
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)11284-4
10.1016/j.heliyon.2024.e35253
e35253
Research Article
Capital and profitability: The moderating role of economic freedom
Abbas Faisal faisalabbaspcc@gmail.com
a
Ali Shoaib Shoaibali.fin@gmail.com
b⁎
Woo Kai Yin kywoo@hksyu.edu
c
Wong Wing-Keung wong@asia.edu.tw
def
a MY Business School, Faculty of Management Sciences, MY University, Islamabad, Pakistan
b Adnan Kassar School of Business, Lebanese American University, Beirut, Lebanon
c Department of Economics and Finance, Hong Kong Shue Yan University, Hong Kong
d Department of Finance, Fintech & Blockchain Research Center, and Big Data Research Center, Asia University, Taiwan
e Department of Medical Research, China Medical University Hospital, Taiwan
f Business, Economic and Public Policy Research Centre, Hong Kong Shue Yan University, Hong Kong
⁎ Corresponding author. Shoaibali.fin@gmail.com
26 7 2024
30 8 2024
26 7 2024
10 16 e352533 2 2024
22 7 2024
25 7 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Using the GMM framework, this paper examines the nexus between capital and profitability in the presence of economic freedom using annual data of US banks ranging from 2002 to 2022. consistent with both the financial stability and regulatory hypotheses, the present study's empirical findings reveal that economic freedom exerts a positive moderating influence on the relationship between bank capital ratio and profitability. The findings are heterogeneous across banks' specific characteristics and market conditions. Furthermore, the results are robust to alternative proxies of profitability. The study's finding is beneficial for policymakers and regulators as liberalization is not always adversely impact the economy; rather, it's a double-edged sword, and they must maintain that delicate balance. The conclusions of this study have meaningful implications for senior bankers and policymakers when formulating strategies for preserving bank value. Specifically, it highlights the importance of considering the interactive role of economic freedom in their decision-making process.

Keywords

Economic freedom
Capital
Profitability
==== Body
pmc1 Introduction

The bank is arguably the critical financial intermediary in an economy because it provides liquidity to the market and also serves as a producer of information (Diamond & Dybvig, 1983). They also play a key economic role by working as a financial intermediary and provide critical financial services that enable economic growth in the majority of countries. Several studies (M. [[1], [2], [3], [4]]) have linked the performance of banks with overall economic growth. Similarly, many researcher (S. [1,5,6]) argued that the stability and growth of banking sector determine the long term projection of the firms as well as the economy. Therefore, banks play an essential role in contemporary economies by providing the monetary framework required for expansion, modernization, and stability [7,8]. The integration of banks with key economic indicators is crucial for decision-makers and economists.

Economic freedom refers to the liberty granted to companies or individuals to participate in economic endeavors such as work, ownership, or consumption, resulting in overall economic well-being. Multiple studies have analyzed the impact of economic freedom on the overall financial and economic well-being of the economy. For instance, Chortareas et al. [9] report a positive association between efficiency and financial freedom. Additionally, the is more significant in freer/open political countries. On the contrary, using a large sample of developed economies Cubillas and González [10] explore the relationship between bank risk and financial freedom. Their result suggests that higher capital requirement decreases the adverse impact of financial liberalization on risk-taking. While examining the nexus between economic freedom and risk, Harkati et al. [11] report that economic freedom increases banks risk. However, the impact of economic freedom is considerably less on conventional banks compared to Islamic banks in Malaysia. In a similar vein, using a sample of MENA banks Ghosh [12] documents that economic freedom increases the volatility in banks profit, thus adding to banks' fragility. Furthermore, they report the asymmetric impact of economic freedom on banks' risk-taking and suggest that economic freedom and risk nexus vary with the market condition. Sufian [13] confirms the relationship between risk and economic freedom depends on the choice of the proxy of economic freedom and argues that business and monetary (financial) freedom positively affect the overall banks' (technical) efficiency. Using the data of ASEAN-5 banking economies, Sufian and Hassan [14] report the asymmetric impact of economic freedom and its sub-components on banks. The results of the above-cited studies are mixed and thus require further indepth analysis. However, there is limited literature specifically addressing the interaction between bank capitalization and profitability under varying degrees of economic freedom.

Although a great deal of research has been done on the effects of economic freedom and its various dimensions on the banking industry in various parts of the world, such as Asia [[13], [14], [15]], the MENA region [12,14,16,17], and the Arab world [18], there is a significant lack of research that specifically addresses the relationship between bank capitalization and profitability under differing levels of economic freedom in the United States. This study attempts to close this gap in the literature. Therefore, this study aims to address the following questions: How does economic freedom influence the relationship between bank capital and profitability? Does this relationship remain consistent across different bank characteristics (capitalization, liquidity) and economic conditions (normal and crisis)? With a nominal GDP of almost $25 trillion in 2023, or roughly 24 % of the entire global GDP, the US has the greatest economy in the world. This is driven by high consumer spending, innovative technology developments, significant trade and investment, a robust and active labor market, and an abundance of natural resources. The American economy is highly diversified, with important sectors including technology, healthcare, finance, manufacturing, and agriculture. The US also enjoys economic supremacy due to its huge and freely traded financial markets, substantial investments in research and education, and a stable political and judicial system.1 Similarly, the US banking industry is very complex, well-governed and highly regulated. Therefore, the study's findings would be more robust, generalisable and authentic.

Using a dynamic econometric method called GMM, this study examines yearly data for US banks by covering a 21-year period, ranging from 2002 to 2022. The primary objective is to have a deeper understanding of how economic freedom influences the connection between capital and profit. The interaction between capital and economic freedom determines the magnitude and direction of their impact on the relationship. Our results show the capital adversely affect the profitability of US banks. However, the relationship becomes positive when economic freedom is present, meaning that economic freedom helps reduce the negative impact of capital on profitability. Our results are robust to various measures of capital ratio. The study results for undercapitalized, high and low liquidity support the baseline results. However, we find slight differences among well-capitalized banks. Furthermore, we didn't find any significant difference on the impact of economic freedom on the capital-profitability nexus during normal or crisis period. Our documented results remain consistent for alternative proxies of capital and profitability, which further strengthen our claim. The diversity of outcomes has ramifications for banking experts, analysts, managers, and policymakers aiming to improve the robust mechanisms of financial systems. The study's finding is beneficial for policymakers and regulators as liberalization is not always beneficial for the economy as its a double-edged sword, and they must maintain that delicate balance. Additionally, the research suggests that both economic freedom and capital are important factors in U.S. bank profitability, but the relationship between them is not clear. The study shows that both factors have a negative impact on profitability when considered separately, but when considered together there is a positive and statistically significant interaction effect on profitability. This suggests that for banks in the United States, both economic freedom and sufficient capital are critical to achieving profitability. Lastly, The heterogeneity of findings across various sub-samples has implications for bank managers and policymakers as its not 'one-size-fits-all' phenomenon rather, it vary based on the banks' specific characteristics.

This research advances current understanding of economic freedom, capital, and bank profitability in several ways. First, it becomes clear that the relationship between capital and bank profitability is nuanced and depends on economic freedom, an aspect not examined in previous studies. Notably, this study is the first to undertake a moderation analysis, introducing economic freedom as a moderator in the relationship between bank capital and profitability. Secondly, our analysis uncovers the unequal influence of economic freedom on the interplay between capital and profitability, especially during crises and normal periods, a dimension that has not been investigated in prior literature. Third, the study adds to what's already been written by looking at how economic freedom affects the link between bank capital and profitability in different ways, taking into account aspects like capitalization and liquidity. Furthermore, it brings forth a novel perspective by revealing the asymmetric nature of the relationship between capital and profitability in the presence of economic freedom across different bank characteristics; the said aspect is unexplored in the banking literature yet.

The layout of this study is organized as follows: The subsequent section presents the literature review, succeeded by the presentation of data, sample, and econometric model in the third section. The fourth section encompasses the findings and discussion, while the study concludes in the final section.

2 Literature review

The literature on the nexus between capital, economic freedom, and banks' profitability is abundant but and scant in the context of the US banking sector. However, we have examined the relevant evidence from the previously conducted studies. For example, Hakimi, Hamdi, and Khemiri [19] highlight how economic independence modifies the relationship between bank profitability and diversification in the MENA region. Jones, Temouri, Kirollos, and Du [20] argued that the effects of property rights and economic freedom played a crucial role in tax adjustment. Wu, Yang, Wu, and Chen [21] showed that interest rate liberalization is an important indicator of the impact on financing procurement and financing efficiency of banks in China. Similarly, Faisal et al. (2024) examined the various components of economic freedom, including open markets, regulatory efficiency, laws, and government size, on the risk-taking behavior of Japanese banks and suggested practical implications. Additionally, they find direct impact of economic freedom on financial institutions stability and risk taking. Doan [22] examined the concepts of economic openness, ownership, and financial fragility using data from Vietnam and conclude that ownership plays a significant role in the relationship between economic freedom and financial fragility, which is a noteworthy finding for policymakers.

The concept of financial liberalization is fundamental to the understanding of economic activities and economic and financial performance. The theory of financial liberalization posits that the removal of constraints on financial institutions and markets leads to enhanced economic efficiency and growth, which in turn affects the financial institutions themselves. Consequently, this theory is highly pertinent to the performance of financial institutions in numerous respects. Financial liberalization is believed to enhance resource allocation by enabling capital to move more unrestrictedly towards its most efficient use. When interest rates are determined by market forces rather than being artificially set, savings can be directed towards investments that generate the highest returns, so improving overall economic efficiency [23]. Moreover, the elimination of limitations on financial institutions can foster competition, so stimulating greater ingenuity in the development of financial products and services. By incentivizing financial organizations to embrace more streamlined methodologies and provide enhanced offerings to consumers, this can enhance the performance of such institutions [24].

Financial liberalization enables organizations to expand their investment portfolios and enhance their risk management capabilities. Financial institutions can mitigate the risk of financial crises by diversifying their investments across a wider array of financial products and marketplaces [25]. Empirical evidence suggests a correlation between financial liberalization and increased rates of economic growth. Financial liberalization has the potential to enhance investment and economic development by enhancing the efficiency of financial intermediation and expanding access to credit [26]. Financial liberalization has the potential to enhance growth and efficiency; however, it can also pose risks to financial stability if not managed effectively. The unanticipated influx of capital can give rise to asset bubbles, while the lifting of restrictions on capital flows can increase the vulnerability of economies to external shocks [27]. A robust policy and regulatory framework is crucial for the successful implementation of financial liberalization. Efficient regulation can mitigate the risks associated with liberalization, ensuring that financial institutions operate securely and contribute to economic stability [28].

Several studies [[29], [30], [31], [32], [33], [34]] favors the positive relationship between bank capital and profitability. The positive association between capital and profitability is consistent with the risk absorption hypothesis, which posits that greater capital acts as a buffer against the shock to the value of assets. Moreover, incentive-based theory argue that higher capital increases the monitoring incentive of the relationship with borrowers [35], or adversely affect their excessive risk-taking behavior refer to the 'moral hazard hypothesis', which ultimately increases the bank's profitability.

However, the studies of ([[36], [37], [38]]; [39]; [[40], [41], [42]]) support the negative impact of capital on banks' profitability. The 'regulatory hypothesis' states that the link between capital and risk is positive, which indicates that regulators push banks to grow their capital in accordance with the amount of risk-taking. [36], where higher risk-taking evaporates the banks' profitability [[43], [44], [45]].

The puzzle between capital and profitability varies across various macroeconomic factors, like market structure [46,47], income level [47], regions [[48], [49], [50], [51], [52], [53]], regulatory environment [54,55]. In addition, numerous academics have emphasized that economic freedom (Institutions, humans, wealth, and products to move about freely and not be subjected to coercion or other restrictions that aren't strictly essential to safeguard and preserve liberty itself)2 is one of the fundamental factors that can affect the way banks perform [56]. Similarly, the following recent research [13,57,58] found that the performance of financial institutions, especially commercial banks, is directly related to the relaxation of economic activities. Chortareas et al. [9] studied that financial liberalization improves the cost efficiency of banks in European countries.

Sufian and Habibullah [15] find that economic and financial (monetary) freedom positively (negatively) influences the bank's profitability in Malaysia. The argument on the impact of relaxation in economic activities on financial organizations is furthered by Sufian and Hassan [59], who provide evidence that freedom in economic activities improves the profitability of banks. While investigating the MENA region Sufian [17] and Malaysian financial organizations Sufian and Habibullah [15] empirical evidence proved that economic freedom boosts profitability and improves efficiency. Using the data of 19 eurozone countries, Asteriou et al. [60] report a positive relationship between economic freedom and bank stability by using an alternative performance measure. On the contrary, Papanikolaou [61] finds that higher economic freedom promotes competition, resulting in a moral hazard problem that could undermine the banks' profitability. In a related context, evidence has recently been presented on the impact of economic freedom on economic well-being in South Asian economies (Ahmed, Mushtaq, Fahlevi, Aljuaid, & Saniuk, 2023).

Due to the importance of the idea of economic freedom, it is essential to uncover the association between capital and profitability in the presence of economic freedom and its components. Most of the above-mentioned studies have relied on non-regulatory capital ratios. There is little research on how changes in regulatory capital adequacy affect US bank profitability. We are unaware of any research examining how economic freedom moderates the link between capital and profitability. We propose the following hypothesis based on the above research and knowledge gaps.Hypothesis 1 For larger US banks, the link between capital and profitability is greatly moderated by economic freedom.

The previous research has shown that the companies differ in terms of their regions, market dynamics, capitalization and profitability. According to Abbas et al. [57], the impact of relaxation in investment, financial and trade activities vary between well, and under-capitalized banks. In similar notions, Sobarsyah et al. [62] argue that bank lending varies based on the capitalization of banks. While examining the impact of diversification on risk appetite, Abbas and Ali [63] find heterogeneous conclusions between high- and low-liquid US larger banks. The landmark study by Altunbas et al. [36] concludes that outcomes vary between savings banks and commercial banks while examining the link between risk and bank capital in Europe. In a manner that is analogous, Jokipii and Milne [64] contend that the link between bank capital and profitability changes depending on the amount of capitalization attained by the bank. Abbas, [65], [66] conducted a study using US banks' data and claimed that the empirical results vary depending on banks' liquidity and capitalization. In predicting the impact of economic factors, Chan and Karim [67] conclude that economic conditions significantly impact bank efficiency. Berger and Bouwman [68] found that economic factors influenced bank performance, notably during the crisis era. Larger bank capital ratios have been adversely impacted by the crisis, as shown by the research of [69]. There is little research on how changes in regulatory capital adequacy affect US bank profitability based on capitalization and liquidity. We are not aware of any study that has examined how economic freedom softens the link between capital and profitability for well and undercapitalized, high and low liquidity banks in the US. Based on the above research and knowledge gaps, we propose the following hypothesis.

Hypothesis 2 For larger US banks, the link between capital and profitability is greatly moderated by economic freedom across market conditions and bank characteristics (capitalization and liquidity).

3 Data and methodology

3.1 Data

For empirical analysis, we collect data from the FDIC for a specified period of time because it is mandatory for larger financial institutions that are insured to report their financial information for regulatory requirements. The sample consists of larger commercial banks as reported by FDIC on December 31, 2022. However, a criterion is set to select the sample under the following assumptions: 1) The bank must be in good standing with the FDIC as of the date of this research; 2) The bank's total consolidated assets must be greater than $300 million; and 3) There should be no gaps in the data stretching back more than a year. After cleaning the data based on the aforementioned conditions, our final data consist of 915 banks over the period of 2002–2022. the data related to macroeconomic variables and economic freedom is taken from St. Louis Federal Reserve "FRED" public database and the heritage foundation website,3 respectively. Moreover, to provide meticulous analysis we further classify the data based on risk-based capital and liquidity ratio. Following FDIC criteria, we define a bank as well(under) capitalized if the risk-based capital ratio is equal or greater ([70]) than 10 (8) %. If a particular bank's regulatory ratio is between 10 % and 8 %, they are considered adequately capitalized. Banks are divided into highly liquid and low liquid based on the mean value of the average liquidity. To conclude, we used the following proxies given in Table 1.Table 1 Measurements of proxies.

Table 1Variables	Measurements	
Profitability (ROA)	Net income divided by total assets [1,71]	
Profitability (ROE)	Net income scaled by total shareholder equity [47,72]	
Profitability (NIM)	Net interest income less net interest expenses divided by total assets [60]	
Capital ratio (CAP)	Total equity divided by total assets [47,63,73]	
Tier-I ratio (TCAP)	Tier-I equity divided by total assets [74]	
Risk-based capital ratio (RBCR)	Tier-I plus Tier-II divided by risk-weighted assets	
Tier-I risk-based ratio (TRBCR)	Tier-I equity divided by risk-weighted assets	
Economic freedom (EFD)	The Heritage Foundation [15,75]	
Liquidity (LIQ)	Liquid Assets divided by Total Assets [34,66]	
Loan ratio (Loans)	Net Loans divided by Total Assets [36]	
Credit risk (LLR)	Loan loss reserve divided by gross loans [76]	
Managerial efficiency (ME)	Total Wages divided by Total Assets [7]	
Size	Natural Log of Total Assets [66,72]	
Economic growth (EG)	Real gross domestic product [8,60,77]	
Financial development (FD)	Domestic credit to the private sector [1,48]	

3.2 Econometric model

For larger US banks, how the link between capital and profitability is moderated by economic freedom, we used the following econometric model.(1) Yi,t=α+β1Yi,t−1+β2Xi,t+β3EFDi,t+β4X*EFDi,t+β5Zi,t+εi,t

In Equation (1) Yi,t is bank profitability, which is a dependent variable, Yi,t−1 denotes its lagged value. In addition, i signify cross-sections (banks) and t represents the time (year). EFDi,t represents economic freedom and Xi,t is capital, which is independent variable, and Zi,t represents control variables.

Since we observe that Equation (1) includes lagged dependent variable as an independent indicator, the use of OLS can be biased due to the following econometric specifications: First, our pre-specification indicates that the independent variable Xi,t, is endogenous. Therefore, causality can exist between bank profits and economic activities of both sides, and the correlation between explanatory variables and errors-term specifications. Second, the availability of fixed effects due to commonalities between banks. The banks' fixed effects include the unknown factors that have their specific impact on the prediction, so we can express the error term in Equation (2) as:(2) ui,t=vi+ei,t

Third, the autocorrelation concerns may be amplified by the inclusion of the lagged dependent series Yi,t−1. Fourth, the dataset demonstrates a reduced temporal dimension and an increased number of cross-sections (N). To mitigate problems related to fixed effects, we performed fixed effects instrumental estimations employing the two-stage least squares (2SLS) approach. The study examined efficiency, financial aspects, and economic aspects as instruments. However, the initial outcomes of the 2SLS method revealed insufficiently strong instruments, which were considered inappropriate for the ultimate study. Consequently, we opted for the Arellano and Bond [78] in predicting economic activity on bank profits.(3) ΔYi,t=β1ΔYi,t−1+β2ΔXi,t+β3ΔZi,t+Δε

Equation (3) uses the difference GMM and solves the fixed effects problem of Equation (1).

Using transformation, the preceding equation is modified as follows:(4) Δyi,t=αΔyi,t−1+β2Δx′i,t+Δε

Equation (4) is the transformed version of Equation (3).

Due to the fact that it is not time-dependent, the equation's modification eliminates the fixed banks-specific component. With the use of equation (2) we can express:(5) ui,t=vi+ei,t

or(6) ui,t−ui,t−1=(vi−vi−1)+(ei,t−ei,t−1)=ei,t−ei,t−1

in Equations (5), (6), we utilize the first-differenced lagged dependent variable along with its historical data as an instrument. In accordance with the suggestion made by Arellano and Bond [78], we refrain from using a one-step procedure because it is prone to significant bias. Windmeijer [79] proposes the utilization of two-stage robust standard errors as an alternative to a basic one- or two-stage strategy. Considering this viewpoint, the two-stage estimator of the system is regarded as more effective and reliable [9,66,80].(7) lnYi,t=ϕYi,t−1+βX′i,t+(ηi+εi,t)

Equation (7) is our baseline model that utilizes a two-step system GMM approach to examine the hypotheses outlined above. The GMM is a reliable statistical methodology employed to estimate parameters in econometric models, particularly advantageous when conventional methods such as Ordinary Least Squares are influenced by endogeneity, resulting in biased results. The methodology entails the process of defining the model and selecting suitable instruments that are correlated with the endogenous variables but not connected with the error term. Instrument-based moment conditions are defined and sample moments are calculated. A selection is made for a weighting matrix, and the objective function of the Gaussian Mixture Model (GMM) is formulated and minimized in relation to the parameters. The approach modifies the weighting matrix iteratively to enhance the efficiency of the estimates. Following the estimate process, the validity of the instruments is assessed by the Sargan/Hansen J-test, while autocorrelation tests are performed to verify the consistency of the model. This approach enables the accurate and reliable estimation of parameters, even in intricate models that involve endogeneity problems. In addition, the system GMM is more consistent and appreciative than the difference GMM.

4 Empirical results

We begin our empirical review by evaluating the data collected in this study. The balanced panel contains 16065 annual observations for each variable used in the estimation. In our descriptive analysis, we provided the mean value along with the standard deviation for each proxy. We've displayed the 1st percentile and 99th percentile along with the skewness and kurtosis statistics. Table 2 presents descriptive statistics for the like mean, standard deviation, and skewness of the variables under consideration. However, the skewness and kurtosis values indicate no abnormality in the variables used in the estimation.Table 2 Descriptive statistics.

Table 2Variables	Obser	Mean	Std. Dev.	Mini	Maxi	p1	p99	Skew.	Kurt.	
Profitability (ROA)	16,065	0.009	0.005	−0.051	0.270	−0.001	0.020	−0.094	3.948	
Profitability (ROE)	16,065	0.092	0.055	−0.185	0.236	−0.009	0.203	0.078	2.629	
Profitability (NIM)	16,065	0.031	0.010	−0.012	0.051	0.001	0.046	−1.195	4.808	
Capital ratio (CAP)	16,065	0.102	0.018	0.065	0.173	0.078	0.136	0.490	2.133	
Tier-I ratio (TCAP)	16,065	0.094	0.015	0.050	0.151	0.073	0.121	0.433	2.116	
Risk-based capital ratio (RBCR)	16,065	0.141	0.027	0.024	0.275	0.108	0.192	0.599	2.360	
Tier-I risk-based ratio (TRBCR)	16,065	0.128	0.020	0.080	0.207	0.104	0.157	0.279	1.605	
Economic freedom (EF)	16,065	0.779	0.021	0.751	0.812	0.751	0.812	0.327	1.708	
Credit risk (LLR)	16,065	0.009	0.003	−0.003	0.020	0.004	0.018	0.746	3.065	
Liquidity (LIQ)	16,065	0.048	0.027	−0.054	0.156	0.018	0.095	0.673	2.180	
Size	16,065	0.136	0.010	0.123	0.155	0.123	0.154	0.516	2.278	
Managerial efficiency (ME)	16,065	3.008	1.773	0.808	6.852	0.808	6.852	0.895	2.816	
Loan ratio (Loans)	16,065	0.714	0.148	0.044	1.185	0.431	0.974	−0.139	2.351	
Economic growth (EG)	16,065	0.020	0.014	−0.025	0.038	−0.025	0.038	−1.919	6.945	
Financial development (FD)	16,065	2.239	0.122	1.925	2.444	1.925	2.444	−0.601	3.505	
This table provides key descriptive statistics for the proxies utilized in the empirical analysis. These include standard deviation, minimum, maximum, mean (average), upper and lower percentiles, as well as measures of skewness and kurtosis. (Source: authors calculation by using Stata).

We also analyzed the direction and correlation between explanatory variables used in econometric models by constructing correlation matrices. The correlation statistics output confirms that there is no higher correlation between desired proxies. Therefore, we can proceed to the economic procedure to test our study hypotheses. Table 3 contains the empirical evidence for the correlation between proxies.Table 3 Correlations statistics.

Table 3Variables	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	
(1) ROA	1															
(2) ROE	0.885*	1														
(3) NIM	0.467*	0.437*	1													
(4) CAP	0.062*	−0.235*	−0.044*	1												
(5) TCAP	0.081*	−0.163*	−0.042*	0.766*	1											
(6) TRBCR	0.044*	−0.141*	−0.096*	0.528*	0.683*	1										
(7) EFD	0.043*	0.135*	0.229*	−0.209*	−0.259*	−0.225*	1									
(8) LLR	−0.050*	−0.080*	0.257*	0.034*	0.098*	−0.112*	−0.001	1								
(9) LIQ	−0.074*	−0.095*	−0.020*	0.036*	0.113*	0.193*	−0.185*	0.095*	1							
(10) Size	−0.040*	−0.060*	−0.236*	0.134*	−0.081*	−0.137*	−0.225*	0.006	−0.064*	1						
(11) ME	−0.416*	−0.399*	0.050*	−0.076*	−0.092*	−0.027*	−0.001	0.027*	0.091*	−0.061*	1					
(12) Loans	0.034*	0.078*	0.136*	−0.084*	−0.055*	−0.470*	0.078*	0.157*	−0.151*	−0.038*	−0.019*	1				
(13) EG	0.166*	0.151*	−0.055*	0.018*	0.057*	0.048*	−0.312*	−0.138*	−0.061*	−0.024*	−0.097*	0.005	1			
(14) FD	−0.147*	−0.201*	−0.376*	0.180*	0.225*	0.101*	−0.358*	−0.058*	0.042*	0.263*	−0.041*	0.037*	0.029*	1		
(15) RBCR	0.069*	−0.100*	−0.060*	0.496*	0.639*	0.912*	−0.211*	−0.054*	0.181*	−0.101*	−0.019*	−0.447*	0.035*	0.093*	1	
In this table, we provide an empiric on the correlation between selected proxies of the study. “* represents the significance at 5 %”.

4.1 Full sample data findings

To test the cause and effect between earnings and capitalization of a US bank, we used GMM's econometric framework. Table 4 contains full sample estimates. The predictions also include how the economic activity will soften the relationship between bank profits and capitalization, taking advantage of the unique period of larger US banks. Following Zheng and Cronje [81], we examine the moderating role of economic freedom by adding the interaction term (capital proxy* EFD). In line with the regulatory hypothesis, we find that capital adversely affects the banks' profitability. Furthermore, the results are supported by Ref. [36], who also find similar relations while examing the relationship between capital and efficiency in the European banking system. The relationship between banks' capital and profitability remains robust to various proxies of capital. Whereas the relationship between economic freedom and banks' profitability is also negative, the financial fragility theory supports the results, according to which increased competition enhances the banks' fragility. The results are also in consonance with [15,82] and contradict the findings of [83,84]. The outcome suggests that banks operating in an environment with greater financial freedom are more likely to default or be less stable, ultimately adversely affecting their profitability.Table 4 Moderating role of economic freedom-full sample results.

Table 4VARIABLES	(1)	(2)	(3)	(4)	
ROA	ROA	ROA	ROA	
L.ROA	2.486*** (0.127)	2.403*** (0.114)	2.475*** (0.125)	2.478*** (0.125)	
CAP	−0.598*** (0.211)				
CAP*EFD	0.738*** (0.269)				
TCAP		−1.205*** (0.248)			
TCAP*EFD		1.486*** (0.317)			
RBCR			−0.502*** (0.143)		
RBCR*EFD			0.614*** (0.182)		
TRBCR				−0.806*** (0.190)	
TRBCR *EFD				1.007*** (0.243)	
EFD	−0.111*** (0.028)	−0.177*** (0.030)	−0.123*** (0.026)	−0.163*** (0.031)	
Credit risk	0.270*** (0.049)	0.280*** (0.047)	0.267*** (0.048)	0.261*** (0.048)	
Liquidity	0.009**(0.004)	0.009**(0.004)	0.011**(0.004)	0.011**(0.004)	
Size	−0.047** (0.019)	−0.063*** (0.018)	−0.063*** (0.019)	−0.060*** (0.019)	
Managerial Efficiency	0.000*** (0.000)	0.000*** (0.000)	0.000*** (0.000)	0.000*** (0.000)	
Loan ratio	−0.007*** (0.001)	−0.007*** (0.001)	−0.009*** (0.001)	−0.008*** (0.001)	
Economic growth	−0.001 (0.006)	−0.001 (0.006)	−0.001 (0.006)	−0.001 (0.006)	
Financial development	0.002*** (0.001)	0.003*** (0.001)	0.002*** (0.001)	0.003*** (0.001)	
Constant	0.075*** (0.022)	0.131*** (0.023)	0.089*** (0.021)	0.119*** (0.024)	
AR(1)	0.000	0.000	0.000	0.000	
AR(2)	0.122	0.093	0.116	0.122	
No. of instruments	13	13	13	13	
Hansen-j statistics	0.525	0.559	0.529	0.562	
Sargen-p statistics	0.660	0.209	0.339	0.308	
Using the GMM technique, this table reports the entire sample results, where the dependent variable is profitability, the independent variable is capital, and the moderating proxy is economic freedom; however, significance is ***1 %, **5 %, and *10 %, accordingly.

Notably, our findings reveal a positive interactive effect between economic freedom and capital, and these findings remain robust across various proxies of capital. Columns 1–4 of Table 4 present results for four different specifications of capital and its interaction term with economic freedom. The outcome reveals that a higher capital ratio helps banks to counter the negative consequences of increased competition through higher economic freedom. Conversely, heightened economic freedom mitigates the adverse effect of capital on profitability. Nations with higher levels of economic freedom tend to provide a more conducive environment for capital accumulation and allocation, fostering higher levels of profitability through mechanisms such as reduced regulatory barriers, stronger property rights protection, and increased market competition. Conversely, in environments characterized by lower economic freedom, barriers to capital accumulation and investment can impede profitability, limiting growth opportunities for businesses. In the context of the US economy, the findings indicate that the combination of economic freedom and capital positively influences banks' profitability. The results are supported by competition stability theory, according to which the higher competition doesn't necessitate an increase in the banks' probability to default, but it can also positively affect its profitability. In line with our second hypothesis, we ascertain a positive and statistically significant coefficient for the interactive term (EFD * capital proxy) reflecting the relationship between economic freedom and fluctuations in bank capital. All in all, the negative impact of capital on banks' profitability is positively moderated by economic freedom. The finding of the study has important implication for the policymakers and decision-makers that they must not only consider how economic freedom affects banks profitability or risk but the must incorporate the interactive impact while formulating new policies or guidelines. Furthermore, economic freedom has a significant positive impact of the nexus between capital and profitability. In summary, these findings underscore the intricate connection between bank capital, profitability, and economic freedom. They underline the significance of regulatory frameworks, market conditions, and economic rationality in influencing the dynamics of the banking industry. Being aware of these consequences can guide policy choices, strategic decision-making by banks, and scholarly investigations focused on comprehending the intricate interaction among financial regulation, market dynamics, and economic results. The banks operating in a higher economic freedom environment can leverage their higher capital by opting for risky investments. Hansen test statistics are all statistically insignificant, proving that the instruments are reliable in all scenarios tested. The model consistency is confirmed by the fact that the null hypothesis that there is no second-order serial correlation in the first difference is correct.

4.2 Analysis of pre- and post-crisis situations

Table 5 contains the findings for the impact of capital on profitability with moderating role of economic freedom in before and after crisis period. The outcome reveals that capital has a statistically significant(in-) relationship with banks earnings before (post) crisis period. However, the results conform to the regulatory hypothesis in the aftermath of the crisis. There is diversity between the pre- and post-crisis eras. More specifically, the impact of capital ratio, risk-based capital ratio, and economic freedom on bank profitability is more noticeable in the time after the crisis as compared to the pre-crisis era. Theoretically, the findings align with economic rationale because banks can perform better in normal economic situations than bad economic conditions. Table 5 also show that the coefficient of the interactive term of capital and economic freedom is statistically significant and positive, however, this relationship is although negative but insignificant during the pre-crisis period. The finding confirms the heterogeneity in the relationship across market conditions. The findings of post crisis period are similar to the baseline findings and economic freedom weaken the negative impact of capital on profitability during post-crisis period and results are consistent across all specification of capital. Banks with higher capital have a greater margin to deal with increased competition in the market than banks with low capital ratios. The outcomes are further supported by financial stability theory.Table 5 Moderating role of economic freedom for Pre and crisis period.

Table 5VARIABLES	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	
Before-crisis Results	Post-crisis Results	
ROA	ROA	ROA	ROA	ROA	ROA	ROA	ROA	
L.ROA	0.475** (0.215)	0.432*** (0.068)	0.435*** (0.067)	0.437*** (0.067)	2.588*** (0.240)	2.508*** (0.221)	2.522*** (0.228)	2.533*** (0.228)	
CAP	−0.115 (0.183)				−1.593*** (0.385)				
CAP*EFD	0.152 (0.229)				2.038*** (0.500)				
TCAP		−0.237 (0.190)				−2.445*** (0.495)			
TCAP*EFD		0.320 (0.238)				3.106*** (0.640)			
RBCR			−0.097 (0.134)				−0.907*** (0.262)		
RBCR*EFD			0.124 (0.169)				1.149*** (0.340)		
TRBCR				−0.097 (0.149)				−1.130*** (0.340)	
TRBCR *EFD				0.116 (0.187)				1.432*** (0.443)	
EFD	0.022 (0.027)	0.004 (0.025)	0.017 (0.028)	0.020 (0.027)	−0.033 (0.051)	−0.132** (0.055)	0.003 (0.055)	−0.016 (0.061)	
Credit risk	0.102*** (0.033)	0.098*** (0.033)	0.108*** (0.033)	0.106*** (0.033)	0.315*** (0.061)	0.341*** (0.060)	0.307*** (0.059)	0.296*** (0.058)	
Liquidity	0.008 (0.005)	0.008** (0.004)	0.009** (0.004)	0.009** (0.004)	0.007 (0.005)	0.007 (0.005)	0.009* (0.005)	0.009* (0.005)	
Size	0.007 (0.017)	0.017* (0.009)	0.010 (0.010)	0.005 (0.009)	−0.002 (0.025)	−0.031 (0.023)	−0.027 (0.024)	−0.028 (0.024)	
Managerial Efficiency	−0.001*** (0.000)	−0.001*** (0.000)	−0.001*** (0.000)	−0.001*** (0.000)	0.001*** (0.000)	0.001*** (0.000)	0.001*** (0.000)	0.001*** (0.000)	
Loan ratio	−0.001** (0.000)	−0.001** (0.001)	−0.001* (0.001)	−0.002*** (0.001)	−0.008*** (0.001)	−0.008*** (0.001)	−0.010*** (0.002)	−0.010*** (0.002)	
Economic growth	0.015 (0.013)	0.011 (0.012)	0.011 (0.012)	0.012 (0.012)	0.149*** (0.028)	0.137*** (0.025)	0.142*** (0.027)	0.143*** (0.026)	
Financial development	−0.001** (0.000)	−0.001** (0.000)	−0.001** (0.000)	−0.001** (0.000)	0.001*** (0.000)	0.001*** (0.000)	0.001*** (0.000)	0.001*** (0.000)	
Constant	0.004 (0.018)	0.016 (0.017)	0.008 (0.019)	0.007 (0.019)	−0.011 (0.044)	0.073 (0.044)	−0.031 (0.047)	−0.016 (0.051)	
Observations	3780	3780	3780	3780	9450	9450	9450	9450	
AR(1)	0.004	0.000	0.000	0.000	0.000	0.000	0.000	0.000	
AR(2)	0.390	0.390	0.411	0.406	0.260	0.230	0.270	0.290	
No. of instruments	15	15	15	15	13	13	13	13	
Hansen-j statistics	0.188	0.318	0.315	0.322	0.737	0.841	0.594	0.619	
Sargen-p statistics	0.212	0.322	0.330	0.302	0.430	0.400	0.433	0.441	
Using the GMM technique, this table reports the crisis period results, where the dependent variable is profitability, the independent variable is capital, and the moderating proxy is economic freedom; however, significance is ***1 %, **5 %, and *10 %, accordingly.

4.3 Banks capitalization base results

The results for the relationship between capital and profitability for well-capitalized and under-capitalized banks is reported in Table 6. Our findings for well-capitalized banks reported in Columns 1–4 show that bank capital contributes to bank profitability. The outcome of the study is in consonance with [30,85]. However, we have a negative but insignificant impact of risk-based capital ratio on profitability. Economic freedom, as postulated by competition stability theory, has a positive effect on the profitability of commercial banks [58,86]. One possible reason for the positive impact is that economic freedom promotes competition and market efficiency, which can lead to increased revenue and reduced costs for banks. Furthermore, economic freedom can also improve the allocation of resources, which can lead to improved efficiency and productivity. It's important to note that for banks with higher capital, the interactive term (EFD * CAP) has a negative and statistically significant coefficient for all measures of capital except the total capital ratio. This result indicates that economic freedom serves as a negative moderator in the relationship between capital and bank profits. The findings suggest that the liberalization or reduced barrier adversely affects the performance of well-capitalized banks. Furthermore, for well-capitalized banks, higher economic freedom adversely affects their stability and profitability.Table 6 Moderating role of economic freedom across bank capitalisation.

Table 6VARIABLES	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	
Well-capitalized banks	Under-capitalized banks	
ROA	ROA	ROA	ROA	ROA	ROA	ROA	ROA	
L.ROA	0.954*** (0.064)	2.123*** (0.191)	1.094*** (0.071)	0.905*** (0.068)	2.215*** (0.241)	1.073*** (0.056)	1.057*** (0.059)	1.072*** (0.058)	
CAP	0.488** (0.210)				−0.894**(0.414)				
CAP*EFD	−0.622** (0.267)				1.160** (0.531)				
TCAP		−0.932* (0.526)				−0.564** (0.270)			
TCAP*EFD		1.138* (0.669)				0.759** (0.347)			
RBCR			0.108 (0.174)				−0.377** (0.182)		
RBCR*EFD			−0.148 (0.223)				0.512** (0.234)		
TRBCR				0.582* (0.305)				−0.562** (0.219)	
TRBCR *EFD				−0.748* (0.388)				0.761*** (0.282)	
EFD	0.055* (0.031)	−0.152** (0.075)	0.007 (0.038)	0.096 (0.059)	−0.147*** (0.054)	−0.080** (0.032)	−0.079** (0.033)	−0.103*** (0.036)	
Credit risk	0.015 (0.029)	0.062 (0.103)	0.057* (0.034)	0.020 (0.027)	0.170** (0.077)	0.015 (0.025)	0.030 (0.023)	0.041* (0.023)	
Liquidity	−0.008 (0.005)	0.008 (0.010)	−0.009* (0.005)	−0.008* (0.005)	0.011 (0.007)	0.004 (0.003)	0.002 (0.003)	0.002 (0.003)	
Size	−0.037*** (0.012)	−0.055 (0.044)	−0.035*** (0.013)	−0.033*** (0.012)	−0.089*** (0.034)	−0.050*** (0.011)	−0.048*** (0.010)	−0.044*** (0.011)	
Managerial Efficiency	−0.001*** (0.000)	0.001 (0.000)	−0.001*** (0.000)	−0.001*** (0.000)	0.001* (0.000)	−0.001*** (0.000)	−0.001*** (0.000)	−0.001*** (0.000)	
Loan ratio	−0.001 (0.001)	−0.001 (0.002)	−0.002* (0.001)	−0.001 (0.001)	−0.007*** (0.002)	−0.002*** (0.001)	−0.001 (0.001)	−0.001 (0.001)	
Economic growth	0.010 (0.009)	−0.004 (0.014)	0.012 (0.009)	0.011 (0.009)	0.012 (0.010)	0.029*** (0.006)	0.029*** (0.006)	0.029*** (0.006)	
Financial development	−0.001***(0.000)	0.001 (0.000)	−0.001** (0.000)	−0.001***
(0.000)	0.001 (0.000)	−0.001*** (0.000)	−0.001*** (0.000)	−0.001*** (0.000)	
Constant	−0.030(0.024)	0.111* (0.059)	0.007 (0.030)	−0.061 (0.046)	0.111*** (0.041)	0.074*** (0.025)	0.070*** (0.025)	0.088*** (0.028)	
Observations	2482	2482	2482	2482	4265	4265	4265	4265	
Number of id	146	146	146	146	251	251	251	251	
AR(1)	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	
AR(2)	0.135	0.163	0.135	0.140	0.214	0.077	0.075	0.078	
No. of instruments	13	13	13	13	13	13	13	13	
Hansen-j statistics	0.054	0.486	0.876	0.099	0.844	0.435	0.765	0.121	
Sargen-p statistics	0.221	0.209	0.210	0.312	0.432	0.233	0.342	0.543	
Using the GMM technique, this table reports the well-capitalized and under-capitalized bank results, where the dependent variable is profitability, the independent variable is capital, and the moderating proxy is economic freedom; however, significance is ***1 %, **5 %, and *10 %, accordingly.

As shown in Columns 5–8 of Table 6, the coefficient capital is statistically significant and negative for under-capitalized banks and results are consistent across all proxies of capital. The finding are in line with the financial fragility-crowding out theory, according to which increased capital reduces banks' lending ability and ultimately adversely affects banks' performance. The interaction results are significantly positive for all the capital specifications, suggesting that for undercapitalized banks economic freedom plays a positive role by reducing the adverse impact of capital on performance. The results support the baseline findings.

4.4 Banks' liquidity-based results

Columns 1–4 (5–8) of Table 7 contain the findings for high (low) liquid banks. The findings show that a capital's statistically significant and negative coefficient is consistent with baseline results. Furthermore, the results are consistent across high and low liquid banks and all capital specifications. The study's results align with previous research by Sarpong-Kumankoma et al. [82] and Sufian and Habibullah [15] that found a negative relationship between economic freedom and performance. However, these results contrast with the findings of [58], which reported a positive relationship.Table 7 Result for the moderating role of economic freedom based on the liquidit of banks.

Table 7VARIABLES	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	
High-liquid banks	Low-liquid banks	
ROA	ROA	ROA	ROA	ROA	ROA	ROA	ROA	
L.ROA	2.296*** (0.160)	1.467*** (0.076)	1.479*** (0.078)	1.488*** (0.079)	2.763*** (0.212)	1.507*** (0.085)	1.525*** (0.088)	1.522*** (0.089)	
CAP	−0.499** (0.252)				−0.811** (0.367)				
CAP*EFD	0.620* (0.323)				1.000** (0.468)				
TCAP		−0.599*** (0.171)				−0.707*** (0.238)			
TCAP*EFD		0.753*** (0.220)				0.895*** (0.303)			
RBCR			−0.226** (0.099)				−0.360** (0.171)		
RBCR*EFD			0.277** (0.127)				0.476** (0.218)		
TRBCR				−0.385***
(0.137)				−0.538***
(0.207)	
TRBCR *EFD				0.492*** (0.175)				0.702*** (0.266)	
EFD	−0.097*** (0.034)	−0.090*** (0.021)	−0.061*** (0.019)	−0.083*** (0.023)	−0.136*** (0.049)	−0.107*** (0.029)	−0.082*** (0.029)	−0.105*** (0.032)	
Credit risk	0.223*** (0.060)	0.130*** (0.030)	0.124*** (0.030)	0.125*** (0.031)	0.204*** (0.078)	0.067** (0.034)	0.063* (0.034)	0.066* (0.034)	
Liquidity	0.00 (0.005)	0.00 (0.003)	0.002 (0.003)	0.002 (0.003)	0.010 (0.007)	0.005 (0.004)	0.005 (0.004)	0.005 (0.004)	
Size	−0.028 (0.023)	−0.038*** (0.011)	−0.040*** (0.011)	−0.034*** (0.011)	−0.075** (0.032)	−0.059*** (0.012)	−0.058***
(0.012)	−0.057***
(0.012)	
Managerial Efficiency	0.001*** (0.000)	−0.001 (0.000)	−0.001 (0.000)	−0.001 (0.000)	0.001*** (0.000)	−0.001** (0.000)	−0.001** (0.000)	−0.001** (0.000)	
Loan ratio	−0.006*** (0.002)	−0.004*** (0.001)	−0.005*** (0.001)	−0.004*** (0.001)	−0.016*** (0.003)	−0.006*** (0.001)	−0.006*** (0.001)	−0.006*** (0.001)	
Economic growth	0.006 (0.007)	0.014*** (0.005)	0.014*** (0.005)	0.015*** (0.005)	−0.012 (0.011)	0.012** (0.006)	0.013** (0.006)	0.012** (0.006)	
Financial development	0.001*** (0.000)	0.001* (0.000)	0.001 (0.000)	0.001 (0.000)	0.001 (0.000)	−0.001** (0.000)	−0.001** (0.000)	−0.001** (0.000)	
Constant	0.058** (0.026)	0.070*** (0.016)	0.048*** (0.015)	0.064*** (0.018)	0.111*** (0.038)	0.095*** (0.022)	0.073*** (0.023)	0.091*** (0.025)	
Observations	7973	7973	7973	7973	8092	8092	8092	8092	
Number of id	469	469	469	469	476	476	476	476	
AR(1)	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	
AR(2)	0.139	0.109	0.090	0.191	0.937	0.131	0.152	0.148	
No. of instruments	13	13	13	13	13	13	13	13	
Hansen-j statistics	0.466	0.320	0.277	0.290	0.726	0.073	0.066	0.060	
Sargen-p statistics	0.655	0.673	0.654	0.532	0.401	0.432	0.501	0.442	
Using the GMM technique, this table reports the high liquid and low liquid bank results, where the dependent variable is profitability, the independent variable is capital, and the moderating proxy is economic freedom; however, significance is ***1 %, **5 %, and *10 %, accordingly.

Moreover, the liberty in economic activities weakens the affiliation between capital and performance, as the negative impact of capital into positive as the coefficient of interaction is higher than the capital coefficient. However, the relaxation in economic activities is beneficial for low-liquidity banking organizations, as highlighted by their higher beta value in comparison to high-liquidity banks. Although the results are similar across high and low growth banks, the magnitude of impact is higher for low liquid banks. Supported by the competition-stability hypothesis, our results suggest that banks in a highly competitive environment enhance their abilities, search for alternatives, and find new ways to grow, ultimately affecting the banks' performance positively.

4.5 Analysis of robustness

To validate and check the robustness of the baseline findings, we use two other proxies to gauge the banks' performance (Net interest margin and return on equity). Columns 1–4 of Table 8 report the result for net-interest margin, while Columns 5–8 present the finding for the return of equity measure of profitability. Overall, the results are consistent in terms of sign and significance across different performance measures, confirming the main findings' robustness.Table 8 Robustness using alternative proxies of profitability.

Table 8	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	
VARIABLES	NIM	NIM	NIM	NIM	ROE	ROE	ROE	ROE	
Lag. Dep	2.081*** (0.023)	2.184*** (0.033)	2.079*** (0.023)	2.184*** (0.033)	2.010*** (0.092)	1.541*** (0.065)	1.992*** (0.090)	1.552*** (0.066)	
CAP	−0.340* (0.201)				−2.919* (1.600)				
CAP*EFD	0.385 (0.259)				4.146** (2.064)				
TCAP		−0.858*** (0.258)				−5.802*** (1.384)			
TCAP*EFD		1.036*** (0.332)				7.455*** (1.780)			
RBCR			−0.153 (0.133)				−3.931*** (1.065)		
RBCR*EFD			0.154 (0.172)				5.119*** (1.364)		
TRBCR				−0.083 (0.184)				−3.953*** (1.077)	
TRBCR *EFD				0.053 (0.237)				5.191*** (1.383)	
EFD	−0.021 (0.026)	−0.081*** (0.030)	−0.005 (0.023)	0.009 (0.029)	−0.914*** (0.225)	−1.047*** (0.174)	−1.220*** (0.208)	−0.995*** (0.183)	
Credit risk	−0.202*** (0.042)	−0.224*** (0.046)	−0.209*** (0.042)	−0.263*** (0.045)	1.679*** (0.345)	0.986*** (0.241)	1.756*** (0.344)	1.039*** (0.250)	
Liquidity	−0.022*** (0.004)	−0.021*** (0.004)	−0.019*** (0.004)	−0.019*** (0.004)	0.083** (0.033)	0.049** (0.024)	0.075** (0.033)	0.047* (0.024)	
Size	0.057*** (0.019)	0.051** (0.021)	0.034* (0.019)	0.045** (0.021)	−0.508*** (0.132)	−0.430*** (0.085)	−0.442*** (0.138)	−0.399*** (0.086)	
Managerial Efficiency	0.001*** (0.000)	0.001** (0.000)	0.001*** (0.000)	0.001*** (0.000)	0.002** (0.001)	−0.001** (0.001)	0.002** (0.001)	−0.001* (0.001)	
Loan ratio	−0.018*** (0.001)	−0.019*** (0.001)	−0.020*** (0.001)	−0.021*** (0.001)	−0.047*** (0.008)	−0.030*** (0.005)	−0.046*** (0.008)	−0.026*** (0.006)	
Economic growth	−0.030*** (0.005)	−0.031*** (0.005)	−0.030*** (0.005)	−0.031*** (0.005)	0.140*** (0.049)	0.182*** (0.034)	0.141*** (0.048)	0.189*** (0.034)	
Financial development	0.001*** (0.000)	0.001*** (0.000)	0.001*** (0.000)	0.001*** (0.000)	0.001 (0.000)	−0.001* (0.000)	0.001 (0.000)	−0.001* (0.000)	
Constant	−0.048** (0.021)	−0.006 (0.024)	−0.054*** (0.018)	−0.072*** (0.023)	0.650*** (0.171)	0.847*** (0.133)	0.897*** (0.159)	0.787*** (0.141)	
AR(1)	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	
AR(2)	0.680	0.845	0.784	0.951	0.192	0.045	0.159	0.051	
No. of instruments	13	13	13	13	13	13	13	13	
Hansen-j statistics	0.391	0.303	0.330	0.306	0.221	0.105	0.110	0.404	
Sargen-p statistics	0.101	0.211	0.201	0.223	0.560	0.076	0.098	0.107	
Using the GMM technique, this table reports the entire sample results when NIM and ROW are used as alternatives for profitability, the independent variable is capital, and the moderating proxy is economic freedom; however, significance is ***1 %, **5 %, and *10 %, accordingly.

5 Conclusion and policy recommendations

Ultimately, economic activities exert a substantial influence on the correlation between capitalization and profitability. Specifically, a collection of economic activities, referred to as economic freedom, serves as a regulating influence and decides the degree to which capital investment is translated into profitability for both financial and non-financial entities. Countries that have higher levels of economic freedom generally create a more advantageous setting for the accumulation and allocation of capital. They also encourage higher levels of profitability through means such as reducing regulatory barriers, enhancing protection of property rights, and fostering increased market competition. Conversely, in environments characterized by lower economic freedom, barriers to capital accumulation and investment can impede profitability, limiting growth opportunities for businesses. Understanding the moderating role of economic freedom is crucial for policymakers and business leaders alike, as it underscores the importance of creating and maintaining an environment that fosters entrepreneurship, innovation, and sustainable economic growth. By prioritizing policies that enhance economic freedom, nations can potentially unlock greater opportunities for capital deployment and ultimately drive higher levels of profitability across banking sectors and other industries.

While earlier research has explored the relationship between economic freedom and bank profitability, there is a lack of understanding of how economic freedom influences the link between bank capital and profitability, particularly in light of the present economic conditions. In the context of US banking, there is a significant gap in understanding how economic freedom impacts the relationship between bank capital and profitability. Especially in the aftermath of the financial crisis, the impact of economic freedom, risk-based capital ratio, and capital ratio on bank profitability appears more pronounced than pre-crisis. We hope that by conducting this study, we can fill this knowledge vacuum and better understand the role that economic freedom plays in shaping this relationship. Our goal is to shed new light on this area and improve our understanding of it, especially as it pertains to commercial banking in the US. To address this gap, we aim to conduct research in this area to gain insight and understanding about how economic freedom affects this relationship. We have formulated hypotheses based on previous studies and used the GMM technique to test these hypotheses.

The research findings indicate that both capital and economic freedom have a negative impact on the profitability of banks in the US. However, when the two factors are considered together, their interactive effect on profitability is positive and statistically significant. This suggests that economic freedom combined with sufficient capital makes a positive contribution to the profitability of banks in the USA. Overall, the results suggest that economic freedom and capital work together to improve the profitability of U.S. banks. The outcome reveals that capital has a statistically significant(in-) relationship with banks earnings before(post) crisis period. The outcomes vary between pre- and post-crisis eras, indicating heterogeneity. Notably, the impact of capital, risk-based capital ratios, and economic freedom on bank profitability seems to be more pronounced in the time after the crisis compared to the period before the crisis. The presence of a significantly negative coefficient for the interaction term (EFD*CAP) indicates that economic freedom has a detrimental impact on the link between capital and profitability, especially for banks that have high levels of capitalization. The outcome suggests the liberalization or reduced barrier adversely affects the performance of well-capitalized banks. The findings are in line with the financial fragility-crowding out theory, according to which increased capital reduces banks' lending ability and ultimately adversely affects banks performance. The results of interaction are significantly positive for all the specifications of the capital, suggesting that for undercapitalized banks, economic freedom plays a positive role by reducing the adverse impact of capital on performance. However, the positive impact of economic freedom is higher for low liquidity banks as highlighted by their higher beta value compared to high liquid banks. Although the results are similar across high and low growth banks, but the magnitude of impact is higher for low liquid banks.

The findings of this study have significant implications for multiple stakeholders, including government officials, legislators, regulators, and bank managers. It is recommended that government and policymakers consider the idea of opening their national borders and establishing a conducive environment with minimal barriers. This will enhance the stability of banks by attracting more competitors, which will in turn compel them to introduce new products and services and enhance the overall governance system. In addition, it is of the utmost importance to prioritize the establishment of a conducive atmosphere that fosters economic liberty and ensures sufficient capitalization within the banking industry. Therefore, policymakers, regulators, and bank management should take into account the influence of economic freedom when making choices about bank capital and profitability. When economic freedom is strong, it is more beneficial for banks to maintain greater capital ratios in order to attain profitability. Conversely, in situations where economic flexibility is constrained, banks may find it more advantageous to have a lower capital ratio in order to attain profitability. Furthermore, bank managers should also take into account the significance of both economic liberty and capital when formulating strategic decisions to attain profitability. Furthermore, the disparity in the impact of economic freedom on the correlation between capital and bank profits during times of crisis and normalcy underscores the necessity of considering the liberty of economic activity when making decisions.

CRediT authorship contribution statement

Faisal Abbas: Writing – original draft, Software, Methodology, Formal analysis, Data curation, Conceptualization. Shoaib Ali: Writing – review & editing, Writing – original draft, Supervision, Resources, Project administration, Conceptualization. Kai Yin Woo: Supervision, Project administration, Investigation, Funding acquisition. Wing-Keung Wong: Resources, Project administration, Funding acquisition.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The forth author would like to thank Robert B. Miller and Howard E. Thompson for their continuous guidance and encouragement. This research has been supported by 10.13039/501100005007 Asia University , 10.13039/501100004391 China Medical University Hospital , Hong Kong Shue Yan University, 10.13039/501100002920 Research Grants Council (RGC) of Hong Kong (project numbers 12502814 and 12500915 ), and the 10.13039/501100004663 Ministry of Science and Technology (MOST, Project Numbers 106-2410-H-468-002 and 107-2410-H-468-002-MY3 ), Taiwan.

1 https://www.statista.com/topics/5642/banking-industry-in-the-us/#topicOverview, World Bank, International Monetary Fund (IMF). U.S. Bureau of Economic Analysis (Asteriou, Pilbeam, & Tomuleasa). And Nasdaq.

2 https://www.heritage.org/index/about.

3 https://www.heritage.org/index/about.
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