The Impact of Political Instability on Foreign Direct Investment in Malaysia

The Impact of Political Instability on Foreign Direct Investment in Malaysia

Mohamad Aizad Mohamad Azahar^1,2; Hafizah Hammad Ahmad Khan^3*

^1,3Faculty of Business and Management, Universiti Teknologi MARA, Kampus Sungai Petani, Merbok, Kedah, Malaysia

²City Zone Express Sdn Bhd, Bukit Mertajam, Pulau Pinang, Malaysia

*Corresponding Author

DOI: https://dx.doi.org/10.47772/IJRISS.2024.8090238

Received: 25 September 2024; Accepted: 30 September 2024; Published: 18 October 2024

ABSTRACT

This study investigates the relationship between political instability and Foreign Direct Investment (FDI) in Malaysia from 2008 to 2023, considering the interplay with other critical macroeconomic factors such as GDP, interest rates, exchange rates, and trade openness. Using the Autoregressive Distributed Lag (ARDL) model, the findings underscore the significant deterrent effect of political instability on FDI, highlighting its role as a critical barrier to attracting foreign investments. Conversely, GDP emerges as a strong enhancer of FDI, indicating that economic vitality is crucial for attracting foreign capital. The study also reveals that while higher interest rates negatively impact FDI, exchange rates and trade openness do not show a significant long-term effect on FDI inflows. This study contributes to the existing literature by providing empirical evidence on the dynamics between political instability and economic factors affecting FDI in Malaysia. The results offer valuable insights for policymakers aiming to enhance Malaysia’s attractiveness as an investment destination.

Keywords: Political instability, FDI, Macroeconomic factors, Cointegration, ARDL model, Malaysia

INTRODUCTION

Foreign Direct Investment (FDI) is widely recognized as a crucial driver of economic growth (Choromides, 2020). FDI provides capital inflows, enhances technology transfer, and fosters job creation, contributing significantly to economic development (Tsen, 2019; Mahembe & Odhiambo, 2014). However, in recent years, Malaysia has observed a declining trend of its FDI inflows. Despite its strategic location and well-developed infrastructure, Malaysia has faced periods of political instability, notably following the 2018 general election and the ensuing frequent leadership changes, which have significantly undermined investor confidence in the stability of its economic environment (Mohamad et al., 2023).

Political instability plays a critical role in shaping FDI inflows in developing countries like Malaysia (Zulkifli, 2024; Kim, 2010). Such instability, characterized by erratic changes in leadership, unpredictable policy frameworks, and social unrest, can create an uncertain business environment. This perceived risk often led to foreign investors to adopt a cautious stance, preferring to invest in countries with more stable political environments to protect their investment.

Given the critical importance of this issue, it is essential to understand the nuanced effects that political instability can have on FDI, especially since studies exploring this dynamic are relatively scarce. Recognizing and addressing the implications of political instability on FDI can guide policymakers in developing strategies that enhance the political and economic environment, thus bolstering Malaysia’s position as an attractive destination for global investors.

Therefore, this study aims to examine the effect of political instability on FDI in Malaysia, providing a comprehensive analysis of how political instability, alongside key macroeconomic variables such as GDP growth, interest rates, exchange rates, and trade openness, influences FDI inflows. Using the Autoregressive Distributed Lag (ARDL) modelling approach, this study not only explores the direct impact of political instability on FDI but also investigates how quickly FDI levels adjust to equilibrium. The ARDL approach offers a distinct advantage in that it allows for the estimation of both short-run and long-run dynamics between variables, even when they are integrated at different levels.

The remainder of this paper is structured as follows. Section 2 presents the literature review, followed by the methodology in Section 3. Section 4 provides the empirical findings and discussion. Finally, Section 5 concludes the study and offers recommendations.

LITERATURE REVIEW

Political instability is widely regarded as a major deterrent to FDI and a barrier to economic development. Characterized by frequent government changes, policy unpredictability, and social unrest, political instability creates uncertainty that complicates long-term investment planning for foreign investors. Alesina et al. (1996) argue that political instability disrupts the economic stability necessary for attracting FDI, as foreign investors become more risk-averse in unpredictable political environments, especially in countries with a history of political volatility. This view is supported by Anyanwu & Yameogo (2015), who identify political stability as one of the most important determinants of FDI, emphasizing that stable political environments foster investor confidence and promote capital inflows.

The negative relationship between political instability and FDI has been demonstrated in numerous studies. Most of the study suggests that countries experiencing political instability are less attractive to foreign investors due to the heightened risks associated with government turnover and policy changes (Ravinthirakumaran et al., 2015; Bhatti, 2023). However, Emudainohwo et al. (2017) argue that political instability, while not always fully deterring FDI, often reduces the profitability of investments, particularly in high-risk environments. Abubakar & Ayuba (2022) also highlight that while political instability generally discourages FDI, certain sectors may continue to attract investment despite the risks, depending on the specific context of the instability.

On the other hand, Daude & Stein (2007) argue that strong institutions can mitigate the negative effects of political instability, as they provide a predictable environment for investors. Bitar et al. (2019) and Qadri et al. (2020) further emphasize that political instability in combination with weak institutions exacerbates the negative impact on FDI by creating an even more unpredictable investment climate. In a recent study, Rosli & Kamaluddin (2023) confirm the importance of political stability for sustaining FDI and economic growth in Southeast Asia, with strong governance structures being key to attracting investment.

In the Malaysian context, Asiedu (2006) and Busse & Hefeker (2007) highlight that political instability, coupled with weak governance, discourages FDI. Aw & Tang (2010) identify market size, economic stability, and favorable trade policies as key factors that traditionally attract FDI to Malaysia, all of which can be disrupted by political uncertainty. Similarly, Mithani et al. (2008) and Kim (2010) argue that political stability is essential for attracting and maintaining FDI inflows in Malaysia, as it reduces uncertainty for foreign investors. Besides that, empirical studies by Nazeer & Masih (2017) and Khan & Akbar (2013) show that political instability negatively affects FDI, especially in developing countries like Malaysia, where economic growth is heavily reliant on foreign investment.

Looking at the current political landscape, it is crucial to examine how far the political instability caused by frequent government changes and policy unpredictability affects FDI inflows in Malaysia. These political fluctuations can severely impact investor confidence, leading to cautious investment strategies and potentially significant reductions in FDI flows. Understanding the specific dynamics of how such political instability influences investment decisions both in the long run and short run is essential for devising effective policies aimed at stabilizing the investment climate. This analysis is particularly important for Malaysia, a nation that heavily relies on FDI for its economic development. Addressing these challenges is not only vital for maintaining current investment levels but also for positioning Malaysia as a competitive player in the Southeast Asian region.

METHODOLOGY

This section discusses the methodology used to investigate the impact of political instability along with the macroeconomic factors on FDI inflows in Malaysia.

Model Specification

The model used to examine the impact of political instability along with the macroeconomic factors on FDI inflows in Malaysia can be represented as follows:

FDI_t = β₀ + β₁GDP_t + β₂IR_t + β₃EX_t + β₄TO_t + β₅POL_t + ε_t                                       [1]

Where:

FDI = Total FDI inflows in Malaysia (RM million)

GDP = Gross Domestic Product measured by Real GDP (RM million)

IR = Interest Rate measured by average lending rates (%)

EX = Exchange Rate (Malaysia Ringgit/ US Dollar)

TO = Trade Openness measured by trade-to-GDP ratio

POL = A dummy variable for political instability based on major political events

Whereby β₀ to β₅ represent the coefficients, indicating the magnitude and direction of the relationship between the independent variables and FDI, while ϵt represents the error term. All variables except for interest rates and the political instability dummy are expressed in natural logarithms to ensure linearity and stabilize variance in the model. The dataset spans from 2008Q1 to 2023Q4 and is sourced from credible institutions, including the World Bank, Department of Statistics Malaysia, Bank Negara Malaysia, and the Malaysia Economic Planning Unit.

Data Analysis

The analysis follows a structured econometric approach. First, the descriptive statistics summarize the data by calculating measures like the mean, median, maximum, and minimum values for each variable. These statistics help identify the general characteristics of the data and highlight any potential anomalies or outliers that could influence the model’s outcomes.

The next step involves conducting unit root tests to assess the stationarity of the time series data used in this study. The Augmented Dickey-Fuller (ADF) test is employed to test for unit roots and assess whether the variables are stationary or need differencing to achieve stationarity. The null hypothesis states that the series contains a unit root (non-stationary), and if rejected, it confirms that the data is stationary.

Finally, the Auto-regressive Distributed Lag (ARDL) Modelling Approach were employed to estimate the long run and short run dynamics of the model. The ARDL method is selected because it offers flexibility with variables that are integrated at different levels, such as I(0) or I(1). Additionally, it is well-suited for small sample size as well as it allows for analyzing both short-run and long-run model.

The ARDL approach begins with a bounds test for cointegration to determine whether a long-run relationship exists among the variables. The test compares the F-statistic with critical values; if the F-statistic exceeds the upper bound, the null hypothesis of no cointegration is rejected, indicating a long-term relationship. The general ARDL model is expressed as:

In this model, ∆ represents the first difference operator, while ρ indicates the optimal lag length. The coefficients β1 to β6 capture the short-run dynamics of the variables, whereas σ1 to σ6 reflect the long-run relationships. Given that the study uses quarterly data, a maximum of four lags is applied, determined by the Akaike Information Criterion (AIC). The following step involves estimating the short-run model, as detailed in the equations below.

Here, λ represents the speed of adjustment parameter, which should be statistically significant and negative, confirming the presence of cointegration among the variables. The Error Correction Term (ECT), which is lagged by one period, indicates how quickly FDI returns to equilibrium after being affected by changes in the independent variables.

In order to ensure the robustness of the results, several diagnostic tests were conducted. First, the Jarque-Bera test is used to check for the normality of the residuals, ensuring that the error terms follow a normal distribution. Next, the Breusch-Godfrey LM test is applied to detect the presence of serial correlation in the residuals. Additionally, the ARCH test is employed to assess for heteroskedasticity, ensuring that the variance of the residuals remains constant across observations. Finally, the stability of the model is evaluated using the CUSUM and CUSUMSQ tests, which check for structural stability over time. If the model passes these tests, it confirms that the results are robust, reliable, and suitable for drawing meaningful conclusions.

FINDINGS AND DISCUSSION

This section provides a comprehensive analysis of the impact of political instability on FDI inflows in Malaysia. It begins by presenting descriptive statistics to outline the characteristics of the data. Unit root tests are then conducted to assess the stationarity of the variables, ensuring the data is suitable for further analysis. Cointegration tests are used to determine if a long-term equilibrium relationship exists between political instability and FDI. The Autoregressive Distributed Lag (ARDL) approach is applied to estimate both long-run effects and the speed of adjustment of the model. Finally, diagnostic tests are performed to ensure the robustness and stability of the models.

Descriptive Statistics

The descriptive analysis reported in Table 1 provided a broad overview of the variables under study. The Foreign Direct Investment (FDI) inflows varied substantially, with a minimum of RM 36,454.34 million and a maximum of RM 92,248.00 million, reflecting the dynamic nature of Malaysia’s investment landscape. Gross Domestic Product (GDP) ranged from RM 306,832.8 million to RM 476,725.6 million, indicating strong economic activity and growth. The interest rates (IR), represented by average lending rates, varied minimally, showing a stable financial policy environment. Exchange rates (EX) fluctuated between 3.78 MYR/USD and 4.70 MYR/USD, demonstrating the currency’s responsiveness to both domestic economic conditions and global financial movements. Trade Openness (TO), measured as the trade-to-GDP ratio, also showed significant variation, highlighting Malaysia’s active engagement in international trade.

Table 1: Descriptive Statistics

Unit Root Test

Unit root tests are vital for validating that the analysis is based on stationary data, thus preventing any spurious results. The results from the Augmented Dickey-Fuller (ADF) test, detailed in Table 2, indicate that the variables exhibit mixed orders of integration whereby there are some variables that are stationary at levels, I(0), while others achieve stationarity at first difference, I(1). This mixture in the order of integration underscores the suitability of the Autoregressive Distributed Lag (ARDL) model for the subsequent analysis, as it effectively handles variables integrated at different levels, ensuring a robust examination of the relationships involved.

Table 2: Augmented Dickey-Fuller (ADF) Unit Root

Notes: The optimal lag is chosen based on the Akaike Information Criterion. The value in parentheses represents the p-value of the test. ***, ** and * indicate the significance level at 1%, 5% and 10% respectively.

Bound Test for Cointegration

The Bounds Test for cointegration is used to determine whether long-run relationships exist among the variables. The result of the F-statistic, 11.1920 as reported in Table 3, exceeds the upper critical bounds at the 1% significance level, confirming a long-term equilibrium relationship among the variables. This outcome indicates that long-run relationships are present, suggesting that political instability, along with GDP, interest rates, exchange rates, and trade openness, jointly determine FDI inflows in Malaysia.

Table 3: Bound Test for Cointegration

Notes: The optimal lag is chosen based on the Akaike Information Criterion with a maximum of 4 lags. *** indicates the null hypothesis of no cointegration among the variables is rejected at 1% significance level.

The ARDL long-run model shows that political instability has a significant and negative effect on FDI, with a 0.27% decrease in FDI for each unit increase in political instability. This finding aligns with the existing literature, highlighting the deterrent effect of political risks on foreign investment.

ARDL Model

The Autoregressive Distributed Lag (ARDL) model was applied to explore the dynamics between political instability, GDP, interest rates, exchange rates, trade openness, and FDI inflows in Malaysia. This approach is particularly suitable for our dataset as it allows for the inclusion of variables with different levels of integration and provides estimates of both long run and short run relationships simultaneously.

As shown in Table 4, the main variable which is the political instability (POL), showed a significant negative impact on FDI, with a 0.27 percent decrease in FDI as the result of the political instability. This finding aligns with the existing literature, highlighting the deterrent effect of political risks on foreign investment (Nazeer & Masih, 2017; Bhatti, 2023). Interestingly, although political instability negatively affects FDI inflows, the impact is relatively modest, indicating that investors may perceive the economic fundamentals of Malaysia as strong enough to outweigh political risks. This resilience suggests that the overall investment climate continues to attract foreign investors despite political uncertainties.

Additionally, economic growth as represented by GDP demonstrated a positive and statistically significant relationship with FDI, suggesting that economic growth is a crucial driver of foreign investment in Malaysia. Specifically, the findings reveal that a 1 percent increase in economic growth corresponds to a 1.6 percent increase in FDI inflows, highlighting the pivotal role of robust economic performance in attracting foreign investment. This relationship highlights the attraction of vibrant economic conditions to foreign investors looking for robust market potentials and growth opportunities (Sarker & Khan, 2020; Sajilan et al., 2019).

Besides that, interest rates demonstrated a negative effect on FDI, illustrating that higher borrowing costs deter foreign investment. Specifically, a 1 percent increase in interest rates is expected to reduce FDI inflows by 0.44 percentage points. This relationship highlights how increased borrowing costs can discourage foreign investment by elevating the cost of capital and diminishing potential returns on investments (Fazira & Cahyadin, 2018). This dynamic is especially significant in environments where access to financing is crucial for business operations and expansion.

Table 4: ARDL Model

Notes: The lag length is chosen based on the Akaike Information Criterion (AIC) with a maximum of 4 lags. Figures in the parentheses represent the p-value of the test. *** indicate the significance at 1%, significance level.

In contrast, the exchange rate did not show a statistically significant impact on FDI in the long-run model. This suggests that while exchange rate fluctuations may affect investor decisions in the short term, their long-term investment strategies are likely influenced more by other economic factors, or mitigated by hedging strategies that buffer against potential losses due to currency fluctuations. Similarly, trade openness showed a positive but statistically insignificant relationship with FDI, suggesting that while Malaysia’s open trade policies and liberal economic stance are generally favorable, they may not be the primary drivers of FDI. This could indicate that other factors, possibly including geopolitical considerations or global economic trends, play more significant roles in influencing FDI levels.

The short-run dynamics of the ARDL model further reveal significant insights into how FDI inflows in Malaysia adjusts to changes. The speed of adjustment coefficient was notably significant and negative, which underscores the efficiency with which FDI responds to deviations from long-term equilibrium. Specifically, the results indicate that any short-term disequilibrium in FDI is swiftly corrected, typically within less than a quarter. This rapid adjustment suggests that while FDI in Malaysia may experience fluctuations due to economic or political shocks, it tends to stabilize quickly, realigning with the established long-term trends. This resilience in the FDI adjustment process highlights the reactive nature of investments to immediate changes and the robustness of Malaysia’s economic environment in maintaining steady investment flows despite temporary disturbances.

To ensure the robustness and reliability of the regression results, several diagnostic tests were conducted. The Jarque-Bera test was employed to assess the normality of the residuals and confirmed that the error terms were normally distributed. Additionally, the Breusch-Godfrey LM test for serial correlation and the ARCH test for heteroskedasticity were conducted, with results showing no evidence of serial correlation or heteroskedasticity within the model. This suggests that the model does not suffer from common problems that could lead to inefficient or biased estimates.

Furthermore, the stability of the ARDL model was verified using the CUSUM and CUSUMSQ tests, as depicted in Figure 1. These tests confirmed that the coefficients remained stable throughout the sample period, indicating that the model’s parameters did not suffer from structural breaks or instabilities over time. These diagnostic checks collectively support the validity of the ARDL model applied in this analysis, affirming that the findings are not only statistically sound but also robust, enhancing the credibility and reliability of the conclusions drawn from the study.

Figure 1: CUSUM and CUSUMSQ test

CONCLUSION

This study provides a comprehensive analysis of the impact of political instability, along with other economic variables, on Foreign Direct Investment (FDI) in Malaysia. The findings reinforce the significant negative influence of political instability on FDI, highlighting the essential need for political stability to attract and maintain foreign investment. Positive economic growth, as indicated by GDP, was shown to significantly boost FDI, demonstrating that economic vitality is a major attractor for foreign capital. Conversely, higher interest rates were found to deter FDI, emphasizing the importance of maintaining competitive borrowing costs to encourage investment. The ARDL model’s results also revealed that exchange rates and trade openness did not significantly impact FDI in the long run, suggesting that these factors might be overshadowed by more dominant economic forces or effectively managed through strategic financial practices such as hedging.

Based on the findings, several policy recommendations are proposed to enhance Malaysia’s attractiveness to Foreign Direct Investment (FDI). First, ensuring political stability should be a top priority for the Malaysian government to reduce uncertainty and risk for foreign investors. Political instability has been shown to significantly deter FDI inflows, as uncertainty in governance makes long-term investment planning risky for foreign investors. Therefore, measures to strengthen political institutions, reduce political volatility, and improve governance transparency can help boost investor confidence.

Additionally, economic policies should focus on sustaining strong GDP growth, as it is a key driver of FDI. Policies aimed at enhancing productivity, investments in infrastructure, human capital, and innovation can create a more conducive environment for economic expansion and attract foreign capital. Besides that, interest rate policies should also be managed carefully, as higher borrowing costs have been found to negatively impact FDI. Keeping interest rates at competitive levels while maintaining macroeconomic stability can make Malaysia a more attractive destination for foreign investors.

Furthermore, while trade openness did not show a direct long-term impact, maintaining an open and competitive trade environment remains crucial. Policies that simplify trade processes and reduce barriers can potentially make Malaysia more competitive on the global stage. Similarly, although exchange rates did not significantly impact FDI, maintaining a stable exchange rate environment is important to minimize the risk for foreign investors and businesses engaged in international trade.

By implementing these policies, Malaysia can bolster its economic resilience and attractiveness to foreign investors, ensuring that it remains a competitive player in the global market and continues to benefit from the growth and employment opportunities that FDI brings.

To further enhance our understanding of Foreign Direct Investment (FDI) dynamics in Malaysia, future research could explore the sectoral impact of FDI to understand how political instability affects different industries. Moreover, more sophisticated measures of political risk could be employed to capture varying degrees of instability. Finally, comparative studies with other Southeast Asian countries could also yield valuable comparative insights, helping to contextualize Malaysia’s unique challenges and opportunities within the regional economic landscape.

ACKNOWLEDGEMENT

The authors would like to express their sincere gratitude to the Kedah State Research Committee, UiTM Kedah Branch, for the funding provided under the Tabung Penyelidikan Am. This support was crucial in facilitating the research and ensuring the successful publication of this article.

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