metadata: authors: 0: author: Catalan, Mario
1: author: Impavido, Gregorio
2: author: Musalem, Alber
count: Malaysia,Thailand,Chile,Singapore,South Africa
docna: 0: docna: Contractual savings or stock market
            development - Which leads?
docty: Policy Research Working Paper
subtopic: Social Funds and Pensions,Insurance & Risk Mitigation,Capital Markets and Capital Flows,Non Bank Financial Institutions,Capital Flows,Mutual Funds,Financial Sector Policy
teratopic: Finance and Financial Sector Development
abstracts: cdata!: The authors study the relationship
            between the development of contractual savings (assets of
            pension funds, and life insurance companies) and non-life
            insurance, and, the development of stock markets (market
            capitalization and value traded). Their contribution lies in
            providing time-series evidence on a hypothesis that is very
            popular - but had not been substantiated - among supporters
            of fully funded pension systems in which funds invest large
            shares of their portfolios in tradable securities (equities,
            bonds). The literature is not clear on its assumption
            regarding causality between contractual savings, and capital
            market development. A one-way or two-way relationship is
            assumed, usually inter-changeably; the authors address the
            questions of which leads empirically. They present the
            evidence, including descriptive statistics, and the results
            of Granger causality tests, for OECD countries, and such
            countries as Chile, Malaysia, Singapore, South Africa, and
            Thailand. They do not present a theoretical framework, but
            do explain how the growth of the contractual savings sector,
            is thought to promote financial development. The authors
            find evidence in the data that causality between
            institutions, and markets either does not exist, or, if it
            exists, runs predominantly from institutions to markets. To
            a lesser extent, there is simultaneous causality between
            institutions, and markets. Furthermore, there is limited
            evidence that causality runs only from markets to
            institutions (the only exception seems to be for non-life
            insurance in developing countries). Results seem to support
            the idea that the development of institutional investors, is
            likely to promote the growth of market capitalization, more
            than that of value traded. In developing countries, there
            seems to be no causality from pension funds to growth in
            value traded, while there is causality from life, and
            non-life insurance.
geo_reg_key: 119228,517198,517195,517191
repnme: repnme: Contractual savings or stock market
            development - Which leads?
display_title: Contractual savings or stock market
            development - Which leads
listing_relative_url: /research/2000/08/693239/contractual-savings-or-stock-market-development-leads
topicv3: Pension Funds m1326066 611,Capital Markets m1326967 332,Mutual Funds m1326970 2180,Financial Sector Development m1327681 1920,Life Insurance m1505058 3837
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Finance and Financial Sector Development
origu: Financial Sctr Operations & Pol (OPD)
no_of_pages: 50
model_extractions: POLICY RESEARCH WORKING PAPER 2421

# Summary findings

Catalan, Impavido, and Musalem study the relationship between the development of contractual savings (assets of pension funds and life insurance companies) and nonlife insurance and the development of stock markets (market capitalization and value traded). Their contribution lies in providing time-series evidence on a hypothesis that is very popular-but had not been substantiated-among supporters of fully funded pension systems in which funds invest large shares of their portfolios in tradable securities (equities, bonds).

The literature is not clear on its assumption regarding causality between contractual savings and capital market development. A one-way or two-way relationship is assumed, usually interchangeably; the authors address the question of which leads empirically. They present the evidence, including descriptive statistics and the results of Granger causality tests, for OECD countries and such countries as Chile, Malaysia, Singapore, South Africa, and Thailand. They do not present a theoretical framework but do explain how the growth of the contractual savings sector is thought to promote financial development.

The authors find evidence in the data that causality between institutions and markets either does not exist or, if it exists, runs predominantly from institutions to markets. To a lesser extent, there is simultaneous causality between institutions and markets. Furthermore, there is limited evidence that causality runs only from markets to institutions (the only exception seems to be for non-life insurance in developing countries).

Results seem to support the idea that the development of institutional investors is likely to promote the growth of market capitalization more than that of value traded. In developing countries, there seems to be no causality from pension funds to growth in value traded, while there is causality from life and non-life insurance.

This paper-a product of the Financial Sector Development Department-is part of a larger effort in the department to study the effects of contractual savings on financial markets. Copies of the paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Patricia Braxton, room MC9-704, telephone 202-473-2720, fax 202-522-7105, email address pbraxton@worldbank.org. Policy Research Working Papers are also posted on the Web at www.worldbank.org/research/workingpapers. The authors may be contacted at mcatalan@ucla.edu, gimpavido@worldbank.org, or amusalem@worldbank.org. August 2000. (42 pages) _The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represen_ **_t_** _he view of the World Bank, its Executive Directors, or the countries they represent._ Produced by the Policy Research Dissemination Center
# **Contractual Savings or Stock Markets**

# **Development: Which Leads?**

Mario Catalan, Gregorio Impavido and Alberto R. Musalemt

## **The** World Bank

## Financial Sector Development Department

## Financial Sector Vice Presidency

tMario Catalan is Ph.D. Candidate, University of California at Los Angeles, Gregorio Impavido is Financial Economist, and Alberto R. Musalem is Advisor, both in the Financial Sector Development Department of the World Bank We appreciate comments received from Asli Demirguc-Kunt, Victor J. Elias, Robert Holzmann, Patrick Honohan, Augusto Iglesias, Estelle James, Robert Palacios, Klaus Schimdt-Hebbel, Thierry Tressel and Dimitri Vittas. The findings, interpretation, and conclusions are the authors' own and should not be attributed to the World Bank, its Executive Board of Directors, or any of its member countries.
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# Table of Contents

|I|INTRODUCTION<br>.........................................................<br>i|
|---|---|
|11|WHAT IS DIFFERENT ABOUT CONTRACTUAL SAVINGS?<br>..................... 3|
|11.1|<br>Specialization in the Financial Sector, the Term Structure of Interest Rates, and Growth ..... 5|
|1IL2|<br>Development of the Stock Market and Growth ....................................................................... 6|
|_113_|Improved Financial Structure of Governments, Banks and Firms, and Reduced Sovereign<br>Debt .................................................<br>7|
|II.4|Linkages Between Contractual Savings and Banking Regulation ................................................<br>7|
|III<br>EX|THE ROLE OF CONTRACTUAL SAVINGS: SOME SIMPLE NUMERICAL<br>AMPLES<br>.8|
|III.1|<br>The Structure of the Economy and the Role of the Financial Sector ...........................................8|
|III.2|<br>Differential Impact of Contractual Savings and Mutual Funds on Capital Markets<br>Development .11|
|_1113_|<br>Contractual Savings Institutions Bias Towards Long-Term Assets and Shares: A Simple<br>Framework ............................................................<br>11|
|IV|DESCRIPTIVE EVIDENCE<br>.....................................................<br>13|
|V<br>CA|ECONOMETRIC<br>EVIDENCE ON CONTRACTUAL SAVINGS AND<br>PITAL MARKETS DEVELOPMENT:<br>WHICH LEADS?<br>..<br>20|
|V.1|Granger causality between contractual savings and market capitalization or value traded.22|
|V.2|Granger causality between pension funds and market capitalization or value traded .<br>23|
|V.3|Granger causality between life insurance and market capitalization or value traded .<br>24|
|_VA_|Granger causality between non-life insurance and market capitalization or value traded ...24|
|V.5|Summary of results .25|
|VI|SUMMARY, CONCLUSIONS<br>AND RECOMMENDATIONS<br>...................... 29|
|VII|APPENDIX 1: GRANGER CAUSALITY TESTS ....................................... 31|
|VIII|APPENDIX 2: DATA ................................................<br>39|
**IX REFERENCES .................................................**

**40**

# **List of Tables**

|Table 1: Contractual savings ratio to GDP (percent) ..........................................|........... 2|
|---|---|
|Table 2: Portfolio Composition .....................................................|9|
|Table 3: Granger causality tests: summary ....................................................|25|
|Table 4: Granger causality (one way) from institutions to markets only ............|.............. 26|
|Table 5: Granger causality (two ways) between institutions and markets ...........|............. 27|
|Table 6: No Granger causality between institutions and markets .......................|.............. 27|
|Table 7: Shares of Stocks in Investment Portfolios: Selected Countries .............|............. 28|
|Table 8: Contractual savings - Granger causality tests ......................................|.............. 31|
|Table 9: Pension funds - Granger causality tests ...............................................|.....<br>33|
|Table 10: Life insurance - Granger causality tests<br>...................................|...<br>35|
|Table 11: Non-life insurance - Granger causality tests<br>.............................|.....<br>37|
|Table 12: List of countries ....................................................|39|

# **List of Figures**

|Figure 1: Households' Asset Portfolio ....................................................<br>9|
|---|
|Figure 2: Payoff Tree ...................................................<br>13|
|Figure 3: Contractual savings in system financial assets (%, 1996) .14|
|Figure 4: Contractual Savings and Market Capitalization, 1996 .15|
|Figure 5: Contractual Savings and Value Traded, 1996 .15|
|Figure 6: Changes in Contractual Savings and Market Capitalization, 1990 - 1996 .<br>16|
|Figure 7: Changes in Contractual Savings and Value Traded, 1990 - 1996 .16|
|Figure 8: United States Financial Institutions Portfolios .......................................<br>17|
|Figure 9: Institutional Investors' Portfolio .......................................<br>19|
# **I Introduction**

In the last two decades, there has been a dramatic growth in the assets managed by contractual saving institutions (pension funds and life insurance companies) in developed countries as well as in some developing countries as shown in Table 1. In most countries in the sample, contractual savings share to GDP (deepening) increased several fold during the period. Furthermore, Netherlands, United Kingdom, Switzerland, and South Africa had contractual savings in excess of 100 percent of GDP in 1996. The only country in the sample that experienced a decline in the participation of contractual savings in GDP is Singapore.

Pension reform favoring funding is considered to be one of the policy options that policy-makers face when attempting to develop the contractual savings sector, especially in developing countries. As evidence of the general interest on contractual savings development and its potential effects in the economy, extensive literature on the macroeconomic role of pension funds has been developed and the debate on the benefits of pension reforms has been enriched and intensified in recent years.' Many studies focused on the effect of pension reforms on household saving rate and results are not conclusive. On the one hand, pension reform that relies on voluntary contributions based on expenditure tax treatment as opposed to income tax treatment is expected to have a negligible effect on saving as indicated by the extensive literature available on the inelasticity of saving to the real interest rate.<sup>2</sup> On the other hand, either myopia or liquidity constraints explain why pension reforms based on mandatory contributions could increase the household saving rate. The liquidity constraints are assumed to affect young or low-income individuals who cannot borrow to consume and offset the compulsory saving.<sup>3</sup> However, the effect on national saving will also depend on the government and firms response to pension reform.

Even if the effect of a pension reform on the national savings rate were not significant, other effects could be important. In particular, capital markets development is indicated as one of the main potential consequences of contractual savings development. 4 This study is part of a larger research project that encompasses various contractual savings and financial sector issues. The purpose of this paper is to analyze the causality between contractual savings and stock markets development. We emphasize the role of pension funds and life insurance companies as financial intermediaries, and we compare I See, for example, Holzmann (1997), Arrau and Sclmidt-Hebbel (1993), Feldstein (1974, 1996), Mackenzie, Gerson and Cuevas (1997), Schmidt-Hebbel (1998).

2 See for example, Whitehouse (1999).

3 See, for example, Feldstein (1978), Munnell (1976), Loayza, Schmidt-Hebbel and Serven (2000), Samwick (2000), Smith (1990), Bailliu and Reisen (1997), Schmidt-Hebbel and Serven, eds. (1999). 4 See, for example, Bodie (1990), Davis (1995), Vittas and Skully (1991), Vittas (1998a, 1998b, 1999).
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results when different institutions, like non-life insurance companies are considered. The literature is not clear on its assumption regarding causality between contractual savings and capital market development. A one-way or a two-way relationship is assumed, usually interchangeably. In this paper, we address the question of which relationship leads empirically. The evidence, including descriptive statistics as well as Granger causality tests is presented for OECD countries and some other countries such as Chile, Malaysia, Singapore, South Africa, and Thailand. The paper does not present a theoretical framework but explains with clear statements and intuitive examples the way in which we think the growth of the contractual savings sector promotes financial development.

**Table 1: Contractual savings ratio to GDP (percent)**

|**Counts**|**1980**|**1985**|**1990**|**1996**|
|---|---|---|---|---|
|Netherlands|66.90|93.65|108.11|148.19|
|United Kingdom<br>|38.81|74.77|86.90|141.72|
|Switzerland|70.00||88.5|131.38|
|United States|43.01|59.33|69.20|94.80|
|Canada<br>|30.29|38.08|47.80|64.59|
|Australia<br>|||33.49|57.52|
|Sweden||23.92|28.63|47.96|
|**Norway**|13.15|17.29|25.80|30.02|
|Belgium<br>||16.42|20.55|27.20|
|Korea, Rep.<br>|4.06|10.48|19.24|24.36|
|Germnany<br>|12.73|17.63|20.68|23.82|
|Austria|||13.28|21.35|
|Spain<br>||3.21|9.87|18.78|
|South Africa|39.27|55.93|78.13|126.01|
|Singapore||153.36|115.13|93.50|
|Chile|1.00||29.28|50.61|
|Malaysia<br>|20.08|35.65|47.18|51.02|
|Thailand|||**2.10**|**4.80**|

**Source:** 1998 OECD Institutional Investors Statistical Yearbook and WB institutional investors database.

The paper is organized as follows. Section II, presents the key propositions on the links between contractual savings and capital markets development. Their effects and implications for the economy as a whole are analyzed in terms of growth, term structure of interest rates, capital structure, regulation, and comparative impact on developing versus developed economies. Section III, discusses the role of contractual savings in the structure of the financial sector. In particular, it distinguishes between the effects of contractual savings, mutual funds and non-life insurance development. Section IV, presents a descriptive analysis of the data, which confirms that there is a positive relation between contractual savings and capital markets development. Section V, analyzes the causality between contractual savings and non-life insurance companies and market
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capitalization or value traded in stock markets.<sup>5</sup> Finally, Section VI summarizes the results and the main conclusions.

# **11 What is Different About Contractual Savings?**

The key point to understanding the macroeconomic role of contractual savings and more specifically, their role as financial intermediaries, is to observe that they have a distinctive characteristic. While banks and open-end mutual funds have mainly shortterm liabilities, contractual savings institutions have long-term liabilities on their balance sheets.<sup>6</sup> This distinction has important implications. It means that the depositors or investors cannot "run" (withdraw their deposits suddenly and in a large scale) against the assets of the contractual savings institutions where they have claims. In contrast, both banks and open-end mutual funds face the risk of an unexpected run against their<sup>assets</sup> that could generate a liquidity problem, and potentially trigger their bankruptcy. As a consequence, the investment and lending strategies of banks and open-end mutual funds differ from those of the contractual savings institutions. Contractual savings institutions have a natural advantage over banks in financing long-term investment projects and their investment strategies will be more biased towards long-term bonds and the equity markets.

A dynamic hedging principle is at work, in the sense that financial institutions try to match the maturity structure of their assets and liabilities. Hedged positions help to reduce the risks they face; conversely the lack of hedged positions imply that either reinvestment (short-term assets and long-term liabilities) or refinancing (long-term assets and short-term liabilities) decisions will have to be taken. The ensuing maturity mismatch implies risk taking and can generate cash flow problems in volatile environments.

As will become clear, for a given amount of total savings in the economy, contractual savings growth (for example, a pension reform from a pay-as-you-go to a funded system, a reform that transforms corporate pensions that are based on book reserves to funded schemes outside the firm, or reforms that improves the regulatory and tax environment) are expected to stimulate financial development. This is because from the point of view of household and corporate sectors, there is an important liquidity effect at work. The accounts held in the contractual savings sector are **completely illiquid** from the depositor's point of view. They can only be liquidated in the long-run upon retirement of the beneficiary (either as a lump sum and/or annuity) or upon the occurrence of a particular event (e.g., death, disability); finms have no access to them. Thus, if large deposits are made in contractual savings, this will change the actual _5_ Market capitalization (also known as market value) is the share price times the number of shares outstanding. Stocks traded refers to the total value of shares traded during a given period.

6 Although open pension funds (as opposed to closed pension funds, which are employer-sponsored plans) operate like open-end mutual funds, their funds are more stable because they are captive to the industry as a whole. Hence, open pension funds are less exposed to systemic risks than are open-end mutual funds.
portfolio composition of both households and corporations between liquid and illiquid assets to a level below their desired ratio. Therefore, to restore equilibrium, households' and corporations' demand for liquidity has to be satisfied with additional holdings of liquid assets. This could be achieved by a reshuffling of portfolios; for instance, by increasing holdings of deposits in the banking sector, open-end mutual funds, and traded securities, at the expense of some other non-liquid assets that households or corporations could have held (e.g., real estate, non-traded financial instruments). Thus, households' and corporations' behavior will reinforce financial market development, which is associated with contractual savings growth.

It is important to remark that these and next propositions hold even when the total saving of the household and corporate sectors remain constant. Total saving proved to be very insensitive to the variables that are supposed to affect it, so the fact that the propositions do not depend on the change in saving in the economy is remarkable.

Our analysis, although different, is consistent with previous work. Davis (1995) finds that pension fund portfolios have a greater proportion of uncertain capital and longterm assets than the household sector. He also finds that the personal sector tends to hold a much larger proportion of liquid assets. "The implication is that a switch to funding would increase the supply of long-term funds to capital markets and reduce bank deposits, even if savings and wealth do not increase, so long as households do not increase the liquidity of the remainder of their portfolios fully to offset growth of pension funds". This, he explains, is the impact of a pension reform on capital markets and the existence of the liquidity effect. Davis also suggests that there is some evidence that such offsetting to restore liquidity exists.

Furthermore, the growth of contractual savings implies a reallocation of savings from intermediaries with a high probability of facing a run against their assets (banks and open-end mutual funds) towards intermediaries with a low probability of facing a run (pension funds and life insurance companies). This reallocation means that funds are moved towards institutions that invest more heavily in long-term bonds and equity. In addition, of course, there could be an independent effect of the reform on total savings that would cause further financial development.

As an application of the previous statements to the case of pension and life insurance reforms, it is apparent that only an increase in the amount of assets accumulated in the contractual savings sector is necessary to develop the capital markets and that an increase in total savings is not necessary at all. Therefore, pension reforms, which increase the level of funding, will imply a large increase in assets managed by pension funds and thus, a higher degree of capital market development. Of course, our hypothesis also implies that if a pay-as-you-go system were to be transformed into a partially funded scheme that would be able to accumulate assets at a sustainable pace it would also produce the same financial deepening effect. This would be the case provided reserves are invested in market instruments and are not used as captive sources of finance
by governments.<sup>7</sup> Accordingly, contractual savings development would imply a movement towards completing financial market development.

Although funding generates positive externalities through capital market development, this does not mean that forcing a given level of funding through mandatory retirement schemes coincides with the social optimum. In other words, there is an argument for a minimum level of mandated funding to provide a minimum level of benefits, leaving the provision of additional benefits to voluntary arrangements. This minimum funding would be sufficient to address the market failures existing in a fully voluntary scheme. These failures derive from myopia of individuals, who do not necessarily save enough for retirement needs or other contingencies (e.g., death, disability); from the moral hazard of individuals relying on Government retirement income guarantee schemes; and from the adverse selection implicit in the different life expectancy of individuals. Hence, a fully funded mandatory pension system that ensures a minimum level of benefits would maximize social welfare, whilst a mandatory PAYG system that precludes the development of stock markets would not.

The design of pension reform is likely to affect social welfare through this and other channels. For instance, regulations imposed on the portfolio composition of pension funds can severely affect the quantitative impact of contractual savings development on capital markets. As an extreme example, if pension funds were restricted to hold only government bonds, the development of contractual savings should have a minimum or no effect on stock markets and social welfare would be lower.

In order to understand the mechanics of capital market development and its relation to contractual savings and the economy as a whole, let us summarize the most important propositions concerning the macroeconomic role of contractual savings. Conceptually, let us think of an economy with banks as the unique financial intermediaries that is subsequently transformed into an economy with both banks and a large contractual savings sector. The main micro/macroeconomic effects are the following.

# **_11.1 Specialization in the Financial Sector, the Term Structure of Interest Rates, and Growth_**

The development of the contractual savings sector will initially have a static effect where the banking sector will tend to specialize in financing investment projects with short maturity and the contractual savings institutions funding those investment projects with long maturity. Of course, portfolios will be diversified and a complete specialization will not be observed, in the sense that only the shortest-maturity projects are financed by banks and only those with the longest maturity are financed by contractual savings institutions. We would rather observe that the diversified portfolios of banks are more biased towards short-term loans and those of the contractual savings 7 There is some evidence however, that governments do use partially-funded public pension schemes as sources of captive finance. For a discussion see Iglesias and Palacios (2000).
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institutions are more biased towards long-term and risky assets but all institutions will have all kinds of assets.

Again, regulations could introduce significant distortions. If pension funds and life insurance companies are restricted to holding primarily securities, there could be an important cost associated to the contraction of the banking system. In the last two decades, some academic economists made important contributions to the understanding of the special role that banks play in the financial system. 8 Banks play an important microeconomic role of monitoring. Among other peculiarities, banks finance "difficult" projects requiring intensive monitoring. These "difficult" projects cannot be financed by the issuance of securities because large numbers of small security holders have no incentive to monitor individually. Bank loans and securities are not perfect substitutes and the expansion of contractual savings can have a very important distributional impact on the economy. For instance, if small firms require more monitoring, the contraction of the banking system will make the financing of those firms very expensive and there will be incentives to create corporations. This effect is exacerbated if contractual saving institutions cannot hold loans, but it could exist even if there is no constraint on portfolio holdings because the issuance of demand deposits and loans are complementary activities.<sup>9</sup> These conclusions are sensitive to the condition of the banking sector in an economy. The introduction of a funded pension scheme in an economy where the probability of bank runs is relatively high (i.e., many emerging economies) will have more important effects than in an economy with a relatively low probability of bank runs (i.e., most developed economies). This is because in the latter case, banks would already be allocating a significant proportion of their portfolio in long-term loans.

The development of contractual savings also implies that the long-term interest rate should fall relative to the short-term rate and thus, more long-term projects will be financed. Given the fact that the expected return of long-term investment projects is higher than the returns on short-term investments (a technologically reasonable assumption), a higher growth rate will be observed.

# **_11.2 Development of the Stock Market and Growth_**

The introduction of a funded pension system in the economy will increase the demand for risky assets and will develop the stock market even when total savings are unchanged. The development of the stock market will be reflected in an increase in market capitalization and value traded as a fraction of the gross domestic product of the economy. This development is usually accompanied by improvements in financial innovation and regulations (including minority shareholders' protection), corporate governance, and overall improvement in financial market efficiency (including reduction in transaction costs), transparency, and competition. All these effects add depth and

> 8 See Fama, 1985, James C. and Wier P.,1988, and Diamond,1984.

> 9 See for instance, Kashyap A., Rajan R. and Stein J.C. (1998).
- 7 -

liquidity to the market and they are extensively discussed in the literature. ' Ultimately, these effects will result in high rates of long-term growth. i"

# **_11.3 Improved Financial Structure of Governments, Banks and Firms, and Reduced Sovereign Debt_**

If there is an increase in the demand for long-term and risky assets, then in equilibrium both the debt/equity ratio of enterprises and the short-term debt/long-term debt ratio of enterprises and governments will fall. This will also be reflected in banks undertaking less term transformation risk. As we argued above, we also expect the substitution of loans for securities to have important implications for the economy.

The 1997 East Asia financial crisis has been, in great part, due to excessive term transformation undertaken by financial institutions, excessive leverage of enterprises and their excessive dependence on short-term debt as opposed to long-term debt and equity finance. This was in part due to the relative scarcity of long-term savings in these economies. Therefore, the development of long-term savings and capital markets would reduce pressures on the banking system, thereby lengthening the maturity of debts and providing more equity-based financing for enterprises.

Furthermore, increasing funding of pension liabilities reduces the implicit government debt. The second potential impact is the development of the market for longterm government bonds. Many developing countries are trying to extend the maturity of the public debt to make their economies less vulnerable to refinancing. Thus, a developed contractual savings sector will increase the set of possibilities of the government having more degrees of freedom to perform an adequate debt management policy.

Accordingly, a developed contractual savings sector contributes to build a more resilient economy, one that would be less vulnerable to interest rate and demand shocks, while creating a more stable business environment, including macroeconomic stability. The result will be a lower country risk premiumn, hence lower equilibrium interest rates, which increase investments and, ultimately, accelerate growth.

# **_11.4 Linkages Between Contractual Savings and Banking Regulation_**

We should keep in mind that the banking sector and the pension fund sector can be seen as imperfect substitutes in their role as financial intermediaries, so these sectors should not be regulated without taking into consideration their links. Independent regulation cannot do better than regulation when all the linkages between banks, pension funds, other financial intermediaries, and the productive sector are considered. Because 10 See, for example, OECD, 1997, Davis, 1995, Vittas, 1998,1999. 11 For discussions on the impact of capital market development on growth see, for example, Levine and Zervos, 1996, and Levine, 1997.
different regulations will affect the portfolio composition of pension funds, especially the fraction of total funds allocated between shares and long-term bonds, the debt-equity ratio of the productive sector will be sensitive to the regulatory regime. For example, if regulations impose a binding maximum weight of equity in the portfolios of pension funds, then these will hold more long-term bonds and loans, and thus, banks will have to be more biased towards short-term loans and firms will be more leveraged.

# **Ill The Role of Contractual Savings: Some Simple Numerical Examples**

This section provides some intuitive analysis and illustrates with simple examples many of the previous propositions in order to motivate the following analysis of the data.

## **_111.1 The Structure of the Economy and the_ Role** **_of the Financial Sector_**

We assume that the household sector owns both financial and non-financial assets. Individuals can hold money, shares, government and corporate bonds (publicly traded and more liquid securities that can be traded in secondary markets), loans, debt, and equity (private and illiquid financial instruments that are non traded in secondary markets), either directly or indirectly through claims on financial intermediaries. These financial intermediaries in turn hold financial assets (and some non-financial assets too). Households and financial intermediaries as a whole hold the primary fmancial assets: money, shares, government bonds, corporate bonds and loans (Figure 1).

In order to show that the development and relative size of institutional investors changes something in the economy as a whole, we have to prove that the demands for primary financial assets will change either in their composition (shares, government bonds, corporate bonds, loans), in their term structure (long-term, short-term), or in their liquidity.

The following exercise provides helpful intuition for organizing our analysis of the data. To begin with, let us suppose that the economy is composed of banks, a household sector (there are no other financial intermediaries) and a corporate sector. The latter can issue either debt (bonds) or equity to finance their productive activities. The consolidated household-banking sector can hold shares, bonds and non financial-illiquid assets.

Initially, household-banks' total savings are equal to $300 and their portfolioweights are the same for shares, bonds, and non-financial assets (i.e., 1/3, 1/3, 1/3). This means that the household-banking sector holds $100 in shares, $100 in bonds and $100 in non-financial assets. That is Case A in Table 2.
- 9 -

Figure 1: Households' Asset Portfolio <!-- Start of picture text --> l ~~~~~~~~~~~~~~~~~~I<br>Money and Banku<br>sDDeposits (money<br>on- inanciaClamsonMuua plus quasi-money) p<br>HouseholdS Shares<br>\ ~~~~~Financial<br>\ Assets \ . FBonds<br>\X / 4|Claims on Mutual N<br>\ / Funds Assets | ~~~~~~~~~~~Money and Bank<br>F u n ds.A ss ets D e p o sits (m o n e y<br>Com s A s Nplus quasi-money)d<br>FinanciF I A<br>Assets e n Shares<br>S| ares Bon Non-Fin. \s SharesFBonus Non-FIn~ Shares Bonds Assetsn. Sh|res Bonds Bonds l<br>B 500 100iquid 100 100 50 Non Financial<br>Financial p Insurance Assets<br>Assets Companies Assets Non-traded<br>\ ~~~~~~~~~~~~~~Financial Asset:s<br>|Non-traded loans,|<br>debt, and equity|<br>Table 2: Portfolio Composition<br>Demand for Assets Household Sector 11 Contractual Savings hMutual Funds<br>CSaras Bonds Non1F1 5 Sha50s Bonds No50Fin. Sha1es 5onds Non0n Sha0s Bonds No0+ln.<br>A 100 100 100 100 100 100 0 0 0 0 0 0<br>B 100 100 100 50 50 50 50 50 50 0 0 0<br>C 150 100 50 50 50 50 100 50 0 0 0 0<br>D 100 100 100 0 50 100 100 50 0 0 0 0<br>E 160 130 10 70 70 10 90 60 0 0 0 0<br>F 150 100 50 50 50 50 0 0 0 100 50 0<br>Notes: I With banks<br><!-- End of picture text -->
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Next, suppose that we introduce in the economy a contractual<sup>savings sector (e.g.,</sup> pension funds) and we induce or force the household sector<sup>to contribute $150 to</sup> contractual savings institutions. Different hypothesis about<sup>the investment behavior of</sup> pension funds and the reaction of the household sector<sup>will imply different results in the</sup> composition of the aggregate demand for assets. Let us<sup>analyze different possibilities and</sup> at the end, we will try to decide which one is the most<sup>likely to be observed in reality.</sup> We assume that the aggregate amount to be saved<sup>is not altered at all in the different</sup> scenarios, this helps understand how the effect of contractual<sup>savings on financial market</sup> development can be independent of the total amount of<sup>savings in the economy.</sup> If the portfolio choice of the contractual savings sector<sup>were (1/3, 1/3, 1/3) and</sup> households maintain their investment policy, there would<sup>be no change in the final</sup> demand for shares and bonds, that is Case B in Table 2.<sup>Next, suppose that the</sup> contractual savings sector is more willing to invest in shares<sup>than the household sector</sup> and its portfolio choice is (2/3,1/3,0), and that households<sup>maintain their investment</sup> policy, then the total demand for shares will be $150, the total<sup>demand for bonds will be</sup> $100, and the aggregate demand for non-financial assets will<sup>be $50. That is Case C in</sup> Table 2.

Of course, it is possible that individuals, knowing that pension funds will<sup>invest</sup> more intensively in shares on their behalf, adjust their investment strategy<sup>in such a way</sup> that at the end they hold the same portfolio of assets as<sup>before the introduction of the</sup> pension fund. That is Case D in Table 2, the portfolio choice<sup>of the household sector is</sup> (0, 1/3, 2/3).

In order to reach valid conclusions, it is very important to<sup>note that individuals</sup> care not only about the asset composition held either directly<sup>or through intermediaries</sup> (contractual savings institutions and mutual funds), but<sup>also about the liquidity of the</sup> assets they hold. It is important to observe that when households<sup>contribute funds to the</sup> contractual savings sector, they suffer a big reduction in<sup>their liquid assets (in either Case</sup> B, C or D). Furthermore, it is necessary to observe<sup>that in order to undo what the</sup> contractual savings sector is doing on their behalf in terms<sup>of asset composition,</sup> households should increase the liquidity of their direct portfolio.<sup>This is why we think</sup> that Case D is very unlikely to be observed in the real world.

Case E is the most likely result of a development of the contractual<sup>savings sector.</sup> Households try to restore their liquidity positions by selling<sup>illiquid assets (non-traded</sup> financial and non-financial) and this implies further development<sup>of the capital market.</sup> Thus, in the case of contractual savings development, the liquidity<sup>effect reinforces the</sup> effect of the contractual savings bias towards shares to promote<sup>capital market</sup> development.

Tn contrast, if there were a reallocation of savings from households<sup>to mutual</sup> funds, the liquidity effect would not exist (as in Case F in<sup>Table 2) or it could even play</sup> in the opposite direction because mutual fund portfolios<sup>are more biased towards liquid</sup> assets. Individuals could try to reduce their own holdings of liquid<sup>assets by selling</sup> shares and bonds in order to buy illiquid assets - i.e., non-traded<sup>financial and non-</sup>
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financial assets. Therefore, from this numerical example we can conclude the proposition described in the next section.

# **_111.2 Differential Impact of Contractual Savings and Mutual Funds on Capital Markets Development_**

For a given amount of total savings, a reallocation of funds from the consolidated household-banking sector towards either the contractual savings or the mutual funds sector is expected to increase the demand for shares and develop the capital market. The impact of contractual savings development on capital markets is expected to be greater than the impact of mutual funds development because in the former case, the liquidity effect reinforces the aggregate demand for shares.

In addition, if the real world were like Case D in Table 2, we would observe in the data that when the financial assets of contractual savings institutions grow, there<sup>is no</sup> increase in market capitalization. As we will see, the data shows a strong correlation between the financial assets of contractual savings institutions and market capitalization, supporting the reasonable hypothesis that the development of contractual savings will move the economy from a Case like A to a Case like E in Table 2. (The same basic intuition can be applied to the comparison between short-term and long-term assets instead of shares and bonds).

# **_111.3 Contractual Savings Institutions Bias Towards Long-Term Assets and Shares: A Simple Framework_**

Pension funds will be more likely to invest in long-term assets and shares than individuals, partly because the large volume of transactions allow them to reduce transaction costs and they can diversify risks more efficiently. Only in this restricted sense, we can say that the pension funds provide similar financial services to those provided by mutual funds. Nonetheless, we should not forget that the nature of these institutions is very different (the savings received by the pension system may be compulsory and a large fraction of the population may be required to contribute, and savings are kept by the institution for long periods of time, etc.) and we expect that their development will produce differential impact on capital markets (volatility, liquidity, etc.).

The most interesting question is why pension funds have an advantage over banks either in financing long-term investment projects (by lending money in the form of loans or by buying long-term corporate or government bonds, ignoring the liquidity aspects for the moment) or in investing in equity.

The simple theoretical structure that follows will provide us the intuition for understanding the different investment strategies pursued by banks and pension funds. To take the simplest case, we show that those intermediaries facing a low probability of a run have an advantage when it comes to financing long-term investment projects.
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Suppose that an institution (we will see later that it could be a bank or a pension fund) receives a deposit of one dollar at date 0 and promises to pay a deposit rate _id = 5_ percent per period to the depositor. At that moment, the institution has to decide whether to lend the money to finance a long-term project (2 periods) or a short-term project (1 period). If the institution finances the long-termn project it will receive a return of _iL_ = 20 percent per period at date 2 and if it finances the short-term project it will receive a return of _is_ = 10 percent per period at date 1.

After the investment decision is taken and before date 1, there is a run against the assets of the institution that occurs with probability P and there is no run with probabi'.Xy 1 - _P._ If the investment decision of the institution was to finance the long-term project and there is a run, then the institution will be in an illiquid position and will default on its debt, thus it will go bankrupt and will lose its reputation with a loss equal to - _C_ = -2 12 If the long-term project was financed and there is no run, it will get (l _+ iL) _(l+id)2_ =0.3375 at date 2.

If the investment decision of the firm was to finance the short-term project and there is a run, the institution will be liquid and able to pay the depositor, the profit will be _(,_ + ) 2S -(1+ _id_ ) _=_ 0.05. If there is no run, the institution will reinvest for one period and at the end it will get (1 _+ is)_<sup>2</sup> _( 1 _+id)_<sup>_2_</sup> = 0.1 07 5.

TIhe strategy to be chosen will be the one that maximizes expected profits. The institution will choose to finance the long-term project if and only if the expected profit of that strategy is greater than the expected profit of the alternative one. In our example, the following condition must be satisfied: -2P+(l-P)0.3375 2 _0.05P+(l-P)0.1075 iff P_ <0.1 Tlhus, the inequality holds for a value of P that is lower or equal to 0.10. In other words, the long-term project will be financed by the institution only if the probability of a run is low enough.

This example is instructive in several directions. We can think of this institution as being a pension fund if _P_ = 0 (you cannot run against the pension fund) and a bank for P greater than 0. Suppose an economy where P in the banking sector is greater than 0.1, that means that the banks will either finance the long-term project at very high interest rates or not finance it at all, while a pension fund will do it, thus, the introduction of pension funds will have a very important real effect in promoting long-term investment and growth. Now, suppose other economy where P in the banking sector is lower than 0.1, that means that the banks will choose to finance the long-term project, thus the development of the pension fund sector will not generate this type of effect.

> 12 This is an arbitrary number that is supposed to represent all the costs of shutting down the institution, including the cost in reputation and the present value of future profits foregone. The message of our story is insensitive to the particular number used.
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Think of the first type of economy as one without a very resilient banking sector where the probability of a bank run is not negligible, and think of the second economy as one with a strong banking sector. We can conclude that the potential benefits of developing the contractual savings sector are greater in economies without very strong banks, at least in terms of financial deepening, the term structure of investment and growth. 13

**Figure 2: Payoff Tree**

<!-- Start of picture text --> ,(1.2)2_(1 os5)2=0.3375=( l+iL)2_(l+id)2<br>No Run /(-P)<br>Long-term<br>/ ~~~Run \P)<br>-2=-C<br># Short-tee (I. 1)2_(l.05 )2=0. 1075=(l +iS)2_(l+id)2<br>0 '(1-P)<br>Run \(P)<br>\ (l.l)-(l.05)=0.05=(1+is)-(l+ id)<br><!-- End of picture text -->

# **IV Descriptive Evidence**

Figure 3 shows how contractual savings have become the dominant financial asset in several countries. In 1996, they represented 50 percent or more of financial assets (defined as the aggregation of money, quasi-money and contractual savings assets) in 9 out of 29 countries.'<sup>4</sup> Furthermore, the same figure shows that non-OECD countries such 13 Of course, in this very simple example, the institution is constrained to hold a completely specialized portfolio, but a rigorous model with portfolio diversification can be constructed and a similar parable can be told. Similarly, the basic structure can also be extended to include risky assets. Money and quasi money are liabilities of the consolidated banking system (including the Central Bank), which are liquid financial assets held by the household sector. Clearly, the assets of contractual
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as South Africa, Chile, Singapore, and Malaysia have a dominant or a very important contractual savings sector.

**Figure 3: Contractual savings in system financial assets (%,1996)**

<!-- Start of picture text --> tO0% - 1 _ l 1 |<br>90%<br>70%<br>60% *<br>50% EI 6||<br>40% |l | X l1 l<br>30% il l<br>20X %ll<br><!-- End of picture text -->

**Source:** 1998 OECD Institutional Investors Statistical Yearbook and WB institutional investors database.

Figure 4 shows the positive correlation between the financial assets of contractual savings institutions and market capitalization as a fraction of GDP for a cross section of OECD and non-OECD countries in 1996 (the positive relation is very stable for different years). Those countries with a more developed contractual savings sector are also countries with more developed stock markets. Furthermore, Figure 5 indicates a positive relationship between contractual savings development and the liquidity of the capital markets (measured by value traded over GDP).

Figure 6 explores the relationship between **changes** in contractual savings as a fraction of GDP and **changes** in market capitalization over GDP for the same countries between 1990 and 1996. Figure 7 presents a similar relationship between **changes** in contractual savings and **changes** in value traded as a fraction of GDP. It is clear that those countries that were able to develop their contractual savings sector also show a higher growth in their stock markets in terms of capitalization and value traded in the same period. The same conclusions are reached with estimates using panel data for 26 countries and with about 300 observations. **'**<sup>**5**</sup> savings institutions belong to the household sector. Of course, there is some double counting since assets of contractual savings institutions include cash and bank deposits. 15 See Impavido and Musalem, 2000
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Figure 4: Contractual Savings and Market Capitalization, 1996 <!-- Start of picture text --> N MCGDP<br>2-<br>ZAF<br>1.5-<br>05 LL~~~~D .5IN1.<br>CSAGDP<br><!-- End of picture text -->

> Notes: The fitted line is given by 5 = 0.177 + 0.958x, with a t statistic of 7.314 for the slope. See Table 12 in Appendix 2 for the list of countries.

Source: 1998 OECD Institutional Investors Statistical Yearbook and WB institutional investors database.

Figure 5: Contractual Savings and Value Traded, 1996 <!-- Start of picture text --> \/T/GDP<br>1.5<br>1- USA<br>NLD<br>5- SW A U S L-W<br>-5-<br>DEU<br>o _ aL<br>0 .5 1 1.5<br>CS/GDP<br><!-- End of picture text -->

> Notes: The fitted line is given by ', = 0.085 +0.480x, with a t statistic of 4.650 for the slope. See Table 12 in Appendix 2 for the list of countries. Source: 1998 OECD Institutional Investors Statistical Yearbook and WB institutional investors database.
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Figure 6: Changes in Contractual Savings and Market Capitalization, 1990 - 1996 <!-- Start of picture text --> D(MC/GDP)<br>1-<br>AUS<br>SGP<br>.5 j<br>0<br>KOR<br>JPN<br>-.2 0 .2 .4 .6<br>D(CSIGDP)<br>The fitted line is given by i, = 0.161 + 0.849x, with a t statistics of 2.593 for the slope. See Table<br>12 in Appendix 2 for the list of countries.<br>1998 OECD Institutional Investors Statistical Yearbook and WB institutional investors database.<br>Figure 7: Changes in Contractual Savings and Value Traded,<br>1990- 1996<br>D(VT/GDP)<br>NLD<br>USA<br>.5SAAU<br>.6 ~~~~~~~~ESP CAN g -B<br>O~~~~~~~TJ DNK CHIN ZA<br>0<br>JPN<br>-.2 ~~~~0 .2.4 .<br>D(CSAGDP)<br><!-- End of picture text --> Notes: The fitted line is given by **i,** = 0.161 + 0.849x, with a t statistics of 2.593 for the slope. See Table 12 in Appendix 2 for the list of countries.

**Source:** 1998 OECD Institutional Investors Statistical Yearbook and WB institutional investors database.

Notes: The fitted line is given by y, = 0.044 + 0.968x, with a **t** statistics of 3.289 for the slope. See Table 12 in Appendix 2 for the list of countries. **Source:** 1998 OECD Institutional Investors Statistical Yearbook and WB institutional investors database.
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Now, let us see whether the data show that contractual savings institutions are more willing to hold risky and long-term assets than other institutional investors and banks. Figure 8 compares the portfolios of US contractual savings institutions with those of the banking sector.

**Figure 8: United States Financial Institutions Portfolios**

<!-- Start of picture text --> US-Portfolios of Pension Funds US-Portfolios of Life Insurance<br>(1996) Companies (1996)<br>ST Loans Other ST Loans Other<br>and Cash ilo 11%and Cash 5%<br>LT Loans ST B-111S2 Loans LT 9% 7/i g 20% Sharesand<br>and Bonds 8 Bills 2u<br>and Bonds<br>57%~~~~~~~~7<br>L Ionvstmn 1 opais196<br>LT Bonds~~~~~~~~~~~~~~T od<br>US-Portfolios of Open-end US-Portfolios of Banks (1996)<br>Investment Companies (1996)<br>ST Loans Other<br>and Cash 80/ Ohr6% Securities<br>LT Loans ST Loans<br>and Bonds<br>Shares<br>W12%<br>LT Loans<br>59%<br>LT Bon s ~~~~~~~~ST Loans<br>and Cash<br><!-- End of picture text -->

**Source:** OECD, Institutional Investors Yearbook, 1997, and Federal Reserve, Monthly Bulletins.

Among the remarkable facts in Figure 8 are the high weight of securities in the portfolios of pension funds (84 percent), life insurance companies (79 percent) and openend investment companies (90 percent) relative to banks (23 percent), and the low weight of short-term loans and cash in the portfolios of those institutions (4 percent, 7 percent, and 8 percent respectively) relative to banks (59 percent). Pension funds, life insurance companies and open-end investment companies are also heavily invested in long-term bonds. Clearly, US contractual savings institutions hold larger fractions of their total assets invested in traded securities such as stocks and long-term bonds while the assets of the banking sector are invested more heavily in private financial instruments (loans) of short-term maturity.
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Finally, Figure 9 shows the average portfolio composition of different institutional investors of some other selected OECD countries. In the United Kingdom, shares and long-term bonds account for 80 percent or more of the portfolios of contractual savings institutions. There is a very high fraction of loans in the portfolios in the Netherlands, but it is also striking that they are almost completely long-term loans. We could be tempted to say that the role of contractual savings institutions in the Netherlands is similar to those of banks in terms of lending strategy, but the financial services provided are absolutely different in terms of maturity structure. In Norway, even when we do not have the maturity structure of loans, the presumption is that a similar story can be told. Sweden and Norway are also examples of our hypothesis that if there are binding restrictions to invest in shares, then long-term bonds and/or loans will be in high demand. Finally, in Australia, contractual savings institutions invest more than 50 percent of their portfolios in shares and long-term bonds; while they represent about 40 percent in other institutional investors' portfolios.

Thus, according to the evidence, if there were a reallocation of assets from the banking sector to the contractual savings sector, there would be a shift in the relative demands for financial instruments. There would be a reduction in the demand for nontraded financial instruments, or in other words, we would observe a reduction in the supply of funds to be lent to firms in the non-corporate sector (i.e., firms that do not issue publicly traded stock and debt), and there would be an increase in the demand for publicly traded financial instruments such as stocks and bonds.

Moreover, the fact that the portfolio weight of long-term bonds is high for contractual savings institutions means that the corporate sector will have additional longterm funds to finance their long-term production plans. As a consequence, the profit opportunities in the corporate sector will induce the entry of new firms that will issue both equity and debt, increasing the market capitalization of the economy, and thus, the market will become more liquid and the value traded in stocks will increase. Finally, the increased volume of transactions will imply a higher demand for money (transaction motive) and overall financial deepening in the economy.

The international evidence suggests some stylized facts about contractual savings institutions. The fraction of investment in either shares or long-term assets (either bonds or loans) tends to be very high. In all the cases, the weight of short-term loans is very low. Obviously, regulations, relative yields, risk and liquidity preferences, and tax treatment could explain the differences in portfolios across these countries. The evidence also suggests that if binding constraints are imposed on the fraction invested in shares, they will try to invest their funds in the closer substitutes such as long-term bonds and long-term loans. The result will be a differential impact on the productive sector of the economy and on the structure of the financial sector.
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Figure 9: Institutional Investors' Portfolio <!-- Start of picture text --> UK-PortfolIos of Life Ineorens _ UK-Portfolio, of Pension Fund. UK-Portfolios of Open-end<br>Cop.n.,s (1990-1995) :198,.1995) Invelmmont Compenles<br>sT Loonse 1t% LT L.-<br>Oth., T ':.~~~~~~~~~~~~~TBl l SSTfln d<br>:~,ILC I LT S TS nd1<br>TLT Bond<br>Shoroc ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ h<br>N eth-iend-Portfo .of Life N.th-S e n- d-Porffollo of NPth.orends-P.rtfotoe. of<br>Inourne Cmp.nlo Ponsion Funds (1980-1995) tnveetm.ent Compenle<br>LToas (190-1999) .. -, LToa LTBil d. )1980-199B)<br>Ot ~ Shore 1a% 12% M<br>SThe "'" 16% nd% ST Loons la t rl l t<br>ST L. IIn LT Bonds 0d C.si<br>-nd Cssh 2 a SBi |ST 17% LT Bond<br>0% STSll ST Loose-<br>01% Rood ~~~~~~~~~ end ~ - LT~~~~~~~~~~~dB.d Coonn<br>LT .l Bnd B LT Loose TB.ndTod T Loon. end~~~~~~~L *dBnsLTo L-nd<br>ST Sill. LB ST Bondi ii LT Bonds<br>Olsonrr LoO irf oenon ler S sl l rl<br>Aotrst Ie-Lifo 0th , In.o....e T..l L- 2% Ao.t,.lI.-Portfo Oth. 9%~~O I1os of Auetreto-Ope..nd 01h0 I-onst-Os % te Oar<br>Co (pn8e- (19BB1995) on F.n ond d 9 B119955 C -on 198819955<br>end Bonde<br>LTBond. ST Bil LTd BondST111,1<br>Su dr -P-ce:. In 00rn5 C.nsp.ei.. of Lifs Sweden-PorOfolios of Pension S19d97PorffolofOpeBdSenvetseni Companeete<br>(1990-1995) F und s (11 9 0-1 995) (1990-1995)<br>Told L-o<br>ST B.H.% Told Loos and Cessh C 14% O.h m oj_ % r 4% 6% hs 1 1 ST ToW too nd 5, dC. 5%STA 7% 1% B%1 Olson 5 _ Shors l l T.W L-n3 nd a~~~~~~~~~~~~~~~S- .h . ed C.Mhn ISh %3Oh 1<br>.nd B.nds L ndB Sn.d B-d.<br>To'^i Bonds Loan- | t | w TolalLoanst LT 4ii % 1 1 i11111~~~~~~ Sh..<br>ST ~ Bil. SBil d CT.,s T o<br>54%78<br>LT Bonds LT Bends<br>N.m.ny.loortf.iios of Life Non-ny.P-tfoli.. of Penion N.rw.y.Portfoltee of Opec-sod<br>10 eneComlpeni. 0F nds (1980-1995) 5 Os-met Compeniss<br>980 995gs (1995 1999)<br>Oth. Sh.- Ot- 3% li% Oth.~~~~hons<br>4% 0% T en CaI 9%<br>( U ~~~~~~~~~~~~~~~ST Bel<br>Tola Loa,ns t<br>LTB.nd. and Cooh LT 00n00<br>1% 8<br>S ~~~~~~~~~~~ST SBil LT Bonds<br>and 01nd. and Bonde<br>Source: OECD, Instituotional Investors Yearbook, 1997.<br><!-- End of picture text -->
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# **V Econometric Evidence on Contractual Savings and Capital Markets Development: Which Leads?**

This paper has emphasized the direction of causality from contractual savings to market capitalization. In Sections II and III, we argued that if contractual savings are developed then market capitalization would follow. In Section IV, we showed evidence of a positive correlation between these two variables across countries but the causality between them was not studied.

It has been indicated (in the literature) that it is difficult for contractual savings. institutions to perform their investment activities effectively in countries whose capital markets are small and illiquid. For instance, the implementation of some active and sophisticated financial strategies require very frequent trading and given the large volume of funds managed by pension funds, the price volatility implied by these strategies would be too high if the stock market is not liquid enough. As Davis (1995) states: "Experience,..., suggests that the successful development of private pensions requires a certain prior level of development of the financial sector." Hence, at least theoretically, the direction of causality could run from market capitalization to contractual savings.

The empirical questions addressed in this section are the following. What happened in each country over time? Does the growth of contractual savings lead to the expansion in market capitalization? Or is it the other way around? Or is it a two-way causation? Or is there no causation in any direction? To answer these questions, we ran Granger causality tests for some OECD and some developing countries. Unfortunately, the number of observations available for each country is not ideal. Hence, the tests presented below provide us with just preliminary answers to our questions. Nevertheless, the results obtained are quite encouraging and deserve to be taken into consideration.

The bivariate Granger causality test analyzes how useful some variables are in forecasting other variables. In this sense, we can say that if variable x is not useful in forecasting y, then x does not Granger-cause y. The test is constructed on the basis of the following OLS regression: where p and q are chosen so that u, is white noise. The test conducted is an F test on the q parameters for the variable x. If the regression is run over n observations, the distribution of the test is F(n, _n_ - 2q - 1). Since the above regression is a dynamic regression, the test is only asymptotically valid. Hence, an asymptotic equivalent test distributed as a X2(q) was reported. **16**

> 16 For a detailed description of Granger causality tests, see Granger (1969) and Harnilton (1994).
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In our study we analyze Granger causality tests between four sets of institutions: 1) contractual savings financial assets over GDP (CS); 2) pension funds financial assets over GDP (PF); 3) life insurance financial assets over GDP (LI); and 4) non-life insurance financial assets over GDP (NL); and two capital market development indicators: 1) market capitalization over GDP (MC); and 2) stock value traded over GDP (VT) for 14 OECD and 5 developing countries taken separately and for periods between 1975 and 1997. In each case, we are interested in the causality between each of the four asset variables and market capitalization and value traded in turn. Tables A-D in Appendix 1 present the Granger causality tests for contractual savings, pension funds, life insurance, and non-life insurance, respectively.

Because our panels are relatively short, we decided to limit the length of the twolag polynomial in order to maximize the number of observations used in the regressions. Hence, we selectedp = q = 1. Finally, because all our regressions use less than 30 observations we also reported the Jarque-Bera test for normality of residuals."<sup>7</sup> The importance of this test is that since we cannot invoke the central limit theorem to justify the distribution of the Granger-causality tests, our results critically depend on the normality of the residuals.

As an example for the interpretation of our results, we will describe in detail the case of the causality test between contractual savings (CS) and market capitalization (MC) or contractual savings and value traded (VT) for the United States which are reported in Table 8 of Appendix 1. The Granger regressions were conducted using 17 observations. In the first line, we test the null hypothesis that contractual savings do not Granger-cause market capitalization. Since p = q = 1, we have 3 d.f. that we have to account for and hence, under the null, the F test is distributed with 1 and 14 d.f. The value of the statistics is 0.035 with a p-value of 0.854. Clearly, we cannot reject the null that contractual savings do not Granger-cause market capitalization. This is confirmed by the asymptotic equivalent test in the following 3 columns, distributed under the null as X<sup>2</sup> (1). For this second test, the statistics is 0.043 with a p-value of 0.837. Finally, in the last 3 columns we report the Jarque-Bera (JB) normality test. Here, the null hypothesis is that residuals are normally distributed, which cannot be rejected. The statistics for this test is 1.060 which under the null is distributed as a X<sup>2</sup> (2) and it gives a p-value of 0.59. Since we can infer that residuals are normally distributed we can also infer that the statistics of the Granger tests are distributed as they should be.

The second line of Table 8 in Appendix 1 tests the null hypothesis that market capitalization (MC) does not Granger-cause contractual savings (CS). Again the null cannot be rejected in both tests and residuals are normally distributed. The last two lines for the United States in Table 8 in Appendix 1 give us the results of the causality tests between contractual savings (CS) and value traded (VT). The absence of causality in both directions cannot be rejected and residuals are normally distributed.

17 See Bera and Jarque, 1980.
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In the next sections, we summarize the results reported in the tables in Appendix 1 by using 10 percent significance level as the critical level for rejecting or failing to reject the null hypothesis in each test.

# **_V. 1 Granger causality between contractual savings and market capitalization or value traded_**

For market capitalization we found 7 cases out of 14 OECD countries (United Kingdom, Belgium, Spain, Netherlands, Canada, Finland, Germany), for which the hypothesis that contractual savings do not Granger-cause market capitalization is rejected and the hypothesis that market capitalization does not Granger-cause contractual savings is not rejected. Therefore, for these countries, it appears that Granger causality runs only from contractual savings to market capitalization and not the other way round. For 2 OECD countries (Norway and Portugal), Granger causality between contractual savings and market capitalization seems to run in both direction. 18 Finally, for 5 OECD countries (United States, Australia, Korea, Sweden, and Austria) both null hypotheses can not be rejected. Therefore, for these countries, the variables contractual savings and market capitalization follow independent auto-regressive processes and neither contractual savings cause market capitalization nor does market capitalization cause contractual savings. For developing countries, causality seems to run from contractual savings to market capitalization only in Thailand;1<sup>9</sup> in both ways for Chile and South Africa; and in neither direction for Singapore and Malaysia.<sup>2 0</sup> For value traded, we found 6 OECD countries (United Kingdom, Korea, Norway, Sweden, Finland, and Austria), for which the null hypothesis that contractual savings does not Granger-cause value traded was rejected while the null hypothesis that value traded does not Granger-cause contractual savings could not be rejected. Hence, for these countries causality between contractual savings and value traded seems to run from contractual savings to value traded only. For 2 OECD countries (Netherlands, and Germany) Granger causality from value traded to contractual savings seems to run in both directions.<sup>2</sup> 1 For 6 OECD countries (United States, Belgium, Australia, Spain, Canada, and Portugal), causality between contractual savings and value traded seems to run in neither direction. For 2 non-OECD countries (Chile and Thailand), causality seems to run from contractual savings to value traded only. For Singapore and South Africa, causality seems to run from value traded to contractual savings only. Finally, for

> 1 8 Although at 5 percent significance level, causality between market capitalization and contractual saving **s** eems to run from contractual savings to market capitalization only for Norway. 19 Although at 5 percent significance level, causality between market capitalization and contractual saving **s** eems to run from contractual savings to market capitalization only for South Africa.

> 20 Notice that the results for Malaysi **a** nd South Africa should be taken as suspicious as normality test was not always passed at _5_ percent significancl **e** vel.

> 21 Notice that the results for Germany should be taken as suspicious as normality test was not always passed even at 5 percent significancl **e** vel.
- 23 -

Malaysia, there seems to be no causality between contractual savings and value traded in either direction.<sup>22</sup>

# **_V.2 Granger causality between pension funds and market capitalization or value traded_**

Since the intersection between the data on pension funds and life insurance companies is not complete and Granger causality tests are very sensitive to the number of observations and lags used, we decided to run the same exercise of the previous section for life insurance and pension funds separately. We also explored the causality between market capitalization or value traded and non-life insurance. In a following section, we summarize these results and compare them with the results on life insurance and pension funds.

Results on causality between pension funds and market capitalization or value traded are reported in Table 9 in Appendix 1. For market capitalization, we found 6 cases out of 14 OECD countries (Korea, Spain, Netherlands, Canada, Norway, Sweden, and Finland), for which the hypothesis that pension funds do not Granger-cause market capitalization is rejected and the hypothesis that market capitalization does not Grangercause pension funds is not rejected. Therefore, for these countries, it appears that Granger causality runs only from pension funds to market capitalization and not the other way round.<sup>23</sup> For Portugal, causality seems to run in both directions.<sup>24</sup> For Belgium, Granger causality between pension funds and market capitalization seems to run from market capitalization to pension funds.<sup>25</sup> Finally, for 4 OECD countries (United States, United Kingdom, Australia, Germany, and Austria), both null hypotheses can not be rejected. Therefore, for these countries the variables pension funds and market capitalization follow independent auto-regressive processes and neither pension funds causes market capitalization nor market capitalization causes pension funds. In Thailand and South Africa, causality seems to run from pension funds to market capitalization. In Chile causality between pension funds and market capitalization seems to run in both directions. In Singapore and Malaysia, causality between pension funds and market capitalization seems to run in neither direction. 26 For value traded, we found _5_ OECD countries (United Kingdom, Belgium, Korea, Norway, Sweden, and Finland), for which only the null that pension funds do not cause value traded could be rejected. Hence, for these countries, it appears that Granger causality runs only from pension funds to value traded and not the other way round. For 22 Notice that the results for Singapore and Malaysia should be taken as suspicious as normality test was not always passed at _5_ percent significance level. 23 Although at 5 percent significance level, there seems to be no causality between market capitalization and pension funds in either direction for Korea and Sweden. 24 But only from pension funds to market capitalization at 5 percent significance level.

25 Although at _5_ percent significance level, no causality between market capitalization and pension funds seems to exist in either direction for Belgium.

26 For South Africa, Thailand, and Malaysia normality test was not always passed and results should be treated with caution.
- 24 -

3 OECD countries (Australia, Netherlands, and Austria), causality between pension funds and value traded seems to run in both directions. For 5 countries (United States, Spain, Canada, Germany, and Portugal) causality between pension funds and value traded seems to run in neither direction. For the developing countries in our sample, two way causality was found only for Chile while all other countries do not show causality significant in either direction.<sup>27</sup>

# **_V.3 Granger causality between life insurance and market capitalization or value traded_**

In the case of life insurance, we have longer series as shown in Table 10 in Appendix 1. For market capitalization, we found 9 OECD countries (United Kingdom, Belgium, Netherlands, Canada, Norway, Finland, Germany, Austria, and Portugal) for which causality seems to run from life insurance to market capitalization only. For all other OCED countries, we found no causality in either direction between life insurance and market capitalization. For developing countries the results are mixed: for Thailand, causality seems to run from life insurance to market capitalization;<sup>28</sup> while for South Africa, causality seems to run in both directions;<sup>29</sup> and for Chile, Singapore, and Malaysia, causality between life insurance and market capitalization seems to run in neither direction.

For value traded, we found 6 OECD countries (United Kingdom, Korea, Norway, Sweden, Finland, and Portugal) for which causality between life insurance and value traded seems to run from life insurance to value traded only. For the Netherlands and Germany, causality seems to run in both ways. For 5 countries (United States, Belgium, Australia, Spain, and Austria) no causality in either direction was found. For developing countries, we found causality from life insurance to value traded only in Chile, Singapore, and Malaysia. We found a two way causality in Thailand and from value traded to life insurance only in South Africa.

# **_V.4 Granger causality between non-life insurance and market capitalization or value traded_**

In the case of non-life insurance results are shown in Table 11 of Appendix 1. We found 6 OECD countries (Belgium, Korea, Netherlands, Sweden, Germany, and Austria) for which causality runs from non-life insurance to market capitalization only. We found two countries (Norway and Portugal) for which causality between non-life insurance and market capitalization runs in both directions. We found 5 countries (United States, United Kingdom, Spain, Canada, and Finland) for which no causality was

> **27** Results for developing countries should be taken with caution as normality test was not always

gassed.

> **'28** But not at 5 percent significance level.

**29** But only from life insurance to market capitalization at 5 percent significance level. Again, results for developing countries should be taken with caution as normnali **t** y est was not always passed.
- 25 -

found between non-life insurance and market capitalization. For developing countries, the picture is mixed: for Thailand, we found causality in both directions; for Singapore and Malaysia, we found causality from market capitalization to non-life insurance only; and for Chile and South Africa, we found no causality in either direction.

For value traded, we found 4 OECD countries (United Kingdom, Netherlands, Norway, and Finland) for which causality runs from non-life insurance to value traded only; 3 countries (Sweden, Germany, and Portugal) for which causality runs in both ways; Australia, for which causality seems to run from value traded to non-life insurance only; and 6 countries (United States, Belgium, Korea, Spain, and Austria) with no causality in either direction between non-life insurance and value traded. In developing countries, we found Chile, Malaysia, and South Africa for which causality runs from nonlife insurance to value traded only; in Thailand, causality seems to run in both directions; and in Singapore, causality seems to run from value traded to non-life insurance.

# **_V.5 Summary of results_**

The following table helps summarize the results obtained with the Granger causality tests. The first column in each quadrant (->) reports the number of countries for which we found Granger causality from one of the institutions (contractual savings, pension funds, life insurance, non-life insurance) to one of the market indicators (market capitalization or value traded); the second column reports the number of countries for which causality runs only from one of the markets to one of the institutions (<-); the third column reports the number of countries for which causality runs both ways (<->); and the fourth column reports the number of countries for which no causality was found in either direction (<>).

**Table** 3: **Granger causality tests: summary**

||||**M**|**c**|||**V**|**T**||
|---|---|---|---|---|---|---|---|---|---|
||CS|7|0|2|5|6|0|2|6|
|c|**PF**|**7**|**1**|**1**|**5**|6|0|3|**5**|
||o**U**|<br>9|0|0|5|6|1|2|5|
||**NL**|6|2|1|5|4|1|3|6|
|**O**|CS|2<br>|0<br>|1<br>|2<br>|2<br>|2<br>|0<br>|1<br>|
||PF|2|0|1|2|0|0|1|4|
|(?|U|1|0|1|3|3|1|1|0|
|2|**NL**|0|2|1|2|3|1|1|0|

There is significant evidence in these data that either causality between institutions and markets does not exist, or if it exists, it is predominantly from institutions to markets only. To a lesser extent, causality simultaneously exists in the two directions between institutions and markets. Furthermore, there is very limited evidence that causality runs from markets to institutions only (the only exception seems to be for nonlife insurance in developing countries). Results seem to support the idea that the
- 26 -

development of institutional investors is likely to promote the development of market capitalization more than value traded. For developing countries, pension funds seem not to Granger cause value traded development while life and non-life insurance do. Thus, in developing countries pension funds predominantly buy and hold shares.

The following tables allow us to analyze other causality patterns among the countries in our sample. Table 4 lists, by institution, the countries for which we find one way Granger causality from institutions to market capitalization or value traded only; these are indicated with a "1". Table 5 lists, by institution, the countries for which we find a two way Granger causality between institutions and markets. Table 6 lists, by institution, the countries for which we could not find Granger causality between institutions and market on either direction.

When causality exists only from institutions to markets this seems to take place in countries where financial markets are not yet completely developed. In countries with complete and sophisticated financial markets like the United States, no causality is found in either direction. Notice though that results are ambiguous for some countries. For example, in Korea, pension funds and non-life insurance seem to Granger-cause market capitalization while life insurance and in general contractual savings seem not to cause market capitalization. For this country causality is stronger among institutions with respect to value traded. In the United Kingdom, all institutions seem to Granger-cause value traded and only contractual savings and life insurance companies, market capitalization.

**Table 4: Granger causality (one way) from institutions to markets only**

||||**M**|**C**|||||**VT**|||
|---|---|---|---|---|---|---|---|---|---|---|---|
||**CS**|**PF**|**LU**|**NL**|**TOT**||**CS**|**PF**|**U**|**NL**|**TOT**|
|**NLD**<br>|1|1|1|1|4|**FIN**<br>|1|1|1|1|4|
|**BEL**<br>|1||1|1|3|**GBR**<br>|1|1|1|1|4|
|**CAN**<br>|1|1|1||3|**NOR**<br>|1|1|1|1|4|
|**DEU**<br>|1||1|1|3|**CHL**<br>|1||1|1|3|
|**FIN**<br>|1|1|1||3|**KOR**|1|1|1||3|
|**THA**<br>|1|1|1<br>||3<br>|M**SWE**<br>|1|1|1<br>||3|
|**AUT**<br>|||1|1|2|**MYS**<br>|||1|1|2|
|**ESP**<br>|1|1|||2|I**AUT**|1||||1|
|**GBR**<br>|**1**||1||2|**BEL**<br>||1|||1|
|**KOR**<br>||1||1|2|**7NLD**<br>||||1|1|
|**NOR**<br>||1|1||2|**PRT**<br>|||1||1|
|**SWE**<br>||1||1|2|**SGP**<br>|||1||**1**|
|**ZAF**|1|1|||2|**THA**|1||||1|
|**PRT**|||1||1|**ZAF**||||1|1|
|**AUS**<br>|||||0|**AUS**<br>|||||°|
|**CHL**|||||0|**CAN**|||||0|
|**MYS**|||||**0**|**DEU**|||||O|
|**SGP**|||||**0**|**ESP**|||||**0**|
|**USA**|||||**0**|**USA**|||||0|
|**TOT**|9|9|10|6||**TOT**|8|6|9|7||

**Notes** See Table 12 in Appendix 2 for the list of countries.
- 27 -

Table 5: Granger causality (two ways) between institutions and markets

||||Mc||||||**VT**|||
|---|---|---|---|---|---|---|---|---|---|---|---|
||CS|**PF**|**U**|**NL**|TOT||CS|PF|**U**|**NL**|TOT|
|**PRT**|1|1||1|3|**DEU**<br>|1||1|1|3|
|**CHL**|1|1|||2|**NLD**|1|1|1||3|
|**NOR**|<br>1|||1|2|**THA**<br>|||1|1|2|
|**THA**||||1|1|**AUS**||1|||1|
|**ZAF**|||1||1|**AUT**<br>||1|||1|
|**AUS**|||||0|**CHL**||1|||1|
|**AUT**|||||0|**PRT**||||1|1|
|**BEL**|||||0|**SWE**||||1|1|
|**CAN**|||||0|**BEL**|||||o|
|**DEU**|||||0|**CAN**|||||**0**|
|**ESP**|||||0|**ESP**|||||**0**|
|**FIN**|||||0|**FIN**|||||0|
|**GBR**|||||0|**GBR**|||||**0**|
|**KOR**|||||0|**KOR**|||||**0**|
|**MYS**|||||**0**|**MYS**|||||**0**|
|**NLD**|||||0|**NOR**|||||0|
|**SGP**|||||0|**SGP**|||||0|
|**SWE**|||||0|**USA**|||||0|
|**USA**|||||**0**|**ZAF**|||||**0**|
|TOT|3|2|1|3||TOT|2|4|3|4||

Notes: See Table 12 in Appendix 2 for the list of countries.

Table 6: No Granger causality between institutions and markets

||||MC||||||VT|||
|---|---|---|---|---|---|---|---|---|---|---|---|
||**CS**|**PF**|**U**|**NL**|**TOT**|<br>|CS|**PF**|**U**|**NL**|**TOT**|
|**USA**|1|1|1|1|4|**ESP**<br>|1|1|1|1|4|
|**AUS**|1|1|1||3|**USA**<br>|1|1|1|1|4|
|**MYS**|1|1|1||3|**BEL**<br>|1||1|1|3|
|**SGP**|1|1|1||3|**CAN**<br>|1|1||1|3|
|**AUT**|1|1|||2|**AUS**|1||1||2|
|**CHL**<br>|||1|1|2|**iMYS**<br>|1|1|||2|
|**ESP**<br>|||1|1|2|**PRT**<br>|1|1|||2|
|**GBR**<br>||1||1|2|**AUT**<br>||||1|1|
|**KOR**<br>|<br>1<br>||1||2|**CHL**<br>|||1||1|
|**SWE**<br>|<br>1||1||2|**DEU**<br>||1|||1|
|**CAN**||||1|1|**KOR**<br>||||1|1|
|**DEU**<br>||1|||1|**SGP**<br>||1|||1|
|**FIN**||||1|1|**THA**||1|||1|
|**ZAF**||||1|1|**ZAF**||1|||1|
|**BEL**|||||0|**FIN**<br>|||||0<br>|
|**NLD**|||||0|**GBR**|||||0|
|**NOR**|||||**0**|**NLD**|||||**0**<br>|
|**PRT**|||||**0**|**NOR**|||||**0**|
|**THA**|||||0|**SWE**<br>|||||0|
|**TOT**|7|7|8|7||**TOT**|7|9|5|6||

Notes: See Table 12 in Appendix 2 for the list of countries.

There are other facts that help interpret some of our results. For example, the absence of causality in either direction in Malaysia and Singapore could be explained by the contractual savings regime in these countries as well as financial sector policies.
- 28 -

Singapore and Malaysia have centrally managed provident funds, which are not geared at investing in shares. In Malaysia, contractual savings institutions invested in shares from 4 to 7 percent of their financial assets during 1987-93. Singapore only recently has allowed some members to pick private managers and to determine how a portion of their Central Provident Fund balance will be invested.<sup>30</sup> Therefore, there should be no surprise that there is no causality in any direction between contractual savings and stock markets in these countries.

**Table** 7: **Shares of Stocks in Investment Portfolios: Selected Countries**

|**Country**|**Year**|**Contractual**|**Life**|**Pension**|
|---|---|---|---|---|
|||**Savigs**||**Funds**|
|**Malaysia**<br>|1993|7.01|17.86|5.17|
|**Singapore**|1996|5.67|33.50|0. 00|

**Source:** WB institutional investors database.

Another particular case is Chile, where causality for pension funds runs in both directions. This could be explained, in great part, by their investment regulations. When the system was introduced, they were quite draconian, at that time; the Government was mainly interested in preserving assets, hence, pension funds were allowed to invest almost exclusively in government securities. In addition, real interest rates on bonds and bills were very high. As the system and the market developed, the regulations allowed increasing participation of shares in pension fund portfolios. At the same time, real interest rates were declining thus demand for shares increased fueled by both effects. Obviously, regulation of investment policies of these institutions and after tax rates of return on financial instruments matters.<sup>31</sup> The cautiousness and reactive approach followed by the Chilean authorities resulted in a two-way causality.

The evidence is consistent with the direction of causality emphasized in this paper. Contractual savings promote capital market development in countries where capital markets are relatively small. Of course, in countries where capital markets are already developed, the effect is not as strong and the direction of causality is not as clear. In those countries, we expect reciprocal and weaker effects between both variables. The latter would be, in part, due to the fact that the illiquidity effect of contractual savings, as discussed above, would be diluted in countries with well-developed financial markets.<sup>32</sup>

> 30 See Asher, 1999.

31 See Srinivas, Whitehouse and Yermo, 1999. 32 The direction of causality from contractual savings to capital markets was also accepted in Impavido and Musalem (2000).
- 29 -

# **VI Summary, Conclusions and Recommendations**

Contractual savings are powerful enough to increase the supply of long-term funds and develop the capital markets in an economy. This is because contractual savings institutions have long-term and illiquid liabilities on their balance sheets.

We argued that contractual savings development, in addition to its primary purpose of providing protection to the insured, produces the following effects: a) specialization in the financial sector where the banking system adjusts towards its comparative advantage as contractual savings grow, thus reducing banks exposure to term transformation risks; b) improvement in the financial structure of firms by reducing their leverage and refinancing risks; c) impact on the term structure of interest rates, the stock market and growth; d) reduce the implicit debt from unfunded liabilities of definedbenefit plans; and e) develop the market for long-term government bonds and increase possibilities of public debt management. We also argued that these effects must be stronger in developing countries than in developed ones, due to the instability of banks in developing countries. Therefore, contractual savings mitigate social and financial risks, thus improving the resilience of the economy to shocks, reducing the country risk premium, the level of interest rates, and the cost of capital, thereby promoting growth.

In addition, the growth of contractual savings or either mutual funds or non-life insurance should produce different effects on capital markets. Contractual savings should be more powerful in developing capital markets because of the additional effect on the liquidity of households' and firms' assets.

In the empirical analysis we showed that those countries with more developed contractual savings sectors are also the countries with more developed stock markets, both in terms of market capitalization and value traded. In addition, those countries where the contractual savings sector grew the most are also the countries that experienced the highest growth in market capitalization and value traded.

In the analysis of causality between contractual savings and both market capitalization and value traded, the evidence strongly favors causality from contractual savings to market capitalization, particularly, in countries where capital markets are relatively small and have an enabling regulatory and policy environment. These results are confirmed by differentiating, with contractual savings institutions, between pension funds and life insurance companies. Causality between other institutional investors, like non-life insurance companies, and markets appear to be much weaker.

For OECD countries, the direction of causality from contractual savings to stock markets and liquidity predominates. The small sample of developing countries results are mixed with Chile exhibiting causality in both directions, while Malaysia and Singapore exhibit little if any form of causality between institutions and markets. In these two countries, the fact that management is public and the governments have severely restricted investments in domestic capital markets is probably responsible for this result.
- 30 -

Countries interested in developing contractual savings are usually confronted with the issue of having underdeveloped capital markets. Hence, sequencing of reforms is important. Our analysis suggests that significant benefits will be derived from developing contractual savings even if capital markets have not reached their appropriate level of development. Initially, contractual savings institutions could invest primarily in government securities, corporate bonds and long-term loans, and to the extent possible, in shares and foreign securities.3 This would be equivalent to a strategy combining Chile and the Netherlands. The difference is that Chile, at the beginning of its pension reform, did not allow investmnents in shares, loans or foreign securities while it allowed investments in bank deposits.<sup>34</sup> Such a strategy could work in an environment of fiscal discipline and sound banking supervision. This is why we believe that long-term loans to the private sector offer better prospects as evidenced by the Netherlands. Simultaneously, the authorities should start improving the regulatory framework for capital markets development (bond and stock markets), including regulations on assetbacked securities (e.g., mortgage bonds), futures and derivatives. As the market develops, investment regulations covering contractual savings institutions could become more flexible while moving from non-market based instruments (e.g., loans) to market based securities and ultimately adopting the prudent person rule.

Thus, the strategy advocates a comprehensive approach to contractual savings and capital market development. We believe that it will provide greater benefits than first pursuing capital market development and only then promoting contractual savings. Both should be pursued simultaneously.

Obviously, a successful reform requires an enabling macroeconomic environment, a sound banking system as well as reliable financial sector regulation and supervision, and an appropriate tax treatment.

> 33 hInvestment inforeign securities provides the potential for risk diversification to the insured (if investments are made in markets which have low or negative correlation with the local market) and could have a direct effect of preventing development of domestic capital markets. However, it signals that the govemment is commnitted tohaving an open capital account which may induce higher capital inflows and an indirect positive effect on capital markets. Hence, the net result could be positive.

34 At the beginning of Chile's pension reform, the investment regulations allowed up to 100 percent in govemment securities, up to 60 percent in corporate bonds, and up to 70 percent in each of the following categories: mortgage-backed securities, letters of credit or fixed term deposits. As the market developed, regulations were relaxed to allow investments in shares, mutual funds, real estate funds, venture capital funds, securitised credit funds, foreign securities and hedging instruments.
- 31 -

# **VII Appendix 1: Granger causality tests**

- **Table 8: Contractual savings Granger causality tests**

|**Country**|**Obs**|||||**Gra**|**nger**|||||**JB**||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|||||||_Statl_|_pvall_||_Stat2 p_|_v/2_||_Stat_|_pval_|
|United States|17|CS|->|MC|F(1,14)|0.035|0.854|Chi2(1)|0.043|0.837|Chi2(2)|1.060|0.590|
||17|MC|-?|CS|F(1,14)|0.707|0.414|Chi2(1)|0.859|0.354|Chi2(2)|0.248|0.884|
||17|CS|-,|VT|F(1,14)|0.494|0.494|Chi2(1)|0.600|0.439|Chi2(2)|2.060|0.357|
||17|VT|-,|CS|F(1,14)|0.294|0.596|Chi2(1)|0.357|0.550|Chi2(2)|0.301|0.860|
|United Kingdom|<br>17|CS|->|MC|F(1,14)|4.120|0.062|Chi2(1)|5.000|0.025|Chi2(2)|0.753|0.686|
||<br>17|MC|-,|CS|F(1,14)|0.108|0.747|Chi2(1)|0.131|0.717|Chi2(2)|0.349|0.840|
||17|CS|-|VT|F(1,14)|4.000|0.065|Chi2(1)|4.850|0.028|Chi2(2)|5.630|0.060|
||17|VT|->|CS|F(1,14)|0.127|0.727|Chi2(1)|0.154|0.694|Chi2(2)|0.599|0.741|
|Belgium|16|<br>CS|->|MC|F(1,12)|2.870|0.116|Chi2(1)|3.59|0.058|Chi2(2)|0.286|0.867|
||15|MC|-|CS|F(1,12)|0.010|0.922|Chi2(1)|0.013|0.911|Chi2(2)|1.540|0.463|
||16|CS|-,|VT|F(1,12)|1.750|0.211|Chi2(1)|2.180|0.140|Chi2(2)|2.560|0.278|
||15|<br>VT|-,|CS|F(1,12)|0.039|0.847|Chi2(1)|0.048|0.826|Chi2(2)|<br>1.510|<br>0.469|
|Australia|9|CS|>|MC|<br>F(1,6)|0.904|0.378|Chi2(1)|1.360|0.244|Chi2(2)|0.203|0.904|
||9|MC|->|CS|F(1,6)|0.117|0.744|Chi2(1)|0.176|0.675|Chi2(2)|1.370|0.503|
||9|<br>CS|-,|VT|<br>F(1,6)|1.440|0.275|Chi2(1)|2.160|0.141|Chi2-(2)|1.270|<br>0.531|
||9|VT|__,_|CS|F(1,6)|0.984|0.359|Chi2(1)|1.480|0 .224|Chi2(2)|<br>0.558|<br>0.756|
|Korea|17|CS|-,|MC|F(1,14)|0.007|0.935|Chi2(1)|0.008|0.927|Chi2(2)|4.300|0.117|
||17|<br>MC|->|CS|F(1,14)|0.284|0.603|Chi2(1)|0.345|0.557|Chi2(2)|<br>5.820|<br>0.055|
||17|CS|-,|VT|F(1,14)|3.550|0.081|Chi2(1)|4.310|0.038|Chi2(2)|<br>1.350|<br>0.509|
||17|<br>VT|_,|<br>CS|F(1,14)|0.356|0.560|Chi2(1)|<br>0.432|0.511|Chi2(2)|<br>2.820|<br>0.245|
|Spain|13|<br>CS|->|MC|F(1,10)|4.230|0.067|Chi2(1)|5.510|0.019|Chi2(2)|<br>1.590|<br>0.451|
||13|<br>MC|->|CS|F(1,10)|0.042|<br>0.841|Chi2(1)|0.055|0.814|Chi2(2)|<br>0.546|0.761|
||13|<br>CS|->|VT|_F(1,10)_|0.644|<br>0.441|Chi2(1)|<br>0.837|0.360|Chi2(2)|<br>1.430|0.489|
||13|<br>VT|_,|<br>CS|F(1,10)|0.501|0.495|Chi2(1)|<br>0.651|0.420|Chi2(2)|<br>0.196|0.907|
|Netherlands|17|<br>CS|-,|MC|F(1,14)|7.090|<br>0.019|Chi2(1)|<br>8.610|0.003|Chi2(2)|<br>1.400|0.496|
||17|<br>MC|->|CS|F(1,14)|0.270|<br>0.612|Chi2(1)|<br>0.327|0.567|Chi2(2)|<br>0.697|<br>0.706|
||17|<br>CS|_>|<br>VT|F(1,14)|4.280|<br>0.058|Chi2(1)|<br>5.200|0.023|Chi2(2)|<br>0.426|<br>0.808|
||17|<br>VT|->|CS|F(1,14)|5.260|<br>0.038|Chi2(1)|<br>6.380|0.012|Chi2(2)|<br>1.790|<br>0.408|
|Canada|17|<br>CS|-,.|MC|F(1,14)|3.740|<br>0.074|Chi2(1)|<br>4.540|0.033|Chi2(2)|<br>1.490|<br>0.474|
||17|<br>MC|->|CS|F(1,14)|0.001|<br>0.972|Chi2(1)|<br>0.002|0.969|Chi2(2)|<br>0.162|<br>0.922|
||17|<br>CS|-,|VT|F(1,14)|2.030|<br>0.171|Chi2(1)|<br>2.530|0.112|Chi2(2)|<br>0.437|<br>0.804|
||17|<br>VT|->|CS|F(1,14)|0.592|<br>0.454|Chi2(1)|<br>0.719|0.396|Chi2(2)|<br>0.242|<br>0.886|
|Norway|15|CS|->|MC|F(1,12)|3.830|0.072|Chi2(1)|4.850|0.028|Chi2(2)|0.264|0.B77|
||15|MC|-|CS|F(1,12)|2.330|<br>0.153|Chi2(1)|<br>2.910|0.088|Chi2(2)|<br>0.528|<br>0.768|
||16|<br>CS|-,|VT|F(1,13)|4.120|<br>0.063|Chi2(1)|<br>5.070|0.024|Chi2(2)|<br>0.497|<br>0.780|
||16|<br>VT|-,|CS|F(1,13)|0.000|<br>0.996|Chi2(1)|<br>0.000|0.995|Chi2(2)|<br>0.680|<br>0.712|
|Sweden|12|<br>CS|-,|MC|<br>F(1,9)|1.280|<br>0.291|Chi2(1)|<br>1.680|0.195|Chi2(2)|<br>0.921|<br>0.631|
||12|<br>MC|-|CS|F(1,9)|0.012|<br>0.914|Chi2(1)|<br>0.017|0.898|Chi2(2)|<br>0.102|<br>0.950|
||12|<br>CS|->|VT|<br>9(1,9)|4.910|<br>0.054|Chi2(1)|<br>6.540|0.011|Chi2(2)|<br>0.273|0.873|
||12|<br>VT|->|CS|<br>F(1,9)|0.130|<br>0.727|Chi2(1)|<br>0.173|0.678|Chi2(2)|<br>0.255|<br>0.880|
|Finland|7|<br>CS|_>|<br>MC|<br>F(1,4)|7.600|<br>0.051|Chi2(1)|13.300|0.000|Chi2(2)|<br>0.732|<br>0.832|
||7|<br>MC|->|CS|<br>F(1,4)|<br>0.033|0.865|Chi2(1)|<br>0.057|0.811|Chi2(2)|<br>0.367|0.832|
- 32 -

|**Country**|**0**77^00<br>**Obs**|000<br>**0**|00<br>;000|00||**G**|**g7;g**|**r**||||**JB**||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|||||||<br>:_Statii _|<br>_p_||St at20_p_|_val_||**_Stat_**|**_PO_**|
||7|CS|->|VT|F(1,4)|17.200|0.014|Chi2(1)|30.100|0.000|Chi2(2)|0.302|0.860|
||7|VT|->|CS|F(1,4)|0.059|0.820|Chi2(1)|0.103|0.748|Chi2(2)|0.213|0.899|
|Germany|17|CS|-|M<br>MC|F(1,14)|5.680|0.032|Chi2(1)|6.900|0.009|Chi2(2)|1.790|0.408|
||17|MC|->|CS|F 1,14)|0.035|0.854|Chi2(1)|0.043|0.836|Chi2(2)|6.040|0.049|
||17|CS|->|VT|F(1,14)|8.330|0.012|Chi2(1)|1o.100|0.001|Chi2(2)|7.300|0.026|
||17|VT|->|CS|F(1,14)|5.240|0.038|Chi2(1)|6.360|0.012|Chi2(2)|10.900|0.004|
|Austria|6|CS|-,|MC|F(1,3)|0.297|0.624|Chi2(1)|0.593|0.441|Chi2(2)|0.365|0.833|
||6|MC|**->**|CS|F(1,3)|0.044|0.847|Chi2(1)|0.088|0.766|Chi2(2)|0.439|0.803|
||6|CS|->|VT|F(1,3)|7.190|0.075|Chi2(1)|14.400|0.000|Chi2(2)|0.483|0.785|
||6|VT|**-,**|CS|F(1,3)|0.192|0.691|Chi2(1)|0.383|0.536|Chi2(2)|0.560|0.756|
|Portugal|8|CS|**->**|MC|F(1,5)|8.320|0.034|Chi2(1)|13.300|0.000|Chi2(2)|0.094|0.954|
||8|MC|**-,**|CS|F(1,5)|3.420|0.124|Chi2(1)|5.470|0.019|Chi2(2)|0.635|0.728|
||8|CS|-,|VT|F(1,5)|1.480|0.278|Chi2(1)|2.370|0 124|Chi2(2)|0.235|0.889|
||8|VT|-,|CS|F(1,5)|0.077|0.793|Chi2(1)|0.122|0.726|Chi2(2)|4.870|0.087|
|Chile|9|<br>CS||MC|F (1,6)|1.990|0.208|Chi2(1)|2.980|0.084|Chi2(2)|0.392|0.822|
||_9_|MC|->|CS|F(1,6)|5.640|0.055|Chi2(1)|8.460|0.004|Chi2(2)|0.707|0.702|
||9|CS|**->**|VT|F(1,6)|5.120|0.064|Chi2(1)|7.690|0.006|Chi2(2)|1.710|0.426|
||9|VT|>|CS|F(1,6)|0.905|0.378|Chi2(1)|1.360|0.244|Chi2(2)|1.120|0.572|
|Singapore|15|CS|->|MC|F(1,12)|1.590|0.231|Chi2(1)|1.990|0.158|Chi2(2)|4.560|0.102|
||15|MC|-,|CS|F(1,12)|0.183|0.677|Chi2(1)|0.228|0.633|Chi2(2)|1.190|0.552|
||15|CS|**->**|VT|F(1,12)|0.001|0.944|Chi2(1)|0.001|0.936|Chi2(2)|22.000|0.000|
||15|VT|**->**|CS|F(1,12)|4.640|0.052|Chi2(1)|5.800|0.016|Chi2(2)|0.728|0.695|
|Malaysia|15|CS|**->**|MC|F(1,12)|0.897|0.362|Chi2(1)|1.120|0.290|Chi2(2)|1.140|0.564|
||15|MC|**->**|CS|F(1,12)|0.316|0.585|Chi2(1)|0.395|0.530|Chi2(2)|7.910|0.019|
||17|CS|**->**|VT|_F_1,14)|0.381|0.547|Chi2(1)|0.463|0.496|Chi2(2)|1.650|0.438|
||17|VT|**-,**|CS|F(1,14)|0.003|0.960|Chi2(1)|0.003|0.955|Chi2(2)|7.960|0.019|
|Thailand|11|CS|->|MC|<br>F(1,8)|3.680|0.091|Chi2(1)|5.060|0.024|Chi2(2)|7.200|0.027|
||11|MC|**->**|CS|F(1,8)|1.450|0.263|Chi2(1)|1.990|0.158|Chi2(2)|3.060|0.216|
||11|CS|->|VT|F(1,8)|3.300|0.107|Chi2(1)|4.530|0.033|Chi2(2)|5.380|0.068|
||11|VT|-,|CS|<br>F(1,8)|0.125|0.733|Chi2(1)|0.172|0.679|Chi2(2)|0.023|0.989|
|South Africa|19|CS|**->**|MC|F(1,16)|<br>6.980|0.018|Chi2(1)|<br>8.280|0.004|Chi2(2)|22.600|<br>0.000|
||19|MC|**->**|CS|F(1,16)|2.700|0.120|Chi2(1)|3.200|0.073|Chi2(2)|1.830|0.400|
||19|CS|->|VT|F(1,16)|1.300|0.271|Chi2(1)|1.550|0.214|Chi2(2)|0.609|0.737|
||19|VT|**->**|CS|F(1,16)|2.460|0.136|Chi2(1)|2.920|0.087|Chi2(2)|1.520|0.468|

**Source:** WB institutional investors dataset and WDI.
- 33 -

**Table 9: Pension funds - Granger causality tests**

|**Country**|**Obs**|||||**Gra**|**nger**|||||**JB**||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|||||||<br>_Stat1_|<br>_pvall_||_Stat2_|_pval2_||_SW_|_at pva_|
|United States|17|<br>PF|->|MC|F(1,14)|<br>0.023|<br>0.883|<br>Chi2(1)|<br>0.027|<br>0.868|<br>Chi2(2)|<br>0.983|<br>0.612|
||17|MC|->|PF|F(1,14)|1.170|0.298|Chi2(1)|1.420|0.234|Chi2(2)|0.432|0.806|
||17|<br>PF|-,|VT|F(1,14)|0.664|0.429|Chi2(1)|0.807|0.369|Chi2(2)|2.100|0.351|
||17|VT|->|PF|_F_(1,14)|0.397|0.539|Chi2(1)|0.483|0.487|Chi2(2)|0.386|0.824|
|UnitedKingdom|<br>17|<br>PF|->|MC|F(1,14)|1.070|0.319|Chi2(1)|1.300|0.255|Chi2(2)|0.067|0.967|
||<br>17|<br>MC|->|PF|F(1,14)|0.098|0.759|Chi2(1)|0.119|0.730|Chi2(2)|0.324|0.851|
||17|<br>PF|->|VT|F(1,14)|4.010|0.065|Chi2(1)|4.870|0.027|Chi2(2)|3.500|0.174|
||17|VT|->|PF|F(1,14)|0.618|0.445|Chi2(1)|0.751|0.386|Chi2(2)|0.456|0.796|
|Belgium|15|PF|->|MC|F(1,12)|0.053|0.823|Chi2(1)|0.066|0.798|Chi2(2)|0.464|0.793|
||15|MC|->|PF|F(1,12)|2.250|0.160|Chi2(1)|2.810|0.094|Chi2(2)|1.060|0.589|
||15|<br>PF|->|VT|F(1,12)|12.200|0.006|Chi2(1)|14.000|0.000|Chi2(2)|0.491|0.782|
||15|VT|-|PF|F8(1,12)|1.970|0.186|Chi2(1)|2.470|0.116|Chi2(2)|1.200|0.549|
|Australia|9|PF|-,|MC|<br>F(1,6)|0.960|0.365|Chi2(1)|1.440|0.230|Chi2(2)|0.371|0.831|
||9|MC|->|PF|<br>F(1,6)|0.756|0.418|Chi2(1)|1.130|0.287|Chi2(2)|0.409|0.815|
||9|<br>PF|->|VT|<br>F(1,6)|2.100|0.198|Chi2(1)|3.140|0.076|Chi2(2)|0.320|0.852|
||9|<br>VT|->|PF|<br>F (1,6)|2.560|0.161|Chi2(1)|3.840|0.050|Chi2(2)|<br>0.181|0.913|
|Korea|17|PF|-,|MC|F(1,14)|2.370|0.146|Chi2(1)|2.870|0.090|Chi2(2)|2.370|0.306|
||17|MC|->|PF|F(1,14)|0.553|0.469|Chi2(1)|0.671|0.413|Chi2(2)|<br>1.560|0.459|
||17|PF|-,|VT|F(1,14)|3.150|0.097|Chi2(1)|3.830|0.050|Chi2(2)|0.328|0.849|
||17|<br>VT|->|PF|F(1,14)|0.494|0.494|Chi2(1)|0.600|0.439|Chi2(2)|1.490|0.474|
|Spain|17|<br>PF|->|MC|F(1,14)|4.980|0.043|Chi2(1)|6.040|0.014|Chi2(2)|<br>3.510|0.173|
||17|<br>MC|->|PF|F(1,14)|1.440|0.251|Chi2(1)|1.740|0.187|Chi2(2)|<br>3.470|0.176|
||17|<br>PF|->|VT|F(1,14)|0.283|0.603|Chi2(1)|0.343|0.558|Chi2(2)|2.510|0.285|
||17|<br>VT|-'|PF|F(1,14)|0 153|0.702|Chi2(1)|0.185|0 .667|Chi2(2)|<br>2 .680|0.261|
|Netherlands|17|<br>PF|->|MC|F(1,14)|4.370|0.055|Chi2(1)|5.300|0.021|Chi2(2)|<br>3.180|0.204|
||17|MC|-'|PF|F(1,14)|1. 090|0. 313|Chi2(1)|1.330|0 .249|Chi2(2)|<br>0.925|0.630|
||17|PF|->|VT|F(1,14)|2.690|0.123|Chi2(1)|3.270|0.071|Chi2(2)|<br>0.499|0.779|
||17|<br>VT|->|PF|F(1,14)|5.760|0.031|Chi2(1)|7.000|0.008|Chi2(2)|<br>1.660|0.437|
|Canada|17|PF|-,|MC|F(1,14)|4.190|0.060|Chi2(1)|5.080|0.024|Chi2(2)|<br>1.530|0.464|
||17|<br>MC|->|PF|F(1,14)|1.070|0.318|Chi2(1)|1.300|0.254|Chi2(2)|<br>0.790|0.674|
||17|<br>PF|->|VT|F(1,14)|2.230|0.158|Chi2(1)|2.700|0.100|Chi2(2)|<br>0.451|<br>0.798|
||17|<br>VT|->|PF|F(1,14)|0.085|0.775|Chi2(1)|0.103|0.748|Chi2(2)|<br>0.464|<br>0.793|
|Norway|15|PF|->|MC|8'(1,12)|7. 110|0.021|Chi2(1)|8.890|0.003|Chi2(2)|<br>2.390|<br>0.303|
||15|MC|->|PF|F(1,12)|0.483|0.500|Chi2(1)|0.603|0.437|Chi2(2)|<br>0.322|<br>0.851|
||16|PF|->|VT|F(1,13)|6.370|0.025|Chi2(1)|7.840|0.005|Chi2(2)|<br>0.367|<br>0.832|
||16|<br>VT|->|PF|F(1,13)|0.655|0.433|Chi2(1)|0.806|0.369|Chi2(2)|1.690|0.429|
|Sweden|12|PF|-,|MC|<br>F(1,9)|2.500|0.148|Chi2(1)|3.340|0.068|Chi2(2)|<br>1.250|<br>0.563|
||12|MC|->|PF|<br>F(1,9)|0.147|0.710|Chi2(1)|0.196|0.658|Chi2(2)|0.064|0.969|
||12|PF|-,|VT|<br>F(1,9)|2.500|0.148|Chi2(1)|3.340|0.068|Chi2(2)|0.450|0.799|
||12|<br>VT|->|PF|<br>F(1,9)|0.655|0.439|Chi2(1)|<br>0.873|0.350|Chi2(2)|<br>0.406|<br>0.816|
|Finland|13|<br>PF|->|MC|P(1,10)|3.870|0.077|Chi2(1)|<br>5.030|0.025|Chi2(2)|<br>0.308|<br>0.857|
||13|<br>MC|->|PF|F(1,10)|0.162|0.696|Chi2(1)|0.210|0.647|Chi2(2)|<br>0.397|<br>0.820|
||16|PF|->|VT|F(1,13)|7.760|0.015|Chi2(1)|9.560|0.002|Chi2(2)|<br>0.459|<br>0.795|
||16|VT|->|PF|F(1,13)|0.069|0.797|Chi2(1)|<br>0.085|0.770|Chi2(2)|<br>0.254|<br>0.881|
|Germany|17|PF|->|MC|F(1,14)|<br>0.020|0.889|Chi2(1)|<br>0.025|0.876|Chi2(2)|<br>1.020|<br>0.601|
- 34 -

|**Co:ntry**|**Obs**|||||**Gra**<br>|**nger**<br>|<br>||||**JB**||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|||||||_;::tl_<br>_a_|_pval;_||_Stat2_|_pval2_||_Stat_|_pvai_|
||17|<br>MC|->|PF|F(1,.14)|0.012|0.915|Chi2(1)|0.014|0.905|Chi2(2)|<br>2.820|0.244|
||17|<br>PF|-,|VT|F(1, 14)|1.210|0.289|Chi2(1)|1.470|0.225|Chi2(2)|1.280|0.527|
||17|<br>VT|-,|PF|F(1,14)|0.233|0.637|Chi2(1)|0.283|0.595|Chi2(2)|2.730|0.256|
|Austria|6|<br>PF|-,|MC|<br>F(1,3)|0.796|0.438|Chi2(1)|1.590|0.207|Chi2(2)|<br>0.401|0.818|
||6|<br>MC|->|PF|<br>F (1,3)|0.000|0.986|Chi2(1)|0.001|0.979|Chi2(2)|0.599|0.741|
||6|<br>PF|-,|VT|<br>F(1,3)|3.800|0.146|Chi2(1)|7.600|0.006|Chi2(2)|0.696|0.706|
||6|<br>VT|->|PF|<br>PF(1,3)|10.300|0.049|Chi2(1)|20.500|0.000|Chi2(2)|0.644|0.725|
|Portugal|8|<br>PF|-,|MC|<br>_F_(1,5)|8.600|0.033|Chi2(1)|13.800|0.000|Chi2(2)|0.255|0.880|
||8|<br>MC|->|PF|<br>F(1,5)|2.110|0.206|Chi2(1)|3.380|0.066|Chi2(2)|0.715|0.699|
||8|<br>PF|-,|VT|<br>F (1,5)|1.460|0.281|Chi2(1)|2.340|0.126|Chi2(2)|0.346|0.841|
||8|<br>VT|->|PF|<br>F(1,5)|0.038|0.853|Chi2(1)|0.061|0.805|Chi2(2)|1.580|0.453|
|Chile|16|PF|->|MC|F(1,13)|7.020|0.020|Chi2(1)|8.640|0.003|Chi2(2)|2.170|0.337|
||16|MC|->|PF|_F_(1,13)|5.450|0.036|Chi2(1)|6.700|0.010|Chi2(2)|0.593|0.743|
||16|PF|-|VT|F(1,13)|12.000|0.004|Chi2(1)|14.800|0.000|Chi2 (2)|12.600|0.002|
||16|VT|-,|PF|F(1,13)|4.260|0.060|Chi2(1)|5.240|0.022|Chi2(2)|0.304|0.859|
|Singapore|16|PF|->|MC|F(1,13)|1.070|0.321|Chi2(1)|1.310|0.252|Chi2(2)|5.670|0.059|
||16|MC|->|PF|F(1,13)|0.019|0.893|Chi2(1)|0.023|0.879|Chi2(2)|0.850|0.654|
||22|PF|-,|VT|F(1,19)|0.127|0.725|Chi2(1)|0.148|0.701|Chi2 (2)|40.900|0.000|
||22|VT|-|P<br>PF|F(1,19)|1.990|0.175|Chi2(1)|2.300|0.129|Chi2(2)|1.060|0.590|
|Malaysia|15|PF|-,|MC|F(1,12)|0.973|0.343|Chi2(1)|1.220|0.270|Chi2(2)|1.120|0.571|
||15|MC|->|PF|F(1,12)|0.144|0.711|Chi2(1)|0.180|0.671|Chi2(2)|7.040|0.030|
||17|PF|->|VT|F(1,14)|0.427|0.524|Chi2(1)|0.519|0.471|Chi2(2)|1.620|0.445|
||17|VT|-,|PF|F(1,14)|0.049|0.828|Chi2(1)|0.060|0.807|Chi2(2)|7.530|0.023|
|Thailand|13|PF|->|MC|F(1,10)|4.460|0.061|Chi2(1)|5.800|0.016|Chi2 (2)|11.300|0.004|
||13|MC|->|PF|F(1,10)|0.317|0.586|Chi2(1)|0.412|0.521|Chi2(2)|0.584|0.747|
||13|PF|-,|VT|F(1,10)|2.040|0.184|Chi2(1)|2.650|0.104|Chi2(2)|5.680|0.058|
||13|VT|->|PF|F(1,10)|1.130|0.312|Chi2(1)|1.480|0.225|Chi2(2)|1.090|0.581|
|SouthAfrica|19|PF|->|MC|F(1,16)|6.970|0.018|Chi2(1)|8.280|0.004|Chi2(2)|22.900|0.000|
||19|MC|->|PF|F8(1,16)|0.118|0.735|Chi2(1)|0.141|0.708|Chi2(2)|0.110|0.946|
||19|PF|-,|VT|_F_(1,16)|1.430|0.249|Chi2(1)|1.700|0.193|Chi2(2)|0.686|0.710|
||19|VT|->|PF|F(1,16)|0.255|0.620|Chi2(1)|0.303|0.582|Chi2(2)|0.077|0.962|

**Source: WB** institutional investors **dataset** and **WDI.**
- 35 -

**Table 10: Life insurance - Granger causality tests**

|**Country**|**Obs**|||||**Gra**|**nger**|||||**JS**||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|||||||_Stat1_|_pvall_||_Stat2_|_pval2_||_Stat_|_pval_|
|United States|17|<br>LI|->|MC|F(1,14)|<br>0.070|<br>0.795|<br>Chi2(1)|<br>0.085|<br>0.770|<br>Chi2(2)|<br> <br>1.230|<br>0.541|
||17|MC|->|LI|F(1,14)|0.050|0.826|Chi2(1)|0.061|0.805|Chi2(2)|0.834|0.659|
||17|<br>LI|->|VT|F(1,14)|0.163|0.692|Chi2(1)|0.198|0.656|Chi2(2)|2.120|0 .347|
||17|<br>VT|->|LI|F(1,14)|0.228|0.640|Chi2(1)|0.277|0.599|Chi2(2)|<br>0.673|0.714|
|United Kingdom|<br>17|<br>LI|->|MC|F(1,14)|5.470|0.035|Chi2(1)|6.640|0.Olo|Chi2(2)|<br>0.045|0.978|
||17|<br>MC|->|LI|F(1,14)|0.001|0.977|Chi2(1)|0.001|0.974|Chi2(2)|<br>0.560|0.756|
||17|<br>LI|->|VT|F(1,14)|3.520|0.082|Chi2(1)|4.270|0.039|Chi2(2)|<br>6.480|0.039|
||17|<br>VT|-,|LI|F(1,14)|0.000|0.992|Chi2(1)|0.000|0.991|Chi2(2)|<br>0.578|0.749|
|Belgium|16|<br>LI|-,|MC|F(1,13)|4.670|0.050|Chi2(1)|5.750|0.017|Chi2(2)|<br>0.229|0.892|
||16|<br>MC|->|LI|F(1,13)|0.128|0.726|Chi2(1)|0.157|0.692|Chi2(2)|<br>3.900|0.142|
||16|LI|->|VT|F(1,13)|0.715|0.413|Chi2(1)|0.157|0.692|Chi2(2)|<br>4.910|0.086|
||16|<br>VT|-,|LI|F(1,13)|0.311|0.586|Chi2(1)|0.383|0.536|Chi2(2)|<br>4.200|0.123|
|Australia|17|LI|->|MC|F(1,14)|0.098|0.758|Chi2(1)|0.120|0.730|Chi2(2)|<br>0.419|0.811|
||17|<br>MC|->|LI|F(1,14)|0.003|0.960|Chi2(1)|0.003|0.955|Chi2(2)|<br>4.520|0.104|
||17|LI|->|VT|F(1,14)|1.090|0.315|Chi2(1)|<br>1.320|0.251|Chi2(2)|<br>0.707|0.702|
||17|VT|->|LI|F(1,14)|0.298|0.594|Chi2(1)|0.361|0.548|Chi2(2)|<br>2.110|0.348|
|Korea|17|LI|->|MC|F(1,14)|0.064|0.804|Chi2(1)|0.077|0.781|Chi2(2)|<br>4.480|0.106|
||17|<br>MC|->|LI|F(1,14)|0.824|0.379|Chi2(1)|<br>1.000|0.317|Chi2(2)|<br>2.870|0.238|
||17|<br>LI|->|VT|F(1,14)|3.140|0.098|Chi2(1)|<br>3.810|0.051|Chi2(2)|<br>1.360|0.505|
||17|VT|->|LI|F(1,14)|0.029|0.868|Chi2(1)|<br>0.035|0.852|Chi2(2)|<br>1.490|0.474|
|Spain|13|<br>LI|->|MC|9(1,10)|0.386|0.549|Chi2(1)|0.501|0.479|Chi2(2)|<br>2.230|0.328|
||13|<br>MC|->|LI|F(1,10)|0.185|0.676|Chi2(1)|<br>0.240|0.624|Chi2(2)|<br>0.424|0.809|
||13|<br>LI|->|<br>VT|F(1,10)|0.110|0.747|Chi2(1)|<br>0.143|0.706|Chi2(2)|<br>6.810|0.033|
||13|<br>VT|-,|<br>LI|F(1,10)|1.560|0.239|Chi2(1)|<br>2.030|0.154|Chi2(2)|<br>0.634|0.728|
|Netherlands|17|<br>LI|->|MC|F(1,14)|7.380|0.017|Chi2(1)|<br>8.970|0.003|Chi2(2)|<br>0.276|0.871|
||17|<br>MC|-,|LI|F(1,14)|0.020|0.891|Chi2(1)|<br>0.024|0.878|Chi2(2)|<br>1.940|0.379|
||17|<br>LI|-'|VT|F(1,14)|6.190|0.026|Chi2(1)|<br>7.510|0.006|Chi2(2)|<br>0.190|<br>0.909|
||17|<br>VT|-,|LI|9(1,14)|4.150|0.061|Chi2(1)|<br>5.040|0.025|Chi2(2)|<br>0.051|0.975|
|Canada|17|LI|->|MC|F(1,14)|2.880|0.112|Chi2(1)|<br>3.490|0.062|Chi2(2)|<br>1.310|0.520|
||17|<br>MC|-s|LI|F(1,14)|1.860|0.195|Chi2(1)|<br>2.250|0.133|Chi2(2)|<br>0.063|<br>0.969|
||17|<br>LI|->|VT|F(1,14)|1.750|0.207|Chi2(1)|<br>2.130|0.145|Chi2(2)|<br>0.411|0.814|
||17|<br>VT|->|LI|F(1,14)|3.590|0.079|Chi2(1)|<br>4.360|0.037|Chi2(2)|<br>0.006|0.997|
|Norway|115|LI||MC|F(1,12)|2.530|0.138|Chi2(1)|<br>3.160|0.075|Chi2(2)|<br>0.179|0.914|
||15|<br>MC|-,|LI|F(1,12)|2.120|0.171|Chi2(1)|<br>2.650|0.103|Chi2(2)|<br>0.529|<br>0.768|
||16|<br>LI|->|VT|F(1,13)|3.200|0.097|Chi2(1)|<br>3.940|0.047|Chi2(2)|<br>0.755|<br>0.686|
||16|<br>VT|-,|LI|F(1,13)|0.036|0.853|Chi2(1)|<br>0.044|0.834|Chi2(2)|<br>0.658|0.720|
|Sweden|12|<br>LI|->|MC|<br>F(1,9)|1.150|0.312|Chi2(1)|<br>1.530|0.216|Chi2(2)|<br>0.900|0.637|
||12|<br>MC|-'|LI|<br>F(1,9)|0.036|0.853|Chi2(1)|0.048|0.826|Chi2(2)|<br>0.108|0.947|
||12|<br>LI|-|VT|<br>F(1,9)|5.020|0.052|Chi2(1)|<br>6.690|0.010|Chi2(2)|<br>0.293|<br>0 .864|
||12|<br>VT|->|LI|F(1,9)|0.167|0.692|Chi2(1)|<br>0.222|0.637|Chi2(2)|<br>0.287|0.866|
|Finland|7|LI|,|MC|F91,4)|9.050|0.040|Chi2(1)|15.800|0.000|Chi2(2)|0.418|0.811|
||7|<br>MC|-,|LI|F(1,4)|0.006|0.940|Chi2(1)|<br>0.011|0.916|Chi2(2)|<br>0 274|0.872|
||7|<br>LI|-,|VT|<br>F(1,4)|6.300|0.066|Chi2(1)|11.000|0.001|Chi2(2)|<br>0.768|0.681|
||7|<br>VT|-|LI|F(1,4)|0.066|0.810|Chi2(1)|<br>0.116|0.734|Chi2(2)|<br>0.321|0.852|
|Germany|17|LI|-|MC|9(1,14)|6.310|0.025|Chi2(1)|<br>7.660|0.006|Chi2(2)|<br>1.910|0.384|
- 36 -

|**Country**|**Obs**<br>**bJB**|||||**ra**<br>_Statl_|**nger**<br>_pvall_||_Stat2_|_pval2_||_Stat_|_pval_|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
||17|MC|->|LI|F(1, 14)|0.053|0.821|Chi2(1)|0.064|0.800|Chi2(2)|8.680|0.013|
||17|LI|->|VT|F(1,14)|6 960|0.019|Chi2(1)|8.450|0.004|Chi2(2)|8.480|0.014|
||17|VT|-'|LI|F(1,14)|5.990|0.028|Chi2(1)|7.270|0.007|Chi2 (2)|12.800|0.002|
|Austria|10|LI|->|MC|F(1,7)|2.730|0.142|Chi2(1)|3.900|0.048|Chi2(2)|0.986|0.611|
||10|MC|->|LI|F(1,7)|0.055|0.821|Chi2(1)|0.079|0.778|Chi2(2)|0.223|0.894|
||10|LI|->|VT|F(1,7)|0.642|0.449|Chi2(1)|0.917|0.338|Chi2(2)|0.449|0.799|
||10|VT|->|LI|F(1,7)|0.222|0.652|Chi2(1)|0.317|0.574|Chi2(2)|0.097|0.953|
|Portugal|17|LI|->|MC|F(1, 14)|4.470|0.053|Chi2(1)|5.430|0.020|Chi2(2)|0.515|0.773|
||17|MC|->|LI|F(1,14)|0.279|0.605|Chi2(1)|0.339|0.560|Chi2(2)|4.000|0.135|
||17|LI|->|VT|F(1,14)|5.070|0.041|Chi2(1)|6.160|0.013|Chi2(2)|1.500|0.472|
||17|VT|-,|LI|F(1,14)|0.885|0.363|Chi2(1)|1.080|0.300|Chi2(2)|2.140|0.343|
|Chile|_9_|LI||MC|F(1,6)|0.352|0.575|Chi2(1)|0.528|0.467|Chi2(2)|0.946|0.623|
||9|MC|-,|LI|F(1,6)|0.847|0.393|Chi2(1)|1.270|0.260|Chi2(2)|0.597|0.742|
||9|LI|-,|VT|F(1,6)|2.430|0.170|Chi2(1)|3.650|0.056|Chi2(2)|2.590|0.273|
||9|VT|-,|LI|F(1,6)|0.674|0.443|Chi2(1)|1.010|0.315|Chi2(2)|0.509|0.775|
|Singapore|15|LI|-,|MC|F(1,12)|1.770|0.208|Chi2(1)|2.210|0.137|Chi2 (2)|10.700|0.004|
||15|MC|-,|LI|F(1,12)|0.105|0.751|Chi2(1)|0.132|0.717|Chi2(2)|0.153|0.926|
||15|LI|->|VT|F(1,12)|3.570|0.083|Chi2(1)|4.470|0.035|Chi2 (2)|10.400|0.006|
||15|VT|->|LI|F(1,12)|0.468|0.507|Chi2(1)|0.585|0.444|Chi2(2)|0.170|0.918|
|Malaysia|19|LI|-,|MC|F(1,16)|1.180|0.293|Chi2((1)|1.400|0.236|Chi2(2)|4.020|0.134|
||_19_|MC|->|LI|F(1,16)|0.603|0.449|Chi2(1)|0.716|0.397|Chi2(2)|3.480|0.175|
||21|LI|->|VT|F(1,18)|4.510|0.048|Chi2(1)|5.260|0.022|Chi2 (2)|27.900|0.000|
||21|VT|>|LI|F(1,18)|0.008|0.929|Chi2(1)|0.010|0.922|Chi2(2)|3.360|0.186|
|Thailand|11|LI||MC|F(1,8)|2.060|0.189|Chi2(1)|2.830|0.092|Chi2(2)|4.780|0.091|
||11|MC|->|LI|F(1,8)|0.049|0.830|Chi2(1)|0.067|0.795|Chi2(2)|8.810|0.012|
||11|LI|->|VT|F(1,8)|3.980|0.081|Chi2(1)|5.470|0.019|Chi2(2)|8.550|0.014|
||11|VT|>|LI|F(1,8)|9.580|0.015|Chi2(1)|13.200|0.000|Chi2(2)|0.415|0.813|
|SouthAfrica|21|LI|->|MC|5(1,18)|5.400|0.032|Chi2(1)|6.300|0.012|Chi2(2)|14.100|0.001|
||21|MC|_>|LI|F(1,18)|2.410|0.138|Chi2(1)|2.810|0.094|Chi2(2)|3.320|0.190|
||22|LI|->|VT|F(1,19)|1.400|0.252|Chi2(1)|1.620|0.203|Chi2(2)|0.776|0.678|
||22|VT|_,|LI|F(1,19)|2.820|0.109|Chi2(1)|3.270|0.071|Chi2(2)|4.540|0.103|

**Source:** WB institutional investors dataset and WDI.
- 37 -

**Table 11: Non-life insurance - Granger causality tests**

|**Country**|**Obs**|||||**Gra**|**nger**|||||**JB**||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|||||||<br>**_Satel_**|<br> _pvail_||_Stat2_|_pv&l2_||_Stat_|_pval_|
|United States|17|<br>NL|**_-,_**|MC|F(1,14)|0.058|<br>0.814|<br>Chi2(1)|<br>0.070|<br>0.791|<br>Chi2(2)|<br>0.449|<br>0.799|
||17|MC|->|NL|F(1,14)|0.017|0.900|Chi2(1)|0.020|0.887|Chi2(2)|0.115|0.944|
||17|NL|**_->_**|VT|F(1,14)|0.344|0.567|Chi2(1)|0.418|0.518|Chi2(2)|2.840|0.241|
||17|VT|**_->_**|NL|F(1,14)|0.340|0.569|Chi2(1)|0.413|0.521|Chi2(2)|0.101|0.951|
|United Kingdom|<br>17|NL|**_->_**|MC|F(1,14)|2.160|0.164|Chi2(1)|2.620|0.106|Chi2(2)|1.530|0.464|
||17|MC|**_->_**|NL|F(1,14)|0.793|0.388|Chi2(1)|0.963|0.326|Chi2(2)|1.740|0.418|
||17|NL|**_->_**|VT|F(1,14)|4.800|0.046|Chi2(1)|5.830|0.016|Chi2(2)|5.410|0.067|
||17|VT|**_->_**|NL|F(1,14)|0.673|0.426|Chi2(1)|0.817|0.366|Chi2(2)|2.090|0.352|
|Belgium|15|NL|-,|MC|F(1,12)|4.480|0.056|Chi2(1)|5.600|0.018|Chi2(2)|0.220|0.896|
||14|MC|**_-_**|N<br>NL|F(1,11)|0.027|0.873|Chi2(1)|0.034|0.853|Chi2(2)|8.590|0.014|
||15|NL|**_->_**|VT|F(1,12)|2.040|0.179|Chi2(1)|2.550|0.110|Chi2(2)|0.037|0.982|
||14|VT|**_-_**|N<br>NL|F(1,11)|0.417|0.532|Chi2(1)|0.531|0.466|Chi2(2)|6.470|0.039|
|Australia|9|NL|**_-,_**|MC|<br>F(1,6)|0.244|0.639|Chi2(1)|0.365|0.545|Chi2(2)|0.875|0.646|
||9|<br>MC|-|N<br>NL|<br>F(1,6)|4.870|0.069|Chi2(1)|7.300|0.007|Chi2(2)|0.172|0.918|
||9|<br>NL|**_->_**|VT|F(1,6)|0.000|0.993|Chi2(1)|0.000|0.991|Chi2(2)|5.300|0.071|
||_9_|<br>VT|**_-_**|N<br>NL|<br>F(1,6)|8.320|0.028|Chi2(1)|12.500|0.000|Chi2(2)|0.441|0.802|
|Korea|17|NL|->|MC|F(1,14)|3.150|0.098|Chi2(1)|3.830|0.050|Chi2(2)|3.790|0.150|
||17|MC|-|N<br>NL|F(1,14)|1.290|0.275|Chi2(1)|1.570|0.210|Chi2(2)|0.219|0.896|
||17|NL|-,|VT|F(1,14)|0.164|0.691|Chi2(1)|0.200|0.655|Chi2(2)|<br>0.400|0.819|
||17|VT|-'|<br>NL|F(1,14)|1.310|0.272|Chi2(1)|1.590|0.208|Chi2(2)|<br>0.595|0.743|
|Spain|13|NL|**_->_**|<br>MC|F(1,10)|0.095|0.764|Chi2(1)|0.124|0.725|Chi22(2)|3.400|0.183|
||13|MC||N><br>NL|F(1,10)|0.227|0.644|Chi2(1)|0.295|0.587|Chi2(2)|<br>5.140|0.077|
||13|NL|->|VT|F(1,10)|0.040|0.846|Chi2(1)|0.052|0.820|Chi2(2)|4.010|0.135|
||13|VT|**_->_**|NL|F(1,10)|0.738|0.410|Chi2(1)|0.960|0.327|Chi2(2)|12.100|0.002|
|Netherands|16|NL|**_->_**|MC|F(1,13)|13.6C0|0.003|Chi2(1)|27.000|0.000|Chi2(2)|0.065|0.968|
||16|MC|**_->_**|NL|F(1,13)|0.129|0.725|Chi2(1)|0.159|0.690|Chi2(2)|1.030|0.598|
||16|NL|-,|VT|F(1,13)|6.930|0.021|Chi2(1)|8.520|0.004|Chi2(2)|<br>1.980|0.371|
||16|VT|**_->_**|NL|F(1,13)|0.310|0.587|Chi2(1)|0.381|0.537|Chi2(2)|5.360|0.068|
|Canada|17|<br>NL|**_-,_**|MC|F(1,14)|2.040|0.175|Chi2(1)|2.480|0.116|Chi2(2)|<br>0.283|<br>0.868|
||17|<br>MC|**_-_**|N<br>ML|F(1,14)|0.937|0.350|Chi2(1)|1.140|0.286|Cbi2(2)|<br>1.240|0.538|
||17|NL|**_-,_**|VT|F(1,14)|0.561|0.466|Chi2(1)|0.681|0.409|Chi2(2)|<br>0.137|0.934|
||17|VT|**_-_**|N<br>ML|F(1,14)|1.060|0.321|Chi2(1)|1.290|0.256|Cbi2(2)|<br>0.578|0.749|
|**Norway**|15|<br>NL|**_->_**|MC|F(1,12)|8.390|0.013|Chi2(1)|10.500|0.001|Chi2(2)|<br>0.273|0.872|
||15|MC|-,|<br>NL|F(1,12)|3.2C0|0.099|Chi2(1)|4.000|0.045|Chi2(2)|<br>0.615|0.735|
||16|NL|**_-,_**|VT|F(1,13)|4.180|0.062|Chi2(1)|5.150|0.023|Chi2(2)|<br>0.579|<br>0.749|
||16|VT|**_-_**|N<br>NL|F(1,13)|0.004|0.953|Chi2(1)|0.004|0.947|Chi2(2)|<br>0.970|0.616|
|Sweden|12|<br>NL|->|MC|<br>F(1,9)|3.860|0.081|Chi2(1)|5.140|0.023|Chi2(2)|<br>0.268|0.875|
||12|MC|-|N<br>NL|<br>F(1,9)|0. 573|0.468|Chi2(1)|0.764|0.382|Chi2(2)|<br>1.030|0.599|
||12|<br>NL|-,|VT|<br>F(1,9)|12.100|0.007|Chi2(1)|16.100|0.000|Chi2(2)|<br>1.250|<br>0.534|
||12|VT|-|N<br>NL|<br>F(1,9)|12.1C0|0.007|Chi2(1)|16.100|0.000|Chi2(2)|<br>6.100|0.047|
|Finland|8|<br>NL|-,|MC|<br>F(1,5)|1.440|0.284|Chi2(1)|2.310|0.129|Chi2(2)|<br>0.760|0.684|
||8|<br>MC|-|N<br>NL|<br>F(1,5)|0.005|0.947|Chi2(1)|<br>0.008|0.930|Chi2(2)|<br>4.880|<br>0.087|
||8|<br>NL|->|VT|<br>F(1,5)|2.450|0.178|Chi2(1)|<br>3.920|0.048|Chi2(2)|<br>0.650|<br>0.722|
||8|<br>VT|->|NL|<br>F(1,5)|0.090|0.776|Chi2(1)|0.145|0.704|Chi2(2)|<br>3.840|0.147|
|Germany|17|NL|**_->_**|MC|F(1,14)|17.7C0|0.001|Chi2(1)|21.500|0.000|Chi2(2)|2.570|0.276|
- 38 -

|**Country**|**Obs**|||||**Gra**<br>_Stat1_|**nger**<br>_pvall_||_Stat2_|_pva!2_||**JB**<br>_Stat_|_pval_|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
||17|MC|->|NL|F(1,14)|<br>1.S90|0.228|Chi2(1)|<br>1.930|0.165|Chi2(2)|4.870|0.088|
||17|NL|->|VT|F(1,14)|9.860|0.007|Chi2(1)|12.000|0.001|Chi2(2)|14.500|0.001|
||17|VT|-,|NL|F(1,14)|<br>7. 510|0.016|Chi2(1)|<br>9.120|0.003|Chi2(2)|3.010|<br>0.222|
|Austria|10|NL|->|MC|<br>F(1,7)|5.950|0.045|Chi2(1)|<br>8.500|0.004|Chi2(2)|0.013|<br>0.994|
||10|MC|->|NL|<br>F(1,7)|0.000|0.994|Chi2(1)|<br>0.000|0 .992|Chi2(2)|<br>0.222|<br>0. 895|
||10|NL|-,|VT|<br>F(1,7)|0.575|0.473|Chi2(1)|<br>0.822|0.365|Chi2(2)|<br>0.506|0.776|
||10|VT|-,|NL|<br>F(1,7)|0.963|0.359|Chi2(1)|<br>1.380|0 241|Chi2(2)|<br>1 050|0.593|
|Portugal|9|NL|->|MC|<br>F)1,6)|6.180|0.047|Chi2(1)|<br>9.260|0.002|Chi2(2)|0.490|0.783|
||_9_|MC|->|NL|<br>F(1,6)|2.210|0.187|Chi2(1)|<br>3.320|0.068|Chi2(2)|<br>2.670|<br>0.263|
||9|<br>NL|->|VT|<br>F(1,6)|7.180|0.037|Chi2(1)|10.800|0.001|Chi2(2)|<br>0.047|<br>0.977|
||9|<br>VT|-|N<br>NL|<br>F(1,6)|2.270|0.183|Chi2(1)|<br>3.400|0.065|Chi2(2)|<br>0.322|<br>0.851|
|Chile|_9_|<br>NL|-,|MC|<br>F(1,6)|0.Oll|0.920|Chi2(1)|<br>0.016|0.898|Chi2(2)|<br>0.971|<br>0.615|
||9|<br>MC|->|NL|<br>F(1,6)|0.725|0.427|Chi2(1)|<br>1.090|0.297|Chi2(2)|<br>3.430|<br>0.18D|
||9|<br>NL|-,|VT|<br>F21,6)|43 .100|0.001|Chi2(1)|64.700|0.000|Chi2(2)|<br>0.667|<br>0.716|
||9|<br>VT|-,|<br>NL|<br>F(1,6)|0.000|0.998|Chi2(1)|<br>0.000|0.997|Chi2(2)|<br>3.100|<br>0.212|
|Singapore|15|NL|-,|MC|F(1,12)|0.011|0.919|Chi2(1)|<br>0.013|0.908|Chi2(2)|<br>8.270|<br>0.016|
||15|MC|-|N<br>NL|F(1, 12)|4.290|0.061|Chi2(1)|<br>5.360|0.021|Chi2(2)|<br>0.477|<br>0.788|
||15|NL|->|VT|F(1,12)|<br>0.457|0.512|Chi2(1)|<br>0.572|0.450|Chi2 (2)|24.300|0.000|
||15|<br>VT|->|NL|F(1,12)|7.200|0.020|Chi2(1)|<br>9.000|0.003|Chi2(2)|<br>0.446|<br>0.800|
|Malaysia|19|NL|-,|MC|F(1,16)|0.049|0.827|Chi2(1)|<br>0.058|0.809|Chi2(2)|<br>5.150|0.076|
||19|MC|-|N<br>NL|F(1,16)|<br>3.090|0.098|Chi2(1)|<br>3.670|0.055|Chi2(2)|<br>0.648|<br>0.723|
||21|NL|-,|VT|F(1,18)|<br>8.830|0.008|Chi2(1)|10.300|0.001|Chi2(2)|34.600|0.000|
||21|VT|->|NL|F(1,18)|0.142|0.711|Chi2(1)|<br>0.165|0.685|Chi2(2)|<br>0.758|<br>0.685|
|Thailand|5|<br>NL|->|MC|<br>F(1,2)|12.400|0.072|Chi2(1)|31.100|0.000|Chi2(2)|<br>0.628|<br>0.731|
||5|<br>MC|-|NL|<br>F(1,2)|3.520|0.201|Chi2(1)|<br>8.810|0.003|Chi2(2)|<br>0.948|<br>0.622|
||5|<br>NL|->|VT|<br>F(1,2)|15.200|0.060|Chi2(i)|38.000|0.000|Chi2(2)|<br>0.399|<br>0.819|
||5|<br>VT|-|N<br>NL|<br>F 1,2)|<br>9.960|0.087|Chi2(1)|24.900|0.000|Chi2(2)|<br>0.232|<br>0.890|
|South Africa|21|<br>NL|->|MC|F(1,18)|2.190|0.156|Chi2(1)|2.560|0.110|Chi2(2)|<br>3.560|<br>0.169|
||21|MC|->|NL|F(1,18)|0.924|0.349|Chi2(1)|<br>1.080|0.299|Chi2(2)|<br>0.183|<br>0.912|
||21|NL|->|VT|F(1,18)|<br>6.520|0.020|Chi2(1)|7.610|0.006|Chi2(2)|<br>0.127|<br>0.938|
||21|VT|->|NL|F(1,18)|0.556|0.465|Chi2(1)|0.649|0.421|Chi2(2)|0.141|<br>0.932|

**Source: WB** institutional **investors** dataset and WDI.
- 39 -

# **Vil Appendix 2: Data**

Data on financial assets of pension funds, life, and non-life insurance companies for OECD countries come from OECD 1997 and 1998 Institutional Investors Statistical Yearbooks. For non-OECD countries the sources are the following:

- a) data for Chile, were specially assembled by Central Bank of Chile at our request.

- b) data for Thailand was obtained from the Association of Provident Funds and the Annual Report of the Department of Insurance in the Ministry of Commerce.

- c) data for South Africa is published in the Federal Reserve Bank quarterly bulletin.

- d) data for Malaysia is published in the insurance annual report and the EPF annual report by Bank Negara.

- e) data for Singapore is published in the yearbook of statistics by the Departrnent of Statistics.

All other variables come from the World Development Indicators database.

**Stock Market Value Traded** Stocks traded refers to the total value of shares traded during the period. Data are in current local currency.

**Stock Market Capitalization:** Market capitalization (also known as market value) is the share price times the number of shares outstanding. Listed domestic companies refer to the number of domestically incorporated companies listed on the country's stock exchanges at the end of the year. Data are in current local currency.

**Table 12: List of countries**

|AUS|Australia|ISL|Iceland|
|---|---|---|---|
|AUT|Austria|ITA|Italy|
|BEL|Belgium|JPN|Japan|
|CAN|Canada|KOR|Korea, Rep.|
|CHE|Switzerland|NLD|Netherlands|
|CHL|Chile|NOR|Norway|
|DEU|Germany|NZL|New Zealand|
|DNK|Denmark|PRT|Portugal|
|ESP|Spain|SGP|Singapore|
|FIN|Finland|SWE|Sweden|
|GBR|United Kingdom|THA|Thailand|
|GRC|Greece|**USA**|United States|
|HUN|Hungary|ZAF|South Africa|