Granger Causality Between the Import Policy and the Comparative

Advantage in China’s Anti-Biotic Product

Yu Hong

, Lin Zhang

, Kexuan Yu

and Aijing Hu

College of International Economics and Trade, Jilin University of Economy and Finance, Changchun, China

Changchun Humanities and Sciences College, Changchun, China

Keywords: China, Import, Antibiotic Product, Granger Causality.

Abstract: This study examined the Chinese "net export ratio" (NX

) that measures the trade balance as a proportion

of the total trade, "revealed symmetric comparative advantage for export" (RX

) and "import restriction"

(HM

) in the anti-biotic products, by using data of 1987-2019 from UN COMTRADE database. Short-run

and the long-run Granger causality tests between "RX

" and "HM

" were performed with both of the

directions with the specific sizes for the effects. The results revealed that in the optimal non-linear models,

improves RX

with positive short-run effect (p=0.033) and long-run effect (p=0.066); HM

lags

have negative long-run effect (p=0.080) on the indicator of HM

itself, indicating that the Chinese import

restriction intervention in the trade of the anti-biotic products has not been inertial.

1 INTRODUCTION

The 2019-ncov (COVID-19) infected pneumonia has

swept China and across the world. World Heath

Organization reckoned it as a pandemic and declared

the disease a Public Health Emergency of

International Concern (PHEIC). Many countries

including China have started the R&D in the

effective COVID-19 vaccine. The disease has also

triggered the interest in developing the other anti-

biotic pharmaceutical products to protect the public

health, and has aroused the necessity of reassessing

the trade policies in the anti-biotic products or the

anti-biotic pharmaceutical industry.

The theories of dynamic comparative advantage

argue that a developing country should support the

development of the key industries by trade

protectionism, in the form of either export promotion

or import restriction or both (List, 2011; Grossman,

1991; Keynes, 1997), in order to improve the

national comparative advantage in the export of the

industries (Smith, 1998). The Chinese policy makers

and a lot of researchers, however, have insisted that

China is of free trade and is to be against any form of

protectionism. Is there an applicable method to

measure the degree of trade protectionism? If there

is, how is the protectionism in the Chinese import in

the anti-biotic products? Can the import restriction

affect the comparative advantage in the trade of anti-

biotic products? This study aims to answer the

questions by empirical analyses.

This research forwarded an innovative approach

to measuring a country's import restriction

protectionism (HM) by the difference between her

net export ability (NX) and her revealed symmetric

comparative advantage in import (RM), which is the

deduction of Ricardian theory of comparative

advantage under the condition of perfect free trade.

(Ricardo, 2015; Salvatore, 2013)

The econometric (time series) analyses based on

the vector error correction (VEC) models revealed

that the Chinese import restriction policy can

increase the country’s comparative advantage in the

export of anti-biotic products, which is in accordance

with the protectionist theory of "dynamic

comparative advantage".

There is another protectionist policy intervention

in the form of import promotion. This research also

reckons the "import promotion" as trade protectionist

policy intervention, because a government may adopt

the trade policies in this form for various reasons.

This may be true for the Chinese trade in energy

products because China has been a country with

booming domestic energy demand in her fast

economic development during the past decades,

which may have encouraged the Chinese government

to promote the energy import instead of restricting it.

Hong, Y., Zhang, L., Yu, K. and Hu, A.

Granger Causality Between the Import Policy and the Comparative Advantage in Chinaâ

Zs Anti-Biotic Product.

DOI: 10.5220/0011730600003607

In Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology (ICPDI 2022), pages 80-84

ISBN: 978-989-758-620-0

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

2 METHODOLOGIES AND DATA

2.1 Data Curation

This research obtained the 4-digit import and export

yearly data for China and the world in the anti-biotic

products (code: 5413) (Chen, 2020) on March 14

2021, for the period of 1987-2019, under the

classification of SITC Rev.1 from United Nation

Comtrade database (https://comtrade.un.org/data/).

Some countries’ postponed data reporting to UN

Statistics Division makes the data for the recent years

only partially available (Balassa, 1965; Dalum,

1998). Note that the later accession to the database

may generate slightly different data that may have

impacts on the results.

2.2

The Indicators for The Import

Patterns

• Net export ratio

The indicator of net export ratio (NX) measures a

county's trade balance in the total trade by

= (X

- M

ck)

/ (X

+ M

) (1)

where X is the export and M is the import. The

subscript of c indicate that China, the k indicates the

anti-biotic product. NX

ranges from -1 to 1 with a

mean value of zero around which NX

is distributed

symmetrically.

• Revealed symmetric comparative advantage

Balassa (1965) originated the indicator of

RCA

= (X

/ X

)/ (X

/ X

) (2)

to capture the comparative advantage that revealed in

the trade. X

is the total export of country c and X

for that of the world (Hong, 2018). RCA

>1 implies

that country c has comparative advantage in product

k, or she is more specialized in product k than the

world as a total (Hong, 2010). Dalum, Laursen and

Villumsen (1998) noted that RCA

ranges from zero

to X

without a definite mean, and designed the

indicator of

=RSCA

= (RCA

- 1)/ (RCA

+ 1) (3)

to address the problem of the asymmetric distribution

of RCA

(Shi, 2019). The value range of RSCA

"revealed symmetric comparative advantage" is [-1,

1] with a definite mean of zero.

This study used RX

to emphasize that it is

applicable to export, and therefore employed

RCAM

= (M

/ M

)/ (M

/ M

) (4)

=-RSCAM

= -(RCAM

- 1)/ (RCAM

+ 1) (5)

to capture the "revealed symmetric comparative

advantage" in country c's import. Because the larger

reflects that country c imports more product k

than the world average, country c is comparative

disadvantaged. Noting this fact, this research added a

negative sign at the right side of the equals sign in

order to ensure that RM

means the same with RX

• The degree of import policy intervention

Under the ideally perfect free trade condition, there is

= RM

(6)

A transposition of this equilibrium generates

= NX

- RM

(7)

where HM

is the indicator of country c's degree of

protectionist import policy intervention which can be

understood as the Chinese import restriction (Pang,

2010).

3 RESULTS AND DISCUSSION

3.1 The Import Patterns of the

Anti-Biotic Product

Figure 1 depicts the Chinese indicators of NX

, RX

and HM

during the sample period of 1987 to 2019.

Figure 1: NX

, RX

and HM

in the Chinese trade in anti-

biotic product (1987-2019).

has been positive but for 1988 when the it

was -0.096. It hit 0.807 in 2015 and the mean is

0.557; RX

was -0.365 in 1990 and reached the high

of 0.583 in 1997 with the mean of 0.283; HM

has

been always positive, implying that China have

adopted the import restriction policies in the anti-

biotic product in order to support the Chinese anti-

biotic industry.

Granger Causality Between the Import Policy and the Comparative Advantage in Chinaâ

Zs Anti-Biotic Product

Table 1: ADF unit root test results for RXck,t and HMck (ln(RXck +1) and ln(HMck +1)).

Variable Test type ADF p-value Variable Test type ADF p-value

C, N, 3 -3.98 0.00 ΔRX

C, N, 1 -5.41 0.00

C, N, 0 -3.36 0.02 ΔHM

N, N, 1 -8.14 0.00

ln(RX

+1) C, N, 1 -5.94 0.00 Δln(RX

+1) N, N, 1 -4.80 0.00

ln(HM

+1) C, N, 0 -3.38 0.02 Δln(HM

+1) N, N, 1 -7.93 0.00

Table 2: Number of co-integration.

Data Trend: None None Linear Linear Quadratic

Test Type

No Intercept Intercept Intercept Intercept Intercept

No Trend No Trend No Trend Trend Trend

Trace 0 1 0 0 0

Max-Eig 0 0 0 0 0

a. Critical values based on MacKinnon-Haug-Michelis

Table 3: VEC model specification results.

Information Criteria Model 1 Model 2 Model 3 Model 4 Model 5

Determinant resid covariance (dof adj.) 0.000 0.000

0.000 0.000 0.000

Determinant resid covariance 0.000 0.000 0.000 0.000 0.000

Log likelihood 91.372

93.926 94.023 94.680 96.072

Akaike information criterion -5.291 -5.395

-5.335 -5.312 -5.338

Schwarz criterion -4.731 -4.788

-4.681 -4.611 -4.591

b. * indicates the model assumption selected by each individual information criterion.

3.2 ADF Unit Root Test Results

Table 1 presents the Augmented Dicky-Fuller

(ADF) test results for RX

and HM

. Because the

relationship of the variables can also be non-linear

and the level series of RX

and HM

recorded have

negative values, the results of ln(RX

+1) and

ln(HM

+1) are also reported. (Shi, 2019; Hong,

2020).

All series are stationary under both linear and

non-linear model assumptions. The first differences,

however, are also stationary (p=0.001), making the

time series are applicable for the econometric

analyses based on the VEC models.

3.3 Selection of The Linea/Non-Linear

Model Assumptions

This research compared the lag interval of

unrestricted vector auto regression (VAR) models

with the maximum lag of 6, which is approximately

one fifth of the total sample period (32 years),

between the linear and the non-linear VAR model

assumptions. For both linear and non-linear model

assumptions, all of the information criteria of FPE,

AIC, SC and HQ selected lag order of 3 as the

optimal. The non-linear models have smaller

information criteria, making us select the non-linear

models with the lag interval of 1-3, which implies

that the optimal VEC models are non-linear with the

lag interval of 1-2.

3.4 Summary of Johansen

Co-Integration

Table 2 summarizes the five sets of co-integration

test types with the critical value set to be 0.05 level.

Trace statistic identified one co-integrating

relation, while Max-eigenvalue identified none. This

may be because the omission of some key

variable(s) in the model, which can be expected to

be improved by extending the model to include the

indicator of the "export policy intervention". This

research, however, reckoned that ln(RX

ck,t

+1) and

ln(HM

ck,t

+1) are co-integrated and then proceeded

to further analyses.

3.5 VEC Model Specification Results

Model 1 in Table 3 assumes "no intercept or

deterministic trend in CE (co-integrating equation)";

model 2 assumes "intercept (no deterministic trend)

ICPDI 2022 - International Conference on Public Management, Digital Economy and Internet Technology

Table 4: Short-run Granger causality test results for ln(RXck,t +1) and ln(HMck,t +1).

Dependent

Independent

Δln(RX

ck,t

+1) Δln(HM

ck,t

+1)

Chi-s

SE Chi-sq

Δln(RX

ck,t-1

+1),

Δln(RX

ck,t-2

+1)

—— —— —— 2.646 0.266 ——

Δln(HM

ck,t-1

+1),

Δln

(

ck,t-2

)

6.850 0.033 1.900 —— —— ——

Table 5: Long-run Granger causality test results for ln(RXck,t +1) and ln(HMck,t +1).

Dependent

Independent

Δln(RX

ck,t

+1) Δln(HM

ck,t

+1)

F-stat p LE F-stat p LE

ECT

t-1

1.604 0.217 —— 0.548 0.466 ——

ECT

t-1

,Δln(RX

ck,t-1

+1), Δln(RX

ck,t-2

+1) 1.251 0.313 —— 0.967 0.111 ——

ECT

t-1

,Δln(HM

ck,t-1

+1), Δln(HM

ck,t-2

+1) 2.719 0.066 0.020 2.531 0.080 -0.105

in CE"; model 3 assumes "intercept (no

deterministic trend) in CE"; model 4 assumes

"intercept and trend in CE"; model 5 assumes

"quadralic deterministic trend", compares the

information criteria for the non-linear VEC models

with the lag interval of 1-2.

The statistics of both "Akaike information

criterion" (AIC) and "Schwarz criterion" (SC)

selected "model 2" as the optimal, and the statistics

of "determinant residual covariance (dof adj.)" also

confirmed this selection. This research thus

determine "model 2" or "intercept in CE, no

deterministic time trend in the VAR" to be the

optimal.

3.6 Short-Run Granger Causality Test

Results

Table 4 reports the results of short-run Granger

causality tests or the block exogeneity Wald tests.

Along with the direction, this research also reports

the specific value(s) for the short-run effect(s) (SE)

by aggregating the coefficients of all lags of the

independent variable(s).

There is a unidirectional Granger causality

running from ln(HM

ck,t

+1) to ln(RX

ck,t

+1)

significantly (p=0.033) with positive short-run effect

(SE=1.900), implying that the import restriction can

improve the Chinese comparative advantage. At

least in the short-run, the prediction of the theories

of dynamic comparative advantage holds for the

trade in anti-biot product.

3.7 Long-Run Granger Causality Test

Results

Table 5 shows the long-run Granger causality test

results.

The long-run effect(s) (LE) are measured by the

converge values (at the 25th period) of the

generalized impulse-response functions after the

shock. The long-run equilibrium error correction

term (ECT

t-1

) of the VEC models does not Granger

cause either Δln(RX

ck,t

+1) or Δln(HM

ck,t

+1). The

lags of Δln(HM

ck,t

+1) jointly with ECT

t-1

, however,

Granger cause Δln(RX

ck,t

+1) with positive long-run

effect (LE=0.020, p=0.066) and Granger cause

Δln(HM

ck,t

+1) with negative long-run effect (LE=-

0.105, p=0.080).

The evidence show that in the long-run, the

Chinese trade in the anti-biot products has also

complied to the predictions of the dynamic

comparative advantage theories. The Chinese import

policy intervention policy has been effective in

improving the export comparative advantage in the

anti-biot product, although marginally significant.

Not surprisingly, the evidence from China differ to

the results for the Indian protectionism policies in

the anti-biotic industry (Hong, 2019). This implies

that even the same industry (product) of the two

comparable developing countries can be different.

4 CONCLUSION

This study obtained the trade patterns of NX

, RX

and HM

for the Chinese trade in the anti-biotic

pharmaceutical products using UN Comtrade annual

data. We conducted time series analyses of "revealed

symmetric comparative advantage for export" (RX

)

and "import restriction" (HM

), including both short-

run and long-run Granger causality tests.

• During the sample period of 1987-2019, China

has restricted the import of the anti-biot product

significantly and has had comparative advantage in

the product export;

Granger Causality Between the Import Policy and the Comparative Advantage in Chinaâ

Zs Anti-Biotic Product

• The Chinese import restriction (HM

) improves

the comparative advantage in the anti-biotic product

(RX

) with positive short-run and long-run effect.

• The lags of HM

have negative long-run effect

on of HM

, implying that the Chinese trade policy

intervention has not been inertial.

The empirical evidence is in accordance with the

predictions of the dynamic comparative advantage

theories. (Ma, 2019; Yang, 2020; Hong, 2021) The

short-run and long-run effects of the import

interventions have improved the comparative

advantage of the anti-biotic industry.

Every country has right to choose its own path to

the development. A developing country's

protectionist policy intervention should not be

criticized so much, as long as it can improve the

country's comparative advantage in a certain specific

industry that is crucial for its development.

ACKNOWLEDGEMENTS

This work was financially supported by Jilin

Provincial Social Science Fund (2020J58, 2020J60),

Changchun Social Science Fund (CSK2020ZYJ-

001) and the College Poverty Stricken Students

Supporting Programme funded by Jilin Provincial

Ecological Industry Company Limited.

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