Why Has Trade Barely Moved Sub-Saharan Africa to Its Economic Potential?
Abstract
:1. Introduction
2. International Trade, Industrialization and Productivity: Setting the Scene
2.1. Evolution of SSA’s Trade and Manufacturing
2.2. Theoretical Model
3. Data Description
Measuring Technical Efficiency
4. Empirical Findings
5. Conclusions
Funding
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Notes
1 | Each region comprised a panel of countries. Asia had 43 countries in the sample, Americas had 26, Europe had 38, and SSA had 22. |
2 | Cameroon, Benin, Botswana, Mauritania, South Africa, Namibia, Kenya, Niger, Guinea, Uganda, Eswatini, Tanzania, Sierra Leone, Togo, Nigeria, Ghana, Gambia, Mozambique, Mauritius, Rwanda, Zimbabwe, and Gabon. |
3 | We experimented with lagging the input variables in the frontier estimation to crudely circumvent the endogeneity problem but hardly noticed any discernible changes to the average efficiency score. |
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Variable | Obs | Mean | Std. Dev. | Min | Max |
---|---|---|---|---|---|
Gdppc (2015 = 100) | 594 | 2114.334 | 2739.181 | 217.6248 | 10,959.34 |
Labour force | 594 | 8,465,686 | 1.16 × 107 | 269,775 | 7.06 × 107 |
GCF | 594 | 21.46502 | 8.508312 | 2.424358 | 60.05831 |
GCONS | 594 | 14.37496 | 5.618962 | 0.9112346 | 36.21686 |
Trade_share | 594 | 65.34951 | 27.81098 | 16.35219 | 175.798 |
Manuf | 594 | 11.4658 | 5.995024 | 1.532609 | 35.21546 |
Null Hypothesis | p-Value | LR Statistic | Decision |
---|---|---|---|
0.00000 | Translog | ||
5% LR critical value [9 restrictions] =16.274 | 2478.31 ** | Translog | |
0.00000 | Hicks non-neutral technical changes | ||
0.00000 | Technical changes | ||
5% LR critical value [1 restriction] = 7.045 | 7.3074 ** | Technical inefficiencies |
Distribution | AIC | BIC |
---|---|---|
Half normal | 734.83 | 900.36 |
Exponential | 260.56 | 426.10 |
Truncated normal | −999.31 | −829.30 |
Variable | Obs | Mean | Std. Dev. | Min | Max |
---|---|---|---|---|---|
Efficiency | 594 | 0.7524164 | 0.1705611 | 0.2337386 | 0.9999995 |
Rank | Country Name | Average Technical Efficiency |
---|---|---|
1 | South Africa | 0.900058 |
2 | Gabon | 0.881168 |
3 | Mauritania | 0.878073 |
4 | Gambia | 0.874137 |
5 | Cameroon | 0.828581 |
6 | Eswatini | 0.81668 |
7 | Benin | 0.808758 |
8 | Niger | 0.771839 |
9 | Togo | 0.760335 |
10 | Botswana | 0.759361 |
11 | Ghana | 0.756308 |
12 | Namibia | 0.745751 |
13 | Nigeria | 0.726598 |
14 | Mauritius | 0.72161 |
15 | Tanzania | 0.714385 |
16 | Guinea | 0.699858 |
17 | Sierra Leone | 0.694809 |
18 | Kenya | 0.689548 |
19 | Mozambique | 0.675626 |
20 | Zimbabwe | 0.632022 |
21 | Uganda | 0.629153 |
22 | Rwanda | 0.610353 |
Threshold | RSS | MSE | F-Stat | Prob | Crit10 | Crit5 | Crit1 |
---|---|---|---|---|---|---|---|
Single | 0.0004 | 0.0000 | 59.38 *** | 0.0000 | 32.0216 | 37.6719 | 45.5497 |
Double | 0.0004 | 0.0000 | 24.34 | 0.1867 | 29.8902 | 34.2523 | 56.4326 |
Triple | 0.0004 | 0.0000 | 11.20 | 0.7700 | 29.3202 | 33.0772 | 47.5187 |
Dynamic Threshold Model | Hansen Static Model | |||
---|---|---|---|---|
Kink | Jump | Jump Without Controls | Jump With Controls | |
Lag_y_b | 0.0602 *** (0.014) | 0.971 *** (0.250) | ||
Trade_share_b | −0.0008 *** (0.0003) | −0.200 ** (0.093) | −0.1244 ** (0.058) | −0.0467 (0.044) |
kink_slope | 0.0216 * (0.011) | |||
Trade_share_d | 0.3907 *** (0.094) | 0.234 *** (0.053) | 0.1568 *** (0.040) | |
GCONS | 0.0002 (0.009) | |||
GCF | 0.005 *** (0.001) | |||
Cons_d | −0.7176 (0.302) | −0.4377 (0.242) | ||
r | 0.152 *** (0.015) | 0.136 *** (0.046) | 0.1601 [0.1508; 0.1608] | 0.1601 [0.1508; 0.1609] |
Obs | 572 | 594 | 594 | 594 |
Manufacturing Share > 15% | Manufacturing Share < 15% | Difference in USD | ||
---|---|---|---|---|
Average Efficiency Score | Mean Income Loss in USD (Distance from the Economic Potential) | Average Efficiency Score | Mean Income Loss in USD (Distance from the Economic Potential) | |
0.77 | USD 651 | 0.74 | USD 766 | USD 115 |
(A) | (B) | (A) | (B) | |
---|---|---|---|---|
>15% of GDP | ≤15% of GDP | >15% of GDP | ≤15% of GDP | |
Trade_share | 0.228 *** | 0.0122 | 0.0761 * | 0.0600 |
(0.0492) | (0.0772) | (0.0437) | (0.0472) | |
GCF | 0.00320 * | 0.00939 *** | ||
(0.00179) | (0.00161) | |||
GCONS | 0.0018 | 0.0110 | ||
(0.00217) | (0.02336) | |||
Constant | 0.0639 | 0.167 *** | 0.0190 | 0.336 *** |
(0.0391) | (0.0623) | (0.0458) | (0.0486) | |
Time dummies | yes | yes | yes | yes |
Observations | 113 | 481 | 113 | 481 |
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Mazorodze, B.T. Why Has Trade Barely Moved Sub-Saharan Africa to Its Economic Potential? Economies 2023, 11, 259. https://doi.org/10.3390/economies11100259
Mazorodze BT. Why Has Trade Barely Moved Sub-Saharan Africa to Its Economic Potential? Economies. 2023; 11(10):259. https://doi.org/10.3390/economies11100259
Chicago/Turabian StyleMazorodze, Brian Tavonga. 2023. "Why Has Trade Barely Moved Sub-Saharan Africa to Its Economic Potential?" Economies 11, no. 10: 259. https://doi.org/10.3390/economies11100259
APA StyleMazorodze, B. T. (2023). Why Has Trade Barely Moved Sub-Saharan Africa to Its Economic Potential? Economies, 11(10), 259. https://doi.org/10.3390/economies11100259