India

Connecting the dots : Climate change, migration and social protection

Format
Analysis
Source
Posted
Originally published
Origin
View original

Attachments

Summary

Background

The agriculture-based seasonal nature of employment in rural areas in India means that communities may not have year-round livelihood options. People are forced to migrate from rural to urban areas in search of employment because they do not have enough savings to meet their consumption needs. ‘Migrarian’ (migration and agriculture) livelihoods now form a crucial part of India’s economy (Sharma et al., 2014), and migration has become a significant livelihood option across rural India (Singh, 2019). The Economic Survey of India (2016–17) estimated that at least nine million people migrated between 2011 and 2016 within the country, most of them in search of work. These internal migrants contribute 10% to the country’s GDP (UNESCO, 2019).

To reduce ‘distress migration’ from rural communities, the Government of India has a long history of running safety net and adaptive social protection programmes.
These aim to provide wage employment through public works programmes during agriculture’s lean periods or during climate extremes like droughts and floods.
The Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) that guarantees 100 days of employment to every rural household in a year is one such programme. It also has provision for 50 days’ additional wage employments in areas effected by climate hazards like floods, cyclones, droughts and so on under its MGNREGA scheme. The intention is to create climate resilience and help the vulnerable households cope and recover from these climatic events. However, actual results show that MGNREGA has been far from successful for several reasons, including operational and administrative issues.
Effective social protection programmes can provide people with a safety net against distress migration. This is especially important as distress migrants may be at a disadvantage in the urban labour market and can be exploited. But we also need to understand that, for many, migration serves as an opportunity, where they would have otherwise fallen deeper into poverty traps.
Migrants can earn higher wages in urban destinations, allowing them to accumulate cash and buy assets back home to secure longer-term livelihoods and exit from intergenerational poverty.

There are several aspects of climate-induced shortterm or circular migration, especially in combination with other socioeconomic factors, that are not fully understood. Without reliable data on the pattern of circular migration, policymakers will not recognise migrants’ needs, issues and vulnerabilities, and these may not be addressed through social protection programmes. It is also important to understand the vulnerability of those left behind. Policymakers need to know whether MGNREGA is supporting rural households and their migrant members to cope with both economic and climate crises.

Research approach and objective

To give policymakers better insights into these issues,
IIED has researched the underlying drivers of migration, patterns associated with it, issues and consequences of migration, and how to support migration so that it helps the community build their resilience. We examine whether migration should be allotted more centrality in MGNREGA guidelines — not to prevent it but rather to help communities use its opportunities.

The relationship between climate change stress and its impact on migration is complex to understand. It is very difficult to distinguish individuals for whom climatic factors are the sole motivation for migration because several economic and sociopolitical factors interplay with climate drivers to increase the vulnerability of a household. This study has used migration intention and a binary logistic regression model to understand the extent to which climate change and socioeconomic factors impact intention to migrate. In the study, migration intention has been used as a proxy to measure the likelihood of future out-migration from the study areas. To understand how the decision to migrate is affected by climate change and socioeconomic factors, 12 independent variables were selected, covering climate-related parameters and the household’s socioeconomic characteristics.
Climate variables covered slow as well as rapid onset events like drought, flood, heatwave and hailstorm. The severity of each event as scored by the household was used in the regression model as the main independent variable. Household size, household income, age, sex and level of education were covered under the socioeconomic variables.

Primary household surveys of 1046 households across three Indian states, Rajasthan, Uttar Pradesh and Madhya Pradesh, and 48 focused group discussions were carried out across sample villages. Out of surveyed households, 27.4% were Scheduled Caste (SC), 36.4% were Scheduled Tribe (ST) and 32.9% were from Other Backward Class (OBC).1 Three regression models were run for the study. The first model (Model 1) examined the relationship between socioeconomic vulnerabilities and migration intention.
The second model (Model 2) examined the relationship between vulnerabilities due to climate change stress and migration intention. The third model (Model 3) analysed the nexus between socioeconomic and climatic factors on migration intention.

Findings

Patterns of migration. Of households surveyed, 37% have had at least one member migrate in the past.
The percentage is highest in Uttar Pradesh (50%), followed by Madhya Pradesh (34%) and Rajasthan (28%). Migration from the three states is predominantly seasonal (61.4%). Males mostly migrate to major cities and different states once or twice a year, depending on climate situation. Low returns or failure of existing livelihoods of agriculture and fisheries trigger seasonal migration. Seasonal migrants usually go to major cities in Maharashtra or Gujarat, or to Delhi. They normally work in brick kiln, construction sites or cotton fields of neighbouring states like Maharashtra and Gujarat.
Migrants send remittances once every month or every two to three months. Remittances have improved migrant households’ standard of living by enabling them to pay for daily consumption, healthcare and education bills.

Drivers of migration — climate acting as a stress multiplier to socioeconomic factors. Of the total surveyed households (1046), more than two thirds (70%) of the respondents indicated that drought/ irregular rainfall is a significant stressor. In addition, 23% of households mentioned flood as a significant stressor, while 8.3% mentioned hailstorms.

Odds ratio (OR) in regression analysis is a measure of association between exposure and an outcome. An OR of one means that there are no higher or lower chances of the outcome happening. An OR above one means that there is a greater likelihood of the outcome and an OR below one means that there is a lesser likelihood of the outcome.

(i) Climate-related events

Drought: The alarming increase in the frequency of droughts is a common trend in all the three droughtprone states. More than 70% of the households in study regions said that the frequency of droughts had increased significantly in the last 5–10 years. Results indicate that households exposed to drought are 1.157 times as likely as those who are not exposed to have the intention to migrate.

Flood: Uttar Pradesh had experienced significant flooding in the last 10–15 years. During monsoons, heavy rains regularly flood villages on the riverbanks.
Households that are exposed to flood are 1.419 times as likely as those who are not exposed to have the intention to migrate.

(ii) Socioeconomic variables

Household size: The size of the household also determines how a household is able to manage in times of climate-related events. The larger the household size, the more vulnerable they may be in times of a climate crisis. On the other hand, larger households might be able to easily send one of their members on migration. The OR of 1.153 suggests that household size increases the intention to migrate by 15%. To enhance climate resilience outcomes, social protection programmes will need to tailor their provisions by taking the current and future demographic trends into consideration.

Age of household head: Higher incidence of male migration occurs in the age group of 21–30 compared to other age categories. Results indicate that an increasing age of the household head decreases the intentions to migrate (OR = 0.981). Older populations are less inclined to migrate. As the migration options and mobility of older household members reduce, the social protection programmes will need to consider provisions that provide them with adequate coverage at village level during the climate crisis.

Education: The educational level of the household head plays an important role in their welfare and determines the level of information available and capacity to prepare for climate-related events. Male migrants with primary and secondary education migrate more than those with higher education. Household heads with no education have more intention to migrate than those with secondary (OR = 0.654) and higher secondary (OR = 0.542).

Migration networks: These are sets of interpersonal ties and links that a household or individual may have with existing migrants, former migrants, and nonmigrants in origin and destination sites, which makes migration easier. These networks provide information and support on place of stay, employment and access to basic services at the destination site, encouraging people to migrate. Results reveal that migration networks increase the intention to migrate by more than 50% (OR = 1.514).

Gender dynamics: In case of female migrants, the decision to migrate is dependent on the household head. In 90% of the villages, there is no family migration, and it is mostly one or two adult members of the family who migrate. Migration of the whole family was mainly seen in Barwani district of Madhya Pradesh. The land/ house and livestock ownership of the family usually restricts the entire family from migrating. Children’s education is also one of the reasons. Females have to take on the additional responsibilities of managing the household and livestock, and mostly work under MGNREGA.

(iii) State-wise results of the regression model

Rajasthan: The results explain 33% of the variation in the data. Household size, age of household head, income and migration network are significant socioeconomic variables that effect natural resourcebased livelihoods and migration decision making. But drought has a positive effect on intention to migrate (OR = 1.112). It can be said that both climate and socioeconomic factors play a role in migration decision making in Rajasthan.

Uttar Pradesh: The results explain 29.8% of the variation in the data. While socioeconomic variables like household size, age, education, income and migration network are important, the model reveals that exposure to drought (OR = 1.941), flood (OR = 1.001) and hailstorm (OR = 2.115) act as ‘stressors’ and drive individuals/households to consider migration as a survival strategy in Uttar Pradesh.

Madhya Pradesh: The results explain 11% of the variation in the data. The model shows that exposure to drought has a positive effect on intention to migration, but socioeconomic factors play a more important role in migration decision making in Madhya Pradesh.

The model empirically and statistically proves that climate impacts act as stress multipliers, particularly for those who are already socioeconomically vulnerable, driving them towards distress migration.

(iv) The push and the pull factors

Migration is becoming increasingly important for climate resilience. Migration is becoming established as a household adaptation strategy to cope with climate and economic stresses in survey areas. During climate distress, when slow-onset events such as drought threaten natural resource-based livelihoods such as agriculture, livestock and fishery, people’s ability to earn a living is compromised. This motivates them to consider migration in search of better economic opportunities.
Similarly, when rapid-onset hazards such as hailstorms or floods damage crops, cultivable lands and property, communities may have little or no options for adapting in situ. Under such situations, migration is the only viable option for survival. Overall, 69.74% households across all three states reported that they migrate immediately after drought, flood, hailstorms or heatwaves occur.
Migration has negative consequences as well as benefits. Whilst migration can give rise to economic benefits, there are other social consequences, both for the migrants and the families (mostly women, children and elderly) that are left behind. Migration has many costs and risks associated with it that are difficult for poor and vulnerable people to cope with.
Migration leads to breaking up of families and affects gender roles. The migrant-receiving areas are often inadequately prepared to accommodate migrants and often lack basic shelter and sanitation facilities and can’t guarantee women’s safety. Where migrants live in unsanitary conditions they are exposed to more disease. Labour and workplace safety laws are widely disregarded. Migrants are often forced to overwork, are paid less than non-migrants, and are exposed to polluting working conditions. Moreover, they do not have any employment security.

Recommendations

Results show that social protection programmes in their current form will not work unless they consider climate stress in their design framework and include climate resilience as one of its outcomes. Revamping MGNREGA would help it achieve its full potential.
Underlying operational inefficiencies and challenges need to be addressed. It also needs to change to help migrants deal with the challenges they face at migration destination sites. Some recommendations to help MGNREGA achieve this are:

Breaking the rural–urban silos. MGNREGA needs to reconsider the current limiting of benefits to people who remain in their native village. Workers who undergo climate-induced distress migration or displacement are left without social protection and often have to live and work in sub-human conditions for survival; devoid of any rights, benefits or entitlements. At the same time,
IIED Working paper www.iied.org not everyone is able to move out. Women, children and people from marginalised communities may be left in straitened circumstances that exacerbate their vulnerability. If the migrant worker cannot send back money, they can be particularly hard hit. Government policy response needs to extend rights and social safety net provisions to migrant workers in the destination sites through MGNREGA in convergence with other social protection schemes.

Strengthening MGNREGA in migration source areas. MGNREGA needs to provide a steady source of income and livelihood security for the poor and the marginalised, so that it can act as an essential means for coping with climate shocks. Our research shows that families and individuals undertook distress migration when they perceived that there was no other option to survive. For these people, MGNREGA did not act as a viable safety net. Administrative delays in sanctioning work and lack of transparency and delays in wage payments are some of the reasons that families do not consider MGNREGA as a fallback option during crisis. Having only 100 days of work guaranteed per year at most, and with comparatively lower pay than urban wage rates, does not help. Migrants feel they will be able to sustain their families better if they migrate, even though it exposes them to hardship at destination sites. Respondents in the research areas across the three states came up with many suggestions on how MGNREGA can be strengthened. While some of these pertained to improving the existing programme’s delivery in terms of timely work availability and wage payments, others relate to revising the scheme, such as by increasing the minimum guaranteed days of employment. These deserve careful consideration by government.

Making workers migration ready and creating safe pathways. Most migrants have little or no education and fall broadly under the category of unskilled workers.
But with rising standards in industry (Make in India;
Zero Defect Zero Effect2) and large construction/ infrastructure projects, the demand for skilled jobs has gone up, creating a mismatch between the skills of labour supply and demand. There is a need to carry out a national-level mapping of the skill requirement in major destination sites and to develop a systematic programme for skill enhancement matching those requirements, complementing this with certification and placement services.

Broadening the focus. There is a need to broaden the focus of MGNREGA from being a purely natural resource management-based approach to one that also emphasises human resource development. It must recognise the multi-locational nature of livelihoods and provide communities with adequate means, resources and information to enable them to make informed choices. MGNREGA should not seek to limit people to rural areas. The scheme needs to recognise that migration is people’s own effort to access employment and should explicitly recognise migration’s central role in protecting and promoting rural livelihoods.
Policymakers should:

• Develop a clear comprehensive framework that integrates migration into the MGNREGA’s operational guidelines, so that it does not lose priority.

• Give due emphasis to developing human capital through skill development, focusing on landless people or those with limited access to land and other natural resource-based livelihoods.

• Expand the scheme’s safety net to address the vulnerabilities of both migrants and those who stay behind. The entitlements for 100 days of work should not just lie with the household members who remain in the village but should also cover the migrant family member.

• Develop effective strategies for convergence with other schemes/programmes on housing, health and education in order to provide comprehensive cover.

• Increase the bargaining capacity of the rural workers to demand decent working conditions and wage rates.