1. SME Financing: A Challenge in a Vulnerable Economy
Presenter
Saqib Farid (UMT, Lahore)
Co-Author
Abdul Rafay (UMT, Lahore)

2. Brief Summary
We empirically investigate the impact of terrorism on external financing extended to SME sector in Pakistan
We use financing extended by banks to SME as proxy of SME development and number of terrorist attacks as proxy of terrorism
Two controlling variables non performing loans of SME sector and Counter Terrorism Funding
Quarterly data from January 2004 to June 2016
JJ cointegration test, vector auto correction model, impulse response functions and variance decomposition analysis

3. Manufacturing Employment Government Support initiatives
Background
SMEs
Economic Growth
Manufacturing Employment
Inadequate financing
Government Support initiatives

4. Trivial Credit History Underdeveloped bank and borrower relationship
SME Access to Finance
SME Opaqueness
Trivial Credit History
Absence of Collateral
Creditworthiness
Meager cash flows
High Risk Premium
Underdeveloped bank and borrower relationship

5. Factors Driving SME Development
Business Environment
Institutional Development
Lending Technologies
Uncertainty Shocks

6. Economic Costs of Terrorism
Poor Economic Growth
Adverse impact on Small Firms
Credit Rationing
Unshielded Sectors
Emerging Economies

7. Linking Terrorism and SMEs Development in Pakistan

8. Civilian Fatalities in Terrorism 2003-16
Year
Terror Fatalities
2003
189
2004
863
2005
648
2006
1471
2007
3598
2008
6715
2009
11704
2010
7435
2011
6303
2012
6211
2013
5379
2014
5496
2015
3682
2016
1640

9. GDP Growth Rate 2002-15 Year GDP Growth Rate (%) 2002-03 4.7 2003-04
7.5 9
5.8
5.5 5
0.4
2.6
3.6
3.8
3.7 4
4.2

10. SME Financing and NPLs in 2004-16

11. Data SME Financing SME NPL Counter Terrorism Funding Terror Incidents
Quarterly Review of SME Financing
SME NPL
Counter Terrorism Funding
Pakistan Economic Survey
Terror Incidents
Global terrorism index
South Asian Portal of terrorism

12. Empirical Model
SMEF = f ( TI, SMENPL, CTF)

13. Unit Root Test First Difference Second Difference SMEF SMENPL TI CTF
First Difference
Second Difference
Model
None
Constant
Constant and Trend
t-statistic
SMEF **
[3]   -
* [5]
* [2]
SMENPL
* [0]
* [0]
* [0] TI
* [0]
* [0]
* [0]
CTF
* [2]
* [1]
* [1]

14. Multivariate JJ-Cointegration Test
Trace Statistic
Critical Value
Max-Eigen Statistic
Max-Eigen Statistic ** **

15. VECM Granger Causality Results
Dependent Variable
Short Term Causilty
Long Term Causality TI
SMENPL
CTF
ECT t-1
SMEF
3.0724**
(0.0463)
(0.9678)
7.3400*
(0.0006) *
(0.0000)

16. VECM Granger Causality Results
Direction of Causilty
Long Run (ECT t-1)
Short Run (F-statistic)
TI causes SMEF
Significant at 1 percent level
Significant at 5 percent level
SMENPL causes SMEF No
CTF causes SMEF

17. IRF of SMEF

18. IRF of SMENPL

19. Variance Decomposition of SMEF
Period
SMEF TI
SMENPL
CTF 1 2 3 4 5 6 7 8 9 10

20. Variance Decomposition of TI
Period
SMEF TI
SMENPL
CTF 1 2 3 4 5 6 7 8 9 10

21. Variance Decomposition of SMENPL
Period
SMEF TI
SMENPL
CTF 1 2 3 4 5 6 7 8 9 10

22. Long-Term and Short-Term Role of Business Environment
Findings
Novel Evidence
Causality
Long-Term and Short-Term
Role of Business Environment

23. Policy Implications SME Performance and Access to Finance
large stagnant SME
Lending Technologies
Need for Higher level of innovation and competitiveness

24. Thank You !