Whether identical workers are treated homogeneously in different sectors indicates how segmented labor markets are. In this study, we test for segmentation in the Indian labor market by using unit-level data from two rounds of nationally representative data each round comprising of nearly half a million individuals for the period 2004–2005 and 2011–2012. We use the finite mixture model (FMM) estimation and correct for selection bias to find the existence of two segments of considerable size in informal sector. We identify statistically different latent segments without a priori definition of the segments. Workers in the upper segment of informal employment receive higher returns to education and skills relative to those in the lower segment. Women earn less than men in both segments of informal and formal employment. The gender–wage disparity, however, is less pronounced in the lower segment of informal employment. Furthermore, we estimate the size of involuntary informal employment to be more than 40% of the entire informal employment. Our findings on unobserved heterogeneity suggest the need to rethink about binaries in the labor market as ideas of formal and informal employment lose relevance when multiple latent segments coexist. The study has potential implications for design of labor policies, skilli development programs, and labor legislation.

中文翻译：

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平等竞争？对印度劳动力市场细分的调查

相同的工人在不同部门是否受到同质待遇表明劳动力市场的分割程度。在这项研究中，我们通过使用来自两轮全国代表性数据的单元级数据来测试印度劳动力市场的细分，每轮数据包括 2004-2005 年和 2011-2012 年期间近 50 万个人。我们使用有限混合模型 (FMM) 估计并校正选择偏差，以发现非正式部门中存在两个相当大的细分市场。我们在没有先验定义的情况下识别统计上不同的潜在片段。相对于下层的工人，处于非正规就业较高层的工人在教育和技能方面获得了更高的回报。在非正规和正规就业领域，女性的收入都低于男性。性别工资差距，然而，在非正规就业的较低阶层中不那么明显。此外，我们估计非自愿非正规就业的规模超过整个非正规就业的 40%。我们对未观察到的异质性的研究结果表明，需要重新考虑劳动力市场中的二元性，因为当多个潜在部分共存时，正式和非正式就业的想法会失去相关性。该研究对劳工政策、技能发展计划和劳工立法的设计具有潜在影响。我们对未观察到的异质性的研究结果表明，需要重新考虑劳动力市场中的二元性，因为当多个潜在部分共存时，正式和非正式就业的想法会失去相关性。该研究对劳工政策、技能发展计划和劳工立法的设计具有潜在影响。我们对未观察到的异质性的研究结果表明，当多个潜在部分共存时，正式和非正式就业的想法失去相关性，因此需要重新考虑劳动力市场中的二元性。该研究对劳工政策、技能发展计划和劳工立法的设计具有潜在影响。