Investigating the effect of governance on unemployment: a case of South Asian countries

Variable	Description	Units	Source
UE	Unemployment rate	% of the total labor force	World Bank
GOV	Governance	Index	Worldwide Governance Indicators
POP	Population growth	Annual %	World Bank
IU	Internet users	Per 100 people	World Bank
MCS	Mobile cellular subscriptions	Per 100 people	World Bank
FBS	Fixed broadband subscriptions	Per 100 people	World Bank
FA	Financial activity	Credit	FDSD
HC	Human capital (education)	Gross % of enrollment	World Bank

Table 2

Descriptive statistics

	UE	GOV	POP	IU	MBS	FBS	HC	FA
Mean	4.4891	0.0045	−0.0259	−0.0798	26.04072	1.0522	−0.0061	40.194
Median	3.9120	0.0074	−0.0357	0.3329	4.761983	0.4996	−0.0966	44.160
Maximum	13.030	0.5988	0.9557	9.5000	115.3790	5.7863	2.7491	86.186
Minimum	0.6500	−0.8829	−1.0564	−21.824	0.000000	−2.1401	−3.4107	−13.850
SD	2.7037	0.2420	0.2114	3.7815	32.52466	1.6768	1.4838	23.982
Skewness	1.2746	−0.4964	0.2574	−2.5320	0.884126	1.1617	−0.2005	−0.6672
Kurtosis	4.1690	4.1290	15.782	13.930	2.372628	4.0800	2.2792	2.7402
Jarque–Bera	46.539	13.373	968.27	858.61	20.79126	38.842	4.0249	10.936
Probability	0.0000	0.0012	0.0000	0.0000	0.0000	0.0000	0.1336	0.004219
Observations	161	161	161	161	161	161	161	161

[i] SD, standard deviation.

Table 3

Panel unit root test

	Levin, Lin & Chu test				Im, Pesaran and Shin test
Variables	Level		First difference		Level		First Difference		Decision
	T−statistics	P−value	T−statistics	P−value	T−statistics	P−value	T−statistics	P−value
UE	−2.427	0.007	−9.034	0.00	−0.454	0.324	−9.715	0.00	I(1)
GOV	−1.626	0.051	−8.769	0.00	−1.28	0.098	−10.05	0.00	I(1)
POP	1.346	0.910	−3.234	0.00	−2.34	0.009	−7.624	0.00	I(1)
IU	5.966	1.000	−9.196	0.00	−1.41	0.078	−9.829	0.00	I(1)
MCS	−1.538	0.062	−5.641	0.00	−3.38	0.000	49.68	0.00	I(1)
FBS	0.114	0.545	−4.275	0.00	−0.832	0.202	49.17	0.00	I(1)
FA	−0.306	0.379	−10.21	0.00	0.007	0.503	−7.058	0.00	I(1)
HC	0.333	0.630	−8.735	0.00	1.400	0.919	−5.99	0.00	I(1)

[i] Null hypothesis: There is a unit root/variable is not stationary.

Table 4

Optimal lag length selection

Lag	Log (L)	LR	FPE	AIC	SC	HQ
0	−1785.819	NA	20168.37	32.61488	32.81128	32.69454
1	−1085.927	1285.255	0.192653	21.05322	22.82081	21.77016
2	−939.9511	246.8322	0.044144	19.56275	22.90152	20.91697
3	−897.7784	65.17604	0.068647	19.95961	24.86957	21.95112
4	−841.4533	78.85510	0.086160	20.09915	26.58030	22.72794

Table 5

Results for Johansen cointegration test

Hypothesized no. of CE(s)	Fisher’s statistic* (from trace test)	p	Fisher’s statistic* (from max-Eigen test)	p
None	6.931	0.7319	6.931	0.7319
At most 1	5.545	0.8519	23.97	0.0077*
At most 2	1.386	0.9992	75.07	0.0000*
At most 3	92.10	0.0000*	92.10	0.0000*
At most 4	205.2	0.0000*	124.7	0.0000*
At most 5	117.9	0.0000*	84.62	0.0000*
At most 6	55.01	0.0000*	41.14	0.0000*
At most 7	35.30	0.0001*	35.30	0.0001*

[i] Null hypothesis: There is no cointegration.

CE, cointegration equation.

*Cointegration exits in this equation.

Table 6

Results for Kao Residual Cointegration Test

Kao Residual Cointegration Test	t-Statistic	p
ADF	−5.252339	0.0000
Residual variance	29.53757
HAC variance	27.06740

[i] Null hypothesis: There is no cointegration.

Table 7

Long-run relationship of VECM

Variables	Coefficients	Standard errors	t−value
FA (–1)	+0.620559	0.95581	−3.59327
FBS (–1)	−0.531762	15.2189	2.64497
GOV (–1)	−0.526023	91.4792	3.20063
HC (–1)	−0.450647	9.79514	2.60362
IU (–1)	−0.334496	7.54714	4.85044
MCS (–1)	−0.127821	0.68663	2.48479
POP (–1)	+0.802420	193.675	−8.16830
C	10.84378
CointEq1	−0.072136	0.01545	−4.66826
R-squared	0.641065
F-statistic	2.535735

[i] VECM, vector error correction model.

Table 8

Results of the Granger causality test

Granger causality test: emerging and growth leading economies

Null hypothesis	F-statistics	p	Decision
GOV does not Granger cause UE	3.04895	0.0505**	Bidirectional
UE does not Granger cause GOV	2.90152	0.0582**	Causality
POP does not Granger cause UE	1.05352	0.3514	No
UE does not Granger cause POP	1.62622	0.2003	Causality
HC does not Granger cause UE	0.85811	0.4265	No
UE does not Granger cause HC	0.45764	0.6339	Causality
IU does not Granger cause UE	2.82781	0.0947**	Unidirectional
UE does not Granger cause IU	1.27496	0.2606	Causality
MCS does not Granger cause UE	0.26316	0.7690	No
UE does not Granger cause MCS	0.27047	0.7634	Causality
FBS does not Granger cause UE	0.55304	0.4582	Unidirectional
UE does not Granger cause FBS	6.51372	0.0117*	Causality
FA does not Granger cause UE	0.76037	0.4696	No
UE does not Granger cause FA	0.80089	0.4512	Causality

[i] Decision rule: Reject H0, if the p-value is less than 0.05.

*Signifies the refusal of a null hypothesis at the 5% level of significance.

**Signifies the refusal of a null hypothesis at the 10% level of significance.

Impulse Response Function: Response to Generalized 1 SD Innovations. SD, standard deviation.

Table 9

Results for forecast error variance decompositions

Period	SE	UE	GOV	POP	IU	MCS	FBS	FA	HC
1	0.700	100.0	0.000	0.000	0.000	0.000	0.000	0.000	0.000
2	0.981	97.54	0.256	0.026	0.038	0.013	0.000	1.816	0.307
3	1.217	97.24	0.261	0.198	0.068	0.312	0.032	1.182	0.699
4	1.504	84.46	1.274	0.254	6.263	0.204	0.316	6.398	0.825
5	1.934	77.34	1.461	0.184	4.640	0.313	0.734	14.294	1.027
6	2.337	71.70	1.763	0.387	3.840	0.291	1.342	17.824	2.843
7	2.809	65.31	1.772	2.655	4.638	0.372	1.564	19.187	4.492
8	3.310	61.43	1.482	6.417	4.493	0.300	1.196	18.027	6.644
9	3.841	58.62	1.117	10.85	4.144	0.277	1.009	16.616	7.356
10	4.354	56.41	1.058	15.73	3.763	0.259	0.939	13.943	7.888

Table 10

Serial Correlation Test

Lags	LM-Stat	p
1	98.19758	0.0039
2	104.3011	0.0011
3	95.75344	0.0062
4	79.53887	0.0912
5	83.15507	0.0541

[i] Null hypothesis: There is no serial correlation.

Table 11

Heteroscedasticity Test (Breusch–Pagan–Godfrey)

Test	Chi-square	p
Joint test	3067.172	0.0683

[i] Null hypothesis: homoscedasticity.

Table 12

Multicollinearity Test

Variables	FA	FBS	GOV	HC	IU	MBS	POP
FA	1.00
	–
FBS	−0.56	1.00
	−8.16	–
GOV	−0.10	0.16	1.00
	−1.20	2.00	–
HC	0.65	−0.23	−0.04	1.00
	10.3	−2.85	−0.51	–
IU	0.26	−0.08	−0.14	0.21	1.00
	3.22	−1.03	−1.77	2.58	–
MBS	−0.36	0.13	0.17	−0.21	−0.27	1.00
	−4.70	1.58	2.08	−2.54	−3.38	–
POP	−0.08	0.15	0.06	−0.10	−0.00	0.04	1.00
	−1.01	1.83	0.72	−1.26	−0.10	0.53	–
UE	−0.24	0.04	0.02	−0.03	0.09	−0.23	−0.28
	−2.99	0.57	0.34	−0.47	1.08	−2.82	−3.46

Table 13

Lags exclusion Wald test

	Chi-squared test statistics for lag exclusion

	d(UE)	d(FA)	d(FBS)	d(GOV)	d(HC)	d(IU)	d(MCS)	d(POP)	Joint
DLag 1	2.506	14.929	17.171	27.848	16.686	10.531	30.875	105.051	287.87
	[0.9614]	[0.0605]	[0.0284]	[0.0005]	[0.0335]	[0.229]	[0.0001]	[0.0000]	[0.000]
DLag 2	3.002	19.338	31.285	12.528	21.656	8.153	13.469	26.211	154.698
	[0.9342]	[0.0132]	[0.0001]	[0.129]	[0.0056]	[0.418]	[0.0967]	[0.0010]	[0.000]
DLag 3	11.082	15.685	12.816	2.6085	19.692	2.411	4.8671	35.783	110.890
	[0.1971]	[0.0471]	[0.1183]	[0.956]	[0.0116]	[0.965]	[0.7717]	[0.0000]	[0.0003]
DLag 4	14.027	16.400	76.592	3.212	13.160	13 .564	19.335	47.179	200.654
	[0.0011]	[0.0370]	[0.0000]	[0.9203]	[0.1065]	[0.093]	[0.0132]	[0.0000]	[0.0000]
df	8	8	8	8	8	8	8	8	64

[i] The numbers written in [] are p-values.

References

Authors

Metrics

Articles in this issue

DOI: https://doi.org/10.2478/ijme-2019-0012 | Journal eISSN: 2543-5361 (formerly 2299-9701) | Journal ISSN: 2299-9701

Journal RSS Feed

Language: English

Page range: 160 - 181

Submitted on: Apr 12, 2019

Accepted on: Jul 12, 2019

Published on: Jun 30, 2019

Published by: SGH Warsaw School of Economics

In partnership with: Paradigm Publishing Services

Publication frequency: 4 issues per year

Keywords:

economic variables,

unemployment,

VECM,

South Asian countries,

governance,

ICT

JEL:

E24,

J64,

000,

011,

E02

Related subjects:

Business and economics,

Business management,

Management accounting, financial controlling, cost calculation, investment

© 2019 Aiza Shabbir, Shazia Kousar, Farzana Kousar, Amna Adeel, Rana Adeel Jafar, published by SGH Warsaw School of Economics
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 55 (2019): Issue 2 (June 2019)

Investigating the effect of governance on unemployment: a case of South Asian countries

Figures & Tables

Figure 1

Table 1

Figure 2