“Did Botswana Escape From the Resource Curse?” by Atsushi Iimi

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This working paper addresses the continued growth of Botswana’s economy and the key factors contributing to the growth. The economic performance of Botswana has been remarkably contrasted with that of other countries in the region making it worth investigating. According to Iimi, Botswana is richly endowed naturally thereby making it one of the richest countries worldwide in terms of diamond abundance (3).

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The country’s economic growth has been attributed mainly to the mining industry, which has been contributing to a growth of 7.8% since the 1980s (Iimi 3). The presence of natural resources is not the only factor that guarantees the growth of an economy. The governance of the revenues from the resources is also a key factor to the progress of the economy. Economies with abundant natural resources have failed to experience economic growth while resource scarce economies have achieved economic growth resulting to “resource curse” phenomenon.

It is expected that countries with more natural resources should have higher economic growth rates from the exploitation of the available natural resources, which at times does not happen because countries endowed with great natural resources have failed to convert them into economic gains for themselves. This failure has been attributed to disagreements and conflicts between various stakeholders involved directly or indirectly during the exploitation of the resource. Taxation exerts the pressure of accountability on governments. However, in the case of natural resource-rich countries, revenue is mostly raised from the exploitation of the natural resources (Iimi 6).

Resource wealth can relieve the government from tax collection pressure, which forms fiscal discipline (Gupta et al. 167). The revenue from the sale of the natural resources may not necessary translate to economic growth due to the Dutch disease problem as sectors without a direct relationship with the natural resources tend to suffer from the appreciation of the national currency (Corden and Neary 830).

Botswana is highly dependent on its natural resources, which contribute to about 80 percent of the total exports from the country (Iimi 8). The country is the 18th largest resource exporter in the world placing it among the top countries that rely mostly on natural resources. This review indicates that even though the country gets a lot of income from natural resources, the labor absorbed by the mining sector is very low, and only accounts for 4 percent of the entire population. The trend analysis of the mining sector against the economic growth elucidates the key developments associated with the revenue from the natural resources.

Botswana has had good governance that has enabled it to experience economic growth from the revenue raised from the sale of diamonds among other minerals (Iimi 26). The continued political stability in the country over a long period has also contributed substantially to the development of the country. An empowered public that is vocal on government accountability is crucial in ensuring that there is transparency and good utilization of the resources available. The presence of an anticorruption authority with powers to report corruption cases to the president in Botswana has played a vital role in ensuring that state resources are not looted.

The office of the attorney general in the country is also independent of the government and politicians, which empowers the office to prosecute corrupt individuals. Most natural resource-rich countries have not developed because of resource unavailability but due to poor governance and utilization of the resources. A study contrasting the economic growth of 89 resource-rich and resource-poor countries has shown significant economic growth in the resource-poor countries compared to the resource-rich countries thereby indicating that the presence of natural resources in abundance in a country does not guarantee economic development.

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The use of data across different countries with different characteristics such as income and continental locality diversifies the study. This study examines the relationship between natural resource wealth, growth and governance by applying empirical growth literature as reported by Barro (34). The use of the gross domestic product from the countries as the dependent variable makes it easy to conduct a trend analysis for the growth in the same countries. The endogenous variable used is a clear indication and reflection of economic performance. That the natural resources extracted are mostly exported abroad is an assumption made to ease the computation and valuation of the values of the minerals as data used is from the World Bank database.

A table of new variables for the growth of the real GDP (at constant prices), the growth of labor force and the ratio of external debt and real GDP

Year ΔY ΔL ΔD ΔD/ΔY
1980
1981 109,558,692 12,932 139,073,275.8 1.269395
1982 160,362,119 12,682 162,127,933.2 1.011011
1983 194,378,325 12,189 20,889,012.1 0.107466
1984 142,956,423 13,311 13,118,902.0 0.091769
1985 129,385,282 14,855 47,887,702.8 0.370117
1986 158,983,800 15,865 30,546,424.2 0.192135
1987 250,023,538 16,816 176,958,517.4 0.707767
1988 457,902,323 17,887 -228,791,614.3 -0.49965
1989 367,251,340 19,792 -83,590,643.3 -0.22761
1990 215,335,843 21,088 -44,664,676.5 -0.20742
1991 253,204,275 23,162 41,165,086.8 0.162577
1992 106,413,298 24,413 -58,703,994.2 -0.55166
1993 71,937,651 26,251 -24,401,685.1 -0.33921
1994 138,815,021 26,114 -39,836,309.9 -0.28697
1995 174,617,774 27,376 -41,239,264.7 -0.23617
1996 229,844,782 26,852 -155,104,878.5 -0.67482
1997 209,152,378 27,090 -74,181,982.5 -0.35468
1998 484,123,280 26,798 -50,283,988.4 -0.10387
1999 256,463,189 25,850 -74,172,859.9 -0.28921
2000 313,072,710 24,460 -20,022,171.9 -0.06395
2001 196,905,195 22,734 -81,055,268.0 -0.41165
2002 522,788,357 20,056 44,358,295.8 0.084849
2003 398,605,855 20,286 18,977,047.8 0.047609
2004 403,325,042 19,269 -28,663,992.5 -0.07107
2005 116,732,453 21,277 -47,271,404.4 -0.40496
2006 372,350,446 22,411 -54,355,701.0 -0.14598
2007 367,364,478 22,018 -2,859,341.4 -0.00778
2008 249,879,886 24,881 -13,716,941.0 -0.05489
2009 -301,765,567 24,566 356,713,227.1 -1.18209

A table of natural logarithms of the growth of the real GDP (at constant prices), the growth of labor force, the ratio of the investment share of real GDP, and the ratio of external debt and real GDP

Year Log Y Log I/Y Log L Log D
1980 9.082286 -0.34833 5.583305 8.739265
1981 9.119971 -0.34669 5.597724 8.83739
1982 9.16983 -0.3098 5.611413 8.929324
1983 9.223472 -0.50045 5.624176 8.93987
1984 9.259083 -0.55533 5.637698 8.946364
1985 9.288975 -0.4389 5.652307 8.96928
1986 9.323094 -0.68466 5.667386 8.98329
1987 9.371854 -0.55736 5.682816 9.056605
1988 9.44904 -0.11691 5.698649 8.959243
1989 9.502347 -0.38722 5.715521 8.917417
1990 9.530807 -0.32975 5.732805 8.893299
1991 9.562049 -0.36012 5.751027 8.915575
1992 9.574536 -0.46357 5.769441 8.88345
1993 9.582779 -0.44117 5.788407 8.869365
1994 9.598256 -0.46344 5.806486 8.84534
1995 9.616973 -0.49675 5.824664 8.818985
1996 9.64044 -0.53685 5.841784 8.70247
1997 9.660745 -0.44225 5.858398 8.633331
1998 9.704396 -0.28241 5.874231 8.579303
1999 9.725856 -0.37489 5.888975 8.484879
2000 9.750693 -0.33329 5.90248 8.455431
2001 9.765616 -0.33536 5.914666 8.310331
2002 9.802916 -0.35037 5.92514 8.395655
2003 9.829348 -0.34285 5.935484 8.427591
2004 9.85455 -0.31551 5.945085 8.3784
2005 9.861579 -0.45075 5.955447 8.282689
2006 9.883269 -0.43581 5.966099 8.137904
2007 9.903658 -0.41691 5.976317 8.128769
2008 9.916998 -0.31007 5.987581 8.082058
2009 9.900835 -0.33809 5.998423 8.678983

Descriptive Statistics for Individual Samples

Gross Domestic Product

Table of GDP Descriptive Statistics
N Range Minimum Maximum Mean Std. Deviation Variance
Y 30 7051733755 1208609087 8260342842 4426993335.07 2240243997.216 5018693167062411300.000
Valid N (listwise) 30

The Ratio of Investment Share of Real GDP

A table of the ratio of investment share of real GDP descriptive statistics
N Range Minimum Maximum Mean Std. Deviation Variance
I/Y 30 .5573 .2067 .7640 .407857 .1023038 .010
Valid N (listwise) 30

Labor Force

Labor force Descriptive Statistics
N Range Minimum Maximum Mean Std. Deviation Variance
L 30 613281 383094 996375 665329.67 196840.180 38746056633.540
Valid N (listwise) 30

Debt

Table of Debt Descriptive Statistics
N Range Minimum Maximum Mean Std. Deviation Variance
D 30 1018416287.1 120797549.4 1139213836.5 566895032.343 302415231.3497 91454972152263536.000
Valid N (listwise) 30

The histograms below indicate the growth of various variables. The years are depicted by numbers ranging from 1 to 30 indicating the period from 1980 to 2010. The representation of the years in this manner has been used in the entire work.

The growth of the real GDP (at constant prices), the growth of labor force, the ratio of the investment share of real GDP and the ratio of external debt and real GDP
Histograms showing the growth of the real GDP (at constant prices), the growth of labor force, the ratio of the investment share of real GDP and the ratio of external debt and real GDP

Growth of the Real GDP

The graph below indicates the increase in the level of the real gross domestic product over the years of utilization of the natural resources. The increase in the national income can be attributed to an increase in mining activities and availability of labor.

Growth of the Real GDP

The Growth of Labor Force

There has been a constant growth in the labor force. The labor has increased substantially over the years. This increase can be attributed to a rise in the number of entrants into the labor market. The increase can also be attributed to the growth in population as well as the Asian crisis where Botswana citizens failed to secure jobs in Asian countries in the last years of analysis.

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The Growth of Labor Force

The Ratio of the Investment Share of Real GDP

The investment ratio to GDP has been fluctuating with 1988 being the highest and 1984 recording the least value. This ratio indicates the proportion of revenue that is invested. Investment of revenues is crucial because Botswana is highly dependent on the mining industry. The country needs to broaden its economic horizons to avoid relying on mining only. To realize this objective, Botswana has to use the resources obtained from the mining industry to develop other sectors of its economy.

The Ratio of the Investment Share of Real GDP

The graph indicates a decline in the ratio of debts to the real gross domestic product. This observation can be attributed to enhanced governance and management of the natural resources revenues. An increase in the ratio indicates that the country has numerous debts.

The figure below indicates a country whose GDP is higher than its debt, which is desirable to all countries.

Indicates a country whose GDP is higher than its debt, which is desirable to all countries

Correlation matrix (from covariance analysis) of the variables: growth of the real GDP (at constant prices), the growth of labor force, the ratio of the investment share of real GDP and the ratio of external debt and real GDP

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Correlation
D/Y D L I/Y
D/Y Pearson Correlation 1 .839** -.928** -.195
Sig. (2-tailed) .000 .000 .301
N 30 30 30 30
D Pearson Correlation .839** 1 -.873** -.218
Sig. (2-tailed) .000 .000 .246
N 30 30 30 30
L Pearson Correlation -.928** -.873** 1 .147
Sig. (2-tailed) .000 .000 .438
N 30 30 30 30
I/Y Pearson Correlation -.195 -.218 .147 1
Sig. (2-tailed) .301 .246 .438
N 30 30 30 30
**. Correlation is significant at the 0.01 level (2-tailed).

The table on correlation indicates that there is no connection between labor growth and the growth of debts. From the table, the correlation matrix is as shown below.

[ 1 0.839 -0.928 -0.195 ]
[ 0.839 1 -0.873 -0.218 ]
[ -0.928 -0.873 1 0.147 ]
[ -0.195 -0.218 0.147 1 ]

Histograms for natural-log versions of the variables: growth of the real GDP (at constant prices), the growth of labor force, the ratio of the investment share of real GDP and the ratio of external debt and real GDP

Growth of the real GDP (at constant prices)

Growth of the real GDP (at constant prices)

Growth of Labor Force

Growth of Labor Force

Ratio of the investment share of real GDP

Ratio of the investment share of real GDP

The ratio of external debt and real GDP

The ratio of external debt and real GDP

Correlation Matrix (from Covariance Analysis) of natural-log versions of the variables: growth of the real GDP (at constant prices), the growth of labor force, the ratio of the investment share of real GDP and the ratio of external debt and real GDP

Correlations
Control Variables L D D/Y I/Y
Y L Correlation 1.000 -.325 -.370 -.190
Significance (2-tailed) . .086 .048 .323
df 0 27 27 27
D Correlation -.325 1.000 .248 -.142
Significance (2-tailed) .086 . .195 .461
df 27 0 27 27
D/Y Correlation -.370 .248 1.000 -.098
Significance (2-tailed) .048 .195 . .612
df 27 27 0 27
I/Y Correlation -.190 -.142 -.098 1.000
Significance (2-tailed) .323 .461 .612 .
df 27 27 27 0

The model chosen is a linear functional form of your model as it has a matrix with correlation.

Time series graph plots: growth of the real GDP (at constant prices), the growth of labor force, the ratio of the investment share of real GDP and the ratio of external debt and real GDP

Growth of the real GDP

The table below shows how the real GDP for Botswana grew from 1980, which is the first year in the graph from 1,208,609,087 to 7,958,577,275 Pula in the 30th year (which is 2010). The trend of the GDP as depicted by the graph shows a constant increase. The increase can be attributed to an increase in mining activities.

Growth of the real GDP

Growth of the Labor Force

The amount of growth in the labor sector is high with the laborers reaching 996,375 in 2010 from 383,098 in 1980. The labor rise greatly contributes to an increase in the output of the mining sector. Despite the growth in the labor force, the mining industry suffers from the lack of skilled workers who can manage and work in technical jobs.

Growth of the Labor Force

The Ratio of External Debt and Real GDP

The ratio of the external debt and the real GDP has been declining indicating that the country has been offsetting its external debt. The low debt ratio by 2010 can be attributed to good utilization of revenues by the government to finance its budget and the avoidance of external borrowing.

The Ratio of External Debt and Real GDP

A scatter plot of the growth of the real GDP and the ratio of the investment share of real GDP

Graph of IY

The value of R2 is 0.029, which is the variance of the dispersion of I/Y. This value is low and the best of fit line does not fall on any of the points thus indicating variation.

Graph of L

A scatter plot of the growth of the real GDP and the growth of labor force

The value of R2 is 0.993, which is the variance of the dispersion of L. The value is high, and the best of fit line nearly cuts on all of the points. This trend indicates that there is minimal variation from the mean.

Graph of DY

A scatter plot of the growth of the real GDP and the ratio of external debt and real GDP

The value of R2 is 0.832, which is the variance of the dispersion of D/Y. The value is fairly high and the best of fit line does not match any of the points thereby indicating the variation.

Regression of the growth of the real GDP (at constant prices) on the ratio of the investment share of real GDP, the growth of labor force and the ratio of external debt and real GDP

Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .672a .452 .386 125611231.174
a. Predictors: (Constant), ?D/?Y, ?D, ?L
Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) 240580482.422 129112448.480 1.863 .074
?L -481.354 6011.619 -.014 -.080 .937
?D -.961 .232 -.652 -4.138 .000
?D/?Y 131934704.386 60806929.313 .381 2.170 .040
a. Dependent Variable: ?Y
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 325300163399236220.000 3 108433387799745408.000 6.872 .002b
Residual 394454534923502460.000 25 15778181396940098.000
Total 719754698322738690.000 28
a. Dependent Variable: ?Y
b. Predictors: (Constant), ?D/?Y, ?D, ?L

The R2 value depicts 0.672 of the variations are explained by the total variation. The coefficients of beta for L-0.014, D-0.652 and D/Y-0.381 affect the variations with these weights. The three variables vary uniquely with each having a different prediction (p) for L-0.08, D-4.138 and D/Y 2.170. The significance of the variables as indicated by the ANOVA table (p=0.002) shows that the model is significant. The variations of the variables as depicted by R2 compared with adjusted R2 have no large difference, which indicates that the variables are related and interdependent.

Residual graph for the growth of labor force

The graph depicts the high growth of labor in the country. The contraction of labor growth between 2001 and 2007 is due to the movement of labor out of the country to the Asian countries.

Graph of logY

Residual graph for the ratio of the investment share of real GDP

The graph of the ratio of investment share of real GDP is negative, which depicts low investments and a bigger portion of the income has to be used in expenditures rather than in investments.

Graph of DY

Residual graph for the ratio of external debt and real GDP

The residual graph for the ratio of external debt and real GDP indicates that there are negative values. The negative values are due to a decline in the level of income where the change in GDP is negative. However, the level of the ratio declines indicating a decline in the debt.

The test of significance at a 5% significance level of the independent variable on the dependent variable of the model is done in Step 15.

One-Sample Test
Test Value = 0
t df Sig. (2-tailed) Mean Difference 95% Confidence Interval of the Difference
Lower Upper
I/Y 21.836 29 .000 .4078567 .369656 .446058
L 18.513 29 .000 665329.667 591828.34 738831.00
D/Y 6.127 29 .000 .21400 .1426 .2854
D 10.267 29 .000 566895032.3433 453971329.108 679818735.578

The variables have t values that are different. D/Y has a t value of 6.127 and has the least confidence interval indicating minimal dispersion.

Testing the overall significance at a 5% significance level of independent variables on the dependent of the model in Step 15

One-Sample Statistics
N Mean Std. Deviation Std. Error Mean
I/Y 30 .407857 .1023038 .0186780
L 30 665329.67 196840.180 35937.936
D/Y 30 .2140 .19130 .03493
D 30 566895032.343 302415231.3497 55213214.6478

Heteroscedasticity

Heteroscedasticity does not exist as the correlation matrix depicts. The high dispersion of variables is not a cause of heteroscedasticity. The model is consistent and significant because the correlation matrix indicates the values of each variable from the matrix have constant variance.

Correlations
Control Variables L D D/Y I/Y
year L Correlation 1.000 -.787 .240 .126
Significance (2-tailed) . .000 .211 .514
Df 0 27 27 27
D Correlation -.787 1.000 .266 -.192
Significance (2-tailed) .000 . .164 .318
df 27 0 27 27
D/Y Correlation .240 .266 1.000 -.194
Significance (2-tailed) .211 .164 . .314
df 27 27 0 27
I/Y Correlation .126 -.192 -.194 1.000
Significance (2-tailed) .514 .318 .314 .
df 27 27 27 0

Heteroscedasticity does not exist because it is below significant levels. The absence of heteroscedasticity indicates that the variance of the data is limited. Multicollinearity does not also exist as the model’s two-tailed test value of significance is zero. The variables are covered explicitly by the model. In addition, there is no autocorrelation indicating that the values are not correlated.

Works Cited

Atsushi Iimi 2006, “Did Botswana Escape from the Resource Curse?IMF Working Paper African Department. Web.

Barro, Robert J 1997, “Determinants of Economic Growth: A Cross-Country Empirical Study.NBER Working Paper No. 5698. Web.

Corden, Max W. and Peter J. Neary. “Booming Sector and De-Industrialisation in a Small Open Economy.” Economic Journal, 92.368(1982): 825-848. Print.

Gupta, Sanjeev, Benedicts Clements, Alexander Pivovarsky, and Erwin Tiongson 2003, “Foreign Aid and Revenue Response: Does the Composition of Aid Matter?” IMF Working Paper 03/176. Web.

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