Symmetrical cointegrating relationship between money supply, interest rates, consumer price index, terroristic disruptions, and Karachi stock exchange: Does global financial crisis matter?

Figures & data

Figure 1. Macroeconomic variability and KSE-100 indexes

Table 1. Variables of interest

Variables	Positive relationship with stock indexes	Negative relationship with stock indexes	Studies included control measure like terroristic attacks?	Relationship between macroeconomic and stock prices in different regimes	Studies carried out in Pakistan
Interest rate(IR)	(Adjasi, 2009; Ghulam, 2018; Günsel et al., 2009; Kocaarslan & Soytas, 2019; Peiró, 2016)	(Ho, 2018)	Not included	Not included	Not included
Money supply(MS)	(Chiang Leong & Hui, 2014; Shrestha & Liu, 2008)	(Adjasi, 2009; Adjasi et al., 2011)	Not included	Not included	Not included
Consumer price Index (CPI)	(Shrestha & Liu, 2008; Adjasi, 2009; Adjasi et al., 2011)	(Agyire‐Tettey & Kyereboah‐Coleman, 2008; Camilleri et al., 2019; Chiang Leong & Hui, 2014; Ho, 2018)	Not included	Not included	Not included

Note: This table shows that some of research articles reported positive and some of them reported negative influence of selected macroeconomic fluctuation on stock indexes without undertaking regime dependence and control measures such as terroristic disruptions. Most of researches have targeted stock markets of developed countries.

Table 2. Descriptive statistics of whole sample period

Statistics	Consumer price index	Interest rate	Money supply	KSE-100 index	Bomb blasts	Terrorist killed	Army men killed
Mean	137.6042	9.065972	1636.258	12082.77	0.618056	208.6389	41.88194
Median	130.0000	9.000000	1355.000	10845.03	0.000000	138.5000	36.50000
Maximum	225.0000	14.50000	4620.629	29984.00	6.000000	1590.000	157.0000
Minimum	60.00000	5.500000	300.0000	2399.140	0.000000	0.000000	0.000000
Std. Dev.	42.64002	2.478048	1192.136	6705.221	0.946074	264.0019	34.43256
Skewness	0.354152	0.802891	0.710961	1.175114	2.218304	2.334732	1.047246
Kurtosis	2.200803	2.963906	2.395855	3.955827	10.22159	10.19846	4.117263
Jarque-Bera	6.842468	15.47902	14.32114	38.62305	431.0090	441.7306	33.81102
Probability	0.032672	0.000435	0.000777	0.000000	0.000000	0.000000	0.000000
Sum	19815.00	1305.500	235621.1	1739919.	89.00000	30044.00	6031.000
Sum Sq. Dev.	259998.4	878.1233	2.03E+08	6.43E+09	127.9931	9966669.	169541.0
Observations	156	156	156	156	156	156	156

Table 3. Descriptive statistics of postcrisis period

Statistics	KSE100 index	Consumer price index	Interest rate	Money supply	Bomb blasts	Army men killed	Terrorist killed
Mean	14943.03	164.3678	9.155172	2366.852	0.839080	58.19540	324.2874
Median	12289.03	160.0000	9.000000	2250.000	1.000000	50.00000	250.0000
Maximum	29984.00	225.0000	14.50000	4620.629	6.000000	157.0000	1590.000
Minimum	5377.420	120.0000	5.500000	950.0000	0.000000	20.00000	16.00000
Std. Dev.	6831.949	31.95022	2.568040	990.1829	1.066112	30.15072	282.3244
Skewness	0.973982	0.353705	0.474441	0.447448	1.887397	1.257343	2.073392
Kurtosis	2.864196	1.981788	2.432152	2.255259	8.364696	4.446460	8.421974
Jarque-Bera	13.82215	5.572296	4.432751	4.913608	155.9803	30.50760	168.9019
Probability	0.000997	0.061658	0.109003	0.085708	0.000000	0.000000	0.000000
Sum	1300043.	14300.00	796.5000	205916.1	73.00000	5063.000	28213.00
Sum Sq. Dev.	4.01E+09	87790.23	567.1552	84319741	97.74713	78179.68	6854806.
Observations	84	84	84	84	84	84	84

Table 4. Descriptive statistics of precrisis period

Statistics	KSE100 index	Interest rate	Consumer price index	Money supply	Bomb blasts	Army men killed	Terrorist killed
Mean	7935.521	9.118644	97.54237	535.6780	0.271186	19.71186	39.42373
Median	7770.520	9.000000	100.0000	550.0000	0.000000	10.00000	9.000000
Maximum	14321.39	14.50000	120.0000	950.0000	3.000000	143.0000	341.0000
Minimum	2399.140	6.500000	60.00000	300.0000	0.000000	0.000000	0.000000
Std. Dev.	3467.413	2.522893	16.51470	183.3088	0.582223	27.98402	69.40491
Skewness	0.145594	1.261307	−0.411634	0.598119	2.539981	2.343820	2.569844
Kurtosis	1.793361	3.506180	2.085701	2.354892	10.33831	9.138219	9.597704
Jarque-Bera	3.787724	16.27368	3.721213	4.540912	195.8231	146.6438	171.9508
Probability	0.150489	0.000293	0.155578	0.103265	0.000000	0.000000	0.000000
Sum	468195.8	538.0000	5755.000	31605.00	16.00000	1163.000	2326.000
Sum Sq. Dev.	6.97E+08	369.1695	15818.64	1948923.	19.66102	45420.10	279388.4
Observations	84	84	84	84	84	84	84

Table 5. BDS test of nonlinearity

Dimensions	BDS test statistics	Std.Error	Normal Prob.	Bootstrap Prob.
Variable: Money supply (M2)
2	0.021	0.12	0.651	0.11
3	0.048	0.54	0.890	0.24
4	0.021	0.41	0.791	0.29
5	0.019	0.11	0.322	0.24
6	0.011	0.965	0.984	0.33
Variable: Interest rate
2	0.0431	0.91	0.669	0.23
3	0.0812	0.15	0.711	0.98
4	0.0119	0.29	0.924	0.18
5	0.033	0.114	0.338	0.33
6	0.0924	0.32	0.492	0.14
Variable: Consumer price index
2	0.097	0.126	0.81	0.1
3	0.054	0.599	0.12	0.97
4	0.011	0.323	0.88	0.76
5	0.032	0.761	0.21	0.22
6	0.084	0.459	0.22	0.23

Note: This table reports that null hypothesis of BDS test is not rejected for all macroeconomic fluctuations, this means that time series are not identically distributed and symmetrical ARDL model can be applied for these variables.

Table 6. Augmented Dickey fuller test

Variables	At level		First differencing		Order of integration
	Intercept	Intercept and trend	Intercept	Intercept and trend
Stock indexes	0.10	0.96(.12)	−11.12***	−11.70***	I(1)
Interest rate	0.61	0.99(0.79)	−6.88***	−7.91***	I(1)
Consumer price Index	1.43	1.98	−3.98***	−4.91***	I(1)
Money supply	0.92	1.43	−6.87***	−9.21	I(1)
Bomb blast	1.132	1.56	−2.87***	−3.65***	I(1)
Terrorist killed	1.55	1.62	−9.94*	−12.76***	I(1)
Army person Fatalities	1.09	1.43	−6.32***	−18.87***	I(1)

Table 7. PP unit root test

Variables	At level		First ifferencing		Order of integration
	Intercept	Intercept and trend	Intercept	Intercept and trend
Stock indexes	−0.04	−1.15(.09)	−6.22***	−9.69***	I(1)
Interest rates	0.97	1.411(0.99)	−3.81***	−7.09***	I(1)
Consumer price index	0.23	0.65	−11.76***	−19.72***	I(1)
Money supply	1.25	2.10	−11.91	−13.45	I(1)
Bomb last	−1.11	−2.063	−12.54***	−18.86***	I(1)
Terrorist killed	−1.485	−1.87	−19.076***	−20.54***	I(1)
Army person fatalities	−1.55	−1.77	−26.67***	−29.987***	I(1)

Table 8. KPSS unit root test

Variables	At level		First differencing		Order of integration
	Intercept	Intercept and trend	Intercept	Intercept and trend
Stock indexes	1.76***	1.98***	0.21	0.28	I(1)
Interest rates	1.8***	1.999***	0.33	0.34	I(1)
Consumer price index	1.48***	1.97***	0.19	0.10	I(1)
Money supply	1.55***	1.76***	0.11	0.17	I(1)
Bomb blast	1.79***	1.89***	0.11	0.19	I(1)
Terrorist killed	1.53***	1.68***	0.39	0.41	I(1)
Army person fatalities	1.77***	1.90***	0.51	0.66	I(1)

Table 9. Zivot Andrew unit root test

Variables	At level		First differencing		Order of integration	Structural Breaks
	Intercept	Intercept and trend	Intercept	Intercept and trend
Stock indexes	−1.23	−1.65	−3.756	−6.846	I(1)	2008
Interest rates	−1.59	−1.87	−6.7454	−9.735	I(1)	2008
Consumer price index	−1.4	−2.1	−8.76	−16.32	I(1)	2008
Money supply	−1.59	−1.87	−9.87	−13.21	I(1)	2008
Bomb blast	−1.19	−1.645	−15.75	−19.7465	I(1)	2006
Terrorist killed	−1.3664	−1.745	−21.46	−36.386	I(1)	2006
Army person fatalities	−1.856	−1.9946	−10.756	−12.635	I(1)	2006

***if Value of ZA test statistics is greater than critical value then we can reject null hypothesis that incorporated time series data has a unit root or non-stationary or seasonality effect. ZA unit root test has identified two structural beak dates of 2008 and 2006, we have introduced a two separate dummy variable and significant dummy variables is incorporated in ARDL model.

Table 10. ARDL model before crisis

Variables	Lag0	Lag1
	Long run results
Ln Money supply	−0.54***
Ln CPI	0.176***
IR	−0.165*
Ln Bomb last	0.41*
Ln Terrorist killed	0.0862
Ln Security person fatalities	0.32
	Short-run results
∆ Ln Money supply	−0.12**
∆ Ln CPI	0.127***
∆ IR	−0.73**	−0.10**
∆ Ln Bomb blast	0.91
∆ In Terrorist killed	0.453
∆ In Security person fatalities	0.45*
Dummy02	0.55***
Model fit:
ADJ $R^2$:	0.86
$EC{M}_{t-1}$:	−0.87***
Lm statistics:	0.99
BP test:	0.117
F statistics:	10.50> upper and lower bound critical values @1% and 5%
Ramsey test for model specification:	1.29 <less than critical value and is insignificant

Table 11. ARDL after crisis

Variables	Lag0	Lag1
	Long run results
Ln Money supply	0.52***
Ln CPI	−0.434
IR	−0.931**
Ln Bomb blast	0.24*
Ln Terrorist killed	0.03
Ln Security person fatalities	0.084
	Short-run results
Ln Money supply	0.398**
∆ Ln CPI	0.976	0.265
∆ IR	0.097	0.043
∆ Ln Bomb blast	0.944
∆ In Terrorist killed	0.0298
∆ In Security person fatalities	0.034
Dummy02	0.942***
Model fit:
ADJ $R^2$:	0.77
$EC{M}_{t-1}$:	−0.81***
Lm statistics:	1.15
BP test:	1.75
F statistics:	9.90> upper and lower bound critical values @1% and 5%
Ramsey test for model specification:	1.54 <less than critical value and is insignificant

Table 12. ARDL model when whole sample is selected

Variables	Lag0	Lag1
	Long run results
Ln Money supply	−0.98
Ln CPI	0.734**
IR	0.005
Ln Bomb blast	0.09
Ln Terrorist killed	0.097*
Ln Security person fatalities	0.12
	Short-run results
Ln Money supply	0.118	−0.610
∆ Ln CPI	0.98
∆ IR	−0.076**
∆ Ln Bomb blast	0.0454*	0.55
∆ In Terrorist killed	0.10
∆ In Security person fatalities	0.017*	0.735
Dummy02	0.542	0.098
Model fit:
ADJ $R^2$:	0.65
$EC{M}_{t-1}$:	−0.36***
Lm statistics:	1.32
BP test:	1.33
F statistics:	3.50> upper and but < than lower bound critical values @1% and 5%
Ramsey test for model specification:	1.11 <less than critical value and is insignificant

Figure 2. ARDL models estimated for three different type of regimes are stable

Table 13. Effect of regimes on macroeconomic-stock price nexus

Regime	Money supply	Interest rate	Consumer price index	$EC{M}_{t-1}$	F statistics for long-run cointegration
Long-run results
Precrisis regime	Negative	Negative	Positive		10.50
Postcrisis regime	Positive	Negative	Negative but insignificant		9.90
When whole sample is selected	Negative but insignificant	Positive but insignificant	Positive		3.50
Short-run results
Precrisis regime	Negative	Negative	Positive	−0.87***
Postcrisis regime	Positive	Positive but insignificant	Positive but insignificant	−0.81***
When whole sample is selected	Positive but insignificant	Negative	Positive but insignificant	−0.36***

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