Author :
Abstract
Bireysel emeklilik sistemi, katılımcıların gönüllülük esasına göre yatırmış olduğu fonların yönetilmesini kapsar. Yatırılan bu fonlar ülkenin tasarruf oranını arttırırken fonların sermaye piyasasında yatırımlara dönüşmesiyle birlikte bireylerin ve ülkenin refah seviyesini arttırması açısından oldukça önemlidir. Özellikle son yıllarda yapılmış olan yatırımlara kaynak sağlamak, tasarruf oranlarını arttırmak ve istenilen düzeye yükseltmek amacı ile bireysel emeklilik sistemine devlet desteğinin arttığı görülmektedir. Bu çalışmanın amacı, Türkiye’deki bireysel emeklilik şirketlerinin 2011-2016 yılları arasındaki etkinliklerini veri zarflama analizi yöntemiyle ölçmektir. Analiz aşamasında Toplam varlıklar, Özsermaye ve katkı payı tutarı girdi değişkeni olarak, prim üretimi ve yatırım gelirleri ise çıktı değişkeni olarak kullanılmıştır. Ele alınan dönem itibari ile ilk yıllarda analize dâhil edilen işletmelerin büyük bir kısmının etkinlik sınırının altında kaldığı ilerleyen yıllarda ise ilgili işletmelerin etkinlik değerlerinde artış olduğu görülmüştür.
Keywords
Abstract
The individual pension system covers the management of the funds invested by the participants on a voluntarily basis. These funds are important in terms of increasing the country's savings rate as well as increasing the welfare of individuals and the country with the transformation of funds into capital market investments. In recent years, states have increasingly supported the private pension system to provide resources to the investments and increase the saving rates. The aim of this study is to measure the effectiveness of individual pension companies in Turkey between the years 2011-2016 with data envelopment analysis method. In the analysis phase, while total assets, equity and contribution rates were used as input variables, premium production and investment income were used as output variables. The majority of companies included in the analysis in the first years were below the efficiency limit and in the following years an increase was observed in the efficiency values of the related companies.
Keywords
- done with data envelopment analysis between 1998 and 1999. In this study, capital, labor and
- Gürbüz, 2000). In another study, Ciftci measured efficiency of
- 62 insurance companies between 1998 and 2002 with DEA to analyze current situation of Turkish
- variables (Çiftçi, 2004). Sezen et al. measured relative efficiency of 28 insurance companies
- operating in Turkey between the years 1998 and 2003 with the DEA. In this study, total technical
- sector between 2005-2007 (Altan, 2010), Özcan measured both operational and financial performances
- of non-life insurance companies (Özcan, 2011), Karakaya et al, measured the efficiency of 14 private
- pension companies in 2011 (Karakaya et al,
- 2014), Özbek measured the financial and operational
- efficiencies of non-life insurance companies between 2010 and 2014 (Özbek, 2015), Ayhan measured
- (Ayhan, 2017). Moreover, Özüdoğru measured the financial
- performance of 7 insurance companies traded on the BIST between the years 2014 and 2016 (Özüdoğru,
- 2017), Özaktaş measured the efficiency of non-life insurance companies for the years between 2002 and with DEA in terms of
- In later periods, it was started to be used in industries working with profit (Yolalan, 1993: 27). However,
- evaluate the relative efficiency of each decision element (Lang 1995: 473). Data envelopment analysis is the best observation value obtained as a result of comparing
- The CCR model, which was first formed by Charnes, Cooper and Rhodes in 1978, is based on the
- The BCC model, which was formed by Banker, Charnes and Cooper for the first time in 1984, is
- variable of the study is total assets which were used studies of (Köseoğlu, 2009) and (Karakaya
- 2014). The second input variable is the equity which was used studies of (Salimi Altan, 2010) and
- (Ertuğrul, 2010). The last input variable is the contribution amount which was used in the studies of
- (Teresa Garcia, 2010) and (Kabak, 2010). The output variables are the premium production which
- was used in the studies of (Sezen et al, 2005) and (Çetintaş Biçen, 2011); and the investment income
- 2012-2016 yılındaki emeklilik şirketlerininden kes Data related to private pension companies was
- As a result of the efficiency measurement conducted with DEA in 2011, it can be seen that only
- CCRmodel, only pension company was efficient. According to the BCC model, Aegon, Alianz Ziraat pension companies were efficient. As in 2011, the companies that are below the efficiency
- data envelopment analysis in 2013, all companies other than Ziraat were below the efficiency limit. In
- In the efficiency measurement which is done with DEA in 2014, according to input-oriented CCR
- by the companies that are not efficient. Aegon P Allianz P Allıanz Anadolu P Avıvasa P In the efficiency measurement which is done with DEA in 2015, according to input-oriented CCR
- oriented BCC model, besides these companies Anadolu pension company was efficient. 2015, the
- number of companies that were taken as a reference increased. Input-Oriented CCR, BCC, Scale Efficiency Values With Reference Cluster of Private Pension BNP Garanti Metlife P Aegon, BNP, Ziraat In 2016, efficiency measurement according to both the input-oriented CCR model and the input
- model for input is used in the analysis. In terms of space saving and exemplary data, only 2016 data
- Participation in the private pension system, which became operational in 2003, is increasing day by day.
- Today, the system is still active effectively. As of 2013, the system has become more attractive with the
- Private pension companies’ efficiency measurement between 2011 and 2016 was done with data
- efficient companies was few between 2011 and 2014. However, it increased between 2015 and 2016. It
- Ziraat. Groupama is the worst performing company between 2011 and 2016, which is below the
- input-oriented CCR model. Only in 2014 it was found to be efficient according to the input-oriented
- BCC model. Metlife was only efficient in 2011 according to the input-oriented BCC. In other years, it
- only in both models in 2016 and not in other years. Anadolu was efficient in 2016 in both models.
- However, it was efficient in 2015 according to BCC model. In other years, it was found that it remained
- below the efficiency limit. Avivasa was found to be efficient between 2014 and 2016 in both models.
- However, it was inefficient between 2011 and 2013 in both models. It is determined that Allianz has a
- Ayhan, C., (2017), Türkiye'deki Sigortacılık Sektörünün Etkinlik Analizi Ve AB Ülkeleriyle Karşılaştırılması, Pamukkale Üniversitesi, Sosyal Bilimler Enstitüsü. (Yüksek Lisans Tezi), Denizli.
- Banker, R., Cooper, W. W., Seiford, L. M., Thrall, R. M., and Zhu, J., (2004), "Returns To Scale İn Different Dea Models", European Journal of Operational Research, C. 154, S. 2, ss.
- Bülbül, S. ve Akhisar, İ., (2005), Türk Sigorta Şirketlerinin Etkinliğinin Veri Zarflama Analizi İle Araştırılması, VII Ulusal Ekonometri ve İstatistik Sempozyumu (s. 1-12). İstanbul: İstanbul Üniversitesi.
- Çetintaş, H. ve Biçen, F., (2011), "Türkiye’de Sigorta Sektörünün Etkinlik Analizi", Tisk Akademi, 124-154.
- Çiftçi, H., (2004), "Türk Sigorta Sektörünün Sorunları: Dea Analizi İle Türk Sigorta Şirketlerinin Etkinlik Düzeylerinin Belirlenmesi", Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, C. 13, S. 1,
- Emeklilik Sektörü İçin Etkinlik Analizi: Türkiye Örneği (2004-2005),
- Kaplan, M. ve Çelik , T., (2007), "Türk Sigortacılık Sektöründe Etkinlik Ve Etkinliği Belirleyen Faktörler", İktisad İşletme ve Finans, C. 22, S. 253, ss.
- Karakaya, A., Kurtaran, A. ve Dağlı, H., (2014), "Bireysel Emeklilik Şirketlerinin Veri Zarflama Analizi İle Etkinlik Ölçümü: Türkiye Örneği", Yönetim ve Ekonomi Araştırmaları Dergisi,
- Karsak, E. ve İşcan, F, (2000), "Çimento Sektöründe Göreli Faaliyet Performanslarının Ağırlık Kısıtlamaları Ve Çapraz Etkinlik Kullanılarak Veri Zarflama Analizi İle", Endüstri Mühendisliği Dergisi, C. 11, S. 3, ss.
- Lorcu, F., (2008), Zarflama Analizi (Dea) İle Ve Avrupa Birliği Ülkelerinin Sağlık Alanındaki Etkinliklerinin Değerlendirilmesi, İstanbul Üniversitesi, Sosyal Bilimler Enstitüsü.
- Özaktaş Davarcıoğlu, F., "Hayat Dışı Sigorta Sektöründe Etkinlik Analizi: Türkiye Uygulaması (2002-2015)", Ç.Ü. Sosyal Bilimler Enstitüsü Dergisi, C.
- Özbek, A., (2015), "Analysis Of Private Pension Companies In Turkey By Eatwos", European Journal of Business and Management,
- Özcan, A. İ., (2011), "Türkiye'de
- Hayat Dışı Sigorta Sektörünün 2002-2009 Dönemi İtibariyle Etkinlik
- Özçelik, H. ve Kandemir, B., (2017), "Veri Zarflama Analizi Ve İmalat Sektöründe Bir Uygulama", Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 22, S. 43
- Özüdoğru, H., (2017), Sigorta Şirketlerinde Veri Zarflama Yöntemi İle Etkinlik Ölçme Üzerine Bir Araştırma", Üçüncü Sektör Sosyal Ekonomi,
- Salimi Altan, M., (2010), "Türk Sigortacılık Sektöründe Etkinlik: Veri Zarflama Analizi Yöntemi İle Bir Uygulama", Gazi Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi,
- Seyrek, İ. H. ve Ata, A., (2010), "Veri Zarflama Analizi Ve Veri Madenciliği İle Mevduat Bankalarında Etkinlik Ölçümü", BDDK Bankacılık ve Finansal Piyasalar,
- Tantan, S., Yolsal, H. and Gürbüz, A. O., (2000), "Efficiencey In Turkish Life Insurance Industry( Using Dea Approach)", European Financial Management Association Conference. Atina: Social Science Research Network.
- Teresa, M. and Garcia, M., (2010), "Efficiency Evaluation Of The Portuguese Pension Funds Management Companies", Journal Of International Financial Markets Intitutions& Money, C. 20, S. 3, ss.
- Tetik, S., (2003), "İşletme Performansını Belirlemede Veri Zarflama Analizi". İ.İ.B.F. Dergisi,
- Tone, K., (2001), "A SlacksBased Measure Of Efficiency In Data Envelopment Analysis", European Journal of Operational Research,
