TITLE: DEMAND FOR MONEY: DOES ECONOMIC UNCERTAINTY MATTER

Abstract

A well organize monetary policy depends on the ability of the economy to make out a stable demand for money. Therefore, the stability of the money demand function is a necessary stance to address the efficiency of the monetary policy strategy of the central bank. The purpose of this research is to investigate the relationship between the stability of money demand with the economic uncertainty index. In doing so, this study postulates that the optimal economic uncertainty index can serve as a predictive content for money demand. Therefore, monetary targeting can serve as an important monetary policy strategy as the uncertainty in the money demand can be pinpointed by using the optimal economic uncertainty index. This study extends the Keynes’s money demand function by including the optimal economic uncertainty index proposed by Gan (2014).

CHAPTER 1

INTRODUCTION

‘No proposition in macroeconomics has received more attention than that there exists, at the level of the aggregate economy, a stable demand for money function.’

Laidler, D. (1982, pg. 39) 1.1 Introduction

A well organize monetary policy depends on the ability of the economy to make out a stable demand for money (Friedman and Schwartz, 1982; Laidler, 1982; Bahmani-Oskooee and Karacal, 2006; Ozturk and Acaravci, 2008). Sriram (1999) and Bathalomew and Kargbo (2009) declare that a stable demand for money enables the monetary aggregates to have a predictable impact on the economic variables such as output, interest rate and inflation rate. Therefore, the stability of the money demand function is a necessary stance to address the efficiency of the monetary policy strategy (i.e., monetary targeting and inflation targeting) of the central bank. In line with this stance, numerous countries used to conduct monetary policies to target certain key policy variables.

Monetary targeting had been a famous monetary policy strategy adopted by several developed countries, namely Canada, Germany, Japan, Switzerland, United Kingdom and United States.1 Other developing countries that adopted this strategy include Korea,

1 Evidence is also obtainable from the central bank’s website. Among others, evidence of monetary targeting is reported by (1) Canada—Freedman (2000), (2) Germany—Issing (2005), (3) Japan—Werner (2002), (4) Switzerland—Mishkin (2000), (5) United Kingdom—Nelson (2001) and (6) United States—Browne (2001).

Indonesia, Malaysia and Thailand.2 However, the failure of the growth of money to serve as a predictive content has caused many countries shifted to other monetary policy strategies (e.g., inflation targeting, exchange rate targeting and interest rate targeting). Unfortunately, the newest strategies adopted by the policy makers of these countries still cannot promote foreseeable economic outcomes. Even though the growth of money is ineffective in the short-run business cycles, but it may be useful to manage inflation (Dwyer, 2001). Therefore, a question raises that whether the growth of money still plays an important role.

The demand for money may influence by the economic uncertainty (i.e., inflation uncertainty, output uncertainty, exchange rate uncertainty and interest rate uncertainty). Economic uncertainty refers to the situation where a little or unknown able future economic events (Bloom et al., 2013). The first innovative work which discussed the effects of uncertainty is done by Knight (1921). The economic uncertainty has increase greatly after the eruption of the subprime crisis in early 2007. Following the global financial crisis in 2008 that caused by the systemic financial risk, the world’s economic recovery is in a slowing pace (Gan, 2014). Thereafter, the world economic uncertainties continue to grow, such as the occurrence of the European sovereign debt crisis since 2009 that prolonged a severe recession, the uncertain ‘Abenomic’ policy in projecting Japan’s longer-term economic growth that kindled a more volatile financial environment, sub-par economic growth in the United States and a slackening growth in emerging Asia (International Monetary Fund, 2013).

Atta-Mensah (2004) and Tödter and Manzke (2007) explains that the economic agents could shift out their nominal assets, including money, into tangible assets such as gold or commodities when the inflation uncertainty increase as the inflation uncertainty may cause the nominal asset become riskier and less predictable. Golob (1994) states that the economy may influences by the inflation uncertainty via the increasing long term interest rates and thus may affect the economic decision makes by the businesses and consumers. The businesses may reduce their investment in the factories and equipment while the consumers may decrease their investment in housing and other durable properties. Choi and Oh (2003) argues that output uncertainty may also affect the demand for money as the demand for money may increase resulting from the substitution effect, when the output uncertainty increased. Bahmani-Oskoee et al. (2012) explain that individual may prefer to substitute less volatile assets, such as real assets for cash when output uncertainty increase. In line with this findings, Bahmani-Oskooee et al. (2013) suggest that the monetary targeting may plays an important role under significant output uncertainty when the demand for money is stable.

On the other hand, Harvey (2012) states that the exchange rate uncertainty may encourage the economic agents to invest in the riskier currency than compared to the secured assets. Pozo and Wheeler (2000) state that the economic agents may prefer to hold more foreign currency compared to the domestic currency when the exchange rate

2 Evidence is also obtainable from the central bank’s website. Among others, evidence of monetary targeting is reported by (1) Korea—Kim and Park (2006), (2) Indonesia—Inoue et al. (2012), (3) Malaysia—Leong et al. (2008) and (4) Thailand—Charoenseang and Manakit (2007).

uncertainty increase. Erdal (2001) claims that the real exchange rate uncertainty affects the domestic and decisions on foreign investment negatively as the real exchange rate uncertainty may cause reallocation of resources among sectors and countries and creates uncertain environment for investment decisions. Chuderewicz (2002) argues that the interest rate uncertainty may also influence the demand for money as economic agents may prefer more liquid assets when interest rate uncertainty increased. Turnovsky (1971) states that increase in interest rate uncertainty may increase the cash balances. Poole (2005) documented that the increasing uncertainty on how the central bank set the interest rate in the future may cause negative effects to the economic stability. Although the economic uncertainty may influence the money demand, the literature which discussed regarding the money demand and economic uncertainty are limited as research in this field is still new (Özdemir and Saygili, 2013).

1.2 Matters of Study

The matter considered in the study of money demand is the economic uncertainty3 matter. The scale variable is a measurement of transactions which relates to the economic activity (i.e., income) while the opportunity cost of holding money is the difference between the rate of return on assets against the money and the own-rate of money. The opportunity cost of holding money is generally represented by the interest rate (Özdemir and Saygili, 2013). (Note that only the matters for chosen determinants which are relevance to the interest of this study are discussed in the following section.)

1.2.1 Economic Uncertainty Matter

Economic uncertainty may influence the demand for the money by affecting the willingness of the individual to hold the money. When uncertainty increased, the risk may increase too. However, the discussion on the role of economic uncertainty in the literature on money demand is mixed and not comprehensive. For example, Bruggerman et al. (2003) find no evidence to prove that there is any relationship between money demand and economic uncertainty. However, Atta-Mensah (2004) shows that the economic uncertainty may lead to a higher M1 that agents willing to hold but the economic uncertainty affects M2 negatively. Bahmani-Oskooee and Xi (2011) find that the measurement of uncertainty does affect the demand for M3 in both the long and short run. However, Bahmani-Oskooee et al. (2012) argues that the measure of uncertainty only affect the money demand in the short-run but not in the long-run.

Other than economic uncertainty per se, the uncertainty on macro variables and policy variables may affect the demand for money, namely exchange rate uncertainty, interest rate uncertainty, inflation uncertainty and output uncertainty. With respect to the uncertainty on policy variables, Pozo and Wheeler (2000) find that the Singapore’s money demand is affected by the fluctuations in the exchange rate uncertainty. Exchange 3 The uncertainty of the economic conditions will be measured by the economic uncertainty index. There are few researchers who have developed their own economic uncertainty index such as Atta-Mensah (2004), Baker et. al (2013) and Gan (2013). However, the research in this study is restricted to Gan’s approach because Gan (2013) has constructed an optimal economic uncertainty index.

rate uncertainty may cause the demand for domestic currency to decrease and increase in the demand for foreign currency in Singapore but not for Malaysia and Thailand (Harvey, 2012). Baum et al. (2001) and Azid et al. (2005) suggest that the estimation on overall impact of the exchange rate uncertainty on the volatility of stock returns may lead to improper implications regarding the underlying relationships. Ozturk (2006) reviews that the profit and the benefits of the international trade are associated negatively with the exchange rate uncertainty. Grydaki and Fountas (2009) argues that the uncertainty in the money supply influence the exchange rate uncertainty positively. Bahmani and Bahmani-Oskooee (2012) say that the volatility of the exchange rate may affect the money demand directly as the exchange rate volatility creates uncertainty in the wealth.

The interest rate uncertainty, on the other hand, Turnovsky (1971) declares that the interest rate instability must be included in the money demand functions as the explanatory variables. Mason (1977) postulates that the demand for money is positively associated with the interest rate uncertainty as the interest-bearing assets are less desirable when interest rate uncertainty increase. Golob (1994) argues that interest rate uncertainty may lead the economic agents to postpone their decisions on investment and the economic agents might prefer to invest in long-term fixed rate debt (i.e., to evade the increasing short-term interest rates) when the interest rates uncertainty increased. Thus, the money demand decreased when the interest rate uncertainty increased. Chuderewicz (2002) claims that the interest rate uncertainty may embody useful and predictive information over to forecast the money. Dixit (1992) and Chang and Feunou (2013) highlight that the economy may influenced negatively by the interest rate uncertainty as the interest rate uncertainty may cause the firms to delay their investment decision.

With respect to the uncertainty on macro variables, Atta-Mensah (2004) suggests that the inflation uncertainty may cause nominal assets become riskier and unpredictable; thus, it may induce the investors to transfer the nominal assets including money into other tangible assets such as gold or other commodities. Belke and Polleit (2009) argue that the individuals may not hold money if the future is uncertain. Higgins and Majin (2009) find mixed effect of the inflation uncertainty on the money demand. The study reports that the inflation uncertainty have a negative effect on demand for M1 while have a positive effect on demand for M2. However, Klein (1977) find that the inflation uncertainty affects the money demand positively; where individuals request for more money when inflation uncertainty increased. Next, Mizrach and Santomero (1990) and Asilis et al. (1993) argue that the inflation uncertainty may relate with the money demand negatively.

The output uncertainty, on the other hand, Choi and Oh (2003) prove that the output uncertainty has a positive significant relationship with money demand but the money demand relates negatively with the uncertainty of money growth. Longworth (2004) states that the central bank of Canada includes numerous different and relevant variables to reduce the uncertainty regarding the output gap estimation. Price (1995) who used the conditional variance of GDP as a proxy of uncertainty proved that the uncertainty is associated negatively with the investment decision by the investors. Coenen et al. (2001) find that money still plays an important role in reducing the uncertainty in estimating the output. Jongwanich and Kohpaiboon (2008) explain that the uncertain economic (e.g.

output uncertainty) creates higher opportunity cost in delaying the investment and thus the investment from the firm may decrease. This may eventually reduce the money demand. Dahmardeh et al. (2011) indicates that the economic uncertainty which measured by the volatility of GDP has a negative relationship with the demand for money in Iran.

1.3 Motivation of the Study

There are two motivations in this study. The details of each motivation are presented at below.

1.3.1 Is the monetary aggregates4 cannot serve as an important predictive content for the monetary policy strategy?

The growth of money is sensible as a part of the eclectic modeling forecasting framework adopted by the U.S. central bank as the growth of money still contain essential information about the future economy development (e.g., CPI and output) (Bernanke, 2006). However, literatures find that the growth of money fails to serve as a predictive content for the future economic development; the relationship between the growth of money and the variables such as inflation and output are unstable at times. Baba et al. (1992) and Choi and Oh (2003) state that the role of monetary aggregates in the monetary policy have been reduced regarding the uncertainty in the velocity of M1, which cannot be clarified by standard money demand models. Friedman and Schwartz (1963) state that the instability of the money supply is one of the factors which caused the Great Depression. Meyer (2001) argues that money does not have any role in today’s consensus macro model and thus money plays no role in the monetary policy. Undoubtedly, most of the central banks have change their policy from money supply targeting that focused on the monetary aggregate as intermediate target to inflation targeting as the central banks may regulate the interest rates to stabilize the prices based on the prediction of inflation (Baxa et al., 2010; Jahan, 2012; Lungu et al., 2012). On the other hand, there are countries changed their policy into other monetary policy strategies (e.g. exchange rate targeting and interest rate targeting). 5 Therefore, the question remains whether or not the monetary aggregates can serve as the predictive content for the monetary policy strategy.

1.3.2 What is the response of economic uncertainty to money demand?

Atta-Mensah (2004) and Jackman (2010) find that economic uncertainty may influence the economic agent’s decision on the quantity of money to hold. Bahmani-Oskooee and Karacal (2006) and Opolot (2007) argue that the instability relationship between money demand function and macro-variables can make policy formulation and predictions difficult. Greiber and Lemke (2005) suggest that the measurements of uncertainty must be included in the specifications of money demand because the variables of uncertainty 4 In this study, the demand for money will used to represent monetary aggregates as a predictive content for the monetary policy strategy. 5 The evidence of countries that pursue different monetary policy strategies are reported by (1) Hong Kong—McCallum (2007), (2) Singapore—Parrado (2004) and (3) Malaysia—Poon and Tong (2009).

may improve the explanatory power of the estimated money demand function for euro area M3. The uncertainty in the economics definitely will alter the directions of the future economics. Thus, it is important to identify the uncertainty in an economic as the modern economics still does not do well in predicting the uncertainty of the world. As stressed by Bernanke (2010), researchers should put more effort to construct useful framework to overcome the economic uncertainties as the current framework still cannot implies meaningful outcomes. Consequently, this study will apply the optimal economic uncertainty index proposed by Gan (2014) to investigate the relationship between the economic uncertainty and demand for money.

1.4 Objectives

The objectives of this research will be divided into two parts which is general objectives and specific objectives.

1.4.1 General Objective

The general objective of this research is to investigate the relationship between the stability of money demand with the economic uncertainty index. In this thesis, the uncertain economic conditions will be determined by using the optimal economic uncertainty index proposed by Gan (2014). By identifying the economic uncertainty using the optimal economic uncertainty index, the central banks can achieve their ultimate goals such as maintaining low inflation and increasing economic growth by controlling the money supply in an economy.

1.4.2 Specific Objectives

The 6 selected developed countries namely Australia, Canada, Japan, New Zealand, Switzerland and United States, and 12 selected developing countries, namely Brazil, China, Colombia, India, Indonesia, Malaysia, Mexico, Republic of Korea, Singapore, South Africa, Thailand and Turkey are taken up in this study. Below are the specific objectives of this research.

1. To investigate the relationship between the economic uncertainty index and the demand for money.

This study postulates that the optimal economic uncertainty index can serve as a predictive content for money demand; the optimal economic uncertainty index is created based on the simple macroeconomic model.

1.5 Significance of the Study

Besides that, this study is significance because it may help the policy makers in making decisions for the monetary policy under the uncertain economic conditions. By using the optimal economic uncertainty index, the policy makers may pinpoint the uncertainties in the economy. Thus, this study may serve as a guideline for the monetary authorities to improve the country’s economy by controlling the money supply as the optimal economic uncertainty index can estimate the uncertain economic conditions. The optimal economic uncertainty index can portrays the uncertainty level of macroeconomic conditions (Gan, 2014).

1.6 Framework of the Study

The framework of this study includes the money view (Hubbard, 1995) and modified money view: economic uncertainty. The framework below assumes that the money demand and the money supply are in an equilibrium level.

1.6.1 Standard Money View

Based on the Keynesian model, the money view indicates the effects of the monetary aggregate on output through interest rate. The transmission mechanism can be explained by the diagram below:

The diagram above shows that a tighten monetary policy (M) may cause the interest rate (r) to increase, which increase the opportunity cost of holding money and thus causing the investment (I) to decrease. When investment decrease, the aggregate demand may decrease and hence decrease the output ( y). The decreasing output also implies that the inflation (π) is decreasing.

1.6.1.1 Modified Money View: Economic Uncertainty

This modified money view below is an extension form the standard money view. The transmission mechanism can be explained by the diagram below:

y (π ↓)

I ↓r ↑M ↓

Economic Outcomes (i.e.

macro variables and policy variables)

Uncertainty inr ,

and yM uncertaintyEU

The diagram above shows that the economic uncertainty (EU) may cause uncertainty in monetary policy used by the central bank and thus cause uncertainty in the interest rate and output. Further, these uncertainties may influence the economic outcomes as the final decision of the macro variables (e.g., output) and policy variables (e.g., interest rate) are unknown. Golob (1994) states that the uncertainty in the interest rates and other economic variables can affect the economic activity negatively; uncertainty may delay investment decisions by the investors. Therefore, it is necessary to solve the economic uncertainty by using the optimal economic uncertainty index. The optimal economic uncertainty index which based on Gan’s approach (2014) may discard the continuous effects of economic uncertainty on the monetary policy and economic outcomes.

1.7 Conclusion

In conclusion, the present chapter has discussed the background, matters and motivation of this study. The remainder of the study will be organized as follows. Chapter 2 will discuss the theoretical background of the demand for money and the empirical literature of the demand for money will be discuss based on the matter presented in this chapter. Next, the discussion regarding the methodology and data used in this study is included in Chapter 3.

CHAPTER 2

LITERATURE REVIEW

2.1 Introduction

This chapter will discuss the past literature which related to this study. This chapter is divided into the theoretical literature and empirical literature.

2.2 Theoretical Literature

The theoretical literature that discussed in this section is the Quantity Theory, the Cambridge approach to Quantity Theory, Keynesian Theory and Friedman Theory of Demand for Money. Although this section discusses variety theoretical literature of money demand, this study will only apply the Keynesian liquidity preference theory.

2.2.1 Keynesian Money Demand

The standard money demand function developed by Keynes’s (1936) is as follows:

M td=f ( y t , rt ) (2.1 )

where M td is the demand for real money balances (i.e., the nominal value of demand for

money is divided by the price level) depends on the level of transactions in the economy (y t -- real income) and the opportunity cost of holding money (rt -- interest rate). Keynesian approach denotes that the demand for money is related positively with real income but related negatively with the interest rate.

Furthermore, Keynes (1936) postulates that the individual holds the money for three main reasons which is the transactions motive, precautionary motive and the speculative motive. The motives of holding the money as stated by Keynes are discussed in detail in the following section.

2.2.1.1 Transactions Motive

Keynes assumed that the first motive of holding the money is the transactions. This is because the money is defined as the medium of exchange where the individual holds the money for daily transactions. Money bridges the gap between the receipt of income and eventual expenditures. The amount of money hold for the transactions purpose would vary positively with the volume of transactions in which the individual engaged. Income is assumed to be a measurement of the volume of transaction. Therefore, the transactions motive of the money demand is predicted to positively relate to the level of income. The relationship between the transactions and the level of income can be portrays in Figure 2.1 shown below.

Figure 2.1 The relationship between the transactions and level of income

2.2.1.2 Precautionary Motive

Keynes believed that, beyond the money held for planned transactions, additional money balances were held in case unexpected expenditures became necessary. For the precautionary motives, the money will be hold for emergencies such as to pay unexpected bills (i.e. medical bills and others). Keynes added the amount of money which hold by the individual are positively related with the income. When the income increase, the money hold by the individual for precautionary will increase too. In addition, the interest rate will also be a factor when individuals tended to economize on the amount of money held for the precautionary motive as interest rate rose. This is because the motives to hold money for precautionary balances are similar with the motive of transactions demand. The relationship between the precautionary and the level of income can be portrays in Figure 2.2 shown below.

Figure 2.2 The relationship between the precautionary motive and level of income

c (y)

0 Level of income, y

No. of transactions, c

p (y)

0 Level of income, y

Precautionary motive, p

2.2.1.3 Speculative Motive

The third motive to hold money postulates by Keynes is speculative motive (i.e., as a store of wealth). Keynes assumed that the households may buy bonds as a speculative motive; households may use the money to purchase bonds and may sell it in the future to earn money. The value of bonds and money depends on interest rates. Therefore, the uncertainty in the interest rates may eventually affect the quantity money demand from the households. The investors may expect that the interest rates will rise in the future during low interest rates and thus the bond prices are expected to fall. This implies that the household will prefer to hold money compared to buy bonds during low interest rate and thus the quantity of money demand increased; the opportunity cost of holding money increased when the interest rate increased. Figure 2.3 below portrays the negative relationship between the interest rates and quantity of money demanded.

Figure2.3 The relationship between interest rates and quantity of money demanded

2.2.1.4 Combining the Three Motives Together

In short, the motives of holding money as stated by Keynes, namely the liquidity preference function can be expressed as the total money demand function as follows:

M d=L1 ( y )+L2 (i )(2.2)M=M 1+M 2=L1 ( y )+L2 (r )=L ( y ,r )(2.3)

Where L1 denotes the motive of transaction and precautionary while L2 denotes the motive of speculative of liquidity preference. y represents income and i represents the interest rate.

2.2.2 Quantity Theory

The level of aggregate demand determines the quantity of money in the classical theory, which in turn will affect the price level. The starting point of the classical quantity theory of money is the equation of exchange which created by the most prominent American quantity theorist, Irving Fisher (1911). He added that the total of expenditures is always

0 Quantity of money demand, M

Interest rates, i

equals to the total income in a transaction. Thus, he has created an equation of exchange as follows:

MV T=PT T (2.4 )

Where M represents the quantity of money, V T denotes the velocity of the circulation of money, PT is the price level for the items which been traded and T represents the volume of transactions. Fisher regard M is the composition of cash and demand deposits. Therefore,

M=M 1+M 2 (2.5 )V=V 1+V 2 (2.6 )

Fisher stated that among the four variables (M , V T , PT and T ), T and V is relatively stable and constant. This is because the development of an economy does not depend on the quantity of money but it is affected by the natural resources and the technical conditions. However, M and P are unstable variables because M can be controlled by the monetary authorities. When T and V are relatively constant, M will influenced T and P. In addition, the price level will change in the amount of the velocity of circulation money with proportional change when the velocity of circulation money and the volume of transaction are in the same conditions. Thus, the price level will determine by the quantity of money rather than price level determines the quantity of money.

2.2.3 The Cambridge Approach to the Quantity Theory

The Cambridge Approach to the Quantity Theory is developed by Marshall. He stated that individuals will save their property and income in form of money as the reserve purchasing power of people willing to maintain. He also stressed the influence of the time and quantity of money hold by individuals to the velocity of money and thus the impact of money value. Pigou (1917) has constructed a cash balance formula which named the Cambridge equation as follows:

M=kPT (2.7)

Where M denotes the stock of money, k represents the fraction of income which the community seeks to hold in the form of cash balance and demand deposits, P is the general price level and T represents the total output.

2.2.4 Friedman Theory of Demand for Money

Milton Friedman (1956) has introduced his theory of demand for money in his famous article named ‘The Quantity Theory of Money: A Restatement’. The demand for money developed by Friedman is almost similar with the analysis of demand money as introduced by Keynes and Cambridge compared to Fisher’s. Friedman equals the factors

which influence the demand for any asset with the factors that affect the demand for money. Therefore, Friedman applied the theory of asset demand to the money.

The demand for money is a function of the resources available to individuals and expected returns on the other assets relative to the expected return on money. Thus, Friedman has constructed his own model of the demand for money as follows:

M d

P=f (Y p ,rb , rm , re , πe ,w ,u )(2.8)

OrM d

P=f (Y p ,rb−rm , re−rm , π e−rm )(2.9)

Where M d

P denotes the demand for real money balances, Y p is the permanent income, rm

represents the expected return on money, rb is the expected return on bonds, re denotes the expected return on equity (common stock), πe is the expected inflation rate, w represents the proportion of human wealth and non-human wealth and u denotes the other factor which may affect the demand for money.

In the function of Friedman’s money demand, rb−rm and re−r m represents the expected return on bonds and the equity relative to the money. When the expected return on bonds and equity relative to money increased, the relative expected return on money will decrease and thus, this will cause the demand for money to decrease. Furthermore, πe−rm denotes the expected return on goods relative to the money. When it increased, the expected return on goods relative to money increased, and therefore the demand for money decreased.

2.3 Empirical Literature

In this section, the empirical literature regarding the economic uncertainty will be discussed.

2.3.1.5 Economic Uncertainty

There are varieties of study that investigates about the uncertainty. For instance, the investment uncertainty and others are the study usually done by the researcher. Based on the previous study, results shows that most of the theoretical and empirical literature about investment under uncertainty stated that uncertainty would bring negative impact to the country’s economic growth and investment (Lensink, 2001). Bernanke (1983) also clarified that uncertainty might delay the investment.

In 2001, Lensink had carried out a research where the concept of the study is same with this study which is create a model to find the effects of the policy uncertainty to the country’s economic growth. The method used by Lensink is a standard cross-country

growth regression. Next, Baker, Bloom and Davis (2011) had construct an index from three types of underlying components which include news coverage about policy-related economic uncertainty, tax code expiration data and economic forecaster disagreement to measure the policy-related economic uncertainty.

Review to the past literature, there are researcher done research related to the uncertainty index. For example, Atta-Mensah (2004) tested the effect of economic uncertainty on the demand of money for Canadian monetary aggregates (M1, M1++ and M2++) by using a general-equilibrium theory. The economic uncertainty index (EUI) is introduced in the research and it is estimated by using GARCH models. Quarterly data from 1960 until 2003 is used in this research. The findings of the result stated that economic agents will keep the money for precautionary reasons when economic uncertainty increased and this may cause the M1 balances to increase too. Moreover, the result also supports the view that the agents will not willing to invest in a risky asset in a general economic uncertainty. The empirical results of the study also found that the raise of economic uncertainty will increased the desired M1 and M1++ balances that the agents would like to hold but the economic uncertainty have negative effect on M2++.

Next, Baker et al. (2013) also have constructed a new index of economic policy uncertainty (EPU) in their research. Three components which include the frequency of news media references to economic policy uncertainty, the number of federal tax code provisions set to expire and the extent of forecaster disagreement over future inflation and government purchases were used to form the EPU. The EPU appears to propose a good proxy for real policy-related economic uncertainty which based on the 5,000 human audited news articles and external surveys such as the frequency of the word ‘uncertainty’ that appear in the FOMC Beige Book and the number of policy related jumps in the stock-market. VAR analysis is used in this research to find the role of the new policy-related uncertainty to the employment and GDP. The result of the study indicates that the policy-related uncertainty is useful in the slow growth and irregular recovery of recent years.

Furthermore, Gan (2014) has constructed an optimal economic uncertainty index in a simple macroeconomic model by using grid search method which can serve as a policy tool for central bank to reduce the uncertainty in macroeconomic conditions. Three developed countries namely Canada, Japan and United States and four developing countries namely Indonesia, Malaysia, Singapore and Thailand are examined in the research. The research concludes that the optimal economic uncertainty index fulfills its role as (i) a good information summary tool to characterize the uncertainty level of macroeconomic conditions and (ii) a guiding policy tool for improving uncertainty levels in macroeconomic conditions. Moreover, the estimated response function of the optimal economic uncertainty index recommends that the exchange rate, inflation, interest rate and output can be used as indicators to help the central banks in making decision while the optimal economic uncertainty index helps to predict the uncertain economic conditions.

On the other hand, Cronin and Kennedy (2007) have investigated the interrelationship between the real growth of money and measures of macroeconomic and the uncertain monetary in United States by utilizing the multivariate GARCH model. The model estimated the uncertainty by using the conditional variance of the data series, to test the impact of the macroeconomic uncertainty and the monetary uncertainty Granger-cause on the real money. The findings of the result shows that the macroeconomic uncertainty are positively related with the US real M2 growth at longer lag lengths so that a rise in macroeconomic uncertainty will cause an increase in real money growth over a one to two year horizon. In contrast, monetary uncertainty has no discernable causal effect on real money growth at all lag lengths examined. Moreover, the result also shows that in a short horizon, the changes of the real money will influenced the monetary uncertainty positively.

Besides that, Ozdermir and Saygili (2013) have analyzed the parameter constancy of the long-run money demand function in Turkey. The methodology used in the study is the cointegrated VAR and quarterly data from 1992 quarter one to 2008 quarter three is collected. The result shows that a suitable measurement of uncertainty is required to estimate a stable and consistent function of money demand for Turkey. Next, Jackman (2010) has examined the relationship between the economic uncertainty and the money demand in Barbados by using the unrestricted error correction model developed by Pesaran et al. (2001). The result shows that the effects of economic uncertainty on money demand are different in the short term and long term. In short term, the increasing economic uncertainty will encourage the money demand. However, in long period of uncertain economic conditions, the nominal assets become less attractive regarding the increasing risk in the nominal assets and thus caused the money demand to decrease.

CHAPTER 3

METHODOLOGY

3.1 Introduction

In this chapter, this thesis begins the discussion with the model apply in this study. The model build in this thesis is based on the objectives discussed in Chapter One.

3.2 Model specification

The Keynes’s standard money demand function (i.e., the liquidity preference function) is applied in this study. The inputs can be presented as follows:

M td=f ( y t , rt ) (3.1 )

where M td is the demand for real money balances (i.e., the nominal value of demand for

money is divided by the price level) depends on the level of transactions in the economy (y t -- real income) and the opportunity cost of holding money (rt -- interest rate) (see Choudhry, 1995). Keynesian approach denotes that the demand for money is related positively with real income but related negatively with the interest rate.

In line with the aims of the study, Equation 3.1 is extended to encompass the optimal economic uncertainty index. The inclusion of the optimal economic uncertainty index in the money demand function is constructed based on the approach proposed by Gan (2014); since the economic uncertainty index is not available in the reality, thus, on can use Gan’s optimal procedure to develop the index. Therefore, the modified money demand function that will be taken up in this study can be written as follows:

M td=f ( y t , rt ,U t ) (3.2 )

The specific form of the money demand function is as below:

M td=β0+ β1 y t+β2 rt+β3U t+ε t(3.3)

Note: β0 is a constant.β1 to β5 are the coefficient for each variable.

The economic rationale suggests that β1>0 while β2<0 and β3<0.where M t

d is the real money demand (M1 or M2), y t represents real output, rt denotes the real interest rate and U is the economic uncertainty index. ε t represents the shocks; all

variables are in log form, except r. Equation 3.3 also known as Goldfeld-type (1973) money demand function.

Based on the model above, the money demand depends positively on the output. An increase in output typically results in an increase in transactions. When the transactions increase, thus, the money demand may increase too. The increasing output may invite inflation. When inflation increase, the money demand may decrease as the money become less desirable; the inflation may reduce the real value of the money.

On the other hand, an increase in interest rates reduces the money demand as the opportunity cost of holding money increased. The investment may decrease when the opportunity cost of holding money increased and this eventually reduce the money demand. Besides that, the economic uncertainty also affects the money demand. The positive economic uncertainty may increase the money demand. For example, an increase in the expected output leads to increase the transactions and thus increase the money demand. Furthermore, the interest rates uncertainty has a negative relationship with the money demand. When the interest rates uncertainty is expected to increase, the economic agents may delay their investment and thus reduce the money demand (Golob, 1994).

3.3 Empirical Methods

This section explains the methods that are applied in estimating the money demand function, namely panel unit root and the panel autoregressive distributed lag (ARDL) developed by Pesaran et al. (1997, 1999). The section also discusses the model of the optimal economic uncertainty index at the end of this section since this study include the optimal economic uncertainty index in the money demand function (see the box of Gan’s (2014) optimal economic uncertainty index procedure).

3.3.1 Panel Unit Root

In this study, the panel unit root test developed by Levin, Lin and Chu (2002), Im, Pesaran and Shin (2003) and Maddala and Wu (1999) are used to examine whether the variables are stationary or non-stationary. The data from different countries are stacked into variables before performing the panel unit root test. The variables are stationary if the variables are integrated of order zero, I(0) and the variables are non-stationary if the variables are integrated of one, I(1).

3.3.2 Panel Autoregressive Distributed Lag (ARDL)

The panel autoregressive distributed lag model (ARDL) is used to examine the short run and long run relationship between the money demand and the variables, namely real output, real interest rate and economic uncertainty index. The advantage of using ARDL approach is this approach allows the variables to be I(1) and I(0). The general panel ARDL model is as follows:

y t=φk xqt+μ t (3.4)k=1 ,…, K ;q=1 , …, n

Therefore, the empirical specification of the panel ARDL model as specified above in equation 3.4 is as follows:

M ¿=αi+∑j=1

p−1

δ̂ij ∆ Mi , t−j+∑

j=0

q−1

δ̂1 ij' ∆ y1i , t−j

+∑j=0

q−1

δ̂2 ij' ∆ r2i , t− j

+∑j=0

q−1

δ̂5 ij' ∆ U 5 i ,t− j

+ γ̂ i (M i , t−1−φ̂1 i y1 i , t−j

−φ̂2 ir 2i , t−j− φ̂5 iU 5i , t− j)+μ i+∈¿ (3.5)

Where M denotes the real money demand (i.e., M1 and M2), y is the real output, r represents the real interest rate and U is the economic uncertainty index. φ̂ i is the long run parameters while γ̂ i are the error correction coefficients.

Box: Gan’s (2014) Optimal Economic Uncertainty Index Procedure

The optimal measure of the economic uncertainty index is subjected to the central bank loss function. The general form of the economic uncertainty index can is defined as follows:

Minimize the loss function

Et∑τ=0

∞

β τ Lt+τ

subject to y it

=δ1 x1 , it+δ2 x2, it

+⋯+δ k−1 xk−1 ,it+ωit

, i=1 , …, N ; k=1 , …, K ;t=1 ,…, T . U t=α k y it

+ϖt(3.6)

where U is the economic uncertainty index. y is the dependent variable and x is the explanatory variable; these variables are in gap form at its equilibrium level (i.e., deviation of the actual value from the potential values). δ and α are coefficients. ω and ϖ are errors. L denotes the central bank loss function; it is assumed that the current policy focus on low and stable inflation.

a. Theoretical Model The optimal economic uncertainty index is constructed using the standard macroeconomic model. The inputs of the small structural model are as bellows:

y gt=∝1 y gt−1

−λ1 rgt −1−δ1 egt−1

+εt (3.7)πgt

=∝2 y gt−1+βπ 1

π gt−1−δ 2egt −1

+ηt (3.8)egt

=λ2 rgt+υt (3.9)

U t=∝3 y gt+βπ 2

π gt−δ 3e gt

−λ3 r gt+ϖt (3.10)

r gt=∝4 ygt −1

+βπ 3π gt−1

−δ 4 egt−1+U t−1+ζ t (3.11)

where y g is the real output gap, πg is the inflation gap, eg is the real exchange rate gap6, r g is the real interest rate gap, and U is the economic uncertainty index. The gap of the variables is the deviations of the actual value form the potential values. The total output of an economy (i.e., open economy IS curve) represented by equation 3.7. Equation 3.8 denotes the Phillips curve of an open economy while equation 3.9 is the reduced form of the exchange rate. The contemporaneous economic uncertainty function is represented by equation 3.10 and equation 3.11 is the monetary policy reaction function.

3.4 Data

The samples of this study are divided into two groups which is developed countries and developing countries. The selected countries are grouped according to the source from the United Nations (2012). Data from 6 developed countries (Australia, Canada, Japan, New Zealand, Switzerland and United States) are chosen as part of this study. While data from another 12 developing countries, namely Brazil, China, Colombia, India, Indonesia, Malaysia, Mexico, Republic of Korea, Singapore, South Africa, Thailand and Turkey are used as data from developing countries. The data are collected and analyzed according to the model created. The quarterly data from 1994 quarter one until 2012 quarter four are collected in this study. The proxy for the exchange rate is the real effective exchange rate index and the interest rate represents the monetary policy variable. The data of the Real Gross Domestic Product (RGDP) is obtained in this study to indicate the real national output or the real income. This paper uses data from a variety of sources, namely, the International Monetary Fund (IMF), International Financial Statistics (IFS), CD-ROM, Bank for International Settlements Statistics (BIS Statistics) and ECONSTATS. The features are as follows:

Real money stock: Data of M1 and M2 for each selected countries will be used in this study.

Consumer price index: The quarterly series of the Consumer Price Index (CPI) for each country is collected from IFS. The first difference of the log of the CPI level is been evaluate to determine the inflation rates.

Real exchange rate: The quarterly series of the Real Effective Exchange Rate (REER) with the index of 2010=100 is taken from BIS Statistics.

Real output: The quarterly series of the Nominal Gross Domestic Product (NGDP) is collected from the IFS. The real output (RGDP) is obtained by dividing the NGDP to the CPI.

Interest rate: The quarterly series of the money market rate is obtained from the IFS to serve as the interest rate.

Economic uncertainty index:

3.5 Conclusion

6 One may soften the economic policy to mitigate the negative level of the economic uncertainty index if the above process is the other way round.

This chapter has discussed the model and methodologies used in this study in detail in Section 3.2 and 3.3 respectively.

CHAPTER 4

CONCLUSION

4.1 Conclusion

1. This study anticipates that the economic uncertainty index has short run and long run relationship with the money demand function.

2. This study postulates that the optimal economic uncertainty index can serve as a predictive content for money demand.

3. Therefore, monetary targeting can serve as an important monetary policy strategy as the uncertainty in the money demand can be pinpointed by using the optimal economic uncertainty index.

4. First limitation of this study is this this study only include 20 countries and three variables in the money demand function, namely the real output, real interest rate and economic uncertainty index. Other variables such as the exchange rate and inflation can be included for future research.

5. Next, the estimation problem in measuring the optimal economic uncertainty index can be extended for future investigations.

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