Causality between economic policy uncertainty and real housing returns in emerging economies: A cross-sample validation approach

Figures & data

Figure 1. Real housing returns and economic policy uncertainty.

Table 1. Descriptive statistics

Real housing returns
Country	Sample period	Mean (%)	Std Dev (%)	Skewness	Kurtosis	Jarque–Bera test (P-value)
Brazil	2001Q1–2016Q2	0.831	2.897	−0.762	3.008	0.052
Chile	1993Q1–2015Q3	0.842	7.407	1.272	9.349	0.000
China	1999Q1–2016Q2	0.526	1.349	−0.497	3.392	0.194
India	2003Q1–2016Q2	1.682	3.772	−0.641	7.834	0.000
Ireland	1985Q1–2016Q2	0.760	2.770	−0.208	2.721	0.521
Russia	2001Q1–2016Q2	0.820	5.858	−2.014	14.398	0.000
South Africa	1985Q1–2016Q5	0.314	2.648	0.046	3.700	0.270
South Korea	1990Q1–2016Q3	−0.270	1.991	−0.669	6.052	0.000
Economic policy uncertainty growth
Country	Sample period	Mean (%)	Std Dev (%)	Skewness	Kurtosis	Jarque–Bera test (P-value)
Brazil	2001Q1–2016Q2	2.269	35.369	0.063	2.580	0.783
Chile	1993Q1–2015Q4	1.514	24.744	−0.172	2.746	0.711
China	1999Q1–2016Q2	1.578	36.854	0.604	3.634	0.069
India	2003Q1–2016Q2	0.045	29.729	0.390	3.528	0.375
Ireland	1985Q1–2016Q2	0.961	33.080	0.249	3.239	0.452
Russia	2001Q1–2016Q2	1.475	34.825	0.085	2.832	0.929
South Africa	1985Q1–2016Q3	1.451	90.020	0.309	4.141	0.012
South Korea	1990Q1–2016Q3	0.288	36.720	0.149	2.772	0.733

Table 2. In-sample, CSV and post-sample Granger causality tests

Country	Brazil	Chile	China	India	Ireland	Russia	South Africa	South Korea
Sample Length	60	90	68	52	123	60	124	105
In-Sample F Test	0.323	0.303	0.016	0.209	0.972	0.259	0.129	0.151
CSV 75 (${\hat{Q}}_{0.75}$) Test	0.467	0.037	0.035	0.177	0.544	0.319	0.113	0.163
Post-sample MSE-F Tests:
5 periods	0.182	0.974	0.971	0.012	0.692	0.078	0.086	0.992
10 periods	0.221	0.989	0.956	0.549	0.498	0.611	0.142	0.993

These are p-values for rejecting the null hypothesis that EPU growth does not Granger cause real housing returns. Values in bold signify that the null hypothesis is rejected.

Figure 2. The cross-sample validation Granger causality test for different rolling windows for Brazil.

Figure 3. The cross-sample validation Granger causality test for different rolling windows for Chile.

Figure 4. The cross-sample validation Granger causality test for different rolling windows for China.

Figure 5. The cross-sample validation Granger causality test for different rolling windows for India.

Figure 6. The cross-sample validation Granger causality test for different rolling windows for Ireland.

Figure 7. The cross-sample validation Granger causality test for different rolling windows for Russia.

Figure 8. The cross-sample validation Granger causality test for different rolling windows for South Africa.

Figure 9. The cross-sample validation Granger causality test for different rolling windows for South Korea.

Table 3. Non-parametric Granger causality test

	Test Statistics
	${\hat{S}}_T^{(1)}$	${\hat{S}}_T^{(2)}$
Brazil	26.076***	17.263**
Chile	0.085	8.921
China	17.919***	26.249***
India	4.618	11.613
Ireland	54.485***	35.209***
Russia	0.734	17.420***
South Africa	57.667***	37.403***
South Korea	0.825***	21.875***

${\hat{S}}_T^{(1)}$ is the test statistics for null of non-Granger causality in mean and ${\hat{S}}_T^{(2)}$ is for non-Granger causality in the second moment (variance). The results are evaluated based on the 5% critical value of 14.38 as provided by Nishiyama et al. (2011). ** and *** Indicate rejection of the null hypothesis of non-Granger causality at 5% and 1% level respectively.

Table A1. Unit root tests with and without breakpoint

Real Housing Prices
	Level				First Difference
	ADF	PP	NP	Zivot-Andrews	Break date	ADF	PP	NP
Brazil	−1.252	−0.772	−16.294*	−3.171	2013Q2	−8.887***	−12.289***	−16.472*
Chile	−2.889	−3.426*	−1.497	−6.098***	1997Q2	−8.483***	−13.592***	−13.858
China	−1.455	−0.876	−6.114	−4.100	2009Q4	−5.374***	−5.386***	−29.190***
India	−2.257	−1.954	−5.574	−5.058*	2008Q2	−7.179***	−12.251***	−25.983***
Ireland	−1.456	−1.013	−6.250	−3.894	2002Q1	−3.459**	−5.789***	−17.998**
Russia	−0.216	−0.296	−0.162	−4.066	2006Q2	−7.450***	−7.467***	−29.830***
South Africa	−2.011	−2.673	−4.050	−3.382	2003Q1	−4.138***	−3.996**	−27.502***
South Korea	−2.438	−1.537	−2.908	−5.085**	2001Q2	−5.795***	−5.829***	−20.604**
Economic Policy Uncertainty
	Level				First Difference
	ADF	PP	NP	Zivot-Andrews	Break date	ADF	PP	NP
Brazil	−2.753	−4.693***	−13.883	−4.648	2010Q2	−12.622***	−22.761***	−23.323**
Chile	−3.597**	−3.597**	−16.694*	−6.363***	2003Q3	−9.243***	−13.922***	−44.855***
China	−3.917**	−4.017**	−20.069**	−4.771	2007Q3	−11.059***	−11.065***	−31.637***
India	−2.541	−2.541	−10.858	−4.511	2011Q3	−8.493***	−9.129***	−25.194***
Ireland	−3.879**	−6.169***	−22.481***	−4.544	1994Q4	−17.068***	−23.722***	−0.205
Russia	−6.308***	−6.256***	−29.016***	−6.850***	2004Q3	−7.716***	−21.405***	−28.974***
South Africa	−5.166***	−8.089***	−35.601***	−5.447**	2007Q4	−12.766***	−44.309***	−55.787***
South Korea	−6.163***	−6.413***	−33.976***	−4.604	2000Q2	−12.348***	−15.280***	−51.721***

*, ** and *** indicate significance or rejection of the null hypothesis at 10, 5 and 1%, respectively.

Table A2. Cointegration test

Trace Test
No. of cointegrating equations	Brazil	Chile	China	India	Ireland	Russia	South Africa	South Korea
None	15.158	13.520	14.007	10.650	11.951	9.876	14.157	18.218
At most one	4.777	4.763	1.423	2.525	2.665	2.168	0.757	5.207
Maximum Eigenvalue Test
No. of cointegrating equations	Brazil	Chile	China	India	Ireland	Russia	South Africa	South Korea
None	10.380	8.757	12.585	8.125	9.2850	7.709	13.399	13.011
At most one	4.777	4.763	1.423	2.525	2.665	2.168	0.757	5.207

The test is evaluated against the following critical values at 5% level of significance: 15.495 and 3.841 for none and at most one null hypothesis under the Trace test, 14.265 and 3.841 for Maximum Eigenvalue Test.

Nishiyama, Y., Hitomi, K., Kawasaki, Y., & Jeong, K. (2011). A consistent nonparametric test for nonlinear causality—Specification in time series regression. Journal of Econometrics, 165, 112–127. doi:10.1016/j.jeconom.2011.05.010

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