scholarly journals Determinants Of Productivity Of Ukrainian Firms

2017 ◽  
Vol 20 (1) ◽  
pp. 5-19 ◽  
Author(s):  
Andrzej Cieślik ◽  
Iryna Gaugner ◽  
Jan Jakub Michałek
Keyword(s):  
Total Factor Productivity ◽  
Firm Size ◽  
Capital Intensity ◽  
Factor Productivity ◽  
Empirical Results ◽  
Ownership Status ◽  
Level Data ◽  
Firm Internationalization ◽  
Service Sectors ◽  
Micro Level

This paper examines the determinants of total factor productivity (TFP) of Ukrainian firms in manufacturing and services, using micro-level data for the years 2005 and 2013. We first estimate regressions for the pooled dataset for the manufacturing and service sectors jointly, and then separately for each sector. Our empirical results show a positive link between the total factor productivity, intangible assets, capital intensity, firm size, competition in the industry, ownership status, and firm internationalization (exports and imports). In addition, we find that the determinants of productivity differ among the sectors and years of our sample.

scholarly journals The Regional Heterogeneity of Productivity Determinants: Evidence from Ukrainian Firms

2017 ◽  
Vol 21 (1) ◽  
pp. 44-50 ◽  
Author(s):  
Andrzej Cieślik ◽  
Jan Jakub Michałek ◽  
Iryna Nasadiuk
Keyword(s):  
Total Factor Productivity ◽  
Firm Size ◽  
Manufacturing Sector ◽  
Capital Intensity ◽  
Private Ownership ◽  
Factor Productivity ◽  
Regional Heterogeneity ◽  
Ownership Status ◽  
Micro Level ◽  
Degree Of Heterogeneity

Abstract This paper studies the determinants of the total factor productivity (TFP) for Ukrainian firms in the manufacturing sector across macro-regions using recent micro-level datasets for 2013. Our empirical results show some degree of heterogeneity across Ukrainian macro-regions; in particular, the link between the total factor productivity, firm size, imports and the level of competition seems to be valid for all macro regions. However, the effects of private ownership status, capital intensity and exports seems to be region specific. In addition, we found no relationship between firm productivity and foreign ownership for any of the regions.

CONVERGENCE AND DIVERGENCE: A NEW APPROACH, NEW DATA, AND NEW RESULTS

2020 ◽  
pp. 1-34
Author(s):  
Michele Battisti ◽  
Gianfranco di Vaio ◽  
Joseph Zeira
Keyword(s):  
Technology Adoption ◽  
Total Factor Productivity ◽  
Large Set ◽  
Factor Productivity ◽  
New Approach ◽  
Empirical Results ◽  
Growth Regressions ◽  
Convergence And Divergence ◽  
Global Frontier ◽  
Over Time

Recently, Penn World Tables include new data that enable calculation of total factor productivity in addition to output for a large set of countries. We use these new data to examine convergence and divergence across countries by applying a new approach, which differentiates between the dynamics of output and of productivity. Our empirical results lead to two main new contributions to the literature. The first is on the interpretation of “β-convergence” in “growth regressions.” It means that output per worker in each country converges to productivity but does not imply convergence across countries, since productivity tends to diverge from the global frontier. The second contribution is to the literature, which finds that income gaps across countries are due mainly to differential technology adoption. This paper shows that the gaps in technology are not only large but keep growing over time.

scholarly journals Economic Policy Uncertainty, Outward Foreign Direct Investments, and Green Total Factor Productivity: Evidence from Firm-Level Data in China

2021 ◽  
Vol 13 (4) ◽  
pp. 2339
Author(s):  
Yuegang Song ◽  
Feng Hao ◽  
Xiazhen Hao ◽  
Giray Gozgor
Keyword(s):  
Economic Policy ◽  
Total Factor Productivity ◽  
Industrial Development ◽  
Positive Impact ◽  
Western China ◽  
Factor Productivity ◽  
Firm Level ◽  
Chinese Firm ◽  
Level Data ◽  
Firm Level Data

This paper uses Chinese firm-level data to investigate the effect of China’s outward foreign direct investment (OFDI) on green total factor productivity (GTFP) under economic policy uncertainties (EPU). We found a significant positive impact of OFDI on GTFP. Moreover, an increase in EPU was shown to decrease GTFP. We also found that OFDI positively contributes to GTFP for private firms and foreign-invested firms in China. Technology-seeking OFDI contributes greater to GTFP than resource-seeking OFDI and market-seeking OFDI. These results remain robust when considering OFDI from firms in Central and East China as well as Western China. The findings are also robust with green labor productivity (GLP) substituting for GTFP using different econometric techniques. We also discuss potential implications in enhancing green innovation performance and sustainable industrial development in China.

scholarly journals Proximity and Investment: Evidence from Plant-Level Data *

2013 ◽  
Vol 128 (2) ◽  
pp. 861-915 ◽  
Author(s):  
Xavier Giroud
Keyword(s):  
Travel Time ◽  
Total Factor Productivity ◽  
Extensive Margin ◽  
Sample Period ◽  
Factor Productivity ◽  
Firm Level ◽  
Level Data ◽  
Plant Level

Abstract Proximity to plants makes it easier for headquarters to monitor and acquire information about plants. In this article, I estimate the effects of headquarters’ proximity to plants on plant-level investment and productivity. Using the introduction of new airline routes as a source of exogenous variation in proximity, I find that new airline routes that reduce the travel time between headquarters and plants lead to an increase in plant-level investment of 8% to 9% and an increase in plants’ total factor productivity of 1.3% to 1.4%. The results are robust when I control for local and firm-level shocks that could potentially drive the introduction of new airline routes, when I consider only new airline routes that are the outcome of a merger between two airlines or the opening of a new hub, and when I consider only indirect flights where either the last leg of the flight (involving the plant’s home airport) or the first leg of the flight (involving headquarters’ home airport) remains unchanged. Moreover, the results are stronger in the earlier years of the sample period and for firms whose headquarters is more time-constrained. In addition, they also hold at the extensive margin, that is, when I consider plant openings and closures.

Immigrant workforce and agriculture productivity: evidence from Italian farm-level data

2020 ◽  
Author(s):  
Edoardo Baldoni ◽  
Silvia Coderoni ◽  
Roberto Esposti
Keyword(s):  
Theoretical Model ◽  
Empirical Support ◽  
Immigrant Workers ◽  
Factor Productivity ◽  
Dynamic Panel ◽  
Farm Level ◽  
Level Data ◽  
Farm Accountancy Data Network ◽  
Micro Level ◽  
Productivity Dynamics

Abstract This paper investigates the farm-level relationship between total factor productivity (TFP) and presence and composition of immigrant workers. A theoretical model expressing how immigrant workforce influences productivity is developed and an explicit and consistent representation of the so-called ‘diversity hypothesis’ is derived. A dynamic panel specification is estimated, and the respective econometric issues are discussed. The analysis is applied to a balanced panel of Italian professional farms extracted from the Farm Accountancy Data Network over the period 2008–2015. The use of micro-level data in such assessment allows to take the wide heterogeneity across farms into account. Results suggest that, when productivity dynamics and farm heterogeneity are accounted for, empirical support to the diversity hypothesis can be found in Italian professional agriculture.

Total Factor Productivity in Manufacturing Industry for Delhi for Last Thirty Years

2014 ◽  
Vol 1 (1) ◽  
pp. 18-36
Author(s):  
Anindya Bhattacharya
Keyword(s):  
Total Factor Productivity ◽  
Manufacturing Industry ◽  
Time Series Data ◽  
Manufacturing Sector ◽  
National Level ◽  
Recent Time ◽  
Manufacturing Industries ◽  
Series Data ◽  
Factor Productivity ◽  
Level Data

This paper attempts to give an overview of the Total Factor Productivity Growth (TFPG) for the NCR or Delhi for the period from 1981-82 to 2011-12 for the manufacturing sector. Using the ASI time series data and Growth Accounting Approach the TFPG Index values are computed. The study reveals that for most of the major group or 2-digit level of manufacturing industries the respective TFPG values are declining over time. The results indicate that the lacklustre performance of the manufacturing sector equally holds in Delhi as it is already verified for the national level data of the sector through many other studies in recent time.

ON THE DETERMINANTS OF TOTAL FACTOR PRODUCTIVITY GROWTH: EVIDENCE FROM SPANISH MANUFACTURING FIRMS

2011 ◽  
Vol 17 (3) ◽  
pp. 501-530 ◽  
Author(s):  
Fabio Castiglionesi ◽  
Carmine Ornaghi
Keyword(s):  
Total Factor Productivity ◽  
Productivity Growth ◽  
Learning By Doing ◽  
Positive Contribution ◽  
Factor Productivity ◽  
Firm Level ◽  
Tfp Growth ◽  
Level Data ◽  
Main Determinants ◽  
Specific Learning

This paper explores the main determinants of productivity growth. The analysis is performed using Spanish firm-level data. We define a framework where the relative magnitudes of alternative, but not exclusive, sources of technical change are simultaneously estimated. Our main finding is that the average total factor productivity (TFP) growth is fully explained by embodied technical progress (i.e., either new capital goods or human capital). Our results contradict the existence of a positive contribution of economywide neutral technological progress in determining average TFP growth. They also leave little room for large, unpriced effects external to the firm, both at the aggregate and at the industry level. We find evidence of firm-specific learning by doing, short-lived and due to adoption of new processes.

Sign in / Sign up

Export Citation Format

Share Document