Job Dissatisfaction and Migration: Evidence from Tajikistan

Having a family member migrant reduces not only the labor force participation but also the job satisfaction of those left behind. Migrants' relatives build their expectations on earnings from migration through received information on the wage distribution in the destination country either from the size of remittances or directly from migrants. If their expected earnings from migration greatly exceed their current wages in the source country, migrant relatives become more dissatisfied with their jobs. Using a simple economic model of job satisfaction and applying both parametric and semiparametric estimations to Tajikistan's data, as well as with controlling for an endogeneity issue with the variable of interest, we estimate the significantly positive effect of the difference of the expected outside country earnings and current earnings of migrants' relatives on their job dissatisfaction. A larger gap between what an individual could earn in the migration destination country and what she receives now at her current job in the source country makes that individual unhappier.


Introduction
Our focus in studying the employment-migration relationship is on the source country.
We look at how the migration of one person to another (destination) country impacts the labor supply decisions of his relatives who remain in a source country. While all previous studies looked at the effect of remittances on the labor supply decisions of migrant relatives, in this paper we examine how the outmigration affects the job satisfaction of non-migrating relatives.
Studying the effect of migration on the labor supply is not new. The pioneering work on the effect of migration on labor supply of non-migrant family members is by Rodriguez and Tiongson (2001). They find a negative effect of remittances on the labor supply of the migrants' family members in urban Philippines: an additional US$40 of remittances per migrant family member decreases male and female labor participation by 0.3 and 0.2 percents respectively. Subsequent papers find further evidence of this negative effect of remittances on the labor supply.
For example, Acosta (2006) finds that remittances received from international migrants reduce the likelihood of labor supply by children and women in migrants' families in El Salvador. Kim (2007) also finds the negative effect of remittances on the labor supply at both the individual and geographical cluster levels in Jamaica. Nguen and Purnamasari (2011) study the Indonesian data and find that migrant family members work 26 hours less per week than members of households without migrants; if migrant is male, his family members work 33 hours less than members of non-migrant households. Amuedo-Dorantes and Pozo (2006) reported that a 100 Peso remittance increase would reduce male formal sector employment by 32 hours per month in both urban and rural areas of Mexico, male self-employment by 11 hours per month in urban areas, female nonpaid employment by 6 hours per month, and female informal sector employment by 12 hours per month. Cabegin (2006) studies migration from the Philippines, finding in families with wifemigrants that an annual increase in wives' earnings by 10,000 Pesos decreases the likelihood of having the full-time paid employment of their husbands by 12 percent more than men in nonmigrant families. The same increase also leads to a rise in the likelihood of husbands being unemployed by 6 percent. In families with husband-migrants, the same size increase in husbands' earnings reduces the likelihood of full employment by their wives by 4 percent relatively to those in non-migrant households.
Why do remittances negatively affect individual labor supply decisions? Since remittances received from the migrant might have the same effect as that of the non-wage income in the individual (or family) utility maximization problem, there are two possible outcomes. [2] Firstly, remittances could result in an interior solution in the labor supply problem, where the marginal rate of substitution between the consumption and leisure is equal to the real wage rate.
Under this condition, if leisure is a normal good, then the increase in non-wage income reduces hours of work of migrant family members. Secondly, remittances might result in a corner solution to the labor supply problem when the marginal rate of substitution of consumption and leisure is greater than the wage rate. Since non-wage income raises individual budget constraints, it also increases individual reservation wages. Once individual reservation wages are increased to such level that they are higher than market wages, migrant family members would choose not to work (for detailed discussion of the effect of the non-wage income on the labor supply see Killingsworth (1983)).
However, as Rodriguez and Tiongson (2001) stated it is not entirely clear "whether migrants' remittances have a similar effect on labor supply as other nonlabor income" (p. 721).
Due to the complexity of migration process there are different attributes that along with remittances influence labor supply decisions of migrant family members. Several authors discuss these indirect effects of remittances and migration. Acosta (2006) mentions that the absence of the migrant along with the inflow of remittances might create positive externalities for neighbors of migrant families by relaxing the financial constraints they face as the migrant's family hires neighbors to do some work in their household to compensate migrant's absence. Kim (2007) hypothesizes that remittances are hurting Jamaica's competitiveness in international market by increasing domestic wages. Nguyen and Purnamasari (2011) argued that remittances might affect labor supply of migrant family members differently depending on both migrant's gender, and his or her influence on household decisions. Amuedo-Dorantes and Pozo (2006) stated that remittances help men to forego benefits of formal jobs and choose to do informal work. The absence of the husband because of migration would induce women with school-age children in remittance receiving families to leave the full time employment (Cabegin, 2006).
We look at another dimension in studying the effect of migration on the labor supply of migrants' family members in the source country --their job satisfaction. Migrant's family members might consider remittances as their lost earning opportunities from not joining their migrant relatives in working abroad. A non-migrating member of a migrant's family would compare her own current earnings from working in the source country to what she might earn from migration basing on observed remittances from her migrant relatives. Additionally, a current or returning migrant provides information on existing labor market opportunities in the destination country. Using this information a non migrating member would create her own [3] expectation on earnings from migration like if she joined the migrant, and compare them to her current wage. Then, the larger the difference between that what she receives now and her expected earnings from migration is, more dissatisfied from her current job she would be.
Individual expectations on earnings from migration might be affected by costs of migration, which are uncertain. Members of migrant families, however, have advantages in reducing such costs basing on their migration experience. First of all, the cost of acquiring information on earnings possibilities in the destination country and on the job search would be lower for migrants' relatives because they learn this information from the migrants' experience.
Migration costs are also lowered once the non-migrating members receive help from their migrant relatives in searching for jobs, housing and fulfilling all working and staying formalities in the destination country when they decide to migrate. Therefore, since the family is involved in migration, its members know how to reduce migration related costs, which allow them to get earnings almost close to their expected values.
Our discussion is consistent with the job satisfaction literature, which defines job satisfaction as an increasing function of the deviation of current workers' wages from the expected wages which they might receive from another employer or occupation. Introduced into the economics literature by Daniel Hamermesh (1977), in his economic model workers compare their wages in their current occupations with those from other job alternatives. If workers' current wages are higher than those from alternative jobs, they would be more satisfied with current jobs, and vice versa. His equilibrium condition at the time when an individual starts his work at the new occupation implies that there is no differential job satisfaction. Once the working experience with the current employer increases, the worker becomes more certain about her earning abilities that increase her job satisfaction. He finds a positive relationship between job satisfaction and the deviation of actual wages from the expected wages which are derived using information on the mean of the country's wage distribution conditioned on worker's individual characteristics such as experience, age, education and gender.
Hamermesh's findings have been confirmed across consequent studies. Clark and Oswald (1996) used two distinct variables in their regression analysis, logarithms of current and expected earnings, instead of a single variable of wage residuals. They found that while the coefficient on the logarithm of current earnings is positive, the coefficient on the logarithm of expected income from other job alternatives is negative and statistically significantly different from zero.
Comparison with alternative specifications allowed them to conclude that individual well-being [4] does not depend on absolute income, but on the income comparison, i.e. on the relationship between what a person gets now and what she probably could get if she changed her job. In his following paper, Hamermesh (2001) finds that current shocks which widen earnings inequality also increases the current job satisfaction of those who are at the top of earning distribution. Diaz-Serrano and Vieira (2005) by analyzing European data found that the low-paid workers are less satisfied with their jobs compared to higher paid workers, except the British as they receive larger compensating non-pecuniary benefits. More recently, Card et.al. (2010) using a randomized manipulation of access to information among employees of the University of California find that granting access to earnings information of other employees increases job dissatisfaction among workers with wages less than the median in their pay unit and the same occupations.
In the next section, we discuss a simple model specification of job satisfaction, and incorporate migration into this model. In the third section we explain the semiparametric ordered response model, and discuss how we control for the endogeneity of migration related variables.
The fourth section provides definitions and explanations of the data used in this paper. We used the data from 2007 World Bank Living Standard Measurement Survey on Tajikistan, a small Central Asian, former Soviet and transitional country which is highly dependent on migration and remittances. Differences in wages in Tajikistan and its migration destination country, Russia, along with increasing migration, make it a good country case for our study. The section five discusses estimation results of migration on the job satisfaction in Tajikistan. The final, fifth, section concludes.

Simple Model of Job Satisfaction
We assume that an individual faces the following utility maximization problem with a constrained amount of leisure: subject to the budget constraint: where is a consumption good , is individual 's choice of the consumption bundle, is the constrained amount of leisure, is the total available time, is the wage rate, and is a nonwage income, both are normalized by consumption prices. Assume also that standard conditions for the utility function along with Inada condition hold, i.e. , and , respectively.
Killingworth (1983) defines three main situations when such constrained leisure exists.
Firstly, many firms for production efficiency set fixed hours of work and organize workers in several group-shifts. Then a person has the option either to take the job with the offered fixed hours of work or leave it. Secondly, person specific factors such as health issues might prevent workers from working more hours than some fixed number of hours. Finally, unemployment caused by imperfect information and imperfect mobility of people results in a discontinuous budget constraint. In such a case, individuals may not be able to immediately take up offers. This sets an upper limit to working hours per period, beyond which the budget becomes discontinuous.
In all these situations, the income and substitution effects have little or no impact on individual labor supply decisions. However, one important aspect of such model is that any possible increase in wages would result in increasing individual consumption. To see this we use Deaton and Muellbauer (1981) results on the linear function of the individual consumption with constrained labor supply. Deaton and Muellbauer (1981) derived the following linear form of the restricted demand function for the consumption good : 2 where and are preference parameters from individual 's utility function.
Notice that an increase in the demand for the consumption good depends on wages, , through total income: once the wage increases it would increase total income available for the individual in such way that she can spend more in buying the consumption goods. If we assume that there are no changes in individual non-wage income, then for any the increment in consumption with constant labor supply can be defined as follows: [6] or, by summing over consumption goods : where , and These expressions are strictly negative since the demand for each consumption good is increasing in wage.
The last expression shows that the relationship between the expected individual demand for a bundle with more consumption goods and her current consumption can be expressed as the difference in work earnings: if a person wants to increase her consumption, such an increase should be compensated by receiving higher wages.
Next, using the mean value theorem, for any , we rewrite the difference between the individual utilities evaluated at and in the following form: which is strictly negative due to the imposed condition on utility function, , and , implying ; and is a random parameter driven by individual utility parameters for expected wage , The important result from (1) is that the comparison of utilities received from consuming different amounts of consumption goods could be made based on the difference between wages.
The economic interpretation of this result is that, using the available information on the within source country wage distribution, an individual would construct her wage expectation from other possible job alternatives. In such a way she can evaluate the possible changes in her consumption if she decides to quit her current job in favor of new jobs with different wages. If her wage expectation from outside jobs is higher than her current wage, or equivalently , then she would be unhappy with her current job. The outside wage is evaluated using the country's internal wage distribution: where and are the minimal wage rate and the wage distribution in the country , respectively.
Notice that in the regression analysis, the expression (1) can be referred to as a Random Coefficient Model, since the parameter is random over population. The most useful way is to write with and , then expression (1) can be rewritten as: where . The final expression has a constant coefficient on the wage differences which is a parameter of interest, as well as the interaction term between the unobserved heterogeneity and wage differences. Therefore, one also needs to calculate the average partial effects of model variables, by averaging over unobserved Using the last expression we can rewrite the function of job satisfaction. First, notice that an individual would be satisfied if her current wage is greater than that which she might receive from any other employer: . Therefore, an individual would compare her current wage, , to the possible wage that she could receive in another job, , for the same hours of work based on her individual worker characteristics and current market conditions.
Define by the index of individual 's job satisfaction; for unknown cut points : (3) Using this specification we can estimate the effect of the difference between the individual expected wages from other jobs and current wages on the job satisfaction. Since by [8] construction , current job satisfaction from having lower wages, i.e. increasing wage difference of , would be a simple t-test on the negative sign of the coefficient .

Migration and Job Satisfaction
Once a household sends a migrant, its members acquire information about outside country wage distribution through either the size of remittances, or information directly received from a migrant. Having such information, a member of the migrant's family would construct her expectation on her earnings from migration as if she has migrated: where and are the minimal wage rate and the wage distribution in the destination country , respectively.
Therefore, with such information she would be able to compare her utility based on her earnings in her source country with her utility from her expected earnings in the destination country: where is the expected wage earnings from migration by individual , is an individual 's target consumption if she migrated, is an heteroscedastic error term, and with reflect changes in utility parameters with observed remittances.
Her current job satisfaction depends on two parallel utility comparisons defined as in (1) and (4): We estimate this equation for migrant family members working in the source country.
Notice that we intentionally add both wage differences in the equation, which allow us to estimate the effect of the difference of the expected outside country wages and current wages of migrants' [9] relatives on their job satisfaction keeping constant the difference in the expected internal country wage and current wages.
Starting from this point, we distinguish these two differences by calling the first difference, i.e. the difference between individual expected wages from internal country jobs and individual's current wages, as the intra-country wage difference. We call the second difference, i.e., the difference between individual expected wages from migration (or the destination country wage distribution) and individual's current wages, as the inter-country wage difference.
One can also interpret the last equation using the definition of first order stochastic dominance. If the destination country's wage distribution dominates the wage distribution in the source country in the sense of the first stochastic dominance, expected utility from migration would be higher than the expected utility of changing jobs within the source country: . This implies a significant negative effect of the intercountry wage difference, , on the their job satisfaction. A similar argument works, if one apply the second order stochastic dominance in considering the wage distributions between the source and destination countries for certain occupations or workers' other individual characteristics.
Using this expression we can rewrite the job satisfaction index function (4) including information on inter-country wage differences of the migrants' relatives: where if the households of the individual receives any remittance from its migrant member, and, is a composite heteroscedastic error term.

Semiparametric Estimation
Both models in (3) and (5) imply heteroscedastic error terms and . The estimation of such models using standard parametric ordered response models could be problematic. [10] According to Wooldridge (2010), the current concerns in parametric estimation are mainly about the signs of the model coefficients as well as their magnitudes. Firstly, if parametric response models are applied, the heteroscedastic error terms might affect the signs of partial effects of the model variables in such way that the true coefficients of model variables would have different signs from the partial effects of those variables. Secondly, in parametric ordered models the signs of estimated coefficients do not necessarily determine the directions of corresponding variable effects on model intermediate outcomes (i.e. for ), because of symmetry and monotonicity properties the standard normal probability distribution function, as well as the size of the cut points. And, finally, the parametric estimation of response models with endogenous variables would produce scaled estimates, thus to derive the original values of coefficients can be estimated by dividing them by bootstrapped standard errors, or using the delta method.
We use the semiparametric estimation for models (3) and (5), which is based on results from Klein and Spady (1993), Blundell and Powell (2004), and Rothe (2009) Such restrictions allow us to improve the finite sample behavior of our estimator by keeping the dimension of the data small, to apply estimation even when the index has a non- linearly functional form. This restriction allows estimating a ratio of coefficients ignoring the constant term along with the thresholds. Imposing such restriction, however, do not help us to recover the original coefficients of the model.
Using such index restriction, we would be able to derive the conditional distribution of on model's data using the following conditional expectations: Each expectation could be derived using a single-index binary model discussed in Klein and Spady (1993). Hence, using the above probabilities we can write the quasi loglikelihood function in the following form: where is a trimming function, which helps to keep the probabilities away from the end of tails, and is a sample size.
These probabilities can be estimated using the kernel regression estimator where is a Gaussian kernel function, and the bandwidth and is a standard deviation of (see Silverman (1986)).

Endogenous Explanatory Variable
The main problem in estimating the effects of migration is the endogeneity issue, as both the decision on emigration, and, consequently, the receipt of remittances are not random events.
Households are self-selected in sending their member(s) abroad; as well migrants are selfselective in returning to their home countries. In addition to these emigration self-selection issues, the duration depending heterogeneity, i.e. the decision on when to migrate, could cause the biasness in estimators (Gibson, McKenzie, & Stillman, 2010 We specify our semiparametric ordered response model with an endogenous explanatory variable: where one of explanatory variables, , is endogenous, and superscript in index implies that it has an endogenous variable as its argument. [13] The endogenous variable is assumed to be determined by the reduced non-linear form: where is a stochastic error term, is an unknown function, are coefficients normalized by the coefficient of excluded from the structural equation, a continuous variable of , is a matrix of all exogenous variables, which has a full rank with probability 1. Then by construction we would have: By defining an index , we can rewrite the conditional expectation of outcome as: where is a cumulative distribution function of conditioned on two indexes, and . Therefore, the semiparametric ordered response model with a continuous endogenous explanatory variable can be characterized as a double index model.
We rewrite the quasi log likelihood function in the following form: where and are trimming functions on continuous variables in , and , respectively.
is estimated in the first stage by running the Semiparametric Nonlinear Least Squares of on . Then conditioning on the estimates of the first stage index , we can estimate functions by the kernel regression estimator: [14] The bandwidth for two-index model is chosen as and , where and are standard deviations of and , respectively.
To confirm that this semiparametric estimation method performs well, we decided to fulfill the experiment using Monte Carlo simulations. The experimental data was generated using the following similar structure of our model: where all 's, and have independent normal distributions. Cut points 's are defined using tertiles of . The sample size is 3000; the number of Monte Carlo replications is 1000.
It is easily seen from these equations that the true semiparametric coefficients in the [15]

Tajikistan's Case
We have chosen the country case of Tajikistan for several reasons. Firstly, it is a transitional country which currently experiences an increasing labor migration due to high wage differences between Tajikistan and the main destination of its migrants, Russia. The average real wages in the Russian Federation in 2010 were about 8.5 times larger than those in Tajikistan.
Such wage differences not only drive more people from Tajikistan to Russia, but might also increase the dissatisfaction among current workers in Tajikistan with their current wages. [16] International migration is relatively new phenomena in Tajikistan. As a country-member of the former Soviet Union, international migration was strictly controlled and even "prohibited" by the Central Soviet Government. After the Union's collapse, this restriction was removed, thereby involving an appreciably large proportion of Tajikistan's population.
These initial conditions make Tajikistan a good case to study, where one does not need to be very concerned about historically well-established patterns and traditions of migration and allowing us to focus only on economic issues and factors which help to explain how these two processes interact. Tajikistan's current migration experience and features allow us to examine our theoretical model in studying the effect of migration on the job satisfaction of migrant family members.

Data and Variables
As a part of the response to the recognition of current migration trends in Tajikistan We look at the reported overall individual satisfaction from current primary jobs in Tajikistan. The survey asks a question "Overall how satisfied are with your job?". The answers are recorded for those who were present in the household during the survey as "Very satisfied", "Satisfied", "Neither satisfied nor dissatisfied", "Dissatisfied", and "Very dissatisfied". Because few observations were reported at extreme values, we put two first answer categories ("Very satisfied" and "Satisfied") together into one category and named it "Satisfied", and two last categories ("Dissatisfied" and "Very dissatisfied") into another single category, and named it "Dissatisfied". This categorical variable is used as the dependent variable in our regression analysis.
The sample size is 3022, including individuals with zero reported wages. We have not excluded them for two reasons. Firstly, working individuals, who reported their job satisfaction, work at different employers that include family owned businesses and farms. In such businesses and farms, involved family members do not necessarily receive individual wages in cash (i.e. they [17] have zero reported individual work earnings), since they work at increasing family's total income which is common. Secondly, since employment in the informal sector is common in Tajikistan, many families have other than wages income from employment that might be not reported (Abdulloev, Gang, & Landon-Lane, 2012). Since, we would allow non pecuniary effects and other non-reported income from current employment to be a part of the error term in our model; we did not exclude these observations from the sample. 3 We are interested in estimating the effects of two variables on job satisfaction; that is the effect of intra-country and inter-country wage differences. 4 The variable intra-country wage difference is constructed as the difference between the reported work earnings, which includes cash, bonuses and in-kind payments, and the expected value of work earnings from the country's internal wage distribution, which are calculated using Mincer's (1970) The appropriate term should be "salary" instead of "wage", because monthly salaries were recorded in the data. We, however, choose to stay with the "wage" term in order to avoid confusion in the discussion of the previous sections of this paper. [18] job is affiliated with a social security scheme (i.e. the National Social Protection Fund that is used to cover expenses on social protection of employees), whether the working place is in a fixed building, whether an individual works in the street or market. The model also includes continuous explanatory variables on individual ages, the number of children in the household, and the total value of durable goods owned by families as a proxy for non-wage income. Definitions of these variables are provided in Table1.
As it was briefly discussed above, a main problem in estimating effects of migration is that the migration related variable in our model  the variable on the inter-country wage difference  is endogenous. There are several ways to deal with endogeneity issue, but the most popular is the instrumental variable approach. Instrument variables, however, vary depending on the subject of studies. Brown and Leeves (2007) used migration networks to instrument the number of migrants in the household. This instrument is constructed using the community level migration patterns. McKenzie and Rapoport (2007) suggest instead using historic networks as an instrument for migration since communities are affected by external shocks that would lead to changes in current migration patterns. While migrant networks are widely used as an instrument to the decisions on family involvement into migration, there are other instrumental variables applied to migration such as distances to roads and main cities, and economic changes.
Since there was no migration history in Tajikistan as it was mentioned above, we used the current migration network per local communities as an excluded variable to control for endogeneity of migration in our semiparametric model. The migrant network variable at the community level is defined as a share of community's migrants in the total number of adults in that community (there are 269 communities in the sample). Adults are defined as those who are 16 years old and above. We define migration network per local community as, where is network variable defined for each community , is a number of migrants in household in the community , and, is a number of adults in household in the country .
Since this variable is defined per community level it is exogenous to individual decisions.  Table 2 shows that individually reported job satisfaction increases with age (age). This result is consistent with findings of Hamermesh (1977), and is probably due to decreasing worker's uncertainty about her future wage distribution. Higher dissatisfaction at younger ages might imply that, firstly, the people do not develop job-specific human capital, consequently, they are less paid relatively to elder workers. With smaller wages, younger workers are more likely being dissatisfied from their jobs than elder workers. It also might be because of the younger workers' mismatch with their current jobs. Since mismatch leads to lower wages, we can hypothesize again that younger workers exhibit higher dissatisfaction relatively to elder workers.
There are also differences in age means between individuals living in families with and without migrants: those people who have migrant relatives are older than their cohorts in the same job satisfaction category. This is not surprising if one takes into account the fact that migrants in Tajikistan are predominantly young men, and because of their absence, the mean age of migrant family members increases.
Both the variables on inter-and intra-country wage differences (resm and resw) are increasing with the job dissatisfaction. Since these variables are constructed as difference between expected wages that individual could receive from other similar jobs either abroad or within the same province of Tajikistan, and her current wages, the increase in these variables would imply that the individual receives less than an average person with similar age and educational background does. The larger these gaps, the more dissatisfied people would be with their jobs because of being underpaid. Another interesting picture is that the distribution between these two variables, the inter-and intra-country wage differences, which are significantly different: the variable on inter-country wage difference is larger on mean than the intra-country wage difference. This difference is due to lower wage distribution in Tajikistan compared to migrants' earnings in their main destination country, Russia.
Number of children (ch14)  (durs) owned by families do not significantly differ among groups with reported dissatisfaction and neither satisfaction nor dissatisfaction. However, the satisfied group of people have a higher amount of family owned durable goods.
The level of education from vocational schools (meduc) does not differ among job satisfaction groups, but differs between individuals living in migrant and non-migrant families.
The educational level from universities (heduc) does not differ among individuals living in families with migrants and without migrants in the dissatisfied group. However, the gap in shares of people with university education between those who live in families with migrants and without migrants increases with satisfaction, as their averages over satisfaction groups do: for neither satisfied nor dissatisfies group, the difference in shares of people with university degree between migrants' relatives and without is about 4.7%, at average 9.2% of people in this group have a degree at least from universities; while, these numbers are 6.1% and 17% are for satisfied group, respectively. This observation is consistent with the fact that the families are self-selected into migration: Tajikistan's families with members with lower skills or lower levels of education chose to be involved into migration, while people with higher education, or professionals, have more opportunities to engage in "unreported" income from their formal jobs, and prefer to remain in Tajikistan (Abdulloev, Gang, & Landon-Lane, 2012). Such access to "unreported" income by professionals might be a reason for their satisfaction from current jobs. scheme feel more "secure" about their future, post retirement pension, and receive state health benefits in cases of emergencies. The social security affiliation might also imply that workers have long term contracts with their employers, as well as employers are being well-established companies, which increases individual job satisfaction A share of people who work in fixed premises (fdpl), such as offices or plants, in average increases over job satisfaction groups.
Conversely, a share of people who work in the street or markets (smpl) decreases over job satisfaction groups. Such different relationships between these two workplaces and the job satisfaction might be explained to the fact that the work within fixed buildings and premises is affiliated with the social security scheme, long term contracts and well-established employers, while working on streets and markets implies self-employment with an absence of social security, or at small and "young" companies. finally, for the satisfied group, the corresponding means of network variable for people with and without migrant relatives are 0.1026 and 0.0705, respectively. Such non-variation of the migrant network variable across job satisfaction groups, and its variation between people living in families with and without migrants, makes it a valid instrument for migration related variable of our model.
In the next section, we use multivariate regression analysis in order to specify the partial marginal effects of migration on individual job satisfaction.

Regression Analysis
Tables 3 and 4 report the results from estimating the effect of an array of the variable specified above on individual job dissatisfaction using the parametric ordered probit and semiparametric ordered response models. There are two models are reported in each inter-country wage difference for individuals living in families with migrants; and, in the Model 2, we estimate the same model as in Model 1 but with the inclusion of the variable on the intercountry wage difference. Notice that we allow both intra-and inter-country wage difference variables in Model 2, since in such way we can estimate the effect of the inter-country wage difference at constant effect of the intra-country wage difference. We also estimated the semiparametric response model accounting for endogeneity of the variable on the inter-country wage difference, which we refer to as Model 2-IV. We also report the average partial effects of all model variables on predicted individual job dissatisfaction.
Both Model 1 and Model 2 that were estimated using the parametric ordered probit show the positive and statistically significant correlation between individual age and job satisfaction.  The positive coefficient on age allows us to consistently estimate signs of normalized coefficients of other variables. Its significance allows ratios of other coefficients with respect to it to be finite. 5 In order to satisfy the identification condition C.3b in Klein and Spady (1993), we did not include other functions of age. [24] Taking into account the positive relationship between individual age and reported job satisfaction, we expect that the signs of the semiparametric estimates of variable coefficients in the Model 1 and the Model 2 would have the same signs as of the parametric coefficient estimates of corresponding variables. Table 4 shows that variables in the semiparametric Model 1 and Model 2 have the same sign effects on individual job satisfaction as in parametric models. Interesting to note is that the significance of the coefficient estimates of variables on number of children (ch14), the value of durable goods (durs), education level from vocational schools (meduc) and universities (heduc), living in the capital city (capl) and working in fixed premises (fdpl) increases to 99% significance level in semiparametrically estimated Models 1 and 2, which might be due to our relaxed distributional assumptions.
Using estimates of variable coefficients, we estimate the average partial effects of the we controlled for endogeneity of the variable on the inter-country wage difference. The endogeneity issue of this variable rises because of the family's selection into migration. It might be also due to the possible simultaneity relationship with the job satisfaction: workers dissatisfied from their current wages might decide to send their relatives abroad in order to compensate in lower work earnings. We did not report the endogeneity correction described by Wooldridge (2010), which is based on the two stage Rivers and Vuong (1988) control function approach, [25] where, at the first stage, the reduced form equation for endogenous variable is estimated, then, at the second stage, residuals from the reduced model should be added into the structural ordered response model in order to control for endogeneity of the variable of interest. This approach is based on the strong distributional assumption that the reduced form error term is normally distributed. We conducted tests for normality for the distribution of the first stage residuals, Shapiro-Wilk and Skewness-Kurtosis tests, both tests rejected the null hypothesis. Instead we decided to implement the endogeneity correction using the semiparametric estimation, where one does not have to make any distributional assumption on the error terms.
After controlling for the endogeneity of inter-country wage differences, the estimates of the coefficients of model variables on durable goods, the level of education from the vocational schools, and gender become not significantly different from zero. The effect of number of children is also reduced, but remains statistically significant at the 95% significance level. Other coefficients remained statistically significant from zero at the 99% significance level. The absolute size of the average partial effect of the intra-country wage difference increases from 0.0918 to 0.1108 after we controlled for endogeneity of migration related variable. Likewise the absolute sizes of average partial effects of individual age, employer's affiliation with the social security, and working in street or market places, increase after controlling for endogeneity.
Conversely, the absolute sizes of the average partial effects of the remaining variables, number of children, current value of durable goods, education levels, gender, living in the capital city, and working in fixed premises, are lessened after we controlled for the endogeneity of inter-country wage differences.
We also report the first stage estimates of the reduced form equation for the inter-country wage difference (resm). The coefficients of variables on age (age), intra-country wage difference (resw), male gender (male), and work in the street or markets (smpl) are statistically significant at 99% significance level. Coefficients on living in the capital city (capl) and working in fixed premises (fdpl) are statistically significant at 95% level. Furthermore, even though the reduced form equation is estimated using the semiparametric nonlinear model, we performed the test for weak instrumental variables basing on the F-statistics from the first stage ordinary least squares estimation. The null hypothesis on the weak instrument was rejected. 6 6 We looked at whether the F statistic from the first stage OLS estimation is larger than 10 (Staiger & Stock, 1997). The reported F statistics is 32.64, which supports the validity of our instrument. Then, by [26] Now we turn to the effect of the inter-country wage difference. The coefficient on this variable in the semiparametric Model 2 is negative and statistically significant at 95% significance level. After controlling for its endogeneity, the size of its coefficient almost doubles, its significance also increases to 99% level. The average partial effect of the inter-country wage difference on the probability of job dissatisfaction is positive and increases from 0.0056 to 0.0135 after we control for its endogeneity. However, the size of its average partial effect even after controlling the endogeneity remains smaller in the absolute size than its average partial effect estimated using the parametric Model 2. This result indicates that even after keeping the effect of intra-country wage differences constant, the difference between the expected wages from migration and current wages of working members among migrant relatives remaining in the source country increases their dissatisfaction from current jobs.
Such a strongly positive effect of the inter-country wage difference on the probability of job dissatisfaction indicates that it might be destructive for economic development of the source country. Since there is a positive relationship between job dissatisfaction and job quits (for example see Kristensen and Westergaard-Nielsen (2004)), migrant relatives would be more likely to leave their jobs once the gap between the outside wage distribution and the intra-country wage distribution increases. Firms in the source country will be losing workers, consequently, their market competitiveness, due to increasing outmigration. Furthermore, the rigidness in wages in the source country compared to the dynamic wage increase in the destination country will be attracting more migrants to the destination country, living the source country with the shortage of labor. With limited capital endowment, the firms in less-developed countries cannot offer higher wages, hence would be less successful in attracting back migrants.
A similar process is observed in our chosen country case, Tajikistan, with respect to its main migration destination country, Russia. Wages in these countries during Soviet period, when the common market existed, were closer to each other. Schroeder (1981)  [27] up the wage divergence between these countries. Figure 1 shows the scale of the accelerating divergence of Tajik real wages from Russian real wages after the collapse of the Soviet Union.

Conclusion
An increasing inflow of remittances is not only destroying the labor participation of remaining members of migrant families, but also increases job dissatisfactions of those who still continue working. Once working migrant relatives in the source country receive information on wage distribution in the destination country through either the size of received remittances or the information received directly from migrants, they are able to build then own expectations on the size of earnings they could receive if they migrated. If the gap between expected wages from migration and current wages increases, working relatives of migrants become dissatisfied with their current jobs.
Using both parametric and semiparametric econometric models, we find a positive significant effect of migration on the increase in the probability of job dissatisfaction of working migrants' relatives in the source country, Tajikistan. The effect remains significant even when we control for possible endogeneity of the migration related variable. Tajikistan has a much lower wage distribution relatively to its main migration destination country, Russia, which attracts more migrants every year from Tajikistan to Russia. An accelerating wage gap between Russia and Tajikistan after the collapse of the Soviet Union not only drives more Tajikistan's population into migration but also increases the job dissatisfaction of those who left behind. [28] Appendixes. [29]