Country Risk Components Effects On Algeriapdf

Attractiveness  forforeign direct investment (1990-2012)

Sissani MIDOUN 

Faculty of Economic , Management and Commercial Sciences

Ibn- Khaldoun University, Tiaret; Algeria.

Belkacem ZAIRI

Faculty of Economic , Management and Commercial Sciences

Mohamed Ben Ahmed University, Oran; Algeria

Abstract :All business transactions involve some degree of risk. But, when business transactions occur across international borders, they carry additional risks called the country risk. 

The two main objectives of this paper are to explain and to examine the impact of Country risk (CR) subcategories including political risk, economic risk, and financial risk on foreign direct investments (FDI) attractiveness towards Algeria during (1990 2012). 

Our second objective is to determine which component matters most for the attractiveness of FDI inflows. We used indices sourced (Data Sources) from the International Country Risk Guide (ICRG) and the multiple regression analysis revealed that R2 = 0.83 and just two components were statistically significant. While using stepwise option, We found that The political variable wasn’t statistically significant. This means that Government stability, and absence of internal conflicts beside corruption Don’t have a high influence on the (FDI) inflow towards Algeria .However, the Financial and Economic factors do . Finally, the results suggest that the increase in FDI is associated with the improvements in only two major components. 

Keywords:Foreign Direct Investments, Country Risk, Rating Agencies, Political Risk.

Jel Classification Codes : C13, C25, F21, F18, F30

I-Introduction :

The economic and political changes with the wide spread of globalization has opened a connectedness of business, production and technologies across developing countries. A great number of earlier studies  discussed the impact of (FDI) on the host countries  and  illustrated  the important role  of multinational companies in increasing competitiveness .This leads to focus on their decision  of when and where to invest abroad especially in uncertain environments .Algeria as  one of  these developing countries  enjoys a large current account surplus  , expected at 20.6% of GDP in 2007  suffered from  low FDI  inflows for a long period, besides unemployment which remains high at 14.1%, although the government has embarked a large public projects to create jobs. Algeria is also still looking for the best equation in order to attract enough FDI since it is rich in natural resources and has really scored high record levels of FDI in the recent years, reaching 280 million USD in 2000 to 2264 million USD in 2010.

Nevertheless, the long civil war between1992 to 2000, military influence, corruption, and cronyism remain prevalent up today. According to transparency international word corruption Index, which is closely watched by investors, economists, and civil society campaigners, Algeria is ranked 112 in 2012 of 174 countries.

There are strong reasons to believe that the level of country risk arises from uncertainties in political, social, and economic factors or other external conditions with residents and companies of those countries in such a way that affects the level of risk or creditworthiness of business undertaking in those countries. So, reducing these kinds of risks is vital in attracting foreign investment.  In spite of the colossal resources and richness of Algeria, there has been little foreign direct investment (FDI) in this country. Why?  Our paper is the first to examine the roles of country risk in inward FDI.

Rating agencies such as Moody’s, Coface, Prsgroup (ICRG) and Standard & Poor's are the most famous agencies assigning credit ratings for the purpose of generating information about default probabilities that are pertinent for pricing hedging risky fixed income securities(1).There is no doubt too, that, the (ICRG) is unique among all rating agencies  since it provides  statistical data with a great  transparency  and effectiveness  for 140 countries, among them Algeria . Why use ICRG data? The answer is simple, because, for more than 25 years, the system has incorporated as many key political, financial, and economic risk elements and published them. The World Investment Report (Unctad,WIR2011)(2)points out that foreign direct investments (FDI) continues to be full of uncertainties and risk.

 “In contrast, inflows to Sub-Saharan Africa jumped from $29.5 billion in 2010 to $36.9 billion in 2011” (3) In this paper we shall address one issue that has so far not received much attention in the discussion: It is the impact of country risk on flows of foreign direct investment (FDI) Shapiro(1999) (4)who defines country risk as the general level of political and economic uncertainty in a country affecting the value of loans or investments in that country. We do agree that, developing and transition nations have a particularly strong interest in attracting foreign direct investments. That’s Why we do focus on FDI especially in Algeria.

II. Different Types of Risk

II.1. Political Risk  (PR)(1)

The "political risk" concept has appeared in the international business literature .It is linked to the stability and instability of government policies and it usually means that there is a strong chance of unwanted consequences arising from political activity. Political risk factors can be divided into macro- and micro-risks. Macro-risk refers to unanticipated and politically motivated environmental changes directed at all foreign enterprise. Micro-risk refers to political changes in the business environment and in unique or selected fields of activity. It affects only selected for­eign oper­a­tions in the host country. However, It is not possible to avoid political risk completely .Table (1).

II.2. Financial Risk (FR)

Financial risk refers to the risk that a country may not be able to repay its foreign liabilities. Without doubt countries with high financial risk cannot easily withdrawn FDI when its financial situation is worse. Therefore, foreign firms are very sensitive to the financial risk of the host country Table (2).

II.3. Economic Risk (ER)

It can be described as the likelihood that an investment will be affected by macroeconomic conditions such as government regulation, exchange rates…etc. It is also, the risk that a venture will face, due to various reasons such as alteration in economic trends or fraudulent activities which ruin a project’s outcome Table (3).

2.4. The Composite Risk Rating

The method of calculating the Composite Political, Financial, and Economic Risk Rating remains unchanged.  The political risk rating contributes 50% of the composite rating, while the financial and economic risk ratings each contribute 25%.

The following formula is used to calculate the aggregate political, financial and economic risk:

CPFER (country X) = 0.5 (PR + FR + ER)   [1]

III. Review of Literature :

Country risk (CR) and Foreign direct investments (FDI) have been widely studied over the years. This paper provides some insights and understanding of prior studies done by different authors in the same field. This helps us to develop hypothesis in one hand and to compare the findings of proposed research. In fact the graduation of risk determines how attractive a country is for the international investments, given the fact that the existence of international investments is explained because investors want to maximize the return on their investments. As a consequence they analyze the risks in order to reduce eventual future.

The literature views remain mixed, the first group concluded that there is no relationship between FDI attractiveness and the country risk components however; the second group concluded that there is a significant relationship.

- Kosmidou et al .(2008)(5)His analysis was based on data for 28 Asian countries using economic and political factor in order to analyse the effect of changes in these factors on risk ratings. He defines country risk as “the probability that a country will fail to generate enough foreign exchange in order to pay its obligation toward foreign creditors. The results of the applied model UTADIS performs quite well between (1999–1997), but its performance on the earliest years (1995–1996) drops below 73%. In terms of the individual error rates, the UTADIS model shows an excellent in identification of the countries of low risk.

- Ephraïm, C., Michel, H, Bouchet, Bertrand G,.( 2003) (6). Wherever and whenever it is not expected country risk emerges and the wealth of information didn’t reduce the risk of default in emerging market countries since the 1982 debt crisis. Results showed that most risk models that drive economic and financial analysis are linear in their structure. Consequently, most tests are designed to detect a linear structure in the data. However, other aspects of economic and financial behavior are non-linear which make using different methods more useful such as discriminant analysis or Monte Carlo Simulations. An example of Value At risk is given too.Prob[δV ≤−VaR] = 1 c

Suppose that VAR is $20 million and the degree of confidence is 99%, then if the time horizon is 10 days, Prob[δV ≤ −$20m] = 1 0.99 = 0.01 means that there is a 1% probability that the portfolio could lose $20 million or more over the next 10 days.

- Etienne Musonera (2008) (7) His study found that attracting more FDI inflows depends on the host country’s institutions and policies. After running SPSS software, the regression results show that the country risk model was significant with p-values less than 0.10 (p-value < 0.10).That means, R-square values were statistical significant at 0.88% for Tanzania and 0.95% for Uganda   but the confidence for Kenya was less at 0.20%.

-Timur Han Gür,(2001)(8) in a carefully considered paper which  estimates country risk using a two-limit ‘Tobit  model in thirty-four developing countries for the period between 1986 and 1998.twenty-four are middle income countries and the remaining ten are low income countries as categorized by the World Bank country classification lists. All the variables used to estimate the debt rescheduling were statistically significant at 10٪ percent level. The database of this study has 408 observations. There are 110 rescheduling observations which make up 27٪ percent of total observations. As a result, we can argue that two-limit ‘Tobit’ model of country-scoring has been successful in estimating the high credibility of some countries.           

-Busse and Hefeker (9)They studied the linkages between political risk, and foreign direct investment inflows. They used econometric techniques for a data sample of 83 developing countries for the period 1984-2003, in order to identify the indicators that matter most for the activities of multinational corporations. Their results showed that government stability, the absence of internal conflict and ethnic tensions, basic democratic rights and ensuring law and order are highly significant. The results of allvariables were significant at the 1٪ percent level. The exception is the coefficient for inflation, which is positive but not significant. Besides, government stability, law and order, democracy and the quality of bureaucracy have a positive impact on FDI inflows, as the coefficients are positive and statistically significant at the 5٪ or 10 ٪ level.

-Txomin, I., Casilda, L. , Ana. U., &Arturo, R.,(2010) (10). They analyzed the degree and evolution of inequality and polarization in country risk in the world from 1990 to 2004 .Data from Euro money and International Country Risk Guide (ICRG) was used. Crises in this period were frequent: from the European Monetary System crisis in 1992, to the crisis in Argentina in 2000-2001, Mexico, Asia, Russia, Brazil and others. The results confirmed that Both polarization and inequality vary, with no steady trend over the period, for example between  Sept. 1992 – March 1996 polarization clearly decreases from .174 to .126 for the Euro money index, and from .074 to .052 for the ICRG. However, all results were remarkably similar pattern of worldwide polarization over time. Although, Polarization declines substantially in the four years 1992-1996 and remains more or less constant in the rest of the period.

-Hadjila,K., Iuliana, M., (2010) (11). They tried to study the linkages among political risk, business climate and foreign direct investment inflows and to provide better supported results concerning these

Linkages. They exploited two panel models: a fixed effect model and a dynamic panel model. They used data sample of 33 developing and transition countries covering the period 1996-2008. The results of the panel analysis concerning the variable of business climate have a positive impact on the FDI inflows. But, the coefficient of this variable is not significant in either panel models. Moreover, GNI per capita appeared significant at 1% or 5%.Besides, “public expenditures” and the “political risk” is significant at 1% and respectively, 5% level. The variable “unit labor costs” is positively linked with FDI inflows but its coefficients are non-significant. Finally, they concluded that reduced levels of political risk are associated with an increase in FDI inflows.

-Zairi, Belkacem., Bachir,A.K,.(2010) (12) The main goal of their paper was to analyze the relationship between The impact of country risk and attractiveness of Foreign direct investments to Algeria. Their Empirical study used data from ‘ICRG’ concerning Algeria between 1987 to 2005. The ordinary Least Square (OLS) method showed that the Adjusted R Square was 0.74 ٪and R about 0.86٪.The results was quite significant .When the risk was at the Medium level, the attraction of FDI raised to 1252.86 and whenever the risk was very high that would lead to a greater decrease in FDI.

There are also a number of papers which find that there is no significance between FDI and some components of the country risk.

- Sandra , A., Mohamed .A., Pedro, C. M.,(2012)(13). Their study consists of a sample of 180 countries with and without FDI in Brazil. Findings about Per capita GDP were not statistically significant. Contrary to expectations, the estimated coefficient of bilateral trade was positive but not statistically significant. Variables measuring distance have the expected signs: Portuguese- and Spanish-speaking countries have a greater propensity to invest in Brazil; and geographic distance appears with theexpected sign, although the estimated coefficient is statistically significant at the 10% percent level. This may be because Brazil’s neighboring countries speak Spanish. They also found that main component of political risk that drove a negative relationship between risk and FDI into Brazil was related to the quality of policy formulation and implementation.

-Leonard K. Cheng., Yum K. Kwan.,(2000)(14). This study is for the purpose to estimate the determinants of foreign direct investment (FDI) in 29 Chinese regions from 1985 to 1995. As China opened its door policy, it became one of the largest recipient of FDI among developing countries in the world between 1992to 1993.Using a GMM panel data estimator. They found that large regional market, good infrastructure, and preferential policy had a positive effect but wage cost had a negative effect on FDI. The effect of education was positive but not statistically significant. The coefficient for the density of all roads is close to 0.2, indicating that a 1% increase in a region’s roads would increase its FDI by 0.2%.But they didn’t find  any kind of relationship between FDI and other components of country risk.

IV. Methods :

The expected relationship of country risk and the attractiveness of foreign direct investments to Algeria will be investigated using multiple regression techniques for the period (1990 to 2012). The Algerian data are all listed by (ICRG) (1). Table4. The data are available upon request.) Table4: Country risk data. Data was analysed using SPSS v17. Table 4.

IV.1.Problem Statement:This study is the first attempt to understand what are the main components of country risk which influence most Algeria and despite the negativity that it being generated about Algeria investment climate, the country continued to attract foreign investments but not as wanted.

IV.2. Originality Of Study :Intensive efforts are needed in Algeria for research in general .Particularly, there is no study which has really explored the impact of Country risk and its components on Algeria attractiveness for foreign direct investments inflow.

IV.3. Objective Of Study :The objective of the study is to investigate the impact of political risk, Economical risk and Macro-Economic risk and determine the factor or factors which matter most for FDI inflows.

IV.4. Algeria Openness to Foreign Direct Investments (FDI)

Algeria, with its population of nearly 36 million (15), its energy wealth, and growing demand for modern infrastructure and consumer products, has begun attracting interest from companies around the world. Algeria is still unable to move forward with Word Trade Organization (WTO). “Algeria’s Working Party was established on 17 June 1987 and met for the first time in April 1998. The latest revised market access offer on goods was circulated in November 2007. A revised offer on specific commitments in services was circulated in February 2012”(16)Accession or modernize its banking sector has prevented significant foreign investment outside the energy sector. However, poverty remains widespread and unemployment high, particularly among Algeria's youth. Endemic government corruption and poor standards in public services are also chronic sources of popular dissatisfaction.

The Algerian government took Series of protectionist measures and settled new rules on FDI by imposing a majority of 49-51% (which requires a 51% Algerian share in all foreign direct investments)(18).This decision was discouraging FDI factor. Similarly, bureaucracy, weak financial sector and the legal uncertainty regarding the rights of intellectual property are obstacles to foreign investors investments. Officially, the government remains committed to economic liberalization and continues to seek foreign investment in sectors such as infrastructure, telecommunications, energy and water. One can also note a shift of FDI on the domestic market through the multiplication of development projects and transport infrastructure. The sectors attracting the most FDI are energy, followed by telecommunications and tourism.

During the past 10 years, the economy recovered from the deep socioeconomic crisis of the1990s. Between 2000 and 2009, real GDP and non-hydrocarbon GDP grew respectively at an annual average of 3.7 and 5.6 percent, whereas real GDP per head increased by 22 percent, and unemployment fell from 29.5 percent to 10.2 percent. Acting the most FDI are energy, followed by telecommunications and tourism (19).

We are witnessing a massive return of foreign direct investment from 1995 to 1999.As noted above, multinationals seem to consider seriously the political risk which Algeria suffered from between 1990 and 1994) (16).It should be interpreted with caution. Thus , it appears that the political stability returned back to Algeria step by step and  within the FDI inflows especially  during the period (1999 to 2012) (Graph No. 1)Thefigure below  is  called drawing on two axes  and it shows an inverse relationshipbetweenforeign investmentandeconomic risk(Risk E).On other hand  both financial risk(Risk F) and economical risk(Risk E)  have a positive  relationship .However the political risk (Risk P) does not appearto have anyrelationshipwithforeign investment flows.  Fig.(1)

The sectors where there is a high concentration of FDI, includes the manufacture of drugs (biotechnology), building materials and housing, and various industries. In addition, more than 4,000 projects have been initiated by national economic operators between July 2010 and July 2011, an increase of 33%, particularly in the fields of building materials and food industries. With the regulatory system of national partnership, based on shared foreign capital and financial participation of 51% and 49%, many foreign investors have agreed to cooperate with Algerian investors, even although European investors have shown reluctance to engage, believing that this procedure is disadvantageous.

We do agree that, in certain cases and due to the inefficiency of the banking system and the heavy bureaucracy, it may take longer to obtain official permission from the central bank to make transfers/payments, or for the local bank to proceed with the transfer. Although, Algeria has large reserves of natural Gas and other hydrocarbons. These natural resources dominate economic activity and account for more than 95% of export earnings and almost half of the country’s gross domestic product. Economic growth slowed to 2.4% in 2009, as oil prices fell and global economic conditions deteriorated. Growth picked up to 3.3% in 2010 and is set to be 3.6% for full year 2011.

IV.5. Country risk classification of Algeria within its modern FDI trends:

The French company for Trade Coface Country Risk" rating maintained (A4) for Algeria in 2012 and Algeria economic growth was estimated in 2011 at just 2.5%, down from 3.3% in 2010, and it is expected to rise by 4.2% in 2013.However, the classification of Algeria according to OECD assessment Country risk was 03 /07 during the previous year 2012 and remained   during the current prevailing year 2013.

 “The economic intelligence unit granted ‘BB’ which means Capacity and commitment to honor obligations currently but susceptible to changes in economic climate”(20).

Besides, The Wall Street Journal and The Heritage Foundation published the 2013 index Economic Freedom and the Algerian economic freedom score is 49.6, making its economy the 145th freest in the 2013 Index.

On other hand, statistical analysis of FDI Trends revealed that Algeria made   more and more FDI inward flow especially after the great three economical programs launched by the president of Algeria. The first between 2001 to 2004 called the economic recovery support program, the second one wasthe Supplementary Programme to Support Growth (PCSC, 2005-2009) where the FDI grew up from 1081Million $  in 2005 to 1746 Million $ in 2009 with  return of the political stability . The level of attractiveness reached almost 2264 Million dollars in 2010 with the third stage economic program named public investment between 2010 to 2014and climbed to 2571 Million dollars Of FDI in 2011.   Table (5)  &  Table (06)

Entitled Model Summary Table (7) contains some measures that have been calculated and can be illustrated as fellow:

1. The value of the correlation coefficient R = 0.912,and the Adjusted R-Square is about 0.81 which is quite very high.

2. The R-square coefficient is specifies how data used independent variables in the estimate of the dependent variable and note that the estimated model expresses the (independent variables together) 82% of the data is explained and that the proposed model adequately.

3. Adjusted R Square is about 83% and is quite obvious and the most accurate.

4. Set miscalculation Std. Error of the Estimate is here 390.93 which means less error of the model. Table (7)

The correlation between FDI flows and the Financial risk and it is almost average between FDI and political risk =0.598 while the correlation between foreign direct and economic risk=0.526 Average too. Durbin Watson (DW) is over 0.80% which is quite reasonable and far from any autocorrelation.In this paper, we find that the regression equation is representing 81 % of the whole data which is quite encouraging.

Table 8 :From ANOVA table, we find that Sig.=000whichisless than  the specified significance level of 0.05 ,so we will reject the null hypothesis .As  a matter of fact ,The regression is significant and of course, the relationship between the independent variables and the dependent variable is confirmed .Table (8)

From the coefficients table (9), We can with draw  the regression equation and  the amount of errors in the estimation which are in the reasonable limits  (std.Error 4,602-0,091-0,153-0,145).We also notice that the financial risk has the greatest coefficient (0.892)  and  sig = 0.000.so,  we conclude that the financial component is the component which matters most for the attractiveness of FDI inflows to Algeria. Table (9)

From table (9) : We concluded  the regression equation as follow :   [2]

V. Discussion: 

The  regressions was run to allow for a more complete assessment, First ,we find that the 12 political risk components(see table1), government stability, socioeconomic conditions, investment profile, internal conflict, corruption, external conflict, religious tensions, democratic accountability, and ethnic tensions have close association with FDI flows and  if the political risk increases by one percent, the FDI inflow towards Algeria will increases about 0.15 % .Any positive efforts may increase the amount of FDI greater. As a result, a positive and highly significant coefficient is obtained for political risk, which suggests that high political risk of host countries deters FDI inflows.

However, 1% of the economic risk decreases the FDI inflow about - 0.33 % .This situation may be explained by the market imperfections and the government bad policies .For instance, privatization in one country does not necessarily diminish inbound FDI. Besides, there is also a relationship between foreign direct investments and the financial risk .We noticed that 1% in the financial risk may reproduce about 0.892 .In order to specify more clearly and precisely the effects of financial risk on FDI flows, it is necessary to disaggregate FDI flows. It is necessary to distinguish between gross and net FDI flows, between the individual components of FDI flows, and between inbound and outbound FDI flows.

According to annual Global Competitiveness Reports 2012-2013 (21), Algeria was in the 87 rank above 144 countries in the world since 2011 and it and shift back to the 110 rank. When the political risk index, the economic risk index and the financial risk index are included, a positive and highly significant coefficient is obtained (0.046) for financial risk, which suggests that high financial risk of the host country deters FDI inflows. In contrast, the political risk variable does not appear to have any linkages with FDI flows (0.113).

     Unlike the financial risk index, the economic risk index enters with negative coefficients (-0,311), this is surprising, contractively to what we anticipated. We do Interpret these results by suggesting that Algeria should modernize its banking system and increase its financial risk to attract more FDI(see table 9).

Many developing countries and Algeria is among them strive to attract foreign direct investment (FDI) hoping that knowledge brought by multinationals will spill over to domestic industries and increase their productivity. So, it is quite necessary to reduce the political risk and promote the financial banking system foster it. Despite the fact that most developing countries such as Algeria does not attract enough FDI because political and financial risk still represents a huge concern for international business. In fact, multinational companies today probably face a much broader array of risks than before. Algeria FDI attractiveness remains very weak and powerless although the great opportunities .Why? From our model we can conclude that terrorism (1990-1995) had a bad influence and effects on FDI inflows. On the one hand a lack of competitiveness and innovation on the other hand lack of incentives. Of course there are limitations in this study that should be addressed in future research. Therefore, this study raises the need for further research to investigate the differences in FDI in developing countries and especially in Africa.

VI. Conclusion :

To illustrate the framework and the complexity of Algeria Country risk phenomenon, the results of this study show that home country economic, financial and political conditions play an important part in the attractiveness of foreign direct investment. The main conclusion  financial risk matter most for Algeria who strives to attract greater foreign direct investment (FDI) hoping that knowledge brought by multinationals will spill over to domestic industries and increase its productivity .Unfortunately, State-owned companies continue to dominate the financial sector (both banking and insurance) and progress towards privatization has been stalled in light of global financial conditions. Algeria must expand and vary its efforts to attract foreign investments since the Algerian political risk remains high, especially terrorist attacks which have picked up in recent years. However political variable is not statistically significant and was omitted from the model.

Undoubtedly, attracting FDI, in sectors other than oil, is still the real challenge for Algeria in the near future. Therefore, the aim of the study is to point out the leverage points to improve FDI attractiveness of Algeria. Many developing countries and Algeria is one among them, need outside capitals to realise their growth objectives such as improving the balance of payments account particularly the current account and for the purpose to provide managerial knowledge and skills including organisational competence and access to foreign markets. Moreover, it can enable the transfer of technology from developed countries to the developing nations. Besides, FDI may provide a wide range of goods and services to residents in the recipient country.

Finally, Policy recommendations for Algeria should focus on improving the investment climate and encouraging the diversification of FDI inflows .This paper attempts to shed light on the potential drivers of FDI and illustrate the framework and the complexity of Algeria Country risk phenomenon but much work remains to be done in the estimation of Country risk and the attractiveness of foreign direct investments to other developing countries in the world. Algeria should also consider a comprehensive review of FDI policies to attract more foreign capital by creating a more FDI-friendly regime.

ANNEXES :

Table (1): Political risk components

Political risk

Variables

Weight(max.)

 

Government Stability

Socioeconomic Conditions

Investment Profile

Internal Conflict

External Conflict

Corruption

Military in Politics

Religion in Politics

Law and Order

Ethnic Tensions

Democratic Accountability

Bureaucracy Quality

12

12

12

12

12

6

6

6

6

6

6

4

Total

 

100

Source : 7/05/ 2014, PRS  GROUP,  Political  Risk  Services Methodolog

From :http://www.prsgroup.com/PRS_Methodology.aspx.

Table (2): Financial risk components (FR)(1)

Financial risk

Variables

Weight (max.)

 

-Foreign Debt as a Percentage of GDP

-Foreign Debt Service as a Percentage of (%  PIB)

-Exports of Goods and Services

-Net International Liquidity as Months of Import Cover

-Exchange Rate Stability

10

10

15

05

10

Total

 

50

Source : 6/05/ 2014,  PRS  GROUP,  Financial risk,  Services Methodology

From :http://www.prsgroup.com/PRS_Methodology.aspx.

Table (3): Economical risk components (ER)(1)

Economic risk

Variables

Weight (max.)

 

- GDP Per Head

- Real GDP Growth

- Annual Inflation Rate

- Budget Balance as a Percentage of GDP

- Current Account as a Percentage of GDP

05

10

10

10

15

Total

 

50

Source : 06/05/2014, PRS  GROUP,  Economical risk,  Services Methodology

From :http://www.prsgroup.com/PRS_Methodology.aspx..

Table (4) :The Algerian data are all listed by(ICRG)

Date

FDI

EconomicalRisk

Financial Risk

Political Risk

1990

40

25,75

26,5

60,42

1991

80

32,13

30,5

56,17

1992

30

27,29

32,42

45,25

1993

90

27,63

31

47,5

1994

150

26

31,92

49,08

1995

210

27,54

34,17

45

1996

270

36

36,42

49,17

1997

260

33,79

36,25

47,67

1998

607

37,9

36,67

42,25

1999

292

31,9

31,63

41,42

2000

280

34,54

33,21

44,25

2001

1108

31,79

39,25

45,13

2002

1065

38,46

38,71

46,42

2003

634

44,33

42,58

45,08

2004

882

43,13

44,92

53,71

2005

1081

44,54

46,63

63,21

2006

1795

45,08

47,46

63,29

2007

1662

44,92

48,78

62,42

2008

2594

43,79

49

61,71

2009

2746

38,83

47,58

60,96

2010

2264

35,25

47,58

60,96

2011

2571

37

48,21

57,21

2012

1484

37,5

47

58

             Source 1:  PRS  GROUP, Services Methodology  (PRS)  

  Source 2: Unctad ,http://unctadstat.unctad.org.

R150101

Fig. (1) FDI inflows and its relation with different risks (1999 to 2012)

Source : Developed by the author according  to unctad and (ICRG) data.

T able (5)  The FDI Trends in Algeria ( 1990 to 2012)

1990

1991

1992

1993

1994

1995

1996

1997

40

30

80

90

150

2010

270

260

1998

1999

2000

2001

2002

2003

2004

2005

607

292

280

1108

1065

634

882

1081

2006

2007

2008

2009

2010

2011

2012

 

1795

1662

2594

1746

2264

2571

1484

 

  Source 2 : 07/05/2014, Unctad ,http://unctadstat.unctad.org.From: http://unctadstat.unctad.org/TableViewer/tableView.aspx?ReportId=88

Table (6): Correlations between FDI country riskvariables.

   

FDI

PR

FR

ER

Pearson Correlation

FDI

1,000

,601

,885

,652

PR

,601

1,000

,822

,455

FR

,885

,822

1,000

,618

ER

,652

,455

,618

1,000

Sig. (1-tailed)

FDI

,001

.

,000

,014

PR

,000

,000

.

,001

FR

,000

,014

,001

.

ER

23

23

23

23

*ER: Economical risk     *PR: Political risk  *FR: Financial  risk

Table (7) :Model Summary and general view about the model.

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

Change Statistics

R Square Change

F Change

df1

df2

Sig. F Change

1

0.885a

0.783

0.773

434,03424

0.78

75,823

1

21

0.000

2

0.912b

0.832

0.816

390,93952

0.49

5,885

1

20

0.025

a. Predictors: (Constant), x2   b. Predictors: (Constant), x2, x1    c. Dependent Variable: y

Table( 8) : the significance of the model  through ANOVAa

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

14283881,831

1

14283881,831

75,823

,000b

Residual

3956100,169

21

188385,722

   

Total

18239982,000

22

     

2

Regression

15183307,792

2

7591653,896

49,673

,000c

Residual

3056674,208

20

152833,710

   

Total

18239982,000

22

     

a. Dependent Variable: FDI     b. Predictors: (Constant), Fin Risk   c. Predictors: (Constant), Fin Risk, Eco Risk

Table (9): The estimation of the model and Std .Errors

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

2

(Constant)

-2979,175

485,567

 

-6,135

,000

Fin Risk

149,880

19,994

1,206

7,496

,000

Eco Risk

-55,064

22,699

-,390

-2,426

,025

*ER: Economical risk     *PR: Political risk   *FR: Financial risk

-References

1. 01/07/2012, PRSGROUP(1980) : http://www.prsgroup.com/ICRG_methodology.aspx

2. Michael Frenkel, Alexander Karmann,BertScholtens Bert.(2004). Sovereign risk and financial crises. Springer-VerlagBerlin :Germany .

3. 22/07/2012, http://www.unctad-docs.org/files/UNCTAD-WIR2011-Full-en.pdf

4.  Shapiro, A. (1999), Multinational Financial Management, 6th Edition, Prentice Hall: London, UK.

5.  Kosmidou, K., Doumpos, M., &Zopounidis, C. (2008). Country Risk Evaluation: Methods and Applications (Vol. 15). Springer.

6. Bouchet, M. H., Clark, E., &Groslambert, B. (2003).Country risk assessment: A guide to global investment strategy. Wiley.

7. 11/02/2013, Etienne Musonera,(2008).Country Risk Factors: An Empirical Study of FDI Determinants in SSA. Journal of International Business Research and Practice, Vol. 3, p. 15, 2009.From :http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1921087

8. T.H. Gur, (2001) "A Country Risk Assessment Model and the Asian Crisis"Central Bank Review, Vol.1, Number 1, Mayıs.

9. Busse, M and Hefeker, C. (2005) Political Risk, Institutions and Foreign Direct Investment, Discussion Paper Series 26388, Hamburg Institute of International Economics.

10. 12/02/2013, Iturralde, T., Lasso, C., Urrutia, A., & Rodríguez, A. (2010).Country Risk Inequality and Polarization in the World.An Empirical Analysis.Journal of Money, Investment and Banking, 13, 44-54.From:  www.eurojournals.com/jmib_13_05.pdf

11. 13/02/2013, Hadjila ,K.,.Iuliana, M., (2010). Business Climate, Political Risk and FDI in Developing Countries: Evidence from Panel Data. International Journal of Economics and Finance, Vol. 2, No. 5; November 2010,from:

http://ccsenet.org/journal/index.php/ijef/article/download/7702/5965

 12. Zairi, Belkacem.,Bachir,A.K,.(2010).The impact of country risk in the attractiveness of foreign direct investment :Case of Algeria .Empirical study. Arabic Economic Journal,v50.

13. Sandra , A., Mohamed .A., Pedro, C. M.,(2012). Foreign Direct Investment and Home-Country Political Risk The Case of Brazil, Latin American Research Review, Vol. 47, No. 2.

14.  Leonard K. Cheng., Yum K. Kwan.,(2000). What are the determinants of the location of foreign direct investment? The Chinese experience, Journal of International Economics 51 (2000) 379–400.

15.  http://www.ons.dz/-Population-et-Demographie-.html.

16.  http://www.wto.org/english/thewto_e/acc_e/a1_algerie_e.htm.

17. 26/03/2013, Case of U.S. Firms, Journal of International Economics, 33:57-76. From :http://www.joradp.dz/JO2000/2009/044/F_Pag.htm

18. http://data.worldbank.org/country/algeria.

19. http://www.andi.dz/fr/?fc=b_declare.

20. http://www.eiu.com/site_info.asp?info_name=sovereign_ratings

21. http://www3.weforum.org/docs/CSI/2012-13/GCR_Rankings_2012-13.pdf