Transcript Modeling the Demand for Bank Loans by Private Business Sector in

By
Faiza Hassan
PhD Student at PIDE , Lecturer, Department of Economics, University of Malakand
Prof. Dr. Abdul Qayyum
Joint Director, Pakistan Institute of Development Economics
1
Introduction
The impact of bank credit on macro-economic fluctuations
has always been a topic of interest in monetary economics
(Meltzer and Brunner 1963)
2
Moore & Threadgold (1985) argued that

money supply is ‘credit-driven’ and

Demand-determined
 at the rate of interest determined by the central bank the money supply
function is horizontal.
Coghlan, 1981; Moore 1979, 1983 illustrated that

Quantity of bank borrowing is largely demand determined
3
• Sensitivity of
Central bank
• Magnitude
of interest
rate
Private sector
credit demand
• Formulation
of effective
Monetary
Policy
4
Monetary Policy
Channels of
Monetary
Transmission
Mechanism
Level of economic
activity
5
Understanding
• Private sector
credit demand
Formulation of
• Effective Monetary
Policy
Achieving
macroeconomic
objectives
• Sustainable
economic growth
• Price stability
• Directing future
economic activity
6
Demand for
credit
Supply of Money
(demand
determined)
Level of
economic activity
7
Pakistan’s Private business sector preferences for bank Credit
Sources of Corporate Financing in Pakistan
(Amount in billion Rupees)
Year
Banks
IPO*
TFC*
2002
525
0.1
4.7
2003
607
2.5
19.5
2004
873
21.7
0.0
2005
1076
9.8
6.6
2006
1270
3.0
3.0
2007
1520
4.9
4.0
2008
2016
6.9
12.6
2009
2065
1.1
0.0
Source: SBP, Financial Stability review 2009-10 page 145
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 The basic purpose of the study is to analyze the long run and short
run dynamics of demand for bank loans by private business sector
in Pakistan for the period 1971 to 2010.
 To investigate whether increased economic activity have positive or
negative impact on the demand for bank loans
 To observe the effect of real rate of return on advances
 To analyze the effect of inflation on demand for bank loans by private
business sector
 To examine the effect of macroeconomic risk, foreign demand pressure,
future state of economy on bank loan demand by private business sector
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11
First category: studies that estimate credit demand as
system
Two reduced form equations are estimated one for credit
demand and other of credit supply
Meltiz and pardue (1973)
12
2nd category: studies which determine demand for bank loan
under equilibrium conditions.
In this approach, a single equation is derived
by
simultaneously solving the demand and supply equation
and by assuming that loans corresponds to a level
where demand and supply are equal or are in equilibrium.
Hicks (1979) and panagopoulos & Spiliotis(1998)
13
The Disequilibrium Approach
Demand and supply equations are estimated separately
and following Maddala and Nelson(1974) derived the
likelihood function. These studies assume that observed
quantity of loans are minimum of demand for loans and
supply of loans.
Laffont & Garcia(1977), Blundell-wignall and gizycki(1992)
and Ghosh & Ghosh (1999) followed this approach
14
Estimation of demand curve in Isolation from supply side of Market
In these studies supply equation is not estimated
it is assumed that at a specific interest rate,
credit to private sector
is determined
by
demand in the market
15
Moore (1983), cuthbertson (1985)
Moore and threadgold(1985),
Arestis(1987-88),
Arestis & Biefang-Frisancho(1995),
Calza, Gartner, Suosa(2001),
Qayyum(2002),
Vera.V Leonardo(2002),
Pandit & Vashisht(2011)
16
Studies with reference to Pakistan
There is a single study over the topic in Pakistan by
Qayyum(2002)
In the study short run and long run dynamics of
demand for bank loans by private business sector
are analyzed
The real rate of interest, inflation and industrial
output were taken as the main determinants of
demand for bank loan
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18
RDBL = f ( RRA , EA, , FDP, INF , MER , EFSE)
19
Interest rate charged on bank loans
Interest rate is the variable included in every study of
demand for bank loan
Hicks(1979), Moore (1983), Cuthbertson (1985), Ghosh &
Ghosh(1999), Qayyum(2002) ................
each and every study included interest rate
20
Economic Activity
Industrial output index is used as indicator of economic
activity
 There are two distinct views in literature about
relationship of demand for bank loans and economic
activity
21
Kashyap, Stein and Wilcox, (1993)
Suggest positive relationship
Robust
economic
growth
Expectations of
firms for higher
profits
Firms will
expand, initiates
new projects
Demand for
bank loans will
increase
22
Friedman and Kuttner (1993) and Bernanke and Gertler (1995)
Proposed a negative relationship
Higher
economic
activity
Increased
current
production and
profits
Firms have
sufficient
resources to
finance their
businesses so
less demand for
loans
23
Foreign Demand Pressure
To see the effect of foreign demand pressure on
demand for bank loans by private sector, indices for
Volume of Exports are included in the model
24
Inflation
If
increase in inflation > increase in interest
increase in inflation compensates the effect of increase
in interest rate.
On the other hand
High level of inflation increases the riskiness of projects
( negative relationship)
25
Macroeconomic Risk
Negative relationship is expected between
macroeconomic risk and demand for bank loans
Variance of Moving Average of Inflation is used.
Vera(2002) has used the same for measuring
macroeconomic risk
26
Expectations about future state of the economy
Stock price indices give signals about expectations of
most informed group about future situation of the
economy.
Moving average of share price indices is used to
approximate Expectations about future state of the
economy.
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AUTOREGRESSIVE DISTRIBUTED LAG MODEL (ARDL)
ARDL approach is found appropriate for data analysis
ΔRDBLt =
𝒌
𝒊=𝟎 𝜷𝟒𝒊
α
+
𝜟𝑭𝑫𝑷𝒕−𝒊 +
𝒌
𝒊=𝟏 𝜷𝟏𝒊
𝜟𝑹𝑫𝑩𝑳𝒕−𝒊
𝒌
𝒊=𝟎 𝜷𝟓𝒊
+
𝜟𝑰𝑵𝑭𝒕−𝒊 +
𝝀𝟏 RDBLt-1 + 𝝀𝟐 EAt-1 + 𝝀𝟑 RRAt-1 +
𝒌
𝒊=𝟎 𝜷𝟐𝒊
𝜟𝑬𝑨𝒕−𝒊
𝒌
𝒊=𝟎 𝜷𝟔𝒊
𝜟𝑬𝑭𝑺𝑬𝒕−𝒊 +
+
𝒌
𝒊=𝟎 𝜷𝟑𝒊
𝜟𝑹𝑹𝑨𝒕−𝒊
𝒌
𝒊=𝟎 𝜷𝟕𝒊
𝜟𝑴𝑬𝑹𝒕−𝒊 +
+
𝝀𝟒 FDPt-1 + 𝝀𝟓 INFt-1 + 𝝀𝟔 MERt-1 + 𝝀𝟕 EFSEt-1 + μt
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Short Run Dynamics (Error Correction model)
ΔRDBLt = γ +
𝒌
𝒊=𝟎 𝜷𝟒𝒊
𝒌
𝒊=𝟏 𝜷𝟏𝒊
𝜟𝑭𝑫𝑷𝒕−𝒊 +
𝜟𝑹𝑫𝑩𝑳𝒕−𝒊 +
𝒌
𝒊=𝟎 𝜷𝟓𝒊
𝜟𝑰𝑵𝑭𝒕−𝒊 +
𝒌
𝒊=𝟎 𝜷𝟐𝒊
𝜟𝑬𝑨𝒕−𝒊 +
𝒌
𝒊=𝟎 𝜷𝟔𝒊
𝜟𝑬𝑭𝑺𝑬𝒕−𝒊 +
𝒌
𝒊=𝟎 𝜷𝟑𝒊
𝜟𝑹𝑹𝑨𝒕−𝒊 +
𝒌
𝒊=𝟎 𝜷𝟕𝒊
𝜟𝑴𝑬𝑹𝒕−𝒊
+ δ ECM(-1) + νt
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Univariate Analysis
In the first step of data analysis individual series has
been checked for existence or non existence of unit root
Hylleberg, Engle, Granger and Yoo( HEGY) test is
employed for the purpose
32
Test of Cointegration
Estimation of ARDL Model
Estimation of Short Run Model
33
34
HEGY test results suggested that
RDBL, EA, FDP,EFSE, RRA, INF are I(1)
while
MER is I(0)
35
ARDL model is estimated using 6 lags and general
to specific rule is followed for eliminating the
insignificant variables
Different diagnostic and stability tests are carried
out to check the validity of the model
36
Test of Co-Integration( Bounds Test)
F-statistics
Probability
7.8431***
0.0000
Significant Level
Lower I(0)
Upper I(1)
1%
3.41
4.68
Pesaran et. al (1999)
37
Long Run Parameter Estimates
RDBL = 4.0238- 0.02974*RRA + 1.3595*EA – 0.1703*INF - 0.04181*MER
(4.88)
(-1.63)
(3.49)
(-4.41)
(-2.92)
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Dependent Variable: D(RDBL)
Variable
Coefficient
Std. Error
t-Statistic
Prob.
ECM(-1)
-0.085443
0.013298
-6.425111
0.0000
D(INF)
-0.016326
0.002038
-8.009247
0.0000
D(EA(-1))
-0.061195
0.028179
-2.171674
0.0317
D(RRA(-3))
-0.018210
0.006408
-2.841678
0.0052
D(INF(-3))
-0.018189
0.006611
-2.751144
0.0068
D(MER(-3))
0.003570
0.001233
2.895490
0.0044
D(FDP(-5))
-0.044828
0.020305
-2.207736
0.0290
D(MER(-5))
0.004985
0.001462
3.409489
0.0009
D(RRA(-6))
0.005260
0.001767
2.977390
0.0035
D(FDP(-6))
0.041371
0.020425
2.025519
0.0448
D(MER(-6))
0.003272
0.001449
2.257062
0.0256
D(EA(-6))
-0.157407
0.031539
-4.990859
0.0000
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Policy Implications
Demand for bank loan by private business sector is found
elastic to RRA so it can help the monetary authorities to
formulate effective monetary policy
The results of MER, INF highlights the importance of
bringing macroeconomic stability
The analysis suggests the need of stable government
policies and macroeconomic stability
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