The impact of risk on bilateral trade in the Southern African Customs Union (SACU)

Figures & data

Table 1. Major steps in the construction of composite indices.

Step	Justification	Procedure
i. Theoretical framework	Gives clear understanding and definition of the multidimensional phenomenon to be measured	Literature review
ii. Data selection	Checks quality, strength and weakness of each selected indicator against alternatives	Economic (economic growth, inflation); Social (poverty, unemployment); Environmental (rain, temperature); Technological (road, telephone networks)
iii. Multivariate analysis	Compares the statistically determined structure of the data set to the theoretical framework	Principal Component Analysis
iv. Normalisation	To make scale adjustments and deal with outliers	Min-Max Re-scaling
v. Weighting and aggregation	Selects appropriate weighting and aggregation procedure(s)	Equal weights and Geometric aggregation
vi. Uncertainty and sensitivity analysis	Identifies all possible sources of uncertainty	Sources of uncertainty: weighting and aggregation

Source: OECD (2008).

Table 2. Statistical properties of the eight sub indicators that compose the CI.

Sub indicator	Goalposts for calculating CI		Statistics across SACU countries
	Observed minimum	Observed maximum	Mean	Standard deviation	Skewness
Economic growth	−7.84	12.3	3.67	2.63	−0.590
Inflation	−9.62	33.8	7.01	4.50	2.30
Poverty	9.42	56.2	32.1	15.1	0.363
Unemployment	16.7	38.6	23.8	5.05	1.36
Rain	22.4	131.4	50.5	19.3	1.18
Temperature	12.4	23.0	19.1	3.28	−0.947
Road	0.00253	0.0293	0.00988	0.00828	1.083
Telephone	0.0113	0.122	0.0594	0.0288	0.00890

Source: Calculations based on raw data.

Table 3. Risk dimension statistics.

	Dimension Statistics
	Economic			Social			Environmental			Technological
Country	Mean	Std. dev	PDF^a	Mean	Std. dev	PDF^a	Mean	Std. dev	PDF^a	Mean	Std. dev	PDF^a
Botswana	0.474	0.121	EVM	0.337	0.211	U	0.319	0.102	U	0.449	0.0336	EVM
Lesotho	0.445	0.119	Lp	0.774	0.153	U	0.208	0.0482	Lp	0.0324	0.0142	U
Namibia	0.474	0.050	Lp	0.283	0.129	T	0.299	0.0955	Lp	0.636	0.0817	P
RSA	0.432	0.0562	U	0.219	0.126	U	0.380	0.0332	EVM	0.388	0.0543	U
Swaziland	0.428	0.0422	N	0.451	0.0197	P	0.578	0.0975	EV	0.0591	0.0234	P

^aEVM (ExtValMin); Lp (Laplace); U (Uniform); N (Normal); T (Triangle); P (Pareto); EV (ExtValue).

Source: @Risk Data simulation.

Table 4. Factor loadings based on rotated principal components.

Variable	Rotated factor loadings			Squared factor loading (scaled to unity)			PCA Weights	Unexplained Variance
	Factor1	Factor2	Factor3	Factor1	Factor2	Factor3
Inflation	0.028	−0 . 5644	0 . 6677	0.00	0 . 319	0 . 446	0.109	0.1566
Econgrowth	0.0937	0 . 7424	0.3152	0.01	0 . 551	0.099	0.270	0.1983
Rain	−0 . 3776	−0.1664	−0.248	0.14	0.028	0.062	0.0570	0.378
Temperature	0 . 4267	−0.2093	0.0637	0.18	0.044	0.004	0.138	0.2721
Poverty	−0 . 4555	0.1365	0.3303	0.21	0.019	0.109	0.119	0.1011
Unemployment	−0 . 3698	0.064	−0.1435	0.14	0.004	0.021	0.190	0.47
Roadcapita	0 . 3936	0.1787	0.2936	0.15	0.032	0.086	0.0684	0.302
Telecapita	0 . 4092	−0.0637	−0 . 4164	0.17	0.004	0 . 173	0.0481	0.2003
Explained variance	1.0008	0.9999	1.0000
Explained variance/total	0.3335	0.3332	0.3333

Extraction method: principal components.

Figure 1. Differences between risk indices constructed using different aggregation and weighting procedures.

Table 5. Gravity equation results using different estimators.

Model Estimators: Dependent variable:	RE (PPML) Xij	Pooled (OLS) Ln(Xij)	FE Ln(Xij)	RE (GLS) Ln(Xij)	FGLS Ln(Xij)	RE (MLE) Ln(Xij)
lnGDPj	0.627* (0.000223)	−0.124*** (0.378)	−1.94*** (1.08)	−2.01** (1.07)	−2.04*** (1.30)	−2.01* (0.825)
lnGDPi	−1.78* (0.000290)	−0.267 (0.356)	3.20** (1.52)	3.25** (1.50)	3.84* (1.39)	3.24* (0.887)
lnDistanceij	−1.54*** (0.886)	−1.91* (0.712)		−2.16** (0.100)	−2.05* (0.772)	−2.16** (0.986)
lnPopj	7.46* (0.000954)	0.512 (1.18)	−3.35 (4.05)	−3.35 (4.04)	2.72 (4.93)	3.35 (3.10)
lnPopi	4.60* (0.00102)	1.83 (1.21)	−8.49 (6.02)	−8.16 (5.97)	−7.93*** (4.84)	−8.16* (3.07)
lnRj	0.0567* (0.0000769)	0.173 (0.355)	0.701** (0.319)	−0.712** (0.319)	0.527 (0.413)	0.712* (0.258)
lnRi	−0.994* (0.0000852)	−0.440 (0.463)	−0.575 (0.411)	−0.559 (0.405)	−0.515 (0.427)	−0.559** (0.271)
Borderij	−3.33*** (1.80)	−0.729 (1.26)		−1.28 (1.85)	−0.652 (1.50)	−1.28 (1.92)
Languageij	0.212 (1.52)	2.68 (3.06)		21.8 (16.5)	18.4 (15.2)	21.8** (9.65)
Colonyij	1.96*** (1.11)	2.05* (0.95)		4.75 (3.73)	4.08 (3.16)	4.75** (2.31)
Currency	5.45* (1.53)	−1.99** (0.918)		−2.41 (2.88)	−0.927 (2.91)	2.41 (2.17)
Landlockedij	−1.91*** (3.09)	−3.07 (2.60)		−8.41 (7.40)	−6.96 (6.86)	−8.41 (5.49)
R^2		46	31	63
Prob > F	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
N	6300	2299	2299	2299	2299	2299
Log likelihood	−2.414e+09				−5658.47	−4864.4
Wald chi^2	9.35e+08		925.3	925.3	2052.1	271.5

*, **, and *** are confidence levels at the 1%, 5% and 10% respectively.

OECD (Organisation for Economic Co-operation and Development), 2008. Handbook on constructing composite indicators. Methodology and user guide. OECD Publishing. Paris. https://www.oecd.org/std/42495745.pdf. Accessed 22 March 2016.

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