Insurance penetration and economic growth nexus: Cross-country evidence from ASEAN

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Abstract

This paper investigates whether there are Granger causal relationships between insurance market penetration, broad money, stock-market capitalization, and economic growth, using panel data for the Association of South East Asian Nations (ASEAN) Regional Forum (ARF) countries for the 1988–2012 period. Using a multivariate framework, we show that all the variables are cointegrated and reveal a network of causal connections, including short-run bidirectional causality between insurance market penetration and economic growth. Recommendations based on this study include establishing a sound regulatory framework for a country's insurance industry, and introducing professional education and certification of insurance personnel to ensure adherence to global best practices and standards. Moreover, opening up a country's domestic insurance market to larger foreign players can ensure a wider choice of cost-effective, quality insurance.

Graphical abstract

Note 1: GDP is the per capita economic growth rate; BRM is broad money; SMC is stock market capitalization; and INS is insurance market penetration (various measures, as per text: LIP, NIP, or TIP).

Note 2: LIP is life insurance penetration; NIP is non-life insurance penetration; and TIP is total insurance (life and non-life) penetration.

Note 3: H1A: INS Granger-causes GDP; H1B: GDP Granger-causes INS; H2A: BRM Granger-causes GDP; H2B: GDP Granger-causes BRM; H3A: SMC Granger-causes GDP; H3B: GDP Granger-causes SMC; H4A: INS Granger-causes BRM; H4B: BRM Granger-causes INS; H5A: INS Granger-causes SMC; H5B: SMC Granger-causes INS; H6A: BRM Granger-causes SMC; and H6B: SMC Granger-causes BRM.

Note 4: Possible Granger causal relationships between any two variables are tested in the presence of the other two variables.

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Introduction

A growing strand of the financial economics literature shows the transition to high and sustained economic growth is preceded by the emergence of modern flexible financial systems, a process called ‘financial diffusion.’ So, well-managed public finances, a stable money supply, central banks, banking systems, securities markets and sound insurance markets causally predate economic development. And the studies show that financial diffusion is important even in small economies; that financial development fosters development by mobilizing savings, mitigating risks and helping to evolve legal and regulatory institutions (for instance, Andersson et al., 2010, Bolbol et al., 2005, Colombage, 2009). But the role of insurance markets in economic growth has been less thoroughly examined than the role of banks and stock markets (Arena, 2008, Chang et al., 2013, Lee et al., 2013a, Lee et al., 2013b, Lee et al., 2013c, Chen et al., 2013).

The importance1 of the insurance–economic growth relationship2 has been recognized in the literature (Beck and Webb, 2003, Guochen and Wei, 2012, Lee et al., 2013a, Lee et al., 2013b, Lee et al., 2013c). Insurance contributes3 to the economy in many ways, both directly and indirectly, to sustain high economic growth. Hence, insurance,4 like other financial services, has grown significantly in importance in ensuring sustainable economic growth (Holsboer, 1999).

Recent studies document positive relationships between insurance penetration and economic growth (for instance, Ward and Zurbruegg, 2000) but neglect the direction(s) of causality. Thus, our challenge here is to advance the research beyond documenting correlations to examining the causal relationship between the development of the insurance industry and economic growth (for instance, Lee et al., 2013a, Lee et al., 2013b, Lee et al., 2013c). Causality may run adversely: insurance penetration may simply be an outcome of economic growth (for instance, Beck and Webb, 2003, Catalan et al., 2000). Those prior studies that do study causality tend to use only a bivariate framework with narrow coverage (for instance, Chang et al., 2013). A multivariate framework is essential for causality analysis between insurance-growth relationships. Some use panel data, involving many countries over time. Some examine the link between insurance markets and other economic growth, banks and stock markets, but few papers concentrate on the causal link(s) between these variables.5

Here we investigate whether there are demonstrable Granger causal relationships6 between insurance penetration, banking intensity, stock market depth, and economic growth, using a panel dataset covering the Association of Southeast Asian Nations (ASEAN) Regional Forum (ARF) countries7 for the 1988–2012 period. Evidently, increased banking activities foster insurance activities. Analogously, insurance penetration requires the development in stock markets for the placement of funds deposited with insurance intermediaries. The direction of causality between these variables in a multivariate framework invites rigorous investigation.

Our multivariate panel-data estimation procedure offers robust estimates by using variations between countries, as well as variations over time. We adopt a sample of countries that have hitherto received little attention; and we use more advanced econometric techniques than have previously been used in this literature, to establish whether there are causal links between the variables. We comment on the direction of the causal nexus between insurance penetration and economic growth. We make a contribution to the literature by determining the direction of causality between any two variables in the presence of the other two variables.

The remainder of this paper is organized as follows: Section 2 provides an overview of insurance markets in the ASEAN countries; Section 3 presents a summary of the prior literature; Section 4 describes our sample, variables, and data; Section 5 describes our econometric estimation strategy and presents the results; and the final section concludes with policy implications and recommendations.

Section snippets

An overview of the development of insurance markets in ASEAN countries

ASEAN has ten member countries, namely Brunei Darulssalam, Cambodia, Indonesia, Laos, Malaysia, Myanmar (Burma), the Philippines, Singapore, Thailand and Vietnam and a population of 600 million people. ASEAN has experienced rapid economic development, with a total income level of close to USD 2.4 trillion (Lim, 2014). The further integration of these ten economies and the implementation of the ASEAN Free Trade Agreements (FTAs) is expected increase regional income and trade by 5% and 11.6%,

Literature review

A summary of studies establishing causal links between financial development (defined as broad money supply or stock market capitalization) and economic growth is given in Table 1. The key relationships between these variables are discussed below.

The first is the supply-leading hypothesis (SLH), which suggests that the development of an insurance sector is a necessary pre-condition for economic growth. Here, the causality runs from development of the insurance sector to economic growth. The

Data and the empirical model

Data on the ARF economies for 1988–2012 are obtained from the World Development Indicators published by the World Bank and Sigma Economic Research & Consulting, Switzerland. Although the ARF, in origin, consists of 25 countries, plus the European Union, we focus on only 18 member nations for our analysis. This is due to lack of adequate time series data on the remaining seven countries The 18 countries included in this study are Australia, Bangladesh, Canada, China, India, Indonesia, Japan, the

Econometric methodology and empirical results

Our specific interest is to detect causal links between economic growth and insurance penetration in the presence of banking sector depth and stock market depth. We conduct two tests: a panel cointegration test and a panel Granger causality test.

Before conducting either test, an essential first step is to identify the stationarity properties of the variables through other tests. This step is necessary because cointegration and causality tests both require variables to be stationary. There are

Conclusion and policy implications

Prior research on the relationships between economic growth, insurance penetration, banking intensity, and the intensity of the stock market tend to focus on the correlations between these variables. Those few studies that consider causality among the variables use a bivariate framework with a narrow coverage. Our study adopts a multivariate, rather than bivariate, framework, testing causality among all four variables simultaneously. In previous studies the role of other variables operating

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