The commercial benefits for Japan
of its aid to Asia
Sabit Amum Otor
ANU graduate and Research Associate at the
Development Policy Centre
1
1. INTRODUCTION




The core objective of official development assistance (ODA)
is to promote sustainable economic development of the
recipient country.
But the strategic and commercial goals of donors are also
recognized to be important for aid.
Commercial impact of aid is possible through tying of aid
(including “informal” tying) and through creation of
“goodwill” and “habit formation”
But most studies focus on the development impact of aid.
There are only a few on the commercial impact of aid.
2
1. INTRODUCTION (CONT.)




There are several studies on the trade impact of European
aid, but only one that includes Asia.
They have mixed results, but several studies find:
 positive impact of own-country aid on its trade.
 negative impact of other-countries aid on the country’s
trade.
The study by Nowak-Lehmann and his colleagues (N-L,
2009) on the impact of German aid on its exports is the
model for this paper.
N-L find:
$US1 of German aid has an average return of $US 1.04-1.50
in exports.
 aid from other European countries crowds out German exports
 ODA causes exports not vice versa

3
1. INTRODUCTION (CONT.)


I use the same methodologies as N-L to ask the same
questions of Japanese exports and aid to Asia.
Japan is of interest because

It is a major donor.



In 2010, Japan disbursed about US$11 billion of foreign aid to developing
countries. About 67 percent of this amount was allocated as bilateral aid.
Japan's bilateral ODA has been concentrated in Asia.
Wagner (2003) the only study to examine Japan (and other
major donors)
Finds an average return for Japan from aid on trade of $US
1.20
 Only looks at short-run, and study now out of date.

4
2. RESEARCH QUESTIONS
This study investigates:
 the short-and long-run effects of Japan’s ODA on
Japan’s exports to the recipient countries
 the short-and long-run effects of DAC ODA
(excluding Japan ODA) on Japan’s exports to the
recipient countries
 the causal relationship between Japan’s ODA and
Japan’s exports to the recipients
5
3. METHODOLOGY
Like N-L, this study uses a gravity model of international
trade, and applies two different econometric techniques:



Dynamic Ordinary Least Squares: to get long-run estimates
Error Correction Model: to get short-run and long-run estimates,
to provide a robustness test, and to test for Granger causality
Data from Japan and15 recipient countries of
Japan’s ODA in Asia (including West Asia),
during the period between 1972 and 2008


The sample includes Bangladesh, Bhutan, India, Indonesia, Lao,
Lebanon, Malaysia, Maldives, Myanmar, Nepal, Pakistan,,
Philippine, Thailand, Sri Lanka and Syria.
Focus on Asia because it is a major recipient of Japanese aid; and
because of data limitations
6
3. METHODOLOGY (CONT.)


The gravity model states that the trade between two
countries is explained by their gross domestic products and
populations, by the distance between their two economic
centres, and by country-pair fixed factors that impede or
facilitate trade such as whether two trading partners have
trade agreements, common language, and common border;
and whether one or both of them have had a colonial history.
For my research purposes I also include own-country and
other-country aid to the recipient as an explanatory variable
for own-country exports to the recipient.
7
4. RESULTS

Panel unit root and co-integration tests:
The unit root tests show that the variables in levels are not
stationary, but the first-differenced of the variables are
stationary. The test for co-integration shows that there is
convincing evidence of co-integration relationship among the
data series. This means that we can use the DOLS (Dynamic
Ordinary Least Squares) and the ECM (Error Correction
Model).
Weak exogeneity test (to address the issue of endogeneity):
The test shows that the dependent variables (except for
exports) are weakly exogenous. This means we can use ECM
(Error Correction Model) to explain exports.
Note: the DOLS method produces good results even some or all
of regressors are endogenous.

8
4. RESULTS (CONT.)
Summary results: The return of Japanese and
other DAC aid on Japanese exports (USD)
Average return on bilateral aid (Japan)
Average return on other DAC bilateral aid (Japan
excluded)
Total average return on bilateral aid (Japan +
other DAC countries)
Long-run
DOLS ECM
1.2
1
Shortrun
ECM
1
2.2
1.4
0.2
3.4
2.4
1.2
Summary results reported using favoured model version controlling for
heteroscedasticity and serial correlation, but all versions for each
technique give similar results. All aid coefficients significant at 10% level,
except for short-run other DAC.
9
4. RESULTS (CONT.)
Tests for Granger causality show that in both the short
and long-run, Japanese aid causes exports but not vice
versa.
Dependent
variable
Source of causation (independent variable)
Short run
LEXPJAP
Long run
LAIDJAP
ECT
Joint (ECT and
LEXPJAP)
LEXPJAP
-
LAIDJAP
0.13
4.41***
-
-0.26***
-
0.04
0.23
Joint
(ECT
and LAIDJAP)
18.69***
-
10
5. CONCLUSION
Impact of Japanese ODA on Japanese exports
 Japan’s ODA has positive and significant impact on
Japan’s exports to Asian countries
 These impacts are not only limited to the short-run, but
are larger in the long-run.
 These results are similar to Wagner for Japan for the
short run (Wagner: $US 1.20; Otor: $1.00)
 These results are also similar to those of N-L for
Germany (cf: N-L, Germany: $US 1.04-1.50 v. Japan:
$US 1.0-1.80 [for long-run])
 We also find that an increase in Japanese ODA causes
an increase in Japanese exports, but not vice versa.
11
5. CONCLUSION (CONT.)
Impact of other-DAC country ODA on Japanese
exports
 ODA from other DAC donors also has positive and
sometimes significant impact on Japan’s exports to
Asian countries
 These impacts are not evident in the short-run, but are
very large in the long-run.
 These results are different to those of N-L for Germany
and also studies of Switzerland (Zarin-Nejadan 2008),
which mainly find either complete or partial crowding
out of other-country ODA on own-country exports.
 Unclear why we get a different result. May rest on large
commercial benefits for Japan from aid-induced Asian
development
12
5. CONCLUSION (CONT.)
Summary
This research supports other findings that owncountry aid does increase own-country exports.
 It also suggests, though less clearly, that othercountry aid increases own-country exports, but
this seems to vary from country to country.
 Given the increasing interest in aid for trade in
Australia, it would be useful to conduct a similar
analysis for Australian aid and trade.

13
THANK YOU
And happy to take your comments
and questions
14
APPENDIX 1
The gravity model of international trade:
EXPij   0GDPi 1 GDPj
2
POPi
3
POPj
4



DISij 5 Fij 6 MRij 7  ij
(1)
Following the recent literature, I included the exchange rate
and ODA for both Japan and other major donors (Japan
excluded) variables into the equation (1), and then
transformed into log-linear form. After restricting   
 3   4 and The equation (1) can be written as
1
2
log(EXPijt )   0  1 log(TGDPt )   2 log(TPOPt )   3 log(EXCH jit )   4 log( AIDJAPijt ) 
 5 log( AIDDACkjt )  ij   t   ijt
(2)
APPENDIX 2
Dynamic Ordinary Least Squares (DOLS)
 This model was proposed by Kao and Chiang ( 2000). They
propose regressing the dependent variable onto
contemporaneous level regressors, lags and leads of the first
differences, and a constant using ordinary least squares
log(EXPijt )   0   ij   t  1 log(TGDPt )   2 log(TPOPt )   3 log(EXCHijt ) 
p
 4 log(AIDJAPijt )   5 log(AIDDACyjt ) 
   log(TGDP
t s )
s
s  p
p
   log(EXCH
s
s  p
p
ji,t  s )

   log(AIDJAP
s
s  p
ij,t  s )
p

   log(TPOP
s


s  p
p

t s )
6  log(AIDDACyj,t  s )
  ijt
(3)
s  p
This estimation technique produces unbiased estimates even when some or
all regressors are endogenous
16
APPENDIX 2 (CON.)
Dynamic Ordinary Least Squares (DOLS)
This model was proposed by Kao and Chiang ( 2000). They propose
regressing the dependent variable onto contemporaneous level regressors,
lags and leads of the first differences, and a constant using ordinary least
squares.

log(EXPijt )   0   ij   t  1 log(TGDPt )   2 log(TPOPt )   3 log(EXCHijt ) 
p
 4 log(AIDJAPijt )   5 log(AIDDACyjt ) 
   log(TGDP
t s )
s
s  p
p
   log(EXCH
s
s  p

p
ji,t  s )

   log(AIDJAP
s
s  p
ij,t  s )
p

   log(TPOP
t s )
s

s  p
p

   log(AIDDAC
6
yj,t  s )
  ijt
(3)
s  p
This estimation technique produces unbiased estimates even when
some or all regressors are endogenous
17
APPENDIX 2 (CON.)
Weak Exogeneity and Causality Tests
LEXPijt



LTGDPijt 
LTPOP

ijt


LEXPijt



LAIDJAPijt 
LAIDDAC 
ijt 

 1 
 
 2
3 
 
4 
5 
 
  6 
1 
 
 2
 3 
 
 4 
 
 5
 6 
ECTt 1 
 ij1 
 
 ij 2 
 
 ij 3  
 ij 4 
 
 ij 5 
 
 ij 6 
 1ijt 


 2ijt 
 
 3ijt 
 4ijt 


 5ijt 


 6ijt 
 t1 
 
 t2 
 t 3 
 
 t 4 
 
 t5 
 t 6 
 11s  12 s  13s  14 s  15s  16 s 


 21s  22 s  23s  24 s  25s  26 s 
p 
 31s  32 s  33s  34 s  35s  38s 










41
s
42
s
43
s
44
s
45
s
46
s
s 1
      
 51s 52 s 53s 54 s 55s 56 s 
 61s  62  63s  64 s  65s  66 s 

LEXPijt s



LTGDPijt s 
LTPOP

ijt s


LEXPijt s



LAIDJAPijt s 
LAIDDAC 
ijt s 

(4)
The test for the null hypothesis (in each equation) that against
the alternative that using t-test. If the estimated coefficient of
the lag of equilibrium residual variable is insignificant (i.e.
fail to reject the hull hypothesis), then the dependent variable
of that equation is weakly exogenous.
18
APPENDIX 2 (CON.)
ECM
LEXPij,t  1
  ij1  t1 
3
  z
s 0
1s
ij ,t  s

1ij,t (6)
1LEXPij,t 1  10  1ij  1 t  11zij,t 1 
Note: By comparing equations (5) and (6) it is easy to
derive estimated coefficients of the variables in
equation (5) from estimated coefficients of equation
(6).
The equation (6) is estimated with 3 lags. And after
applying the General-to-Specific technique we
reported the estimated results of this equation in
Table (6).
19
APPENDIX 3
RESULTS
Unit Root Test:
Two tests: the first test was proposed by Breitung (2000), and the second was proposed by Choi
(2001)
Breitung
Statistic
Fisher-ADF
Prob
Statistic
Prob
-3.56***
-0.60
-0.70
2.70
0.71
0.21
0.00
0.28
0.24
1.00
0.76
0.58
-16.34***
-10.69***
-1.95**
-10.33***
-21.40***
-16.37***
0.00
0.00
0.03
0.00
0.00
0.00
Level
LEXP
LTGDP
LTPOP
LEXCH
LAIDJAP
LAIDDAC
1.21
2.19
-10.86***
1.59
-2.66***
1.80
0.89
0.20
0.00
0.94
0.00
0.96
First-difference
ΔLEXP
ΔLTGDP
ΔLTPOP
ΔLEXCH
ΔLAIDJAP
ΔLAIDDAC
-8.22***
-2.43***
4.32
-9.87***
-11.93***
-9.98***
0.00
0.00
1.00
0.00
0.00
0.00
Table (2): Panel unit root test results of the Breitung and Fisher-ADF tests
Note: All variables are in logarithms. Breitung and Fisher-ADF represent the panel unit root tests of
Breitung (2000) and Choi (2001) respectively. ***, ** indicates statical significant at 1%, 5% level
respectively. Statistics of the tests an asymptotically distributed as standard normal.
20
APPENDIX 2 (CON.)
RESULTS
Panel Co-integration test, Pedroni (1999, 2004)
Estimated results:
unweighted
Statistic
weighted
Prob
Statistic
Prob
-0.35
0.64
-3.20
1.00
1.37
0.91
-0.35
0.36
-2.18***
0.01
5.66***
-2.05***
0.02
-5.77***
0.51
0.70
Within-dimention
Panel v-Statistic
Panel rho-Statistic
Panel PP-Statistic
Panel ADF-Statistic
0.00
0.00
between-dimension
Group rho-Statistic
Group PP-Statistic
Group ADF-Statistic
-5.86***
-6.11***
0.00
0.00
Note: *** indicates statical significant at 1% level. Probabilities
21
APPENDIX 3 (CON)
RESULTS
Dynamic Ordinary Least Squares (DOLS)
Technique
Variable
LTGDP
LTPOP
LEXCH
LAIDJAP
LAIDDAC
Long-run
return
bilateral aid (Japan)
(1)
Estimates
0.25**
-2.35***
-0.21***
0.19***
0.28***
(2)
Stats
1.98
-4.57
-4.51
3.53
4.04
Estimates
0.25
-2.35***
-0.21***
0.19**
0.28*
(3)
Stats
0.97
-2.69
-2.83
2.14
1.85
Estimates
0.53***
-1.44**
-0.18**
0.13*
0.29***
Stats
5.06
-2.26
-2.56
1.67
2.98
on
Long-run return on other
DAC bilateral aid (Japan
excluded)
Total long-run return on
bilateral aid (Japan + other
DAC countries)
Dummy for country fixed
effects
Dummy for year fixed
effects
Adj R2
R2
Obs
US$1.7
US$1.7
US$1.2
US$2.2
US$2.2
US$2.2
US$3.9
US$3.9
US$3.4
yes
yes
Yes
yes
0.96
0.96
480
yes
480
No
0.95
480
Model 1 doesn’t control for heteroscedasticity and serial correlation;
Model 2 and 3 do. ***, ** and * indicate statistical significance at the 1%
%5 and 10% respectively.
22
APPENDIX 3 (CON.)
RESULTS
Weakly Exogeneity test results
Dependent
Variable
Number of lags
1 lags
Estimates
2 lags
t-stats
Estimates
ΔLEXP
ΔLTGDP
-0.47 ***
0.00
ΔLTPOP
-0.00
-1.35
-0.00
ΔLEXCH
-0.02
-0.24
ΔLAIDJAP
0.00
ΔLAIDDAC
-0.00
-17.64
0.98
-0.81***
0.00
3 lags
t-stats
-35.17
0.35
Estimates
t-stats
-0.26***
-1.12
-7.77
0.74
-1.30
-0.00*
-1.91
-0.00
-0.09
-0.01
-0.37
0.15
-0.00
-0.08
0.04
0.71
-0.31
-0.01
-0.45
-0.02
-0.54
23
APPENDIX 3 (CON)
RESULTS
Error Correction Model (ECM): long-run results
Technique
Variable
(1)
(2)
Estimates
LTGDP
LTPOP
LEXCH
LAIDJAP
LAIDDAC
0.38***
-1.82***
-0.20***
0.20***
0.22***
Stats Estimates
Long run estimates
3.3
0.38*
-3.7
-1.82**
-4.63
-0.20***
4.37
0.20***
3.64
0.22*
ECTt-1
-0.82***
-37.43
-0.82***
(3)
Stats
Estimates
Stats
1.83
-2.26
-3.08
2.97
1.76
0.62***
-1.52***
-0.15***
0.11**
0.18***
7.66
-3.4
-2.86
2.34
2.81
-6.63
-0.95***
-60.68
Long-run return on bilateral aid
(Japan)
Long-run return on other DAC
bilateral aid (Japan excluded)
Total long-run return on bilateral
aid (Japan + other DAC
countries)
US$1.8
US$1.8
US$1.0
US$1.7
US$1.7
US$1.4
US$3.5
US$3.5
US$2.4
Model 1 doesn’t control for heteroscedasticity and serial correlation;
Model 2 and 3 do. ***, ** and * indicate statistical significance at the 1%
%5 and 10% respectively.
24
APPENDIX 3 (CON)
RESULTS
Error Correction Model (ECM): short-run results
Short run estimates
-0.03
1.51
-0.03
-1.31
-0.06***
-3.56
LTGDP
0.74***
3.60
0.74*
1.91
0.62***
5.92
LTPOP
-9.49**
-2.28
-9.49
-1.61
-11.84
-1.38
LEXCHt-2
0.10
1.00
0.10
1.4
0.07
1.06
LAIDJAP
0.15***
4.17
3.78
0.11***
3.33
0.02
0.35
0.31
0.03
0.6
LEXPJAPt-1
LAIDDAC
Short-run return on bilateral aid (Japan)
Short-run return on other DAC bilateral aid
(Japan excluded)
Total short-run return on bilateral aid (Japan
+ other DAC countries)
0.15***
0.02
US$1.4
US$1.4
US$1.0
US$0.2
US$0.2
US$0.2
US$1.6
US$1.6
US$1.2
Model 1 doesn’t control for heteroscedasticity and serial correlation;
Model 2 and 3 do. ***, ** and * indicate statistical significance at the 1%
%5 and 10% respectively.
25