Work Migration and Poverty Reduction in Nepal

Michael Lokshin, Mikhail Bontch-Osmolovski, Elena Glinskaya

DECRG-PO and SASPR

The World Bank

Country background

Poorest country of South Asia Per capita GDP $240 ($1,420 PPP) Maoist Insurgency and political instability Diminishing export markets, difficult economic

situation ButBut Between 1995 and 2004 poverty declined

from 42 to 31 percent Per capita expenditure grew 40 percent in

real terms

Why?Why?

Work migration and remittances

Increase in work migration and remittances About 1M prime age males work outside

Nepal The proportion of households receiving

remittances has increased from 24 percent in 1995 to 32 percent in 2004

Remittances grew at 30% per year, from 3% of GDP in 95 to 15% of GDP in 04

Official statistics: $1 billion comes in Nepal as remittances. Unofficial statistics: even larger

Migration and remittances in Nepal

The history of Nepal foreign employment dates back almost 200 years. Gurkhas.

The Foreign Employment Act of 1985 officially recognized the benefits of “overseas” migration.

Labor migration from Nepal extended from India to the countries of Southeast and Far East, and to Arab countries of the Gulf.

Internal migration: predominantly rural-to-rural migration is twice as large as rural-to-urban migration. Mid-West and Far-West experienced net out-migration. Maoists insurgency. Malaria.

Research on effects of migration and remittances on poverty

The empirical research of the impacts of work migration and remittances on poverty and inequality is limited.

Most studies indicate that increase in remittances leads to decline in poverty. Lesotho (Gustafson and Makonnen 1993); Egypt (Adams 1995); Nicaragua (Barham and Boucher 1998); Uganda, Bangladaash, Ghana (Adams 2005); China (Yang et al 2005)

No formal studies for Nepal. Few mostly descriptive works by the local researchers.

Our paper provides the first formal evidence of the impact of work migration and remittances on income distribution in Nepal.

Data

Use two rounds of Nepal Living Standard Survey (NLSS).

First round June 1995- June 1996; 3,373 households in 274 PSU’s

Second round April 2003-April 2004; 3912 households in 326 cross-sectional and 95 panel PSU’s.

2001 Nepal Census data

Table 1: Percent of households receiving remittances by regions of Nepal and total Receive remittances

from Nepal Receive remittances

from abroad Receive any remittances

1995/96 2003/04 1995/96 2003/04 1995/96 2003/04 Regions Kathmandu 14.3 7.8 3.6 5.7 17.9 13.5 Other urban areas 13.1 17.1 6.0 14.3 19.2 31.3 Rural West mount/hills 10.6 11.1 19.6 29.4 30.2 40.4 Rural Eastern mount/hills 11.1 16.9 2.0 9.3 13.1 26.2 Rural western Terai 12.0 12.6 10.6 19.2 22.6 31.8 Rural eastern Terai 14.7 14.6 11.0 18.1 25.7 32.7 Land holdings a year ago. No farm plot 11.3 14.8 10.2 13.2 21.4 28.0 Farm plot < 0.5 ha 13.1 14.3 11.7 18.5 24.7 32.8 Farm plot 0.5-1 ha 11.7 11.7 10.7 20.0 22.5 31.8 Farm plot: 1-2 ha 12.8 13.7 11.4 17.5 24.2 31.2 Farm plot > 2 ha 11.9 17.3 6.2 18.3 18.1 35.6 Caste Brahman \ Chhetri 13.4 15.8 11.1 19.9 24.5 35.7 Dalit 12.0 9.8 15.1 24.7 27.0 34.5 Newar 13.2 14.3 3.6 7.8 16.8 22.1 Terai-Hill Janajatis 9.8 14.6 9.4 15.4 19.2 30.0 Muslim \ Other Minorities 13.1 12.1 11.4 18.3 24.4 30.3 Total 12.3 13.9 10.6 17.7 23.0 31.6

Mean

0

.1

.2

.3

.4

.5

.6

.7

Pro

port

ion

of

hou

seho

ld r

eceiv

ing r

em

itta

nces

1 2 3 4 5 6 7 8 9 10 11 12+

Any remittances

Foreign remittances

1995

Mean

0

.1

.2

.3

.4

.5

.6

.7

1 2 3 4 5 6 7 8 9 10 11 12+

2004

-5

0

5

20

35

50

60

Tota

l am

ount

of

receiv

ed r

em

itta

nces,

if

recie

ved,

00

0s

1 2 3 4 5 6 7 8 9 10 11 12+

Household size

1995

-5

0

5

20

35

50

60

1 2 3 4 5 6 7 8 9 10 11 12+

Household size

2004

0

1

.12

.35

Pro

babi

lity

of re

ceiv

ing

rem

ittan

ces

3 6 9 12 14Log of Lagged Asset Index

Incidence of Receiving Remittances

95% confidence interval

0

100

200

300

Rs

2003

, 000

's

3 6 9 12 14Log of Lagged Asset Index

Average Remittances

Average Positive Remittances

95% confidence interval

Non-parametric regression of incidence of migration and amount of remittancesby lagged asset index

Work Migration and Remittances Q1: What is the impact work migration? Q2: What is the impact of remittances? A1: Compare the current expenditure distribution with the

counterfactual distribution of less(no) migration (that also means no remittances). Counterfactuals: household with a migrants – similar household with no migrate.

A2: Compare the current expenditure distribution with the counterfactual distribution of no remittances. Counterfactuals: household with migrant who sends remittances – household with a migrant who sends no remittances. All other consequences of migration are disregarded.

A1: Important policy implications; Easily affected by the government policies.

A2: Limited policy implications; Hard to measure. Not that simple to affect.

This paper focuses on Q1This paper focuses on Q1

Theoretical framework (1)

Effect of work migration on household wellbeing: Change relative productivity of members of the sending

households. Labor market implications for the household members Affects health and educational attainments, etc

Remittances as the most tangible benefits of migration: enable households to overcome credit and risk constraints on

their ability to engage into the modern and more productive activities.

Investment in housing and schooling Direct consumption, etc.

The observed consumption behavior is the result of all The observed consumption behavior is the result of all these effects.these effects.

Theoretical framework (2)

Main assumption: Three states of migration: Migration abroad, Internal

migration, No migration. Every household has a choice to send its member to work

abroad or inside Nepal. Migration has to be planned ahead.

Two period model of utility maximization Period 1: Households compare expected net benefits (in

period 2) in each state of migration and select the state providing highest utility.

Period 2: Households observe the realized labor market outcomes; a migrant inform his household about his wages and remittances. The household decides on the LFP of its members, investment decisions, adjusts levels of consumption.

Theoretical framework (3)

Presence of unobserved factors that would simultaneously affect the migration decision and consumption decisions.

Selection of household into migration states could be non-random.

The challenge for our empirical strategy is to estimate our model controlling for such unobserved factors and selectivity.

Need an instrument to identify the non-random selection.

Identification strategy

Theory some conditions that affect migration decision in period 1 have no effect on consumption in period 2.

Two instruments (standard in the field): A proportion of abroad migrants in a ward in 2001

(based on 2001 Census). A proxy for ward-level migration networks, affects cost of abroad migration.

A proportion of internal migrant in a district in 1995 (NLSS 1995). Affects cost of internal migration.

Theory Applied only for households that have a choice to send a migrant. This imposes restrictions on our sample.

Empirical model

Indirect utility function for state s:

Choice of migration state:

Consumption in a particular state:

Five-variate normal distribution:

, 1,2,3is i s isV Z s

max( ) , 1,2,3is ij j sV V s

, 1,2,3 max( )is s i is is ij j sC X s if V V

33

2322

131211

232221

131211

32121

1

1

);,0(),,,,(

s

ss

sssNf

Empirical specification

Households with a working migrants are identified by the reported remittances. We have no information on characteristics of the migrants except their age.

Among abroad destination we cannot differential between India and other countries (small sample).

Explanatory variables: can only include variables that are not affected by migration: household productive characteristics, demographics, education of females.

Set of characteristics of the localities: labor market, literacy. To control for community-specific characteristics. See Table 2.

Empirical results: choice of migration state (Table 3) Households living in wards with historically higher proportion of external

migrants are significantly more likely to migrate abroad. Households from the districts with larger shares of internal migrants are

more likely to send their members to work inside Nepal. Large households, households with a higher proportion of adult males and

households with less educated females are more likely to have their member working outside Nepal.

Newars are more likely to migrate within Nepal. Dalits prefer to send their members abroad.

Households with large plots are more likely to have a migrant. The probability to have a migrant is lower among the low-wealth

households. Individuals residing in Katmandu are less likely to migrate relative to

respondents living in other areas of Nepal. Households from Rural Western Mountains and Hills are more likely to migrate.

Households living in wards with higher proportion of the illiterates are less likely to migrate. Households from the wards with a large share of wage employment are less likely to send members to work inside Nepal.

Empirical results: consumption equation(Table 4) The observed household characteristics play more import role in

determining the level of consumption in no-migrant households compared with households with a migrant.

Households with larger shares of children 0 to 8 years old have lower per capita consumption relative to households with older or no children.

Household with larger shares of all groups other than adult males are correlated with lower levels of per capita consumption.

Households with better-educated females enjoy higher levels of per capita consumption.

The size of a land plot has a positive and significant impact on consumption of households with no migrants and with internal migrants. For households with external migrants, those possessing more than two hectares of land have significantly higher per capita consumption relative to landless households.

Households from the upper percentiles of the index have higher per-capita expenditure regardless of their members’ migration status.

Households receiving pensions are better off in all three migration groups.

Simulations (1)

Common mistakes in estimation of the effect of migration and remittances on poverty, inequality, etc. Estimate consumption regressions for different state of

migration independently from migration choice equation. Use conditional mean expenditure in order to cacluate

counterfactual poverty and inequality rates. Problems with this approach:

Errors in the consumption regression come from multivariate distribution.

We need to estimate the expectation of the error term conditional on the migration choice.

We need to recover the whole distribtuion in order to predict poverty and inequality changes.

Simulations (2)

Generate counterfactual distributions based on estimated parameters of our model. For each observation we generate 1000 sets of 5 error terms drawn from estimated multivariate distribution (3,912,000 simulated households)

Different levels of internal and external migration are simulated through the changes in values of our two instruments.

The household size is adjusted for the presence of would be a migrant, all variables constructed using the household size, shares of various age-gender groups, are adjusted.

All parameters of the counterfactual distribution could be recovered from the simulated sample: poverty and inequality rates, mean expenditure by groups, etc.

Table 5: Simulated changes in expenditure, poverty and inequality rates for the different migration scenarios.

Migration scenarios Actual No

migration

Level of migration

as in 1995-96

+10% point increase

in internal migration

+10% point increase

in abroad migration

Household types Poverty rate All Households

29.9 33.6 31.9 27.3 29.5

Households with no migrants 30.5 30.5 31.2 27.2 29.3 Households with migrants within Nepal 22.7 46.6 29.6 22.7 25.3 Households with migrants abroad 32.8 35.0 35.6 30.5 32.8

Average expenditure, NRP 10,000’s All Households

1.492 1.403 1.442 1.569 1.512

Households with no migrants 1.492 1.492 1.474 1.595 1.531 Households with migrants within Nepal 1.578 1.081 1.464 1.578 1.530 Households with migrants abroad 1.438 1.337 1.327 1.481 1.438

Inequality rate (Gini) All Households

0.463 0.444 0.452 0.470 0.481

Table 6: Simulated changes in predicted consumption for the households with internal and abroad migrants (rs, 10.000) Expected consumption

Conditional on:

Actual No

migration

Level of migration

as in 1995-96

+10% point

increase in

internal migration

+10% point

increase in abroad migration

Ethnicity Brahman/Chhetri 1.848 1.748 1.793 1.943 1.867 Dalit 1.049 1.030 1.028 1.088 1.054 Newar 2.667 2.555 2.608 2.778 2.693 Terai-Hill Janajatis 1.172 1.065 1.120 1.238 1.201 Muslim \ Other Minorities 1.255 1.182 1.213 1.325 1.270 Land holdings a year ago Landless households 1.863 1.736 1.803 1.947 1.891 Farm plot < 1 ha 1.294 1.221 1.252 1.368 1.310 Farm plot: 1-2 ha 1.548 1.464 1.501 1.629 1.567 Farm plot > 2 ha 1.874 1.758 1.806 1.949 1.907 Lagged durable asset index No Assets 1.022 0.961 0.988 1.074 1.034 Asset poor (1 - 33th percentile) 1.074 0.987 1.032 1.148 1.090 (33th - 66th percentile) 1.470 1.377 1.419 1.559 1.488 Asset rich (66th - 100th ) 3.100 2.943 3.010 3.221 3.147 Geography dummies Katmandu 3.497 3.336 3.420 3.607 3.543 Other urban areas 2.479 2.293 2.391 2.587 2.527 Rural western mount/hills 1.184 1.148 1.153 1.242 1.194 Rural eastern mount/hills 1.133 1.061 1.100 1.198 1.146 Rural western Terai 1.271 1.176 1.223 1.381 1.279 Rural eastern Terai 1.389 1.297 1.334 1.452 1.413 Total 1.492 1.403 1.444 1.569 1.512

Main findings

About 20 percent of total poverty reduction in Nepal between 1995 and 2004 could be explained by the increase in work migration and remittances.

Out of total 2 percentage points poverty reduction because of the migration: Increase in external migration and remittances contributed 53

percent. Increase in internal migration contributed 38 percent. The rest (9 percent) could attributed to the interaction effects

of internal and abroad migration and remittances. In the absence of migration the poverty rate in Nepal would

increase from the currently observed 29.9 percent to 33.5 percent and the mean per capita expenditure would decline from 16,400 NRP to 15,000 NPR.

Work migration and remittances increase income inequality in the country.

Caveats

Our estimations neglect the general equilibrium effects of increased work migration and remittances. We measure only direct impact on household consumption. No spill-over.

We might have misclassified households with a migrant without remittances.

We neglect household- and community specific effects.

We cannot differentiate between India and the rest of the world as migration destination.

Conclusion Our estimates provide only low bounds for the effect of

work migration and remittances in Nepal. The proper estimation of these effects is a very data

demanding and econometrically challenging task. New, preferably panel surveys with better developed

remittances and migration modules are necessary. We need to know about the characteristics and living

standards of the migrants – surveys in the host countries. Further research is necessary to understand better the

impact of migration and remittances on wellbeing of Nepali households.