demand function n india
TRANSCRIPT
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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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The Institute of Developing Economies (IDE) is a semigovernmental,
nonpartisan, nonprofit research institute, founded in 1958. The Institutemerged with the Japan External Trade Organization (JETRO) on July 1, 1998.
The Institute conducts basic and comprehensive studies on economic and
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The views expressed in this publication are those of the author(s). Publication does
not imply endorsement by the Institute of Developing Economies of any of the viewsexpressed within.
INSTITUTE OF DEVELOPING E CONOMIES (IDE), JETRO
3-2-2, W AKABA , M IHAMA -KU , C HIBA -SHI
C HIBA 261-8545, JAPAN
2008 by Institute of Developing Economies, JETRO
No part of this publication may be reproduced without the prior permission of theIDE-JETRO.
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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
component. Table 7 indicates the results of cointegration tests for Model 1 and Model 2. As is
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
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 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
component. Table 11 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 12 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 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
component. Table 14 indicates the results of cointegration tests for Model 1 and Model 2. As is
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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References
Bahmani-Oskooee, Mohsen, and Hafez Rehman. 2005."
Stability of the Money Demand
Function in Asian Developing Countries."
Applied Economics 37, no. 7: 773-792.Bhattacharya, Radha. 1995.
"
Cointegrating Relationships in the Demand for Money in India."
The Indian Economic Journal 43, no. 1: 69-75.
Das, Samarjit, and Kumarjit Mandal. 2000."
Modeling Money Demand in India: Testing Weak,
Strong & Super Exogeneity."
Indian Economic Review 35, no. 1: 1-19.
Dickey, David A., and Wayne A. Fuller. 1979."
Distribution of the Estimators for Autoregressive
Time Series with a Unit Root. " Journal of the American Statistical Association 74, no. 366:
427-431.
Faig, Miquel. 1988. " Characterization of the Optimal Tax on Money when it Functions as a
Medium of Exchange."
Journal of Monetary Economics 22, no. 1: 137-148.
International Monetary Fund. 2008. International Financial Statistics . Washington, D.C.: IMF,
April.
Johansen, Sren. 1991."
Estimation and Hypothesis Testing of Cointegration Vectors in
Gaussian Vector Autoregressive Models."
Econometrica 59, no. 6: 1551-1580.
Kimbrough, Kent P. 1986a. " Inflation, Employment, and Welfare in the Presence of
Transactions Costs. " Journal of Money, Credit, and Banking 18, no. 2: 127-140.
Kimbrough, Kent P. 1986b. " The Optimum Quantity of Money Rule in the Theory of Public
Finance."
Journal of Monetary Economics 18, no. 3: 277-284.
Moosa, Imad. 1992."
The Demand for Money in India: A Cointegration Approach."
The Indian
Economic Journal 40, no. 1: 101-115.
Nag, Ashok K., and Ghanshyam Upadhyay. 1993."
Estimating Money Demand Function: A
Cointegration Approach."
Reserve Bank of India Occasional Papers 14, no. 1: 47-66.
Newey, Whitney and Kenneth, West. 1987."
A Simple Positive Semi-Definite,
Heteroskedasticity and Autocorrelation Consistent Covariance Matrix."
Econometrica 55,
no.3: 703708.
Parikh, Ashok. 1994."
An Approach to Monetary Targeting in India."
Reserve Bank of India
Development Research Group Study , no. 9, October.
Pesaran, M. H., Y. Shin, and R. J. Smith. 2001."
Bounds Testing Approaches to the Analysis of
Level Relationships."
Journal of Applied Econometrics 16, no. 3: 289-326.
Pradhan, B. K., and A. Subramanian. 1997."
On the Stability of the Demand for Money in
India."
The Indian Economic Journal 45, no. 1: 106-117.
Ramachandran, M. 2004."
Do Broad Money, Output, and Prices Stand for a Stable Relationship
-
8/6/2019 Demand Function n India
13/34
10
in India?" Journal of Policy Modeling 26, nos. 8-9: 983-1001.
Rao, Bhaskara B., and Shalabh. 1995."
Unit Roots Cointegration and the Demand for Money in
India."
Applied Economics Letters 2, no. 10: 397-399.
Rao, Bhaskara B., and Rup Singh. 2006."
Demand for Money in India: 1953-2003."
Applied Economics 38, no. 11: 1319-1326.
Reserve Bank of India. 2006. Handbook of Monetary Statistics of India . Mumbai: RBI, March.
Reserve Bank of India. 2007a. Macroeconomic and Monetary Developments First Quarter
Review 2007-08 . Mumbai: RBI, July.
Reserve Bank of India. 2007b. Handbook of Statistics on Indian Economy . Mumbai: RBI,
October.
Reserve Bank of India. 2008. Macroeconomic and Monetary Developments in 2007-08 .
Mumbai: RBI, April.
Reserve Bank of India. various issues. RBI Bulletin . Mumbai: RBI.
Sen, Kunal, and Rajendra R. Vaidya. 1997. The Process of Financial Liberalization . Delhi:
Oxford University Press.
-
8/6/2019 Demand Function n India
14/34
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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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Table 3 Dynamic OLS (M1, Monthly data, Model 2)
0 1 2log( 1 ) log( ) log( ) 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 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
Note: SE is the Newy-West HAC Standard Error (lag truncation=5).
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14
Table 4 Cointegration Tests (M2, 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 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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15
Table 5 Dynamic OLS (M2, Monthly data, Model 1)
0 1 2log( 2 ) 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 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
Note: SE is the Newy-West HAC Standard Error (lag truncation=5).
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17
Table 7 Cointegration Tests (M3, 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 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
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18
Table 8 Cointegration Tests (M1, Annual 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 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
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19
Table 9 Dynamic OLS (M1, Annual 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 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
Note: SE is the Newy-West HAC Standard Error (lag truncation=5).
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20
Table 10 Dynamic OLS (M1, Annual data, Model 2)
0 1 2log( 1 ) log( ) log( ) 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 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
Note: SE is the Newy-West HAC Standard Error (lag truncation=5).
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21
Table 11 Cointegration Tests (M2, Annual 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 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
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22
Table 12 Dynamic OLS (M2, Annual 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 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
Note: SE is the Newy-West HAC Standard Error (lag truncation=5).
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23
Table 13 Dynamic OLS (M2, Annual data, Model 2)
0 1 2log( 1 ) log( ) log( ) 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 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
Note: SE is the Newy-West HAC Standard Error (lag truncation=5).
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24
Table 14 Cointegration Tests (M3, Annual 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 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
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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
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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
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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
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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"
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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
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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
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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
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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
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114Jan OOSTERHAVEN,Dirk STELDER andSatoshi INOMATA
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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
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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
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100 Akifumi KUCHIKI The Flowchart Model of Cluster Policy:The Automobile Industry Cluster in China 2007
99Seiro ITOH, MarikoWATANABE, and NoriyukiYANAGAWA
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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
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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
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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
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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
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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
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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
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49Maki AOKI-OKABE, YokoKAWAMURA, and ToichiMAKITA
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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
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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
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30 Satoshi INOMATATowards the Compilation of the Consistent Asian InternationalI-O Table: The Report of the General Survey on National I-OTables
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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
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23 Etsuyo MICHIDA Management for a Variety of Environmental Pollution and
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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
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19 Hitoshi SUZUKI Structural Changes and Formation of R st -shahr in Post-
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18Tomokazu ARITA, MasahisaFUJITA, and Yoshihiro
KAMEYAMA
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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
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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
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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
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