Choice for rigid demander investing in real estate outside of China: Thailand or Malaysia?

Figures & data

Figure 1. The establishment of the real estate investment environment indicator system.

Table 1. Thailand and Malaysia index of each factor (Knoema, 2019a, 2019b; Uoolu, 2019; Marsh JLT., 2020; E-House, 2020).

Factors	Indicators	Thailand	Malaysia
Political Environment	Country risk index	65	75
	Integrity index	36	51
	Peace index	2.25	1.53
Economic Environment	GDP (10Billion USD)	509.20	336.33
	GDP per capita (USD)	7295	10192
	Employment rate (%)	65.40	61.30
	Unemployment rate (%)	1	4.9
	FDI stock (Billion USD)	2544.16	1689.80
Policy Environment	Exchange rate	0.0307	0.2433
	Inflation rate	0.71	0.7
	Easy business	80.10	81.50
Market Environment	Gross rental yield	5.10	3.70
	Urban housing ownership rate	80.00	46.3
	Per capita living area of commercial housing	21.60	12.00
	City house price to income ratio	27.60	11.00
Social Environment	Population (million)	69.80	32.367
	Land (square kilometers)	510890	328550
	Agriculture land	43.30	26.30
	Tourists (million)	39.917	26.10
	Happiness index	5.99	5.38

The data is from 1 Knoema website; 2 Uoolu 2019 Ten Countries on Belt and Road Property Investment Data report; 3 E-House 2020 report on the house price-to-income ratio in 80 cities worldwide; 4 The 2020 Political Risk Map from Marsh.

Table 2. Scale of relative importance according to saaty’s scaling method (Saaty, 1980)

Intensity of importance	Definition	Explanation
1	Same	Neither of the two alternatives is preferable over the other
3	Weak	One alternative is preferred slightly over the other
5	Clear	One alternative is preferred clearly over the other
7	Strong	One alternative is preferred strongly over the other
9	Very Strong	One alternative is preferred very strongly over the other
2, 4, 6, 8	Compromise	Can be used for graduation between evaluation
Reciprocals of above	If activity $i$ has one of the above nonzero numbers assigned to it when compared with activity $j$, then $j$ has the reciprocal value when compared with $i$	A comparison mandated by choosing the smaller element as the unit to estimate the larger one as a multiple of that unit

Table 3. Random consistency index RI (Saaty, 1980).

Size of matrix	1	2	3	4	5	6	7	8	9	10
Comparative value	0	0	0.52	0.89	1.12	1.26	1.36	1.41	1.46	1.49

Table 4. The evaluation index judgment matrix of real estate investment environment.

	B1	B2	B3	B4	B5	Weight
B1	1	1/3	1/5	1/5	3	0.0862
B2	4	1	3	1/4	5	0.2952
B3	2	1	1	1/3	4	0.1876
B4	3	2	3	1	4	0.3786
B5	1/2	1/5	1/4	1/5	1	0.0525
λmax=5.2833 CI = 0.0708 CR = 0.0632

Table 5. The evaluation index judgment matrix of real estate investment political environment.

	C1	C2	C3	Weight
C1	1	1/5	1	0.1418
C2	5	1	5	0.7088
C3	1/2	1/3	1	0.1495
λmax=3.0546 CI = 0.0273 CR = 0.0525

Table 6. The evaluation index judgment matrix of real estate investment economic environment.

	C4	C5	C6	C7	C8	Weight
C4	1	1	1/3	1/5	1/3	0.0890
C5	1	1	1/3	1	4	0.2159
C6	3	1	1	1/5	2	0.1719
C7	5	1	5	1	4	0.4130
C8	2	1/4	1/2	1/5	1	0.0922
λmax=5.3831 CI = 0.0958 CR = 0.0856

Table 7. Real estate investment policy environmental evaluation index judgment matrix.

	C9	C10	C11	Weight
C9	1	3	5	0.6231
C10	1/2	1	4	0.3002
C11	1/6	1/5	1	0.0786
λmax=3.0819 CI = 0.04 CR = 0.0788

Table 8. The evaluation index judgment matrix of real estate investment market environment.

	C12	C13	C14	C15	Weight
C12	1	5	5	1/5	0.2433
C13	1/4	1	1	1/7	0.0670
C14	1/4	1/2	1	1/6	0.0626
C15	5	6	6	1	0.6272
λmax=4.1786 CI = 0.0610 CR = 0.0669

Table 9. The evaluation index judgment matrix of real estate investment social environment.

	C16	C17	C18	C19	C20	weight
C16	1	1/3	1/3	1/3	1/3	0.0741
C17	3	1	1/3	1/5	1/2	0.1057
C18	2	2	1	1/3	1/3	0.1407
C19	7	5	5	1	5	0.5617
C20	4	1/3	1/3	1/5	1	0.1178
λmax=5.1658. CI = 0.0415    CR = 0.0370

Table 10. Individual index weight.

Individual Index	Weight	Individual Index	Weight
C1	0.0122	C2	0.0611
C3	0.0129	C4	0.0263
C5	0.0637	C6	0.0507
C7	0.1219	C8	0.0272
C9	0.1169	C10	0.0563
C11	0.0147	C12	0.0921
C13	0.0254	C14	0.0237
C15	0.2375	C16	0.0039
C17	0.0055	C18	0.0074
C19	0.0295	C20	0.0062

Table 11. Standardized data and weighted results.

Index	Thailand	Malaysia
C1	0.8667	1
C2	0.7059	1
C3	1	0.68
C4	1	0.6605
C5	0.7158	1
C6	1	0.9373
C7	0.2041	1
C8	1	0.6642
C9	0.1262	1
C10	1	0.9859
C11	0.9828	1
C12	1	0.7255
C13	1	0.5788
C14	1	0.5556
C15	1	0.3986
C16	1	0.4637
C17	1	0.6431
C18	1	0.6074
C19	1	0.6539
C20	1	0.8982
Integrate Score	0.7580	0.7618

Table 12. Total value of the real estate investment environment of the two countries.

Country	Environments					Total Value
	Political	Economic	Policy	Market	Social
Thailand	0.0666	0.1747	0.0855	0.3787	0.0525	0.7580
Malaysia	0.0821	0.2686	0.1871	0.1894	0.0347	0.7618

Knoema. (2019a). Thailand Data Atlas. Retrieved from https://knoema.com/atlas/Thailand.

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Knoema. (2019b). Malaysia Data Atlas. Retrieved from https://knoema.com/atlas/Malaysia.

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Uoolu. (2019). Ten Countries on Belt and Road Property Investment Data report. Retrieved from https://america.uoolu.com/news/detail-47.html.

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Marsh JLT. (2020). Political risk map 2020: Trade tensions threaten political stability. https://www.marsh.com/cn/zh/insights/research/political-risk-map-2020.html

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E-House. (2020). The house price-toincome ratio in 80 cities worldwide report. Retrieved from http://admin.fangchan.com/uploadfile/uploadfile/annex/2/1841/5ebe50ad82d50.pdf.

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