Labor, Digital and Growth GDP Analysis: Case Study of ASEAN

Countries

Helmi Adam

, Muhammad Asrian Mirza, Sri Iswati

Universitas Borobudur Jakarta

Keywords : Labor, Digital, GDP, ASEAN

Abstract :The ASEAN Economic Community was formed with the aim of achieving the perfection of economic

integration in the ASEAN region which is believed to provide tangible benefits for all elements of society.

On the other hand, the use of technology in the company will also affect how much work is needed.

Technological sophistication alone does not necessarily result in a decrease in the number of workers.

Technological progress will lead to better production results. This study uses a quantitative method with

panel data secondary to the 2011-2015 period by combining 10 ASEAN countries (Indonesia, Malaysia,

Singapore, Thailand, Philippines, Vietnam, Myanmar, Brunei, Laos, Cambodia). From the calculation of T-

Test, Effect of Labor on GDP so that it can be concluded that the labor variable partially influences the

significance of the GDP variable and effect of Digital on GDP so it can be concluded that the Digital

variable partially influences the positive significance of the GDP variable. From the calculation of F value,

that simultaneously or together the independent variables have a significant effect on the dependent

variable. Koefisein Determination, Based on the table above, the Adjusted R-Square value is 0.9975. This

shows that the model is able to explain 99.75% of the dependent variable, while the remaining 0.25% is

influenced by other factors outside the regression model. Labor and digital influences on GDP are already

good, but there are some countries that have to be improved again such as Myanmar, Laos and Cambodia.

The policies of these three countries in the use of digital technology are expected to improve the welfare of

the workforce. If digital technology has been implemented properly, all countries in ASEAN will get the

same welfare.

1 INTRODUCTION

The ASEAN Economic Community (AEC) was

formed with the aim of achieving the perfect

economic integration in the ASEAN region which is

believed to provide tangible benefits for all elements

of society. According to Abdurofiq (2015) explains

there are at least 4 (four) things that become the

focus of the implementation of the AEC, first,

countries in the market unity and production base.

Second, AEC will be used as a region with a very

high level of competition. Third, the AEC will be

used as a joint with equitable economic

development. Fourth, the AEC will be integrated

into equitable economic development among the

entire ASEAN region.

In the case of Labor, Increasing the wage rate

will result in an increase in production costs, so that

it will increase the per unit price of the product

produced. If the per unit price of the product being

sold is increased, the reaction that usually arises is to

reduce the purchase or no longer buy the product. So

that there will be a change in the production scale

called the effect of production scale (scale effect)

where a condition that forces producers to reduce the

number of products produced, which in turn can also

reduce the company's workforce. An increase in

wages assuming the price of other capital goods

remains, the entrepreneur has a tendency to replace

labor with machinery. The decrease in the number of

workers due to the replacement with a machine is

called the substitution effect. On the other hand, the

use of technology in the company will also affect

how much work is needed. Technological

sophistication alone does not necessarily result in a

decrease in the number of workers. Technological

progress will lead to better production results, but its

ability to produce products in the same or relatively

equal quantity. Furthermore, the amount of labor

demanded can be determined by the level of

Adam, H., Mirza, M. and Iswati, S.

Labor, Digital and Growth GDP Analysis: Case Study of ASEAN Countries.

DOI: 10.5220/0008784802570261

In Proceedings of the 2nd International Research Conference on Economics and Business (IRCEB 2018), pages 257-261

ISBN: 978-989-758-428-2

257

productivity of the workforce itself. Productivity is

the ability to produce something.

2 LITERATURE REVIEW

2.1 Labor

According to Takyuddin (2016) explains Labor is

defined as a population in the working-age

population. Whereas the definition of labor is

contained in Law No. 25 of 1997 concerning

Manpower, namely every man or woman who is in

and/or will do work, both inside and outside the

employment relationship to produce goods or

services to fulfill community needs. According to

Dumairy (1997) labor is a population that has an age

within the working age limit. The purpose of

choosing the age limit is so that the definition given

is as possible as describing the actual reality. Each

country chooses a different age limit because the

situation of labor in each country is also different, so

that the working age limit between countries is not

the same. In Indonesia, the minimum age limit for

labor is 15 years without maximum limits.

2.2 Digital

Setiawan (2017) explains that the digital world not

only offers great opportunities and benefits for the

public and business interests. But it also presents

challenges to all areas of life to improve quality and

efficiency in life. The use of various technologies

really makes life easier, but even a digital lifestyle

will depend more on cellphone and computer usage.

According to Musafak (2012) explained that the

digital economy is an economy based on electronic

goods and services produced by electronic

businesses and traded through electronic commerce.

That is, businesses with electronic production and

management processes and who interact with

partners and customers and conduct transactions

through the Internet and Web technologies. Musafak

(2012) also describes the Digital Economy definition

version of Encarta Dictionary is "Business

transactions on the Internet: the marketplace that

exists on the Internet". Understanding Digital

Economy focuses more on transactions and markets

that occur in the internet world. A broader

understanding of just transactions or markets is the

New Economy which according to PC Magazine is

"The impact of information technology on the

economy". The understanding is more emphasized

on the application of information technology in the

economic field. The digital economy is the

economic sector which includes goods and services

when developing, producing, selling or supplying

depends on digital technology.

2.3 GDP

Economic growth is the development of activities in

the economy which causes goods and services

produced in society to increase so that it will

increase the prosperity of the community (Sukirno,

1994) in Suparyati (2015). Still in Suparyati (2015)

according to Budiono that economic growth is a

process of increasing per capita output in a long

period.

According to Athukorala (2003) in (Jufrida,

2016), foreign investment has a positive impact on

the economy of the host country because through

foreign investment can increase the availability of

funds for the host country (recipient country). But

the results of research conducted did not find a

significant relationship between FDI and economic

growth, especially for developing countries. (Liu

and Su 2016 in Jufrida, 2016) also conducted

research on the impact of FDI and human capital on

economic growth in China by using panel data of

cities in China from 1991 to 2010. They tested the

determinants of economic growth with a focus on

the role of FDI and human capital with the human

capital-augmented Solow model. The results show

that the GDP growth rate per capita is negatively

related to the rate of population growth and is

positively related to the level of investment in

physical capital and human capital. They also found

that FDI had a positive effect on GDP per capita

growth and this effect was intensified by ownership

of urban human capital. The total foreign investment

and domestic investment, both government and

private, is one of the variables in the calculation of

national income which is a benchmark of economic

growth, therefore investment should be maintained

in the development of stability and continued efforts

to increase.

3 METHOD

The population that became the object in this study

came from secondary data obtained from the

company Knoema, one of the digital economic data

provider companies. The sampling method uses

purposive sampling method, namely the

determination of samples with certain

considerations. In this study the sample was used

IRCEB 2018 - 2nd INTERNATIONAL RESEARCH CONFERENCE ON ECONOMICS AND BUSINESS 2018

258

using panel data obtained by time series data for 5

years and cross-section data of 10 ASEAN countries

namely Indonesia, Malaysia, Singapore, Philippines,

Thailand, Vietnam, Myanmar, Laos, Brunei,

Cambodia.

3.1 Variable Identification

Research variables are independent and dependent.

for the independent variables that exist in this study

are Labor (X1), Digital (X2) while the dependent

variable GDP (Y).

3.2 Data analysis

The analytical method used in this study is a

quantitative technique that uses mathematical and

statistical models that are classified in certain

categories to facilitate analysis using the Eviews

program. While the analysis technique used is

multiple linear regression analysis techniques to see

the relationship between the independent variable

and the dependent variable. The data used is the

panel data there are three kinds of data panel

estimation techniques, namely pooled the least

square, fixed effect model, and random effect model.

Test the suitability of the model to determine the

most appropriate model is to use the Chow test.

After that, the classic assumption test is a normality

test and also hypothesis testing, namely partial t-test,

simultaneous F test, a test of the coefficient of

determination.

3.3 Econometry Model

The analysis technique in this study is a panel data

regression analysis, while the regression model in

the form of logs can be written as follows:

ln Y

= β

+ β

ln X1

+ β

ln X2

+ e

(1)

Where:

Y = Tourism; X1 = Labor; X2 = Digital, i =

Country; and t = time.

4 RESULT

There are three estimations of panel data regression,

namely common effects (OLS), fixed effect models

(FEM) or Random Effect (REM) models.

Determining the panel model that will be used in this

study, several tests must be carried out. Chow Test

that can be used to determine whether the panel data

model can be regressed with common effect models

(OLS), fixed effect models (FEM) or Random Effect

(REM) models. Chow test is used to determine

whether the panel data model is regressed with the

Common Effect model or with the Fixed Effect

model.

H0: The best model is the Common Effect

H1: The best model is the Fixed Effect

4.1 Chow Test

Table 1: Chow Test

The table above shows that the best model is the

fixed effect because the Chi-square probability value

is below 0.05, this means that H0 is accepted.

Table 2: Fixed Effect Model

From the results of panel data regression with the

selected model is the Fixed Effect model, the

regression model equation is obtained as follows:

GDP = -4.90 (Labor) + 2.61 (DIGITAL) + e (2)

Labor, Digital and Growth GDP Analysis: Case Study of ASEAN Countries

259

4.2 Normality test

Figure 1: Histogram

From the output that has been tested, it states that the

histogram form is distributed symmetrically so that

the residuals are distributed normally. Based on the

JB statistical test, the value is 3.287 with a

probability of 0.1932 while the chi-square value

with significance (α = 5%) is 0.05, so JB < Chi

Square, then H0 is accepted and H1 is rejected

meaning that the residual is normally distributed.

4.3 T test (Partial)

Table 3: T test (partial)

Based on the results above as follows:

4.3.1 Effect of Labor on GDP

The t-statistical probability value obtained is 0.0489,

then the statistical probability <α = 5% is 0.0489

<0.05, but the coefficient value is -4.90. So it can be

concluded that the labor variable partially does not

affect but the significance of the GDP variable.

4.3.2 Effect of Digital on GDP

The obtained t-statistical probability value is 0.0007.

Then the statistical probability <α = 5% is 0.0007 <

0.05. So it can be concluded that the Digital variable

partially influences the positive significance of the

GDP variable.

4.4 F Test (Simultaneous)

From the calculation of F value, it is known that F

arithmetic > F table (1431.317 > 3.18) then H0 is

accepted and H1 is rejected (F arithmetic is in H1

reception area). Then also the probability (prob.) Of

the table above is equal to 0.000 > 0.005, then H0 is

accepted and H1 is rejected. So that simultaneously

or together the independent variables have a

significant effect on the dependent variable.

Coefficient of Determination

 , Based on the table

above, the Adjusted R-Square value is 0.9975. This

shows that the model is able to explain 99.75% of

the dependent variable, while the remaining 0.25%

is influenced by other factors outside the regression

model.

Table 4: Growth Labor

growth

La bo

Indonesia Malaysia Si ngapura Thai land Phil ipnes Vietnam Myanmar Laos Brunei Kamboja

2012 2,58 3,43 3,42 (0,23) 1,00 1,75 0,73 1,29 0,48 (2,17)

2013 1,11 3,89 0,86 (1,64) 1,16 1,47 0,78 1,24 (0,64) 0,05

2014 1,23 2,09 1,15 (0,17) 1,98 1,34 0,80 1,26 (0,37) 1,65

2015 1,19 1,64 1,97 (0,08) 2,12 1,08 0,66 1,60 1,42 1,74

5 DISCUSSION

Effect labor, digital to GDP is good enough, but

must be increased in labor. In table 4 it can be

explained that Singapore has good labor, it looks

good labor growth. Whereas for the country of

Thailand has decreased, this means that labor factors

are very problematic in this country. Whereas other

countries, seen the growth of labor has been good

even though growth from year to year often changes,

IRCEB 2018 - 2nd INTERNATIONAL RESEARCH CONFERENCE ON ECONOMICS AND BUSINESS 2018

260

sometimes increases, sometimes decreases.

Government policy to provide training so that labor

becomes quality and has high productivity. Mastery

of digital technology for labor is needed so that labor

can work effectively and efficiently.

6 CONCLUSION

This study aims to analyze the relationship between

Labor, digital towards ASEAN countries GDP in the

period 2011-2015 using panel data regression

analysis techniques. Based on the results of

statistical tests, the following conclusions can be

drawn:

6.1 Effect of Labor on GDP

The t-statistical probability value obtained is 0.0489,

then the statistical probability <α = 5% is 0.0489 <

0.05. So that it can be concluded that the labor

variable partially influences the significance of the

GDP variable. Effect of Digital on GDP, the

obtained t-statistical probability value is 0.0007.

Then the statistical probability <α = 5% is 0.0007 <

0.05. So it can be concluded that the Digital variable

partially influences the positive significance of the

GDP variable.

6.2 The Calculation of F Value

It is known that F arithmetic > F table (1431.317 >

3.18) then H0 is accepted and H1 is rejected (F

arithmetic is in H1 reception area). Then also the

probability (prob.) Of the table above is equal to

0.000 > 0.005, then H0 is accepted and H1 is

rejected. So that simultaneously or together the

independent variables have a significant effect on

the dependent variable. Coefficient of

Determination, Based on the table above, the

Adjusted R-Square value is 0.9975. This shows that

the model is able to explain 99.75% of the

dependent variable, while the remaining 0.25% is

influenced by other factors outside the regression

model.

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