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

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ondřej Dvouletý ◽  
Ivana Blažková
Keyword(s):  
Capital Structure ◽  
Least Squares ◽  
Total Factor Productivity ◽  
Firm Size ◽  
Factor Productivity ◽  
Firm Age ◽  
Firm Level ◽  
Productivity Level ◽  
Content Type

PurposeThe objective of the study is to identify and explore factors affecting the productivity of companies in the Czech Republic with a focus on the role of firm size, firm age, indebtedness and long-term negative equity, efficiency of assets usage, liquidity, legal form, location and sector affiliation.Design/methodology/approachThe study utilizes a large unbalanced panel dataset of 91,257 firms (548,998 observations in total) covering the period 2000–2019. The dependent variable, i.e. total factor productivity (TFP), reflecting the overall firm productivity, was estimated by ordinary least squares (OLS) regression. The main findings were obtained through the estimation of two econometric models explaining the effects of factors on firm-level TFP. First, the OLS regressions together with Nomenclature of Territorial Units for Statistics (NUTS) 3 regions, year dummies and robust standard errors were estimated. Second, as a robustness check, the very same model was estimated with the random effects (RE) generalized least squares (GLS) method.FindingsThe analysis has shown a statistically significant U-shaped relationship (with the turning point of 38, resp. 36 years) between firm age and the overall TFP among the Czech enterprises. The authors provide two key findings in terms of a firm size-productivity relationship. Firms with fewer employees, often officially registered as self-employed individuals/freelancers, report higher levels of productivity. Nevertheless, when it comes to firm property (assets), the authors find a positive relationship between firm size and TFP. A high proportion of debts in the capital structure of analysed companies, or even negative equity, has been negatively associated with TFP levels.Research limitations/implicationsMore research is needed in the deeper exploration of sectoral and regional determinants of firm TFP, as both regional and sectoral heterogeneity were observed in the study. The authors propose the employment of a multi-level modelling approach, including a range of continuous variables and investigation of their role in shaping firm-level productivity.Practical implicationsConcerning the results, managers should be mindful of optimal capital structure principles due to the negative impact of a high level of debts on the productivity level. High indebtedness means high-interest payments drawing earnings off, which may be, especially in the long term, a hindrance to investments. The entrepreneurship and small- and medium-sized enterprise policies may be targeted at the soft policy actions, including advisory services and counselling on business development or risk and on the provision of financial capital allowing firms to strive for growth-oriented projects.Originality/valueTo the best of the authors' knowledge, this is the first attempt to provide insight into the firm-level productivity determinants, based on the large dataset covering enterprises across the whole economy over the long term, representing the structure of the country's entrepreneurial activity.

What drives total factor productivity and its growth in post-communist countries? The case of the Czech food industry

2020 ◽  
Vol 10 (3) ◽  
pp. 285-305
Author(s):  
Ivana Blažková ◽  
Ondřej Dvouletý ◽  
Ondřej Machek
Keyword(s):  
Total Factor Productivity ◽  
Food Industry ◽  
Generalized Method Of Moments ◽  
Sustainable Growth ◽  
Factor Productivity ◽  
Firm Age ◽  
Firm Level ◽  
Data Set ◽  
Content Type ◽  
The Impact

PurposeThe paper aims to investigate factors that drive the total factor productivity (TFP) and its growth in the Czech food industry over 2003–2017. The authors’ analysis focuses on firm-level characteristics such as location choice, sub-sector affiliation, use of debt, liquidity, asset turnover, firm size and firm age.Design/methodology/approachThe determinants of productivity were tested econometrically by estimation of multivariate regression models. The firm-level panel data set consisted of 14,488 observations (data of 980 firms spanning 15 years). TFP was estimated by three regression-based techniques – ordinary least squares (OLS) regression, instrumental variables (IV) approach and two-way generalized method of moments (GMM) regression. All three measures of TFP were used as outcome variables to estimate the impact of firm-level determinants on both TFP level and growth.FindingsThe results have shown statistically significant and reversed U-shaped relationship between the firm age and the TFP level (with a turning point in the age of 12.5 years). However, the dynamic models investigating the TFP growth have found that younger firms achieve higher productivity growth in comparison with older ones. Higher market share and assets turnover were positively associated with both TFP level and its growth.Research limitations/implicationsThis study brings several relevant propositions for future research. First, the authors recommend future researchers to study not only differences in the levels of productivity but also determinants of its growth. Second, the authors believe that adding a non-linear component to age as a factor explaining changes in the levels of productivity might be a very relevant contribution to the literature.Originality/valueAlthough it is generally accepted that successful and sustainable growth of firms, regions and economies can be achieved particularly through viable companies with high productivity, there is still a limited number of firm-level studies explaining the determinants of productivity levels and growth in agribusiness sectors in transition economies. Therefore, this study is expected to contribute to a better understanding of this important topic.

Factors affecting financial leveraging for BSE listed real estate development companies in India

2018 ◽  
Vol 23 (3) ◽  
pp. 274-294
Author(s):  
Rakesh Kumar Sharma
Keyword(s):  
Real Estate ◽  
Capital Structure ◽  
Short Term ◽  
Firm Level ◽  
Content Type ◽  
Factors Affecting ◽  
Tax Shield ◽  
Total Debt ◽  
Real Estate Sector

PurposeThe real estate sector in India has assumed growing importance with the liberalisation of the economy. Developments in the real estate sector are being influenced by the developments in the retail, hospitality and entertainment (e.g. hotels, resorts and cinema theatres) segment, economic services (e.g. hospitals, schools) and information technology-enabled services (such as call centres), and vice versa. This paper aims to study the determinants of capital structure by taking into account 125 major Bombay Stock Exchange (BSE) listed real estate companies selected on the basis of their market capitalisation.Design/methodology/approachTo discover what determines capital structure, nine firm level explanatory variables (profitability-EBIT margin, return on assets, earnings volatility, non-debt tax shield, tangibility, size, growth, age debt service ratio and tax shield) were selected and regressed against the appropriate capital structure measures, namely, total debt to total assets, long-term debts to total assets, short-term debts to total assets, total liabilities to total liabilities plus equity, total debt to capital used and total debt to total liabilities plus equity. A sample of 125 real estate companies was taken and secondary data were collected. Consequently, multivariate regression analysis was made based on financial statement data of the selected companies over the study period of 2009-2015.FindingsThe major findings of the study indicated that profitability, size, age, debt service capacity growth and tax shield variables are the significant firm-level determinants.Research limitations/implicationsThe present study is carried out by taking data of only 25 companies listed on the BSE and time period covered from 2009 from 2015. Time period and sample size may be limitations of the current study.Practical implicationsThe present study is an empirical analysis of the determinants of leverage of real estate sector in India with most recent available data. Different regression equations have been formed to develop the models using firm-specific determinants and different measures of leverage or capital structure. Data were regressed using SPSS application software, and the resulting (or obtained) regression outputs are analysed. This study will help the Indian real estate companies to the know the impact of different variables while raising short-term and long-term loans.Social implicationsThe current study will benefit all stakeholders of society who are fascinated to be acquainted with the financing of real estate companies and the factors affecting long-term and short-term financing of this sector. Specifically, public engrossed in different modes of investment and financial institution will be the prime gainers.Originality/valueThe present study has been completed using authentic data from the annual reports and database. This study uses explanatory variables and different measures of leverage which were limited in use in previous studies. Moreover, this research is a comprehensive study that deals with developing different regression models by using diverse measures of leverage.

scholarly journals Understanding the components of profitability and productivity change at the micro level

2019 ◽  
Vol 69 (5) ◽  
pp. 1061-1079 ◽  
Author(s):  
Bernd Andreas Wiech ◽  
Athanassios Kourouklis ◽  
James Johnston
Keyword(s):  
Total Factor Productivity ◽  
Scale Effects ◽  
Future Research ◽  
Productivity Change ◽  
Factor Productivity ◽  
Productivity Measurement ◽  
Firm Level ◽  
Content Type ◽  
Using Data ◽  
Productivity Indicators

Purpose The purpose of this paper is to present a refined framework providing clarity in terms of the components of profitability and productivity change from the perspective of the firm level. Design/methodology/approach The literature is analysed with a scoping study and a systematic literature review. Productivity measurement approaches are compared using data at the product level. Findings The definition of total factor productivity (TFP) in the literature negatively affects the accuracy of profitability and productivity measurement. In the usual case of a dynamic output mix, TFP change encompasses biasing output mix effects relating to profitability, but not to productivity change. Therefore, this paper defines changes of a ratio of output quantities to input quantities not as TFP change, but as quantitative profitability (QP) change. A framework is proposed decomposing profitability change into price recovery and QP change, whereas the latter comprises of valid productivity change (encompassing technological, technical efficiency and productivity-related scale effects) and output mix change (encompassing proportion, quality, output switching and profitability-related scale effects). Research limitations/implications Future research should include literature from the industrial organisation field of economics. The presented framework should be transferred to the standard production function framework used in economics. Practical implications The paper can help preventing faulty decision making or distrust due to the use of biased profitability or productivity indicators. TFP-based productivity indicators are unsuitable for most firms. To measure productivity meaningfully, firms should use adequate approaches (e.g. standard input- or adjusted total factor productivity-based ones). Originality/value The paper contributes to a more accurate performance measurement approach, as researchers and practitioners better understand the components of profitability and productivity change.

Impact of Determinants of Industrial Development on Employment and Wages in Indian Manufacturing

2020 ◽  
pp. 18-30
Keyword(s):  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Technical Change ◽  
Positive Impact ◽  
Manufacturing Sector ◽  
Factor Productivity ◽  
Firm Level ◽  
Employment Level ◽  
The Impact ◽  
Level Performance

ABSTRACT The present study was undertaken to explore the evolution of the impact of firm-level performance on employment level and wages in the Indian organized manufacturing sector over the period 1989-90 to 2013-14. One of the major components of the economic reform package was the deregulation and de-licensing in the Indian organized manufacturing sector. The impact of firm-level performance on employment and wages were estimated for Indian organized manufacturing sector in major sub-sectors in India during the period from 1989-90 to 2013-14 of the various variables namely profitability ratio, total factor productivity change, technical change, technical efficiency, openness (export-import), investment intensity, raw material intensity and FECI in total factor productivity index, technical efficiency, and technical change. The study exhibited that all explanatory variables except profitability ratio and technical change cost had a positive impact on the employment level. Out of eight variables, four variables such as net of foreign equity capital, investment intensity, TFPCH, and technical efficiency change showed a positive impact on wages and salary ratio and rest of the four variables such as openness intensity, technology acquisition index, profitability ratio, and technical change had negative impact on wages and salary ratio. In this context, the profit ratio should be distributed as per the marginal rule of economics such as the marginal productivity of labour and capital.

Two sides, but not of the same coin: digitalization, productivity and unemployment

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Oxana Krutova ◽  
Pertti Koistinen ◽  
Tuuli Turja ◽  
Harri Melin ◽  
Tuomo Särkikoski
Keyword(s):  
Total Factor Productivity ◽  
Job Loss ◽  
Labour Productivity ◽  
Research Problem ◽  
Quality Of Work Life ◽  
Macro Level ◽  
Factor Productivity ◽  
Content Type ◽  
Technological Unemployment ◽  
Factors Of Production

PurposeThis paper aims to examine how input from the digital restructuring of the workplace and productivity affects the risk of job loss and unemployment.Design/methodology/approachRelying on the concepts of technological unemployment and the productivity paradox as well as the theory of skills-biased technological change, the analysis incorporated micro-level individual determinants of job loss, macro-level economic determinants of input and the contribution from traditional (machinery and equipment) vs innovative (ICT) factors of production. The model has been also controlled for “traditional” indicators of “outsiderness” in the labour market. The Quality of Work Life Survey, which is a broad-based national interview survey produced by Statistics Finland, for 2018, the latest year available (N = 4,110) has been used in the analysis. Binomial logistic regression has been applied in order to estimate the effects of individual- and macro-level factors on the risk of job loss.FindingsThe results support arguments for the divergence between effects from labour- vs total-factor productivity on the risks of job loss, as well as the divergence between effects for temporary (layoff) vs permanent job loss (dismissal or unemployment). While the contribution from “traditional” factors of production to labour productivity potentially decreases the risk of permanent job loss, input from “innovative” factors of production on total-factor productivity potentially causes adverse effects (e.g. growing risks of permanent job loss).Originality/valueThe paper contributes to the theoretical discussion about technological unemployment and productivity by means of including two different concepts into a single econometric model, thus enabling examination of the research problem in an innovative way.

Does foreign direct investment spillover total factor productivity growth? A study of Indian drugs and pharmaceutical industry

2017 ◽  
Vol 24 (7) ◽  
pp. 1937-1955 ◽  
Author(s):  
Nitin Arora ◽  
Preeti Lohani
Keyword(s):  
Foreign Direct Investment ◽  
Pharmaceutical Industry ◽  
Total Factor Productivity ◽  
Direct Investment ◽  
Spillover Effect ◽  
Foreign Firms ◽  
Factor Productivity ◽  
Content Type ◽  
Domestic Firms ◽  
Tfp Growth

Purpose Foreign firms have certain advantages which may spillover to domestic firms in the form of improvements in total factor productivity (TFP) growth. The purpose of this paper is to empirically observe the presence of TFP spillovers of foreign direct investment (FDI) to domestic firms through analyzing source of TFP growth in Indian drugs and pharmaceutical industry. Design/methodology/approach This paper examines the sources of TFP spillovers of FDI in Indian drugs and pharmaceutical industry over the period 1999 to 2014. The data of 304 firms has been used for estimation of the growth rates of TFP and its sources under stochastic frontier analyses based Malmquist productivity index framework. For frontier estimation, the Wang and Ho (2010) model has been executed using translog form of production function. Findings The results show that there exists significant TFP spillover effect from the presence of foreign equity in drugs and pharmaceutical industry of India. The results also show that the major source of TFP fluctuations in the said industry is managerial efficiency that has been significantly affected by FDI spillover variables. In sum, the phenomenon of significant Intra-industry (horizontal) efficiency led productivity spillovers of FDI found valid in case of Indian drugs and pharmaceutical industry. Research limitations/implications The number of foreign firms is very less to imitate the significant impact of foreign investment on TFP growth of Indian pharmaceutical industry at aggregated level; and the Wang and Ho (2010) model is failing to capture direct impact of FDI on technological change under Malmquist framework. Practical implications Since, there exists dominance of domestic firms in Indian drugs and pharmaceutical industry, the planners should follow the policy which not only attract FDI but also benefit domestic firms; for example, developing modern infrastructure and institution which will further help domestic firms to absorb spillovers provided by the Multinational Corporations and also accelerate the growth and development of the economy. Social implications In no case, the foreign firms should dominate the market share otherwise the efficiency spillover effect will be negative and the domestic firms will be destroyed under the self-centric approach of foreign firms protected by the recent patent laws. Originality/value The study is a unique attempt to discuss the production structure and sources of TFP spillovers of FDI in Indian drugs and pharmaceutical industry with such a wide coverage of 304 firms over a period of 16 years under Wang and Ho (2010) model’s framework. The existing studies on TFP spillovers are using either a small sample size of firms or based upon traditional techniques of measuring spillover effects.

Silk Road Economic Belt strategy and industrial total-factor productivity

2019 ◽  
Vol 30 (1) ◽  
pp. 260-282 ◽  
Author(s):  
Jian Feng ◽  
Lingdi Zhao ◽  
Huanyu Jia ◽  
Shuangyu Shao
Keyword(s):  
Sustainable Development ◽  
Total Factor Productivity ◽  
Causal Effect ◽  
Silk Road ◽  
Factor Productivity ◽  
Positive Role ◽  
Content Type ◽  
Silk Road Economic Belt ◽  
The Difference

Purpose The purpose of this paper is to assess the effectiveness of the Silk Road Economic Belt (SREB) strategy and its role of industrial productivity in China. Design/methodology/approach To identify the causal effect of this strategy on industrial sustainable development, the authors first use the slacks-based measure model to calculate industries’ total-factor productivity (TFP) considered with CO2 emissions as undesirable output on the provincial level. Then, the authors use the PSM-DID method to identify the difference of TFPs between provinces and industries before and after the implementation of SREB strategy. Findings However, the authors find that there is no difference or even a relative decrease in TFPs of industries in target provinces after the implementation of the strategy, which reveals that the SREB strategy does not play a positive role of the industries’ sustainable development in years of 2014 and 2015. Originality/value The value of this result is to identify the short-term impact of SREB strategy and to seek for probable causes and appropriate solutions.

scholarly journals Impact of COVID-19 on the trade of goods and services in Spain

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Asier Minondo
Keyword(s):  
Negative Impact ◽  
The European Union ◽  
Firm Level ◽  
Health Crisis ◽  
Content Type ◽  
Goods And Services ◽  
Containment Measures ◽  
Trade Of Services ◽  
The Impact

Purpose This paper aims to analyze the impact of COVID-19 on the trade of goods and services in Spain. Design/methodology/approach This paper uses monthly trade data at the product, region and firm level. Findings The COVID-19 crisis has led to the sharpest collapse in the Spanish trade of goods and services in recent decades. The containment measures adopted to arrest the spread of the virus have caused an especially intense fall of trade in services. The large share of transport equipment, capital goods, products that are consumed outdoors (i.e., outdoor goods) and tourism in Spanish exports has made the COVID-19 trade crisis more intense in Spain than in the rest of the European Union. Practical implications The nature of the collapse suggests that trade in goods can recover swiftly when the health crisis ends. However, COVID-19 may have a long-term negative impact on the trade of services that rely on the movement of people. Originality/value It contributes to understand how COVID-19 has affected the trade in goods and services in Spain.

The impact of gender inequality in education and employment on economic performance in Turkey: evidence from a cointegration approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ömer Esen ◽  
Gamze Yıldız Seren
Keyword(s):  
Least Squares ◽  
Economic Performance ◽  
Ordinary Least Squares ◽  
Estimation Methods ◽  
Content Type ◽  
Cointegration Tests ◽  
Johansen Cointegration ◽  
Education And Employment ◽  
The Impact

PurposeThis study aims to empirically examine the impact of gender-based inequalities in both education and employment on economic performance using the dataset of Turkey for the period 1975–2018.Design/methodology/approachThis study employs Johansen cointegration tests to analyze the existence of a long-term relation among variables. Furthermore, dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS) estimation methods are performed to determine the long-run coefficients.FindingsThe findings from the Johansen cointegration analysis confirm that there is a long-term cointegration relation between variables. Moreover, DOLS and FMOLS results reveal that improvements in gender equality in both education and employment have a strong and significant impact on real gross domestic product (GDP) per capita in the long term.Originality/valueThe authors expect that this study will make remarkable contributions to the future academic studies and policy implementation, as it examines the relation among the variables by including the school life expectancy from primary to tertiary based on the gender parity index (GPI), the gross enrollment ratio from primary to tertiary based on GPI and the ratio of female to male labor force participation (FMLFP) rate.

Evaluation of Firm Performances in Emerging Markets

2020 ◽  
pp. 329-354
Author(s):  
Seda Ekmen Özçelik
Keyword(s):  
Emerging Markets ◽  
Total Factor Productivity ◽  
Labor Productivity ◽  
Value Added ◽  
Factor Productivity ◽  
Firm Level ◽  
Average Value ◽  
The World Bank ◽  
The World ◽  
Enterprise Surveys

This chapter provides basic understanding of firm performance in emerging markets by focusing on labor productivity and total factor productivity. In the study, labor productivity is measured in terms of average value added per worker. Total factor productivity is obtained from estimations of Cobb-Douglas production function where value added is a function of labor and capital. Data is obtained from the firm-level Enterprise Surveys by the World Bank. According to the results, differences in average labor productivities are significant among the sectors within each emerging region. Also, the value of factor elasticities changes across sectors as well as across regions. Moreover, the elasticity of capital is lower than the elasticity of labor for all sectors in regions. It implies that labor plays a more significant role and the firms are operating in a more labor-intensive production process in emerging markets.

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