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ISSN: 2168-9601
Journal of Accounting & Marketing
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The Impact of Terrorism on Foreign Direct Investment in Jordan

Rabia Najaf*

Department of Accounting and Finance, University of Lahore, Islamabad Campus, Pakistan

*Corresponding Author:
Najaf R
Department of Accounting and Finance
University of Lahore, Islamabad Campus, Pakistan
Tel: +92 (0)42111-865-865
E-mail: [email protected]

Received Date: Janaury 10, 2017; Accepted Date: April 04, 2017; Published Date: April 11, 2017

Citation: Najaf R (2017) The Impact of Terrorism on Foreign Direct Investment in Jordan. J Account Mark 6: 227. doi:10.4172/2168-9601.1000227

Copyright: © 2017 Najaf R. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

The main objective of this paper is to find out the long run relationship between terrorism and foreign direct investment of Jordan. For this purpose, we have taken the monthly data from 1996 to 2014. We have found that data are stationary at first difference. For the analysis of finding the long run association, we have applied the Johnson co integration approach. The results are showing that terrorism have negative relationship with the foreign direct investment. This study suggested that there is need of proper planning for the improvement of the foreign direct investment.

Keywords

Foreign direct investment; Cointegration; Jordan; Long run association

Introduction

From last few decades, it is very interesting topic to discuses that impact of terrorism on the foreign direct investment of all developing and under developing countries. The discussion about the decisiveness of foreign direct investment is the very burning topic for all researchers. For foreign direct investment has crucial role for the development of the poverty. Foreign direct investment is the best way to enhance the managerial skills and latest technology. All the emerging countries are formulating the latest polices for the better performance. According to William foreign direct investment is the basic element for the development of the economy. There is need of rigorous view to understand the importance of the foreign direct investment. Unfortunately, only few countries are getting benefit from the foreign direct investment [1-5]. Most of the scholars had worked out on this issues that why rate of foreign direct investment is moving towards decline position. According to different surveys, it is proved that Pakistan has the come at the low that due to terrorism activities the foreign direct investment is at very critical position. The terrorism activates are increasing day by day due to lack of security system. Since 2006, the ratio of terrorism actives are at the peak. Due to terrorism actives the economics of Pakistan is facing the problems like declines the productivity. According to poon the current position of the Jordan economy is going towards decline position. According to Akhtar after 1947 the inflows level of foreign direct investment is low in Jordan due to political instability. Our study is trying to show that terrorism has very worst impact on the economy of Jordan. The main reason of increasing the terrorism activists mismanagement of security. Foreign direct investment is known as the single way for the strength of the national markets [6-10]. Therefore, most of the emerging countries are keen about the increasing inflows level of foreign direct investment. In Jordan, there is not proper source to fulfill the gap between saving and investment. It is seen that foreign direct investment is the single tool through which any country can enhance the managerial skills. In 1980s, the inflows of foreign direct investment of Jordan were 17$ billion. During the period of 2005, the growth rate was 2.5$. Consequently, the foreign direct investment rate is going to decline due to poor policies [10-30].

Objective

1) The impact of terrorism on the foreign direct investment of Jordan.

2) The impact of terrorism on the foreign investors.

3) The impact of foreign direct investment on the welfare of the society.

Problem statement

The Impact of terrorism on the stock exchange of Jordan (Figure 1).

accounting-marketing-terrorism

Figure 1: Trends of terrorism and FDI in Jordan.

Literature Review

Abadie and Gardeazabel analyzed the impact of terrorism on performance of the stock market of Pakistan. For this purpose, they were collected the data from 1998 to 2008 and applied the VAR model. Their results are showing that terrorism had negative influences on the stock market of Pakistan. They suggested that Government should have focused on such sort of terrorism activities [1].

Accam observed the impact of terrorism on performance of the stock market of India. For this purpose, they were collected the data from 1999 to 2010 and applied the ECM model. Their results are showing that terrorism had negative influences on the stock market of India. They suggested that Government should have focused on such sort of terrorism activities [2].

Agrawal and Ramaswami applied the impact of terrorism on performance of the stock market of Malaysia. For this purpose, they were collected the data from 1995 to 2005 and applied the OLS model. Their results are showing that terrorism had negative influences on the stock market of Malaysia. They suggested that Government should have focused on such sort of terrorism activities [3].

Agrawal analyzed the impact of terrorism on performance of the stock market of UK. For this purpose, they were collected the data from 1993 to 2001 and applied the ARDL model. Their results are showing that terrorism had negative influences on the stock market of UK. They suggested that Government should have focused on such sort of terrorism activities [4].

Ali and Sharafat employed the impact of terrorism on performance of the stock market of USA. For this purpose, they were collected the data from 1986 to 2004 and applied the multiregression equation. Their results are showing that terrorism had negative influences on the stock market of USA. They suggested that Government should have focused on such sort of terrorism activities [5].

Asiedu and Freeman analyzed the impact of terrorism on performance of the stock market of France. For this purpose, they were collected the data from 1989 to 2009 and applied the ECM model. Their results are showing that terrorism had negative influences on the stock market of France. They suggested that Government should have focused on such sort of terrorism activities [6].

Bandera and White observed the impact of terrorism on performance of the stock market of France. For this purpose, they were collected the data from 1989 to 2009 and applied the ECM model. Their results are showing that terrorism had negative influences on the stock market of France. They suggested that Government should have focused on such sort of terrorism activities [7].

Belington viewed the impact of terrorism on performance of the stock market of Libya. For this purpose, they were collected the data from 1983 to 2001 and applied the unit root model. Their results are showing that terrorism had negative influences on the stock market of Libya. They suggested that Government should have focused on such sort of terrorism activities [8].

Bloomberg and Ashoka applied the impact of terrorism on performance of the stock market of Nigeria. For this purpose, they were collected the data from 1989 to 2009 and applied the ADRL model. Their results are showing that terrorism had negative influences on the stock market of Nigeria. They suggested that Government should have focused on such sort of terrorism activities [9].

Bloomberg et al. examined the impact of terrorism on performance of the stock market of China. For this purpose, they were collected the data from 1981 to 2005 and applied the VAR model. Their results are showing that terrorism had negative influences on the stock market of China. They suggested that Government should have focused on such sort of terrorism activities [10].

Theoretical framework

Research methodology was explained in Figure 2.

accounting-marketing-methodology

Figure 2: Research methodology.

Research Methodology

Data

In this paper, analyzed that there is long run relationship between terrorism and foreign direct investment, for this purpose taken the data from 1996 to 2014 and applied the different tests. Foreign direct investment is the considered dependent variable and CPI, trade openness, exchange rate and terrorism (Tables 1-6).

  LNFDI LNGDP LNCPI LNER LNTO LNTX TIND
LNFDI 1            
LNGDP 0.1152 1          
LNCPI -0.1083 -0.1272 1        
LNER -0.2123 -0.1212 0.94018 1      
LNTO -0.3739 0.24169 -0.6568 -0.4712 1    
LNTX -0.0778 -0.3254 0.85238 0.7589 -0.7046 1  
TIND 0.04086 -0.1393 0.68658 0.46717 -0.7669 0.70274 1
Mean -0.0008 0.02 0.0045 -0.0058 0.0014 -0.0024 5.6487
Maximum 0.3392 0.7968 0.0309 0.0234 0.1162 0.1762 7.6293
Minimum -0.1896 -0.582 -0.0433 -0.0354 -0.0898 -0.2216 4.1097
Std. Dev. 0.0487 0.1023 0.008 0.0062 0.0195 0.0265 1.0187
Skewness 1.7055 2.4538 1.478 0.3715 0.8945 -2.5358 0.2188
Kurtosis 18.0377 33.2953 9.0028 8.5808 15.8577 45.9997 2.0284
Jorque-Bera 1614.83 6396.95 304.002 215.266 1144.52 12732.4 7.7142

Table 1: Mathematically the relationship between the variables.

Variables ADF test at level PP test at first difference At level At first difference
LnFDI -5.075038 -12.03272    
LnGDP -2.3354 -5.57621 -2.519 -11.48708
LnCPI -5.88733 -4.324997    
LnTX -1.2266 -15.05503 -1.2262 -15.05505
LnTO -5.48509 -12.03412    
LnER -0.4587 -3.641328 -1.0127 -8.68566
LnTINDX -5.354386 -12.00103    
At Critical Level        
1% level -6.92204 -6.918331    
5% level -2.8748 -2.874933 -2.8742 -2.874144
10% level -5.148487 -5.147063    

Table 2: Mathematically the relationship between the variables.

  Eigenvalue Trace statistic 0.05 Critical value Prob.
None 0.1504 136.6 125.6155 0.0092
At most 1 0.13619 99.8538 95.75367 0.0254
At most 2 0.09214 66.918 69.81888 0.0834
At most 3 0.08046 45.1702 47.85612 0.0872
At most 4 0.06402 26.2992 29.79702 0.11
At most 5 0.04378 11.3973 15.49472 0.1883
At most 6 0.00587 1.3216 3.841467 0.2504

Table 3: Mathematically the relationship between the variables.

Variables Coefficient Standard error t-Statistics
LnGDP 1.725829 0.40739 3.08872
LnCPI -8.73469 3.12065 2.55353
LnTO 3.615505 1.43799 -2.51428
LnTX -2.283366 2.73637 -0.83447
LnER -9.131476 3.23279 -2.82566
LnTIND 1.775638 0.41443 -4.28462

Table 4: Mathematically the relationship between the variables.

  Obs. F-Statistic Prob.
RGDP does not Granger Cause RFDI 227 4.94924* 0.0078
RFDI does not Granger Cause RGDP 0.7898 0.4553  
RCPI does not Granger Cause RFDI 227 3.62107** 0.0285
RFDI does not Granger Cause RCPI   6.34972* 0.0022
RTO does not Granger Cause RFDI 227 1.62632 0.198
RFDI does not Granger Cause RTO 3.18838** 0.0432  
RTX does not Granger Cause RFDI 227 2.60786*** 0.077
RFDI does not Granger Cause RTX   0.44477 0.6416
RER does not Granger Cause RFDI 227 0.34312 0.7098
RFDI does not Granger Cause RER 0.3114 0.7329  
RTIND does not Granger Cause RFDI 227 0.43669 0.6477
RFDI does not Granger Cause RIND Source: author’s calculations   1.05449 0.3502

Table 5: Mathematically the relationship between the variables.

  S.E. LNFDI LNGDP LNCPI LNTX LNTO LNER LTIND
1 0.05849 100 0 0 0 0 0 0
2 0.09492 99.8654 0.00024 0.00267 0.04076 0.05743 0.0078 0.02598
3 0.13293 99.4409 0.00427 0.0317 0.11504 0.27219 0.01785 0.11827
4 0.16825 98.8788 0.00754 0.10208 0.17628 0.55467 0.02976 0.25102
5 0.20196 98.1387 0.01106 0.24035 0.23063 0.91547 0.03969 0.42424
6 0.23393 97.2639 0.0138 0.45777 0.27783 1.31885 0.04642 0.62166
7 0.26454 96.2518 0.01588 0.76768 0.31938 1.76044 0.04918 0.8357
8 0.29399 95.1169 0.0178 1.17452 0.35593 2.22992 0.04826 1.05696
9 0.3226 93.8636 0.01949 1.68024 0.38804 2.72456 0.04453 1.27967
10 0.35028 92.5008 0.02148 2.28198 0.41608 3.24162 0.03927 1.49869

Table 6: Mathematically the relationship between the variables.

Mathematically the relationship between the variables can be presented as follows

LnFDI=β01Ln GDP+β2LnER+β3LnTX+β4LnCPI+β5LnTO+β6LnTIND+?

Empirical Results and Conclusion

Table 1 is showing that there is positive association between GDP and FDI. There is found negative association between exchange rate and foreign direct investment. There is moderate correlation between trade openness and foreign direct investment. Our results are showing the tax and terrorism index are negatively correlated with foreign direct investment. In this paper, the relationship is analyzed with the help of the co-integration. Our results are showing that data are stationary at level 1 at first difference. Then used Phillips-Perron test and found that there is weak dependency in all variables. The value of Schwarz criterion is showing that it is at lag2. There are found spurious results, so, OLS is not the best here, therefore we applied the co-integration. Different researchers studied that there is positive impact of long run market size and foreign direct investment. Here, there has also found long run relationship between inflation and foreign direct investment. There is significant negative association between trade openness and foreign direct investment. It is proved that there is negative association between terrorism and foreign direct investment. This thing is showing that due to terrorism activates investors are feel fear to invest in Jordan. Table 5 is showing that there has found both unidirectional and bidirectional relationship. There is unidirectional relationship between FDI and GDP and bidirectional relationship between CPI and FDI. There is not found lead lag relationship between FDI, terrorism and exchange rate. Table 6 is showing that there is 99% volatility in FDI. The main variables are trade openness and terrorism, which has main role in the volatility of FDI.

References

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