View More View Less
  • 1 Corvinus University of Budapest
  • | 2 Magyar Nemzeti Bank (MNB, the central bank of Hungary)
Restricted access

Purchase article

USD  $25.00

1 year subscription (Individual Only)

USD  $700.00

The aim of this paper is to estimate the efficiency of Hungarian banks with several models and to calculate the Lerner index for both the household and the corporate credit market. We apply stochastic frontier analysis (SFA) and data envelopment analysis (DEA) models to estimate the efficiency and calculate profit and cost efficiency with and without taking credit losses into consideration. In terms of cost efficiency, banks are nearly homogeneous and improved their efficiency after the crisis. Banks, however, are extremely heterogeneous in terms of profit efficiency. During the crisis, a gradual improvement could be observed across the sector after the initial downturn. Since the operating conditions of the household and the corporate credit markets are different, we estimated the intensity of competition separately for both the markets. While the Lerner index showed strong market power in the household credit market, the corporate credit market was characterised by intense competition. Regarding efficiency, various models often resulted in different conclusions, especially in the case of cost efficiency. Therefore we recommend that the regulatory decision-making process should always consider the results of several models. Moreover, the Lerner indices demonstrate that it might be important to use disaggregated models when modelling the features of credit markets.

  • Aczél, Á. Banai, Á.Borsos, A.Dancsik, B. (2016): Identifying the Determinants of Housing Loan Margins in the Hungarian Banking System. Financial and Economic Review, 15(4): 544.

    • Search Google Scholar
    • Export Citation
  • Aigner, D.Lovell, K. C. A.Schmidt, P. (1977): Formulation and Estimation of Stochastic Frontier Production Function Models. Journal of Econometrics, 6(1): 2137.

    • Search Google Scholar
    • Export Citation
  • Banai, Á. Király, J.Nagy, M. (2010): Az aranykor vége Magyarországon. “Külföldi” szakmai és “lokális” tulajdonú bankok – válság előtt és válság után (The Demise of the Halcyon Days in Hungary. “Foreign” and “Local” Banks – Before and After the Crisis. Közgazdasági Szemle, LVII(February): 105131.

    • Search Google Scholar
    • Export Citation
  • Bauer, P. W.Berger, A. N.Ferrier, G. D.Humphrey, D. B. (1998): Consistency Conditions for Regulatory Analysis of Financial Institutions: A Comparison of Frontier Efficiency Methods. Journal of Economics and Business, 50(2): 85114.

    • Search Google Scholar
    • Export Citation
  • Bodnár, I.Hegedűs, S.Plajner, Á.Pulai, Gy. (eds) (2017): Célzott hitelösztönzés: NHP-tól az NTP-ig (Targeted Lending Stimulus: From the Funding for Growth Scheme to the Growth Supporting Programme). In: Lehmann, K.Palotai, D.Virág, B. (eds): A Magyar út – célzott jegybanki politika (The Hungarian Way – Targeted Central Bank Policy). Magyar Nemzeti Bank.

    • Search Google Scholar
    • Export Citation
  • Bos, J.Koetter, M. (2011): Handling Losses in Translog Profit Models. Applied Economics, 43(3): 307-312.

  • Casu, B.Girardone, C.Molyneuy, P. (2004): Productivity Change in European Banking: A Comparison of Parametric and Non-Parametric Approaches. Journal of Banking and Finance, 28(10): 25212540

    • Search Google Scholar
    • Export Citation
  • Charnes, A.Cooper, W. W.Rhodes, E. (1978): Measuring the Efficiency of Decision Making Units. European Journal of Operational Research, 2(6): 429444.

    • Search Google Scholar
    • Export Citation
  • Dancsik, B.Hosszú, Zs. (2017): Banki hatékonyság és piaci erő mérése a háztartási és a vállalati hitelpiacon a hitelezési kockázatok figyelembevétele mellett (Measuring Bank Efficiency and Market Power in the Household and Corporate Credit Markets Considering Credit Risks). MNBtanulmányok, 133. Magyar Nemzeti Bank.

    • Search Google Scholar
    • Export Citation
  • Delis, M. D.Anastasia, K. F.Staikoura, C. K.Katerina, G. (2009): Evaluating Cost and Profit Efficiency: A Comparison of Parametric and Non-Parametric Methodologies. Applied Financial Economics, 19: 191202.

    • Search Google Scholar
    • Export Citation
  • Diallo, B. (2017): Bank Efficiency and Industry Growth during Financial Crises. Economic Modelling journal homepage.

  • Dong, Y.Hamilton, R.Tippett, M. (2014): Cost Efficiency of the Chinese Banking Sector: A Comparison of Stochastic Frontier Analysis and Data Envelopment Analysis. Economic Modelling, 36: 298308.

    • Search Google Scholar
    • Export Citation
  • Drake, L.Weyman-Jones, T. G. (1996): Productive and Allocative Inefficiencies in UK Building Societies: A Comparison of Non-Parametric and Stochastic Frontiers Techniques. Manchester School, 64(1): 229245.

    • Search Google Scholar
    • Export Citation
  • Eisenbeis, R.Ferrier, G.Kwan, S. (1999): The Informativeness of Stochastic Frontier and Programming Frontier Efficiency Scores: Cost Efficiency and Other Measures of 20 Bank Holding Company Performance. Federal Reserve Bank of Atlanta, Working Paper, No. 23.

    • Search Google Scholar
    • Export Citation
  • Ferrier, G. D.Lovell, C. A. K. (1990): Measuring Cost Efficiency in Banking: Economic and Linear Programming Evidence. Journal of Econometrics, 46(1-2): 229245.

    • Search Google Scholar
    • Export Citation
  • Fries, S.Taci, A. (2005): Cost Efficiency of Banks in Transition: Evidence from 289 Banks in 15 Post-Communist Countries. Journal of Banking & Finance, 29(1): 5581.

    • Search Google Scholar
    • Export Citation
  • Greene, W. (2005): Reconsidering Heterogeneity in Panel Data Estimators of the Stochastic Frontier Model. Journal of Econometrics, 126(2): 269303.

    • Search Google Scholar
    • Export Citation
  • Gulati, R.Kumar, S. (2016): Assessing the Impact of the Global Financial Crisis on the Profit Efficiency of Indian Banks. Economic Modelling, 58: 167181.

    • Search Google Scholar
    • Export Citation
  • HFSA (2012): Gyorselemzés a végtörlesztésről (Flash Analysis on the Early Repayment Scheme). Hungarian Financial Supervisory Authority. https://www.mnb.hu/letoltes/gyorselemzes-vegtorlesztes-120312j.pdf

    • Search Google Scholar
    • Export Citation
  • Havrylchyk, O. (2005): Efficiency of the Polish Banking Industry: Foreign versus Domestic Banks. Journal of Banking & Finance, 30(7): 19751996.

    • Search Google Scholar
    • Export Citation
  • Huang, T. H.Wang, M. H. (2002): Comparison of Economic Efficiency Estimation Methods: Parametric and Non-Parametric Techniques. Manchester School, 70: 682709.

    • Search Google Scholar
    • Export Citation
  • Kézdi, G.Csorba, G. (2013): Estimating Consumer Lock-in Effects from Firm-Level Data. Journal of Industry, Competition and Trade, 13(3): 431452.

    • Search Google Scholar
    • Export Citation
  • Koutsomanoli-Filippaki, A.Margaritis, D.Staikouras, C. (2009): Efficiency and Productivity Growth in the Banking Industry of Central and Easter Europe. Journal of Banking & Finance, 33(3): 557567.

    • Search Google Scholar
    • Export Citation
  • Lerner, A. P. (1934): The Concept of Monopoly and the Measurement of Monopoly Power. Review of Economic Studies, 1(34): 157175.

  • MNB (2016): Financial Stability Report, May 2016. Magyar Nemzeti Bank.

  • MNB (2017): Financial Stability Report, May 2017. Magyar Nemzeti Bank.

  • Molnár, J.Nagy, M.Horváth, Cs. (2007): A Structural Empirical Analysis of Retail Banking Competition: the Case of Hungary. MNB Working Papers, 2007/1. Magyar Nemzeti Bank.

    • Search Google Scholar
    • Export Citation
  • Molnár, M.Holló, D. (2011): How Efficient are Banks in Hungary? OECD Economics Department Working Papers, No. 848. OECD Publishing.

    • Search Google Scholar
    • Export Citation
  • Móré, Cs. Nagy, M. (2003): Relationship between Market Structure and Bank Performance: Empirical Evidence for Central and Eastern Europe. MNB Working Papers, 2003/12. Magyar Nemzeti Bank.

    • Search Google Scholar
    • Export Citation
  • Móré, Cs. Nagy, M. (2004): Competition in the Hungarian Banking Market. MNB Working Papers, 2004/9. Magyar Nemzeti Bank.

  • Meeusen, W. – Van den Broeck, J. (1977): Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error. International Economic Review, 18(2): 435444.

    • Search Google Scholar
    • Export Citation
  • Niţoi, M.Spulbar, C. (2015): An Examination of Banks’ Cost Efficiency in Central and Eastern Europe. Procedia Economics and Finance, 22: 544551.

    • Search Google Scholar
    • Export Citation
  • Nurboja, B.Kosak, M. (2017): Banking Efficiency in South East Europe: Evidence for Financial Crises and the Gap between New EU Members and Candidate Countries. Economic Systems, 41: 122128.

    • Search Google Scholar
    • Export Citation
  • Resti, A. (1997): Evaluating the Cost Efficiency of the Italian Banking System: What Can Be Learned from the Joint Application of Parametric and Non-Parametric Techniques. Journal of Banking and Finance, 21(2): 221250.

    • Search Google Scholar
    • Export Citation
  • Tone, K. (2002): A Strange Case of the Cost and Allocative Efficiencies in DEA. Journal of Operational Researchers Society, 53(11): 12251231.

    • Search Google Scholar
    • Export Citation
  • Wang, H. (2002): Heteroskedasticity and Non-Monotonicity Efficiency Effects of a Stochastic Frontier Model. Journal of Productivity Analysis, 18(3): 241253.

    • Search Google Scholar
    • Export Citation
  • Weill, L. (2006): Measuring Cost Efficiency in European Banking: A Comparison of Frontier Techniques. Journal of Productivity Analysis, 21(2): 133152.

    • Search Google Scholar
    • Export Citation
Submit Your Manuscript
 
The author instruction is available in PDF.
Please, download the file from HERE.

 

The description of the refereeing procedure is available in PDF.
Please, download the file from HERE.

 

 

Senior editors

Editor(s)-in-Chief: Prof. Dr. Mihályi, Péter

Editor(s): Ványai, Judit

Editorial Board

  • Ádám Török (Chairman) / University of Pannonia; Budapest University of Technology and Economics
  • Edina Berlinger / Corvinus University of Budapest, Department of Finance
  • Péter Halmai / Budapest University of Technology and Economics; National University of Public Service
  • István Kónya / Institute of Economics Centre for Regional and Economic Studies, University of Pécs
  • János Köllő / Institute of Economics Centre for Regional and Economic Studies
  • István Magas / Corvinus University of Budapest, Department of World Economy; University of Physical Education, Department. of Sports and Decision Sciences
 

Advisory Board

  • Ǻslund, Anders, Institute of International Economics, Washington (USA)
  • Kolodko, Grzegorz, Kozminski University, Warsaw (Poland)
  • Mau, Vladimir, Academy of National Economy (Russia)
  • Messerlin, Patrick A, Groupe d’Economie Mondiale (France)
  • Saul Estrin, London School of Economics (UK)
  • Wagener, Hans-Jürgen, Europa Universität Viadrina (Germany)

Corvinus University of Budapest
Department of Economics
Fővám tér 8 Budapest, H-1093, Hungary

Indexing and Abstracting Services:

  • EconLit
  • Elsevier GEO Abstracts
  • GEOBASE
  • International Bibliographies IBZ and IBR
  • JEL
  • Referativnyi Zhurnal
  • RePEc
  • SCOPUS
  • Social Science Citation Index
  • Index Copernicus

 

2020  
Total Cites 275
WoS
Journal
Impact Factor
0,875
Rank by Economics 325/377 (Q4)
Impact Factor  
Impact Factor 0,534
without
Journal Self Cites
5 Year 0,500
Impact Factor
Journal  0,38
Citation Indicator  
Rank by Journal  Economics 347/549 (Q3)
Citation Indicator   
Citable 37
Items
Total 37
Articles
Total 0
Reviews
Scimago 13
H-index
Scimago 0,292
Journal Rank
Scimago Economics and Econometrics Q3
Quartile Score  
Scopus 225/166=1,4
Scite Score  
Scopus Economics and Econometrics 392/661 (Q3)
Scite Score Rank  
Scopus 0,668
SNIP  
Days from  289
sumbission  
to acceptance  
Days from  447
acceptance  
to publication  

2019  
Total Cites
WoS
212
Impact Factor 0,914
Impact Factor
without
Journal Self Cites
0,728
5 Year
Impact Factor
0,650
Immediacy
Index
0,156
Citable
Items
45
Total
Articles
45
Total
Reviews
0
Cited
Half-Life
3,9
Citing
Half-Life
9,5
Eigenfactor
Score
0,00015
Article Influence
Score
0,052
% Articles
in
Citable Items
100,00
Normalized
Eigenfactor
0,01891
Average
IF
Percentile
28,437
Scimago
H-index
12
Scimago
Journal Rank
0,439
Scopus
Scite Score
214/165=1,3
Scopus
Scite Score Rank
Economics and Econometrics 355/637 (Q3)
Scopus
SNIP
0,989

 

Acta Oeconomica
Publication Model Hybrid
Submission Fee none
Article Processing Charge 900 EUR/article
Printed Color Illustrations 40 EUR (or 10 000 HUF) + VAT / piece
Regional discounts on country of the funding agency World Bank Lower-middle-income economies: 50%
World Bank Low-income economies: 100%
Further Discounts Editorial Board / Advisory Board members: 50%
Corresponding authors, affiliated to an EISZ member institution subscribing to the journal package of Akadémiai Kiadó: 100%
Subscription fee 2021 Online subsscription: 588 EUR / 732 USD
Print + online subscription: 688 EUR / 860 USD
Subscription fee 2022 Online subsscription: 600 EUR / 750 USD
Print + online subscription: 704 EUR / 880 USD
Subscription Information Online subscribers are entitled access to all back issues published by Akadémiai Kiadó for each title for the duration of the subscription, as well as Online First content for the subscribed content.
Purchase per Title Individual articles are sold on the displayed price.

Acta Oeconomica
Language English
Size B5
Year of
Foundation
1966
Publication
Programme
2021 Volume 71
Volumes
per Year
1
Issues
per Year
4
Founder Magyar Tudományos Akadémia
Founder's
Address
H-1051 Budapest, Hungary, Széchenyi István tér 9.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 0001-6373 (Print)
ISSN 1588-2659 (Online)