Israeli Government Debt: Altruistic Investors in the Absence of Arbitrageurs

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Israeli Government Debt:Altruistic Investors in the Absence of Arbitrageurs

Matthew Salzberg

Presented to the Department of Economicsin partial fulfillment of the requirements

for a Bachelor of Arts degree with Honors

Harvard College

Cambridge, Massachusetts

March 17, 2005

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ABSTRACT

In this paper, I examine the market for non-negotiable Israeli government debt in

order to understand unconventional investor motivations. Using a unique dataset

provided by the Israeli government, I find that investors in these bonds partially exhibit

altruistic preferences. In fact, I show that investors increase their demand for bonds in

the face of both greater terrorist attacks and religious holidays as a way of supporting the

state. Furthermore, I find that investors overweight the importance of the nominal yield

on these bonds relative to benchmark investments and underweight the importance of the

Israeli default risk premium. Consequently, the State of Israel is able to uniquely harness

the goodwill of investors in order to raise capital at favorable terms.1

1Acknowledgements: I would like to thank my advisors Professor Jeremy Stein and Professor JeffreyMiron for their valuable advice and continuous feedback during the entire thesis-writing process.Furthermore, the successful completion of this paper was made possible by the wonderful people at theIsraeli Ministry of Finance and the Development Corporation for Israel. Specifically, I would like to thankShirley Strifler, Joseph Rychalski and Raphael Rothstein for being kind enough to assist a completestranger with an unusual data request. I owe thanks to Ryan Geraghty for his thoughtful comments. Lastly,I would like to thank my parents for their continued support. They have been a source of invaluableencouragement and good ideas. Special thanks are deserved by my mother, whose annual purchase ofIsrael Bonds inspired this entire project.

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Table of Contents

Abstract and Acknowledgements 2

Table of Contents 3

I. Introduction 4

II. Literature Review and Background 6

III. Three: Theory: A Model for the Israel Bonds Market 11

IV. Empirical Strategy 16a. The Casual Effect of Altruistic Events on Quantity and Spread 17b. Demand Effects 19

V. Data 24a. Israel Bond Instruments 24b. Constructing Comparable Investment Variables 30c. Constructing Altruism Indicators and Event Variables 32

VI. Evidence 36a. Equilibrium Quantity Results 36b. Event Salience 41c. Equilibrium Yield Changes 43d. Demand-Only Effects 47

VII. Conclusion 50

VIII. References 53

IX. Figures and Tables 54

Mathematical Appendices 76Mathematical Appendix A 76Mathematical Appendix B 77

Appendices 79Appendix A: Israel Bonds Marketing Materials 79Appendix B: Israel Bond Prospectus Features 81

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I. Introduction

Traditionally, economists have viewed financial investors as fully-rational, profit-

seeking individuals. They demand financial assets in an effort to maximize monetary

return while simultaneously minimizing the associated risk. Recently, however, much

interest has been given to behavioral approaches to finance, which take into account a

greater variety of investor motivations. The current debate over Harvard Management

Companys holdings of PetroChina, for example, demonstrates that the investment

decision for some investors includes political and ethical concernsin this case, over

genocide in Sudan. Similarly, ethical investment funds allow investors to maintain

portfolios which only hold those companies that they deem as ethical, or socially

desirable. For instance, some investors choose only to hold environmentally-friendly

stocks. As more and more research has begun to document, the existence of broader

investor motivations in specific markets and circumstances requires a rethinking of

traditional economic models.

Of particular interest to practitioners should be how behavioral approaches to

finance may be used to improve macroeconomic policy outcomes. In other words, can

countries use non-private investor motivations to their advantage? For years,

governments have attempted to use social forces and civically-minded marketing to lower

their cost of debt capital. For instance, the governments of most developed nations used

War Bonds to raise capital during both World War I and World War II. These bonds

partially relied on the patriotic sentiments of citizens to raise capital for the war effort.

During World War I, the United States government marketed both Liberty Bonds and

Victory Bonds as a way to capitalize on the patriotism of its citizens and their support

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for the war. More recently, the United States government began issuing Patriot Bonds

after the 9/11 terrorist attacks, which serve as patriotic versions of U.S. savings bonds. If

investors exhibit altruism or patriotism as motivations for investment decisions

regarding government debt, policy makers might be able to use this information to tailor

capital raising schemes more efficiently and lower a countrys effective cost of debt

capital. Consequently, a lower cost of capital helps save a country money and makes

more investment projects efficient to undertake.

In this paper, I examine one of the largest known governmental programs of this

type, the Israel Bonds program, implemented by the State of Israel. This program

markets non-negotiable government debt to altruistic investors in the United States and

Canada as a way to support the State of Israel. For the purposes of this research, I have

been provided with a unique dataset by the Ministry of Finance of Israel, which allows

analysis of changes in prices (yields) and quantities of these securities. By looking at

various events which are likely correlated with altruistic sentiment, like religious holidays

and terrorist attacks, I examine whether investors in these securities react differently to

political and religious news events than purely profit-seeking individuals.

The next chapter of this paper provides background information on investor

motivations and the Israel Bonds program. In chapter 3, I develop a simple model of the

Israel Bonds market to provide an intuition for how and why altruism enters into the

supply and demand decision. Chapter 4 expands upon this model to explain how it is

possible to identify altruistic effects in an empirical context. Chapter 5 describes the

particulars of my data and chapter 6 reports my findings. Finally, I conclude in chapter 7.

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II. Literature Review and Background

Diverse investor motivations have recently become a subject of research in

finance, notably with regard to investment in ethical funds. The development of these

investment funds, where investors limit their portfolios to specific companies that fulfill a

set of socially responsible criteria, is still relatively new. Cullis, Lewis and Winnett

(1992) document the growth in ethical unit trusts in the United Kingdom. Theoretically,

one would expect that if investors weigh social or ethical factors when making an

investment decision, they must forgo higher levels of financial return per unit of risk.

This is because an investor who is maximizing return will chose a different optimal

portfolio than an investor who is maximizing return with other considerations

simultaneously. The latter investor will substitute between financial return and these

other factors, thereby choosing a portfolio with a less-than-maximum return at a given

risk level.

Empirically, however, the results concerning whether ethical investors receive

lower returns have been mixed. Diltz (1995), Sauer (1997) and Guerard (1997) find that

there is no statistical difference between ethical and non-ethical performance in the

United States. Similarly, Statman (2000) and Gregory, Matatko and Luther (1997)

conclude that there is no difference between the performance of ethical and non-ethical

unit trusts in both the United Kingdom and the United States. Yet, other studies do find

that ethical funds under-perform their benchmarks. For instance, Tippit (2001) finds that

ethical mutual funds in Australia under-perform an index benchmark by 1.5% per annum

Furthermore, Ali and Gold (2002) find that investors lose 0.7% per year when companies

in non-ethical industries are removed from a market portfolio.

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This body of research has focused largely on firm-level securities and diversified

portfolios where there are a variety of outlets and substitutes for a particular type of

ethical investing (i.e. there are many investment outlets for an investor who wants to

support environmentally friendly companies). As a result, an investor may not have to

make as serious a departure from his optimal portfolio in order to invest ethically in these

cases. This is because as more securities become eligible for him, his accessible

investment universe will approach the market and he will be closer to being able to

construct the risk-return maximizing portfolio. Yet, the fact that investors may be willing

to forgo even some financial return in order to invest in these ethical funds indicates

that investor motivations may be more complex than traditional economics suggests.

Unfortunately, little research has been done to see the effects of ethical

investing on the cost of capital of a sovereign government, despite the fact that countries

deliberately market their securities with the hopes of attracting these types of investors.

Notably, governments have tried to tie their bonds to a political or patriotic cause in times

of war. Rockoff (2004) looks at U.S. war bonds from World War I and concludes that

they were, in fact, priced to sell as purely financial investments. His analysis rests on the

fact that the spread between Liberty Bonds and municipal bonds does not shrink after the

armistice that ended the war. The bonds traded during World War I, however, were not

as prominently marketed as later patriotic bond issues and were allowed to trade on the

open market. Since they traded on the market, prices reflected what profit-seeking bond

traders were willing to pay, rather than what the civically-minded investor would pay.

After World War I, however, war bonds were sold as non-marketable securities, which

prevented non-civically minded investors from selling and causing the premium to

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vanish. Many have speculated that the government was more successful in raising debt at

below-market rates during World War II; although, no empirical research has been done

on these bonds.

Perhaps the largest governmental program still at work today is the Israel Bonds

program, which sells Israeli government debt in the United States and Canada as a way

for Diaspora Jews and other investors sympathetic to Israel to support the state. This is

done through a retail agency called the Development Corporation for Israel (DCI), a

NASD-registered broker/dealer headquartered in New York, which markets the debt in

the United States. Since these bonds are non-transferable, arbitrageurs cannot sell and

drive prices towards their fundamental values. As a result, these bonds provide a unique

opportunity to search for price and quantity fluctuations caused by the altruistic sentiment

of investors.

The program has been operating since 1951 and has contributed significantly to

Israels fundraising ability abroad. To date, bond sales have exceeded $25 billion.

Relative to the size of the external debt, the program constitutes a large share of borrowed

funds (Figure 1). Indeed, as of September 2004, Israel Bonds accounted for 33.3% of

Israels external debt of approximately $30 billion and approximately 8% of the countrys

total debt.

While sales from the bonds are designated by Israels Ministry of Finance for

general use, DCI highlights the development projects to which they contribute as part of

the marketing campaign. For instance, the DCI website highlights the fact that the funds

go towards nation-building and economic infrastructure, like agriculture, energy,

security and transportation. In fact, it is explicitly stated in the prospectuses of the Israel

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Bonds that these offerings may have a special appeal to persons with an interest in the

State of Israel rather than the general public. By linking Israels prosperity and security

to sales of these bonds, DCI attempts to capitalize on the goodwill of investors in a way

that is unique among other sovereign nations. Appendix A provides examples of the type

of marketing materials used to sell these bonds.

In a recent paper by the Bank of Israel, Rechavi and Weingarten (2003) argue that

the goal of the Israel Bonds program is partially to decrease the cost of debt of the State

of Israel. In fact, they argue that in the programs early years marketing was done

specifically to those Jews with a direct or indirect tie to the Holocaust. Since these Jews

saw the purchase of Israel Bonds as a way to make a contribution to the State of Israel

(and a good cause), they were willing to invest at rates favorable to the Bank relative to

other credit sources. Rechavi and Weingarten argue that the Second Generation of

Jews is willing to pay a smaller premium to support the State of Israel than the earlier

Holocaust generation; however, they believe that they are still willing to buy the bonds at

submarket rates. Unfortunately, however, no empirical evidence has been shown to

support these claims.

Previous research by Liviatan (1980) suggests, however, that the Israel Bonds

program itself is non-economic in naturethat is, the cost of debt at which Israel is able

to issue securities though the program is not more favorable than the going market rates.

While he observes that the direct interest on the bonds is favorably low, other factors

make the effective interest on the bonds comparable to other credit sources. For instance,

the likelihood that the sale of Israel Bonds crowds out charitable transfers through

charities like the United Jewish Appeal (UJA) may raise the effective cost of the bonds.

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Furthermore, DCI incurs above-average marketing and distribution costs in order to

implement the program. Taken together, he concludes that the overall cost of the loan

resembles that of an ordinary commercial loan from abroad. His analysis, however, only

concludes that at that point in time the effective interest on the bonds is comparable to

other credit sources. Over the years, he admits, the effective interest on these bonds has

varied. In fact, Liviatan (1980) cites the Six Days War as an event which induced

substantial capital inflow through the program. Had investors been fully rational, one

would expect this event to raise the risk premium that investors demand for Israeli debt,

and in turn, make Israel Bonds less attractive investments, all else equal. However, it

seems that the opposite occurs the war caused the bonds to become more attractive

investments. By better understanding investor motivations in these securities, it is

possible that the state can use this information to further tailor the Israel Bond program

and enhance its cost-effectiveness.

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III. Theory: A Model for the Israel Bonds Market

In this chapter, I will develop a simple model of the Israel Bonds market. As with

all economic models, this model greatly simplifies reality. This simplified case, however,

will give the reader a better intuition for how and why altruistic events and interest rates

can factor into both the supply and demand decision. In the next chapter, I will expand

the model to a form that can be easily used to identify these effects in an empirical

context.

The market for Israel Bonds is unique in the world of financial markets.

Traditional theory predicts that frictionless markets permit unlimited arbitrage, driving

security prices to their fundamental values associated with the future cash flows of the

security discounted at a rate appropriate to the risk. In the market for Israel Bonds,

however, arbitrage is impossible. The government mandates that these securities are non-

negotiable, which means that investors can buy, but they cannot sell. Consequently, there

is no guarantee that the prices of these bonds are associated with their fundamental

values. Furthermore, the absence of arbitrageurs means that the traditional finance

conception of inventors with perfectly elastic demand curves is not necessarily a good

description of this market.

Since prices may not reflect their fundamental values, it is reasonable to model

the Israel Bonds market with a system of supply and demand functions. In the model, it

is assumed that demand is a function of the spread of the bond and altruism, which is

exogenously shifted by news events such as terrorist attacks. Investors care about the

spread of the bond (i.e. how much it yields relative to a benchmark investment) rather

than the nominal yield because the bond only constitutes a small part of a diversified

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portfolio of investor holdings. When choosing how to allocate a marginal dollar of

capital, investors will analyze these bonds relative to their other opportunities. As a

result, the spread captures this important opportunity cost of funds2. The demand for

bonds is assumed to be linear and can be described as:

Equation 1.1

Qdt = at + b * st

where Qdt is the quantity of bonds demanded in period t, st is the spread on the bonds in

period t, b is a positive constant, and at is the level of altruism in period t.

Next, I will describe the supply decision. According to the Israeli government,

the Ministry of Finance sets annual fundraising quotas for bond sales planned in

accordance with the governments foreign currency requirements (Rechavi and

Weingarten, 2003). The model assumes that the Ministry sets bond spreads each period

to minimize the cost of debt, while maintaining this exogenous quota 3. The Ministry is

concerned with the spread on the bonds rather than the nominal interest rate because the

Israel Bonds market is only one of several possible avenues to raise capital.

Consequently, the spread will indicate the cost relative to other sources4. The Ministrys

minimization problem overtperiods of changing interest rates becomes:

2 In the model, the spread is assumed to be equal to the nominal yield on the bond minus a comparableinvestment. This comparable investment can be decomposed into two components: the U.S. treasury rate(the return required to compensate investors for the time value of money) and the Israeli default riskpremium (the excess return required to compensate investors for the risk of default on the debt). st = yield (U.S. rate + risk premium) where risk premium is the difference between Israeli tradable debt and the U.S.rate. Since the U.S. rate and the risk premium are determined in different markets, they can be considered

exogenous, and are thus, not included separately in the model for simplicity.3 While it is simplest here to assume supply and demand both react on the same time horizon, in practicethis does not occur. In fact, the Ministry of Finance sets a fixed nominal rate for an entire sales period(generally, one month) and allows investors to buy as many bonds as they demand at that price within theperiod.4 In the model, I assume that the Ministry and investors demand spread relative to the same benchmarkinvestment. In practice, this may not be true. It is possible that unsophisticated investors, or those withaltruistic motivations, may be overly sensitive to the nominal yield and less sensitive to the risk premiumthan rational economic actors. The possibility that investors may get the benchmark rate component of thespread wrong is discussed in more detail in chapter 6.

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minimize (Qst * st)subject to Qst = k

where Qs

t is the quantity of bonds supplied in period t, and k is the annual fundraising

quota. The supply function is defined by the spreads, st,which the Ministry sets each

period to fulfill this condition. Using constrained minimization, one finds that the

Ministry sets each periods spread such that:

dQst/dst * st + Qst = * dQ

st/dst

which implies that rates are set according to the following supply function5:

Equation 1.2

st = + c * Qst

-1

where and c are constants with c > 0. If the Ministry is sufficiently forward looking

and can foresee the shape (or at least form expectations) of the demand function for each

of the tperiods, and one assumes that the demand function changes from period to period

only in terms of the altruism variable, at (which causes shifts in the curve), it follows that

rates will be set lower in periods where anticipatable altruism is higher.

In equilibrium, the quantity supplied must equal the quantity demanded.

Combining equation 1.1 and equation 1.2, and taking comparative statics, it is clear that

in equilibrium:

st = + c * Qdt

-1 = + c * (at + b * st)-1

Equation 1.3

dst/dat = [ - c * Qdt-2 ] / [ 1 + bc * Qdt

-2 ]

Equation 1.4

5 See Mathematical Appendix A for a proof.

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dQt/dat = 1 / [ 1 + bc * Qdt-2 ]

From this, it follows that dst/dat < 0 and dQt/dat > 0 for all upward sloping supply and

downward sloping demand curves. Consequently, it is clear that under these

assumptions, one will observe lower spreads and higher quantities transacted in periods

where anticipatable altruism is higher.

In the model, altruism only enters as a parameter in the demand function when

considering the market within years. This is because when the annual fundraising quota

is constant, the Ministry of Finances only goal is to minimize the cost of debt.

Therefore, movements of prices and quantities within the year must be related to altruism

shocks on demand. It is plausible, however, to think that the Ministrys annual

fundraising quota may change in relation to altruistic events, such that movements in

prices and quantities across years may be the result of both supply and demand shifts.

For instance, the government may have a need for greater capital at times with more

frequent altruistic events like terrorist attacks in order to pay for security needs.

Alternatively, the state may have an interest in encouraging American Jews to hold its

securities to align their financial well-being with the policy preferences of Israel. For

example, if Israel needs U.S. aid, a U.S. bondholder may be more likely to support pro-

Israeli policies if he holds Israeli bonds. If the goal of the program is to maintain contact

with Diaspora Jews and influence country policy preferences in relation to Israel, the

benefits of policy leverage are likely higher in times of turmoil when attacks are high6.

Since the annual fundraising quota changes infrequently, it seems intuitive that

over relatively short time horizons the effect of altruism on supply should be small

6 There is some evidence that this may at least be partially true. Rechavi and Weingarten (2003) explicitlyrecognize one of the programs goals as maintaining contact with Diaspora Jews.

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relative to the effect of altruism on demand. Consequently, it is probably a reasonable

simplifying assumption that the annual fundraising quota may be considered exogenous.

In order to be sure, however, the analysis in this paper will allow for the possibility that

supply may be independently affected by the same events that cause altruism in investors.

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IV. Empirical Strategy

In this paper, I examine the Israel Bonds market in order to determine whether

altruistic investors react differently to political and religious news events than profit-

seeking investors. To do this, I analyze several types of events to find out whether they

cause altruistic shifts in the demand for bonds. The two principal kinds of events

considered are Jewish religious holidays and Israel-specific news events, like terrorist

attacks. I choose these events because of their likely tie to altruistic sentiment for the

State of Israel. It is assumed here that altruism is at least partially caused by empathy

with the misfortune of others. If this is the case, one would expect that terrorism and

violence tend to evoke feelings of community and sympathy in investors. Furthermore,

because of Israels unique significance to the Jewish religion, altruism may also be partly

religiously motivated. While technically religiously-motivated altruism may actually be

guilt or some other emotion, it can be considered as part of altruism for the purposes of

this paper (defined as the selfless contribution to the demand of bonds).

In this chapter, I first examine whether altruism is casually related to the quantity

of bonds transacted. In other words, are higher equilibrium quantities observed following

events that should increase altruism or in periods with more frequent altruistic events?

Secondly, I examine whether altruism is casually related to the equilibrium spreads set

for each period. Do spreads rise or fall in tandem with altruistic events? Finally, I show

how it is possible to use these casual effects to estimate the portion of quantity

movements associated only with demand shocks.

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The Casual Effect of Altruistic Events on Quantity and Spread

To first test whether quantities move in relation to altruistic events, a reduced

form regression will be run in the form:

Regression 1.1

lnQi,t= 0 + 1 * holiday t + 2 * terrorismt+ 3 *US ratei,t

+ 4 *Riskpi,t+ 5 * timevart+ 6 * instrumenti + 7 * dowt

where lnQi,tis the log-transformed sales for instrument i in period t, instrumenti is a

dummy variable for each of the 3 instrument types, holiday tis an indicator of religious

holidays, terrorismt is an indicator of terrorist attacks, dowt is a dummy variable for each

day of the week (to allow for cyclical patterns in sales), timevaris a time variable that

allows for a time trend in the series,Riskpi,tis an interaction variable for each of the i

instruments with the Israeli default risk premium (i.e. a dummy variable for each

instrument multiplied by the spread for that instrument), and US ratei,t is an interaction

variable for each of the i instruments with the appropriately comparable U.S. treasury

rate. Since the quantity data follows a right-skewed distribution, a log transformation is

used to make this variable more closely follow a normal distribution. Consequently, the

regression coefficients, 1 and 2, can be interpreted as percent increases or decreases in

quantity rather than changes in levels.

The nominal yield on Israel Bonds is excluded from this reduced form regression

in order to avoid simultaneity bias. This bias is caused because the spread that the

Ministry of Finance sets is a function of the quantity demanded, while at the same time

the quantity demanded is a function of the spread set. As a result, including the nominal

yield causes correlation between the regressor variable and the error term. In the next

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section, I will explain how I deal with this bias in order to properly identify the effect of

altruism on the demand curve alone. In this reduced form regression, however, the

coefficients, 1 and 2, represent only the effect on equilibrium quantities. In other words,

they are the effect on quantities after both demand andsupply adjust accordingly.

The Israeli default risk premium and the U.S. treasury rate are included in the

regression as controls for the exogenous part of the spread. These rates are the important

benchmarks to which investors and the Israeli government compare the nominal yield of

the bonds when assessing the attractiveness of the investment. They represent a base

return required to compensate investors for the time value of money (the U.S. treasury

rate) and the additional return required to compensate investors for the possibility of an

Israeli default on the debt (the Israeli default risk premium). Notably, the default risk

premium is possibly correlated with the same events that cause shifts in altruism. For

instance, a terrorist attack may simultaneously increase the risk premium that investors

demand and increase sympathy for the state. Empirical research has shown mixed

support for this possibility. Blass, Peled, and Yafeh (2004) argue, for instance, that

Israel-specific events (like terrorism) have little impact on the risk premium relative to

international events from 1996-1999, but do impact the risk premium in 2000.

If the risk premium is also correlated with the quantity of bonds transacted,

omitting it may create a bias in the coefficients of altruistic events. Since the nominal

yields on these bonds change infrequently, changes in the risk premium between sales

periods (when the nominal yield is fixed) may be correlated with changes in the spread

that investors demand to hold the bonds. In fact, between periods, the only movement in

the spread that investors receive results from movement in the exogenous risk premium

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and the U.S. treasury rate. Therefore, including the exogenous benchmark rates is

important in order to prevent omitted variable bias; however, the complexity of how they

enter into the model makes the coefficients estimated for their effect meaningless to

interpret.

Next, I will examine whether spreads move in relation to altruistic events7. A

second reduced form regression is run:

Regression 1.2

Yieldi,t= 0 + 1 * holiday t + 2 * terrorismt

+ 3 *US ratei,t+ 4 *Riskpi,t+ 5 * timevart+ 6 *instrumenti

where Yieldi,t is the nominal rate for instrument i in period t, instrumenti is a dummy

variable for each of the 3 instrument types, holiday tis an indicator of religious holidays,

terrorismtis an indicator of terrorist attacks,Riskpi,tis an interaction variable for each of

the i instruments with the Israeli default risk premium, US ratei,tis an interaction variable

for each of the i instruments with the appropriately comparable U.S. treasury rate and

timevartis a variable that allows for a time trend in the series. Since the spread is only

changed periodically, this regression will be run on the subset of observations that

includes only the times at which the interest rate setting decision is made (generally, this

is 5 days before a monthly sales period begins).

Demand Effects

Once it has been determined that bond sales increase or that bond spreads fall in

tandem with altruistic events, it is interesting to understand which portion of this

7 In this paper, I sometimes use the words yield and spread interchangeably. This is because a changein the yield, when holding the U.S. rate and risk premium constant, is equivalent to a change in the spread.

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variation is the result of the demand curve alone, as the primary motivation of this paper

is to understand unconventional investor motivations. In the model of the Israel Bonds

market presented above, altruism shocks affect the demand curve directly and affect the

supply curve through changes in the annual fundraising quota across years. Therefore,

within years, one expects the spread to fall in conjunction with altruistic events, but

across years, it is possible that a supply effect will offset this fall. Consequently, the net

effect on spreads is indeterminate. Yet, the fact that the spread likely adjusts somehow in

relation to altruistic events implies that the actual effect of altruism on quantity demanded

is different than the casual effect of altruism on equilibrium quantities estimated with

reduced form regression 1.1.

For instance, the model predicts a unit increase in altruism across periods will

result in a decrease in spreads within years. The resultant decrease in spreads, however,

means that there will be an offsetting decrease in demand. Therefore, quantities in

equilibrium within years may actually move less than the full demand shift would predict.

If the effect of exogenous spread movements on quantity demanded can be determined, it

is possible to solve for the other parameters that identify the demand function using

results from regressions 1.1 and 1.2.

In the model presented in chapter 3, quantity demanded is assumed to be a linear

function of spread and altruism, while the spread supplied is a linear function of the

inverse quantity and altruism (since it is allowed that the annual fundraising quota is

related to altruistic events like attacks). Consequently, it is necessary to identify the

following structural regression equations for supply and demand8:

8 In the same way that the right-skewed distribution of quantity is log-transformed to ensure that it followsa more normal distribution, the right-skewed distribution of inverse quantity, which enters the supplyfunction, is log-transformed as well. Since ln(Q-1) = -ln(Q), I expect that the estimated coefficient 1 willtake the opposite sign that the parameterc has in the model from equation 1.2 in chapter 2. Consequently,

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S: Yield= 0 + 1 lnQuantity + aA + 3 US+ 4Risk+ 5X

D: lnQuantity = 0 + 1 Yield+ aA + 3 US + 4Risk+ 5X

whereA represents an indicator of an altruistic event, USrepresents the appropriate U.S.

treasury rate,Riskrepresents the Israeli risk premium, andXrepresents exogenous

controls in the regressions. Combining these structural equations with regressions 1.1

and 1.2, it is possible to solve for the unobservable coefficient a (the effect of altruism

on demand alone) in terms of a (the coefficient on an indicator of altruism in regression

1.1: the causal effect of altruism on equilibrium quantities), a (the coefficient on an

indicator of altruism in regression 1.2: the causal effect of altruism on equilibrium

spreads), 3, 3, and 3 (the coefficients on the U.S. rate from regression 1.1, 1.2 and the

structural demand equation)9. It can be shown that10:

Equation 1.5

a = a - a * [(3 3)/ 3]

In order to properly estimate 3, it is necessary to examine the lag structure of the

Israel Bonds market. The market works in the following way. For each sales period

(generally a month-long period), the Ministry of Finance sets the interest rate at which

each instrument of Israel Bonds will be sold for the duration of the period. Therefore, the

state sets one price for the entire period and allows orders to be filled as investors will

demand within that period. Since supply is fixed to be perfectly elastic within each

period, demand shifts can be recognized by changes in short-term quantity fluctuations.

the resultscan be interpreted to imply a 1 % increase in inverse quantity results in a -1 change in the spreadsupplied.9 For a proof see Mathematical Appendix B.10 As a preview to the reader, the value of a appears not to be statistically different from zero in mostcircumstances. If a is assumed to be zero, the full demand shift, a, is close to a (the amount thatquantities move in equilibrium, estimated in regression 1.1). In other words, almost all of the movement ofquantities in equilibrium can be attributed to demand shifts.

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Notably, within each sales period, the spreads that investors receive change, even

though the nominal yields on the bonds do not. This is because the opportunity cost of

funds, or the bottom half of the spread, varies within periods. For instance, the yield on

Zero Coupon Israel Bonds may be a fixed 6% for a sales period, but within that period

U.S. treasuries and the Israeli risk premium change daily. As a result, the spread, which

is the difference between the bond yield and some combination of U.S. treasuries and the

Israeli risk premium, varies substantially. Since both yields from the U.S. treasury

market and the tradable Israeli debt market can reasonably be taken as exogenous, the

variation of these rates within a given period will trace out the price elasticity of demand.

Furthermore, by using this methodology, it is possible to estimate these elasticities over

longer periods of data than would otherwise be possible. Since changes in the spread

within sales periods are only determined by U.S. treasuries and the risk premium, it is not

necessary to have Israel Bond yield data for this calculation. Therefore, estimates can be

made incorporating data from several years before 2001 when the yield data begins,

improving the overall quality of the estimates.

To identify the price elasticity of demand, a fixed-effects regression, controlling

for each sales period and instrument type, will be run in the following form:

Regression 1.3

lnQi,t= 0 + 3 * US ratei,t+ 4 *Riskpi,t

+ 5 * timevart+ 6 *instrumenti + 7 * dowt+ 8 * periodj

where lnQi,tis the log-transformed sales for instrument i in period t, instrumenti is a

dummy variable for each of the i instrument types, US ratei,tis an interaction variable for

each of the i instruments with the comparable U.S. treasury rate,Riskpi,tis an interaction

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variable for each of the i instruments with the Israeli default risk premium,periodj

represents a dummy variable for each of thej sales periods, dowt is a dummy variable for

each day of the week, and timevaris a time variable that allows for a time trend in the

series. Since many of the indicators of altruistic events used in this paper change slowly

relative to the length of a sales period, they are not used in this regression11.

Including dummy variables for the sales periods in the regression allows analysis

of changes of spreads within periods, when their movement is exogenously determined.

Since changes in the spread are exogenous when controlling for the sales period, 3 can

be interpreted as the effect of a change in U.S. interest rates on the quantity demanded,

holding all other variables constant, including the yield. Specifically, 3 is the price

elasticity of demand the percent change in quantity associated with a unit change in the

treasury rate, all else equal.

11 The point of this exercise is precisely to identify the coefficient a, the effect of altruistic events on thequantity demanded. It is my belief that altruism works over long time horizons. Consequently, it will notbe possible to observe the true value of aby including it in regression 1.3, which only looks within salesperiods (time horizons in the range of one month). Since altruistic events are not correlated with the U.S.treasury rates, omitting them should not bias the regression estimates.

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V. Data

Israel Bond Instruments

For the purposes of this paper, a unique and confidential dataset has been

constructed with information provided by the Israeli Ministry of Finance on the prices

and sales of the Israel Bonds. Data is provided on the yields and quantities at which

several Israel Bond instruments were sold over the 1990-2004 period. The dataset

contains monthly yield information on the Infrastructure and Absorption Issues (Zeros),

the Jubilee Issues Series A (5 years), the Jubilee Issues Series B (10 years), the Chai

Issues, several Canadian Issues and several variable rate (Libor-based) issues from 2001

to 2004. Furthermore, daily data on the quantity of bonds sold for three of these

instrument types (the Infrastructure and Absorption Issues and the two Jubilee Series) is

provided from 1990-2004.

For the purposes of this paper, I will focus entirely on the Infrastructure and

Absorption Issues and the two series of Jubilee Issues sold in the United States. The

limitations of the data provided make these bonds the easy choice, as they are the only

instruments for which daily quantity data is available. Furthermore, they are among the

most popular instruments with investors and therefore the most relevant to policy

considerations. In 2001, the combined dollar value of the Jubilee and Zero Coupon

bonds accounted for 57% of all Israel Bonds sold. This statistic rose to 76% in 2002 and

2003 and looks to be even higher in 2004 (78% as of November 2004).

Additionally, the terms of these particular instruments make them more likely to

be held by individual investors for whom one would expect the altruism effect to be the

greatest. For instance, the Jubilee A and B Series each offer fixed annual interest and the

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Infrastructure and Absorption Issue is a zero-coupon discount bond. These interest

payment methods are simple and therefore more likely to be attractive to individual

investors than variable rate bonds with complex interest calculation methods. Also, these

instruments offer relatively small minimum subscription stipulations. The Zero Coupon

bonds are sold at a minimum face value of $6,000 and the Jubilee Bonds are sold with a

minimum subscription of $25,000 (although subsequent purchases can be as low as

$5,000). Other Israel Bond instruments tend to have higher minimum subscription

requirements. For instance, the 4th Variable Rate Libor notes come in minimum

subscriptions of $100,000 and the 3

rd

Libor Notes come in minimum subscriptions of

$150,000. While the Mazel Tov notes are also sold in much smaller denominations

(minimum subscriptions of $100), they serve primarily as gifts rather than investments

and only constitute a very small part of the Israeli debt. Appendix B provides additional

detail on the terms of these bonds from their prospectuses.

Finally, these three bond instruments offer the greatest chance of finding

systematic variation in the yield spreads. The yields set by the Ministry of Finance

generally change monthly for these instruments, whereas a few other instruments only

change quarterly. For instance, the Mazel Tov Bonds and the Chai Dollar Savings Bonds

only adjust their offered rates every six months. Furthermore, the Libor-tied notes tend to

be a fixed spread over Libor. Only very rarely is the offered spread above Libor changed.

For example, the 4th Variable Rate Libor notes have been a constant 60 basis points above

Libor for the past several years. While the nominal rates on these bonds vary, the fact

that they maintain a constant spread with Libor means that they do not fluctuate period to

period in conjunction with changes in altruism for Israel.

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Each instrument type has gone through several different issues over time. For

instance, the Infrastructure and Absorption Issue (Zero Coupon) was first issued in 1990.

Eventually, when the bonds from this subscription were sold, a second issue was released

in December 1991. As of December 2004, the Zero Coupon Bond is in its 8th Issue.

Similarly, the two Jubilee Series Bonds have each had 4 issues since their release in 1998

until the present day. When analyzing the sales of these instruments over long periods of

time, it is important to ensure that there are no important changes in the terms of their

prospectuses which could significantly alter their attractiveness to investors between

issues.

To ensure cross-comparability, a dataset was manually compiled by looking

through Securities and Exchange Commission filings made by the State of Israel. Copies

of all available prospectuses and registration supplements filed from 1993 until the

present were downloaded from the online Thomson Research database and read for their

essential features. While it was discovered that the essential terms of the bonds remained

constant across issues, the frequency at which Israel updated the nominal interest rates on

the bonds changed significantly. In the early 1990s, the interest rate that the bonds were

being sold at was only updated quarterly. Eventually, this policy changed and rates were

updated approximately every 45 days. More recently, the interest rates offered on the

bonds have become updated monthly. These sales periods, or periods within which the

supply of bonds is fixed, are necessary to understand in order to properly measure the

effect of altruism on demand alone. Therefore, dummy variables are included in the

dataset for each sales period. Table 1 shows the dates of changes from one sales period

convention to another.

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The raw dataset provided by DCI required some alteration to make it suitable for

analysis. Firstly, overlap between consecutive issues of the same instrument was

eliminated in order to make the data easier to work with. Obvious cases where sales for

an issue were recorded at a time when the issue was either not yet being sold or finished

being sold were deleted. Furthermore, when small periods of overlap were found

between one issue and the next, a time was selected to consider the end of the previous

issue and the start of the following one. This time was selected to match as best as

possible the start of a new sales period. In all but one case, such overlap was small and

inconsequential (i.e. only a few days), making it easiest to simply delete the improper

observations. This procedure makes the most sense because it is likely that sales before

the start and end date of the issue were either sales unavailable to the general public,

accounting corrections or coding errors. Therefore, including them in the dataset would

provide no useful information regarding how investors react to altruistic events. Overlap

between the 4th and 5th issues of the Zero Coupon bond, however, was substantial. For a

period of 4 months from January 1997 through April 1997 both issues were sold in

material quantities. Therefore, these sales were added together in the final dataset in

order to prevent underestimation of the true quantity of Zero Coupon bonds sold during

this period.

Furthermore, there were several missing observations in the data. One would

expect that a sales observation would be present for each instrument on every weekday

that the DCI office was open. Instead, there are many weekdays for which there are no

observations. There are three possibilities for why this could be the case. Firstly, it could

be that a missing observation means that sales for that day were zero. Secondly, a

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missing observation could mean that DCI was closed that day for either a holiday or

some other reason. Thirdly, it is possible that the recording of new sales for the day was

simply pushed off until a later date. For instance, it is possible that when sales are low,

paperwork is only processed every other day rather than daily.

After consulting with the National Director of Operations at DCI, it seems most

likely that the missing observations are a mix of both office closings and days with zero

sales. The record keeping system used by DCI was changed in April 2001 when they

changed fiscal agents from Chase Manhattan Bank to the Bank of New York.

Consequently, old sales data was converted manually in order to be compatible with the

new system. DCI believes the data from these two periods to be comparable as a result of

this conversion. Interestingly, before 2001, missing observations are less common and

observations of zero sales are present. After 2001, missing observations are more

common and there are substantially fewer observations listed explicitly as zero.

Furthermore, variation within the data shows that there are several days with low enough

sales such that the presence of a day with no sales is plausible. As a result, I believe that

these missing observations are days with zero sales mixed with a small number of office

holidays.

Since an accurate list of historical office closings is not available, and it is

unlikely that the number of office holidays is large enough (or is sufficiently correlated

with altruistic events) to materially bias regression estimates, the following procedure

was used to handle missing observations. A comprehensive list of United States Treasury

yields was taken from Global Financial Data server. This list was then merged with the

Israel Bond sales data. In the case where both the U.S. Treasury data and the Israel

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Bonds data had no observations for a given day, the day was dropped from the dataset

and considered an office closing. Since the U.S. Treasury data is comprehensive and

from a reliable source, I assume that these observations represent only official market

(and therefore also national) holidays. When either U.S. Treasury data was available or

one of the three Israel Bonds instruments had a sales observation but the others did not,

all missing observations for that day were considered to be zero. Similarly, a very

small number of negative sales, which likely represent accounting adjustments, were

considered zero observations if they were present on a weekday.

Finally, a number of weekend observations were found in the dataset. For these

observations, it is possible that they were properly meant to be included in the previous or

following business day. Feedback from DCI indicates that the sales report was

balanced by month, which means that the sum of the daily data was set to match their

official sales numbers from each month. In addition, these weekend observations can

sometimes be substantially larger-than-average observations, which may influence

regression estimates if improperly handled. Consequently, it is likely that these weekend

observations either represent a residual amount of sales for a week, the sum of sales

coded without dates for the week, or simply an error in the dataset. For these reasons, the

most sensible way to handle the weekend observations is to delete them.

The resulting dataset contains 7148 observations. Since all bonds are non-

negotiable, they are all new issues which mature at a fixed time from the issue date and

cannot be traded, except in special instances. Therefore, each yield and quantity data

point represents the price and amount at issuance of new bonds sold. Figures 2-4 display

some descriptive statistics of the data for each instrument type.

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The main shortcoming associated with this dataset is that the sales records do not

match perfectly with the time that the investment decision is made. Sales are only

recorded when receipt of payment is made to DCI. Since there is paperwork and an

application process to apply for these bonds, there is a lag between the time the investor

decides to buy the bonds and the time the sale is recorded. The Ministry of Finance

suspects that this lag can be anywhere from one day to 2 or more weeks depending on the

circumstances of the investor. To account for this, events will be looked at on a lagged

basis (i.e. number of attacks in the last month) and the evolution of quantity movements

after an event will be analyzed

12

.

Constructing Comparable Investment Variables

Variables are added to the datasets to serve as comparable investments. Ideally, a

non-altruistic security would be used that matches all of the important characteristics of

each Israel Bond instrument so that changes in the spread are only representative of how

much investors are willing to forgo to selflessly support the state (and a fixed illiquidity

premium to compensate for the transfer restrictions of the bonds). Unfortunately, there

exists no one security that matches the Israel Bonds perfectly in all respects. Instead, I

will control for both the U.S. treasury rate (the time value of money) and Israeli default

risk premium (the incremental rational return required to hold Israeli debt instead of U.S.

debt) separately.

Data on United States 5-year and 10-year treasuries are taken from the Global

Financial Data server. These rates, which are the ones that the Ministry of Finance

12 Evidence from the event studies conducted in chapter 6 suggests that this lag time is approximately 5-8business days, or 1-2 weeks.

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claims that it uses when setting the rates for the Israel Bonds, are useful because they will

match the Bonds both in terms of which currency the principal is paid in and in terms of

time to maturity.

Figure 5 shows the U.S. 10-year government bond yield along with the yields on

the Jubilee 10-year and Zero Coupon. Figure 6 shows the U.S. 5-year rate compared to

the Jubilee 5-year. From these figures, it is clear that the nominal yields on these bonds

closely track the comparable U.S. treasury benchmark.

Since the U.S. rates do not account for Israel-specific risk, it is important to

control for the default risk premium as well. Given the constraints of the available data,

it is only possible to control for a spread that will have close co-movement with the actual

risk premium. Since 1-year constant maturity Israeli debt yields are available from the

Thomson DataStream data service, it is possible to calculate the spread between 1-year

tradable Israeli debt and 1-year U.S. treasuries. Since the Israeli debt is denominated in

New Israeli Shequelim (NIS), however, this spread is an imperfect approximation of the

true default risk premium. The calculated risk premium includes expected inflation and

an inflation risk premium in addition to the default and liquidity risks. While liquidity

risk for government debt should be small, expected inflation and the inflation risk

premium likely account for a significant portion of this spread. It would be possible to

eliminate the inflation-related aspects of this spread by converting the currency on the

Israeli bond into U.S. dollars using forward currency rate data. Unfortunately, while

forward currency rates are available at the 1-year horizon from Bloomberg, the frequency

of the observations is too sporadic to be meaningfully employed as a correction in the

spread. Therefore, it will be impossible to eliminate expected inflation and inflation risk

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from this spread. Fortunately, since there is unlikely to be a strong correlation between

altruistic events and inflation, this spread should be an unbiased approximation of the

Israeli default risk premium.

Additionally, it is potentially flawed to use the default risk at the 1-year horizon to

approximate the default risk at the 5-year and 10-year horizons. Theoretically, it is

possible that the default risk premium varies differently at various time horizons.

Therefore, in using this spread I am making the assumption that the Israeli risk premium

is relatively constant across time horizons; however, even if it does vary across horizons,

it should not bias the regression estimates so long as it does not vary systematically with

altruistic events.

Furthermore, because the bonds used as comparable investments have differences

in interest payment conventions and coupon amounts with the Israel Bonds, there will be

slight mismatching in terms of duration. This additional error, however, is only of

second-order importance relative to the correct matching of maturities. Since the largest

cash flow from these securities comes at maturity with the repayment of principal, a close

matching of maturities is significantly more important when calculating the spread.

Constructing Altruism Indicators and Event Variables

Variables are constructed for altruistic events using a historical timeline of

relevant terrorist attacks from the Israeli Ministry of Foreign Affairs website entitled,

Suicide and Other Bombing Attacks in Israel Since the Declaration of Principles (Sept

1993).13 This timeline of events is considered exhaustive and is used to represent the

universe of all possible Israeli terrorist attacks in this period. A total of 121 terrorist

13 http://www.mfa.gov.il/

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attacks are identified from 1993-2004. Each is coded according to date, number of

attacks, number killed, and number wounded, as provided by the timeline14. The number

of Israelis killed or wounded serves as an objective proxy for categorizing the salience of

individual events. The death of the suicide bomber in a terrorist attack is not included in

these tallies because it is unlikely that pro-Israeli altruistic investors consider this a

relevant factor in their perceptions of salience. Tables 2a and 2b provide descriptive

statistics of these variables.

All news events documented on weekends or holidays are moved to the following

business day. This correction is made to ensure that the first day of an event, in event-

time, is the same as the first day an investor can act on the news information (i.e. the day

of the attack). Since Jerusalem is 7 to 10 hours ahead of the United States, in most cases,

investors in the United States will have already incorporated all information from an

event in Israel by the start of that same business day in the United States. In the event

that multiple attacks are coded on the same day, the statistics for both dead and wounded

are added together.

To discern the pattern of sales following an event, dummy variables are created

for consecutive periods of fixed length after an event. For instance, a variable is

constructed that has value of 1 for the first day after an attack and 0 otherwise. Similar

variables are created for the second day, third day, and so on for 75 days following a

terrorist attack. Using these variables will help identify the abnormal sales for each day

following an event. Furthermore, several index variables are created from these events to

14 Where information on the number of killed or wounded is not available from the MFA website, thedataset is supplemented with information from the Jewish Virtual Library.Source: http://www.jewishvirtuallibrary.org/jsource/Terrorism/TerrorAttacks.html

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mimic changes in altruistic sentiment. For example, variables are created for the

frequency of attacks in the last 2 weeks, 1 month and 2 months.

Lastly, religious holidays are coded in a similar manner. Due to the large number

of Jewish holidays, the most important holidays are selectively chosen to be examined.

Allowing for too many religious events to be included in the regression simultaneously

will likely over fit the data. Holidays are selected according to their prominence for

American Jews and their religious/symbolic significance. The holidays analyzed include:

Rosh Hashana (Jewish New Year), Yom Kippur (Day of Atonement/Holiest Day of the

Year), Yom HaShoah (Holocaust Memorial Day), and Yom HaAtzmaut (Israeli

Independence Day). Since Jewish holidays are fully-anticipatable events unlike terrorist

attacks or political developments, I expect that spread changes will be more obvious for

these events than for terrorist attacks. Table 2c contains a calendar of these holidays

from 2000-2005.

Since holidays are cyclical events, it will require caution when interpreting their

effect on sales. Sales in the Israel Bonds market are bound to be very cyclically driven

throughout the year. Much of the variation in sales will be tied to roll-overs of maturing

issues. Furthermore, some institutions may regularly purchase bonds at a particular time

of the year (for instance, at the start of a quarter or a half-year period). Since there will

be little to no variation in the date of a particular holiday (i.e. Rosh Hashanah generally

occurs in September), it will be hard to separate the effect of a particular holiday from

another seasonal or cyclical effect. Additionally, since holidays occur in relatively fixed

intervals, it will be necessary to analyze holidays as groups. For instance, when

analyzing sales after Rosh Hashanah and Yom Kippur, it will be essential to look at sales

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patterns from the start of Rosh Hashanah until long after Yom Kippur. The fact that Yom

Kippur regularly occurs 8 days after Rosh Hashanah makes it impossible to consider its

effects separately. Similarly, Yom HaShoah is shortly followed by Yom HaAtzmaut and

Yom HaZikaron (Israeli Memorial Day), which makes it difficult to identify their effects

separately as well.

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VI. Evidence

The evidence suggests that quantities in equilibrium increase substantially when

attacks are more frequent. Furthermore, there appears to be a significant period

following individual attacks and important holidays with higher than average sales. On

the other hand, there is little statistical evidence that equilibrium spreads move relative to

altruistic events. While there is some evidence that spreads rise when the Israel risk

premium rises to compensate investors for the additional risk, it is found that investors

themselves seem to ignore Israel-specific risk. In fact, they purchase additional bonds

when the default risk premium is higher.

Equilibrium Quantity Results

Table 3 provides details of the regression estimates for equilibrium quantities for

all three instruments and Table 4 provides estimates broken down by instrument type.

Regression estimates are shown for altruistic events measured on the 2 week, 1

month and 2 month time horizons for log-quantity, quantity and a transformed log-

quantity15. I estimate an increase of 6.6% in sales for each additional attack in the last

two weeks, an increase of 6.1% for each additional attack in the last month and an

increase of 4.5% for each additional attack in the last two months. All estimates are

statistically significant at the 1% level, except on the 2 week horizon which is significant

at the 5% level16. While all 3 instruments show sales movements in relation to terrorist

15 While regression results using log-quantity are believed to be the most reliable, specifications usingquantity and a transformed log-quantity are shown to illustrate the effect of how missing observations weretreated on the results. The variable lnQplus is equal to ln(2745+Q) so that observations with Q=0 do nothave to be dropped from the ln(Q) regression. The number 2745 was selected because it is the smallestnon-zero quantity observation in the dataset.16 Since there appears to be serial correlation in the data, Newey-West standard errors are used to correctfor arbitrary heteroskedasticity and serial correlation of 7 lags. Significance is reported throughout thepaper using 7 lags for daily quantity data and 40 lags (approx. 2 months) for less frequent yield data.

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attacks, the Jubilee 10-year appears to move the most with a 16.5% increase in sales per

additional attack in the last 2 week period.

Figure 7 graphs the frequency of attacks over time with average daily sales of the

Zero Coupon bond. As the first Palestinian intifada, or uprising, waned around 1991,

both low attacks and sales are observed. Following the Declaration of Principles in

September 1993 (also known as the Oslo Accords a significant step in the peace

process), attacks briefly rise, as do sales. A period of relative calm and low sales

followed until the start of the most recent intifada (the al-Aksa Intifada) in September

2000. This new intifada ushered in a new wave of violence, and interestingly, also

significantly increased bond sales.

With respect to Rosh Hashana, daily sales are higher on average by 23.5% over

the 1 month period following the holiday and by 29.7% over the 2 month period

following the holiday. These increases are driven strongly by sales of the Zero Coupon

bond, which has 41.1% higher sales in the month long period following the holiday and

56.5% higher sales in the 2 month period following the holiday. Since DCI organizes

extensive marketing of the Israel Bonds to Jews attending religious services on Rosh

Hashanah and Yom Kippur, this result is not surprising. The Zero Coupon bonds are

most attractive to these small investors because they require the smallest minimum

purchase and pay interest using the simplest convention. Consequently, one would

expect that the religiously-motivated sentiment created by these bond drives for small

investors would show up in greater sales of the instruments most attractive to this

investor class.

Different lag specifications were tested and it was found that significance was robust to these changes.

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Regressions 7 and 8 from Table 3 show statistically significant results, which are

opposite those one would expect to find for Rosh Hashanah but consistent with what one

would expect to find for terrorist attacks. In these regressions, a variable lnQplus is used

to represent quantity. This variable represents a transformed log-quantity equal to

ln(2745+Q) so that observations with Q=0 do not have to be dropped from the regression.

Replacing zero values with relatively small numbers, however, can falsely create huge

effects when using logs. Since there is significant uncertainty about the correctness of

the observations with zero values in the first place (see discussion in data section),

these results cannot be trusted without scrutiny. The observations with zero values were

determined by comparing U.S. treasury market data with Israel Bond sales--- if there was

U.S. market data but no Israel Bond observation, it was assumed that the day had zero

sales. It is possible, however, that several holidays that were observed in the Israel Bond

office were not observed by the U.S. market. Specifically, it is likely that the Israel Bond

office was closed for several days during the Rosh Hashanah and Yom Kippur period.

Since these observations were listed as zero rather than dropped (as an office closing

should be), using this specification with logs can negatively bias the coefficient estimate

dramatically. The fact that the coefficient for terrorist attacks seems to match the results

from the other regression specifications, supports this theory because attacks should not

systematically occur near days with different holiday conventions.

The evolution of sales in event time is shown for terrorist attacks, Rosh Hashanah

and Yom HaShoah in Figures 8-16. These figures graph the cumulative abnormal

percent increase (or decrease) for each day following an event. In other words, a straight

line in these figures represents a period of relatively constant above average sales (in the

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amount of the slope of the line, per day). All patterns are found to be statistically

significant, unless otherwise noted. Chi-squared statistics are listed in the appendix with

the corresponding figures17.

Figure 8 provides the pattern of sales for all 3 instruments together for Rosh

Hashana. The findings are consistent with what one would expect. Following Rosh

Hashanah, there is a period of 5 to 8 business days with below-average to normal sales

followed by a steep increase in sales thereafter. During this 5 to 8 business day period,

Yom Kippur occurs and the High Holy Days end. Following the end of the High Holy

Days, bond sales come in daily at 52% higher than average amounts until day 31

18

. From

days 31 to 65, sales slow to 35% above average, until sales return to normal from day 66

to 7519.

Figures 9 and 10 show the pattern of sales following Rosh Hashana for the Jubilee

10-Year and Jubilee 5-Year, respectively. Both instruments follow a similar pattern

indicative of a small surge in sales shortly following the holiday. Both instruments

exhibit average or below-average sales for 5-9 days following Rosh Hashana. After that,

there is a brief period of approximately 7 days with above average sales, followed by a

prolonged period of average sales (as indicated by a flat line in the graph) for about 35

days. This inactivity is followed by another brief surge and then again average sales20.

17

To determine significance of the cumulative abnormal sales, aX2

test was run on the dummy variables foreach day following an attack of a particular salience. The test determined whether the sum of each of the75 coefficients (one for each day after an event) was statistically significant. Newey West standard errorswere used to control for arbitrary hetereoskedacity and serial correlation of up to 7 lags.18 This amount is estimated using the slope of the line from day 9 (13.7%) to day 31 (1159.3%) in Figure 8.19 This amount is estimated using the slope of the line from day 32 (1119.5%) to day 65 (2265.8%) inFigure 8.20 This second surge in sales is likely to be attributable to seasonality in bond sales. Since bond sales can becyclically-driven, it is difficult to separate the effect of a holiday (which also occurs around the same timeevery year) from seasonality.

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The pattern of cumulative abnormal sales for these two instruments is only statistically

significant at the 15% level.

Figure 11 shows a much more prominent effect following Rosh Hashana for the

Zero Coupon bond. For the Zero Coupon, bond sales are average until 11 days following

the holiday. At that point, sales come in daily at 65% above average for the next 60 days,

until they gradually return to normal21. This pattern is found to be statistically significant

at the 1% level. This evidence supports my earlier finding that the Zero Coupon bond is

the primary instrument affected by the High Holy Days season because of its

attractiveness to small investors and its use in religious bond drives.

Figure 12 shows the evolution of sales following a terrorist attack for all three

instruments together. The pattern supports the claim that following a terrorist attack there

is a period of elevated bond sales. For instance, Figure 12 shows a period of

approximately 8 days following an attack with average sales. This period is observed

because of the lag associated with the purchase of these bonds. Immediately following

this period, there is a period of approximately 34 days with consistent above-average

sales of 7.9% per day22. Sales then return to normal levels from day 44 to 75, with a brief

bump from days 60-75. This pattern is mimicked in Figures 13, 14 and 15 for the

Jubilee 10-year, Jubilee 5-year and Zero Coupon bonds, respectively. Notably, the

Jubilee 10-year bond reacts the most predictably to terrorist attacks. These bonds

immediately increase in sales following an attack and remain at elevated levels until

approximately 40 days after the attack when they return to normal levels. These figures

also seem to suggest that the Zero Coupon bondholders react slower to news of an attack

21 This amount is estimated using the slope of the line from day 10 (49.0%) to day 65 (3620.6%) in Figure11.22 This amount is estimated using the slope of the line from day 9 (-20.6%) to day 43 (248.3%) in Figure12.

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then Jubilee bondholders. Figure 15 suggests that it takes approximately 30 days after an

attack before observing above-average sales for these investors. It is possible that these

smaller investors either take a longer time to complete the bond purchase paperwork or

incorporate new information slower than larger investors.

Figure 16 provides the pattern of abnormal sales following Yom HaShoah. The

pattern for Yom HaShoah is much more difficult to explain than the patterns for terrorist

attacks and Rosh Hashana. Yom HaShoah is a much less prominent event than Rosh

Hashana. Furthermore, Yom HaShoah occurs close by to several other important cyclical

events. Passover, Yom HaZikaron and Yom HaAtzmaut all occur within a short period.

In addition, the chi-squared statistic indicates that the cumulative abnormal sales 75 days

from the event is statistically insignificant. The pattern appears to become positive

approximately one month after Yom HaShaoh, which coincides with the month of June,

the cyclical half-point of the year, and then falls sharply again. Therefore, given the

pattern of the variation it seems likely that this event can better be attributed to cyclical

forces (such as bond renewals or other purchases) associated with the 6 month mark in

the year.

Event Salience

Events are further broken down to identify their effect by salience. Terrorist

attacks are divided into a low salience and high salience group according to the number

of people wounded in each attack. Each salience group contains one half of the total

attacks so that the high salience group contains all attacks with over 29 people wounded

and the low salience group contains all attacks with 0 to 28 people wounded.

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The pattern of sales following these events shows that high salience terrorist

attacks increase sales more than low salience events while controlling for the High Holy

Days season. Figure 17 shows the evolution of abnormal sales in event time for the 75

business day period following an attack. After 75 days, the high salience events produce

an average increase in sales of 5.5% per day, while the low salience events produce an

average increase of only 1.9% per day. Cumulative abnormal sales for the low salience

group are found to be statistically insignificant (X2=0.81; P =0.3690), while cumulative

abnormal sales for the high salience group are statistically significant at the 1% level

(X

2

=9.62; P =0.0019).

Additionally, the 11 most salient attacks in terms of number of persons wounded

are identified and examined for their effect. Figure 18 shows the pattern of sales

following these 11 large attacks. Figures 19, 20 and 21 show the pattern of sales after the

attacks for the Jubilee 10-year, Jubilee 5-year and Zero Coupon individually. I find a

consistent pattern of greatly above-average sales following these events. For all three

instruments together, I estimate above-average sales of 23.6% per day over the entire 75

day period tested23. In addition, I estimate above-average sales of 31.3% per day for the

Jubilee 10-year, 24.3% per day for the Jubilee 5-year and 14.9% per day for the Zero

Coupon over the course of the same 75 day period24. The pronounced nature of these

nearly monotonically increasing patterns, along with the steep slopes (indicating

relatively high abnormal sales) suggests that salience is an important factor motivating

bond sales. In fact, I previously found that the average terrorist attack only produces 34

23 This amount is estimated using the slope of the line from day 1 (-43.9%) to day 75 (1707.0%) in Figure18.24 This amount is estimated for the Jubilee 10-year from the slope of the line from day 1 (8.8%) to day 75(2323.1%) in Figure 19; for the Jubilee 5-year from the slope of the line from day 1 (70.9%) to day 75(1728.9%) in Figure 20; and for the Zero Coupon from the slope of the line from day 1 (62.8%) to day 75(1043.2%) in Figure 21.

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days of above average sales with an increase of 7.9% per day. Consequently, it appears

that more salient attacks (as defined by the number of persons wounded) increase sales by

much larger amounts and for much longer periods of time.

Equilibrium Yield Changes

Interestingly, while quantities do move statistically relative to holidays and

terrorist attacks, yields generally do not. Table 5 shows the regression results for all

instruments together looking at events on the 1 month and 2 month horizon. There is no

statistically significant evidence that altruistic events cause yields to move, holding the

U.S. rate and risk premium constant25. The only event variable that moves spreads

statistically significantly is Yom HaShoah. As discussed in the previous section,

however, it appears this variable likely captures the cyclical effect of the half-year.

Consequently, it is not surprising that spreads move concurrently.

Table 6 lists the same results broken down by instrument type. Similarly, few

events are statistically significant aside from Yom HaShoah. Notably, however, there is

statistically significant evidence that spreads move relative to terrorist attacks for the

Jubilee 10-year bonds. In fact, I estimate that spreads increase by 0.019 for every

additional terrorist attack in the past month and that spreads increase by 0.014 for every

additional terrorist attack in the past 2 months for this instrument type. The fact that

there is some statistical evidence that spreads increase when attacks are more frequent

suggests that there may also be a supply effect. If the number of terrorist attacks only

entered into the demand function (through altruism), one would only expect to see yields

25 As noted earlier, yield data is only available from 2001-2004. Since yields only change monthly in thisperiod, the number of observations available is small. As a result, it will be difficult to be statisticallyconclusive about changes in yields.

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fall when attacks are greater. In the next section, I will show that even though spreads

may increase with greater attacks, they do not move enough to fully account for all of the

variation I find in quantities.

Yields in equilibrium are explained very well by movements in the U.S. treasury

rate and the Israeli risk premium. Depending on the instrument, 95% - 98% of the

variation in yields can be explained by these variables. If yields could be explained

perfectly by the U.S. rate and risk premium, it would imply that the Ministry of Finance

sets yields exogenously as a constant spread over these rates. While this is obviously not

the case here, the fact that yields are explained very well by these rates means that this is

close to what happens.

Notably, yields in equilibrium move very strongly with the U.S. treasury rates, but

less so with the Israeli risk premium. Yields for the Jubilee 5-year increase by 0.70 for

every percentage point increase in the comparable U.S. treasury rate, while the Jubilee

10-year yield increases by 0.73 and the Zero Coupon yield increases by 0.68. Figures 5

and 6 show the close co-movement of these rates. Furthermore, the yield increases by

0.03 per percentage point of risk premium for the Zero Coupon and Jubilee 10-year, but

varies statistically insignificantly for the Jubilee 5-year. These findings suggest two

interesting results. Firstly, investors care more about the nominal yield on the bond than

the yield relative to alternative investments. Secondly, investors discount the importance

of the risk premium relative to U.S. treasuries. Assuming that the Ministry of Finance

demands the rational spread, supply can be denoted linearly as:

Yield U.S. Rate Risk Premium = a + b * Qs

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If investors demand a spread that weights the U.S. rate and risk premium separately (by

factors of and ), demand can be denoted:

Qd = c + d * [Yield * (U.S. Rate + * Risk Premium)]

In equilibrium, one would expect that:

dYield/dUS = (1-bd) / (1-bd)

dYield/dRisk = (1-bd) / (1-bd)

Therefore, the finding that dYield/dUS < 1 implies that < 1. In other words, investors

discount the opportunity cost component of the spread relative to the nominal rate.

Similarly, finding that dYield/dUS > dYield/dRisk implies that < 1, or that investors

discount the component of the return they demand from the risk premium relative to U.S.

treasuries. If investors weighted the components of the spread in the same way that the

Bank did, we would observe = = 1 and the nominal yield would move 1 to 1 with the

risk premium and U.S. treasury rate in equilibrium. Additionally, it makes intuitive sense

that the instrument held most by the smallest investors, the Zero Coupon bond, is the one

that puts the most undue emphasis on the nominal yield (i.e. has the lowest estimate of

the movement of yields relative to U.S. treasuries).

While the measure used for the risk premium here is imperfect (i.e. is at the 1-

year horizon and includes expected inflation and an inflation risk premium), it seems

reasonable to assume the inflation is random noise (which should not bias the coefficient

estimate). Furthermore, if anything, using a risk premium on the 1-year horizon should

underestimate the risk premium investors would demand at the 5 or 10-year horizon. The

reason for this is that the chances of defaulting over a longer period should be higher than

the chances of defaulting over a short period. Consequently, one would expect a greater

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than 1 to 1 movement with a 1-year risk premium in this specification. This interesting

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