1. Export Performance of Landlocked
Developing Countries
Ramesh Paudel
Panel: Chandra Athukorala
Peter Warr
Paul Burke
Crawford PhD Conference 2012
Australian National University
November 27, 2012
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing November 27, 2012
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2. Outline
1 Research Questions
2 Policy and Logistic Contexts
3 Export Performance: Trends and Patterns
4 Determinants: Gravity Modelling Framework
5 Results
6 Conclusions
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3. Research Questions
Research Questions
How landlocked developing countries’ export performance differs from
that of other developing countries.
What are the determinants of export performance in the LLDCs
Does export performance of African landlocked countries differ from
that of other LLDCs.
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing November 27, 2012
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4. Research Questions
Research Questions
How landlocked developing countries’ export performance differs from
that of other developing countries.
What are the determinants of export performance in the LLDCs
Does export performance of African landlocked countries differ from
that of other LLDCs.
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing November 27, 2012
Export Performance Crawford PhD Conference 2012Countries National Univer
Australian 3 / 25

5. Research Questions
Research Questions
How landlocked developing countries’ export performance differs from
that of other developing countries.
What are the determinants of export performance in the LLDCs
Does export performance of African landlocked countries differ from
that of other LLDCs.
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing November 27, 2012
Export Performance Crawford PhD Conference 2012Countries National Univer
Australian 3 / 25

6. Policy and Logistic Contexts
Policy and Logistic Contexts
Conventional wisdom that export performance is aided by economic
openness
Indicators of Openness:
Sachs-Warner Index
Exports or trade to GDP
Tariffs
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7. Policy and Logistic Contexts
Sachs-Warner Index
A Country is liberalised when it has,
Non tariff barrier no more than 40%
Average tariff rate no more than 40%
Black market premium on exchange rate no more than 20%
Not export marketing board controlled by government
Not the socialist state
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing November 27, 2012
Export Performance Crawford PhD Conference 2012Countries National Univer
Australian 5 / 25

8. Policy and Logistic Contexts
Sachs-Warner Index
A Country is liberalised when it has,
Non tariff barrier no more than 40%
Average tariff rate no more than 40%
Black market premium on exchange rate no more than 20%
Not export marketing board controlled by government
Not the socialist state
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing November 27, 2012
Export Performance Crawford PhD Conference 2012Countries National Univer
Australian 5 / 25

9. Policy and Logistic Contexts
Sachs-Warner Index
A Country is liberalised when it has,
Non tariff barrier no more than 40%
Average tariff rate no more than 40%
Black market premium on exchange rate no more than 20%
Not export marketing board controlled by government
Not the socialist state
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing November 27, 2012
Export Performance Crawford PhD Conference 2012Countries National Univer
Australian 5 / 25

10. Policy and Logistic Contexts
Sachs-Warner Index
A Country is liberalised when it has,
Non tariff barrier no more than 40%
Average tariff rate no more than 40%
Black market premium on exchange rate no more than 20%
Not export marketing board controlled by government
Not the socialist state
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing November 27, 2012
Export Performance Crawford PhD Conference 2012Countries National Univer
Australian 5 / 25

11. Policy and Logistic Contexts
Sachs-Warner Index
A Country is liberalised when it has,
Non tariff barrier no more than 40%
Average tariff rate no more than 40%
Black market premium on exchange rate no more than 20%
Not export marketing board controlled by government
Not the socialist state
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing November 27, 2012
Export Performance Crawford PhD Conference 2012Countries National Univer
Australian 5 / 25

12. Policy and Logistic Contexts
Table 1: Sachs-Warner Criteria up to 2009
Region/Country year Tariff NTB BM X Board S- State
EAP: Lao PDR - 11.3 na na 0 0
Mongolia 1997 4.8 0 0 0 0
ECA: Armenia 1995 2.2 0 0 0 0
Azerbaijan 1995 4.9 0 0 0 0
Belarus - 6.3 na 0 0 0
Kazakhstan - 4.4 na na 0 0
Kosovo - na na na 0 0
Kyrgyz Republic 1994 4.3 0 0 0 0
Macedonia, FYR 1994 5.3 0 0 0 0
Moldova 1994 2.3 0 0 0 0
Serbia - 6.6 na na 0 0
Tajikistan 1996 5.3 0 0 0 0
Turkmenistan - 1.44 na na 0 0
Uzbekistan - 6.6 na 0 0 0
LAC: Bolivia 1985 7.5 0 0 0 0
Paraguay 1989 7.7 0 0 0 0
SA: Afghanistan - 5.5 na 22 0 0
Bhutan - 18.0 na 0 0 0
Nepal 1991 15 0 0 0 0
SSA: Botswana 1979 7.9 0 0 0 0
Burkina Faso 1998 11.2 0 0 0 0
Burundi 1999 13.2 0 0 0 0
CA Republic - 15.5 na 0 1 0
Chad 2001 14.1 0 0 0 0
Ethiopia 1996 12.6 0 0 0 0
Lesotho 2001 15.3 0 0 0 0
Malawi 2001 13.1 0 0 0 0
Mali 1988 9.8 0 0 0 0
Niger 1994 11.1 0 0 0 0
Rwanda 2001 12.5 0 0 0 0
Swaziland 2001 7 0 0 0 0
Uganda 1988 7.7 0 0 0 0
Zambia 1993 9.3 0 0 0 0
Zimbabwe - 20.3 0 29 0 0
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing November 27, 2012
Export Performance Crawford PhD Conference 2012Countries National Univer
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13. Policy and Logistic Contexts
Table 2: Trade to GDP Percent Average
Countries / Region 1995-99 2000-04 2005-10 Average 1995-2010
X/GDP T/GDP X/GDP T/GDP X/GDP T/GDP X/GDP T/GDP
EAP 30 84 29 95 33 98 31 93
Lao PDR 21 71 17 68 21 81 20 74
Mongolia 39 96 42 122 44 115 42 112
ECA 35 92 39 103 37 96 37 98
Armenia 15 77 19 76 13 62 16 71
Azerbaijan 19 77 37 96 58 93 39 89
Belarus 44 114 58 137 50 123 51 125
Kazakhstan 28 75 43 96 45 88 39 86
Kosovo - - - - - 71 - -
Kyrgyz Republic 31 87 32 85 34 130 32 103
Macedonia, FYR 31 84 32 100 36 113 33 100
Moldova 43 122 38 131 29 131 36 128
Serbia - 47 15 65 22 82 21 68
Tajikistan 65 143 61 151 33 81 52 122
Turkmenistan 52 135 69 139 54 102 58 124
Uzbekistan 25 51 27 61 34 72 29 62
LAC 13 79 18 71 28 91 20 81
Bolivia 14 49 18 50 33 74 22 59
Paraguay 12 108 18 91 23 107 18 102
SA 21 72 13 79 18 81 16 78
Afghanistan - - 3 111 4 79 4 90
Bhutan 33 86 24 75 42 117 33 93
Nepal 9 58 11 50 8 46 10 51
SSA 21 63 23 70 25 73 23 67
Botswana 47 93 40 83 37 78 41 84
Burkina Faso 10 38 8 32 10 37 10 10
Burundi 8 27 6 33 6 57 7 35
Cen. Af. Republic 15 40 13 36 9 36 12 37
Chad 16 50 21 85 50 107 30 83
Ethiopia 6 30 6 40 7 45 6 39
Lesotho 23 150 47 163 47 161 39 158
Malawi 24 66 21 64 20 69 22 66
Mali 20 60 24 Burke of70
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul 24 Developing November 23 2012
66 Countries National Univer
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Landlocked 27, 65 / 25
7

14. Policy and Logistic Contexts
Table 3: Export Policy and Logistic Indicators
Countries /Region EDBs LPI T2X Doc2x Cost2X Dis2Port
EAP Lao PDR 163 2.46 48 9 1860 373
Mongolia 89 2.25 46 8 2131 1323
ECA Armenia 61 2.52 13 5 1665 337
Azerbaijan 69 2.64 38 8 2980 525
Belarus 91 2.54 15 9 1772 401
Kazakhstan 47 2.83 76 9 3005 2091
Kosovo 117 - 17 8 2230 269
Kyrgyz Republic 67 2.62 63 8 3010 1917
Macedonia, FYR 34 2.77 12 6 1376 178
Moldova 99 2.57 32 6 1765 145
Serbia 88 2.69 12 6 1398 320
Tajikistan 152 2.35 82 11 3350 1370
Turkmenistan - 2.49 - - - 414
Uzbekistan 164 2.79 71 10 3150 1450
LAC Bolivia 147 2.51 19 8 1425 540
Paraguay 100 2.75 33 8 1440 803
SA Afghanistan 154 2.24 74 10 3545 1081
Bhutan 146 2.38 38 8 2230 560
Nepal 110 2.2 41 9 1960 641
SSA Botswana 52 2.32 28 6 3010 358
Burkina Faso 151 2.23 41 10 2412 413.6
Burundi 177 2.31 25 9 2747 1129
Central African Republic 183 - 54 9 5491 986
Chad 182 2.49 75 8 5902 1067
Ethiopia 104 2.41 43 7 1760 563
Lesotho 142 - 31 8 1680 328
Malawi 141 - 41 10 1713 451
Mali 148 2.27 26 6 2202 715
Niger 172 2.54 59 8 3545 797
Rwanda 50 2.04 35 8 3275 1091
Swaziland 123 - 18 9 1745 132
Uganda 119 2.82 37 7 2780 932
Zambia 80 2.28 44 6 2664 849
Zimbabwe 168 Peter WarrPaul Burke of Landlocked Developing November 27, 2012
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15. Export Performance: Trends and Patterns
Export Performance: Trends and Patterns
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16. Export Performance: Trends and Patterns
Export Performance: Trends and Patterns
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17. Determinants: Gravity Modelling Framework
Gravity Modelling Framework
Tinbergen (1962): Trade between 2 countries is determined by some
gravitional forces such as exporters and importers GDP and distance
between them.
Anderson (1979); Bergstrand (1985) and Deardorff (1995)
contributed theoretical background
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 11 / 25

18. Determinants: Gravity Modelling Framework
Model
Ln(Xij,t ) = α + β1 Ln(GDPi,t ) + β2 Ln(GDPj,t ) + β3 Ln(DISij )
+ β4 (LLOCKi) + β5 Ln(RERi,t ) + β6 Ln(GDPPCi,t ) + β7 Ln(GDPPCj,t )
+ β8 (LANij,t ) + β9 (BORij,t ) + β10 Ln(RFEi,t )
+ β11 (OPENi,t ) + β12 (RTAij,t ) + ij,t ......... (1)
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 12 / 25

19. Determinants: Gravity Modelling Framework
Model contd.....
X - Real non-oil exports between trading countries, the dep. variable
GDP - Real (GDP), a measure of the economic size (+)
DIS- The distance between the business cities of country i and j (-)
LLOCK - If the exporter is landlocked countries, binary dummy (-)
RER - Real exchange rate (+) (Its domestic currency/US$)
GDPPC - Per capita GDP (+,-)
LAN - Common language, a measure of cultural affinity (+)
BOR - Common boarder of trading countries (+)
OPEN - Openness measured by weighted average tariff rate (-)
RFE - Relative factor endowment (+, -), either H-O or Linder hypothesis
RTA - Regional Trade Agreements (+)
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Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 13 / 25

20. Determinants: Gravity Modelling Framework
Model contd.....
For Landlocked Developing Countries
Ln(Xij,t ) = Υ1 +Υ2 Ln(GDPi,t )+Υ3 Ln(GDPj,t )+Υ4 Ln(DISij,t )+Υ5 Ln(RERi,t )
+ Υ6 Ln(GDPPCi,t ) + Υ7 Ln(GDPPCj,t ) + Υ8 (LANij,t )
+ Υ9 (BORij,t ) + Υ10 (RFEi,t ) + Υ11 (OPENi,t )
+ Υ12 (RTAij,t ) + Υ13 (AFLLOCKj,t ) + ij,t ......... (2)
Where,
AFLLOCK= Binary Dummy for African landlocked country (-/+)
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 14 / 25

21. Determinants: Gravity Modelling Framework
Data Compilation and Sources
Country pair level annual data, non-oil export from 1995-2010
World-Bank (2012)-WDI- real GDP in US$, real GDP and nominal
GDP in local currency to calculate the GDP deflator, nominal
exchange rate, weighted average tariff rate, and GDPPC
UNCOMTRADE: Exports country to country
CEPII data base: distance, language and border
de Sousa (2012), recently updated RTAs
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 15 / 25

22. Determinants: Gravity Modelling Framework
Econometric Methodology
Most previous studies use OLS, RE and FE methods
OLS is suffered by heterogeneity bias so RE is preffered over OLS, but
the assumption of country specific effects are uncorrelated with all
regressor- has been rejected in many studies so FE is preferred over
OLS and RE.
One problem for us in FE is main variable of interest is time invariant,
can not obtain the coefficient for time invariant variable
Hence, Later Hausman and Taylor (1981) instrumental variable (HT)
estimator is used
In this estimation, HT estimator could not pass the normality test
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 16 / 25

23. Determinants: Gravity Modelling Framework
Econometric Methodology
Most previous studies use OLS, RE and FE methods
OLS is suffered by heterogeneity bias so RE is preffered over OLS, but
the assumption of country specific effects are uncorrelated with all
regressor- has been rejected in many studies so FE is preferred over
OLS and RE.
One problem for us in FE is main variable of interest is time invariant,
can not obtain the coefficient for time invariant variable
Hence, Later Hausman and Taylor (1981) instrumental variable (HT)
estimator is used
In this estimation, HT estimator could not pass the normality test
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 16 / 25

24. Determinants: Gravity Modelling Framework
Econometric Methodology
Most previous studies use OLS, RE and FE methods
OLS is suffered by heterogeneity bias so RE is preffered over OLS, but
the assumption of country specific effects are uncorrelated with all
regressor- has been rejected in many studies so FE is preferred over
OLS and RE.
One problem for us in FE is main variable of interest is time invariant,
can not obtain the coefficient for time invariant variable
Hence, Later Hausman and Taylor (1981) instrumental variable (HT)
estimator is used
In this estimation, HT estimator could not pass the normality test
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 16 / 25

25. Determinants: Gravity Modelling Framework
Econometric Methodology
Most previous studies use OLS, RE and FE methods
OLS is suffered by heterogeneity bias so RE is preffered over OLS, but
the assumption of country specific effects are uncorrelated with all
regressor- has been rejected in many studies so FE is preferred over
OLS and RE.
One problem for us in FE is main variable of interest is time invariant,
can not obtain the coefficient for time invariant variable
Hence, Later Hausman and Taylor (1981) instrumental variable (HT)
estimator is used
In this estimation, HT estimator could not pass the normality test
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 16 / 25

26. Determinants: Gravity Modelling Framework
Econometric Methodology
Most previous studies use OLS, RE and FE methods
OLS is suffered by heterogeneity bias so RE is preffered over OLS, but
the assumption of country specific effects are uncorrelated with all
regressor- has been rejected in many studies so FE is preferred over
OLS and RE.
One problem for us in FE is main variable of interest is time invariant,
can not obtain the coefficient for time invariant variable
Hence, Later Hausman and Taylor (1981) instrumental variable (HT)
estimator is used
In this estimation, HT estimator could not pass the normality test
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 16 / 25

27. Determinants: Gravity Modelling Framework
Econometric Methodology Contd.....
Hence, Poisson Pseudo Maximum Likelihood (PPML) developed by
Silva and Tenreyro (2006) is applied. PPML deals with hetorogeneity
Some issues with the log linearization and missing data-some
countries data are not available for the dependent variable and results
are not consistent due to heteroskedasticity in trade data- coefficients
are still unbiased but doubtful t-statistics. In this situation, Silva and
Tenreyro (2006) PPML is applied, because
Time invariant variable can be estimated
Can deal with missing value , and
Log linearization problem- dependent variable is level not in log.
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 17 / 25

28. Determinants: Gravity Modelling Framework
Econometric Methodology Contd.....
Hence, Poisson Pseudo Maximum Likelihood (PPML) developed by
Silva and Tenreyro (2006) is applied. PPML deals with hetorogeneity
Some issues with the log linearization and missing data-some
countries data are not available for the dependent variable and results
are not consistent due to heteroskedasticity in trade data- coefficients
are still unbiased but doubtful t-statistics. In this situation, Silva and
Tenreyro (2006) PPML is applied, because
Time invariant variable can be estimated
Can deal with missing value , and
Log linearization problem- dependent variable is level not in log.
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 17 / 25

29. Determinants: Gravity Modelling Framework
Econometric Methodology Contd.....
Hence, Poisson Pseudo Maximum Likelihood (PPML) developed by
Silva and Tenreyro (2006) is applied. PPML deals with hetorogeneity
Some issues with the log linearization and missing data-some
countries data are not available for the dependent variable and results
are not consistent due to heteroskedasticity in trade data- coefficients
are still unbiased but doubtful t-statistics. In this situation, Silva and
Tenreyro (2006) PPML is applied, because
Time invariant variable can be estimated
Can deal with missing value , and
Log linearization problem- dependent variable is level not in log.
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 17 / 25

30. Determinants: Gravity Modelling Framework
Econometric Methodology Contd.....
Hence, Poisson Pseudo Maximum Likelihood (PPML) developed by
Silva and Tenreyro (2006) is applied. PPML deals with hetorogeneity
Some issues with the log linearization and missing data-some
countries data are not available for the dependent variable and results
are not consistent due to heteroskedasticity in trade data- coefficients
are still unbiased but doubtful t-statistics. In this situation, Silva and
Tenreyro (2006) PPML is applied, because
Time invariant variable can be estimated
Can deal with missing value , and
Log linearization problem- dependent variable is level not in log.
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 17 / 25

31. Determinants: Gravity Modelling Framework
Econometric Methodology Contd.....
Hence, Poisson Pseudo Maximum Likelihood (PPML) developed by
Silva and Tenreyro (2006) is applied. PPML deals with hetorogeneity
Some issues with the log linearization and missing data-some
countries data are not available for the dependent variable and results
are not consistent due to heteroskedasticity in trade data- coefficients
are still unbiased but doubtful t-statistics. In this situation, Silva and
Tenreyro (2006) PPML is applied, because
Time invariant variable can be estimated
Can deal with missing value , and
Log linearization problem- dependent variable is level not in log.
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 17 / 25

32. Results
Table 9:All Countries
Dep. Var.: export (log) / export (HT) (PPML)
Landlockedness (Dummy) -2.621*** 0.075***
(0.330) (0.000)
GDP (log GDPi,t) 1.176*** 0.884***
(0.035) (0.000)
Partner’s GDP (log GDPj,t) 1.360*** 0.786***
(0.036) (0.000)
Distance (log Dij) -1.418*** -0.527***
(0.040) (0.000)
Openness (Tariff Rate %) -0.000 -0.000***
(0.000) (0.000)
Relative Factor Endowment -0.081*** 0.016***
(0.008) (0.000)
Bilateral RER -0.000** -0.000***
(0.000) (0.000)
Per Capita GDP (log) 0.043 -0.174***
(0.035) (0.000)
Partner’s per capita GDP (log) 0.166*** 0.002***
(0.037) (0.000)
Common Border (Dummy) 0.585*** 0.560***
(0.195) (0.000)
Common Language (Dummy) 1.077*** 0.210***
(0.079) (0.000)
Regional Trade Agreement 0.154*** 0.356***
(0.016) (0.000)
Number of observations 203,556 203,556
Number of country pairs 18,133
F Statistics 1,150.91
Sargan Hansen Statistics 535.41
Sargan Hansen P-value 0.000
Pseudo R-squared 0.88
RESET test p-values 0.25
Year Effect Yes Yes
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 18 / 25

33. Results
Table 10:All Developing Countries
Dependent Variable.: exports (PPML) (PPML) (PPML) (PPML)
Landlockedness (Dummy) -0.250*** -0.229*** -0.641*** 6.461***
(0.000) (0.000) (0.000) (0.000)
GDP (log GDPi,t) 1.063*** 1.078*** 1.078*** 1.078***
(0.000) (0.000) (0.000) (0.000)
Partner’s GDP (log GDPj,t) 0.803*** 0.800*** 0.800*** 0.803***
(0.000) (0.000) (0.000) (0.000)
Distance (log Dij) -0.593*** -0.557*** -0.557*** -0.554***
(0.000) (0.000) (0.000) (0.000)
Openness (Tariff Rate %) -0.085*** -0.084*** -0.084*** -0.084***
(0.000) (0.000) (0.000) (0.000)
Relative Factor Endowment 0.071*** 0.080*** 0.080*** 0.080***
(0.000) (0.000) (0.000) (0.000)
Bilateral RER 0.001*** 0.000*** 0.000*** 0.000***
(0.000) (0.000) (0.000) (0.000)
Per Capita GDP (log) -0.269*** -0.332*** -0.332*** -0.332***
(0.000) (0.000) (0.000) (0.000)
Partner’s per capita GDP (log) 0.046*** 0.030*** 0.030*** 0.031***
(0.000) (0.000) (0.000) (0.000)
Common Border (Dummy) 1.118*** 1.040*** 1.040*** 1.041***
(0.000) (0.000) (0.000) (0.000)
Common Language (Dummy) 0.798*** 0.806*** 0.806*** 0.807***
(0.000) (0.000) (0.000) (0.000)
Regional Trade Agreement 0.315*** 0.315*** 0.312***
(0.000) (0.000) (0.000)
llock*gdp 0.018***
(0.000)
llock*partgdp -0.246***
(0.000)
Number of observations 123,507 123,507 123,507 123,507
Pseudo R-squared 0.88 0.88 0.88 0.86
RESET test p-values 0.27 0.18 0.29 0.27
Year Effect Yes Yes Yes Yes
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 19 / 25

34. Results
Table 11: Landlocked Developing Countries
Dependent Variable: exports (PPML) (PPML) (PPML) (PPML)
GDP (log GDPi,t) 0.682*** 0.814*** 0.674*** 0.801***
(0.000) (0.000) (0.000) (0.000)
Partner’s GDP (log GDPj,t) 0.782*** 0.814*** 0.782*** 0.813***
(0.000) (0.000) (0.000) (0.000)
Openness (Tariff Rate %) -0.030*** -0.040*** -0.027*** -0.037***
(0.000) (0.000) (0.000) (0.000)
Bilateral RER 0.001*** 0.001*** 0.001*** 0.001***
(0.000) (0.000) (0.000) (0.000)
Per Capita GDP (log) 0.430*** 0.318*** 0.394*** 0.286***
(0.000) (0.000) (0.000) (0.000)
Partner’s per capita GDP (log) -0.220*** -0.218*** 0.061*** 0.043***
(0.000) (0.000) (0.000) (0.000)
Distance (log Dij) -0.834*** -0.723*** -0.876*** -0.762***
(0.000) (0.000) (0.000) (0.000)
African Landlocked (Dummy) 0.337*** 0.528*** 0.304*** 0.492***
(0.000) (0.000) (0.000) (0.000)
Common Border (Dummy) 1.455*** 1.052*** 1.297*** 0.927***
(0.000) (0.000) (0.000) (0.000)
Common Language (Dummy) 0.567*** 0.241*** 0.586*** 0.253***
(0.000) (0.000) (0.000) (0.000)
Regional Trade Agreement 1.180*** 1.150***
(0.000) (0.000)
Relative Factor Endowment -0.243*** -0.225***
(0.000) (0.000)
Number of observations 22,409 22,409 22,409 22,409
Pseudo R-squared 0.67 0.70 0.68 0.71
RESET test p-values 0.28 23.00 0.25 0.29
Year Effect Yes Yes Yes Yes
Note: *** , ** and * indicate the significance levels at 1%, 5% and 10% level of significance, the figures in the parenthesis are
standard errors.
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 20 / 25

35. Results
Key Points from Empirical Analysis
Landlockedness deters export more to poor countries
Having common language and border increase export but border’s
role is more important
RFE- results suggest trade between poor countries is the phenomenon
of LLDCs
RER has positive significant role even small magnitude
Having more bilateral and regional trade agreements is more
favourable exports
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 21 / 25

36. Results
Key Points from Empirical Analysis
Landlockedness deters export more to poor countries
Having common language and border increase export but border’s
role is more important
RFE- results suggest trade between poor countries is the phenomenon
of LLDCs
RER has positive significant role even small magnitude
Having more bilateral and regional trade agreements is more
favourable exports
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 21 / 25

37. Results
Key Points from Empirical Analysis
Landlockedness deters export more to poor countries
Having common language and border increase export but border’s
role is more important
RFE- results suggest trade between poor countries is the phenomenon
of LLDCs
RER has positive significant role even small magnitude
Having more bilateral and regional trade agreements is more
favourable exports
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 21 / 25

38. Results
Key Points from Empirical Analysis
Landlockedness deters export more to poor countries
Having common language and border increase export but border’s
role is more important
RFE- results suggest trade between poor countries is the phenomenon
of LLDCs
RER has positive significant role even small magnitude
Having more bilateral and regional trade agreements is more
favourable exports
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 21 / 25

39. Results
Key Points from Empirical Analysis
Landlockedness deters export more to poor countries
Having common language and border increase export but border’s
role is more important
RFE- results suggest trade between poor countries is the phenomenon
of LLDCs
RER has positive significant role even small magnitude
Having more bilateral and regional trade agreements is more
favourable exports
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 21 / 25

40. Conclusions
Conclusions
Landlockedness remains binding constraint- opportunities exist to
improve export performance creating a more trade friendly
environment through lowering the tariffs and focusing trade
promotion effort on bilateral trade agreements
Landlockedness matters more to LLDCs compared to rich LC.
RFE-measured by the difference between the per capita income of
trading partners confirm the Linder hypothesis that trade links are
much stronger among countries with similar income levels.
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 22 / 25

41. Conclusions
Conclusions
Landlockedness remains binding constraint- opportunities exist to
improve export performance creating a more trade friendly
environment through lowering the tariffs and focusing trade
promotion effort on bilateral trade agreements
Landlockedness matters more to LLDCs compared to rich LC.
RFE-measured by the difference between the per capita income of
trading partners confirm the Linder hypothesis that trade links are
much stronger among countries with similar income levels.
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 22 / 25

42. Conclusions
Conclusions
Landlockedness remains binding constraint- opportunities exist to
improve export performance creating a more trade friendly
environment through lowering the tariffs and focusing trade
promotion effort on bilateral trade agreements
Landlockedness matters more to LLDCs compared to rich LC.
RFE-measured by the difference between the per capita income of
trading partners confirm the Linder hypothesis that trade links are
much stronger among countries with similar income levels.
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 22 / 25

43. Conclusions
Conclusions Contd.....
LLDCs have many products line that have revealed comparative
advantage. Mostly the product lines are high value light products
such as processed foods, garments-textiles, tea and coffee.
Distance-related trade costs deter export performance more in
landlocked developing countries compared with other developing
countries.
Having common border is more important than having common
language for export performance of these countries
On the contrary, African landlocked countries export levels are about
30 percent higher-perhaps reflect the impact of liberalisation reforms
undertaken by a number of these countries since the mid 1990s
-which are not adequately captured by the explanatory variables used
in the model.
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 23 / 25

44. Conclusions
Conclusions Contd.....
LLDCs have many products line that have revealed comparative
advantage. Mostly the product lines are high value light products
such as processed foods, garments-textiles, tea and coffee.
Distance-related trade costs deter export performance more in
landlocked developing countries compared with other developing
countries.
Having common border is more important than having common
language for export performance of these countries
On the contrary, African landlocked countries export levels are about
30 percent higher-perhaps reflect the impact of liberalisation reforms
undertaken by a number of these countries since the mid 1990s
-which are not adequately captured by the explanatory variables used
in the model.
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 23 / 25

45. Conclusions
Conclusions Contd.....
LLDCs have many products line that have revealed comparative
advantage. Mostly the product lines are high value light products
such as processed foods, garments-textiles, tea and coffee.
Distance-related trade costs deter export performance more in
landlocked developing countries compared with other developing
countries.
Having common border is more important than having common
language for export performance of these countries
On the contrary, African landlocked countries export levels are about
30 percent higher-perhaps reflect the impact of liberalisation reforms
undertaken by a number of these countries since the mid 1990s
-which are not adequately captured by the explanatory variables used
in the model.
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 23 / 25

46. Conclusions
Conclusions Contd.....
LLDCs have many products line that have revealed comparative
advantage. Mostly the product lines are high value light products
such as processed foods, garments-textiles, tea and coffee.
Distance-related trade costs deter export performance more in
landlocked developing countries compared with other developing
countries.
Having common border is more important than having common
language for export performance of these countries
On the contrary, African landlocked countries export levels are about
30 percent higher-perhaps reflect the impact of liberalisation reforms
undertaken by a number of these countries since the mid 1990s
-which are not adequately captured by the explanatory variables used
in the model.
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 23 / 25

47. Conclusions
Comments and Feedback
Thank You !
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 24 / 25

48. Conclusions
Comments and Feedback
Thank You !
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 24 / 25

49. Conclusions
Reasons to think Why Africa is Different
Africa Had slow growth for almost 2 decades compared to other
countries
Africa initiated trade reforms in 1990s Africa Booming See Richard
Dowden (2009) Africa Altered States, Ordinary Miracles
Investment from China and other developing countries
Ramesh Paudel (Panel: Chandra Athukorala Peter WarrPaul Burke of Landlocked Developing Countries 2012
Export Performance Crawford PhD Conference 2012 Australian National Univer
November 27, 25 / 25