Total factor productivity of the non-life insurers in India: Malmquist index with a new decomposition

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ashiq Mohd Ilyas ◽  
S. Rajasekaran
Keyword(s):  
Total Factor Productivity ◽  
Life Insurance ◽  
Economies Of Scale ◽  
Negative Impact ◽  
Malmquist Index ◽  
Scale Efficiency ◽  
Factor Productivity ◽  
Decomposition Approach ◽  
Content Type ◽  
Insurance Sector

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.

Total Factor Productivity Growth of Indian Life Insurance Companies: A Malmquist Approach

2021 ◽  
pp. 232-236
Keyword(s):  
Total Factor Productivity ◽  
Life Insurance ◽  
Productivity Growth ◽  
Malmquist Index ◽  
Secondary Data ◽  
Private Life ◽  
Annual Reports ◽  
Insurance Companies ◽  
Factor Productivity ◽  
Insurance Sector

This study aimed to investigate the productivity growth of Indian life insurance companies using the Malmquist index. This study analyzed all the 24 life insurance companies' productivity performance in India from the financial year 2012-2013 to 2016-2017 using the Malmquist index based on the secondary data collected from Insurance Regulatory and Development Authority's Annual Reports. Findings indicated that the total factor productivity (TFP) of the life insurance sector increased at an average of 27.6 percent during the study period. On average, this improvement was ascribed to an efficiency improvement of 5.5 percent and a technological improvement of 20.9 percent. The results also indicated that the private life insurers experienced higher productivity growth of 30.2 percent than the state-owned Life Insurance Corporation of India's 17.2 percent. This is the first study that comprehensively analyzed the changes in total factor productivity of the Indian life insurance sector. The study holds important and practical insights for policymakers, practitioners, and decision-makers.

scholarly journals Measuring Total Factor Productivity of China Provincial Non-Life Insurance Market: A DEA-Malmquist Index Method

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Fangping Yu ◽  
Hang Chen ◽  
Jiaqi Luo ◽  
Haibo Kuang
Keyword(s):  
Total Factor Productivity ◽  
Life Insurance ◽  
Technological Progress ◽  
Insurance Industry ◽  
Malmquist Index ◽  
Insurance Market ◽  
Scale Efficiency ◽  
Factor Productivity ◽  
Index Method ◽  
Life Insurance Industry

The unbalanced economic development results in the difference in operating efficiency of the non-life insurance industry in China’s provinces; based on the DEA-Malmquist index method, this paper investigates the provincial differences, dynamic change characteristics, and causes of non-life insurance productivity in 31 provinces of China from 2004 to 2017. The results show that in the sample period, there are significant differences between provinces and regions in China’s non-life insurance efficiency, which generally shows the echelon spatial characteristics of “strong in the west and weak in the east”. Technological progress in the western region promotes the rapid growth of total factor productivity, while the low efficiency of technological progress in the eastern region restrains the improvement of total factor productivity. The overall total factor productivity of China’s provincial non-life insurance industry is on the rise, mainly due to the improvement of pure technical efficiency and scale efficiency, while technological progress has an inhibiting effect on the contrary. These conclusions are of reference value for relevant stakeholders in China’s provincial non-life insurance market to formulate development strategies and business strategies.

scholarly journals A Study on the Efficiency of Tourism Poverty Alleviation in Ethnic Regions Based on the Staged DEA Model

2021 ◽  
Vol 12 ◽  
Author(s):  
Jianchun Yang ◽  
Ying Wu ◽  
Jialian Wang ◽  
Chengcheng Wan ◽  
Qian Wu
Keyword(s):  
Ethnic Minority ◽  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Poverty Alleviation ◽  
Malmquist Index ◽  
Great Difficulty ◽  
Local Economy ◽  
Scale Efficiency ◽  
Factor Productivity ◽  
Two Stages

Poverty alleviation through tourism is an important way for China to achieve targeted poverty alleviation and win the battle of poverty alleviation. As a region with deep poverty and great difficulty in poverty alleviation, whether tourism development has injected key impetus into ethnic minority areas needs to be tested by both qualitative analysis and quantitative measurement. This paper takes eight ethnic provinces (regions) in China as an example to conduct an empirical study. Based on the Data Envelopment Analysis (DEA)-BCC model and Malmquist index, it evaluates the tourism investment and tourism poverty alleviation efficiency of the ethnic regions in the two stages of tourism poverty alleviation, and analyzes them by classification. The results of the study show: (1) The pure technical efficiency in the first stage is relatively high, but the total factor productivity of each region is declining; (2) The pure technical efficiency in the second stage is also relatively high, but the scale efficiency is low, and the change rate of total factor productivity of the provinces in China has increased significantly; (3) The “double high” type includes Guangxi, Inner Mongolia, and Guizhou, and the “double low” type includes Qinghai, Yunnan, Tibet, Xinjiang, and Ningxia. The results of the study generally show that tourism poverty alleviation has brought about the improvement of the living standards of residents and the development of local economy, but the efficiency of tourism poverty alleviation needs to be improved. On this basis, the article puts forward corresponding improvement measures, in order to further help the ethnic minority areas get rid of poverty in a comprehensive way by promoting the efficient and sustainable development of tourism.

scholarly journals Cost Efficiency and Total Factor Productivity: An Empirical Analysis of Pakistan’s Insurance Sector

2016 ◽  
Vol 21 (1) ◽  
pp. 123-150
Author(s):  
Uzma Noreen ◽  
Shabbir Ahmad
Keyword(s):  
Total Factor Productivity ◽  
Malmquist Index ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Innovative Technology ◽  
Average Score ◽  
Factor Productivity ◽  
Tobit Regression ◽  
Insurance Sector ◽  
The Impact

This study uses data envelopment analysis and the Malmquist index to examine the impact of financial sector reforms on the efficiency and productivity of Pakistan’s insurance sector over the period 2000–09. Our results indicate that the sector is cost-inefficient, with an average score of 58 percent – an outcome of the inappropriate use of inputs. The Malmquist productivity index performs better, indicating an improvement in total factor productivity of about 3 percent on average. The second-stage Tobit regression analysis shows that large firms are relatively inefficient from an allocative perspective as they are unable to equate the marginal product of inputs with their factor prices. Furthermore, the results demonstrate that private firms are more efficient than public firms in the nonlife insurance sector. The empirical findings suggest that a more competitive environment, diversified products and innovative technology could improve the productivity of insurance firms in Pakistan.

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
Keyword(s):  
Total Factor Productivity ◽  
Economies Of Scale ◽  
Banking Sector ◽  
Value Added ◽  
Productivity Index ◽  
Annual Data ◽  
Fiscal Deficit ◽  
Factor Productivity ◽  
Content Type ◽  
Frontier Analysis

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.

Productivity in professional Spanish basketball

2014 ◽  
Vol 4 (3) ◽  
pp. 196-211 ◽  
Author(s):  
Marta Brosed Lázaro ◽  
Manuel Espitia-Escuer ◽  
Lucía I. García-Cebrián
Keyword(s):  
Total Factor Productivity ◽  
Malmquist Index ◽  
Efficient Frontier ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Content Type ◽  
Potential Output ◽  
Productive Function ◽  
Contest Design ◽  
Basketball Teams

Purpose – The purpose of this paper is twofold: first, to evaluate the performance of Spanish first-division basketball teams, in terms of efficiency, by defining previously a productive function and obtaining also their potential output. Second, to examine the total factor productivity evolution having information from several years, which allows us to draw conclusions about the changes in the efficient frontier. Design/methodology/approach – In order to assess the efficiency level and the potential output of each team in the ACB competition, between the season 2008/2009 and 2011/2012, an input-oriented version with constant returns of data envelopment analysis is used. The total factor productivity evolution is studied by employing the values of the Malmquist index. Findings – The main conclusion is that the final position of the Spanish basketball teams depends on the efficiency and any technological progress is needed to maintain themselves on top of rank. Practical implications – Performing on the field efficiently is the best way to increase the profits by generating savings, which minimize costs. This analysis allows us to make a series of observations, comments and conclusions with regard to the management of the budgets and the relationship between efficiency and sports performance. Originality/value – The innovations provided by this paper are the use of a different methodology and a different analysis unit from the previous studies. Moreover, it focuses on European basketball, specifically the Spanish league, which is considered the most powerful league after NBA and whose connection with academic studies is quite limited to date. Finally it tries to incorporate the play-off stage, which is complicated but really interesting because of the contest design of these competitions.

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.

Productivity of the Indian non-life insurance sector

2019 ◽  
Vol 69 (4) ◽  
pp. 633-650
Author(s):  
Ashiq Mohd Ilyas ◽  
S. Rajasekaran
Keyword(s):  
Life Insurance ◽  
Average Rate ◽  
Insurance Companies ◽  
Scale Efficiency ◽  
Index Number ◽  
Content Type ◽  
Insurance Sector ◽  
Index Number Theory ◽  
Practical Implications ◽  
Observation Period

Purpose The purpose of this paper is to analyse the performance of the Indian non-life (general) insurance sector in terms of total factor productivity (TFP) over the period 2005–2016. Design/methodology/approach This study utilises Färe‒Primont index (FPI) to access the change in TFP and its components: technical change, technical efficiency and mix and scale efficiency over the observation period. Moreover, it employs the Mann–Whitney U-test to scrutinise the difference between the public and the private insurers in terms of growth in productivity. Findings The results reveal that the insurance sector possesses a very low level of TFP. Also, the results divulge an improvement of 11.98 per cent in TFP of the insurance sector at an annual average rate of 12.41 per cent over the observation period. The growth in productivity is mainly attributable to the improvement of 10.81 per cent in the scale‒mix efficiency. The progress in scale‒mix efficiency is mainly the result of improvements in residual scale and residual mix efficiency. The results also show that the privately owned insurers have experienced a high productivity growth rate than the state-owned insurers. Practical implications The results hold practical implications for the regulators, policymakers and decision makers of the Indian non-life insurance companies. Originality/value This study is the first of its kind to use FPI, which satisfies all economically relevant axioms and tests defined by the index number theory to comprehensively access the change in TFP of the Indian non-life insurance sector.

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.

scholarly journals Is There any Improvement in Total Factor Productivity Growth of Indian Pharmaceutical Industry after TRIPS Agreement? : Evidence from Biennial Malmquist Index

2018 ◽  
Vol 2 (3) ◽  
pp. 53
Author(s):  
Dipyaman PAL ◽  
Chandrima CHAKRABORTY ◽  
Arpita GHOSE
Keyword(s):  
Pharmaceutical Industry ◽  
Total Factor Productivity ◽  
Productivity Growth ◽  
Malmquist Index ◽  
Trips Agreement ◽  
Total Factor Productivity Growth ◽  
Scale Efficiency ◽  
Factor Productivity ◽  
Firm Level ◽  
Indian Pharmaceutical Industry

Aim: Indian Pharmaceutical Industry (IPI) has undergone a massive makeover–from a modest beginning of “process patents regime” in the seventies to a modern and WTO compatible regime under the Trade Related Intellectual Property Rights System (TRIPS) in 2005. This paper estimates Total Factor Productivity Growth (TFPG) of Indian Pharmaceutical Industry (IPI) using firm level data from 2000 to 2013. Design / Research methods: We have used nonparametric approach of Data Envelopment Analysis (DEA) using Biennial Malmquist Index. Conclusions / findings: The results of estimation suggest an increase in overall TFPG of IPI after TRIPS agreement and also those vertically integrated firms involved in both bulk drugs production and formulation activities are less productive compared to firms that are involved in production of only bulk drug or formulation activity. Originality / value of the article: This paper examines whether productivity of IPI has increased after 2005 i.e. after the period of TRIPS, by estimating TFPG for two sub-periods, i.e., from 2000 to 2005 and 2006 to 2013. Implications of the research: The decomposition of TFPG suggests that for overall period 2000-2013, scale changes are the most important factor causing the productivity changes and among the other two alternative sources of TFPG, efficiency change dominates over technical changes. For the sub-period 2006-2013, the improvement in the scale efficiency may push the firms to a higher TFPG, whereas for 2000-2005 the better utilization of factors of production is the main driver of TFPG. A second stage panel regression suggests that R&D expenditure, Marketing expenditure, Market size, Capital-Labour ratio, import intensity and export intensity have positive and significant influence on TFPG.

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