Public Private Partnerships in Sub-Saharan Africa: A Policy Framework AnalysisChristopher Jackson Moore Conference 2016, College of Charleston Department of Political ScienceAdvisor: Dr. Christopher DayPanel 6

What is PPP and why does it matter?

Brief Overview of PPP

➔ Public Private Partnership

➔ Means to provide infrastructure services

➔ Particularly interesting for developing countries

Research Question

PPP Policy Framework = PFA

Does the Adoption of Public Private Partnership Policy Frameworks (PFA) Increase the Viability of Infrastructure-Based PPP Projects in Sub-Saharan African Countries?

Existing Literature

PFA = Success

What about Sub-Saharan Africa?

PPP Data in Sub-Saharan Africa Very limited → affected variable selection World Bank endorsed PPP Database High internal validity; lower external validity Local reporting of data cannot have any accuracy

guarantees Drew from Quality of Government Database

Variables: Defining Viability

Independent Variable

Policy Framework Adoption (PFA)-Governmental policies-Inclusion of segmented policies

Dependent Variable*

Indicators of Viability (IOV)

1.Change in Project Number from Year to Year (+∆Nx)

2.Total number of projects (Nx)

3.Multilateral Cooperation (MC)

*Variable constraints due to data limitations

Methodology1.Logistic Regression2.Linear Regression3.Simple Percentage Test

Why? -- verify claims on PFA in SSA

Quantitative Methods

Summary of Proposed Causal Relationships

PFA – Independent

Variable

IOV 1: ∆Nx – Dependent

Variable

IOV 2: SA (Nx)- Dependent

Variable

IOV 3: MC – Dependent

Variable

PFA Occurs ∆Nx will be positive after PFA (+∆Nx)

Total Nx in given country is increased

Endorsement from multilateral

organization

Absence of PFA ∆Nx will equal 0 or be negative

Total Nx is comparatively

lower

No endorsement from multilateral

organization

General Hypothesis: Hmain

If PFA occurs in a Sub-Saharan country, the viability of PPP projects will be bolstered in that country.

33.1%PFA has no effect on Validity

Hypothesis 3

Hmain Accept the null hypothesis:

The adoption of a policy framework (PFA) suggests no statistically significant effect on PPP viability

Implications

PFA may be wasteful and inefficient

Literature on PPP and policy frameworks may not hold in Sub-Saharan Africa

Why do we see this result?

Lack of transparencyWeakness of African legislative authority Neoliberal tendency to replicate regimesQuestion of the chicken or the egg?

Future ResearchSuggestions and

Speculation

Based on H1 and H2 results, income may have something to do with it: chicken or the egg?

Adopt new approach: redefine viability; if PFA isn’t responsible, what is?

Why does it matter?

→ The global community wants to see Sub-Saharan African development. Answering the PPP question may help to accomplish this goal.

Acknowledgements:Dr. Christopher Day (Advisor)Dr. Karyn Amira (Secondary Reader and Quantitative Methods Support)

Q&AFor more information on datasets, statistical output, or PPP in

general, please contact me:

Christopher Jacksonjacksoncw@g.cofc.edu

704-609-2987

Photograph URLs

http://blogs.worldbank.org/publicsphere/files/publicsphere/ppp_mooc.jpg

http://businessfacilities.com/wp-content/uploads/2015/06/public-private.jpg

https://upload.wikimedia.org/wikipedia/commons/6/65/Sub-Saharan_Africa_definition_UN.png

http://images.indianexpress.com/2015/09/airport.jpg

Hypothesis 1 (H1)

If PFA occurs in a country in year X, Nx in that country will increase (+∆Nx).

H1 Dataset Sample

Country Unit

of Analysi

s

Financial

Closure Year

Nx ∆Nx PFA* Income

Group 1**

Income Group

2

Income Group

3

Imf_gd+

Angola 2001 1 0 0 0 1 0 .16

Angola 2003 1 0 0 0 1 0 .16

*PFA: 0 indicates absence of PFA; 1 indicates PFA occurred

**Income Group Key: Lower income; Income Group 2: Lower middle; Income Group 3; Upper middle (0 indicates criteria not met; 1 indicates criteria met)+imf_gd: Amount of debt owed to IMF as expressed as percent of GDP; scaled to 0-1 scale for consistency

Hypothesis 2 (H2)

If PFA occurs in a given country at any point, the total number of PPPPs in that country will increase

H2 Dataset Sample

Country (Unit of

Analysis)

Nx1990

-2015

Nx1990-2015

ScaledPFA*

Income Group

1**

Income Group

2

Income Group

3

Aid_crnio

scaled+

Angola 9 0.1 1 0 1 0 0.15

Benin 5 0.05 1 1 0 0 0.08

Botswana 3 0.02 1 0 0 3 0.62

*PFA: 0 indicates absence of PFA; 1 indicates PFA occurred

**Income Group Key: Lower income; Income Group 2: Lower middle; Income Group 3; Upper middle (0 indicates criteria not met; 1 indicates criteria met)+aid_crnio: rescaled to 0-1 scale; max value=13; min value=0

Hypothesis 3 (H3)

If PFA occurs, there will be a higher probability that MC occurs as well

H3 Dataset Sample

Project (Denoted by Country) YMC* YPFA** YMC ≥ YPFA+

Benin 2002 2002 1

Burkina Faso 2001 2009 0

Cameroon 2000 2006 0

Cameron 2006 2006 1

*YMC=Year of Multilateral Cooperation

**YPFA=Year of PFA

+YMC≥YPFA= Does MC occur after PFA? Yes=1; No=0