Direct, Indirect, and Total Effects in the Spatial Model of FDI

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Direct, Indirect, and Total Effects in the Spatial Model of FDI
An analysis of regional competition for FDI
among VIetnam's provinces during 20112014 using Spatial Durbin modeling (SDM)
Le Van Thang, Nguyen Luu Bao Doan
University of Economics – Ho Chi Minh City
Vietnam
SBTI Seminar Series
University of Economics – Ho Chi Minh City
May 2017
Outline
•
•
•
•
•
Background
Sources of spatial interaction of provincial FDI
Modeling with SDM
Spatial econometric results
Policy implications
Distribution of Total Registered FDI by Main Economic Sectors from
1988 to 2014
Others
16%
Accomodation and
food service
5%
Construction
4%
Manufacturing
56%
Real Estate
19%
FDI Distribution in Vietnam during 1988-2014
Registered and Implemented FDI (in million USD) and Number of registered FDI
projects
$80,000
2000
$70,000
1800
1600
$60,000
1400
$50,000
1200
$40,000
1000
$30,000
800
600
$20,000
400
$10,000
200
$0
0
Registered FDI
Implemented FDI
Number of projects
Source: Vietnam’s General Statistics Office, 2015
Sources of spatial interaction
• Agglomeration economies theory
• (Henderson 1986, O’Sullivan 2013)
• Spatial interaction theory (MNEs’ motives)
• (Blonigen et al. 2007, Helpman 1984, Markusen 1984)
Motivation of MNEs
Motives of FDI
Sign of neighbor FDI
Sign of surrounding
inflow
market potential
Horizontal
0
0
Vertical
-
0
Regional Trade Platform
-
+
Complex Vertical
+
0/+
Source: Blonigen et al., 2007
Recent emperical studies of spatial
interaction of FDI
• A majority of studies at international level (Blonigen et al. 2007;
Gamboa 2013, Garretsen and Peeters 2009) and they used SAR or
SEM models except for Nwaogu (2012) which used SDM
• Fewer studies at sub-national level (Blanc-Brude et al. 2014,
Coughlin and Segev 2000, Ledyaeva 2009) and only Kayam et al.
(2013) used SDM
Emperical studies of provincial FDI in
Vietnam
• A majority of those studies failed to take into consideration
interconnectedness of provinces (Pham 2002, Nguyen 2002, Meyer
and Nguyen 2005, Anwar and Nguyen 2010).
• Two studies examine the spatial interaction of FDI in Vietnam
(Hoang and Gujoun 2014, Esiyok and Urgur 2015) and they used
SEM and SAR models. Their selection of models and weights
remained arbitrary.
Research objectives
• To explore the possible spatial interaction among Vietnam’s
provinces concerning FDI after the global financial crisis
• To analyze marginal effects of provincial determinants on FDI
Spatial models
• General form of panel spatial model be written as follows (Elhorst, 2010) :
• 𝑦𝑖𝑡 = 𝜌𝑊𝑦𝑖𝑡 + 𝑥i𝑡 𝛽 + 𝑊𝑥𝑖𝑡 𝜃 + 𝑢𝑖𝑡
• 𝑢𝑖𝑡 = 𝜆𝑊𝑢𝑖𝑡 + 𝜀
• 𝑦: the vector of the dependent variable with 𝑁𝑥1 observations from region
1 to region N;
• 𝑥: the matrix of independent variables 𝑁𝑥𝐾 from region 1 to region N with
K variables;
• 𝛽: the vectors of coefficient- Kx1 from K variables; 𝑢 is the vectors or error
term and 𝑊 is the spatial weight matrix of N regions .
• 3 kinds of spatial interaction: the endogenous interaction 𝜌𝑊y; the
exogenous interaction 𝑊𝑥𝜃 and the interaction through error term 𝜆𝑊𝑢.
Spatial Durbin Model (SDM)
• ρ ≠ 0, θ ≠ 0 and λ = 0 (Anselin 1988, 2013; LeSage and Pace
2009)
• SDM offers the examination of marginal effects of the independent
variables on the dependent variable.
• The selection of a spatial model follows “general to specific” rule
(Mur and Angula 2009)
Weight matrix
• The general form of weight matrix:
0 ⋯ 𝑤1𝑗
• W=
⋮
⋱
⋮
𝑤𝑖1 ⋯ 0
• Where W is a matrix with 𝑖 rows and 𝑗 columns and each element
𝑤𝑖𝑗 reflects the spatial relation between unit 𝑖 and unit 𝑗.
Weight matrix selections
Akaike Information Criteria (AIC) values (Blanc-Brude et al. 2014 and
Kissling and Carl 2008)
AIC
AIC
AIC
CW
1233
CW_180
1228
K_4
1260
IDW
1251
CW_300
1240
K_7
1251
Moran’s I coefficients of dependent variables
Variables
Moran’s I
p-value
FDI_2011
0.250
0.000
FDI_2012
0.202
0.006
FDI_2013
0.035
0.533
FDI_2014
0.242
0.001
Variable
Literature
Market size
Blonigen et al. (2007), Hoang and Goujon (2013), Esiyok and Urgur (2015)
Labor quality
Esiyok and Urgur (2015), Hoang and Goujon (2013), Meyer and Nguyen (2002),
Pham (2002)
Anwar and Nguyen (2005), Couglin and Segev (2002), Esiyok and Urgur (2015),
Hoang and Goujon (2013), Meyer and Nguyen (2005), Pham (2002)
Anwar and Nguyen (2005), Blanc-Brude et al. (2014), Esiyok and Urgur (2015)
Labor cost
Degree of Openness
Infrastructure
Institution quality
Foreign
Agglomeration
Budget Balance
Basic Construction
Coughlin and Segev (2000), Hoang and Goujon (2013), Kayam et al. (2013),
Ladyeva (2009)
Blonigen (2005), Esiyok and Urgur (2015), Hoang and Gujon (2013)
Blanc-Brude et al. (2014), Hoang and Goujon (2013)
Esiyok and Urgur (2015)
Variable
Definition
FDI
Log of Registered FDI in Vietnam in USD
Market size
Log of provincial GDP in million VND
+
Labor quality
Rate of trained labor of ages over 15
+
Labor cost
Log of average wage of labor of ages over 15 in US
dollars
Ratio of sum of export and import over GDP
-
Degree
Openness
Infrastructure
of
Institution quality
Foreign
Agglomeration
Budget Balance
Basic Construction
Expected sign
+
Dummy variable, 1 if a province possesses a seaport,
otherwise 0.
Log of Provincial Competitiveness Index
+
Share of foreign enterprise employment over total
employment
Ratio of budget balance over GDP
Log of government expenses on construction and
maintenance of state fixed assets in VND
+
+
+
+
Mean
S.D
Min
Max
Count
287000000
609000000
0.93
3230000000
252
42400000
75000000
3750150
542000000
252
14.28
6.03
5
36.2
252
2516.619
456.0675
1574.303
4164.36
252
0.81
1.04
0.0019
6.38
252
0.22
0.41
0
1
252
Institutional
Quality
58.08
4.38
45.11
73.53
252
Foreign
Agglomeration
15.41
17.69
0.0157
65.13
252
-0.06
0.23
-1.1
0.53
252
2295544
3547596
125587
28800000
252
FDI
Market Size
Labor Quality
Labor Cost
Degree of
Openness
Infrastructure
Budget Balance
Basic
Construction
Pooled OLS
Variable
Coefficient
Standard error
Constant
32.40*
(18.34)
Market Size
0.95***
(0.29)
Labor Quality
0.18***
(0.04)
-5.41***
(1.51)
Degree of Openness
0.19
(0.25)
Infrastructure
0.74
(0.55)
Institutional Quality
1.82
(2.79)
0.06***
(0.014)
2.31**
(1.04)
Labor Cost
Foreign Agglomeration
Budget Balance
R-squared
0.44
Adjusted R-squared
0.42
Model 1 with CW matrix
Model 2 with CW_180 weight matrix
Direct
Indirect
Total effect
Direct
Indirect
Total effect
Market size
0.84***
0.84
1.68***
0.57**
-2.09**
-1.52
(0.29)
(0.53)
(0.45)
(0.28)
(1.04)
(1.01)
Labor Quality
0.097*
0.35***
0.45***
0.15***
0.24***
0.39***
(0.05)
(0.072)
(0.05)
(0.05)
(0.07)
(0.05)
Labor Cost
-4.58**
-2.79
-7.37***
-4.30**
-7.00***
-11.31***
(2.07)
(2.55)
(1.73)
(1.82)
(2.52)
(2.00)
Degree of Openness
-0.02
-0.32
-0.34
0.15
-0.60
-0.45
(0.23)
(0.54)
(0.53)
(0.23)
(0.75)
(0.73)
Infrastructure
1.34**
-0.54
0.80
0.99*
3.51***
4.51***
(0.54)
(0.80)
(0.69)
(0.54)
(1.34)
(1.38)
Institutional Quality
7.96***
-8.49**
-0.52
6.72**
-13.73***
-7.00*
(3.03)
(3.71)
(3.35)
(2.83)
(4.20)
(3.91)
Foreign
0.004
0.06**
0.06***
0.04***
0.16***
0.2***
Agglomeration
(0.017)
(0.02)
(0.02)
(0.01)
(0.04)
(0.04)
Budget Balance
1.18
2.42
3.61*
2.20**
4.65
6.86**
(1.06)
(1.85)
(1.89)
(1.05)
(3.53)
(3.27)
Basic Construction
-0.08
-1.37***
-1.45***
-0.027
-2.26***
-2.29***
Rho
-0.41***
-0.76***
(0.09)
(0.14)
Test SDM vs SAR
72.96***
83.08***
Test SDM vs SEM
52.07***
53.46***
P= 0.0074
P= 0.06
Hausman Test
Discussion and Implications
• The results suggest that the observed spatial interaction pattern
of FDI in Vietnam from 2011 to 2014 is regional trade-platform.
FDI going to one province subsitutes for FDI going to other
provinces.
• In other words, neighboring provinces must compete for FDI. And
MNEs take advantage of the market size of a large area beyond
the host province.
• The finding is consistent with recent work by Hoang and Gujoun
(2014), which covers the period of 2001 to 2010.
• Labor quality of the host province and its neighbors matter to
MNEs’ location decision.
• What is interesting is the marginal indirect effect of labor quality
is more important to attract FDI.
• In other words, a province benefits its neighbors more when
upgrading the quality of its existing labor force or attract high.
• Model 2 indicates that the labor cost has a negative regional
effect on FDI. In other words, MNEs react negatively to labor costs
of the host province and its neighbors.
• Meanwhile, Model 2 shows that foreign agglomeration has a
positive regional effect on FDI. As a province successfully attracts
foreign companies, it exerts even bigger spillover effects onto its
neighbors. Thus the agglomeration is reinforced at the regional
level.

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