The Impact of Remittances on Human Resource Development Decisions, Youth Employment Decisions, and Entrepreneurship in the Philippines Using CBMS Data

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The impact of remittances on human resource development decisions, youth employment decisions, and entrepreneurship in the Philippines using CBMS Data

Christopher James R. Cabuay Angelo King Institute for Economic and Business Studies De La Salle University

I. Introduction a. Background

For the past few decades, international migration has been an avenue for Filipinos to seek employment abroad. The stock of Filipino migrants has reached 10,489,628 in 2012 (Commission of Filipinos Overseas [CFO], 2014). Overseas Filipino Workers (OFWs) have been going to Saudi Arabia, United Arab Emirates, Singapore, Hong Kong, and Qatar for employment (Philippine Overseas Employment Administration [POEA], 2014). Migration is often coupled with the sending of remittances to one’s household in the country of origin. These remittances have become a major avenue for many households to maximize income and smoothen consumption spending over time. OFW remittances has been a significant driver of the Philippine economy especially since it fuels the property market with a strong demand from medium-low-income wage earners among families with OFWs (Villegas, 2014). Remittances have grown over the past decades and have reached 18.76 USD billion in 2010 (BangkoSentralngPilipinas [BSP], 2014) and growing further to 22.97 USD billion in 2013. The largest remittances come from USA (about 9.9 USD billion), followed by Saudi Arabia (approximately 2.1 USD billion), United Kingdom (1.32 USD billion) United Arab Emirates (1.26 USD billion), Singapore, Japan, and Canada (BSP, 2014). This indicates the dependency of the Philippine economy to the remittances from overseas workers. Despite the prevalence of the phenomenon, a significant question still remains: how are remittances being used by families? Tabuga (2007) finds that remittances generally decrease the household’s budget allocated for food, but increases the budget allocated for education, medical care, housing and repairs, consumer goods, leisure, gifts, and durables. Many studies (Orbeta, 2008; Tullao, Cortez, and See, 2007; Tabuga, 2007) have pointed to remittances having an improving effect on the human capital accumulation of households, namely education.

However, a debate still stands on whether or not remittances improve a household’s labor force participation or causes dependency among recipients. In the Philippine setting, studies (Tullao, Cortez, and See, 2007; Rodriguez and Tiongson, 2001) have found the labor force participation and employment is lower in remittance-receiving households, but some studies (Ducanes and Abella, 2007; Cabegin, 2006) find that remittances may not cause dependency, but simply enhances avenues for self-employment.

As for the Philippine youth, the segment of the population aged 15-24, unemployment has been fluctuating between 16% to 16.7% from 2011 to 2013 (World Bank, 2015). In the country, a youth of this age has either the option to enter tertiary or post-secondary education, or to enter the workforce. Using the data gathered by the Community-Based Monitoring System (CBMS), particularly with the social protection for the informal sector (SPIS) and youth employment and entrepreneurship (YEE) information, this study aims to characterize the unemployment among youths, while empirically tracing the impact of remittances on whether they are more likely to pursue tertiary or post-secondary education, enter the labor force, or possibly causing dependency at the individual level. Furthermore, the study aims to empirically trace the impact of remittances on the employment decision of youths, that is compare the impact on their propensity to enter self-employment, employment with institutions, and aid in family-run establishments. Lastly, the study aims to empirically trace the impact of remittances on the propensity of the household and youths to engage in entrepreneurship.

The role of remittances in households is to pay for needs such as food, clothing, utilities, rent and the like. After paying for these necessities, there is disposable income for the households to use. Households can spend on renovations on the house, electronics and other luxuries. A point of interest in this study is how remittances are spent on education and entrepreneurial endeavours. Households investing in these areas may have an effect on the youth employment decisions.

b. Objectives of the Study  Using CBMS data for the Philippines, trace the impact of remittances on the human resource development decisions of youths using a multinomial logistic regression

 Using CBMS data for the Philippines, trace the impact of remittances on the employment decision of youths using multinomial logistic regression.

 Using CBMS data for the Philippines, trace the impact of remittances on the propensity of households and youths to engage in entrepreneurship using propensity score matching and instrumental variable regressions.

II. Migration and Remittances (M&R), Human Resource Development, Youth Employment, and Entrepreneurship

Migration and remittances have a variation of impacts on the human capital accumulation of a country. In the case of school participation, remittances can be beneficial (Buoiyour&Miftah, 2015). But, the absence of a parent or parents can decrease school participation (PPP, 2014). There are also other factors that can affect school participation rate like the household’s perception on the return of the investment in education, the opportunity cost of a child foregoing work and the expected economic gain from a youth migration. Acosta (2007) stated, “the direction of the relationship between remittances and child education would depend on idiosyncratic characteristics of each country”. Another issue that is highlighted in the literature of M&R and human capital formation is brain gain/ brain drain. The migration of workers has consequences on the labor market. There will usually be an emigration of low skilled and professional workers. The loss of professional workers is equivalent to a brain drain in the home country. Kugler (2008) found the developing countries are more prone to brain drain or human capital losses. However, the prospect of migration can help increase schooling rates that can lead to brain gain. This has been suggested by Stark and Dorn (2013) and Stark, Helmenstein, and Prskawetz (1998). Stark et al (1998) suggest that although migrants take along more human capital than if there was no prospect of migration, workers that stay will also have more human capital because of the prospect and aspiration to migrate. This was extended by Stark and Dorn (2013) who show that in the presence of savings, with a low degree of relative risk aversion, a worker who saves when there is a prospect of migration will acquire more human capital than without the prospect of migration.

The link between remittances and human resource development has already been the discussion of many studies. Orbeta (2008) provides a review of Philippine-based remittance literature. Tullao, Cortez and See (2007) and Tabuga (2007) find that remittance-receiving households are highly elastic to housing, education, health care, durables, transportation and communications expenditures. This implies that remittances increase the demand for better education, and hence, investment in human capital (Tullao and Cabuay, 2012). To receive remittances implies that a household has sent a member to work or has relatives in foreign countries. The brain drain and the complementary brain gain may facilitate human capital accumulation because members of remittance-receiving tend to have an inclination to increase their labor productivity in the home country in hopes of overseas migration in the future (Tullao& Cabuay, 2012; Ang, 2006). However, there are debates to this view that state that households use remittances to consume rather than invest in entrepreneurial capacity and human capital (Opiniano, 2007; Burgos & De Vera, 2005). This largely depends on what motivates the migrant to send remittances (Tullao& Cabuay, 2012). Wang (2012) suggests that given the case of parental migration, schooling may be disrupted due to the absence of the parents, but there is also a possibility that it may be enhanced when remittances are sent, or that children exhibit the aspiration to migrate. More recently, Theoharides (2014) finds that migration can increase secondary school enrolment in the Philippines.

On the other hand, there is much debate about the link between remittances and employment. Following the line of thought of the previous discussion on how remittances may help in increasing human capital, remittances may therefore encourage household members to enter the labor force. Labor migration (brain drain) induces the remaining household members to increase their labor productivity, thereby making themselves more employable (brain gain) although this may come with the hope of emigration in the future as well (Tullao& Cabuay, 2012; Ang, 2006). However, Tullao, Cortez and See (2007) find that labor participation and employment rates are lower in remittance-receiving households. Rodriguez and Tiongson (2001) find that the presence of OFWs in the household decreases labor participation due to increased demand for leisure. Ducanes and Abella (2007) have found otherwise, particularly in a case where there are OFWs present in the household. Cabegin (2006) finds that the labor supply decision of households vary between men and women depending on the presence of school-age children. In general, remittances decrease labor participation for both, although depending on the presence of work-age children, it increases self-employment work hours for women, which is the entrepreneurial option when receiving remittances. Yang (2006) looks into international data and finds that remittances do not affect the number of work hours, but increases the work hours under self-employment which is consistent with Cabegin (2006). Drinkwater, Levine, Lotti and Pearlman (2003) also looks into international data and finds that remittances has decreasing albeit insignificant effect on unemployment. Empirical studies in the literature are inconsistent because of the endogenous nature of migration, which is highly dependent for a household’s motivation to send a migrant (Tullao and Cabuay, 2012).

The discussion on the impact of remittances on youth employment paints a picture similar to the debate on the impact of remittances on the decision of households and its members to participate in the labor force. In their study of Kyrgyzstan, Karymshakov, Abdieva, Sulaimanova, and Sultakeev (2015) find that remittances have no impact on the propensity of youth to be self- employed or to be employed by an institution, but impact positively to contributing to a family- run establishment. This reinforces hypotheses that members have a higher likelihood of contributing to a family-run establishment so as to replace the migrant member. In addition, they find that young males have higher propensity to be engaged in self-employment.

On the other hand, the study of Petreski, Maojsoska-Blazevski, Ristovska, and Smokvarski (2014) reported mixed findings regarding the impact of remittances on the propensity of remittance-receiving households for youth self-employment. Using OLS and Probit regressions, their findings suggest that remittance receiving households exhibit higher propensities to engage in youth employment, but taking into account the potential endogeneity of remittances using IV regressions, they find that remittance-receiving households have lower propensities to engage in youth self-employment. They find as well, that young households’ members from remittance-receiving households have significantly higher probabilities of setting up their own businesses as compared to non-young counterparts, which suggests that young persons recognize remittances as a way to finance long-term productive ventures. Similarly, Yang (2006) found that given favourable exchange rate shocks, household with migrants experience more work hours put into self-employment and higher entrepreneurial income. There are some studies that conclude a migrant’s remittances is not a strong enough factor to encourage entrepreneurial activities (Chalise, 2014). Other factors such as education and easier access to capital have a higher likelihood of increase the propensity of entrepreneurship (Vasco, 2013).

III. Methodology a. Community –Based Monitoring System

This study utilizes the 2015 Community-Based Monitoring System (CBMS) data set with the Youth Employment and Entrepreneurship (YEE) and Social Protection and the Informal Sector (SPIS) rider questionnaires. The total observations equal 23,855 households and 105,336 individuals.

The dataset basically includes 4 regions: Region 4A (CALABARZON) and National Capital Region (NCR), Region 6 (Western Visayas), and Region 10 (Northern Mindanao). Manila is one of the cities for NCR wherein two project sites (barangays) are involved. The other is Marikina with 3 barangays. The region 4A municipalities included are Lipa City in Batangas, and Maragondon and Dasmarinas in Cavite which include one barangay each. For Region 6, Bago City of Negros Occidental constitutes the largest portion of the survey comprised of 7 barangays. Region 10 is represented by Ozamiz City of Misamis Occidental and is comprised of two barangays. Due to the data being very recent, and only a select sites of CBMS were given the YEE and SPIS rider questionnaires, it may be seen that a significant portion of the observations are taken from Marikina and Bago, whereas the observations in other sites are relatively fewer however still represent a relatively sizeable amount of observations for each site.The sample used in this study is comprised mainly of the youth, individuals aged 15-30. This is the main interest of the study, and is particularly needed for the econometric models due this cohort’s ability to choose to be in a school outcome, or a particular work outcome.

b. Description of the Sample

We present a short description of the sample from the CBMS data. We report the proportion of the sample with OFWs, remittances, the human resource development, employment, and entrepreneurial decision outcomes of the youth ages 15 to 30. Initially, we show in table 1 the rural/urban intensity of the youth in participating provincial sites.

Table 1. Urban/rural intensity of provincial sites Sites by Province # in Rural # in Urban Total Manila (Code 39) 0 1,083 1,083 Marikina (Code 74) 0 14,920 14,920 Batangas (Code 10) 0 438 438 Cavite (Code 21) 311 492 803 Negros Occidental 9,888 2,626 12,514 (Code 42) Misamis Occidental 210 839 1,049 (Code 45) All Sites 10,409 20,398 30,807

It may be seen that there are more observations in urbanized areas than in rural areas. Manila, Marikina, and Batangas are purely residing in urbanized areas. Cavite and Misamis Occidental are relatively more urban, whereas Negros Occidental is dominantly rural.

Table2. Frequency of individuals in households with OFWs Sites by Province Frequency % of Sample # of Observations Manila (Code 39) 135 12.47 1,083 Marikina (Code 74) 1,644 11.02 14,920 Batangas (Code 10) 77 17.58 438 Cavite (Code 21) 70 8.72 803 Negros Occidental 881 7.04 12,514 (Code 42) Misamis Occidental 105 10.01 1,049 (Code 45)

Table 2 presents the frequency of individuals in households with OFWs. It may be noticed only a relatively small part of the sample has households with OFWs. The average portion of individuals in households with OFWs across all sites is 11.1%. Batangas has the highest proportion of OFW households with 17.58%, followed by Manila, Marikina and Misamis Occidental.

Table3. Frequency of individuals in households that receive remittances Sites by Province Frequency % of Sample # of Observations Manila (Code 39) 92 8.49 1,083 Marikina (Code 74) 1,383 9.27 13,920 Batangas (Code 10) 103 23.52 438 Cavite (Code 21) 31 3.86 803 Negros Occidental 891 7.12 12,514 (Code 42) Misamis Occidental 126 12.01 1,049 (Code 45)

Table 3 presents the frequency of individuals living in households that receive remittances from OFWs. Similar to the finding on the proportion of individuals in households with OFWs, there are only a few individuals residing in households that receive remittances. The average portion that receives remittances across all sites is 10.71%. Batangas has the highest proportion with 23.52%, followed by Misamis Occidental, Marikina then Manila.

Table 4. Human resource development outcomesaccording to school and job indicators in CBMS data of youth ages 15 to 30, per province site Sites by Province School Working Idle Part-timing Manila (Code 39) 322 413 314 15 Marikina (Code 74) 5,028 5,339 4,245 130 Batangas (Code 10) 143 174 109 1 Cavite (Code 21) 172 307 302 9 Negros Occidental 3,566 4,359 4,356 53 (Code 42) Misamis Occidental 280 342 397 12 (Code 45) All sites 9,511 10,934 9,723 220

Table 4 presents the human resource development outcomes per provincial project site included in the CBMS data. The outcomes include 1) in school and not in work, 2) in work and not in school, 3) neither in school nor working (idle), and 4) both in school and working (part- timing). It may be seen that a significant portion of the sample in each site is in the working and not in school outcome (about 35.98%). This may be observed across all project sites. The proportion of in school and not working is 31.30%, idle is 32.00%, and part-timing is 0.72%.

Table 5. Youth employment outcomes according to worker classification in CBMS data of youth ages 15 to 30, per province site Private Public/Private Self- Family-Run Not Sites by Province Household Establishment Employed Business Working Manila (Code 39) 55 238 25 20 465 Marikina (Code 893 4,703 116 187 9,021 74) Batangas (Code 42 137 4 5 250 10) Cavite (Code 21) 55 238 25 20 465 Negros Occidental (Code 427 3,673 470 69 7,875 42) Misamis Occidental (Code 99 217 51 17 665 45) All sites 1,571 9,315 705 309 18,907

Table 5 presents the worker classifications of youth aged 15 to 30. It may be seen that there are more not working than those working (around 61.37% are not working). In terms of those working (about 11,900 respondents, or 38.62% of the sample respondents), the largest portion are those working in either private enterprises or public institutions (9,315 in total, around 78.28% of those working) followed by those working in a private household (13.20% of the working sample). There are only 5.9% self-employed, and 2.60% working in a family-run enterprise either with pay or no pay.

Table 6. Frequency of youth aged 15 to 30 in households with entrepreneurial activity Sites by Province Frequency % of Sample # of Observations Manila (Code 39) 11 1.67 659 Marikina (Code 74) 283 2.92 9,686 Batangas (Code 10) 2 0.77 259 Cavite (Code 21) 10 2.02 495 Negros Occidental (Code 70 0.87 8,008 42) Misamis Occidental (Code 8 1.14 1.14 45) All sites 384 1.94% 19,808

Table 6 presents the number of youth in households that have entrepreneurial activity. It may be seen that only a very small part of the sample has entrepreneurial activity (around 384 individuals, or 1.94% of the sample). The largest are those from Marikina with 283 individuals or 2.92%, followed by Cavite with 2.02% of their subsample.

Table 7. Percentage of youth aged 15 to 30 in households with entrepreneurial activity by industry Manuf Trans Poultr Fisher Forest Retail acturin Servic portati Constr Activity Crop y y ry Trade g e on Mining uction Manila Sites 0.46 0.00 0.00 0.00 1.29 0.46 1.11 2.12 0.00 1.48 N = 1083 Marikina Sites 0.13 0.11 0.11 0.04 6.16 0.75 0.70 1.96 0.13 1.63 N = 14920 Batangas Sites 3.88 13.70 0.00 0.00 1.83 1.37 1.83 2.28 0.00 4.33 N = 438 Cavite Sites 1.74 0.62 5.97 1.25 6.48 1.12 1.00 2.37 0.50 4.11 N = 803 Negros Occidental 3.43 2.68 1.39 0.25 15.12 0.58 0.62 6.72 0.10 2.14 Sites N = 12514 Misamis Occidental 19.26 20.59 5.15 3.15 9.15 0.57 1.62 4.58 0.10 2.76 Sites N = 1049 All Sites 2.22 2.06 0.95 0.26 9.67 6.8 0.74 4.00 0.12 1.97

Table 7 reports the proportion of the youth aged 15 to 30 that reside in households with entrepreneurial activity classified according to industry. Across all sites, it appears that most youth are engaged in retail trade-related activities (9.67%), followed by manufacturing (6.8%) and transportation (4.00%). There is a wide variation across provinces in comparison with the all-site aggregate regarding their entrepreneurial industrial intensity. In Manila, the most would be in transportation (2.12%) followed by construction (1.48%), retail trade (1.29%) and services (1.11%). Marikina has relatively more people in retail trade (6.16%), transportation (1.96%) and construction (1.63%). Batangas has quite a lot in poultry (13.70%), construction (4.33%) and crop farming (3.88%) despite being purely urban. It still has quite a lot of youth in urban-related entrepreneurial work such as retail trade, manufacturing, services, transportation and construction. Cavite has relatively more in retail trade (6.48%), fishery (5.97%), and construction (4.11%), also despite being dominantly urban. It may be that most youth in the rural area link with the urban areas which may explain why the province has strong fishery. Negros Occidental surprisingly has more youth in retail trade (15.12%) and transportation (6.72%) than in crop farming (3.43%), but it may be the case that they are able to link their agricultural networks to businesses and markets in urban areas.Misamis Occidental surprisingly has quite a lot of their youth in poultry (20.59%), crop farming (19.26%), than in retail trade (9.15%) despite being predominantly urban.

c. Empirical Models

The Link Between Remittances and the Human Resource Development Decisions of Youths

In estimating the impact of remittances on the human resource development decisions of youths, a multinomial logit regression will be used to run the following model:

Pr [HRDdecisionij] = f(Remittancesj)

Such that

HRDdecisionij ∈ [1,2,3,4] which represent human resource development decisions: 1 if the individual is in school and not working, 2 if the individual is working and not in school, 3 if the individual is neither, and 4 if the individual is part-timing both in school and working.

Remittances ∈ [0,1] which represents whether or not the individual comes from a household that receives remittances: 1 if the household receives remittances and 0 otherwise.

The Link Between Remittances and the Employment Decisions of Youths

In estimating the impact of remittances on the employment decisions of youths, a multinomial logit regression will be used to run the following model:

Pr [YouthEmploymentDecisionij] = f(Remittances )

Such that YouthEmploymentDecisionijwill be presented in two variations.

The first variation will be: YouthEmploymentDecisionij∈ [1,2,3,4,5] which represents the kind of employment the ith individual in the jth household they may choose to undertake: 1 if employed in private household, 2 if employed in an institution/establishment whether public or private, 3 if self-employed, 4 if contributing to a family-run business, or 5 if he is not working.

The second variation will be: YouthEmploymentDecisionij∈ [1,2,3,4] which takes up the same specification as the first variation but drops outcome 5. This forces the outcomes to be purely working outcomes, implying that if an individual will end up in a work state, which working state will he most likely be in with the receipt of remittances. This is similar to the setup of Karymshakov et al (2014).

Endogeneity of Remittances

In the course of linking migration and remittances to human resource-related outcomes, endogeneity may arise from the remittances variable. Migrants are determined by self-selection, meaning that in order to migrate, these households have accumulated some minimum level of human capital or have some level of wealth in order to send a migrant. The same may apply to remittances. In accounting for the possible endogeneity of remittances, this study utilizes a “first- stage” regression which provides instruments for the binary remittance variable. A logit regression is used to estimate the probability of receiving remittances (since the remittance variable is binary) conditional on the domestic wage earnings of the household, and the level of human capital and job indication of the household head. This, however, may not completely account for endogeneity because of the self-selection of migrants. It is in this light that matching methodologies may be a useful alternative in a sense that instead of improving the estimation for conditional probability of receiving remittances, remittance-receiving and non-remittance- receiving households may be compared by the same probability of receiving remittances and have nearly-identical observable characteristics.

The Link Between Remittances and the Entrepreneurial Decisions of Households

In estimating the impact of remittances on the entrepreneurial decisions of households, many studies (Karymshakov, Abdieva, Sulaimanova, and Sultakeev, 2015; Petreski, Maojsoska- Blazevski, Ristovska, and Smokvarski, 2014) have made use of multinomial logit, binary probit and instrumental variable regression techniques to determine the inclination of households and individuals to engage in entrepreneurial ventures. To approach the problem in the light of quasi- experimental methods, and to contribute to the debate using a method the requires more rigor, the study will run the following model using the impact evaluation technique, Propensity Score Matching (PSM):

Pr [EntrepreneurialDecision] = f(Remittances)

Such that

EntrepreneurialDecision∈ [0,1] which represent whether or not a household is engaged in entrepreneurship or not; 1 if household is engaged in entrepreneurship, and 0 otherwise.

Remittances ∈ [0,1] will be viewed as a treatment that households undergo. But since remittances will be viewed as a treatment, it will be necessary to provide a model for program selection, that is a model that will determine whether or not a household will undergo the treatment given certain characteristics. Remittances will therefore have a set of instruments: Demographic Characteristics which represent characteristics of individuals that reflect their literacy or those of their parents such as educational attainment, parents’ occupation, and family size and Wealth Characteristics which represent characteristics of individuals or their household’s standard of living such as income, salary, and possession of assets.

This will require the computation of the average treatment effect on the treated (ATT), or to put simply, the effect of the treatment (remittances) on the outcome (entrepreneurial decision). The ATT is simply the average differences in outcomes between treatment and control groups, the average difference in the propensity to go into entrepreneurship between households that receive remittances and those that don’t. Its computed as

푁푇 1 퐴푇푇 = 푌푇 − 푌퐶 푁푇 1

Such that YT is the outcome of the treated observation matched to the corresponding YC which is the outcome of the matched control observation. NT is the matched sample. Standard errors are generated with the use of bootstrap (Khandker, Koolwal, and Samad, 2010).

This model aims to capture the impact the remittances make on the propensities of households to engage in entrepreneurial activity, given similar characteristics of households.

IV. Results and Discussion

Table 8. Marginal Effects and RRR of Remittances on Human Resource Development Outcomes Area (Code) SP LF IDLE PART TIME All Sites 1.39*** -0.6251*** -0.752*** -0.156** (0.085) (0.09) (0.093) (0.208) ^0.0031*** ^0.0026*** ^0.0085*** Cavite Sites (21) 1.56*** -1.42*** -0.27* 0.12 (0.57) (0.69) (0.70) (0.12) ^0.00003*** ^0.0021* 158.62 Batangas Sites 1.49*** -0.1484* -1.28*** -0.062 (10) (0.443) (0.43) (0.49) (0.13) ^0.021* ^0.00007*** ^0.000 Bago Sites (45) 2.05*** -1.42*** -0.57*** -0.051 (0.21) (0.245) (0.22) (0.053) ^0.00002*** 0.0009*** 0.000 Ozamis Sites 2.53** -4.28** 1.65 0.09 (42) (1.39) (1.95) (1.63) (0.36) ^8.94e-12 *** ^0.15 0.106 NCR-Manila 1.00*** 0.07* -0.97*** -0.10 Sites (39) (0.23) (0.22) (0.27) (0.10) ^0.124 ^0.0025 0.000085 NCR-Marikina 1.18*** -0.68*** -0.44*** -0.06** Sites (74) (0.12) (0.12) (0.11) (0.04) ^0.0047 ^0.131 ^0.0023 *,**,*** denote 10%, 5% and 1% level of significance respectively. P-values based on multinomial logit regression. Standard errors in parentheses. ^ represents RRR. Base outcome for RRR is SP.

Table 8 reports the marginal effects and the relative risk ratios(RRR) of remittances for the four human resource development outcomes. Looking at marginal effects, it may be said that individuals in households with higher probability to receive remittances have a higher likelihood of being in school. This is consistent in the different province sites and especially large for the Bago sites and Ozamis sites. This confirms the findings and suggestions of Theoharides (2014), Stark and Dorn (2013), Tullao& Cabuay, 2012, Tullao et al (2007), Tabuga (2007), Ang, 2006, and Stark et al (1998). At the same time, youth that belong to households that receive remittances have lower likelihood to be in the labor force, idleness, and part-timing outcomes. This confirms the proposition of Tullao et al (2007) and Rodriguez and Tiongson (2001) that remittance receiving households may have lower labor participation rates, but this indicates that they do not turn to idleness. Looking at the RRR of remittances for the labor force, idle, and part-timing outcomes, it may be seen that the RRRs are less than one. This indicates that the probability change in the ith outcome (any one of the three) is less than the probability change in the base outcome which is schooling. This implies that a higher probability of receiving remittances will more likely go into the base outcome schooling than the other outcomes of labor force participation and idleness.

This may serve as an indication that individuals, particularly the youth, who drop from the labor force upon receiving remittances may not purely be due to leisure spending, dependence or idleness, but may perhaps be a shift towards stronger human capital accumulation outcomes. This supports the suggestions of Theoharides (2014) which suggests a liquidity effect and relative-wage effect of migration and remittances. Migration, and now with the receipt of remittances, will encourage participation in school since a household’s liquidity constraint is relaxed (liquidity effect), but will discourage those working school-aged members to work since their current wage given their current level of education is surely lower compared to their potential earnings if they invest further in their human capital or when they face the prospect of migration to a country with higher earning (relative-wage effect). This relative-wage effect also confirms the theoretical suggestions of Stark and Dorn (2013) and Stark et al (1998).

Table 9.Marginal Effects and RRR of Remittances on Youth Employment Decision Outcomes Yi = 5 (no work included) No Work Private Private/Public Self Employed Family- Household Establishment Owned All Sites 0.71*** -0.09816*** -0.435*** -0.01517*** -0.0208 (0.9) (0.04) (0.785) (0.416) (0.195) ^0.397 ^0.047 ^0.0000013 ^0.0392 Cavite Sites 2.56*** -0.68*** 0.36 -0.45 -1.79*** (21) (0.86) (0.49) (0.60) (0.40) (0.77) ^2.62e-10 ^0.91 ^1.64e-10 1.61e-31 Batangas 0.64 -0.71* 0.13 0.04 0.02 Sites (10) (0.46) (0.39) (0.38) (0.05) (0.4) ^0.00003 ^0.39 0.0052 0.003 Negros 1.38*** -0.52*** -0.77*** -011* 0.02 Occidental (0.000) (0.15) (0.20) (0.08) (0.2) Sites (45) ^2.12e-08 ^0.004 ^0.0009 ^10.54 Misamis 10.25*** -12.26*** 2.40 0.15 -0.54 Occidental (2.9) (3.36) (0.88) (0.63) (0.89) Sites (42) ^6.95e-64 ^355.33 ^3.10e-06 1.83e-33 NCR-Manila 0.18 0.002 -0.05 -0.09 -0.04 Sites (39) (0.22) (0.08) (0.20) (0.09) (0.7) ^0.827 ^0.623 ^0.0016 ^0.0106 NCR- 0.76*** -0.08** -0.6*** -0.06** -0.05* Marikina (0.12) (0.06) (0.11) (0.04) (0.03) Sites (74) ^0.0816 ^0.0198 ^5.03e-06 ^0.0057 Yi = 4 (no work not included) No Work Private Private/Public Self Employed Family- Household Establishment Owned All Sites -- -0.223 -0.0308 -0.053 0.107*** (0.043) (0.058) (0.044) (0.023) ^0.89 ^0.718 ^8.752 Cavite Sites -- -0.79 7.30 -0.54 -5.97** (21) (1.31) (2.38) (1.09) (2.78) ^3.90e-09 ^2.44e-09 ^1.70e-38 Batangas -- -1.73* 1.45* 0.20 0.08 Sites (10) (0.91) (0.92) (0.20) (0.14) ^0.00005 ^7063.79 ^875.137 Bago Sites -- -0.90** 0.77** -0.005 0.14* (45) (0.44) (0.46) (0.24) (0.075) ^0.0002 ^0.348 ^542.22 Ozamis Sites -- -22.39*** 19.13*** -0.41 -0.41 (42) (4.59) (3.68) (2.22) (2.26) ^1.12e-69 ^3.77e-13 ^5.20e-43 NCR-Manila -- 0.079 0.36 -0.30 -0.13 Sites (39) (0.277) (0.44) (0.32) (0.23) ^1.35 ^0.0016 ^0.0127 NCR- -- 0.224 -0.03 -0.14 -0.05 Marikina (0.19) (0.22) (0.12) (0.11) Sites (74) ^3.318 ^0.0012 ^0.36 Note: base category used for Yi=5 is no work, for Yi=4 is private establishment *,**,*** denote 10%, 5% and 1% level of significance respectively. P-values based on multinomial logit regression. Standard errors in parentheses. ^ represents RRR. Base outcome for RRR is SP.

Table 9 above presents the marginal effects and RRRs of remittances on youth employment decisions for all sites in the dataset. The first half of the table reports the impacts of remittances on the likelihood that the individual will end up in the five outcomes of no work, working in private household, working in private/public establishment, self-employed, and working in family-owned business. There is quite a large variation in results here, but there is one significant commonality. Noticeably, across all sites (except Manila), the marginal effects of remittances into the not working outcome is positive, whereas the marginal effects for the types of employment are all negative. In terms of RRR, all RRR for the four working outcomes are less than one, which implies that the change in probability in the ith outcome is less than the change in probability in the base outcome. This coincides with the predictions in the first model that when given the outcome of not working, individuals in households that have a higher probabilities of receiving remittances are more likely to not be working as they may be going into a school participation state.

The second half of table 9 presents the results of the second variation of the model on youth employment decisions. Note that the outcome variable for the multinomial logit model dropped the not working outcome, isolating the working-only segment of the youth observations in the sample. Noticeably, the results are different than the predictions of the first variation of the model and the combinations of outcomes are different across sites. For all sites in the sample, the marginal effects are negative for working in private household, private/public establishment, and self-employment. The RRRs for these outcomes are less than one as well. It may be noticed however, that the marginal effect for the fourth outcome, working in family-run business/enterprise is positive and that the RRR is greater than one. This implies that remittances mostly have no impact on the likelihood of an individual working in a private household, a private/public establishment, or be self-employed. It may be seen however, that receiving remittances increases the likelihood of an individual working in a family-run business. This is a peculiar finding since an examination of the sample reveals that only a very small portion is engaged in a family-run business, and there are more individuals working in a private/public establishment or working for a private household. This is consistent with the findings of Karymshakov, Abdieva, Sulaimanova, and Sultakeev (2015) in Kyrgyzstan. This may also be evidence that remittances may have an entrepreneurial enhancing effect as we will be elaborating in the next portion.

Across the different sites, results vary as well. In Cavite, remittances has practically no impact for most outcomes. It was found that remittances actually decrease the likelihood that they work for family business, which is counter intuitive to the findings for all sites. Examining Cavite, it may be seen that it has the lowest portion of households receiving remittances (table 3) and more youth being idle than in school (table 5). Most of the youth in Cavite are working in private/public establishment.

In Batangas, Bago, and Ozamis, it may be seen that the impact of remittances is significant and negative for private household and significant but positive for private/public enterprises and is positive. Additionally, remittances has a positive, albeit small, effect on the likelihood of being in a family-owned business in Bago. This may be an indication that remittances acts more as a liquidity-relaxer for households, enabling their children to go into school, not work for private households (presumably as domestic help), and increase their desire to be employed in an establishment. There is only weak evidence in Bago that remittances may now encourage people to work in family-run businesses.

Manila and Marikina report similar findings, where remittances have no significant impact on the likelihood of being in any work classification.

Overall, what appears in the regression for all sites, is the increase in the propensity to be working in a family-run business. This may indicate that household receiving remittances may be using remittances to fuel school participation and household/family-run entrepreneurial ventures. It may be said therefore that remittances received by the household however does not encourage entrepreneurship for the youth as self-employment, but may serve as capital for the the household to engage in entrepreneurship and their working age children to help in their business. We investigate the impact of remittances on the propensity that a household may be engaged in entrepreneurial activity in the next model. We also classify the impact of remittances on the propensity for entrepreneurial activity according to industry.

Table 10. ATT of remittances on the likelihood of entrepreneurial activities for All Sites Activity Wealth Wage Household Wage and Effect Head Job HHH Job Summary Indicator Indicator Entrepreneurship 0.021 0.019 0.031 0.033 (0.006) (0.002) (0.002) (0.003) Positive [3.708] [7.497] [13.022] [10.857] Crop 0.056 0.013 0.013 0.014 (0.007) (0.003) (0.003) (0.004) Positive [8.616] [3.780] [4.424] [3.922] Poultry -0.003 0.014 0.017 0.014 (0.006) (0.003) (0.003) (0.003) Positive [-0.463] [4.978] [6.724] [4.513] Fishery -0.006 0.001 0.000 0.001 Weakly (0.003) (0.002) (0.001) (0.002) Negative [-1.779] [0.744] [0.236] [0.405] Forestry -0.003 -0.001 0.000 -0.001 No (0.002) (0.001) (0.001) (0.001) Significant [-1.374] [-0.994] [0.051] [-1.208] Effect Retail Trade -0.022 0.038 -0.003 0.033 Mixed (0.011) (0.006) (0.005) (0.007) Positive [-1.876] [6.414] [-0.487] [5.002] Manufacturing 0.060 -0.008 -0.008 -0.007 Mixed (0.003) (0.002) (0.002) (0.003) Weakly [18.383] [-3.260] [-3.635] [-2.843] Negative Service 0.007 0.004 0.003 0.026 (0.003) (0.001) (0.001) (0.008) Positive [2.183] [2.818] [2.798] [3.012] Transportation -0.014 0.013 -0.012 0.009 (0.008) (0.004) (0.004) (0.005) Mixed [-1.784] [3.011] [-3.007] [1.980] Mining 0.001 0.001 0.001 0.002 Weakly (0.001) (0.000) (0.000) (0.000) Positive [1.515] [3.714] [7.555] [4.783] Construction 0.068 0.014 0.010 0.015 (0.005) (0.002) (0.002) (0.002) Positive [14.050] [7.078] [5.997] [6.974] Note: Standard errors in ( ), t-ratios in [ ]. Highlighted cells represent significant findings at 5%.

Table 10 summarizes the ATTs of remittances on the likelihood of being engaged in an entrepreneurial activity in general and for specific industries for all sites. Four different combinations of the observable characteristics have been used so as to be able to meet the balancing property, meaning that control and treatment groups are observationally comparable.

It may be seen that the ATT for general entrepreneurship is positive. This implies that on average, given comparable wealth, wage income, and household head employment, households that receive remittances have a 1.9-3.3% higher likelihood of being engaged in entrepreneurial activity. This reinforces the suggestions of Cabegin (2006) and Yang (2006). This coincides with the results in the previous two models. Households that receive remittances shift their youth from work outcomes to school outcomes, but when the youth are in a state of work, they are more likely to be working for family-run enterprises. The finding here implies that remittances are used to fund entrepreneurial ventures, but looking at the magnitude of the ATT, only by a little extent.

Looking at different ventures across industries, it may be seen that the effect on crop farming, poultry raising, service, and construction are consistently positive. This may be a reflection of the property of the sample containing all sites wherein there are more in urban areas (table 1), hence an encouraging impact on services (albeit small, 0.3-2.6%) and construction (about 1.0- 6.8%), but there are province sites that are highly intensive in crop-farming and poultry raising (Batangas, Negros Occidental, and Misamis Occidental) so the ATTs are quite high for crop- farming (1.3-5.6%) and poultry raising (1.4-1.7%). The positive impact on construction is also quite expected as remittances are often used for the extension or the expansion of migrants’ homes and may not necessarily be used as capital for new construction-related businesses.

The effect on mining is weakly positive although consistently significant across all models (despite mining having the lowest incidence across sites. Check table 7). Although retail trade is a popular venture across province sites, the impact of remittances is not robust as there is a negative significant ATT when controlling for wealth, but positive significant ATTs when controlling for wages and the job of the household head. Transportation is not robust as well with negative ATTs when controlling for wealth and household head employment, but positive ATTs when controlling for wage and the combination of wage and household head employment. Furthermore, there are weak negative effects on fishery despite it being strong in Cavite and Misamis Occidental (although they only contribute very few observations), and a mixed, non- robust weak negative for manufacturing, which is not very strong across province sites.

Table 11. ATT of remittances on the likelihood of entrepreneurial activities for Cavite Sites (Code 21) Activity Wealth Wage Household Wage and Effect Head Job HHH Job Summary Indicator Indicator Entrepreneurship -0.027 -0.029 0.002 -0.028 No (0.026) (0.023) (0.021) (0.026) Significant [-1.057] [-1.266] [0.0102] [-1.064] Effect Crop -0.018 -0.018 -0.006 -0.019 No (0.023) (0.019) (0.016) (0.020) Significant [-0.790] [-0.961] [-0.385] [-0.944] Effect Poultry -0.020 0.023 -0.011 0.012 No (0.014) (0.022) (0.016) (0.024) Significant [-1.422] [1.063] [-0.702] [0.495] Effect Fishery -0.018 -0.023 0.024 -0.027 No (0.034) (0.030) (0.023) (0.031) Significant [-0.534] [-0.771] [1.014] [-0.878] Effect Forestry 0.000 0.000 0.013 0.000 Weakly (0.000) (0.000) (0.003) (0.000) Positive […] […] [4.625] […] Retail Trade -0.057 -0.072 -0.073 -0.069 (0.038) (0.041) (0.039) (0.047) Negative [-1.488] [-1.752] [-1.882] [-1.449] Manufacturing 0.000 0.000 0.011 0.000 Weakly (0.000) (0.000) (0.003) (0.000) Positive […] […] [4.392] […] Service 0.000 0.027 0.017 0.031 (0.000) (0.016) (0.003) (0.016) Positive […] [1.639] [5.265] [1.949] Transportation 0.005 -0.024 0.006 -0.005 No (0.025) (0.028) (0.017) (0.024) Significant [0.215] [-0.855] [0.349] [-0.214] Effect Mining 0.000 0.014 0.002 0.020 (0.000) (0.009) (0.001) (0.011) Positive […] [1.530] [1.7141] [1.778] Construction 0.030 0.005 0.056 0.007 Weakly (0.025) (0.011) (0.006) (0.011) Positive [1.219] [0.474] [9.827] [0.588] Note: Standard errors in ( ), t-ratios in [ ]. Highlighted cells represent significant findings at 5%.

Looking at the compiled ATTs for Cavite (Table 11), we find that the impact of remittances is quite lacklustre. The impact on general entrepreneurship, crop-farming, poultry-raising, fishery, and transportation is statistically zero. This is surprising since the incidence of fishery-related businesses in households is quite strong in households with the youth. Going back to table 3, however, it may be found that the Cavite sites have the lowest incidences with regard to the presence of OFWs and the receipt of remittances. This is consistent with the findings on youth employment decisions in Table 9 as well, wherein those receiving remittances are less likely to be working for a family-run business. The only positive impact remittances has is on services and mining, and weakly positive for manufacturing, forestry, and construction. The impact is negative for retail trade despite Cavite having a high incidence of retail-trade ventures. These warrants a closer investigation into the participating sites.

Table 12. ATT of remittances on the likelihood of entrepreneurial activities for Batangas Sites (Code 10) Activity Wealth Wage Household Wage and Effect Head Job HHH Job Summary Indicator Indicator Entrepreneurship 0.019 0.019 0.009 0.006 No (0.016) (0.013) (0.008) (0.011) Significant [1.171] [1.457] [1.136] [0.554] Effect Crop -0.006 -0.011 0.030 -0.007 No (0.011) (0.008) (0.008) (0.011) Significant [-0.563] [-1.422] [3.541] [-0.630] Effect Poultry 0.027 0.133 0.105 0.143 (0.027) (0.028) (0.016) (0.032) Positive [1.004] [4.776] [6.645] [4.469] Fishery 0.000 0.000 0.000 0.000 No (0.000) (0.000) (0.000) (0.000) Significant […] […] […] […] Effect Forestry 0.000 0.000 0.000 0.000 No (0.000) (0.000) (0.000) (0.000) Significant […] […] […] […] Effect Retail Trade 0.003 -0.019 -0.027 -0.026 (0.016) (0.011) (0.010) (0.013) Negative [0.172] [-1.665] [-2.668] [-2.013] Manufacturing 0.000 0.004 0.015 0.005 Weakly (0.000) (0.007) (0.004) (0.008) Positive […] [0.566] [4.004] [0.560] Service 0.011 0.036 0.011 0.035 (0.011) (0.011) (0.006) (0.014) Positive [0.971] [3.229] [2.008] [2.576] Transportation 0.022 0.009 0.032 0.014 Weakly (0.014) (0.009) (0.005) (0.012) Positive [1.54] [0.966] [5.930] [1.128] Mining 0.000 0.000 0.000 0.000 No (0.000) (0.000) (0.000) (0.000) Significant […] […] […] […] Effect Construction 0.005 0.017 0.040 0.024 (0.011) (0.007) (0.006) (0.012) Positive [0.776] [2.358] [6.569] [1.972] Note: Standard errors in ( ), t-ratios in [ ]. Highlighted cells represent significant findings at 5%.

Table 12 reports the ATTs for Batangas. It may be seen that there is no significant effect for general entrepreneurship, crop-farming, fishery, forestry, and mining. The findings for fishery, forestry and mining are understandable since there is zero incidence in these industries (table 7), but it is surprising that there is no significant effect on crop-farming given that there is a fairly-high incidence for the industry. The finding for general entrepreneurship is quite unexpected as well since Batangas has the highest relative frequency for individuals in households that receive remittances. This may be explained partly due to the low incidence of general entrepreneurial ventures. Partly, this may be due to the relatively small sample provided by Batangas compared to the other sites. A closer inspection on the nature of each participating barangay may prove enlightening as well.

Despite the Batangas sites being purely urban, remittances have a strong positive effect on the likelihood of being in poulty-raising (10.5-14.3%) which is evidently the industry with the highest incidence. The effect is also positive for services (1.1-3.6%) and construction (1.7-4.0%), and only weakly positive for manufacturing and transportation. Surprisingly, the impact on rtail trading is negative despite it having a relatively high incidence.

Table 13. ATT of remittances on the likelihood of entrepreneurial activities for Negros Occidental Sites (code 45) Activity Wealth Wage Household Wage and Effect Head Job HHH Job Summary Indicator Indicator Entrepreneurship 0.021 0.011 0.013 0.013 (0.005) (0.004) (0.004) (0.005) Positive [4.581] [2.726] [3.447] [2.623] Crop 0.050 0.016 0.013 0.021 (0.007) (0.006) (0.006) (0.007) Positive [7.355] [2.848] [2.183] [3.021] Poultry 0.037 0.005 0.021 0.008 (0.006) (0.004) (0.005) (0.005) Positive [6.147] [1.232] [4.607] [1.441] Fishery -0.006 0.001 -0.001 0.001 No (0.003) (0.003) (0.003) (0.003) Significant [-1.888] [0.493] [-0.248] [0.479] Effect Forestry 0.000 -0.001 -0.002 0.043 No (0.001) (0.001) (0.001) (0.051) Significant [0.212] [-0.556] [-1.263] [0.853] Effect Retail Trade 0.024 0.050 -0.012 0.044 (0.012) (0.010) (0.010) (0.012) Positive [1.895] [4.931] [-1.148] [3.632] Manufacturing -0.015 -0.011 -0.014 -0.011 (0.004) (0.004) (0.004) (0.004) Negative [-3.618] [-2.827] [-3.320] [-2.462] Service 0.004 0.001 -0.000 0.002 No (0.003) (0.002) (0.002) (0.003) Significant [1.388] [0.494] [-0.218] [0.661] Effect Transportation -0.016 0.023 -0.016 0.018 (0.009) (0.007) (0.008) (0.009) Mixed [-1.781] [3.167] [-2.097] [2.104] Mining 0.003 0.000 0.001 0.001 Weakly (0.001) (0.000) (0.000) (0.000) Positive [4.885] [2.000] [3.458] [1.540] Construction -0.004 0.005 -0.001 0.006 No (0.005) (0.004) (0.004) (0.004) Significant [-0.931] [1.469] [-0.282] [1.304] Effect Note: Standard errors in ( ), t-ratios in [ ]. Highlighted cells represent significant findings at 5%.

Table 13 reports the ATTs for the Negros Occidental Sites. It may be seen that impact on general entrepreneurship is consistently positive (1.1-2.1%),although Negros Occidental has one of the lower incidence of general entrepreneurial activity and remittances. This may partly be due to the dominantly rural setting of the sites from this province. Receiving remittances may serve as the exogenous income increase needed to help fund entrepreneurial ventures as it may be seen that Negros Occidental has a very large portion that is poor. Remittances may then be a view as a channel to engage in entrepreneurship to get out of poverty. This is largely evident as an exogenous income transfer such as remittances encourages crop-farming, poultry-raising, and retail trading which are common entrepreneurial ventures for rural areas. It discourages manufacturing, which may be a very costly industry, but presents a mixed impact for transportation which is also an industry with high incidence in the province (table 7).

Table 14. ATT of remittances on the likelihood of entrepreneurial activities for Misamis Occidental Sites (Code 42) Activity Wealth Wage Household Wage and Effect Head Job HHH Job Summary Indicator Indicator Entrepreneurship 0.054 0.000 0.046 0.000 (0.023) (0.000) (0.010) (0.000) Positive [2.388] […] [4.780] […] Crop 0.429 0.0228 0.399 0.225 (0.076) (0.065) (0.054) (0.076) Positive [5.627] [3.511] [7.385] [2.969] Poultry 0.354 0.256 0.381 0.234 (0.076) (0.062) (0.044) (0.077) Positive [4.648] [4.097] [8.739] [3.027] Fishery -0.076 -0.028 -0.082 -0.047 (0.028) (0.032) (0.033) (0.039) Negative [-2.738] [-0.876] [-2.518] [-1.201] Forestry 0.052 -0.010 0.031 0.000 No (0.043) (0.032) (0.050) (0.000) Significant [1.197] [-0.322] [0.626] […] Effect Retail Trade 0.135 -0.109 -0.022 -0.089 (0.059) (0.042) (0.041) (0.050) Negative [2.286] [-2.559] [-0.538] [-1.798] Manufacturing 0.000 0.004 0.002 0.002 No (0.000) (0.010) (0.002) (0.012) Significant […] [0.366] [1.261] [0.174] Effect Service 0.089 0.024 0.020 0.027 (0.031) (0.019) (0.005) (0.024) Positive [2.850] [1.222] [3.934] [1.108] Transportation -0.152 -0.145 -0.106 -0.129 (0.038) (0.039) (0.040) (0.042) Negative [-4.041] [-3.713] [-2.624] [-3.043] Mining 0.000 0.000 0.000 0.000 No (0.000) (0.000) (0.000) (0.000) Significant […] […] […] […] Effect Construction 0.000 0.060 0.019 0.057 (0.000) (0.017) (0.005) (0.024) Positive […] [3.562] [3.784] [2.347] Note: Standard errors in ( ), t-ratios in [ ]. Highlighted cells represent significant findings at 5%.

Looking at the ATTs for the Misamis Occidental Sites (Table 14), it may be seen the remittances has a positive impact on general entrepreneurship (4.6-5.4% although significant only for two out of four models). This is a significant finding since Misamis Occidental has a relatively high incidence for the receipt of remittances although quite a low incidence for entrepreneurial activity (Table 6). As seen in table 7, the sites in the province are frequently engaged in crop- farming and poultry raising, and the impact of remittances is to fuel these activities further as can be seen in the very large ATTs (22.5-42.9% for crop farming, 23.4-38.1 for poultry-raising). The impact is also positive for service (around 2-8.9%) although significant only for two models, and construction (1.9-6.0%). There is no significant effect for forestry, manufacturing and mining.

The impact on fishery is consistently negative partly due to the industry having relatively lower incidence compared to crop-farming and poultry-raising. Though retail trade has the third highest incidence for the sites in the province (9.15%, table 7) the impact of remittances is not robust. The impact is positive when controlling for wealth, but negative when controlling for the wage and household head employment, which may indicate a shifting toward crop-farming and poultry-raising, although new evidence must be produced to support this.

Table 15. ATT of remittances on the likelihood of entrepreneurial activities for Manila Sites (Code 39) Activity Wealth Wage Household Wage and Effect Head Job HHH Job Summary Indicator Indicator Entrepreneurship 0.006 0.022 0.067 0.014 (0.013) (0.010) (0.009) (0.014) Positive [0.480] [2.150] [7.629] [0.981] Crop 0.000 0.001 0.002 0.001 Weakly (0.000) (0.002) (0.001) (0.003) Positive […] [0.703] [2.232] [0.507] Poultry 0.000 0.000 0.000 0.000 No (0.000) (0.000) (0.000) (0.000) Significant […] […] […] […] Effect Fishery 0.000 0.000 0.000 0.000 No (0.000) (0.000) (0.000) (0.000) Significant […] […] […] […] Effect Forestry 0.000 0.000 0.000 0.000 No (0.000) (0.000) (0.000) (0.000) Significant […] […] […] […] Effect Retail Trade 0.009 0.013 0.018 0.013 (0.009) (0.006) (0.003) (0.007) Positive [0.977] [2.120] [6.932] [1.960] Manufacturing 0.002 0.000 0.004 0.000 Weakly (0.005) (0.000) (0.001) (0.000) Positive [0.308] […] [3.295] […] Service 0.005 0.004 0.012 0.003 Weakly (0.008) (0.007) (0.002) (0.005) Positive [0.658] [0.533] [5.598] [0.659] Transportation 0.001 0.007 0.020 0.006 Weakly (0.008) (0.004) (0.003) (0.006) Positive [0.123] [1.576] [7.216] [1.137] Mining 0.002 0.006 0.002 0.004 Weakly (0.005) (0.004) (0.001) (0.004) Positive [0.443] [1.409] [2.510] [0.880] Construction 0.004 0.008 0.009 0.007 Weakly (0.008) (0.005) (0.002) (0.006) Positive [0.472] [1.560] [4.717] [1.237] Note: Standard errors in ( ), t-ratios in [ ]. Highlighted cells represent significant findings at 5%.

Table 15 reports the ATTs for the Manila Sites. It may be seen that the impact of remittances is quite weak for most industries, except perhaps on retail trade. This is quite surprising for an area in the NCR which is the centre of economic activity. This may partly be due to employment decisions of the youth which are dominantly in public/private establishments rather than self- employment and family-run businesses. The impact on general entrepreneurship is still positive (2.2-6.7%) albeit only for two models. Manila has relatively low remittance and entrepreneurial incidence but the effect may still be seen.

There is no significant impact on poultry-raising, fishery and forestry, and the impact on crop- farming, manufacturing, and mining is absolutely weak, although positive, but this may be expected since Manila is a purely urbanized area with nearly no space for such activities. The same cannot be said for services, transportation and construction, however, because these are activities that are usually available in urban areas. The impact on transportation and construction may not be surprising however since the markets for these industries are controlled heavily by big players, and not much room is available for micro-small-medium enterprises. It would mostly depend on the type of transportation and the process of construction that the would-be entrepreneur would like to enter.As for services, we speculate that capital requirements to start service-based businesses may be too high and though remittances encourage it, it may not be enough to be a significant driving force. It may be seen that retail trade has consistently positive ATTs (1.3-1.8% although insignificant when controlling for wealth) since it retail trade is not a capital-intensive form of entrepreneurial venture.

Table 16. ATT of remittances on the likelihood of entrepreneurial activities for Marikina Sites (Code 74) Activity Wealth Wage Household Wage and Effect Head Job HHH Job Summary Indicator Indicator Entrepreneurship 0.020 0.028 0.051 0.054 (0.007) (0.004) (0.004) (0.005) Positive [2.849] [6.657] [13.860] [11.055] Crop -0.003 -0.003 -0.002 -0.003 No (0.002) (0.002) (0.002) (0.002) Significant [-1.492] [-1.670] [-1.099] [-1.613] Effect Poultry 0.001 0.001 0.001 0.001 Weakly (0.001) (0.000) (0.000) (0.001) Positive [0.772] [2.171] [4.347] [1.779] Fishery 0.000 0.000 0.002 0.000 Weakly (0.001) (0.001) (0.000) (0.001) Positive [0.164] [0.700] [5.326] [0.711] Forestry 0.002 0.001 0.001 0.001 Weakly (0.002) (0.000) (0.000) (0.001) Positive [1.328] [2.493] [3.705] [1.962] Retail Trade -0.015 0.011 -0.002 0.009 No (0.011) (0.009) (0.009) (0.009) Significant [-1.412] [1.241] [-0.243] [0.925] Effect Manufacturing -0.008 -0.012 -0.011 -0.012 Weakly (0.005) (0.005) (0.004) (0.005) Negative [-1.513] [-2.702] [-2.533] [-2.623] Service 0.007 0.006 0.004 0.006 Weakly (0.003) (0.002) (0.002) (0.002) Positive [2.117] [2.815] [2.236] [2.478] Transportation -0.011 -0.012 -0.023 -0.010 (0.007) (0.007) (0.006) (0.007) Negative [-1.581] [-1.771] [-3.553] [-1.535] Mining 0.000 0.001 0.002 0.001 Weakly (0.001) (0.001) (0.000) (0.001) Positive [0.164] [1.588] [5.935] [1.509] Construction 0.013 0.024 0.014 0.024 (0.003) (0.002) (0.001) (0.002) Positive [4.699] [11.338] [14.387] [10.016] Note: Standard errors in ( ), t-ratios in [ ]. Highlighted cells represent significant findings at 5%.

Table 16 presents the ATTs for the Markina Sites. As may be seen, the impact of remittances on general entrepreneurship is positive (2.0-5.4%). This may be expected since Marikina has the highest incidence of entrepreneurial activity in the sample although it does not have a relatively high incidence of remittances receipts (only 9.27% of the youth live in households that receive remittances).

There is no significant impact on crop-farming, which may be expected since Marikina is an urban area. There is a weak positive effect on poultry-farming, fishery, forestry and mining, which may indicate businesses that have some external linkage with other regions. Surprisingly, remittances have no significant impact on the likelihood for retail trade, which has the highest incidence of entrepreneurial activity in the area (table 7). At the same time there is a negative impact on manufacturing ( 1.1-1.2% lower likelihood) and transportation (1.2-2.3% lower likelihood). This may reveal that the role of remittances in the area may not be for encouraging entrepreneurship since Marikina, which is a known manufacturer of shoes, may already have sufficient entrepreneurial ventures. This may be seen in the previous multinomial logit regressions on human resource development and youth employment outcomes, wherein a higher probability of receiving remittances contributes more to school-related outcomes among the youth rather than employment-related or business-related outcomes. This may indicate that above all outcomes, those in Marikina tend to use remittances more to finance education rather than employment or entrepreneurship. Remittances however, have a positive impact on service- based businesses (0.4-0.7%) and construction (1.3-2.4%), which indicates a shift away from simple retail trading (which usually does not require high capital) and towards more capital- intensive service-based business.

V. Conclusion and Recommendations

M&R have been given a negative perception by some in society. Migration is often associated with brain drain, the erosion of family ties as members become immersed in very different cultures, and disruptive effects on the schooling of children left behind especially in the case of parental migration (Wang, 2012). Remittances have been perceived to induce dependence or idleness among working age members of households (Tullao, Cortez, and See, 2007), and although overall beneficial, have been known to exclusively smoothen consumption and leisure spending (Tullao, Cortez, and See, 2007; Tabuga, 2007).

In this study however, we find direct evidence that despite these known negative impacts, M&R can result in greater human capital accumulation, which confirms the hypothesis put forth by Stark and Dorn (2013) and Stark et al (1997). We also find direct evidence that remittances, as an exogenous income transfer, increases the likelihood that households are engaged in entrepreneurial ventures.

Using 2015 CBMS data with YEE and SPIS indicators, which covers respondent sites from the provinces of Cavite, Batangas, Misamis Occidental, Negros Occidental, and two cities from the NCR (Manila and Marikina), this study estimates the impact of remittances on human resource development decisions, youth employment decisions, and the likelihood for entrepreneurship of the youth aged 15 to 30. Using a multinomial logitregression, we find that remittances shifts the youth away from labor participation and idleness and into school participation. Furthermore, using a multinomial logit regression, remittances have no standard impact on the likelihood that a young person will be working in a private household, private/public establishment, or self- employed (although this varies with the various provinces and cities) since a person will more likely be in a non-working state (school participation). However, remittances are found to increase the likelihood of working in a family-run enterprise, which may indicate that remittances encourage entrepreneurial family ventures. Using the treatment evaluation method PSM to generate ATTs on the impact of remittances on the likelihood of entrepreneurial ventures, it was found that households that receive remittances have a higher likelihood of being engaged in an entrepreneurial activity. However, the impact on the likelihood of entrepreneurship differs across industries.

What can we make out of this? M&R can serve as an avenue to improve a country’s work force through greater investment in human capital via liquidity and aspiration. As Theoharides (2014) puts it, with remittances, households can attain higher levels of educational investment which may be unreachable given domestic wages and incomes. At the same time, with a relaxed liquidity constraint, a person would more likely go into school to increase his human capital given the knowledge that his relative-wage is higher when he has higher human capital in the future, than to work given his current level of human capital which is lower. In this light, there is a need to smoothen the channels of remittances, and reduce financial and administrative costs of sending remittances.

The evidence also reveals that remittances have an encouraging effect for households to engage in entrepreneurial ventures. However, the proportion of households in the sample that are engaged in some form of entrepreneurship is very low. This may be expected since the financial and administrative costs of setting up businesses are quite high. In cases of rural or near-poor households, however, remittances may be the boon needed to finance retail entrepreneurship, which has the highest incidence across all sites. Remittances may not serve as sufficient capital, but it is an exogenous income transfer which may be allocated accordingly.

However, it cannot be denied that a big question remains: how exactly do migrant households manage the remittances they receive? What is needed is a direct assessment of how remittances may be managed or mismanaged among migrant households. There is a need to persuade migrant households to prioritize education for the youth above all and improve their commitments toward human capital accumulation and to urge migrant households to consider pursuing entrepreneurial ventures, rather than spending on leisure and luxuries.

Manila and Marikina both exhibit similar characteristics perhaps since they are both located in the NCR. They also have nearly the same relative incidence of OFWs and remittances. The drive in these locations really is to use remittances as an avenue to invest in human capital rather than entrepreneurship, especially since the NCR is concentrated with large companies that hire their own employees or professionals that usually require secondary to tertiary level education. The youth in these areas are also mostly taking tertiary education, or high school graduates or college graduates. M&R is desirable for households here to finance education rather than spur entrepreneurship, although venturing into entrepreneurship may prove to be rewarding for some with low risk aversion and the sufficient capital to finance larger ventures.

The respondent sites in Batangas and Cavite are mostly urban, although there are some rural sites in Cavite. These two areas exhibit quite different characteristics even if they belong to the same region (CALABARZON). There are relatively more OFWs and a higher remittance incidence in Batangas than in Cavite. Both exhibit the shifting of the youth from labor participation to school participation. When it comes to employment outcomes of the youth however, there is mostly no significant impact in Cavite but a lower likelihood to be in a family business. This is evident in their ATTs where remittances was found to have nearly no impact in encouraging entrepreneurship in general. This indicates that the thrust in Cavite may not be to encourage entrepreneurship. Surprisingly, among the youth in the province, there are more that are idle than those in school, and the number of idle youth is nearly the same as the number of working youth. A close inspection of the distribution of educational attainment among the youth (Appendix) in the Cavite sites reveals that most of the youth are only high school graduates, and very few are college graduates. This also reveals that there is a great proportion of the youth that have not yet finished primary or secondary education even though respondents from the Cavite sites are dominantly non-poor (Appendix). There is a strong need for local governments in Cavite to push its citizens to pursue higher educational and human capital outcomes, even though entrepreneurship is not the obvious priority. Entrepreneurship also appears to be an unpopular motivation for remittances in Batangas as evidenced by the general entrepreneurship ATTs. They do however have higher incidences of poultry-raising which is enhanced by remittances, and their service-based and construction-related ventures are more responsive to remittances. The sites in Batangas are reported to have more non-poor than poor, and it appears that their drive is strongest toward higher educational outcomes as evidenced by the distribution of educational attainment among the youth. Most of their youth have not yet finished secondary education, but there are more college graduates than high school graduates among the youth in the Batangas sites. It might be that their drive is toward getting better employment in the NCR (where the demand for professionals is stronger) instead of self-employment or entrepreneurial developments for their respective localities. It is desirable, however, that local governments encourage investment in entrepreneurial activities in the area so as to spur the growth and development of the province.

The Negros Occidental sites are dominantly rural and the number of poor nearly equals the number of non-poor in the region. There is no surprise then that the incidence of OFWs and remittances, and general entrepreneurial activities are relatively low for the province with the most observations in the sample. We notice, however that there is a high incidence of retail trade in these sites. We also find that remittances have very strong impacts on general entrepreneurial activities, crop-farming, poultry-raising, and retail trade. This paints a clear picture on the motivations of households. Remittances allow households to invest in their youth’s human capital, which enables them to work in both private/public establishments and family-run businesses, outcomes that may have been closed to them prior to the receipt of remittances. Crop-farming and poultry-raising which are mainly rural ventures are further enhanced by remittances. Retail trade is enhanced by remittances as well, and is the logical and usual type of investment that households engage in to get out of poverty. Lastly, it is evident in the distribution of educational attainment in the province that the largest portion of their youth are only high school graduates, although this is followed by college graduates, but there are more that have not finished primary or secondary education. It has been documented previously that M&R serve as a very strong avenue for households to make use of wage differentials across domestic regions or countries in order to get out of poverty and enhance their welfare (Pernia, Pernia, Ubias and San Pascual, 2014). Similar to Cavite, Negros Occidental also has more youth that are idle than those in school, so it is imperative for local government to look into how households manage remittances, and how much they prioritize education as their way to get out of poverty.

The Misamis Occidental sites are dominantly urban, and the number of poor youths is about half the number of non-poor youths. The sites from the province also report a relatively high incidence of OFWs and remittances, although the incidence of entrepreneurial activities is relatively low. The picture for Misamis Occidental is similar to that of Negros Occidental, wherein remittances encourages youths to be engaged more in school than in work, but if they are working they are more likely to be engaged in private/public establishments and significantly less likely in private households. The likelihood for general entrepreneurial activities is quite responsive for the area, and is very strong for crop-farming, poultry-raising, services and construction, since this may be the primary source of livelihood for the province sites. Retail trade, however, is discouraged by remittances on average across models. It may be that the households’ priority for remittances in this province is to finance education to gain access to occupations that require professional skills or tertiary level education. Looking at the distribution of educational attainment for the sites in this province, we find that the largest portion are those that have not yet finished primary and secondary school, followed by high school graduates. College graduates are relatively few in this province. What is striking, however, much like Cavite and Negros Occidental, the number of idle youth is higher than those in school.

Overall, what is needed to enhance the impact of remittances on these human capital accumulation outcomes is an investigation into the implementation and enforcement of public education in these provinces. Especially more so that public education, primary and secondary education is supposed to be free. Despite the negative associations that society has given to M&R, learning to channel the benefits that come along with it into more productive outcomes is what will allow households to find an optimal solution in getting out of poverty and enhancing welfare.

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Appendix

EDUCATIONAL DISTRIBUTION ACROSS PROVINCE SITES

POVERTY ACROSS PROVINCE SITES

| Income poor Province | Non-Poor Poor | Total ------+------+------Batangas | 1,161 368 | 1,529 Cavite | 1,931 623 | 2,554 NCR 1st Dist | 2,806 677 | 3,483 Misamis Occidental | 2,165 1,184 | 3,349 Negros Occidental | 22,777 22,240 | 45,017 NCR 2nd Dist | 41,380 8,008 | 49,388 ------+------+------Total | 72,220 33,100 | 105,320