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ains alaysiana 43(9)(2014): wo-tage ethod in dentifying the xogenous actors of nsurers isk and nvestment anagement fficiency (aedah ua-eringkat dalam engenal asti aktor uaran erhadap ecekapan
ains alaysiana 43(9)(2014): wo-tage ethod in dentifying the xogenous actors of nsurers isk and nvestment anagement fficiency (aedah ua-eringkat dalam engenal asti aktor uaran erhadap ecekapan engurusan isiko dan elaburan enanggung nsurans) UY Y*, ZU YU, & ZU he objective of this study was to identify the exogenous variables of risk and investment management efficiency by using a two-stage data envelopment analysis () method. he first stage involves obtaining the efficiency scores of risk and investment management via that requires only the traditional inputs and outputs. n the second stage, the obit regression analysis is conducted in which the efficiency score obtained from the first stage is treated as a dependent variable, while the exogenous factors are considered to be independent variables. he exogenous factors consist of operating systems, organizational form, consumer preference and size. he results showed that the mutual company as well as the takaful system demonstrate better risk management performance than their stock and conventional system counterparts. n addition, size is also a significant indicator for risk management efficiency in which the larger insurer/ takaful operator exhibits better risk management performance than the smaller one. owever, consumer preference is found to be insignificantly correlated with the efficiency of risk management. n contrast, with risk management, organizational form, operating system and size are not indicators of the investment management efficiency, but consumer preference is significantly and positively associated with investment management efficiency. eywords: fficiency; exogenous factors; risk and investment management; two-stage bjektif kajian ini adalah untuk mengenal pasti pemboleh ubah luaran terhadap kecekapan pengurusan risiko dan pelaburan dengan menggunakan kaedah analisis penyampulan data () dua-peringkat. eringkat pertama melibatkan perolehan skor kecekapan pengurusan risiko dan pelaburan melalui yang hanya memerlukan input dan output tradisi. ada peringkat kedua, analisis regresi obit dijalankan dengan skor kecekapan yang diperoleh dari peringkat pertama dilayan sebagai pemboleh ubah bersandar, manakala faktor luaran dipertimbangkan sebagai pemboleh ubah bebas. aktor luaran terdiri daripada sistem operasi, bentuk organisasi, keutamaan pengguna dan saiz. eputusan menunjukkan bahawa syarikat bersama, begitu juga sistem takaful mempunyai prestasi pengurusan risiko yang lebih baik berbanding rakan-rakan syarikat stok dan sistem konvensional mereka. i samping itu, saiz juga merupakan penunjuk yang signifikan bagi kecekapan pengurusan risiko syarikat insurans/pengendali takaful yang lebih besar mempamerkan prestasi pengurusan risiko yang lebih baik daripada syarikat yang lebih kecil. Walau bagaimanapun, keutamaan pengguna didapati tidak berkorelasi secara signifikan dengan kecekapan pengurusan risiko. erbeza dengan pengurusan risiko, bentuk organisasi, sistem operasi dan saiz bukan merupakan penunjuk kepada kecekapan pengurusan pelaburan, tetapi keutamaan pengguna mempunyai hubungan yang signifikan dan positif dengan kecekapan pengurusan pelaburan. ata kunci: dua-peringkat; faktor luaran; kecekapan; pengurusan risiko dan pelaburan U Underwriting, pricing and claims handling are the technical elements of the insurance production process, which is referred to as manufacturing by lack and kipper (2000). uring the process, there is a need for the insurance company to make decisions relevant to risk, capital and investment. he mismanagement of these elements can affect the whole system both within and outside the insurer/takaful operator, thus making the risk and investment management function very important to insurance/takaful business. his study has identified four conditions to motivate insurers/takaful operators in enhancing their risk and investment management. irst, is the increasing number of cases of insolvency among insurers. nsolvency can happen even to large insurers that have been involved in the business for a long time. n average, the insolvency problem is caused by the inefficiency of the risk management function. econd, is the uncertainty of financial markets and fluctuation of interest rates. oth of these factors affect the investment portfolio of insurers, which is highly important in considering the appropriate matching between their assets and liabilities. hird, globalization has intensified competition. Unfortunately for insurers, competition is keen among themselves as well 1440 as from other financial institutions, such as banks, mutual fund organizations, finance companies and securities firms. ast but not least, consumer preferences have changed to a more complex product with a small margin but higher risk. ecently, protection-based products seem to have been overtaken by investment-based products. lthough the risk is transferred to policyholders in investment-based products, the attractive investment element makes it more interesting. learly, based on these four reasons, insurers/ takaful operators must respond with far greater efficiency in their risk and investment management. owever, the efficiency of risk and investment management depends on various exogenous factors. hese factors could be macroeconomics or/and firm-specific variables. hus, the main objective of this study was to identify the exogenous variables that affect the risk and investment management efficiency of life insurers as well as takaful operators, since alaysia has two different insurance markets, namely, conventional life insurance and takaful. two-stage data development analysis () method is most suitable to perform this analysis. he first stage involves obtaining the efficiency scores of risk and investment management via the slack-based measure () - that requires only the traditional inputs and outputs. n the second stage, the obit regression analysis is conducted in which the efficiency score obtained from the first stage is treated as a dependent variable, while the exogenous factors are treated as independent variables. he exogenous variables that are considered in this study are limited to non-financial firm-specific variables that are not the traditional inputs and assumed to not be under the control of managers (oelli et al. 2005). hese variables include organizational form, operating system, consumer preference and size. his study contributes to the literature of efficiency in terms of two elements. irst, this study will investigate exogenous factors that affect the efficiency of the primary functions of an insurance company, known as risk and investment management functions. his is in contrast to many previous insurance efficiency studies, which mostly focused on the causes that affect the insurance firms as a whole. inally, it is very constructive to engage takaful operators in this study because of the privileges of the insurance industry in this country that have two different operating systems, namely, conventional insurance and takaful. urthermore, very few studies have been undertaken on the efficiency of the risk and investment management function among takaful operators. he paper unfolds as follows. he following section discusses the literature on previous studies and the subsequent section describes the methodology and data. he next section discusses the experimental results and the final section concludes the study. U VW n recent years, a considerable amount of literature has been published concerning the efficiency of insurance firms. n measuring the firm s efficiency, erger and umphrey (1997) and ummins (1999) suggested that frontier efficiency methodologies as a better alternative. hey clarified that the frontier efficiency methodologies seemed very important and this new benchmarking techniques measured the firm performance relative to best practice frontiers derived from firms in the industry or branches within financial firms. he advantage of such measures, as compared to financial ratio analysis, is their ability to summarize firm performance in a single statistic that controls for differences among firms using a sophisticated multidimensional framework (ummins 1999). oreover, ummins and Weiss (2000) commented that all economic hypotheses related to insurers about such matters as economies of scope and scale, distribution systems, organizational forms and the effect of & will not be convincing unless they applied the frontier-based performance measures. frontier efficiency methodology that has become increasingly important is the which is first introduced by harnes et al. (1978). he centre attention of is largely on the technological aspects of production correspondences, thus it can be applied to calculate technical and scale efficiency without requiring estimates of input and output prices. n the other hand, if the data on input prices are available, cost efficiency also can be measured by using (ly et al. 1990; errier & ovell 1990). ummins and Weiss (2000) write, ntuitively, the method involves searching for a convex combination of firms in the industry that dominate a given firm. hey further explained that these firms form the given firm s reference set and if the reference set comprises only of the firm itself, it is said self-efficient and has efficiency score equal to 1. onversely, if other firms instituted the dominant set, then the firm s efficiency is less than 1 and thus considered as inefficient. ubsequently, they were extended to find the cause of the difference in efficiency between decision making units (Us) by associating the inefficiency measurement with the exogenous factors. hese exogenous environmental factors include the operating system, size, changes in consumer preference, labour relations, ownership differences, location characteristics, the legal system and government regulations and organizational form (ried et al. 1999) ccordingly, many previous researchers had investigated the empirical relationship between insurance firm efficiency and organizational form and their findings were mixed. rockett et al. (2005, 2004), ummins et al. (2009) and ussels and Ward (2007) supported the expense preference hypothesis by showing that the stock insurers were more efficient than mutual insurers. n contrast, the findings by ttiea et al. (2009), arr (1997), ckles (2003) and ling and uhnen (2010) were not consistent with the expense preference behaviour hypothesis. eanwhile, ummins and Zi (1997), ukuyama (1997), ardner and race (1993) and reene and egal (2004) found mutual and stock insurers to be equally efficient. 1441 biding by the concept of scale and scope economies, Yao et al. (2007) was convinced that larger insurers were more efficient than smaller insurers. he same results were obtained by ummins and Zi (1997), iacon et al. (2002), ckles (2003), ardner and race (1993), ao and hou (2005), lumpes (2007) and eador et al. (1997). imilarly, ao (2008) proved that, on average, the large firms experienced higher cost efficiency than the smaller firms. n addition, arr et al. (1999) concluded that large insurers are more efficient because they have the advantage of distribution channels and market power. owever, ummins et al. (2009) formed a different conclusion in which the larger insurers indicate lower efficiency changes compared with smaller insurers, while Yuengert (1993) found that size and efficiency were significantly uncorrelated. lobalization, technological change and shifting consumer preferences have led to firms adopting a number of innovative business strategies (era 2003). mpirical evidence provided by eador et al. (1997) suggested that firms that diversify across multiple insurance as well as investment insurance products, can enhance their X-efficiency more than a focused production strategy firm. his result is consistent with the prediction of haled et al. (2001) who studied the scope and scale economies of the ew Zealand insurance industry. n contrast, ao (2007) indicated that product mix could not help the life insurers in aiwan to increase their level of efficiency. imilarly, takaful operators with limited product lines were experiencing higher cost efficiency than takaful operators with a variety of product lines (bdul ader et al. 2010). t seems that only a few of the previous studies correlate the legal system with the efficiency of the insurance industry. his situation may be due to the fact that many countries in the world apply the same legal system for all insurance companies operating in the country. owever, in some countries in sia, urope and frica, there are two insurance systems operating in the market, namely, conventional insurance system and slamic insurance system (takaful). n this respect, ling and uhnen (2010) examined the effects of civil, mixed and common law on the efficiency of the insurance industry internationally. heir study proved that the efficiency of the insurer was not affected by the type of legal system practiced in the country. t is possible to adjust these exogenous variables accordingly to compare their relationship with the efficiency of Us. here are four common techniques in which these variables can be accommodated in (oelli et al. 2005). he first technique was introduced by anker and orey (1986). he second approach is the so-called frontier separation approach, established by harnes et al. (1981). he third method is known as the all-in-one approach (ried et al. 1999), while the fourth is commonly known as the two-stage approach. he twostage approach has, so far, been the most recommended as it likely addresses the problems encountered in the above methods (oelli et al. 2005). he other advantages suggested by oelli et al. (2005) are that this method is easy to calculate and simple and enable one to perform the statistical test in determining the significant exogenous variables affecting efficiency. or the purpose of this study, the selection of the firms is restricted to direct insurers (composite and life) and takaful operators operating in alaysia. oreover, data for this study are limited to the life and family takaful business as well as investment-linked business. or the composite insurers that offer general and life products, the data is segregated between the two lines of business and can be obtained from the financial report of the companies. he study also totally excluded the new entrants during the study periods but maintained the firms involved in merger and acquisition activities. inally, this left a sample of 20 firms, consisting of 7 life insurers, 9 composite insurers and 4 takaful operators that were consistently present throughout the period 2003 to his sample represents about 91% of the total players for the study period and accounts for approximately more than two-thirds of the total assets of the life insurance fund as well as the family takaful fund in the overall life insurance and takaful industry, respectively. ata on the financial statement of the firms is adopted from the ompanies ommission of alaysia. he firms under observation according to the type of business are depicted in able 1. he 5 year time span of is considered as this period is after the financial crisis of 2001 and 2002 and before the global credit crunch in s Zurich inancial ervices (2007) reported that when the stock market dropped substantially between 2000 and 2002 and the level of corporate bond weakens, the insurance company has suffered severe losses in their investment portfolios. he same thing happened during the credit crisis in 2008, where insurers posted U239 billion in write downs and credit losses worldwide from the global credit crunch in hese extreme cases have to be excluded in order to avoid biased results. n addition, over the years, various insurance companies had been coming and going out of the alaysian insurance industry. here are also quite a number of merger and acquisition (&) activities within the industry. his has posted a challenge to get a most consistent set of data representing the highest percent of the players in the industry. he larger the number of years would imply more challenge to achieve that. asically, the study excluded the new entrants during the study periods but maintained the firms involved in & activities. W- V Y () his study will implement the two-stage method in order to identify the exogenous factors that affect the risk and investment management efficiency of insurers/takaful he list of insurer/takaful operator under observation o. ame of irm ype of usiness llianz ife nsurance alaysia erhad () Uni. sia ife ssurance erhad () anulife nsurance (alaysia) erhad() sia ife () erhad () ayban ife ssurance hd () reat astern ife ssurance (alaysia) erhad () ommerce ife ssurance erhad () ahan nsurance alaysia erhad () ong eong ssurance erhad () mssuranceerhad () Zurich nsurance erhad () alaysian ational nsurance erhad () alaysian ssurance lliance erhad () akaful asionaldn. hd. () akaful khlas alaysia dn. hd. () yarikat akaful alaysia erhad () aybanakafulerhad () rudential ssurance alaysia erhad () nsurance erhad () merican nternational ssurance ompany, td () ife ife ife ife ife ife ife operators. ccording to oelli et al. (2005), the first stage involves obtaining the efficiency scores via, which only requires the traditional inputs and outputs. n the second stage, the regression analysis is conducted in which the efficiency score obtained from the first stage is treated as a dependent variable, while the exogenous factors are independent variables. he second-stage regression analysis is used to determine separately the effect of exogenous variables on efficiency. hey also explained that the exogenous variables include all the factors that cannot be treated as traditional inputs and are not assumed to be directly under the control of managers. n the second stage, the obit regression analysis is used in order to obtain the exogenous factors that influence the risk and investment management efficiency of the insurers/takaful operators (anker & atarajan 2008; oelli et al. 2005; asiouras 2008). he first stage had been undertaken separately, which is slack-based measure data envelopment analysis (-). his study focuses only on the second-stage regression analysis. owever, the firststage - will also be explained in order to facilitate understanding in the second-stage. - he model is a variant of the additive model, which was first presented by one (2001). s in the additive model, the differs from the harnes, ooper and hodes () and anker, harnes and ooper () model as it combines both orientations in a single model, i.e. input-oriented model and output-oriented model. focuses on maximizing the non-zero slacks in the optimal objective. he slacks give the estimate of input excess and output shortfalls that could be improved without worsening any other input and output. ccording to one (2001), for each U j ( and input matric used by U j and amount of output matric yielded by U j, with the assumption, the data set is positive and, the production possibility set for is defined by: = {(x, y) ǀx Xλ,y Yλ, λ 0} (1) where λ is a nonnegative vector in n. n an attempt to estimate the efficiency of a U (x o, y o ), the following fractional program () is formulated: subject to x o = Xλ j + s y o = Yλ j s + 0 λ, s, s + (2) hen, (2) is replaced by the following linear program () in t,, + and Λ: (3) 1443 subject to tx o = XΛ + ty o = YΛ + Λ,, + 0; t 0 he constraint t 0 make the transformation is reversible, thus, the is equivalent to (ooper et al. 2007). f the optimal solution of would be (τ *, t *, Λ *, *, +* ), then, the optimal solution of will be defined by (p * = τ *, λ * = Λ * /t *, s * = * /t*, s +* = +* /t * ). herefore, based on this definition, a U (x o, y o ) can be decided as -efficient if and only if ρ * = 1. his condition is achieved when s * = 0 and s +* = 0, i.e. the value of all slack variables is equal to zero. oth Us in this st
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