scholarly journals Low Agricultural Potential Exacerbates the Effect of Temperature on Civil Conflicts

2020 ◽  
Author(s):  
Jonathan Goyette ◽  
Maroua Smaoui
Keyword(s):  
Policy Implications ◽  
Effect Of Temperature ◽  
Control Group ◽  
Civil Conflicts ◽  
Country Level ◽  
Agricultural Potential ◽  
Causal Impact ◽  
Potential Impact ◽  
Cross Country ◽  
Using Data

Abstract Using data on 172 countries from 1946 until 2014, this paper examines how time-wise variations in temperature at the country level interacted with cross-country variations in agricultural potential impact the incidence of civil conflicts. In the analysis, countries exhibiting high agricultural potential act as a control group for countries with a lower agricultural potential and variations in temperature act as a treatment from one period to the next. This allows identifying the causal impact of the interaction on conflict incidence. We find that deviations in annual or decennial temperature are conducive to a higher probability of being in conflict in countries with lower agricultural potential. The findings have important policy implications to predict, avoid or mitigate conflicts related to climate change.

Do Country-level Creditor Protections Affect Firm-level Debt Structure Concentration?

2021 ◽  
Author(s):  
Kose John ◽  
Mahsa S Kaviani ◽  
Lawrence Kryzanowski ◽  
Hosein Maleki
Keyword(s):  
Debt Structure ◽  
Difference In Differences ◽  
Firm Level ◽  
Creditor Rights ◽  
Country Level ◽  
Bankruptcy Costs ◽  
Cash Flow Volatility ◽  
Cross Country ◽  
Using Data ◽  
Alternative Settings

Abstract We study the effects of country-level creditor protections on the firm-level choice of debt structure concentration. Using data from 46 countries, we show that firms form more concentrated debt structures in countries with stronger creditor protection. We propose a trade-off framework of optimal debt structure and show that in strong creditor rights regimes, the benefit of forming concentrated structures outweighs its cost. Because strong creditor protections increase liquidation bias, firms choose concentrated debt structures to improve the probability of successful distressed debt renegotiations. Firms with ex-ante higher bankruptcy costs, including those with higher intangibility, cash flow volatility, R&D expenses, and leverage exhibit stronger effects. Firms with restricted access to capital are also affected more. A difference-in-differences analysis of firms’ debt structure responses to creditor rights reforms confirms the cross-country results. Our findings are robust to alternative settings and a battery of robustness checks.

scholarly journals A Comparison of Approaches to Regional Land-Use Capability Analysis for Agricultural Land-Planning

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 458
Author(s):  
Tara A. Ippolito ◽  
Jeffrey E. Herrick ◽  
Ekwe L. Dossa ◽  
Maman Garba ◽  
Mamadou Ouattara ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Planning ◽  
Crop Production ◽  
Agricultural Land ◽  
Arable Land ◽  
Agricultural Activity ◽  
Field Samples ◽  
Agricultural Potential ◽  
Fertility Data ◽  
Using Data

Smallholder agriculture is a major source of income and food for developing nations. With more frequent drought and increasing scarcity of arable land, more accurate land-use planning tools are needed to allocate land resources to support regional agricultural activity. To address this need, we created Land Capability Classification (LCC) system maps using data from two digital soil maps, which were compared with measurements from 1305 field sites in the Dosso region of Niger. Based on these, we developed 250 m gridded maps of LCC values across the region. Across the region, land is severely limited for agricultural use because of low available water-holding capacity (AWC) that limits dry season agricultural potential, especially without irrigation, and requires more frequent irrigation where supplemental water is available. If the AWC limitation is removed in the LCC algorithm (i.e., simulating the use of sufficient irrigation or a much higher and more evenly distributed rainfall), the dominant limitations become less severe and more spatially varied. Finally, we used additional soil fertility data from the field samples to illustrate the value of collecting contemporary data for dynamic soil properties that are critical for crop production, including soil organic carbon, phosphorus and nitrogen.

Calculation of Predictive Odds for Possible Carriers of Haemophilia

1975 ◽  
Author(s):  
G. D. Forbes ◽  
A. D. McLaren ◽  
C. R. M. Prentice
Keyword(s):  
Biological Activity ◽  
Discriminant Analysis ◽  
Factor Viii ◽  
Factor Vii ◽  
Control Group ◽  
Posterior Odds ◽  
Linear Discriminant ◽  
Bayesian Calculation ◽  
Using Data ◽  
Betting Odds

The predictive odds for possible carriers of haemophilia have been calculated using data derived from normal and known carrier populations. For each individual the concentration of factor VII-related antigen (A) and factor VIII biological activity (B) was measured. The data has been studied by linear discriminant analysis linked to a Bayesian calculation of posterior odds using the predictive distributions of both the normal and obligatory carrier populations. The proportion of possible carriers assigned to the definite carrier group or control group is dependent on which betting odds are regarded as most suitable for counselling patients. For instance, if betting odds of 5 : 1 were given it was possible to assign 22 of 32 possible carriers (69 per cent) to control or carrier groups. Of this group of 22 possible carriers, 11 were thought to be normal and 11 were thought to be haemophilia carriers.

High-speed railway and tourism development in China

2021 ◽  
pp. 135481662199852
Author(s):  
Shujie Yao ◽  
Xu Yan ◽  
Chun Kwok Lei ◽  
Feng Wang
Keyword(s):  
High Speed ◽  
Tourism Development ◽  
Policy Implications ◽  
Control Group ◽  
Difference In Differences ◽  
Transportation Mode ◽  
High Speed Railway ◽  
Model Cities ◽  
Large Panel ◽  
Research Findings

High-speed railway (HSR) is a new and increasingly popular transportation mode in China bringing about a significant impact on the economy, including tourism development. This article investigates the effect of HSR on tourism development in China based on a time-varying difference-in-differences model. Cities connected by HSR in 2013 and 2014 are regarded as the treatment group, while those without HSR services until 2017 are placed in the control group. The empirical analyses cover a large panel dataset comprising 163 cities in 2009–2017. The empirical results suggest that both domestic tourism revenue and tourist number are positively affected by HSR, and the effect is stronger for the undeveloped or geopolitically less important regions such as the inland or prefecture-level cities. Other relevant determinants of tourism include the availability of airports and the number of hotels in the cities. Our research findings have important policy implications for tourism development in China with respect to HSR.

scholarly journals Estimating Causal Effects When the Treatment Affects All Subjects Simultaneously: An Application

2021 ◽  
Vol 5 (2) ◽  
pp. 22
Author(s):  
Chiara Binelli
Keyword(s):  
Machine Learning ◽  
Carbon Dioxide ◽  
Global Warming ◽  
Carbon Dioxide Emissions ◽  
Control Group ◽  
Sources Of Information ◽  
Average Global Temperature ◽  
Causal Impact ◽  
The Impact ◽  
Robust Evidence

Several important questions cannot be answered with the standard toolkit of causal inference since all subjects are treated for a given period and thus there is no control group. One example of this type of questions is the impact of carbon dioxide emissions on global warming. In this paper, we address this question using a machine learning method, which allows estimating causal impacts in settings when a randomized experiment is not feasible. We discuss the conditions under which this method can identify a causal impact, and we find that carbon dioxide emissions are responsible for an increase in average global temperature of about 0.3 degrees Celsius between 1961 and 2011. We offer two main contributions. First, we provide one additional application of Machine Learning to answer causal questions of policy relevance. Second, by applying a methodology that relies on few directly testable assumptions and is easy to replicate, we provide robust evidence of the man-made nature of global warming, which could reduce incentives to turn to biased sources of information that fuels climate change skepticism.

scholarly journals Relationship between MODIS Derived NDVI and Yield of Cereals for Selected European Countries

Agronomy ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 340
Author(s):  
Ewa Panek ◽  
Dariusz Gozdowski
Keyword(s):  
Linear Regression ◽  
Grain Yield ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Arable Land ◽  
Early Spring ◽  
European Countries ◽  
Yield Prediction ◽  
Country Level ◽  
Using Data

In this study, the relationships between normalized difference vegetation index (NDVI) obtained based on MODIS satellite data and grain yield of all cereals, wheat and barley at a country level were analyzed. The analysis was performed by using data from 2010–2018 for 20 European countries, where percentage of cereals is high (at least 35% of the arable land). The analysis was performed for each country separately and for all of the collected data together. The relationships between NDVI and cumulative NDVI (cNDVI) were analyzed by using linear regression. Relationships between NDVI in early spring and grain yield of cereals were very strong for Croatia, Czechia, Germany, Hungary, Latvia, Lithuania, Poland and Slovakia. This means that the yield prediction for these countries can be as far back as 4 months before the harvest. The increase of NDVI in early spring was related to the increase of grain yield by about 0.5–1.6 t/ha. The cumulative of averaged NDVI gives more stable prediction of grain yield per season. For France and Belgium, the relationships between NDVI and grain yield were very weak.

scholarly journals Depression and loneliness of older adults in Europe and Israel after the first wave of covid-19

2021 ◽  
Author(s):  
Josefine Atzendorf ◽  
Stefan Gruber
Keyword(s):  
Older Adults ◽  
Well Being ◽  
Individual Characteristics ◽  
Control Measures ◽  
Epidemic Control ◽  
Government Response ◽  
Country Level ◽  
Interaction Terms ◽  
Share Data ◽  
Using Data

AbstractEpidemic control measures that aim to introduce social distancing help to decelerate the spread of the COVID-19 pandemic. However, their consequences in terms of mental well-being might be negative, especially for older adults. While existing studies mainly focus on the time during the first lockdown, we look at the weeks afterward in order to measure the medium-term consequences of the first wave of the pandemic. Using data from the SHARE Corona Survey, we include retired respondents aged 60 and above from 25 European countries plus Israel. Combining SHARE data with macro-data from the Oxford COVID-19 Government Response Tracker allows us to include macro-indicators at the country level, namely the number of deaths per 100,000 and the number of days with stringent epidemic control measures, in addition to individual characteristics. The findings show that both macro-indicators are influential for increased feelings of sadness/depression, but that individual factors are crucial for explaining increased feelings of loneliness in the time after the first lockdown. Models with interaction terms reveal that the included macro-indicators have negative well-being consequences, particularly for the oldest survey participants. Additionally, the results reveal that especially those living alone had a higher risk for increased loneliness in the time after the first COVID-19 wave.

Factors affecting desired family size in Bangladesh

1994 ◽  
Vol 26 (3) ◽  
pp. 369-375 ◽  
Author(s):  
M. Kabir ◽  
Ruhul Amin ◽  
Ashraf Uddin Ahmed ◽  
Jamir Chowdhury
Keyword(s):  
Regression Analysis ◽  
Family Size ◽  
Contraceptive Use ◽  
Policy Implications ◽  
Work Status ◽  
Factors Affecting ◽  
Rural Bangladesh ◽  
Contraceptive Prevalence ◽  
Using Data ◽  
Desired Family Size

SummaryFactors affecting desired family size in rural Bangladesh are examined using data from contraceptive prevalence surveys conducted between 1983 and 1991. The analysis suggests that mothers having two sons and one daughter are more inclined to perceive their family as complete than those having three sons and no daughter. Logistic regression analysis indicates that important determinants of desire for more children are age of woman, current contraceptive use status, work status, and family planning worker's visit. The policy implications of these findings are discussed.

Explaining Country Heterogeneity in E-Government Evolution Based on Longitudinal Analysis of Nations

2021 ◽  
Vol 12 (3) ◽  
pp. 83-95
Author(s):  
Prakrit Silal ◽  
Debashis Saha
Keyword(s):  
Longitudinal Analysis ◽  
Clustering Analysis ◽  
Policy Implications ◽  
Development Indicators ◽  
The Past ◽  
Country Level ◽  
The Government

E-government (EGOV) has emerged as an important innovation disrupting the government-citizen relationship in the past two decades. It has attracted wide attention from scholars across varied domains. However, most of these scholarly works, while richly contributing to this evolving domain, assume homogeneity and uniformity in its design, implementation, and impact. This “one size fits all” approach fails to account for the contextual richness, often culminating in a “design-reality” gap. Also, the existing literature lacks adequate investigation of EGOV heterogeneities along time. To address the lacuna, this study attempts to uncover country-level heterogeneities inherent in EGOV longitudinal evolution. Using a dataset over 2008-2018, the study performs a longitudinal clustering analysis and identifies four distinct cohorts with varying EGOV trajectories. Further, the study uncovers variations in EGOV's influence on country-level development indicators across the four cohorts. The findings help derive theoretical and policy implications while identifying avenues for future works.

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