Comparative Impacts of Ex-Ante and Ex-Post Regulation in Digital Markets: An Event Study Analysis of Stock Price Reactions
-
Koki Arai
Abstract
In the analysis of digital markets and competition, it is imperative to consider the regulatory landscape. Specifically, with the shift from ex post to ex ante regulation in competition law, establishing a competitive environment reflective of regulatory costs becomes imperative. This study investigates the market’s assessment of ex ante regulation through stock price event analysis. The findings reveal that the market perceives a 10–20 % negative impact on businesses from ex ante regulation for each event upon finalization of the regulatory framework or identification of regulated entities. Unlike ex-post regulation, which targets specific businesses and yields varied impacts in competition law violations, ex ante regulation’s broader influence is remarkable. ex ante regulation incurs significant business costs, with the market assessing its impact as surpassing that of ex-post regulation when viewed holistically. Acknowledging these regulatory costs underscores the imperative for stringent oversight to guarantee the attainment of regulatory aims and objectives.
1 Introduction
One perspective to analyze the relationship between digital markets and competition is the pertinence of ex ante regulation or a preemptive regulatory approach. One of the fundamental shifts in the EU Digital Markets Act (DMA) is the preemptive regulatory approach, as opposed to the ex post enforcement of traditional competition and antitrust law.[1] Traditional competition and antitrust reviews often required detailed case-by-case analysis to prove anticompetitive conduct and its effects. However, the DMA, recognizing the fast-moving nature of digital markets and the difficulty of addressing damage after its occurrence, has placed an ex ante obligation on designated gatekeepers. This approach is designed to prevent anticompetitive behavior before it has a detrimental impact on competition and consumer welfare. From a competition policy perspective, this represents a shift to a more proactive regulatory stance, which can be positioned as aimed at ensuring competition and fairness in the market without waiting for harm to materialize.
Enforcement is set to begin in March 2024, with its effectiveness to be quantitatively assessed in the future.[2] In this section, we examine the market evaluation of the Act on Improvement of Transparency and Fairness of Specified Digital Platforms (Digital Platform Transparency Act) in Japan with regard to the legality of the same type of pre-emptive regulatory approach. Specifically, the Digital Platform Transparency Act came into effect on February 1, 2021, and in the process of its implementation, (1) Amazon, (2) Rakuten, (3) Yahoo, (4) Apple and iTunes, and (5) Google were designated as “specified digital platform providers” subject to regulation on April 1, 2021.[3] This study aims to explore how the stock market perceives the designation of (1) Amazon, (2) Rakuten, (3) Yahoo, (4) Apple and iTunes, and (5) Google as “specified digital platform providers” subject to the regulation, by examining the stock price trends of each company and how the prior regulation was evaluated by the market.[4]
Japan’s initiatives were motivated by the following factors. In recent years, vertical integration by platform providers in the digital market has intensified, raising concerns in Japan about the market’s increasing concentration on a global scale. Additionally, concerns about the competitive environment, transparency, and consumer data privacy have been actively discussed. In Europe, the U.S., and other major economies, the digital advertising market has been experiencing substantial growth. Recognizing the increasing efforts in Europe, the U.S., and other major countries to establish regulations for the digital advertising market, Japan is anticipated to take a leading role in implementing these regulations. It is within this context that the Digital Platform Transparency Act was enacted.
Concerning Japan’s platform policy, Japan’s Digital Platform Transparency Act, in contrast to the EU’s DMA, imposes obligations on digital platform operators above a certain size to disclose information on trading conditions. While the content of the rules is similar to the European P2B rules, Japan’s Transparency Act is unique in that it includes an obligation to submit reports and an obligation to make efforts for voluntary improvements based on an evaluation by the Minister of Economy, Trade and Industry (METI). The METI evaluation released in December 2022 calls for improvements in app store fees and billing methods, account suspensions, preferential treatment for the company and its affiliates, and handling of returns and refunds.
In recognition of this reality, this paper is also meant to contribute to the development of a methodology as one measure for future DMA verification. In addition, assessing the comprehension of policy effects of the Digital Platform Transparency Act in the context of its steady progress in operation is not only meaningful today, but also is beneficial for future research. From these perspectives, this study shall expand upon previous qualitative discussions and begin the discussion as a first step toward a quantitative perspective.
This paper is organized as follows: Section 2 of this paper summarizes the previous studies. There, the focus is primarily on institutional and qualitative discussions of DMAs, although some discussion of the costs involved in their implementation can also be found. Section 3 presents the methodology of this study, which attempts to measure ex ante and ex-post regulatory market valuations with the same kind of yardstick. Section 4 presents the results based on this methodology. Section 5 examines the impact on foreign firms and comparisons with other firms in the same type of business from multiple perspectives. Section 6 is a concluding statement.
2 Previous Research
With regard to the various costs arising from regulation of these digital platforms, there is an analysis of three aspects of direct regulatory costs: lobbying, global trends in big tech regulation, and the ability of EU companies to compete with third market leaders (Alexandre 2021). The paper evaluates the DMA from a critical perspective. It begins with a historical review of the evolution of the EU’s digital strategy, leading to proposals for the DMA aimed at countering market concentration by large online platforms and ensuring fair competition, as well as how the DMA specifically targets certain groups of companies with significant market power and is deemed unfair They explain that while it prohibits certain practices, it mandates compliance with a set of fair practices. Alexandre (2021) then examine the lobbying activities surrounding the DMA in particular, revealing the extent to which significant financial resources, particularly from GAFAM (Google, Apple, Facebook, Amazon, and Microsoft), have been mobilized to influence the legislative process. They reveal that the DMA is one of the most lobbied pieces of legislation in the EU, indicating that economic and strategic interests play a large role in regulatory outcomes.
The evolving landscape of digital market regulation in Europe, marked by the introduction of the DMA, has sparked significant scholarly debate. Geradin’s work highlights the challenges of defining digital gatekeepers and suggests refining the DMA’s criteria to ensure that only platforms creating actual dependencies are regulated, emphasizing the importance of multi-homing as a protective measure against gatekeeping practices (Geradin 2021). The analysis of Lancieri and Pereira Neto (2022) introduces a two-level framework for designing remedies in digital markets, advocating for a harmonious integration of antitrust and regulatory measures to foster competition without imposing undue risks of over-enforcement.
Bostoen’s critique of the DMA explores its goals, assumptions, and the practicality of its enforcement mechanisms, offering a nuanced view on the act’s potential to reshape digital competition in Europe (Bostoen 2023). Additionally, the work by Crémer et al. (2023) focuses on the enforcement of the DMA, emphasizing the need for clear compliance mechanisms, strategic case prioritization, and effective coordination between the European Commission and national authorities. Together, these scholarly contributions underline the complexity of regulating digital platforms, stressing the need for precise, dynamic, and informed approaches to ensure the DMA effectively addresses the unique challenges of digital markets while fostering innovation and protecting consumer interests. This dialogue exemplifies the ongoing effort to balance the intricate interplay between regulation, competition, and innovation in the digital age.
The scholarship on European digital market regulation, particularly through the lens of the DMA, showcases an evolving dialogue on balancing ex ante and ex post regulatory frameworks. Hoffmann Herrmann, and Kestler (2024) critique the DMA’s centralization, warning it could privilege gatekeepers by exempting them from national regulations that still apply to SMEs, suggesting a recalibration towards more localized enforcement to maintain competitive equity. Yan and He (2022), focusing on data combination practices, argue for strengthening the DMA’s ex ante measures to ensure ecosystem compatibility and endorse data portability, highlighting the importance of preemptive regulation in preventing monopolistic behaviors in digital markets. Hoeppner and Kirchner (2015) introduce a behavioral perspective, critiquing the effectiveness of ex post governance strategies due to inherent behavioral biases and advocating for ex ante incentive contracting as a superior solution for aligning digital platform operations with broader societal values. This body of work collectively underscores the necessity for a nuanced approach to digital market regulation in Europe, blending ex ante and ex post strategies while considering behavioral insights to craft regulations that are both effective and equitable in promoting competition and innovation in the digital economy.
The DMA has sparked a rich academic debate, focusing on its economic implications and the challenge of regulating large online platforms that act as gatekeepers. The report by Cabral et al. (2021) endorses the DMA’s ex ante obligations for gatekeepers, addressing the need to balance network effects’ benefits with the potential harms of anti-competitive behaviors. It emphasizes the importance of addressing novel forms of anti-competitive practices and the issue of information asymmetry between platforms and regulators. In contrast, Fletcher et al. (2024) highlights how the DMA incorporates economic thinking, despite forgoing some traditional elements of competition law for clarity and enforceability. This paper argues that economic analysis, including behavioral insights, is crucial for achieving the DMA’s goals, suggesting an evolving role for economics in interpreting and applying the Act. Together, these works underscore a consensus on the necessity of the DMA while highlighting areas where economic insight is crucial for addressing the digital economy’s unique challenges. They reflect an ongoing dialogue on how best to balance innovation and competition, suggesting a dynamic interplay between economic theory and regulatory practice in shaping the future of digital markets in Europe.
Japan’s Digital Platform Transparency Law was passed on May 27, 2020, promulgated on June 3, 2020, and went into effect on February 1, 2021. The purpose of this law is to protect the interests of users and others while taking into consideration the autonomy and self-governance of digital platform providers, against the backdrop of changes in socioeconomic structure and the growing importance of digital platforms resulting from the development of information and communication technologies. Business operators regulated under the Digital Platform Transparency Act are selected based on specific designation criteria. These include two main categories: general online malls for goods sales and app stores. In the comprehensive online mall for goods sales, businesses with a total domestic distribution value of 300 billion yen or more are eligible. This includes Amazon Japan G.K. (amazon.co.jp), Rakuten Group, Inc. (Rakuten Ichiba), and Yahoo Japan Corporation (Yahoo! Shopping). In app stores, businesses with a total domestic distribution value of 200 billion yen or more are eligible. The designated operators based on this standard include Apple Inc. and iTunes Corporation (App Store) and Google LLC (Google Play Store). Through the designation of such specified digital platform providers, disclosure of the terms and conditions of provision, and evaluation of transparency and fairness, the JFTC aims to improve the transparency and fairness of specified digital platforms and contribute to the improvement of people’s lives and the sound development of the national economy through the promotion of fair and free competition. Nonetheless, these regulations do not specifically target individual digital platforms (Kajimoto 2021; Yamada 2021; Yamada et al. 2021).
Moreover, these regulations are thought to impose specific regulatory costs on regulated entities, however. For instance, such regulations could hinder innovation (when new business models or technological innovations do not fit within the regulatory framework, companies face enormous regulatory hurdles before trying new ideas), increase administrative burdens (each time new services or business models emerge, regulators must evaluate whether they meet regulatory standards and approve them), and impose additional costs on the market, barriers to market entry (regulatory requirements require significant funding and resources in the early stages), and lack of flexibility (the digital economy is by its nature highly dynamic and fast changing, and rigid pre-regulation makes it difficult to be flexible enough to accommodate future changes and the emergence of new technologies), and uncertainty of effectiveness (problems may arise that were not foreseen at the time the regulations were developed). In this analysis, we investigate how the market has assessed the direct increase in compliance costs and other constraints. Specifically, when such regulations are introduced, firms need to be prepared to comply with them. This involves creating internal guidelines to comply with regulatory requirements, training employees, and establishing monitoring systems. These costs cannot be disregarded. We contend that the market recognizes the deterioration in the business environment due to these costs, as reflected in the stock price.
Although not evidence of a direct increase in costs, the following graph shows the changes in selling, general, and administrative expenses for the businesses under consideration Figure 1.
Selling, general and administrative expenses of Rakuten and Yahoo!.
3 Methodology
Stock price event analysis, also known as event study analysis, is used to evaluate the impact of a specific event on the stock price of a listed company. Its purpose is to determine whether an event causes abnormal price movements and to quantify the magnitude of those price movements. Investors, analysts, and researchers use this type of analysis to understand the market reaction to a particular event and to assess its impact (Fama et al. 1969). Specifically related to mergers, this study examined the reaction of stock prices to mergers and acquisitions. It shows that shareholders of the target company usually demonstrate a positive stock price reaction, whereas shareholders of the acquiring company usually demonstrate a negative stock price reaction (Jensen and Ruback 1983). In addition, numerous event studies have been conducted and a great deal of information has been analyzed, including corporate reactions to various announcements, mergers, and incidents (MacKinlay 1997; Page and Connell 2020).
The standard stock event analysis method is a simple and effective way to measure the reaction of a stock price to an event.[5] This method, however, has certain limitations. For example, it assumes that the benchmark is a perfect proxy for the stock under study. This is not always the case, and the results may be subject to errors. Furthermore, the method does not account for other factors that may have affected stock prices during the event window.
Nevertheless, because of its simplicity, clarity, and quantitative objectivity, this method of examining the cost-benefit of policy initiatives based on stock market trends has been used in the analysis of the impact of sudden events (Baker, Frydman, and Hilt 2023). There, the assassination of President William McKinley in September 1901 is discussed, and the potential extent of political discretion in the aggressiveness of antitrust enforcement is estimated from changes in stock prices.[6] The analysis suggests that the market was judging the prospects for policy initiatives by changes in stock prices. There is also an analysis of how the market evaluated announcements of the development of large-scale language models such as ChatGPT (Arai 2023).
This study utilizes weekly closing stock price data collected by Yahoo Finance from January 1, 2015 through March 18, 2024. Descriptive statistics for each of the representative variables used here are shown in Table 1.
Descriptive statistics.
| NIKKEI | RAKUTEN | YAHOO | MERCARI | SOFTBANKG | AMAZON | APPLE | ALPHABET | NASDAQ | |
|---|---|---|---|---|---|---|---|---|---|
| Mean | 23,634.5 | 1,061.208 | 464.58 | 3,484.013 | 5,095.2 | 93.80931 | 86.49125 | 75.43553 | 9,200.48 |
| Median | 22,512.08 | 1,030.5 | 456 | 3,054 | 4,897 | 91.16 | 54.83 | 60.77 | 8,031.71 |
| Maximum | 39,910.82 | 2,357.5 | 825.5 | 7,070 | 10,635 | 185.97 | 197.57 | 153.79 | 16,274.94 |
| Minimum | 14,952.02 | 489.5 | 266 | 1,630 | 2,082 | 14.54 | 22.63 | 25.33 | 4,337.51 |
| Std. dev. | 5,013.521 | 356.6468 | 108.0331 | 1,327.357 | 1,588.823 | 49.18455 | 57.43593 | 37.63372 | 3,547.21 |
| Observations | 479 | 479 | 479 | 299 | 479 | 479 | 479 | 479 | 479 |
While sensitivity analysis of the significance of the coefficients is discussed in the next section, we first visually confirm the time-series trends. In Figure 2 below, the Nikkei 225, the stock prices of each company, and the timing of the event (vertical line:EVENT1-6) are depicted.
Stock price trends.
3.1 Ex Ante Regulation
In this study, we use a stock price event study methodology in which movements related to the Digital Platform Transparency Act are considered events, and we infer the costs exerted by ex ante regulation from its impact on stock prices. As demonstrated in previous studies, the key to this study is to understand how the market perceives regulatory moves, so this study focuses on the following events: (1) Cabinet approval of the draft law (February 18, 2020), (2) passage of the law (May 27, 2020), (3) publication of the framework of the ministerial ordinance (August 24, 2020), (4) (4) the start of public comments (December 5, 2020), (5) the enforcement of the law (February 1, 2021), and (6) the designation of the operators subject to discipline (April 1, 2021).
In this study, we specifically examined the magnitude of the coefficient of the event dummy (a variable that takes zero before the event and one after the time of the event) rather than the cumulative abnormal return. Here, the expected result is that the coefficient is estimated to be negative at any or all of the following timings: the announcement of the introduction of a preemptive regulation, several stages of the debate, and the passage and implementation of the law. However, actual responses may vary depending on factors such as firm performance, competition, and market sentiment. In equity event studies, data are collected and statistical methods are used to examine abnormal returns. Possible outcomes include a rise, flattening, or decline in stock prices. Comparison of multiple studies can provide insight into investor perceptions, influencing factors, and market sentiment toward digital platform technologies. Such an analysis would look at trends in firms’ and investors’ investment decisions and perceptions of market conditions, as well as help understand the need for regulation regarding digital platform transparency.
3.2 Ex Post Facto Regulations
Ex Post Facto Restrictions under the Antimonopoly Law have been applied to Rakuten. On February 28, 2020, the Japan Fair Trade Commission (JFTC) filed a petition to the Tokyo District Court for an emergency stay order under Article 70–4, Paragraph 1 of the Antimonopoly Law, requesting a temporary halt to Rakuten’s uniform introduction of the “common shipping inclusive line”. Subsequently, on March 6, 2020, Rakuten announced that it would take measures such as allowing stores to opt out of the application of the “common shipping cost inclusion line,” and subsequently established a procedure for businesses opening stores to apply to opt out of the application. On March 10, 2020, the JFTC withdrew the petition, judging that if store operators could choose whether or not to participate in the “common shipping cost line” at their own discretion, the urgency of requesting a temporary suspension would diminish for the time being. Subsequently, the JFTC decided that it was necessary to determine whether or not the arbitrariness of the selection of the stall operators would be ensured, and the JFTC has continued its examination, but Rakuten submitted a request for remedial measures. On December 6, 2021, the JFTC announced that it had decided to terminate its examination of the case after reviewing the contents of the application.
We consider this individual case as an ex post regulation against Rakuten, and compare the magnitude of the coefficients by expressing the week in which the regulation was implemented by the same event dummies as in the previous section. The stock price movements assumed here would be negative for the announcement of the emergency suspension order, positive for the announcement of its withdrawal, and negative for the subsequent announcement of the offer of remedial action and the termination of the review. This is because the emergency suspension order is expected to significantly restrict business activities, the withdrawal of the emergency suspension order is expected to restore a free business environment, and the offer of remedial action is expected to worsen the business environment by offering and announcing restrictions on one’s own business. The reason for this is that the business environment is likely to worsen as a result of the proposed and announced restrictions.
4 Results
4.1 Estimation Equations and Results for Ex-Ante Regulation
The estimating equation used in this study is as follows (Equation (1))
where i is a subscript for each company (i = Rakuten, Yahoo Line) and j is a subscript identifying the event. SP is the stock price of each firm and NIKKEI is the Nikkei Stock Average. EventDummy is a variable that represents the point in time when several events related to the Digital Platform Transparency Act occurred, taking zero before an event occurs and one after the event date. The subscript t represents time, and data are collected on a weekly basis. Then, in a normal stock price event analysis, the cumulative abnormal return (CAR) is obtained by subtracting the actual stock price from the assumed stock price using β i from the day after the announcement date, but in this analysis, a constant coefficient β i is estimated and the magnitude of the coefficient β j on the event variable is also examined. α, β i and β j are the coefficients to be obtained, and e is the error term.
The α and β for each company are shown in Table 2 below.
Coefficients of events for each company.
| Dependent variable | RAKUTEN | RAKUTEN | YAHOO | YAHOO |
|---|---|---|---|---|
| Method: least squares | n = 479 | n = 479 | n = 479 | n = 479 |
| Coefficient | Coefficient | Coefficient | Coefficient | |
| (Std. error) | (Std. error) | (Std. error) | (Std. error) | |
| C | 1,925.365a | 2,002.925a | 387.728a | 563.464a |
| (67.5004) | (113.8997) | (23.5634) | (34.8411) | |
| NIKKEI | −0.037a | −0.040a | 0.003a | −0.006a |
| (0.0028) | (0.0056) | (0.0010) | (0.0017) | |
| EVENT1 | −366.376a | −57.512b | ||
| (84.2426) | (25.7692) | |||
| EVENT2 | 228.837 | 176.041a | ||
| (117.4629) | (35.9311) | |||
| EVENT3 | 190.455 | 143.018a | ||
| (108.4036) | (33.1599) | |||
| EVENT4 | 55.414 | 30.827 | ||
| (151.0489) | (46.2048) | |||
| EVENT5 | 289.452 | −52.092 | ||
| (165.3805) | (50.5887) | |||
| EVENT6 | −409.063a | −139.900a | ||
| (101.5801) | (31.0726) | |||
| R 2 | 0.264 | 0.320 | 0.023 | 0.307 |
| Adjusted R2 | 0.263 | 0.310 | 0.021 | 0.297 |
| S.E. of regression | 306.252 | 296.203 | 106.908 | 90.606 |
| Akaike info criterion | 14.291 | 14.237 | 12.186 | 11.867 |
-
Where arepresents less than 0.01 and brepresents less than 0.05. The same conventions are applied in the subsequent tables.
As shown in Table 2, the coefficients for EVENT1 and EVENT6 are negative and strongly significant for both RAKUTEN and YAHOO. In particular, the Cabinet decision on the draft law on digital platform transparency had an impact of 18.3 % for Rakuten and 10.2 % for YAHOO (coefficient/value of the constant term), while the designation of businesses subject to discipline (start of application) had a 20.4 % and 24.8 % lower stock price impact for Rakuten and YAHOO, respectively. In total, the magnitude of the impact is 38.7 % for Rakuten and 35.0 % for Yahoo! However, the coefficients for EVENT2 and EVENT3 are significant only for YAHOOOLINE. In addition, EVENT4 and EVENT5 are not significant for both. This suggests that of the events used as events in this study, only the Cabinet decision on the draft law and the designation of businesses subject to the discipline (start of application) were particularly significant. In fact, in discussions at the time of enactment of laws in Japan, bills submitted by the Cabinet are intensely negotiated in terms of their schedule, but as for their contents, they are usually enacted as they are. In addition, the framework of ministerial ordinances and public comments were considered to be within the scope of expectations, so it is thought that they did not have a significant impact here.
In addition to this, regarding digital platform regulations, for example, a study group of the METI and/or JFTC have made announcements on several occasions that include the contents of the regulations, and the possibility that such information is reflected in stock prices cannot be denied. Because this study regards the elimination of uncertainty in the announcement of official opinions as a single event, in principle, the date of the official announcement regarding the laws and regulations of each regulation is regarded as the event date. Then, based on this, the cumulative abnormal returns on each event date and after the event date are examined from the values of the coefficients of the dummy variables. A limitation of this study, however, the possibility of stock price fluctuations due to information leaks or other information manipulation cannot be completely ruled out.
4.2 Estimation Equations and Results for Ex Post Facto Regulation
The estimation equation in this section is as follows (Equation (2)):
where i is a subscript for each firm (i = Rakuten, Yahoo Line) and k is a subscript that identifies the posterior regulatory event for Rakuten. SP is the stock price of each firm and NIKKEI is the Nikkei Stock Average. CaseDummy is a variable that represents the point in time when several events related to the Antimonopoly case review of Rakuten’s abuse of dominant position occurred, taking zero before a case proceeding is announced and one after the week the proceeding is announced. The subscript t represents time, and data are collected on a weekly basis. Then, as in the previous section, in a normal stock price event analysis, the cumulative abnormal return (CAR) is obtained by subtracting the actual stock price from the assumed stock price using β i from the day after the announcement date, but in this analysis, a constant coefficient β i is estimated and the magnitude of the coefficient β j on the event variable is also examined. α, β i and β j are the coefficients to be obtained, and e is the error term.
The results are shown in Table 3 below.
Impact of Rakuten’s antimonopoly case.
| Dependent variable | RAKUTEN | YAHOO |
|---|---|---|
| Method: least squares | n = 479 | n = 479 |
| Coefficient | Coefficient | |
| (Std. error) | (Std. error) | |
| C | 1,529.047a | 403.447a |
| (94.5355) | (28.9258) | |
| NIKKEI | −0.016a | 0.002 |
| (0.0046) | (0.0014) | |
| SER1 | −451.323b | −64.919 |
| (202.8704) | (62.0739) | |
| SER2 | 456.739b | 217.440a |
| (206.7460) | (63.2597) | |
| SER3 | −351.586a | −170.070a |
| (43.4659) | (13.2996) | |
| R 2 | 0.363 | 0.350 |
| Adjusted R2 | 0.358 | 0.345 |
| S.E. of regression | 285.751 | 87.434 |
| Akaike info criterion | 14.159 | 11.790 |
-
Where arepresents less than 0.01 and brepresents less than 0.05. The same conventions are applied in the subsequent tables.
As shown in Table 3, the coefficients indicating the impact of the filing of the emergency stay order with the Tokyo District Court on Rakuten in particular are large, negative, and significant. Subsequently, the coefficients on the dummy variables are positive and significant for the withdrawal of the motion for an emergency stay order and negative for the announcement of the end of the examination, respectively. These are significant because the implementation of the ex post regulation, the disposition under the Antimonopoly Law, had a negative impact on business activities, the subsequent withdrawal of the disposition had a positive impact on business activities, and the announcement of remedial measures had a negative impact because it may lead to restrictions on business activities, and these three consistent with the expected responses to the three measures. Compared to the magnitude of the constant term, respectively, the magnitude of this coefficient would have been 29.5 % at the beginning (SER1), then the withdrawal (SER2) almost eliminated this negative impact (+29.9 %), and then a negative magnitude impact of 23.0 % at the announcement of the remedial action (SER3). This movement, which in aggregate did not occur in Yahoo, but only in Rakuten, is considered to be a characteristic of ex post regulation.
On the other hand, in the impact of YahooLINE stock prices during the same period, the first event of the incident does not have a significant impact at the time of the initial event, and the subsequent announcement of the withdrawal of the disposition and the remedial action shows a similar coefficient value movement as Rakuten. Although this is an ex post regulatory action against a competitor, the market’s view seems to be that the impact on the firm’s business is not significant.
4.3 Comparative Study
We examined the market’s evaluation of both responses to ex ante regulation in Section 4.1, and the cases in which ex post regulation was imposed on Rakuten in Section 4.2. In the case of ex ante regulation, negative and significant coefficients were observed for both the cabinet’s decision on the pivotal draft law and the establishment of regulated businesses. In the case of ex post regulation of Rakuten, negative and significant coefficients were observed for the announcement of the emergency suspension order and subsequent improvement measures. The signs of these coefficients are all as expected. The values for the coefficients are larger in the case of ex ante regulation than those for ex post regulation, particularly in the context of Rakuten.
This is put into the same estimation equation (3) as before to estimate
The meaning of each variable is the same as in equations (1) and (2).
The results are shown in the fourth column of Table 4 below.
Effects of ex-ante and ex-post regulation as seen in Rakuten.
| Dependent variable | RAKUTEN | RAKUTEN | RAKUTEN | RAKUTEN |
|---|---|---|---|---|
| Method: least squares | n = 479 | n = 479 | n = 479 | n = 479 |
| Coefficient | Coefficient | Coefficient | Coefficient | |
| (Std. error) | (Std. error) | (Std. error) | (Std. error) | |
| C | 1,925.365a | 2,002.925a | 1,529.047a | 1,914.942a |
| (67.5004) | (113.8997) | (94.5355) | (105.1514) | |
| NIKKEI | −0.037a | −0.040a | −0.016a | −0.035a |
| (0.0028) | (0.0056) | (0.0046) | (0.0051) | |
| EVENT1 | −366.376a | −267.732 | ||
| (84.2426) | (272.7327) | |||
| EVENT2 | 228.837 | 202.806 | ||
| (117.4629) | (115.6796) | |||
| EVENT3 | 190.455 | 181.597a | ||
| (108.4036) | (99.6160) | |||
| EVENT4 | 55.414 | 39.877 | ||
| (151.0489) | (138.8086) | |||
| EVENT5 | 289.452 | 283.649 | ||
| (165.3805) | (151.9677) | |||
| EVENT6 | −409.063a | −25.684 | ||
| (101.5801) | (101.7737) | |||
| SER1 | −451.323b | −205.248 | ||
| (202.8704) | (333.5154) | |||
| SER2 | 456.739b | 122.526 | ||
| (206.7460) | (210.8297) | |||
| SER3 | −351.586a | −496.719a | ||
| (43.4659) | (52.5563) | |||
| R 2 | 0.264 | 0.320 | 0.363 | 0.430 |
| Adjusted R2 | 0.263 | 0.310 | 0.358 | 0.418 |
| S.E. of regression | 306.252 | 296.203 | 285.751 | 272.177 |
| Akaike info criterion | 14.291 | 14.237 | 14.159 | 14.073 |
-
Where arepresents less than 0.01 and brepresents less than 0.05. The same conventions are applied in the subsequent tables.
The fourth column of this Table 4 is estimated by putting the same set of events for the pre-regulation and the change in incidents for the post-regulation. According to it, the coefficients of EVENT1 and EVENT6 for ex ante regulation are no longer significant, and SER1 for ex-post regulation is also no longer significant. It may be that the market perceives the regulatory impact as not significantly greater than its impact on businesses. It is also possible that the market does not consider the impact of regulation to be significant on business, since both ex ante and ex-post regulation were in place at the same time. In this estimation, the coefficients for EVENT1, EVENT6 and SER1 show a trend in the expected direction, and the magnitude of the effect may not be clear. The effect may have become less clear as several events occur.
5 Multifaceted Considerations
5.1 Impact on Japanese Competitors
We examine the impact of the government regulation by comparing the stock price trends of the companies subject to the Digital Platform Transparency Law and the companies that were not included in the law but are attempting to establish a comprehensive online shopping mall-like business in Japan. Here, we chose Mercari Inc. and SoftBank Group Corp. as the companies to be compared.
Mercari Inc. is a Japanese company founded on February 1, 2013, and is primarily engaged in the planning, development, and operation of the “Mercari” flea market app. Mercari provides a service that allows users to easily buy and sell products in a C2C marketplace where goods can be bought and sold between individuals. Although Mercari has a high name recognition and user base in Japan, it is positioned as a C2C marketplace. Mercari is listed on the TSE Prime Market and is classified as an information and communications company.
Established in 1981, the SoftBank Group is a Japanese holding company that owns telecommunications companies, mainly cell phone companies, as well as Internet and AI-related companies. The SoftBank Group’s management philosophy is to make people happy through an information revolution, and in addition to its telecommunications business, the group is actively engaged in global investment activities through its Vision Fund and in technology areas such as AI and semiconductor design.
Both of these companies are not general merchandising online malls, but are primarily engaged in online information and telecommunications, and as companies that are not subject to regulation, they were selected as appropriate companies to compare with the companies subject to discipline when looking at the impact of the Digital Platform Transparency Law on these companies. The companies were selected as appropriate for comparison with the disciplined businesses when looking at the impact of the Digital Platform Transparency Act on the companies.
The stock price trends of these firms were collected, and the estimation equation was the same as in equation (1), with similar stock prices of both firms taken as variables. The estimation results for each company are shown in Table 5 below, with two columns added to the left for ease of reading, one for Rakuten and the other for Yahoo, which are particularly relevant in Table 2.
Comparison and contrasting businesses.
| Dependent variable | RAKUTEN | YAHOO | MERCARI | SOFTBANKG |
|---|---|---|---|---|
| Method: least squares | n = 479 | n = 479 | n = 479 | n = 479 |
| Coefficient | Coefficient | Coefficient | Coefficient | |
| (Std. error) | (Std. error) | (Std. error) | (Std. error) | |
| C | 2,002.925a | 563.464a | 3,888.732a | −613.160b |
| (113.8997) | (34.8411) | (659.5276) | (274.1564) | |
| NIKKEI | −0.040a | −0.006a | −0.046 | 0.233a |
| (0.0056) | (0.0017) | (0.0294) | (0.0134) | |
| EVENT1 | −366.376a | −57.512b | −620.609 | 393.847 |
| (84.2426) | (25.7692) | (356.6092) | (202.7718) | |
| EVENT2 | 228.837 | 176.041a | 1,770.850a | 892.015a |
| (117.4629) | (35.9311) | (467.8013) | (282.7332) | |
| EVENT3 | 190.455 | 143.018a | 763.301 | 527.189b |
| (108.4036) | (33.1599) | (429.9348) | (260.9274) | |
| EVENT4 | 55.414 | 30.827 | 659.350 | 558.405 |
| (151.0489) | (46.2048) | (600.5380) | (363.5745) | |
| EVENT5 | 289.452 | −52.092 | 229.801 | 1,263.378a |
| (165.3805) | (50.5887) | (653.6565) | (398.0708) | |
| EVENT6 | −409.063a | −139.900a | −1,781.601a | −3,634.379a |
| (101.5801) | (31.0726) | (401.1807) | (244.5032) | |
| R 2 | 0.320 | 0.307 | 0.242 | 0.802 |
| Adjusted R2 | 0.310 | 0.297 | 0.223 | 0.799 |
| S.E. of regression | 296.203 | 90.606 | 1,169.810 | 712.960 |
| Akaike info criterion | 14.237 | 11.867 | 16.993 | 15.993 |
-
Where arepresents less than 0.01 and brepresents less than 0.05. The same conventions are applied in the subsequent tables.
Digital Platform Transparency Act are negative and strongly significant, especially in the coefficients on the EVENT1 and EVENT2 variables, whereas the coefficient on EVENT1 is not significant for the comparison firms. The coefficient on EVENT6 is, however, negative and significant. In addition, the coefficients are positive and significant at three time points, especially for the SoftBank Group (and one time point for Mercari). This was not the case for Rakuten, which is subject to the comprehensive goods online mall rule, and can be seen as the market giving a different evaluation. Overall, we believe that the market is evaluating the government regulation as having a negative impact at several points in the regulation, especially on the disciplined operators.
5.2 Impact on U.S. Firms
In this study, we use a stock price event study methodology in which movements related to the Digital Platform Transparency Act are considered as events, and the costs exerted by ex ante regulation are inferred from their effects on stock prices. In doing so, we have examined the effects of market regulation movements by specifically targeting the affected Japanese firms for analysis. However, the entities regulated under the Digital Platform Transparency Act include Amazon Japan LLC for general online malls for goods sales, and for app stores, Apple Inc. and iTunes Corporation (App Store) and Google LLC (Google Play) (App Store) and Google LLC (Google Play Store) for the app store. These companies are not listed on the Japanese stock market, and the impact of Japanese government regulation does not account for the majority of the global market. For this reason, we check whether effects different from the direct impact on Japanese firms are occurring.
The estimation equation is the same as in equation (1), but instead of the Nikkei Stock Average, the variable is the change in the total index of NASDAQ in the U.S., where these three companies are listed.
The estimation results for each company are shown in Table 6 below.
Impact of Japanese regulations on U.S. firms.
| Dependent variable | AMAZON | APPLE | ALPHABET |
|---|---|---|---|
| Method: least squares | n = 479 | n = 479 | n = 479 |
| Coefficient | Coefficient | Coefficient | |
| (Std. error) | (Std. error) | (Std. error) | |
| C | −56.071a | −7.373a | −12.563a |
| (2.0868) | (2.4218) | (1.0421) | |
| NASDAQ | 0.018a | 0.007a | 0.009a |
| (0.0003) | (0.0004) | (0.0002) | |
| EVENT1 | 14.821a | 15.600a | −1.292 |
| (2.7274) | (3.1652) | (1.3620) | |
| EVENT2 | 3.357 | 12.200a | −7.907a |
| (3.7271) | (4.3253) | (1.8612) | |
| EVENT3 | −10.092a | 11.460a | −4.019b |
| (3.4355) | (3.9870) | (1.7156) | |
| EVENT4 | −23.924a | 3.894 | −5.305b |
| (4.7563) | (5.5197) | (2.3751) | |
| EVENT5 | −8.473 | −9.351 | 10.818a |
| (5.2250) | (6.0637) | (2.6092) | |
| EVENT6 | −17.262a | 35.711a | 20.502a |
| (3.2121) | (3.7277) | (1.6040) | |
| R 2 | 0.964 | 0.965 | 0.985 |
| Adjusted R2 | 0.964 | 0.964 | 0.985 |
| S.E. of regression | 9.366 | 10.869 | 4.677 |
| Akaike info criterion | 7.329 | 7.626 | 5.940 |
-
Where arepresents less than 0.01 and brepresents less than 0.05. The same conventions are applied in the subsequent tables.
According to this Table 6, many of the event dummy coefficients are significant. However, while some of them are realized with respect to the assumed signs (negative at EVENT1 and EVENT6), etc., many of them are not consistently or uniformly fulfilled. Thus, the impact of Japanese government regulations does not seem to extend to these U.S. firms, at least not to the same extent as it does to Japanese firms. One reason why Japan’s ex ante regulations have not had a significant impact on global IT firms may be that the market has seen that, from the perspective of market size, even if the cost of compliance is incurred locally, the impact is small on a global basis.
6 Discussion and Conclusion
This study conducted a specific examination of how the market evaluates the impact of ex ante regulations using a stock price event analysis. The results revealed that the market considers ex ante regulations to have a negative impact on businesses, with a reduction in value of 10–20 % at the time when the regulatory outline is finalized/the business subject to discipline is confirmed. In comparison with ex-post regulation, the emergency suspension order in the Rakuten case involving alleged violation of the Antimonopoly Law, its subsequent withdrawal, and the announcement of remedial measures had a negative impact of about 23 % in total. In other words, it is clear that the market is evaluating the effects of ex ante regulations to be larger in the aggregate. Ex post regulation has an effect only on specific businesses, and its impact is different, but the impact of the ex ante regulation is noteworthy. The impact of the ex ante regulation on the overall stock prices of foreign firms doing business in Japan was not significant. The results also showed that similar information and telecommunications-focused businesses were not affected. ex ante regulation is perceived by the market as having a certain magnitude as a cost to business, and its impact is considered to be greater than the cost of ex-post regulation from an overall perspective. This is seen as the market’s perception of the regulation allows for strict monitoring in order to achieve its intended purpose.
The contribution of this study is that one perspective of analyzing the relationship between digital markets and competition involves examining the Digital Platform Transparency Act, which is a real-world case of ex ante regulation, and to quantitatively estimate how the market evaluated the introduction of transparency and fairness regulations, which were seen as having a certain level of effectiveness and appropriateness. The implication of this study is that it reveals the arguments for the effectiveness of qualitative ex ante regulation in prior studies need further practical examination, as we found a market view that ex ante obligations to designated gatekeepers have significant costs. As a policy recommendation, the study indicates the importance of increasing welfare by ensuring market competitiveness and fairness through regulation and the need for research and verification of such regulation, considering the significant costs associated with the shift to a more proactive regulatory stance in Japan.
The research design of this paper is straightforward, focusing on an event study of two firms. These firms possess unique characteristics, which could lead to a disproportionate negative impact. However, a significant contribution of this study is its focus on the effects specific to digital platform firms, and its design allows for a clear representation of the impacts of both ex ante and ex post regulation. Although these short-term swings in stock prices may seem excessive, they indicate that the market has acknowledged a significant impact.
The study addresses further considerations as follows: Concerning the analysis method’s appropriateness, employing stock price event analysis to deduce regulatory impacts from stock movements has limitations. Yet, it remains a quantitative approach grounded in objective data, serving as a valuable indirect evaluation of regulatory impacts. On the data’s scope and representativeness, this study utilizes Japanese data, reflective of the Digital Platform Transparency Act’s national context, with well-defined criteria for company selection. Concerning the possibility of a comprehensive assessment of regulatory costs, this study distinctly concentrates on the costs of regulatory compliance. This approach enabled a comparison between ex ante and ex-post regulatory costs, with further synthesis identified as a future research direction. Considering time constraints, this study encompasses data up to March 2024, necessitating future research to ascertain impacts such as those of the DMA. In addressing the imperative to scrutinize regulatory objectives, an analysis of the regulations’ social costs and benefits from the market’s viewpoint is crucial, alongside an assessment of the quantifiable advantages of realizing the regulations’ policy aims.
The decision to address competition law violations in the digital market through ex ante or ex post regulation reflects not only the stance of competition authorities but also the broader engagement of governments and societies with digital market competition.[7] However, few studies have conducted concrete and quantitative analyses of this issue, with the debate often dominated by speculative discussions. This study stands as extremely significant, offering a comprehensive assessment of the authorities’ response to digital market competition, evaluating both direct costs and market implications.
Concerning the limitations of this study and future issues, it can be said that the study was only able to evaluate the market in Japan, despite the fact that the importance of the role played by digital platforms is increasing due to changes in the socioeconomic structure on a global scale caused by recent technological innovations in the field of information and telecommunications technology. Furthermore, a forthcoming challenge involves comprehending the actual circumstances between technological innovation and fair and free competition, considering the need to protect user interests in product provision, and the autonomy and self-governance of digital platform providers.
Acknowledgments
In preparing this paper, conversations with Ritsuko Okada were helpful. In addition, discussions at the Competition Law Advanced Practice Workshop were also informat. The comments from the session participants at ASLEA2024 where this paper was presented, especially from commentator Hsin-Hsuan Lin, contributed to the revision of this paper, and I would like to thank them for their comments, which are noted here. I used Grant-in-Aid for RISTEX JPMJRX21J1, and Grant-in-Aid for Scientific Research (KAKENHI Kiban C: 23K01404) for the preparation of this paper.
-
Competing interests: None declared.
-
AI-Related statement: In preparing this document, the author utilized ChatGPT for English proofreading assistance. After using this tool/service, the author reviewed and edited the content as needed and takes full responsibility for the content of the publication.
References
Alexandre, C. 2021. How Can the Digital Markets Act Impact the Current EU Digital Market and what Does that Imply for European and Foreign Actors? Louvain School of Management, Université catholique de Louvain. Also Available at: http://hdl.handle.net/2078.1/thesis:31232.Search in Google Scholar
Arai, K. 2023. “Law and Economics of Language Model Development: Empirical Examination of Corporate Strategies and Vaporware Claims.” Asian Journal of Law and Economics 15 (1): 31–53. https://doi.org/10.1515/ajle-2023-0118.Search in Google Scholar
Baker, R. B., C. Frydman, and E. Hilt. 2023. “Political Discretion and Antitrust Policy: Evidence from the Assassination of President McKinley.” The Journal of Law and Economics 66 (4): 837–73. https://doi.org/10.1086/725590.Search in Google Scholar
Bostoen, F. 2023. “Understanding the Digital Markets Act.” Competition Law Review 68 (2). https://doi.org/10.1177/0003603X231162998.Search in Google Scholar
Cabral, L. M. B., J. Haucap, G. Parker, G. Petropoulos, T. M. Valletti, and M. W. Van Alstyne. 2021. The EU Digital Markets Act: A Report from a Panel of Economic Experts. Luxembourg: Publications Office of the European Union.Search in Google Scholar
Crémer, J., D. Dinielli, P. Heidhues, G. Kimmelman, G. Monti, R. Podszun, M. Schnitzer, F. Scott Morton, and A. de Streel. 2023. “Enforcing the Digital Markets Act: Institutional Choices, Compliance, and Antitrust.” Journal of Antitrust Enforcement 11 (3): 315–49. https://doi.org/10.1093/jaenfo/jnad004.Search in Google Scholar
Fama, E. F., L. Fisher, M. C. Jensen, and R. Roll. 1969. “The Adjustment of Stock Prices to New Information.” International Economic Review 10 (1): 1–21. https://doi.org/10.2307/2525569.Search in Google Scholar
Fletcher, A., J. Crémer, P. Heidhues, G. Kimmelman, G. Monti, R. Podszun, M. Schnitzer, F. Scott Morton, and A. de Streel. 2024. “The Effective Use of Economics in the EU Digital Markets Act.” Journal of Competition Law and Economics. https://doi.org/10.1093/joclec/nhad018.Search in Google Scholar
Geradin, D. 2021. “What Is a Digital Gatekeeper? Which Platforms Should Be Captured by the EC Proposal for a Digital Markets Act?” SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3788152.Search in Google Scholar
Hoeppner, S., and C. Kirchner. 2015. “Ex Ante versus Ex Post Governance: A Behavioral Perspective.” Review of Law & Economics 12 (2). https://doi.org/10.1515/rle-2015-0003.Search in Google Scholar
Hoffmann, J., L. Herrmann, and L. Kestler. 2024. “Gatekeeper’s Potential Privilege—The Need to Limit DMA Centralization.” Journal of Antitrust Enforcement 12 (1): 126–47. https://doi.org/10.1093/jaenfo/jnad040.Search in Google Scholar
Jensen, M. C., and R. S. Ruback. 1983. “The Market for Corporate Control: The Scientific Evidence.” Journal of Financial Economics 11 (1–4): 5–50. https://doi.org/10.1016/0304-405X(83)90004-1.Search in Google Scholar
Kajimoto, K. 2021. Commentary on Government Ordinances and Guidelines Concerning the Act on Improvement of Transparency and Fairness of Specified Digital Platforms (2) – Commentary on the Guidelines (Based on Points to Note for Platform Operators). NBL, No. 1193, Shojihomu, May 1, 34–40. NAID 40022553298. (In Japanese).Search in Google Scholar
Lancieri, F., and C. M. S. Pereira Neto. 2022. “Designing Remedies for Digital Markets: The Interplay between Antitrust and Regulation.” Journal of Competition Law and Economics 18 (3): 613–69. https://doi.org/10.1093/joclec/nhab022.Search in Google Scholar
MacKinlay, A. C. 1997. “Event Studies in Economics and Finance.” Journal of Economic Literature 35 (1): 13–39.Search in Google Scholar
McWilliams, A., D. S. Siegel, and S. H. Teoh. 1999. “Issues in the Use of the Event Study Methodology: A Critical Analysis of Corporate Social Responsibility Studies.” Organizational Research Methods 2: 340. https://doi.org/10.1177/109442819924002.Search in Google Scholar
Na, Y. 2024. “Is the Korea Fair Trade Commission Abusing the Provision for Abuse of Superior Trading Position? A Critical Analysis of the Act on Fair Intermediary Trade of Online Platforms.” Asian Journal of Law and Economics. https://doi.org/10.1515/ajle-2023-0176.Search in Google Scholar
Page, S. J., and J. Connell. 2020. The Routledge Handbook of Events, 2nd ed. Routledge.10.4324/9780429280993Search in Google Scholar
Watanabe, H. 2024. The Meaning of Techlash. Chiyoda, Tokyo: Chuokoron-Shinsha.Search in Google Scholar
Yamada, M. 2021. Commentary on Government Ordinances and Guidelines Concerning the Act on Improvement of Transparency and Fairness of Specified Digital Platforms (3, Complete) – Commentary on Disclosure Obligations (Focusing on Impact on Platform User Businesses). NBL, No. 1194, Shojihomu, May 15, 26–32. NAID 40022562328. (In Japanese).Search in Google Scholar
Yamada, M., K. Kajimoto, H. Murase, and H. Sakuma. 2021. Commentary on Government Ordinances and Guidelines Concerning Laws to Improve Transparency and Fairness of Specific Digital Platforms (1) – Outline of the System. NBL, No. 1192, Shoji Homu, April 15, 4–12. NAID 40022541225. (In Japanese).Search in Google Scholar
Yan, X., and H. He. 2022. “Fine-Tuning the Ex Ante Approach to Regulating Data Combination Practices.” Journal of Competition Law and Economics 18 (4): 881–904. https://doi.org/10.1093/joclec/nhac005.Search in Google Scholar
© 2024 the author(s), published by De Gruyter, Berlin/Boston
This work is licensed under the Creative Commons Attribution 4.0 International License.
