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1 

 

 

    ECONOMIC & SOCIAL REVIEW  

                                                               AESR VOL 11 NO 1 (2023) P-ISSN 2576-1269  E-ISSN 2576-1277 
                                                  

   Available online at https://www.cribfb.com 

                                                                                                                                    Journal homepage: https://www.cribfb.com/journal/index.php/aesr 
                                                                                                                                                                                             Published by CRIBFB, USA 

DETERMINANTS OF GDP PER CAPITA IN BANGLADESH: AN 

EMPIRICAL STUDY         

 
 Md. Idris Ali (a)    Md. Faisal-E-Alam  (b)1  
 

(a) Assistant Professor (Statistics), Department of Business Studies, North Bengal International University, Rajshahi, Bangladesh; E-mail: 

idris.stat@gmail.com 
(b) Assistant Professor, Department of Management Studies, Begum Rokeya University, Rangpur, Bangladesh; E-mail: faisal14.ru@gmail.com 

 

 
A R T I C L E I N F O 

 
 

Article History: 
 

Received: 8th August 2023 

Revised: 26th October 2023 

Accepted: 27th October 2023 

Published: 28th October 2023 

 
Keywords: 

GDP per capita, Inflation Rate, 

Exchange Rate, Total Reserves 

(includes gold and USD) 

 
      JEL Classification Codes:  

 

      E31, F31, O47 

 
A B S T R A C T 

 
When making cross-country comparisons regarding the well-being and economic conditions of a 

population, GDP per capita is the most commonly used indicator. Hence, various economic indicators 

can affect GDP per capita. This study investigates the impact of inflation, exchange rate, and total 

reserves (including gold and USD) on GDP per capita in Bangladesh. The study employs a quantitative 

approach and follows a longitudinal research design. Time series data from 2012 to 2021 is collected 

using a stratified random sampling technique from the World Development Indicators provided by the 

World Bank. A range of statistical tests, such as Normality Test, Multivariate Outlier Analysis 

(Mahalanobis Distance), Multicollinearity Assessment (Tolerance and VIF), Goodness-of-Fit (GoF) 

Test, ANOVA Test, and Multiple Regression Analysis, were performed using SPSS v.22. The results 

reveal that exchange rate has a significant influence on GDP per capita, making it crucial factor for 

economic development, resilience, and export competitiveness. Total reserves were found to have 

minimal relation with GDP per capita. In contrast, inflation rate, although adversely impacting GDP 

per capita, remains important for maintaining overall economic stability. Thus, the findings of this study 

suggest that effective currency management is paramount for economic development. 

 
 

© 2023 by the authors. Licensee CRIBFB, USA. This article is an open access article  distributed 
under the terms and conditions of the Creative Commons Attribution (CC BY) license 
(http://creativecommons.org/licenses/by/4.0/). 

                                                                                   

 

INTRODUCTION 

Gross Domestic Product (GDP) measures a nation's total monetary value of goods and services produced within its borders 

in a specific time frame. Bangladesh has been experiencing economic growth, and its per capita income has been steadily 

increasing over the years (Ferdous et al., 2019). The GDP per capita serves as a key indicator of a country's economic health, 

providing insight into the average income and living standards of its citizens (Dynan & Sheiner, 2018). GDP per capita has 

a greater impact on cross-country happiness variation than the Human Development Index (Dipietro & Anoruo, 2006). It is 

a metric commonly utilized by scholars and policymakers to formulate strategies in both the public and private sectors 

(Voumik & Smrity, 2020). For a developing nation like Bangladesh, this metric takes on even greater significance, as it 

reflects the progress and prosperity of a population of over 160 million people (Huque & Khan, 2017). Numerous factors 

influence GDP per capita (Formánek, 2019), among which inflation, exchange rate (Semuel & Nurina, 2014), and total 

reserves play pivotal roles.   

Bangladesh is a democratic country, but the notion that all democratic countries have a high GDP per capita is not 

universally true. For instance, while Qatar ranks high in GDP per capita, it does not show a strong democratic system (Ilter, 

2017). The economy of Bangladesh, primarily based on agriculture (Islam et al., 2022), has evolved into a more diversified 

landscape with significant contributions from the manufacturing and service sectors (Raihan & Khan, 2020). This 

transformation has been characterized by impressive GDP growth rates and increased foreign direct investment (Abubakar, 

2023). Despite these positive developments, Bangladesh faces several economic challenges (Sawada et al., 2018). Like 

                                                      
1Corresponding author: ORCID ID: 0000-0002-7341-7945 

© 2023 by the authors. Hosting by CRIBFB. Peer review under responsibility of CRIBFB, USA.  
https://doi.org/10.46281/aesr.v11i1.2106 

 

To cite this article: Ali, M. I., & Faisal-E-Alam, M. (2023). DETERMINANTS OF GDP PER CAPITA IN BANGLADESH: AN EMPIRICAL STUDY. 
American Economic & Social Review, 11(1), 1-7. https://doi.org/10.46281/aesr.v11i1.2106 

http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)
https://doi.org/10.46281/aesr.v11i1.2106
https://orcid.org/0009-0000-4771-4738
https://orcid.org/0000-0002-7341-7945


Ali & Faisal-E-Alam, American Economic & Social Review 11(1) (2023), 1-7

  

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recurring inflation concerns, exchange rate volatility, the need to maintain adequate reserves, and the necessity for well-

informed policy decisions to address these issues and promote sustainable economic growth. The quest to understand how 

these critical economic factors interrelate and influence a nation's GDP per capita has fueled extensive academic 

investigation. Therefore, this study aims to explore the impact of these economic variables on GDP per capita in Bangladesh.  

GDP per capita is a critical tool for the government to form tax policies, social welfare programs, and infrastructure 

development initiatives (Teshome, 2006). Also, the factors of Human Development Index (HDI), such as life expectancy, 

educational attainment, and decent living standards within a country, are interconnected with its economic growth, which is 

evident in GDP per capita (Elistia & Syahzuni, 2018). Understanding how inflation, exchange rate, and total reserves affect 

GDP per capita in Bangladesh can inform decisions on monetary and fiscal measures to control inflation, stabilize exchange 

rate, and maintain adequate reserves. Moreover, this study may aid investors and businesses in making informed choices in 

a constantly evolving economic environment. Furthermore, it can contribute to the academic literature by adding knowledge 

about the specific context of Bangladesh, which may also have implications for other emerging economies. 

The remaining part of this study first covers a detailed literature review, highlighting existing studies in the field. 

Then, the materials and methods section is explained. The results section presents the study's findings, while the discussions 

section determines their implications for Bangladesh's economic development and policymaking. Finally, the conclusions 

section contains the key findings, limitations, and potential future research directions in this context.  

 

LITERATURE REVIEW 

In the evolving realm of economic theory and practice, the effect of economic factors on GDP per capita stands as a focal 

point of inquiry, as shown distinctly in the following reviews. 

A long-standing debate in economics revolves around determining whether changes in inflation are primarily 

driven by demand-side factors resulting from increased economic activity or by supply-side factors arising from increased 

costs. Milton Friedman, in 1963, penned the famous phrase, "Inflation is, in every case, a monetary phenomenon." In simple 

terms, inflation can have both positive and negative impacts on GDP per capita. When inflation is moderate and controlled, 

it can stimulate economic growth by encouraging spending and investment. However, if inflation becomes too high and 

unpredictable, it can erode the purchasing power of individuals and lead to economic instability. The inflation rate and GDP 

per capita growth rate are co-integrated (Feyera, 2015). But the study did not provide specific finding related to the impact 

of inflation rate on GDP per capita. Barro (1995) found that higher inflation rates are associated with lower growth rates of 

real per capita GDP and a decrease in the ratio of investment to GDP. Gillman & Kejak (2011) argued that inflation 

negatively affects output growth, investment, and the real interest rate in the long run. The interaction between inflation rate 

and GDP per capita is a complex area of study that seeks to comprehend how changes in prices impact the financial security 

of a nation's people and the strength of its economy. 

In the domain of open economies, the optimal choice of an exchange rate system has also been a subject of debate. 

Modern analysts have argued in favor of flexible exchange rate over fixed ones, citing that flexible rate offers better 

protection against foreign economic shocks (Islam & Biswas, 2009). However, the impact of the exchange rate on GDP per 

capita refers to how changes in a country's exchange rate can affect its GDP per capita. The exchange rate is the rate at 

which one country's currency can be exchanged for another, and it plays a vital role in international trade of a nation. 

Exchange rate can impact a country's GDP per capita through its effect on trade (Broda, 2004). A strong domestic currency 

can make a country's exports more expensive, potentially reducing exports and affecting economic growth. Conversely, a 

weaker currency can boost exports (Morrissey, 2005) and contribute to GDP per capita growth. A weaker currency may 

also make imports more expensive, encouraging domestic consumers to purchase locally produced goods, which can further 

stimulate economic growth. However, it can also lead to inflation if not managed effectively (Singh, 2013). Exchange rate 

significantly impacts a nation's trade balance, which, in turn, has a profound effect on both exports and imports, ultimately 

shaping a country's economic progress. 

A nation's total reserves have a significant impact on its economic standing, and the international financial market 

assesses the nation's creditworthiness and the effectiveness of its monetary policies based on these reserves (Salan et al., 

2023). Adequate total reserves can help stabilize a country's exchange rate. A stable exchange rate, in turn, provides a 

conducive environment for international trade and investment. A stable currency encourages foreign investors to invest in 

the country, which can lead to economic growth. Reserve accumulation depreciates the real exchange rate and attracts FDI, 

which endogenously promotes productivity growth (Matsumoto, 2018). Moreover, reserve accumulation is positively 

associated with domestic private investment in the long-run (Mahraddika, 2019). One study found a positive correlation 

between the level of reserves and GDP per capita, suggesting that higher level of reserves can contribute to economic growth 

(Bentum-Ennin, 2014). The demand for international reserves by many developing countries has been dominated by 

precautionary motives against possible domestic and external uncertainties, crises, sudden stops in capital inflows, and 

macroeconomic fragilities (Ayhan & Turgutlu, 2015). In light of these findings, maintaining the total reserves is not only 

essential for economic stability but also plays an essential role in driving economic advancement. 

This section reviews the effect of each individual independent variable on the dependent variable as a predictor of 

GDP per capita in Bangladesh. It is also worth noting that no previous study has observed these relationships simultaneously. 

Consequently, this study formulates the following three alternative hypotheses to determine and establish the aforesaid 

relationships:  

H1: There is a significant positive connection between inflation rate and GDP per capita. 

H2: Exchange rate has a significant impact on GDP per capita.  

H3: Total reserves, including gold and USD, are positively correlated with GDP per capita. 



Ali & Faisal-E-Alam, American Economic & Social Review 11(1) (2023), 1-7

  

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MATERIALS AND METHODS 
Research Approach and Design 

This study employs a quantitative research approach. A quantitative approach is chosen for its ability to systematically 

analyze numerical data and draw statistical inferences about the relationships between variables. The study design also 

incorporates the longitudinal framework.  

Data Collection 

This study followed a stratified random sampling method to select the dataset. The dataset spans a ten-year period from 

2012 to 2021. It comprises economic variables sourced from the World Development Indicators, a reliable data repository 

provided by the World Bank. The selected variables include inflation rate (IR), exchange rate (ER), total reserves including 

gold and current USD (TR), and GDP per capita (GDPC). 

Data Analysis Tools 

In the data analysis phase, a series of statistical tests were applied to the dataset using SPSS v.22. A Normal Probability Plot 

(P-P plot) was used to evaluate the normal distribution of data, a critical assumption for parametric tests. Multivariate outlier 

detection through Mahalanobis Distance assessed the presence of multivariate outliers, a prerequisite for addressing 

potential anomalies in the dataset. A Multicollinearity Test with Tolerance and Variance Inflation Factor (VIF) determined 

the independence of predictor variables. Prior to presenting the Multiple Linear Regression model, a Goodness-of-Fit (GoF) 

Test and ANOVA Test were conducted. These critical components offered a complete view of the model's performance and 

statistical significance. The core analysis involved Multiple Linear Regression, which modeled the relationship between 

independent variables (IR, ER, and TR) and the dependent variable (GDPC). This analysis provided coefficients with 

statistical validity for each predictor variable. The outcomes of these statistical tests are showcased in graphical and tabular 

formats. 

Inclusion and Exclusion Criteria 

Data collected from 2012 to 2021 was included to capture a substantial time frame. Selected variables encompassed IR, ER, 

TR, and GDPC due to their economic significance. However, variables unrelated to economic factors, such as social or 

demographic factors, were also excluded to keep the study centered on economic aspects. 

Ethical Considerations   
Ethical issues in this study primarily involve data collection and usage. The researchers have adhered to ethical guidelines 

by sourcing data from reliable and reputable sources, such as the World Development Indicators provided by the World 

Bank. Privacy and confidentiality have been maintained, as no individual-level data or personally identifiable information 

was used.  

 

RESULTS 

Normal Probability Plot Test  

The normal probability plot displaying a fairly straight diagonal line is a strong indicator that the sample data follows a 

normal distribution. This means the data is symmetrically distributed around the mean, providing a solid foundation for 

conducting analyses and making valid statistical inferences that rely on the assumption of normality (see figure 1). 

 

Figure 1. Normal Probability Plot of Regression Standardized Residual 
Source: Authors’ Calculation 

Multivariate Outlier Detection 

Mahalanobis Distance is a common metric for detecting multivariate outliers. For this study, the maximum Mahalanobis 

Distance observed is 5.879. This value is less than the critical value of 16.27 for Mahalanobis Distance with 3 degrees of 

freedom (df), as stated by Mahalanobis (1936). The maximum distance is lower than the critical value suggests that the data 



Ali & Faisal-E-Alam, American Economic & Social Review 11(1) (2023), 1-7

  

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points do not uncover extreme multivariate relationships. As a result, the dataset can be considered relatively free from 

multivariate outliers based on this analysis (see table 1). 

 

Table 1. Residuals Statistics for outlier detection by using Mahalanobis Distance 

 
 Minimum Maximum Mean Std. Deviation N 

Mahal. Distance 0.881 5.879 2.700 1.691 10 

Source: Authors’ Calculation 

Multicollinearity Test 

Table 2 provides collinearity statistics, specifically Tolerance and Variance Inflation Factor (VIF), which are crucial 

indicators for assessing multicollinearity in the dataset. Notably, the calculated values of Tolerance for all the independent 

variables are less than 1.00, and the corresponding VIF values are also less than 10. This outcome implies that there are no 

significant issues with multicollinearity. Tolerance values below 1.00 suggest that each independent variable contributes to 

the regression model independently, while VIF values under 10 further affirm that there is no excessive redundancy or 

correlation among the predictors (Chatterjee & Hadi, 2006). These findings provide assurance that the parameter estimates 

of regression model are reliable. In light of the absence of multicollinearity concerns, the dataset is well-suited for 

multivariate analysis. 

 

Table 2. Analysis of Multicollinearity Using Variance Inflation Factor (VIF) Statistics 

 
 Tolerance VIF 

Inflation Rate .441 2.267 

Exchange Rate (in USD) .544 1.837 

Total reserves (including gold and current USD) .458 2.186 

Source: Authors’ Calculation 

Goodness-of-Fit (GoF) Test  

The model summary table shows an overview of the regression model's performance. The coefficient of determination, R-

squared (R²), stands at 0.965, indicating that approximately 96.50% of the variance in GDP per capita is accounted for by 

the included independent variables, namely inflation rate, exchange rate, and total reserves (including gold and current 

USD). This high R-squared value underscores the strong explanatory power of the model, signifying that the selected 

predictors collectively provide an excellent fit for the variation in GDP per capita. Additionally, the adjusted R-square value, 

which adjusts for the number of predictors, remains notably high at 0.947, further confirming the model's goodness of fit. 

With a low standard error of the estimate, which is 129.188, the model demonstrates a strong ability to predict GDP per 

capita (see table 3).  

 

Table 3. Model Summary 

 
R R Square Adjusted R Square Std. Error of the estimate 

0.982 0.965 0.947 129.188 

Source: Authors’ Calculation 

ANOVA Test 

On the basis of the results of the F test below, the value of the calculated F Statistic is 55.111, with a probability (F-Statistic) 

of 0.000, which is smaller than the significance level set at 5%. Therefore, the regression model, as a whole is deemed to be 

statistically significant. This highly significant F Statistic accentuates the model's effectiveness in explaining variation in 

the dependent variable and advocates the importance of the included independent variables in enhancing our understanding 

of the phenomenon under investigation. Consequently, the regression model can be considered a powerful tool for making 

inferences related to the specific analysis (see table 4).  

 

Table 4. Results of ANOVA  

 
Model Sum of Squares df Mean Square F Sig 

Regression 2759336.739 3 919778.913 55.111 0.000 

Residual 100136.861 6 16689.477   

Total 2859473.600 9    

Source: Authors’ Calculation 

Multiple Regression Analysis 

In the regression equation, each independent variable holds a distinct role in explaining the variation in GDP per capita. 

Each coefficient represents the estimated change in the dependent variable for a one-unit change in the corresponding 

independent variable, while keeping all other variables constant. For the variable IR, the coefficient is negative, at -74.851, 

and its associated p-value is 0.455, which is greater than the significance level of 0.05. This finding suggests that IR has a 

negative relationship with GDP per capita, which is statistically insignificant. Conversely, ER shows statistical significance 

at the 5% level. This indicates the substantial impact of ER on GDP per capita. The coefficient is extremely small for TR 



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(B = 0.00000003824, p<0.05), specifying that this particular independent variable has a very low impact on the dependent 

variable (see table 5). 

 

Table 5. Coefficients of Multiple Linear Regression 

 
Model Unstandardized Coefficients   

 B Std. Error t p 

(Constant) -3382.721 1810.742 -1.868 .111 

IR -74.851 93.756 -.798 .455 

ER 53.333 18.926 2.818 .030 

TR 3.824E-8 .000 6.228 .001 

Source: Authors’ Calculation 

 

DISCUSSIONS 

The study findings hold important implications for policymakers and stakeholders in Bangladesh. The first hypothesis is 

not supported by the outcomes of this study. Close attention to inflation patterns in Bangladesh is required (Hassan & 

Shakur, 2017). While this variable exhibits a negative connection with GDP per capita, it remains important to control 

inflation for managing economic fluctuations and achieving price stability. Several studies have also confirmed that inflation 

and GDP per capita are inversely related (Ilter, 2017; Ayyoub et al., 2011). The second hypothesis is accepted, validating a 

significant impact of the exchange rate on GDP per capita (Salan et al., 2023). Effective management of exchange rate also 

enhances a country's resilience against global economic challenges, such as currency crises or economic recessions. It 

provides a buffer that can be used to stabilize the economy during periods of uncertainty, protecting businesses and jobs. In 

addition to these benefits, a favorable exchange rate can boost the competitiveness of exports, especially in labor-intensive 

industries like textiles and garments in Bangladesh. This can generate an expansion of the export sector, creating a positive 

trade balance and contributing to GDP per capita growth. Such growth can also enhance the livelihoods of workers in those 

industries and potentially reduce income inequality. Further, a fixed exchange rate sends positive signals to foreign investors. 

This can result in increased foreign direct investment (FDI) inflows (Hossain, 2008), which are necessary for economic 

growth. Attracting foreign capital through FDI can lead to the creation of new industries, technological advancements, and 

employment opportunities, also driving GDP per capita growth (Shourave, 2020). The third hypothesis finds support in the 

presence of a notably weaker connection between total reserves and GDP per capita. Although, accumulating reserves does 

not necessarily represent a prerequisite or guarantee of economic growth (Polterovich & Popov, 2003). Because, total 

reserves are more related to a nation's capacity to manage its external financial obligations and maintain confidence in its 

currency (Qian & Steiner, 2017). Policymakers can use this information to create more effective economic strategies for 

sustainable improvements in GDP per capita, ultimately enhancing citizens' quality of life.  

 

CONCLUSIONS  

This study specifically identifies the role of exchange rate on variation in GDP per capita in case of Bangladesh. The results 

also illustrate a substantially weak link between total reserves and GDP per capita as well as an adverse link between 

inflation and GDP per capita. The considerations from this study illuminate the path to economic growth, stressing the 

significance of currency management, sensible investments, and the need for inflation control. Further, developing countries 

like Bangladesh should increase their development budgets while reducing non-developmental expenditures, as this strategy 

plays a significant role in controlling inflation, reducing unemployment, and enhancing economic growth. This study not 

only serves as a beacon for Bangladesh's policymakers but also contributes to the comprehensive dialogue on economic 

development. However, this study primarily employs economic factors, potentially overlooking social and demographic 

factors, such as transparency ranking and population growth that can significantly influence GDP per capita. Further, the 

exclusion of other relevant macroeconomic indicators, including the unemployment rate, gross national product, purchasing 

power parity, and poverty level, may restrict the breadth of analysis. To address these limitations, future research efforts 

could explore a wider range of variables that affect economic growth. Additionally, comparative studies involving multiple 

countries or regions could provide a broader perspective on the relationships observed here, further advancing our 

knowledge of economic development processes. 

 

 
Author Contributions: “Conceptualization, M.I.A. and M.F.A.; Methodology, M.I.A. and M.F.A.; Software, M.I.A. and M.F.A.; Validation, M.I.A. and 
M.F.A.; Formal Analysis, M.I.A. and M.F.A.; Investigation, M.I.A. and M.F.A.; Resources, M.I.A. and M.F.A.; Data Curation, M.I.A. and M.F.A.; Writing 

– Original Draft Preparation, M.I.A. and M.F.A.; Writing – Review & Editing, M.I.A. and M.F.A.; Visualization, M.I.A. and M.F.A.; Supervision, M.I.A. 

and M.F.A.; Project Administration, M.I.A. and M.F.A.; Funding Acquisition, M.I.A. and M.F.A. Authors have read and agreed to the published version 
of the manuscript. 

Institutional Review Board Statement: Ethical review and approval were waived for this study, due to that the research does not deal with vulnerable 

groups or sensitive issues. 
Funding: The authors received no direct funding for this research. 

Acknowledgement: Not applicable. 

Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. 
Data Availability Statement: The data presented in this study are available on request from the corresponding author. The data are not publicly available 

due to restrictions. 

Conflicts of Interest: The authors declare no conflict of interest. 

 



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