Interactions between business conditions, economic growth and crude oil prices

An earlier version of this research article was presented in the 11th Conference of the Eurasia-Business-and-Economics-Society (EBES), Location: Russian Acad Sci, Inst Econ, Ural Branch, Ekaterinburg, Russia, September 12–14, 2013.

Figures & data

Table 1. PP (1988) Unit Root Test.

Variables	With Constant	And time trend	With constant,	But no time trend
	Level	First difference	Level	First difference
Euro Area
Ln GDP	-1.3027[2]	-5.0151[5]*	-1.8286[4]	-4.8309[4]*
Ln IND	-2.5630[3]	-5.5881[5]*	-1.1276[4]	-5.6489[5]*
Ln Oil	-2.4258[2]	-7.7698[0]*	-2.4143[3]	-7.8637[1]*
European Union
Ln GDP	-1.9922[2]	-4.5994[5]*	-1.1315[3]	-4.5882[4]*
Ln IND	-2.7135[3]	-5.5630[6]*	-0.9048[5]	-5.6413[6]*
Ln Oil	-2.3677[3]	-7.8682[1]*	-2.3158[3]	-7.8698[2]*
Latin America and the Caribbean
Ln GDP	-2,4462[1]	-4.2817[4]*	-0.4945[0]	-4.4178[4]*
Ln IND	-2.6025[1]	-4.3972[5]*	-0.5028[2]	-4.5304[5]*
Ln Oil	-1.4055[3]	-7.2066[3]*	-0.9314[3]	-7.0490[3]*
South Asia
Ln GDP	-0.7610[0]	-7.4202[3]*	4.3221[4]	-6.0670[3]*
Ln IND	-1.2491[3]	-4.6542[7]*	2.9882[7]	-4.4428[3]*
Ln Oil	-2.5609[3]	-7.3399[2]*	-1.5526[3]	-7.4751[2]*
Sub-Saharan Africa
Ln GDP	0.2357[2]	-4.7079[2]*	1.9939[2]	-3.7462[2]*
Ln IND	-0.7290[3]	-3.8096[1]**	1.1794[2]	-3.5459[0]**
Ln Oil	-2.1698[3]	-7.3184[2]*	-1.1923[2]	-7.3456[2]*

Note: This table reports the results of the Pillps-Perron (PP) tests applied to time series data. The test is based on the null hypothesis of a unit root. All of the series are at their natural logarithms. GDP represents real gross domestic product; IND represents industrial productions; oil represents oil prices. When using PP test, numbers in brackets represent Newey-West Bandwith (as determined by Bartlett-Kernel). PP test unit root test where performed from the most general to the least specific model by eliminating trend and intercept across the models.

Source: Authors’ own calculations.

*, ** and *** denote rejection of the null hypothesis at the 1%, 5% and 10% levels respectively. The bold values ‘-2.42’ and ‘-2.41’ are not statistically significant, while the bold values ‘-4.44’ and’-7.33’ are statistically significant at the 1% level. Test for unit roots have been carried out in E-VIEWS 6.0.

Table 2. Zivot and Andrews Test.

Variables	Ln Oil	Ln GDP	Ln IND
Euro Area
Model A	-4.615[0]	-3.637[2]	-3.769[1]
Model B	-5.417[0]	-4.090[2]	-3.281[0]
Model C	-5.246[0]	-3.947[2]	-3.952[0]
European Union
Model A	-4.684[0]	-3.542[1]	-4.107[1]
Model B	-5.210[0]	-3.656[1]	-3.394[0]
Model C	-4.993[0]	-4.218[3]	-4.022[0]
Latin America and the Caribbean
Model A	-3.696[0]	-2.161[0]	-5.058[4]
Model B	-4.691[0]	-3.902[2]	-4.709[2]
Model C	-4.539[0]	-2.703[0]	-4.929[4]
South Asia
Model A	-4.640[0]	-2.775[0]	-3.521[0]
Model B	-4.896[0]	-3.400[0]	-4.083[1]
Model C	-4.633[0]	-3.353[0]	-4.147[1]
Sub-Saharan Africa
Model A	-4.971[0]	-2.335[2]	-2.579[1]
Model B	-4.679[0]	-5.102[2]	-3.036[1]
Model C	-4.314[0]	-4.970[2]	-4.132[0]

Note: This test includes three models, those are: model A, model B and model C and critical values at 1%, 5% and 10% significance levels are -4.24, -4.80 and -5.34 respectively for model A, and -4.93, -4.42 and -4.11 respectively for model B and, -5.57, -5.08 and -4.82 respectively for model C. It is quoted to remind that the all and alternative hypothesis of ZA tests are the same with those in ADF and PP tests.

Source: Authors’ own calculations.

Table 3. Critical Values for the ARDL Modelling Approach.

K=2	0.10		0.05		0.01
	I (0)	I (1)	I (0)	I (1)	I (0)	I (1)
FIV	3.66	4.37	4.36	5.13	5.98	6.97
FV	4.47	5.42	5.38	6.43	7.52	8.80
FIII	3.37	4.37	4.13	5.26	5.89	7.33

Note: K is the number of regressors for the dependent variable in ARDL models, F_IV represents the F-statistic of the model with unrestricted intercept and restricted trend, F_V represents the F-statistic of the model with unrestricted intercept and trend, and F_III represents the F statistic of the model with unrestricted intercept and no trend. Source: Narayan (2005) for F-statistics.

Source: Authors’ own calculations.

Table 4. Bounds Tests for Level Relationships.

Variables	With Deterministic Trends			Without Deterministic Trend
	FIV	FV		FIII	Conclusion
Euro Area
F (lnGDP / lnOIL, lnIND)					H0
p = 3^*	9.851c	8.652c	p = 1^*	9.764c
4	1.842a	1.601a	2	3.936b	Rejected
5	1.773a	1.784a	3	3.265a
6	1.345a	1.533a	4	0.987a
European Union
F (lnGDP / lnOIL, lnIND)					H0
p = 3^*	7.000c	6.432c	p = 1^*	8.191c
4	2.421a	2.036a	2	2.185a	Rejected
5	5.023b	5.141b	3	2.632a
6	2.237a	2.684a	4	1.824a
Latin America & Carribean
F (lnGDP / lnOIL, lnIND)					H0
p = 1^*	5.951c	7.765c	p = 1^*	5.432c	Rejected
2	2.702a	3.581a	2	1.604a
3	3.274a	4.362a	3	3.865a
4	1.411a	1.563a	4	1.044a
South Asia
F (lnGDP / lnOIL, lnIND)					H0
p = 3^*	4.251b	4.784b	p = 3^*	5.222c	Rejected
4	2.074a	2.743a	4	2.087a
5	1.471a	1.931a	5	2.074a
6	2.853a	3.658a	6	4.173a
Sub-Sharan Africa
F (lnGDP / lnOIL, lnIND)					H0
p = 2^*	4.533c	2.969a	p = 2^*	3.455b	Rejected
3	2.067a	1.544a	3	2.293a
4	2.584a	0.846a	4	2.951a
5	9.429c	5.932c	5	7.710c

Note: Schwartz Criteria (SC) was used to select the number of lags required in the co-integration test. p shows lag levels and.

Source: Authors’ own calculations.

^* denotes optimum lag selection in each model as suggested by SC. F_IV represents the F statistic of the model with unrestricted intercept and restricted trend, F_V represents the F statistic of the model with unrestricted intercept and trend, and F_III represents the F statistic of the model with unrestricted intercept and no trend. t_V and t_III are the t ratios for testing σ₁ = 0 in equations (15) through (20) with and without deterministic linear trend.

^a İndicates that the statistic lies below the lower bound.

^b That it falls within the lower and upper bounds.

^c That it lies above the upper bound.

Table 5. Level coefficients in the long-run growth models through the ARDL approach.

	Dependent Variable		Regressors
	lnGDP	lnOIL	lnIND	Intercept
Euro Area	-	-0.024*	0.702*	9.563
European Union	-	-0.018**	0.283	21.326*
Latin America and the Caribbean	-	0.011*	0.838*	5.402
South Asia	-	0.011	0.936*	3.098*
Sub-Saharan Africa	-	0.100*	-0.127	28.429

Notes: Numbers in brackets are prob. values of t statistics in each model.

Source: Authors’ own calculations.

^*, ^** and ^*** denote the statistical significance at the 1%, 5%, and 10% levels respectively.

Table 6a. Conditional error correction models through the ARDL approach.

Panel (a). Euro Area				Panel (b). European Union
Dependent Variable: GDP (5, 1, 3)^a				Dependent Variable: GDP (5, 5, 2)^a
Regressor	Coefficient	Standard Error	T-Test	Regressor	Coefficient	Standard Error	T-Test
ût-1	-0.2545	0.0554	-4.5911	ût-1	-0.2491	0.0630	-3.9504
ΔlnGDPt-1	0.2047	0.1539	1.3299	ΔlnGDPt-1	-0.0845	0.1680	-0.5028
ΔlnGDPt-2	0.2782	0.1484	1.8747	ΔlnGDPt-2	0.1328	0.0426	3.1131
ΔlnGDPt-3	-0.0454	0.0346	-1,3111	ΔlnGDPt-3	0.0888	0.0467	1.8995
ΔlnGDPt-4	-0.1168	0.0366	-3.1908	ΔlnGDPt-4	-0.0977	0.0343	-2.8436
ΔlnOIL	-0.0037	0.0017	-2.1852	ΔlnOIL	-0.0024	0.0015	-1.6444
ΔlnIND	0.4582	0.0147	31.0414	ΔlnOILt-1	0.0038	0.0020	1.9218
ΔlnINDt-1	-0.0718	0.0736	-0.9753	ΔlnOILt-2	0.0030	0.0020	1.5292
ΔlnINDt-2	-0.1585	0.0785	-2.0190	ΔlnOILt-3	0.0057	0.0018	3.1556
Intercept	0.0027	0.0020	1.3399	ΔlnOILt-4	0.0038	0.0013	2.8560
				ΔlnIND	0.4984	0.0171	29.0232
				ΔlnINDt-1	0.1663	0.0909	1.8298
				Intercept	0.0044	0.0030	1.4373
Adj. R^2= 0.9866, S.E. of Regr. = 0.0021, AIC = -9.1610, SBC = -8.7076, F-stat. = 189.5564, F-prob. = 0.000, D-W stat. = 2.2312				Adj. R^2= 0.9900, S.E. of Regr. = 0.0020, AIC = -9,3041, SBC = -8.7146, F-stat. = 165,4214, F-prob. = 0.000, D-W stat. = 2.3838

^a Denotes p lag structures in the model.

Source: Authors’ own calculations.

Table 6b. Conditional error correction models through the ARDL approach (continued).

Panel (c). Latin America and the Caribbean				Panel (d). South Asia
Dependent Variable: GDP (2, 2, 4)^a				Dependent Variable: GDP (3, 1, 1)^a
Regressor	Coefficient	Standard Error	T-Test	Regressor	Coefficient	Standard Error	T-Test
ût-1	-0.4828	0.1116	-4.3238	ût-1	-0.3906	0.0796	-4.9026
ΔlnGDPt-1	0.4807	0.1397	3.4410	ΔlnGDPt-1	-0.2477	0.0860	-2.8812
ΔlnOIL	-0.0028	0.0033	-0.8400	ΔlnGDPt-2	-0.0663	0.0905	-0.7322
ΔlnOILt-1	-0.0080	0.0035	-2.2462	ΔlnOIL	-0.0058	0.0064	-0.9103
ΔlnIND	0.07336	0.0337	21.7400	ΔlnIND	0.7754	0.0767	10.1020
ΔlnINDt-1	-0.3356	0.1035	-3.2422	Intercept	-0.0004	0.0076	-0.0537
ΔlnINDt-2	-0.0905	0.0381	-2.3725
ΔlnINDt-3	0.0526	0.0396	1.3291
Intercept	0.0044	0.0026	1.6682
Adj. R^2= 0.9622, S.E. of Regr. = 0.0053 AIC = -7.4096, SBC = -7.0056, F-stat. = 79.7544, F-prob. = 0.000, D-W stat. = 1.9183				Adj. R^2= 0.8323, S.E. of Regr. = 0.0099, AIC = -6.2262, SBC = -5.9595, F-stat. = 28.7978, F-prob. = 0.000, D-W stat. = 2.0233

^a Denotes p lag structures in the model.

Source: Authors’ own calculations.

Table 6c. Conditional error correction models through the ARDL approach (continued).

Panel (e). Sub-Saharan Africa
Dependent Variable: GDP (8, 5, 7)^a
Regressor	Coefficient	Standard Error	T-Test
ût-1	-0.3725	0.0588	-6.3285
ΔlnGDPt-1	-0.0837	0.1592	-0.5260
ΔlnGDPt-2	-0.5767	0.1258	4.5838
ΔlnGDPt-3	-0.2204	0.1755	-1.2554
ΔlnGDPt-4	-0.0781	0.1041	-0.7504
ΔlnGDPt-5	0.6736	0.1144	5.8844
ΔlnGDPt-6	0.5278	0.1026	5.1420
ΔlnGDPt-7	0.0599	0.0898	-0.6676
ΔlnOIL	0.0019	0.0042	0.4719
ΔlnOILt-1	-0.0011	0.0039	-0.2861
ΔlnOILt-2	-0.0101	0.0052	-1.9543
ΔlnOILt-3	-0.0074	0.0060	-1.2425
ΔlnOILt-4	0.0129	0.0055	2.3492
ΔlnIND	0.5981	0.0408	14.6446
ΔlnINDt-1	0.0197	0.0813	0.2426
ΔlnINDt-2	-0.1163	0.0552	-2.1042
ΔlnINDt-3	-0.0070	0.0579	-0.1217
ΔlnINDt-4	-0.1153	0.0523	-2.2026
ΔlnINDt-5	-0.3547	0.0648	-5.4679
ΔlnINDt-6	-0.3612	0.0835	-4.3232
Intercept	7.7123	0.0062	1.2307
Adj. R^2= 0.9924, S.E. of Regr. = 0.0030,
AIC = -8.5343, SBC = -7.5534,
F-stat. = 59.4348, F-prob. = 0.000,
D-W stat. = 2.3575

^a Denotes p lag structures in the model.

Source: Authors’ own calculations.

Narayan, P. K. (2005). The saving and investment Nexs for China: Evidence from Co integration Tests. Applied Economics, 37, 1979–1990.10.1080/00036840500278103

 Web of Science ®Google Scholar