Market Setting Research Articles

Behind closed doors: unveiling earnings management in private subsidiaries of public firms

PurposeThis study examines the earnings quality of private-subsidiary firms using a large sample data from India.Design/methodology/approachThe impact of parent–subsidiary relationship on earnings quality is examined using two common proxies. Findings are robust to alternative research designs, including different earnings quality proxies, endogeneity and matching techniques.FindingsThe study finds that private firms that are subsidiaries of listed firms tend to have lesser (greater) earnings quality (manipulation). Further, the study reports that this relationship is more pronounced when the parent firm is relatively larger than the subsidiaries. The study finds no evidence that Big 4 affiliation of the parent company improves earnings quality among private subsidiaries; instead, it exacerbates earnings manipulation in some cases. Finally, the authors document that subsidiary firms use tax management, as proxied by book tax differences, to engage in income-increasing earnings manipulation.Research limitations/implicationsThis study examines how affiliation with a listed entity as a subsidiary impacts the earnings quality of private companies. Future research could investigate the financial reporting practices of both private subsidiary firms and standalone private firms, comparing them in similar or differing regulatory environments across various countries.Practical implicationsThe findings of this study will help investors, bankers, creditors and regulators to understand the financial reporting of private firms. The study calls for enhanced audit quality at the subsidiary level by making the auditor of the parent firm responsible for auditing a subsidiary, a practice that is currently absent in India.Originality/valueThe results contribute to the existing debate on how firms manage earnings using data of private firms in a large emerging market setting. Previous research has not paid enough attention to the earnings quality of private subsidiaries. The study also emphasizes the necessity for a more robust system of governance and supervision for private firms, particularly in India and generally in other countries.

Beyond markets. On field competition in higher education

ABSTRACT Competition today has become a central policy imperative in higher education. Connected to resource efficiency and scarcity, it remains closely attached to the idea of the market but reaches beyond when related to positional or status orders. In the higher education literature such varieties of competition – as distinct social processes – are still under-investigated. In drawing on common references to competition in the literature and empirical examples the paper identifies and outlines two separable forms: market and field competition. The distinction shows that there are fundamental differences in the way competition in higher education plays out which should not be viewed merely as variations of market settings. To outline the differences among the two forms the paper follows a two-step iterative process. The paper first highlights a time-bound analytical problem in common market-references. Drawing on empirical work by Michel Callon it specifies market competition as the construction, singularisation and detachment of a good. As empirical examples from the German higher education case show, such singularisation and detachment are rarely complete, competition rather operates through the attachment of universities to status-consecrating intermediaries, as analysed in the status competition literature. In a second step, the paper outlines the main premises of status competition but also its lack of a comprehensive frame that could qualify it as a distinct form of competition. The ‘field’ fills this void by providing a selective relational space on which universities can act and observe themselves competing, reinforced by multiple intermediaries.

Fixing the Proprietary Cost Assumption in Discretionary Disclosure Models

ABSTRACT I present a critique of the common assumption of fixed proprietary costs in discretionary disclosure models, which are frequently used to motivate and interpret empirical analyses of voluntary disclosures in capital market settings (e.g., management guidance, segment performance, and major customers). In a fairly general model, proprietary costs that are fixed (i.e., independent of the disclosed information) are contradictory to their proprietary nature. To sustain informational independence requires either that the party (e.g., competitor) imposing proprietary costs on the disclosing firm is indifferent to the information or that the disclosing firm is indifferent to what the competitor/counterparty will do with the information. Either of these is inconsistent with a plain interpretation of proprietary disclosure costs, which arise precisely because of responses to disclosed information. I suggest that researchers should explicitly consider how the disclosed information will be used rather than derive predictions or interpret results based on information-insensitive proprietary costs. JEL Classifications: D21; G32; M41.

Ownership concentration and SME IPO underpricing in India – moderating impact of board monitoring and resource provision role

PurposeThe study aims to explore how the monitoring and resource provision function of board of directors impact the association between ownership concentration and small- and medium-sized enterprise (SME) initial public offering (IPO) underpricing in the context of an emerging economy like India.Design/methodology/approachThe sample comprises 390 SME IPOs listed on Bombay Stock Exchange SME platform and National Stock Exchange EMERGE (EMERGE is the NSE new initiative for SMEs to raise the funds from investors) in India. To test the moderating impact of the board monitoring role and resource provision role, the study employs hierarchical moderated regression subject to the fulfillment of assumptions.FindingsThe findings divulge that ownership concentration significantly reduces underpricing, hinting towards the operationalization of alignment of interest hypothesis. With regards to moderating relationship, the study found that while board resource providing role negatively moderates the relationship between ownership concentration and SME IPO underpricing, board monitoring function fails to cast any significant impact on the relationship between ownership concentration and SME IPO underpricing.Research limitations/implicationsThe present study ignores larger firms listed on the main platform which have complex decision-making than smaller firms. Besides, it is confined to only a single country, i.e. India. Extending the study to other countries with similar institutional characteristics would have validated the findings. Furthermore, the moderating impact of other organizational factors like firm age, lifecycle of firm and change in technology would form an interesting avenue for future research.Practical implicationsThe findings of the study have practical implications for managers in designing the adequate board structure that significantly reduces underpricing. It thus further advices the issuers on focusing more on strengthening the resource provision role of board of directors for achieving higher rewards. The findings are helpful to policymakers in framing such policies that enhance the resource-oriented role of board of directors and resource accessibility for SMEs. Furthermore, the results advise the investors to be relatively assured about the SMEs whose board exercises its resource provision role emphatically. Accordingly, findings are helpful to investors in making investment decisions in alternative market settings characterized by the concentrated ownership structure.Originality/valueThe study furthers the debate on the importance of two prominent roles played by board as a moderating variable in the underexplored context of IPO underpricing of small and medium-sized firms in India.

A Bayesian theory of market impact

Abstract The available liquidity at any time in financial markets falls largely short of the typical size of the orders that institutional investors would trade. In order to reduce the impact on prices due to the execution of large orders, traders in financial markets split large orders into a series of smaller ones, which are executed sequentially. The resulting sequence of trades is called a meta-order. Empirical studies have revealed a non-trivial set of statistical laws on how meta-orders affect prices, which include (i) the square-root behaviour of the expected price variation with the total volume traded, (ii) its crossover to a linear regime for small volumes and (iii) a reversion of average prices towards its initial value, after the sequence of trades is over. Here we recover this phenomenology within a minimal theoretical framework where the market sets prices by incorporating all information on the direction and speed of trade of the meta-order in a Bayesian manner. The simplicity of this derivation lends further support to the robustness and universality of market impact laws. In particular, it suggests that the square-root impact law originates from over-estimation of order flows originating from meta-orders.

Strategic Adaptation and Governance in Disruptive Market Environments: Frameworks and Case Studies

Background: Adaptive governance methods have become critical for organizational resilience and sustainability in today's turbulent and disruptive market settings. This article examines the important issue of altering governance systems to effectively deal with disruptive market dynamics. Objective: The article aims to look into how adaptive governance might increase an organization's competitiveness and agility in the face of rapid market changes. Methodology: This study applies a mixed-methods approach, investigating multiple case studies of organizations from various industries. The study looks at how adaptive governance frameworks are implemented, namely their structures, procedures, and decision-making mechanisms. In-depth information is acquired utilizing both qualitative and quantitative data collection techniques, such as surveys, interviews, and performance indicators. Results: The results highlight the importance of adaptive governance in fostering flexibility, innovation, and responsiveness in organizational contexts. This study uses case studies to demonstrate the association between greater resilience to market changes and adaptive governance approaches. It focuses on critical components of effective adaptive governance, such as strategic flexibility, inclusive decision-making, and iterative learning procedures.Conclusion: The article emphasizes the need of adaptive governance as a key strategy for organizations dealing with fluctuating market situations. Implementing adaptive governance structures allows organizations to preserve long-term competitiveness, encourage innovation, and respond proactively to market uncertainty. The study provides useful insights for professionals and decision-makers, underlining the necessity of adaptable governance in developing organizational resilience and future-proofing measures in the face of volatile market conditions.

Financial Hedging of Operational Risk Constraints: A General Framework

We consider the operation of a non-financial corporation and present a novel risk-management framework that supports the joint optimization of the firm’s operational and financial decisions. Specifically, we study the problem of maximizing the firm’s operating profits when these profits depend on movements in the financial markets, and where the decision maker—the firm’s manager—is risk averse. Critically, our framework (i) imposes risk aversion through a generic class of risk constraints, and (ii) considers explicitly the differences that can exist between the shareholders’ and manager’s beliefs about future market risks. Together, these aspects allow us to remove speculation so that financial instruments can only be used for hedging purposes. We analyze our problem in an incomplete financial market setting and consider different informational assumptions. Within this framework, we characterize the optimal financial hedging strategy so that the problem reduces to a constrained maximization over operational policies. Our results show how financial hedging can be effectively used to expand the set of admissible operating policies, and identify conditions under which the risk constraint can be completely ignored when solving for an optimal operating policy. We illustrate our methodology in the context of an exporter firm which faces exchange rate risk in trading.

Dynamic Mean–Variance Portfolio Optimization with Value-at-Risk Constraint in Continuous Time

Recognizing the importance of incorporating different risk measures in the portfolio management model, this paper examines the dynamic mean-risk portfolio optimization problem using both variance and value at risk (VaR) as risk measures. By employing the martingale approach and integrating the quantile optimization technique, we provide a solution framework for this problem. We demonstrate that, under a general market setting, the optimal terminal wealth may exhibit different patterns. When the market parameters are deterministic, we derive the closed-form solution for this problem. Examples are provided to illustrate the solution procedure of our method and demonstrate the benefits of our dynamic portfolio model compared to its static counterpart.

Estimando el efecto del clima en la agricultura con el valor productivo de la tierra agrícola

Objective: the Ricardian model, in which market land values are modeled as a function of climate, has been estimated extensively in the context of developing countries where its core assumptions are likely to fail due to missing or incomplete markets. This article proposes a new measure of land valuation that better reflects agricultural productivity in such contexts: the Productive Value of Agricultural Land (PVAL). Methodology: a three-step empirical strategy is applied to data from a survey of Mexican rural households. The first step is the estimation of an agricultural production function. In the second step, parameter estimates are used to calculate PVAL. In the third step, PVAL is used as the dependent variable in a Ricardian regression. Results: suggests that PVAL increases with more precipitation and decreases with by extreme heat. When the Ricardian regression is estimated using market land values, the positive effect of precipitation is underestimated and the effect of extreme heat on land productivity is null. Limitations: omitted variables bias could still influence the Ricardian estimates obtained using PVAL. Originality: a novel version of the Ricardian model is estimated, one that does not rely on market values of land. Conclusions: failing to account for the market setting of agricultural producers, particularly in developing countries, may lead to an underestimation of the effects of climate change in agricultural productivity.

Food Acquirability: An Unexplored Component of Food Security?

The key elements, or pillars, of food security are stated as food availability, food access, food utilization, and stability. These food security pillars are often linked to food security interventions at the national, community or household level. However, if the urban 'household' is the unit of interest for any food security intervention, this research asks if a more holistic element, or pillar, is needed. The aim of this research has been to explore the socio-economic aspects of food security/insecurity that we have termed as a result of the research "food acquirability". Through the use of structured questionnaires (n = 120), and analysis of the data derived from local market and supermarket settings in the city of Awka, Nigeria, the concept of food acquirability has emerged and been conceptualized and critiqued. The contribution of this paper is to frame the concept of acquirability with regard to food security in Nigeria in order to develop a better understanding of the factors that impact household urban food security/insecurity and how they can be effectively mitigated. Factors of acquirability that emerged were culture, time poverty, resource availability and cooking skills, and household food preference and meal choice.

Risk management under weighted limited expected loss

We present and solve an optimal asset allocation problem under a weighted limited expected loss (WLEL) constraint. This formulation encompasses the risk management problem with a limited expected loss (LEL) constraint as a specialized instance and offers a pertinent internal risk management instrument for firms. We observe that a WLEL constraint makes the optimizing investor pursue less volatile payoffs than the unconstrained Merton solution. Compared to the LEL-constrained problem with the same weighted default threshold, the WLEL optimal terminal wealth displays a less dispersed distribution with a smaller variance, suggesting a more secure risk management framework. Conducting a comprehensive equilibrium analysis in the presence of a WLEL risk manager, we validate the relatively conservative investment approach undertaken by the WLEL manager. Subsequently, we expand our findings to encompass broader incomplete market settings, wherein the uniqueness of the equivalent local martingale measure is not assured.

To Change or Not to Change: The Informativeness of REIT Annual Reports

Increasingly similar corporate disclosures may fail to provide potential investors with adequate information about a company to facilitate astute, informed, and/or rational decision making. In light of this repeatedly expressed SEC concern, the current investigation uses a sample of 1,910 annual report (10-k) filings by 234 separate equity REITs from 2000-2020 to examine the impact of year-over-year linguistic similarity on the perceived information content of corporate disclosures. Consistent with the aforementioned concerns, we document a significant increase in the degree of REIT annual report similarity over time. Despite this trend, we find that innovations in annual report disclosures remain directly related to observable changes in both the operational complexity and financial position of the firm. Furthermore, these innovations engender significant market reactions including changes in options trading activity, annual report readability, and the firm’s cost of equity capital. Lastly, these findings are both robust to the inclusion of alternative information channels and are significantly more pronounced within informationally opaque market settings. In sum, we find REIT annual reports remain a value-relevant source of information for market participants.

The Effect of the Countercyclical Capital Buffer on the Stability of the Housing Market

AbstractAfter the great turmoil of the latest financial crisis, the criticism of the regulatory frameworks became increasingly stronger. The rules that banks needed to comply with are presumed to be procyclical and unable to prevent and mitigate the extent of strong financial and economic cycles. As a result, Basel III introduced a set of macroprudential tools to overcome these regulatory shortfalls. One tool that strives to counteract the issue of procyclicality is the countercyclical capital buffer ($$CCyB$$ CCyB ). This paper introduces a heterogeneous agent-based model that investigates the implication of the new regulatory measure. We develop a housing and a financial market where economic agents trade residential property that is financed by financial institutions. To examine the macroeconomic performance of the $$CCyB$$ CCyB , we evaluate the dynamics of key stability indicators of the housing and the financial market under four different market conditions: in an undisturbed market and in times of three different structural shocks. Computational experiments reveal that the $$CCyB$$ CCyB is effective in stabilizing the housing and the financial market in all market settings. The new macroprudential tool helps to mitigate economic fluctuations and to stabilize market conditions, especially in the aftermath of a crisis. It is not able to prevent any of the crises tested. However, the extent of the stabilizing effect varies according to market conditions. In the shock scenarios, the $$CCyB$$ CCyB performs better in dampening market fluctuations and increasing banking soundness than in the base scenario.

Pricing derivatives on foreign assets using Markov-modulated cojump-diffusion dynamics

In this study, cross-currency derivatives pricing under stochastic interest rates is analyzed when Markov-modulated cojump-diffusion dynamics with both idiosyncratic and simultaneous jumps drive the underlying foreign equity price and foreign exchange rate processes. More specifically, the noise dynamics of these two assets are captured by the correlated Wiener processes, and the two types of jump events are described as two independent compound Poisson processes with log-normal jump amplitudes. Cojumping addresses the correlation between these two asset price jumps. In an incomplete market setting, the dynamic Esscher transform approach is applied to determine a pricing kernel. According to the resulting dynamics, explicit analytical formulas for evaluating values of European foreign equity call options are provided. Numerical experiments are also described.

Deep Learning Pricing of Processing Firms in Agricultural Markets

The pricing behavior of agricultural processing firms in input markets has large impacts on farmers’ and processors’ prosperity as well as the overall market structure. Despite analytical approaches to food processors’ pricing in agricultural input markets, the need for models to represent complex market features is urgent. Agent-based models (ABMs) serve as computational laboratories to understand complex markets emerging from autonomously interacting agents. Yet, individual agents within ABMs must be equipped with intelligent learning algorithms. In this paper, we propose supervised and unsupervised learning agents to simulate the pricing behavior of firms in agricultural markets’ ABMs. Supervised learning firms are pre-trained to accurately best respond to their competitors and are deemed to result in the market Nash equilibria. Unsupervised learning firms play a course of pricing interaction with their competitors without any pre-knowledge but based on deep reinforcement learning. The simulation results show that unsupervised deep learning firms are capable of approximating the pricing equilibria obtained by the supervised firms in different spatial market settings. Optimal discriminatory and uniform delivery pricing emerges in agricultural input markets with the high and intermediary importance placed on space. Free on board pricing emerges in agricultural input markets with small importance placed on space.

Wage outcomes after temporary employment in Germany and the UK: Taking within- and between-employer transitions into account

This study investigates wage outcomes of former temporary workers by distinguishing workers obtaining permanent jobs with the same employer from those who find permanent work with a new employer. With this distinction, we build on studies investigating the wage consequences of temporary jobs, which have thus far mainly focused on cross-sectional wage gaps and longer-term wage consequences without considering employer changes. We compare Germany and the UK as two prime examples of different labour market settings and look at labour market subgroups relevant for social stratification. We estimate fixed effects individual slopes regression with data from the German Socio-Economic Panel (1995–2021), the British Household Panel Study (1992–2008), and the UK Household Longitudinal Study (2010–2021). Results show that in the rigid German and in the more flexible UK labour market, wage increase of former temporary workers is larger if the permanent job is obtained with the same employer, but only if it coincides with a job change within the firm. For transitions occurring on the same job, only workers in Germany experience wage increase. This wage increase is not higher compared to the wage increase of workers who switch employers. These patterns are similar across subgroups, with the largest deviances found for older workers in Germany.

Collective intelligence for fighting food waste: changing the way things are done with participatory design

PurposeThis study aims to explore the use of a double diamond design method to engage the industry in a sector-wide response to the issues of food waste as constructed by consumers. This particular design method is achieved by an exploration of a collective intelligence-participatory design (CIPD) project to engage industry participants in understanding and responding to consumers’ perceptions of the role of packaging in reducing food waste.Design/methodology/approachUsing the UK Design Council’s double diamond design method as a guiding conceptual principle, the project recruited industry participants from medium to large food businesses across various food categories. Two scoping workshops with industry were held prior to the initiation of a 12-stage project (n = 57), and then two industry workshops were held (n = 4 and 14). Eighty participants completed an online qualitative survey, and 23 industry participants took part in a Think Tank Sprint Series. The Think Tanks used participatory design approaches to understand barriers and opportunities for change within food industry sub-sectors and test the feasibility and acceptability of package designs to reduce consumer waste.FindingsFor CIPD to work for complex problems involving industry, it is vital that stakeholders across macro- and micro-subsystems are involved and that adequate time is allowed to address that complexity. Using both the right tools for engagement and the involvement of the right mix of representatives across various sectors of industry is critical to reducing blame shift. The process of divergence and convergence allowed clear insight into the long-term multi-pronged approach needed for the complex problem.Originality/valueParticipatory design has been useful within various behaviour change settings. This paper has demonstrated the application of the double diamond model in a social marketing setting, adding value to an industry-wide project that included government, peak bodies, manufacturing and production and retailers.

Turning Customers into Citizens: The Impact of Online Experiential Value on Customer Citizenship Behaviour

This research aims to understand customer motivations to display customer citizenship behaviour in the emerging market setting of Egypt. It develops and empirically tests the multidimensional perspective of online experiential value (grounded in the theory of consumption value) and customer citizenship behaviour to determine customer motivations to become company citizens on social media brand pages. Using an online self-administered survey, 294 responses were collected. Data were analyzed using structural equation modelling to achieve the research objectives. Findings confirm there is a positive and significant relationship between online experiential value and customer citizenship behaviour on social media brand pages. This research contributes to the literature by providing an understanding of how to employ the online experiential value dimensions to drive customer citizenship behaviour. The findings of this research will help marketers build effective social media marketing strategies where they provide customers with the five essential components of online experiential value necessary to establish customer citizenship behaviour.

Students’ individual entrepreneurial orientation and the scope of startup activities in Russia: The role of university infrastructure

The development of startup activity among students is often considered a key ingredient to increasing entrepreneurship levels and reducing unemployment rates among youth. This study examines the role of personal characteristics and university infrastructure components in the context of nascent entrepreneurship in an emerging market setting. Drawing on the self-efficacy perspective, we theorize the effect of students' individual entrepreneurial orientation on the scope of their startup activity. Based on the university embeddedness theory, we further explore whether the university entrepreneurial environment and entrepreneurial program learning moderate this relationship. Our sample was drawn from the 2021 GUESSS project, which includes 1521 students from 21 universities in Russia. Data were analyzed using hierarchical multiple regression models with the help of Stata MP software. We found that individual entrepreneurial orientation increases the scope of students' startup activities, and the university entrepreneurial environment that is evaluated above the median score strengthens this relationship, while the entrepreneurial program learning has no effect. Our research seeks to draw researchers' and practitioners' attention to the need of both exploring the nuances of students’ personal traits that influence their involvement in startup activities and building an effective university entrepreneurial ecosystem to stimulate entrepreneurial endeavors among youth.

Ratiometric fluorescence sensor based on deep learning for rapid and user-friendly detection of tetracycline antibiotics

The detection of tetracycline antibiotics (TCs) in food holds great significance in minimizing their absorption within the human body. Hence, this study aims to develop a rapid, convenient, real-time, and accurate detection method for detecting antibiotics in an authentic market setting. A colorimetric fluorescence sensor was devised for tetracycline detection utilizing PVA aerogels as the substrate. Its operating principle is based on the IFE effect and antenna effect. A detection device is designed to capture fluorescence images while deep learning was employed to aid in the detection process. The sensor exhibits high responsiveness with a mere 60-s requirement for detection and demonstrates substantial color changes(blue to red), achieving 99% accuracy within the range of 10–100 μM with the assistance of deep learning (Resnet18). Real sample simulation tests yielded recovery rates between 95% and 130%. Overall, the proposed strategy proved to be a simple, portable, reliable, and responsive solution for rapid real-time TCs detection in food samples.