The bulk of our work is conducted on data from the Annual Survey of Industries (ASI) by the Indian Ministry of Statistics and Programme Implementation (MoSPI). The survey spans over many years and covers the entire manufacturing sector comprising industrial units (“factories”) registered under Sections 2(m)(i) and 2(m)(ii) of the _Factories Act_ , 1948.<sup>14</sup> This includes all firms employing 10 or more workers using power, and those with 20 or more workers regardless of the use of power. The ASI data collect detailed information on employment, material inputs, and output that can be conveniently used to recover mark-ups and estimate production functions. The data set also provides information on the location of the factory at the state and district level.

The ASI data are available both as detailed, unit-level cross-sections without firm identifiers, and as panel data with firm identifiers.<sup>15</sup> Both these data sets have been widely used in the literature, most notably by Allcott et al. (2016), Hsieh and Klenow (2009), and Martin et al. (2017). In our work, we use the panel version for the period 1999-2014 for the sample of the major Indian states.<sup>16</sup> For our analysis on adjustment costs, we use four main outcome variables from the ASI – wage bill of permanent labor, wage bill of contract labor, value of land (owned and leased), and value of fixed capital excluding land. In line with our discussion in Section 3.2.3, we further divide all our outcome variables by the expenditure on materials consumed (or on electricity consumed and purchased in our robustness checks), which is our reference input for measuring relative input adjustment costs.<sup>17</sup> Descriptive statistics by year on the main ASI variables used in our analysis are reported in Table 3.2.

As regards our classification of fast- and slow-growing states, we use value added time series provided by the Institution for Transforming India Policy Commission of the Government of India (NITI Aayog) and compute the growth rate of manufacturing value added from 1999 to 2014. States are classified as fastgrowing if they have an above-median rate of growth (Annex Table A3.1).

Our main governance classification is sourced from a study carried out by Transparency International India and the Centre for Media Studies (CMS) in 2005 on the experience of the average citizen with 11 public services18 across the country. The measure combines information on aspects such as level of satisfaction in the services of the relevant State Department, or on number of households reporting paying bribes, or using influence to speed up administrative processes. States are then ranked with respect to a weighted average of the scores obtained by the various Departments, and we assign a State to a “low governance” group if its score lies in the bottom 50 percent of the ranking. Alternative governance indicators come from the Indian National Council of Applied Economic Research (NCAER), the Enterprise Survey of the World Bank, the Indian National Crime Records Bureau, and various policy reports, and are described in more detail in Section 6.

> 14 The main central government’s law on conditions of work. See Section 5 for details.

> 15 The cross-sectional data sets are available for the years 1983-84, 1984-85, 1989-90, 1993-94, 1994-95, and more recently from 1996-2014, whereas the panel data is available from 1998 onwards.

> 16 Our final sample includes Andhra Pradesh, Assam, Bihar, Chhattisgarh, Delhi, Goa, Gujarat, Haryana, Himachal Pradesh, Jharkhand, Karnataka, Kerala, Madhya Pradesh, Maharashtra, Odisha, Punjab, Rajasthan, Tamil Nadu, Telangana, Uttar Pradesh, Uttarakhand, West Bengal.

> 17 To define expenditure on materials consumed, we use the Tabulation Programme provided by the MoSPI. Materials consumed include expenditure on total basic items, non-basic chemicals, packing items, consumable stores, and total imports consumed.

9