The empirical results show that wages and employment opportunities considerably differ across regions. We use Blinder-Oaxaca decomposition method (Blinder, 1973 and Oaxaca, 1973) to identify the relative role of individual and regional characteristics in wage determination in different regions. Wage differential is decomposed into two parts, one part that can be explained by differences in individual characteristics, such as age, education and gender, and one residual part that may capture the effects regional structural characteristics and unobservable characteristics.<sup>14</sup> Table 12 presents the results of the Oaxaca decomposition study, taking NCR as reference. The results offer support to the significant difference in wage structure between NCR and the other regions. Individual characteristics account for roughly one-third of the difference between NCR and other regions while other characteristics account for about twothirds.

**Table 12: Decomposition of the Effects of Individual and Other Characteristics on Regional –** **<u>Wage Differentials Using Years of School as An Indicator of Human Capital</u>**

||**Mean Daily Wage**<br>**(pesos)**|**Effects of Individual**<br>**Characteristics (Age,**<br>**Education, and Gender) on**<br>**Mean Wage Differential**<br>**between the Region in**<br>**Question and the NCR**|**Effects of Other Characteristics on**<br>**Mean Wage Differential between**<br>**the Region in Question and the**<br>**NCR**|
|---|---|---|---|
|NCR|262|--|--|
|Luzon|195|35.7%|64.3%|
|Visayas|157|32.0%|68.0%|
|Mindanao|165|28.4%|71.6%|

# **5. Conclusions**

The findings suggest large disparities in labor market performance across regions and individual groups in the Philippines. Development gaps widened between the Manila Metropolitan Area and other islands. Compared with other regions, NCR is characterized by high active population rate, low participation rate, low employment rate, high unemployment rate, and high daily wage. The youth, less educated, and women face more challenges in getting employed and earning a good salary, others things being equal.

Disparities in labor market performance are largely associated with the difference in regional structure and human capital endowment. Individual characteristics account for roughly one-third of the difference in wage between NCR and other regions; while regional structures and other unobservable factors account for two-thirds. Regional structural characteristics, such as industrial composition, labor productivity and prevalence of SMEs, are significantly associated with employment opportunities and wage levels. As expected, workers in regions with higher productivity and higher share of industry production are more likely to have higher wage, others being equal. The share of SMEs is positively associated with employment opportunities but negatively with wage, which is probably related to the nature of jobs created in SMEs. For similar reasons, a higher share of services to regional GDP is positively associated with higher employment opportunities, but not with wage. Individual characteristics, such as age, education

> 14 Further examination of roles of regional characteristics and that of unobservable characteristics is of interest for future studies.

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