Does auditor–client geographic proximity matter? New evidence from an emerging market Open Access

Auditing serves as a foundation of financial transparency and accountability, providing stakeholders with assurance about the accuracy and reliability of financial statements. Numerous factors can influence the effectiveness and quality of an audit; however, one important but little-studied factor is the geographical proximity of the auditors to their clients (Kedia and Rajgopal, 2011; Choi et al., 2012; Defond et al., 2018). Notwithstanding the dramatic decrease in the cost of transportation and communication as well as the rapid advancement of information technology, economic agents’ decision-making behavior is still influenced by geographic proximity (Coval and Moskowitz, 1999). The impetus for this study is derived from an expanding body of research in accounting and finance that highlights the significance of geographical proximity between economic agents. Previous research in the marketing literature has concentrated on the spatial distribution of buyers and sellers and the associated physical distribution costs. However, more recent marketing studies have shifted their focus to the role of geographic proximity in interfirm relationships (Ganesan et al., 2005). Similarly, the finance literature has documented the effects of distance, highlighting the significance of proximity in various contexts such as investor portfolio management (Coval and Moskowitz, 1999; Ivkovic and Weisbenner, 2005), equity analysis (Malloy, 2005; Bae et al., 2008) and debt contracting (Agarwal and Hauswald, 2010; Hollander and Verriest, 2012). These studies collectively indicate that geographic proximity influences decision-making behaviors and contractual relationships among economic agents. This study aims to examine the impact of auditor–client geographic proximity on three critical aspects of the audit process: audit fees, audit report lag (ARL) and audit quality.

The association between auditor–client proximity and different audit attributes has been relatively underexplored in the field of research. The majority of prior investigations have been conducted within the framework of developed economies. For instance, studies by Choi et al. (2012), Beck et al. (2019) and Francis et al. (2022) have probed into the relationship between geographical distance and audit quality in the context of the USA. Similarly, Zhang (2020) examined the nexus between distance and audit fees in the Chinese context. Studies such as those by Dong et al. (2018) and Bazrafshan and Dehghani Madise (2022) have explored the impact of geographic proximity on audit report timeliness, focusing on the USA and Iran, respectively. However, there remains a notable gap in research within the context of emerging economies, particularly those in South Asia. With predictions that emerging markets would account for a sizable share of the global GDP by 2050, it is imperative to highlight economies like Bangladesh (PwC, 2017). Addressing this gap will require closer knowledge and more educated practices in emerging economies.

One of the first studies to assess the association between auditor–client geographical proximity and audit quality was conducted by Choi et al. (2012) in the context of the USA. The study found a positive relationship between proximity and audit quality based on the fact that information advantage can help the local auditors in deterring and detecting earnings management practice by clients. However, the US sample used in Choi et al. (2012) is marked by high level of litigation and reputation risks for auditors, which may discourage auditors from compromising their independence, thereby maintaining high audit quality. Consequently, it would be relevant to investigate the validity of the relationship between auditor–client distance and audit quality in a market with distinct characteristics. That is why this study focuses on the context of Bangladesh, a fast-growing emerging economy characterized by weak corporate governance, high shortage of auditors and frequent rotation of audit firms.

Bangladesh, as an emerging economy, presents a convincing background for analyzing the impact of auditor–client geographic proximity on audit outcomes. The country’s weak governance structure exacerbates these concerns, as corporate governance in Bangladesh is often influenced by political and familial ties, leading to a lack of effective regulatory oversight (Khan et al., 2016). The auditing profession itself is underdeveloped, with low auditor independence and a concentrated market dominated by a few large firms, which reduces competitive pressures that might otherwise improve audit quality (Muttakin et al., 2017). The regulatory environment in Bangladesh struggles to enforce strict audit standards. The Financial Reporting Council, established to regulate the auditing profession, has faced challenges in its implementation and independence, particularly due to political and bureaucratic influence. This weak regulatory structure exacerbates the already fragile state of auditing culture in Bangladesh, where audit fees remain extremely low, limiting the capacity for auditors to perform comprehensive reviews (Siddiqui, 2024). Geographic proximity is a particularly important variable in the Bangladeshi context because of its infrastructural limitations. Auditors based far from their clients may struggle with logistical challenges such as limited access to timely information, unreliable transportation and excessive traffic. These challenges can result in delayed audit reports, reducing the timeliness and effectiveness of audits. Conversely, geographic proximity may allow auditors to develop closer relationships with clients, which can improve the flow of information but might also compromise their independence and increase the risk of bias. All these factors make the relationship between auditor–client proximity and audit outcomes especially significant in the Bangladeshi context.

The primary objective of this study is to investigate the relationship of auditor–client geographic proximity with audit fees, ARL and audit quality. The study used 469 firm-year observations from companies listed on the Dhaka Stock Exchange (DSE) in Bangladesh, covering the period from 2018 to 2021. Geographic proximity was assessed using both spatial distances, measured in kilometers and temporal distance, measured in minutes. The study has found that auditor–client proximity is positively and significantly associated with audit fees and ARL. On the other hand, the relationship between auditor–client proximity and audit quality is found to be negative and significant. The findings indicate that distant auditors not only conduct high-quality audits but also charge lower fees and maintain timeliness of reporting.

This study will contribute to the existing field of literature in many ways. First, unlike prior studies that assessed the impact of auditor–client proximity on a single aspect like audit fees, ARL or audit quality, this study comprehensively investigates the relationship by integrating all three dimensions (fees, lag and quality), providing a more holistic view. Second, it provides empirical evidence from Bangladesh, an emerging market, enriching the global discourse on audit practices with context-specific insights. To the best knowledge of the authors, this is the first study to address the association of auditor–client proximity with audit fees, ARL and audit quality in the context of a developing country. Finally, the findings of this study offer practical implications for audit firms, regulators and investors operating in emerging market contexts like Bangladesh. Audit firms can use it to optimize their service delivery methods by understanding how geographic proximity affects audit fees, report latency and quality, while regulators can use this information to customize regulatory actions to meet particular geographical concerns. Investors can also apply these insights to their decision-making processes, realizing that auditor–client proximity is crucial for determining the accuracy of financial data.

The rest of the study is organized as follows: Section 2 discusses the theoretical framework used in the study. Section 3 demonstrates the development of hypotheses based on prior studies. Section 4 discusses the methodology used in the study, including data, sample and research design. Section 5 investigates the findings of the study by presenting descriptive statistics, bivariate analysis and multivariate analysis, and section 6 makes a detailed discussion of the key findings. Finally, Section 7 draws the conclusion and highlights the possible implications of the study.

To investigate the nature of auditor–client geographical proximity prior studies have used different theories, mostly cluster theory (Chen et al., 2016) and transaction cost theory (Zhang, 2020). Cluster theory posits that geographical proximity of firms fosters social network sharing (Porter, 1990). Close geographic proximity is advantageous to higher levels of social interactions and information exchanges among actors within the region (Chen et al., 2016). The theory suggests such interactions establish trust among actors and reduce the tendency for opportunistic behavior like earnings manipulation. In auditing, frequent interaction and information exchanges between geographically proximate auditors and clients can reduce information asymmetry and ease audit procedures, ultimately increasing audit quality. Discussions about company matters often occur during social meetings between managers and auditors, helping people learn and acquire new information, especially about topics like strong internal controls. Members of a social network typically behave non-opportunistically to maintain the confidence of other members rather than prioritizing personal brands. However, under lower litigation and reputation risks, constant interaction can lead to familiarity threat. Local auditors may sacrifice audit quality to maintain good relationships with client management and retain clients. Geographic proximity can foster frequent social interactions between auditors and company executives, potentially compromising the auditor’s professional skepticism, critical for ensuring audit quality. Moreover, proximity may increase client influence on auditor judgment due to repeated engagements within the same business network. Clients may implicitly pressure auditors to overlook irregularities or adopt more favorable reporting standards to avoid negative financial consequences (Bazrafshan and Dehghani Madise, 2022). The proximity between the client and auditor raises concerns regarding auditor independence, particularly when close relationships create potential conflicts of interest. According to Chen et al. (2020), an auditor’s capacity to provide an independent opinion may be compromised if relationships with the client are perceived as excessively cordial. The familiarity bias hypothesis suggests that auditors may charge higher fees to clients in the same geographic area. Clients might exploit this relationship to engage in financial misreporting, offering higher fees for auditor leniency. Furthermore, intense competition and low concentration can exert significant pressure on auditors to retain their clientele. Such competition may incentivize auditors with local connections to accommodate their clients’ self-interested accounting practices, potentially increasing the incidence of audit failures and subsequent legal ramifications (Yuan et al., 2023). Therefore, while geographic proximity between auditors and clients can bring operational efficiencies, it poses significant risks in maintaining audit independence and objectivity.

The transaction cost theory posits that decreased geographical proximity among market participants reduces information asymmetry, thereby diminishing transaction costs. Geographical distance hinders entities’ ability to gather information, requiring more time, effort, money and resources to obtain relevant information about enterprises (Zhang, 2020). Investors favor local stocks in their portfolios due to familiarity with local businesses and ease of obtaining corporate information (Coval and Moskowitz, 1999; Hau, 2001). Local financial analysts exhibit increased accuracy in predicting companies’ production and revenue due to available thorough information (Malloy, 2005). Zhang et al. (2019) found a negative correlation between independent directors’ meeting attendance and their distance from firms, leading to declined financial reporting quality. This emphasizes how geographical distance affects independent directors’ performance and supervisory role, suggesting higher monitoring costs and information asymmetry regarding management and internal operations. From the auditing perspective, geographical distance between auditor and client can increase transaction costs and information asymmetry. Higher transaction costs result in auditors demanding higher audit fees, while increased information asymmetry results in lower audit quality. Auditors need to spend more effort collecting evidence from distant clients and demand higher fees for such extra effort. Due to locational inconvenience, auditors may not collect sufficient appropriate evidence, leading to low-quality audits or late submission of audit reports. However, this theory may not hold true if distant auditors implement a price-cutting approach to capture or retain clients. Studies show auditors may set audit fees lower than overall expenditures during the first year and make up the difference in subsequent years (DeAngelo, 1981). Thus, although transaction costs are higher for distant auditors, they might charge lower fees by sacrificing profit to expand their market by capturing new clients. According to Eshleman and Lawson (2017), in less concentrated and more competitive markets, auditors might adopt aggressive pricing strategies, including offering lower fees to distant clients, to expand their market share. Besides, the adoption of advanced technologies, accelerated by the unforeseen impact of the pandemic, has driven a rapid digital transformation within the auditing industry. Castka et al. (2020) observe that auditors have introduced a preaudit analysis step to address challenges posed by remote auditing, particularly in supplier audits. Similarly, Li et al. (2023) provide evidence that remote work can improve audit quality and efficiency, provided that firms adequately support their audit teams. These technological advancements have also reduced the transaction costs associated with information access, enhancing the overall efficiency of audit processes.

According to Arens et al. (2013), “Audit is a professional service that improves the quality of information for decision makers”. Auditors charge a fee varying by company characteristics, industry and effort required. If geographical distance between auditor and client is long, audit fee is likely high due to increased communication and transportation costs. Greater distance results in greater information asymmetry, requiring more client communication to reduce the information gap, leading to higher audit fees to cover increased verification costs. Previous studies found a negative association between professional monitoring and geographical distance. Kedia and Rajgopal (2011) found companies near SEC offices tend to avoid financial misreporting, believing in a positive association between SEC monitoring cost and distance. Defond et al. (2018) found auditors more prone to modifying audit reports for clients geographically distant from the Securities and Exchange Commission (SEC). Nonlocal auditors find it more difficult to monitor client activities, requiring more effort for effective monitoring and quality maintenance, resulting in high audit fees. Jensen et al. (2015) found a positive association between audit premium and auditor–client geographical distance, with distant auditors charging more due to information asymmetry. However, the client’s motive for hiring nonlocal auditors is important. Firms recruit high-quality auditors with more reputation and higher fees for signaling, while firms seeking higher discretion over reported income recruit low-quality distant auditors or those accepting lower fees (Jensen and Payne, 2005). Geographic distance between auditors, clients and SEC offices is inversely related to audit fees, indicating greater information asymmetry results in reduced audit quality (Fu et al., 2024). Diminished audit fees reflect lower assurance levels. Yuan et al. (2023) found auditors’ place attachment is particularly strong with clients exhibiting high accrual levels, often linked to greater information asymmetry. Due to greater complexity and risk, auditors justify higher fees because of familiarity bias favoring clients with higher accruals.

According to the studies conducted by Beck et al. (2019) and Francis et al. (2022), greater geographical distance between the auditor and the client can degrade the audit quality. Clients will be reluctant to pay higher fees to the auditors if the audit quality becomes substandard. The apparent decrease in audit fees can be attributed to the lack of advantageous circumstances resulting from geographic closeness, especially in cases when the auditor and the client are located at a significant distance from one another. This finding emphasizes how the auditor’s location has a significant influence on the dynamics of negotiable power and pricing strategies in the context of auditing engagements (Liu, 2014; Ye, 2016). However, Mazza et al. (2023) did not find any significant relationship between auditor distance and audit fee. Based on the above explanation, the following hypothesis can be drawn:

Two of the most important factors for investors and stakeholders in today’s capital markets are accuracy and timeliness of information. Independent auditors satisfy the demand for accuracy by validating financial statements. The timeliness of audited financial statements depends on the timeliness of audit reports. Investors desire quick release of audit reports to make investment decisions. However, studies have shown concern regarding the timeliness of audit reports (Krishnan and Yang, 2009; Bronson et al., 2011). One factor influencing delays in audit reports is the geographical distance between clients and auditors. Local auditors can gather client-specific information more conveniently than nonlocal auditors, decreasing information asymmetry (Choi et al., 2012; Jensen et al., 2015). Local auditors have easier access to soft information that is difficult to store in written or electronic form (Stein, 2002). Liberti and Mian (2009) suggest that long distances reduce dependence on subjective information and increase reliance on objective information, creating difficulty in data transfer and affecting timeliness. Although technological advancement may reduce the advantage of proximity, most studies have found that geographical proximity can improve audit quality significantly (Choi et al., 2012; Jensen et al., 2015). This proximity can enhance monitoring and control as local auditors are familiar with clients’ business environments and can conduct fieldwork more frequently. They can visit clients often, communicate with suppliers and customers and evaluate local market conditions (Kang and Kim, 2008). Dong et al. (2018) found that geographically proximate auditors provide audit reports 7–10 days earlier than other auditors. Conversely, Bazrafshan and Dehghani Madise (2022) found no significant association between auditor distance and audit delay. However, they noted that strong corporate governance, efficient audit committees and high-quality auditors can significantly influence this relationship and decrease audit delays incurred by local auditors.

However, as discussed earlier, geographical distance can result in substandard audit quality, which can be observed in the accelerated submission of audit reports, ultimately reducing the ARL (Beck et al., 2019; Francis et al., 2022). Studies conducted by Bryant-Kutcher et al. (2013) and Doyle and Magilke (2013) found that there exists a trade-off between reporting quality and audit report timeliness. Due to the potential negative impact of geographical distance between auditors and clients on audit quality (Berger et al., 2005; Li et al., 2020), auditors situated at a distance may attempt to address this limitation by expediting the issuance of audit reports. Besides, local auditors can offer prompt services to potential distant clients to expand their market. If a client holds substantial significance and contributes significantly to the audit fees of the auditing firm, the auditor may be inclined to retain the client, leading to expedited issuance of audit reports, notwithstanding the considerable geographical distance of the client (Bamber et al., 1993; Afify, 2009). Based on the above explanation, the following hypothesis can be drawn:

Previous studies on audit quality document various engagement-specific factors (e.g. non-audit services and auditor tenure) that influence auditors’ independence and audit quality. Geographic proximity between the client and audit firm is another factor potentially impacting audit quality. Proximity is expected to help auditors gain a deeper understanding of client-specific motivations, competencies and potential for substandard reporting, enabling local auditors to supervise client reporting behavior and reduce financial reporting bias more efficiently. Choi et al. (2012) found a positive association between geographic proximity and audit quality, as informational benefits of being close enable auditors to learn about client-specific traits, including incentives, capabilities, chances for earnings manipulation and business risks. Local auditors can frequently visit clients and have informal conversations with executives, employees and stakeholders to gather more information. They are familiar with local regulations, business environment and market conditions, which helps them better evaluate clients and improve audit quality (Hong et al., 2004). Gordon and McCann (2000) stated that increased social interaction between auditor and client generates trust in their relationship. To maintain trust, social actors (auditors and clients) will act in a non-opportunistic way (Calton and Lad, 1995). Li et al. (2020) found that real earnings management is lower when a firm is audited by a local auditor. Although geographic proximity poses a threat to auditor independence, this is outweighed by enhanced competence due to better information access and monitoring. Francis et al. (2022) found that audit quality decreases when the partner resides far from the client.

However, sometimes geographical proximity between auditor and client can hamper auditor independence. Constant interaction with nearby clients can create familiarity threat, adversely affecting auditor’s independence. Increased physical separation between auditors and clients may lessen the possibility of intimate connections that could jeopardize auditor independence. The familiarity bias hypothesis posits that auditors’ place attachment can create opportunities for clients to secure favorable audit opinions, even while engaging in financial misreporting. Geographic proximity or shared characteristics may compromise auditors’ independence and diminish professional skepticism. Consequently, auditors may exhibit preferential treatment toward geographically connected clients, potentially issuing unqualified audit opinions despite indications of earnings management (Yuan et al., 2023). Sharma et al. (2022) demonstrate that relationships between auditors and audit committee members are linked to a significant increase in nonaudit services provision, adversely affecting audit quality. Extending the analysis beyond auditor–client relationships, Chen et al. (2022) reveal that mutual fund managers with social connections to certain firms’ auditors tend to hold larger equity positions in these firms and achieve enhanced portfolio returns, suggesting such connections may yield privileged information or strategic advantages. When auditors are not located near the client, they might feel more empowered to uphold objectivity and professional skepticism. Geographical remoteness may make it more difficult for clients to put undue pressure on auditors. Physical distance may make auditors less vulnerable to client requests, enabling a more exhaustive and independent audit. As per DeAngelo (1981), Rahmina and Agoes (2014) and Yakubu and Williams (2020), increased auditor independence can generate high-quality audits. When working with geographically remote clients, auditors could focus more on risk assessment and planning. To improve audit quality, auditors may take a more exacting approach to detecting and resolving audit risks due to logistical obstacles and information access constraints. Based on the findings of the prior studies, the following hypothesis can be drawn:

The data set includes all the companies listed on the DSE from 2018 to 2021, a period marked by significant reforms in auditing, including changes in audit reports and the introduction of key audit matters reporting. Data have been gathered from the annual reports of these listed firms, ensuring data reliability through the application of both simple and α coefficients, surpassing the 0.75 threshold recommended by Milne and Adler (1999). Initially, there were 1,767 firm-year observations, but after excluding 882 firm-years due to their unique operations and regulatory status (e.g. mutual funds, bonds, debentures) and an additional 416 firm-years due to missing variables of interest, the final data set comprises 469 firm-years, representing over 80% of the total market capitalization. In Table 1, Panel B presents the distribution of the sample across industry sectors, with textiles being the most prominent at 18.76%, followed by insurance, engineering and banking at 13.65%, 13.22% and 12.15%, respectively. Other sectors collectively contribute approximately 40% of the sample. The yearly breakdown shows 176 observations for year 1, 166 for year 2 and 127 for year 3.

Regression models have been developed based on the specifications outlined in prior studies (Pinto and Morais, 2019; Rahaman and Karim, 2023; Rahaman et al., 2023) to assess the hypotheses. H1 is examined through models 1 and 2, H2 through models 3 and 4 and H3 through models 5 and 6. In Model 1, 3 and 5, the measurement of auditor–client geographic proximity is in kilometers, while in Models 2, 4 and 6, the same proximity is measured in minutes. This approach aligns with established methodologies and allows for a systematic examination of the hypotheses in varying regression scenarios:

The description and measurement of the variables are explained in Table 2.

Audit quality is measured using four different models to ensure robustness of the results. The first one is the Jones (1991) model, which has been used by Choi et al. (2012), Minutti-Meza (2013) and Jung et al. (2016). The model is as follows:

where:

TA_t = Total accruals measured as the difference between net income and cash flow from operations.

A = Total assets

ΔREV = Changes in revenue

ΔREC = Changes in sales

PPE = Property, plants and equipment

ROA = Return on assets

Here, the residual (ɛ) is the measure of discretionary accruals, which is used as the proxy for audit quality.

The second model that has been applied to measure audit quality is the Dechow and Dichev (2002) model which was also used by Abid et al. (2018), Carp and Istrate (2021) and Horton et al. (2021). The model is as follows:

where:

CA = Current accrual (net income before extraordinary items, plus depreciation and amortization, minus operating cash flows)

A = Total Assets

CFO = Cash flow from operations

ΔREV = Changes in revenue

PPE = Property, plants and equipment

Here, the residual (ɛ) is the measure of discretionary accruals, which is used as the proxy for audit quality.

The third model that has been used to measure audit quality is the Stubben (2010) model. Andriawan and Setyawan (2020), Zuhri and Ratnasari (2021) and Horton et al. (2021) also used this model in their studies. The model is as follows:

where:

ΔAR = Change in accounts receivable

ΔREV = Change in revenue

Here, the residual (ɛ) is the measure of discretionary revenue which will be used as the proxy for audit quality.

Finally, the fourth model that has been used as a measurement of audit quality is small profit, which takes value of one for the years in which the client’s net income before extraordinary items scaled by total assets was less than 3% and zero otherwise. In alignment with Francis and Yu (2009), Aobdia (2018) and Khurana et al. (2021), this proxy is used to gauge a client’s propensity to meet or exceed earnings thresholds. A lower likelihood of clients reporting minimal profits correlates with enhanced audit quality.

Table 3 provides descriptive statistics for key variables used in this study based on a sample of 469 observations. The table shows that the mean (average) value for audit fee and ARL are approximately 6.04 and 4.76, with a standard deviation of 0.90 and 0.34, respectively. The minimum value observed in the data set is 2.30 and 3.3, while the maximum value is 8.94 and 5.69, respectively. This information suggests that audit fees and audit report timelines vary within the data set, with a relatively narrow spread around the mean. The mean values of three proxies of audit quality used in the study are 0.04 (Jones, 1991), 0.05 (Dechow and Dichev, 2002) and 0.03 (Stubben, 2010), respectively.

Regarding the auditor–client proximity, the findings suggest that, on average, there is a 7.4-km separation between auditors and their clients, with distances ranging from as close as 0.03 km to as far as 50 km. Furthermore, auditors typically require around 24 min to travel to their client’s office, with travel times spanning from a minimum of 1 min to a maximum of 120 min. These statistics highlight the diverse geographic relationships between auditors and their clients, which could have implications for auditing processes and audit quality. Among the control variables, the presence of female as a CEO and Board Chair is observed in approximately 14% of the cases, and the proportion of female directors on the board has an average value of 0.16, indicating an insignificant women representation on the board in Bangladeshi companies. The mean value of auditor’s tenure with the client is 2.26 years, with a minimum value of 2 years and maximum value of 5 years, which indicates that all the sample companies have reappointed the previous auditor for at least one year. The average values of natural logarithm of audit committee size, natural logarithm of firm age, natural logarithm of firm size and profitability (ROA) are 1.38, 3.20, 16.02 and 3%, respectively, with varied ranges and standard deviations indicating diversity in the financial and organizational attributes of the firms. The proportion of independent directors on the board is 23% with minimum 0% and maximum 83%, indicating differences in corporate governance structure among the firms in the economy.

Table 4 shows the Pearson correlation matrix consisting of the variables used in the study. The table shows that audit fee is positively and significantly correlated to auditor–client proximity in terms of kilometers and minutes. This shows that auditors are paid lower when the clients are in greater geographical distance. In addition, ARL and audit quality show negative but insignificant correlation with auditor–client geographic proximity in the matrix. Finally, none of the control variables show a correlation coefficient exceeding the threshold of 0.80, indicating no multicollinearity issues.

Table 5 provides the outcomes of the econometric models, using the ordinary least squares method with fixed effects in year and industry. Models 1 and 2 are associated with testing H1, which pertains to the association between audit fees and auditor–client proximity. In these models, the influence of auditor–client proximity (measured in kilometers in Model 1 and in minutes in Model 2) on audit fees is explored.

The results indicate a positive and significant relationship between auditor–client proximity and the audit fees. In Model 1, geographic proximity (measured in distance) shows a significant positive coefficient (0.007) with a standard error of 0.004, suggesting that as the distance between auditor and client decreases, audit fees tend to increase. Model 2 also exhibits a significant positive coefficient (0.003) with a smaller standard error of 0.001, indicating a similar positive association between proximity and audit fees. This suggests that auditors tend to charge higher audit fees when they are geographically proximate to their clients. These findings hold statistical significance at the 5% level in both models, underscoring the reliability of the results. These findings align with the conclusions of previous studies, such as Jensen and Payne (2005), Beck et al. (2019) and Francis et al. (2022).

Among the control variables, notably, gender of the board chair and the ratio of female directors show consistent negative coefficients (significant at 5% level), while firm size demonstrates a positive relationship (significant at 1% level) with audit fees in both models. Other variables, such as ARL and firm age, exhibit significant negative coefficients at 5% and 1% levels, respectively. The adjusted R-squared value of 0.475 in both models indicates that the included variables explain a substantial portion of the variance in audit fees. Overall, the F-statistic is significant, suggesting the overall model’s statistical significance.

Table 6 presents the regression results investigating the relationship between auditor–client proximity and ARL (H2). In both Models, geographic proximity in kilometers and minutes shows significant positive coefficients, respectively, suggesting that as the distance between auditors and clients decreases, ARL tends to increase. This is consistent with the studies conducted by Bamber et al. (1993), Afify (2009), Bryant-Kutcher et al. (2013), Doyle and Magilke (2013), Beck et al. (2019) and Francis et al. (2022). Therefore, the hypothesis that auditor–client proximity has a positive and significant association with ARL is supported.

In addition, gender of the board chair exhibits consistent negative coefficients, indicating that a female chair is associated with shorter ARLs. However, other variables, such as female director ratio and firm age, do not show significant associations with ARL in either model. The adjusted R-squared values of 0.134 and 0.135 in Models 1 and 2, respectively, indicate that the included variables explain a limited portion of the variance in ARL. The F-statistics are significant, suggesting the overall model’s statistical significance.

Table 7 displays the regression results pertaining to the third hypothesis (H3), which examines the association between auditor–client geographic proximity and audit quality. Four different audit quality models (Jones-91, Dechow-02, Stubben-10, Small Profit) are considered across two measurements of proximity (kilometers and minutes) as in Models 5–12 (Jones, 1991; Dechow and Dichev, 2002; Stubben, 2010). As the increase in value of residuals indicates higher level of discretionary accruals and lower level of audit quality, the regression results show a negative and significant relationship (at 5% and 10% levels) between auditor–client proximity and audit quality across the models. Thus, we can accept the hypothesis that proximity hurts audit quality or, in other words, distance improves audit quality.

Several control variables, such as chair gender, female director ratio, audit committee size, firm age, firm size, audit tenure, ROA, year-end effect, BIG4 and independent director ratio, are included across the models, but their impact on audit quality varies. The adjusted R-squared values indicate that the models explain a certain portion of the variability in audit quality.

A subsample analysis is conducted to examine the relationship between proximity and audit outcomes for low- and high-risk firms, using leverage as a risk proxy. Firms with leverage above the median are classified as high-risk, and those below as low-risk. Table 8 Panel A reveals a positive, significant association between proximity and audit fees for low-risk firms, indicating that proximate auditors charge higher fees to low-risk clients while offering more competitive rates to high-risk clients. This suggests distant auditors may lower fees to attract low-risk clients. However, no significant link between proximity and ARL is observed for either risk category (see Table 8 Panel B). Finally, Table 8 Panel C shows a significant positive association between proximity and audit quality in low-risk firms, while no significant effect is found for high-risk firms across various audit quality measures.

This indicates that audit quality decreases with proximity or increases with distance for clients with lower exposure to risk. Greater distance can aid the auditors in maintaining their objectivity and independence. And if the client is exposed to lower risks, the relative benefits of distance can be more pronounced, as the auditors can focus more on ensuring compliance and accuracy without being overly concerned about mitigating high-risk factors. This can result in a thorough and high-quality audit process.

This study examines the influence of auditor–client geographic proximity on key audit outcomes in the emerging economy of Bangladesh, focusing on audit fees, ARL and audit quality. Using panel regression analysis, the findings reveal a significant positive association between proximity and both audit fees and ARL, while proximity is negatively associated with audit quality. These results remain robust when alternative measures of proximity and audit quality are used, indicating that auditors in closer geographic proximity charge higher fees, take longer to issue audit reports and deliver lower-quality audits. Conversely, distant auditors tend to offer lower fees, issue audit reports more promptly and maintain higher audit quality. While the association between proximity and audit fees aligns with existing literature, the relationships with audit quality and ARL contrast with findings from studies in developed economies (Choi et al., 2012; Dong et al., 2018; Francis et al., 2022). These studies find that proximity is positively associated with audit quality and negatively related to ARL.

The observed associations can be interpreted through the lenses of transaction cost theory and cluster theory. These frameworks suggest that geographic proximity fosters social networks and enhances information exchange, which may theoretically reduce information asymmetry and transaction costs (Chen et al., 2016; Zhang, 2020). Consequently, proximity is expected to decrease audit fees, shorten ARL and improve audit quality (Choi et al., 2012). However, proximity also introduces a familiarity threat, compromising auditor independence and impairing audit outcomes (Daoust and Malsch, 2020; Chen et al., 2022). Familiarity can encourage auditors to prioritize relational dynamics over professional skepticism, leading to higher fees and diminished audit quality (Hussey, 1999). Prior studies indicate that auditors connected through social or personal ties with audit committees are linked to elevated audit fees and reduced audit quality (He et al., 2017; Sharma et al., 2022). Regarding ARL, proximity-related familiarity may also result in informal relationships that undermine timely audit completion. Close auditor–client ties foster trust, which can reduce the urgency to meet reporting deadlines. In contrast to distant relationships, where logistical barriers necessitate greater efficiency, proximate auditors may feel less pressured to conclude audits quickly, contributing to longer ARL.

These findings are further contextualized by the unique cultural and economic characteristics of Bangladesh, as cultural differences have differential impact on auditing and financial reporting (Mamatzakis, Neri and Russo, 2023). The country’s audit environment is shaped by strong political connections, family-owned businesses and weak corporate governance (Khan et al., 2016; Siddiqui, 2024). Auditor selection often prioritizes opportunistic motives over efficiency, with clients seeking either lower fees for minimal audit scrutiny or higher fees for favorable unmodified audit opinions to satisfy regulatory requirements (Karim and Zijl, 2013; Khan et al., 2016). Family-controlled firms, viewing audits as a regulatory burden, prefer familiar local auditors to secure clean reports (Muttakin et al., 2017). Consequently, the use of proximate auditors reflects a strategy to balance compliance with minimal disruption, even at the cost of audit quality and higher fees.

In additional analysis, we document that the effects of proximity on audit fees and audit quality are more pronounced in low-risk firms, while no significant association is observed for ARL in either risk category. Specifically, auditors charge higher fees and compromise quality when auditing low-risk clients, as the reduced oversight pressure and lower litigation concerns allow for greater leniency (He et al., 2017; Daoust and Malsch, 2020). In contrast, high-risk firms face stricter scrutiny, where auditors balance competitive pricing with maintaining quality to mitigate reputational and litigation risks (Chen et al., 2016). Since auditing riskier firms requires more thorough procedures, overall audit fees tend to be higher, but quality remains intact to safeguard audit firm credibility. Regarding ARL, its variation is influenced more by governance practices and behavioral traits of both auditors and clients rather than risk levels, explaining its lack of significance in this context (Afify, 2009).

This study offers a novel perspective on the relationship between auditor–client proximity and audit outcomes within the context of an emerging economy. Drawing on both cluster theory and transaction cost theory, it examines how proximity influences audit quality, ARL and audit fees, particularly in the presence of familiarity threats. Using a data set of 469 firm-year observations from DSE-listed companies in Bangladesh between 2018 and 2021, the findings reveal a negative and significant relationship between proximity and audit quality, along with a positive association between proximity and both audit fees and ARL. These results remain robust across alternative measures and are more pronounced in low-risk firms. While these findings contrast with prior studies from developed economies, where stronger governance and regulatory frameworks mitigate familiarity risks, they highlight unique dynamics in markets with weaker institutional structures.

This study makes significant and original contributions to the existing literature through its innovative conceptualization, unique measurement of the key variable “ auditor–client proximity,” robust research methodology and novel findings. First, it provides fresh evidence from an emerging economy, Bangladesh, extending prior research on the relationship between auditor–client proximity and audit outcomes, including audit quality, fees and report lag. By examining these dynamics in a developing market, the study enriches the understanding of geographic proximity’s influence on audit practices. Second, the research uniquely links three critical audit outcomes to proximity, a rare approach in existing studies. Third, the models and methodologies used to test the hypotheses are rigorous, delivering insightful and robust findings. Finally, the study underscores the importance of geographic proximity in audit engagements, particularly in emerging economies. Auditors and clients must recognize how proximity affects familiarity threats, auditor independence and audit outcomes. This awareness can guide audit planning, fee negotiation and expectations around audit timeliness and quality, ultimately improving decision-making and enhancing audit processes.

Nonetheless, this study has certain limitations. It focuses on testing the hypotheses within the context of an emerging economy. To further enhance the generalizability of the results, future research could consider examining developed economies and cross-country settings. In addition, the distance is measured from client office to audit firm office rather than auditor’s residential address, from where auditors may visit client directly. Future research can explore whether the variation in measuring distance has alternative implications. Furthermore, geographic distance/proximity can be linked with other variables in subsequent studies to provide a more comprehensive understanding of its implications in the field of auditing and financial reporting.

This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.

Data are available on request from the corresponding author.

Declarations of interest: no conflict of interest.