And What About the Family Back Home? International Migration and Happiness

And What About the Family Back Home? International Migration and Happiness

Fernando Borraz, Susan Pozo, Maximo Rossi

ABSTRACT

In this study we use data on subjective well being and migration in Cuenca, one of the

Ecuador's largest cities. We examine the impact of migration on the happiness of the

family left behind. We use the propensity score matching estimator to take into account

the endogeneity of migration. Our results indicate that migration reduces the happiness of

those left behind. We also find that the monetary inflows (remittances) that accompany

migration do not increase happiness levels among recipients. These results suggest that

the family left behind cannot be compensated, for the increase in unhappiness that it

sustains on account of the emigration of loved ones, with remittances from abroad.

JEL Codes: A12, F22, I31.

Keywords: Happiness, migration, remittances.

A. Introduction

International migration can be motivated by a number of factors. Some migrate in

order to escape dire poverty. Others go into exile in search of religious or political

freedoms. Some move to invest in education, others to join relatives abroad, and still

others in pursuit of adventure and new opportunities. While a great deal of research has

analyzed the short-run and long-run outcomes for those that move to new areas (e.g.

Borjas, 2002; Chiswick, 2002; Smith, 2003; Card, 2005) in this paper we turn out focus

to the family left behind. In particular we consider whether the international migration of

one or more family members serves to increase or decrease the level of "happiness" of

household members who remain in the home community.

There are a number of reasons for expecting that migration and its potential byproducts

will continue to touch ever increasing numbers of individuals in the world. First

of all, the incidence of international migration has been rising. In 1970, about 2.2 percent

of the world’s population lived in a country other than their country of birth. In contrast,

by 2000, the foreign born accounted for close to 3 percent of the world’s population

(International Organization for Migration 2005, p. 379). A second reason for expecting

rising impacts of migration is due to the observation that emigration impacts more than

those moving to another country. Barriers to migration often make it difficult for whole

families to migrate. Therefore the incidence of migration-impacted households can

change with public policy which ultimately accentuates family separations and

dislocations. Massey (2006) has noted that increased enforcement at the US/Mexico

border implemented to stem illegal immigration has had the unintended effect of

extending the stay of unauthorized immigrants who would normally periodically return

home. Longer stays by unauthorized immigrant are likely to lead to longer-lasting and

permanent family separations. A third reason for expecting migration to touch larger

portions of the world population stems from policy shifts in immigration legislation

toward preferences for skill labor migration at the expense of family reunification. If

legislation continues to be developed along these lines, it follows that a larger circle of

individuals will be affected by migration due to longer-run family separations. Finally,

continued rapid technological progress of the sort observed in the more recent decades is

likely to continue, further reducing transportation and communication costs, easing travel

and facilitating international migration (UNDP, 1999).

Given the expectation of greater family dislocations via migration, what are our

priors on the impact of migration on happiness? We hypothesize that migration reduces

happiness levels of the family left behind. The emigration of a household member is

likely to directly cause disruptions in the household since the absent household member

may have been contributing to the household via market or house work. Thus, in addition

to discomfort stemming from the absence of loved ones, household and monetary

responsibilities now need to be assumed by other family members. The reallocation of

household chores and market work is likely to be costly for the remaining family

members, reducing happiness levels.

In this paper we also explore a second mechanism by which migration may

impact the household. Many immigrants remit money home. In fact, the raison d'etre

for migration in the first case is often couched in terms of obtaining opportunities to remit

money home. These monetary inflows, which many migrant households4 eventually

enjoy, may compensate in whole or in part for the losses felt on account of the absent

household member. In sum, we therefore seek to explore two questions. In the first we

ask whether migration decreases the level of happiness of the family back home. Next

we explore whether the monetary by-products (remittances) that often follow migration

increase the happiness levels of those households.

In order to examine the impact of migration on the happiness of the family left

behind we exploit information contained in the Discrimination and Economic Outcomes

Survey undertaken in Ecuador in 2006 under the auspices of the Inter-American

Development Bank.5 The survey contains information from 665 households: 480 in

Cuenca and 185 in San Fernando. In this paper we only include households residing in

Cuenca. Cuenca is the third largest city in Ecuador with nearly a half million inhabitants

while San Fernando is a very small town with approximately 3,000 inhabitants6. If the

household does claim a migrant member, limited information on that migration is

collected. Furthermore, information concerning the receipt of remittances is collected of

all households as is a question that assesses the "happiness" of the survey respondent.

B. Literature and Measurement Concerns

To what extent is it possible to discern "happiness" from surveys such as the one

in question? Di Tella and MacCulloch (2005) note that other social scientists including

psychologists have relied upon happiness data much like the data included in the

Discrimination and Economic Outcomes Survey that we are working with. They claim

that: “….well-being data pass what psychologists sometimes call validation exercises.

Pavot (1991), for example, finds that respondents who report that they are very happy

tend to smile more, an act that arguably is correlated with true internal happiness”.

Layard (2005) further rationalizes the use of happiness data by noting research in

neuroscience (Davidson, 2000) which have found that different regions in the brain are

associated with positive and negative affects. Thus when people describe their feelings

there is some biological basis and their claims are not purely subjective. Furthermore,

self-reported happiness is correlated with others' assessments of happiness. As such,

many argue that happiness can be measured and can be compared between individuals

and over time. In our case, respondents happiness are assessed by way of asking whether

they are "very satisfied," "fairly satisfied," "not satisfied," or "very unsatisfied" with their

life. With this information we construct a happiness dummy variable equal to "1" if the

house head is very satisfied or fairly satisfied with their life and "0" otherwise.

The literature on happiness suggests that a number of demographic, cultural and

economic factors play a role in individual's happiness. A review of the empirical

literature appears to concur with common expectations regarding the relationship

between personal variables and happiness. For example, separated individuals and

divorced individuals are found to be less happy (Clark and Oswald, 1994; Blanchard and

Oswald, 2000) and the degree of happiness is found to be "U-shaped" with respect to age

(Blanchflower and Oswald, 2000). Happiness decreases with age but eventually rises as

individuals get older. In contrast, education and happiness are found to be "inverse Ushaped.

More education increases happiness, but only up to a certain point. That is,

education can be "too much of a good thing," since beyond a certain point, additional

levels of education are found to contribute negatively to happiness levels (Hartlog et al.,

1997).

Other variables are found to have less obvious and sometimes even

counterintuitive impacts on happiness. For example, absolute income levels do not seem

to be important as determinants of happiness (Easterlin, 1974; Blanchflower and Oswald,

2000; Rayo and Becker, 2007). Relative income or wage standing, instead appear to

affect happiness levels (Frank, 1985; Easterlin, 2001, Miles et al., 2005). Interestingly,

self-employment is found to increase happiness for individuals in developed economies,

while having the opposite effect for individuals residing in developing economies

(Graham et al., 2001).

A number of other variables have been found to affect happiness, but with less

robust findings. For example, while it has been reported that women are happier than

men, the reported happiness among women is found to be declining over time. And while

religious denomination does not appear to impact happiness, religiosity, measured by

attendance at religious ceremonies, seems to be correlated with greater levels of

happiness (e.g. Blanchflower and Oswald 2000).

Our intent is to contribute to this literature by assessing the impact of migration

on happiness. To this end one might consider estimating a regression of the following

form:

Happiness for the head of household i (Hi) is presumed to depend on vectors of

household (Fi) and personal head of household (Pi) variables8. Following the literature

on happiness, the vector Fi includes absolute (or relative) per capita income and

household wealth. Personal (Pi) variables that are presumed to affect happiness are

gender, age and employment status. We would augment the standard happiness equation

to include one or a vector of migration related variables Mi, (whether there is a migrant in

the household j, whether the household j enjoys the receipt of remittances from abroad)

which may, in turn, have important impacts on happiness. Finally, εi is the unobserved

heterogeneity for the household i.

While (1) may seem a reasonable specification, it may not be appropriate if we

cannot justify that all right hand side variables in equation (1) are exogenous -- that there

is no correlation between the right hand side variables and the error term. This proves

problematic for the following reasons. Consider, for example, a very simple migration

variable -- a dummy variable assuming the value "1" for households that claim that one

of its members is a migrant and "0" otherwise. Correlation between the migration

dummy variable and the error term might very well exist on account of reverse causality.

While we are presuming that migration impacts happiness (e.g. family remaining behind

miss the migrant and their former contributions to the family and therefore are less

happy), it is also conceivable that happiness affects migration. For example, a very

unhappy household head may "drive family away" thereby prompting out-migration.

In addition to endogeneity originating from reverse causality, unobserved

heterogeneity may also play a role. Migrant households are not likely to be randomly

selected from the population, but we may not be able to observe and control for that

selection. For example, it may be that migrants tend to originate from households willing

to indulge in risk-taking behavior. But risk attitudes may also play a role in determining

happiness. If we cannot control for risk attitudes on the right hand side of (1) the

migration variable and error term will be correlated and our inferences regarding

migration and happiness will be biased.

Non-migration regressors in equation (1) may also suffer from endogeneity. One

obvious candidate is income. Positive work attitudes may very well be a factor in

determining income, but work attitudes are also likely to affect happiness. If we do not

observe and therefore control for work attitudes, this will be reflected in the error term

which will now be correlated with income, biasing the coefficient on income and

incorrectly assessing income's impact on happiness.

A common solution for endogeneity is to find instruments for the endogenous

variables in question. By finding variables that are correlated with the endogenous right

hand side variable yet not related to the dependent variable, we can purge the equation of

endogeneity and thereby obtain consistent estimates that reliably describe how the right

hand side variables affect happiness. In many cases, however, good instruments are

difficult to obtain. Furthermore, once we find good candidates, diagnostic tests of the

suitability of instruments are sometimes of questionable reliability, making it difficult to

justify their use. While we might venture to use instrumental variables to correct for one

endogenous regressor, we feel less confident about finding and justifying instruments for

all the regressors in equation (1) that are likely to be endogenous. For this reason we

seek an alternative technique to assess the impact of migration and migration related

variables on happiness.

D. Conclusions

In this paper we set out to study the impact of migration and remittances on the

happiness of the family left behind. We exploit the results of a survey conducted in

Cuenca, Ecuador in 2006 that collects information on both migration of family members

and on the receipt of remittances. In addition the survey asks a question about the level

of happiness experienced by the respondent, the household head. This allows us to check

for the impacts of migration and migration related variables on happiness.

17

As in any study of happiness, the primary challenge is to correct for endogeneity.

A large number of variables are likely to affect the "happiness" of individuals, but it is

also the case that happiness is likely to impact on many variables of interest. Given

selectivity in terms of who migrates, unobserved heterogeneity is also likely to

complicate the assessment of migration on happiness. Dealing with this endogeneity is

essential if we are to obtain credible and reliable results. In our case we choose to deal

with the endogeneity of happiness by using matching methods. To assess the impact of

migration on happiness we first estimated a propensity score for migration. These scores

were then used to find matched controls for those observations that were "treated" with

migration. We found that the matched controls were more happy than the treated. In

other words we were able to infer, in this case, that families with migrants are less happy.

Migration reduces the happiness of those left behind. In a second experiment we test to

see the impact of remittance recipiency on happiness. Are families who receive

remittances happier?

In conjunction, the two experiments suggest that remittances, the monetary

inflows that often accompany migration, cannot compensate for the absence of household

members through migration. This is interesting because it is often claimed that the raison

d'etra of international migration from developing to developed economies is the

acquisition of additional monetary resources from abroad for family back home to enjoy.

But it does not appear that these transfers can be used to raise the happiness levels of the

family left behind. As such one cannot compensate the family left behind for the absence

of loved ones with remittances from abroad.