Empirical Results The models used in this study have been introduced at the end of previous chapter. In this section, we present original results and interpretations concerning both of the observed models. Insert Table 3 Here 5.1 Life Insurance Penetration The results in Table 4 show that the variation of life insurance penetration across countries significantly and positively depends on income level, average years of schooling and health expenditure to GDP. These three variables show significant coefficients to the 1,5 or 10 per cent level in our baseline regression. Whereas the results for real interest rates, quasimon/M2 inflation, young dependency ratio, old dependency ratio, rule of law, control of corruption and government effectiveness are less robust.. As suggested in the previous studies, GDP per capita has a positive and significant influence on life insurance penetration. The results suggest that a 1% increase in GDP per capita is associated with an increase of about 0,0168 percentage points.in life insurance penetration. The results are consistent with the models of Campbell (1980) and Lewis (1989). Truett and Truett (1990), Browne and Kim (1993), Outreville (1996), and Beck and Webb (2002) obtain similar coefficients. The results underline the importance of a high level of education for life insurance consumption. The coefficient on average years of schooling indicating that the rise in average years of schooling by 1 year improves life insurance penetration by 0.0016 percentage points Reflecting the conflicting indications of previous studies that have sought to determine its effect, health expenditure expenditure appears to have a positive and significant influence on life insurance penetration. Thus 1% increase in health expenditure expenditure leads to 0.0123 percentage points rise in life insurance penetration. Hence, it would appear as in Browne and Kim (1993) that health expenditure reflects the high level of wealth of a country and should therefore be associated with higher life insurance demand. This result is consistent with Lewis (1989) and confirms the findings of Beenstock, Dickinson, and Khajuria (1986). Contrary to most previous studies, real interest rates, quasimon/M2, inflation, young dependency ratio, old dependency ratio, rule of law, control of corruption and government effectiveness cannot explain the variation in life insurance density across countries. As we expected, inflation and real interest rate is inversely related with penetration but are not significant. The relation between inflation and real interest rate with the demand proxies does not corroborate with earlier studies and hence we conclude that current interest rate and real interest rate or price situation does not affect in life insurance penetration. The value of quasi money to M2 ratio, produces an expected positive sign and can be an important source of growth in the insurance industry but it was found to be insignificant. Although the results of the regression showed that value of quasi money to M2 ratio is statistically insignificant this variable my be a crucial factor in increasing demand for life insurance. This might due to the fact that a more developed financial institutions can increase competition with other financial sectors, especially insurance companies. This assertion is particularly appropriate for banking-type products offered by life insurers. The links between this two sectors, for instance, in Baltic
www.ccsenet.org/ijef International Journal of Economics and Finance Vol. 4, No. 3; March 2012
ISSN 1916-971X E-ISSN 1916-9728 244
countries were observed going back to the end of 1990th (several life insurance companies were the bank subsidiaries in Estonia, Lithuania and Latvia), the cooperation between the two sectors in CSEE countries is still in its initial stage. The mentioned cooperation is known as bancassurance – expressed in acquiring the existing life insurance companies by banks or, what is more common, selling of insurance and banking products mutually through bank branches. The upward trend for this kind of services is justified by the positive experience of Western economies. 35% of sales in European life insurance market are accounted for bancassurance, which became a prevailing distribution channel for a number of Western economies including France, Spain, Italy and Belgium (Milliman, 2005). The negative relationship between young dependency ratio and life insurance demand is not surprising. We expected ambiguous relationship. As young population earns no salary, they are not prompted to buy protection against early death in order to substitute actual salaries. Moreover, they cannot afford savings products. The old dependency ratio has also expected sign but it was found to be insignificant. It suggests that rising old dependency ratio will increase the demand for both the mortality and the savings component of life insurance policies. While the theoretical work focuses mostly on the life insurance policies held by primary wage earners, life insurance policies held by retirees have gained importance in many developed countries. This conclusion was confirmed in our study where we had as a sample of former socialist countries in Central and South- Eastern Europe. The results in columns 1 indicate that out of our three indicators of institutional quality only the control of corruption is positively correlated with life insurance penetration, although is not significant. The coefficients on both the rule of law and government effectiveness are insignificant and have a negative sign. This can be interpreted as lack of evidence that these supply side deterninants are important. 5.2 Life Insurance Density Now, proceeding to the density regression, the results indicate the following relationship: income level, average years of schooling, health expenditure to GDP and rule of law have a significant positive impact on the demand for life insurance, inflation influence significant negatively impact. These results are very similar to the ones obtained for life insurance penetration, so that in the following we will concentrate on the differences. The important advantage of density regression is the significant impact of real personal income, which is highly supported by previous findings and shows that 1US dollars increase in income level of a person pushes life insurance density up by 11.56 US dollar. The level of education also positively determines the demand for life insurance, indicating that the rise in average years of schooling by 1 year improves life life insurance density by 0.15 percentage points. This is relatively large impact of this socioeconomic factor comparing to other researchers, which emphasizes the importance of education in life insurance demand. The coefficient of health expenditure is also positively determines the demand for life insurance.The hypothesis of a negative relationship, resulting from life insurance provided by social insurance programs substituting for private life insurance, is not supported by this study, postulates that 1 % increase in health expenditure results in 1,70 percentage points increase in life insurance demand. These results show that there is a greater influence on life insurance density on than was the case with life insurance penetration. The results from our three indicators of institutional quality only the rule of law is positively correlated and significant with life insurance density. The results do show evidence to support the hypothesis that quality of property right factors is determinants of life insurance consumption in economies. It indicates that uprise in ratio by 1% increase life insurance density by 2.210 percentage points. Contrary to most previous studies the coefficient on the inflation rate is significantly negative in all specifications. So 1% increase in inflation rate would reduce life insurance density by 1.041 percentage points. Such economic, demographic and institutional factors as real interest rates, quasimon/M2, young dependency ratio, old dependency ratio, control of corruption and government effectiveness do not explain variation in the demand for life insurance across the CSEE countries. 6. Conclusion In this paper we have analyzed the determinants of life insurance demand in panel of 14 countries in Central and South- Eastern Europe over the period 1998 - 2010, using two indicators of life insurance demand, life insurance penetration and life insurance density. Consistent with previous research, we find that life insurance penetration and life insurance density increase with higher per-capita income. The results indicate that, increase in per-capita income level have the robustly impact the
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Published by Canadian Center of Science and Education 245
life insurance demand. As overall income level and the share of middle class rises, we can expect demand for life insurance to rise too. The analysis show that from economic variables QuasiMon/M2 have a positive but not significant effect on life insurance demand. But in our opinion as bancassurance will continue growing in the CSEE and, more important, in the CSEE countries and occupy its share in the life insurance products, the change in this relationship is expected. Although bancassurance is in its initial stage in CSEE countries, the tendency towards its growth is observed due to increase in consumers’ crediting activity of the banks The results also imply that real interest rates do not have robust link on life insurance density. Positive impact of real interest rate on the life insurance penetration in the selected countries may indicate the awareness of potential consumers about the benefits of life insurance and negligence to the
ประจักษ์ผลรุ่นที่ใช้ในการศึกษานี้ได้รับการแนะนำในตอนท้ายของบทก่อนหน้า ในส่วนนี้ เรานำผลลัพธ์และตีความเกี่ยวกับทั้งสองรูปแบบสังเกต แทรกตาราง 3 นี่ 5.1 ประกันชีวิตเจาะผลในตาราง 4 แสดงว่า รูปแบบของประกันชีวิตเจาะทั่วประเทศอย่างมีนัยสำคัญ และบวกขึ้นอยู่กับระดับรายได้ เฉลี่ยปีรายจ่ายของการศึกษาและสุขภาพให้ GDP ตัวแปรเหล่านี้สามแสดงสัมประสิทธิ์สำคัญไป 1.5 ระดับร้อยละ 10 ของเราถดถอยหลัก ในขณะที่ผลลัพธ์สำหรับอัตราดอกเบี้ยที่แท้จริง quasimon/M2 อัตราเงินเฟ้อ อัตราการขึ้นต่อกันของหนุ่มสาว อัตรา ส่วนอ้างอิงเก่า นิติธรรม ควบคุมประสิทธิภาพความเสียหายและรัฐบาลจะไม่แข็งแกร่ง... เป็นข้อเสนอแนะในการศึกษาก่อนหน้านี้ GDP มีอิทธิพลแบบบวก และที่สำคัญประกันชีวิตเจาะต่อ capita ผลการแนะนำ 1% เพิ่มขึ้นใน GDP ต่อ capita ว่าเกี่ยวข้องกับการเพิ่มขึ้นของเกี่ยวกับเปอร์เซ็นต์ 0,0168 points.in ประกันชีวิตเจาะ ผลลัพธ์ไม่สอดคล้องกับรุ่นของ Campbell (1980) และลูอิส (1989) และ Truett, Truett (1990) และ Browne คิม (1993) และ Outreville (1996), และเบ็คเวบบ์ (2002) รับคล้ายสัมประสิทธิ์ ผลลัพธ์ขีดเส้นใต้ความสำคัญของการศึกษาการใช้ประกันชีวิตในระดับสูง ค่าสัมประสิทธิ์เฉลี่ยปีประถมบอกว่า เพิ่มขึ้นในปีเฉลี่ยของประถมปีที่ 1 ปรับปรุงประกันชีวิตเจาะ 0.0016 เปอร์เซ็นต์จุดสะท้อนอย่างนั้นขัดแย้งกันของการศึกษาก่อนหน้านี้ที่ได้มีการกำหนดผลของ รายจ่ายรายจ่ายสุขภาพดูเหมือนจะ มีอิทธิพลแบบบวก และที่สำคัญประกันชีวิตเจาะ จึง เพิ่มขึ้น 1% ของรายจ่ายของรายจ่ายสุขภาพนำไป 0.0123 เปอร์เซ็นต์จุดเพิ่มขึ้นการเจาะประกันชีวิต ดังนั้น มันจะปรากฏใน Browne และคิม (1993) ว่า รายจ่ายสุขภาพสะท้อนสูงระดับของประเทศ และดังนั้นจึงควรเชื่อมโยงกับความต้องการประกันชีวิตสูง ผลนี้สอดคล้องกับลูอิส (1989) และยืนยันผลการวิจัยของ Beenstock สัน และ Khajuria (1986) ขัดกับส่วนใหญ่การศึกษาก่อนหน้านี้ อัตราดอกเบี้ยที่แท้จริง quasimon/M2 เงินเฟ้อ อัตราส่วนพึ่งพาสาว อัตราส่วนอ้างอิงเก่า นิติธรรม การควบคุมความเสียหายและรัฐบาลประสิทธิภาพไม่อธิบายการเปลี่ยนแปลงในความหนาแน่นของประกันชีวิตทั่วประเทศ ตามเรา อัตราเงินเฟ้อและอัตราดอกเบี้ยที่แท้จริง inversely ที่เกี่ยวข้องกับเจาะ ได้ไม่สำคัญ ความสัมพันธ์ระหว่างเงินเฟ้อและอัตราดอกเบี้ยที่แท้จริงกับผู้รับมอบฉันทะต้อง corroborate ไม่ มีการศึกษาก่อนหน้านี้ และดังนั้น เราสรุปว่า ปัจจุบันอัตราดอกเบี้ย และอัตราดอกเบี้ยที่แท้จริง หรือสถานการณ์ราคาไม่มีผลในการเจาะประกันชีวิต ค่าเงินเสมือนต่อ M2 ผลิตเครื่องบวกการคาด และสามารถเป็นแหล่งสำคัญของการเจริญเติบโตในธุรกิจประกันภัย แต่พบเป็นสำคัญ แม้ว่าผลของการถดถอยแสดงให้เห็นว่าค่าเงินเสมือน M2 อัตราส่วนสำคัญทางสถิติตัวแปรนี้ของฉันเป็นปัจจัยสำคัญในการเพิ่มความต้องการสำหรับการประกันชีวิต นี้อาจเนื่องจากข้อเท็จจริงที่ว่าสถาบันการเงินที่พัฒนามากขึ้นสามารถเพิ่มการแข่งขันกับภาคอื่น ๆ การเงิน บริษัทประกันโดยเฉพาะอย่างยิ่ง นี้เหมาะอย่างยิ่งสำหรับลูกค้าประเภทผลิตภัณฑ์ที่นำเสนอ โดยญี่ปุ่นชีวิต การเชื่อมโยงระหว่างนี้ทั้งสองภาค ตัวอย่าง ในบอลติก www.ccsenet.org/ijef International Journal of Economics and Finance Vol. 4, No. 3; March 2012 ISSN 1916-971X E-ISSN 1916-9728 244countries were observed going back to the end of 1990th (several life insurance companies were the bank subsidiaries in Estonia, Lithuania and Latvia), the cooperation between the two sectors in CSEE countries is still in its initial stage. The mentioned cooperation is known as bancassurance – expressed in acquiring the existing life insurance companies by banks or, what is more common, selling of insurance and banking products mutually through bank branches. The upward trend for this kind of services is justified by the positive experience of Western economies. 35% of sales in European life insurance market are accounted for bancassurance, which became a prevailing distribution channel for a number of Western economies including France, Spain, Italy and Belgium (Milliman, 2005). The negative relationship between young dependency ratio and life insurance demand is not surprising. We expected ambiguous relationship. As young population earns no salary, they are not prompted to buy protection against early death in order to substitute actual salaries. Moreover, they cannot afford savings products. The old dependency ratio has also expected sign but it was found to be insignificant. It suggests that rising old dependency ratio will increase the demand for both the mortality and the savings component of life insurance policies. While the theoretical work focuses mostly on the life insurance policies held by primary wage earners, life insurance policies held by retirees have gained importance in many developed countries. This conclusion was confirmed in our study where we had as a sample of former socialist countries in Central and South- Eastern Europe. The results in columns 1 indicate that out of our three indicators of institutional quality only the control of corruption is positively correlated with life insurance penetration, although is not significant. The coefficients on both the rule of law and government effectiveness are insignificant and have a negative sign. This can be interpreted as lack of evidence that these supply side deterninants are important. 5.2 Life Insurance Density Now, proceeding to the density regression, the results indicate the following relationship: income level, average years of schooling, health expenditure to GDP and rule of law have a significant positive impact on the demand for life insurance, inflation influence significant negatively impact. These results are very similar to the ones obtained for life insurance penetration, so that in the following we will concentrate on the differences. The important advantage of density regression is the significant impact of real personal income, which is highly supported by previous findings and shows that 1US dollars increase in income level of a person pushes life insurance density up by 11.56 US dollar. The level of education also positively determines the demand for life insurance, indicating that the rise in average years of schooling by 1 year improves life life insurance density by 0.15 percentage points. This is relatively large impact of this socioeconomic factor comparing to other researchers, which emphasizes the importance of education in life insurance demand. The coefficient of health expenditure is also positively determines the demand for life insurance.The hypothesis of a negative relationship, resulting from life insurance provided by social insurance programs substituting for private life insurance, is not supported by this study, postulates that 1 % increase in health expenditure results in 1,70 percentage points increase in life insurance demand. These results show that there is a greater influence on life insurance density on than was the case with life insurance penetration. The results from our three indicators of institutional quality only the rule of law is positively correlated and significant with life insurance density. The results do show evidence to support the hypothesis that quality of property right factors is determinants of life insurance consumption in economies. It indicates that uprise in ratio by 1% increase life insurance density by 2.210 percentage points. Contrary to most previous studies the coefficient on the inflation rate is significantly negative in all specifications. So 1% increase in inflation rate would reduce life insurance density by 1.041 percentage points. Such economic, demographic and institutional factors as real interest rates, quasimon/M2, young dependency ratio, old dependency ratio, control of corruption and government effectiveness do not explain variation in the demand for life insurance across the CSEE countries. 6. Conclusion In this paper we have analyzed the determinants of life insurance demand in panel of 14 countries in Central and South- Eastern Europe over the period 1998 - 2010, using two indicators of life insurance demand, life insurance penetration and life insurance density. Consistent with previous research, we find that life insurance penetration and life insurance density increase with higher per-capita income. The results indicate that, increase in per-capita income level have the robustly impact the www.ccsenet.org/ijef International Journal of Economics and Finance Vol. 4, No. 3; March 2012 Published by Canadian Center of Science and Education 245life insurance demand. As overall income level and the share of middle class rises, we can expect demand for life insurance to rise too. The analysis show that from economic variables QuasiMon/M2 have a positive but not significant effect on life insurance demand. But in our opinion as bancassurance will continue growing in the CSEE and, more important, in the CSEE countries and occupy its share in the life insurance products, the change in this relationship is expected. Although bancassurance is in its initial stage in CSEE countries, the tendency towards its growth is observed due to increase in consumers’ crediting activity of the banks The results also imply that real interest rates do not have robust link on life insurance density. Positive impact of real interest rate on the life insurance penetration in the selected countries may indicate the awareness of potential consumers about the benefits of life insurance and negligence to the
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