technologically advanced, capital intensive, and globally integrated industries typically have lower unorganized sector shares in India.

Discussions of India’s industrial landscape and transformation often use the terms “traditional” and “modern”, although there are no established or precise definitions of these sectors. To provide some traction for this work, we defined these sectors ourselves through grouping the industries in Tables 3a and 3b. We classify an industry as being modern if its unorganized share is the less than the unweighted average unorganized share across industries for its sector in 2000-2001. Thus, by definition, the traditional sector has a larger unorganized worker share than the modern sector. More important, the unorganized share is very stagnant in traditional industries for both manufacturing and services. This share is increasing in the modern manufacturing sector and decreasing in modern services.

These descriptive tables highlight several key traits of India’s unorganized sector. First, the unorganized sector is very large. Second, the unorganized sector is extremely persistent. Despite India’s rapid changes over the past two decades, the unorganized share shows no signs of declining. While the organized sector has grown over the past two decades, the unorganized sector has kept pace.<sup>4</sup> Third, this persistence is not due to particular subsets of states or industries. Despite the great range in average levels of unorganized sector shares in Tables 2-3b, the persistence over time is pervasive. Thus, the persistence is not due to diverging trends, with some states or industries becoming much more organized, and others becoming less so.

Tables 4a and 4b quantify these observations. Table 4a shows correlations of unorganized sector changes with district-level traits taken from the 1991 and 2001 Population Censuses. Column headers indicate sector and time period. Panel A considers how district traits correlate with the change in unorganized sector share of district employment; Panel B quantifies instead correlations with log unorganized sector employment growth. We show results from the district level to maximize the number of observations and the granularity in local conditions.

Our selected district traits reflect several factors that prior studies have found important for India’s economic geography. Population and population density are natural baselines. We next model the district’s age structure (Bönte et al. 2009) as the ratio of working age population to non-working age population. This ratio relates to the demographic dividend often discussed in

> 4 As a useful comparison point, many commentators worry about India’s slow path to urbanization. Across the 1989-2005 period, the share of Indian manufacturing employment that is urbanized grew from 33% to 41% (Ghani, Grover, et al. 2011). This change is much more substantial than anything present for the unorganized share. This decoupling of urbanization change and informality change in India is an important topic for future work, empirically and to inform two-sector theoretical models (e.g., Harris and Todaro 1970, Zenou 2011). Henderson (2010) reviews the literature on urbanization and development.

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