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.

Total factor productivity measurement with carbon reduction

2017 ◽  
Vol 24 (4) ◽  
pp. 575-592 ◽  
Author(s):  
Xiancun Hu ◽  
Chunlu Liu
Keyword(s):  
Total Factor Productivity ◽  
Construction Projects ◽  
Driving Forces ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Productivity Analysis ◽  
Factor Productivity ◽  
Productivity Measurement ◽  
Content Type ◽  
Carbon Reduction

Purpose The purpose of this paper is to present an approach for productivity measurement that considers both construction growth and carbon reduction. Design/methodology/approach The approach applied is a sequential Malmquist-Luenberger productivity analysis based on a directional distance function and sequential benchmark technology using the data envelopment analysis (DEA) technique. The sequential Malmquist-Luenberger productivity change index is decomposed into pure technical efficiency, scale efficiency, and technological change indices, in order to investigate the driving forces for productivity change. Findings The construction industries of the Australian states and territories were selected implement the new approach. The results indicate that construction growth and carbon reduction can be achieved simultaneously through the learning of techniques from benchmarks. Practical implications Current research on total factor productivity (TFP) in construction generally neglects carbon emissions. This does not accurately depict the nature of construction and therefore yields biased estimation results. TFP measurement should consider carbon reduction, which is beneficial for policymakers to promote sustainable productivity development in the construction industry. Originality/value The approach developed here is generic and enhances productivity and DEA research levels in construction. This research can be used to formulate policies for evaluating performance in worldwide construction projects, organizations and industries by considering undesirable outputs and desirable outputs simultaneously, and for promoting sustainable development in construction by identifying competitiveness factors.

Measuring total factor productivity change of microfinance institutions in India using Malmquist productivity index

2018 ◽  
Vol 12 (1) ◽  
pp. 105-130 ◽  
Author(s):  
Dilip Ambarkhane ◽  
Ardhendu Shekhar Singh ◽  
Bhama Venkataramani
Keyword(s):  
Total Factor Productivity ◽  
Financial Institutions ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Microfinance Institutions ◽  
Factor Productivity ◽  
Content Type ◽  
The Poor

PurposeMicrofinance institutions (MFIs) provide small loans and other financial services to the poor. These institutions are established for helping the poor to raise income levels and to reduce poverty. Recently, MFIs are required to reduce their dependence on grants and subsidies. Consequently, they face conflicting objectives of improving reach and profitability. These can be achieved by improving productivity. This paper aims to investigate productivity change in 21 major MFIs in India which are rated by Credit Rating and Information Services of India Limited in 2014.Design/methodology/approachThis paper attempts to examine total factor productivity change in 21 major Indian MFIs during the period from 2014 to 2016 using Malmquist productivity index. The inputs and outputs are selected considering objectives of outreach and financial sustainability. The authors have categorized MFIs in three categories, namely, large, medium and small, depending on asset size.FindingsIt is revealed that large MFIs are able to catch up with industry best practices by improving their systems and processes, but they need to improve scale efficiency. The Reserve Bank of India has recently initiated a policy of granting banking licenses to those financial institutions which have good outreach and are financially strong. It can be used for shortlisting MFIs before granting permission to operate as banks. The method can also be used for benchmarking them for productivity. It can also be replicated in other countries.Originality/valueIn India, MFIs are playing important role in economic development by providing microcredit to the poor. However, very few studies have been undertaken regarding productivity of MFIs in India. The present study intends to fill this gap. It will facilitate benchmarking of MFIs as competitive and sustainable financial institutions catering to the requirements of small borrowers.

Measurement of financial efficiency and productivity of Turkish Public Universities by using non-parametric methods

2019 ◽  
Vol 11 (4) ◽  
pp. 876-896
Author(s):  
Aslı Günay ◽  
Murat Ali Dulupçu
Keyword(s):  
Total Factor Productivity ◽  
Public Universities ◽  
Productivity Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Financial Efficiency ◽  
Data Set ◽  
Content Type ◽  
Efficiency And Productivity

Purpose The purpose of this paper is to measure the financial efficiency and productivity of 23 public universities founded in 1992 in Turkey over the period between 2004 and 2013. The results obtained will provide managerial information and act as a guide to public universities’ administrations, in using their resources more effectively. Design/methodology/approach Data envelopment analysis is applied to assess the relative financial efficiency of these universities, while Malmquist total factor productivity index is used to measure the total factor productivity change concerning financial inputs of the universities. Findings The number of financially efficient universities and the number of universities showing an increase in their productivity according to their financial inputs change annually and both of them display a rough trend over the years. A decrease of about 5 percent in the financial productivity of the universities is observed which stems from a technological recession. Therefore, public universities in Turkey are not able to develop effective policies to diversify, increase and use their financial resources. Originality/value When the lack of studies within the literature measuring the financial efficiency of higher education institutions is taken into account, this study can fill a gap in this area. The analyses conducted here distinguish from existing studies on this subject with regards to the extent and diversity of financial data set and the measurement of both efficiency and productivity change of universities considering financial inputs concurrently.

scholarly journals Measuring total factor productivity in agriculture: a bibliometric review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Łukasz Kryszak ◽  
Katarzyna Świerczyńska ◽  
Jakub Staniszewski
Keyword(s):  
Total Factor Productivity ◽  
Secondary Data ◽  
Future Research ◽  
Policy Reforms ◽  
Factor Productivity ◽  
Content Type ◽  
Main Research ◽  
Agriculture Economics ◽  
Future Research Agenda ◽  
Bibliometric Review

PurposeTotal factor productivity (TFP) has become a prominent concept in agriculture economics and policy over the last three decades. The main aim of this paper is to obtain a detailed picture of the field via bibliometric analysis to identify research streams and future research agenda.Design/methodology/approachThe data sample consists of 472 papers in several bibliometric exercises. Citation and collaboration structure analyses are employed to identify most important authors and journals and track the interconnections between main authors and institutions. Next, content analysis based on bibliographic coupling is conducted to identify main research streams in TFP.FindingsThree research streams in agricultural TFP research were distinguished: TFP growth in developing countries in the context of policy reforms (1), TFP in the context of new challenges in agriculture (2) and finally, non-parametric TFP decomposition based on secondary data (3).Originality/valueThis research indicates agenda of future TFP research, in particular broadening the concept of TFP to the problems of policy, environment and technology in emerging countries. It provides description of the current state of the art in the agricultural TFP literature and can serve as a “guide” to the field.

Empirical Productivity Indices and Indicators

2018 ◽  
pp. 76-120 ◽  
Author(s):  
Bert M. Balk
Keyword(s):  
Total Factor Productivity ◽  
Output Growth ◽  
Productivity Change ◽  
Main Task ◽  
Factor Productivity ◽  
Productivity Measurement ◽  
Ex Post ◽  
Key Concepts ◽  
Productivity Indices ◽  
Total Price

The empirical measurement of productivity change (or difference) by means of indices and indicators starts with the ex post profit/loss accounts of a production unit. The key concepts are profit, leading to indicators, and profitability, leading to indices. The main task for the productivity analyst is to decompose profit or profitability change into price and quantity components, leading to measures of total factor productivity change and total price recovery. This chapter discusses various input–output models and their linkages; the relation between productivity measurement and growth accounting; the relation between total and partial productivity measures; and aggregation issues. The approach advocated here is able to deliver the same results as the neoclassical approach; for example, it appears that for a table in which output growth is decomposed into the contributions of total factor productivity change and input growth, the neoclassical assumptions are neither necessary nor do they contribute anything to our understanding of what productivity precisely is.

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.

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.

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.

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