Unveiling the drivers of large-scale land acquisitions in Asian countries: society, economy and environment

Figures & data

Figure 1. LSLAs flows between investors countries and host countries in Asia (all signed deals) in 2000–2022 period from our database.

This figure represents a chord diagram plot which depicts cumulative LSLAs flows between countries. A chord diagram consists of two main components: an outer fragmented circle and inner arcs. Every fragment of the outer circle represents a country. The size of every fragment is proportional to the cumulated land deal size which involves that country, whether as host or investor. On the other hand, the size of an inner arc is proportional to the land deal size negotiated between the two countries linked.

Table 1. Variables description.

	Description	Measuring unit	Source (year)
Land deals size	Size of land deal Dependent variable	ha	Land Matrix (2022: period 2003–2021)
Distance (Gravity Model variable)	Distance between host and investor	km	CEPII (2015)
Language (Gravity Model variable)	Host and investor have a common official language	Dummy (0 = not; 1 = yes)	CEPII (2015)
Colony (Gravity Model variable)	Host and investor have a past colonial relationship	Dummy (0 = not; 1 = yes)	CEPII (2015)
Agricultural land (Gravity Model variable)	Agricultural area of the country	ha	Faostat (2019)
Cropland (Gravity Model variable)	Cropland area of the country	ha	Faostat (2019)
Arable land (Gravity Model variable)	Arable land area of the country	ha	Faostat (2019)
GDP (Gravity Model variable)	Gross Domestic Product of the country	$ (billions)	Miller et al. (2019)
GDP per capita (Gravity Model variable)	Gross Domestic Product of the country per capita	$ (billions) / inhabitants (n)	Miller et al. (2019)
GDP growth rate (Gravity Model variable)	The annual percentage growth rate of real GDP derived from constant currency units	%	Miller et al. (2019)
Population (Socio-political variable)	Population of the country	People (millions)	Miller et al. (2019)
Population density (Socio-political variable)	Population density	People per square kilometres of land area (n / km^2)	Miller et al. (2019)
Tariff rate (Socio-political variable)	Tariff rate of the country	%	Miller et al. (2019)
Income tax rate (Socio-political variable)	Tax imposed on income	%	Miller et al. (2019)
Corporate tax rate (Socio-political variable)	Tax on the profits of a corporation	%	Miller et al. (2019)
Tax burden (Socio-political variable)	The top marginal tax rate on individual income	0–100 (0 = low; 100 = high)	Miller et al. (2019)
Tax burden (% of GDP) (Socio-political variable)	The top marginal tax rate on individual income as a percentage of GDP	%	Miller et al. (2019)
Fiscal health (socio-political variable)	Fiscal health of the country	0–100 (0 = low; 100 = high)	Miller et al. (2019)
Public debt (Socio-political variable)	Public debt in percentage of GDP of the country	%	Miller et al. (2019)
Property rights (Socio-political variable)	Measures the strength of property tenure in a country	0–100 (0 = low; 100 = high)	Miller et al. (2019)
Government spending (Socio-political variable)	The burden imposed by government expenditures, which includes consumption by the state and all transfer payments related to various entitlement programs	0–100 (0 = low; 100 = high)	Miller et al. (2019)
Government expenditure (% of GDP) (Socio-political variable)	The burden imposed by government expenditures, which includes consumption by the state and all transfer payments related to various entitlement programs	%	Miller et al. (2019)
Business freedom (Socio-political variable)	Measures the extent to which the regulatory and infrastructure environments constrain the efficient operation of businesses	0–100 (0 = low; 100 = high)	Miller et al. (2019)
Labour freedom (Socio-political variable)	Considers various aspects of the legal and regulatory framework of a country’s labour market	0–100 (0 = low; 100 = high)	Miller et al. (2019)
Investment freedom (Socio-political variable)	Evaluates a variety of regulatory restrictions that typically are imposed on investment	0–100 (0 = low; 100 = high)	Miller et al. (2019)
Monetary freedom (Socio-political variable)	The weighted average rate of inflation for the most recent three years and a qualitative judgement about the extent of government manipulation of prices through direct controls or subsidies	0–100 (0 = low; 100 = high)	Miller et al. (2019)
Trade freedom (Socio-political variable)	The trade-weighted average tariff rate and a qualitative evaluation of nontariff barriers (NTBs)	0–100 (0 = low; 100 = high)	Miller et al. (2019)
Financial freedom (Socio-political variable)	An indicator of banking efficiency as well as a measure of independence from government control and interference in the financial sector	0–100 (0 = low; 100 = high)	Miller et al. (2019)
Judicial effectiveness (Socio-political variable)	Judicial independence, quality of the judicial process, and perceptions of the quality of public services and the independence of the civil service	0–100 (0 = low; 100 = high)	Miller et al. (2019)
Government integrity (Socio-political variable)	Measures the degree of institutions fairness in a country	0–100 (0 = low; 100 = high)	Miller et al. (2019)
Unemployment (Socio-political variable)	Unemployment rate of the country	%	Miller et al. (2019)
Inflation (Socio-political variable)	The annual percent change in consumer prices	%	Miller et al. (2019)
FDI inflows (Socio-political variable)	The total annual inward flow of FDI	$ (millions)	Miller et al. (2019)
Women (Socio-political variable)	Ratio of female to male labour force participation rate	%	MDGI (2019)
Women 2 (Socio-political variable)	Seats held by women in national parliament in the country	%	MDGI (2019)
Caloric intake (Socio-political variable)	Number of calories consumed per person per day	kcal/ capita / day	Faostat (2019)
Annual freshwater withdrawals, total (Environmental variable)	Annual freshwater withdrawals, total	Billion cubic meters	UNSD (2017)
Renewable internal freshwater resources, total (Environmental variable)	Renewable internal freshwater resources, total	Billion cubic meters	UNSD (2017)
Renewable internal freshwater resources p_c (Environmental variable)	Renewable internal freshwater resources per capita	Cubic meters	UNSD (2017)
Protected areas (Environmental variable)	Protected areas in a country	ha	UNSD (2018)
Temperature change (Environmental variable)	Temperature variability	°C	Dell et al. (2012)
Precipitation (Environmental variable)	Average precipitation in depth	mm per year	Dell et al. (2012)

Table 3. PPML estimation gravity models.

	Dependent variable: Land acquisition size
	Mod. 1	Mod. 2	Mod. 3	Mod. 4
	Base Mod.	Soc.-Pol. Var.	Env. Var.	Full Mod.
Constant	7.291** (3.506)	3.885 (8.247)	0.852 (4.491)	11.600* (6.047)
log (distance)	−1.672*** (0.253)	−1.834*** (0.246)	−1.839*** (0.252)	−1.855*** (0.239)
log (GDP per capita_host)	−1.351*** (0.414)	−1.279* (0.716)	−1.576*** (0.432)	−2.088*** (0.640)
log (GDP per capita_inv)	1.310*** (0.185)	1.335*** (0.165)	1.493*** (0.163)	1.358*** (0.164)
log (Agricultural land_host)	0.594*** (0.124)	0.568*** (0.138)	0.679*** (0.137)	0.612*** (0.149)
log (Agricultural land_inv)	0.296*** (0.084)	0.328*** (0.080)	0.336*** (0.088)	0.340*** (0.081)
Language (dummy)	0.245 (0.861)	−0.064 (0.760)	−0.021 (0.822)	−0.194 (0.743)
Latitude_host	−0.058*** (0.011)	−0.037*** (0.012)	−0.014 (0.019)	0.007 (0.024)
Longitude_host	0.073*** (0.020)	0.109*** (0.032)	0.108*** (0.027)	0.079*** (0.019)
Tariff rate_host		−0.237*** (0.090)		−0.412*** (0.115)
Tax burden as % of GDP_host		−0.088** (0.044)		−0.137* (0.074)
Unemployment_host		−0.252** (0.117)		−0.105 (0.094)
Inflation_host		0.471*** (0.165)		0.334** (0.157)
Labour freedom_inv		0.014 (0.009)		0.015* (0.009)
Renewable internal freshwater Resources per capita_host			0.0001*** (0.00003)	−0.00001 (0.00003)
Precipitation_host			0.001*** (0.0005)	0.001** (0.0004)
Protected areas_host			−0.047* (0.025)	0.078** (0.037)
Rsquare	0.198	0.448	0.413	0.480
Max VIF	3.057	4.751	3.361	5.461
Observations	2,625	2,604	2,625	2,604

Notes: *p < 0.1; **p < 0.05; ***p < 0.01; Robust standard errors are in parentheses.

Table 2. Descriptive statistics.

Variables	Mean	S.D.	Min	Max
Land deals size_host	1,144,442.20	2,319,429.80	254	9,232,772.84
Land deals size_inv	194,180.58	653,614.34	0	5,407,881.17
Agricultural land_host	61,737.74	122,409.95	380	528,512.10
Agricultural land_inv	35,799.43	79,129.37	0.66	528,512.10
Cropland_host	25,258.14	44,621.89	230	169,317.00
Cropland_inv	12,324.50	27,794.34	0.66	169,317.00
Arable land_host	21,221.08	40,485.75	155	156,317.00
Arable land_inv	10,997.26	26,052.24	0.56	157,736.80
Property rights_host	49.29	11.62	29.7	84.1
Property rights_inv	57.01	19.25	25.3	97.4
Judicial effectiveness_host	43.4	15.61	13.1	75.2
Judicial effectiveness_inv	49.33	18.18	18.1	92.4
Government integrity_host	35.8	9.43	16.7	55.4
Government integrity_inv	45.68	21.77	14.3	96.7
Tax burden_host	84.39	6.92	70.4	96.3
Tax burden_inv	76.35	11.91	42	99.8
Government spending_host	75.94	19.61	0.9	94.5
Government spending_inv	65.79	21.61	3.9	96.6
Fiscal health_host	62.79	28.71	6.2	98.7
Fiscal health_inv	67.54	29.77	0	100
Business freedom_host	64.05	12.15	29.9	83.9
Business freedom_inv	66.34	13.53	29.9	96.4
Labour freedom_host	60.62	11.1	41.8	86.2
Labour freedom_inv	59.6	13.5	29.3	91
Monetary freedom_host	73.45	5.69	58.9	85
Monetary freedom_inv	76.2	7.89	49.1	88
Trade freedom_host	75.19	6.49	62.6	83
Trade freedom_inv	76.58	10.35	45	95
Investment freedom_host	46.43	16.82	10	75
Investment freedom_inv	61.64	20.6	5	95
Financial freedom_host	42.38	17.58	10	70
Financial freedom_inv	53.36	18.47	10	90
Tariff rate_host	4.79	2.77	1.6	10.7
Tariff rate_inv	5.18	4.15	0	17.5
Income tax rate_host	24.71	9.71	10	45
Income tax rate_inv	30.58	12.56	0	57
Corporate tax rate_host	23.62	7.98	7.5	45
Corporate tax rate_inv	24.3	7.82	0	45
Tax burden (% of GDP)_host	14.87	4.82	6.5	25.47
Tax burden (% of GDP)_inv	22.58	10.67	1.6	45.9
Government expenditure (% of GDP)_host	26.83	9.31	13.6	57.5
Government expenditure (% of GDP)_inv	32.04	10.72	10.6	56.6
Population_host	184.79	395.03	1.2	1390.10
Population_inv	58.55	178.47	0.2	1390.10
GDP_host	2146.43	5243.79	6.8	23,159.10
GDP_inv	1027.09	2951.29	0.7	23,159.10
GDP growth rate_host	5.51	2.01	−0.5	7.5
GDP growth rate_inv	3.65	2.31	−4.6	10.9
GDP per capita_host	11,524.10	7767.94	3211.98	29,040.84
GDP per capita_inv	23,934.61	23,576.35	789.95	124,529.05
Unemployment_host	5.37	4.72	0.2	18.2
Unemployment_inv	6.76	5.23	0.1	27.3
Inflation_host	4.43	3.18	0.6	12.5
Inflation_inv	4.88	6.67	−0.9	41.5
FDI inflows_host	13,024.73	29,808.53	6.7	136,320.00
FDI inflows_inv	11,768.52	31,392.65	−8296.90	275,381.00
Public debt_host	48.24	23.91	0	95.6
Public debt_inv	59.19	36.17	0.1	236.4
Annual freshwater withdrawals, total_host	102.35	182.76	0.46	647.5
Annual freshwater withdrawals, total_inv	30.92	93.39	0.02	647.5
Renewable internal freshwater resources, total_host	469.94	752.35	0.68	2812.90
Renewable internal freshwater resources, total_inv	337.76	830.2	0	5661.00
Renewable internal freshwater resources p.c._host	6297.74	7196.73	69.69	27,383.74
Renewable internal freshwater resources p.c._inv	14,805.86	48,161.20	0	495,049.50
Population density_host	190.67	241.11	2.07	1117.28
Population density_inv	276.21	959.56	2.07	7842.84
Precipitation_host	1331.00	911.77	111	2875.00
Precipitation_inv	1108.97	789.45	18.1	3240.00
Temperature change_host	1.23	0.41	0.77	2.52
Temperature change_inv	1.34	0.41	0.38	2.52
Protected areas_host	13.1	8.45	0.2	29.9
Protected areas_inv	18.08	10.88	0.2	41.9
Women_host	63.99	21.42	22.29	95.87
Women_inv	73.36	18.38	22.29	103.11
Women 2_host	18.64	7.56	4.8	32.31
Women 2_inv	22.72	11.71	0	61.25
Calorie intake_host	2848.95	344.12	2231.00	3732.00
Calorie intake_inv	2969.12	462.77	1704.00	3861.00

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DATA AVAILABILITY STATEMENT

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.