INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XV October 2025 | Special Issue on Economics
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Asymmetric Causality between Economic Uncertainty and Financial
Development: Empirical Evidence
Rafiqa Murdipi
International Islamic University of Malaysia, BATU 6 1/2 JALAN GOMBAK, Kuala Lumpur, Malaysia
DOI: https://dx.doi.org/10.47772/IJRISS.2025.915EC00749
Received: 04 October 2025; Accepted: 10 October 2025; Published: 07 November 2025
ABSTRACT
This study analyses the asymmetric causal relationship between economic uncertainty and financial development
across 86 countries. The employing of asymmetric Granger causality, as proposed by Hatemi-J (2012), indicates
the presence of an asymmetric causal relationship between economic uncertainty and financial development.
Positive change, namely a rise in economic uncertainty, adversely affects the growth of financial institutions.
The advancement of financial institutions mitigates economic instability. Simultaneously, an escalation in
economic uncertainty leads to heightened fluctuations in the financial market. Heightened fluctuations in the
financial market will aggravate economic instability. This research will benefit policymakers, financial
institutions, and investors by examining the dynamic link between economic uncertainty and financial
development for risk reduction and forecasting.
Keywords: Economic uncertainty, financial development, asymmetric granger causality
INTRODUCTION
More and more policymakers and researchers are paying attention to the issue of economic uncertainty,
especially since the global financial crisis of 2008 and COVID-19. The well-established theoretical and empirical
research has shown that the uncertainty in the economy has an effect on business cycles and the financial system.
When there is more uncertainty, businesses and investors tend to "wait and see" and hold off on investing. This
leads to slower growth in production. (Bloom, 2009). The financial market was also affected because there were
rising shocks of uncertainty. Baker et al. (2020) have put forth the most recent theory that the Covid-19 pandemic
may be the cause of the economy's tendency to be hard to predict, which would make things even more uncertain.
It is widely recognised that finance significantly influences economic growth; thus, attaining sustainable
financial development should be a primary objective for numerous countries. Conversely, several scholarly
works caution that an overabundance of finance may result in heightened economic instability, consequently
impeding economic development. Although there exists a connection between economic uncertainty and
financial development, it is crucial to examine the dynamic causation between these two factors. There exists a
potential for the absence of bidirectional causality or the relevance of Granger causality in the unidirectional
relationship between financial development and economic uncertainty, attributed to prior research
predominantly emphasising the influence of economic uncertainty on financial development.
This paper aims to fill up the gap in literature by examining an asymmetric Granger causality between economic
uncertainty and the expansion of the financial system. Earlier models have focused on the premise that there
exists a linear and symmetric relationship between economic variables and the financial system. Because
economic uncertainty can cause both positive and negative shocks, the financial sector will grow in different
ways, both in terms of size and direction. The growth of the financial sector can also cause positive and negative
shocks, which may have different effects on how uncertain the economy is. Negative shocks to the economy, or
increasing uncertainty, could hurt the growth of the financial sector more and for a longer time than positive
shocks. To create strong financial systems and beneficial macroprudential rules, it is important to understand
this kind of asymmetric causation.
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This study contributes significantly to the existing body of knowledge. This study examines the dynamic
interrelations between economic uncertainty and financial system development through the analysis of Granger
causality between these two variables. Macroeconomic and financial variables tend to exhibit greater dynamism
than stability; therefore, it is crucial to examine the dynamic relationships between economic uncertainty and
financial development through the asymmetric Granger causality methodology. This study provides an advanced
perspective on the dynamic relationship between financial system expansion and economic uncertainty. This
study employs the econometric method of the asymmetric Hatemi causality test, in contrast to the traditional
symmetric or linear Granger causality test. This study goes beyond the usual idea that uncertainty only affects
the financial system in one way by looking at the possible two-way relationship between economic uncertainty
and figuring out which way Granger causality goes between these two variables. This study is distinctive as it
distinguishes between the asymmetric positive and negative shocks of one variable on another. This method
gives policymakers and banks a lot of information to help them make smart decisions about how to deal with
economic uncertainty and stabilise both the economy and the financial system.
The rest of the paper is as follows:The literature review offers the previous studies related to economic
uncertainty and financial development. The data and methodology section describes the data sources,
methodology, and empirical model. The results and discussion section describes the empirical findings and the
final conclusion.
LITERATURE REVIEW
The study suggests that the economic uncertainty likely represented a significant manifestation of the adverse
relationship between economic uncertainty and the stock market. A significant amount of previous evidence
indicates that economic uncertainty negatively affects stock and bond markets (Antonakakis et al., 2013; Chen
et al., 2024; Chinzara, 2011; Huang et al., 2023; Javaheri & Amani, 2022). This is based on the idea that Bernanke
(1983) put forward, which said that high levels of uncertainty make businesses put off hiring and investing.
There is a strong link between how uncertain the economy is and how volatile the market is. This economic
uncertainty has a big effect on stocks and bonds. Huang et al. (2023) look at how economic uncertainty affects
the return volatility of financial assets. Chen et al. (2024) show that exposure to Chinese uncertainty has a
negative effect on the future returns of major companies in Japan, Hong Kong, and India over different trading
horizons by doing a portfolio-level sorting analysis.
Banks are greatly affected by economic uncertainty. Ozili & Bank (2023) investigates the influence of economic
policy uncertainty (EPU) on bank profitability in 22 industrialised countries. The findings demonstrate that
heightened economic policy uncertainty (EPU) negatively affects bank non-interest revenue. Wang & Duan
(2025) investigate the impact of economic policy uncertainty on loan concentration within a sample of Chinese
commercial banks from 2007 to 2020. Using a panel dataset of 311 institutions, the findings demonstrate a
significant negative correlation between economic policy uncertainty and the lending concentration of banks.
Danisman et al. (2020) investigates the impact of Economic Policy Uncertainty (EPU) on loan growth, utilising
a sample of 2,977 private and publicly listed banks in the EU-5 countries (the United Kingdom, Germany, Spain,
Italy, and France) from 2009 to 2018. two-step difference GMM estimators show that European banks can't lend
as much money because they don't know what the economy will do.
Ma and Hao (2022) stressed that financial development lessens the negative effects of economic uncertainty.
Financial development will lessen the enterprise's financial limitations, thereby diminishing economic
instability. Fortin et al. (2023) illustrate that economic uncertainty significantly hampers economic growth. Ullah
et al. (2024) examines the relationship between economic policy uncertainty (EPU) shocks and stock market
development in China, demonstrating that positive EPU shocks significantly hinder stock market growth, while
negative EPU shocks substantially promote it.
DATA , EMPIRICAL MODEL AND METHODOLOGY
The empirical study encompasses 86 countries from 1990 to 2021. The financial development data was sourced
from the Global Financial Development Database. This study utilises various indicators for assessing the
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
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development of financial institutions (private credit, liquid liabilities to GDP, and deposit money banks to GDP)
and the stock market (stock market capitalisation to GDP, stock market total value traded to GDP, and stock
market turnover ratio). To assess economic uncertainty, this study utilises two indicators: the World Uncertainty
Index (WUI) (Ahir et al., 2022) and Economic Policy Uncertainty (Baker et al., 2016)
It is the Granger causality test that serves as the foundation for the empirical investigation.An asymmetric version
of this test, which was developed by Hatemi-J (2012), is described in the following table.This type of testing is
able to differentiate between the causal impact of positive shocks and the effect of negative shocks.Taking into
account asymmetric causal effects is consistent with the reality, particularly in the context of financial markets,
where investors have a tendency to respond more strongly to changes that are unfavourable than they do to
changes that are favourable.The performance of this asymmetric causation is likewise satisfactory in situations
in which the underlying data does not follow a normal distribution and the volatility varies over time.Testing for
asymmetric causation is based on a similar technique, with the primary distinction being that the causal effect of
positive shocks may be different from the causal impact of negative shocks. This is the key difference.As a
result, it is essential to create these shocks, which may be accomplished by making use of the cumulative sums
of the shocks that are operating under the surface. Hatemi-j et al. (2014) contend that conducting causality tests
within a panel yields numerous advantages compared to the traditional time series approach, as panel data
increases degrees of freedom and may enhance efficiency by incorporating cross-sectional spillover effects.
Let as economic uncertainty and as financial development.
For i=1, …, n. Where n is the size of the cross sectional dimension and is the white noise error term. The
shocks can be identified as
= max(
,
= max(
= min(
,
= min(
. Utilising these definitions, we can formulate the cumulative sums of the shocks as :
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
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RESULTS AND DISCUSSION
Table 1: Homogeneity Test
Δ
p-value
Δadj
p-value
CREDIT, UNC
0.249
0.803
0.358
0.720
LIQUIDITY,UNC
-0.341
0.733
-0.492
0.623
ASSET, UNC
0.442
0.658
0.633
0.527
SMCAP, UNC
0.901
0.368
1.275
0.202
SMVALUE,UNC
2.715
0.007
3.844
0.000
SMTURNOVER,UNC
3.292
0.001
4.656
0.000
Before conducting the granger panel data analyses, the homogeneity test is tested and the results are tabulated
in Table 1. The findings of homeigeity test of null hyphotesis of homegeity are majority fail to reject. Hence,
this study conduct the panel granger asymmetric causality.
The results of the causality tests are shown in Tables 2 and 3. The asymmetric causality tests indicate that the
null hypothesis, which posits that positive shocks in the WUI do not induce positive shocks in financial
development, fails to be rejected. In this instance, the estimated parameter is negative. A rise in uncertainty
shocks would adversely affect the growth of financial institutions. Likewise, the null hypothesis about positive
shocks of Economic Policy Uncertainty (EPU) in relation to positive liquidity finance development is not
rejected. Financial institutions react adversely to favourable developments in economic uncertainty.The findings
corroborate the hypothesis posited by Danisman & Tarazi (2024), which asserts that heightened economic
uncertainty results in diminished bank stability and reduced credit availability (Caglayan & Xu, 2019). The null
hypothesis posits that the emergence of positive financial institutions does not induce positive effects on
economic uncertainty, failing to reject the WUI and exhibiting weakness in the EPU. Nonetheless, adverse
changes are substantial. Consequently, the growth of financial institutions reduces economic uncertainty. This
results in line with literature by Kıvanç Karaman & Yıldırım-Karaman (2019), and Ma and Hao (2022).
According to them, financial development mitigates the negative effect of the impact of economic uncertainty
on growth.
Table 3 presents the findings of the asymmetric Granger causality between economic uncertainty and financial
market growth. The favourable alteration of economic uncertainty for both WUI and EPU significantly
contributes to beneficial changes in financial market development indicators. According to Ghani & Ghani
(2024), uncertainty in US economic policy can be a good predictor for the stock market in other countries, like
Pakistan. This is because the study found that uncertainty had a significant impact on the stock market. Faferko
et al. (2025) in their study demonstrate the significant effect of uncertainty on stock market anomalies. These
studies align with the empirical findings of this research, which indicated significant positive stocks in response
to favourable stock market developments.
However, negative change does not lead to rejection. This suggests that heightened economic uncertainty
correlates with increases in favourable financial market developments. The null hypothesis is rejected for the
impact of positive financial market changes on WUI, but not rejected for negative ones. Consequently,
heightened fluctuations in financial markets enhance economic uncertainty.
Table 2: Asymmetric Hatemi-J causality test economic uncertainty and financial institutions development
W stat
Bootstrapped critical values
W stat
Bootstrapped critical values
1%
5%
10%
1%
5%
10%
H
0
: UNC
+
≠> FD
+
( FINANCIAL INSTITUTIONS)
H
0
: FD
+
( FINANCIAL INSTITUTIONS)≠> UNC
+
WUI
CREDIT
0.258
12.355
4.333
2.201
0.044
10.935
4.454
2.344
LIQUID
0.155
12.364
4.014
2.221
0.099
16.604
5.669
2.662
ASSET
0.026
14.905
4.29
2.281
0.000
11.918
4.132
1.972
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EPU
CREDIT
6.737**
10.214
6.206
4.561
5.18*
9.148
6.118
4.956
LIQUID
1.167
7.371
3.712
2.522
0.212
13.604
5.519
3.906
ASSET
6.603**
11.153
6.063
4.700
9.046**
14.206
4.332
2.086
H
0
: UNC
-
≠> FD
-
( FINANCIAL INSTITUTIONS)
H
0
: FD
-
( FINANCIAL INSTITUTIONS) ≠> UNC
-
WUI
CREDIT
4.355**
9.933
3.932
1.950
9.475**
10.91
4.593
2.460
LIQUID
6.447**
11.088
4.086
2.357
8.857**
11.88
4.254
2.310
ASSET
7.282**
10.034
4.669
2.197
4.320
9.101
6.027
4.699
EPU
CREDIT
5.341*
14.656
5.968
4.181
95.696***
17.932
8.942
6.314
LIQUID
3.448**
9.335
3.357
2.047
75.033***
19.845
6.262
4.179
ASSET
29.256***
18.915
7.633
5.535
115.534***
17.455
8.168
5.676
Note: *, ** and *** indicate statistical significance at 10, 5 and 1% level respectively. Critical values are obtained
from 10000 bootstrap replications.
Table 3: Asymmetric Hatemi-J causality test economic uncertainty and financial market development
W stat
Bootstrapped critical values
W stat
Bootstrapped critical values
1%
5%
10%
1%
5%
10%
H
0
: UNC
+
≠> FD
+
( FINANCIAL MARKET)
H
0
: FD
+
( FINANCIAL MARKET)≠> UNC
+
WUI
SMCAP
4.284**
7.856
3.393
2.326
2.935*
6.454
3.118
2.070
SMVALUE
4.253**
9.606
3.735
2.319
3.187**
8.459
3.903
2.256
SMTURNOVER
3.987**
8.049
3.467
2.312
3.013*
7.431
3.993
2.382
EPU
SMCAP
7.18**
12.469
3.313
2.326
0.024
9.714
3.365
2.201
SMVALUE
5.68**
8.273
4.095
2.384
1.055
8.391
3.807
2.402
SMTURNOVER
2.772*
9.421
3.605
2.385
1.444
9.086
3.893
2.562
H
0
: UNC
-
≠> FD
-
( FINANCIAL MARKET)
H
0
: FD
-
( FINANCIAL MARKET) ≠> UNC
-
WUI
SMCAP
0.768
7.347
3.17
2.246
0.301
6.934
3.584
2.508
SMVALUE
0.837
8.301
3.711
2.136
1.141
6.081
2.985
2.081
SMTURNOVER
0.968
8.718
3.818
2.497
0.001
8.861
4.394
2.484
EPU
SMCAP
0.001
8.616
3.702
2.297
0.037
9.755
3.933
2.437
SMVALUE
2.164
9.717
3.494
2.308
2.243
6.729
3.391
2.318
SMTURNOVER
3.004*
11.946
4.322
2.842
3.709*
10.418
4.119
2.521
Note: *, ** and *** indicate statistical significance at 10, 5 and 1% level respectively. Critical values are obtained
from 10000 bootstrap replications.
CONCLUSION AND POLICY IMPLICATION
This paper examined the causal effects of economic uncertainty on financial development across 86 countries.
This research employs an asymmetric causality test for this aim. The empirical findings indicate the presence of
an asymmetric causal relationship between economic uncertainty and financial development. The findings
indicate that a rise in economic uncertainty (positive developments) significantly causes a decline in the growth
of financial institutions. The significant advancements in financial institutional development at that time resulted
in a decrease in economic uncertainty. The findings indicate that favourable alterations in economic uncertainty
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will lead to beneficial adjustments in the financial market. Heightened economic uncertainty will amplify
volatility in the financial market. Nonetheless, favourable alterations in the financial market induce heightened
economic uncertainty. The findings reveal asymmetric causation about uncertainty in financial development. As
economic uncertainty increasingly manifests as a worldwide phenomena, more study is essential to enhance
knowledge of the relationship between uncertainty and the financial system.
The findings have implications for policy. This study found that there are asymmetric causality shocks between
economic uncertainty and the development of the financial system. It also showed that positive increases in
economic uncertainty shocks have a significant Granger effect on financial institutions and market development.
This finding helps policymakers come up with ways to reduce risks so that financial development can continue
despite the rise of uncertainty shocks. The research established a bidirectional causation between the positive
impacts of financial market expansion and economic uncertainty, offering investors and policymakers insights
into the relationship between stock markets and economic uncertainty.
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