Determinants influencing Vietnam coffee exports

Figures & data

Figure 1. Coffee exports of Vietnam for the period 2005–2019.

Source: General Department of Vietnam Customs in 2019.

Figure 2. Two major types of autocorrelation spatial dependencies.

Source: LeSage (1999) Spatial Econometrics.

Table 1. Variables and source data.

Variables	Contents	Sources
$Y$	Bilateral trade exports between the two countries ($)	UN Comtrade
GDP	Gross domestic product of country ($)	World Databank, WDI
$\mathit{\text{POP}}$	Population of country (person)
$D$	The shortest distance between countries (km), (25 knot), (oil price).	AXSMarine, EIA
$\mathit{\text{PROD}}$	Total output of coffee exports (t)	FAO
$\mathit{\text{TA}}$	Tax rates for coffee, using HS code (%)	WTO
$\mathit{\text{NTB}}$	Number of non-tariff barriers (SPS, TBT)	WTO
$\mathit{\text{REER}}$	Real effective exchange rate (REER)	IMF, UNCTADSTAT
$\mathit{\text{FTA}}$	Free trade agreement in force	WTO

Gross domestic product (GDP) and population data are independent variables. These data are taken from World Databank and World Development Indicator, which include the gross domestic product (GDP) and the population of the country of origin and the country of destination.

Figure 3. Research model proposed.

Table 2. Spatial autocorrelation test result.

	Inverse distance matrix $\left(\frac{1}{d_{\mathit{\text{ij}}}}\right)$			Inverse distance square matrix $\left(\frac{1}{d_{\mathit{\text{ij}}}^2}\right)$
	${\mathit{W}}_{\mathit{o}}$	${\mathit{W}}_{\mathit{d}}$	${\mathit{W}}_{\mathit{w}}$	${\mathit{W}}_{\mathit{o}}$	${\mathit{W}}_{\mathit{d}}$	${\mathit{W}}_{\mathit{w}}$
LM-lag test	78.0 (0.00)	92.7 (0.00)	43.8 (0.00)	78.0 (0.00)	82.5 (0.00)	36.1 (0.00)
LM-error test	145.6 (0.00)	125.3 (0.00)	133.8 (0.00)	145.6 (0.00)	98.8 (0.00)	112.5 (0.00)

Table 3. Hypothesis testing and panel data model selection.

	Fixed effects model	Random effects model	Hausman test	Autocorrelation test over time
	F test	χ^2 test	χ^2 test	F test
Static analysis	25.14* (0.00)	14067.32* (0.00)	262.63* (0.00)	55.24* (0.00)
Dynamic analysis	73.48* (0.00)	0.00 (1.00)	–

Note: * mean at 5%.

Table 4. Estimated results of experimental models.

Variables	Model 1	Model 2 ${\mathit{W}}_{\mathit{d}}$	Model 3 ${\mathit{W}}_{\mathit{o}}$	Model 4 ${\mathit{W}}_{\mathit{w}}$	Model 5 ${\mathit{W}}_{\mathit{d}}$	Model 6 ${\mathit{W}}_{\mathit{o}}$	Model 7 ${\mathit{W}}_{\mathit{w}}$
		Inverse distance matrix (1/${\mathit{d}}_{\mathit{\text{ij}}}$)			Inverse distance square matrix (1/${\mathit{d}}_{\mathit{\text{ij}}}^2$)
Lag dependent variable	0.391* (−0.012)	0.265* (0.010)	0.228* (0.010)	0.302* (0.010)	0.223* (0.010)	0.208* (0.010)	0.285* (0.011)
${\mathit{\text{GDP}}}_o$	0.621* (−0.211)	0.818* (0.224)	0.165 (0.425)	1.169* (0.240)	0.621* (0.218)	0.134 (0.340)	1.133* (0.223)
${\mathit{\text{GDP}}}_d$	0.643* (−0.201)	0.729* (0.254)	0.934* (0.203)	1.027* (0.205)	0.716* (0.243)	0.820* (0.202)	0.867* (0.207)
${\mathit{\text{POP}}}_o$	−4868* (−1.257)	−5.010* (1.304)	−9.426* (2.622)	−2.873* (1.335)	−7.012* (1.268)	−8.381* (1.859)	−5.846* (1.502)
${\mathit{\text{POP}}}_d$	5.210* (−1.254)	9.231* (1.854)	8.351* (1.209)	9.215* (1.348)	7.150* (1.508)	7.458* (1.214)	8.263* (1.303)
	−0.428* (−0.183)	−0.836* (0.300)	−0.524 (0.482)	−1584* (0.223)	0.547* (0.242)	−0.417 (0.268)	−1.55* (0.315)
${\mathit{\text{PROD}}}_o$	0.211 (−0.220)	0.368* (0.206)	0.813 (0.410)	0.148 (0.201)	0.619* (0.216)	0.846* (0.309)	0.379 (0.210)
${\mathit{\text{PROD}}}_d$	0.003 (−0.102)	−0.055* (0.101)	−0.072 (0.130)	−0.085 (0.080)	−0.015 (0.100)	−0.081 (0.121)	−0.048 (0.090)
${\mathit{\text{TA}}}_o$	0.324 (−0.401)	0.768* (0.344)	0.833 (0.905)	0.551 (0.364)	1.026* (0.401)	0.807 (0.615)	0.844* (0.401)
${\mathit{\text{TA}}}_d$	−2.024* (−0.416)	−2.468* (0.549)	−2.354* (0.312)	−2.507* (0.383)	−2.906* (0.505)	−2.670* (0.325)	−2.468* (0.384)
${\mathit{\text{SPS}}}_o$	−0.006 (−0.050)	0.026* (0.042)	−0.071 (0.101)	0.035 (0.043)	0.020 (0.046)	−0.061 (0.081)	0.041 (0.048)
${\mathit{\text{SPS}}}_d$	0.016 (−0.043)	−0.038* (0.071)	−0.009 (0.044)	−0.006 (0.045)	−0.035 (0.060)	−0.019 (0.042)	−0.021 (0.044)
${\mathit{\text{TBT}}}_o$	0.186* (−0.071)	0.061* (0.073)	0.073 (0.170)	0.083 (0.080)	0.062 (0.081)	0.076 (0.128)	0.103 (0.088)
${\mathit{\text{TBT}}}_d$	−0.134* (−0.068)	−0.403* (0.015)	−0.325* (0.072)	−0.315* (0.081)	−0.429* (0.091)	−0.369* (0.083)	−0.340* (0.082)
${\mathit{\text{REER}}}_o$	−1.142* (−0.286)	−1.465* (0.283)	−1.192* (0.540)	−1.600* (0.271)	−1.325* (0.283)	−1.108* (0.448)	−1.530* (0.290)
${\mathit{\text{REER}}}_d$	−0.148 (−0.210)	0.356* (0.255)	0.127 (0.231)	0.003 (0.240)	0.425 (0.250)	0.357 (0.242)	0.193 (0.236)
$\mathit{\text{OECD}}$	−0.169 (−0.266)	−0.04* (0.276)	−0.156 (0.310)	−0.186 (0.274)	0.048 (0.270)	−0.091 (0.296)	−0.126 (0.272)
$\mathit{\text{APEC}}$	−0.365 (−0.329)	0.091* (0.321)	0.305 (0.501)	0.076 (0.311)	0.025 (0.321)	0.281 (0.440)	0.014 (0.306)
$\mathit{\text{FTA}}$	0.120 (−0.156)	0.045* (0.151)	−0.206 (0.170)	−0.078 (0.173)	0.073 (0.172)	−0.132 (0.181)	0.021 (0.173)
$\rho$	−0.906* (0.102)	−0.539* (0.047)	−0.171* (0.051)	−0.912* (0.108)	−0.289* (0.034)	−0.088* (0.035)	−0.324* (0.041)
$\lambda$	0.871* (0.022)	0.550* (0.024)	0.589* (0.025)	0.817* (0.026)	0.341* (0.027)	0.408* (0.026)	0.625* (0.028)
$R^2$	0.021	0.068	0.032	0.115	0.035	0.034	0.080
LL (Log-Likelihood)		−12907	−12663	−12833	−12961	−12752	−12889

Note: * means at 5% level.

Table 5. Elasticity analysis results (based on model 4).

Variables	Coefficient	Total impact	Direct impact	Indirect effects
Lag dependent variable	0.302* (0.010)	0.155* (0.010)	0.301* (0.010)	−0.142* (0.010)
${\mathit{\text{GDP}}}_o$	1.169* (0.240)	0.613* (0.132)	1.174* (0.240)	−0.563* (0.121)
${\mathit{\text{GDP}}}_d$	1.027* (0.205)	0.542* (0.106)	1.046* (0.194)	−0.501* (0.098)
POPo	−2.873* (1.335)	−1580* (0.703)	−3.028* (1.430)	1.421* (0.680)
${\mathit{\text{POP}}}_d$	9.215* (1.348)	4.832* (0.751)	9.340* (1.340)	−4.506* (0.710)
$D$	−1584* (0.223)	−0.845 (0.270)	−1.608* (0.482)	−0.703* (0.728)
${\mathit{\text{PROD}}}_o$	0.148 (0.201)	0.086 (0.112)	0.172 (0.217)	−0.084 (0.103)
${\mathit{\text{PROD}}}_d$	−0.085 (0.080)	−0.041 (0.050)	−0.085 (0.092)	0.048 (0.041)
${\mathit{\text{TA}}}_o$	0.551 (0.364)	0.287 (0.186)	0.556 (0.371)	−0.266 (0.180)
${\mathit{\text{TA}}}_d$	−2.507* (0.383)	−1,325 (0.224)	−2.550* (0.389)	1.230* (0.202)
${\mathit{\text{SPS}}}_o$	0.035 (0.043)	0.016 (0.024)	0.032 (0.043)	−0.014 (0.021)
${\mathit{\text{SPS}}}_d$	−0.006 (0.045)	−0.003 (0.028)	−0.068 (0.042)	0.002 (0.011)
${\mathit{\text{TBT}}}_o$	0.083 (0.080)	0.041 (0.045)	0.081 (0.092)	−0.044 (0.041)
${\mathit{\text{TBT}}}_d$	−0.315* (0.081)	−0,173* (0.040)	−0.322* (0.071)	0.151* (0.036)
${\mathit{\text{REER}}}_o$	−1.600* (0.271)	−0,845 (0.150)	−1618* (0.264)	0.745* (0.142)
${\mathit{\text{REER}}}_d$	0.003 (0.240)	−0.002 (0.115)	−0.005 (0.271)	0.093 (0.132)
$\mathit{\text{ECD}}$	−0.186 (0.274)	−0.104 (0.142)	0.194 (0.272)	0.090 (0.132)
$\mathit{\text{APEC}}$	0.076 (0.311)	0.051 (0.168)	0.102 (0.328)	−0.050 (0.152)
$\mathit{\text{FTA}}$	−0.078 (0.173)	−0.040 (0.086)	−0.081 (0.172)	0.039 (0.085)
$\rho$	−0.912* (0.108)
$\lambda$	0.817* (0.026)
LL (Log-Likelihood)	−12833

Note: * means at 5% level.

LeSage, J. (1999). The theory and practice of spatial econometrics. University of Toledo. https://d1wqtxts1xzle7.cloudfront.net/55768690/sbook-libre.pdf?1518297040=&response-contentdisposition=inline%3B+filename%3DThe_theory_and_practice_of_spatial_econo.pdf&Expires=1713268784&Signature=R3DvXxR79IhopfIdFw4bGRME66jZwWiIhIWY8Ar-vw9FksMj3GgBrr∼u-U2zt0HyR7yYsIHRQ∼d97UsU3iRL4L3vzKGEmzSJ6P5aQ2pCZV41RpmR7kBu5l9oecKhllkWXiOoYP4RYLAwxDQT7zjQjLQH3rqXtk03lOK678uXl1xJRgcnosvzoZWAd4wIWIpKlCgmCWnRczjLl6yW5wtu∼zKnoE3L6x0NDaMgdAXCdYHc6oVrJYcPaFon0pXQFHvkaZYpspVNZ4J3me854H∼jthr62RNg00HTsNnha∼ptaKsy∼∼hetR0K3IQP5jIdlTbmOWp∼Rxlo7jdDhwj42kQ__&Key-Pair-Id=AP KAJLOHF5GGSLRBV4ZA

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