scholarly journals Technical Efficiency in the European Dairy Industry: Can We Observe Systematic Failures in the Efficiency of Input Use?

2021 ◽  
Vol 13 (4) ◽  
pp. 1830
Author(s):  
Lukáš Čechura ◽  
Zdeňka Žáková Kroupová
Keyword(s):  
Technical Efficiency ◽  
Distance Function ◽  
Efficiency Analysis ◽  
Potential Cost ◽  
Robust Estimate ◽  
Processing Industry ◽  
Input Distance Function ◽  
Structural Problems ◽  
Dairy Processing ◽  
Input Use

The paper provides findings on the technical efficiency of the European dairy processing industry, which is one of the most important subsectors of the food processing industry in the European Union (EU). The ability to efficiently use inputs in the production of outputs is a prerequisite for the sustainability and competitiveness of the agri-food sector as well as for food security. Thus, the aim of this paper is to provide a robust estimate of technical efficiency by employing new advances in productivity and efficiency analysis, and to investigate the efficiency of input use in 10 selected European countries. The analysis is based on two-stage stochastic frontier modelling incorporating country-specific input distance function (IDF) estimates and a meta-frontier input distance function estimate, both in specification of the four-component model, which currently represents the most advanced approach to technical efficiency analysis. To provide a robust estimate of these models, the paper employs methods that control for the potential endogeneity of netputs in the multi-step estimation procedure. The results, based on the Amadeus dataset, reveal that companies manufacturing dairy products greatly exploited their production possibilities in 2006–2018. The dairy processing industry in the analysed countries cannot generally be characterized by a considerable waste of resources. The potential cost reduction is estimated at 4–8%, evaluated on the country samples mean. The overall technical inefficiency (OTE) is mainly a result of short-term shocks and unsystematic failures. However, the meta-frontier estimates also reveal a certain degree of systematic failure, e.g., permanent managerial failures and structural problems in European dairy processing industry.

scholarly journals Revisiting firm flexibility and efficiency: evidence from the EU dairy processing industry

2019 ◽  
Vol 47 (3) ◽  
pp. 971-1008 ◽  
Author(s):  
Stefan Hirsch ◽  
Ashok Mishra ◽  
Niklas Möhring ◽  
Robert Finger
Keyword(s):  
Technical Efficiency ◽  
Economic Crisis ◽  
Economic Conditions ◽  
Processing Industry ◽  
Firm Efficiency ◽  
Dairy Processing ◽  
Production Flexibility ◽  
Specific Factors ◽  
Flexibility Measures ◽  
The Eu

Abstract We analyse the flexibility of EU dairy processors to adjust production to fluctuating economic conditions. For a set of 2,186 firms, we derive production flexibility measures representing the effect of output variations on costs. The results reveal that flexibility is highest in Poland and Italy and lowest in Spain. Several firm-specific factors, such as size and age of the firm, are found to affect firm flexibility. Moreover, we detect a tradeoff between flexibility and technical efficiency for large firms indicating that a sole focus on firm efficiency can be insufficient. Finally, the results show that during economic crisis flexibility can help to sustain profitability.

scholarly journals TECHNICAL EFFICIENCY ANALYSIS IN INDONESIAN FISHERY PROCESSING INDUSTRY: A CASE OF FISHERY CANNED PRODUCT FIRMS

2019 ◽  
Vol 9 (1) ◽  
pp. 53
Author(s):  
Munawar Asikin ◽  
Arief Daryanto ◽  
Machfud . ◽  
Subagio Dwijosumono
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Efficiency Analysis ◽  
Least Square ◽  
Time Varying ◽  
Efficient Manner ◽  
Processing Industry ◽  
Frontier Analysis ◽  
Ordinary Least Square

This study aims to analyze technical efficiency and evaluate the effect of some sources of inefficiency in the Indonesian fishery canned firms during the period of 1990-2015. We calculate technical efficiency using the Stochastic Frontier Analysis (SFA) method with Time Varying Decay. The average of technical efficiency in this industry during the period of 1990-2015 was only 57%. It indicates that firms in this industry still encounter a problem in allocating the resources in efficient manner.  However, during the period of 1994-2015, the efficiency in the Indonesian fishery canned industry has declined. We also employed the Ordinary Least Square (OLS) method to evaluate the sources of inefficiency. The results showed that eight variables affected to the efficiency in this industry, thereby it will reduce fishery product competitiveness in the future

scholarly journals Technical Efficiency and Evidence of Economies of Scope in Botswana Agriculture: A Stochastic Input Distance Function Approach (1979-1996)

2015 ◽  
Vol 1 (1) ◽  
pp. 92 ◽  
Author(s):  
Johane Moilwa Motsatsi
Keyword(s):  
Technical Efficiency ◽  
Distance Function ◽  
Percent Level ◽  
Function Approach ◽  
Economies Of Scope ◽  
Commercial Sector ◽  
Economic Returns ◽  
Input Distance Function ◽  
Livestock Feeds ◽  
Stochastic Input

<p><em>This study estimate technical efficiency indices and examines evidence of economies of scope in Botswana agriculture for each 18 districts and commercial sector using a multiple-output multiple-input stochastic input distance function approach covering data from 1979 to 1996. The estimated model provides input-output relations, economies (diseconomies) of scope and technical inefficiency. All the production outputs (cattle, crops and goats/sheep) were significant with expected signs. The estimated mean technical efficiency of 0.885 for 18 districts and the commercial sector was obtained. This suggest the existence of inefficiency in Botswana agricultural production which indicates that there is opportunity to increase production with the same quantities of input factors, and through adaptation of improved technology such as irrigation, use of fertilisers, and improved high quality crops and livestock. There is significant in economies of scope between the production of cattle and goat/sheep, at the 1 percent level, and cattle and crops at 5 percent level. This existence of economies of scope indicates that higher economic returns are possible through efficient use of labour and livestock feeds, and reducing risk by not producing output (e.g., crops) that is easily affected by droughts and poor soils.</em></p>

Incorporating Risk into Technical Efficiency: The Case of ASEAN Banks

2018 ◽  
Author(s):  
Ngo Thanh Tra ◽  
Le Quang Minh ◽  
Cai Phuc Thien Khoa ◽  
Ngo Phu Thanh
Keyword(s):  
Technical Efficiency ◽  
Distance Function ◽  
Stochastic Frontier ◽  
Efficiency Analysis ◽  
Directional Distance Function ◽  
Economic Modelling ◽  
Bank Efficiency ◽  
Frontier Analysis ◽  
Asean Countries ◽  
The Impact

The objective of this paper is to incorporate risk in technical efficiency of listed ASEAN banks in a panel data framework for the period 2000 to 2015. Many researchers apply frontier estimation techniques such as data envelopment analysis (DEA) or stochastic frontier analysis (SFA) for their efficiency analysis. However, the banks’ complex production process requires more sophisticated techniques to account for internal structures within the black box so relying only traditional DEA or SFA is not adequate to deal with a multiple-input and multiple-output production technology. To incorporate undesirable outputs such as risk into inefficiency, we rely on the directional distance function (DDF). We employ the DDF under both parametric (SFA) and semi-parametric (SEMSFA) framework to make a comparison efficiency scores with risk adjusted in two scenarios. Our results suggest that risk is an important factor that bank managers should pay more focus to achieve long-term efficiency in ASEAN banks Keywords Bank efficiency; risk; directional distance function (DDF); semiparametric estimation of stochastic frontier models (SEMSFA) References ADB. (2013). The road to ASEAN financial integration: A combined study on assessing the financial landscape and formulating milestones for monetary and financial integration in ASEAN. Andor, M., & Hesse, F. (2014). The StoNED age: the departure into a new era of efficiency analysis? A monte carlo comparison of StoNED and the ‘‘oldies’’ (SFA and DEA). J Prod Anal 41, 85-109. doi: 10.1007/s11123-013-0354-yBerger, A. N., & DeYoung, R. (1997). Problem loans and cost efficiency in commercial banks. Journal of Banking & Finance, 21(6), 849-870. Berger, A. N., & Humphrey, D. B. (1997). Efficiency of financial institutions: international survey and directions for future research. European Journal of Operational Research, 98, 175-212. Chan, S.-G., Koh, E. H. Y., Zainir, F., & Yong, C.-C. (2015). Market structure, institutional framework and bank efficiency in ASEAN 5. Journal of Economics and Business, 82, 84-112. Chang, C.-C. (1999). The Nonparametric Risk-Adjusted Efficiency Measurement: An Application to Taiwan’s Major Rural Financial Intermediaries. American Journal of Agricultural Economics, 81(4), 902-913. Chang, T.-C., & Chiu, Y. H. (2006). Affecting factors on risk-adjusted effciency in Taiwan’s banking industry. Contemporary Economic Policy 24(4), 634-648. Gardener, E., Molyneux, P., & Nguyen-Linh, H. (2011). Determinants of efficiency in South East Asian banking. The Service Industries Journal, 31(16), 2693-2719. Huang, T.-H., Chiang, D.-L., & Tsai, C.-M. (2015). Applying the New Metafrontier Directional Distance Function to Compare Banking Efficiencies in Central and Eastern European Countries. Economic Modelling, 44, 188-199. Karim, M. Z. A. (2001). Comparative Bank Efficiency across Select ASEAN Countries. ASEAN Economic Bulletin, 18(3), 289-304. Karim, M. Z. A., Sok-Gee, C., & Sallahudin, H. (2010). Bank efficiency and non-performing loans: Evidence from Malaysia and Singapore. Prague Economic Papers, 2, 118-132. doi: 10.18267/j.pep.367Khan, S. J. M. (2014). Bank Efficiency in Southeast Asian Countries: The Impact of Environmental Variables. In Handbook on the Emerging Trends in Scientific Research. Malaysia: PAK Publishing Group. Laeven, L. (1999). Risk and Efficiency in East Asian Banks (Vol. 2255). Washington, D.C. : World Bank, Financial Sector Strategy and Policy Department.Manlagnit, M. C. V. (2011). Cost efficiency, determinants, and risk preferences in banking: A case of stochastic frontier analysis in the Philippines. Journal of Asian Economics, 22, 23-35. Sarifuddin, S., Ismail, M. K., & Kumaran, V. V. (2015). Comparison of Banking Efficiency in the selected ASEAN Countries during the Global Financial Crisis. PROSIDING PERKEM, 10, 286-293. Sarmientoa, M., & Galán, J. E. (2015). The Influence of Risk-Taking on Bank Efficiency: Evidence from Colombia. CentER Discussion Paper, 2015-036. Vidoli, F., & Ferrara, G. (2015). Analyzing Italian citrus sector by semi-nonparametric frontier efficiency models. Empir Econ, 45, 641-658. Williams, J., & Nguyen, N. (2005). Financial Liberalisation, Crisis, and Restructuring: A Comparative Study of Bank Performance and Bank Governance in South East Asia. Journal of Banking and Finance, 29(8-9), 2119-2154. Wong, W. P., & Deng, Q. (1999). Efficiency analysis of banks in ASEAN countries. Benchmarking: An International Journal, 23(7), 1798-1817. Yueh-Cheng Wu, I. W. K. T., Wen-Min Lu, Mohammad Nourani, Qian Long Kweh. (2016). The impact of earnings management on the performance of ASEAN banks. Economic Modelling, 53, 156-165. Zhu, N., Wang, B., Yu, Z., & Wu, Y. (2016). Technical Efficiency Measurement Incorporating Risk Preferences: An Empirical Analysis of Chinese Commercial Banks. Emerging Markets Finance and Trade, 52, 610-624.  

scholarly journals Technical efficiency of Serbian dairy processing industry

2018 ◽  
Vol 65 (2) ◽  
pp. 569-581 ◽  
Author(s):  
Rade Popović ◽  
Dalibor Panić
Keyword(s):  
Technical Efficiency ◽  
Processing Industry ◽  
Dairy Processing

scholarly journals Production risk, technical efficiency, and input use nexus: Lessons from Bangladesh aquaculture

2021 ◽  
Vol 52 (1) ◽  
pp. 57-72
Author(s):  
Md. Akhtaruzzaman Khan ◽  
Ratna Begum ◽  
Rasmus Nielsen ◽  
Ayoe Hoff
Keyword(s):  
Technical Efficiency ◽  
Production Risk ◽  
Input Use

scholarly journals Accounting for rainfall and the length of growing season in technical efficiency analysis

2018 ◽  
Vol 20 (4) ◽  
pp. 2583-2608
Author(s):  
Yiorgos Gadanakis ◽  
Francisco José Areal
Keyword(s):  
Technical Efficiency ◽  
Physical Environment ◽  
Farming Systems ◽  
Growing Season ◽  
Efficiency Analysis ◽  
Performance Measurements ◽  
East Anglia ◽  
Dea Model ◽  
Efficiency Ranking ◽  
Business Survey

Abstract The physical environment of farming systems is rarely considered when conducting farm level efficiency analysis, which is likely to lead to bias of performance measurements based on benchmarking methods such as Data Envelopment Analysis (DEA). We incorporate variations of the physical environment (rainfall and length of growing season) through the specifications of the linear programming in DEA to investigate performance measurement bias. The derived technical efficiency estimates are obtained using a sub-vector DEA which ensures farms are compared in a homogenous environment (i.e. accounting for differences in rainfall levels amongst distinct farm units). We use the Farm Business Survey to analyse a representative sample of 245 cereal farms in the East Anglia region between 2009 and 2010. Efficiency rankings obtained from a standard DEA model and a non-discretionary DEA model that incorporates the variations in the physical environment. We show that incorporating rainfall and the length of the growing season as non-discretionary inputs into the production function had significantly altered the farm efficiency ranking between the two models. Hence, to improve extension services to farmers and to reduce biased estimates of farm technical efficiency, variations in environmental conditions need to be integral to the analysis of efficiency.

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