Minimize Monitoring Costs Research Articles

Financial Intermediation, Economic Growth, and Business Cycles

This paper aims to examine the importance of financial intermediation in economic activity. We also explore the effects of monetary factors and financial frictions on the relationship between financial intermediation and economic growth, the drivers of business cycles, and how shocks spread through the intermediation process. Financial intermediaries improve fund allocation, minimize monitoring costs, minimize liquidity risk, simplify risk management, and facilitate portfolio diversification and resource allocation to more productive activities. In addition, financial intermediaries collect and analyze information about investment projects, allocating resources and managing information more efficiently than individual investors. We conclude that financial intermediation is significant for economic growth. In addition, we show that financial market frictions can amplify exogenous shocks, affecting investment, economic growth rates, and macroeconomic stability. Reducing financial frictions through intermediation is crucial.

Ownership Design and Managerial Efficiency

The relationship between strategy and structure is a longstanding one. In this paper, we argue that corporate groups are organized to maximize managerial efficiency in the presence of diversification. We construct a novel dataset that tracks the ownership links of nearly 1.2M parent companies from 201 countries down to nine layers of controlled subsidiaries. These 2.9M ‘ownership paths’ allow us to investigate in detail the legal organizational structures of companies around the world and derive new insights. We demonstrate that vertical (or pyramidal) ownership structures are rarely used to magnify the control rights of ultimate owners. We propose, rather, that vertical ownership structures exist to minimize monitoring costs in (industrially and geographically) diversified firms. The results show that more diversified and unrelated firms have longer ownership paths, that is, more pyramidal structures. This is consistent with the idea that these structures may allow for more efficient management in diversified or unrelated conglomerates.

Avoiding critical thresholds through effective monitoring.

A major challenge in sustainability science is identifying targets that maximize ecosystem benefits to humanity while minimizing the risk of crossing critical system thresholds. One critical threshold is the biomass at which populations become so depleted that their population growth rates become negative-depensation. Here, we evaluate how the value of monitoring information increases as a natural resource spends more time near the critical threshold. This benefit emerges because higher monitoring precision promotes higher yield and a greater capacity to recover from overharvest. We show that precautionary buffers that trigger increased monitoring precision as resource levels decline may offer a way to minimize monitoring costs and maximize profits. In a world of finite resources, improving our understanding of the trade-off between precision in estimates of population status and the costs of mismanagement will benefit stakeholders that shoulder the burden of these economic and social costs.

The Shining Path of Peru: An Organizational Theory for Conflict

Violent political insurgencies display resilient structures that allow their growth and success. They must provide incentives to avoid internal rent-seeking among the members and, at the same time, discourage coalitions from undermining the direction and control of the insurgency. I study how insurgencies’ response to these trade-offs determines their political and military structures. A vertical and centralized hierarchy will prevail to minimize monitoring costs. However, a horizontal hierarchy will emerge within the insurgency to cede part of the insurgency surplus to solve their collective action problems and effectively coordinate violence. The evidence rests on the analysis of the Shining Path, the most radical face of the Communist revolution in the Western Hemisphere and a pioneer organization for the most recent insurgencies. I argue that the variation of this internal hierarchy played a significant role in its dramatic growth from a small group of students to a lethal terrorist organization with international outreach.

Discussion of “Are Related Party Transactions Red Flags?”

AbstractKohlbeck and Mayhew () create a new data set featuring two types of related party transactions. They use empirical‐archival methods to investigate the effect of such transactions on the likelihood of restatements and on audit fees. Their findings suggest that related party transactions related to directors, officers and major shareholders are associated with poor “tone at the top” and that this leads management to negotiate for lower‐quality audits to minimize monitoring costs. To offer avenues for future research, we focus our discussion on three aspects of their paper related to causality, definitions of variables, and generalizability to non‐U.S. jurisdictions.

Stick or twist: roe deer adjust their flight behaviour to the perceived trade-off between risk and reward

Because avoiding predation is crucial for fitness, foraging animals must trade acquisition of high-quality resources against risk avoidance when the best resources occur in locations with high predation risk. Although optimality models predict the distance at which an animal should initiate vigilance and flight, many studies have shown that animals generally flee soon after detecting an approaching threat, supporting the ‘flush early and avoid the risk’ (FEAR) hypothesis. Despite this, flight behaviour varies markedly depending on context, suggesting some behavioural plasticity in the response of prey to a given threat. We evaluated the degree of plasticity in the flight responses of roe deer, Capreolus capreolus, a highly flexible species which thrives in human-dominated landscapes. Based on individually identifiable animals and a standardized flight initiation protocol, we measured the distance at which a deer detected an approaching threat, and the distance at which it subsequently initiated flight. Our results provide strong support for the FEAR hypothesis, suggesting that alert and flight responses are strongly coupled in roe deer. However, the perceived level of both risk (in terms of landscape openness and proximity to human infrastructure) and reward (in terms of habitat quality) influenced the time it took for a deer to detect an approaching threat, and the subsequent time for which the threat was tolerated prior to flight. Overall, our findings indicate that although roe deer minimize monitoring costs when assessing risk by fleeing early, they also adjust their monitoring and flight responses to the local risk–resource trade-off.

Optimizing bulk milk dioxin monitoring based on costs and effectiveness

Dioxins are environmental pollutants, potentially present in milk products, which have negative consequences for human health and for the firms and farms involved in the dairy chain. Dioxin monitoring in feed and food has been implemented to detect their presence and estimate their levels in food chains. However, the costs and effectiveness of such programs have not been evaluated. In this study, the costs and effectiveness of bulk milk dioxin monitoring in milk trucks were estimated to optimize the sampling and pooling monitoring strategies aimed at detecting at least 1 contaminated dairy farm out of 20,000 at a target dioxin concentration level. Incidents of different proportions, in terms of the number of contaminated farms, and concentrations were simulated. A combined testing strategy, consisting of screening and confirmatory methods, was assumed as well as testing of pooled samples. Two optimization models were built using linear programming. The first model aimed to minimize monitoring costs subject to a minimum required effectiveness of finding an incident, whereas the second model aimed to maximize the effectiveness for a given monitoring budget. Our results show that a high level of effectiveness is possible, but at high costs. Given specific assumptions, monitoring with 95% effectiveness to detect an incident of 1 contaminated farm at a dioxin concentration of 2 pg of toxic equivalents/g of fat [European Commission’s (EC) action level] costs €2.6 million per month. At the same level of effectiveness, a 73% cost reduction is possible when aiming to detect an incident where 2 farms are contaminated at a dioxin concentration of 3 pg of toxic equivalents/g of fat (EC maximum level). With a fixed budget of €40,000 per month, the probability of detecting an incident with a single contaminated farm at a dioxin concentration equal to the EC action level is 4.4%. This probability almost doubled (8.0%) when aiming to detect the same incident but with a dioxin concentration equal to the EC maximum level. This study shows that the effectiveness of finding an incident depends not only on the ratio at which, for testing, collected truck samples are mixed into a pooled sample (aiming at detecting certain concentration), but also the number of collected truck samples. In conclusion, the optimal cost-effective monitoring depends on the number of contaminated farms and the concentration aimed at detection. The models and study results offer quantitative support to risk managers of food industries and food safety authorities.

A regulatory framework for pervasive e-health: A case study

To facilitate superior healthcare delivery and address current challenges faced by healthcare today, a plethora of pervasive e-health solutions are emerging. However, existing regulatory regimes are ill-equipped for dealing with them. This not only causes frustration to various stakeholders including patients, providers, healthcare organizations and payers, not to mention vendors but also means that the most appropriate solution cannot be accessed and used. Hence this exploratory study serves to investigate institutional regulatory factors that can impact the adoption of such pervasive e-health solutions. These factors are important as they can shape both the nature of these solutions and their diffusion trajectory. We argue that co-regulation, a mixture of direct monitoring and intervention of regulators through legislation and complete industry self-regulation, can be an effective approach especially in view of the complex and dynamic nature of this industry, co-regulation can minimize monitoring costs and enhance compliance. We illustrate with a case vignette.

Advancing assessment and design of stormwater monitoring programs using a self-organizing map: Characterization of trace metal concentration profiles in stormwater runoff

Stormwater runoff poses a great challenge to the scientific assessment of the effects of diffuse pollution sources on receiving waters. In this study, a self-organizing map (SOM), a research tool for analyzing specific patterns in a large array of data, was applied to the monitoring data obtained from a stormwater monitoring survey to acquire new insights into stream water quality profiles under different rainfall conditions. The components of the input data vectors used by the SOM included concentrations of 10 metal elements, river discharge, and rainfall amount which were collected at the inlet and endpoint of an urban segment of the Yeongsan River, Korea. From the study, it was found that the SOM displayed significant variability in trace metal concentrations for different monitoring sites and rainfall events, with a greater impact of stormwater runoff on stream water quality at the upstream site than at the downstream site, except under low rainfall conditions (≤4 mm). In addition, the SOM clearly determined the water quality characteristics for “non-storm” and “storm” data, where the parameters nickel and arsenic and the parameters chromium, cadmium, and lead played an important role in reflecting the spatial and temporal water quality, respectively. When the SOM was used to examine the efficacy of stormwater quality monitoring programs, between 34 and 64% of the sample size in the current data set was shown to be sufficient for estimating the stormwater pollutant loads. The observed errors were small, generally being below 10, 6, and 20% for load estimation, map resolution, and clustering accuracy, respectively. Thus, the method recommended may be used to minimize monitoring costs if both the efficiency and accuracy are further determined by examining a large existing data set.

Many‐objective groundwater monitoring network design using bias‐aware ensemble Kalman filtering, evolutionary optimization, and visual analytics

This study contributes the Adaptive Strategies for Sampling in Space and Time (ASSIST) framework for improving long‐term groundwater monitoring decisions across space and time while accounting for the influences of systematic model errors (or predictive bias). The new framework combines contaminant flow‐and‐transport modeling, bias‐aware ensemble Kalman filtering (EnKF), many‐objective evolutionary optimization, and visual analytics‐based decision support. The ASSIST framework allows decision makers to forecast the value of investments in new observations for many objectives simultaneously. Information tradeoffs are evaluated using an EnKF to forecast plume transport in space and time in the presence of uncertain and biased model predictions that are conditioned on uncertain measurement data. This study demonstrates the ASSIST framework using a laboratory‐based physical aquifer tracer experiment. In this initial demonstration, the position and frequency of tracer sampling was optimized to (1) minimize monitoring costs, (2) maximize the information provided to the EnKF, (3) minimize failures to detect the tracer, (4) maximize the detection of tracer fluxes, (5) minimize error in quantifying tracer mass, and (6) minimize error in quantifying the centroid of the tracer plume. Our results demonstrate that the forecasting, search, and visualization components of the ASSIST framework represent a significant advance for observation network design that has a strong potential to innovate our characterization, prediction, and management of groundwater systems.

Regulating Mobile Services

While the development of mobile services is experiencing a spectacular growth in many countries worldwide, existing regulatory regimes are ill equipped for dealing with them. In this paper, the authors use qualitative evidence to investigate the manner in which institutional regulatory factors, including legal, societal, and economic factors, can impact mobile services in the Australian mobile telecommunications industry. These factors are important as they shape both the nature of emerging mobile services and their diffusion trajectory. The investigation culminates with an innovative institutional regulatory framework that includes factors such as consumer and intellectual property protection, market and resources access. The authors argue that co-regulation, a mixture of direct monitoring and intervention of regulators through legislation and complete industry self-regulation, is an effective approach for regulating the mobile telecommunications industry. Given the complex and dynamic nature of this industry, co-regulation can minimize monitoring costs and enhance compliance.