The role of the macroeconomic environment in shaping capital market co-movement in C.E.E. countries

Figures & data

Table 1. Variables used in the analysis of the macroeconomic determinants of the interdependence between the C.E.E. markets and Western European capital markets.

Variable	Description	Source of data
Dependent variable
${\mathit{WCS}}_{ij,f}$	Are wavelet coherence coefficients between a Western European capital market and a capital market in C.E.E.s where i = Germany and United Kingdom and j = Bulgaria, Croatia, Czech Republic, Estonia, Latvia, Lithuania, Poland, Slovakia and Hungary; and f is the range of frequencies and time that are considered in our analysis: monthly frequency f1 (low frequency), f2 quarterly (3 months) annual frequency f3 (average frequency) and bi-annual frequency f4 (high frequency)	Author calculations based on wavelet coherence analysis
Macroeconomic factors
${\mathit{IPI}}_i$	Seasonally adjusted monthly industrial production index value in the initiator country	Eurostat
${\mathit{IPI}}_{\mathit{dom}}$	The value of the seasonally adjusted monthly industrial production index in the recipient country	Eurostat
${\mathit{Inf}}_i$	Monthly inflation rate value – Harmonized Index of Consumer Prices in value in the initiator country	Eurostat
${\mathit{Inf}}_{\mathit{dom}}$	Monthly inflation rate – Harmonized Consumption Price Index of the recipient country	Eurostat
${\mathit{Intrate}}_i$	The monthly interest rate on 3-month interbank loans in country in the initiator country	World Bank and OECD Database
${\mathit{Intrate}}_{\mathit{dom}}$	Monthly interest rate on 3-month interbank loans in the recipient country	World Bank and OECD Database
${\mathit{Exchrate}}_i$	The value of the exchange rate index in the initiator country	BIS – Bank of International Settlements
${\mathit{Exchrate}}_{\mathit{dom}}$	The value of the exchange rate index in the recipient country	BIS – Bank of International Settlements

Note: Each macroeconomic factor indictor represent either the initiator countries i, or the recipient countries dom. In the case of the initiator – i we have Germany and United Kingdom, and in the case of the recipient dom – can be: Bulgaria, Croatia, Czech Republic, Estonia, Latvia, Lithuania, Poland, Romania, Slovakia and Hungary.

Table 2. Descriptive statistics of the variables used in the analysis.

	${\mathit{WCS}}_{\mathit{ij}.\mathit{}1}$	${\mathit{WCS}}_{\mathit{ij}.\mathit{}2}$	${\mathit{WCS}}_{\mathit{ij}.\mathit{}3}$	${\mathit{WCS}}_{\mathit{ij}.\mathit{}4}$	${\mathit{IPI}}_{\mathit{i}}$	${\mathit{IPI}}_{\mathit{dom}}$	${\mathit{Inf}}_{\mathit{i}}$	${\mathit{Inf}}_{\mathit{dom}}$	${\mathit{Intrate}}_{\mathit{i}}$	${\mathit{Intrate}}_{\mathit{dom}}$	${\mathit{Exchrate}}_{\mathit{i}}$	${\mathit{Exchrate}}_{\mathit{dom}}$
Mean	0.533	0.487	0.484	0.433	101.962	99.009	1.772	3.528	2.350	5.103	107.379	94.500
Median	0.559	0.491	0.495	0.428	102.200	100.300	1.750	2.800	2.087	4.163	104.750	96.790
Maximum	0.996	0.994	0.980	0.978	129.100	151.100	5.200	41.300	6.581	45.150	130.330	121.920
Minimum	0.000	0.000	0.000	0.000	65.600	52.100	−0.800	–3.000	−0.315	−0.390	70.420	56.850
Std. Dev.	0.263	0.261	0.262	0.250	8.946	18.541	1.076	4.394	1.945	5.189	11.706	9.231
Skewness	−0.239	−0.049	−0.070	0.156	−0.300	−0.142	0.476	3.787	0.383	2.923	0.499	–1.162
Kurtosis	2.010	1.956	1.867	1.971	3.099	2.701	3.375	26.535	1.705	18.349	2.639	5.079
Jarque-Bera	195.5639	177.793	210.648	187.008	59.972	27.463	169.550	98831.2	365.898	43617.6	182.368	182.368
Probability	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
Observations	3880	3880	3880	3880	3880	3880	3880	3880	3880	3880	3880	3880

Source: Author’s estimates.

Table 3. Correlation matrix.

	${\mathit{WCS}}_{\mathit{ij}.\mathit{}1}$	${\mathit{WCS}}_{\mathit{ij}.\mathit{}2}$	${\mathit{WCS}}_{\mathit{ij}.\mathit{}3}$	${\mathit{WCS}}_{\mathit{ij}.\mathit{}4}$	${\mathit{IPI}}_{\mathit{i}}$	${\mathit{IPI}}_{\mathit{dom}}$	${\mathit{Inf}}_{\mathit{i}}$	${\mathit{Inf}}_{\mathit{dom}}$	${\mathit{Intrate}}_{\mathit{i}}$	${\mathit{Intrate}}_{\mathit{dom}}$	${\mathit{Exchrate}}_{\mathit{i}}$	${\mathit{Exchrate}}_{\mathit{dom}}$
${\mathit{WCS}}_{\mathit{ij}.\mathit{}1}$	1
${\mathit{WCS}}_{\mathit{ij}.\mathit{}2}$	0.921***	1
${\mathit{WCS}}_{\mathit{ij}.\mathit{}3}$	0.057***	0.114***	1
${\mathit{WCS}}_{\mathit{ij}.\mathit{}4}$	0.158***	0.160***	0.251***	1
${\mathit{IPI}}_{\mathit{i}}$	0.013	0.051**	0.004	−0.070***	1
${\mathit{IPI}}_{\mathit{dom}}$	−0.065***	−0.059***	0.084***	−0.246***	0.299***	1
${\mathit{Inf}}_{\mathit{i}}$	0.040**	0.070***	0.086***	0.032**	0.022	0.007	1
${\mathit{Inf}}_{\mathit{dom}}$	−0.004	0.009	0.010	0.080***	0.019	−0.255***	0.249***	1
${\mathit{Intrate}}_{\mathit{i}}$	0.138***	0.183***	−0.016	0.152***	0.204***	−0.460***	0.248***	0.446***	1
${\mathit{Intrate}}_{\mathit{dom}}$	0.019	0.014	−0.002	0.109***	−0.068***	−0.392***	0.054***	0.521***	0.394***	1
${\mathit{Exchrate}}_{\mathit{i}}$	0.077***	0.087***	−0.094***	0.030*	0.316***	−0.313***	−0.041***	0.147***	0.526***	0.218***	1
${\mathit{Exchrate}}_{\mathit{dom}}$	−0.030*	−0.027*	0.118***	−0.128***	0.015	0.485***	0.217***	−0.180***	−0.299***	−0.151***	−0.376***	1

Note: ***, ** and * mean statistical significant at 1%, 5% and 10%.

Source: Author’s Estimates.

Figure 1. Results of wavelet coherence analysis Germany vs C.E.E. countries. Note: Contours with black represent a 5% significance estimated on the basis of Monte Carlo simulations with random surrogate series. The colours used to represent the wavelet range from blue (low power) to red (high power). Scale-Y indicates the frequency range from the shortest (four days) to the longest (1,024 days). Scale-X is the analysis period in years. Black vertical lines are key moments in adopting codes of governance in C.E.E. countries. The relationship between two variables indicated by the direction of the arrows is as follows: (1) If the arrow indicates the direction to the right, the indices are synchronised; (2) the first index leads if the arrow points to the upper right; (3) the first index is behind if the arrow indicates the right direction down; (4) the indexes are out of sync (exerting anti-cyclic effects between them) if the arrow points to the left; (5) desynchronised and the first index leads if the arrow points to the left and top; and (6) De-synchronised and the first index leads if the arrow indicates the left-most direction. Source: Author’s estimates.

Figure 2. Results of the wavelet coherence analysis U.K. vs C.E.E. countries. Source: Author’s estimates.

Table 4. Results from panel unit root testing.

Method	Levin, Lin and Chu (level)		Breitung		Im, Pesaran and Shin		ADF – Fisher Chi-square		PP - Fisher Chi-square
Variable	Stat	Prob.	Stat	Prob.	Stat	Prob.	Stat	Prob.	Stat	Prob.
${\mathit{WCS}}_{ij.1}$	15.527	0.999	−8.108	0.000	−8.007	0.000	136.072	0.000	152.231	0.000
${\mathit{WCS}}_{ij.2}$	17.025	0.999	−5.707	0.000	−6.123	0.000	104.504	0.000	147.481	0.000
${\mathit{WCS}}_{ij.3}$	12.967	0.999	−1.735	0.041	1.175	0.880	21.566	0.992	70.408	0.002
${\mathit{WCS}}_{ij.4}$	11.857	0.999	3.930	0.999	3.787	0.999	33.539	0.754	46.328	0.227
${\mathit{IPI}}_i$	−0.246	0.402	−3.588	0.000	−6.199	0.000	102.675	0.000	1566.37	0.000
${\mathit{IPI}}_{\mathit{Dom}}$	4.097	0.999	0.636	0.737	−3.632	0.000	71.849	0.001	777.325	0.000
${\mathit{Inf}}_i$	0.375	0.646	−2.654	0.004	−2.472	0.006	50.149	0.130	50.719	0.119
${\mathit{Inf}}_{\mathit{Dom}}$	−5.071	0.000	−0.081	0.467	−6.338	0.000	114.617	0.000	80.143	0.000
${\mathit{Intrate}}_i$	−1.804	0.035	0.246	0.802	−0.165	0.434	27.198	0.938	25.730	0.960
${\mathit{Intrate}}_{\mathit{Dom}}$	−6.322	0.000	−5.777	0.000	−4.638	0.000	117.667	0.000	118.529	0.000
${\mathit{Exchrate}}_i$	−0.506	0.306	−1.330	0.091	0.090	0.535	27.539	0.932	43.580	0.321
${\mathit{Exchrate}}_{\mathit{Dom}}$	1.588	0.943	2.117	0.982	2.689	0.996	21.570	0.992	22.573	0.988

Source: Author’s estimates.

Table 5. Results from panel data cointegration tests.

Kao Residual Cointegration Test
	${\mathit{WCS}}_{\mathit{ij}.\mathit{}1}$		${\mathit{WCS}}_{\mathit{ij}.\mathit{}2}$		${\mathit{WCS}}_{\mathit{ij}.3}$		${\mathit{WCS}}_{\mathit{ij}.\mathit{}4}$
ADF test	−40.154		−40.054		−20.258		−2.656
	(0.000)		(0.000)		(0.000)		(0.003)
Johansen Fisher Panel Cointegration Test
	Fisher (trace)	Fisher (max-eigen)	Fisher (trace)	Fisher (max-eigen)	Fisher (trace)	Fisher (max-eigen)	Fisher (trace)	Fisher (max-eigen)
None	727.9	1360	702.8	1412	642.9	1550	432.0	2033
	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)
At most 1	874.8	643.1	916.5	670.1	954.6	681.9	1263	805.0
	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)
At most 2	292.9	187.4	289.8	186.5	300.4	202.5	381.3	259.2
	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)
At most 3	141.4	73.98	139.6	71.72	141.1	70.93	176.2	96.04
	(0.000)	(0.000)	(0.000)	(0.001)	(0.000)	(0.001)	(0.000)	(0.001)
At most 4	82.55	52.54	82.86	52.65	83.64	54.05	98.99	53.53
	(0.000)	(0.088)	(0.000)	(0.086)	(0.000)	(0.068)	(0.000)	(0.074)
At most 5	45.97	27.30	46.24	27.32	45.39	23.92	60.43	31.71
	(0.238)	(0.936)	(0.230)	(0.936)	(0.230)	(0.979)	(0.020)	(0.822)
At most 6	35.00	17.32	35.35	17.39	37.18	16.96	44.87	27.70
	(0.694)	(0.999)	(0.679)	(0.999)	(0.679)	(0.999)	(0.275)	(0.929)
At most 7	43.62	30.33	43.91	30.64	46.75	33.35	43.60	28.84
	(0.320)	(0.865)	(0.309)	(0.856)	(0.309)	(0.762)	(0.320)	(0.905)
At most 8	74.87	74.87	74.67	74.67	76.03	76.03	78.55	78.55
	(0.000)	(0.0007)	(0.000)	(0.0007)	(0.000)	(0.000)	(0.000)	(0.0007)

Note: The first row are the coefficients. The second row in parenthesis are the probabilities of the test.

Source: Author’s Estimates.

Table 6. Results from the A.R.D.L. panel model estimation.

	${\mathit{WCS}}_{ij.1}$	${\mathit{WCS}}_{ij.2}$	${\mathit{WCS}}_{ij.3}$	${\mathit{WCS}}_{ij.4}$
Long run equation
${\mathit{IPI}}_i$	0.001	−0.002**	0.003	−0.001*
	(1.434)	(−2.069)	(2.591)	(−1.878)
${\mathit{IPI}}_{\mathit{Dom}}$	0.000	0.000	0.001*	−0.002***
	(1.154)	(0.877)	(1.704)	(−5.574)
${\mathit{Inf}}_i$	−0.010	−0.009	−0.028***	−0.040***
	(−1.184)	(−1.121)	(−3.006)	(−6.033)
${\mathit{Inf}}_{\mathit{Dom}}$	−0.004	−0.003	0.013***	0.006***
	(−1.414)	(−1.134)	(3.738)	(2.593)
${\mathit{Intrate}}_i$	0.026***	0.0362***	0.030***	0.024***
	(4.060)	(5.823)	(3.924)	(4.744)
${\mathit{Intrate}}_{\mathit{Dom}}$	0.004	0.001	−0.001	−0.008***
	(1.390)	(0.522)	(−0.305)	(−3.327)
${\mathit{Exchrate}}_i$	−0.000	−0.002*	−0.006***	−0.004***
	(−0.683)	(−1.857)	(−3.915)	(−3.845)
${\mathit{Exchrate}}_{\mathit{Dom}}$	−0.001	−0.001	0.006***	−0.006***
	(−1.025)	(−1.402)	(5.927)	(−8.172)
Short-run equation
${\mathit{WCS}}_{ij.-1}$	1.797***	1.941***	2.492***	2.865***
	(82.284)	(93.715)	(226.73)	(664.58)
${\mathit{WCS}}_{ij.-2}$	−1.491***	−1.661***	−2.332***	−2.823***
	(−53.996)	(−66.397)	(−125.65)	(−438.91)
${\mathit{WCS}}_{ij.-3}$	0.603***	0.655***	0.821***	0.956***
	(45.125)	(61.862)	(82.152)	(321.50)
${\mathit{IPI}}_i$	−0.0002***	−0.0002***	−0.000	0.00008*
	(−2.668)	(−2.634)	(−0.922)	(1.809)
${\mathit{IPI}}_{\mathit{Dom}}$	0.0001**	0.0001***	0.000	0.00008
	(1.982)	(2.268)	(−0.330)	(1.513)
${\mathit{Inf}}_i$	0.006***	0.004***	0.0002	0.00003***
	(4.558)	(4.578)	(1.380)	(3.185)
${\mathit{Inf}}_{\mathit{Dom}}$	0.000	0.000	0.000	0.000
	(1.570)	(0.544)	(1.028)	(−0.668)
${\mathit{Intrate}}_i$	−0.004	−0.001	−0.000***	0.00008***
	(−2.174)	(−0.755)	(−3.728)	(2.816)
${\mathit{Intrate}}_{\mathit{Dom}}$	0.002**	0.001***	−0.000	−0.00001
	(2.071)	(2.894)	(−1.349)	(−0.803)
${\mathit{Exchrate}}_i$	0.001***	0.000**	0.000	0.00006
	(2.701)	(2.113)	(0.473)	(0.756)
${\mathit{Exchrate}}_{\mathit{Dom}}$	0.001***	0.001***	0.000	0.00001*
	(3.994)	(2.941)	(1.295)	(1.896)
Intercept	0.031***	0.029***	0.000	0.001***
	(17.659)	(19.727)	(0.762)	(7.969)

Note: The first row are the coefficients. The second row in parenthesis are the T-statistics of the results ***, ** and *mean statistical significant at 1%, 5% and 10%.

Source: Author’s Estimates.