Is Theory Useful for Conflict Prediction? A Response to Beger, Morgan, and Ward

2021 ◽  
pp. 002200272110267
Author(s):  
Robert A. Blair ◽  
Nicholas Sambanis
Keyword(s):  
Civil Wars ◽  
Performance Metrics ◽  
Value Added ◽  
Roc Curves ◽  
Conflict Escalation ◽  
Original Analysis ◽  
Is Theory ◽  
A Minor ◽  
Conflict Prediction ◽  
Technical Question

Beger, Morgan, and Ward (BM&W) call into question the results of our article on forecasting civil wars. They claim that our theoretically-informed model of conflict escalation under-performs more mechanical, inductive alternatives. This claim is false. BM&W’s critiques are misguided or inconsequential, and their conclusions hinge on a minor technical question regarding receiver operating characteristic (ROC) curves: should the curves be smoothed, or should empirical curves be used? BM&W assert that empirical curves should be used and all of their conclusions depend on this subjective modeling choice. We extend our original analysis to show that our theoretically-informed model performs as well as or better than more atheoretical alternatives across a range of performance metrics and robustness specifications. As in our original article, we conclude by encouraging conflict forecasters to treat the value added of theory not as an assumption, but rather as a hypothesis to test.

Forecasting Civil Wars: Theory and Structure in an Age of “Big Data” and Machine Learning

2020 ◽  
Vol 64 (10) ◽  
pp. 1885-1915 ◽  
Author(s):  
Robert A. Blair ◽  
Nicholas Sambanis
Keyword(s):  
Civil War ◽  
Civil Wars ◽  
Structural Characteristics ◽  
Value Added ◽  
Contentious Politics ◽  
Forecasting Accuracy ◽  
Conflict Escalation ◽  
Parsimonious Model ◽  
Temporal Windows ◽  
Civil War Onset

Does theory contribute to forecasting accuracy? We use event data to show that a parsimonious model grounded in prominent theories of conflict escalation can forecast civil war onset with high accuracy and over shorter temporal windows than has generally been possible. Our forecasting model draws on “procedural” variables, building on insights from the contentious politics literature. We show that a procedural model outperforms more inductive, atheoretical alternatives and also outperforms models based on countries’ structural characteristics, which previously dominated models of civil war onset. We find that process can substitute for structure over short forecasting windows. We also find a more direct connection between theory and forecasting than is sometimes assumed, though we suggest that future researchers treat the value-added of theory for prediction not as an assumption but rather as a hypothesis to test.

scholarly journals The Influence of R&D Intensity on Financial Performance: The Mediating Role of Human Capital in the Semiconductor Industry in Taiwan

2020 ◽  
Vol 12 (12) ◽  
pp. 5128
Author(s):  
Tsung-Chun Chen ◽  
Yenchun Jim Wu
Keyword(s):  
Human Capital ◽  
Financial Performance ◽  
Capital Investment ◽  
Performance Metrics ◽  
Intangible Assets ◽  
Semiconductor Industry ◽  
Value Added ◽  
Positive Influence ◽  
High Tech ◽  
The Relationship

Knowledge transfer is a strategy used by high-tech companies to acquire new knowledge and skills. Knowledge can be internally generated or externally sourced. The access to external knowledge is a quick fix, but the risks associated with reliance on external sources are often overlooked. However, not acquiring such knowledge is even riskier. There have been a slew of litigations in the semiconductor industry in recent years. The acquisition and assurance of intangible assets is an important issue. This paper posits that internal R&D should take into consideration the knowledge intensity and capital investment in the industry. This study focuses on the relationship between intangible assets and financial performance. It sourced the 2004 to 2016 financial data of semiconductor companies in Taiwan for panel data modeling and examined case studies for empirical validation. This study found that the higher the R&D intensity (RDI) in the value-added component of human capital, the better the financial performance of the company. RDI has a positive influence on the accumulation of human capital and financial performance metrics, and such influence is deferred. Meanwhile, human capital is a mediating factor in the relationship between RDI and financial performance. RDI is integral to the semiconductor industry’s pursuit of business sustainability.

scholarly journals Value added or tunneling? Evidence from new product announcements by Taiwanese business groups

2016 ◽  
Vol 22 (5) ◽  
pp. 623-641
Author(s):  
Shao-Chi Chang ◽  
I-Fen Chen
Keyword(s):  
Business Groups ◽  
Value Added ◽  
Market Value ◽  
New Product ◽  
Network Ties ◽  
Family Control ◽  
Original Analysis ◽  
Multiple Network ◽  
The Impact ◽  
Group Member

AbstractUsing new product announcement events made by group member firms in Taiwan, this study examines whether the firms’ multiple network ties within business groups benefit member firms or whether they provide a channel for controlling shareholders to tunnel. We find that the announcement of new products by group member firms has a positive effect on the market value of other, non-announcing group peers. This evidence is consistent with the value-added hypothesis. More importantly, this effect is stronger when member firms are connected via equity ties. Furthermore, we also offer an original analysis of how family control in business groups affects the impact of network ties on value creation. Our results suggest that the controlling family may discount the market value of member firms.

scholarly journals Model Assessment with ROC Curves

2011 ◽  
pp. 1316-1323 ◽  
Author(s):  
Lutz Hamel
Keyword(s):  
Performance Metrics ◽  
Confusion Matrix ◽  
Model Performance ◽  
Roc Curves ◽  
Parametric Models ◽  
Classification Model ◽  
Model Assessment ◽  
Classification Models ◽  
The Difference ◽  
Class Skew

Classification models and in particular binary classification models are ubiquitous in many branches of science and business. Consider, for example, classification models in bioinformatics that classify catalytic protein structures as being in an active or inactive conformation. As an example from the field of medical informatics we might consider a classification model that, given the parameters of a tumor, will classify it as malignant or benign. Finally, a classification model in a bank might be used to tell the difference between a legal and a fraudulent transaction. Central to constructing, deploying, and using classification models is the question of model performance assessment (Hastie, Tibshirani, & Friedman, 2001). Traditionally this is accomplished by using metrics derived from the confusion matrix or contingency table. However, it has been recognized that (a) a scalar is a poor summary for the performance of a model in particular when deploying non-parametric models such as artificial neural networks or decision trees (Provost, Fawcett, & Kohavi, 1998) and (b) some performance metrics derived from the confusion matrix are sensitive to data anomalies such as class skew (Fawcett & Flach, 2005). Recently it has been observed that Receiver Operating Characteristic (ROC) curves visually convey the same information as the confusion matrix in a much more intuitive and robust fashion (Swets, Dawes, & Monahan, 2000). Here we take a look at model performance metrics derived from the confusion matrix. We highlight their shortcomings and illustrate how ROC curves can be deployed for model assessment in order to provide a much deeper and perhaps more intuitive analysis of the models. We also briefly address the problem of model selection.

scholarly journals Soy dairy performance metrics

2021 ◽  
Vol 21 (105) ◽  
pp. 19016-19039
Author(s):  
J Krause ◽  
◽  
M Cornelius ◽  
P Goldsmith ◽  
M Mzungu ◽  
...  
Keyword(s):  
Performance Metrics ◽  
Dairy Product ◽  
Value Added ◽  
Regulatory Compliance ◽  
Fixed Costs ◽  
Firm Level ◽  
Recordkeeping System ◽  
Tropical Environments ◽  
Level Data ◽  
Manufacturing Technologies

Soybean (Glycine max (L. Merr.) has been a crop of interest to address both poverty and malnutrition in the developing world because of its high levels of both protein and oil, and its adaptability to grow in tropical environments. Development practitioners and policymakers have long sought value added opportunities for local crops to move communities out of poverty by introducing processing or manufacturing technologies. Soy dairy production technologies sit within this development conceptual model. To the researchers’ knowledge, no research to date measures soy dairy performance, though donors and NGOs have launched hundreds of enterprises over the last 18 years. The lack of firm-level data on operations limits the ability of donors and practitioners to fund and site sustainable dairy businesses. Therefore, the research team developed and implemented a recordkeeping system and training program first, as a 14-month beta test with a network of five dairies in Ghana and Mozambique in 2016-2017. Learning from the initial research then supported a formal research rollout over 18 months with a network of six different dairies in Malawi and key collaboration from USAID’s Agricultural Diversification activity. None of the beta or rollout dairies kept records prior to the intervention. The formal rollout resulted in a unique primary dataset to address the soy dairy performance knowledge gap. The results of analysis show that the dairies, on average, achieve positive operating margins of 61%, yet cannot cover the fixed costs associated with depreciation, amortization of equipment and infrastructure, working capital, marketing and promotion, and regulatory compliance. The enterprises in our sample operate only at 9% of capacity, which limits their ability to cover the normal fixed costs associated with the business. The challenge is not the technology itself, as when operated, it produces a high-quality dairy product. The challenges involve a business that requires too much capital for normal operations relative to a nascent and small addressable market.

Relationship between EVA (Economic Value Added) and Share Prices of Select Companies in BSE-SENSEX - An Empirical Study

2015 ◽  
Vol 4 (3and4) ◽  
Author(s):  
Mathangi Aravind ◽  
K. Ramya
Keyword(s):  
Performance Metrics ◽  
Explanatory Power ◽  
Economic Value ◽  
Value Added ◽  
Market Value ◽  
Economic Value Added ◽  
Share Prices ◽  
The World ◽  
The Impact ◽  
The Relationship

In todays competitive world, corporate companies all around the world are trying to maximize the wealth of their shareholders in order to gain market value as well as satisfy their stakeholders. With the gaining popularity of value based performance measures like Economic Value Added (EVA), Total Shareholder Return (TSR), Cash Value Added (CVA) etc., many corporate companies in India have started assessing their value in terms of these measures. This paper investigates the relationship between EVA and share prices of select companies in BSE-SENSEX for a period of six years from 2008 to 2013. The study focuses on the explanatory power of EVA with respect to share prices of the selected companies. In turn, the performance of the selected companies belonging to different sectors in BSE-SENSEX was analyzed using EVA. The volatile nature of the capital markets characterized by various speculative activities have a greater influence on share prices, eventually undermining the impact of performance metrics on them. Thus, the findings of the study enumerates that EVA does not have a considerable explanatory power on share prices.

scholarly journals The Paradox of Safe Areas in Ethnic Civil Wars

2018 ◽  
Vol 10 (3) ◽  
pp. 362-386 ◽  
Author(s):  
Stefano Recchia
Keyword(s):  
At Risk ◽  
High Risk ◽  
Civil Wars ◽  
Medium Term ◽  
Short Term ◽  
Conflict Escalation ◽  
Civilian Protection ◽  
Causal Mechanisms ◽  
Peace Negotiations ◽  
Conflict Zone

Safe areas established by powerful states can improve short-term civilian protection during ethnic civil wars. Paradoxically, however, they may worsen the plight of vulnerable civilians over the medium term. This can occur in three ways. First, when safe areas encompass sizeable territories within a broader conflict zone, they may reduce incentives for protected groups to compromise during peace negotiations, thus prolonging hostilities. Second, there is a nontrivial possibility that protected groups will use the safe areas as a base for launching high-risk offensives, deliberately putting civilians at risk in the hope of drawing the protection forces more deeply into the war. Third, safe areas may embolden protected groups to seek unilateral secession, further increasing the risk of conflict escalation. By elucidating the causal mechanisms involved, this article helps us assess the probability of these outcomes occurring. States that consider intervening militarily to establish safe areas in ethnic civil wars need to weigh the short-term benefits against these possible longer-term downsides.

scholarly journals AGRICULTURAL PERFORMANCE OF OIL-DEPENDENT ECONOMIES

2018 ◽  
Vol XX (6) ◽  
pp. 35-40 ◽  
Author(s):  
Katarzyna Czech
Keyword(s):  
United Arab Emirates ◽  
Rural Economy ◽  
Agricultural Sector ◽  
Oil And Gas ◽  
Value Added ◽  
Minor Component ◽  
Oil And Gas Industry ◽  
Agricultural Performance ◽  
Oil Rents ◽  
A Minor

The aim of the paper is to present the agricultural performance of oil-dependent economies. Based on oil rents as a share of GDP ratio, twenty of the most oil-dependent countries are selected. It is shown that food exports constitute a tiny part of total merchandise exports. It concerns all selected countries apart from Ecuador and Norway. Moreover, agriculture value added is a minor component of GDP for the majority of selected oil-dependent economies. Chad and Nigeria are distinguished by the highest agricultural value added to GDP ratio. Qatar, Kuwait and the United Arab Emirates, on the other hand, are among countries in which the ratio is lower than 1%. Many oil-dependent countries have neglected the rural economy since oil discovery. The agricultural sector is largely ignored in favour of the oil and gas industry. However, it should be emphasized that although agriculture constitutes only a minor share of GDP, in many oil-dependent developing countries, the agricultural sector still provides the main livelihood for most people.

scholarly journals Evaluating the Performances of Biomarkers over a Restricted Domain of High Sensitivity

Mathematics ◽  
2021 ◽  
Vol 9 (21) ◽  
pp. 2826
Author(s):  
Manuel Franco ◽  
Juana-María Vivo
Keyword(s):  
Roc Curve ◽  
Performance Metrics ◽  
High Sensitivity ◽  
Roc Curves ◽  
Upper And Lower Bounds ◽  
Area Index ◽  
Colon Cancers ◽  
Partial Area ◽  
Variance Estimates ◽  
Inappropriate Expression

The burgeoning advances in high-throughput technologies have posed a great challenge to the identification of novel biomarkers for diagnosing, by contemporary models and methods, through bioinformatics-driven analysis. Diagnostic performance metrics such as the partial area under the ROC (pAUC) indexes exhibit limitations to analysing genomic data. Among other issues, the inability to differentiate between biomarkers whose ROC curves cross each other with the same pAUC value, the inappropriate expression of non-concave ROC curves, and the lack of a convenient interpretation, restrict their use in practice. Here, we have proposed the fitted partial area index (FpAUC), which is computable through an algorithm valid for any ROC curve shape, as an alternative performance summary for the evaluation of highly sensitive biomarkers. The proposed approach is based on fitter upper and lower bounds of the pAUC in a high-sensitivity region. Through variance estimates, simulations, and case studies for diagnosing leukaemia, and ovarian and colon cancers, we have proven the usefulness of the proposed metric in terms of restoring the interpretation and improving diagnostic accuracy. It is robust and feasible even when the ROC curve shows hooks, and solves performance ties between competitive biomarkers.

scholarly journals The information content of Economic Value Added of food-processing firms in the Czech Republic in the comparison with the information content of traditional performance metrics

2006 ◽  
Vol 54 (6) ◽  
pp. 77-84
Author(s):  
Gabriela Chmelíková
Keyword(s):  
Information Content ◽  
Performance Measures ◽  
Food Processing ◽  
Performance Metrics ◽  
Empirical Studies ◽  
Economic Value ◽  
Value Added ◽  
Superior Performance ◽  
Economic Value Added ◽  
Traditional Performance

The topic of this paper is motivated by the increasing popularity of Economic Value Added (EVA) and by the need to make the managing process of Czech agribusiness firms more efficient. Through adoption of EVA principle, the proponents of EVA argue, that EVA will lead to increased efficiency in the management and allocation of all assets and hence increased shareholder value. Though from the theoretical point of view EVA is seen as a superior performance metric, the results of the most empirical studies do not support this claim. One of the standard argument against EVA superiority results from the statistical survey of the relationship between EVA and traditional performance measures. Despite of the results of the most empirical studies this paper assumes (with regard to the specifics of Czech food processing sector) a difference in information content of EVA and traditional performance metrics. The intent of this article is to provide a simple regression test of the hypothesis that between EVA and traditional performance metrics is not tight linear dependency, which would point out that EVA has the same information content as traditional performance measures. The regression results indicate in all cases a positive correspondence between EVA and financial performance metrics with very low dependency of EVA on the financial metrics, which supports the examined hypothesis.

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