metadata: authors: 0: author: Grover,Arti Goswami
1: author: Mattoo,Aaditya
count: India
docna: 0: docna: Why Do Manufacturing Firms Sell Services ?
            Evidence from India
docty: Policy Research Working Paper
abstracts: cdata!: Manufacturers in India are increasingly
            selling services—a phenomenon referred to as servitization.
            Both the proportion of manufacturers selling services and
            the share of services in total revenue of manufacturers
            increased threefold between 1994 and 2013. More productive
            manufacturers and those more exposed to import competition
            are more likely to sell services and to obtain a higher
            share of their revenue from services. A 10 percent increase
            in servitization is associated with 2.6 percent increase in
            manufacturing revenue. However, servitizing firms suffer a
            greater contraction in manufacturing revenue with increased
            import competition. This evidence suggests that
            servitization is not a successful defensive strategy to
            maintain manufacturing sales in the face of import
            competition, and it is more likely to be an exit strategy to
            flee import competition. Corroborative results indicate that
            past services sales are positively associated with the
            introduction of new services products and eventually a
            switch out of manufacturing and into services as the primary
            activity. Thus, servitization appears to be an aspect of
            “premature deindustrialization” in India, driven by the
            inability of manufacturers to cope with import competition,
            rather than structural transformation associated with a
            maturing manufacturing sector.
geo_reg_key: 517198,517212,517191
repnme: repnme: Why Do Manufacturing Firms Sell Services ?
            Evidence from India
display_title: Why Do Manufacturing Firms Sell
            Services Evidence from India
listing_relative_url: /research/2021/06/33190537/manufacturing-firms-sell-services-evidence-india
publishtoextweb_dt: 2021-06-18T00:00:00Z
dois: 10.1596/1813-9450-9701
origu: EFI-FCI-TIC-Firms,Entrep,&Innov. (ETIFE)
no_of_pages: 24
author_keys: 0: author_key: 1066720
1: author_key: 429183
model_extractions: Policy Research Working Paper 9701 Why Do Manufacturing Firms Sell Services? Evidence from India _Arti Grover Aaditya Mattoo_ Finance, Competitiveness and Innovation Global Practice June 2021
Policy Research Working Paper 9701

# **Abstract**

Manufacturers in India are increasingly selling services—a phenomenon referred to as servitization. Both the proportion of manufacturers selling services and the share of services in total revenue of manufacturers increased threefold between 1994 and 2013. More productive manufacturers and those more exposed to import competition are more likely to sell services and to obtain a higher share of their revenue from services. A 10 percent increase in servitization is associated with 2.6 percent increase in manufacturing revenue. However, servitizing firms suffer a greater contraction in manufacturing revenue with increased import competition. This evidence suggests that servitization is not a successful defensive strategy to maintain manufacturing sales in the face of import competition, and it is more likely to be an exit strategy to flee import competition. Corroborative results indicate that past services sales are positively associated with the introduction of new services products and eventually a switch out of manufacturing and into services as the primary activity. Thus, servitization appears to be an aspect of “premature deindustrialization” in India, driven by the inability of manufacturers to cope with import competition, rather than structural transformation associated with a maturing manufacturing sector.

This paper is a product of the Finance, Competitiveness and Innovation Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at agrover1@worldbank.org and amattoo@worldbank.org .

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Why Do Manufacturing Firms Sell Services? Evidence from India**

**Arti Grover and Aaditya Mattoo***

**Keywords:** Services, Servitization, Trade competition, Innovation, Structural transformation **JEL Classification codes:** F12, F15, F23, L23, L25, L6

*World Bank, 1818 H Street, Washington DC, USA. Arti Grover, Email:  agrover@worldbank.org; Aaditya Mattoo, Email: amattoo@worldbank.org.  Research for this paper has been supported in part by the World Bank’s Strategic Research Program and the Services-led Development flagship report, EFI. We are grateful for comments from participants in the authors’ workshop of the flagship report, in particular, Valerie Mercer Blackman, Mary HallwardDriemeier, William Maloney, Denis Medvedev and Gaurav Nayyar. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.
# **Section 1: Introduction**

Manufacturing firms are increasingly selling services as well as manufactured products - a phenomenon referred to as servitization.<sup>1</sup> For example, Honeywell, a leading manufacturer in the semi-conductor industry, offers in-flight monitoring of engine systems. Apple offers iPods and iPhones with maintenance and support services, both digital and personal. General Electric, which manufactures a range of products from home appliances to aircraft engines, also offers medical imaging and financing services. In fact, some manufacturing firms have “transitioned” into services firms, such that services activity has become the primary source of revenue.

Even though servitization is not new, and the pattern was evident even in the 1850s (Schmenner, 2009), the emerging literature has only recently begun empirically to address several key questions. Is the trend unique to advanced countries or also visible in manufacturing firms in developing countries?<sup>2</sup> What drives manufacturing firms to sell services? What factors – e.g. technological change, increased competition – have influenced the degree of servitization? Which firm attributes – e.g. size, productivity – are most likely to lead to servitization? Is servitization a pre-curser to, or an aspect of structural transformation? This paper addresses these questions in the context of the manufacturing sector in a developing country, India, which has seen its revealed comparative advantage grow in services at the expense of manufacturing.

In principle, manufacturers may sell services for two broad reasons. _First_ , because of economies of scope in production, i.e. because services offered are a natural extension of the firm’s core strengths. That explains why Apple offers specialized apps which draw on skills and technologies that produce the iPad and iPhone and why an Indian manufacturer such as Asian Paints, belonging to the chemical and chemical products industry, offers interior design and painting services. _Second_ , because of externalities in consumption, i.e. because consumers prefer to buy a manufacturing product and related services from the same firm, and a firm’s bundling the two enhances the appeal of its products.<sup>3</sup> Thus, Apple also offers financial services and personal and recreation services (e.g. iTunes), which are not necessarily an extension of the production capabilities of the firm, but are convenient for consumers to purchase from Apple.<sup>4</sup> In certain cases, servitization happens for both reasons. For example, Apple offers repair and maintenance services for the iPad and iPhone, because it is both well-equipped to and trusted by consumers to do so. Likewise, Bombay Dyeing, an Indian textile firm founded in 1879, offers retail services to its consumers.

Previous empirical work has examined some implications of both rationales for servitization. Breinlich et al. (2014) propose a model where firms allocate their finite stock of accumulated industry expertise in order to augment the productivity of their goods and services production. Using firm-level data from the manufacturing sector in the United Kingdom, they show that accumulated expertise, as embodied by a firm’s stock of research and development, facilitates the transition to more intensive services provision in the face of goods market trade liberalization. In contrast, a larger physical capital stock is associated with a significantly weaker shift into services. Thus, in the case of a shared finite production asset, enhanced goods market competition, whether foreign or domestic, could motivate firms to shift into services. In these circumstances, increasing services revenue is likely to be associated with declining manufacturing revenue.

> 1 The literature on servitization encompasses both the use of services as inputs and their sale as final products by manufacturers (Lodefolk, 2013). In this paper, however, we focus only on the latter aspect, given the unavailability of data on disaggregated inputs.

> 2 Compelling evidence on servitization is primarily drawn from developed countries (Vandermerwe and Rada, 1988; Neely et al., 2011).

> 3 See for example, Mathieu, 2001; Gebauer and Fleisch, 2007; Oliva and Kallenberg, 2003; Wise and Baumgartner, 1999; Mallaret, 2006. To reflect the preferences of consumers’ desire to bundle services with manufactured products, a study on Italian firms shows the strategic relevance of after-sales services for manufacturers of durable goods (Saccani et al. 2007).

> 4 Between 2002 and 2010, Apple sold over 206 million iPods and over one billion songs through the iTunes Music Store (Benedettini et al. 2010).

2
In contrast, servitization motivated by consumers’ preference for bundling could be an avenue to maintain or expand manufacturing revenue. Case studies of GE IBM, Siemens and Hewlett Packard suggest that servitization helped stabilize overall revenues (through diversification), while increasing revenue from main manufactured products (Visnjic and Van Looy, 2009; Sawhney, 2004).<sup>5</sup> These bundled products are also less sensitive to price-based competition which can increase firms’ profits (Mallaret, 2006). This effect may be especially important for “smoothing” services like finance, insurance or highly customized services (e.g. Cusumano et al., 2015). Analysis of French firm-level data reveals that over the period 1997-2007, servitized firms increased their sales of goods by 3.6 percent and profitability between 3.7 and 5.3 percent (Crozet and Milet, 2015).

However, servitization may not always be successful in defending domestic manufacturing sales – an outcome referred to as the _servitization paradox_ (Neely et al., 2011). Some studies have alluded to the importance of reaching threshold levels of servitization before reaping superior financial returns (Fang et al, 2008). Others argue that firms need to have the capacity to handle the cultural and organizational shifts required with servitization (Gebauer et al, 2005). Servitization may require firms to incur fixed costs of servitization, which only the more productive firms may be able to afford.

Our work contributes to the literature on the servitization of manufacturing by conducting a rigorous firmlevel study in a developing country. Most existing studies either use a case study approach or, even when they rely on firm-level data, the samples are hardly representative (e.g. Neely et al., 2011). Although a few studies such as Crozet and Milet (2015) and Breinlich et al. (2014) study servitization using representative firm-level data from France and the United Kingdom, there is no previous firm-level analysis of servitization in a developing country. We fill this gap by studying the patterns of servitization and its correlates for India. We go beyond existing work by exploring whether servitization can be seen as a transitional phase in structural transformation.

We find that the share of manufacturing firms offering services has increased threefold from one-in-five manufacturing firms in 1994 to nearly three-in-five in 2013. At the same time, the intensity of servitization has also tripled: the average share of services revenue in total revenue increased from 7 to 21 percent. Consistent with the trends in advanced countries, firms in high-tech industries are the ones that are most servitized. Among the services provided by manufacturing firms, the share of firms offering financial and business services has increased dramatically over the sample period, while a large share of servitized firms continue to offer retail and wholesale services.

Our analysis shows that servitization of Indian manufacturers is positively associated with exposure to import competition. In addition, it also appears that there are fixed costs of servitization because the phenomenon is associated with the more productive firms. The positive link with import competition is stronger for servitization driven by consumers’ preference for bundling than that based on production economies of scope. That is, firms bundle goods with services preferred by consumers to protect their markets when exposed to global competition.

Our results suggest that servitization does not shield firms from competition. In fact, servitized firms most exposed to import competition see declines in their manufacturing revenue. These results are consistent with the proposition that firms are using servitization as a strategy to gradually flee manufacturing. In this context, we find that servitization in a prior period is associated with a higher probability of product innovation in services. Furthermore, many firms have switched from being primarily manufacturers to primarily service providers by way of servitization and incremental innovation in services. We find that the

> 5 Firms opt in to servitize because it can lead to higher market values (Fang et al. 2008) or higher profitability (Neely 2008, Suarez et al. 2013, Visnjic et al. 2014; Crozet and Milet, 2015).

3
share of firms switching primarily to services activity is correlated with servitization in a prior period. These findings suggest that servitization could possibly pave the way for fuller structural transformation.

The paper is organized as follows. Section 2 reviews the relevant literature and evidence on servitization, Section 3 presents a simple framework for the underlying motivations, as well as the data and estimation strategy. Section 4 presents the overall and industry-level patterns in servitization. Section 5 takes a regression approach to delve deeper into the correlates of servitization. Section 6 seeks to understand the importance of servitization for innovation and structural transformation, and section 7 concludes.

# **Section 2: Servitization across the World: Some Evidence**

The term “servitization” was coined by Vandermerwe and Rada (1988) to describe the phenomenon of bundling services with manufacturing. These services could be an extension of a firm’s productive abilities or allow the manufacturer to differentiate its product from its competitors. Neely et al. (2011) study this phenomenon over the more recent years 2007, 2009 and 2011 in 23 countries. Their work suggests that on average 30 percent of manufacturing firms are servitized across the sample of 23 countries, and this average did not change much over the period they study.<sup>6</sup> This average level masks heterogeneity across countries. For example, 55 percent of firms in the United State, and 19 percent in China were servitized in 2011. In France, the share of servitized firms remained stable at 69 percent over the 10-year period 1997-2007 (Crozet and Milet, 2015), while in Sweden nearly all firms are servitized (Lodefalk 2013, 2015).

Data challenges complicate the analysis of servitization at the intensive margin. For instance, many firms do not report services revenues separately in their accounts due to differences in accounting standards. Industry-level supply-use tables suggest that selling services is still a comparatively limited phenomenon with only 5 percent of revenue in European Union (EU) manufacturing being generated from services (Figure 1). However, industry-level data on services output may not fully measure the extent to which manufacturers sell services. For example, industry-level data from 2011 suggests that services output contributes to about 11 percent output of manufacturing firms in Sweden, while firm-level analysis finds this share to have increased from 13.6 to 20.3 percent of total sales over the 1997-2006 period (Lodefalk 2013, 2015).<sup>7</sup> In France, industry-level figures in 2011 suggest a small contribution of services (2 percent), while firm-level data suggests that this share was close to 18 percent during 1997-2007 (Crozet and Milet, 2015). In the United Kingdom, Figure 1 suggests services share in total revenue to be around 7 percent, while a firm-level study finds this share to have increased from 5 percent in 1997 to slightly over 20 percent in 2007 (Breinlich et al., 2014).<sup>8</sup> In advanced countries, high-tech manufacturing seems to be leading this trend towards servitization. In France, the mechanical and electrical equipment industries are the most servitized with a service intensity of 5 percent, in contrast to food, beverages and tobacco, which have the lowest service intensity, close to 1 percent (Crozet and Milet).<sup>9</sup> In the EU, supply-use tables also suggest that the share of revenue generated from selling services is 6 percent in the more technology intensive industries compared to 3 and 4 percent in medium- and low-tech manufacturing. This can be understood in light of the Dachs et al. (2012) and

> 6 Neely et al. (2011) cover over 10,000 manufacturing firms with over 100 employees in 2007, 2009 and 2011.

> 7 Notice that a 6% increase is considered a significant increase for a country like Sweden where most services are skill-intensive and high value add services. Additionally, many of these manufacturing services are also sold in international market.

> 8 Over and above the evidence detailed below, there are related studies for Austria (Walter and Dell'mour, 2010) and Italy (Federico and Tosti, 2012).

> 9 By comparison, in Sweden Lodefalk (2013, 2015) finds that Medicines; Coke, refined petroleum, nuclear and chemicals; Rubber and plastic products are the most servitized ones while ITC equipment; Paper, pulp, publishing and printing and Basic metals; fabricated metal products are the least servitized. Some of the differences across countries could be explained by differences in definitions of servitization – for instance, in Sweden servitization includes both the use and sale of services, while in France and other countries the definition includes only sales of services.

4
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production economies (top left quadrant) but also other services such as financial because consumers have a strong preference for bundling, irrespective of their technical capacity to provide these services (bottom) left quadrant. When there are neither production economies nor consumption externalities, manufacturers do not have a clear rationale to servitize.<sup>12</sup>

**_Table 1: Servitization is motivated by externalities in consumption and/or economies of scope in_** **_<u>production</u>_**

|||**Consumer preference f**<br>Yes|**or bundling by firms**<br>No|
|---|---|---|---|
|**Economies of**<br>**scope in**<br>**production**|Yes|Production and consumption driven<br>servitization (e.g. repair and<br>maintenance services);|Production driven servitization<br>(e.g. rental & leasing; IT)|
||No|Consumption driven servitization<br>(financial; professional services; retail<br>and wholesale; transport)|No clear rationale for servitization|

# **_Which firms servitize?_**

We focus on two key factors that influence a firm’s decision to servitize: _firm productivity_ and _exposure to import competition_ . Although economies of scope in production and consumer preferences are more likely to push certain industries towards servitization, not all firms within an industry servitize. Servitization is likely to require organizational changes that impose additional fixed costs of bundling services with goods (Gebauer et al, 2005). Given the large productivity differences across firms within narrowly defined industries (Syverson, 2011), it is likely that only the more productive firms servitize.

External competition can induce servitization by firms as a strategy to maintain their sales. With trade liberalization, for instance, firms adapt through quality upgrading, innovation or improving management to survive and even grow.<sup>13</sup> Breinlich et al. (2015) use firm-level data from the United Kingdom to show that servitization could be an additional channel of adjustment. The increase in servitization of UK manufacturing between the period 1997-2007 can be associated with the decline in import tariffs. In an attempt to flee competition, even firms for which it would not be otherwise optimal, such as low productivity manufacturing firms, may find it attractive to bundle their manufactured goods with services valued by consumers. Services that are either more protected from global competition or innately nontradable or both are natural candidates for such manufacturers. Foreign manufacturers find it harder to provide such bundles because trade costs are much higher for many services than goods. For example, the absolute level of ad valorem trade costs in services is estimated to be over 200 percent for India (Mirdout et al., 2013).

# **_3.2 Data sources_**

Given the dearth of firm-level studies for developing countries, we work with firm-level data for India. The firm-level data used in this paper is constructed from the Prowess database which is collected by the Centre for Monitoring the Indian Economy (CMIE). Prowess accounts for 60 to 70 percent of the economic activity in the organized industrial sector and the firms included in this data set contribute to 75 percent of corporate

> 12 Consumers clearly benefit from servitization  when they prefer the bundling of goods and services (Table 1, column 1). Consumers could also benefit when servitization is motivated by economies of scope in production, because quality-adjusted prices are likely to be lower.

> 13 See Khandelwal, 2010; Mayer, Melitz and Ottaviano, 2013; Bloom, Draca and Van Reenen, 2011; Bloom, Sadun and Van Reenen, 2010.

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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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<!-- Start of picture text --> 70% 25%<br>60%<br>20%<br>50%<br>15%<br>40%<br>310%<br>10%<br>20%<br>5%<br>10%<br>0% 0%<br>1994 1996 1998 2000 2002 2004 2006 2008 2010 2012<br>G@shaecfsevitizediims = s-_serice intensity<br><!-- End of picture text -->
<!-- Start of picture text --> Average servitization 2008-2013<br>70% 20.0<br>18.0<br>60% 74<br>16.0<br>50% 140<br>12.0<br>40%<br>10.0<br>30%<br>0 8.0<br>3 8 °<br>20% 9 4 60<br>@48<br>40<br>10%<br>20<br>0% 0.0<br>Wood and wood Allmanufacturing Radio, television, and Electrical machinery Motor vehicles, trailers Medical, precision and = Machineryand —_—Office, accounting and<br>product comm. equipment andapparatus,n.ec. andsemitrailers optical ngruments, | equipment,n.ec. computing machinery<br>watches<br>mw Shareofservitizedfirms @Sevitization intensity<br><!-- End of picture text -->

|Servicescategory|1995-2000|2008-2013|
|---|---|---|
|Financial|14.1%|24.7%|
|Information Technology|2.1%|1.5%|
|Otherservices|9.0%|13.6%|
|Personal, cultural and recreation|0.8%|1.1%|
|Businessand Professional|7.5%|14.2%|
|Repair and Maintenance|0.9%|0.9%|
|Retail and wholesaletrade|63.4%|41.5%|
|Transport|1.2%|1.4%|
|||Average in|
|---|---|---|
|Service|Disaggregate Service|2008-2013|
||Computer and related|9%|
|Business|OtherProfessionalservices|27%|
||<br>Real Estate|10%|
||Rental and leasing|54%|
||Asset financing and management|39%|
|Financial|Financial, including leasing|39%|
||Securitiesservices|23%|

|Industry|STRI|Meantrade cost|
|---|---|---|
|Manufacturing|n.d.|0.769|
|wholesale trade|n.d.|3.041|
|Retail trade|75|6.02|
|transportation|62.30|3.224|
|Information|50|TATA|
|Finance and Insurance|48.06|3.669|
|Real estate and leasing|n.d.|22.05|
|Professional services|87.5|4.887|
|Admin services|n.d.|4,657|
|overall|65.72|3.166|
|Manufacturing Industry|Communication|Financial|Information<br>Technology|Other<br>services|Personal&<br>recreation|Business&<br>Professional|Repair &<br>Maintenance|Retail&<br> wholesaletrade|Transport|
|---|---|---|---|---|---|---|---|---|---|
|Food products and beverages|0.0%|15.9%|0.2%|14.2%|1.1%|10.0%|0.0%|56.5%|1.8%|
|Tobacco products|0.0%|8.6%|0.0%|3.0%|5.5%|14.0%|0.0%|69.0%|0.0%|
|Textiles|0.0%|19.4%|0.5%|13.0%|0.8%|14.8%|0.1%|50.2%|1.1%|
|Wearing apparel; dressing and dyeing offur|0.0%|16.4%|0.6%|16.0%|0.7%|10.8%|0.0%|54.1%|1.3%|
|Leathertanning; luggage, handbags, footwear|0.0%|14.8%|0.0%|11.7%|3.3%|7.1%|3.3%|54.3%|4.8%|
|Wood and wood products|0.0%|13.4%|0.0%|9.0%|0.0%|15.4%|0.0%|60.6%|0.0%|
|Paperand paper products|0.5%|26.8%|0.5%|14.1%|1.2%|11.8%|0.0%|42.2%|2.6%|
|Publishing, printing and media reproduction|3.3%|32.3%|0.0%|21.9%|44%|25.9%|0.0%|10.7%|0.0%|
|Coke, refined petroleum and nuclear fuel|0.1%|16.6%|0.2%|13.8%|0.2%|10.4%|0.0%|55.5%|2.4%|
|Chemicals and chemical products|0.0%|17.0%|0.6%|16.4%|0.5%|10.2%|0.0%|53.0%|0.4%|
|Rubberand plastic products|0.1%|19.5%|0.1%|16.2%|0.1%|10.1%|0.3%|51.7%|1.6%|
|Other non-metallic mineral products|0.1%|23.8%|0.0%|13.7%|1.1%|10.8%|0.1%|45.6%|4.3%|
|Basic metals|0.3%|18.1%|0.3%|13.2%|0.1%|10.3%|0.0%|56.3%|1.1%|
|Fabricated metal products, except machinery|1.0%|15.7%|0.0%|24.6%|1.5%|9.1%|1.3%|42.8%|3.1%|
|Machineryand equipment, n.e.c.|0.4%|13.3%|0.6%|30.2%|1.0%|15.9%|3.6%|33.7%|0.9%|
|Office, accounting and computing machinery|1.6%|10.6%|11.0%|18.8%|0.0%|16.9%|8.5%|32.6%|0.0%|
|Electrical machineryand apparatus, n.e.c.|1.6%|13.0%|1.4%|27.5%|0.4%|10.4%|5.3%|39.7%|0.7%|
|Radio, television, and comm. equipment|3.5%|13.7%|4.4%|31.8%|0.0%|8.9%|3.7%|32.9%|0.4%|
|Medical, precision and optical instruments|0.0%|17.0%|4.1%|35.0%|1.5%|15.3%|1.9%|23.1%|1.3%|
|Motor vehicles, trailers and semi-trailers|0.0%|17.2%|0.0%|27.8%|0.0%|3.9%|2.4%|46.6%|2.1%|
|Other transport equipment|0.0%|13.9%|1.3%|25.0%|0.3%|9.7%|1.3%|45.3%|3.2%|
|Furniture,manufacturingn.e.c|0.4%|18.2%|0.4%|12.9%|1.8%|12.8%|1.7%|49.4%|1.4%|
|Dependent variable-->||Extensive|Margin|||Intensive|Margin||
|---|---|---|---|---|---|---|---|---|
|Total factor productivity|0.093***<br>(0.024)|0.113***<br>(0.031)|0.224***<br>(0.077)|0.094***<br>(0.024)|0.035**<br>(0.014)|0.047***<br>(0.018)|0.032<br>(0.029)|0.035**<br>(0.014)|
|Logged age|0.091|0.087|0.228|0.108|-0.014|-0.018|-0.255**|-0.013|
||(0.123)|(0.123)|(0.300)|(0.123)|(0.073)|(0.073)|(0.121)|(0.073)|
|Small-sized firm|-0.384***|-0.384***|-0.081|0.049|0.141**|0.142**|= 0.142|0.211|
||(0.098)|(0.098)|(0.381)|(0.221)|(0.058)|(0.058)|(0.127)|(0.154)|
|Mid-sized firm|-0.287***|-0.288***|-0.424***|-0.206|0.011|0.010|0.006|-0.049|
||(0.060)|(0.060)|(0.158)|(0.140)|(0.032)|(0.032)|(0.059)|(0.085)|
|Logged goods exports|0.018***|0.018***|0.014|0.018***|0.002|0.002|0.002|0.002|
||(0.004)|(0.004)|(0.012)|(0.004)|(0.002)|(0.002)|(0.004)|(0.002)|
|Logged services exports|0.064***|0.064***|0.063***|0.064***|0.016***|0.016***|0.014***|0.016***|
||(0.007)|(0.007)|(0.011)|(0.007)|(0.002)|(0.002)|(0.003)|(0.002)|
|Logged imports|0.030***|0.030***|0.061***|0.030***|0.008***|0.008***|0.007|0.008***|
||(0.005)|(0.005)|(0.019)|(0.005)|(0.003)|(0.003)|(0.006)|(0.003)|
|Exposure to imports|0.132***|0.123***|0.182|0.158***|0.094***|0.088***|0.132**|0.091***|
||(0.038)|(0.038)|(0.174)|(0.042)|(0.018)|(0.018)|(0.053)|(0.019)|
|Highproductivity firm||0.004||||0.004|||
|*exposure to imports||(0.013)||||(0.005)|||
|Low productivity firm||0.020||||0.013**|||
|*exposure to imports||(0.014)||||(0.005)|||
|LoggedR&D intensity|||0.025||||0.019||
||||(0.106)||||(0.038)||
|LoggedR&D intensity|||-0.000||||-0.002||
|*exposure to imports|||(0.026)||||(0.008)||
|Small-sized firm||||-0.124**||||-0.020|
|*exposure to imports||||(0.057)||||(0.037)|
|Mid-sized firm||||-0.023||||0.016|
|*exposure to imports||||(0.036)||||(0.019)|
|Number ofobservations|29168|29168|6519|29168|36128|36128|9407|36128|
|Numberoffirms|3137|3137|699|3137|4314|4314|1138|4314|

Notes: Services revenue includes all services offered by firms ever classified as manufacturing. This include firms that offer construction and other services. Services estimations at the extensive margins are done with logit function, while those at the intensive margins use the poisson pseudo maximum likelohood (PPML) estimator. All estimations include firm and year fixed effects and report standard errors clustered at the firm-level. Significance levels are indicated with *** (at 1 % level), ** (at 5% level) and * (at 10% level).
|Dependent variable—>|Extensive|Margin|Intensive|Margin|
|---|---|---|---|---|
||Consumer<br>based<br>|Producer<br>based<br>|Consumer<br>based<br>|Producer<br>based<br>|
||rr<br>—@|rr<br>i)|a a<br>CG)<br>CG|a<br>)|
|Total factor productivity|0.067|0.059|-0.018***|0.005|
||(0.041)|(0.072)|(0.005)|(0.026)|
|Exposure to imports|0.136**|-0.029|0.025***|-0.000|
||(0.061)|(0.107)|(0.008)|(0.038)|
|Number ofobservations|27888|6022|33701|6578|
|Numberoffirms|2994|625|3990|739|

Notes: See Table 3a. Estimations from columns 1 and 4 are repeated by separating out servitization based on consumers and producers preference. All estimations include the controls presented in Columns 1 and 4 of Table 3a. Significance levels are indicated with *** (at 1 % level), ** (at 5% level) and * (at 10% level).
|DV: logged total||||Intensive|margin (Se|rvitized|
|---|---|---|---|---|---|---|
|manufacturing sales<br>|Extensiv<br>|e Margin (<br>|All firms)<br>||firms)<br>||
|i|a<br>(1)|a<br>(2)|a<br>(3)|a<br>(4)|a<br>(5)|(6)|
|Exposure to import competition|-O.115*** <br>(0.025)|-0.115***<br>(0.025)|-0.097***<br>(0.024)|-0.302***<br>(0.044)|—-0.303*** <br>(0.044)|-0.209***<br>(0.036)|
|Servitization||-0.018<br>(0.018)|0.114**<br>(0.052)||0.014<br><br>(0.018)|= 0.263***<br>(0.057)|
|Exposure*Servitization|||-0.037***|||-0.060***|
||||(0.014)|||(0.013)|
|Total observations|62720|62720|62720|22315|23695|22556|
|Numberoffirms|8874|8874|8874|4756|4954|3815|

Notes: The table shows estimation results of a regression of manufacturing revenue on firm traits, including exposure to imports and servitization. Columns 1-3 use a dummy to characterize servitization, while columns 4-6 use services revenue as a share of total revenue to measure servitization. All estimations include firm and year fixed effects and report standard errors clustered at the firm-level. Significance levels are indicated with *** (at 1 % level), ** (at 5% level) and * (at 10% level).

||Serviti|zation at th|e extensive|margin|Inten|sive margin|(Servitized|firms)|
|---|---|---|---|---|---|---|---|---|
|DV: logged total<br>manufacturingsales<br>|Consu<br>bund<br>|mers'<br>ling<br>|Produ<br>Economies<br>|cers'<br>ofScope<br>|Consu<br>bund<br>|mers'<br>ling<br>|Produ<br>Economies<br>|cers'<br>ofScope<br>|
|<br>———n>smm||||<br>||D||<br>N|
|Exposure to importcompetition|-0.115*** <br>(0.025)|-0.106*** <br>(0.025)|= -0.115***<br>(0.025)|-0.111***<br>(0.025)|-0.302***<br>(0.044)|-0.227***<br>(0.045)|-0.301***<br>(0.044)|—-0.306***<br>(0.042)|
|Servitization|-0.021|0.037|-0.143***|-0.131***|0.000|0.019**|-0.006*|-0.012|
||(0.018)|(0.034)|(0.046)|(0.046)|(0.003)|(0.008)|(0.003)|(0.013)|
|Exposure*Servitization||-0.018*||-0.007||-0.005***||0.002|
|||(0.009)||(0.005)||(0.002)||(0.003)|
|Total observations|62720|62720|62720|62720|25947|25947|25947|25947|
|Numberoffirms|8874|8874|8874|8874|5198|5198|5198|5198|

Notes: See Table 4a. Columns 1-4 measure the effect of servitization at the extensive margin: with columns 1-2 measursing the correlation with respect to consumer based services and 3-4 for producer based services. 5-8 repeat the same with servitization at the intensive margin. All estimations include firm and year fixed effects and report standard errors clustered at the firm-level. Significance levels are indicated with *** (at 1 % level), ** (at 5% level) and * (at 10% level).
|DV: Product innovation||Extensive Mar|gin||Intensive mar|gin|
|---|---|---|---|---|---|---|
|(dummy)<br>|All<br><br>|Services<br><br>|Manufacturing<br><br>|All<br>|Services<br>|Manufacturing<br><br>|
||1|a a<br>2|a a<br>3|a<br>4|a<br>5|a<br>al<br>6|
|Exposure to imports|0.125***|0.101**|0.139***|0.122***|0.086*|0.139***|
||(0.030)|(0.045)|(0.032)|(0.030)|(0.045)|(0.032)|
|Lagged Servitization|0.345***|0.811***|0.032|0.105***|0.235***|0.006|
||(0.036)|(0.050)|(0.040)|(0.015)|(0.019)|(0.016)|
|Total factorproductivity|-0.022|0.012|-0.020|-0.022|0.009|-0.020|
||(0.019)|(0.029)|(0.020)|(0.019)|(0.029)|(0.020)|
|Total observations|38994|24238|36870|38994|24238|36870|
|Numberoffirms|5228|3029|4921|5228|3029|4921|

Notes: These estimations regress an indicator variable on firm's product innovation at a 5-digit level on firm level trait. including exposure to import competition and servitization strategy. Columns (1) and (2) consider servitization at the extensive margins, while columns (3) and (4) use servitization as a continuous variable. All estimations include standard vector of firm traits, firm and year fixed effects and report standard errors clustered at the firm-level. Significance levels are indicated with *** (at 1 % level), ** (at 5% level) and * (at 10% level).
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<!-- Start of picture text --> Extensive _ Intensive<br>DV: Switch to services as primary All Margin margin<br>product (dummy) | rr(1) a(2) a(3)<br>Exposure to imports 0.536*** —0.561*** 0.531***<br>(0.091) (0.101) (0.103)<br>Lagged Servitization 0.671*** 0.256***<br>(0.196) (0.046)<br>Total factor productivity -0.227*** -0.152* -0.152*<br>(0.070) (0.082) (0.083)<br>Total observations 3156 2546 2546<br>Number of firms 404 344 344<br>Notes: These estimations regress an indicator variable for switch into services. All<br>estimations include standard vector of firm traits, firm and year fixed effects and report<br>standard errors clustered at the firm-level. Significance levels are indicated with *** (at<br>1 % level), ** (at 5% level) and * (at 10% level).<br><!-- End of picture text -->

|||Extensive|_Intensive|
|---|---|---|---|
|DV:Switchtoservicesasprimary<br>|All<br>|<br>Margin<br>|<br>margin<br>|
|<br>product (dummy)|| rr <br>(1)|a <br>(2)|a<br>(3)|
|Exposure to imports|0.536***<br>(0.091)|—0.561***<br>(0.101)|0.531***<br>(0.103)|
|Lagged Servitization||0.671***<br>(0.196)|0.256***<br>(0.046)|
|Total factor productivity|-0.227***<br>(0.070)|-0.152*<br>(0.082)|-0.152*<br>(0.083)|
|Total observations|3156|2546|2546|
|Number offirms|404|344|344|
|Notes: These estimations regress an indicato<br>estimations include standard vector offirm tr<br>standard errors clustered at the firm-level. Si<br>1%level),**(at5%level)and*(at10%le|r variable for s<br>aits, firm and <br>gnificance leve<br>vel).|witch into serv<br> year fixed effe<br>ls are indicate|ices. All<br>cts and report<br>d with *** (at|
# **Section 6: Conclusions**

By highlighting the “servitization of manufacturing” in India, we present evidence that the distinction between manufacturing and services firms is artificial. Our work suggests that over the period 1994-2013 both the share of servitized firms and the share of services sales in total revenue increased threefold. Much of the servitization in Indian manufacturing can be attributed to high-tech industries, and towards provision of financial and business and professional services.

Manufacturers servitize because of economies of scope in offering services bundled with goods or due to consumers’ preferences for goods bundled with services. In the absence of competition, manufacturers are not inclined to offer services based on consumers’ preferences. However, when countries open up to trade, manufacturers’ response can change. Our analysis suggests that servitization in India is strongly and positively correlated with exposure to import competition. It is notable that low productivity manufacturers servitize more aggressively when exposed to import competition.

Servitization boosts revenue but does not help shield manufacturing revenue from import competition. Our results suggest that although a 10 percent increase in servitization intensity is associated with a 2.6 percent increase in manufacturing revenue, servitized firms with higher exposure to imports actually register a decline in manufacturing revenue. This suggests that servitization may be a gradual escape route from manufacturing into services. In fact, we find that servitization is positively associated with product innovation in services rather than manufacturing, and it is also associated with a switch out of manufacturing. In this story of transition from being a manufacturer to a service provider, firm productivity seems to play a negative role. Said differently, the firms that innovate more in services and those that switch out of manufacturing are the low productivity ones, thereby suggesting that (this form of) structural transformation may be more premature deindustrialization (Rodrik, 2015) rather than an endogenous transition to a more advanced stage of development.

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19
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<!-- Start of picture text --> DV: Dummy representing whether a Services (excl. construction Services, product based<br>firm is servitized or not and others) description<br>a a a a ar rr a a re<br>(1) (2) (3) (4) (5) (6) (7) (8)<br>Total factor productivity 0.082*** 0.083*** 0.169** 0.082*** 0.109**#* 0.129*** 0.214*** 0.110***<br>(0.024) (0.032) (0.081) (0.024) (0.024) (0.032) (0.077) (0.024)<br>Logged age 0.216* 0.212 0.312 0.224* 0.095 0.090 0.033 0.109<br>(0.129) (0.129) (0.320) (0.129) (0.123) (0.123) (0.290) (0.123)<br>Small-sized firm -0.275*** -0.276*** -0.238 0.056 -0.303*** -0.302*** -0.046 0.101<br>(0.101) (0.101) (0.387) (0.232) (0.099) (0.099) (0.381) (0.225)<br>Mid-sized firm -0.175*** -0.176*** -0.330** -0.230 -0.186*** -0.187*** -0.353** — -0.174<br>(0.063) (0.063) (0.158) (0.149) (0.061) (0.061) (0.155) (0.144)<br>Logged goods exports 0.023*** 0.023*** 0.037*** 0.023*** 0.022*** 0.022*** 0.035*** 0.022***<br>(0.005) (0.005) (0.012) (0.005) (0.004) (0.004) (0.012) (0.004)<br>Logged services exports 0.064*** 0.064*** 0.067*** 0.064*** 0.068*** 0.068*** 0.069*** 0.068***<br>(0.007) (0.007) (0.011) (0.007) (0.007) (0.007) (0.011) (0.007)<br>Logged imports 0.021*** 0.021*** 0.042** 0.020*** 0.028*** 0.028*** 0.047** 0.028***<br>(0.005) (0.005) (0.019) (0.005) (0.005) (0.005) (0.019) (0.005)<br>Exposure to imports 0.208*** 0.197*** -0.016 0.215*** 0.160*** 0.151*** 0.210 0.177***<br>(0.040) (0.040) (0.178) (0.044) (0.038) (0.039) (0.172) (0.043)<br>High productivity firm 0.019 0.006<br>*exposure to imports (0.013) (0.013)<br>Low productivity firm 0.016 0.021<br>*exposure to imports (0.014) (0.014)<br>Logged R&D intensity 0.178* 0.050<br>(0.107) (0.103)<br>Logged R&D intensity -0.035 -0.003<br>*exposure to imports (0.026) (0.025)<br>Small-sized firm -0.093 -0.114**<br>*exposure to imports (0.059) (0.058)<br>Mid-sized firm 0.016 -0.003<br>*exposure to imports (0.038) (0.036)<br>Number of observations 27499 27499 6347 27499 28061 28061 6491 28061<br>Number of firms 2944 2944 674 2944 3014 3014 694 3014<br>Notes: See Table 3<br><!-- End of picture text -->

|DV: Dummy representingwhether a|Services|(excl. con|struction||Service|s, product|based||
|---|---|---|---|---|---|---|---|---|
|firmisservitizedornot<br>|a<br>|ndothers<br>|)<br>||d<br>|escription<br>|||
|<br>a|a<br>(1)|<br>a<br>(2)|a<br>(3)|ar<br>(4)|rr <br>(5)|a<br>(6)|a<br>(7)|re<br>(8)|
|Totalfactorproductivity|0.082***|0.083***|0.169**|0.082***|0.109**#*|0.129***|0.214***|0.110***|
||(0.024)|(0.032)|(0.081)|(0.024)|(0.024)|(0.032)|(0.077)|(0.024)|
|Logged age|0.216*|0.212|0.312|0.224*|0.095|0.090|0.033|0.109|
||(0.129)|(0.129)|(0.320)|(0.129)|(0.123)|(0.123)|(0.290)|(0.123)|
|Small-sized firm|-0.275***|-0.276***|-0.238|0.056|-0.303***|-0.302***|-0.046|0.101|
||(0.101)|(0.101)|(0.387)|(0.232)|(0.099)|(0.099)|(0.381)|(0.225)|
|Mid-sized firm|-0.175***|-0.176***|-0.330**|-0.230|-0.186***|-0.187***|-0.353**|—-0.174|
||(0.063)|(0.063)|(0.158)|(0.149)|(0.061)|(0.061)|(0.155)|(0.144)|
|Loggedgoods exports|0.023***|0.023***|0.037***|0.023***|0.022***|0.022***|0.035***|0.022***|
||(0.005)|(0.005)|(0.012)|(0.005)|(0.004)|(0.004)|(0.012)|(0.004)|
|Logged services exports|0.064***|0.064***|0.067***|0.064***|0.068***|0.068***|0.069***|0.068***|
||(0.007)|(0.007)|(0.011)|(0.007)|(0.007)|(0.007)|(0.011)|(0.007)|
|Logged imports|0.021***|0.021***|0.042**|0.020***|0.028***|0.028***|0.047**|0.028***|
||(0.005)|(0.005)|(0.019)|(0.005)|(0.005)|(0.005)|(0.019)|(0.005)|
|Exposure to imports|0.208***|0.197***|-0.016|0.215***|0.160***|0.151***|0.210|0.177***|
||(0.040)|(0.040)|(0.178)|(0.044)|(0.038)|(0.039)|(0.172)|(0.043)|
|High productivity firm||0.019||||0.006|||
|*exposure to imports||(0.013)||||(0.013)|||
|Lowproductivity firm||0.016||||0.021|||
|*exposure to imports||(0.014)||||(0.014)|||
|LoggedR&D intensity|||0.178*||||0.050||
||||(0.107)||||(0.103)||
|LoggedR&D intensity|||-0.035||||-0.003||
|*exposure to imports|||(0.026)||||(0.025)||
|Small-sized firm||||-0.093||||-0.114**|
|*exposure to imports||||(0.059)||||(0.058)|
|Mid-sized firm||||0.016||||-0.003|
|*exposure to imports||||(0.038)||||(0.036)|
|Number ofobservations|27499|27499|6347|27499|28061|28061|6491|28061|
|Number offirms|2944|2944|674|2944|3014|3014|694|3014|
|Notes:SeeTable3|||||||||
|Dependent variable: Shar<br>services revenue|e of<br>S|ervices, v|alue base|d|Services|, product|based de|scription|Relative|to manuf|acturing|revenue|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|
|Total factor productivity|0.043***|0.057***|0.059*|0.042***|0.025|0.037*|0.047|0.025|0.025*|0.034*|0.024|0.025*|
||(0.015)|(0.020)|(0.033)|(0.015)|(0.016)|(0.021)|(0.034)|(0.016)|(0.015)|(0.019)|(0.031)|(0.015)|
|Loggedage|-0.087|-0.091—|-0.367***|-0.088|-0.119=|-0.123*|=-0.395***|-0.122|-0.011|-0.015|-0.294**|=-0.005|
||(0.073)|<br>(0.073)|<br>(0.121)|<br>(0.073)|<br>(0.074)|<br>(0.074)|<br>(0.123)|<br>(0.075)|(0.076)|(0.076)|<br>(0.122)|<br>(0.076)|
|Small-sized firm|0.144**|0.144**|0.147|0.187|0.152**|0.153**|0.172|0.160|0.144**|0.145**|0.118|0.304*|
||(0.059)|(0.059)|(0.129)|(0.152)|(0.061)|(0.060)|(0.133)|(0.158)|(0.062)|(0.062)|(0.134)|(0.162)|
|Mid-sized firm|0.019|0.019|0.011|-0.089|0.023|0.022|0.010|-0.093|0.015|0.014|-0.004|0.005|
||(0.033)|(0.033)|(0.062)|(0.089)|(0.034)|(0.034)|(0.062)|(0.092)|(0.034)|(0.034)|(0.060)|(0.091)|
|Logged goods exports|0.002|0.002|0.004|0.002|0.001|0.001|0.003|0.001|0.000|0.000|0.002|0.000|
||(0.002)|(0.002)|(0.004)|(0.002)|(0.002)|(0.002)|(0.004)|(0.002)|(0.002)|(0.002)|(0.004)|(0.002)|
|Logged services exports|0.018***|0.018***|0.018***|0.018***|0.018***|0.018***|0.018***|0.018***|0.017***|0.017***|0.015***|0.016***|
||(0.002)|(0.002)|(0.003)|(0.002)|(0.002)|(0.002)|(0.003)|(0.002)|(0.002)|(0.002)|(0.003)|(0.002)|
|Logged imports|0.007**|0.007**|0.002|0.007**|0.006**|0.006**|0.002|0.006**|0.007***|0.007***|0.008|0.007***|
||(0.003)|(0.003)|(0.006)|(0.003)|(0.003)|(0.003)|(0.006)|(0.003)|(0.003)|(0.003)|(0.006)|(0.003)|
|Exposure to imports|0.063***|0.056***|0.126**|0.056***|0.062***|0.054***|0.147**|0.053**|0.133***|0.127***|0.153***|0.137***|
||(0.019)|(0.019)|(0.057)|(0.021)|(0.020)|(0.020)|(0.061)|(0.021)|(0.020)|(0.020)|(0.053)|(0.021)|
|High productivity firm||0.005||||0.007||||0.006|||
|*exposure to imports||(0.006)||||(0.006)||||(0.006)|||
|Lowproductivity firm||0.015***||||0.015**||||0.012**|||
|*exposure to imports||(0.006)||||(0.006)||||(0.006)|||
|LoggedR&D intensity|||-0.003||||-0.024||||0.040||
||||(0.045)||||(0.047)||||(0.038)||
|LoggedR&D intensity|||0.005||||0.010||||-0.007||
|*exposure to imports|||(0.009)||||(0.010)||||(0.008)||
|Small-sized firm||||-0.013||||-0.003||||-0.044|
|*exposure to imports||||(0.036)||||(0.037)||||(0.038)|
|Mid-sized firm||||0.028||||0.030||||0.003|
|*exposure to imports||||(0.020)||||(0.021)||||(0.021)|
|Number ofobservations<br>|34639<br>|34639<br>|9121<br>|34639<br><br>|34639<br>|34639<br>|9121<br><br>|34639<br><br>|36128<br>|36128<br>|9407<br>|36128<br>|
|Numberoffirms|4128|4128|1097|4128|4128|4128|1097|4128|4314|4314|1138|4314|

Notes: See Table 3.