Measurement and determinants of total factor productivity: evidence from Indian banking industry

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Biswabhusan Bhuyan ◽  
Subhamitra Patra ◽  
Ranjan Kumar Bhuian

PurposeThe purpose of this study is to measure the level of total factor productivity of the Indian banking sector and to identify both the bank-specific and macroeconomic determinants of the total factor productivity after the global subprime mortgage crisis.Design/methodology/approachThe research sample consists of 61 commercial banks including 21 public sector banks, 18 private sector banks and 22 foreign banks. The annual data is collected from the website of Reserve Bank of India from 2008 to 2019. The authors employed the non-parametric DEA approach to estimate Malmquist total factor productivity index for each bank as well as across different ownership groups. The panel data estimation technique was used to identify the determinants of total factor productivity.FindingsThe results suggested that an increase in the technological shift raised the bank's productivity above the optimal frontier. Among the bank-specific determinants, the bank size and bank diversifications are significantly declining productivity, whereas credit-deposit ratio and return on asset significantly increasing productivity. Among the macro-specific determinants, inflation, growth rate and fiscal deficit ratio negatively affect productivity, whereas capital formation to the GVA ratio boosts the level of productivity.Research limitations/implicationsThe authors have used intermediate method to select the inputs and outputs as per the suitability to the context. However, the disaggregate level such as state and district level analysis can be done using production and value-added approaches to explore the regional variations of the banking performance. Furthermore, the parametric methods such as stochastic frontier analysis can be used to examine banking performance, which the authors left for the future research.Practical implicationsThis study suggested that banks should increase the economies of scale of their total assets and focus on the interest-earning activity. The banks need to proactively operate the business policy by following the changing path of inflation. The banks need to reduce their rate of fiscal-deficit to the GVA with the purpose to boost their level of productivity.Originality/valueThe study provides an important implication for bankers and policymakers in terms of heightening the banking performance during the period of dynamic economic events.

Author(s):  
Jorge Benzaquen

Purpose The purpose of this paper is to propose and analyze a model to obtain a total factor productivity of an industry through quantitative empirical analysis in order to determine the joint contribution of the production and technology function, and the change and technical progress. The case of the Peruvian large shipbuilding industry between the years 1969 and 1990 was considered for the analysis of the proposed model. The large shipbuilding in Peru finished in 1992 and has restarted in 2014. The importance of the study lies in the fact that the analysis is focused on an industry which is resurfacing, and in this regards, the study of the first production period will yield more and accurate information to make decisions regarding its future development. Design/methodology/approach One way of considering the several effects of technical progress, in line with Sato (1970) such as growth and bias, is to specify a production function maintaining the linear homogeneity property, such as: Y(t)=F [A(t)K(t), B(t)L(t)], where Y(t) is the aggregate product over a period of time (t); K(t) is the capital; L(t) is the labor; and A(t) and B(t) are the efficiencies or augmentations of K(t) and L(t), respectively. Based on the regression analysis data, the value of σ can be estimated to a residual growth rate (Kennedy and Thirlwall, 1972) that allows assessing the technical knowledge that is not attributable to the factors’ efficiency grains: TCTR = T ˙ / T − ( α ( A ˙ / A ) + β ( B ˙ / B ) ) . This last expression measures the residual technological growth rate (TCTR, by its Spanish acronym). Findings The results of the analysis of the large shipbuilding at SIMA-Callao during the given period (22 years of operation, between 1969 and 1990) show that the necessary installed capacity and the technological knowledge was available in order to develop a complex industrial process in the South Pacific region, thus, contributing to the sector’s growth in the country. The evolution of the shipbuilding activities coincides with the GDP expansion and decline periods in Peru. According to the results, the total factor productivity increased during 1969-1976, 1979-1982, and 1986-1987 periods and it has been confirmed that the contribution of the efficiencies of the production factors were inversely related to the economies of scale and output growth. Practical implications The analysis is based on the activities carried out throughout 22 years of operations in SIMA-Callao shipyards (1969-1990). The data regarding the product, labor, imported materials costs, local material costs, direct expenses, wages, and man-day costs was obtained from several sources within the shipyard. Direct expenses correspond to classification, inspections, administrative expenses (dock, quality control, equipment rental, etc.), drawings, technical data, insurance, and materials freight. Additionally, the sources of information are project construction contracts, annual expenses reports, and man-day cost quarterly reports of the shipbuilding area. The man-day cost includes salary, social benefits, and the company’s functional cost. Originality/value There are different ways to obtain productivity index. In this case, the authors used the stated model. In addition, based on this experience, this can be applied to other industries.


2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Bilge MEYDAN ◽  
Aydin ULUCAN ◽  
Kazim Baris ATICI

This research aims to measure the change of provincial development levels of Turkey’s 81 provinces through banking sector data. The applied methodology is the Malmquist Total Factor Productivity Index (MTFPI). We perform the analysis based on two models. The main difference between models relies on handling the factor associated with ‘loans’. The first approach sees the loans as an output factor, which is based on the idea that loans indicate investment and therefore development. In the second model, we take the loans as an input factor, which represents the idea that loans indicate debt and therefore they should be minimized. We evaluate the findings with respect to geographical classification and the province development index.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ashiq Mohd Ilyas ◽  
S. Rajasekaran

PurposeThis paper aims to measure the change and the sources of change in total factor productivity (TFP) of the Indian non-life insurance sector over the period 2005–2016.Design/methodology/approachThis study employs the bootstrapped Malmquist index (MI) to assess the changes in the TFP and adopts a decomposition approach proposed by Balk and Zofío (2018). Moreover, it utilises truncated regression to identify the determinants of the TFP. In addition, it employs Wilcoxon-W test and t-test to scrutinise the difference between the state-owned and the private insurers in terms of variations in TFP and its various components.FindingsThe results divulge a miniature improvement in TFP of the insurance sector, which is primarily attributable to the improvement in scale efficiency (economies of scale). The results also reveal that there are no significant TFP differences across the ownership. However, private insurers have better scale efficiency and lower input-mix efficiency than state-owned insurers. In addition, the results unveil that size, diversification and reinsurance have a negative impact on the TFP, while age has a positive impact on it.Practical implicationsThe results may help the policymakers to frame new consolidation policies. Moreover, the findings may guide the decision-makers of the Indian non-life insurance companies to abate inefficiency and improve TFP.Originality/valueThis study estimates bias-corrected changes in TFP and efficiency in the non-life insurance sector. Moreover, it adopts an elaborated decomposition of the MI to identify the true sources of change in the TFP.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Panayiotis Tzeremes

PurposeThis research analyzes, for the first time, the linkage among the gathered dataset of globalization indicators, the total factor productivity index and tourism development in a panel of 25 European countries during the 1995–2016 period.Design/methodology/approachThe Generalized Method of Moments estimator for panel Vector Autoregressive Regression model is implemented and as a robustness test, the panel Granger causality test is used.FindingsThe findings have divulged that globalization and total factor productivity increase tourism development. An increase in the economic globalization de factor indicator will cause an increase in tourism development in European countries. Moreover, an increase in the social globalization de jure indicator will lead to a higher level of tourism development in European countries.Practical implicationsPolicy-makers should use the complementary association between globalization and international tourism to promote productivity in European countries. These countries can also utilize the tourism sector as a tool to enhance the connectivity of their economies and societies with other parts of the world.Originality/valueWe use for the first time the globalization index as proposed by Gygli et al. (2019) in the tourism discipline. We evaluate the total factor productivity index instead of the economic growth applied by the majority of the researchers and we employ for the first time in the tourism field the GMM–PVAR framework.


Kybernetes ◽  
2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ruihan Zhang ◽  
Bing Sun ◽  
Mingyao Liu ◽  
Jian Hou

Purpose This paper aims to analyze the spatiotemporal heterogeneity of regional total factor productivity (TFP) growth and explores how haze pollution and different levels of new-type urbanization affect China’s economic growth. Design/methodology/approach This paper constructs an index for evaluating the TFP growth of China’s 31 provinces by integrating slack-based measures and the Global Malmquist (GM) productivity index. Meanwhile, the panel threshold estimation method is used to examine the complex relationships among haze pollution, new-type urbanization and TFP growth. Findings The results reflect conspicuous spatiotemporal heterogeneity in TFP growth in China. Interestingly, the influence of haze pollution on TFP growth is limited by the “critical mass” of new-type urbanization in China. When new-type urbanization does not cross the first threshold, haze pollution has a negative but non-significant effect on TFP growth. When new-type urbanization crosses the first threshold but not the second, haze pollution has a significant positive impact on TFP growth. When new-type urbanization crosses the second threshold, haze pollution significantly and positively affects TFP growth with the strongest positive effect. Originality/value This study innovates by combining haze pollution and TFP growth and proposing an integrated framework from the perspective of new-type urbanization, providing insight into how different degrees of new-type urbanization impact the mechanism between haze pollution and TFP growth. Using panel data in China and emphasizing green development, a sustainable economy and new-type urbanization, this study contributes to the current studies on haze pollution and economic development based on developed countries.


2009 ◽  
Vol 1 (1) ◽  
pp. 39-56 ◽  
Author(s):  
S.N. Rajesh Raj ◽  
Mihir K. Mahapatra

PurposeThe purpose of this paper is to examine the performance of small manufacturing enterprises (SMEs) in India during the pre‐reforms (prior to 1991) and reforms period (1991 onwards) with focus on 15 major states from different levels of development.Design/methodology/approachIn order to capture variation across different categories of states, 15 major states in India have been classified into high‐, middle‐ and low‐income states. Further, to capture productivity growth in the sector during the pre‐reforms and reforms period, both partial factor productivity and total factor productivity method (growth accounting approach) have been adopted. The analysis is based on different rounds of nationwide survey conducted by the National Sample Survey Organization (NSSO) of the Government of India during 1978‐2001.FindingsThe findings of the study reveal erosion in growth of output in the SMEs during the reforms period as compared to the pre‐reforms period with variation across different categories of states. The decline in growth of output during the reforms period can be primarily on account of fall in growth of employment and investment. The total factor productivity growth has also declined during the reforms period suggesting the need to enhance the level of technical efficiency and skills of the labour force in the sector. This is noticed in spite of major role played by the SMEs in providing employment (80 per cent of the total manufacturing sector employment) opportunities and in generating output (contributes 60 per cent of net domestic product) in the country.Research limitations/implicationsOn account of non‐availability of annual data, the study relied on data collected by the NSSO of the Government of India periodically. In addition, the study did not examine the factors that explain decline in productivity growth in the sector.Originality/valueThere is a large body of literature on regional growth and productivity in the Indian manufacturing sector but most of the studies have considered only the organized manufacturing sector. This study contributes to the literature by analyzing the inter‐state variation in growth and productivity performance of SMEs in the pre‐reforms and reforms periods.


2018 ◽  
Vol 12 (1) ◽  
pp. 105-130 ◽  
Author(s):  
Dilip Ambarkhane ◽  
Ardhendu Shekhar Singh ◽  
Bhama Venkataramani

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.


2019 ◽  
Vol 11 (4) ◽  
pp. 876-896
Author(s):  
Aslı Günay ◽  
Murat Ali Dulupçu

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.


2013 ◽  
Vol 60 (2) ◽  
pp. 139-159 ◽  
Author(s):  
Benli Keskin ◽  
Suleyman Degirmen

The objective of this study is to measure the total factor productivity and the changes in components of the total factor productivity generated by the banks in Turkish Banking Sector (TBS) during the period of 2004-2009. Based on these measurements, we quantify the production efficiency of the banks. To that end, the total factor productivity is taken as an initial point, and various performance comparisons are made both within the specified three sub-groups and among all deposit banks in TBS. Within the context of performance measurement, we use input and output variables to test technical efficiency index, which represents a combination of change in technical efficiency and in technology, and to test a change in total factor productivity index which comprises a change in pure technical efficiency and scale efficiency. In the calculation of these indexes, Malmquist total factor productivity index method is employed. Computed indexes provide us with the opportunity to make performance comparisons in order to assess which group and bank have comparatively highest performance among the groups and banks included in this study. When we consider the effects of 2007-2008 global crises on Turkish economy, notably on TBS, calculating the performance change ratio for previous periods or estimating the same for the following periods becomes vital in terms of enduringly changing and developing banks. The growing competition in TBS forces banks to attach more importance to productivity factor for sustainable growth purposes. In this regard, Malmquist total factor productivity index gives us the opportunity to quantify the changes in total factor productivity over the years. Accordingly, this study applies group analysis to determine which group is working efficiently. To do this, Malmquist total factor productivity index requires the use of panel data and depicts efficiency changes by years, representing crucial information for us to produce policy implications. In brief, the test results obtained by this study indicate that the foreign banks, thanks to positive changes in their technology, technical efficiency and total factor productivity, are more effective than other private and state banking groups.


2018 ◽  
Vol 11 (6) ◽  
pp. 170
Author(s):  
Moses Mumba ◽  
Abdi-Khalil Edriss

Smallholder maize production in Zambia has been characterised by low productivity despite concerted efforts at improving the situation as is evident in budgetary allocations to programmes such as the Farmer Input Support Programme (FISP). The study assessed if there was a change in total factor productivity (TFP) in smallholder maize production in Southern Province of Zambia between the 2010/11 and 2013/14 agricultural seasons. Using a balanced panel of 778 smallholder farmers, a Stochastic Frontier Analysis was used to estimate the Malmquist Productivity Index (MPI) in measuring the productivity change in maize production. The change in TFP was further decomposed into its components, efficiency change (EC) and technical change (TC) so as to understand more on the change in productivity. It was found that over the period of study, the mean EC was 0.8734, implying that technical efficiency (TE) had declined by 12.7 % with the mean TFP of 0.9401, indicating that over the study period TFP had fallen by 5.99 %. The results further showed that the age of the farmer, education of the farmer, household size, membership to a farmer organization, ownership of cattle, access to credit, and drought stress were significant (ρ<0.05) factors in explaining TFP. In light of the findings, some recommendations were made for policy including the need to facilitate farmers’ access to credit, sensitize farmers on the benefits of belonging to farmer organizations, on ownership of livestock such as cattle and for massive investment in irrigation infrastructure.


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