Population, Education and Income Inequality

2021 ◽  
Author(s):  
Osiris Jorge Parcero
Keyword(s):  
Secondary Education ◽  
Income Inequality ◽  
Population Size ◽  
Large Population ◽  
Density Increase ◽  
Lower Income ◽  
Redistributive Policies ◽  
Population Education

In non-democracies, a large population size and density lead to more redistributive policies and lower income inequality. This is the result of the interconnection of two intermediate hypotheses. First, in non-democracies a larger population size and density increase the chance of a revolution attempt to overthrow the governing elites. Second, this revolution threat prompts the elites to better re-distribute the country’s income in an attempt to fend off this threat. This paper suggests and empirically tests that wider spread primary and, to a lesser extent, secondary education is one of the channels through which the elites achieve this better distribution.

WHY DO SOCIETIES WITH HIGHER AVERAGE COGNITIVE ABILITY HAVE LOWER INCOME INEQUALITY? THE ROLE OF REDISTRIBUTIVE POLICIES

2017 ◽  
Vol 50 (3) ◽  
pp. 347-364
Author(s):  
Raufhon Salahodjaev ◽  
Satoshi Kanazawa
Keyword(s):  
Income Inequality ◽  
Cognitive Ability ◽  
Lower Income ◽  
Major Mechanism ◽  
Redistributive Policies ◽  
Level Data ◽  
Multiple Regression Models ◽  
Societal Level ◽  
Social Transfers

SummaryPast studies suggest that, across nations, the average cognitive ability of a population is negatively associated with income inequality; societies with higher average cognitive ability tend to have lower levels of income inequality. However, it is not clearwhy. This paper proposes that social transfers from the wealthy to the poor may be a major mechanism by which some societies achieve lower income inequality than others, because more intelligent individuals may be more likely to have a preference for such transfers. Publicly available societal-level data were analysed in a series of multiple regression models. The empirical results in this study replicate the earlier finding that societies with higher cognitive ability have lower levels of income inequality, but the association isentirelymediated by social transfers. Social transfers therefore appear to be the primary mechanism by which societies with higher levels of cognitive ability achieve lower income inequality.

scholarly journals Who Becomes Unhappy when Income Inequality Increases?

2021 ◽  
Author(s):  
Bjorn Lous ◽  
Johan Graafland
Keyword(s):  
Life Satisfaction ◽  
Income Inequality ◽  
Harmful Effect ◽  
World Values Survey ◽  
Lower Income ◽  
Negative Effects ◽  
Average Life ◽  
Income Groups ◽  
The World ◽  
Negative Effect

AbstractLiterature has established that, on a macroeconomic level, income inequality has a negative effect on average life satisfaction. An unresolved question is, however, which income groups are harmed by income inequality. In this paper we investigate this relationship at the microeconomic level combining national indicators of income inequality with individual data of life satisfaction from the World Values Survey for 39 countries over a period of 25 years. Tests on moderation by income category show that the Gini coefficient is most negatively related to life satisfaction of the lowest income groups, but the negative effects also extends to other income groups. For the income share of the top 1% we find a similar result. These findings show that income inequality is especially a concern for the lower income groups, but that the harmful effect of income inequality also spillovers to the life satisfaction of other income groups.

scholarly journals Macroeconomic Impacts of Climate Change Driven by Changes in Crop Yields

2018 ◽  
Vol 10 (10) ◽  
pp. 3673 ◽  
Author(s):  
Shinichiro Fujimori ◽  
Toshichika Iizumi ◽  
Tomoko Hasegawa ◽  
Jun’ya Takakura ◽  
Kiyoshi Takahashi ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Population Size ◽  
Large Population ◽  
Food Prices ◽  
Production Volume ◽  
Total Uncertainty ◽  
Indicator Value ◽  
Macroeconomic Impacts ◽  
Macroeconomic Indicator

Changes in agricultural yields due to climate change will affect land use, agricultural production volume, and food prices as well as macroeconomic indicators, such as GDP, which is important as it enables one to compare climate change impacts across multiple sectors. This study considered five key uncertainty factors and estimated macroeconomic impacts due to crop yield changes using a novel integrated assessment framework. The five factors are (1) land-use change (or yield aggregation method based on spatially explicit information), (2) the amplitude of the CO2 fertilization effect, (3) the use of different climate models, (4) socioeconomic assumptions and (5) the level of mitigation stringency. We found that their global impacts on the macroeconomic indicator value were 0.02–0.06% of GDP in 2100. However, the impacts on the agricultural sector varied greatly by socioeconomic assumption. The relative contributions of these factors to the total uncertainty in the projected macroeconomic indicator value were greater in a pessimistic world scenario characterized by a large population size, low income, and low yield development than in an optimistic scenario characterized by a small population size, high income, and high yield development (0.00%).

POPULATION DYNAMICS OF SEX-DETERMINING ALLELES IN HONEY BEES AND SELF-INCOMPATIBILITY ALLELES IN PLANTS

Genetics ◽  
1979 ◽  
Vol 91 (3) ◽  
pp. 609-626 ◽  
Author(s):  
Shozo Yokoyama ◽  
Masatoshi Nei
Keyword(s):  
Population Dynamics ◽  
Population Size ◽  
Honey Bee ◽  
Honey Bees ◽  
Finite Population ◽  
Large Population ◽  
Allele Frequencies ◽  
Self Incompatibility ◽  
Overdominant Selection ◽  
Incompatibility Alleles

ABSTRACT Mathematical theories of the population dynamics of sex-determining alleles in honey bees are developed. It is shown that in an infinitely large population the equilibrium frequency of a sex allele is l/n, where n is the number of alleles in the population, and the asymptotic rate of approach to this equilibrium is 2/(3n) per generation. Formulae for the distribution of allele frequencies and the effective and actual numbers of alleles that can be maintained in a finite population are derived by taking into account the population size and mutation rate. It is shown that the allele frequencies in a finite population may deviate considerably from l/n. Using these results, available data on the number of sex alleles in honey bee populations are discussed. It is also shown that the number of self-incompatibility alleles in plants can be studied in a much simpler way by the method used in this paper. A brief discussion about general overdominant selection is presented.

Evaluation of several initialization methods on arithmetic optimization algorithm performance

2021 ◽  
Vol 31 (1) ◽  
pp. 70-94
Author(s):  
Jeffrey O. Agushaka ◽  
Absalom E. Ezugwu
Keyword(s):  
Population Size ◽  
Optimization Algorithm ◽  
Beta Distribution ◽  
Random Number ◽  
Large Population ◽  
Latin Hypercube Sampling ◽  
Rayleigh Distribution ◽  
Population Based ◽  
Algorithm Performance ◽  
Number Of Iterations

Abstract Arithmetic optimization algorithm (AOA) is one of the recently proposed population-based metaheuristic algorithms. The algorithmic design concept of the AOA is based on the distributive behavior of arithmetic operators, namely, multiplication (M), division (D), subtraction (S), and addition (A). Being a new metaheuristic algorithm, the need for a performance evaluation of AOA is significant to the global optimization research community and specifically to nature-inspired metaheuristic enthusiasts. This article aims to evaluate the influence of the algorithm control parameters, namely, population size and the number of iterations, on the performance of the newly proposed AOA. In addition, we also investigated and validated the influence of different initialization schemes available in the literature on the performance of the AOA. Experiments were conducted using different initialization scenarios and the first is where the population size is large and the number of iterations is low. The second scenario is when the number of iterations is high, and the population size is small. Finally, when the population size and the number of iterations are similar. The numerical results from the conducted experiments showed that AOA is sensitive to the population size and requires a large population size for optimal performance. Afterward, we initialized AOA with six initialization schemes, and their performances were tested on the classical functions and the functions defined in the CEC 2020 suite. The results were presented, and their implications were discussed. Our results showed that the performance of AOA could be influenced when the solution is initialized with schemes other than default random numbers. The Beta distribution outperformed the random number distribution in all cases for both the classical and CEC 2020 functions. The performance of uniform distribution, Rayleigh distribution, Latin hypercube sampling, and Sobol low discrepancy sequence are relatively competitive with the Random number. On the basis of our experiments’ results, we recommend that a solution size of 6,000, the number of iterations of 100, and initializing the solutions with Beta distribution will lead to AOA performing optimally for scenarios considered in our experiments.

Anadromous Sturgeons: Habitats, Threats, and Management

2007 ◽  
Keyword(s):  
Growth Rate ◽  
Population Size ◽  
Yellow River ◽  
Large Population ◽  
Leading Edge ◽  
The Yellow River ◽  
Gulf Sturgeon ◽  
Successful Recruitment ◽  
Viable Population ◽  
Size Growth

<em>Abstract.</em>—The Gulf sturgeon <em>Acipenser oxyrinchus desotoi</em> is an anadromous species listed as threatened under the Endangered Species Act in 1991. We conducted a 3year tagging study to estimate population size, growth, mortality, and age composition for sturgeon in the Yellow River. Capture probabilities and population size were estimated using Program MARK and a Cormack-Jolly–Seber model. Total mortality of Gulf sturgeon was estimated using a Beverton–Holt mortality equation. Growth rate was determined from annuli on the leading edge of pectoral fin-ray. A total of 522 Gulf sturgeon captures were made, and 399 individual fish were tagged. The population estimates for the Gulf sturgeon over 3 years ranged from 500 to 911 fish. The age structure of the population suggests successful recruitment and a viable population. The total annual mortality estimate for Yellow River Gulf sturgeon was 11.9%. Growth rate for the Yellow River population was comparable to other populations of Gulf sturgeon. The Yellow River Gulf sturgeon population is a dynamic population based upon consistent age-classes as an indicator of successful recruitment, a large population size relative to most rivers where Gulf sturgeon are found, and estimates of mortality below the reported range for the species.

Is Its Success Generalizable?

2019 ◽  
pp. 72-93
Author(s):  
Lane Kenworthy
Keyword(s):  
Income Inequality ◽  
Population Size ◽  
Labor Unions ◽  
Low Income ◽  
Work Ethic ◽  
Unique Feature ◽  
Tax Compliance ◽  
Small Population ◽  
Close Inspection ◽  
Social Democratic

Abstract: Social democratic capitalism’s chief practitioners have been the Nordic nations: Denmark, Finland, Norway, and Sweden. Skeptics discount the Nordics’ success on the presumption that these nations have some unique feature that allows them, and only them, to reap the benefits of social democratic policies without suffering tradeoffs. Versions of this story identify the Nordics’ secret weapon as an immutable work ethic, superior intelligence, trust, solidarity, small population size, racial and ethnic homogeneity, institutional coherence, effective government, corporatism, a willingness to be taxed, tax compliance, strong labor unions, or low income inequality. I examine these hypotheses. None holds up to close inspection.

scholarly journals Choosing Mutation and Crossover Ratios for Genetic Algorithms—A Review with a New Dynamic Approach

Information ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 390 ◽  
Author(s):  
Ahmad Hassanat ◽  
Khalid Almohammadi ◽  
Esra’a Alkafaween ◽  
Eman Abunawas ◽  
Awni Hammouri ◽  
...  
Keyword(s):  
Population Size ◽  
Optimization Problems ◽  
Large Population ◽  
Small Population ◽  
Mutation Rates ◽  
Mutation Operators ◽  
Tuning Methods ◽  
Two Parameters ◽  
The Impact ◽  
Crossover And Mutation

Genetic algorithm (GA) is an artificial intelligence search method that uses the process of evolution and natural selection theory and is under the umbrella of evolutionary computing algorithm. It is an efficient tool for solving optimization problems. Integration among (GA) parameters is vital for successful (GA) search. Such parameters include mutation and crossover rates in addition to population that are important issues in (GA). However, each operator of GA has a special and different influence. The impact of these factors is influenced by their probabilities; it is difficult to predefine specific ratios for each parameter, particularly, mutation and crossover operators. This paper reviews various methods for choosing mutation and crossover ratios in GAs. Next, we define new deterministic control approaches for crossover and mutation rates, namely Dynamic Decreasing of high mutation ratio/dynamic increasing of low crossover ratio (DHM/ILC), and Dynamic Increasing of Low Mutation/Dynamic Decreasing of High Crossover (ILM/DHC). The dynamic nature of the proposed methods allows the ratios of both crossover and mutation operators to be changed linearly during the search progress, where (DHM/ILC) starts with 100% ratio for mutations, and 0% for crossovers. Both mutation and crossover ratios start to decrease and increase, respectively. By the end of the search process, the ratios will be 0% for mutations and 100% for crossovers. (ILM/DHC) worked the same but the other way around. The proposed approach was compared with two parameters tuning methods (predefined), namely fifty-fifty crossover/mutation ratios, and the most common approach that uses static ratios such as (0.03) mutation rates and (0.9) crossover rates. The experiments were conducted on ten Traveling Salesman Problems (TSP). The experiments showed the effectiveness of the proposed (DHM/ILC) when dealing with small population size, while the proposed (ILM/DHC) was found to be more effective when using large population size. In fact, both proposed dynamic methods outperformed the predefined methods compared in most cases tested.

scholarly journals Genetic diversity, demographic history and neo-sex chromosomes in the Critically Endangered Raso lark

2020 ◽  
Vol 287 (1922) ◽  
pp. 20192613 ◽  
Author(s):  
Elisa G. Dierickx ◽  
Simon Yung Wa Sin ◽  
H. Pieter J. van Veelen ◽  
M. de L. Brooke ◽  
Yang Liu ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Population Size ◽  
Sex Chromosomes ◽  
Demographic History ◽  
Large Population ◽  
Effective Population ◽  
Island Species ◽  
Population Sizes ◽  
Approaches To Study ◽  
Genetic Signatures

Small effective population sizes could expose island species to inbreeding and loss of genetic variation. Here, we investigate factors shaping genetic diversity in the Raso lark, which has been restricted to a single islet for approximately 500 years, with a population size of a few hundred. We assembled a reference genome for the related Eurasian skylark and then assessed diversity and demographic history using RAD-seq data (75 samples from Raso larks and two related mainland species). We first identify broad tracts of suppressed recombination in females, indicating enlarged neo-sex chromosomes. We then show that genetic diversity across autosomes in the Raso lark is lower than in its mainland relatives, but inconsistent with long-term persistence at its current population size. Finally, we find that genetic signatures of the recent population contraction are overshadowed by an ancient expansion and persistence of a very large population until the human settlement of Cape Verde. Our findings show how genome-wide approaches to study endangered species can help avoid confounding effects of genome architecture on diversity estimates, and how present-day diversity can be shaped by ancient demographic events.

scholarly journals Protected by dragons: Density surface modeling confirms large population of the critically endangered Yellow-crested Cockatoo on Komodo Island

The Condor ◽  
2020 ◽  
Author(s):  
Anna Reuleaux ◽  
Benny A Siregar ◽  
Nigel J Collar ◽  
Maria R Panggur ◽  
Ani Mardiastuti ◽  
...  
Keyword(s):  
Population Size ◽  
Local Density ◽  
Large Population ◽  
Distance Sampling ◽  
Surface Modeling ◽  
Habitat Associations ◽  
Critically Endangered ◽  
Topographic Wetness Index ◽  
Monsoon Forest ◽  
Density Surface

Abstract Intense trapping of the critically endangered Yellow-crested Cockatoo (Cacatua sulphurea) for the international pet trade has devastated its populations across Indonesia such that populations of &gt;100 individuals remain at only a handful of sites. We combined distance sampling with density surface modeling (DSM) to predict local densities and estimate total population size for one of these areas, Komodo Island, part of Komodo National Park (KNP) in Indonesia. We modeled local density based on topography (topographic wetness index) and habitat types (percentage of palm savanna and deciduous monsoon forest). Our population estimate of 1,113 (95% CI: 587–2,109) individuals on Komodo Island was considerably larger than previous conservative estimates. Our density surface maps showed cockatoos to be absent over much of the island, but present at high densities in wooded valleys. Coincidence between our DSM and a set of independent cockatoo observations was high (93%). Standardized annual counts by KNP staff in selected areas of the island showed increases in cockatoo records from &lt;400 in 2011 to ~650 in 2017. Taken together, our results indicate that KNP, alongside and indeed because of preserving its iconic Komodo dragons (Varanus komodoensis), is succeeding in protecting a significant population of Indonesia’s rarest cockatoo species. To our knowledge this is the first time DSM has been applied to a critically endangered species. Our findings highlight the potential of DSM for locating abundance hotspots, identifying habitat associations, and estimating global population size in a range of threatened taxa, especially if independent datasets can be used to validate model predictions.

Sign in / Sign up

Export Citation Format

Share Document