The Future is a Moving Target: Predicting Political Instability

2019 ◽  
Vol 50 (4) ◽  
pp. 1405-1417 ◽  
Author(s):  
Drew Bowlsby ◽  
Erica Chenoweth ◽  
Cullen Hendrix ◽  
Jonathan D. Moyer
Keyword(s):  
Political Institutions ◽  
Armed Conflict ◽  
Predictive Power ◽  
Political Instability ◽  
Explanatory Power ◽  
State Level ◽  
Recent Period ◽  
Arab Uprisings ◽  
Out Of Sample ◽  
Over Time

AbstractPrevious research by Goldstone et al. (2010) generated a highly accurate predictive model of state-level political instability. Notably, this model identifies political institutions – and partial democracy with factionalism, specifically – as the most compelling factors explaining when and where instability events are likely to occur. This article reassesses the model’s explanatory power and makes three related points: (1) the model’s predictive power varies substantially over time; (2) its predictive power peaked in the period used for out-of-sample validation (1995–2004) in the original study and (3) the model performs relatively poorly in the more recent period. The authors find that this decline is not simply due to the Arab Uprisings, instability events that occurred in autocracies. Similar issues are found with attempts to predict nonviolent uprisings (Chenoweth and Ulfelder 2017) and armed conflict onset and continuation (Hegre et al. 2013). These results inform two conclusions: (1) the drivers of instability are not constant over time and (2) care must be exercised in interpreting prediction exercises as evidence in favor or dispositive of theoretical mechanisms.

Usefulness of Accounting Estimates

2016 ◽  
Vol 32 (1) ◽  
pp. 123-135 ◽  
Author(s):  
Li Li Eng ◽  
Thanyaluk Vichitsarawong
Keyword(s):  
Cash Flow ◽  
Exploratory Study ◽  
Abnormal Returns ◽  
Cash Flows ◽  
Recent Period ◽  
Future Earnings ◽  
China And India ◽  
Accounting Estimates ◽  
Out Of Sample ◽  
Over Time

This is an exploratory study to examine the quality or usefulness of accounting estimates of companies in China and India over time. Specifically, we examine how well the accounting estimates are able to predict future earnings and cash flows during the period 2003-2013. The results for India indicate that the out-of-sample earnings and cash flow predictions derived are more accurate and more efficient in the more recent period (2010-2013) than the earlier period (2003-2006). In contrast, the out-of-sample earnings and cash flow predictions for China are generally more biased, less accurate, and less efficient. The results indicate abnormal returns earned on hedge portfolios formed on earnings (cash flow) predictions for India in the recent period. In contrast, none of the portfolios for China earn positive returns. The results suggest that the accounting estimates in India in recent years have become better predictors of future earnings and cash flow than accounting estimates in the earlier period. However, the accounting estimates in China are not relevant for predicting earnings and cash flows over the years in the sample period.

Microstructure in the Machine Age

2020 ◽  
Author(s):  
David Easley ◽  
Marcos López de Prado ◽  
Maureen O’Hara ◽  
Zhibai Zhang
Keyword(s):  
Machine Learning ◽  
Market Efficiency ◽  
Predictive Power ◽  
Explanatory Power ◽  
Futures Contracts ◽  
Machine Age ◽  
Price Process ◽  
Out Of Sample ◽  
Asset Classes ◽  
Out Of Sample Prediction

Abstract Understanding modern market microstructure phenomena requires large amounts of data and advanced mathematical tools. We demonstrate how machine learning can be applied to microstructural research. We find that microstructure measures continue to provide insights into the price process in current complex markets. Some microstructure features with high explanatory power exhibit low predictive power, while others with less explanatory power have more predictive power. We find that some microstructure-based measures are useful for out-of-sample prediction of various market statistics, leading to questions about market efficiency. We also show how microstructure measures can have important cross-asset effects. Our results are derived using 87 liquid futures contracts across all asset classes.

Land Warfare

2018 ◽  
Author(s):  
Christopher Tuck
Keyword(s):  
Armed Conflict ◽  
Modern System ◽  
The One ◽  
Over Time

This chapter charts the key developments in European land warfare since 1900. On the one hand, it is possible to identify overarching explanatory ideas, metanarratives, that can be used to identify continuities in development over time across Europe’s armies. These include the concept of ‘modern system’ land warfare and the ‘transformation paradigm’. However, as this chapter also shows, these two points of continuity do not mean either that European armies are homogenous, or that their conceptual assumptions are uncontested. European land warfare remains a heterogeneous phenomenon, shaped by the variety in national contexts and by contending debates on how appropriate Europe’s armies are to the actual challenges of contemporary and future armed conflict.

scholarly journals Analysis of 220 Years of Floodplain Population Dynamics in the US at Different Spatial Scales

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 141
Author(s):  
Firoza Akhter ◽  
Maurizio Mazzoleni ◽  
Luigia Brandimarte
Keyword(s):  
Population Dynamics ◽  
Large Scale ◽  
Spatial Scales ◽  
National Level ◽  
State Level ◽  
Economic Activities ◽  
Protection Measures ◽  
Management Planning ◽  
The Us ◽  
Over Time

In this study, we explore the long-term trends of floodplain population dynamics at different spatial scales in the contiguous United States (U.S.). We exploit different types of datasets from 1790–2010—i.e., decadal spatial distribution for the population density in the US, global floodplains dataset, large-scale data of flood occurrence and damage, and structural and nonstructural flood protection measures for the US. At the national level, we found that the population initially settled down within the floodplains and then spread across its territory over time. At the state level, we observed that flood damages and national protection measures might have contributed to a learning effect, which in turn, shaped the floodplain population dynamics over time. Finally, at the county level, other socio-economic factors such as local flood insurances, economic activities, and socio-political context may predominantly influence the dynamics. Our study shows that different influencing factors affect floodplain population dynamics at different spatial scales. These facts are crucial for a reliable development and implementation of flood risk management planning.

Explanation Plus Prediction—The Logical Focus of Project Management Research

2021 ◽  
pp. 875697282199994
Author(s):  
Joseph F. Hair ◽  
Marko Sarstedt
Keyword(s):  
Project Management ◽  
Statistical Models ◽  
Predictive Power ◽  
Mean Absolute Error ◽  
Explanatory Power ◽  
Absolute Error ◽  
Model Parameters ◽  
Mean Square ◽  
Management Research ◽  
The Mean

Most project management research focuses almost exclusively on explanatory analyses. Evaluation of the explanatory power of statistical models is generally based on F-type statistics and the R 2 metric, followed by an assessment of the model parameters (e.g., beta coefficients) in terms of their significance, size, and direction. However, these measures are not indicative of a model’s predictive power, which is central for deriving managerial recommendations. We recommend that project management researchers routinely use additional metrics, such as the mean absolute error or the root mean square error, to accurately quantify their statistical models’ predictive power.

scholarly journals German forecasters’ narratives: How informative are German business cycle forecast reports?

2021 ◽  
Author(s):  
Karsten Müller
Keyword(s):  
Business Cycle ◽  
Fixed Effects ◽  
Predictive Power ◽  
Recursive Estimation ◽  
Regression Methods ◽  
Inflation Forecasts ◽  
Fixed Effects Panel Regression ◽  
Weak Evidence ◽  
Out Of Sample ◽  
Different Characteristics

AbstractBased on German business cycle forecast reports covering 10 German institutions for the period 1993–2017, the paper analyses the information content of German forecasters’ narratives for German business cycle forecasts. The paper applies textual analysis to convert qualitative text data into quantitative sentiment indices. First, a sentiment analysis utilizes dictionary methods and text regression methods, using recursive estimation. Next, the paper analyses the different characteristics of sentiments. In a third step, sentiment indices are used to test the efficiency of numerical forecasts. Using 12-month-ahead fixed horizon forecasts, fixed-effects panel regression results suggest some informational content of sentiment indices for growth and inflation forecasts. Finally, a forecasting exercise analyses the predictive power of sentiment indices for GDP growth and inflation. The results suggest weak evidence, at best, for in-sample and out-of-sample predictive power of the sentiment indices.

scholarly journals Predicting Mixture Effects over Time with Toxicokinetic–Toxicodynamic Models (GUTS): Assumptions, Experimental Testing, and Predictive Power

2021 ◽  
Vol 55 (4) ◽  
pp. 2430-2439
Author(s):  
Sylvain Bart ◽  
Tjalling Jager ◽  
Alex Robinson ◽  
Elma Lahive ◽  
David J. Spurgeon ◽  
...  
Keyword(s):  
Predictive Power ◽  
Experimental Testing ◽  
Mixture Effects ◽  
Over Time

Longitudinal Stability of Personality

1992 ◽  
Vol 70 (2) ◽  
pp. 483-498 ◽  
Author(s):  
David D. Smith
Keyword(s):  
Human Brain ◽  
Predictive Power ◽  
Total Variance ◽  
Global Dynamics ◽  
Longitudinal Stability ◽  
Normal Human Brain ◽  
Adult Personality ◽  
Normal Human ◽  
Personality Theories ◽  
Over Time

Estimates of the longitudinal stability of the normal adult personality decrease with increase in the length of the assessment-reassessment interval over which stability is measured, regardless of the method employed. This randomness in the evolution of personality is attributed to the inherent indeterminacy of the global dynamics of the normal human brain. The predictive power of theories of personality is fundamentally constrained. Explanatory personality theories should not be evaluated in terms of the proportion of the total variance that they predict over time but rather on the proportion of the predictable variance they account for.

Ex Post Contract Market Structure: Implications for Performance Over Time

2015 ◽  
Vol 47 (5) ◽  
pp. 588-598 ◽  
Author(s):  
Julia L. Carboni
Keyword(s):  
Management Strategies ◽  
State Level ◽  
Individual Performance ◽  
Contract Management ◽  
Structural Factors ◽  
Structural Embeddedness ◽  
Contract Performance ◽  
Ex Post ◽  
Structural Variables ◽  
Over Time

Government increasingly relies on complex arrangements of providers to deliver public services. There is burgeoning public administration literature on contract management and performance. This literature emphasizes contract management strategies such as contract design and ex post monitoring and relationship building to promote contractor performance. The literature does not examine effects of structural variables on contract performance in ex post contract markets, though work on interorganizational networks has long established that structural factors influence individual performance. This study examines the influence of structural variables on publicly funded contract performance in networked structures of exchange using 5 years of state-level contract data. Network concepts are used to develop contracts as networked exchange structures and develop measures of structural embeddedness for individual programs. Findings include that the structural embeddedness of individual programs influences individual contract performance on quality and cost dimensions over time.

scholarly journals Cross-Correlations in Meat Prices in Brazil: A Non-Linear Approach Using Different Time Scales

Economies ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 133
Author(s):  
Derick Quintino ◽  
José Telo da Gama ◽  
Paulo Ferreira
Keyword(s):  
Time Scales ◽  
Cross Correlation ◽  
Positive Association ◽  
Recent Period ◽  
Linear Approach ◽  
Long Run ◽  
Short Run ◽  
Cross Correlations ◽  
Over Time ◽  
Different Time Scales

Brazil is one of the world’s largest producers and exporters of cattle, chicken and swine. Therefore, co-movements of Brazilian meat prices are important for both domestic and foreign stakeholders. We propose to analyse the cross-correlation between meat prices in Brazil, namely, cattle, swine and chicken, including also in the analysis information from some commodities, namely maize, soya beans, oil, and the Brazilian exchange rate. Our sample covers the recent period which coincided with extensive macroeconomic and institutional changes in Brazil, from 2011 to 2020, and is divided in two periods: (i) presidential pre-impeachment (P1), occurring in August 2016, and; (ii) post-impeachment (P2). Our results indicate that in P1, only the prices of swine and chicken showed a positive and strong correlation over time, and that cattle showed some positive correlation with chicken only in the short run. In P2, there was also a positive and consistent correlation between swine and chicken, and only a positive association with swine and cattle in the long run. For more spaced time scales (days), the changes in the degree of correlation were significant only in the long run for swine and cattle.

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