An Economics Analysis of Relationship between the AEC's Demand for ICT and Economy Development Using PCHVAR(x)-Model

Procedia Economics and Finance 14 ( 2014 ) 110 – 119

2212-5671 © 2014 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).Selection and/or peer-review under responsibility of the Organizing Committee of ICOAE 2014doi: 10.1016/S2212-5671(14)00692-3

ScienceDirectAvailable online at www.sciencedirect.com

An economics analysis of relationship between the AEC’s demand for ICT and economy development using

PCHVAR(x)-model

Prasert Chaitipa, ChukiatChaiboonsrib

aAssoc. Prof., Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand bLecturer. Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand.

Abstract

This research is preliminary information of some empirical findings based on an analysis demand for ICT by the panel conditionally homogenous vector autoregressive(x)-model (PCHVAR(x)-model). Moreover, the data was used in this research started from 1996-2011 by panel data in terms of yearly. The empirical results from this research based on simultaneous equation analysis (PCHVAR(x)-model) has already indicated that the AEC demand for fixed phone was higher impacted by AEC population than AEC demand for mobile phone. However, the AEC demand for mobile phone was higher impacted by AEC GDP than AEC demand for fixed phone. In terms of AEC demand for internet user was not involved into the panel conditionally homogenous vector autoregressive(x)-model because it has a difference number of order in the panel unit root test process among of each country in AEC. It is meaning that among of each country in AEC has a different opportunity to access the world wide information. This is a big duel to stimulate ICT’s plan to keep going develop for AEC countries more than now a day. © 2014 The Authors. Published by Elsevier B.V. Selection and/or peer-review under responsibility of the Organising Committee of ICOAE 2014. Keyword: AEC; ICT; demand; the panel conditionally homogenous vector autoregressive(x)-model

1. Introduction

In 2015, AEC will be started process of the vision is “Single Market and Production Based”. Based on this vision can be extended more meaning by five polices in actions such as free flow of goods, free flow of service; free flow of investment, free flow of capital, and free flow of skilled labour (Department of Trade Negotiation(DTN, Thailand). According to five polices have already pointed out belong to this vision need to more connect with each other in among of AEC country by ICT sector. The meaning of ICT in this research is come from the Information Communication Technology. In the present time, the AEC demand of ICT is going very fast in within all of them. For example, the ICT demand of mobile phone in AEC countries increased every year since 1996 until 2010 ((source: from ITU World Telecommunication (1996-2010)). Moreover, the

© 2014 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).Selection and/or peer-review under responsibility of the Organizing Committee of ICOAE 2014

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111 Prasert Chaitip and Chukiat Chaiboonsri / Procedia Economics and Finance 14 ( 2014 ) 110 – 119

ICT demand of internet user in AEC countries also increased every year since 1996 until 2010 too. However, the ICT demand has not found that a lot of study from researchers in previously. In among of researches have already studied relate with this topic such as Cette and Lopez(2009), Diminescu, Hepp, Welling, Maya-Jariego, and Yates (2009), and Prasert and Chukiat (2013). From previous studied, this topic still have a research gaps to study more especially in AEC countries. This study examines the factors that influence ICT by using public users’ choices among business arrangements offered in the AEC countries. An empirical analysis based on the panel conditionally homogenous vector autoregressive(x)-model was conducted to estimate the relationship between AEC demand for ICT and the macro variables have to involve the study.

2. The objective of research

To estimate the relationship between demand of ICT and macro variable (GDP of each country in AEC and the numbers of population of each country in AEC) in during period of 1996-2011 by panel data in terms of yearly. 3. Scope of this research

The panel data was used on this research such as the numbers of mobile phone in use of AEC countries, the numbers of fixed phone in use of AEC, the number of internet user in use of AEC countries, the GDP of each country in AEC, and the numbers of population in AEC countries for during period of 1996-2011.

4. Literature reviews

The Cette and Lopez(2009) studied about the behaviour of ICT demand in case of international comparison. This research concluded that the demand of ICT correlated with the population in higher education level of OECD countries based on data cover period 1981-2005. Diminescu, Hepp, Welling, Maya-Jariego, and Yates (2009), studied about the ICT supply and demand in immigrant and ethnic minority communities in France, Germany, Spain, and the United Kingdom. The conclusion result from this research was found that the social-economics variables did not impact to ICT demand of these countries. Prasert and Chukiat(2013), studied about the AEC’s demand for ICT. The result from this research was found that the macro variables (GDP of AEC, Population of AEC) have positive impact to ICT demand of AEC.

5. The research framework and methodology

5.1 The research framework of this study The research framework of this paper was applied to analysis of relationship between AEC’s demand for ICT and their economy development. Based on both the research framework and methodology are presented follow below that:-


Figure 1 presents the concept frame work of economics analysis of relationship between the AEC’s demand for ICT and economy development

5.2 The statistics methodology

The Panel Conditionally Homegenous Vectorautoregressive Model was employed to estimate the relationship between the demand of ICT and social economics variable in among of AEC countries. The PCHVAR-model (the command from Math-lab code) was originated by Georgios (2012). This model can be written from equation (1) and also this equation was presented below that:-

(1)

And where i = (1,..,N) is represented the cross-section data as well as t = (1,..,p) is represented the time series data. Moreover, Aj (.) is coefficient of model and yit is represented the endogenous variable in the model (Mobile phone in use, internet in use, Fixed Phone in use (in among of AEC countries). Furthermore, the panel conditionally homegenous vectorautoregressive (X)-model can be written from equation (2) (2) Defined that:- ᵟi = Constant term, Fixed effects, Cross-section time trends or Seasonal dummies, W

t = Exogenous variable with homogeneous effect in this model(GDPit,Popit) Vit = Exogenous variable with cross effect in this model (Popit) yit = The endogenous variable in this model(Mobile phone in use, internet in use, Fixed Phone in use (in among of AEC countries).

),0(,).(..).().( ,2,21,1 uititptiitptiittiitit uuyzAyzAyzAy

ptiptiitptiittiitit yyzAyzAyzAy ,,2,21,1 .).(..).().(

,,00 .......... itftiifiitiqtqti uvFvFwBwBi

Information and technology

will be Growth

Economy Growth

Population Growth


Fi = Coefficient of model Based on the equation (2) was conducted to estimate for the model was used in this research.

6. Data description

The number of mobile phone in use of each country in AEC during period cover 1996-2011 (yearly data) was displayed by figure (2). Moreover, the figure (3) presents the number of fixed phone in use of each country in AEC during period cover 1996-2011 respectively.

Figure (2) the number of mobile phone in use of each country in AEC during period cover 1996-2011 (Yearly data, unit: 000s)

From: ITU World Telecommunication/ICT Indicators Database.

Figure (3) the number of fixed phone in use of each country in AEC during period cover 1996-2011 (Yearly data, unit: 000s)

From: ITU World Telecommunication/ICT Indicators Database

Furthermore, the percentage of internet user of each country in AEC in period cover 2001-2011 was displayed by figure (4). From three figures were conducted to conclude that the AEC demand of ICT will be increased by continuously since 1996 until 2011.


Figure (4) the percentage of internet user of each country in AEC during period cover 1996-2011 (Yearly data, unit: the percentage of people age more than 10 year olds)

From: ITU World Telecommunication/ICT Indicators Database

The percentage change of GDP (%) of each country in AEC since 1996-2011 was displayed by figure (5). From this figure was found that the Asian financial crisis (1997-1999) has deep negative impacted to their percentage change of GDP. However, after this crisis some the AEC countries were recovered their economy by the International Monetary Fund (IMF) such as currency packages, banking, and financial system reforms (http://en.wikipedia.org/wiki/1997_Asian_financial_crisis). Finally, the percentage change of GDP (%) of each country in AEC will be increased since 2000 until 2009. One again, the Global Financial Crisis was started from 2007 until 2008 as well as this crisis has negative impacted to only some country in AEC such as Brunei, Indonesia, Singapore, Malaysia, and Thailand(see figure 5). Figure (5) the percent change of GDP (%) of each country in AEC during period cover 1996-2011 (Unit: Percent change (%))

From: International Monetary Fund - 2011 World Economic Outlook


The population of each country in AEC was presented by table (1) as well as the largest population country in AEC is Indonesia. And the second largest population country in AEC is Philippines and then Vietnam respectively. Table (1) the number of population in each of AEC countries during period cover 1996-2011 (Unit: Million people) Country Obs. Mean Std. Dev. Min Max

Brunei 16 .3569687 .0408993 .295 .417 Cambodia 16 13.27153 .8157756 11.819 14.289

Indonesia 16 216.5945 12.39303 198.32 237.641 Laos 16 5.733406 .4814978 4.932 6.437

Malaysia 16 25.20138 2.428206 21.169 28.251 Myanmar 16 53.70744 5.128096 45.57 61.187 Philippines 16 82.58263 7.946714 69.952 94.013 Singapore 16 4.422 .4707114 3.796 5.165

Thailand 16 62.43009 1.062303 60.116 63.878 Vietnam 16 81.26825 4.964553 73.157 88.257

From: International Monetary Fund - 2011 World Economic Outlook

7. Empirical results of research

The estimation results based on the panel conditionally homogenous vector autoregressive(x)-model was displayed by table (2). From the appendix A, the impulse responses analysis based on PCHVAR(X)-model estimation for ICT sector in AEC countries was presented by figure (7) until figure (9). Two results of this estimation are shown by graphically in these figures. First result of estimation based on panel conditionally (fixing at mean of AEC population) homogenous vector autoregressive(x)-model is implied that demand of fixed phone was higher impacted by AEC population than demand of mobile phone.

Table (2) present the result of estimation based on the panel conditionally homogenous vector autoregressive (X)-model(PCHVAR(X)-model)

Items Mobile

Phonei,t-1

Fixed Phonei,t-1

Fixed effects

Time trends GDPt Popi

Mobile Phoneit 0.397672 -0.00985 -0.17645 -0.19769 0.056695 -0.09814 (t-value) (1.825785) (-0.37258) (-2.32169) (-0.45013) (0.894945) (-0.35818)

Fixed Phoneit 0.683075 -0.12903 0.094765 1.615967 -0.37362 0.355572 (t-value) (1.893729) (-2.94789) (0.752926) (2.221784) (-3.56131) (0.783624)

From: computed Second result of estimation based on panel conditionally (fixing at mean of AEC GDP) homogenous vector autoregressive(x)-model is implied that demand of mobile phone was higher impacted by AEC GDP than demand of fixed phone(see more detail from appendix A) . 8. The conclusion and recommendation The conclusions from this research are empathized that that the AEC demand for mobile phone was higher impacted by AEC GDP than AEC demand for fixed phone. In terms of AEC demand for internet user was not


involved into the panel conditionally homogenous vector autoregressive(x)-model because it has difference order of unit root test among of each country in AEC. It is meaning that among of each country in AEC has a different opportunity to access the world wide information.

References

1) Breitung, J., Pesaran, H., (2005), Unit Roots and Cointegration in Panels, CESIFO Working Paper No. 1565 2) Chaiboonsri, C., Chokethaworn,K., and Chaitip,P. (2012), “Frontier of Econometrics Time Series Analysis in ICT's Stock Market of Thailand: Maximum Entropy Bootstrap Approach”, Procedia Economics and Finance, Volume 1, 2012, Pages 81-87 3) Chaitip, P., & Chaiboonsri, C. (2013). AEC’s Demand for ICT: Maximum Entropy Bootstrap Approach in Panel data (pp. 1-440 (2012)) The International Conference on Applied Economics (ICOAE), Uppsala, Sweden, 2012 Procedia Economics and Finance 4) Dana Diminescu, Andreas Hepp, Stefan Welling, Isidro Maya-Jariego, and Simeon Yates,(2009), ICT Supply and Demand in Immigrant and Ethnic Minority Communities in France, Germany, Spain and the United Kingdom, European Commission Joint Research Centre Institute for Prospective Technological Studies. 5) Hrishikesh D. Vinod and Javier L_opez-de-Lacalle,(2009 ), “ Maximum Entropy Bootstrap for Time Series: The meboot R Package”, Journal of Statistical Software. 6) Hyndman RJ (1996). “Computing and Graphing Highest Density Regions." The American Statistician, 50, 120-126. 7) Hausman JA (1978). “Specification Tests in Econometrics.”, Econometrica, 46, 1251-1271. 8) Hyndman RJ (2008). hdrcde: Highest Density Regions and Conditional Density Estimation. R package version 2.09, URL http://CRAN.R-project.org/package=hdrcde. 9) Georgios Georgiadis,(2012), The Panel Conditionally Homogenous Vectorautoregressive Model Goethe University Frankfurt March 30, 2012 10) Georgiadis, Georgios (2012): The panel conditionally homogenous vectorautoregressive model. MPRA is a RePEc service hosted by the Munich University Library in Germany. 11) Gibert Cette and Jimmy Lopez,(2009), ICT demand behavior: An international comparison, Banque de France and Université de la Méditerranée (DEFI), 12) Im, K., Pesaran, H., Shin, Y., (2003), Testing for unit roots in heterogenous panels, Journal of Econometrics, vol. 115. 13) Pesaran, H., (2003), A Simple Panel Unit Root Test in the Presence of Cross Section Dependence, Cambridge Working Papers in Economics 0346, Faculty of Economics (DAE), University of Cambridge 14) M. Hashem Persaran(2007), A Simple Panel Unit Root Test in Presence of Cross-section Dependence, J. Appl. Econ. 22: 265–312 (2007), Published online in Wiley InterScience

Appendix A

Table (3) Present data description of panel conditionally homogenous vector autoregressive (X)-model

Items G_Fixed Phone G_Internet G_ Mobile Phone G_Population GDP Mean 11.98827 19.56082 41.46545 1.456000 5.733300

Median 2.905000 8.460000 31.25000 1.640000 5.819000 Maximum 561.9900 71.00000 222.0000 5.450000 14.47100 Minimum -29.22000 0.000000 -0.400000 -1.750000 -2.363000


Std. Dev. 56.02475 22.07973 37.12169 1.194348 3.555151 Skewness 8.795357 0.968164 1.798341 -0.259692 0.027252 Kurtosis 86.19724 2.558010 7.553244 4.298544 3.334480

Jarque-Bera 33143.07 18.07999 154.3123 8.964895 0.526386 Probability 0.000000 0.000119 0.000000 0.011306 0.768594

Panel unit root test* I(0) I(1) I(0) I(0) I(0) CADF panel unit root

test** I(1) I(2)+,I(3)++ I(1) I(1) I(1) Observations 110 110 110 110 110

*/ Levin, Lin & Chu t (assumes common unit root process), Im, Pesaran and Shin W-stat (assumes individual unit root process)^/

**/ It is now relatively easy to construct panel unit root tests that simultaneously take account of cross-section dependence and residual serial correlation.( M. HASHEM PESARAN, J. Appl. Econ. 22: 265–312 (2007) ) +/ only 7 countries such as Brunei, Indonesia, Malaysia, Philippine, Thailand, and Vietnam. ++/ only 3 countries such as Cambodia, Loa, and Myanmar. ------------------ ^/ Panel unit root test based on standard methods such as Levin, Lin & Chu t and Im, Pesaran and Shin W-stat are assumed that the error terms of each cross-sections (i) are independently. And other standard panel unit root methods such as ADF - Fisher Chi-square and PP - Fisher Chi-square can be removed auto-correlation problem from the panel data to be tested. However, based on previous standard panel unit root test have already mentioned that as well as all of them are not good enough to test the panel data of this research. Therefore, this research will be used the CADF panel unit root test (PESARAN ,2007) instead of them. Figure (6) Present all of data were employed to estimate based on PCHVAR(X)-model such as the ICT data of AEC country, Population of AEC country, and GDP of AEC country cover period of 2001-2010

1=Brunei, 2=Cambodia, 3= Indonesia, 4=Laos, 5=Malaysia, 6=Myanmar,7=Philippine,8=Singapore, 9= Thailand, 10=Vietnam

-100

0

100

200

300

400

500

600

1 -

01 1

- 05

1 -

09 2

- 02

2 -

06 2

- 10

3 -

03 3

- 07

3 -

11 4

- 04

4 -

08 5

- 01

5 -

05 5

- 09

6 -

02 6

- 06

6 -

10 7

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7 -

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8 -

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9 -

01 9

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9 -

09 1

0 - 0

2 1

0 - 0

6 1

0 - 1

0

G_FIXP G_INTER G_MBPG_POP GDP


Figure (7) Present the impluse respondses of mobile phoneit/ fixed phoneit/ GDPit/Popit based on

PCHVAR(X)-Model estimation

At the mean of Popit

At the mean of GDPit

Figure 8 Forecast Error Variance Decompositions of ICT demand (Coditionally by AEC GDP)


Figure (9) Forecast Error Variance Decompositions of ICT demand (Coditionally by AEC Population)

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An Economics Analysis of Relationship between the AEC's Demand for ICT and Economy Development Using PCHVAR(x)-Model