Explaining firm-level total factor productivity in post-transition: manufacturing vs. services sector

Abstract

Abstract. Post transition economies carry the legacy of previous system, supposed to have collapsed in partly due to inability to sustain innovation and technical progress. In terms of innovation activity, they still lag behind advanced market economies. This brings the issue of total factor productivity (TFP) for these countries/industries/firms in focus of research interest. Relying on the TFP firmlevel estimates from the World Bank' Enterprise Survey dataset, we analyse the main contributing factors in following post-transition economies: Georgia, Turkey, Ukraine, Russia, Romania, Bosnia and Herzegovina, FYR Macedonia, Mongolia, Slovenia and Croatia. The potential determinants include variables frequently named in the literature: R&D efforts, human capital, ICT investment, competition (product market regulation) and international trade. The data for the TFP determinants is drawn from Business Environment and Enterprise Performance Survey (BEEPS V), which includes both objective variables and perceptions of firms' management. Since many objective variables are simultaneously determined with our dependent variable, we argue that by relying on perceptions we omit the endogeneity issue. In addition to aggregate firm-level TFP determinants, we also distinguish between the manufacturing and service sector. The aim of the research is to emphasize the structural differences between these two segments of post-transition economies.

Exploring firm-level and sectoral variation in total factor productivity (TFP)

“…Previously published studies on productivity determinants (Botri c et al, 2017;Cie slik et al, 2019;Du and Temouri, 2015) examine and confirm various factors that cause variability in productivity levels, and agree on considerable and persistent heterogeneity in the firm-level productivity, across countries and industries. For instance, the research based on the industrial organisation literature usually addresses the relationship between productivity levels and market structure (Syverson, 2004), the influence of competition (Galdon-Sanchez and Schmitz, 2002;Holmes and Schmitz, 2010), technology issues and technology spillovers (Bloom et al, 2013;Castellacci, 2007;Los and Verspagen, 2007) or organizational structures (Chang and Lee, 2016;Lim and Sanidas, 2011;Schoar, 2002) in the context of productivity growth.…”

“…Within the international trade theory, the studies usually confirm that the exporter status has significant contribution for firm-level productivity heterogeneity (Bravo-Ortega et al, 2014;Manso Machado, 2019;Nunes et al, 2020;Salomon and Jin, 2008). Several studies also examine the spatial dimension of the differences in firm-level productivity (Cie slik et al, 2019;Mart ınez-Victoria et al, 2018) or productivity variations across industries (Biatour et al, 2011;Botri c et al, 2017). Although the existing research literature related to this topic is very large in scale and scope, robust empirical analyses on the firm-and sectoral-level productivity variations, based on large longitudinal and representative datasets, are still sparse, as well as studies that examine the long-term relationships between economic variables and productivity development (Erken et al, 2018).…”

How Heterogeneous Are the Determinants of Total Factor Productivity in Manufacturing Sectors? Panel-Data Evidence from Vietnam

“…External drivers of productivity differences are also listed such as productivity spillovers (Martin et al 2011), horizontal linkages (Nichter and Goldmark 2009), competition (Foster et al 2008;Ali and Peerlings 2011), deregulation or proper regulation (Bridgman et al 2009;Fabrizio et al 2007;Brown et al 2006), flexible input markets (Maksimovic and Phillips 2001;Hsieh and Klenow 2009;Bartelsman et al 2009). Since the work of Syverson (2011), several empirical studies have explored further potential determinants and in many directions (see, for example, Kreuser and Newman 2018;Kim 2018;Botrić et al 2017;Satpathy et al 2017;Venturini 2015;İmrohoroglu and Tüzel 2014;Mohnen and Hall 2013). Kreuser and Newman (2018), using a firm-level sample of the South African manufacturing sector, found that there is heterogeneity of growth across subsectors.…”

Demographic Forecasts and Volatility of Investment Rates vs. Labor Productivity Trajectories

“…Therefore, for the description of investments they introduce a sinusoidally dependent function from time. The analyzes carried out by the authors show that an introduction of interest rates sine-dependent investments in time affects significantly the cyclicality of technical work equipment and labor productivity (Kudinova & Verba, 2014;Botrić, Božić, & Broz, 2017).…”