Intangible assets and the efficiency of manufacturing firms in the age of digitalisation: the Russian case

Turovets, Yulia

doi:10.2478/emj-2021-0001

Figures & Tables

Framework of the study in the context of productivity analysisSource: elaborated by the author based on Kumbhakar and Fuss, 2000; Coelli et al., 2003; Corrado, Hulten and Sichel, 2005; Borras and Edquist, 2013.

Distribution of technical efficiency for the full sample with inefficiency determinants

Distribution of technical efficiency for the firms from high-tech sectors with inefficiency determinants

Distribution of technical efficiency for the firms from low-tech sectors with inefficiency determinants

Average technical efficiency dynamic in 2009–2018 for the full sample modelNote: TE — technical efficiency for the full sample, TE high-tech — technical efficiency for the firms of the high-tech sectors, TE low-tech — technical efficiency for the firms of the low-tech sectors.

Estimations of time-invariant (TI) and time-variant (TVD) models by the two time periods and the groups of firms

	Model 1 TI-model without trend and inefficiency determinants for high-tech firms	Model 2 TI-model without trend and inefficiency determinants for low-tech firms	Model 3 TVD-model for high-tech firms	Model 4 TVD-model for high-tech firms after 2014	Model 5 TVD-model for low-tech firms	Model 6 TVD-model for low-tech firms after 2014
Production frontier (dependent variable ln_y)
Number of observations	1,472	1,443	1472	770	1443	764
ln_fa_real	0.107^*** (0.014)	0.073^*** (0.007)	0.064^*** (.018)	0.076^*** (0.010)	0.047^*** (0.016)	0.033^** (0.014)
ln_assets	0.339^*** (0.016)	0.430^*** (0.019)	0.294^*** (0.027)	0.462^*** (0.029)	0.42^*** (0.028)	0.311^*** (0.030)
ln_l	0.552^*** (0.023)	0.483^*** (0.024)	0.642^*** (0.038)	0.450^*** (0.038)	0.558^*** (0.032)	0.522^*** (0.033)
ln_ita_real	0.010^*** (0.004)	0.014^*** (0.003)	0.014^*** (0.005)	0.014^*** (0.005)	0.004 (0.005)	0.005 (0.006)
t			0.071 (0.045)	0.039^*** (0.008)	0.234^*** (0.031)	0.016 (0.014)
const	4.542^*** (0.202)	4.729^*** (0.186)	6.148 (0.651)	4.281^*** (0.284)	2.920^*** (0.318)	6.878^*** (0.336)
eta			−0.047^** (0.019)	−0.042^*** (0.012)	−0.240^*** (0.022)	0.001 (0.012)
	−1.373^*** (0.067)	−2.219 (0.102)
	−0.136^** (0.070)	0.116 (0.056)

Strategies and policy tools to support digitalisation according to the technology intensity of firms

High-tech firms

Low-tech firms

Develop an intangible technology asset

Effects

Frontier shift ++
Efficiency change −

Policy tools

Grants
Venture capital
Tax incentives
Preferential loans
Standardisation
Testbeds
Regulatory sandbox

Effects

Frontier shift +
Efficiency change +

Policy tools

Grants
Tax incentives
Preferential loans
Standardisation
Testbeds

Acquire an intangible technology asset

Effects

Frontier shift −
Efficiency improvement ++

Policy tools

Tax incentives
Preferential loans
Technology transfer centres
Guidelines and information platforms

Effects

Frontier shift +
Efficiency improvement ++

Policy tools

Tax incentives
Preferential loans
Technology transfer centres
Guidelines and information platforms

Panel Estimation of the Stochastic Production Frontier for the full sample of firms

	Model 1 (stochastic frontier without inefficiency determinants)	Model 2 (stochastic frontier with inefficiency determinants)	Model 3 (stochastic frontier with inefficiency determinants before 2014)	Model 4 (stochastic frontier with inefficiency determinants after 2014)
1. Production frontier (dependent variable ln_y)
Number of observations	2,915	2,915	1,381	1,534
ln_fa_real	0.106^*** (0.007)	0.106^*** (0.007)	0.124^*** (0.011)	0.096^*** (0.009)
ln_assets	0.347^*** (0.013)	0.354^*** (0.013)	0.325^*** (0.019)	0.381^*** (0.018)
ln_l	0.561^*** (0.016)	0.557^*** (0.017)	0.507^*** (0.026)	0.591^*** (0.023)
ln_ita_real	0.019^*** (0.006)	−0.011^* (0.007)	−0.018 (0.011)	−0.023 (0.017)
t	0.016^** (0.006)	0.017^* (0.009)	0.008 (0.031)	0.082^*** (0.024)
ita_t	−0.003^*** (0.001)	−0.003^*** (0.001)	−0.004 (0.004)	−0.001 (0.003)
const	4.732^*** (0.136)	4.753^*** (0.135)	5.294^*** (0.201)	3.758^*** (0.242)
2. Inefficiency equation (dependent variable)
ln_ita_real_t		−0.108^*** (0.011)	−0.178^*** (0.021)	−0.065^*** (0.013)
t		−0.002^*** (0.016)	−0.177^*** (0.066)	0.235^*** (0.051)
const	0.072 (0.048)	0.362 (0.084)	0.806^*** (0.137)	−1.583^*** (0.403)
3. Stochastic noise (dependent variable)
const	−1.495^*** (0.058)	−1.424 (0.014)	−1.336 (0.074)	−1.447 (0.094)

Panel Estimation of the Stochastic Production Frontier for sub-samples of firms by R&D expenditures and R&D intensity

	Model 5 (stochastic frontier for the firms of high-tech sectors)	Model 6 (stochastic frontier for the firms of low-tech sectors)	Model 7 (stochastic frontier for the firms with R&D expenditures)	Model 8 (stochastic frontier for the firms without R&D expenditures)
Production frontier (dependent variable ln_y)
Number of observations	1,472	1,443	734	2,181
ln_fa_real	0.106^*** (0.017)	0.112^*** (0.007)	0.109^*** (0.013)	0.076^*** (0.007)
ln_assets	0.426^*** (0.028)	0.332^*** (0.015)	0.350^*** (0.016)	0.397^*** (0.019)
ln_l	0.599^*** (0.034)	0.552^*** (0.02)	0.531^*** (0.023)	0.522^*** (0.025)
ln_ita_real	−0.120^*** (0.026)	−0.021^*** (0.009)	−0.019^** (0.009)	0.008 (0.008)
t	0.004 (0.048)	−0.015 (0.009)	0.026^* (0.013)	0.021^** (0.009)
ita_t	0.003 (0.004)	0.001 (0.001)	−0.0001 (0.001)	−0.004^*** (0.001)
const	4.021^*** (0.377)	5.082^*** (0.149)	4.838^*** (0.190)	4.922^*** (0.17)
Inefficiency equation (dependent variable)
ln_ita_real_t	−0.262^*** (0.046)	−0.158^*** (0.018)	−0.125^*** (0.016)	−0.102^*** (0.012)
t	0.296^*** (0.057)	−0.112^*** (0.023)	−0.008 (0.023)	−0.036^*** (0.021)
const	−0.030 (0.495)	0.668^*** (0.096)	0.373^*** (0.119)	0.445^*** (0.10)
Stochastic noise (dependent variable)
const	−1.568 (0.111)	−1.315 (0.017)	−1.336 (0.065)	−2.082 (0.018)

Intangible assets and the efficiency of manufacturing firms in the age of digitalisation: the Russian case

Figures & Tables

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Estimations of time-invariant (TI) and time-variant (TVD) models by the two time periods and the groups of firms

Strategies and policy tools to support digitalisation according to the technology intensity of firms

Effects

Policy tools

Effects

Policy tools

Effects

Policy tools

Effects

Policy tools

Panel Estimation of the Stochastic Production Frontier for the full sample of firms

Panel Estimation of the Stochastic Production Frontier for sub-samples of firms by R&D expenditures and R&D intensity

Paradigm

My account