Transcript Financial Constraints and Private Sector Development

Financial Constraints
and Private Sector
Development within
the ECOWAS
Presented by: Amie Gaye, CREPOL
ACRIA 4, Abidjan,
4th July 2013
SSA in Perspective
• Emerged as least affected region from 2007 global
financial crisis
• Presently 7 of 10 fastest growing countries within SSA
• Forecasted 5.5% growth into 2014 (IMF 2013).
Key question:
• Has
GDP growth =
welfare for SSA?
• Chronic unemployment and health issues; women and
youth
• Poor performance in HDI
• Constrained and dormant private sector requires
unleashing as a means of addressing several
developmental issues faced by policymakers.
P.S.D, Engine of Growth and Development
• To date, no economy has observed long term economic
prosperity without thriving Private Sector.
• Positive welfare effects: employment creation, poverty
alleviation, boosts aggregate demand, maximizes citizen
contribution, emboldens entrepreneurial spirit, encourages
human capital accumulation (formal & Informal) and
innovation which cumulatively drives growth.
• A role for policymakers: creating conducive business
environments, sound macro policies; stable exchange rate,
low inflation, practical fiscal policies and political stability.
• PSD essential to ward off years of erratic growth on a path to
sustainable, inclusive development
• China modern day example in exhibiting potentials of
unleashing private sector
An overview of the ECOWAS in 2012
• Table 1: Selected economic statistics
Country
Cape Verde
Gambia
Ghana
Guinea
Liberia
Nigeria
Sierra Leone
Benin
Burkina Faso
Cote d'Ivoire
Guinea Bissau
Mali
Niger
Senegal
Togo
Average
•
Real GDP
Growth
4.3
3.9
7.0
3.9
8.3
6.3
19.8
3.8
8.0
9.8
-1.5
-1.2
11.2
3.5
5.0
6.14
Exports
% of
GDP
42.5
28.0
43.1
29.7
45.8
38.3
25.4
14.9
26.9
55.0
16.4
30.7
25.4
26.4
40.0
32.57
External
Debt % of
GDP
77.9
43.6
21.7
30.8
12.3
2.4
33.3
17.6
25.1
24.5
18.0
28.6
20.0
31.9
17.7
27.03
Inflation
2.5
4.6
9.2
15.2
6.8
12.2
13.8
6.7
3.6
1.3
2.2
5.3
0.5
1.1
2.6
5.84
Trade
Balance of
Goods
-42.0
-28.8
-10.8
-18.4
-35.6
15.2
-15.3
-11.9
-2.0
10.2
-7.1
0.4
-9.2
-19.2
-14.8
-12.62
Source: IMF regional economic outlook, May 2013
Fiscal
Balance
% GDP
(incl
grants)
-7.5
-4.4
-11.5
-3.3
-0.5
0.9
-2.8
-0.8
-3.1
-3.4
-1.8
-1.1
-3.5
-5.7
-6.8
-3.69
An overview of the ECOWAS in 2012 cont’d
• Average growth rate at 6%, Sierra Leone driven by
natural resource prices
• Cote d’Ivoire: highest exports % of GDP; predominantly
from commodities, potential vulnerability to shocks (poor
harvest and drought)
• Cape Verde and Gambia external debt well above
average with weak export base and limited natural
resources. Weak intl. position and wide balance of trade
disequilibria threatens development in small countries.
• WAEMU countries observe lowest inflation rates within
ECOWAS (except Cape V), primary convergence
criteria being Max inflation of 3%
• Nigeria only country with Trade and Fiscal balance
surpluses, benefiting from sharp resurgence in oil prices
Business Environment
• Chart 1: ECOWAS countries’ rankings on Ease of Doing
Business Survey 2013
•
Source: World Bank Doing Business 2013
Business Environment cont’d
•
Survey of 183 countries across 10 categories; starting a business,
construction permits, getting credit etc.
•
Singapore a score of 1, best place to do business
•
SSA regional average score of 140, with only 4 countries > SSA
average = Gambia
All 8 WAEMU countries are below average, trailing all nonmembers except Guinea
•
•
Heavy bureaucracy and red tape a key impediment for WAEMU
•
WAEMU-8 receive identical rankings of 129 and 127 in 2013 and
2012 respectively in ‘Getting Credit” category
•
Note: Rankings are indicative of country’s competitiveness only
but not precise and holistic
•
Other considerations; HCAccum., transport costs, infrastructure,
water and land rights.
Credit Constraints and Development
• Several factors affecting PSD. Study focusses on financial
constraints identified by other studies as a key impediment
(World Bank survey 2003).
Why Financial constraints?
• Globally, SSA least recipient of FDI (UNCTAD 2013)
• Positive correlation btw FDI inflows and natural resource
endowment of source country in SSA.
• Steeper competition for capital globally post crisis.
• SSA risk profile limits ability to borrow from intl. private lenders.
• Persistent external debt issues due to loans utilized on
economically non-productive proceeds e.g. consumption,
with long maturity periods and servicing based on volatile
exports receipts (Seck 2008).
• Growth of private sector credit within ECOWAS averaged
0.12% between 2006 to 2011. Growth remained low during
years of boom and busts, evidence to financial repression
hypothesis.
Credit Constraints and Development cont’d
• Multifaceted implication of limited integration in global
financial system:
1)Limited availability of finance, empirically proven
to drive growth; (King and Levine ;1993, McKinnon and
Shaw; 1973) and inability to benefit from global booms.
Thus curbs region’s growth potential
Conversely, 2)Cushioned from external negative shocks
such as 2007 crisis relative to other regions, due to
weakened transmission mechanism.
• Recent calls for financial market development within SSA
to unleash finance and drive growth.
• Aim of research; 1)Assess significance of finance for
growth within ECOWAS. 2)Evaluate determinants of
private sector credit
Credit Constraints and Development cont’d
• Table 2: Money and Credit
M2 as % of
GDP
Claims on
central
government, etc.
(% GDP)
Domestic credit
to private sector
(% of GDP)
Country
Benin
Burkina Faso
Cote d'Ivoire
Guinea-Bissau
Mali
Niger
Senegal
Togo
Average CFA
2000
29.88
21.13
22.2
42.72
23.68
8.16
23.72
26.75
24.78
2011
40.01
29.57
40.46
40.23
29.72
21.45
40.22
48.52
36.27
2000
-3.7
2.66
7.38
10.23
-2.17
4.39
4.81
6.34
3.74
2011
-2.82
-1.81
7.24
1.73
-4.07
0.56
2.51
5.79
1.14
2000
12.09
11.72
15.5
7.9
16.5
4.8
18.68
16.04
12.9
2011
24.55
19.77
18.06
11.78
21.00
14.18
28.96
29.62
20.99
Cape Verde
Gambia, The
Ghana
Guinea
Liberia
Nigeria
Sierra Leone
64.37
19.8
28.17
11.68
11.64
22.16
16.36
76.98
54.95
30.85
36.41
38.21
33.58
28.66
23.99
0.55
19.28
4.24
170.43
-2.65
51.38
13.56
24.39
10.61
22.82
13.69
1.71
5.92
40.13
6.74
13.97
3.99
3.29
12.46
2.11
64.49
16.33
15.19
9.14
16.44
21.09
10.15
Average Non-CFA
Average Non-CFA
excl. Cape Verde
24.88
42.8
38.17
13.24
11.81
21.83
18.30
37.11
40.54
13.19
7.09
14.72
Credit Constraints and Development cont’d
•
In sum; M2, Claims on gov’t, Private Sector Credit
•
For WAEMU, traditionally low levels of lending to gov’t due to
stringent rules; non-monetization of fiscal deficits.
•
Central Bank is also independent. Thus increases in M2 translates
into private credit relative to gov’t.
•
By contrast: non-CFA countries face no such rules or unified
directives and free to exercise discretion at the national level.
•
Limited central bank independence= frequent monetization of
deficits. Evidence of crowding-out by public sector in Non-CFA
•
Financial repression most severe in Guinea, Guinea Bissau & Sierra
Leone
•
•
Similar proportions of money creation within 2 zones
Excluding Cape V., private credit is higher within WAEMU
•
M2 however low in ECOWAS compared to other emerging
regions; East Asia (China 180%, Malaysia 139%, Singapore 136%)
and L. America (Brazil 74%, Chile 76%, Bolivia 69%).
Growth Model
• Augmented-Solow model as per MRW (1992) expanded
to incorporated private credit to assess:
Does credit spur growth with ECOWAS?
Is HCAccum in presence of increased credit
better for growth?
• An interactive term between credit and HC indicator for
second question. Positive coefficient implies that
augmented credit must occur simultaneously as
investment in HCAccum.
• Empirical Models:
𝑳𝒏𝑹𝑮𝑫𝑷𝒊𝒕 = 𝜶 + 𝜷𝟏𝒊 𝑳𝒏𝑮𝑭𝑪𝑭𝒊𝒕 − 𝜷𝟐𝒊𝑳𝒏 𝒏 + 𝒈 + 𝜹 𝒊𝒕 + 𝜷𝟑𝒊 𝑳𝒏𝑬𝒏𝒓𝒐𝒍𝒊𝒕 + 𝜷𝟒𝒊 𝑳𝒏𝑪𝑹𝑬𝑫𝑰𝑻𝒊𝒕 + 𝜺𝒊𝒕 (𝟏)
𝑳𝒏𝑹𝑮𝑫𝑷𝒊𝒕 = 𝜶 + 𝜷𝟏𝒊 𝑳𝒏𝑮𝑭𝑪𝑭𝒊𝒕 − 𝜷𝟐𝒊 𝑳𝒏 𝒏 + 𝒈 + 𝜹 𝒊𝒕 + 𝜷𝟑𝒊 𝒈𝑳𝒏𝑬𝒏𝒓𝒐𝒍 + 𝜷𝟒𝒊 𝑳𝒏𝑪𝑹𝑬𝑫𝑰𝑻𝒊𝒕 + 𝜷𝟓𝒊 𝑪𝑹𝑬𝑫𝑰𝑻 ∗
𝑬𝒏𝒓𝒐𝒍 𝒊𝒕 + 𝜺𝒊𝒕
(𝟐)
Results with Robust Errors
• Table 3: Panel Growth Results
Analysis & Discussion
• Model 1: Education and credit; similar coeff., positive
and significant at 1%, as per endogenous growth models
• Model 2: M2 is insignificant in driving growth perhaps due
to crowding out. Population growth consistently
insignificant throughout exercise.
• Model 3: Interactive term positive & significant whilst
Credit and Enrol. Are negative. Evidence of
complementarity btw finance and education;
coordinated increase in both required. Fin market
sophistication
Credit
HCAccum.
• Columns A & B for sensitivity analysis, positive quadratic
terms imply positive returns to scale of factors and
supports endogenous theory.
Contextualizing Credit within the ECOWAS
• Thus private sector credit is significant for ECOWAS
growth. HOWEVER….model of credit rationing
Quantity
Demanded
(Q)
Q4
C
A
Q1
Q3
X
S2
D
Q2
B
E
S1
Q2
D1
I2
I1
Lending Rate (i)
Determinants of Credit
• Model presented captures dynamics from
illustration:
𝐶𝑟𝑒𝑑𝑖𝑡𝑖𝑡 = 𝜋 + 𝛿1 𝑅𝐺𝐷𝑃𝑖𝑡 − 𝛿2 𝐿𝑅𝑖𝑡 + 𝛿3 𝐸𝐶𝑅𝑖𝑡 + µ𝑖𝑡
• ECR captures degree of economic diversification,
• -ve ECR coeff.= low divers., less credit
• +ve ECR coeff. = on path to divers., efforts to
increase credit.
• Most economically diverse country in sample (19952010) is Senegal (0.24) and least Nigeria (0.86)
• Similar levels of diversification within 2 zones
• No significant variation of lending rates within
WAEMU countries, thus regression for non-CFA only
Determinants of Credit cont’d
• Table 4: Results with log of Credit
Variables
Constant
LRGDP
LLR
LECR
Exports
Imports
Observations
Wald-statistic
Model (1)
-7.4629
(0.5949)***
1.5564
(0.0598)***
-0.3889
(0.0786)***
0.1689
(0.0737)**
_
Model (3)
-8.6143
(0.5712)***
1.6592
(0.0598)***
-0.2424
(0.0733)***
0.1817
(0.0735)**
_
-0.0038
(0.0012)***
-0.0039
(0.0013)***
_
112
_
89
_
89
_
0.0002
(0.0017)
91
χ2(3)= 1481.58,
(0.000)
χ2(4)=
1499.45,
(0.000)
χ2(4)=
1585.51,
(0.000)
χ2(3)= 1620.78,
(0.000)
Model (2)
-8.3865
(0.5497)***
1.6107
(0.0551)***
-0.2553
(0.0714)***
Model (4)
-8.2459
(0.6121)***
1.6312
(0.0611)***
-0.3012
(0.0819)***
0.19324
(0.0751)**
Discussion
• Expected signs, ECR indicates diversification is under
way which is slow but should increase with credit.
• High interest rates an impediment.
• Diversification= resilience from external shocks
• Model 2 includes exports to test whether increased
exports (or export-oriented countries) yield more credit.
• Coeff. Is negative, significant but small. Credit
substitution effect between limited local sources and
foreign sources in receipt of exports.
• Import variable included to capture ability of local
importers to acquire credit. Variable emerges
insignificant
Conclusion
• Positive growth rates should translate into improved welfare
attainable via PSD
• Thriving private sector required to accelerate momentum and
address socio-economic challenges
• Alleviating credit constraints and promoting growth requires both
increased private credit and Human capital accumulation.
• Study identifies +ve correlation btw central bank independence
and Fiscal discipline. Lesser independence leading to crowdingout of private sector.
• Lending institutions reluctant in face of inadequate information on
borrowers, perceived risk profile, issues of credit control and debt
collection.
• WAEMU operates integrated surveillance bodies of banking
system. Should be emulated by non-CFA
• Findings to be factored in designing policies to encourage the
private sector and unleash its full potential.
MERCI