Model Insights Research Articles

Minding the gap? Blind spots in the ILO's and the EU's perspective on anti-forced labour policy

This article critically examines the EU's recent proposal to ban products made with forced labour from its market, which adopts the ILO's definition of ‘forced labour’ as outlined in the Forced Labour Convention of 1930 (No. 29). The authors argue that the EU's endorsement of the ILO's approach is problematic due to two flawed assumptions: (1) the definition of ‘forced labour’ is universally accepted across the EU, and (2) it is well-suited to combat forced labour in contemporary supply chains. Through an analysis of ongoing debates between the ILO and its Member States, the article demonstrates a lack of consensus regarding the interpretation of the Convention, particularly in the context of hybrid public-private prison labour arrangements. Furthermore, introducing a new Hybrid Multi-Dimensional (HMD) model for analysing contemporary prison labour practices, the article reveals blind spots in the ILO's approach that may inadvertently allow the incorporation of prison labour into supply chains, contrary to the EU's objectives. The article argues that the EU's unequivocal endorsement of the ILO's definition disregards these fundamental issues and may hinder the effective implementation of its proposed ban. The authors suggest that the HMD model offers a more comprehensive framework for analysing the complex realities of modern prison labour and could provide a roadmap for resolving the ILO-States debate. The article concludes that the EU should reconsider its wholesale adoption of the ILO's approach in light of the HMD model's insights in order to fulfil the objectives of its proposed forced labour product ban.

The process and perils of coming around: The assimilation of political appointees into bureaucratic agencies

AbstractThe tendency for political appointees to assimilate into the bureaucratic agencies that they lead is a recurring source of tension between appointees and the executives who appoint them. This paper employs a formal model to explore how appointees come around to the views of the civil servants whom they oversee. We conceptualize a bureaucrat as providing a cheap‐talk message about privately known, policy‐relevant conditions to an appointee who uses that information to update her beliefs and set two types of policy. Though the bureaucrat's and appointee's preferences are aligned conditional on beliefs, the appointee's prior beliefs about the likelihood of various states of the world differ from the bureaucrat's. In equilibrium, truthful reporting and inducing belief convergence may be at odds and we identify when the bureaucrat will strategically choose to issue false reports. We apply the model's insights to the budget process and agency recommendations during the COVID‐19 pandemic.

A multiscale mechanics model for elastic properties of densified wood

We introduce a multiscale mechanics model for analyzing the elastic properties of super-strong densified wood (DW). Our model incorporates microstructural features such as microfibril angle and densification ratio, along with chemical parameters including degree of polymerization, crystallinity, and density of hydrogen bonds. At the nanoscale and microscale, the elastic properties of cellulose nanofibril and cell wall layers are derived analytically using the mechanics of composite materials. Finite element simulations based on representative volume elements are conducted at the mesoscale to obtain homogenized effective elastic properties at the macroscale. Our quantitative investigations validate that microstructural changes and alterations in chemical components significantly enhance DW's mechanical performance. Densification and chemical changes, especially increased cellulose content and reduced lignin, emerge as vital mechanisms for strengthening DW. The model's insights offer valuable guidance for optimizing the two-step preparation process of DW to achieve superior mechanical performance. Additionally, the versatility of the model allows for exploring the influence of cell dimensions and potential applications in designing bioinspired materials.

The Ramsey Model's Insight on Long-Term Growth Amidst Brexit and the COVID-19 Pandemic

The Ramsey Model's Insight on Long-Term Growth Amidst Brexit and the COVID-19 Pandemic

A numerical study of a new non-linear fractal fractional mathematical model of malicious codes propagation in wireless sensor networks

This paper presents a novel non-linear fractal fractional mathematical model for analyzing the spread of malicious codes in wireless sensor networks (WSNs). The model incorporates fractional calculus and non-linear interactions among nodes in a WSN. It is based on the Fractal-Fractional (FF) operator, a powerful mathematical tool that combines fractional and fractal calculus. This study explores the potential of fractional derivatives in addressing computer virus-related issues and proposes a model that elucidates the spread of viruses in a vulnerable system and potential countermeasures. The Fractal-Fractional operator is utilized to fractionalize the model, and the fixed point theory of Schauder and Banach is applied to establish the existence and uniqueness of a solution. Numerical simulations, employing MATLAB and the Adams-Bashforth method, validate the effectiveness of the proposed model in capturing the propagation dynamics of malicious codes. Ulam-Hyers stability techniques are also employed for stability analysis. The model's insights contribute to enhancing the security and robustness of WSNs against malicious code propagation, paving the way for more secure network designs. This research provides a unique perspective on analyzing the dynamics of WSNs and underscores the significance of fractional derivatives in addressing security threats in network systems.

IMPACT ON THE MARKETCAPITALIZATION OF BLOCKCHAIN-BASED CRYPTOCURRENCIES

This paper presents an advanced econometric model specifically designed to analyze the intricate relationship between blockchain technology and various economic variables. The model serves as a robust framework for comprehending the impact of blockchain on investment patterns, adoption rates, and market trends. By quantifying these relationships, the model enables predictions regarding future trends in the blockchain industry and facilitates the identification of factors influencing growth or hindering adoption. With its wide-ranging applicability, the model offers profound insights for policymakers, investors, entrepreneurs, and researchers, shedding light on the economic implications of this rapidly evolving technology.The findings of this study reveal a multitude of significant insights regarding the economic implications of blockchain technology. The econometric model demonstrates a strong positive relationship between blockchain investment and adoption rates, indicating that increased investment leads to higher adoption levels. Moreover, the model identifies specific market trends and factors that influence the growth and adoption of blockchain technology. By highlighting these factors, stakeholders can make informed decisions and strategize accordingly.The econometric model forblockchain technology offers numerous applications and implications for various stakeholders. Policymakers can leverage the model's insights to develop regulatory frameworks that foster blockchain innovation while mitigating risks. Investors can utilize the model to make data-driven investment decisions and identify lucrative opportunities within the blockchain industry. Entrepreneurs can gain valuable insights into the factors driving adoption and tailor their business strategies accordingly. Additionally, researchers can expand their understanding of the relationship between technology and economic variables, contributing to the development of new theories and frameworks.

Cognition-Enhanced Machine Learning for Better Predictions with Limited Data.

The fields of machine learning (ML) and cognitive science have developed complementary approaches to computationally modeling human behavior. ML's primary concern is maximizing prediction accuracy; cognitive science's primary concern is explaining the underlying mechanisms. Cross-talk between these disciplines is limited, likely because the tasks and goals usually differ. The domain of e-learning and knowledge acquisition constitutes a fruitful intersection for the two fields' methodologies to be integrated because accurately tracking learning and forgetting over time and predicting future performance based on learning histories are central to developing effective, personalized learning tools. Here, we show how a state-of-the-art ML model can be enhanced by incorporating insights from a cognitive model of human memory. This was done by exploiting the predictive performance equation's (PPE) narrow but highly specialized domain knowledge with regard to the temporal dynamics of learning and forgetting. Specifically, the PPE was used to engineer timing-related input features for a gradient-boosted decision trees (GBDT) model. The resulting PPE-enhanced GBDT outperformed the default GBDT, especially under conditions in which limited data were available for training. Results suggest that integrating cognitive and ML models could be particularly productive if the available data are too high-dimensional to be explained by a cognitive model but not sufficiently large to effectively train a modern ML algorithm. Here, the cognitive model's insights pertaining to only one aspect of the data were enough to jump-start the ML model's ability to make predictions-a finding that holds promise for future explorations.

Valence, Elections, and Legislative Institutions

AbstractTo the degree that voters care about competence, expertise, and other valence characteristics of their representatives and political parties care about winning elections, parties have an incentive to signal that their legislators have such characteristics. We construct a model of parties, motivated by both reelection and by policy, that attempt to signal individual incumbents' valences to voters through the assignment of these members to positions of authority. The model illustrates how electorally motivated party leaders will have an incentive to promote less competent incumbents than they would if voters did not make inferences from promotion decisions. We derive the model's empirical implications and test them with original data on the careers of Chilean senators serving between 1998 and 2013. In support of the model's insights, we find that promotion to a leadership position is an effective signal to voters only if the promoted incumbent has extreme views relative to the party.

Intermediation in the Supply of Agricultural Products in Developing Economies

Problem Definition: Farmers face several challenges in agricultural supply chains in emerging economies that contribute to extreme levels of poverty. One common challenge is that farmers only have access to one channel, often an auction, for which to sell their crops. Recently, e-intermediaries have emerged as alternate, technology-driven posted-price channels. We aim to develop insights into the structural drivers of farmer and supply chain profitability in emerging markets and understand the impact of e-intermediaries. Academic/Practical Relevance: In practice, much attention has been given to e-intermediaries and they have often been touted as for-profit social enterprises that improve farmers' welfare. Yet, studies in the operations literature that systematically analyze the impact of e-intermediaries are lacking. Our work fills this gap and answers practical questions regarding the responsible operations of e-intermediaries. Methodology: We develop an analytical model of a supply chain that allows us to study several key features of intermediated supply chains. We complement the model's insights with observations from a numerical study. Results: In the absence of an e-intermediary, auctions cause farmers to either overproduce or underproduce compared to their ideal production levels in a vertically integrated chain. The presence of an e-intermediary with limited market share improves farmers' profits; however, if the e-intermediary grows too large, it negatively impacts both farmers' and supply chain profits. Finally, as the number of farmers increases, farmers' profits approach zero, irrespective of the e-intermediary's presence. Managerial Implications: Our results provide a balanced perspective on the value of e-intermediation, compared to the generally positive views advanced by case studies. For-profit e-intermediaries that also aim to improve farmers' livelihoods cannot blindly operate as pure profit-maximizers, assuming that market forces alone will ensure that farmers benefit. Even when e-intermediation benefits farmers, it is insufficient to mitigate the negative effects of supply fragmentation, suggesting that for farmers, market power is more important than market access.

Trading Fees and Intermarket Competition

We model an order book with liquidity rebates (make fees) and trading fees (take fees) that faces intermarket competition, and use the model's insights to explain changes in market quality and market shares following changes in make-take fees. As predicted by our model, we document that fee changes by one venue affect market quality and market shares for all venues that compete for order flow. Furthermore, we document cross-sectional differences in changes in market quality and market shares following a simultaneous decrease in both make and take fees consistent with traders in large (small) capitalization stocks being more sensitive to the change in make (take) fees.

Trading Fees and Intermarket Competition

We model an order book with liquidity rebates (make fees) and trading fees (take fees) that faces intermarket competition, and use the model's insights to explain changes in market quality and market shares following changes in make-take fees. As predicted by our model, we document that fee changes by one venue affect market quality and market shares for all venues that compete for order flow. Furthermore, we document cross-sectional differences in changes in market quality and market shares following a simultaneous decrease in both make and take fees consistent with traders in large (small) capitalization stocks being more sensitive to the change in make (take) fees.

North American natural gas and energy markets in transition: insights from global models

This modeling comparison exercise looks at the global consequences of increased shale gas production in the U.S. and increased gas demand from Asia. We find that differences in models' theoretical construct and assumptions can lead to divergences in their predictions about the consequences of U.S. shale gas boom. In general, models find that U.S. High Shale Gas scenario leads to increased U.S. production, lower global gas prices, and lower gas production in non-U.S. regions. Gas demand in Asia alone has little effects on U.S. production; but together with the shale gas boom, the U.S. can have a large export advantage. Overall, models find U.S. exports level range from 0.06 to 13.7 trillion cubic feet (TCF) in 2040. The comparison of supply, demand, and price changes in response to shocks reveals important differences among models. First is how the demand shocks were implemented and how the model responds to shocks: static and elastic within each time period vs. endogenous to the long-term gross domestic product (GDP) growth. Second is how the supply response is expressed through fuel/technology substitutions, particularly the flexibility of cross-fuel substitution in the power sector. Identifying these differences is important in understanding the model's insights and policy recommendations.

Spatiotemporal data visualisation for homecare monitoring of elderly people

Elderly people who live alone can be assisted by home monitoring systems that identify risk scenarios such as falls, fatigue symptoms or burglary. Given that these systems have to manage spatiotemporal data, human intervention is required to validate automatic alarms due to the high number of false positives and the need for context interpretation. The goal of this work was to provide tools to support human action, to identify such potential risk scenarios based on spatiotemporal data visualisation. We propose the MTA (multiple temporal axes) model, a visual representation of temporal information of the activity of a single person at different locations. The main goal of this model is to visualize the behaviour of a person in their home, facilitating the identification of health-risk scenarios and repetitive patterns. We evaluate the model's insight capacity compared with other models using a standard evaluation protocol. We also test its practical suitability of the MTA graphical model in a commercial home monitoring system. In particular, we implemented 8VISU, a visualization tool based on MTA. MTA proved to be more than 90% accurate in identify non-risk scenarios, independently of the length of the record visualised. When the spatial complexity was increased (e.g. number of rooms) the model provided good accuracy form up to 5 rooms. Therefore, user preferences and user performance seem to be balanced. Moreover, it also gave high sensitivity levels (over 90%) for 5-8 rooms. Fall is the most recurrent incident for elderly people. The MTA model outperformed the other models considered in identifying fall scenarios (66% of correctness) and was the second best for burglary and fatigue scenarios (36% of correctness). Our experiments also confirm the hypothesis that cyclic models are the most suitable for fatigue scenarios, the Spiral and MTA models obtaining most positive identifications. In home monitoring systems, spatiotemporal visualization is a useful tool for identifying risk and preventing home accidents in elderly people living alone. The MTA model helps the visualisation in different stages of the temporal data analysis process. In particular, its explicit representation of space and movement is useful for identifying potential scenarios of risk, while the spiral structure can be used for the identification of recurrent patterns. The results of the experiments and the experience using the visualization tool 8VISU proof the potential of the MTA graphical model to mine temporal data and to support caregivers using home monitoring infrastructures.

Fragility in Money Market Funds: Sponsor Support and Regulation

Money Market Funds (MMFs), which are crucial to short-term funding markets, rely on voluntary support of fund sponsors to maintain stable share values. I develop a general equilibrium model of MMFs to study how sponsor support affects the industry's fragility and regulation. Adverse asset-quality shocks lead MMFs to liquidate assets. When liquidity in asset markets is limited, asset prices are lower if more funds liquidate. Lower asset prices, in turn, make sponsor support costlier and even more liquidations occur. This feedback leads to complementarities in sponsors' support decisions. Based on the model's insights, I derive implications for the regulation of MMFs.

Interpretive structural modeling of supply chain risks

PurposeThe aim of this paper is the structural analysis of potential supply chain risks. It will demonstrate how interpretive structural modeling (ISM) supports risk managers in identifying and understanding interdependencies among supply chain risks on different levels (e.g. 3PL, first‐tier supplier, focal company, etc.). Interdependencies among risks will be derived and structured into a hierarchy in order to derive subsystems of interdependent elements with corresponding driving power and dependency.Design/methodology/approachISM was used to identify inter‐relationships among supply chain risks and to classify the risks according to their driving and dependence power. The theoretical findings of the modeling and the applicability for practical use has been tested in two case studies with two German industry and trade companies.FindingsISM was proven as a useful methodology to structure supply chain risks in an easy and distributed approach that can also be carried out in a step‐by‐step process on several manufacturing stages. The input to the algorithm has to be well‐defined to give the user an exact understanding of all risks that have to be assessed, i.e. the better the input to ISM is prepared the better the outcome and representation will be. Finally, when applying the method, a moderated process proved to be more reliable than an assessment based on paper questionnaires only.Originality/valueThis model's insight would assist supply chain (risk) managers in the effective allocation of risk management resources in the subsequent risk management phases.

Anatomy of Welfare Reform Evaluation: Announcement and Implementation Effects

This paper formulates a simple model of female labor force decisions which embeds an in-work benefit reform and explicitly allows for announcement and implementation effects. We explore several mechanisms through which women can respond to the announcement of a reform that increases in-work benefits, including sources of intertemporal substitution, human capital accumulation, and labor market frictions. Using the model's insights and information of the precise timing of the announcement and implementation of a major UK in-work benefit reform, we estimate its effects on single mothers' behavior. We find important announcement effects on employment decisions. We show that this finding is consistent with the presence of short-run frictions in the labor market. Evaluations of this reform which ignore such effects produce impact effect estimates that are biased downwards by 15 to 35 percent.

Languages in the European Union: The quest for equality and its cost

The European Union has recently expanded from 15 to 25 countries, bringing the number of official languages to 20. Currently, the EU extends equal treatment to all member countries’ official languages. This, however, is costly, especially since many Europeans speak one of the procedural languages, English, French or German, either as a native or a foreign language. We develop a simple theoretical model of linguistic-regime choice in a multilingual society and apply the model's insights to the case of the EU: we compute disenfranchisement rates that would result from using only the three procedural languages for all EU business and then proceed to quantify the average cost per person and cost per disenfranchised person associated with providing translations and interpreting into the remaining languages. Both the disenfranchisement rates and costs are shown to vary substantially across the different languages, raising important questions about the economic efficiency of equal treatment for all languages. We argue that an efficient solution would be to decentralize the provision of translations.

China's Energy Strategy: Economic Structure, Technological Choices, and Energy Consumption (review)

i88 China Review International: Vol. 5, No. 1, Spring 1998 Xiannuan Lin. China's Energy Strategy: Economic Structure, Technological Choices, and Energy Consumption. Westport, Connecticut: Praeger Publishers , 1996. xvii, 203 pp. Hardcover $65.00, isbn 0-275-95306-8. This book offers important insights into a fascinating feature of China's economic growth during the reform era—the declining energy intensity of the Chinese economy. The book crisply proceeds through summarizing the issue, propounding an input-output model of energy consumption, explaining the results produced by the model, and pursuing the model's insights in a case study of the iron and steel industry. As they grow, developing economies usually exhibit increasing energy intensity (the ratio of commercial energy consumption to GDP), a trend followed by China for thirty years after the founding of the People's Republic. The uniformity of this trend across China and other developing countries led outside observers reasonably to expect that growing energy and electric power shortages in China in the late 1970s would constrain economic growth. For example, the CIA (1980) predicted that electric power shortages would restrict China's economic growth to 3 percent per year in the first half of the 1980s.1 The Chinese economy dramatically disproved these predictions. From 1981 to 1987, the time period studied in this book, the Chinese economy grew about 10 percent per year. As the book stresses, this growth was not fueled by an equal growth of commercial energy consumption. Instead, the energy intensity of the Chinese economy "decreased by almost 22 percent" between 1981 and 1987 (p. 3). This unexpected decline has been the topic of much speculation and recent research . In the 1980s, the decline was often attributed to the shift in emphasis from heavy industry to light industry. In the 1990s various researchers have more carefully examined the available data to develop a more sophisticated understanding of this remarkable decline. This study adds to the research by decomposing the change in energy consumption, using China's 1981 and 1987 input-output tables. Input-output analysis provides a wealth of information about the interconnections between an economy's production and consumption sectors. As this book shows, much can be learned about energy consumption from looking at the changes in production technology and in the structure of final demand. Chapter 1 introduces the issue of falling energy intensity in the Chinese economy, explaining why this phenomenon warrants attention. Then it succinctly© 1998 by University states the research goals of the study and emphasizes their importance. This chapofHawai 'i Presster serves as a most accessible introduction to the topic for nonspecialists. Chapter 2, using tables and charts, describes energy consumption in China for 1981 and 1987 by production and consumption sector and by energy source. This gives the Reviews 189 reader a working knowledge ofthe data that the autiior's model explores in greater depth. Chapter 3, which presents the basic model of the book, may prove mildly frustrating to those readers who carefully try to follow the matrix algebra of the model.2 All readers can trust in the actual implementation ofthe model and should quickly grasp the basic technique: calculate the energy required to produce 1987 final demand using 1981 technology; then compare this to actual energy use in 1987. Using the 1981 and 1987 input-output tables, the key equation ofthe model (equation 8 on p. 49) shows that die change in energy use in China between 1981 and 1987 can be decomposed into a "final-demand shift" and a "production -technology change." The final-demand shift equals the extra energy required to produce 1987 intermediate output using 1981 technologyplus the increase from 1981 to 1987 in energy directiy used by final consumers. The production -technology change is the difference between intermediate energy used to produce 1981 final demand using 1987 technology and actual intermediate energy used to produce 1981 final demand using 1981 technology. The model elaborates on this basic idea, further decomposing the final demand shift and the production technology change by final demand sectors and by production sectors. Table 3.4 on page 54 concisely summarizes the elements ofthe model. Chapters 4 and 5 detail the findings yielded by...

Intra-Alliance Bargaining and U.S. Bosnia Policy

Alliances are promises of cooperation, but allies typically have to bargain over what policy should be adopted when a given contingency arises. Whether this bargaining leads to collaborative outcomes and what form cooperation by allies takes have important implications for the effectiveness of an alliance. Neorealism and neoliberal institutionalism, the author argues, do not provide adequate explanations for this problem because they mischaracterize, or fail to come to grips with, the bargaining process at work. To redress such shortcomings, the author turns to game theory, providing a general model of intra-alliance bargaining. The model's insights are then used to interpret the historical record on U.S. Bosnia policy from 1991 until the fall of 1995. The author shows how domestic and international considerations affected the preferences and beliefs of the Bush and Clinton administrations. These led, as suggested by the model, to the U.S. tendency to avoid bargaining hard with the NATO allies and to pursue compromise strategies with them in the Bosnian crisis.