taxes and 95 percent of excise duty collected by the Government of India (CMIE) (Goldberg et al., 2010).<sup>14</sup> Prowess records detailed product-level information at the firm level and can track changes in firm scope over the sample period. Prowess is therefore particularly well suited for understanding how firms adjust their product lines over time, for example, in response to changes in import competition. Prowess enables us to track firms’ product mix over time because Indian firms are required by the 1956 Companies Act to disclose product-level information on capacities, production and sales in their annual reports. As discussed extensively in Goldberg et al. (2010), several features of the database give us confidence in its quality. Product-level information is available for 85 percent of the manufacturing firms, which collectively account for more than 90 percent of Prowess’ manufacturing output and exports. More importantly, product-level sales comprise 99 percent of the (independently) reported manufacturing sales.<sup>15</sup> From Prowess, we use the data on firms that were classified as manufacturing firms at any point during the period 1994-2013.<sup>16</sup>

# **_3.3 Estimation Strategy_**

To explore the correlates of servitization, we estimate the following equation: e + Φ + Ψ (1) ii,tt ii,tt ii,tt ii,tt ii tt ii,tt Where ss = αα T is a measure of TT + ββ e sse _Servitization_ ee + γγΠ for firm _i_ at time+ εε _t._ CMIE data provides information on each product offered by a firm. At the extensive margin, servitization is measured as a binary variable, where one of the ii,tt products offered by a manufacturing firm is a services activity.ss<sup>17</sup> At the intensive margin, servitization is measured as the share of revenue from services sales in total sales of the firm. T is _firm productivity_ for firm _i_ at time _t._<sup>18</sup> Firm level information on value added, capital and labor is required, at the very least, ii,tt to estimate a production function, Since firms in Prowess do not report the count of employees, we estimate TT it by dividing the total wage bill of the firm with the median wages by industry, state and year from the Annual survey of industries data. For estimating the production function, we use the Levinshon and Petrin (2003) method, with expenses on power, fuel and water as the proxy variable. And, e e is _exposure to import competition_ for firm _i_ at time _t._ An industry’s exposure to import competition is measured as the ii,tt share of imports relative to output in the industry. To compute firm level exposure, we weigh the industry-sse ee Where level exposure with the share of manufactured products. = <u>j, ,</u> is the revenue from sales of manufactured product EEe eesse eeii,tt = �ρρjj jj,ii,tt ∗IIjj,tt _j_ by firm _i_ , , as a share of total manufacturing activity of the firm ρρjj,ii,tt RRRRii,iitttt _i_ at time _t_ , and = IO I <u>j,</u> is the share of imports in industry RRjj,ii,tt _j_ at IItt tt time _t_ in total output of the industry at time _t._ Imports at the industry level are obtained from WITS database, RRii,tt IIjj,tt ttIIOOttjj,tt

> 14 Prowess is not well suited for understanding firm entry and exit because firms are under no legal obligation to report to the data collecting agency. However, since Prowess contains only relatively large Indian firms, entry and exit is not necessarily an important margin for understanding the process of adjustment to increased openness within this subset of the manufacturing sector. In fact, very few firms exit from the sample during this period (7%) and there is no statistical difference in initial firm scope, output, TFP and R&D activity between continuing and exiting firms (Goldberg et al., 2010).

> 15 See Goldberg et al. (2010) for detailed summary statistics.

> 16 Data quality checks for the years after 2013 suggests that firms do not consistently report their product details because Schedule VI of the erstwhile Companies Act 1956 modified in February 2011 made 'Quantitative Disclosures' like 'Products Details Schedule' optional.  .

> 17 There are varying views regarding electricity, gas, water supply and construction services as services provided by manufacturing firms. For most of our analysis we included these as non-manufacturing products provided by a goods producer, however, the analysis in the annex tables illustrates robustness checks excluding these services.

> 18 Strictly speaking, servitization may be related to firm productivity in previous periods, but, given that TFP is likely to be correlated over time, we present the relationship as contemporaneous. Empirically, we also test the relationship with lags and the results remain robust.

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