The nexus between spatial structure and labour income: evidence from Vietnam

Figures & data

Figure 1. Dimensions in spatial structure.

Source: Adapted from Meijers and Burger (2010).

Cases are created from two spatial dimensions: the horizontal axis represents the dispersed-centralised dimension, and the vertical axis represents the monocentric-polycentric dimension.

Figure 2. Rank–size distribution for Ninh Thuan (left) and Đăk Nong (right).

Source: Author’s calculations.

The slope of the regression line represents the polycentric-monocentric dimension in Ninh Thuan province is steeper than in Đăk Nong province.

Table 1. Descriptive statistics of variables in models.

Variables	Mean	SD	Minimum	Maximum
Dependent variable
Inc (million VND)	3.66	1.26	1.58	7.43
Independent variable
Edu (ratio)	0.20	0.08	0.09	0.48
Trans (ratio)	0.05	0.04	0.01	0.17
NonAgr (ratio)	0.73	0.10	0.52	0.93
Urb (million persons)	0.53	1.01	0.07	7.13
Poly (rank–size)	−1.07	0.29	−2.24	−0.24
Dis (ratio)	0.72	0.17	0.13	0.90
Red River Delta (dummy)	0.17	0.38	0.00	1.00
Northern mountain (dummy)	0.22	0.42	0.00	1.00
Central coastal (dummy)	0.22	0.42	0.00	1.00
Central Highlands (dummy)	0.08	0.27	0.00	1.00
South East (dummy)	0.10	0.30	0.00	1.00
Mekong River Delta (dummy)	0.21	0.41	0.00	1.00
Urb 1979 (million persons)	0.13	0.35	0.00	2.70
Poly 1979 (rank–size)	−0.13	0.22	−1.07	0.00
Dis 1979 (ratio)	0.87	0.18	0.11	1.00

Source: Author’s calculations.

Figure 3. Main features of the spatial structure of Vietnam: (a) population distribution, (b) degree of polycentric–monocentric dimension and (c) degree of decentralized–centralized dimension.

Source: Author’s calculations.

Three figures reflect the spatial structure of Vietnam in which, Figure A. Distribution of population across areas. Figure B. Degree of polycentric-monocentric dimension is indicated by slope of rank-size regression . Figure C. Degree of decentralized-centralized dimension is indicated by share of population not live in urban areas.

Table 2. Results from ordinary least squares regression (OLS) for the effects of spatial structure on labour income.

Variables	(1) Urb	(2)	(3)	(4) U+P	(5) U+D	(6) P+D	(7) All
Constant	2.30*** (0.31)	1.91*** (0.39)	3.92*** (0.62)	1.92*** (0.43)	3.91*** (0.63)	3.60*** (0.73)	3.58*** (0.73)
Edu	9.69*** (1.51)	9.82*** (1.15)	6.90*** (1.50)	9.73*** (1.50)	7.17*** (1.66)	7.01*** (1.51)	7.33*** (1.68)
Trans	4.58* (2.89)	5.74* (2.72)	5.67* (2.46)	5.62* (2.95)	6.13* (2.69)	6.18** (2.52)	6.73** (2.76)
NonAgr	1.73 (1.23)	1.35 (1.22)	1.05 (1.15)	1.44 (1.26)	1.00 (1.20)	0.90 (1.18)	0.82 (1.23)
Red River Delta	−0.91** (0.44)	−1.10*** (0.41)	−0.64* (0.38)	−1.08** (0.45)	−0.70* (0.42)	−0.75* (0.40)	−0.82* (0.44)
Northern mountain	−1.73*** (0.24)	−1.72*** (0.23)	−1.45*** (0.24)	−1.72*** (0.24)	−1.46*** (0.24)	−1.46*** (0.24)	−1.47*** (0.24)
Central coastal	−1.26*** (0.25)	−1.31*** (0.24)	−1.11*** (0.23)	−1.30*** (0.25)	−1.13*** (0.23)	−1.14*** (0.23)	−1.16*** (0.24)
Central Highlands	−0.75** (0.30)	−0.76** (0.30)	−0.75** (0.28)	−0.76** (0.30)	−0.75** (0.28)	−0.76** (0.28)	−0.76** (0.28)
South East	0.81** (0.31)	0.76** (0.30)	0.70** (0.01)	0.76** (0.31)	0.72** (0.29)	0.67** (0.29)	0.69** (0.29)
Urb	0.18** (0.03)			0.20** (0.04)	0.21** (0.03)		0.20** (0.03)
Poly		−0.34 (0.16)		−0.54** (0.16)		−0.32 (0.18)	−0.52** (0.16)
Dis			−1.73*** (0.60)		−1.78*** (0.61)	−1.64*** (0.61)	−1.69*** (0.62)
Observations	63	63	63	63	63	63	63
Multiple R^2	0.82	0.82	0.84	0.82	0.84	0.84	0.84
Adjusted R^2	0.79	0.80	0.82	0.79	0.82	0.82	0.82

Source: Author’s calculations.

Table 3. Results from ordinary least squares regression (OLS) for the effects of interaction between spatial dimensions on labour income.

Variables	(8) Urb × Poly	(9) Urb × Dis	(10) All
Constant	3.98*** (0.77)	3.95*** (0.78)	4.03*** (0.79)
Edu	7.06*** (1.66)	6.57*** (1.76)	6.82*** (1.79)
Trans	7.99*** (2.80)	7.68*** (2.80)	8.07*** (2.83)
NonAgr	0.63 (1.22)	0.75 (1.22)	0.65 (1.23)
Red River Delta	−0.91** (0.44)	−0.83* (0.44)	−0.90** (0.44)
Northern mountain	−1.42*** (0.24)	−1.34*** (0.26)	−1.38*** (0.26)
Central coastal	−1.08*** (0.24)	−1.09*** (0.24)	−1.08*** (0.24)
Central Highlands	−0.73** (0.28)	−0.75** (0.28)	−0.73** (0.28)
South East	0.68** (0.29)	0.75** (0.29)	0.71** (0.30)
Urb	0.20*** (0.03)	0.24*** (0.03)	0.24*** (0.03)
Poly	−0.50** (0.15)	−0.56** (0.16)	−0.53** (0.15)
Dis	−1.80*** (0.62)	−2.11*** (0.70)	−1.94** (0.72)
Urb × Poly	−0.17*** (0.03)		−0.16*** (0.03)
Urb × Dis		0.73 (0.55)	0.28 (0.75)
Observations	63	63	63
Multiple R^2	0.85	0.84	0.85
Adjusted R^2	0.82	0.82	0.82

Source: Author’s calculations.

Table 4. Results from two-stage least squares (TSLS) for the effects of spatial dimensions on labour income.

Variables	(11) No interaction	(12) Urb × Poly	(13) Urb × Dis
Constant	3.24*** (0.78)	4.16*** (0.88)	3.88*** (0.83)
Edu	10.84*** (2.78)	10.06*** (3.39)	9.72*** (3.33)
Trans	7.20*** (3.01)	7.40*** (2.38)	6.51*** (2.09)
NonAgr	0.76 (1.72)	0.78 (1.64)	1.10 (1.75)
Red River Delta	−1.59** (0.68)	−1.48** (0.71)	−1.37* (0.76)
Northern mountain	−1.88*** (0.38)	−1.80*** (0.41)	−1.79*** (0.39)
Central coastal	−1.50*** (0.32)	−1.40*** (0.40)	−1.39* (0.36)
Central Highlands	−0.75** (0.35)	−0.73** (0.34)	−0.71** (0.34)
South East	0.66* (0.38)	0.65** (0.36)	0.72** (0.38)
Urb	0.32*** (0.03)	0.37*** (0.03)	0.35*** (0.02)
Poly	−0.54** (0.17)	−0.34 (0.20)	−0.51** (0.20)
Dis	−2.20** (0.72)	−1.95*** (0.65)	−2.31*** (0.67)
Urb × Poly		−0.28*** (0.03)
Urb × Dis			0.33 (0.81)
Weak instruments (F-test) – Urb		66.01***
Weak instruments (F-test) – Poly		11.68***
Weak instruments (F-test) – Dis		14.36***
Weak instruments (F-test) – Urb × Poly		24.81***
Weak instruments (F-test) – Urb × Dis			32.65***
Wu–Hausman test	2.92**	2.80**	2.85**
Sargan test	0.56	0.45	0.25
Observations	63	63	63
Multiple R^2	0.79	0.82	0.81
Adjusted R^2	0.75	0.78	0.77

Source: Author’s calculations.

Meijers, E. J., & Burger, M. J. (2010). Spatial structure and productivity in US metropolitan areas. Environment and Planning A: Economy and Space, 42(6), 1383–1402. https://doi.org/10.1068/a42151

 Web of Science ®Google Scholar

DATA AVAILABILITY

Data available on request from the authors.