Abstract
Selected Issues
The Effect of Remittances on Household’s Expenditure Patterns and Labor Supply1
This study measures the extent to which Nepal’s households change their expenditure patterns and labor supply in response to remittances, using the Nepal Household Risk and Vulnerability Survey – 2016 and employing a propensity score matching method. The results show that remittances have supported greater consumption of productive goods (such as durable goods, education and health), without discouraging labor supply of remittance-receiving family members.
A. Introduction
1. Remittances play a core role in the Nepalese economy. Since the early 2000s, Nepal’s economy has been reshaped by the emigration of its workers—mainly to India, Gulf Cooperation Council (GCC) countries, and Malaysia—and the corresponding sharp growth of inbound remittances. Workers’ remittances reached US$7.8 billion in FY2018/19. This corresponds to a quarter of total GDP, 3 times total exports of goods and services, and about ten times official foreign aid. It is the largest single component in the current account balance of Nepal, helping to offset the large trade deficit, and is the essential item propping up foreign reserves.
2. Growing remittances have been critical to raising household (HH) income and reducing poverty. The poverty headcount ratio at $1.9 a day fell by 31 percentage points between 2003 and 2010, and is likely to have fallen further. Remittances have also provided insurance against shocks, for instance supporting households in the aftermath of natural disasters. Moreover, remittances have contributed to human capital development when used for education opportunities and access to health care by left behind family members.
3. Reliance on remittances, both at the macro and household levels, makes Nepal highly vulnerable to shifts that could diminish remittance inflows. The slowdown in growth of remittances has been significant since 2016, owing to weak economic performance in major remittance-sending economies and less outward migration. The annual growth rate of workers’ remittances has decreased to an average of 7.5 percent over the past three years, from 23 percent in the 2000s. The number of official monthly new emigrant workers fell to 18 thousand in October 2019, compared to a peak of 62 thousand in July 2014. The outlook for remittances is uncertain, in light of the completion of major infrastructure projects, such as those in preparations for the 2020 Dubai World Expo and the 2022 FIFA World Cup in Qatar.
Foreign migrations (new)
Citation: IMF Staff Country Reports 2020, 097; 10.5089/9781513539768.002.A001
Sources: Nepali authorities: and IMF staff estimates.Foreign migrations (new)
Citation: IMF Staff Country Reports 2020, 097; 10.5089/9781513539768.002.A001
Sources: Nepali authorities: and IMF staff estimates.Foreign migrations (new)
Citation: IMF Staff Country Reports 2020, 097; 10.5089/9781513539768.002.A001
Sources: Nepali authorities: and IMF staff estimates.
Remittances
Citation: IMF Staff Country Reports 2020, 097; 10.5089/9781513539768.002.A001
Sources: Nepali authorities-and IMF staff estimates.Remittances
Citation: IMF Staff Country Reports 2020, 097; 10.5089/9781513539768.002.A001
Sources: Nepali authorities-and IMF staff estimates.Remittances
Citation: IMF Staff Country Reports 2020, 097; 10.5089/9781513539768.002.A001
Sources: Nepali authorities-and IMF staff estimates.4. This study provides stylized facts on migrant workers and remittance-recipient households, and then analyzes the effect of remittances on HHs’ expenditure patterns and labor supply. This study uses the Nepal Household Risk and Vulnerability Survey – 2016 (NRVS-2016), compiled by the World Bank, and employs a propensity score matching (PSM) method to solve methodological problems such as selectivity and reverse causality. It used more updated data compared to previous studies (Thapa and Sanjaya, 2017) that relied on the Nepal Living Standard Survey 2010/11 (NLSS-2010/11), capturing changes since the 2015 earthquakes and trade disruptions.
B. Stylized Facts
Migrant workers
5. Migrant workers are typically young, male, from rural areas, and have been abroad for two years. Close to 10 percent of total individuals in the HH roster in the survey are recorded to be away from home, of which 21 percent are working in other domestic cities and 79 percent abroad. Broken down further for foreign migrants by the destination country, the GCC region accounts for the highest share of workers with 42 percent, followed by India2 with 30 percent, Malaysia with 22 percent, and other countries such as South Korea and Japan with 6 percent. Almost all migrants are male (95 percent), and two-thirds of them are from rural areas in Nepal, with these values slightly lower in the case of workers going abroad. The average age of migrants is 29.6 years. Their average stay in other cities or countries is 23 months.
6. Foreign migrants obtain higher incomes and remit more money to their families, but also face higher costs than those migrating domestically (Table 1). The average monthly income of the migrants who responded in this survey3 is NPR 31,376 (about US$295), which is 4.6 times the monthly per capita GDP in 2016 (NPR 82 thousand). However, there is a wide difference between domestic and foreign workers. The average monthly income of foreign migrants (NPR 34,871, or US$328) is almost twice that of domestic migrants (NPR 17,653). Almost all foreign migrants paid a significant amount for their emigration, at NPR 107,342 (US$1,009) on average, which corresponds to three months of their foreign income. In contrast, the average cost for domestic migration is less than a third of their average monthly income. A much higher proportion (84 percent) of foreign migrants remit money to their family/relatives or friends, also to pay back their higher migrating costs. Comparisons by the destination country (GCC, India, Malaysia, and others) are also included in Table 1.
Descriptive Statistics of Migrants 1/
Observations: total migrants (2,742), domestic migrants (592), foreign migrants (2,150).
Descriptive Statistics of Migrants 1/
| All migrants | Domestic | Foreign | India | Malaysia | GCC | Others | Rural | Urban | |
|---|---|---|---|---|---|---|---|---|---|
| Domestic migrants | 20.7% | 100% | 21.6% | 18.9% | |||||
| Foreign migrants | 79.3% | 100% | 78.4% | 81.1% | |||||
| to India | 30.4% | 30.4% | 33.2% | 24.6% | |||||
| to Malaysia | 22.3% | 22.3% | 23.0% | 20.9% | |||||
| to GCC | 41.5% | 41.5% | 38.2% | 48.2% | |||||
| to other countries | 5.8% | 5.8% | 5.6% | 6.3% | |||||
| From rural areas | 67.4% | 71.0% | 67.4% | 73.6% | 69.5% | 62.2% | 64.6% | 100% | |
| From urban areas | 32.6% | 29.0% | 32.6% | 26.4% | 30.5% | 37.8% | 35.4% | 100% | |
| Male | 95.3% | 89.8% | 96.8% | 99.2% | 98.2% | 96.0% | 84.3% | 95.5% | 94.9% |
| Female | 4.6% | 10.0% | 3.1% | 0.8% | 1.8% | 3.8% | 15.7% | 4.4% | 5.0% |
| Age (years) | 29.6 | 29.2 | 29.7 | 28.8 | 28.4 | 31.0 | 30.8 | 29.2 | 30.4 |
| Duration (months) | 22.8 | 21.0 | 23.2 | 29.1 | 22.0 | 19.4 | 24.4 | 23.1 | 22.1 |
| Pay cost for migrating | 91.3% | 68.7% | 97.2% | 94.1% | 99.1% | 99.2% | 91.6% | 90.2% | 93.6% |
| Cost value | 85,991 | 4,260 | 107,372 | 4,641 | 124,824 | 108,546 | 568,983 | 81,456 | 95,700 |
| Remitting | 79.8% | 63.5% | 84.0% | 71.6% | 88.7% | 91.0% | 80.9% | 76.9% | 85.9% |
| Remittance (NRP, 1 year) | 158,088 | 57,319 | 178,025 | 64,794 | 200,914 | 193,416 | 482,200 | 153,945 | 166,023 |
| Monthly income (NPRs) | 31,376 | 17,653 | 34,871 | 16,367 | 31,899 | 36,897 | 122,097 | 29,956 | 34,235 |
Observations: total migrants (2,742), domestic migrants (592), foreign migrants (2,150).
Descriptive Statistics of Migrants 1/
| All migrants | Domestic | Foreign | India | Malaysia | GCC | Others | Rural | Urban | |
|---|---|---|---|---|---|---|---|---|---|
| Domestic migrants | 20.7% | 100% | 21.6% | 18.9% | |||||
| Foreign migrants | 79.3% | 100% | 78.4% | 81.1% | |||||
| to India | 30.4% | 30.4% | 33.2% | 24.6% | |||||
| to Malaysia | 22.3% | 22.3% | 23.0% | 20.9% | |||||
| to GCC | 41.5% | 41.5% | 38.2% | 48.2% | |||||
| to other countries | 5.8% | 5.8% | 5.6% | 6.3% | |||||
| From rural areas | 67.4% | 71.0% | 67.4% | 73.6% | 69.5% | 62.2% | 64.6% | 100% | |
| From urban areas | 32.6% | 29.0% | 32.6% | 26.4% | 30.5% | 37.8% | 35.4% | 100% | |
| Male | 95.3% | 89.8% | 96.8% | 99.2% | 98.2% | 96.0% | 84.3% | 95.5% | 94.9% |
| Female | 4.6% | 10.0% | 3.1% | 0.8% | 1.8% | 3.8% | 15.7% | 4.4% | 5.0% |
| Age (years) | 29.6 | 29.2 | 29.7 | 28.8 | 28.4 | 31.0 | 30.8 | 29.2 | 30.4 |
| Duration (months) | 22.8 | 21.0 | 23.2 | 29.1 | 22.0 | 19.4 | 24.4 | 23.1 | 22.1 |
| Pay cost for migrating | 91.3% | 68.7% | 97.2% | 94.1% | 99.1% | 99.2% | 91.6% | 90.2% | 93.6% |
| Cost value | 85,991 | 4,260 | 107,372 | 4,641 | 124,824 | 108,546 | 568,983 | 81,456 | 95,700 |
| Remitting | 79.8% | 63.5% | 84.0% | 71.6% | 88.7% | 91.0% | 80.9% | 76.9% | 85.9% |
| Remittance (NRP, 1 year) | 158,088 | 57,319 | 178,025 | 64,794 | 200,914 | 193,416 | 482,200 | 153,945 | 166,023 |
| Monthly income (NPRs) | 31,376 | 17,653 | 34,871 | 16,367 | 31,899 | 36,897 | 122,097 | 29,956 | 34,235 |
Observations: total migrants (2,742), domestic migrants (592), foreign migrants (2,150).
Remittance-Receiving Households
7. The share of domestic remittance-receiving HHs has decreased noticeably over the past 5- 6 years. Table 2 shows that 29 percent of HHs in the survey (NRVS-2016) receive remittances either locally or internationally, which is significantly lower than 52 percent in the previous survey (NLSS-2010/11). This reflects fewer HHs receiving domestic remittances in 2016 (4 percent), compared to 18 percent in 2010. HHs receiving foreign remittances increased by one percentage point to 25 percent. This may reflect limits on the expansion of foreign migration given restrictions in destination countries.
Descriptive Statistics of Households
The difference between the two groups is statistically significant at 1 % (>>>, <<<), at 5% (>>, <<), and at 10% (>, <).
VDC: Village Development Committee.
Descriptive Statistics of Households
| NRVS-2016 | NLSS-2010/11 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| All HHs | Remittance recipients | Remittance non-recipients | All HHs | Remittance recipients | Remittance non-recipients | |||||
| Mean | Std. Err. | Mean | Std. Err. | Mean | Std. Err. | diff1/ | Mean | Mean | Mean | |
| HH characteristics | ||||||||||
| Share of children 0–6 | 11.2% | 0.2% | 12.7% | 0.4% | 10.5% | 0.002 | >>> | 13.0% | 13.0% | 12.0% |
| Share of children, ages 7–15 | 18.7% | 0.3% | 17.5% | 0.5% | 19.2% | 0.003 | <<< | 21.0% | 21.0% | 21.0% |
| Share of adults, ages 16–64 | 60.9% | 0.3% | 58.4% | 0.6% | 61.9% | 0.004 | <<< | 59.0% | 58.0% | 60.0% |
| Share of elders, age 65+ | 7.1% | 0.2% | 6.3% | 0.4% | 7.4% | 0.003 | << | 7.0% | 8.0% | 7.0% |
| Household size | 4.878 | 0.028 | 4.698 | 0.054 | 4.952 | 0.032 | <<< | 4.75 | 4.61 | 4.94 |
| Dependency ratio | 86.5% | 1.2% | 99.2% | 2.7% | 81.3% | 0.012 | >>> | 42.0% | 40.0% | 45.0% |
| Migration from VDC’s (%) 2/ | 11.2 | 0.087 | 13.6 | 0.161 | 10.1 | 0.099 | >>> | 6.65 | 6.81 | 6.45 |
| Rural area | 68.5% | 0.7% | 66.6% | 1.2% | 69.3% | 0.008 | < | 65.0% | 71.0% | 59.0% |
| Urban area | 31.5% | 0.7% | 33.4% | 1.2% | 30.7% | 0.008 | > | 35.0% | 29.0% | 41.0% |
| Remittance receiving HH | 29.3% | 0.6% | 100% | 0% | 53.0% | |||||
| Domestic remit-receiving HH | 4.4% | 0.3% | 15.1% | 0.9% | 0% | 18.0% | ||||
| Foreign remit-receiving HH | 25.4% | 0.6% | 86.8% | 0.8% | 0% | 24.0% | ||||
| HH head characteristics | ||||||||||
| Female to male ratio | 1.331 | 0.013 | 1.622 | 0.028 | 1.211 | 0.014 | >>> | 1.03 | 1.01 | 1.04 |
| Age of HH head | 48.5 | 0.191 | 49.5 | 0.357 | 48.1 | 0.225 | >>> | 45.99 | 46.20 | 44.78 |
| Male of HH head | 0.813 | 0.005 | 0.597 | 0.013 | 0.902 | 0.005 | <<< | |||
| No school (HH head education) | 0.408 | 0.007 | 0.464 | 0.013 | 0.385 | 0.008 | >>> | 0.44 | 0.49 | 0.39 |
| Primary school | 0.260 | 0.006 | 0.277 | 0.012 | 0.253 | 0.007 | > | 0.14 | 0.13 | 0.15 |
| Secondary school | 0.128 | 0.005 | 0.104 | 0.008 | 0.137 | 0.006 | <<< | 0.13 | 0.12 | 0.13 |
| High school | 0.161 | 0.005 | 0.118 | 0.008 | 0.179 | 0.006 | <<< | 0.11 | 0.10 | 0.13 |
| University + | 0.040 | 0.003 | 0.033 | 0.004 | 0.043 | 0.003 | < | 0.17 | 0.16 | 0.19 |
| Ariculture (HH head occupation | 0.589 | 0.007 | 0.674 | 0.012 | 0.554 | 0.008 | >>> | 0.44 | 0.50 | 0.37 |
| Non-agriculture | 0.263 | 0.006 | 0.128 | 0.009 | 0.319 | 0.008 | <<< | 0.44 | 0.36 | 0.53 |
| No job | 0.143 | 0.005 | 0.195 | 0.010 | 0.122 | 0.005 | >>> | 0.12 | 0.14 | 0.10 |
The difference between the two groups is statistically significant at 1 % (>>>, <<<), at 5% (>>, <<), and at 10% (>, <).
VDC: Village Development Committee.
Descriptive Statistics of Households
| NRVS-2016 | NLSS-2010/11 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| All HHs | Remittance recipients | Remittance non-recipients | All HHs | Remittance recipients | Remittance non-recipients | |||||
| Mean | Std. Err. | Mean | Std. Err. | Mean | Std. Err. | diff1/ | Mean | Mean | Mean | |
| HH characteristics | ||||||||||
| Share of children 0–6 | 11.2% | 0.2% | 12.7% | 0.4% | 10.5% | 0.002 | >>> | 13.0% | 13.0% | 12.0% |
| Share of children, ages 7–15 | 18.7% | 0.3% | 17.5% | 0.5% | 19.2% | 0.003 | <<< | 21.0% | 21.0% | 21.0% |
| Share of adults, ages 16–64 | 60.9% | 0.3% | 58.4% | 0.6% | 61.9% | 0.004 | <<< | 59.0% | 58.0% | 60.0% |
| Share of elders, age 65+ | 7.1% | 0.2% | 6.3% | 0.4% | 7.4% | 0.003 | << | 7.0% | 8.0% | 7.0% |
| Household size | 4.878 | 0.028 | 4.698 | 0.054 | 4.952 | 0.032 | <<< | 4.75 | 4.61 | 4.94 |
| Dependency ratio | 86.5% | 1.2% | 99.2% | 2.7% | 81.3% | 0.012 | >>> | 42.0% | 40.0% | 45.0% |
| Migration from VDC’s (%) 2/ | 11.2 | 0.087 | 13.6 | 0.161 | 10.1 | 0.099 | >>> | 6.65 | 6.81 | 6.45 |
| Rural area | 68.5% | 0.7% | 66.6% | 1.2% | 69.3% | 0.008 | < | 65.0% | 71.0% | 59.0% |
| Urban area | 31.5% | 0.7% | 33.4% | 1.2% | 30.7% | 0.008 | > | 35.0% | 29.0% | 41.0% |
| Remittance receiving HH | 29.3% | 0.6% | 100% | 0% | 53.0% | |||||
| Domestic remit-receiving HH | 4.4% | 0.3% | 15.1% | 0.9% | 0% | 18.0% | ||||
| Foreign remit-receiving HH | 25.4% | 0.6% | 86.8% | 0.8% | 0% | 24.0% | ||||
| HH head characteristics | ||||||||||
| Female to male ratio | 1.331 | 0.013 | 1.622 | 0.028 | 1.211 | 0.014 | >>> | 1.03 | 1.01 | 1.04 |
| Age of HH head | 48.5 | 0.191 | 49.5 | 0.357 | 48.1 | 0.225 | >>> | 45.99 | 46.20 | 44.78 |
| Male of HH head | 0.813 | 0.005 | 0.597 | 0.013 | 0.902 | 0.005 | <<< | |||
| No school (HH head education) | 0.408 | 0.007 | 0.464 | 0.013 | 0.385 | 0.008 | >>> | 0.44 | 0.49 | 0.39 |
| Primary school | 0.260 | 0.006 | 0.277 | 0.012 | 0.253 | 0.007 | > | 0.14 | 0.13 | 0.15 |
| Secondary school | 0.128 | 0.005 | 0.104 | 0.008 | 0.137 | 0.006 | <<< | 0.13 | 0.12 | 0.13 |
| High school | 0.161 | 0.005 | 0.118 | 0.008 | 0.179 | 0.006 | <<< | 0.11 | 0.10 | 0.13 |
| University + | 0.040 | 0.003 | 0.033 | 0.004 | 0.043 | 0.003 | < | 0.17 | 0.16 | 0.19 |
| Ariculture (HH head occupation | 0.589 | 0.007 | 0.674 | 0.012 | 0.554 | 0.008 | >>> | 0.44 | 0.50 | 0.37 |
| Non-agriculture | 0.263 | 0.006 | 0.128 | 0.009 | 0.319 | 0.008 | <<< | 0.44 | 0.36 | 0.53 |
| No job | 0.143 | 0.005 | 0.195 | 0.010 | 0.122 | 0.005 | >>> | 0.12 | 0.14 | 0.10 |
The difference between the two groups is statistically significant at 1 % (>>>, <<<), at 5% (>>, <<), and at 10% (>, <).
VDC: Village Development Committee.
8. Heads of household in remittance-receiving HHs tend to be female and have a lower level of education compared to HHs that do not receive remittances. They also are more likely to be work in agriculture or have no job. Similar results are found in the 2016 and 2010/11 surveys.
9. Migrants’ remittances have been an essential source of income for their family in Nepal. The average annual income of remittance-receiving HHs before remittances was only 60 percent of that of non-recipient HHs in 2016. But, when remittances were added, total income increases significantly, reaching as high as 1.5 times that of non-recipients. The increase was even higher for foreign remittance recipients.
HHs’ Income and Remittances (2016)
HHs’ Income and Remittances (2016)
| Remittance recipients | Foreign remittance recipients | Domestic remittance recipients | Remittance non-recipients | |
|---|---|---|---|---|
| Total annual income (NPRs) | 125,706 | 123,785 | 138,464 | 205,526 |
| Remittances (1 year, NPRs) | 204,782 | 222,390 | 97,736 | |
| Income + remittances (NPRs) | 330,489 | 346,175 | 236,200 | 205,526 |
HHs’ Income and Remittances (2016)
| Remittance recipients | Foreign remittance recipients | Domestic remittance recipients | Remittance non-recipients | |
|---|---|---|---|---|
| Total annual income (NPRs) | 125,706 | 123,785 | 138,464 | 205,526 |
| Remittances (1 year, NPRs) | 204,782 | 222,390 | 97,736 | |
| Income + remittances (NPRs) | 330,489 | 346,175 | 236,200 | 205,526 |
10. Remittance values have increased considerably in recent years. Table 4 shows the change in annual remittance values between 2010/11 and 2016, comparing them as a share of per capita GDP. Foreign remittances increased from 60 percent of per capita GDP in 2010 to 67 percent in 2016. Domestic remittances increased from 34 percent of per capita GDP in 2010 to 41 percent in 2016. The increase in foreign remittance values is mainly related to a higher share of migrations in recent years to GCC, Japan, and Korea that have higher wage levels than those in India and Southeast Asian countries. This also explains why there has been a growth of inbound remittances despite recent slowdown in the number of foreign migrants.
Comparison of Remittance Value
Comparison of Remittance Value
| NRVS-2016 | NLSS-2010/11 | |||||
|---|---|---|---|---|---|---|
| Remittance recipients | Foreign remittance r | Domestic emittance | Remittance recipients | Foreign remittance | Domestic remittance | |
| Per Capita HH remittances (A, NPRs) | 53,047 | 55,606 | 34,075 | 25,323 | 28,553 | 16,160 |
| Per Capita nominal GDP (B, NPRs) | 82,644 | 82,644 | 82,644 | 47,379 | 47,379 | 47,379 |
| Ratio (A/B) | 0.642 | 0.673 | 0.412 | 0.534 | 0.603 | 0.341 |
| Growth of ratio (%) | 20.1% | 11.6% | 20.9% | |||
Comparison of Remittance Value
| NRVS-2016 | NLSS-2010/11 | |||||
|---|---|---|---|---|---|---|
| Remittance recipients | Foreign remittance r | Domestic emittance | Remittance recipients | Foreign remittance | Domestic remittance | |
| Per Capita HH remittances (A, NPRs) | 53,047 | 55,606 | 34,075 | 25,323 | 28,553 | 16,160 |
| Per Capita nominal GDP (B, NPRs) | 82,644 | 82,644 | 82,644 | 47,379 | 47,379 | 47,379 |
| Ratio (A/B) | 0.642 | 0.673 | 0.412 | 0.534 | 0.603 | 0.341 |
| Growth of ratio (%) | 20.1% | 11.6% | 20.9% | |||
C. Effects of Remittances on HHs’ Economic Activities
Methodological Issues
11. There are a couple of methodological issues that need to be addressed in order to assess the effect of remittances on the economic activities of HHs. The literature stresses the importance of solving the problems of selection bias and reverse causality. Selection bias occurs when there is a different selectivity of HHs or people in comparing characteristics between the two groups (treatment vs. control groups). For example, as was explained in the previous section, remittance-receiving HHs tend to have more cases of female HH head. In this case, remittance-receiving HHs’ expenditure patterns are not only affected by remittances but also from different expenditure patterns of female heads. Reverse causality is also a problem. International remittances may help reduce poverty in developing countries, but it is also possible that the level of poverty influences the amount of remittances.
12. To address these problems, this analysis employs a propensity score matching (PSM) method. The propensity score is the probability of receiving treatment (in this case, getting remittances), conditional on the covariates (HH and HH head characteristics), and is applied to correct the estimation of treatment effects controlling for the existence of the confounding factors. It is based on the idea that the selectivity bias is reduced when the comparisons of outcomes are performed by matching each treated unit with a non-treated unit of similar characteristics using the propensity score.
13. The propensity score matching is set up as follows.
1) Construct a logit model with remittance-receiving HHs as a binary dependent variable with other variables that might affect receiving remittances as independent variables (share of children/adults/elders, household size, rural area based, HH head age, male HH head, HH head education),
2) Find the propensity score for each HH from the logit/probit model (the probability of getting remittances),
3) Formulate an artificial control group of HHs by matching each remittance-receiving HH with a non-receiving HH of the similar propensity score,
4) Implement the balancing test to check for similarity in distribution of the covariates between groups after matching,
5) Get the effect of treatment (getting remittances) on the outcomes (HH expenditure patterns and labor supply) by contrasting treated and control groups.4
Effect on Households’ Expenditure Patterns
14. Table 5 shows the main results. This study focuses on the analysis of foreign remittances, given that most migrant workers are abroad.
The effect of foreign remittances on the HH expenditure patterns is negative and highly significant for the consumption of food, while the share of expenditure on non-food daily consumer goods such as fuel, clothes, public transportation service, and entertainment is positive and statistically significant.
The shares of expenditure on durable goods and education, which are associated more with medium-term investments at the HH level, are higher for remittance recipients.
Comparison of HHs’ Expenditure Pattern
The difference is statistically significant at 1 % (>>>, <<<), at 5% (>>, <<), and at 10% (>, <).
Comparison of HHs’ Expenditure Pattern
| NRVS-2016 | NLSS-2010/11 | ||||||
|---|---|---|---|---|---|---|---|
| Foreign remittance recipients | Remittance non-recipients | diff1/ | Foreign remittance recipients | Remittance non-recipients | diff 1/ | ||
| Expenditure pattern | |||||||
| Food consumption | 56.7% | 61.0% | <<< | 58.0% | 58.5% | ||
| Non-food daily consumption | 25.6% | 23.7% | >>> | 14.0% | 13.0% | ||
| Durable goods | 2.7% | 2.2% | >> | 4.0% | 3.0% | >>> | |
| Education | 6.3% | 5.3% | >>> | 6.0% | 7.0% | ||
| Health | 3.8% | 3.7% | 7.0% | 6.0% | > | ||
| Utilities, rent | 4.9% | 4.1% | >>> | 15.0% | 16.0% | >> | |
The difference is statistically significant at 1 % (>>>, <<<), at 5% (>>, <<), and at 10% (>, <).
Comparison of HHs’ Expenditure Pattern
| NRVS-2016 | NLSS-2010/11 | ||||||
|---|---|---|---|---|---|---|---|
| Foreign remittance recipients | Remittance non-recipients | diff1/ | Foreign remittance recipients | Remittance non-recipients | diff 1/ | ||
| Expenditure pattern | |||||||
| Food consumption | 56.7% | 61.0% | <<< | 58.0% | 58.5% | ||
| Non-food daily consumption | 25.6% | 23.7% | >>> | 14.0% | 13.0% | ||
| Durable goods | 2.7% | 2.2% | >> | 4.0% | 3.0% | >>> | |
| Education | 6.3% | 5.3% | >>> | 6.0% | 7.0% | ||
| Health | 3.8% | 3.7% | 7.0% | 6.0% | > | ||
| Utilities, rent | 4.9% | 4.1% | >>> | 15.0% | 16.0% | >> | |
The difference is statistically significant at 1 % (>>>, <<<), at 5% (>>, <<), and at 10% (>, <).
15. The results show a positive effect, albeit small, of remittances on HH’s expenditure that contribute to human capital development. Remittances are found to contribute to slightly higher spending on education and access to health care, compared to non-recipient HHs. However, the total share of the productive consumption (durable goods, education, and health) was still low at less than 15 percent of total spending.
16. The results suggest that HHs are treating remittances as temporary income5. According to the permanent income hypothesis, changes in permanent income, rather than changes in temporary income, are what drive changes in consumer expenditure patterns. Using this hypothesis, studies6 also state that the marginal propensity to invest (or more broadly “save”) out of temporary income is higher than the marginal propensity to consume out of temporary income in order to smooth/enhance lifetime consumption or to guard against declines in future income. The expenditure on productive goods (investment) should contribute positively to increases in future income. This hypothesis is instrumental in explaining the above results. With an increase in temporary income (remittances), HHs’ marginal propensity to invest gets higher (statistically higher share of expenditure on productive goods). However, the share of total expenditure between consumer and productive goods does not change significantly without noticeable changes in permanent income (domestic wages).
Effect on HHs’ Labor Supply
17. This study also analyzes the effect of remittances on labor market participation of left behind household heads, using a propensity score matching method. In addition, in order to identify the labor supply effect by gender, this study carries out the comparisons separately for HHs with male and female heads, which has not been tried in other studies.
18. Table 6 shows that there is no significant difference in unemployment of household heads between remittance recipient and non-recipients. The results are different from previous empirical studies7 which have the findings that remittances reduce labor market participation. It is interesting that the statistically significant difference before propensity score matching (20 percent for remittance recipients vs. 13 percent for non-recipients) disappears after the matching. The PSM method, not used in the previous studies, can be viewed as instrumental in removing noise factors (bias) in comparing HHs’ labor supply. The findings of no difference in labor supply can be effectively explained by the view that HHs regard remittances as temporary income. So, HH heads may want to keep their current job even after receiving remittances for fear of the difficulties in reemployment after the return of migrants.
Comparison of HHs’ Labor Supply (2016)
Comparison of HHs’ Labor Supply (2016)
| Foreign remittance recipients | Remittance non-recipients | |||
|---|---|---|---|---|
| Labor market participation | ||||
| Male head | ||||
| Agriculture | 68.0% | 67.8% | ||
| Non-agriculture | 12.4% | 13.2% | ||
| No job | 19.4% | 18.2% | ||
| Female head | ||||
| Agriculture | 66.7% | 66.0% | ||
| Non-agriculture | 17.7% | 18.5% | ||
| No job | 15.5% | 14.8% | ||
| Non-agriculture | 17.7% | 18.5% | ||
| No job | 15.5% | 14.8% | ||
Comparison of HHs’ Labor Supply (2016)
| Foreign remittance recipients | Remittance non-recipients | |||
|---|---|---|---|---|
| Labor market participation | ||||
| Male head | ||||
| Agriculture | 68.0% | 67.8% | ||
| Non-agriculture | 12.4% | 13.2% | ||
| No job | 19.4% | 18.2% | ||
| Female head | ||||
| Agriculture | 66.7% | 66.0% | ||
| Non-agriculture | 17.7% | 18.5% | ||
| No job | 15.5% | 14.8% | ||
| Non-agriculture | 17.7% | 18.5% | ||
| No job | 15.5% | 14.8% | ||
D. Conclusions
19. Remittances have been a key stabilizer of Nepal’s weak external sector, but they also have direct/indirect benefits to HHs. They have improved recipients’ standard of living and provided a cushion for economic shocks in Nepal. This study, using the NRVS-2016 survey and a propensity score matching method, analyzed the effect of remittances on HHs’ expenditure patters and labor supply in Nepal. The stylized facts in the survey indicates that typically young male migrants (30 years old and from urban areas) have been abroad for two years. Heads of remittance-receiving HHs tend to be female with a low education level. They also tend to work in agriculture or have no job. Remittances are an essential source of income to the family. This study finds that remittance-receiving households spend less on consumer goods (food) but more on productive goods (durable goods, education, and health). This suggests that remittances are being treated as temporary income. Unlike other research, this study shows that remittance-receiving HHs do not decrease their labor supply in Nepal.
20. Several studies have explored options to reap more benefits from remittances. These include lowering foreign migrating costs8, and creating incentives so that more remittances flow through formal channels9. To reduce vulnerability to sudden declines in remittances and the return of foreign migrants, measures are needed to strengthen domestic quality employment opportunities. It will be critical to incentivize greater private investment, including by removing constraints to FDI, more and better infrastructure investment, greater competition in product and services markets, and reducing red-tape.
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Prepared by Kyung-Seol Min.
This survey is likely to underestimate the number of migrant workers to India because of informality.
70 percent of total migrants in the survey (2,742) provided information on monthly income.
HHs’ expenditure patterns entail the food consumption ratio, non-food daily consumption ratio, durable goods consumption ratio, education-related consumption ratio, health-related consumption ratio, and other consumption ratio. HHs’ labor supply refers to the unemployment (no job) ratio of male HH heads and female HH heads.
Cabegin (2006), Funkhouser (2006), Kim (2007)
Dhakal and Maharjan (2018), Kharel (2011), WB (2016), ADB (2018, 2019), UNCTAD (2009)
Hagen-Zanker (2014), Bjuggren, Dzanzi and Shukur (2010), Dhakal and Maharjan (2018), Kharel (2019), Sapkota (2013), WB (2011), ADB (2018)
