The commercial benefits for Japan of its aid to Asia Sabit Amum Otor ANU graduate and Research Associate at the Development Policy Centre

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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

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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$US 1.20 Only looks at short-run, and study now out of date.

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2. RESEARCH QUESTIONSThis 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

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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

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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.

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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.

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4. RESULTS (CONT.)

Summary results: The return of Japanese and other DAC aid on Japanese exports (USD)

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.

Long-runShort-

runDOLS ECM ECM

Average return on bilateral aid (Japan) 1.2 1 1Average return on other DAC bilateral aid (Japan excluded) 2.2 1.4 0.2Total average return on bilateral aid (Japan + other DAC countries) 3.4 2.4  1.2

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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 Long run

LEXPJAP LAIDJAP ECT Joint (ECT and LEXPJAP)

Joint (ECT and LAIDJAP)

LEXPJAP - 4.41*** -0.26*** - 18.69***

LAIDJAP 0.13 - 0.04 0.23 -

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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.

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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

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5. CONCLUSION (CONT.)

SummaryThis research supports other findings that own-country aid does increase own-country exports.It also suggests, though less clearly, that other-country 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

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APPENDIX 1

The gravity model of international trade:

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

and The equation (1) can be written as

)1(76543210 ijijijijjijiij MRFDISPOPPOPGDPGDPEXP

21

43

)2()log(

)log()log()log()log()log(

5

43210

ijttijkjt

ijtjitttijt

AIDDAC

AIDJAPEXCHTPOPTGDPEXP

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

16

)3()log()log()log(

)log()log()log()log(

)log()log()log()log(

,6,,

54

3210

p

ps

p

psijtstyjstijs

p

psstjis

p

pssts

p

psstsyjtijt

ijttttijijt

AIDDACAIDJAPEXCH

TPOPTGDPAIDDACAIDJAP

EXCHTPOPTGDPEXP

This estimation technique produces unbiased estimates even when some or all regressors are endogenous

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.

This estimation technique produces unbiased estimates even when some or all regressors are endogenous

)3()log()log()log(

)log()log()log()log(

)log()log()log()log(

,6,,

54

3210

p

ps

p

psijtstyjstijs

p

psstjis

p

pssts

p

psstsyjtijt

ijttttijijt

AIDDACAIDJAPEXCH

TPOPTGDPAIDDACAIDJAP

EXCHTPOPTGDPEXP

17

APPENDIX 2 (CON.)Weak Exogeneity and Causality Tests

(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.

ijt

ijt

ijt

ijt

ijt

ijt

LAIDDAC

LAIDJAP

LEXP

LTPOP

LTGDP

LEXP

6

5

4

3

2

1

6

5

4

3

2

1

ij

ij

ij

ij

ij

ij

6

5

4

3

2

1

t

t

t

t

t

t

p

s

sssss

ssssss

ssssss

ssssss

ssssss

ssssss

1

666564636261

565554535251

464544434241

383534333231

262524232221

161514131211

sijt

sijt

sijt

sijt

sijt

sijt

LAIDDAC

LAIDJAP

LEXP

LTPOP

LTGDP

LEXP

6

5

4

3

2

1

1tECT

ijt

ijt

ijt

ijt

ijt

ijt

6

5

4

3

2

1

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APPENDIX 2 (CON.) ECM

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).

tijLEXP ,1 1ij 1t

stijs

s z ,

3

01

1 1,1111011, tijtijtij zLEXP )6(,1 tij

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APPENDIX 3 RESULTSUnit Root Test: Two tests: the first test was proposed by Breitung (2000), and the second was proposed by Choi

(2001)

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.

Breitung Fisher-ADF

Statistic Prob Statistic Prob

Level

LEXP 1.21 0.89 -3.56*** 0.00

LTGDP 2.19 0.20 -0.60 0.28

LTPOP -10.86*** 0.00 -0.70 0.24

LEXCH 1.59 0.94 2.70 1.00

LAIDJAP -2.66*** 0.00 0.71 0.76

LAIDDAC 1.80 0.96 0.21 0.58

First-difference

ΔLEXP -8.22*** 0.00 -16.34*** 0.00

ΔLTGDP -2.43*** 0.00 -10.69*** 0.00

ΔLTPOP 4.32 1.00 -1.95** 0.03

ΔLEXCH -9.87*** 0.00 -10.33*** 0.00

ΔLAIDJAP -11.93*** 0.00 -21.40*** 0.00

ΔLAIDDAC -9.98*** 0.00 -16.37*** 0.00

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APPENDIX 2 (CON.) RESULTS

Panel Co-integration test, Pedroni (1999, 2004) Estimated results:

Note: *** indicates statical significant at 1% level. Probabilities

unweighted weighted

Statistic Prob Statistic Prob

Within-dimention

Panel v-Statistic -0.35 0.64 -3.20 1.00

Panel rho-Statistic 1.37 0.91 -0.35 0.36

Panel PP-Statistic-2.18*** 0.01 5.66***

0.00

Panel ADF-Statistic-2.05*** 0.02 -5.77***

0.00

between-dimension

Group rho-Statistic0.51 0.70

Group PP-Statistic -5.86***

0.00

Group ADF-Statistic -6.11***

0.00

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APPENDIX 3 (CON) RESULTS

Technique (1) (2) (3)

Variable Estimates Stats Estimates Stats Estimates StatsLTGDP 0.25** 1.98 0.25 0.97 0.53*** 5.06LTPOP -2.35*** -4.57 -2.35*** -2.69 -1.44** -2.26LEXCH -0.21*** -4.51 -0.21*** -2.83 -0.18** -2.56LAIDJAP 0.19*** 3.53 0.19** 2.14 0.13* 1.67LAIDDAC 0.28*** 4.04 0.28* 1.85 0.29*** 2.98Long-run return on bilateral aid (Japan) US$1.7 US$1.7 US$1.2

Long-run return on other DAC bilateral aid (Japan excluded)

US$2.2 US$2.2 US$2.2

Total long-run return on bilateral aid (Japan + other DAC countries)

US$3.9 US$3.9 US$3.4

Dummy for country fixed effects yes yes YesDummy for year fixed effects yes yes NoAdj R2 0.96 - -R2 0.96 - 0.95Obs 480 480 480

Dynamic Ordinary Least Squares (DOLS)

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.

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APPENDIX 3 (CON.) RESULTS

Dependent Variable

Number of lags

1 lags 2 lags 3 lags

Estimates t-stats Estimates t-stats

Estimates t-stats

ΔLEXPΔLTGDP

-0.47 *** -17.640.00 0.98

-0.81*** -35.170.00 0.35

-0.26*** -7.77-1.12 0.74

ΔLTPOP -0.00 -1.35 -0.00 -1.30 -0.00* -1.91

ΔLEXCH -0.02 -0.24 -0.00 -0.09 -0.01 -0.37

ΔLAIDJAP 0.00 0.15 -0.00 -0.08 0.04 0.71

ΔLAIDDAC -0.00 -0.31 -0.01 -0.45 -0.02 -0.54

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Weakly Exogeneity test results

APPENDIX 3 (CON) RESULTS

Error Correction Model (ECM): long-run results

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.

Technique (1) (2) (3)

Variable Estimates Stats Estimates Stats Estimates StatsLong run estimates

LTGDP 0.38*** 3.3 0.38* 1.83 0.62*** 7.66LTPOP -1.82*** -3.7 -1.82** -2.26 -1.52*** -3.4LEXCH -0.20*** -4.63 -0.20*** -3.08 -0.15*** -2.86LAIDJAP 0.20*** 4.37 0.20*** 2.97 0.11** 2.34LAIDDAC 0.22*** 3.64 0.22* 1.76 0.18*** 2.81

ECTt-1 -0.82*** -37.43 -0.82*** -6.63 -0.95*** -60.68Long-run return on bilateral aid (Japan)

US$1.8 US$1.8 US$1.0Long-run return on other DAC bilateral aid (Japan excluded) US$1.7 US$1.7 US$1.4Total long-run return on bilateral aid (Japan + other DAC countries)

US$3.5 US$3.5 US$2.4

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APPENDIX 3 (CON)RESULTS

Error Correction Model (ECM): short-run results

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.

Short run estimates

LEXPJAPt-1 -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 0.15*** 3.78 0.11*** 3.33

LAIDDAC 0.02 0.35 0.02 0.31 0.03 0.6Short-run return on bilateral aid (Japan)

US$1.4 US$1.4 US$1.0Short-run return on other DAC bilateral aid (Japan excluded) US$0.2 US$0.2 US$0.2Total short-run return on bilateral aid (Japan + other DAC countries) US$1.6 US$1.6 US$1.2

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