1. 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

2. 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

3. 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

4. Sensitivity of Private sector credit demand Magnitude of interest rate Central bank Formulation of effective Monetary Policy 4

5. Channels of Monetary Transmission Mechanism Level of economic activity 5

6. Understanding Private sector credit demand Formulation of Effective Monetary Policy Achieving macroeconomic objectives Sustainable economic growth Price stability Directing future economic activity 6

7. Demand for credit Supply of Money (demand determined) Level of economic activity 7

8. Source: SBP, Financial Stability review 2009-10 page 145 8 Year (Amount in billion Rupees) BanksIPO*TFC* 20025250.14.7 20036072.519.5 200487321.70.0 200510769.86.6 200612703.0 200715204.94.0 200820166.912.6 200920651.10.0 Pakistan’s Private business sector preferences for bank Credit Sources of Corporate Financing in Pakistan

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10.  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 10

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12. 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

13. 2 nd 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

14. 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

15. 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

16. 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

17. 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 17

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19. RDBL = f ( RRA, EA,, FDP, INF, MER, EFSE) 19

20. 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

21. 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

22. 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

23. 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

24. 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

25. 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

26. 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

27. 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. 27

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29. AUTOREGRESSIVE DISTRIBUTED LAG MODEL (ARDL) ARDL approach is found appropriate for data analysis 29

30. Short Run Dynamics (Error Correction model) 30

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32. 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

33. Test of Cointegration Estimation of ARDL Model Estimation of Short Run Model 33

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35. HEGY test results suggested that RDBL, EA, FDP,EFSE, RRA, INF are I(1) while MER is I(0) 35

36. 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

37. Test of Co-Integration( Bounds Test) 37

38. Long Run Parameter Estimates 38

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40. 40 Dependent Variable: D(RDBL) VariableCoefficientStd. Errort-StatisticProb. ECM(-1)-0.0854430.013298-6.4251110.0000 D(INF)-0.0163260.002038-8.0092470.0000 D(EA(-1))-0.0611950.028179-2.1716740.0317 D(RRA(-3))-0.0182100.006408-2.8416780.0052 D(INF(-3))-0.0181890.006611-2.7511440.0068 D(MER(-3))0.0035700.0012332.8954900.0044 D(FDP(-5))-0.0448280.020305-2.2077360.0290 D(MER(-5))0.0049850.0014623.4094890.0009 D(RRA(-6))0.0052600.0017672.9773900.0035 D(FDP(-6))0.0413710.0204252.0255190.0448 D(MER(-6))0.0032720.0014492.2570620.0256 D(EA(-6))-0.1574070.031539-4.9908590.0000

41. 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 41

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