This paper investigates heterogeneity in Total Factor Productivity (TFP) of a sample of Knowledge-Intensive Business Services (KIBS) firms actively operating in Italy over the period 2012-2018. Business service industries can be defined as KIBS if they are private sector organizations that offer specialist professional, consultancy, and outsourcing services to other organization relying heavily on professional knowledge. On the basis of an ample literature, KIBS firms support the innovation process of organizations in different industry market, including, in particular, small and medium-sized ones, and of those operating in the public sector, through knowledge generation and diffusion. Starting from the underlying idea that KIBS firms differ from each other in several ways, whatever their location, and such heterogeneity in firm-specific characteristics is supposed to translate into heterogeneity in business performance, the main object of the present contribution is to analyze KIBS productivity heterogeneity on the basis of their localization and business sector. The empirical analysis is conducted at firm-level using a large sample of KIBS firms, obtained, as primary source, from the AIDA- Bureau van Dick database, which contains all Italian firms’ dis-aggregated balance sheet and profit and loss statement information for the period 2012-2018. In particular, we consider the following Eurostat NACE Rev. 2 statistical sectors: 62-63 (information technology and communication sectors), 69-70-71-72-73-74 (professional, scientific and technical sectors). Based on the efficiency scores obtained from DEA (Data Envelopment Analysis), we estimate the Malmquist Productivity Index for the period under investigation (2012-2018) to measure the variation of firms TFP. Moreover, in order to investigate if the source of productivity heterogeneity among the firm can be explained by firm specific features (geographic location, activity sector), a multilevel statistical modelling approach is used.
The Source of Productivity Heterogeneity in the Italian Knowledge-Intensive Business Services (KIBS) Industry
Morea D.
2020-01-01
Abstract
This paper investigates heterogeneity in Total Factor Productivity (TFP) of a sample of Knowledge-Intensive Business Services (KIBS) firms actively operating in Italy over the period 2012-2018. Business service industries can be defined as KIBS if they are private sector organizations that offer specialist professional, consultancy, and outsourcing services to other organization relying heavily on professional knowledge. On the basis of an ample literature, KIBS firms support the innovation process of organizations in different industry market, including, in particular, small and medium-sized ones, and of those operating in the public sector, through knowledge generation and diffusion. Starting from the underlying idea that KIBS firms differ from each other in several ways, whatever their location, and such heterogeneity in firm-specific characteristics is supposed to translate into heterogeneity in business performance, the main object of the present contribution is to analyze KIBS productivity heterogeneity on the basis of their localization and business sector. The empirical analysis is conducted at firm-level using a large sample of KIBS firms, obtained, as primary source, from the AIDA- Bureau van Dick database, which contains all Italian firms’ dis-aggregated balance sheet and profit and loss statement information for the period 2012-2018. In particular, we consider the following Eurostat NACE Rev. 2 statistical sectors: 62-63 (information technology and communication sectors), 69-70-71-72-73-74 (professional, scientific and technical sectors). Based on the efficiency scores obtained from DEA (Data Envelopment Analysis), we estimate the Malmquist Productivity Index for the period under investigation (2012-2018) to measure the variation of firms TFP. Moreover, in order to investigate if the source of productivity heterogeneity among the firm can be explained by firm specific features (geographic location, activity sector), a multilevel statistical modelling approach is used.File | Dimensione | Formato | |
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