The most commonly used statistical models of civil war onset fail to correctly predict most occurrences of this rare event in out-of-sample data. Statistical methods for the analysis of binary data, ...such as logistic regression, even in their rare event and regularized forms, perform poorly at prediction. We compare the performance of Random Forests with three versions of logistic regression (classic logistic regression, Firth rare events logistic regression, and L
1-regularized logistic regression), and find that the algorithmic approach provides significantly more accurate predictions of civil war onset in out-of-sample data than any of the logistic regression models. The article discusses these results and the ways in which algorithmic statistical methods like Random Forests can be useful to more accurately predict rare events in conflict data.
Spurred by the classic work of Dunning, MNE location has become the focus of a growing body of research in the field. In this paper we argue that international business (IB) research examining the ...spatial dimension has serious weaknesses, stemming from its traditional assumption of the country as the location unit of analysis. While border-crossing remains the key research context of IB, placing it within a general spatial framework that recognizes both international and subnational spatial heterogeneity opens up vast new vistas for research. Analyzing MNEs as border-crossing multi-location enterprises allows the researcher to distinguish between (discrete) border effects and (continuous) distance effects and undertake a more fine-grained analysis of location. Within such analysis national borders may appear as
qualitative discontinuities
in space, that is, points at which spatial heterogeneity changes abruptly. However, subnational spatial heterogeneity is often the characteristic that drives firm strategy as MNEs decide to locate in particular agglomerations and not at random locations within a country. The complex firms that IB scholars study typically include multiple units within the same country, so that a complete analysis requires considering both subnational distance effects as well as international border effects.
We investigate the hypothesis that macroeconomic fluctuations are primitively the results of many microeconomic shocks. We define fundamental volatility as the volatility that would arise from an ...economy made entirely of idiosyncratic sectoral or firm-level shocks. Fundamental volatility accounts for the swings in macroeconomic volatility in the major world economies in the past half-century. It accounts for the "great moderation" and its undoing. The initial great moderation is due to a decreasing share of manufacturing between 1975 and 1985. The recent rise of macroeconomic volatility is chiefly due to the growth of the financial sector.
We are flooded with large-scale, dynamic, directed, networked data. Analyses requiring exact comparisons between networks are computationally intractable, so new methodologies are sought. To analyse ...directed networks, we extend graphlets (small induced sub-graphs) and their degrees to directed data. Using these directed graphlets, we generalise state-of-the-art network distance measures (RGF, GDDA and GCD) to directed networks and show their superiority for comparing directed networks. Also, we extend the canonical correlation analysis framework that enables uncovering the relationships between the wiring patterns around nodes in a directed network and their expert annotations. On directed World Trade Networks (WTNs), our methodology allows uncovering the core-broker-periphery structure of the WTN, predicting the economic attributes of a country, such as its gross domestic product, from its wiring patterns in the WTN for up-to ten years in the future. It does so by enabling us to track the dynamics of a country's positioning in the WTN over years. On directed metabolic networks, our framework yields insights into preservation of enzyme function from the network wiring patterns rather than from sequence data. Overall, our methodology enables advanced analyses of directed networked data from any area of science, allowing domain-specific interpretation of a directed network's topology.
Income inequality and national wealth are strong determinants for health, but few studies have systematically investigated their influence on mortality across the early life-course, particularly ...outside the high-income world.
We performed cross-sectional regression analyses of the relationship between income inequality (national Gini coefficient) and national wealth (Gross Domestic Product (GDP) averaged over previous decade), and all-cause and grouped cause national mortality rate amongst infants, 1-4, 5-9, 10-14, 15-19 and 20-24 year olds in low and middle-income countries (LMIC) in 2012. Gini models were adjusted for GDP.
Data were available for 103 (79%) countries. Gini was positively associated with increased all-cause and communicable disease mortality in both sexes across all age groups, after adjusting for national wealth. Gini was only positively associated with increased injury mortality amongst infants and 20-24 year olds, and increased non-communicable disease mortality amongst 20-24 year old females. The strength of these associations tended to increase during adolescence. Increasing GDP was negatively associated with all-cause, communicable and non-communicable disease mortality in males and females across all age groups. GDP was also associated with decreased injury mortality in all age groups except 15-19 year old females, and 15-24 year old males. GDP became a weaker predictor of mortality during adolescence.
Policies to reduce income inequality, rather than prioritising economic growth at all costs, may be needed to improve adolescent mortality in low and middle-income countries, a key development priority.
This study analyzes the relationship between globalization, energy consumption, and economic growth among selected South Asian countries to promote the green economy and environment. This study also ...finds causal association between energy growth and nexus of CO
2
emissions and employed the premises of the EKC framework. The study used annual time series analysis, starting from 1985 to 2019. The data set has been collected from the World Development Indicator (WDI). The result of a fully modified ordinary least square (FMOLS) method describes a significantly worse quality environment in the South Asian region. The individual country as Bangladesh shows a positively significant impact on the CO
2
emissions and destroys the level of environment regarding non-renewable energy and globalization index. However, negative and positive growth levels (GDP) and square of GDP confirm the EKC hypothesis in this region. This study has identified the causality between GDP growth and carbon emission and found bidirectional causality between economic growth and energy use.
The primary goal of this study was to examine the relationship between fossil fuel energy, electricity production from nuclear sources, renewable energy, CO
2
emissions, and economic growth in ...Pakistan. Data ranging from 1975 to 2019 were utilized, and the stationarity of this data was verified through the unit root testing. The dynamic connections between variables were investigated by utilizing the linear autoregressive distributed lag technique. Long-run analysis results uncover that fossil fuel energy, renewable energy use, CO
2
emissions, and GDP per capita have a productive relationship with economic progress in Pakistan, whereas electric power consumption, electricity produced from nuclear sources, and energy utilization have an adverse effect on economic growth. Furthermore, the consequences revealed that fossil fuel energy, renewable energy consumption, carbon dioxide emissions, and GDP per capita have a significant linkage to Pakistan’s economic growth via short run, whereas we revealed that the variables electric power consumption, electricity produced from nuclear sources, and energy usage have an adversative linkage to Pakistan’s economic growth. Feasible progressive policies are required from the Pakistani government to pay more attention for tackling the energy and power sectors’ issues in terms of fulfilling the country’s energy requirements.
Attempts to create measures of national wellbeing and progress have a long history. In the UK, they go back at least as far as the 1790s, with Sir John Sinclair's Statistical Account of Scotland. ...More recently, worldwide interest has led to the creation of various indices seeking to go beyond familiar economic measures like gross domestic product. We review the 'Measuring national well-being' development programme of the UK's Office for National Statistics and explore some of the challenges which need to be faced to bring wider measures into use. These include the importance of getting the measures adopted as policy drivers, how to challenge the continuing dominance of economic measures, sustainability and environmental issues, international comparability and methodological statistical questions.
After the 9/11 attacks, much of the political and media debate on terrorism has focused on prevention policies. The widespread view that poverty creates terrorism has dominated much of this debate. ...This is hardly surprising. After all, the notion that poverty generates terrorism is consistent with the results of most of the literature on the economics of conflicts. Because terrorism is a manifestation of political conflict, these results seem to indicate that poverty and adverse economic conditions may play an important role in explaining terrorism. Recent empirical studies, however, have challenged the view that poverty creates terrorism. Using US State Department data on transnational terrorist attacks, Alan B. Krueger and David L. Laitin and James A. Piazza find no evidence suggesting poverty may generate terrorism. Conversely, among countries with similar levels of civil liberties, richer countries seem to be preferred targets for transnational terrorist attacks. However, these studies may suffer, in principle, from some potential shortcomings.
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