demand function n india

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INSTITUTE OF DEVELOPING ECONOMIES

IDE Discussion Papers are preliminary materials circulatedto stimulate discussions and critical comments

Keywords : cointegration, DOLS, India, money demand JEL classification: E41, E52

* Institute of Developing Economies ([email protected]).** Faculty of Economics, Kobe University ([email protected]).

IDE DISCUSSION PAPER No. 166

An Empirical Analysis of the MoneyDemand Function in India

Takeshi INOUE * andShigeyuki HAMORI **

September 2008

Abstract This paper empirically analyzes Indias money demand function during the period of 1980 to

2007 using monthly data and the period of 1976 to 2007 using annual data. Cointegration test

results indicated that when money supply is represented by M1 and M2, a cointegrating vector is

detected among real money balances, interest rates, and output. In contrast, it was found that

when money supply is represented by M3, there is no long-run equilibrium relationship in the

money demand function. Moreover, when the money demand function was estimated using

dynamic OLS, the sign conditions of the coefficients of output and interest rates were found to be

consistent with theoretical rationale, and statistical significance was confirmed when moneysupply was represented by either M1 or M2. Consequently, though Indias central bank presently

uses M3 as an indicator of future price movements, it is thought appropriate to focus on M1 or

M2, rather than M3, in managing monetary policy.


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An Empirical Analysis of the Money Demand Function in India

Inoue Takeshi

(Institute of Developing Economies)

and

Shigeyuki Hamori

(Faculty of Economics, Kobe University)

Abstract

This paper empirically analyzes Indias money demand function during the period of 1980 to

2007 using monthly data and the period of 1976 to 2007 using annual data. Cointegration test

results indicated that when money supply is represented by M1 and M2, a cointegrating vector

is detected among real money balances, interest rates, and output. In contrast, it was found that

when money supply is represented by M3, there is no long-run equilibrium relationship in the

money demand function. Moreover, when the money demand function was estimated using

dynamic OLS, the sign conditions of the coefficients of output and interest rates were found to

be consistent with theoretical rationale, and statistical significance was confirmed when money

supply was represented by either M1 or M2. Consequently, though Indias central bank

presently uses M3 as an indicator of future price movements, it is thought appropriate to focus

on M1 or M2, rather than M3, in managing monetary policy.

JEL classification : E41; E52

Keywords : Cointegration; DOLS; India; Money Demand


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1. Introduction

In India, financial sector deregulation was undertaken beginning in the mid-1980s, when

steps like the introduction of 182-day Treasury bills, lifting of the call money interest-rateceiling, and the introduction of certificates of deposit and commercial paper were taken in a bid

to make the government securities market and the money market more efficient (Sen and Vaidya

1997 [18]). Furthermore, with the balance of payments crisis in 1991, there began an

intermittent series of more systematic financial sector reforms that continues even today. For

example, the reform of the Indian interest-rate structure, which had been strictly managed by the

Reserve Bank of India (RBI), began with the April 1992 deregulation of deposit rates and has

progressed to the point where commercial banks are now permitted to freely set term deposit

rates and lending rates for loans above Rs.2 lakh. 1 Moreover, the RBI, which had long been

constrained by the Indian government's fiscal management, entered into an agreement with the

government in September 1994 to limit the issuance of 91-day ad hoc Treasury bills, which

were used to finance fiscal deficits, and eventually eliminated these securities altogether in April

1997, greatly reining in the central bank's automatic monetization of fiscal deficits. 2

The above are just a few examples of how interest-rate structure deregulation and the

introduction of new financial products have progressed in India over the past 20 years.

Theoretical research and empirical analyses, using primarily data on developed countries, have

shown that the money demand function can become unstable as a result of such financial

innovations and financial sector reforms. Partly because of instability in the money demand

function, many central banks have in recent years switched from money supply targeting

focused on monetary aggregates as the intermediate target, to inflation targeting, which seeks to

stabilize prices by adjusting interest rates based on inflation forecasts. The RBI abandoned the

flexible monetary targeting approach in favor of the multiple indicator approach in April 1998,

putting an end to the use of money supply as the intermediate target, but retaining it as an

important indicator of future prices. Consequently, examining the characteristics of the money

demand function of India's financial sector, which has undergone significant change since the

1980s, should bear significant meaning for present and future considerations of the RBIs

monetary policy. This paper, therefore, uses annual data for the period of 1976 to 2007 and

monthly data for the period of January 1980 to December 2007 to estimate India's money

1 Except for bank savings deposits, non-resident deposits, loans for less than 200,000 rupees, andexport credit, interest rates have been greatly deregulated.2 Financial deregulation beginning in the 1990s also loosened requirements, like those requiringcommercial banks to keep central bank balances equal to a certain percentage of their own deposits

and purchase government bonds and government-specified bonds, and the deregulation relaxedbarriers to entering the banking sector and opened stock markets to foreign participants.


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demand function, which is derived from real money balances, interest rates, and output, and

shed light on its characteristics.

The next section of this paper consists of a review of relevant prior research and a discussion

of the unique contributions of this paper. In the third section, the models are presented and in thefourth section, variables are defined, sources are provided, and data characteristics are explained.

Moving into the fifth section, cointegration tests are performed using both monthly and annual

data, the long-term stability of the money demand function is examined, and dynamic OLS

(DOLS) is used to examine the sign conditions and significance of output and interest-rate

coefficients. Lastly, analysis results are used to discuss the characteristics of India's money

demand function and the implications for India's monetary policy.

2. Literature Review

India's money demand function has been the subject of numerous quantitative research efforts.

Among these was the first study to explicitly consider the stationarity of, and cointegration

relationships among, the variables of the money demand function. Moosa (1992) used three

types of money supply cash, M1, and M2 to perform cointegration tests on real money

balances, short-term interest rates, and industrial production over the period beginning with the

first quarter of 1972 and extending through the fourth quarter of 1990. Results indicated that for

all three types of money supply, the money balance had a cointegrating relationship with output

and interest rates. However, greater numbers of cointegrating vectors were detected for cash and

M1 than for M2, so Moosa (1992) states that narrower definitions of money supply are better

for pursuing monetary policy.

Bhattacharya (1995), like Moosa (1992), considered three types of money supply M1, M2,

and M3 and used annual data for the period of 1950 to 1980 to analyze India's money demand

function. Bhattacharya (1995) performed cointegration tests for real money balances, real GNP,

and long-term and short-term interest rates, detected a cointegrating relationship among

variables only when money supply was defined as M1, and clearly showed that long-term

interest rates are more sensitive to money demand than are short-term interest rates. In addition,

Bhattacharya (1995), after estimating an error correction model based on cointegration test

results, found that, in the case of M1, the error correction term is significant and negative, and

held that monetary policy is stable over the long term when money supply is narrowly defined.

Bahmani-Oskooee and Rehman (2005) analyzed the money demand functions for India and

six other Asian countries during the period beginning with the first quarter of 1972 and ending

with the fourth quarter of 2000. Using the ARDL approach described in Pesaran et al. (2001),


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they performed cointegration tests on real money supplies, industrial production, inflation rates,

and exchange rates (in terms of US dollar). For India, cointegrating relationships were detected

when money supply was defined as M1, but not M2, so they concluded that M1 is the

appropriate money supply definition to use in setting monetary policy.Contrasting with the above, there is also prior research that uses money supply defined

broadly in holding that India's money demand function is stable. In one example, Pradhan and

Subramanian (1997) employed cointegration tests, an error correction model, and annual data

for the period of 1960 to 1994 to detect relationships among real money balances, real GDP, and

nominal interest rates. They estimated an error correction model using M1 and M3 as money

supply definitions and found the error correction term to be significant and negative. Their

position, therefore, was that the money demand function is stable not only with M1 but also

with M3.

Das and Mandal (2000) considered only the M3 money supply in stating that India's money

demand function is stable. They used monthly data for the period of April 1981 to March 1998

to perform cointegration tests and detected cointegrating vectors among money balance,

industrial production, short-term interest rates, wholesale prices, share prices, and real effective

exchange rates. Their position, therefore, was that long-term money demand relevant to M3 is

stable. Similarly, Ramachandran (2004), too, considered only the M3 money supply in using

annual data for the period of 1951/52 to 2000/01 to perform cointegration tests on nominal

money supply, output, and price levels. Because stable relationships were discovered among

these three variables, Ramachandran (2004) states that, over the long term, it is possible to use

an increase in M3 as a latent indicator of future price movements.

As is the case with the studies referred to above, prior research in general states that India's

money demand function is stable. 3 Furthermore, studies performed using multiple money

supply definitions have tended to draw the conclusion that because India's money demand

function is more stable when money supply is defined narrowly, the central bank should adopt

cash or M1 as the narrow definition of money supply when determining monetary policy.

Contrasting with that position, however, other studies have concluded that the money demand

function is stable when money supply is broadly defined. Views on what definition of money

supply to use for monetary policy, therefore, differ.

This paper uses both monthly and annual data, considers three types of money supply M1,

M2, and M3, and comprehensively estimates India's money demand functions for each case. It

3 Nag and Upadhyay (1993), Parikh (1994), Rao and Shalabh (1995), Rao and Singh (2006), andothers as well have also performed quantitative analyses of Indias money demand function.


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also discusses the implications of empirical results for the RBIs monetary policy formation. In

contrast with prior studies, this paper, after performing cointegration tests on money supply,

output, and interest rates as money demand function variables, applies DOLS and sheds light on

the characteristics of India's money demand function through examinations of the signconditions and statistical significance of variable coefficients.

3. Models

There are various theories concerning the money demand function. For example, Kimbrough

(1986a, 1986b) and Faig (1988) came up with the following money demand function as a result

of explicitly considering transaction costs.

( , )t t t t

M L Y R

P = 0Y L > , 0R L < (1)

In this formula, t M represents nominal money supply for period t ; t P represents the price

index for period t ; t Y represents output for period t ; and t R represents the nominal

interest rate for period t . Increases in output bring increases in money demand, and increases

in interest rates bring decreases in money demand.

We use two models corresponding to equation (1) in order to conduct an empirical analysis.

Model 1: 0 1 2ln( ) ln( ) ln( )t t t t t M P Y R u = + + + , 1 20, 0 > < (2)

Model 2: 0 1 2ln( ) ln( ) ln( ) ln( )t t t t t M P Y R u = + + + , 1 20, 0 > < (3)

Both Models (2) and (3) are log linear models, but Model (2) uses the level of interest rates and

Model (3) uses the logarithm value of interest rates.

4. Data

This paper uses both monthly data and annual data for empirical analysis. For monthly data,

we use data over the period of January 1980 to December 2007. The data source for the

industrial production index (seasonally adjusted by X12) and the wholesale price index is IMF

(2008). We obtained M1, M2, and M3 from various issues of the RBI Bulletin. We deflate these

monetary aggregates by the wholesale price index, and we use the call rate as the interest rate.


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The call rate was obtained from RBI (2006) over the period of January 1980 to December 2005,

RBI (2007a) and RBI (2008) over the period of January 2006 to December 2007.

For annual data, we use data over the period of 1976 to 2007. Real GDP and the GDP deflator

were taken from IMF (2008). We obtained M1, M2, and M3 from various issues of the RBIBulletin. We deflate these monetary aggregates by the GDP deflator, and we use the call rate as

the interest rate. The call rate was obtained from RBI (2007b) and RBI (2008). Logarithm

values are used for money supply, price levels, and output (industrial production and GDP).

Interest rates are analyzed in two ways, taking a logarithm in one case and not in the other.

As a preliminary analysis, we carried out the augmented Dickey-Fuller tests for the logs of

real money balances, output, and interest rates (Dickey and Fuller 1979). As a result, the level of

each variable was found to have a unit root, whereas the first difference of each variable was

found not to have a unit root. Thus, we can say that each variable is a nonstationary variable

with a unit root.

5. Empirical Results

5.1 Monthly Data

First, we analyzed the money demand function in relation to the use of M1 using the monthly

data over the period of January 1980 to December 2007. For that analysis, we conducted

Johansen cointegration tests for the money demand function (Johansen 1991). There are two

kinds of Johansen-type tests: the trace test and the maximum eigen-value test.

Table 1 shows the results of cointegration tests for Model 1 and Model 2. Model 1 includes

the logs of real money balances, the logs of industrial production, and the interest rate; whereas

Model 2 includes the logs of real money balances, the logs of industrial production, and the logs

of interest rates. As is evident from Table 1, the null hypothesis of no cointegrating relation is

rejected at the 5% significance level for both models. As the existence of the cointegrating

relation was supported, we estimated the money demand function using dynamic OLS (DOLS). 4

Table 2 shows the estimation results with respect to Model 1. As is evident from this table, the

output coefficient is significantly estimated to be at positive values (1.1484 for K=1, 1.1498 for

K=2, and 1.1556 for K=6). The interest rate coefficient is significantly estimated to be at

negative values (-0.0043 for K=1, -0.0049 for K=2, and -0.0050 for K=6). Thus, the sign

condition of the money demand function holds for all cases. Table 3 shows the estimation

results with respect to Model 2. As is evident from this table, the sign condition of the money

demand function holds for all cases. The output coefficient was significantly estimated at

4 Standard errors are calculated using the method of Newey and West (1987).


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positive values (1.1432 for K=1, 1.1437 for K=2, and 1.1478 for K=6), while the interest rate

coefficient was significantly estimated at negative values (-0.0480 for K=1, -0.0548 for K=2,

and -0.0595 for K=6). As is evident from the above results, it became clear that a cointegrating

relation was supported and that the existence of a money demand function with respect to M1was statistically supported.

Next, we considered the money demand function when using M2 for the money supply

component. Table 4 indicates the results of cointegration tests for Model 1 and Model 2. As is

evident from the table, the null hypothesis of no cointegration is rejected at the 5% significance

level for both models. As the existence of the cointegrating relation was supported, we

estimated the money demand function using DOLS. Table 5 shows the estimation results with

respect to Model 1. As is evident from this table, the sign condition of the money demand

function holds. The output coefficient was significantly estimated at positive values of 1.0966

for K=1, 1.0977 for K=2, and 1.1023 for K=6, while the interest rate coefficient was

significantly estimated at negative values of -0.0049 for K=1, -0.0055 for K=2, and -0.0059 for

K=6. Table 6 shows the estimation results with respect to Model 2. As is evident from this table,

the sign condition of the money demand function holds. The output coefficient was significantly

estimated at positive values of 1.0907 for K=1, 1.0908 for K=2, and 1.0934 for K=6, while the

interest rate coefficient was significantly estimated at negative values of -0.0543 for K=1,

-0.0617 for K=2, and -0.0685 for K=6. As is evident from the above results, it became clear that

a cointegrating relation was supported and that the existence of a money demand function with

respect to M2 was statistically supported.

Finally, we considered the money demand function when using M3 for the money supply


evident from this table, the null hypothesis (in which there is no cointegrating relation) is not

rejected at the 5% significance level for either of the models. It became clear that a

cointegrating relation was not supported and thus that the existence of a money demand

function with respect to M3 was not statistically supported.

5.2 Annual Data

We also analyzed the money demand function in relation to the use of M1 using the annual

data over the period from 1976 to 2007. Since industrial production does not necessarily reflect

the total level of output in the Indian economy, it is worthwhile to analyze the money demand

function using annual data, which enables us to use the GDP data. Table 8 shows the results of

cointegration tests for Model 1 and Model 2. As is evident from Table 8, the null hypothesis of


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no cointegrating relation is rejected at the 5% significance level for both models. As the

existence of the cointegrating relation was supported, we estimated the money demand function

using DOLS. Table 9 shows the estimation results with respect to Model 1. As is evident from

this table, the output coefficient is significantly estimated to be positive (1.0037 for K=1, 0.9812for K=2, and 0.9769 for K=3). The interest rate coefficient is significantly estimated to be

negative (-0.0366 for K=1, -0.0260 for K=2, and -0.0242 for K=3). Thus, the sign condition of

the money demand function holds for all cases. Table 10 shows the estimation results with


function holds for all cases. The output coefficient was significantly estimated to be positive

(1.0020 for K=1, 1.0011 for K=2, and 1.0624 for K=3), while the interest rate coefficient was

significantly estimated to be negative (-0.3399 for K=1, -0.2321 for K=2, and -0.2378 for K=3).

As is evident from the above results, it became clear that a cointegrating relation was supported

and that the existence of a money demand function with respect to M1 was statistically

supported.

Next, we considered the money demand function when using M2 for the money supply


evident from the table, the null hypothesis of no cointegration is rejected at the 5% significance

level for both models. As the existence of the cointegrating relation was supported, we

estimated the money demand function using DOLS. Table 12 shows the estimation results with


function holds. The output coefficient was significantly estimated at positive values of 0.9402

for K=1, 0.9173 for K=2, and 0.9132 for K=3, while the interest rate coefficient was

significantly estimated at negative values of -0.0397 for K=1, -0.0295 for K=2, and -0.0278 for

K=3. Table 13 shows the estimation results with respect to Model 2. As is evident from this

table, the sign condition of the money demand function holds. The output coefficient was

significantly estimated at positive values of 0.9381 for K=1, 0.9374 for K=2, and 0.9988 for

K=3, while the interest rate coefficient was significantly estimated at negative values of -0.3669

for K=1, -0.2648 for K=2, and -0.2715 for K=3. As is evident from the above results, it became

clear that a cointegrating relation was supported and that the existence of a money demand

function with respect to M2 was statistically supported.

Finally, we considered the money demand function when using M3 for the money supply


evident from this table, the null hypothesis (in which there is no cointegrating relation) is not

rejected at the 5% significance level in three out of four cases. It became clear that a

cointegrating relation may not be supported and thus that the existence of a money demand


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function with respect to M3 may not be statistically supported.

Our empirical results using annual data are consistent with those using monthly data. Thus,

the cointegrating relation for the money demand function is statistically supported for M1 and

M2, but not for M3 for both monthly and annual data.

6. Some Concluding Remarks

If an equilibrium relationship is observed in the money demand function, financial authorities

can employ appropriate money supply controls to maintain a reasonable inflation rate. This

paper empirically analyzed India's money demand function over the period of 1980 to 2007

using monthly data and the period of 1976 to 2007 using annual data. Results supported the

existence of an equilibrium relation in money demand when money supply was defined as M1

or M2, but no such relation was detected when money supply was defined as M3. These results

were obtained for both monthly and annual data, so they were not affected by data intervals and

were robust in this sense.

What are the implications of these results for India's monetary policy? In the mid-1980s, the

RBI adopted monetary targeting focused on the medium-term growth rate of the M3 money

supply. Monetary targeting was used as a flexible policy framework to be adjusted in

accordance with changes in production and prices, rather than as a strict policy rule. However,

amid ongoing financial innovations and financial sector reforms, the RBI announced in April

1998 that it would switch to the multiple indicator approach in order to be able to consider a

wider array of factors in setting policy. Under this new policy framework, the M3 growth rate is

used as one reference indicator.

In general, a reference indicator, as an indicator of future economic conditions, is used as

something between an operating instrument and a final objective, and no target levels are set, as

is the case, for example, with intermediate targets. However, in India, where it is used as a

reference indicator, the forecast growth rate for the M3 money supply is publicly announced on

an annual basis, and it is focused on as a measure of future price movements. Consequently,

Indian financial authorities, despite the fact that they have changed their policy framework,

continue to pay significant attention to M3 movements. The empirical results of this paper,

though, suggest that the RBI would be able to more appropriately control price levels if it would

refer to the M1 and M2, rather than the M3, money supplies in managing monetary policy.


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Stability of the Money Demand

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"

Cointegrating Relationships in the Demand for Money in India."

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Strong & Super Exogeneity."

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Distribution of the Estimators for Autoregressive

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Faig, Miquel. 1988. " Characterization of the Optimal Tax on Money when it Functions as a

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Estimation and Hypothesis Testing of Cointegration Vectors in

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Kimbrough, Kent P. 1986b. " The Optimum Quantity of Money Rule in the Theory of Public

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Economic Journal 40, no. 1: 101-115.

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Estimating Money Demand Function: A

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A Simple Positive Semi-Definite,

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Do Broad Money, Output, and Prices Stand for a Stable Relationship


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in India?" Journal of Policy Modeling 26, nos. 8-9: 983-1001.

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Table 1 Cointegration Tests (M1, Monthly data)

* indicates that the null hypothesis is rejected at the 5% significance level.

Model

Hypothesized

Number of

Cointegration

Equations

Maximum Eigen-

Value TestTrace Test

Model 1 0 60.8885* 75.5725*

At most 1 13.9371 14.6841

At most 2 0.7470 0.7470

Model 2 0 62.6358* 77.4240*

At most 1 14.0725 14.7883

At most 2 0.7157 0.7157


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Table 2 Dynamic OLS (M1, Monthly data, Model 1)

0 1 2log( 1 ) log( ) log( ) log( )K K

t t t t yi t ri t t i K i K m p y r y r u

= = = + + + + +

Lead and

LagVariable Coefficient SE t-Statistic P-value 2 R

1K = Constant 2.9533 0.0741 39.8611 0.0000 0.9911

log( )t y 1.1484 0.0158 72.4935 0.0000

t r -0.0043 0.0012 -3.5416 0.0005

2K = Constant 2.9478 0.0626 47.0700 0.0000 0.9923

log( )t y 1.1498 0.0135 85.2199 0.0000

t r -0.0049 0.0012 -4.0843 0.0001

6K = Constant 2.9130 0.0539 54.0741 0.0000 0.9947

log( )t y 1.1556 0.0107 108.2575 0.0000

t r -0.0050 0.0015 -3.3923 0.0008

Note: SE is the Newy-West HAC Standard Error (lag truncation=5).


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0 1 2log( 1 ) log( ) log( ) log( ) log( ) log( )K K


= = = + + + + +

Lead and


1K = Constant 3.0363 0.0894 33.9515 0.0000 0.9911

log( )t y 1.1432 0.0164 69.6620 0.0000

t r -0.0480 0.0134 -3.5715 0.0004

2K = Constant 3.0445 0.0755 40.3038 0.0000 0.9924

log( )t y 1.1437 0.0138 82.8285 0.0000

t r -0.0548 0.0127 -4.3211 0.0000

6K = Constant 3.0247 0.0655 46.2015 0.0000 0.9950

log( )t y 1.1478 0.0104 109.8776 0.0000

t r -0.0595 0.0144 -4.1434 0.0000



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Model

Hypothesized

Number of

Cointegration

Equations

Maximum Eigen-


Model 1 0 25.3333* 39.3050*

At most 1 11.8306 13.9716

At most 2 2.1411 2.1411

Model 2 0 26.2955* 39.6353*

At most 1 11.0450 13.3398

At most 2 2.2948 2.2948


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0 1 2log( 2 ) log( ) log( ) log( )K K


= = = + + + + +

Lead and


1K = Constant 3.2129 0.0760 42.2970 0.0000 0.9899

log( )t y 1.0966 0.0165 66.5934 0.0000

t r -0.0049 0.0012 -3.9508 0.0001

2K = Constant 3.2096 0.0655 49.0098 0.0000 0.9913

log( )t y 1.0977 0.0143 76.7408 0.0000

t r -0.0055 0.0012 -4.5206 0.0000

6K = Constant 3.1817 0.0583 54.5536 0.0000 0.9938

log( )t y 1.1023 0.0117 94.5821 0.0000

t r -0.0059 0.0015 -3.8277 0.0002



19/34


20/34

17



Model

Hypothesized

Number of

Cointegration

Equations

Maximum Eigen-


Model 1 0 20.4033 27.3507

At most 1 5.2173 6.9474

At most 2 1.7301 1.7301

Model 2 0 19.4088 25.9354

At most 1 5.0979 6.5266

At most 2 1.4287 1.4287


21/34

18

Table 8 Cointegration Tests (M1, Annual data)


Model

Hypothesized

Number of

Cointegration

Equations

Maximum Eigen-


Model 1 0 29.0382* 40.3709*

At most 1 8.8912 11.3327

At most 2 2.4415 2.4415

Model 2 0 31.2939* 42.7403*

At most 1 8.9359 11.4464

At most 2 2.5105 2.5105


22/34

19

Table 9 Dynamic OLS (M1, Annual data, Model 1)

0 1 2log( 1 ) log( ) log( ) log( )K K


= = = + + + + +

Lead and


1K = Constant 4.0407 0.2939 13.7502 0.0000 0.9716

log( )t y 1.0037 0.0768 13.0640 0.0000

t r -0.0366 0.0099 -3.7002 0.0014

2K = Constant 3.8224 0.1669 22.9069 0.0000 0.9944

log( )t y 0.9812 0.0448 21.9224 0.0000

t r -0.0260 0.0058 -4.4821 0.0005

3K = Constant 3.7578 0.1312 28.6378 0.0000 0.9952

log( )t y 0.9769 0.0470 20.7860 0.0000

t r -0.0242 0.0048 -5.0189 0.0010



23/34

20




= = = + + + + +

Lead and


1K = Constant 4.4896 0.3875 11.5861 0.0000 0.9738

log( )t y 1.0020 0.0772 12.9872 0.0000

t r -0.3399 0.0873 -3.8949 0.0009

2K = Constant 4.0882 0.2591 15.7774 0.0000 0.9942

log( )t y 1.0011 0.0524 19.1028 0.0000

t r -0.2321 0.0615 -3.7765 0.0020

3K = Constant 3.8970 0.1522 25.6072 0.0000 0.9944

log( )t y 1.0624 0.0446 23.8410 0.0000

t r -0.2378 0.0532 -4.4676 0.0021



24/34

21



Model

Hypothesized

Number of

Cointegration

Equations

Maximum Eigen-


Model 1 0 29.4465* 40.2924*

At most 1 8.9430 10.8459

At most 2 1.9029 1.9029

Model 2 0 31.8685* 42.6966*

At most 1 8.9294 10.8281

At most 2 1.8988 1.8988


25/34

22


0 1 2log( 1 ) log( ) log( ) log( )K K


= = = + + + + +

Lead and


1K = Constant 4.3669 0.2886 15.1317 0.0000 0.9676

log( )t y 0.9402 0.0760 12.3674 0.0000

t r -0.0397 0.0098 -4.0638 0.0006

2K = Constant 4.1610 0.1650 25.2232 0.0000 0.9936

log( )t y 0.9173 0.0443 20.7286 0.0000

t r -0.0295 0.0057 -5.1387 0.0002

3K = Constant 4.1007 0.1311 31.2843 0.0000 0.9948

log( )t y 0.9132 0.0478 19.1190 0.0000

t r -0.0278 0.0049 -5.7213 0.0004



26/34

23




= = = + + + + +

Lead and


1K = Constant 4.8505 0.3788 12.8058 0.0000 0.9702

log( )t y 0.9381 0.0757 12.3845 0.0000

log( )t r -0.3669 0.0857 -4.2806 0.0004

2K = Constant 4.4693 0.2556 17.4837 0.0000 0.9935

log( )t y 0.9374 0.0511 18.3566 0.0000

log( )t r -0.2648 0.0613 -4.31665 0.0007

3K = Constant 4.2862 0.1556 27.5495 0.0000 0.9938

log( )t y 0.9988 0.0463 21.5558 0.0000

log( )t r -0.2715 0.0541 -5.0207 0.0010



27/34

24



Model

Hypothesized

Number of

Cointegration

Equations

Maximum Eigen-


Model 1 0 20.7221 31.4139*

At most 1 6.7122 10.6918

At most 2 3.9796 3.9796

Model 2 0 18.0444 28.3185

At most 1 6.5157 10.2741

At most 2 3.7584 3.7584


28/34

No. Author(s) Title

165 Mayumi MURAYAMA Re-Examining Difference andDevelopment: A Note onBroadening the Field of Gender and Development in Japan 2008

164 Jose Luis CORDEIRO Constitutiond aroumd the World: A View from Latin America 2008

163 Takahiro FUKUNISHI Clothing Export from sub-Saharan Africa: Impact on Povertand Potential for Growth 2008

162 Koichi USAMI Re-thinking Argentina's Labour and Social Security Reform inthe 1990s: Agreement on Competitive Corporatism 2008

161 Mai FUJITA Value Chain Dynamics and the Growth of Local Firms: TheCase of Motorcycle Industry in Vietnam 2008

160 Kazunobu HAYAKAWA,Kuo-I CHANGBorder Barriers in Agricultural Trade and the Impact of TheirElimination: Evidence from East Asia 2008

159Satoru KUMAGAI, ToshitakaGOKAN, Ikumo ISONO,

Souknilanh KEOLA

The IDE Geographical Simulation Model: Predicting Long-Term Effects of Infrastructure Development Projectso 2008

158 Satoru KUMAGAI A Journey Through the Secret History of the Flying GeeseModel 2008

157 Satoru KUMAGAI A Mathematical Representation of "Excitement" in Games: AContribution to the Theory of Game Systems 2008

156 Kazunobu HAYAKAWA,Fukunari KIMURAThe Effect of Exchange Rate Volatility on International Trade:The Implication for Production Networks in East Asia 2008

155 Kazunobu HAYAKAWA The Choice of Transport Mode: Evidence from JapaneseExports to East Asia 2008

154 Jose Luis CORDEIRO Monetary Systems in Developing Countries: An UnorthodoxView 2008

153 Takao TSUNEISHIDevelopment of Border Economic Zones in Thailand:Expansion of Border Trade and Formation of Border EconomicZones

2008

152 Nguyen Binh Giang Improving the Foreign Direct Investment Capacity of thMountainous Provinces in Viet Nam 2008

151 Syviengxay Oraboune Infrastructure (Rural Road) Development and PovertyAlleviation in Lao PDR 2008

150 Chap Moly Infrastructure Development of Railway in Cambodia: A LongTerm Strategy 2008

149 Thandar Khine Foreign Direct Investment Relations between Myanmar andASEAN 2008

148 Aung Kyaw Financing Small and Midium Enterprises in Myanmar 2008

147 Toshihiro KUDO Myanmar Sugar SMEs: History, Technology, Location andGovernment Policy 2008

146 Momoko KAWAKAMI Exploiting the Modularity of Value Chains: Inter-firmDynamics of the Taiwanese Notebook PC Industry 2008

145 Toshikazu YAMADA Sustainable Development and Poverty Reduction underMubaraks Program 2008

144 Miki HAMADA Bank Borrowing and Financing Medium-sized Firms inIndonesia 2008

143 Yoko IWASAKI Methodological Application of Mode Historical Science toQualitative Research 2008

142 Masahiro KODAMA Monetary Policy Effects in Developing Countries withMinimum Wa es 2008

141 Yasushi HAZAMA The Political Economy of Growth: A Review 2008

Previous IDE Discussion Papers


29/34

No. Author(s) Title

140 Kumiko MAKINO The Changing Nature of Employment and the Reform of Laborand Social Security Legislation in Post-Apartheid South Africa2008

139 Hisao YOSHINO Technology Choice, Change of Trade Structure, and A Case of Hungarian Economy 2008

138 Shigeki HIGASHIThe Policy Making Process in FTA Negotiations: A Case Studyof Japanese Bilateral EPAs 2008

137 Arup MITRA andMayumi MURAYAMA Rural to Urban Migration: A District Level Analysis for India 2008

136 Nicolaus Herman SHOMBE Causality relationship between Total Export and Agricultural

GDP and Manufacturing GDP case of Tanzania 2008

135 Ikuko OKAMOTO The Shrimp Export Boom and Small-Scale Fishermen inMyanmar 2008

134 Chibwe CHISALAUnlocking the Potential of Zambian Micro, Small and MediumEnterprises "learning from the international best practices - theSoutheast Asian Experience"

2008

133 Miwa YAMADA Evolution in the Concept of Development: How has the WorldBank's Legal Assistance Extended its Reach? 2008

132 Maki AOKI-OKABELooking Toward the New Era:Features and Background of the Japan-Thailand EconomicPartnership Agreement

2008

131 Masanaga KUMAKURA andMasato KUROKOChinas Impact on the Exports of Other AsianCountries: A Note 2007

130 Koichiro KIMURA Growth of the Firm and Economic Backwardness:A Case Study and Analysis of China's Mobile Handset Industry2007

129 Takahiro FUKUNISHI Has Low Productivity Constrained Competitiveness of African

Firrms?: Comparison of Firm Performances with Asian Firms2007

128 Akifumi KUCHIKI Industrial Policy in Asia 2007

127 Teiji SAKURAI JETRO and Japans Postwar Export Promotion System:Messages forLatin American Export Promotion Agencies 2007

126 Takeshi KAWANAKA Who Eats the Most? Quantitative Analysis of Pork BarrelDistributions in the Philippines 2007

125 Ken IMAI and SHIU Jingming A Divergent Path of Industrial Upgrading: Emergence andEvolution of the Mobile Handset Industry in China 2007

124 Tsutomu TAKANE Diversities and Disparities among Female-Headed Householdsin Rural Malawi 2007

123 Masami ISHIDAEvaluating the Effectiveness of GMS Economic Corridors: Whyis There More Focus on the Bangkok-Hanoi Road than the East-West Corridor

2007

122 Toshihiro KUDO Border Industry in Myanmar: Turning the Periphery into theCenter of Growth 2007

121 Satoru KUMAGAI A Mathematical Representation of "Excitement" in Games fromthe Viewpoint of a Neutral Audience 2007

120 Akifumi KUCHIKI A Flowchart Approach to Malaysia'sAutomobile Industry Cluster Policy 2007

119 Mitsuhiro KAGAMI The Sandinista Revolution and Post-ConflictDevelopment - Key Issues 2007

118 Toshihiro KUDO Myanmar and Japan: How Close Friends Become Estranged 2007

117 Tsutomu TAKANE Gambling with Liberalization: Smallholder Livelihoods inContemporary Rural Malawi 2007

116 Toshihiro KUDO and FumiharuMIENOTrade, Foreign Investment and Myanmar's EconomicDevelopment during the Transition to an Open Economy 2007

115 Takao TSUNEISHI Thailand's Economic Cooperation with Neighboring Countriesand Its Effects on Economic Development within Thailand 2007


30/34

No. Author(s) Title

114Jan OOSTERHAVEN,Dirk STELDER andSatoshi INOMATA

Evaluation of Non-Survey International IO ConstructionMethods with the Asian-Pacific Input-Output Table 2007

113 Satoru KUMAGAI Comparing the Networks of Ethnic Japanese and EthnicChinese in International Trade 2007

112 Rika NAKAGAWAInstitutional Development of Capital Markets in Nine AsianEconomies 2007

111 Hiroko UCHIMURA andJohannes JTTINGFiscal Decentralization, Chinese Style: Good for HealthOutcomes? 2007

110 Hiroshi KUWAMORI andNobuhiro OKAMOTOIndustrial Networks between China and the Countries of theAsia-Pacific Region 2007

109 Yasushi UEKI Industrial Development and the Innovation System of theEthanol Sector in Brazil 2007

108 Shinichi SHIGETOMI Publicness and Taken-for-granted Knowledge:A Case Study of Communal Land Formation in Rural Thailand2007

107 Yasushi HAZAMA Public Support for Enlargement: Economic, Cultural, or

Normative?2007

106 Seiro ITO Bounding ATE with ITT 2007

105 Tatsufumi YAMAGATA Securing Medical Personnel: Case Studies of Two SourceCountries and Two Destination Countries 2007

104 Tsutomu TAKANE Customary Land Tenure, Inheritance Rules, and SmallholderFarmers in Malawi 2007

103 Aya OKADA and N. S.SIDDHARTHANIndustrial Clusters in India: Evidence from Automobile Clustersin Chennai and the National Capital Region 2007

102 Bo MENG and Chao QU Application of the Input-Output Decomposition Technique toChina's Regional Economies 2007

101 Tatsufumi YAMAGATA

Prospects for Development of the Garment Industry in

Developing Countries: What Has Happened since the MFAPhase-Out?

2007

100 Akifumi KUCHIKI The Flowchart Model of Cluster Policy:The Automobile Industry Cluster in China 2007

99Seiro ITOH, MarikoWATANABE, and NoriyukiYANAGAWA

Financial Aspects of Transactions with FDI: Trade CreditProvision by SMEs in China 2007

98 Norio KONDO Election Studies in India 2007

97 Mai FUJITA Local Firms in Latecomer Developing Countries amidst China'sRise - The case of Vietnam's motorcycle industry 2007

96Kazushi TAKAHASHI andKeijiro OTSUKA

Human Capital Investment and Poverty Reduction overGenerations: A Case from the Rural Philippines, 1979-2003 2007

95 Kazushi TAKAHASHI Sources of Regional Disparity in Rural Vietnam: Oaxaca-Blinder Decomposition 2007

94 Hideki HIRAIZUMI Changes in the Foreign Trade Structure of the Russian Far Eastunder the Process of Transition toward a Market Economy 2007

93 Junko MIZUNO Differences in Technology Transfers to China among Europeanand Japanese Elevator Companies 2007

92 Kazuhiko OYAMADA Is It Worthwhile for Indonesia to Rush into a Free Trade Dealwith Japan? 2007

91 Haruka I. MATSUMOTOThe Evolution of the "One China" Concept in the Process of Taiwan's Democratization 2007

90 Koji KUBO Natural Gas and Seeming Dutch Disease 2007

89 Akifumi KUCHIKI Clusters and Innovation: Beijing's Hi-technology IndustryCluster and Guangzhou's Automobile Industry Cluster 2007

88 DING Ke Domestic Market-based Industrial Cluster Development inModern China 2007


31/34

No. Author(s) Title

87 Koji KUBODo Foreign Currency Deposits Promote or DeterFinancial Development in Low-income Countries?:An Empirical Analysis of Cross-section Data

2007

86 G. BALATCHANDIRANE IT Offshoring and India: Some Implications 200785 G. BALATCHANDIRANE IT Clusters in India 2007

84 Tomohiro MACHIKITAAre Job Networks Localized in a Developing Economy? SearchMethods for Displaced Workers in Thailand 2006

83 Tomohiro MACHIKITA Career Crisis? Impacts of Financial Shock on the Entry-LevelLabor Market: Evidence from Thailand 2006

82 Tomohiro MACHIKITA Is Learning by Migrating to a Megalopolis Really Important?Evidence from Thailand 2006

81 Asao ANDO and Bo MENG Transport Sector and Regional Price Differentials:A SCGE Model for Chinese Provinces 2006

80 Yuka KODAMA Poverty Analysis of Ethiopian Females in the Amhara Region:Utilizing BMI as an Indicator of Poverty 2006

79 So UMEZAKI Monetary and Exchange Rate Policy in Malaysia before the

Asian Crisis2006

78 Ikuo KUROIWA Rules of Origin and Local Content in East Asia 2006

77 Daisuke HIRATSUKA Outward FDI from and Intraregional FDI in ASEAN:Trends and Drivers 2006

76 Masahisa FUJITA Economic Development Capitalizing on Brand Agriculture:Turning Development Strategy on Its Head 2006

75 DING Ke Distribution System of Chinas Industrial Clusters:Case Study of Yiwu China Commodity City 2006

74 Emad M. A. ABDULLATIFAlaniCrowding-Out and Crowding-In Effects of Government BondsMarket on Private Sector Investment (Japanese Case Study) 2006

73 Tatsuya SHIMIZU Expansion of Asparagus Production and Exports in Peru 2006

72 Hitoshi SUZUKI The Nature of the State in Afghanistan and Its Relations withNeighboring Countries 2006

71 Akifumi KUCHIKI An Asian Triangle of Growth and Cluster-to-Cluster Linkages 2006

70 Takayuki TAKEUCHI Integration under One Country, Two Systems - The Case of Mainland China and Hong Kong- 2006

69 Shinichi SHIGETOMI Bringing Non-governmental Actors into the PolicymakingProcess: The Case of Local Development Policy in Thailand 2006

68 Kozo KUNIMUNE Financial Cooperation in East Asia 2006

67 Yasushi UEKI Export-Led Growth and Geographic Distribution of the PoultryMeat Industry in Brazil 2006

66 Toshihiro KUDOMyanmar's Economic Relations with China: Can China Supportthe Myanmar Economy? 2006

65 Akifumi KUCHIKI Negative Bubbles and Unpredictability of Financial Markets:The Asian Currency Crisis in 1997 2006

64 Ken IMAI Explaining the Persistence of State-Ownership in China 2006

63 Koichi FUJITA and IkukoOKAMOTOAgricultural Policies and Development of MyanmarAgriculture: An Overview 2006

62 Tatsufumi YAMAGATA The Garment Industry in Cambodia: Its Role in PovertyReduction through Export-Oriented Development 2006

61 Hisaki KONOIs Group Lending A Good Enforcement Scheme for AchievingHigh Repayment Rates?Evidence from Field Experiments inVietnam

2006

60 Hiroshi KUWAMORI The Role of Distance in Determining International TransportCosts: Evidence from Philippine Import Data 2006

59 Tatsuya SHIMIZU Executive Managers in Peru's Family Businesses 2006

58 Noriyuki YANAGAWA, SeiroITO, and Mariko WATANABETrade Credits under Imperfect Enforcement: A Theory with aTest on Chinese Experience 2006


32/34

No. Author(s) Title

57 Reiko AOKI, Kensuke KUBO,and Hiroko YAMANEIndian Patent Policy and Public Health: Implications from theJapanese Experience 2006

56 Koji KUBO The Degree of Competition in the Thai Banking Industry beforeand after the East Asian Crisis 2006

55 Jiro OKAMOTO Australia's Foreign Economic Policy: A 'State-Society Coalition'Approach and a Historical Overview 2006

54 Yusuke OKAMOTO Integration versus Outsourcing in Stable Industry Equilibriumwith Communication Networks 2006

53 Hikari ISHIDO andYusuke OKAMOTOWinner-Take-All Contention of Innovation under Globalization:A Simulation Analysis and East Asias Empirics 2006

52 Masahiro KODAMA Business Cycles of Non-mono-cultural Developing Economies 2006

51 Arup MITRA and YukoTSUJITAMigration and Wellbeing at the Lower Echelons of theEconomy: A Study of Delhi Slums 2006

50

Bo MENG, Hajime SATO, JunNAKAMURA, NobuhiroOKAMOTO, Hiroshi

KUWAMORI, and SatoshiINOMATA

Interindustrial Structure in the Asia-Pacific Region: Growth andIntegration, by Using 2000 AIO Table 2006

49Maki AOKI-OKABE, YokoKAWAMURA, and ToichiMAKITA

International Cultural Relations of Postwar Japan 2006

48 Arup MITRA and Hajime SATOAgglomeration Economies in Japan: Technical Efficiency,Growth and Unemployment 2006

47 Shinichi SHIGETOMIOrganization Capability of Local Societies in RuralDevelopment: A Comparative Study of MicrofinanceOrganizations in Thailand and the Philippines

2006

46 Yasushi HAZAMA Retrospective Voting in Turkey: Macro and Micro Perspectives 2006

45 Kentaro YOHIDA and MachikoNAKANISHIFactors Underlying the Formation of Industrial Clusters in Japanand Industrial Cluster Policy: A Quantitative Survey 2005

44 Masanaga KUMAKURA Trade and Business Cycle Correlations in Asia-Pacific 2005

43 Ikuko OKAMOTO Transformation of the Rice Marketing System and Myanmar'sTransition to a Market Economy 2005

42 Toshihiro KUDO The Impact of United States Sanctions on the MyanmarGarment Industry 2005

41 Yukihito SATO President Chain Store Corporation's Hsu Chong-Jen: A CaseStudy of a Salaried Manager in Taiwan 2005

40 Taeko HOSHINO Executive Managers in Large Mexican Family Businesses 2005

39 Chang Soo CHOE Key Factors to Successful Community Development: TheKorean Experience 2005

38 Toshihiro KUDO Stunted and Distorted Industrialization in Myanmar 2005

37 Etsuyo MICHIDA and KojiNISHIKIMI North-South Trade and Industly-Specific Pollutants 2005

36 Akifumi KUCHIKI Theory of a Flowchart Approach to Industrial Cluster Policy 2005

35 Masami ISHIDA Effectiveness and Challenges of Three Economic Corridors of the Greater Mekong Sub-region 2005

34 Masanaga KUMAKURA Trade, Exchange Rates, and Macroeconomic Dynamics in EastAsia: Why the Electronics Cycle Matters 2005

33 Akifumi KUCHIKITheoretical Models Based on a Flowchart Approach toIndustrial Cluster Policy 2005

32 Takao TSUNEISHI The Regional Development Policy of Thailand and ItsEconomic Cooperation with Neighboring Countries 2005

31 Yuko TSUJITA Economic Reform and Social Setor Expenditures: A Study of Fifteen Indian States 1980/81-1999/2000 2005


33/34

No. Author(s) Title

30 Satoshi INOMATATowards the Compilation of the Consistent Asian InternationalI-O Table: The Report of the General Survey on National I-OTables

2005

29 Bo MENG and Asao ANDO An Economic Derivation of Trade Coefficients under theFramework of Multi-regional I-O Analysis 2005

28Nobuhiro OKAMOTO, TakaoSANO, and Satoshi INOMATA

Estimation Technique of International Input-Output Model byNon-survey Method 2005

27 Masahisa FUJITA and TomoyaMORI Frontiers of the New Economic Geography 2005

26 Hiroko UCHIMURA Influence of Social Institutions on Inequality in China 2005

25 Shinichiro OKUSHIMA andHiroko UCHIMURA Economic Reforms and Income Inequality in Urban China 2005

24 Banri ITO and TatsufumiYAMAGATA

Who Develops Innovations in Medicine for the Poor? Trends inPatent Applications Related to Medicines for HIV/AIDS,Tuberculosis, Malaria and Neglected Diseases

2005

23 Etsuyo MICHIDA Management for a Variety of Environmental Pollution and

North-South Trade2005

22 Daisuke HIRATSUKA The "Catching Up" Process of Manufacturing in East Asia 2005

21 Masahisa FUJITA and TomoyaMORITransport Development and the Evolution of EconomicGeography 2005

20 Graciana B. FEMENTIRACase Study of Applied LIP Approach/Activities in thePhilippines: The Training Services Enhancement Project forRural Life Improvement (TSEP-RLI) Experience

2005

19 Hitoshi SUZUKI Structural Changes and Formation of R st -shahr in Post-

revolutionary Rural Society in Iran 2004

18Tomokazu ARITA, MasahisaFUJITA, and Yoshihiro

KAMEYAMA

Regional Cooperation of Small & Medium Firms in JapaneseIndustrial Clusters 2004

17 Karma URA Peasantry and Bureaucracy in Decentralization in Bhutan 2004

16 Masahisa FUJITA and ToshitakaGOKANOn the Evolution of the Spatial Economy with Multi-unitMulti-plant Firms: The Impact of IT Development 2004

15 Koji KUBO Imperfect Competition and Costly Screening in the CreditMarket under Conditions of Asymmetric Information 2004

14 Marcus BERLIANT andMasahisa FUJITA Knowledge Creation as a Square Dance on the Hilbert Cube 2004

13 Gamini KEERAWELLA Formless as Water, Flaming as a Fire Some observations onthe Theory and Practice of Self-Determination 2004

12 Taeko HOSHINOFamily Business in Mexico: Responses to Human ResourceLimitations and Management Succession 2004

11 Hikari ISHIDO East Asias Economic Development cum Trade Divergence 2004

10 Akifumi KUCHIKI Prioritization of Policies: A Prototype Model of a FlowchartMethod 2004

9 Sanae SUZUKI Chairmanship in ASEAN+3: A Shared Rule of Behaviors 2004

8 Masahisa FUJITA and ShlomoWEBEROn Labor Complementarity, Cultural Frictions and StrategicImmigration Policies 2004

7 Tatsuya SHIMIZU Family Business in Peru: Survival and Expansion under theLiberalization 2004

6 Katsumi HIRANO Mass Unemployment in South Africa: A Comparative Studywith East Asia 2004

5 Masahisa FUJITA and Jacques-Francois THISSEGlobalization and the Evolution of the Supply Chain: WhoGains and Who Loses? 2004

4 Karma URA The First Universal Suffrage Election, at County (Gewog)Level, in Bhutan 2004

3 Gamini KEERAWELLA The LTTE Proposals for an Interim Self-Governing Authorityand Future of the Peace Process in Sri Lanka 2004


34/34

No. Author(s) Title

2 Takahiro FUKUNISHI International Competitiveness of Manufacturing Firms in Sub-Saharan Africa 2004

1 Pk. Md. Motiur RAHMAN andTatsufumi YAMAGATA Business Cycles and Seasonal Cycles in Bangladesh 2004

demand function n india

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