scholarly journals Building a Model of Government Spending Using Autoregressive Distributed Lag (ARDL) Analysis from 2001 to 2019: A Case Study of Jordan

2021 ◽  
Vol 16 (2) ◽  
pp. 30
Author(s):  
Ateyah Mohammad Alawneh
Keyword(s):  
Growth Rate ◽  
Population Growth ◽  
Public Debt ◽  
Government Spending ◽  
Population Growth Rate ◽  
Inflation Rate ◽  
Negative Relationship ◽  
Short Term ◽  
Independent Variables ◽  
The Government

The study aims to build a model of government spending in Jordan using ARDL analysis through the use of an E-views program by determining the relationships between government spending and variables, such as the gross domestic product (GDP), government revenues, economic openness (OP), inflation rate, unemployment, population growth rate, and public debt. The statistical analysis showed a significant positive relationship between government spending and (GDP) and government revenues. It revealed significant positive relationships between government spending and) OP (and inflation. It found the statistically significant negative effect of the unemployment rate and the population growth rate on government spending. A negative relationship was found between government spending lag (1) and current government spending. Public debt was found to have a positive but not statistically significant effect on government spending. The relationships between the dependent variable and independent variables of government spending were consistent with unrestricted ARDL analysis in the long term. The analysis showed a statistically significant positive relationship between government spending and GDP at a short-term level but a statistically significant negative relationship between government spending and independent variables, such as population growth rate, inflation rate, and unemployment rate at a short-term level. One of the most important recommendations of the study was working to increase government spending in a way that is compatible with the increasing population growth. The study recommends government intervention to bring in more revenue through income-generating economic activities. Contribution / Originality: This will be one of the few studies to build a model of government spending using Autonomous Distributed Regression (ARDL). The study also provides a scientific addition in the field of financial and economic sciences from a scientific point of view through the use of different statistical methods using ARDL analysis on the long and short levels to assist the government in preparing the state's general budget. The study also helps the government to develop in the field of public finances and prepare an unconventional general budget.

scholarly journals Demographic determinant of primary school repeater in Indonesia

2021 ◽  
Vol 244 ◽  
pp. 11023
Author(s):  
Omas Bulan Samosir
Keyword(s):  
Growth Rate ◽  
Population Growth ◽  
General Education ◽  
Primary School ◽  
World Bank ◽  
Population Growth Rate ◽  
Infrastructure Development ◽  
The World Bank ◽  
The World ◽  
The Government

The development of a country is supported by its education development. In general, education is financed by the government. It is expected that all school-age population can participate in education. Indonesia has implemented the nine-year compulsory basic education program. The aim of this study is to examine the demographic factors that affect the primary school repeater in Indonesia. The data source was from the World Bank Development Indicator of the World Bank. The data coverage was from 1971 to 2018. The dependent variable was the primary school repeater rate. The independent variables were the population growth rate and fixed telephone subscription. The data were analyzed using multiple regression analysis. The results of the study indicate that higher primary school repeater was associated with higher population growth rate and lower fixed telephone subscription. Therefore, Indonesia needs to manage its population growth rate and improve infrastructure development, in particular information technology infrastructure.

scholarly journals An Empirical Analysis of the Effects of Population Growth on Economic Growth in Ethiopia using an Auto Regressive Distributive Lag (ARDL) Model Approach

2021 ◽  
Author(s):  
Alemayehu Temesgen Befikadu ◽  
Berhanu Alemu Tafa
Keyword(s):  
Economic Growth ◽  
Growth Rate ◽  
Population Growth ◽  
Empirical Analysis ◽  
Population Growth Rate ◽  
Total Population ◽  
Long Run ◽  
Auto Regressive ◽  
The Government ◽  
Model Approach

Abstract ObjectiveThe study examines An Empirical Analysis of the Effects of Population Growth on Economic Growth in Ethiopia using an Auto Regressive Distributive Lag (ARDL) Model Approach from the period of 1980 through 2019 with specific focus on total population, Growth Domestic Product, population growth rate, and foreign direct investment, inflow. This study investigated to understand the effects of total population on economic growth, and to analyze the short run and long run relationship of economic growth with respect to population growth.ResultsFrom the results of the study, personal remittance is stationary at level, while total population, FDI net inflows, population growth rate, rate of inflation, and gross capital formation are stationary at first difference. From the finding of long run equilibrium relationships between RGDP, population number, FDI, personal remittance, population growth rate, rate of inflation and GCF is existed since the value of F-statics is greater than the upper boundary line. Finally, to increase the economic growth of Ethiopia; the government should adopt policies that can attract the foreign investors. The government also should put a standard to guarantee that the economy grows at a larger rate than the population growth.

scholarly journals Demographic Change and Governance Issues

2006 ◽  
Vol 45 (4II) ◽  
pp. 589-598 ◽  
Author(s):  
Mohammad Nizam-Ud-Din
Keyword(s):  
Growth Rate ◽  
Population Growth ◽  
Population Growth Rate ◽  
Current Level ◽  
Replacement Level ◽  
Population Replacement ◽  
The World ◽  
The Government ◽  
Lower Population ◽  
Populous Country

Pakistan is the 6th most populous country in the world while it ranks 4th in Asia. Its population has increased from 34 million in 1951 to an estimated 160 million in the year 2006, growing at the rate of three million persons per year. At this speed of growth, Pakistan’s population is projected to reach the 220 million mark by the year 2020; as we arrive at the Population Replacement Level. While Population Growth Rate (PGR) has declined from over 3 percent in previous decades to its current level of 2.1 percent per annum, which is, nevertheless, the highest population growth rate in South Asia, a dubious achievement when compared to the situation in the neighbouring countries. Therefore, the government policy remains intact, which is to lower population growth rate from its current level to 1.3 percent per annum by the year 2020, to reduce the total fertility rate to 2.1 percent and to reach replacement level of fertility by the year 2020. Unless its growth rate swiftly, by the year 2060, Pakistan is destined to become the 4th most populated country in the world, its population reaching over 305 million mark. In 1950s it was ranked 14.

Transient population dynamics drive the spread of invasive wild pigs in North America

2021 ◽  
Author(s):  
Ryan S Miller ◽  
Michael Tabak ◽  
Christopher L Burdett ◽  
David W Wolfson
Keyword(s):  
Growth Rate ◽  
Population Dynamics ◽  
North America ◽  
Population Growth ◽  
Population Growth Rate ◽  
Spatial Models ◽  
Initial Population ◽  
Short Term ◽  
Wild Pigs ◽  
Transient Population

Invasion of nonindigenous species is considered one of the most urgent problems affecting native ecosystems and agricultural systems. Mechanistic models that account for short-term population dynamics can improve prediction because they incorporate differing demographic processes that link the environmental conditions of a spatial location explicitly with the invasion process. Yet short-term population dynamics are rarely accounted for in spatial models of invasive species spread. Accounting for transient population dynamics, we predict the population growth rate and establishment probability of wild pigs following introduction into any location in North America. We compared predicted population growth rate with observed geographic rates of spread and found significant relationships between the annual rate of spread and population growth rates. We used geospatial data on the distribution of mast producing tree species (a principle forage resource of wild pigs) and agricultural crops that can replace mast in their diets to predict population dynamics using transient population simulations. We simulated populations under different initial population sizes (i.e. number of introduced individuals, often termed propagule size) and for different amounts of time following introduction. By varying the initial population size and simulation time, we were able to identify areas in North America with high probability for establishment of wild pigs if introduced. Our findings can be used to inform surveillance and removal efforts to reduce the potential for establishment and spread of wild pigs.

scholarly journals Biological scaling in green algae: the role of cell size and geometry

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Helena Bestová ◽  
Jules Segrestin ◽  
Klaus von Schwartzenberg ◽  
Pavel Škaloud ◽  
Thomas Lenormand ◽  
...  
Keyword(s):  
Growth Rate ◽  
Population Growth ◽  
Population Growth Rate ◽  
Internal Diffusion ◽  
Scaling Exponent ◽  
Power Scaling ◽  
Nutrient Distribution ◽  
Metabolic Scaling ◽  
Key Factor ◽  
Size And Morphology

AbstractThe Metabolic Scaling Theory (MST), hypothesizes limitations of resource-transport networks in organisms and predicts their optimization into fractal-like structures. As a result, the relationship between population growth rate and body size should follow a cross-species universal quarter-power scaling. However, the universality of metabolic scaling has been challenged, particularly across transitions from bacteria to protists to multicellulars. The population growth rate of unicellulars should be constrained by external diffusion, ruling nutrient uptake, and internal diffusion, operating nutrient distribution. Both constraints intensify with increasing size possibly leading to shifting in the scaling exponent. We focused on unicellular algae Micrasterias. Large size and fractal-like morphology make this species a transitional group between unicellular and multicellular organisms in the evolution of allometry. We tested MST predictions using measurements of growth rate, size, and morphology-related traits. We showed that growth scaling of Micrasterias follows MST predictions, reflecting constraints by internal diffusion transport. Cell fractality and density decrease led to a proportional increase in surface area with body mass relaxing external constraints. Complex allometric optimization enables to maintain quarter-power scaling of population growth rate even with a large unicellular plan. Overall, our findings support fractality as a key factor in the evolution of biological scaling.

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