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© 2021 by the authors; licensee Eastern Centre of Science and Education, USA 

 

Asian Business Research Journal 
Vol. 6, 7-13, 2021 
ISSN: 2576-6759 
DOI: 10.20448/journal.518.2021.6.7.13 
© 2021 by the authors; licensee Eastern Centre of Science and Education, USA 

 
 

 

 
Uncertainty, Financial Development and FDI Inflows:  France Evidence 

 
Francois Smith 
 

 
 
 University of Bordeaux, France. 

 

Abstract 
The economic policy and world uncertainties are negatively effects on the whole economy, 
specifically on the financial sector of France. The outbreak of corona virus in the last quarter of 
2019 makes the situation worst, specifically for the case of France. The outbreak of this virus 
results in a drastic reduction in liquidity and solvency of French corporations. The inflows of 
foreign direct investment (FDI) in France are also reduced by 17% during the outbreak of virus. 
However, after analyzing the situation of world uncertainty and economic policy uncertainty in 
France, it is found to be crucial to examine the role of economic policy and world uncertainties in 
defining FDI and financial development. Present study thus attempts to investigate the impact of 
economic policy uncertainty and world uncertainty on FDI and financial development in France. 
For this purpose, the study collects the data for the period of 1997-2018 from different secondary 
data sources. The study applied ARDL bound testing approach to estimate the results. Findings 
report negative impact of economic policy uncertainty and world uncertainty on FDI and financial 
development. The study suggests the France government to monitor the sources and size of 
uncertainty shock while formulating different economic policies. 

 
Keywords: Economic policy uncertainty, World uncertainty, Foreign direct investment, Financial development, France. 

 
1. Introduction 

Since the publication of “The Age of Uncertainty” in 1977, many major events have been occurred that result in 
an economic and political uncertainty around the globe (Al-Thaqeb & Algharabali, 2019). This globalization or 
uncertainty is highly aligned with the fact that we exist in the “hyper-connected” world, where an event which 
arises in one part of the world will definitely have an influence on the other part of the world (French & Li, 2021). 
Evidences reveal that financial crises of 2008, Arab springs of 2012, and European sovereign debt crises of 2010 are 
the underlying causes of increased economic, political and world uncertainties around the globe. Hence, many 
researchers have started conducting their research to explore the effects of these uncertainties on the macro-
economy. Specifically, the effects of economic policy uncertainty (EPUC) on financial variables have received a lot 
of attention of economic researchers.   

Researchers indicated the adverse and detrimental effects of these uncertainties on the whole economy. The 
particular literature shows that higher level of EPUC in a nation reduces production (Mian & Sufi, 2010) 
investment (Shen, Zhang, Liu, & Hou, 2020) stocks (Hu, Kutan, & Sun, 2018) inflow of capital (Wang, Luo, Wang, 
Xu, & Wu, 2021) trade credit (Godil, Sarwat, Sharif, & Jermsittiparsert, 2020) and financial stability (Phan, Iyke, 
Sharma, & Affandi, 2021). It is argued that financial sector of a country plays an important role in its economic 
development. The inflow of capital and domestic credit to private sector are two pillars of the financial sector which 
is highly affected with the EPUC and world uncertainty (WUC). The outbreak of corona virus in the last quarter of 
2019 make the situation more worst, specifically for the case of France. The outbreak of this virus results in a 
drastic reduction in liquidity and solvency of French corporations (see Figure 1). The inflows of FDI also reduces 
by 17% during the outbreak of virus (see Figure 2). Hence, researchers indicated that the global pandemic is 
another cause of world and economic policy uncertainty. This scenario motivates the authors to investigate the 
effect of EPUC and WUC on the FDI and financial development (FNDP) of France.  

 

 
Figure-1. Reduction in Liquidity and Solvency of France Corporations. 

http://ecsenet.com/index.php/2576-6759/article/view/96
http://ecsenet.com/index.php/2576-6759/article/view/96


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Figure-2. Drop in FDI of France. 

 
Researchers have extensively worked on the inflows of foreign capitals as FDI plays a very important role in 

promoting the economic growth. Many researchers have spent their days and nights in finding the determinants of 
FDI. One of the most crucial determinant which captures the importance of different researchers and policy makers 
is “uncertainty”. This uncertainty can be of any type (i.e., it can be economic, political, social, economic policy or 
world uncertainty). Uncertainty arises when the economic body cannot envisage whether, when and how the 
government will change its current economic policy (Goodell, McGee, & McGroarty, 2020).  Researchers indicated 
that higher level of EPUC reduces the inflows of capital as EPUC is a signal of a limited protection from host 
nation’s legal and political institutions (Albulescu, Demirer, Raheem, & Tiwari, 2019). It also reduces the return on 
stock markets, and this effect is more persevering during the high volatility periods (Liow, Liao, & Huang, 2018).  
According to the world investment report, EPUC is among those factors that hinder the recovery of FDI. Thus, it 
is concluded that EPUC is very detrimental for the FDI. 

Economic or world uncertainty do not only reduce the inflows of FDI, but also plays a negative role in the 
financial development. It also reduces the liquidity and solvency of the corporations (Zhao, 2020) and bank credit 
growth (Ashraf & Shen, 2019) which is again a biggest threat for the financial development because banks and 
corporations contribute 20% in the financial development of the nation. According to Avom, Njangang, and Nawo 
(2020) 1-unit of increase in WUC tends to reduce 12%-16% FNDP of the nation. Hence, the present study 
concluded that EPUC and WUC is having adverse effects on FNDP. However, after analyzing the situation of 
economic policy and world uncertainty of France since 1997 (see Figures 3 and 4 respectively), present study 
proposes that it is crucial to investigate the impact of EPUC and WUC on the FDI and FNDP of China. It is very 
surprising for the authors that until now this relationship has not been investigated by the prior researchers. 
Hence, present study contributes to the existing debate of uncertainties by analyzing the role of EPUC and WUC 
on the FDI and FNDP for the context of France.  
  

 
Figure-3. Economic policy uncertainty index. 

 

 
Figure-4. World uncertainty of France. 



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2. Literature Review 
This section reviews the existing literature of the study along with the development of hypothesis. The 

conceptual model of the study is also highlighted in this section.  The effects of time capricious uncertainty on the 
macro-economy have received a considerable attention in the recent years. Many researchers have predicted the 
negative role of uncertainty on different macro-economic variables. Specifically, the effects of economic policy 
uncertainty (EPUC) on financial variables have received a lot of attention of economic researchers. For instance, 
Azam, Khan, and Iqbal (2012) analyzed the impact of EPUC on FDI for the case of South Asian economics by 
utilizing the data from 1990-2018. The study applied ARDL to analyze the short run and long run impact of EPUC 
on FDI. The findings of the study reveal the insignificant relationship between EPUC and FDI in short run while 
significant and negative relationship between EPUC and FDI in long run. The study states that increase in the 
level of EPUC increases the political and financial risk which is detrimental for the inflows of FDI. Busse and 
Hefeker (2007) analyzed the role of political uncertainty in FDI for the case of 84 developing economies and 
showed the negative role of political uncertainty in the inflows of FDI. The study concluded that political 
uncertainty is a severe intimidation for the contract of investment that is signed between host country and 
international bodies. Hence, the yield on capital can be depreciated in the nations having more chances of political 
risk.  

Drobetz, El Ghoul, Guedhami, and Janzen (2018) examined the empirical relationship between WUC and FDI 
by using world uncertainty index as a measurement of world uncertainty. In this regard, the study gathered data of 
45 developed and developing economies for the period of 1990-2018. The study indicated the negative link between 
WUC and FDI. Phan et al. (2021) investigated the impact of EPUC on financial instability for the case of 23 
nations for the period of 1996-2016 and indicated the negative bond between these variables. The study implies 
that 1-standardize unit of increase in EPUC tends to reduce the financial stability between 3.73% to 8.02% for the 
selected nations. The study concluded that this impact is strongest for the nations with advanced competition, 
small regulatory capital and smaller financial systems. Canh, Binh, Thanh, and Schinckus (2020) investigated the 
role of EPUC in the financial sector of Malaysia and indicated the detrimental role of EPUC in the financial 
development of the selected nation. The study concluded that high level of EPUC substantially reduces the bank 
lending growth with its stronger influence of large sized and riskier banks. Caglayan and Xu (2019) analyzed the 
influence of EPUC on the stability of credit and financial institutions. For this purpose, the study gathered the data 
of 18 developed economies for the period of 1994-2013 and indicated the negative trade-off between the selected 
variables. The study provides the strong evidence that uncertainty diminishes the availability of credit and leads to 
an increase in the non-performing loans of banks. This concluded the detrimental role of EPUC on the financial 
development of the nation and indicated that EPUC not only having its detrimental effects for the developing 
economies, but also for the developed economies.  

Choi, Furceri, and Yoon (2021) studied the effects of WUC on the financial system of 13 OECD economies. For 
this purpose, the study collected the data for the period of 2000-2015 and indicated the adverse effects of WUC on 
the financial system of the selected economies. Avom et al. (2020) analyzed the role of WUC on the FNDP of 139 
developing and emerging economies and indicated the negative connection between these variables. The study 
concluded that increased WUC is aligned with many other uncertainties i.e., financial uncertainty, political and 
economic uncertainty etc. which are very detrimental for the financial systems, and thus, negatively contributes to 
the FNDP. The study implies that 1% of increase in WUC tends to reduce 12%-16% FNDP. Li and Zhong (2020) 
conducted their research in the context of China and analyzed the role of EPUC on the financial development of 
China for the period of 1995-2016. the study measures EPUC by global economic uncertainty index, while financial 
development with financial condition index. The study used EPUC as independent while FNDP as a dependent 
variable of the study. Results of the study indicated the negative relationship between these variables. Shi, Qiu, and 
Fan (2020) examined the empirical relationship between WUC and FDI for the case of 35 Asian economies for the 
period of 2000-2018. The study applied VAR model to analyze the empirical results. Results of the study showed 
adverse impacts of WUC on the inflows of FDI in the host country.   

Abaidoo (2019) analyzed the role of economic, political and world uncertainty in the inflow of FDI and imports 
for the case of China. For this purpose, the study collected the data from 1990-2015 and applied ARDL model to 
estimate the coefficients. The study used different uncertainty dimensions (i.e., economic policies and world 
uncertainty) as explanatory variables. Results of the study did not reveal any significant association between the 
chosen variables in short run, while the study indicated the significant negative rapport between the chosen 
variables in long run.  The study concluded that the uncertainties are very detrimental for the foreign inflows. 
Demir and Ersan (2018) conducted their research on Turkey and analyzed the influence of WUC on its financial 
markets for the period of 2003-2014. The Study indicted the negative role of WUC on the financial markets. 
Debata and Mahakud (2018) analyzed the role of EPUC on the stock market development of 25 developing 
economies by incorporating the moderating role of financial crises. The study indicated the negative influence of 
EPUC on the stock market development for the selected countries which become more negative in the presence of 
financial crises. The study concluded the enhancing role of financial crises in the nexus between EPUC and stock 
market development.  

Guo, Wei, Zhong, Liu, and Huang (2020) indicated that EPUC arises when the economic body cannot envisage 
whether, when and how the government will change its current economic policy. Author indicated that EPUC 
having significant impacts on the behavior of different financial and market bodies of the country, especially related 
to the financial decision making i.e., investment decisions. Hence, this importance of the EPUC motivated the 
authors to conduct their research in the uncertainty-financial market nexus. In this regard, the study gathered the 
data of China for the period of 1990-2018 and applied ARDL to estimate the results. Results reveal that uncertainty 
in the economic policies is very unfavorable for the financial markets. Henceforth, the study concluded the negative 
link between chosen variables. Wu, Zhang, Zhang, and Zou (2020) examined the role of economic, financial, 
political, and pandemic uncertainty on the inflows of foreign capital for the case of South Asian Economies. In this 
regard, the study gathered the data for the period of 1990-2017. The study applied ARDL and revealed the adverse 
(negative) impact of economic, financial, political, and endemic uncertainty on the foreign inflows of capital. In 



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addition, the study indicated that the impact of economic uncertainty is more adverse as compare to other 
uncertainties.  Liu and Dong (2020) also indicated the adverse effects of pandemic and economic uncertainty on the 
inflow of capitals. Nguyen, Kim, and Papanastassiou (2018) used the firm level data across 25 economies for the 
period of 1996Q1 to 2016Q1 to analyze the role of WUC in foreign inflows and trade credit provisions. The study 
indicated that increase in WUC tends to reduce the foreign inflow of capital and provision of trade credit. After 
reviewing the above literature, present study hypothesized that: 
H1: “Economic policy uncertainty has negative impact on foreign direct investment.” 
H2: “Economic policy uncertainty has negative impact on financial development.” 
H3: “World uncertainty has negative impact on foreign direct investment.” 
H4: “World uncertainty has negative impact on financial development.”  
 

2.1. Conceptual Model 
The conceptual model of the study is presented in Figure 5. The study aims to analyze the influence of 

economic policy uncertainty (EPUC) on foreign direct investment (H1) and financial development (H2). The study 
also analyses the role world uncertainty on foreign direct investment (H3) and financial development (H4). 
 

 
Figure-5. Conceptual Model. 

 

3. Methodology 
This section presents the data collection techniques, measurement of variables and different econometric 

techniques to analyze the empirical results of the study. The fundamental purpose of the study is to analyze the 
impact of EPUC and WUC on FDI and FNDP. In this regard, the study uses time series data. In order to 
accomplish the fundamental aim of the study, the study gathered the data of France for the period of 1997-2018. 
The data of EPUC and WUC are collected from www.policyuncertainty.com provided by Naker, Scott; Bloom, 
Nick; Davis, Stephen and Ahir, Hites; Bloom, Nick; Furcer, Davide. While, the data of FDI and FNDP are gathered 
from world bank. The study uses EPUC and EUC as independent variables while FDI and FNDP as dependent 
variables.  However, the operationalization or measurement of variables is shown in Table 1. 
 

Table-1. Operationalization or measurement of variables. 

Variable name  Measurement  Reference  Notation  

Independent variables 
Economic policy uncertainty Economic policy uncertainty index Zhu, Jia, and Wu (2019) EPUC 
World uncertainty  World uncertainty index Nguyen and Lee (2021) WUC 
Dependent variables  
Foreign direct investment  Net inflows (% of GDP) Azam et al. (2012) FDI 
Financial development  Domestic credit to private sector (% of 

GDP) 
Ahmed, Kousar, Pervaiz, and 
Ramos-Requena (2020) 

FNDP 

 
Present study uses following two econometric models to accomplish the fundamental purpose of the study  

Model 1: FDI =                       

Model 2: FNDP =                       
Where: “FDI is foreign direct investment, FNDP is financial development, EPUC is economic policy 

uncertainty, WUC is world uncertainty,           are intercepts, and                 are the coefficients of 
EPUC and WUC in models 1 and model 2 respectively, e is error term.” 

In order to estimate the empirical results of the study, the study first tests the stationarity and order of 
integration of the modeled variables to choose the best suitable technique for the estimation. To test the stationary 
properties and order of integration of data, the study used extensively applied augmented dickey fuller (ADF) unit 
root test. After this, the study applied some diagnostic tests i.e., test of autocorrelation, heteroscedasticity, and 
multicollinearity to make sure that the data for the present study are free from the econometric errors. After this, 
the study applies auto regressive distributive lag (ARDL) model to test the hypothesized relations among variables 
as ARDL is the best suitable approach when the variables are integrated of mixed order. Bounds test is the pre-
condition to apply ARDL approach which tests the co-integrating relation among modeled variables. The study 
uses Equations 3 and 4 to test the long run relationship between variables. 

          ∑   
 
           ∑   

 
    (    )    ∑   

 
    (   )         (   )      (    )    

  (   )       --- 3 

           ∑   
 
            ∑   

 
    (    )    ∑   

 
    (   )         (    )    

  (    )      (   )      --- 4 



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Where: “FDI is foreign direct investment, FNDP is financial development, EPUC is economic policy 

uncertainty, WUC is world uncertainty,           are intercepts,                       are the coefficients of 

short run for Equations 3 and 4 respectively,   is the difference operator,            ,           are the 

coefficients of long run for Equations 3 and 4 respectively, and    is white noise error term.” 
Both Equations 3 and 4 used F-statistic to test the long run relationship between the modeled variables for the 

selected time period. This test involves the testing of the null hypothesis of “no-cointegration”. After examining the 
long run relationship between variables, the study used Equations 4 and 5 to estimate short run parameters and the 
error correction term (ECT). 

          ∑   
 
           ∑   

 
    (    )    ∑   

 
    (   )         (   )       --- 4 

           ∑   
 
            ∑   

 
    (    )    ∑   

 
    (   )         (   )       --- 5 

Where; ∆ is the first difference operator,        α0 are the intercept term,   ,   ,                 are the slope 
coefficients of short run, ECMt-1 is the error correction term, which signifies the speed of adjustment or the level of 

long run equilibrium, and   t is the residual or stochastic error term.”  
 

4. Empirical Results 
4.1. Descriptive Statistics 

Table 2 shows the results of descriptive statistics. Table represents the mean, median, maximum and minimum 
values of the data along with skewness and kurtosis. The test statistic of Jarque-Bera is also reported in this Table 
which is used to test the normality of residuals. The insignificant probability values of Jarque-Bera shows that the 
data for the current study are normally distributed. 

 
Table-2. Descriptive Statistics. 

Particulars EPUC FDI FNDP WUC 

 Mean 155.7398 2.9719 87.6970 0.1822 

 Median 126.9852 2.2960 92.5250 0.1579 
 Maximum 317.1186 12.8815 107.6418 0.4264 

 Minimum 37.6033 0.2032 68.3989 0.0562 

 Std. Dev. 88.8044 2.9345 11.8812 0.0993 

 Skewness 0.3841 2.4268 -0.1458 1.0384 

 Kurtosis 1.8490 8.2244 1.6861 3.3047 

 Jarque-Bera 1.8353 1.7351 1.7348 0.2229 

 Probability 0.3994 0.1000 0.4200 0.1210 
Where: “FDI is foreign direct investment, FNDP is financial development, EPUC is economic policy uncertainty, and 
WUC is world uncertainty. 

 

4.2. ADF Test of Stationarity and Multicollinearity 
Present study applies extensively used Augmented Dicky Fuller (ADF) unit root test to know about the order 

of integration and the stationarity properties of the data. The test is applied on level and first difference for two 
cases i.e., with intercept, and with intercept and trend. Test is having the null hypothesis of the “non-stationary 
series”. Results in Table 3 (Panel A) show that the test statistic of EPUC and WUC are insignificant at level in both 
cases (i.e., with intercept, and with intercept and trend). This depicts the problem of non-stationary in these 
variables at level. However, the test statistic becomes significant at first difference in both cases by rejecting the 
null hypothesis of non-stationary series. This depicts that the EPUC and EUC are stationary at first difference and 
integrated of order 1. On the contrary, the test statistic of FDI and FNDP are significant at both (level and first 
difference) in both the cases. This implies that FDI and FNDP are free from the problem of unit root and 
integrated of order 0 i.e., I (0). As some of the variables are integrated of I (0), and some are integrated of I (1), 
hence, it is concluded that the variables of the present study are integrated of mix order. 

Table 3 (Panel B) shows the results of correlation matrix which is used to detect the problem of 
multicollinearity. Results depict that the data for the current study are free from the problem of multicollinearity as 
the coefficient of correlation between two any variables is less than 0.50. 
 

Table-3. ADF Unit Root and Multicollinearity. 

Panel A: ADF Unit Root Test 

 
Variables 

Level First Difference  
Decision Intercept Intercept and trend Intercept Intercept and trend 

EPUC -2.1958 -2.1600 -5.3025*** -5.2095*** I (1) 

WUC -1.3370 -1.2161 -3.3755** -3.2301** I (1) 
FDI -3.2125** -3.9845*** -4.8353*** -4.9745*** I (0), I (1) 
FNDP -3.4876*** -3.4825*** -4.1190*** -4.8355*** I (0), I (1) 
Panel B: Multicollinearity 

Variables EPUC FDI FNDP WUC 

EPUC 1    

FDI -0.1908 1   

FNDP 0.2481 -0.6469 1  

WUC 0.2366 -0.3124 0.1024 1 
Where: “FDI is foreign direct investment, FNDP is financial development, EPUC is economic policy uncertainty, WUC is world uncertainty, and **,*** 

is level of significance at 5% and 10% respectively.” 
 

4.3. Autocorrelation, Heteroscedasticity and Bounds Co-Integration Test 
Results of autocorrelation, heteroscedasticity and bound test for both of the study model are presented in Table 

4. Both tests are having the hull hypothesis of “no serial correlation” and “no heteroscedasticity” respectively. The 



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insignificant p-values reported in Panel A and Panel B indicating the acceptance of null hypothesis which specifies 
that the data for the present study are free from the econometrics problem like auto/serial correlation and 
heteroscedasticity. The study applies bounds cointegration test to determine the cointegrating relation among 
modeled variables. The test is applied for both the models. Results of Table 4 (Panel C) indicate the presence of 
long run relation between the variables of both models as the value of F-statistic (8.823 and 9.945 respectively) is 
greater than the upper bounds at 10%, 5% and 1% level of significance. Hence, the respective study concluded that 
the chosen variables of the study move together in long run for the period of 1997-2018. 

 
Table-4. Test of Autocorrelation and Heteroscedasticity. 

Panel A: Auto Correlation 

Model 1 Model 2 

Breusch-Godfrey 
Serial 
Correlation 

Test 
statistic 

P-value Decision Test statistic P-value Decision 

1.9833 0.1647 No serial correlation 0.2345 0.1773 No serial correlation 

Panel B: Heteroscedasticity 

Model 1 Model 2 

Breusch-Pagan-
Godfry HSK 

Test 
statistic 

P-value Decision Test statistic P-value Decision 

1.8938 0.3326 No heteroscedasticity 0.1534 0.2413 No heteroscedasticity 

Panel C: Bound Test 

F-Bounds Test Model 1 Model 2 Null Hypothesis: No levels relationship 

Test Statistic Value Value Significance I(0) I(1) 

F-statistic 8.623 9.945 10% 4.19 5.06 
K 2 2 5% 4.87 5.85 

  1% 6.34 7.52 

 

4.5. Hypotheses Testing  
Present study uses ARDL to estimate the empirical results. Results are reported in Table 5. Panel A of Table 5 

shows the long run association between variables, while panel B shows the speed of adjustment between variables. 
In panel A, the coefficient of EPUC in model 1 shows the negative and significant relationship between EPUC and 
FDI at the level of 1%, while the coefficient of EPUC in model 2 shows the negative and significant relationship 
between EPUC and FNDP at 5% level of significance. Result implies that 1-unit of increase in EPUC results in a 
decrease of 3.5540 units in FDI while 5.7845 units of FNDP in long run. Hence, the 1st, and 3rd hypotheses of the 
study are supported. On the other hand, the coefficients of WUC in model 1 and model 2 reveal the negative impact 
of WUC on FDI and FNDP. Results show that 1-unit of increase in WUC result in a decrease of 2.9845 and 3.9853 
units in FDI and FNDP in long run at the level of 5% and 1%, respectively. Hence, the 2nd and 4th hypotheses of the 
study are also supported. In panel B, the coefficient of ECT is negative and highly significant at the level of 1%. 
Result shows that 74.65% (63.44%) inconsistency between the long term and short term FDI (FNDP) will be 
corrected within a year. Finally, the values of adjusted R-squares of model 1 and model 2 show that EPUC and 
WUC collectively explained 66.63% variations in FDI while 69.57% variations in FNDP. 
 

Table-5. Estimations of ARDL. 

Variables Model 1 (DV: FDI) Decision Model 2 (DV: FNDP) Decision 

Coefficient  p-value  Coefficient  p-Value 

Panel A: Long run results  
EPUC -3.5540 0.0034*** H1: Supported -5.7845 0.0263** H3: Supported 
WUC -2.9845 0.0453** H2: Supported -3.9853 0.000*** H4: Supported 

Panel B: Short run/ECM regression  
ECT -0.7465 0.000*** -- -0.6344 0.0000*** -- 
R2 0.7475 -- 0.7898 
Adj. R2 0.6663 -- 0.6957 

Where: “FDI is foreign direct investment, FNDP is financial development, EPUC is economic policy uncertainty, WUC is world uncertainty, and 
**,*** is level of significance at 5% and 10% respectively.” 

 

5. Conclusion 
Since the publication of “The Age of Uncertainty” in 1977, many major events have been occurred that results 

in an economic and political uncertainty around the world. This uncertainty is highly aligned with the fact that we 
exist in the “hyper-connected” world, where an event which arises in one part of the world will definitely have an 
influence on the other part of the world. Evidences reveals that financial crises of 2008, Arab springs of 2012, and 
European sovereign debt crises of 2010 are the underlying causes of increased economic, political and world 
uncertainties around the globe. These uncertainties are imposing adverse and detrimental effects on the whole 
economy, specifically on the financial sector of France. The outbreak of corona virus in the last quarter of 2019 
makes the situation more worst, specifically for the case of France. The outbreak of this virus results a drastic 
reduction in liquidity and solvency of French corporations. The inflows of FDI in France also reduces by 17% 
during the outbreak of virus. However, after analyzing the situation of WUC and EPUC in France, Present study 
propose that it is crucial to examine the role of EPUC and WUC on the FDI and FNDP on France. For this 
purpose, the study gathers the data of France for the period of 1997-2018. The study applied ARDL bound testing 
approach of estimation. Results of the study show the negative impact of WPUC and WUC on FDI and FNDP of 
France. Results are aligned with prior studies (Avom et al., 2020; Caglayan & Xu, 2019; Choi et al., 2021; Li & 
Zhong, 2020). Findings imply that world and economic policy uncertainty are very detrimental for the foreign 
inflows and financial development of the France. Therefore, the study suggests that the France government should 
monitor the source and size of uncertainty shock while formulating different economic policies. 



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Citation: Francois Smith (2021). Uncertainty, Financial 
Development and FDI Inflows:  France Evidence. Asian Business 
Research Journal, 6: 7-13. 
History:  
Received: 19 February 2021 
Revised: 14 June 2021 
Accepted: 12 July 2021 
Published: 10 August 2021 
Licensed: This work is licensed under a Creative Commons 

Attribution 3.0 License  
Publisher:  Eastern Centre of Science and Education 

Funding: This study received no specific financial support.    
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interests regarding the publication of this paper. 
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accurate, and transparent account of the study was reported; that no vital 
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study as planned have been explained. 
Ethical: This study follows all ethical practices during writing.  
 

Eastern Centre of Science and Education is not responsible or answerable for any loss, damage or liability, etc. caused in relation to/arising out of the use 
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