AbstractThis article attempts to determine whether the peace negotiation process initiated in Colombia that culminated with the Peace Treaty in 2016 had a positive economic effect, using the National Gross Domestic Product per capita as a measure. We apply a synthetic control method that is appropriate for a policy evaluation. Considering the anticipated and realized effects on economic variables, our results suggest that the Peace Treaty has positively influenced gross domestic product per capita. Furthermore, this positive effect has been maintained through 2021, the last available year of data. Data to 2021 show post‐pandemic Colombia is better off when compared with a hypothetical Colombia—or synthetic Colombia—that did not begin a peace negotiation process.
A shift in population distribution toward older ages is underway in industrialised countries throughout the world and will continue well into the future. We make use of a framework that we developed in earlier work to isolate the pure effects of population aging on per capita GDP in the 10 Canadian provinces and derive the rates of productivity growth required to offset those effects. For comparison, we consider also some changes relating to the supply of labour as possible alternative offsets.
In this study, a new approach for time series modeling and prediction, &ldquo ; deep assessment methodology,&rdquo ; is proposed and the performance is reported on modeling and prediction for upcoming years of Gross Domestic Product (GDP) per capita. The proposed methodology expresses a function with the finite summation of its previous values and derivatives combining fractional calculus and the Least Square Method to find unknown coefficients. The dataset of GDP per capita used in this study includes nine countries (Brazil, China, India, Italy, Japan, the UK, the USA, Spain and Turkey) and the European Union. The modeling performance of the proposed model is compared with the Polynomial model and the Fractional model and prediction performance is compared to a special type of neural network, Long Short-Term Memory (LSTM), that used for time series. Results show that using Deep Assessment Methodology yields promising modeling and prediction results for GDP per capita. The proposed method is outperforming Polynomial model and Fractional model by 1.538% and by 1.899% average error rates, respectively. We also show that Deep Assessment Method (DAM) is superior to plain LSTM on prediction for upcoming GDP per capita values by 1.21% average error.
It is argued that the use of annual real gross domestic product (GDP) per capita to measure human welfare is misleading because it fails to take into account important factors such as health, education, & political rights. Alternative measures such as the Human Development Index published annually by the United Nations Development Program, which factors in health & education, also fails to accurately reflect human welfare because they, like the GDP, omit transactions from household production & underground economic activity. These omissions, it is claimed, may result in overestimation of real growth in output & thus, human welfare. However, it is claimed that the most serious shortcoming of the GDP & alternative measures of human welfare is that they fail to measure the lifetime welfare of individuals. The Expected Individual Lifetime Welfare (EILW) -- a measure derived by multiplying annual real GDP per capita & life expectancy at birth -- is considered a more accurate method for calculating lifetime individual welfare. 2 Tables, 3 Figures, 32 References. J. Paul
Using annual data from 1985 to 2016, the study conducts a robust panel stationarity analysis by accounting for cross‐sectional dependency, sharp breaks and gradual structural shifts for per capita Gross Domestic Product (PCGDP) of Central and Eastern Europe (CEE) and Commonwealth of Independent State (CIS) countries. The empirical finding reveals that PCGDP at different Fourier frequency and model structure (trend or constant) for both CEE and CIS countries are unit root process. Moreover, the PCGDP of CEE and CIS countries are nonmean reverting in the presence of cross‐sectional dependence and gradual structural shifts which previous studies using well‐known panel stationarity estimators fail to find. Policy insights are highlighted in the conclusion section.
URL del artículo en la web de la Revista: https://www.upo.es/revistas/index.php/RevMetCuant/article/view/2881 ; En este artículo se estima el impacto provocado por la inmigración en el crecimiento del Producto Interior Bruto per cápita (PIBpc) en cada uno de los países de la Unión Europea de los 15 (UE-15) durante el período 1995-2013, lo que nos permitirá comparar una fase de crecimiento económico (1995-2008) y otra de crisis (2008-2013). En concreto, se descompone el PIBpc en tres componentes asociadas a la productividad del trabajo, la tasa de empleo y la proporción de personas en edad de trabajar en el conjunto de la población. Posteriormente, con el objetivo de estimar la contribución de la inmigración al crecimiento del PIBpc, se realiza una desagregación para nativos y extranjeros. Ahora bien, las funciones utilizadas en la correspondiente desagregación pueden alterar los resultados relativos a la productividad del trabajo, por lo que hay que ser cautos en el momento de escoger las unidades de medida del PIB. ; This paper describes the impact caused by immigration on the estimated growth of gross domestic product per capita (GDPpc) in each of the countries of the 15 members of the European Union (EU-15) during the period 1995 to 2013. Specifically, GDPpc breaks down into three factors: labour productivity, employment rate and proportion of people of working age in the general population. To approximate the contribution of immigration to GDPpc growth, a disaggregated estimate for natives and foreigners is done. However, functions used in the relevant disaggregation can affect the findings regarding labour productivity, consequently care must be taken when measurement units of GDP are chosen. ; Universidad Pablo de Olavide
Son zamanlarda gelirin yaşam kalitesi, daha iyi yaşam düzeyi ve yaşam memnuniyeti üzerindeki etkisinin belirlenmesi konusunda yapılan çalışmalar, kişi başına düşen Gayri Safi Yurtiçi gelirin kullanılmasına şüphe ile yaklaşılmasını önermektedir. Bu çalışmanın amacı illerin daha iyi yaşam endeksinde yer alan genel indeks düzeyi ile kişi başına düşen gayrisafi yurt içi hasıla arasında bir ilişki olup olmadığını araştırmaktır. Söz konusu amaca ulaşmak için, araştırmada kullanılan veriler Türkiye İstatistik Kurumu veri tabanından elde edilmiş ve analizler SPSS 17 ile gerçekleştirilmiştir. Hiyerarşik çoklu regresyon analizi neticesinde, illerin kişi başına düşen gelir düzeyleri arttıkça, daha iyi yaşam düzeyi indeks değerlerinin de iyileştiği sonucuna ulaşılmıştır.
En este artículo se estima el impacto provocado por la inmigración en el crecimiento del Producto Interior Bruto per cápita (PIBpc) en cada uno de los países de la Unión Europea de los 15 (UE-15) durante el período 1995-2013, lo que nos permitirá comparar una fase de crecimiento económico (1995-2008) y otra de crisis (2008-2013). En concreto, se descompone el PIBpc en tres componentes asociadas a la productividad del trabajo, la tasa de empleo y la proporción de personas en edad de trabajar en el conjunto de la población. Posteriormente, con el objetivo de estimar la contribución de la inmigración al crecimiento del PIBpc, se realiza una desagregación para nativos y extranjeros. Ahora bien, las funciones utilizadas en la correspondiente desagregación pueden alterar los resultados relativos a la productividad del trabajo, por lo que hay que ser cautos en el momento de escoger las unidades de medida del PIB. --- This paper describes the impact caused by immigration on the estimated growth of gross domestic product per capita (GDPpc) in each of the countries of the 15 members of the European Union (EU-15) during the period 1995 to 2013. Specifically, GDPpc breaks down into three factors: labour productivity, employment rate and proportion of people of working age in the general population. To approximate the contribution of immigration to GDPpc growth, a disaggregated estimate for natives and foreigners is done. However, functions used in the relevant disaggregation can affect the findings regarding labour productivity, consequently care must be taken when measurement units of GDP are chosen.
The article puts forward a hypothesis about the resultant nature of the indicator "life expectancy"; all other socio-economic indicators of the country's development are significant or insignificant factors. In order to test this hypothesis, the methodology of analysis of the countries of the world was described, an analytical and statistical analysis of life expectancy, gross domestic product per capita for the countries of the world was carried out; and on this basis, an assessment of the impact of real per capita GDP on life expectancy is given using the method of grouping, correlation and regression analysis. It is established that, in general, the relationship between them is positive and has a moderate character. It can be stated that real GDP per capita is an important, but most likely far from the most significant factor in ensuring high life expectancy, and further studies of the factors influencing life expectancy are required. At the same time, it was found that it is worth considering separately countries with high and very high levels and countries with medium and low levels of life expectancy and real GDP per capita, since the statistical relationship of the analyzed indicators in 2020 is somewhat different: in countries where GDP is above $13000, life expectancy is above 75 years, to increase life expectancy by 1 year, you need to increase GDP by $14000, and in countries below these values, an increase in GDP of only $5000 can lead to an increase in life expectancy by 1 year. The study also identified critical values (2020) for life expectancy and real GDP per capita. They respectively amounted to 69.20 years (first quartile), 75.50 years (median) and per capita GDP of $5050 and $13300 respectively. In this regard, it turns out that Russia belongs to countries with an average level of development in terms of life expectancy (LE - 72 years or the 158th place in the rating out of 227), in terms of GDP — to highly developed countries (per capita GDP — $26500 or the 70th place in the rating out of227). The example of Russia is a vivid illustration of the fact that the relationship between life expectancy and GDP is statistical and moderate.
The total economic output or gross domestic product (GDP), of South Carolina was $190 billion in 2014. Federal, State and Local Government account for 16.2 percent of South Carolina's GDP. The private sector makes up 83 percent of the total economic output of South Carolina. Manufacturing is the largest industry.
