Pauvreté saisonnière et saisonnalité - Recherche en IA spécialisée au MIT

Pauvreté saisonnière et saisonnalité
Migration in Asia
Ahmed Mushfiq Mobarak and Maira Emy Reimão∗

Four in ﬁve poor people in the Asia and Paciﬁc region live in rural areas. Crop
cycles in agrarian areas create periods of seasonal deprivation, or preharvest
“lean seasons,” when work is scarce and skipped meals become frequent. Dans ce
papier, we document this phenomenon of seasonal poverty and discuss existing
formal mechanisms for coping with it. We then focus on seasonal migration
from rural to urban areas as a potential coping strategy and review the evidence
on the effects of encouraging seasonal migration through transport subsidies.
Over the past 10 années, we have conducted a series of randomized control
trials in Bangladesh and Indonesia that provided rural agricultural workers with
small migration subsidies to pay for the cost of round-trip travel to nearby
areas in search of work. This paper summarizes the lessons learned from this
multicountry, multiyear series of seasonal migration trials, the implications
of these results for spatial misallocation, urbanization, et la croissance, et le
replicability and relevance of this and other policies encouraging domestic
migration more broadly for other areas in the Asia and Paciﬁc region.

Mots clés: Asia, Bangladesh, migration, seasonal poverty, seasonality
Codes JEL: J61, O12, O15

je. An Introduction to Seasonal Poverty and Domestic Seasonal Migration

In the Asia and Paciﬁc region, poverty is highly concentrated in rural areas.
Four out of every ﬁve poor people in Asia live in rural areas (Asian Development
Bank 2007), and the rural concentration of poverty is even starker within some
des pays. In Viet Nam and Cambodia, par exemple, rural areas account for 90% de
all poor people (Balisacan, Edillon, and Piza 2005). In Bangladesh, 35% of rural
households are poor, compared to 21% in urban areas. In Pakistan, these ﬁgures are
36% et 18%, respectivement, and in the Lao People’s Democratic Republic, 29% de

∗Ahmed Mushﬁq Mobarak (corresponding author): Professeur, Yale University, United States and Deakin University,
Australia. E-mail: ahmed.mobarak@yale.edu; Maira Emy Reimão (corresponding author): Professeur adjoint,
University of Florida. E-mail: maira.reimao@uﬂ.edu. We thank Innovations for Poverty Action Bangladesh, Rangpur
Dinajpur Rural Service (RDRS) Bangladesh, and Evidence Action for ﬁeld and implementation support; et
GiveWell and Evidence Action for ﬁnancial support. We would also like to thank the managing editor and
the anonymous referee for helpful comments and suggestions. Mobarak acknowledges support from a Carnegie
Fellowship (Grant ID G-F-17-54329). The usual ADB disclaimer applies.

Revue du développement en Asie, vol. 37, Non. 1, pp. 1–42
https://doi.org/10.1162/adev_a_00139

© 2020 Asian Development Bank and
Asian Development Bank Institute.
Publié sous Creative Commons
Attribution 3.0 International (CC PAR 3.0) Licence.

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2 Revue du développement en Asie

Chiffre 1. Trends in Rural and Urban Population Distributions by Region

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Source: Authors’ calculations using World Bank, World Development Indicators data. https://datacatalog.worldbank
.org/dataset/world-development-indicators (accessed 7 May 2019).

rural households are poor, almost three times the share for urban residents (10%)
(World Bank 2018).1

As a subregion, South Asia is the most rural in the world and the only one
besides sub-Saharan Africa in which the share of the population living in rural areas
still exceeds that for urban areas (Chiffre 1). A majority of the population in rural
domaines, coupled with a concentration of poverty in these same places, translates into
a large number of poor rural households in relative and absolute terms. Most of
these households are engaged in agriculture and are vulnerable to more severe
and frequent shocks compared to urban households. In this paper, we discuss the
seasonal variation in poverty within rural, agrarian areas and summarize ﬁndings
depuis 10 years of research on a strategy many poor rural households use as a way to
cope with seasonal deprivation: temporary, within-country seasonal migration. Both
pilot and larger-scale interventions conducted in Bangladesh and Indonesia reveal

1Based on the national poverty lines.

Seasonal Poverty and Seasonal Migration in Asia 3

that policies that encourage seasonal migration by providing transport subsidies and
lowering migration costs can, under certain conditions, help poor families mitigate
the adverse effects of seasonal poverty by expanding their access to urban labor
marchés.

UN.

Internal Migration

Internal migration—permanent,

temporary, seasonal, or cyclical—is a
common coping strategy among rural households and has played a key role in
accelerating urbanization in the region. Il y a 282 million internal migrants in
Asia, which account for over one-third of all internal migrants globally (UN DESA
2013).2 In the region, a lot of internal migration has historically been of a more
permanent nature—such as relocation to urban or manufacturing areas—but this
pattern has slowed down in several countries since the late 1990s. In Indonesia,
Malaisie, and Viet Nam, this deceleration is likely related to an aging population
(who are less likely to migrate), economic growth, and a reduction in interregional
wage gaps. The People’s Republic of China (RPC) is an exception to this trend, comme
within-province migration actually increased by well over 100% entre 1990 et
2000, likely due to the loosening of restrictions on migration to its large cities (Cloche
and Charles-Edwards 2014).

In contrast to the deceleration in permanent migration, temporary, seasonal,
and circular migration have increased in Asia over the last few decades as temporary
employment opportunities in urban and manufacturing centers expanded. Given
crowding and limited access to housing in urban areas, a lot of the recent
rural–urban movement has been temporary and reversible in nature (Deshingkar
2006). Beyond the draw of better employment opportunities in cities, there are also
a couple of push factors that drive rural people into internal, seasonal migration:
predictable preharvest lean periods in agricultural crop cycles during which labor
demand is low in rural areas, and high levels of vulnerability to unanticipated
shocks, which further exacerbate income ﬂuctuations.

Risk and Vulnerability in Rural Areas as Drivers of Internal Migration

Le 2014 World Development Report on risk and opportunity analyzed the
incidence of adverse shocks using household survey responses and found a much
higher prevalence of shocks in rural areas compared to urban ones (World Bank
2013). In India, 62% of rural households reported experiencing at least one negative
shock within the previous 12 months and 24% reported two or more. In the Lao

2This ﬁgure, based on data from individual countries, generally does not include seasonal migrants or those

who have relocated for less than a year.

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4 Revue du développement en Asie

People’s Democratic Republic, 36% of rural residents reported a negative shock
compared to 12% of urban residents. Economic activity in rural areas is much more
weather dependent and less diverse than in urban areas, and rural residents report
facing both aggregate shocks such as natural disasters (par exemple., droughts and ﬂoods)
and idiosyncratic health shocks. While health shocks are also common in urban
domaines, natural disasters do not appear to be as big a concern for urban households
when compared to rural ones (World Bank 2013).

Acute shocks in rural areas such as droughts and ﬂoods certainly contribute
to the heavy ﬂux of temporary migration observed in Asia. Dans 2010, par exemple,
14 million people were temporarily displaced in Pakistan because of ﬂoods (Lucas
2015). And in 2001, almost two-thirds of all people in Bolangir, a district in the
Indian state of Odisha, migrated during a drought (Deshingkar 2006). It is estimated
that between 2011 et 2050, autant que 26 million people in Bangladesh may have
to migrate because of ﬂoods, storms, riverbank erosion, and sea-level rise (Siddiqui
et autres. 2014).

Alongside these dramatic responses, a lot of temporary migration is recurring
in nature, as people move not only because of unanticipated shocks but also to
cope with predictable seasonal variation in employment opportunities in rural areas.
In northern Bangladesh, every year, one-third of poor households in rural areas
send a migrant to work elsewhere in the country for an average of 2–3 months
(Khandker and Mahmud 2012). This massive movement of people that occurs at a
predictable time of the year is the result of seasonal ﬂuctuations in income and work
opportunities in areas of origin due to the agricultural crop cycle and not because
of unexpected natural disasters.

In areas with little crop diversiﬁcation and distinct cycles, there is a lean
season between planting and harvest periods, a time when agricultural jobs are
scarce, harvest income is yet to come in, and poor households regularly skip meals
and suppress expenditures. Though food insecurity is a nonnegligible issue for
poor households throughout the year, there is a stark increase in extreme levels
of deprivation during this period. Dans 2006 (a typical year in terms of agriculture),
47% of poor households in northern Bangladesh experienced hunger during the
agricultural lean season (Khandker and Mahmud 2012). In contrast, only 9% de
households went hungry outside the lean season that same year.

More recent data we have collected in the region show spikes in hunger in
two different lean periods within the course of a year: from August to October and
brieﬂy around March (Chiffre 2). The main rice crop (aman) is typically harvested
from November to January, and the secondary rice harvest (boro) is in April. Le
periods before each of these harvests are marked by heightened food insecurity
among landless rural households: whereas over half of poor households reported
at least sometimes skipping meals during the main lean season (from August to
Octobre), fewer than 25% reported doing the same once the aman harvest was
underway or after the boro harvest.

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Seasonal Poverty and Seasonal Migration in Asia 5

Chiffre 2. Seasonal Hunger in Northern Bangladesh

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Source: Authors’ calculations using the 2016 Household Follow-Up Survey for the 2014 randomized control trial
round (control group only). Shading denotes historical lean seasons (Food and Agriculture Organization of the United
Nations 2008).

The Effects of Seasonal Poverty

Income ﬂuctuations, even when seasonal and expected, can have dramatic
consequences for the poor who live close to subsistence and are unable to
accumulate savings and smooth consumption. In rural areas in the PRC, pour
instance, households in the bottom 10th percentile in wealth respond to a drop
de 100 yuan (CNY) in income with a decrease in food and nonfood expenditure
of CNY40 on average. In contrast, for the top-third of households considered
“nonpoor,” the same drop in income results in just a CNY10 decrease in
expenditures (World Bank 2013).

Such consumption drops among the poor have serious implications for health
and well-being, especially for pregnant women and young children. Skipping meals
and decreasing food intake leads to stunting, nutrient deﬁciencies, and other health
issues, with potential repercussions for future cognitive capacity and earnings.
Given the concentration of poverty—and vulnerability to agricultural cycles—in
rural areas, it is perhaps not surprising then that Bangladesh has the fourth-highest
prevalence of stunting among poor households around the world, and South Asia
remains the region with the largest number of stunted children under the age of 5
(World Bank 2018). Increases in population per hectare of crop land in several Asian
countries forebodes further competition for the few tasks that are available in rural

6 Revue du développement en Asie

agrarian areas during the preharvest period. As is, there is a danger of potentially
worsening health outcomes for the rural poor over the next few decades (Deshingkar
2006).

Seasonal Migration as a Policy Tool to Counter Seasonal Poverty

The limited set of tools readily used by the rural poor to cope with
seasonal income ﬂuctuations include starting a nonagricultural business, engaging
in nonfarm employment, or temporarily migrating. Business creation and nonfarm
employment are strategies most commonly used in sub-Saharan Africa (World Bank
2012) and can help households diversify away from agricultural income and its
cycles. En même temps, these are reliable coping tools only if there are proﬁtable
opportunities within rural areas, which appear not to be the case in large parts of
rural Asia (World Bank 2012). Social or cultural constraints may further restrict
households’ ability to engage in nonfarm employment. Poor rural households in
Bangladesh, where women are less likely to work outside the home due to cultural
norms, have even less diversiﬁed income sources than in neighboring India, pour
example (World Bank 2013).

In contrast

to rural-based livelihood diversiﬁcation strategies, seasonal
migration may be proﬁtable even when local rural areas are poor and offer sparse
employment opportunities. If travel between villages of origin in rural areas and
urban destinations is manageable and not too expensive, then spatial wage gaps
may create an arbitrage opportunity. Migrants can take advantage of employment
opportunities in urban areas and send remittances or bring money back home at
the end of their period of employment to help their family cope during the lean
period. One study estimates that migrants in Dhaka send as much as 60% of their
income back home (Deshingkar 2006), while another shows that a quarter of rural
Indonesian households have a migrant, avec 85% of urban migrants sending money
home (Lu 2013).

Beneﬁts from seasonal migration and its role in smoothing consumption
may extend beyond averted hunger alone and into other gains in human capital. Dans
rural Bangladesh, school attendance is higher among children in households with
temporary migrants than in those without; and in Bangladesh, India, and Nepal,
households with seasonal migrants report higher expenditures on education than
nonmigrant households (Srivastava et al. 2014).

Our research, as described in detail in section III, employs a series of
randomized control trials (RCT) to explore whether encouraging more seasonal
migration from rural areas helps poor households mitigate the adverse effects
of seasonal deprivation. Since 2008, we have been testing the effects of small
migration subsidies ($8.5–$19) in rural Bangladesh and have found that this
low-cost intervention increases consumption and income among treated households
relative to a control group. The main economic results are reported in studies by

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Seasonal Poverty and Seasonal Migration in Asia 7

Bryan, Chowdhury, and Mobarak (BCM) (2014); Akram, Chowdhury, and Mobarak
(ACM) (2017); and Lagakos, Mobarak, and Waugh (LMW) (2018). BCM (2014)
and ACM (2017) show that the impact of a one-time subsidy also carries over
to subsequent years, as treated households are more likely to send a migrant
up to 3 years after the initial treatment. Cependant, LMW (2018) show that the
ﬁnancial beneﬁts of migration are tempered by the disutility associated with bad
living conditions experienced in destination areas, particularly urban slums. Nous
are continuing to develop further evidence on this program with each new year
of implementation and asking new questions as the program scales.

Over the last 10 années, through multiple phases of testing this intervention,
we gradually moved from the original RCT covering 1,900 households to testing
a program called “No Lean Season,” which was run by a separate entity and
disbursed zero-interest migration loans to over 80,000 households in the 2018–2019
lean season alone.3 This scale-up required more local engagement and resources
and adjustments to the delivery system, moving from an intervention carefully
monitored by researchers at each step of the way to one with greater autonomy for
implementing partners and a slightly more hands-off approach to test scalability.

En même temps, the shift from RCT to the program demanded attention
to effects that might not be relevant to an initial study but that come into play
as the target population and area expands. With this transition as motivation,
ACM (2017) focused on general equilibrium effects on nonmigrant households in
villages of origin, considering the effects of offering migration subsidies to some
households on the consumption levels and incomes of other poor households in the
same village. Other papers have explored the noneconomic effects of encouraging
migration, such as those on beliefs, attitudes, and social norms (Mobarak, Reimão,
and Thachil 2018), effects on intimate partner violence (Mobarak and Ramos
2018), pressures toward urbanization in the long run (Chowdhury, Mobarak, et
Reimão 2018), effects on informal insurance networks (Meghir et al. 2017),
and the relevance of the intervention to other settings, such as in rural eastern
Indonésie (Bryan et al. 2018). We are also preparing to study (je) whether seasonally
timed consumption loans (as opposed to seasonal migration subsidies) is the right
policy response in a different setting, with a new experimental design in Nepal;
(ii) the effects of the scaled-up version of the program on urban labor markets in
Bangladesh; et (iii) the role of implementation changes on targeting and migration
résultats.

3“No Lean Season” was a program run by the Beta division of Evidence Action and implemented in
Bangladesh through its partner RDRS Bangladesh. One of the authors of this document was a postdoctoral fellow
with Evidence Action, and the entire research team engaged with Evidence Action on a regular basis to provide input
for program decisions. No Lean Season, as funded by Evidence Action, was discontinued after the 2018 lean season,
but RDRS Bangladesh has continued to offer migration loans. The research team has not been involved in these
subsequent activities.

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8 Revue du développement en Asie

Other Policy Options to Counter Seasonal Poverty

less

seasonal variations

acute—and investments

Explicit support for seasonal migration through transportation subsidies is
only one option in a suite of potential policies to address seasonal deprivation in
rural areas. In Japan; la République de Corée; and Taipei,Chine, Par exemple,
in agricultural
increased crop diversity—which makes
employment opportunities
in transportation
infrastructure to improve access to other regions played key roles in the national
development trajectory (UNFPA 2016). With improved and expanded transport
réseaux, rural households could both commute and temporarily migrate to cities,
better allocating their labor between local agriculture and other employment
options—between members as well as over time. On a related note, Asher and
Novosad (2018) show that a rural road construction program in India allowed
connected villages to reduce their reliance on agricultural income earned inside the
village.

De même, Bangladesh (and other countries in South Asia and Southeast Asia)
could beneﬁt from investments in deeper and safer transportation networks and in
better housing options for the poor in urban areas. This strategic funding could
transform temporary migration from a coping strategy to a predictable and desirable
yearly pattern for rural residents, while enabling local governments and employers
to better manage and respond to the inﬂux. Improved transportation can also expand
commuting opportunities, which would counter people’s need to migrate and live
in destination areas for long periods. Cependant, for the foreseeable future (jusqu'à
transportation networks vastly improve or rural residents have better access to local
jobs year round, or both), explicit support for seasonal migration will likely continue
to play a role in helping the poor cope with seasonal deprivation.

Dans la section suivante, we discuss a broader range of policies that governments
and development organizations typically employ to help the rural poor deal with
employment and income shocks, including guaranteed work schemes, universal
basic income, crop insurance, and microﬁnance, and we point to the gap that can be
ﬁlled by seasonal migration subsidies. In section III, we discuss in greater depth the
design and results of the seasonal migration support programs we have implemented
and tested over the last 10 années. We discuss the implications of our research
for other countries in the Asia and Paciﬁc region in section IV and subsequently
conclude.

II. Rural Development Policies to Address Seasonal Poverty

One of the largest and best known seasonal income support programs in
the world is India’s National Rural Employment Guarantee Act (NREGA). Under
this program, all rural workers in the country are in theory entitled to 100 jours

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Seasonal Poverty and Seasonal Migration in Asia 9

Tableau 1. Some Policies for Addressing Economic Shocks in Rural Areas

Policy

Design Strengths

Caveats

Guaranteed work

Self-targeted
Supports local infrastructure
development by design

Basic cash or food

guarantee

Universal targeting ensures even
those who cannot work receive
beneﬁts

Crop or agricultural

Transfers tied to actual agricultural

insurance

shocks

May encourage risk-taking and

investment by softening downside
of shocks

Discourages migration in search of

jobs elsewhere

Costly

Costly, with leakage to nonpoor

households

Implementation costs also very high

for food distribution

Does not address seasonality of
agricultural employment and
outputs, only shocks to it

Does not address idiosyncratic shocks
Documented low take-up rates
Possible abuse of subsidized system
by nonagricultural households (comme
documented in Mexico; Monde
Bank 2013)

Microcredit and
savings for
agriculture

Microcredit for
nonfarm
enterprises

Support for
seasonal
migration

Supports investment in agricultural
entreprise (versus subsistence)

Less relevant for landless poor
Documented low take-up rates in

général

Supports diversiﬁcation of income
away from agriculture in rural
domaines

Relies on proﬁtable business
opportunities in rural areas
Assumes entrepreneurial skill;

Self-targeted

training is costly and results mixed

Relies on having temporary

employment opportunities within
reasonable traveling distance

Source: Authors’ compilation.

of guaranteed employment per year and are primarily hired for projects that
support local community development, such as irrigation and road construction.
Other common rural poverty programs include promoting ﬁnancial services such
as microﬁnance (a concept that also originated in South Asia), crop insurance,
and support for savings (Tableau 1). Many governments around the world have
also experimented with cash transfers—either unconditional or conditional on
a speciﬁed activity like school attendance—and transfers in the form of food
subsidies or free food distribution have been deployed in acute situations around
the world for decades.

Besides these formal policies, poor households have long used informal
coping systems as well. In times of distress, they rely on their social networks
for gifts and transfers, on informal loan providers, on temporary or permanent
migration, or on invoking the very costly strategy of cutting back on consumption,
or a combination of these. Dans cette section, we provide an overview of commonly
employed antipoverty policies for rural areas and discuss the evidence of impact of

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10 Revue du développement en Asie

such programs, drawing on data from Asian countries whenever possible. We close
the section by explaining how subsidies for seasonal migration can ﬁll a gap left by
these programs.

UN.

Guaranteed Work Schemes

NREGA, enacted in 2006, is an ambitious program to address rural seasonal
poverty in India. It is a cash-for-work program that provides guaranteed employment
during the lean season for rural households across the country. Within 6 years of
inception, this program had provided over 12 billion person-days of employment for
the rural poor. In the 2017–2018 ﬁscal year, presque 80 million individuals worked
under the scheme (NREGA 2018).

NREGA relies on “self-targeting,” in that offered wages are deliberately
low relative to the market, to ensure that only those facing weak employment
opportunities will seek out the program. Malgré cela, no state has been able to
provide all of the employment that rural workers have demanded and are entitled
à (World Bank 2012, Dutta et al. 2012). En fait, in the 2017–2018 ﬁscal year,
the average number of days worked per participant household was 46 jours, well
below the guarantee of 100 days per person (NREGA 2018). Nevertheless, là
is evidence that the opportunities offered by NREGA have had a spillover effect
on the private sector, pushing up market wages and beneﬁting the poor more
broadly (Imbert and Papp 2015; Muralidharan, Niehaus, and Sukhtankar 2018).
Studies report other positive effects of NREGA, including on consumption, assets,
nutrition, education expenditures, and women’s empowerment (Das and Singh
2013, Dasgupta 2017, Deininger and Liu 2013), but since the program rollout
was not designed with research in mind, it has been difﬁcult to establish some
of the evidence very rigorously. In contrast, a similar rural employment guarantee
scheme in Malawi was evaluated using an RCT, and it found no meaningful beneﬁts
in terms of agricultural investment, food security, or labor market opportunities
for beneﬁciaries (Beegle, Galasso, and Goldberg 2017). This study even reported
a negative spillover effect on untreated households operating in the same labor
markets as the beneﬁciaries of the cash-for-work program.

Guaranteed work schemes, even when they are effective, are very costly to
operate because they must force job creation in a rural area where the structure
of the agricultural economy is such that it is difﬁcult to generate employment.
This is likely related to crop cycles. Lean seasons often appear in agrarian areas
during the period between planting and harvest, where cultivators must patiently
wait for the crop to grow. There is relatively little to do on the farm, as weeding and
other land management tasks do not require as many workers as during planting
and harvest. These preharvest lean periods constitute expected seasonal downturns
marked by job scarcity and are known as “monga” in Bangladesh, “musim paceklik”
in Indonesia, or simply “hungry seasons” in Malawi, Mozambique, Senegal, et

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Seasonal Poverty and Seasonal Migration in Asia 11

Zambia. The private sector does not generate sufﬁcient employment during this
period in rural areas, but it is not clear whether this is due to a market failure or is
the natural result of economic conditions given the concentration of poor people
with little buying power during the lean season. Nevertheless, government-led
guaranteed employment programs expend vast amounts of resources to go against
this tide and create local jobs each year during the lean season.

Even setting aside their debatable potential as efﬁciency-enhancing programs
that address a market failure, and instead looking at them as a social safety net
for the extreme poor, food- and cash-for-work programs are difﬁcult to design
to meet local needs. The wages offered through the program need to achieve a
balance between being low enough to properly target the poor and needy who should
self-select into the program, but high enough to actually address seasonal poverty
and be of use to those poor households (who may also face higher prices during
the lean season). NREGA participants in India receive an average of 175 rupees
($2.50) per day, and there are indications that the program is well targeted for the poor (Imbert and Papp 2019). In contrast, the wages offered in the Malawi government program are apparently so low relative to outside options that only 50% of households offered employment through the system actually accepted (Beegle, Galasso, and Goldberg 2017). A job guarantee program in Bangladesh called Food for Assets (FFA) is also reportedly well targeted to the poorest households, because the nature of the work is physically demanding and the program offers low pay. Of FFA participants, 72% come from the lowest decile of the income distribution (Ahmed et al. 2009). Job availability also generally overlaps—though not perfectly—with the lean season, as most of the work is provided between December and May. There is some evidence, cependant, that this program crowds out other income, as participants are required to work full days, thereby foregoing labor opportunities in private markets. En tant que tel, every 100 taka (Tk) paid through the FFA program increases household income by an average of only Tk32 (Ahmed et al. 2009). Rural workfare programs also discourage labor migration to urban areas, as one must be present in the rural area to take advantage of the job guarantee scheme. Since these programs are more common during the lean season (both to address seasonality and because construction projects are challenging to implement during monsoon periods), they also directly compete with seasonal migration-based coping strategies that those households may have otherwise employed. Research in India reveals that districts that were early implementers of NREGA experienced a 50% decrease in seasonal out-migration relative to a comparison group of districts where the program was not yet implemented at the time (Imbert and Papp 2019). In our own research in Bangladesh, we ﬁnd that displacement of migration limits the positive effect of work programs on household welfare. Simulations reported in LMW (2018) show that introducing a rural workfare program in northern Bangladesh would decrease the seasonal emigration rate of the poorest quintile l D o w n o a d e d f r o m h t t p : / / direct . m je t . / e du a d e v / art – pdlf / / / / / 3 7 1 1 1 8 4 6 7 5 7 a d e v _ a _ 0 0 1 3 9 pd . f par invité 0 7 Septembre 2 0 2 3 12 Asian Development Review by 4–6 percentage points and produce lower household welfare gains, on average, relative to migration subsidies or an alternate program providing unconditional cash transfers without imposing a requirement to remain in the rural area (LMW 2018). B. Unconditional Transfers Unconditional cash transfers (UCTs) have gained popularity in recent years as a benchmark against which to measure the impact and cost-effectiveness of other poverty alleviation programs. In LMW (2018), we directly compare the effects of seasonal migration subsidies on household welfare to the welfare that would be generated under an untargeted UCT program. The overall welfare gain across the population produced by an untargeted UCT is by deﬁnition greater than that of a transfer conditional on migration, because a migration conditionality imposes a constraint on people, and constraints can only make rational people (weakly) worse off. Cependant, the migration transfer generates some targeting beneﬁts relative to the UCT, since it tends to induce only the people who actually need the support to participate, as opposed to the universal coverage of the UCT, which ends up beneﬁting many people who are not as poor or who did not face an acute adverse seasonal shock during the year. Donc, when we conduct a budget-neutral comparison between migration subsidies and UCTs, we see that the migration subsidies improve the welfare of the poorest quintile by about 14% more than a UCT program (LMW 2018). These results highlight a feature of UCTs that is both their strength and their weakness: the lack of any conditionality means that anyone can receive a UCT, which includes both the nonpoor (who are not intended beneﬁciaries of pro-poor programs) and households who may be so poor and so constrained that they may have difﬁculty complying with the conditions required by a conditional cash transfer (CCT) program. A study by Baird, McIntosh, and Ӧzler (2011) highlights this particular beneﬁt of UCTs by directly comparing a UCT program against a CCT in which transfers for adolescent girls are conditioned on school attendance. This RCT-based study shows that while the CCT produces larger effects on the schooling outcomes on which transfers are explicitly conditioned, it does not decrease marriage and pregnancy rates among young girls by as much as the UCT. This is because there is a subgroup of extremely vulnerable households who cannot comply with the conditionality and therefore do not receive beneﬁts under the CCT program. These types of households are still helped in the UCT. This logic implies that, relative to seasonal migration support programs or rural workfare programs, a basic income transfer might better reach households that may not have a working member who is able to migrate or even work in the rural area. A substantial part of the transfers, cependant, would also go to those who may not be in as dire a situation as the target population. l Téléchargé à partir du site Web : / / direct . m je t . / e du a d e v / art – pdlf / / / / / 3 7 1 1 1 8 4 6 7 5 7 a d e v _ a _ 0 0 1 3 9 pd . f par invité 0 7 Septembre 2 0 2 3 Seasonal Poverty and Seasonal Migration in Asia 13 Of relevance to this difference in coverage, we also implemented an RCT in West Timor, Indonésie, designed to empirically compare the relative effects of UCTs and migration transfers directly (Bryan et al. 2018). Not surprisingly, take-up among eligible households is over 90% in the UCT arm, compared to 52%–59% in the CCT arm. The conditional transfer increases migration by about 30 percentage points relative to the UCT, and average gains in household income are larger for the CCT group compared to the UCT. Nevertheless, the difference in take-up rates is composed of both households that are too wealthy to be interested in migrating and households that may have been unable to migrate or ﬁnd a job in destination areas. A CCT such as a seasonal migration support program cannot directly reach the latter group, a disadvantage relative to UCT programs or other unconditional safety nets. Seasonal migration—and programs supporting it—is not and cannot be a substitute for basic income, particularly for households that do not have a working member. It is also important to acknowledge that cash and food transfers for the poorest households are relevant in several circumstances besides seasonal drops in income. That said, these programs are relatively costly to implement and also vulnerable to elite capture. Ahmed et al. (2009) evaluate transfer programs targeting the ultra poor in Bangladesh, including Income Generation for Vulnerable Group Development (IGVGD), a food transfer and credit program, and Food Security Vulnerable Group Development (FSGVD), a combined food and cash transfer program. The study ﬁnds that 10% of IGVGD-beneﬁciary households were actually in the top three deciles of the income distribution. Only 43% et 38% of beneﬁciaries for IGVGD and FSGVD, respectivement, were in the bottom decile; in contrast, the respective share was 72% for the FFA guaranteed workfare program (Ahmed et al. 2009). On the other hand, the same study also reports that the food-for-work program is the most expensive way to increase household consumption, with the FFA requiring Tk440 per beneﬁciary per month to increase daily consumption per capita by 100 calories. IGVGD requires Tk249, while FSGVD, the combined food and cash transfer program, requires Tk156 per month. The workfare program is likely even more costly in ways that are not measured, since participation in workfare generally requires beneﬁciaries to forego other labor market opportunities. The coverage of these transfer programs is also precarious, as only 6%–7% of the Bangladeshi poor are actually covered by any food or cash transfer or workfare program (Ahmed et al. 2009), a statistic likely related to the high cost of implementing such schemes. These programs are therefore inadequate in their present form to address the recurrent seasonal poverty that afﬂicts well over one-third of the rural population in northern Bangladesh each year. Seasonal migration support may therefore serve as a useful policy complement to these existing social safety net programs in this setting—and similar ones with low safety net coverage and high seasonal vulnerability. l Téléchargé à partir du site Web : / / direct . m je t . / e du a d e v / art – pdlf / / / / / 3 7 1 1 1 8 4 6 7 5 7 a d e v _ a _ 0 0 1 3 9 pd . f par invité 0 7 Septembre 2 0 2 3 14 Asian Development Review C. Agricultural Insurance Agricultural insurance programs are designed to mitigate losses associated with extreme events and unexpected weather shocks, rather than predictable and recurrent seasonality. Index-based insurance programs circumvent the adverse selection and moral hazard problems that undermine traditional crop insurance by tying payouts to veriﬁable weather events or other aggregate outcomes such as average losses at the regional level. By design, alors, agricultural insurance is not meant to address seasonal deprivation that arises on a cyclical basis through the regular agricultural calendar, as payouts are made based on deviations from expected patterns. A more sophisticated tool ties agricultural insurance to a safety net, as is done in Mongolia. Under this particular program, Mongolian herders fully absorb losses of up to 6% (indexed on the average mortality of adult livestock in each county); losses between 6% et 30% are covered by index insurance; and participants are automatically enrolled in a safety net program if losses surpass 30% (World Bank 2013). Though crop (livestock) insurance is traditionally aimed at landowners (livestock owners), payouts are not tied to individual output, so it is possible to expand the target population for crop (livestock) insurance from landed to landless (livestock-less) households, who are also vulnerable to extreme shocks through decreased farm (herding) employment opportunities. En fait, in an RCT in India where landless laborers were offered rainfall insurance, their take-up rate was only 4% lower than that of landowning households (Mobarak and Rosenzweig 2013). Cependant, selling crop or weather insurance to the landless poor necessarily requires the use of index insurance, where payments are not tied to individual outcomes but to a measurement along the lines of a weather index or an aggregate outcome. This in turn implies that the policy can only insure against aggregate risks (such as weather, pest, or price shocks) and not idiosyncratic risks that poor rural households may face, such as consumption drops due to a mortality or morbidity event in the household. Empirical research on agricultural insurance also reveals that take-up is relatively low in some contexts even at actuarially fair prices, and its use has not necessarily led to higher levels of investment and technology adoption (Lybbert and Carter 2015; Carter, Cheng, and Sarris 2016). In a study offering insurance to landless households, roughly 40% of all households purchased insurance—a fairly low rate considering that subsidies of 0%, 10%, 50%, ou 75% on the insurance product were randomized across households (Mobarak and Rosenzweig 2013). A new tool combining index insurance and loans, in the form of emergency loans that are made available to farmers in the event of ﬂooding, has been recently designed and implemented in Bangladesh. The key innovation of this intervention is that, unlike other insurance forms, it does not require any upfront payment by l D o w n o a d e d f r o m h t t p : / / direct . m je t . / e du a d e v / art – pdlf / / / / / 3 7 1 1 1 8 4 6 7 5 7 a d e v _ a _ 0 0 1 3 9 pd . f par invité 0 7 Septembre 2 0 2 3 Seasonal Poverty and Seasonal Migration in Asia 15 farmers; only eligibility is determined before the crop cycle. Preliminary ﬁndings are generally positive, indicating that these emergency loans not only provide relief as expected in the case of ﬂoods, but also lead prequaliﬁed farmers to plant 15% more rice once they know they will be eligible for the loan in the event of major ﬂooding (voie 2018). This can generate spillover beneﬁts for the landless poor in terms of greater labor market opportunities when the weather cooperates, particularly during the planting period (Mobarak and Rosenzweig 2013), but still cannot fully address the regular decrease in employment opportunities during the lean season. D. Microcredit and Savings Microcredit and savings consist of a broad array of programs that provide small loans for the creation or expansion of nonfarm enterprises, credit for agricultural inputs, programs encouraging savings for farm or nonfarm businesses, and any combination of these. Small loans for nonfarm enterprises became a hugely popular idea in international development in the 1990s, and South Asia is the birthplace of large microﬁnance institutions, including Grameen Bank and BRAC. But recent meta-analyses of RCTs on microﬁnance generally ﬁnd modest impacts at best from this type of intervention. A review of six microﬁnance studies, two of which were implemented in Asia (India and Mongolia), notes that take-up rates of microloans are relatively low and the impact on family income or consumption was not statistically signiﬁcant in any of the six settings (Banerjee, Karlan, and Zinman 2015). Limited take-up is to be expected even before considering loan characteristics, as not all individuals aspire to be entrepreneurs or have a promising business idea, but half of the studies also found no impact on the ownership, start, or closure of a business, while the other half only found effects in one of these outcomes. The evaluation in India found signiﬁcant increases in expenditures on durable goods but not on consumption (Banerjee et al. 2015). And the evaluation in Mongolia shows positive impacts on household food consumption but not income for a group liability loan, while individual liability loans generally had no impact across the board (Attanasio et al. 2015). A Bayesian hierarchical analysis of an overlapping set of seven microﬁnance studies (Meager 2019) echoes the limited power of microﬁnance, showing that its impact on consumption is at best small and unlikely to be transformative, with relatively little heterogeneity across beneﬁciaries. Notably, this study also shows that, for households with no previous business experience, as would likely be the case for most primarily agricultural households in rural areas, microﬁnance also has zero impact on household proﬁts. It is clear, alors, that microﬁnance for entrepreneurship, though potentially beneﬁcial to some households—mainly those with existing enterprises—cannot reliably serve as an avenue for income l D o w n o a d e d f r o m h t t p : / / direct . m je t . / e du a d e v / art – pdlf / / / / / 3 7 1 1 1 8 4 6 7 5 7 a d e v _ a _ 0 0 1 3 9 pd . f par invité 0 7 Septembre 2 0 2 3 16 Asian Development Review diversiﬁcation or consumption smoothing for a large number of poor agricultural households. The seasonal migration support program we have evaluated in Bangladesh is in essence a version of a microcredit program with some crucial differences from how microﬁnance has traditionally been conceptualized.4 First, these loans are explicitly conditioned on migration rather than a business plan or business ownership. Deuxième, the loans are meant to encourage job search rather than require beneﬁciaries to set up a business. This difference expands the relevance of the loan and removes undue pressure toward business creation, as there are likely many more “employees” than “entrepreneurs” in the world; many more would prefer a job with a stable income rather than take on the risk of starting a business. Troisième, our seasonal migration support was in some cases a grant rather than a loan, and in others, a loan with zero interest rate. While microﬁnance institutions require proﬁtability to be sustainable, our intervention is designed to subsidize migration for the poorest households rather than turn a proﬁt. Fourth, the repayment period for our loans has been set at the end of the lean season, typically 3–4 months after loans are disbursed. In contrast, microcredit programs typically require biweekly repayment or other short intervals (Field, Holland, and Pande 2014), which may in itself distort household decisions away from seasonal migration. En fait, data from Bangladesh indicate that clients of microﬁnance organizations are less likely to migrate than nonclients (Khandker and Mahmud 2012). Agricultural loan programs tailored to rural areas (to encourage investment in agricultural inputs) also move away from short repayment periods and instead offer credit at the start of the planting season and collect repayment at harvest. Cependant, take-up of such loans is also low: a study in Mali found that just 22% of women who were offered an agricultural loan accepted it, and only the more productive farmers self-selected into taking out these loans (Beaman et al. 2015). Savings programs, including agricultural savings accounts, have been studied more extensively in Africa. An RCT in Malawi that encouraged savings after harvest to invest in inputs next season (Brune et al. 2016) found that, on average, only one-quarter of the original deposit was still in a savings account 2 weeks later. When an Abdul Latif Jameel Poverty Action Lab research team tried introducing new savings products through banks in Chile, Malawi, and Uganda, the programs generally failed, presumably because banks found it too costly to administer products in which poor people deposited very small amounts of savings each month.5 Our data from Bangladesh indicate that the landless poor, who are most vulnerable to seasonal hunger, typically do not have anything to save, especially 4The main implementing partner in northern Bangladesh, RDRS Bangladesh, was originally a microcredit organization. 5A related research paper by Dupas et al. (2018) concludes that traditional bank accounts are unappealing to the majority of the currently unbanked rural households in all three settings. l Téléchargé à partir du site Web : / / direct . m je t . / e du a d e v / art – pdlf / / / / / 3 7 1 1 1 8 4 6 7 5 7 a d e v _ a _ 0 0 1 3 9 pd . f par invité 0 7 Septembre 2 0 2 3 Seasonal Poverty and Seasonal Migration in Asia 17 during the lean season. Both ACM (2017) and BCM (2014) report signiﬁcant treatment effects on income and consumption from the migration subsidies introduced, but the studies do not observe any increase in savings in any of the multiple years in which the program was evaluated. The marginal propensity to consume extra income during the lean season is very high for the landless poor. The evidence suggests that it will likely be difﬁcult to induce savings among the poor as a way to address seasonal deprivation. Fink, Jack, and Masiye (2018) identify a more promising option: a well-timed loan during the lean season can reduce farmers’ desperation to suboptimally supply labor to other farms at low wages to address their short-run cash needs for meeting their family’s subsistence requirements. In this treatment, loans of either cash or grains are not envisioned as encouraging leaps in productivity or business creation; rather, they are disbursed to farmers during the lean season to discourage the use of more costly coping mechanisms, particularly working in other farms. The authors ﬁnd that these loans, which are also to be repaid after the lean season (effectively at a 4%–5% interest rate), do in fact encourage subsistence farmers to work on their own land during the lean season rather than in other farms, with positive repercussions for their subsequent harvest. Landless rural households may also beneﬁt from seasonally timed consumption loans, disbursed at the beginning of the lean season and repaid at the end with no conditionality. This may be a particularly sensible solution in countries where migration already occurs at high rates and usually over greater distances and for longer periods, but where seasonal poverty remains. Our initial exploration in Nepal indicates that seasonal consumption loans may be relevant there and calls for further research on this type of consumption loan, with a closer look at repayment rates. In Zambia, repayment rates on lean-season loans dropped between the ﬁrst and second years of treatment even though the harvested output increased for treated households (Fink, Jack, and Masiye 2018). Ensuring high repayment rates year after year is critical for the sustainability of such a program in the long run, and future experiments will be useful for illuminating that path. E. Temporary Migration In addition to the formal markets and mechanisms described above (employment guarantee schemes, insurance, credit, and savings transfers, programs), the poor use a variety of informal tools to cope with seasonal volatility. They may draw on support from friends and relatives, secure loans from informal money lenders, or attempt to diversify their income by engaging in informal business enterprises or by entering the labor market outside the village—or a combination of these approaches. Multiple years of data from northern rural Bangladesh show that, in any given year, about a third of poor households in the area send a family member to labor markets elsewhere in the country to cope with the l D o w n o a d e d f r o m h t t p : / / direct . m je t . / e du a d e v / art – pdlf / / / / / 3 7 1 1 1 8 4 6 7 5 7 a d e v _ a _ 0 0 1 3 9 pd . f par invité 0 7 Septembre 2 0 2 3 18 Asian Development Review seasonal shock through temporary, circular migration. This reliance on migration is not limited to Bangladesh and is common across the region. It is estimated that two- thirds of the 740 million internal migrants in the world reside in Asia (World Bank 2013), and that India alone is home to an estimated 30 million temporary internal migrants (Deshingkar 2006). Our research focuses on seasonal migration, a type of temporary migration that occurs at a predictable time in the year (often—but not always—during the lean season) and lasts a few weeks to a few months. As a policy intervention, encouraging seasonal migration involves supporting the movement of people to where there are jobs and allowing the market to provide employment and income, which may be more efﬁcient and easier than bringing jobs to local areas (as in a workfare program). Seasonal migration is a form of spatial arbitrage in which people move from areas where there are few jobs during a given season (par exemple., due to lean periods in the agricultural crop cycle) and into areas with better employment opportunities during the same period. Seasonal migration not only diversiﬁes income but may also have an indirect effect on other informal coping mechanisms. Par exemple, the temporary migration of a subset of members in a risk-sharing network may have a spillover effect on others in the network through a system of gifts and transfers (Meghir et al. 2017). Lowering the cost of migration via grants or loans, as we do in our intervention- based research, may also make it easier for others to migrate because they can travel together with grant recipients as they share costs and risks. Dans la section suivante, we will delve into the details of the research methods and lessons from our multiyear, multisite research program on encouraging seasonal migration. l Téléchargé à partir du site Web : / / direct . m je t . / e du a d e v / art – pdlf / / / / / 3 7 1 1 1 8 4 6 7 5 7 a d e v _ a _ 0 0 1 3 9 pd . III. Evidence on Seasonal Migration While our research program encourages more migration, one-third of poor households in rural areas of northern Bangladesh (in particular, the Rangpur region) already rely on internal seasonal migration as a coping strategy to deal with deprivation during the lean season. Those households send a migrant for weeks or months at a time for employment in urban areas or other rural areas within the country where wages are higher or employment opportunities are more broadly available or both. Data from 2017, par exemple, reveal that the median daily wage among individuals in our study was Tk200 at home ($2.4) during the lean period,
but Tk333 ($4) for those who migrated domestically. The starting point for our research was that the prevailing seasonal migration rate of one-third actually seemed puzzlingly low: given the lack of jobs in rural areas during the lean season, the relatively ample availability of jobs in urban areas during the same period, higher average wages offered to low-skilled workers in common f b y g u e s t t o n 0 7 Septembre 2 0 2 3 Seasonal Poverty and Seasonal Migration in Asia 19 destination areas, and the evident feasibility of temporary travel in this context, economic theory would predict a higher seasonal migration rate in the absence of market failures (and as long as individuals were not already sorted according to their comparative advantage). Our research was therefore designed to examine market failures that might prevent poor households in northern Bangladesh from temporarily moving to where there are jobs and to explore whether an external intervention could help overcome those hurdles. Rangpur is one of the poorest regions in Bangladesh, and its rural residents are more reliant on agricultural income than residents of other regions. Rural Rangpur households, on average, derive 50% of their income from farming, compared to 28% for rural households elsewhere in Bangladesh (Khandker and Mahmud 2012). This heavy reliance on agriculture leaves poor households more vulnerable to seasonal ﬂuctuations from crop cycles (predominantly rice in this setting), making seasonal emigration a sensible strategy during periods when agricultural jobs are scarce. International remittance receipts are also relatively low in Rangpur compared to other regions in Bangladesh, as it often takes a fair amount of money to migrate internationally. And while 32% of households in Rangpur participate in some type of social safety net (mainly food transfers), the beneﬁt amounts are too low to adequately address seasonal deprivation (Khandker and Mahmud 2012). With high poverty rates, savings constraints, and low safety net transfer amounts, ﬂuctuations in employment opportunities and income translate into substantial drops in consumption during the preharvest period. Using data from our research, Chiffre 2 shows that up to 20% of poor households in this setting regularly miss meals during the lean season, and fewer than 40% never face food insecurity. Unaddressed, this can have disastrous consequences for those already living close to subsistence, especially families with pregnant women and young children. Reduced consumption for up to 3 months of the year can adversely affect the physical and cognitive development of children, with attendant effects on learning, productivity, and future earnings. Since 2008, we have tested whether transport subsidies can facilitate out-migration and help poor rural households avoid drastic drops in consumption during the lean season, speciﬁcally by taking advantage of employment opportunities elsewhere in the country. And since 2013, we have partnered with Evidence Action, a nongovernmental organization (NGO) supporting and implementing evidence-based programs, to explore the viability and impact of a scaled-up version of this intervention. Working with Evidence Action’s “No Lean Season” project, we went beyond the ﬁrst step of measuring the direct effects of seasonal migration subsidies on targeted beneﬁciaries to exploring the potential effects of a large intervention under the same framework, such as the effects on destination workers, permanent migration, and beliefs and social norms. l Téléchargé à partir du site Web : / / direct . m je t . / e du a d e v / art – pdlf / / / / / 3 7 1 1 1 8 4 6 7 5 7 a d e v _ a _ 0 0 1 3 9 pd . f par invité 0 7 Septembre 2 0 2 3 20 Asian Development Review A. Direct Effects of Seasonal Migration Support on Beneﬁciaries In 2008, we implemented an RCT covering 1,900 households across 100 villages in Rangpur (discussed in further detail in BCM [2014]). D'abord, each village was randomly assigned into one of four arms: (je) villages offered a grant for seasonal migration, (ii) villages offered a zero-interest loan for seasonal migration, (iii) villages given information about migration and job opportunities and wages at the destination, ou (iv) a control group. Suivant, within each village, 19 poor households were randomly selected for the study, so that each of the 19 households living in the same village was assigned into the same RCT arm.6 In August 2008, those in the ﬁrst treatment arm were given information on popular migration destinations and their prevailing low-skill wages and offered a grant of Tk800 ($8.5)
conditional on the temporary migration of at least one household member in the
upcoming lean season. This amount was intended to cover the cost of a bus ticket
and a few days of food, and in our data, we ﬁnd that migrants spent on average
Tk450 on migration transport in that round and Tk529 when including food and
incidentals related to the journey (BCM 2014).7

There were no further restrictions to the grant, and beneﬁciaries could choose
the speciﬁc member(s) who would travel, the destination, the length of stay, et le
nature of their job search. For the majority of the sample, we also did not impose any
restriction on destination or the identity of travel companions. The second treatment
arm was similar to the ﬁrst, except that the disbursement was offered in August 2008
as a zero-interest loan rather than a grant. Repayment was expected upon return,
but forgiven in the case of failure to ﬁnd a job, though this latter feature was not
disclosed upfront. The third arm only received information on popular destinations
and prevailing wages using the same script as the ﬁrst two arms, while the control
group did not receive anything.

This RCT design helped us evaluate whether the treatments were successful
in encouraging more migration, which in turn allowed us to learn about
the constraints limiting seasonal migration. We found that the small subsidy
signiﬁcantly increased the migration rate from 36% in the control group to 59%
for those receiving the grant and 57% for those receiving the loan. The difference
between the latter two is not statistically signiﬁcant, while the average migration
rate remained at 36% in villages with the information-only treatment. From these
résultats, it appears that the relatively low rate of seasonal migration in the region,

6Eligibility was deﬁned as having less than 50 decimals (half an acre) of land and having skipped meals in

the previous lean season. Of the households in these 100 villages, 70% were considered eligible (BCM 2014).

7Migrants may have taken more than one trip or households may have sent more than one migrant, mais le
transfer amount is limited to Tk800 per household regardless of the number of trips. Calculating the overall cost of
living at destination is problematic, as over half of migrants in our study receive housing and/or meals from their
employer as part of compensation, ou, in the case of rickshaw drivers, may be given housing above the garage. Le
monetary value assigned to these beneﬁts differ by migrant, the quality of housing and food, and also from employers’
perspectives on the value of the beneﬁts they provide.

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Seasonal Poverty and Seasonal Migration in Asia 21

despite the availability of jobs in urban areas, was not due to a lack of information
about jobs—poor households either already know about the availability of jobs and
prevailing wages in urban areas, or this piece of information is not relevant to the
decision to migrate.

To study the effect of the program in subsequent lean seasons, we tracked
migration rates 1 et 3 years later, without repeating the intervention itself in
those villages. During the lean season a year later (2009), 47% of households in
villages where conditional subsidies (loans or grants) had been offered in 2008 sent
a seasonal migrant, which was signiﬁcantly higher than the migration rate in the
control and information groups. The migration rate in the grant and loan villages
was still signiﬁcantly higher (par 7 percentage points) than the control group even in
2011, the next year we collected data on this sample.

Using the randomized treatment as an instrument, we ﬁnd that households
that were induced to migrate through this program increased both food and nonfood
expenditures by 30%–35% relative to the control group, and consumed 550–700
more calories per person per day. This is equivalent to each person in the house
eating one additional meal per day, during a period when food is scarce and meals
are commonly skipped. Compared to the Tk800 transfer, households that sent a
migrant in response to the subsidy increased their consumption by Tk350–Tk400
per person per month (BCM 2014). In a context where migration lasts 2–3 months
and households have between four and ﬁve members, this represents a large rate of
return on the initial subsidy. Chiffre 3 illustrates how the subsidies work, enabling
households to send a migrant for temporary employment elsewhere in the country
and using the additional earnings to raise consumption and calorie intake.

Further analysis of our data indicates that poor families close to subsistence
were hesitant to invest in the uncertain returns to migration partly because they
were too risk averse. Even though seasonal migration is proﬁtable on average—as
indicated by the average gains in expenditures and consumption for households
that responded to the subsidy by migrating—any chance of migration failure
(par exemple., spending the money for transport but failing to ﬁnd a job, or at least one
that is worth the travel) can have devastating consequences for households living at
the edge of subsistence. Par conséquent, even with knowledge about average beneﬁts,
poor households may be unwilling to risk spending the little money they have on
migration. The migration subsidy acts as insurance against this downside risk,
protecting households from having to use their own money upfront to pay for
migration.

Further Exploration for Scale-Up

Results from the initial RCT show that providing ﬁnancial support for
seasonal migration has potential as a tool for addressing seasonal poverty. C'est
certainly cheaper to implement than work guarantee programs (which require

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Chiffre 3. Seasonal Migration Subsidies in Practice

Note: The subsidy amount has varied across rounds, depuis 800 taka to 1,500 taka ($8.5–$19, with variation in the
exchange rate over the years) to respond to rising costs in migration as well as improved knowledge on the actual
costs associated with migrating, which may include prepurchasing food for the family before migration.
Source: Figure was directly provided by Evidence Action.

paying beneﬁciaries for each day of work), owing to the fact that a one-time
transport subsidy allows beneﬁciaries to earn market wages on their own at
the destination. It is also more easily scalable considering the complexities of
program implementation: the number of potential direct beneﬁciaries depends on
the capacity of an institution to make subsidy disbursements but does not require the
creation and management of jobs and payments. The upper bound of scalability may
be constrained by the capacity of potential destination areas to absorb temporary
laborers.

But before declaring that support for seasonal migration should be scaled
up and implemented as a policy for addressing seasonal poverty in Rangpur or
other agrarian areas of Asia, the potential indirect effects and spillover effects of
this intervention demand some attention. To move from an RCT to a policy, it
is not sufﬁcient for an RCT to simply demonstrate positive effects on its treated
sample, particularly for a complex program that can in theory have repercussions
for other parts of the population. When considering implementing an intervention
as a large-scale policy, we must also look at the effect of the intervention on,
say, other poor households who are operating in the same labor markets and
competing for the same jobs. It is also important to understand any unintended
noneconomic consequences on social norms, political beliefs, or intrahousehold
decision-making. In contemplating a move from pilot-scale research to an

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Seasonal Poverty and Seasonal Migration in Asia 23

at-scale program, programmatic issues also arise or gain more importance, tel
as the incentives and constraints faced by funders and implementers and the
cost-effectiveness of the intervention. In the following subsections, we discuss these
additional areas we have studied, providing information on the potential of this
particular intervention as a scalable policy while also illustrating some issues that
come into play in the move from RCT to at-scale program.

Targeting and Welfare

The research described above focuses on the economic returns to migration,
but there is also the question of whether migration raises welfare more broadly. If
the extra income and consumption from migration comes at the cost of temporary
family separation, worse living conditions for the migrant in urban slums, or any
other negative experience stemming from migration, the effect of the subsidies on
the welfare of targeted households cannot be represented simply by their income
or consumption gain. Much of this “disutility” is difﬁcult to directly observe or
collect through survey questions. LMW (2018) use a simulated method of moments
approach to implement a model that allows for unobserved disutility and matches
this model to experimental moments generated from the same RCT reported in
BCM (2014). In the initial RCT described above (mis en œuvre dans 2008), roughly
80% of migrants experienced success at the destination in economic terms, but at
most 50% chose to remigrate in subsequent years. This gap between “success” (dans
terms of employment, revenu, and consumption) and the revealed preference of
remigration choices is informative about how large the unmeasured disutility must
have been, as a sizable portion of migrants who experienced success according to
our economic metrics nonetheless choose not to migrate again in a subsequent year.
The quantitative model in LMW (2018) matches these moments in the data to infer
the disutility and the net welfare gains from migration.

Through this method, LMW (2018) deduce that migration comes with
substantial disutility, and that the actual welfare gains from the subsidies are smaller
than the 30%–35% consumption increase observed through the experiment. Nous
validate this inference with discrete choice experiments on the same BCM (2014)
experimental sample, asking potential migrants to choose between migration and
stay-at-home options that vary in the (hypothetical) conditions associated with
the migration experience such as wages, the likelihood of ﬁnding work, living
conditions at the destination, and the length of family separation. We learn that,
of these dimensions, the quality of living conditions in the city is the component
of welfare that matters most to migrants. In this context, toilet type and access
serve as realistic proxies for living conditions, and we ﬁnd that having housing with
an indoor latrine (as opposed to public options) at the destination leads to a 17
percentage point increase in the reported propensity to migrate. This large effect
is equivalent to increasing destination wages by 21%, or increasing the likelihood

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24 Revue du développement en Asie

of ﬁnding work threefold. The clear policy implication is that governments should
invest in urban living conditions and improve housing and sanitation in slum areas,
as this would be valuable not only with respect to human rights and dignity but
also for its economic draw. In a survey of migrants working in construction jobs in
Dhaka, 71% report worse housing conditions at the destination compared to their
own homes in rural areas (Srivastava et al. 2014).

Given the disutility from worse living conditions, this model suggests
that potential migrants would only choose to leave when they are sufﬁciently
economically desperate and the situation at home is precarious. The LMW (2018)
modeling exercise allows us to learn about the types of households that are most
likely to respond to the migration support intervention and the conditions under
which they would choose to migrate in any given year. Understanding who exactly
this migration support program manages to target is an important component of
understanding the economic growth or welfare generated by this program.

It could have been the case that there are many rural workers who would fare
well in the city but who are “spatially misallocated” in rural Bangladesh because
they are not sure about their prospects in the city and do not travel as a result. Le
ﬁnancial incentive for migration would allow them to try out the urban labor market,
and those who then learn that they have a comparative advantage in the city become
repeat cyclical migrants or even permanent migrants. The results derived through
the LMW (2018) model suggest that this is not the case, likely because those with
a strong comparative advantage in the city are for the most part already there.

Plutôt, it is those who have experienced recent bad shocks but are hesitant
to draw down their small savings to make another trip (that may fail) that are
induced to migrate by the ﬁnancial incentive. The migrants from these households
are not necessarily a lot more productive in the city compared to the village, mais
the migration support program allows them to weather unexpectedly bad periods
by accessing jobs in urban areas. En tant que tel, this program does not generate much
economic growth, as workers are not generally spatially misallocated and moving
them does not create substantial changes to aggregate productivity. Plutôt, the value
of the program lies elsewhere: it offers a safety net to extremely poor households,
enabling them to cope with cyclical and idiosyncratic shocks.

This is also an efﬁcient mechanism for targeting support to such households.
The migration requirement acts as an ordeal that, in effect, aids in the selection
of households who really need to travel that year, due to dire circumstances or
an adverse shock they experienced at home. It is precisely through the disutility
of migration that the program is able to better target those who can beneﬁt from
migration but are unable to afford its risk, compared to other possible programs
we have discussed in this paper: (je) UCTs, which target participants much more
broadly—often based on ﬁxed assets—are vulnerable to leaks to the nonpoor
and cannot easily identify those who have faced recent shocks; (ii) agricultural
insurance, which typically targets richer, landed households; et (iii) weather index

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Seasonal Poverty and Seasonal Migration in Asia 25

insurance for landless households (Mobarak and Rosenzweig 2013), which can
only indemnify aggregate shocks and not protect households from uniquely harsh
idiosyncratic shocks.

Labor Market Spillover Effects in Sending Communities

As a migration support program is scaled up, with offers made to more and
more poor households, it may start indirectly affecting other poor households who
live in the same communities as program participants, but who may themselves
not receive the transfer or may not be able to send a migrant. In other papers, nous
investigate such “general equilibrium effects” of the migration support program
through labor market channels and risk-sharing channels in villages where the
program is implemented.

ACM (2017) report on an expanded trial

mis en œuvre dans 2014 que
randomized 133 study villages into three arms: (je) a high-intensity treatment in
which around 70% of eligible households were offered the migration subsidy
simultaneously (47 villages), (ii) a low-intensity treatment in which around 14%
of eligible households were offered the migration subsidy (48 villages), ou (iii)
a control group (38 villages).8 This setup creates ﬁve types of study households:
(1) offered a subsidy in villages where many others were also offered the subsidy;
(2) offered a subsidy but residing in a village where few others were offered the
same subsidy, (3) not offered the subsidy but in a village where many others were
offered the subsidy, (4) not offered a subsidy and in a village where few others were
offered a subsidy, et (5) not offered a subsidy and in a village where no one was
offered the subsidy either.

The ACM (2017) analysis reveals strong network effects in migration
decisions: while households in low-intensity villages who were offered the subsidy
sont 25 percentage points more likely to migrate than the control group, those in
high-intensity villages who were offered the subsidy are 40 percentage points more
likely to migrate. The difference between these groups is statistically signiﬁcant,
and both represent a very large jump in migration rates from a mean of 34% for the
control group (type 5 households). Notably, even those who were not offered the
subsidy directly but who reside in high-intensity villages (type 3 households) sont
10 percentage points more likely to send a migrant relative to households in control
villages.

Migration decisions therefore appear to be strategic complements, as one is
more likely to migrate if others within one’s network are also migrating. Plus loin
analysis reveals that connections matter, as migrants frequently travel in groups
with others from the same village. An operational implication of this ﬁnding is that

8Eligibility criteria remained the same as in the previous RCT rounds: households who own less than 0.5

acres of land and reported hunger (c'est à dire., at least one member skipped meals) in the previous year’s lean season.

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26 Revue du développement en Asie

a program offering migration subsidies in this context will be more cost-effective by
targeting many people concentrated in fewer villages rather than few people spread
out across many villages, taking advantage of the positive spillovers within villages
and networks in migration decisions.9

ACM (2017) also document a positive spillover on households residing in
the same village who do not send a migrant. For every 10 percentage point increase
in the emigration rate, agricultural wages in the village rise by an average of 2.2%.
This beneﬁts agricultural workers who do not migrate as well as migrants during
the weeks of the lean season when they are home. The real effects of the program
sont, cependant, slightly smaller, as food prices also increase by 0.9% for that same 10
percentage point increase in the emigration rate. This rise in the food price index
is largely driven by a rise in the local price of ﬁsh, as families with (réussi)
migrants increase their protein consumption, particularly by consuming more ﬁsh
(BCM 2014).

Risk-Sharing Spillover Effects in Sending Communities

the same informal

While ACM (2017) focuses on spillover effects through labor market
chaînes, in a separate study (Meghir et al. 2017), we look at how a migration
support program may affect local risk-sharing networks, particularly for households
risk-sharing network as program
that are members of
beneﬁciaries and reside in the same villages. En théorie, migration could erode these
informal risk-sharing networks, as migrants who are exposed to a new labor market
opportunity may choose to self-insure instead and exit the network. Plus généralement,
even if the drastic outcome of network exit does not happen, other members
may need to offer migrants a larger share of the risk-sharing pie to keep them
interested in participating in the network. In this sense, migration subsidies could
have a negative spillover effect on nonbeneﬁciaries. Inversement, the new migration
opportunity may improve risk sharing in the aggregate across the network, par
providing some members of the network a new income stream that is less correlated
with the village income stream. The network’s sources of income as a whole become
more diversiﬁed, and aggregate risk sharing improves.

Using a structural model on our panel data of migrants across four rounds,
the paper by Meghir et al. (2017) ﬁnds that the latter effect dominates: migration
opportunities not only weaken the link between own income and own consumption
for those who migrate, but they do so for others in the village as well. C'est,
program villages exhibit higher levels of risk sharing after the treatment compared
to control villages. Household consumption levels for both migrant and nonmigrant

9To optimize cost-effectiveness, this consideration can be balanced against coverage of inframarginal
households who would migrate because neighbors receive a subsidy and do not really need a subsidy themselves
to be induced.

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Seasonal Poverty and Seasonal Migration in Asia 27

households in program villages become less volatile and less dependent on the
household’s own income. Households evidently diversify their income through
migration and choose to remain in the network, consequently sharing the beneﬁts of
this diversiﬁcation with other households in the village. This is a positive spillover:
both direct beneﬁciaries and other village residents are better able to smooth their
consumption through migration opportunities.

Noneconomic Effects of Migration: Changes to Social Norms

It has been documented that the permanent movement of people over long
distances changes social or behavioral norms—or both—among both migrants
and their host communities through pressures such as assimilation, adoption,
and backlash (World Bank 2011). In northern Bangladesh, seasonal migration is
generally characterized by the migration of just one member while the rest of the
family stays home. Most of these temporary migrants are male heads of households
(over 80% of all migrants in our sample) who are away for 2–3 months at a time, et
the majority of households are nuclear, with only two adult members. During their
absence, migrants may be exposed to different lifestyles, norms, ideas, and ideals,
which could in turn transform their beliefs and actions once they return home. À
the same time, during this period, women in nuclear households may take on more
decision-making roles with respect to the family and the home, a shift that can also
in theory have a persistent effect on the way the household is managed even once
the migrant is back.

We explore these possible changes in a study by Mobarak, Reimão, et
Thachil (2018) and ﬁnd that migrants do become more progressive in their beliefs:
individuals offered migration subsidies in treated villages become 2 percentage
points more likely to recognize that women are capable of managing a household on
their own, an effect best attributed to wives (or other female household members)
effectively taking on that role during a male migrant’s absence (as opposed to
migrants simply observing other women outside the family doing so, either in
destination areas or in one’s village with heightened male out-migration). Quand
migrants are away, there is also a substantial shift in decision-making roles. While
men clearly dominate decision-making when they are at home, the proportion of
women reporting that they participate (alone or jointly) in decisions regarding
household expenses triples for periods in which the migrant has traveled away.
These changes in beliefs and experiences are statistically signiﬁcant even after
adjusting for multiple hypothesis testing. Individuals in treated households also
tend to take on some other more progressive views with respect to society, tel
as agreeing with the notion that governments should address income inequality and
rejecting vote buying by political parties.

These changes, cependant, do not appear to translate into a difference in actions
when migrants return home. Even though women take on additional responsibilities

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during the male migration period and migrants are more likely to recognize
women’s capabilities upon their return, there are no signiﬁcant differences between
treatment and control villages with respect to women’s participation in household
decisions—including those regarding their own physical mobility outside the
house—once migrants return. We also see no difference in the use of social services
or in civic participation, or in behaviors tied to gender norms, such as female
labor force participation or expenditure allocations. It appears that, in this setting,
le (perceived) social costs for deviating from the social norm are so high that
migrants do not change their behavior even after adopting more progressive beliefs
(Mobarak, Reimão, and Thachil 2018).

While it is disappointing that we do not see any positive effect of seasonal
migration toward more progressive and inclusive behaviors, it is also reassuring
that we do not detect any negative effects, such as the deterioration of norms or
a backlash. We observe these (non) effects in the short run (a few months to 2
years after offering migration subsidies), and it remains to be seen whether the
observed changes in beliefs translate into broader changes in social norms regarding
women’s role in society as momentum builds and individuals learn about each
other’s (transformed) beliefs (Bursztyn, González, and Yanagizawa-Drott 2018;
Dhar, Jain, and Jayachandran 2019).

Effects on Intimate Partner Violence

Dans 2015, the Bangladesh Bureau of Statistics carried out a survey on
violence against women, uncovering that 75% of women in rural Bangladesh have
experienced some form of intimate partner violence (IPV) in their lifetime, et
28% experienced physical or sexual violence in the 6 months prior to the survey
(Bangladesh Bureau of Statistics 2016). Mobarak and Ramos (2018) explore how
subsidies to seasonal migration affect the likelihood of IPV in practice, particularly
in light of the various forces through which seasonal migration can inﬂuence IPV
in theory.

There are three competing forces shaping the potential effect of migration
on IPV. D'abord, limited resources can raise conﬂict within the family, en particulier dans
contexts with traditional gender roles, where men are expected to provide most of
the ﬁnancial support for their family and failure to do so can be seen as failure in
a broader social role. Poor households facing seasonal ﬂuctuations in income may
be particularly vulnerable to this type of conﬂict. A positive income shock through
migration (and its subsidy) may reduce these poverty stressors and, with it, decrease
the incidence of violence.

Alternativement, increases in male income can strengthen their bargaining
position, increasing female relative vulnerability and, potentiellement, susceptibility to
violence. Dernièrement, reducing the time a woman spends with her potential perpetrator
can itself decrease the risk of victimization. Since migrants are overwhelmingly

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Seasonal Poverty and Seasonal Migration in Asia 29

male in Bangladesh, subsidies that encourage migration can effectively decrease
women’s exposure to their spouses—and potential abusers—mechanically leading
to less overall IPV experienced by women in treated households.

Using data from the 2017 RCT and focusing on the effect of the migration
of married male heads of households, Mobarak and Ramos (2018) ﬁnd evidence
that subsidies to migration may decrease IPV, particularly by reducing women’s
exposure to their male heads of households. Relative to the control group, femmes
in households who are offered the migration subsidies are 3.5 percentage points
less likely to say they have experienced physical or sexual violence in the 6 mois
prior to the survey (un 10% decrease in incidence). The results are most consistent
with the idea that seasonal migration has an additional mechanical beneﬁt, giving
women some temporary relief by physically separating them from their perpetrators.
Whether this produces any persistent reductions in violence beyond the period of
migration, including perhaps through a shift in gender norms over time, is still an
open question.

Long-Term Effects on Permanent Migration

In Chowdhury, Mobarak, and Reimão (2018), we explore whether seasonal
migration leads to permanent migration—as migrants build networks in and gain
familiarity with the city—or instead makes rural living more viable and permanent
moves into the city less likely. For this analysis, we use a follow-up survey of all
households included in the 2008 étude, gathering information on the whereabouts
of each member 8 years after the initial treatment. Household members or, dans
their absence, their neighbors were interviewed, producing a dataset with very low
attrition—we do not know the migration status of less than 1% of households.

Dans l'ensemble, we ﬁnd relatively low levels of permanent out-migration from rural
Rangpur in general. Over an 8-year period (2008–2016), only 5% of households
in the BCM (2014) sample (aggregating across treatment and control villages)
permanently migrated away from their home village. This is consistent with other
district-level data that document comparatively low levels of out-migration from the
northern part of Bangladesh, particularly relative to the southeast (UNFPA 2016).10
De plus, it is no more difﬁcult for us to ﬁnd the original 2008 sample
households from the treatment villages than it is to ﬁnd those from the control
villages, or to learn of their whereabouts. There is also no signiﬁcant difference
in the likelihood in permanent migration of the household or one of its members
between treated and control villages. The data are precise enough to rule out large
effects: the seasonal migration subsidies induced at most one in 200 households to
permanently migrate over an 8-year period after the offer.

10Compare, Par exemple, a lifetime net migration (in-migration minus out-migration) of –39.49 per 1,000

people in Rangpur to –167.22 per 1,000 people in Barisal (UNFPA 2016).

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30 Revue du développement en Asie

For the subsample of households that were primarily engaged in agriculture
at baseline, the subsidies actually decreased their likelihood of permanent migration
relative to the control group, with households in treated villages 3.8 percentage
points less likely to permanently leave the area than those in control villages.11
This indicates that, rather than serving as a gateway to permanent migration,
seasonal migration actually makes living in rural areas more viable in the long
run, particularly for households whose skills and experience are in agriculture.
For households with a comparative advantage in agriculture, a one-time support
for seasonal migration helps them draw on it as a coping strategy in subsequent
years and thereby avoid the more costly and drastic coping strategy of permanent
migration. For policy makers in Bangladesh concerned about overcrowding and
congestion in Dhaka and other populated urban areas, this ﬁnding implies that
supports for seasonal migration may be a tool for easing urban pressures that come
from permanent rural-to-urban population inﬂuxes.

Other Open Questions

In contemplating the implementation of a migration support program at
this scale or larger, one must also be aware of the spillover effects on poor
households in destination areas—and potentially other rural villages. We designed
the most recent implementation rounds (2017 et 2018) to capture these economic
and noneconomic spillover effects, as loan offers are made to well over 100,000
households in each season (compared to fewer than 1,500 dans le 2008 étude).

We initially expected the 2017 results to provide some information on
general equilibrium effects, revealing the effect of seasonal migration subsidies
on the employment prospects and earnings for would-be construction workers
and rickshaw drivers (two of the most popular jobs for seasonal migrants in
our research rounds when they reach urban areas) already living in destination
domaines. Malheureusement, cependant, le 2017 intervention did not lead to a statistically
signiﬁcant effect on migration, contrary to all previous rounds. This was likely
due to a conﬂuence of factors—both avoidable and unavoidable—such as having
disbursement targets for each migration ofﬁcer set too low, heavy workloads, et
the worst ﬂooding in the region in over 40 années (for more information, see Levy
and Sri Raman 2018).12 To better understand these results and to learn about the
effect of seasonal migration subsidies on poor households outside target villages,
le 2018 round was implemented with a very similar design as the previous
year—though of course addressing some of the weaknesses encountered in 2017.

11Deﬁned as having a plurality of workers within the household indicating agriculture as their sector of

employment.

12Migration ofﬁcers are the local implementers who make loan offers, disburse the loan, check on migration,

and collect repayment.

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Seasonal Poverty and Seasonal Migration in Asia 31

Chiffre 4. Cumulative Weekly Disbursements in 2017 et 2018

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EID = Eid al-Adha.
Note: Training was completed, and eligibility screening and applications were processed in some villages before
the Eid al-Adha holiday. No activities were planned around the holiday, and disbursements were scheduled to start
immediately after.
Source: Figure was directly provided by Evidence Action.

The administrative data reﬂects these changes: while the implementing organization
(Rangpur Dinajpur Rural Service [RDRS] Bangladesh) disbursed just over 40,000
migration loans during the 2017 lean season, this ﬁgure was close to 90,000 loans
dans 2018 (Chiffre 4).

Although we do not yet know the effect of the 2018 intervention on the
seasonal migration of those in treated villages, we do expect the impact of these
subsidies, even at over 85,000 direct beneﬁciary households, to be relatively small
on residents of popular destination areas, particularly Dhaka. In the past rounds,
migration destinations were quite varied, with less than 25% of all migrants
traveling to Dhaka, even though it is the single most popular destination for
migrants from Rangpur (and elsewhere in the country).

Dhaka is home to 14 millions de personnes, so even if one-quarter of all loan
recipient households send a migrant to the megacity, this would amount to less than
0.2% of its regular population. Nevertheless, it is possible that while this inﬂux
is negligible for the general population in Dhaka, individuals engaged in particular
sectors popular with migrants—namely, construction and rickshaw pulling—do feel
an effect, positive or negative (depending on whether seasonal migrants’ labor
are complements or substitutes to local labor). We expect the results from the
2018 intervention to provide more information on this potential spillover effect

32 Revue du développement en Asie

on destination workers, which becomes relevant as we move from pilot to at-scale
program.

Another consideration relates to the effect of seasonal migration on
agricultural employers. We have found that, in the short run, inducing temporary
migration out of rural areas increases local agricultural wages (ACM 2017).
While this is beneﬁcial to poor rural workers who do not migrate (ainsi que
those who do migrate on the weeks they are home), it also imposes a cost on
agricultural employers in the same villages, who must now offer higher wages to
secure the labor they need. In the short run, this results in a pecuniary transfer
from comparatively richer employers to poorer employees, reducing inequality in
treated areas. Cependant, landed employers are also more likely to be a politically
powerful group, so that their losses can potentially pose a risk to the sustained
implementation of this intervention. They may also choose to shift toward more
labor-saving technology, with both theoretically positive and negative consequences
for local residents. In Nepal, we are planning to test a way to guard against negative
political risk, by designing an RCT that offers agricultural employers subsidized
access to a labor-saving technology in the same villages where migration subsidies
are provided. By conducting an intervention that deals with demand and supply
simultaneously, we expect to learn about labor market interactions as general
equilibrium effects come into play in response to the subsidies.

Comparisons to Other Programs

A program offering seasonal migration subsidies is one among several
potential antipoverty interventions, and a part of our research agenda has been
designed to study its merits and effects relative to other interventions in this group.
Through an RCT in Indonesia (Bryan et al. 2018), we directly compare the effects of
migration subsidies to a UCT of an equivalent amount. The results from this RCT
implemented in West Timor (Nusa Tenggara Timur province) dans 2017 reveal that
only 13% of households who are offered the UCT migrate in the 6 months following
disbursements, compared to 42%–46% when the transfer is made conditional on
migration. The lower effect on migration from the UCT is not in itself surprising,
but highlights the fact that lack of funds is not the only (or even main) factor limiting
households’ migration decisions.

LMW (2018) take a completely different route for comparing effects
between subsidies for seasonal migration and UCTs, combining data from
the 2008–2011 interventions with a structural model to simulate effects. Le
simulations indicate that a UCT of the same amount as the migration subsidies
would increase migration by less than 1% among poor households in Rangpur, et
its welfare beneﬁts for the poorest quintile of households would also be slightly
lower. The simulations indicate that a one-time migration subsidy improves welfare
(measured as consumption over a lifetime) of the poorest quintile by 1%, whereas a

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Seasonal Poverty and Seasonal Migration in Asia 33

budget-neutral UCT program would improve it by 0.9%. This difference is driven
by the fact that migration subsidies rely on self-targeting: only households who have
faced negative shocks and are desperate for money take up the CCT and migrate,
while the UCT transfers are applied uniformly to all households. In contrast to these
two policies, a rural workfare scheme increases welfare of the poorest quintile by
only two-thirds as much, ou 0.6%, as it discourages households from migrating to
locations that offer better wages.

We have also directly compared the cost-effectiveness of seasonal migration
subsidies to other existing transfer programs in Bangladesh using secondary
information, as discussed in subsection II.B. As with seasonal migration subsidies,
the majority of beneﬁciaries for each of the three existing pro-poor programs (food
transfer, food and cash transfer, and guaranteed work) are in the bottom three
income deciles. Ahmed et al. (2009) estimate that the food transfer (IGVGD) et
the food and cash transfer (FSVGD) programs each increase consumption by ﬁve
times as much as the workfare program per dollar spent. By our calculations,
the seasonal migration support program is even more cost-effective, increasing
consumption on a per-dollar-spent basis by almost twice as much as the food and
cash transfer program, which is the most cost-effective of the three (Mobarak and
Akram 2016). And disbursing the offers as zero-interest loans rather than grants
(which can be recovered and reused for the program in subsequent years) makes
seasonal migration subsidies three times as cost-effective as the food and cash
transfer program.

IV. Implications for Asia

For the last 10 années, our research on seasonal migration has been primarily—
though not exclusively—in Rangpur,
the most rural division in Bangladesh
(UNFPA 2016). The potential for this intervention to improve the welfare of poor
rural households vulnerable to seasonal ﬂuctuations in agricultural income and
employment opportunities, cependant, evidently extends well beyond the area, into
other parts of Bangladesh and the Asia and Paciﬁc region more broadly. Dans ce
section, we discuss requirements and adaptations for seasonal migration subsidies
as a concept and as a program, as well as the importance of context—in terms of
both time and place—for its viability.

UN.

Applicability and Adaptability

Subsidies for seasonal migration may be relevant to many subnational areas
throughout the Asia and Paciﬁc region. En général, for such an intervention to have
potential as a tool for addressing seasonal poverty, target settings must have three
minimum characteristics:

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34 Revue du développement en Asie

(je) An agricultural lean season. Recurring and predictable periods of hunger
indicate that there are constraints that keep consumption and income tied too
closely together and that existing coping mechanisms and support systems
are not adequate for weathering drops in income.

(ii) Households that ﬁnd spending on migration risky. Supporting seasonal
migration makes sense if there is a large rural population living close to
subsistence and for whom spending money on migration but failing to earn
enough to offset costs could be catastrophic. Seasonal migration subsidies
lower the cost of failure to ﬁnd a job in destination areas and enable would-be
migrants to set aside money or goods as a cushion for their families prior to
migration.

(iii)

Jobs available in nearby areas. Ideal conditions include the availability of
employment opportunities in several urban areas 4–8 hours away. For any
distance closer than this, rural residents can commute and probably do so,
and larger distances may require much higher subsidies. The existence of
multiple destination areas also makes it more likely that an increased inﬂux of
migrants can be absorbed without large impacts on the target labor market(s).

Many rural areas around the world match these conditions, though not all.
We conducted exploratory work for a potential replication in Malawi and Zambia,
Par exemple, but decided not to test the program further in either setting because
we were not convinced that they met the third condition. It is not clear that either
country has vibrant urban labor markets with labor demand that can absorb many
domestic migrants.

Plutôt, we chose to pilot and test a version of this intervention in West
Timor, Indonésie, a setting where most poor households in rural areas are not
landless (as is the case in Rangpur). This changed one fundamental aspect of the
program design. During the preharvest period, poor rural household members in
West Timor generally have to stay home and work on weeding and land management
of their own farm and are not interested in migrating at that time—even though,
like in Bangladesh, that is the period of seasonal deprivation. In response to this,
we adapted the intervention to allow for migration in other periods. Although poor
households have relatively more cash after a harvest, this period tends to also be best
for migration among landowning poor households since there is little agricultural
work to be done. In this study site, landowning migrants traveled after the harvest,
aiming to save money in anticipation of the next lean season.

When considering the implementation of migration subsidies in a new
contexte, there may be other norms and processes that need to be accounted for as
well, such as the prevailing labor migration arrangement. Par exemple, a survey of
construction workers found that in Bangladesh, only 10% of workers that secured

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Seasonal Poverty and Seasonal Migration in Asia 35

a job through a contractor received any payment in advance, whereas 52%–80% of
workers in India received advance payments. These advances facilitate migration,
helping migrant households purchase goods to be left at home and guarantee some
consumption during migration (Srivastava et al. 2014), and may change the role
of transfers or the amount required for migration subsidies. A migration support
program in India may also affect welfare along a different margin: wages for
workers who secure jobs at destination areas tend to be higher than for those who are
recruited and receive advances from contractors, so that a migration subsidy may
serve as an alternative to the use of contractors, enabling individuals to arrange their
travel ﬁrst and search for a higher-paying job upon arrival at their destination.

Nevertheless, it is clear from our experience in Indonesia that subsidies for
seasonal migration are viable solutions outside of Rangpur and that the program can
be adapted to a certain extent to local conditions. Dimensions over which seasonal
migration subsidies could be modiﬁed to account for circumstances include—but
are certainly not limited to—transfer amounts, timing, modality (par exemple., loans, subventions,
or even transport tickets), number of members to whom subsidies are made, et
even the extent to which the program works with employers or contractors and
facilitates hiring in advance. Some of these modiﬁcations are more drastic than
others, and a few might require piloting and further testing, but none alter the
fundamental nature of the concept, which is to support and subsidize the temporary
movement of people from rural areas to destinations where there are more job
prospects for low-skilled workers.

Limitations

Drawing a distinction between subsidies for seasonal migration (le concept)
and “No Lean Season” (the program), we recognize that while the former has
a broader potential and applicability than the latter, neither is implementable
partout. Not only are seasonal migration subsidies likely not a worthwhile
investment in settings where one of the three requirements above are not met, mais
the extent to which subsidies can induce migration is highly context dependent.

Dans 2013, we attempted to implement the ﬁrst version of “No Lean Season”
after the positive results of the initial RCT on seasonal migration. That same
année, cependant, mass political strikes (hartals) “designed to disrupt the county’s
transportation network” and that involved the burning of buses (the main mode of
transportation used by migrants from Rangpur) took place throughout Bangladesh
(Ahsan and Iqbal 2016). As one of the main goals of this form of protest was
to “restrict vehicular movement in key urban areas,” it naturally led to longer
transport times and higher costs during that period, not to mention fear among the
population in and outside the cities (Ahsan and Iqbal 2016). While the lack of take-
up in response to our migration subsidy offers under these conditions might not
be surprising in hindsight, it also points to an implementation challenge for such

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36 Revue du développement en Asie

a program. As strikes are often unpredictable more than a few weeks in advance,
implementation of the program—from contracting to loan offers—may already be
underway when it becomes clear that circumstances will limit take-up.

We witnessed a similarly low take-up in 2017 and suspect that extreme
ﬂooding in northern Bangladesh—the likes of which had not been seen in 40
years—contributed to this pattern. In Rangpur, the yearly swelling of rivers can
lead to houses or entire villages being swept away, but that year’s uniquely severe
ﬂooding made implementation of the program especially difﬁcult and may have also
discouraged seasonal migration, as potential migrants cannot abandon their families
under likely disastrous weather conditions, and transport may be more limited or
précaire.

External shocks such as extreme weather conditions and violence impose
limitations on the applicability of seasonal migration subsidies as a concept,
indicating that even in settings where the intervention would normally work, it
might not work in certain years, no matter the design. This is distinct from—and
in addition to—programmatic limitations related to implementation capacity and
delivery.

In the transition from a closely delivered and monitored RCT during 2008–
2011 to “No Lean Season,” the implementation of the program was handed over
to a local partner, RDRS Bangladesh, a microﬁnance institution. We have learned
that its decades of experience in microﬁnance and in the region are both a beneﬁt
and a hurdle, as its managers and ofﬁcers are used to thinking in terms of loan
disbursement and repayment and its institutional measurements are tailored around
that model. But if one were to implement “No Lean Season” as a pure microcredit
program, it would make sense to focus efforts on individuals most interested in
migrating and most likely to repay—not necessarily those who recently experienced
a drastic negative shock. While we believe that ﬂooding played a role in the
2017 migration rates, we suspect that part of this dampened result also stemmed
from targeting issues, as migration ofﬁcers were given disbursement goals by their
managers and may have concentrated their efforts on households most likely to
migrate anyway. In response to these ﬁndings, RDRS Bangladesh changed the
goals set for its ofﬁcers in 2018. Most recent loan disbursements show a promising
changement, with twice as many loans made per branch compared to the previous year
(Chiffre 4).

It is also worth noting that, while the intervention in Bangladesh has
been transformed into “No Lean Season,” migration subsidies can in theory
be implemented not only outside this program but also without an NGO or
microﬁnance institution entirely. The concept could be taken on by national or
subnational governments for whom cost–beneﬁt calculations may weigh differently.
A program that might not be feasible from the perspective of an NGO, lequel
typically requires a minimum impact per dollar, may nevertheless be worthwhile
to a government for its beneﬁt to the rural poor in addressing seasonal deprivation.

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Seasonal Poverty and Seasonal Migration in Asia 37

V. Conclusion

The last 10 years of research on seasonal migration has shown that an
intervention that supports this strategy by subsidizing travel can have large positive
impacts on poor rural households. In several study rounds conducted in northern
Bangladesh, households that were offered a small migration subsidy were 22–40
percentage points more likely to migrate over a given lean season compared to
control households. Households that responded by sending a migrant also recorded
on average higher levels of consumption, revenu, and expenditures during the
lean season than those not offered the subsidy. Villages in which a large share of
poor households were offered the migration subsidies also experienced an increase
in wages during this period, which is usually characterized by low employment
opportunities and pay. A one-time migration transfer continued to have a positive
effect on migration rates up to 3 years later.

We believe that this type of intervention may be an appropriate tool for
poverty alleviation—particularly seasonal poverty—in rural areas where a large part
of the population (both in relative and absolute terms) is engaged in agriculture and
lives close to subsistence for at least part of the year and where potential destinations
with ample low-skill temporary employment opportunities are within a reasonable
travel time (4–8 hours). The complete lack of seasonal migration is not a required
element, as exempliﬁed in Rangpur, and potential beneﬁciaries are not restricted to
traveling to destinations 4–8 hours away. Among migrants in our study in northern
Bangladesh, Par exemple, migration is already fairly common (but still lower than
expected given the availability of jobs elsewhere in the country), and Dhaka is a
popular destination despite being a day’s travel away. In India, temporary migrants
are just as likely to migrate to urban centers within their state as to other states,
and they are actually less likely to migrate within their district (Imbert and Papp
2019).

There are other programmatic requirements for the success of a migration
subsidy intervention, a topic that we have not covered in depth here. Local
implementation capacity and political support are likely crucial. In Rangpur, notre
intervention has been implemented through RDRS Bangladesh, a local institution
with a strong presence and long history in the northern part of the country since
2014. In Indonesia, we have experimented with collaborating with local government
agencies. En général, the nature of the implementing partner (par exemple., local NGO,
international organization, or government) may be less important than its capacity,
will, and presence in rural areas, as the design of the intervention offers some
ﬂexibility to adapt to an implementer’s priorities and requirements.

Our research results also highlight the importance of removing other types
of barriers to temporary migration. The PRC, Par exemple, imposes many explicit
restrictions on the movement and employment of rural workers. Other countries in
the region also have policies that implicitly deter poor rural households from taking

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38 Revue du développement en Asie

advantage of urban labor markets. In India and Viet Nam, Par exemple, full access
to social safety nets is given only to individuals at their permanent residence area
(Deshingkar 2006), which limits poor households’ willingness to send a migrant
away in search of jobs elsewhere lest they lose beneﬁts at home.

Encouraging seasonal migration is a complex intervention that may produce
a range of indirect effects and unintended consequences beyond the direct economic
effects on treated households. Over the last 10 années, our research agenda
has expanded from considering the effect of these subsidies on the migration,
consommation, and income of targeted households to exploring the secondary
effects on both beneﬁciaries and nonbeneﬁciaries, with scaling up always in mind.
Results from the initial RCT in Bangladesh with 1,900 households only indicated
that this intervention was “promising.” The path from a successful RCT to an
implementable program called for a greater understanding of potential general
equilibrium, noneconomic, and long-term effects.

The majority of the population in Asia remains rural and agrarian. Support
for seasonal migration can play a valuable role in helping poor rural families cope
with drops in employment opportunities and income during lean periods in the
agricultural cycle. The Asia and Paciﬁc region has a uniquely large concentration
of poor households in rural areas, but it is also peppered with large urban areas
and manufacturing zones that have attracted both domestic and regional migrants.
While the applicability of seasonal migration subsidies may vary across and within
countries—depending on the dominance of the agricultural cycle, proximity of
poor households to potential destination areas, and the ability of an area to absorb
temporary migrants—the basic elements of demand for this intervention exist in
many parts of the region today.

Lowering the barriers to temporary migration—through changes in policies
(either explicit or implicit), investment in transportation networks, or subsidies, or a
combination of these—can expand poor rural households’ access to labor markets
elsewhere in their countries. And while encouraging seasonal migration might not
be a path to growth in contexts where migration is already common and rural
residents are unlikely to be spatially misallocated, facilitating the free movement
of people within their own countries—enabling them to take advantage of labor
opportunities elsewhere and to avoid resorting to hunger—is a desirable pursuit in
its own right.

Poverty reduction in Asia has been associated with diversiﬁcation away
from farm activities—of which employment opportunities in urban areas is one
possibility—as opposed to increasing farm productivity (World Bank 2012).
Policies that support seasonal migration can help steer countries down that path,
encouraging poor rural households to diversify their income sources and increasing
labor supply for sectors with higher-productivity potential than agriculture. En fait,
seasonal migration may be a valuable but temporary tool. As countries develop,
transportation networks improve, and nonagricultural employment opportunities for

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Seasonal Poverty and Seasonal Migration in Asia 39

rural residents expand at home, the need for seasonal migration as a coping strategy
might decrease. Until then, supporting seasonal migration—through direct policies
or interventions such as “No Lean Season,” or both—can help address seasonal
poverty and hunger in various parts of the region.

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3 Seasonal Poverty and Seasonal image

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