ppt for seminar

1. Title: The Nexus between Corruption and Economic
Growth in Sub-Saharan Africa
BY: Urgessa F
Advisor: Abdella M(PhD)

2.  Background of the Study
 Statement of the problem
 Objectives of the seminar
 Methodology
 Result and Discussion
 Conclusion and Recommendation

3.  One of the most dangerous social ills for many society, which eats the political and
economic growth of any country and as well abolishes the functioning of various
societies organs is called corruption(Mongi & Saidi, 2023).
 Corruption is a base for all the ills of a nation which weakens the foundation and the
economic performance of a country.
 Misuse of public office for personal benefit is a valid explanation for public corruption
and
 Corruption include things like bribery and misappropriation of public funds, kickbacks
in public procurement, and the sale of government property by officials (Acaravcet al.
2023; Anh et al., 2016; Azam, 2022;Ghauri et al., 2022; Svensson, 2005).

4.  Several-socio-economic issues like poverty, inflation,
unemployment, income inequalities, and commercial limitations
are the well-known factors that cause corruption (Akçay, 2001).
 Sub-Saharan Africa (SSA) has facing continues economic
hardships until today than other continents, because of sluggish
economic expansion, high rates of joblessness, extensive/rampant
corruption, and rise of the general consumer price index
(Ndoricimpa, 2017; Seleteng et al., 2013; Van Eyden et al.,
2015)

5.  Theoretically, the literature do not reaches on agreement about the effect of
corruption on economic growth.
 The finding of many studies on the impact of corruption on economic growth
is contradictory.
 Some papers indicate that corruption can important for economic growth as
supporting “the grease of the wheels” hypothesis whereas, many scholars
argues that corruption harms economic growth and firms’ performance that
supports the “sands of the wheels” hypothesis.

6.  Corruption works like piece/portion rate pay for bureaucrats , induces
/encourage a more efficient provision of government services, and it
provides a leeway/freedom for entrepreneurs to bypass inefficient
regulations (Dreher & Gassebner, 2013)
 From this perspective, corruption acts as a lubricant that smoothers
operations and, hence it raises the efficiency of an economy.
 Gazdra(2010) stated that there is a positive relationship between corruption
and Economic growth, when the quality of governance is very low

7.  Further scholars support the grease of the wheels hypothesis, for instance
some researchers like (Houston, 2007; P. G. Méon & Sekkat, 2005; P. Méon
& Weill, 2008) continue to argue that corruption may be economically
justified as it provides opportunities to avoid inefficient regulations and red
tape, and allows the private sector to correct government failures and
inefficiency.
 On the other side, the advocators of “sands of the wheels” believe that
corruption is an obstacle to economic growth and development (Aidt,
2009; Amoh et al., 2022; Bardhan, 2017; Ibrahim et al., 2015; Mohammed et
al., 2022; Sharma & Mishra, 2022).

8.  Employed the fixed effect and random-effects model, Mohammed et
al.(2022) had studied about the organized crime, corruption and their
challenges to the economic growth of the Economic Community of West
African States (ECOWAS) by using time series data from 2000 to 2019
and finds that corruption significantly reduces economic growth.
 Shittu et al. (2018) conducted study on the impact of external debt and
corruption on economic growth in the selected five Sub-Saharan African
(SSA) countries, from 1990 to 2015 and
 The result of fully modified OLS and dynamic OLS techniques shows a
positive relationship between corruption and economic growth in five
SSA.

9.  Even though there is growing attention to the issue of corruption and
economic growth, there is a contradiction or inconclusive result forwarded
from different researcher regarding the relationship between corruption and
economic growth as a general and in SSA in particular.
 Further as far as my knowledge is concerned, there is limitation of study in
the Sub-Saharan African (SSA) related to corruption and economic growth
 In this study, for addressing the gabs and endogeneity problem that did not
addressed in past studies, the System Generalized Method of Moments
(SGMM) model used for analyzing the dynamic panel data for 40 SSA
countries.

10.  This SGMM model also provide efficient estimates and allow us to examine
the impacts of corruption, on economic growth, as well as the combined
effect of corruption and Unemployment on economic growth, by accounting
the time varying effects and control for unobserved heterogeneity across
countries.
 Thus, this study investigates the nexus between corruption and economic
growth in SSA by using dynamic panel data of forty(40) SSA countries from
2008-2022 and tried to filled the gap that did not covered by former studies.

11.  The general objectives of Seminar- is to analyze the relationship between
Corruption and Economic Growth in Sub-Saharan Africa.
 The specifically the seminar is aims to:
 To examine the effect of corruption on economic growth in SSA.
 To analyze the interactive effect of Corruption and Unemployment on
Economic growth in SSA
 To provides the empirical evidence that can inform policymakers and
stakeholder in designing effective strategies to address the issues of
corruption in SSA with the aim of promoting economic growth.

12.  Description of Variable, their measurements and Sources
Variables Discribtions Measurements Expecte
d Sign
Source
Gross Domestic
Product per capita
(GDP pc)- is dpv
This gross domestic product per capita, is a measure of the
economy’s output per population of the countries
current US$ WDI
Corruption (CPI) The level of corruption perception index, measured using the
index such as corruption perception index (CPI)
Estimated +/- TI
Unemployment (UN) The unemployment rate represents the percentage of labor
force that is actively seeking employment but unable to find it
% of total labor
force) (modeled
ILO estimate
- WDI
Inflation (INF) The inflation indicates that the continuous rises of the general
price level of a commodities or goods and service over a period
of time
consumer prices
(annual %)
-/+ WDI

13. Political stability
and absence of
violence (PS)
PS is a situation in which a notions or regions
live in peaceful and secure the political
environments without civil war, armed conflicts,
political upheavals and any other part of
violence.
Estimated + WGI
Government
effectiveness (GE)
It shows the quality of public services, quality of
policy formulation and implementation, the
degree of independence from political pressures,
and the competence of the civil service
Estimated + WGI
Foreign direct
investment (FDI)
The FDI is the capital accumulation or investment
engaged by investors of abroad country and flow
in to another country
net inflows (% of
GDP)
+/- WDI
Countries legal
system (LSD
The legal law system (LSD) is dummy variable is
represented a value of 1 for civil law and 0 for
other legal systems
dummy +/- Countries
Websites
Note: WDI-represent World Development Indicators
TI-represent Transparency international
WGI -represent World Governance Indicators

14.  The System GMM model is designed for situations with N>T (small T
which is 15 years in this study and large N, which is 40 SSA ) are
required, and
 The independent variables do not have to be strictly exogenous, which
means that they are correlated with past and possibly current realizations
of the error term, and also system GMM overcomes the problems of
heteroskedasticity, autocorrelation and fixed effects within individuals
 The model specification using the system -GMM involves incorporating
lagged variable and instrumental variables to address the potential
endogeneity issue.

15.  According to the former researcher Roodman (2009) the model of system GMM can be
estimates as the following dynamic panel data model:
𝒚𝐢𝐭 = 𝒋=𝟏
𝒑
𝜶𝒋 𝒚𝐢𝐭−𝒋+𝛃𝟏𝑿𝐢𝐭+𝛃𝟐𝒘𝐢𝐭+𝒗𝒊+𝛆𝐢𝐭-------eq (1)
Where 𝜶𝒋 are 𝑝 parameters to be estimated/autoregressive(persistence) parameter
 𝒚𝐢𝐭−𝒋 is lagged dependent variable(endogenous by construction) and correlated with the
unobserved panel-level effect.
 𝑿𝐢𝐭 is the vectors of exogenous variables
 𝒘𝐢𝐭 is the vectors of predetermined or endogenous variables
 𝛃𝟏 𝒊𝒔 parameters to be estimated for exogenous variables
 𝛃𝟐 𝒊𝒔 parameters to be estimated for predetermined or endogenous variables
 𝒗𝒊 are panel level effect/fixed effect error term, which may be correlated with the
covariates and 𝛆𝐢𝐭 is iid, disturbance term

16. Then from the above equation (1)
𝐆𝐃𝐏𝐩𝐜𝐢𝐭 = 𝛃𝟏𝐆𝐃𝐏𝐩𝐜𝐢𝐭−𝟏+𝛃𝟐𝐂𝐏𝐈𝐢𝐭+𝛃𝟑𝐔𝐍𝐢𝐭+𝛃𝟒𝐈𝐍𝐅𝐢𝐭+𝛃𝟓𝐅𝐃𝐈𝐢𝐭+𝛃𝟔𝐆𝐄𝐢𝐭+𝛃𝟕𝐏𝐒𝐢𝐭+
𝛃𝟖Dit+𝛆𝐢𝐭--eq (2)
 Where: 𝐆𝐃𝐏𝐩𝐜𝐢𝐭= is represent the economic growth in country i at time t
 𝐆𝐃𝐏𝐩𝐜𝐢𝐭−𝟏= is the lagged value of economic growth to capture the dynamic effects
 𝐂𝐏𝐈𝐢𝐭= is level of corruption perception index in country i at time t
 𝐔𝐍𝐢𝐭= is represent the unemployment rate in country i at time t
 𝐈𝐍𝐅𝐢𝐭= is the inflation rate in country i at time t
 𝐅𝐃𝐈𝐢𝐭= is represent the foreign direct investment inflow in to country i at time t

17. 𝐆𝐄𝐢𝐭= shows the government effectiveness in country i at time t
 𝐏𝐒𝐢𝐭= indicates the political stability and absence of violence in
country i at time t
 𝐃𝐢𝐭 = is a dummy variable
as
1 𝑖𝑓 𝑡ℎ𝑒 𝑙𝑒𝑔𝑎𝑙 𝑠𝑦𝑡𝑒𝑚 𝑜𝑓 𝑡ℎ𝑒 𝑐𝑜𝑢𝑛𝑡𝑟𝑦 𝑖 𝑖𝑠 𝑐𝑖𝑣𝑖𝑙 𝑙𝑎𝑤 𝑎𝑛𝑑
0 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒 𝑖. 𝑒; 𝑐𝑜𝑚𝑚𝑢𝑛𝑎𝑙, 𝑑𝑢𝑎𝑙, 𝑚𝑖𝑥𝑒𝑑
 𝛃𝟏 , 𝛃𝟐 , 𝛃𝟑 , 𝛃𝟒 , 𝛃𝟓 , 𝛃𝟔 , 𝛃𝟕 ,and 𝛃𝟖 = are parameters and
𝛆𝐢𝐭= is error term

18.  The following table presents the results of two different SGMM panel data
estimation techniques, but for this study the two step SGMM was accepted based on
the results and efficiency of the two step SGGM estimators. This table shows
absence of autocorrelation and Validity of the model
Arellano-Bond-test for
AR(1)
One step SGMM
P-value =0.050
Two step SGMM
P-value =0.00
Arellano-Bond test
for AR(2)
P-value =0.141
P-value =0.759
Sargan test of overid
restrictions
P-value = 0.257
P-value =0.278

19.  According to the Arellano-Bond tests, there isn't autocorrelation test
AR(2) in the model means that no second-order autocorrelation,
since the P-value is greater than 0.05 which is a P-value =0.759
 The Sargan test of over identification restrictions show that model's
instruments are valid, on the other hands we cannot reject the Null
hypothesis, since P-value =0.278 is greater than 0.05, so that the
instruments used in the model are valid.

20. Dependent variable: GDPpc in natural logarithm(lnGDPpc)
Explanatory variables One step System GMM Two step System GMM
LlnGDPpc 0.60424
(0.00**)
0.7532
(0.00**)
CPI -0.0022
(0.2310
-0.0337
(0.04**)
UN 0.03332
(0.00**)
-0.0033
(0.881)
INF -0.0004
(0.027**)
0.00054
(0.352)
FDI 0.00303
(0.576)
0.01305
(0.037**)
GE 0.30818
(0.00**)
0.75696
(0.002**)
PS 0.00214
(0.894)
-0.0401
(0.633)
CPI*UN -0.0002
(0.05**)
0.00052
(0.255)
LSD -0.0474
(0.03**)
0.51927
(0.064*)
Cons 2.86426
(0.00**)
3.10103
(0.00**)

21.  The coefficient of the LlnGDPpc is about 0.7532 (0.00**), this means that ceteris
paribus, a one unit increases in LlnGDPpc leads to a 75.32% unit increases in the
current year value of Economic growth in the SSA, and it is significant at 5%.
 This shows that there is a high persistence or memory in the Economic growth.
 The value of coefficient of CPI is -0.0337(0.04**) which shows the negative
relationship between the GDPpc and CPI in SSA, means that a one unit increase in
CPI associated with a 3.37% decreases in GDP per capita of the SSA countries,
holding other variables constants. And the result also show the effect of CPI on
GDP per capita is significant at 5%
 The coefficient value of UN is -0.0033(0.881), which shows that the one unit
increase in UN lead to a 0.337% decreases in GDP per capita of the SSA countries,
holding other variables constants, but this result is not significant on the Economic
growth of the region.

22.  The coefficient value of INF is 0.00054 (0.352), ceteris paribus, a one unit increasing
of INF leads to a 0.054% unit increase in the value of Economic growth in the SSA, but
this is not significant
 CPI*UN 0.00052(0.255), this reveals that the interaction of CPI&UN is positively affect
the GDPpc of SSA countries
 LSD is 0.51927(0.064*) this reveals that , ceteris paribus, being a Civil law legal system
country compared to the Mixed law legal system country is a 51.9269% more of
GDPpc, this means that the countries with a Civil law legal system(coded as 1) have on
average a 0.51927 unit higher lnGDPpc compared to a countries with a Mixed law legal
system (coded as 0), and it’s significance level is 0.064 which is slightly significant at
10% 0f significance level.

23. Conclusion:-
 The dynamic panel data was used in order to address the Primary objective and
specific objective of the seminar that intended to analyze the relationship
between Corruption and Economic Growth in 40 Sub-Saharan Africa countries.
 The data was collected from World Bank data set via online, from 2008 -2022
and filled the time gaps that did not covered by former studies.
 The SGMM model was used in order to capture the short term and long-term
relationship between the variables
 Since the lagged dependent variable which can create endogeneity issue was
incorporated in the explanatory variables
 so two step SGMM is very important for provide efficient estimates and allow us to
examine the impacts of corruption, on economic growth, as well as the combined effect
of Corruption and Unemployment on growth, by accounting the time varying effects
and control for unobserved heterogeneity across countries.

24.  The result of two step SGMM shows that, Corruption is negatively affect the SSA
countries economic growth or which indicates that there is a negative relationship
between the economic growth and Corruption in SSA countries
 Or it means that a one unit increase in CPI associated with a 3.37% decreases in
GDP per capita of the SSA countries, holding other variables constants. And the
result also shows that the effect of CPI on GDP per capita is significant at 5%.
 However the result show that corruption and unemployment jointly increase the
SSA economic growth, which means that there CPI*UN 0.00052(0.255), this
reveals that the interaction of CPI&UN is positively related to the GDPpc of SSA
countries.
 The study also show that there are other independent variables which positively
affect the SSA growth such as FDI, GE, LSD and INF

25. Based on the findings the following recommendation was forwarded;
 In most SSA countries, Corruption is one of the major factors that hinder the
economic growth in the region, so effective governing system that can
reduce corruption should be constructed in the region in order to address
corruption and promote economic growth in SSA.
 The effective government system can strengthening governance, improving
transparency and accountability, and implementing anti-corruption
measures.
 Unemployment is major economic variable that can affect growth in SSA,
this unemployment even can be happen because of the corruption in the
area, so all concerned body have to see this issues in serious and try to boost
the economic growth in the SSA.

26.  The FDI plays a key role for economic relation and growth by
providing job opportunities, technologies and markets for the SSA
countries
 so the government should increases the investment engaged by investors of
abroad country and flow in to a home country for economic growth of SSA
 The SSA countries have to effectively work on the Political stability,
Government effectiveness and on their legal system in order to
reduce corruption and increases economic growth

27. Thank you
for your attention