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Exports & growth in island economies Times series cross-sectional analysis Naren Prasad ILO.

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Presentation on theme: "Exports & growth in island economies Times series cross-sectional analysis Naren Prasad ILO."— Presentation transcript:

1 Exports & growth in island economies Times series cross-sectional analysis Naren Prasad ILO

2 Plan Aim Conceptual framework & some statistics Econometric models and estimation Results Conclusions

3 Questions Is export-led growth hypothesis valid in SIC? If yes, which kind of exports? If no why? Small islands are often asked to specialize in services, esp. tourism. How relevant is this argument?

4 Conceptual & Theoretical Framework Exports leads growth is as old as Smith & Ricardo –Increase in productivity, competitiveness, technological advancement, increased foreign exchange, better allocation of resources, creation of employment……

5 Some Descriptive statistics Growth in island economies

6 Exports of Goods and Services

7 Imports & exports of merchandise

8

9

10 GDP per capita

11 Model & Estimation Traditional Approach New Growth Theory Where

12 Our equations (1) (2) (3)

13 Model specification Affects all observation at time t Country effect Error term (omitted variables, measurement error)

14 Data 1985-2002 for 25 SIC –Cross sectional time series Sources –WDI 2004, UNCTAD Handbook of Statistics, UN Statistical Yearbook, UNIDO statistics

15 Method of estimation OLS FE are eliminated, no time-constant variables allowed. Additional problems of heteroskedacity in and serial correlation. GLS To control for country unobservables To correct for heteroskedasticity across countries & residual serial correlation Time dummies capture contemporaneous correlation across countries GMM Good in dynamic equations, but are eliminated Use lagged variables as IV

16 Specification & Diagnostic tests Serial correlation We find that the error terms are correlated Heteroskedasticity We reject the homoskedasticity situation Unit Roots & cointegration We find that the series have unit root (non- stationary) and cointegrated Endogeneity

17 Income levels World Bank’s definition –Low (7), Middle (14), High (4) income countries Alternative definition –Low $5,001 (6) Putting High & Middle together in opposition to Low income

18 OLS Estimation ALLHICMICLIC OLS Static Growth X 0.079 (5.61)*** -0.013 (0.24) 0.092 6.07)*** 0.075 (1.64) XS 0.003 (0.29) 0.222 (2.66)** 0.007 (0.58) -0.017 (0.80) XM 0.041 (4.26)*** 0.012 (0.61) 0.061 (5.23)*** 0.021 (0.84) Values X 0.194 (11.47)*** 0.077 (0.70) 0.242 (9.23)*** 0.166 (6.22)*** XS 0.074 (3.88)*** 0.003 (0.01) 0.061 (2.06)** 0.009 (0.32) XM 0.088 (6.00)*** 0.178 (2.31)** 0.073 (3.79)*** 0.158 (4.29)*** OLS Dynamic Growth XS 0.004 (0.36) 0.204 (2.47)** 0.011 (0.81) -0.015 (0.68) XM 0.042 (4.28)*** 0.022 (1.01) 0.064 (5.36)*** 0.023 (0.92) Values XS -0.007 (0.70) 0.250 (2.68)** 0.003 (0.21) -0.040 (1.71)* XM0.035 (4.80)*** -0.033 (0.81) 0.036 (4.35)*** 0.078 (2.88)***

19 GLS Estimation ALLHICMICLIC GLS Static Growth X 0.063 (6.29)*** -0.011 (0.31) 0.070 (6.05)*** 0.076 (2.82)*** XS 0.007 (1.09) 0.185 (4.07)*** 0.002 (0.26) 0.017 (1.11) XM 0.027 (4.29)*** 0.019 (1.64) 0.052 (5.75)*** 0.016 (1.14) Values X 0.137 (9.87)*** 0.107 (1.83)* 0.133 (9.04)*** 0.105 (3.97)*** XS 0.083 (5.61)*** 0.166 (1.41) 0.025 (1.53) -0.001 (0.03) XM 0.062 (5.53)*** 0.118 (3.04)*** 0.069 (6.32)*** 0.079 (3.44)*** GLS dynamic Growth XS 0.006 (1.06) 0.209 (4.60)*** 0.004 (0.45) 0.017 (1.06) XM 0.028 (4.39)*** 0.021 (1.81)* 0.057 (5.98)*** 0.017 (1.23) Values XS -0.005 (0.59) 0.226 (4.53)*** 0.004 (0.47) -0.049 (2.97)*** XM0.038 (6.57)*** -0.022 (0.99) 0.049 (7.41)*** 0.073 (3.90)***

20 GMM estimation ALLHICMICLIC GMM Growth X 0.074 (4.75)*** -0.011 (0.19) 0.086 (5.44)*** 0.103 (2.01)** XS -0.014 (1.29) 0.204 (2.55)** 0.005 (0.33)) -0.040 (1.86)* XM 0.034 (3.19)*** 0.022 (1.05) 0.051 (3.98)*** -0.040 (0.71) Values X 0.085 (5.51)*** 0.061 (1.01) 0.115 (5.72)*** 0.045 (1.89)* XS -0.012 (0.86) 0.250 (2.67)*** 0.021 (1.09) -0.051 (2.32)** XM 0.042 (3.67)*** -0.033 (0.81) 0.070 (4.99)*** 0.049 (1.97)**

21 Summary results Exports in general (G&S) does have positive and significant impact on GDP growth in our sample as a whole, but it is inconclusive in HIC Why? Exports of goods have positive and significant impact in our sample as a whole. However, it seems to have more impact in MIC and LIC compared to HIC Why? HIC are more service-based economies The impact of service exports is mixed in our sample as a whole. In HIC it tends to have positive and significant impact on growth, while it tends to have negative impact on growth in LIC (nothing can be said for MIC) Why?

22 Why negative impact of service in LIC? Theoretically, service exports earnings help in economic development –by financing imports of capital goods necessary for the growth of the manufacturing sector Requires high degree of linkage between service and other economic sectors In the case of tourism for example, we have the income multiplier to measure this linkage

23 Tourism income multiplier Kiribati0.37Seychelles0.88-1.03 Samoa0.39-0.66Cyprus1.14 Tonga0.42Egypt1.23 Vanuatu0.56-0.80Ireland1.72 Fiji0.69-0.72United Kingdom1.73 Antigua0.88Turkey1.96 Mauritius0.96 Source: UN 1999

24 High degree of Leakages Leakage arise from: imports of materials and equipment for construction; imports of consumer goods, (food & drinks); repatriation of profits earned by foreign investors; overseas promotional expenditures amortization of external debt incurred in the development of hotels and resorts. Fiji56 St. Lucia45 Mauritius43 Seychelles30 Antigua25 Source: UN 1996

25 Policy implications Since exports of merchandise doesn’t have much impact in HIC, should they continue to develop their service economy? And should LIC put more emphasis on services, or should they try to develop their traditional export sector? Should they be building their local economic capacity? And what about the MIC?


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