Introduction Statement of the Problem

Do remittances affect the consumption pattern of the Filipino households?

The objective of this paper is to formulate structural models to illustrate the change in consumption pattern of the Filipino households. In this study, our aim is to use an advanced econometric approach to find out if there is indeed such change in the consumption pattern of the household receiving remittances as compared to those who only get their income from domestic sources.

There are several studies regarding the consumption patterns of household. One of which is the study made by Taylor and Mora (2006), they studied about the effect of migration in reshaping the expenditure of rural households in Mexico. The conclusion that they made is that remittances has positive effects on total expenditures and investment. They also found out that as the remittances of rural household increases, the proportion of the income on consumption decreases (Taylor & Mora, 2006). Another one is the study of Rasyad A. Parinduri & Shandre M. Thangavelu (2008), wherein they used the Indonesia Family Life Survey data to observe the effect of remittances to the consumption patterns of the Indonesian households. In their study, they used the matching and difference-in-difference matching estimators to observe the relationship. They found out that remittances do not improve the living standard of the households, nor do remittances have an effect on economic development. They used the education and medical expenditure as indicators of economic development. The major findings that they have are that most of the Indonesian households used the remittances in terms of investing them into luxury goods such as house and jewelries (Parinduri & Thangavelu, 2008). Using the same study, we intend to observe the consumption pattern of the households, based not only on the remittances but also to other sources of income. In addition to that, instead of looking at economic development, we intend to look at the consumption goods that households normally consume, and see if there are indeed changes in the consumption patterns of the selected households.

Methodology and Data

In the methodology and data part, our main concern is to find ways to observe the consumption patterns of the Filipino households here in this country. In order to do that, we tried to find a dataset that will explain such relationship. Based from the available datasets here in the country, we would say that the Family Income and Expenditure Survey or the FIES best suits our study. The dataset enlists all the possible consumption goods that were being consumed by the households during a specific year. In addition to that, we can also determine the source of income of the different households that was made available in the dataset. By examining the relationship of consumption and income, we will be able to observe the behavioral aspect of the Filipino households’ consumption based from the income that they received.

Due to the inaccessibility of the latest data, we settled for the 2003 edition. Based on this data, we will be able to observe the impact of the different sources of income to the kind of goods that the Filipino families consume, using an advanced econometric approach called the simultaneous equation model (SEM).

After acquiring the right dataset for this study, we must next formulate the different structural equations to illustrate the consumption patterns. In this paper, we have formulated four equations, one of which is based from the Engel’s Law, which again, states that when an individual’s income increases, his/her percentage of consumption decreases (Engel’s Law, n.d.). As for the other three other equations which are mainly composed of different sources of income, mainly wages, domestic source, and foreign source, we have used other studies conducted by (SOURCE) ,to see what are the factors that affects or determine the different sources of income.

After formulating the equations, we decided to use the log-log model for the estimation, simply because our study aims to observe the income elasticity of the different goods. With the use of the log-log model, we will be able to determine the elasticity of the different consumption goods, by just looking at their respective estimated coefficients. Another reason why we chose the log-log model is because of the limited information about the domestic and foreign source of income in the FIES data. There are several households in the data who either do not receive domestic or foreign source of income, or the data gatherers failed to obtain these data from the respective respondents. By using the log-log model, we will be able to exclude those unrecorded observations, so that the results will be not inconsistent and will not be affected by the people who do not receive income from either domestic or foreign source.

After citing the reasons for the construction of the model, next, we will be observing three consumption goods, particularly the total food expenditures, the total non food expenditures, and the tobacco-alcohol consumption.

Estimation Techniques

After the identification problems of the simultaneous equation problem, we proceed to the estimation techniques. As discussed by Gujarati and Porter (2009), they provided three estimation techniques in order to solve for SEM, namely the ordinary least squares (OLS), indirect least squares (ILS), and the two-stage least squares (2SLS). The OLS is used for the recursive, triangular, or causal models (Gujarati and Porter, 2009). Meanwhile, the ILS focuses more on the reduced form of the simultaneous equations, wherein there exists only one endogenous variable in the reduced form equation and it is expressed in terms of all existing exogenous/predetermined variables in the model. It is estimated through the OLS approach, and this method best suits if the model is exactly identified (Gujarati and Porter, 2009). Lastly, the 2SLS approach, wherein the equations are estimated simultaneously. Unlike ILS, 2SLS can used to estimate exact and over-identified equations. (Gujarati and Porter, 2009)

The three approaches discussed by Gujarati and Porter (2009) are all based from the single equation approach. If there are CLRM violations such as autocorrelation and heteroscedasticity in the models, we must use the system approach, particularly the three-stage least squares (3SLS), to correct these violations. The only drawback of the 3SLS method is that if any errors in one equation will affect the other equations.

Check for equality and unit elasticity

As indicated in the appendices (last part), we also check if there lnwages and lnconab in the food consumption equation are indeed equal. We used the test command in STATA, to see if the two variables are equal, by looking at its p-value. The resulting p-value of the test is 0.8614, meaning we have no evidence to reject the null hypothesis that the two variables’ coefficients are equal. We made the same process for the lnwages and lncondo in the nonfood consumption equation, and the resulting p-value of the test is 0.6846, which means that lnwages and lncondo are also equal in the estimation. Aside from the check for equality, we also check if the lnconab’s income elasticity to tobacco-alcohol consumption is equal to 1. The resulting p-value for the test is 0.8007, which means that the income elasticity of lnconab to tobacco-alcohol consumption is 1, meaning it is unit elastic.

Results

In the first model, which is the total food expenditure model, the variable domestic source of income in the 1st equation is considered to be statistically insignificant. This means that it will be meaningless to interpret the results of that particular variable. As for wages and foreign source of income, we can see that the two coefficients are very similar, which means that for every one percent increase in wages and foreign source of income, food consumption increases by 0.22 and 0.21 percent respectively. The results are clearly consistent with Engel’s Law of food consumption that the proportion of food expenditure decrease as an individual’s income increases.

For the 2nd equation, which is the wage equation, the result shows that the impact of non-agricultural activities is greater compared to agricultural activities. This is consistent with our a-priori expectation of one having a larger impact than the other. In reality, we can see that non-agricultural activities result to higher income due to its high value added products that it produces. The higher the value added the work is, the higher the changes are that wages or salaries received will be also higher.

For the 3rd and 4th equation, which is considered to be similar except for the source of income where it comes from, the results show that only highest grade completed is considered to be statistically significant in the 3rd equation, while in the 4th equation, the household head’s age is the only one which is statistically insignificant. For the domestic source of income, we can observed that people who has a larger share of the wages or salaries in the company, have typically higher educational attainment compared to those who have lower educational attainment. The result of the 3rd equation maybe attributed to that factor. For the 4th equation, it is the same explanation for the highest grade completed by the household head as in the 3rd equation. While for the total family members employed with pay, it has a positive relationship, simply because if there are larger number of family members who are working and receiving salaries, the cumulative source of income will be larger, compared to those families who have fewer number of family members working with pay. The last variable in the 4th equation, which is the dummy variable contract worker, we can see in the result that if an individual is a contract worker, generally, that individual will receive lower wages compared to those regular employees. This is because contractual workers are given limited period of time to work for certain companies, and companies hire contractual workers for short term uses. With that, companies usually pay lower amount of wages to these short term workers.

For the 2nd model, the nonfood consumption model, all the variables in the 1st equation are all statistically significant. The coefficients of wages and domestic source of income are similar, but there is a disparity between these two variables and the foreign source of income, which resulted to a higher coefficient. The higher coefficient means that the foreign source of income is more sensitive to nonfood consumption compared to the initial two variables – wages and domestic income. We can see in the result that a household who receives foreign source of income are more inclined to nonfood expenditures. In reality, we observed that children of the household who rely on foreign source of income or remittances, typically has more gadgets or technological advances stuff compared to the children of the household who rely only to domestic source of income. This may explains that households have larger incomes if they receive remittances compared to those who only rely on domestic source of income.

The results of the 2nd, 3rd, and 4th equations are the same as food consumption model. Therefore, there is no need to interpret the results of these equations, since it has been interpreted in the previous model.

The last model, which is the tobacco-alcohol consumption model, the results were a bit unexpected. This is because the domestic source of income is negatively related to the tobacco-alcohol consumption, as compared to wages and foreign source of income, which are positively related to the tobacco-alcohol consumption. This means that households who rely only to domestic source of income have the tendency to reduce their vices as their income increases. While the implication of the positive relationship between foreign source of income and the tobacco-alcohol consumption is that, the long distance relationship between the household heads and the family who stayed in the country may have contributed some psychological factors which lead to the increase in the vices consumption of the households living domestically.

Aside from the positive and negative relationship of the variables, we also test the income elasticity of the foreign source of income to the tobacco-alcohol consumption. Based from the test results, it shows that the foreign income elasticity of the good is 1, which indicates that tobacco-alcohol consumption is unit elastic in the case of remittances.

Conclusion

Based from the results of the three consumption goods, food consumption pattern remains unchanged regardless of the source of income. As for the nonfood consumption pattern, the foreign source of income became more sensitive in terms of having higher income elasticity as compared to wages and domestic source of income. This means that people who are receiving remittances or other form of foreign source of income, are more inclined to purchase nonfood items, this can be in the form of gadgets, household equipment, and the like. As for the tobacco and alcohol consumption, we can see a significant change in the consumption pattern. When a household rely only on domestic source of income, they are discourage to consume these vices as their income increases. But when a household receives remittances, they tend to consume more tobacco and alcohol as indicated in the result. The reason behind this kind of relationship can be attributed to the psychological aspect of the Filipino households.

Our overall conclusion in this paper is that remittances have contributing factors in changing the consumption patterns of the Filipino households. As indicated in the introduction, since the year 2003 up until the present, the OFW remittances has more than doubled, which indicates that the consumption pattern of these households who are receiving remittances might have some changes in their way of consuming different goods or services.

Recommendation

Our recommendation in this study is to use the latest version of the FIES to see whether the food and nonfood consumption patterns have changed. In addition to that, the latest FIES data might have more observations containing the domestic and foreign income information that might actually improve the results of the study.

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