Do bank stock prices efficiently reflect the information content in a key tax reform event?

Ahmad, Ahmad; Rumman, Ghaleb Abu; Idris, Mohammed; Allozi, Nurah; Melhem, Muntaser J. Article Do bank stock prices efficiently reflect the information content in a key tax reform event? Cogent Economics & Finance Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Ahmad, Ahmad; Rumman, Ghaleb Abu; Idris, Mohammed; Allozi, Nurah; Melhem, Muntaser J. (2024) : Do bank stock prices efficiently reflect the information content in a key tax reform event?, Cogent Economics & Finance, ISSN 2332-2039, Taylor & Francis, Abingdon, Vol. 12, Iss. 1, pp. 1-17, https://doi.org/10.1080/23322039.2024.2411559 This Version is available at: https://hdl.handle.net/10419/321623 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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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/4.0/ Cogent Economics & Finance ISSN: 2332-2039 (Online) Journal homepage: www.tandfonline.com/journals/oaef20 Do bank stock prices efficiently reflect the information content in a key tax reform event? Ahmad Ahmad, Ghaleb Abu Rumman, Mohammed Idris, Nurah Allozi & Muntaser J. Melhem To cite this article: Ahmad Ahmad, Ghaleb Abu Rumman, Mohammed Idris, Nurah Allozi & Muntaser J. Melhem (2024) Do bank stock prices efficiently reflect the information content in a key tax reform event?, Cogent Economics & Finance, 12:1, 2411559, DOI: 10.1080/23322039.2024.2411559 To link to this article: https://doi.org/10.1080/23322039.2024.2411559 © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group Published online: 16 Oct 2024. Submit your article to this journal Article views: 471 View related articles View Crossmark data Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=oaef20 FINANCIAL ECONOMICS | RESEARCH ARTICLE Do bank stock prices efficiently reflect the information content in a key tax reform event? Ahmad Ahmad a , Ghaleb Abu Rumman a , Mohammed Idris b , Nurah Allozi c and Muntaser J. Melhem a a Department of Accounting, The University of Jordan, Amman, Jordan; b Department of Accounting, Faculty of Business, Applied Science Private University, Amman, Jordan; c Department of Accounting, School of Business, The University of Jordan, Amman, Jordan ABSTRACT This study examines the behavior of bank stock prices in Jordan in relation to a significant tax reform event. We analyze a sample of all banks listed on the Amman Stock Exchange to study the market response to the Amended Income Tax Law 2018. In the proposal period, investors were anticipating a mandatory tax increase of 5%, though the enacted law differed from expectations by implementing only a temporary, slight tax increase of 3%. Our findings reveal that there are higher stock returns observed during the post-approval period of the Amended Income Tax Law 2018 compared to the preapproval period. This holds for both individual stocks and portfolios, indicating a positive market response to the tax reform. This paper contributes to the existing body of literature that examines pricing anomalies. The findings of this study indicate that when a tax bill is passed with a corporate tax rate lower than the proposed level, it creates a positive earnings surprise. However, the market displays inefficiency in promptly revising its expectations, resulting in a delay in the stock return pattern. This suggests that there is a discrepancy between the market’sreactionasimpliedbytheefficientmarkethypothesis and the actual impact of the tax reform on bank stock prices. IMPACT STATEMENT This study investigates the impact of a significant tax reform event on the behavior of bank stock prices in Jordan. Using event study methodology, the research examines whether the market responds rationally to the earnings news related to the establishment of the National Solidarity Account, comprising 3% of banks’taxableincomeunder the enacted Amended Income Tax Law 2018, compared to a higher increase of 5% of banks' taxable income proposed during the pre-approval period of the tax law. The findings suggest that tax laws influence financial markets and affect stock prices, as stock investors extrapolate their prior negative expectations into the future making it possible to trade based on this macroeconomic event. Investor sentiment, limited attention capacity, overconfidence, and anchoring bias could lead investors to react irrationally to actual statistics on the release date by taking prior forecasts at face value. The study has important implications for academics, practitioners and policymakers. ARTICLE HISTORY Received 13 November 2023 Revised 18 September 2024 Accepted 27 September 2024 KEYWORDS Tax reform; earnings surprises; bank stocks; market reaction; market efficiency SUBJECTS Accounting; Finance; Macroeconomics 1. Introduction Corporate income taxes are a challenging aspect of revenue policy for governments, as taxes reduce the earnings and cash flows available for common stock holders, inhibit the potential of their investments, and create risks that adversely affects stock prices (e.g. Ardagna, 2009; Arin et al., 2009; Blouin et al., 2009; Dai et al., 2008; Gaertner et al., 2020; Golob, 1995; Lang & Shackelford, 2000; Wang & Macy, 2022). Chang et al. (2017) point out that taxes have significant economic implications and that firms can increase their dividends and stock prices when corporate taxes are reduced. Erosa and Gonz alez (2019) demonstrate that taxes harm after-tax income, reducing firms’growth potential. Indeed, the role of CONTACT Ahmad Ahmad [email protected] Department of Accountings, The University of Jordan, Amman, Jordan ß2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. COGENT ECONOMICS & FINANCE 2024, VOL. 12, NO. 1, 2411559 https://doi.org/10.1080/23322039.2024.2411559 earnings in stock prices is very well emphasized (e.g. Huang et al., 2015; Johnson & Zhao, 2012; Le et al., 2019; Miller, 2005; Park et al., 2014). During the pre-approval period of the Amended Income Tax Law (AITL) in Jordan dated Sunday, 2 December 2018, a new tax bill proposed to increase the corporate tax rate of banks from 35% to 40%, which the market may perceive as negative earnings news. However, the enacted AITL 2018 did not approve this 5% increase, instead maintaining the 35% tax rate and establishing the National Solidarity Account consisting of 3% of banks’taxable income. The revenues of this account shall be allocated in the general budget to settle the public debt. This account is mandatory as long as the country has public debt. The study conducted by He and Li (2020) introduces the concept of using the prior day’s average earnings surprise as a reference point for investors who experience cognitive constraints when processing information. This reference point serves as a benchmark for their decision-making process. On the other hand, Hartzmark and Shue (2018) explore the impact of errors in investors’perceptions rather than their expectations. Their research highlights how these perceptual errors can influence investment decisions and subsequently affect market outcomes. Both studies shed light on different aspects of investor behavior and decision-making, emphasizing the role of cognitive limitations and perceptual errors in shaping market dynamics. Following these studies, we test whether investors use prior tax news based on the higher tax rate proposal, as a relevant earnings reference point and classify the AITL 2018 announcement date as containing positive earnings news. Second, because earnings news has information content related to stock prices (e.g. Bouteska & Regaieg, 2017;Choy&Zhang,2021;Ozo&Arun,2019;Sponholtz,2008; Syed & Bajwa, 2018), we explore whether the less-experienced individual investors in the Amman Stock Exchange (ASE), who constitute a relatively high proportion, extrapolate their pessimism into future, pushing prices below their fundamental values. Put differently, we aim to determine the outcome if stock investors could adjust their expectations about the earnings surprise at the time the tax bill was signed into law, but failed to efficiently reflect this updated information quickly, making it possible to trade on that basis. We contribute to the existing literature by utilizing data on banks, which constitute the dominant economic sector in Jordan, to examine the market reactions to a key tax reform event. 1 This study differs from prior work in several ways. First, we compare the buy-and-hold returns (BHRs) of the sample banks in the preand post-AITL 2018 approval periods based on individual stocks and portfolios. 2 The portfolio approach has the advantage of diversifying away the most unsystematic risks. Second, when using the portfolio approach on a value-weighted basis, we recalculate a bank’s market capitalization for the preand post-approval periods. Third, we employ panel regression methods to test for the effect of the tax reform on the stocks’cumulative abnormal returns (CARs). We check the robustness of the results by comparing the results of the BHRs and CARs. Fourth, we rely heavily on the efficient market hypothesis (EMH) to consider how the market integrates publicly available information into stock prices using four test windows from the event date. According to Lagoarde-Segot and Lucey (2009), the ASE is the most efficient market in the Middle Eastern region. Finally, to the best of our knowledge, this is the first study to explore stock price behavior in the banking sector around a key tax reform event in the region. The remaining sections of the article are structured as follows: Section 2 provides a concise review of the pertinent literature and establishes the research hypotheses based on the existing knowledge in the field. Section 3 outlines the data utilized in the study and explains the empirical methodology employed to analyze the data. Section 4 presents the primary findings of the study. Finally, section 5 concludes the article, summarizing the main findings, discussing their implications, and suggesting avenues for further research. 2. Theoretical framework and hypothesis development Our analysis is grounded in the Efficient Market Hypothesis (EMH), which suggests that stock prices fully reflect all available information (Fama, 1970). EMH states that any new information, including tax law changes, should be quickly integrated into stock prices, leaving no room for abnormal returns based on publicly available data. However, empirical evidence suggests that tax laws do influence financial markets and thus affect stock prices, albeit in ways that may sometimes seem at odds with the predictions of EMH (Chudek et al., 2011; Eichfelder & Lau, 2014; Wagner et al., 2018a,2018b; Wang & Macy, 2021). Tasnia et al. (2021) posit that investors are tax-averse, finding a positive association between taxes and the volatility of bank returns. Stock price reactions to tax changes largely depend on the 2 A. AHMAD ET AL. unanticipated component of a tax announcement, as documented by P astor and Veronesi (2012). Wang and Macy (2021) examine how markets in different countries react to corporate tax cuts using a global dataset covering 16 years starting from 2002. Their findings indicate that the greater the tax decrease, the higher the abnormal returns earned by investors. Moreover, they observe that sample markets reacted to expected tax changes well before and continued after the tax change, challenging the assumption that markets fully and immediately integrate economic effects as the EMH would imply. Wagner et al. (2018a) explore the market reaction to the election of Donald J. Trump as U.S. president in 2016 by regressing abnormal stock returns on cash effective tax rates (ETR), with abnormal returns estimated using both the capital asset pricing model and the Fama-French three-factor model. Anticipating large tax cuts, they found excess returns positively (negatively) associated with high (low) tax-paying corporations. Moreover, firms with substantial deferred tax liabilities outperformed those with deferred tax assets. Wagner et al. (2018b) extend this work by investigating stock market reactions to the Tax Cuts and Jobs Act of 2017 during its legislative period. They found a significant positive coefficient on the ETR explanatory variable for the full legislative period, suggesting that highly taxed corporations benefited more from the new tax law and thus outperformed firms with low taxes. However, the evidence on the relationship between corporate taxes and stock returns is mixed. Gaertner et al. (2020) observed heterogeneous stock price reactions around the U.S. Tax Cuts and Jobs Act of 2017 across different foreign exchanges. Chinese firms suffered significant negative returns, while firms in other sample countries experienced positive returns. Wang and Macy (2022) studied market responses to large corporate tax cuts in European countries, finding positive cumulative abnormal returns (CARs) for Slovakia and Germany, but negative returns for Poland and Austria. The researchers attributed the unexpected negative returns in Poland and Austria to noise or simultaneous events offsetting the expected benefits from the tax cuts. Further inconclusive evidence exists. Muthitacharoen (2021) found an adverse relationship between corporate taxes and investments in less developed countries. Sankarganesh and Shanmugam (2021) documented a similar adverse relationship between effective taxes and corporate investments. Dobbins and Jacob (2016) report an inverse relationship between marginal corporate taxes and investments by local firms. Conversely, Gary et al. (2016) observed significant growth in intercorporate investment following increases in corporate marginal tax rates, which they attributed to firms redirecting excess resources from less attractive internal expansion to more attractive equity investments. Finally, corporate income taxes and the potential for future payouts are key determinants of firms’ resource allocation. Venezian (2007) emphasized that, in addition to tax changes, stock prices also depend on firms’future payouts. Wong et al. (2017) showed that news of dividend tax reductions led to significant excess returns. Similarly, Becker et al. (2013) demonstrated that elevated dividend taxes encourage profitable firms to finance their investments internally. Campbell et al. (2013) found that lower taxes on firms’payouts improve corporate investment. Market efficiency requires stock prices to reflect publicly available events fast enough that any observed abnormal returns are a mere luck. In a tax context, Eichfelder and Lau (2014) find a delayed market response to tax announcements, caused mainly by investors who are not fully tax-aware, making trading on that basis a plausible investing strategy. Adam et al. (2015) demonstrate that in response to a tax change, less sophisticated investors emphasize past performance relative to more sophisticated investors, which drives assets prices away from fundamentals, creating the opportunity for wealth reallocation. Additionally, Wagner et al. (2018a,2018b) observe stock price anomalies in response to tax changes. Specifically, investors require a long time to fully integrate the information about the tax change, and they find that abnormal returns exhibit a non-monotonic pattern. The earnings-related literature adds to the debate on why stock prices may deviate from the EMH. (e.g. Birz, 2017; Chudek et al., 2011; Ekholm, 2006; Gervais & Odean, 2001; Gilbert et al., 2012; Jacobs & Weber, 2012). According to Birz et al. (2021), anchoring bias makes investors unable to correctly recognize the surprise component of macroeconomic announcements, and they therefore react irrationally to actual statistics upon their release, taking prior forecasts at face value. Using Chinese data to test the market reaction to releases of earnings news, Feng and Hu (2014) report that behavioral bias can explain investors’initial underreaction at the earnings announcement date. The authors also document that the more earnings announcements occurring on the same day, the weaker the immediate market response COGENT ECONOMICS & FINANCE 3 and the stronger the post-announcement drift. Similarly, Hirshleifer et al. (2009) observe that investors become confused if they perform multiple analyses simultaneously, attributing this irrational behavior to investors’limited attention. A more recent study by Dong et al. (2022) emphasizes that investor attention distorts stock prices. Wagner et al. (2018b) make similar arguments in the taxation context. Further evidence that the market cannot properly price capital assets is based on investor sentiment, where investor emotions irrationally drive stock prices (e.g. Abdelhedi-Zouch & Ghorbel, 2016; Karavias et al., 2021; Ke & Sieracki, 2019). Investor sentiment plays an important role in investor fund selection decisions (e.g. Jiang & Y€ uksel, 2019). Using data from Finnish companies, Ekholm (2006) finds systematic differences between large investors representing the minority and smaller investors representing the majority. While large investors are less willing to sell after good earnings news, small investors are more likely to sell. Ekholm (2006) attributes the irrational behavior of smaller investors reducing their holdings following good public news to overconfidence. Rational large (irrational small) investors exhibit less overconfidence (more overconfidence) when perceiving good public news as correct (less correct). Ekholm (2006) draws on Gervais and Odean (2001), who find that inexperienced new traders who are successful can become overconfident, highly crediting their skills. Over time, inexperienced traders will learn, become more sophisticated, and thus become less overconfident. The researchers conclude that the market will always have new, irrational, overconfident traders. Thus, the rationality with which the Jordanian market reacts to tax-related macroeconomic announcements is unclear. Unsophisticated individual investors, who tend to be irrational and driven by attention and emotions, represent 35% of all investors in the ASE. 3 Therefore, we propose that investors in Jordan’s banking sector mistakenly exhibit contrasting effects when they look at the current earnings surrounding the AITL 2018 event date by reacting to the extra and temporary (based on the existence of public debt) tax of 3% in terms of the earnings news in the pre-approval period when the proposed tax bill suggested a higher, permanent tax rate of 5%, and classify the new tax law as containing positive earnings news. Hence, we would find a positive market reaction (see: Hartzmark & Shue, 2018). Again, in light of the theoretical rationale of the efficient market hypothesis (EMH), stock prices comprehensively encompassing existing information, and additional information is promptly and precisely assimilated into stock prices (Beechey et al., 2000). In relation to tax reform event (AITL 2018), the announcement and following approval of the tax reform act can be considered substantial information that has the potential to impact the financial performance of banks (Hellwig, 2009;Huangetal.,2019). Hence, during the preapproval period, market participants may have harbored uncertainties regarding the outcome and potential consequences of the tax reform. Accordingly, the prices of bank stocks might not have fully reflected the anticipated effects of the reform. Nevertheless, subsequent to the approval of the tax reform act, the market gains clarity concerning the specific provisions and their impact on the financials of banks. Looking more closely at the case of Jordan, the banking sector notably plays a crucial role in the development of its economy (Mohammad & Darwish, 2022), and any significant regulatory or policy changes can have a significant impact on the financial performance and investor sentiment towards banks. In the context of emerging markets like Jordan, the market dynamics can be influenced by various factors, including information asymmetry, investor sentiment (Healy & Palepu, 2001) and informal institutions (Melhem & Darwish, 2023). The latter adds a significant layer of informality to the flow of market and regulatory news that could be accessed by informal networks’actors. During the pre-approval period of AITL 2018, investors in Jordan’s banking sector might have faced uncertainty regarding the specific provisions and implications of the proposed tax reform. The emerging market context, combined with potential information asymmetry and limited financial information, may have caused market participants to exhibit caution and delay their reactions to the expected impact of the tax reform. However, after the tax reform act is approved, the market receives clarity on the tax provisions and their implications for banks operating in Jordan. This increased transparency and understanding among market participants can lead to a reassessment of the information and a more informed valuation of bank stocks. Hence, in the context of Jordan, the market’s response to the tax reform event is likely to be more pronounced. The positive news of a lower-than-expected tax increase can generate optimism and enhance investor confidence in the banking sector. Alternatively, this could be accessed by informal network actors prior to the news release considering the salience of informal networking 4 A. AHMAD ET AL. modes in Jordan. Consequently, this positive sentiment can drive higher demand for bank stocks, resulting in increased BHRs during the post-approval period compared to the pre-approval period in Jordan. Hence, we propose the following hypothesis: H1: For banks listed on the ASE, the BHRs on individual stocks are higher for the AITL 2018 post-approval period than in the pre-approval period. Notably, the impact of a tax reform event on bank stock prices can extend beyond individual stocks to influence the overall performance of the sector. According to portfolio theory, investors often adopt diversification strategies to manage risk and enhance returns (Scholtens, 2009). Given the economic significance of the banking sector, it represents a crucial component of investment portfolios. Tax reform events, such as the AITL 2018, can significantly affect the financial prospects and performance of multiple banks within a portfolio simultaneously (Hemmelgarn & Teichmann, 2014). Furthermore, tax reforms introduce systemic risk to the banking sector, as changes in tax policies can impact the profitability and financial health of banks, leading to a collective response in the market (Hellwig, 2009; Huang et al., 2019). In an emerging market like Jordan, where market participants may exhibit higher sensitivity to systemic risk factors, the post-approval period of a tax reform event can trigger a more pronounced reaction, influencing the performance of the entire banking sector portfolio. Investor sentiment and market efficiency also play significant roles in portfolio performance. As suggested by the EMH, markets should quickly and accurately incorporate new information, including tax reforms. However, deviations from this ideal, such as delayed reactions or investor sentiment-driven behavior, can result in significant shifts in portfolio performance (Gao et al., 2021). Positive news, such as a lower-than-expected tax increase, can boost investor confidence, leading to increased buying interest in bank stocks and driving up the prices of individual stocks within the portfolio. This positive market sentiment could contribute to higher BHRs for the portfolio during the post-approval period compared to the pre-approval period. Taking these factors into account, we propose the following hypothesis: H2: For banks listed on the ASE, the BHRs on a portfolio consisting of all stocks is higher for the AITL 2018 post-approval period than in the pre-approval period. Wang and Macy (2022) emphasize the market’s forward looking. Consequently, by the time a tax bill becomes law as on the event date, regressing the abnormal stock returns on the AITL 2018 differential tax effect should yield a positive coefficient. It can also be argued that changes in tax policies can directly impact earnings of firms (see, for example, Guenther, 1994). In the case of the AITL enactment, banks in Jordan may experience variations in their tax liabilities and potential adjustments in their financial statements. Market participants, including investors and analysts, are likely to incorporate these earnings implications into their expectations and valuation models. Also, as the efficient market hypothesis suggests, stock prices reflect all available information, including earnings surprises; positive earnings surprises, which occur when actual earnings exceed market expectations, often lead to upward stock price adjustments (see Beechey et al., 2000). In the context of the AITL enactment, if the earnings implications are perceived as positive by the market, banks’cumulative abnormal stock returns are expected to be positively affected. Our third hypothesis is therefore: H3: For banks listed on the ASE, cumulative abnormal stock returns are positively affected by the earnings implications of the AITL enactment on 2 December 2018. 3. Data and methodology 3.1 Data The main data consist of the daily returns for all 15 banks listed on the ASE from Sunday, 11 November 2018 to Thursday, 20 December 2018. Thus, we consider bank returns for 30-working days consisting of two equal periods: 15 days before and 15 days after the AITL 2018 announcement date when it was enacted into law (referred to as the event date). We collected stock prices directly from the ASE’s official website (https://www.ase.com.jo). No stock price restatements or cash dividend adjustments were needed as no capital changes such as stock splits, scrip issues, or declarations of cash dividends COGENT ECONOMICS & FINANCE 5 occurred during this sample period. Finally, we calculated the study variables using banks’data for the third and fourth quarters of 2014-2018 from https://www.ase.com.jo/en/disclosures. 3.2 Methodology We employ an event study methodology to investigate the consequences of the AITL 2018 on banks’ stock prices in Jordan. More specifically, we use data on all 15 banks listed on the ASE to examine whether investors in the banking sector efficiently perceived the earnings-related effects of the tax law enacted on 2 December 2018. As the ASE does not maintain a stock return file, starting from 11 November 2018 to 20 December 2018, we estimate individual stock returns as the difference between the stock price on day tand the price on day t-1, divided by the price on day t-1. For a day twith no trading, and therefore no price record, we use the value for t-1, following a similar approach as Wagner et al. (2018b). Then, we explore the AITL 2018 post-approval estimated differential tax effect on banks’stock prices using three main approaches. First, we compare the 15 stock return observations before and after the event date using 15 counterpart-test periods starting from one day, and accumulated daily until the longest of 15 working days. For this purpose, we analyze the BHRs, which is a common metric in research (e.g. Dorey et al., 2017; Jegadeesh & Titman, 1993; Vo & Truong, 2018;Gangetal.,2019; Boussaidi & Dridi, 2020; Barbopoulos et al., 2020;Ahmadetal.,2021; Ahmad & Abu-Ghunmi 2021). For stock i,theBHRs i accumulated over period tare: BHRit ¼Y t t¼0 ½1þRit−1, (1) where R it is the simple daily return on stock iduring period t. Extending the event windows on a daily basis allows us to observe if the market needs time before it fully absorbs any tax-related effect. We applied the Mann Whitney Utest to check the equality between the paired BHRs. After applying the first approach, if a stock’s BHRs during the AITL 2018 preand postapproval periods are statistically different, then a portfolio analysis may support such a finding. Thus, we conduct a portfolio analysis to test if the BHRs on an investment consisting of holding all stocks from the banking sector for periods of 2, 5, 10, and 15 working days before 2 December 2018 are statistically different from the subsequent counterpart BHRs. We employ equallyand value-weighted methods to estimate the portfolio returns. In the former, the portfolio’s raw daily returns are equal to the arithmetic mean return of all the stocks in the portfolio; in the latter, the market capitalizations according to the ASE are proportionate to the portfolio returns only for the investment on the first day for each test period (2, 5, 10, and 15 working days). The market capitalizations for each stock are then calculated based on the stock’s corresponding daily returns thereafter. Thus, we avoid the effect of transactions such as equity issues, mergers, acquisitions, and so on, on a firm’s capitalization. Third, we assess if the introduction of the AITL 2018 can explain the stock returns from 2 December 2018 to the end of the sample period using a panel regression to consider the cross-sectional and timevarying effects. Specifically, we regress banks’CARs on the AITL 2018 estimated differential tax effect (EDTE), an income tax expense component representing the independent variable, and control variables that include earnings per share (EPS), the natural log of total assets (Ln.TA), the debt ratio calculated as total liabilities divided by total assets (D.Ratio), and the quick ratio (Q.Ratio) defined as ‘cash and balances at central banks plus balances and deposits at banks and financial institutions plus financial assets at fair value through profit’all divided by total deposits (customers deposits plus banks and financial institutions deposits). Shafi et al. (2023) test how firm-specific aspects can play a role in the green tax incentive scheme introduced in Sweden. As in Brown and Warner (1985) and others (Bouteska & Regaieg, 2019; Chang et al., 2017; Ozo & Arun, 2019; Wang & Macy, 2022), we estimate bank i’s abnormal returns (ARi) for day tusing the following model: 4 ARit ¼Rit − ^ aiþ ^ BiRmt  , (2) where R i and R m are the returns for bank iand the market on day t, and ^ ai,and ^ Bi  are the market model estimated intercept and slope obtained using a 250-day estimation period that ends 15 days 6 A. AHMAD ET AL. before the event date to prevent the effects of other events from influencing the estimated parameters (see Ellis & Keys, 2014). Some other researchers use event study methodology and skip just 10 days before the event date to start the estimation period (e.g. Singh & Padmakumari, 2020). We then estimate the CARs for each stock. For consistency with the prior tests, CARip represents the estimated daily accumulated abnormal returns for bank ifor a period of days, p, where p can equal 2 working days (D0-D1), 5 working days (D0-D4), 10 working days (D0-D9), and 15 working days (D0-D14), all as from the event day (D0), as follows: CARip ¼X D1,D4,D9,D14 p¼D0 ARip, (3) Hence, we establish our main regression model: CARip ¼a1þa2EDTEip þa3EPSip þa4Ln:TAip þa5D:Ratioip þa6Q:Ratioip þei,t, (4) where EDTEip is the AITL 2018 post-approval estimated differential tax effect for bank i, accumulated on a daily basis considering the four test windows (p ¼2, 5, 10, and 15) and scaled by the total assets for each period of (p). EPSip,Ln:TAip,D:Ratioip,and Q:Ratioip represent the control variables for bank i, all accumulated on a daily basis for each event window period (p). Therefore, we use this regression to observe delays in investors’reactions to the public information released at the AITL 2018 announcement. 5 However, since the tax reform law was signed 63 days into Q4 2018, to test for any related effects on banks’daily returns for periods of 2, 5, 10, and 15 working days using equation (4), investors will need first to estimate the banks’variables as of the event date; that is, 2 December 2018. We therefore employ a two-step procedure. First, we estimate the regression variables’growth rates in Q4 for the five most recent years, including 2018. We use the ASE official site to obtain the banks’financial reports for Q3 (dated 30 September) and Q4 (dated 31 December) of 2014 through 2018. We include the data for 2018 because investors are likely to search for leaked information for the current year prior to the year end. We then calculate the Q4’s 2018 arithmetic growth rate mean for each regression variable based on the five sample years. In the second step, we apply the estimated variables’arithmetic growth rate means, obtained from the first step, to adjust the variables’corresponding actual amounts for Q3 2018, making them daily estimates as of 2 December 2018 through 20 December 2018. 6 Finally, to estimate a stock’s EDTE, we apply the AITL 2018 additional tax rate of 3% to the stock’s estimated income before tax, all scaled by corresponding estimated total assets depending on the length of the test window (p). 4. Results and discussion We would first expect to observe higher stock returns for the post-AITL 2018 approval period relative to the pre-approval period, as enacting a lower-than-expected corporate tax rate should represent a positive earnings surprise. Second, in a more efficient market, investors reflect their perceptions of the earnings surprise in stock prices more quickly, making it unprofitable to trade based on such information. 4.1 Comparing the preand post-approval period stock returns The results in Table 1 evaluate a stock’s mean BHRs for the AITL 2018 preand post-approval periods. The individual BHRs for each stock are higher for the AITL 2018 post-approval period relative to the pre-approval period, regardless of the period length. However, the difference is statistically significant on 12 out of 15 days, with P values equal to or lower than 1%. This could be because of the relatively small sample size. We then repeat this test on a portfolio basis to eliminate the possibility that the individual stock returns can be explained by a diversifiable risk. In Table 2, we summarize the portfolio BHRs using the equally and value-weighted approaches. We find that the estimated BHRs are higher during the AITL 2018 post-approval periods than in the corresponding pre-approval periods, regardless of the length of the test window (p¼2, 5, 10, and 15). COGENT ECONOMICS & FINANCE 7 the University of Jordan, and a PhD degree in accounting from The World Islamic Science & Education University. Her main areas of research interest are FinTech in accounting, AIS, and managerial accounting. Muntaser J Melhem holds a PhD degree in Management Accounting from the University of Kent. Currently, an assistant professor in Accounting at the University of Jordan, he brings extensive teaching experience in diverse accounting subjects. Driven by a passion for research, his interests span management accounting, HRM, and organizations, with a particular focus on informal institutions in emerging markets. He has published in these areas in leading HR and Industrial Relations journals including Human Resource Management and Employee Relations. 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