexploded ordnance removal, electrical technician, construction jobs, minimart shop or outsourcing of mechanized farm equipment, such as tractors. In each village, off-farm work occurred primarily in Thailand, with an estimated 20–120 households per village having members working in Thailand. Up to 60 households had members working in Vientiane. The total percentage of households in the sample with members engaging in off-farm employment ranged from 30% to 80%.
3.3. Analysis of Survey Data
We interrogated survey data from the electronic voting exercise in the 18 villages to (1) explore important gender-related summary statistics generated from the survey; and (2) undertake statistical analysis, including chi-square tests, to understand any systematic differences in participant responses between men and women, and differences due to age, education and household role. Based on the statistical analysis, we discuss the relevance of these results in terms of how the current agrarian transition is influencing gender relations and, in turn, how gender relations may be influencing the agrarian transition. Relevant qualitative information from focus groups, interviews and field observations enabled a greater explanatory capability when combined with the statistical analysis.
We also note that some questions refer to the participant as an individual and some questions refer to the individual’s household, but in the majority of cases, the respondent was the head of the household, and in 81% of the cases the respondent was either the head of the household or the wife of the head of the household.
In all, 745 participants from 18 villages in 2 provinces, with 39% (293) women and 61% (452) men, attended the electronic voting exercise. Depending on how each question was asked, the participants sometimes responded on behalf of the household, and sometimes on behalf of themselves as individuals. A total of 81% of the respondents were either the head of the household or the wife of the head of the household. The gender balance of participants differed markedly across the 18 villages, with one village having had as few as 6% women participating, whilst at the other extreme, one village had as many as 69% women participating. Local government officers recruited villagers to meet in the common facility in each village and as participation was voluntary, we cannot account for the dynamics that resulted in variations in gender participation.
4.1. Gender-Related Differences in Age and Educational Level
To provide some baseline information about who the respondents were, we explored age and education, and any gendered differences in these attributes. The age and education profiles of female and male participants were significantly different, as shown in Figure 1
and Figure 2
. Female participants were predominantly in the 31–40 age group, while male distribution by age was more evenly distributed between age categories. Nearly half of the female participants were illiterate, compared with 31% illiteracy for men. Overall, men were much more highly educated than women. A multinomial logistic regression model found that age and gender both had a statistically significant effect on education level, with gender having a stronger effect (in the analysis of variance table, gender had a p
-value of 8.545 × 10−11
whilst age had a p
-value of 4.881 × 10−7
4.2. Gender-Related Differences in the Embrace of New Practices
An important aspect of the agrarian transition involves the adoption of new agricultural practices. These changes in practices are variously supported by agricultural researchers, but more often by Lao government extension officers who provide training and advice to farmers. New practices also gather momentum and often become adopted by farmers independently through a process of innovation diffusion.
Through our survey, farmers in the villages were asked specifically about the extent to which they, as individuals, had been participants in activities that involved evaluating new practices (here referred to as projects), and also the number of new practices (here referred to as technologies) that they had adopted; and whether they still used those practices; and whether they found the practice change to be useful.
As shown in Table 1
, there were no statistically significant differences in how many new practices women and men adopted (NumberOfTechs), or in their involvement in trialling new agricultural practices (ProjectInvolvement). There were however other differences:
Men tended to adopt more new practices, but this difference was not statistically significant.
Women tended to participate more often in trials of new practices, but this difference was not statistically significant.
Women who adopted new practices more often reported that the adopted practices were useful, and this difference was statistically significant.
Women who adopted new practices tended to adopt more practices than men, and this difference was statistically significant.
A total of 17% of women who adopted new practices compared with 11% of male adopters reported to have entirely abandoned all their new practices, and this difference was statistically significant.
As women tended to abandon new practices more frequently than men, we explore the reasons given for not continuing. Results in Figure 3
are in response to the question “Why did you stop using the technologies?” The multiple-choice options to answer were: (1) I did not stop. I am still using them (Still using); (2) I didn’t try any of them (Didn’t try); (3) They were not worth the effort (Not worth the effort); (4) The benefit was too small (Benefit too small); (5) I can use the time better by getting an off-farm job (Time better spent). The p
-value for the chi-square test exploring whether women and men tended to respond differently to the question, “Why did you stop using the technologies?” was 0.07, which is statistically significant only at the 0.1 level, i.e., indicating a relatively weak association. As illustrated below, women more often tended to note that the benefits were too small to warrant continuous use.
4.3. Gender-Related Differences in Strategy and Attitudes towards Rice Selling
When asked about which best describes the participants’ strategy as a head of household, participants were presented with the following multiple-choice options based on our analytical nomenclature as well as survey descriptions:
Feed family: As head of the household I need to feed my family. I try to make some extra money from selling surplus produce. My farm is my priority.
Maximize farm income: As head of the household, I need to feed my family and make some extra money. I plan to have surplus rice for sale every year and I sell animals when I need extra money. Sometimes I get an off-farm job to make a bit more money.
Maximize off-farm income: As head of the household, it is my job to maximize labour time for off-farm jobs because this maximizes our income. It is not worth our effort to increase rice production much more than what we need to feed my family. Rice, animals, and cash crops are important, but off-farm jobs are the best way to maximize income.
Not head of household.
Whilst 172 (23% of all participants including 40% of female, and 12% of male participants) respondents answered “Not head of household”; amongst those who were able to respond to this question, there was a clear difference between female and male respondents. Male heads of households were much more likely to focus on feeding the family or maximizing farm income and were significantly less focused on maximizing off-farm income. In fact, whilst 65% of men had strategies that were primarily focused on farming (FeedFamily + MaximizeFarmIncome), 62% of women adopted strategies that were focused on maximizing off-farm income. Numbers are shown in Table 2
Furthermore, individual participants were asked about their openness to change in their farming practices in terms of on-farm agricultural production decisions including rice, cash crops, small and large livestock, non-forest products; as well as off-farm income. As shown in Table 2
, participants had the following multiple-choice options and responses (our analytical nomenclature as well as survey descriptions):
Modern farmer: I farm like most other farmers around here. There must be a very good reason for me to do something very different from what most other farmers do.
Pragmatist: I am interested in what other farmers do but if it suits me, I will do things differently to other farmers.
Traditionalist: I farm in the way that my parents and grandparents did. I do not want to change because farming in this way is part of who I am.
Small proportions of both men and women reported little openness to change (i.e., were traditionalists), but amongst the non-traditionalists the difference was more pronounced: women to a greater extent than men were pragmatists and men to a greater extent than women were modern farmers, indicating that on average women were more open to changing practices.
When asked about their attitude towards selling rice, as individuals, participants were given the following multiple-choice options and responded as per Table 2
, with multiple-choice options being:
“Feed family: I am a farmer. I grow rice mainly to feed my family and sell any surplus.
Sell surplus: I am a farmer. I grow rice to feed my family and sell the surplus. I am always looking for opportunities to improve my income.
Entrepreneur: I am a farmer and entrepreneur. I grow rice to feed my family and for income. I am interested in anything that might help me make more money from growing rice.”
Shows the statistical levels of significance between the variables: openness to change in farming practices, gender, level of education and age.
4.4. Gender-Related Differences in Household Income
We explore the question of whether there are differences between men and women, if any, in the ability to generate income and engage with farming markets. To explore this, we (1) explore whether there are any gender-related differences in household income, and (2) which key factors that influence household income. Our results indicate that for most of the survey participants, agriculture serves the primary purpose of generating an income. The question we posed was: are household incomes influenced by gender? We explored associations of self-reported household incomes, as described in comparative terms by members of poor, medium-income and wealthy households, as well as other variables. Based on chi-square tests (Figure 5
), we found that there was an association between education and household incomes but no similar association for age and household income. There was however an even stronger and statistically significant association between gender and household income (Figure 5
) indicating that the difference was not simply based on education. This was the case even if the lower education levels of women may be a factor in women reporting lower incomes. These are unexpected results considering that female participants reported the income on behalf of their household—not their income—during the survey.
Hence, we set out to further explore the association of gender, age, education and household income, employing chi-square tests to filter out the survey variables most strongly associated with household income. The following variables emerged with the strongest association (Table 3
Access to the market price for rice. “I can easily get the local market price for rice”. Stronger agreement with this statement was correlated with a higher household income. This factor was significantly associated with gender, with women being more likely to disagree with this statement.
Access to multiple buyers. “If I want to sell rice, I have several buyers available”. An agreement with this statement was generally associated with a higher household income and vice versa. The average access to multiple buyers was not statistically different for men and women; however, a statistically significant larger proportion of women reported strong disagreement with the statement that they “have access to multiple buyers”, indicating a small but important group that was particularly vulnerable.
Access to a fair price for seeds and other inputs. There was a statistically significant difference between women and men in response to question “I know I pay a fair price for seed, fertilizer and pesticide”, with women more likely to agree with this statement.
Priority for selling livestock. “How much do you prioritize selling livestock?” A higher stated priority of selling livestock was generally associated with a higher household income and vice versa. Women reported on average a lower priority for selling livestock.
Future-orientation. “When I think about improving my farm the most that I look ahead is x”. Participants responded to timeframes from “this season” to “more than three years”. Individual future orientation was strongly associated with household income. The level of future orientation revealed an interesting set of nuances. Most men and women considered productivity benefits season by season, and rarely did participants consider benefits a year or two into the future. However, on average women reported a higher level of longer-term future-orientation (>3 years); and the individuals with this long-term view reported the lowest average household incomes. As many as 15% of women looked more than 3 years into the future, compared to only 6% of the men. On the other hand, men reported a higher proportion of future-orientation in the middle range of one or two years—and the individuals with such a future-orientation reported the highest average household income.
The differences in average priorities and p
-value of chi-square tests against these variables are shown in Table 3
. Average scores were based on converting Likert scales to numbers distributed in an equidistant manner between 0 and 1.
The attitudes and openness to change concerning farming have also been found to be statistically associated with household income. Household incomes of low, medium and high were translated to numerical scores of 0, 0.5 and 1. This allowed the calculation of average household income scores for different groups of participants. For example, farmers reporting different attitude towards farming and different levels of openness had markedly different average household income scores. For the various attitudes to rice farming, the entrepreneurs had the lowest average household income score (0.31), followed by modern farmers (0.32) and those reporting focus on feeding family had the highest average income score (0.47). In terms of openness to change, traditionalists had the lowest average household income score (0.31), followed by modern farmers (0.32) but the pragmatists had the highest average score (0.37).
In an attempt to remove confounding variable effects, we then explored the combined influence of previously discussed factors on household incomes in a linear regression model. The summary results of the generalized linear model calculated in R (family = Gaussian, link = identity) are shown in Table 4
. The model was applied at the level of individual responses.
We found that gender is correlated with household income. However, the gender-related effect was also linked to several other factors, namely, future orientation; inequitable access to market relating to having access to multiple buyers and being able to sell rice at market price; differences in farming strategy (maximizing farm income) and an entrepreneurial attitude towards selling rice. A focus on farm-income was correlated with a lower household income.
In the context of agrarian transition amongst smallholder farmers in Southern Lao PDR, this paper explores differences in how women and men embrace new technologies, their preferred farming strategies and their capacity to engage with modern markets. The most important difference relates to livelihood strategies and we found that women tend to focus on off-farm income, whilst men tend to focus on rice-farming. Both men and women adopt new practices at a similar rate, but women tend to abandon technologies more often, and on average female adopters tend to adopt more practices. There are indications that women to a greater extent tend to evaluate the new practices in terms of their potential negative impact on labour productivity or off-farm income opportunities. The marked difference between male and female education and literacy could also very well be a factor in accounting for the different outlooks revealed by our study. Men tend to engage more strongly with rice markets and generally gain more reward from doing so, as they, on average, report higher incomes. The complex reasons for perceptions of lower household incomes by females include having less access to multiple buyers for their produce, having generally lower education levels, a different pattern of future-orientation, a greater openness to change, and focus on different livelihood strategies. However, even after all these factors are accounted for, there is a gender-based effect which shows that women may not have equal opportunity in the primarily male-dominated rice markets. We have shown that the introduction of new technologies influences livelihood strategies and possibly gender-related power relations. We argue that the current changes to agricultural systems and increased commercialisation strongly interact with gender dynamics in the household and, hence, international development agencies and local governments need to be cognizant of the gendered complexities when introducing change. We have presented an exploratory gender study, highlighting several knowledge gaps and complexities associated with the gender implications of agrarian transition.