Financial reporting quality and investment efficiency: A transnational evidence

Khan, Muhammad Azhar; Safdar, Nabeel; Manzoor, Wajiha Article Financial reporting quality and investment efficiency: A transnational evidence Pakistan Journal of Commerce and Social Sciences (PJCSS) Provided in Cooperation with: Johar Education Society, Pakistan (JESPK) Suggested Citation: Khan, Muhammad Azhar; Safdar, Nabeel; Manzoor, Wajiha (2024) : Financial reporting quality and investment efficiency: A transnational evidence, Pakistan Journal of Commerce and Social Sciences (PJCSS), ISSN 2309-8619, Johar Education Society, Pakistan (JESPK), Lahore, Vol. 18, Iss. 2, pp. 285-305 This Version is available at: https://hdl.handle.net/10419/301669 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc/4.0/ Pakistan Journal of Commerce and Social Sciences 2024, Vol. 18(2), 285-305 Pak J Commer Soc Sci Financial Reporting Quality and Investment Efficiency: A Transnational Evidence Muhammad Azhar Khan NUST Business School, National University of Sciences and Technology, Islamabad, Pakistan Email: azhar.phd19nb[email protected]st.edu.pk Nabeel Safdar (Corresponding author) NUST Business School, National University of Sciences and Technology, Islamabad, Pakistan Email: [email protected] Wajiha Manzoor Department of Economics, COMSATS University Islamabad, Pakistan Email: wajiha.manzoo[email protected] Article History Received: 18 Apr 2024 Revised: 23 June 2024 Accepted: 26 June 2024 Published: 30 June 2024 Abstract In developed markets, the connection between financial reporting quality (FRQ) and enhanced investment efficiency is well-documented. However, it remains uncertain whether this relationship holds true in emerging, frontier, and various other markets. This research probes into this relationship across 18,231 publicly listed firms spanning thirtysix countries worldwide, encompassing various market categories. Comprehensive accounting data is gathered for publicly traded firms from 2009 to 2023, spanning 40 different industries in these markets. We used Stata and employed fixed-effects regression analysis, augmented by alternative proxies and robustness investigation, causal connections are explored. The endogeneity concerns are addressed using 2SLS regression analysis. The findings disclose a positive influence of FRQ on investment efficiency not only in developed markets but also across emerging, frontier, and other markets. Furthermore, our analysis of overand under-investment scenarios highlights a significant relationship between FRQ and investment efficiency in both contexts. These findings expand the current body of knowledge, indicating that the relationship between FRQ and investment efficiency extends beyond developed markets to include emerging, frontier, and other markets with varied reporting standards and financial environments. Keywords: Financial reporting quality, investment efficiency, modified Jones model, emerging markets, developed markets, frontier markets. Financial Reporting Quality and Investment Efficiency 286 1. Introduction The literature delineates the efficiency of the firm in three forms. These are productive, labour and investment efficiencies. This study focuses only on the investment efficiency of the firm. The concept of investment efficiency refers to a firm's adeptness in pursuing ventures with positive NPV , as opposed to occurrences of overinvestment or underinvestment, characterised by engaging in negative NPV ventures or abstaining from positive NPV opportunities, respectively. This definition of efficiency is aligned with the overarching objective of firms to maximise shareholder wealth (Gomariz & Ballesta, 2014). On the other hand, financial reporting quality (FRQ) denotes the accuracy of the business accounts in the transmission of intuitions regarding a firm's operations, particularly crucial for equity investors, i.e., anticipated cash-flows (Biddle et al., 2009). Financial reporting serves as a means for firms to transmit business health, losses, operating hazards, and communications with equity investors (Trinh et al., 2022). However, challenges arise from information asymmetry, complicating oversight of firms (Renneboog & Szilagyi, 2020). Although existing literature has extensively examined the link between FRQ and the investment efficiency of a country within developed countries (e.g., Biddle, Hilary & Verdi, 2009; Gomariz & Ballesta, 2014), the gap in knowledge continues about this relationship in markets like emerging and frontier. Frontier markets, typically small in size and low in accessibility, often fall behind their emerging counterparts. Despite their potential, valuation challenges stemming from information asymmetry are prevalent in these markets (Alfraih, 2016). The significance of FRQ may be diminished, in emerging, frontier and other markets, owing to market failures that hinder shares’ price capability to imitate existing information of the firm. Particularly, information asymmetry may increase due to information paucity, as observed in the emerging stock market of China (Hussain et al., 2020). However, information produced by accounting reports remains crucial in these markets, potentially surpassing substitutive sources (Lopes, 2002). This study aims to investigate the impact of FRQ on the investment efficiency, expanding upon prior research by examining a universal context that encompasses emerging, frontier, and other markets, apart from developed markets. As the emerging, frontier, and other markets are branded by the prevalence of concentrated ownership, we anticipate that investment decisions will be made with moderate risks. Furthermore, distinguishing subtleties in earnings management practices in emerging and frontier markets lead to dissimilarities with markets with developed status (Martens, Yapa, & Safari, 2021; Lin & Wu, 2014). Khan, Safdar & Manzoor 287 To shed light on these complexities, we investigate the influence of FRQ on investment efficiency in publicly traded firms across developed, emerging, frontier, and other markets, providing a comprehensive perspective. We used accounting data from 2009 to 2023 for 18,231 firms across thirty-six countries. We used Stata software and employed regression using fixed effects, and a two-staged least square was used to address endogeneity. Our results disclose a positive link between financial reporting quality and investment efficiency in various types of emerging, frontier and other markets apart from developed markets. Our study contributes to the literature by extending the exploration of the FRQinvestment efficiency relationship to diverse markets, demonstrating a significant association in both under-investment and over-investment situations. Despite the prevalence of concentrated ownership and earnings management in emerging and frontier markets, the results reveal that the linkage between FRQ and investment efficiency is not context-dependent by providing transnational empirical evidence. The structure of this paper is organized into following sections. Section 2 delves into a review of pertinent literature, and subsequently proposes the hypotheses that will be tested. Section 3 elaborates on the research design and methodology, detailing the processes and techniques employed in the study. Section 4 presents the empirical findings, offering a thorough analysis and discussion of the results obtained from the research. Finally, Section 5 concludes the paper by summarizing the key contributions and implications of the study, highlighting its significance and potential impact on the field. 2. Literature Review The financial reporting standards and GAAP mandate the least requirements for revealing bookkeeping figures. These standards and principles may allow leeway in financial reporting, presenting opportunities for managers to exercise discretion, and may lead to adaptable conduct (Leuz et al., 2003). The managers of a firm with commendable performance may aspire to differentiate themselves by the use of greater FRQ, leveraging on the visible financial reports to highlight their firms’ invisible qualities (Zhang & Wiersema, 2009). Conversely, firms with low FRQ are frequently related to earnings management. They can yield antagonistic outcomes (Hickman et al., 2021; Lara, Osma, & Penalva, 2016), as exemplified in the Enron, Satyam Computer Services, and WorldCom cases. Managers' voluntary disclosure of information aligns with the agency (Jensen & Meckling, 1976) and signaling (Spence, 1973) theories (Alsos & Ljunggren, 2017; Yasar, Martin & Kiessling, 2020). Agency theory postulates that conflicts of interest arise due to the separation of power and control, which may provoke managers to make decisions that serve their personal objectives at the cost of shareholders or investors (Alam, Ramachandran, & Nahomy, 2020). Agency theory underscores a robust correlation between financial reporting disclosures and profitability, i.e., investment efficiency tester of a firm (Watson et al., 2002). Firms equipped with high-quality information exhibit reduced deviation from the suitable investment planes (Chen et al., 2011; McNichols & Stubben, 2008). The Financial Reporting Quality and Investment Efficiency 288 second guiding principle shaping the relationships among variables is signaling theory. This theory posits that corporate choices of managers are like signals from a firm to investors, reducing the asymmetry of information. It further proposes that proficient firms attempt to communicate their excellence to shareholders via the quality of their financial reporting, thereby diminishing asymmetries of information, bolstering the efficiency of investment, and fostering investors' confidence in managerial capabilities (Watson et al., 2002). The accounting literature indicates that accounting practices play a crucial role in guiding management's investment decisions and mitigating agency conflicts, integrates agent’s and shareholder’s objective functions, and diminishes the likelihood that manager acts against shareholders' interests (Bushman & Smith, 2001). An expectation model for investment is built by Richardson (2006) for measuring investment efficiency. This model bifurcates firms’ total investment as ‘maintenance’ and ‘new’ and reflects the use of residuals from ‘new’ investment as a substituting variable for investment efficiency. Qingyuan (2009) uses this model and provides empirical evidence that good accounting information quality is negatively related to overinvestment in firms. This finding aligns with the deduction by Fazzari, Hubbard and Petersen (1988) that investment efficiency increases when information asymmetry decreases. Biddle and Hilary (2006) empirically test the relationship between accounting information and investment efficiency and report a significant positive association. Chen, Hope, Li and Wang (2011) examine the non-traded private firms and document a significant positive effect of suitable financial reporting on the efficiency of investment. They state that quality accounting information mitigates the asymmetry of information and renders the finest quality of financial reporting necessary. Which in turn influence the investment decision making by the users of the reports. Evidence is available in developed markets that good financial reporting quality diminishes the propensity of overinvestment owing to better information environment and resultant monitoring by investors (Gomariz & Ballesta, 2014). They explain that when information relevant to a decision is distorted (i.e., there is high information asymmetry), it will result in suboptimal investment decisions in the form of overinvestment. Song (2016) reveals that good quality financial reporting curbs under-investment. The current study contends that good financial reporting quality limits managers from engaging in both underinvestment and overinvestment. Overinvestment is limited because good financial reporting quality restrains dishonest usage of free cash flows since outside investors have almost the same level of information as the managers have (Fazzari, Hubbard & Petersen, 1988; Gomariz & Ballesta, 2014). This precludes the consumption of funds by self-centered managers from accepting negative net present value projects and may prevent overinvestment. On the other hand, under-investment is limited because good accounting practices play a crucial role in guiding management's investment decisions and mitigating agency conflicts, integrates the agent’s and shareholder’s objective function, and diminishes the likelihood that the manager acts against shareholders' interests (Bushman & Smith, 2001; Song, 2016). These monitoring efforts for the alignment of Khan, Safdar & Manzoor 289 interests induce managers to accept positive net present value projects. Hence, the chances of underinvestment are reduced. When financial reporting quality is high in a firm, it helps in better identification of projects via true accounting numbers, which means internal decision-making is enhanced (Chen et al., 2011; Gomariz & Ballesta, 2014). Hence, investment efficiency is improved. In other words, managers of the firms having above average performance have incentive to send good signals, in the form of financial reporting quality, and resultantly the investment efficiency of the firm is enhanced owing to reduced information asymmetry. Against the backdrop of the prevalent agency issues of conflicts of interest and the need for signaling disclosure, this study proposes that high financial reporting quality significantly influences investment efficiency. This effect stems from several vital reasons. The first reason is that FRQ acts as a deterrent against conflicts of interest, thus nurturing improved investment decisions by facilitating in assortment of extra money-making ventures (Bushman & Smith, 2001). The second reason is that strong FRQ helps alleviate the asymmetry of information between investors and managers, thereby reducing monitoring costs (Chen, Hope, Li & Wang, 2011), which may lead to investment efficiency. The third reason is that better reporting quality empowers financiers to monitor and glean valued understandings from the investment activities of a firm, thereby bolstering investment decisions (Gomariz & Ballesta, 2014). By leveraging on the stated literature, this study anticipates that better FRQ displays a key part in improving investment efficiency across publicly traded firms in developed, emerging, frontier, and other markets. Consequently, the study formulates its hypotheses as follows: ➢ H1: FRQ has a significant positive impact on investment efficiency worldwide. ➢ H2: FRQ positively influences investment efficiency in developed markets. ➢ H3: FRQ positively affects investment efficiency in emerging markets. ➢ H4: FRQ positively impacts investment efficiency in frontier and other markets. 3. Research Methodology 3.1 Variable Measurement 3.1.1 Investment Efficiency and Financial Reporting Quality Investment Efficiency (IEb) is the dependent variable, which is measured by multiplying - 1 to the absolute value of the residues (Biddle et al., 2009). The higher the IEb values, the higher the investment efficiency. FRQ is the independent variable and is measured using modified Jones (FRQJ) (Dechow et al., 1995), Kothari et al. (2005) (FRQK) and McNichols and Stubben (2008) (FRQMS) models. To offset the bias of one proxy, use of multiple proxies is encouraged (Assad & Alshurideh, 2020). All of the FRQ measures are calculated by multiplying -1 to the absolute value of the residues of the models. The higher the FRQ values, the higher the financial reporting quality. Financial Reporting Quality and Investment Efficiency 290 3.1.2 Control Variables In line with previous literature, several control variables are included to alleviate the concerns of bias due to omitted variables. These variables encompass firm size (SIZE), the market value to book value ratio (MBR), the standard deviation (SD) of cash flows from operations (CFO), SD of sales (SALES), SD of all investments (INVEST), distress measure of the firm (ZSCORE), the assets’ tangibility of (TNG), leverage measure of the firm (LEV) and industry (INDUS), cash flows from operations to sales (OCFS), cash and shortrange investments to net PPE ratio (SLACK), age of the firm (AGE), a binary variable for the dividend payment (DIV) (1 for paying and 0 for non-paying firms), firm’s operating cycle (OPCYL), and a binary variable for loss (LOSS) (1 for negative EBIT firms and 0 otherwise). 3.2 Sample Description This study covers all publicly listed firms categorized according to the 48-industry classification of Fama & French, with financial and utility firms excluded owing to high regulatory constraints and comparability issues. Data is sourced from DataStream, spanning from 2009 to 2023, ensuring the final dataset of 157,908 firm-year observations across forty industries within thirty-six markets having developed, emerging, frontier, and other statuses. Classification of developed, emerging and frontier markets is based on criteria outlined by Morgan Stanley Capital International (MSCI), while the remaining markets are categorized as 'others'. The sample selection includes Australia, Belgium, Canada, Denmark, Finland, France, Germany, Hong Kong, Israel, Italy, Japan, Netherlands, Norway, Singapore, Spain, Sweden, UK and USA to represent developed markets. Emerging markets are exemplified by China, Greece, India, Indonesia, S. Korea, Kuwait, Malaysia, Philippines, Poland, South Africa, Taiwan, Thailand and Turkey. Whereas Jordan, Pakistan, Sri Lanka, Russia and Vietnam show representation of frontier and other markets. 3.3 Econometric Model Following is the baseline OLS panel regression to address the research questions: 𝐼𝐸𝑏(𝑗,𝑡) = ⍺0 + ⍺1𝐹𝑅𝑄𝑗,𝑡−1 + 𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠 + 𝑌𝑒𝑎𝑟 𝐹𝐸 + Ind FE + Con FE + ɛ𝑗,𝑡 (1) Where IEb(j,t) is the dependent variable investment efficiency for firm j in year t, FRQj,t-1 represents the financial reporting quality measure. Controls denote control variables and fixed-effects (FE) indicator variables for year (Year), Industry (Ind), and country (Con). The random error term is indicated by ɛ𝑗,𝑡. 4. Results and Discussion 4.1 Descriptive Statistics The sample consists of 18,231 firms across eighteen developed, thirteen emerging and five frontier and other markets, resulting in a total of 157,908 firm-year observations across thirty-six countries in the overall sample. A significant portion is represented by China, Khan, Safdar & Manzoor 291 India, Japan, South Korea, Taiwan, and the USA, contributing 11,837 firms with 114,837 observations (72% of 157,908). Conversely, the eight smallest constituents, including Belgium, Denmark, Finland, Greece, Jordan, Kuwait, Netherlands, and Norway, collectively account for 737 observations. The FF industry classification indicates that business services hold the largest share, followed by construction and business services, totaling 31,287 observations. Conversely, aircraft, uncategorized firms, and beer and liquor are the three smallest constituents in the sample, comprising 512 observations. We observe a substantial increase in observations in recent years. The descriptive statistics are presented in Table 1, which show observations, mean, maximum values, standard deviation (SD) and minimum values for the variables. Investment efficiency (IEb) displays the mean (SD) of -0.9 (86.3), FRQJ has -0.8 (5.8), FRQK has -0.2 (2.5), and FRQMS has -0.1 (5.3). The values are comparable with prior research (e.g., Gomariz & Ballesta, 2014). Pair-wise correlations are shown in Table 2. We see positive correlations between FRQ and investment efficiency measures. Table 1: Descriptive Measurements (A) Panel A: Full Sample Panel B: Developed Countries VARIABLES Obs. Mean SD Min. Max. Obs. Mean SD Min. Max. IEb 157,908 -0.9 86.3 -442.7 0.0 78,779 -0.8 23.7 -169.2 0.0 FRQJ 157,908 -0.8 5.8 -984.2 0.0 78,779 -1.4 8.1 -984.2 0.0 FRQK 157,908 -0.2 2.5 -470.4 0.0 78,779 -0.4 3.5 -470.4 0.0 FRQMS 157,908 -0.1 5.3 -208.0 0.0 78,779 -0.1 7.4 -208.0 0.0 SIZE 157,908 15.4 3.1 4.8 22.0 78,779 14.6 3.4 4.8 22.0 MBR 157,908 1.3 2.2 0.0 30.4 78,779 1.4 2.5 0.0 30.4 CFO 157,908 0.1 0.3 0.0 3.7 78,779 0.1 0.3 0.0 3.7 SALES 157,908 0.5 1.0 0.0 13.0 78,779 0.6 1.1 0.0 13.0 INVEST 157,908 0.1 1.8 0.0 286.3 78,779 0.1 2.5 0.0 286.3 ZSCORE 157,908 0.3 7.9 -112.0 4.8 78,779 -0.5 10.7 -112.0 4.8 TNG 157,908 0.3 0.2 0.0 1.0 78,779 0.3 0.3 0.0 1.0 LEV 157,908 0.2 0.2 0.0 0.9 78,779 0.2 0.2 0.0 0.9 INDUS 157,908 0.2 0.1 0.0 0.3 78,779 0.1 0.1 0.0 0.3 OCFS 157,908 -0.8 6.4 -61.7 1.4 78,779 -1.6 8.6 -61.7 1.4 SLACK 157,908 3.7 15.6 0.0 156.1 78,779 5.3 19.0 0.0 156.1 AGE 157,908 25.3 15.9 0.0 159.0 78,779 30.2 18.5 0.0 159.0 DIV 157,908 0.3 0.4 0.0 1.0 78,779 0.6 0.5 0.0 1.0 OPCYL 157,908 3.8 2.5 -3.3 9.1 78,779 3.4 3.0 -3.3 9.1 LOSS 157,908 0.1 34.0 0.0 1.0 78,779 0.3 0.4 0.0 1.0 Financial Reporting Quality and Investment Efficiency 292 Table 1: Descriptive Measurements (B) Panel C: Emerging Countries Panel D: Frontier & Other Countries VARIABLES Obs. Mean SD Min. Max. Obs. Mean SD Min. Max. IEb 75,281 -0.6 57.9 -151.6 0.0 3,630 -0.1 0.3 -12.1 0.0 FRQJ 75,281 -0.2 0.5 -80.5 0.0 3,630 -0.2 0.1 -1.4 0.0 FRQK 75,281 -0.1 0.1 -7.2 0.0 3,630 -0.1 0.1 -0.7 0.0 FRQMS 75,281 0.0 0.1 -9.7 0.0 3,630 0.0 0.1 -1.1 0.0 SIZE 75,281 16.0 2.4 5.5 22.0 3,630 18.8 2.7 7.5 22.0 MBR 75,281 1.3 1.9 0.0 30.4 3,630 0.5 1.0 0.0 24.6 CFO 75,281 0.1 0.2 0.0 3.7 3,630 0.1 0.2 0.0 3.7 SALES 75,281 0.5 1.0 0.0 13.0 3,630 0.6 1.1 0.0 13.0 INVEST 75,281 0.1 0.3 0.0 29.4 3,630 0.0 0.0 0.0 0.5 ZSCORE 75,281 1.2 2.7 -11.0 4.8 3,630 1.1 3.7 -112.0 4.8 TNG 75,281 0.3 0.2 0.0 1.0 3,630 0.3 0.3 0.0 1.0 LEV 75,281 0.1 0.2 0.0 0.9 3,630 0.2 0.3 0.0 0.9 INDUS 75,281 0.2 0.1 0.0 0.3 3,630 0.2 0.1 0.1 0.3 OCFS 75,281 0.0 2.0 -61.7 1.4 3,630 -0.1 2.2 -61.7 1.4 SLACK 75,281 2.0 10.6 0.0 156.1 3,630 1.5 9.1 0.0 156.1 AGE 75,281 20.4 10.1 1.0 117.0 3,630 15.6 9.4 0.0 64.0 DIV 75,281 0.7 0.5 0.0 1.0 3,630 0.6 0.5 0.0 1.0 OPCYL 75,281 4.2 1.7 -3.3 9.1 3,630 4.3 1.8 -3.3 9.1 LOSS 75,281 0.5 0.2 0.0 1.0 3,630 0.1 0.3 0.0 1.0 Table 2: Pair-wise Correlations (A) Variables 1 2 3 4 5 6 7 8 9 10 (1) IEb 1 (2) FRQJ 0.201 1 (3) FRQK 0.210 0.179 1 (4) FRQMS 0.183 0.001 0.001 1 (5) SIZE 0.009 0.139 0.104 0.011 1 (6) MBR -0.033 -0.156 -0.135 -0.005 -0.366 1 (7) CFO -0.001 -0.124 -0.124 -0.005 -0.358 0.416 1 (8) SALES 0.001 -0.027 -0.03 -0.002 -0.158 0.157 0.624 1 (9) INVEST -0.04 -0.019 -0.025 -0.007 -0.034 0.026 0.042 0.134 1 (10) ZSCORE 0.03 0.194 0.148 0.008 0.411 -0.578 -0.466 -0.133 -0.037 1 (11) TNG -0.001 -0.003 0.01 0.004 0.108 -0.135 -0.088 -0.101 0.009 0.04 (12) LEV 0.001 0.021 0.021 -0.001 0.23 -0.241 -0.125 -0.092 -0.008 0.065 (13) INDUS 0.001 0.036 0.039 -0.008 0.223 -0.174 -0.107 -0.017 -0.012 0.116 (14) OCFS 0.001 0.078 0.063 0.004 0.26 -0.223 -0.173 -0.009 -0.024 0.35 (15) SLACK -0.001 -0.032 -0.024 -0.001 -0.169 0.134 0.124 0.036 0.004 -0.092 (16) DIV 0.001 0.019 0.022 0.006 0.229 -0.116 -0.063 -0.021 -0.002 0.041 (17) AGE 0.002 0.054 0.052 0.008 0.434 -0.173 -0.214 -0.106 -0.014 0.22 (18) OPCYL 0.005 0.064 0.037 0.001 0.156 -0.148 -0.13 -0.041 -0.018 0.181 (19) LOSS -0.006 -0.046 -0.06 -0.006 -0.383 0.185 0.189 0.022 0.016 -0.332 Khan, Safdar & Manzoor 299 Table 6: Split Sample Analysis Dependent variable: Investment Efficiency (IEb) Panel A: China, India, Japan, S.Korea, Taiwan and the USA Panel B: Other Countries Variables 1 2 3 4 5 6 FRQJ 0.030*** 0.0694** (4.0084) (2.2523) FRQK 0.0145* 1.84*** (1.7261) (2.6991) FRQMS 0.2673* 14.1*** (1.7775) (2.642) Observations 114,387 114,387 114,387 43,521 43,521 43,521 R-sq. 0.1135 0.1467 0.1173 0.1195 0.1894 0.1354 Country/Ind./Year FE Yes Yes Yes Yes Yes Yes CONTROLS Yes Yes Yes Yes Yes Yes Notes: For the table's brevity, control variables are omitted. FE (Country, Industry and Year) panel OLS regressions are employed. t-Stats (in parentheses) clustered at firm level robust to heteroscedasticity. *** p<0.1, ** p<0.05, * p<0.01 We investigate the correlation between FRQ and IEb by utilizing Eq. (1), employing different proxies as compared to those utilized in the baseline regressions. We ensure the robustness of our findings by employing alternative measures for IE and FRQ to mitigate any potential biases due to use of any proxy This approach is used to enhance the reliability and validity of our results along with consistency. Our alternative metric for Investment Efficiency (IEc) is derived from Chen et al. (2011), incorporating sales growth opportunities and potential losses into the determination of expected investment levels for a given year. Similarly, the alternative measure for Financial Reporting Quality (FRQ) remains consistent. Table 7 explains the results using Eq. (1), In Panel A, the alternative measure of Investment Efficiency (IEc) is employed alongside the same three FRQ proxies utilized in the baseline regression. Panel B, on the other hand, utilizes alternative measures of Financial Reporting Quality (FRQagg) in conjunction with the alternative proxy for investment efficiency (IEc). Across all proxies the findings consistently demonstrate a significant and positive association between the alternative measure of FRQ and IEc, Financial Reporting Quality and Investment Efficiency 300 Table 7: Alternative Measures of Baseline Models Panel A: Alternative measures of IE Panel B: Alternative measures of FRQ and IE: Alternate measure IEc IEc IEc IEc & FRQagg Variables 1 2 3 4 FRQJ 0.1807* ** (2.9486) FRQK 1.4173* * (2.3102) FRQMS 8.4901* * (2.3677) FRQagg 0.2114*** (4.0725) Observations 157,908 157,908 157,908 157,908 R-squared 0.1208 0.1853 0.1828 0.1715 Country FE Yes Yes Yes Yes Industry FE Yes Yes Yes Yes Year FE Yes Yes Yes Yes CONTROLS Yes Yes Yes Yes Notes: For the table's brevity, control variables are omitted. FE (Country, Industry and Year) panel OLS regressions are employed. t-Stats (in parentheses) clustered at firm level robust to heteroscedasticity. *** p<0.1, ** p<0.05, * p<0.01 4.5 Endogeneity Test Our initial analysis operates under the assumption that FRQ influences investment efficiency (IEb), supported by a solid theoretical framework and a comprehensive array of control and auxiliary variables. However, in this section, we consider the possibility that the observed relationships between FRQ and IEb may be affected by the endogenous nature of FRQ. To address this concern, we employ a Two-Staged Least Squares (2SLS) approach. Previous research, as demonstrated by studies like Chin, Chen and Hsieh (2009), Huang (2022) and La Porta et al. (1997), have extensively documented that countries with common-law jurisdictions typically provide a more conducive institutional environment for business operations. Additionally, research by Dayanandan, Donker, Ivanof and Karahan (2016) reveals that these jurisdictions show high financial transparency levels and disclosures, indicative of stronger FRQ as opposed to civil-law jurisdictions. Leveraging on this knowledge, we introduce an instrumental variable termed "IPcc" for the study encompassing thirty-six markets from emerging, frontier, and other categories apart from the main developed markets. This indicator variable is assigned a value of 1 for commonlaw jurisdictions and 0 for civil-law jurisdictions. In the first-stage of our analysis, we regress the aggregate measure of FRQ (FRQagg) on IPcc and calculate the predicted value of FRQp. This allows us to capture the variation in FRQ attributable to legal origins, thus mitigating potential endogeneity concerns. Subsequently, in the second-stage, we use FRQp in the baseline analysis to assess its impact on investment efficiency. Khan, Safdar & Manzoor 301 In the two-stage analysis, as depicted in Table 8, we find that our results stay robust across all four panels, indicating that the relationship between FRQ and investment efficiency persists even after addressing potential endogeneity issues. Table 8: 2SLS Estimation (A) Panel A: Full Sample Panel B: Developed Countries Stage 1 Stage 2 Stage 1 Stage 2 VARIABLES FRQagg IEb FRQagg IEb 1 2 3 4 IPcc 0.693*** 0.997*** (6.084) (4.1177) FRQp 2.856*** 2.467*** (2.7836) (5.5493) Observations 157,908 157,908 78,997 78,997 R-sq. 0.1332 0.1246 0.1313 0.1213 Country/Ind./Year FE Yes Yes Yes Yes CONTROLS Yes Yes Yes Yes Table 8: 2SLS Estimation (B) Panel C: Emerging Countries Panel D: Frontier and Other Countries Stage 1 Stage 2 Stage 1 Stage 2 VARIABLES FRQagg IEb FRQagg IEb 5 6 7 8 IPcc 0.052*** 0.027*** (7.9984) (2.8979) FRQp 1.409** 0.026** (2.3492) (2.5197) Observations 75,281 75,281 3,630 3,630 R-sq. 0.0907 0.0948 0.0826 0.1901 Country/Ind./Year FE Yes Yes Yes Yes CONTROLS Yes Yes Yes Yes Notes: For the table's brevity, control variables are omitted. FE (Country, Industry and Year) panel OLS regressions are employed. t-Stats (in parentheses) clustered at firm level robust to heteroscedasticity. *** p<0.1, ** p<0.05, * p<0.01 5. Conclusion and Recommendations Our study rigorously examined the impact of Financial Reporting Quality (FRQ) on investment efficiency across a substantial sample of 18,231 publicly listed firms where research in the domain of emerging, frontier, and other markets is relatively sparse, with few existing studies exploring this multifaceted landscape only in developed markets. Spanning the period from 2003 to 2022, our analysis encompassed a diverse sample of Financial Reporting Quality and Investment Efficiency 302 thirty-six countries, including developed, emerging, frontier, and other markets. The regression outcomes revealed that heightened financial reporting quality not only boosts investment efficiency within developed countries but also outspreads its beneficial impact on the emerging, frontier, and other market segments. This outcome is consistent with existing literature, reaffirming FRQ's role as a monitoring tool that mitigates agency issues, consequently aiding in making optimal investment choices. Further investigation into overand under-investment scenarios within our sample yielded results consistent with those observed in the overarching investment efficiency model, thereby strengthening the influence of FRQ across a spectrum of markets, including developed, emerging, frontier, and others. Our study adds valuable insights to the investment efficiency literature by highlighting the substantial and positive impact of heightened FRQ on investment efficiency across a diverse range of publicly listed firms, encompassing developed, emerging, frontier, and other countries. Notably, our findings resonate with previous research conducted by Houcine et al. (2022) on publicly listed firms in developed countries and by Khan et al. (2024) in emerging and frontier countries. This consistency in results underscores the robustness of the relationship between FRQ and investment efficiency, even in settings characterized by lower levels of FRQ, such as frontier and other markets. Despite the inherent complexity of including both common-law and civil-law economies in the selected sample, the findings of the study endure congruence with those observed in developed economies, further strengthening the validity of our results. This study holds substantial implications within the institutional context of emerging and frontier economies, encompassing thirty-six countries with diverse legal frameworks. These implications are broad, affecting investors evaluating firms' investment efficiency, managers developing appropriate reporting and investment strategies, and policymakers formulating effective national and international policies related to accounting and financial reporting for publicly listed companies. Our research provides valuable insights that could motivate firms to enhance their ethical standards and adhere to regulations more strictly, thus contributing to the efficient functioning of the market by reducing agency issues of moral hazard or adverse selection. Nevertheless, our study has its limitations that warrant acknowledgement. This study focuses to explore the connection between FRQ and investment efficiency in transnational environments. Nevertheless, it is conceivable that the country-level corporate governance, financial constraints faced by the firms, risk-taking inclination of the managers and other factors also play a role in the stated relationship. Hence, upcoming research studies could investigate these factors and their potential influence on the relationship between FRQ and investment efficiency. Acknowledgement The authors acknowledge the valuable inputs of the participants of the international conference titled ‘ICBELLP-2024’ arranged by Eurasia Research. 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