1. Presented by : Idowu Ayodeji Adetunji
Supervised by: Prof. Liu Ying
June 4th 2013.

3.  The Federal Government of Nigeria aims to make Nigeria
one of the top twenty economies by the year 2020.
 To achieve this aim, the economy must be diversified-
recourse to agriculture.
 Government now aggressively sources for more domestic
and foreign investments into the agricultural sector.
 Though Nigeria has, over the years, attracted huge volumes
of foreign direct investment (FDI).
 Surprisingly, large chunk of these investments escape the
agricultural sector.

4.  Little or no research work has been done to
evaluate “FDI-Agriculture” relationship in Nigeria.
 The few studies that observed this relationship
employed FDI that was obtained in the entire
economy rather than that which was specifically
obtained in the agricultural sector.

5.  To evaluate and forecast the relationship between
the level of productivity in the agricultural sector
relative to the amount of foreign direct investment
that has been obtained in the sector.

6.  The level of agricultural sector output is significantly related
to the level of FDI the sector receives.
 The level of labor generation of the agricultural sector is
significantly related to FDI in the agricultural sector.
 FDI into the agricultural sector and the agricultural sector
output have a complementary long-run relationship.
 Foreign investment inflows to the agricultural sector have a
complementary long run relationship with labor generation
in the agricultural sector.

7.  To understand the link between FDI inflows and
productivity levels of the agricultural sector.
 To uncover channels through which FDI
stimulates the growth and development of
Nigeria’s agricultural sector.
 To identify the policy levers that may be
engineered to maximize both inflows and gains of
FDI into the agricultural sector.

8.  Theory and evidence shows that an agricultural
economy is strategic to national development,
particularly for developing countries (Okorie and
Eboh, 1990).
 Nigeria’s agriculture enjoyed a boisterous era
between the sixties and the seventies but started to
decline soon after the discovery of oil.
 Quantity and quality of government spending is low
(Mogues et al, 2008).

9.  The relationship between FDI and economic
growth in Nigeria is unclear (Ayanwale, 2007).
 Question of the significance and sustainability of
FDI to Nigeria’s economic growth is yet
unanswered.
 Autoregressive models are more robust to detect
the dynamic interactions involved within their
framework.

10.  In order to evaluate and forecast the impact of FDI in the
agricultural sector of Nigeria; the relationship between the
three time series variables from 1980- 2007 was examined
in a vector autoregressive (VAR) environment.
 Data used in this study was obtained from Central Bank
of Nigeria (CBN) statistical bulletin.

11. Figure 1: Sectorial Analysis of Cumulative Foreign Direct Investment in Nigeria

12. We employ a vector auto regression system of three time
series variables; FDI, output and labor. An unrestricted
VAR with lag length p can be expressed as:
Where;
Yt denotes a vector of variables (agricultural output, labor
and FDI),
C represents a vector of corresponding constant terms;
Φ1,…,Φp are matrices of coefficients and,
Ψt is an unobservable zero-mean independent white
noise process.
1 1 ... .................(1)t t p t p tY C Y Y− −= + Φ + + Φ + Ψ

13. Our model consists of three equations. Each variable serves as
the dependent variable in each of the equations while the
regressors are lagged values of all the variables.
1 1 1 1 1
1 1 1
1 1 2 3 .........................(2)
k k k
t j t j j t j j t j t
j j j
Y Y Y Yα β δ ϕ ε− − −
= = =
= + + + +∑ ∑ ∑
2 1 1 1 2
1 1 1
2 1 2 3 .........................(3)
k k k
t j t j j t j j t j t
j j j
Y Y Y Yα β δ ϕ ε− − −
= = =
= + + + +∑ ∑ ∑
3 1 1 1 3
1 1 1
3 1 2 3 ............................(4)
k k k
t j t j j t j j t j t
j j j
Y Y Y Yα β δ ϕ ε− − −
= = =
= + + + +∑ ∑ ∑

14. This was done using ADF to determine the integration
order of the variables. They all had an order: I(1)
1 1
1
...................................(5)
k
t t t i t t
i
y y y yρ λ µ− −
=
∆ =∆ + + ∆ +∑
1 1
1
.........................................(6)
k
t t i t t
i
y y yα ρ λ µ− −
=
∆ = + + ∆ +∑
1 1
1
.................................(7)
k
t t t i t t
i
y y y yα ρ λ µ− −
=
∆ = + + + ∆ +∑
1Where is the first difference of the series; , and are parameters to be estimated
while is a stochastic disturbance term.
ty t ty y ρ λ
µ
−∆ = − µ

15. This was done using JJ max likelihood to obtain the
number of co-integrating vectors.
( )1
ˆln 1 .................................................(8)
n
trace i
i r
Tλ λ
= +
= − −∑
( )max 1
ˆln 1 ........................................(9)rTλ λ += − −
max
1
Where is the trace statistic, is the eigen max statistic,
ˆ denotes the smallest Eigen values, and is the sample size.
traceλ λ
λ
−
− Τ

16. LOG (FDI) LOG (LABOR) LOG (OUTPUT)
Mean 6.163550 9.437671 11.17186
Median 7.097342 9.440102 11.42612
Maximum 7.192859 9.448491 11.84764
Minimum 4.764735 9.418330 9.975622
Std. Dev. 1.076626 0.007886 0.593251
Skewness -0.342763 -1.045413 -0.809189
Kurtosis 1.247110 3.199716 2.309315
Jarque-Bera 4.132996 5.146683 3.612223
Probability 0.126628 0.076280 0.164292
Sum 172.5794 264.2548 312.8119
Sum Sq. Dev. 31.29634 0.001679 9.502557
Observations 28 28 28
Table 1: Descriptive Statistics of Data

17. Table 4.1.3 Unit Root Test at stationarity at First difference
Variable Statistic ADF None ADF Intercept ADF Trend &
Intercept
ln(output) 5% sig level -1.9654 -2.9810 -3.5950
ADFα -2.1368 -5.8028 -6.3071
Probability 0.0340 0.0001 0.0001
Ho: D(lnoutput) has a unit root
Variable Statistic ADF None ADF Intercept ADF Trend &
Intercept
ln(labor) 5% sig level -1.9544 -3.0049 -3.6450
ADFα -2.4680 -0.9926 -14.752
Probability 0.0158 0.7373 0.0000
Ho: D(lnlabor) has a unit root
Variable Statistic ADF None ADF Intercept ADF Trend &
Intercept
Ln(FDI) 5% sig level -1.9544 -2.9810 -3.5950
ADFα -4.6297 -5.0351 -4.9915
Probability 0.0101 0.0004 0.0024
Ho: D(lnFDI) has a unit root
Table 2: Unit Root Test for stationarity at First difference

18. Table 4.1.4.1 Unrestricted Cointegration Rank Test (Trace)
Hypothesized No.
of CE(s) Eigenvalue Trace Statistic 0.05 Critical Value Prob.**
None * 0.768647 51.24535 29.79707 0.0001
At most 1 0.441895 14.65010 15.49471 0.0667
At most 2 0.002792 0.069893 3.841466 0.7915
Trace test indicates 1 cointegrating eqn(s) at the 0.05 level
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values
Table 4.1.4.2 Unrestricted Cointegration Rank Test (Maximum Eigenvalue)
Hypothesized No.
of CE(s) Eigenvalue Trace Statistic 0.05 Critical Value Prob.**
None * 0.768647 36.59525 21.13162 0.0002
At most 1 * 0.441895 14.58020 14.26460 0.0446
At most 2 0.002792 0.069893 3.841466 0.7915
Max-eigenvalue test indicates 2 cointegrating eqn(s) at the 0.05 level
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values
Table 3: Unrestricted Co-integration Rank Test (Trace)
Table 4: Unrestricted Co-integration Rank Test (Maximum Eigenvalue)

19. Figure 2: AR Roots of Characteristic Polynomial

20. Lags LM-Stat Prob
1 11.64723 0.2339
2 14.11512 0.1183
probs from chi-square with 9 df
Table 5 shows results of residual test, we fail to reject Ho to further confirm there is
no serial correlation of the residuals.
Source: Author’s estimation from E-views 5.1
Table 5: Residual Test
Ho: no serial correlation at lag order h

21. Figure 3: Response of LNFDI to LNFDI

22. Figure 4: Percent LNFDI variance due to LNFDI

23. Figure 5: Response of LNLABOR to LNFDI

24. Figure 6: Percent LNLABOR variance due to LNFDI

25. Figure 7: Response of LNOUTPUT to LNFDI

26. Figure 8: Percent LNOUTPUT variance due to LNFDI

27.  FDI inflows is not significant on output of the
sector.
 FDI inflows is significant on labor generation.
 FDI inflows does not have a complimentary long-
run relationship with output of the sector.
 FDI inflows has a complimentary long-run
relationship with labor generation.

28.  There is a very low level of FDI that is obtained in
the agricultural sector of Nigeria.
 Bottlenecks that lead to high costs of doing
business should be removed.
 Policies geared towards FDI should be open.
 The availability of FDI would help to provide
resources which are lacking in the sector.

29.  More FDI should be sought for the agricultural sector.
 Focus should be on attracting FDI that seeks to enhance domestic
capacity or domestic investment.
 FDI that is able to generate spillover effects in the entire value chain
of the agricultural sector should be targeted.
 Research and development (R & D) institutions such as universities
should be better funded so that new innovations can be created.
Overall, government is urged to run agriculture strictly as a business
and not as a developmental programme.

30. Thank you

31. Thank you

32. Thank you