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Insurance Sector Development & Economic Growth in Malaysia

Aug 19, 2014



To investigate the link between the insurance sector development and economic growth of Malaysia and to fill a gap in the current finance-growth nexus.
Research Based.

  • According to the finance-growth nexus theory, financial development promotes economic growth through channels of marginal productivity of capital, efficiency of channeling savings to investment, saving rate and technological innovation (Levine, 1997). Financial intermediaries companies such as insurance realized economic growth. They play an important role in economic growth as they are the risk management tool for individuals and companies. In line with the increasing share in the aggregate financial sector in almost every developing country, the importance of insurance is growing compared from the past. SNH
  • Widening income disparity and globalization are the issues that increase possibleimpact on the economic development as insurancecompanies are one of the biggest institutional investors in stock, bond and real estate markets. Besides that, it is important for the stability of the economy to have access on insuranceservices and this can make the business participants accept aggravated risk. Insurance companies are playing an important role by enhancing internal cash flow at the assured and by creating large amount of assets placed on the capital market. SNH
  • As we all know, insurance sector is one of the industries that contributingto Malaysia since1988.The aim is to support the economythrough the financial systembesides providingMalaysian consumerswith world class product and services. According to BNM, the market penetration increasedsignificantlyfromthe total insurance fund assets and average asset base per insurance fund increasedby 545.9% and 521% respectivelyduringthe period from 1988 to 1999.It shows that insurance sector has played a role in expandingeconomic activitiesand growth. However,there is still lack of clear viewon the impact, rationale,and relationship betweenthe sector and Malaysiaseconomy. This study was emphasizingon the relationand focusing the matter specificallyin Malaysia. SNH
  • The main objective of this study is to investigate the link between the insurance sector development and economic growth of Malaysia and to fill a gap in the current finance-growth nexus. SNH
  • To define the purpose of insurance sector in Malaysia To identify whether the development of the sector help economic growth To know how the sector development give impacts towards economic growth To know the relevancy of the sector development for coming years To determine the ways to encourage the sector development effectively SNH
  • What are the purposes of insurance sector in Malaysia? Does the development of the sector help economic growth? How does the sector development influence economic growth? Should government continuethe sector development? What are the ways to develop the sector in more effectively? SNH
  • It is expected that all the explanatory variables except inflation rate (INF) should be positively related to GDP while inflation rate (INF) is expected to be negative in relation to GDP SNH
  • Hughes (1996) The impact of unemployment insurance on unemployment duration. The unemployment insurance benefit give more impact to high wage group as compared to counterpart. The study reveals that individual with high wage experience shorter unemployment period. SNH
  • Ward and Zurbruegg (2000) Granger causality toanalyze the relationships betweeninsurance premiums and economic growthfrom nine OECD countries from1961 to 1996. The relationships betweeninsurance market andeconomic growthis dependent oncountry and whether the insurance industry promote economic growthdepends on a number of national circumstance. Lim and Haberman (2003) The interest rate for savings depositsandprice is significant inthe equation. The positive signfor the interest rate puzzles the authors. This couldbe in line withfindings of Webb et al. (2002) whofoundthe best results when insurance andbanking sector are combinedinthe estimates. SNH
  • Arena and Marco (2006) They used the average rate of real per capita GDP growth. Life and non-life insurance premium has a positive and significant impact on the economic growth. In the case of life insurance the impact on economic growth is only experience by high-income countries only. The result is also being the same for the non-life insurance. SNH
  • Marijuana et al. (2009) Examinedthe relationshipbetween insurance sector development and economic growthin 10 transition EuropeanUnion member countries. Three different insurance variableswere used;life, non-life andtotal insurance and other control variables like education, openness, inflation, investment, bank credit, stock capitalization. insurance sector development positively and significantly affectseconomic growth. Oke and Ojo (2012) Examinedthe short and long-run relationshipsbetweeneconomic growth and insurance sector developmentinthe Nigerianeconomy. Gross domestic product (GDP) was usedas proxy for the level of economicgrowth. The result shows that insurance sector growthand development positively and significantly affects economicgrowth. However, fromthe Granger causality test, it shows that the influence of insurance sector growthoneconomic growthwas limiteddue tocultural, attitudinal traits and values in the country. SNH
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  • GDP= Bo + B1ALI + B2INF + B3NLA + SNH
  • We estimate standardgrowthequationusing adataset over the period 2000-2010. Basedfrom the main journal that we have studied, the model adopted gross domestic product (GDP) growthas dependent variable while life, non-lifeandtotal insurance as independent variable. The model usedis modifiedby using gross domestic product (GDP) at market price as the dependent variable, furthermore the insurance assets is dividedintoassets of life andnon-life insurance. Inflationrate is chosenas the control variable. SNH
  • GDP LFE GNRL INF Mean 22756.23 83815.95 19155.19 2.150909 Median 23388.50 79739.55 18689.23 1.685000 Maximum 25008.00 153877.2 26975.62 8.200000 Minimum 19849.92 33950.00 13944.00 -2.000000 Std. Dev. 1476.065 35850.97 3936.271 1.789125 Skewness -0.770812 0.307370 0.419243 1.248944 Kurtosis 2.294566 1.888529 2.012071 6.636015 Jarque-Bera 5.269441 2.957668 3.078281 35.67675 Probability 0.071739 0.227903 0.214565 0.000000 Sum 1001274. 3687902. 842828.4 94.64000 Sum Sq. Dev. 93687011 5.53E+10 6.66E+08 137.6416 Observations 44 44 44 44 SNH
  • GDP LFE GNRL INF GDP 1.000000 0.711388 0.681082 0.317363 LFE 0.711388 1.000000 0.997031 0.172067 GNRL 0.681082 0.997031 1.000000 0.153563 INF 0.317363 0.172067 0.153563 1.000000 SNH
  • All variables exceptthe inflation rate (INF) are positivelycorrelated with the gross domestic product (GDP) There is a relationship betweenlife insurance total assets and generalinsurance total assets with gross domesticproduct where the value for lifeinsurance total assets is 0.711and the value for general insurance total assets is 0.681 SNH
  • Dependent Variable: GDP Method: Least Squares Date: 11/22/12 Time: 15:10 Sample: 2000Q1 2010Q4 Included observations: 44 SNH
  • Variable Coefficient Std. Error t-Statistic Prob. LFE 0.208745 0.051407 4.060603 0.0002 GNRL -1.647054 0.466764 -3.528664 0.0011 INF 98.55762 80.27478 1.227753 0.2267 C 36597.70 4699.812 7.787056 0.0000 R-squared 0.653196 Mean dependent var 22756.23 Adjusted R-squared 0.627186 S.D. dependent var 1476.065 S.E. of regression 901.2635 Akaike info criterion 16.53198 Sum squared resid 32491037 Schwarz criterion 16.69418 Log likelihood -359.7036 F-statistic 25.11297 Durbin-Watson stat 0.523075 Prob(F-statistic) 0.000000 SNH
  • The R-squaredis 0.6531 which shows that 65.31% of the GDP can be explainedby the 3 independent variables. The t-Statistic for lifeinsurancetotal asset is 4.060 whichindicate that the variable is significant. Same goes togeneral insurance total asset, the value of t-Statistic is -3.528. The negative signof the value can be ignored. However the t-Statistic for inflationrate is less than2.0, therefore the variable is not significant. SNH
  • The Durbin Watson statistic falls on 0.523which indicates a rejectH0 with the evidence of positive correlations betweenthe variables SNH
  • Using the data of the total asset of both lifeand non-life insurance from the period of 2000-2010,we examinedthe insurance sector contribution towards the economicgrowth