The study investigated the Comparative Analysis of Budgetary Allocation to Education and GrossDomesticProductPer- Capita (GDPc) in Nigerian from 1980-2015. The objective of the study was to comparatively analyze the relative impact of federal government actual budgetary allocation to education alongside UNESCO 26% recommended budgetary allocation to education. In respect to the above, relevant theoretical and empirical literature were reviewed. The researcher formulated the relevant objective ,research question and hypotheses to guide the study. In the course of the study, relevant data relating to the variables needed by the researcher were extracted from various document analys is such as Central Bank of Nigeria (CBN) Statistical Bulletin and National Bureau of Statistics (NBS) Statistical Bulletin. The Classical Linear Regression Model was employed in modelling the relationship between per-capita income and the budgetary allocation variables. The Ordinary Least Square (OLS) equation technique was used in analyzing the data. The unit root analysis revealed that all the variables were not stationary at levels. But at first difference, all the variables became stationary. The Johansen cointegration analysis revealed that the variables were cointegrated and had a valid error correction mechanism. The analysis of the Error Correction Mechanism (ECM) showed that all
The study investigated the Comparative Analysis of Budgetary Allocation to Education and GrossDomesticProductPer- Capita (GDPc) in Nigerian from 1980-2015. The objective of the study was to comparatively analyze the relative impact of federal government actual budgetary allocation to education alongside UNESCO 26% recommended budgetary allocation to education. In respect to the above, relevant theoretical and empirical literature were reviewed. The researcher formulated the relevant objective, research question and hypotheses to guide the study. In the course of the study, relevant data relating to the variables needed by the researcher were extracted from various document analys is such as Central Bank of Nigeria (CBN) Statistical Bulletin and National Bureau of Statistics (NBS) Statistical Bulletin. The Classical Linear Regression Model was employed in modelling the relationship between per-capita income and the budgetary allocation variables. The Ordinary Least Square (OLS) equation technique was used in analyzing the data. The unit root analysis revealed that all the variables were not stationary at levels. But at first difference, all the variables became stationary. The Johansen cointegration analysis revealed that the variables were cointegrated and had a valid error correction mechanism. The analysis of the Error Correction Mechanism (ECM) showed that all the models were significant and the estimates unbiased. The analysis further revealed that budgetary allocation to education in Nigeria has the correct signs and significantly impacted on income per- capitaIt was therefore, recommended that the government at all levels should increase their budgetary allocation to education towards the UNESCO’s 26% criteria as a strategy to fast-tract national economic development in Nigeria. Also, the study further recommended that greater percentage of the budgetary allocation to education, should be spent on capital projects.
In this article, the author performs a regression and correlation analysis on the relationship between GDP percapita and individual income tax revenue. The result shows that the effect of GDP percapita on individual income tax revenue is a positive significant at 5% level of significance. How to increase individual income tax revenue through GDP percapita in the coming period in Vietnam? Firstly, Vietnam maintains a high growth rate and continues to be among the countries with the highest growth rates in the world. Secondly, Vietnam uses flexible monetary and fiscal policies to stimulate economic growth. Because, after years of economic crisis, Vietnam has always controlled monetary policy and tightened public expenditure, many people and small and medium enterprises were difficult to access bank credit and other capital mobilization channels, so annual economic growth rate of Vietnam in recent years (2009-2018) was about 6.3% while during the period 1999-2008 was about 7.21%. Thirdly, continue to expand international economic relations to attract foreign investment to supplement social investment capital, thereby contributing to economic growth. Finally, in fact, a comparison result shows that due to individual income tax revenue in applying the law was much higher than the ordinance. Socio-economic situation has many changes over time, many types of newly formed incomes, change of many macroeconomic indicators, therefore law on individual income tax continues to be revised and supplemented several articles to increase tax revenue without exceeding the tolerance of the people.
Ecuador is an oil exporter country but it is also an importer of oil derivatives products. In this research the relationship between its real grossdomesticproduct (GDP) percapita and the oil price, gas price, inflation and total expenditure is studied, taking annual data of all from 1980 to 2015 by using the methodology of autoregressive distribution lag bound test. It is concluded it exists a long run relationship between variables and the speed of adjustment to any disequilibrium in the short run is corrected at an approximately rate of 85%. The model showed itself stable. In addition it was demonstrated that there is a causal relationship from all regressors selected except total expenditure to real GDP percapita according to the Toda-Yamamoto technique.
The ultimate goal of different measures of economic growth is to provide a report card for government to see how their economy is doing and measure economic performance at the instance or over time. Real grossdomesticproductpercapita (RGDPPC) as one of the measures for economic growth is defined as the average of individual incomes in the economy adjusted for inflation i.e. taking real grossdomesticproduct (GDP) and dividing it by the population (Jim, 2019). The relationship between economic growth and macroeconomic variables (determinants) has long been a trendy issue of discussions in the literature of economic development (Nihat, et al. 2013). Research on economic growth being undertaken in both theoretical and applied work, focuses on macroeconomic policies to achieve stable prices (low inflation), low levels of debt (both foreign and domestic), free market economy, low rate of unemployment and an open economy (Mbulawa, 2015).
Abstract—Annual cross-country data from the World Bank database during the years 1998 and 2014 demonstrate wide variation in infant mortality rates (IMR) and grossdomesticproductpercapita (GDPpc). All the datasets show that there is a range of high infant mortality at low GDPpc levels and there is a range of high GDPpc levels with low infant mortality. Unfortunately, the data are so noisy that there cannot be stated any simple relationship between IMR and GDPpc. However, using least squares estimates of infant mortality rates and assuming that GDPpc is subject to non-decreasing returns offers a meaningful method that is quite appropriate for modeling these datasets. Indeed, we understand at once the increasing slope of the IMR curve and we provide a quantitative explanation to what economists have observed: that at highest GDPpc levels, IMR increases after bottoming out. The advantage of our method is that it gives a clear quantitative model for confirmation of assumptions which so far had only qualitative support.
In equation (1), Economic growth is measured by proxy of grossdomesticproductpercapita; banks' performance is measured by proxies of return on assets and return on equity, control variables are corruption control, inflation, interest rate, unemployment rate, regulatory quality and government effectiveness. Some of the variables were transformed into their natural logarithm to avoid fluctuation in the data series thus all the variables except the regulatory quality and government effectiveness. After taking the natural logarithm of the variables then the econometric model transformed into equation (2) below;
Maternal mortality tare (the number of maternal deaths per 100000 live births); Grossdomesticproductpercapita (in inter- national dollar); primary health care center ratio; the total fertility rate; health expendi- ture share of grossdomesticproduct (total health expenditure to GDP); urbanization (the proportion of urban population to total population); women’s education (the 15- year-old and older women’s literacy rate); and percentage of births attended by skilled health personnel.
- The GrossDomesticProductpercapita (nominal) reflects an overall net decline of US$ 2 662 (-30.75% growth) between 2011 and 2015. In particular there was a decrease of US$ 1 035 from 2011 to 2012, a decrease of US$ 932 between 2012 and 2013, a decrease of US$ 90 between 2013 and 2014, and a decrease of US$ 614 between 2014 and 2015. The latter serves as evidence that the average income per South African citizen decreased from year-to-year over the applicable period, justifying the limited investment made in the production of local goods and/or services. Moreover, the aforementioned also suggests that the standard of living in South Africa has deteriorated from 2011 to 2015 which, in turn, may have been caused by increases in national unemployment. The Gini coefficient shows how well money is disseminated among citizens of a country. It is depicted as a number between 0 (absolute equality) and 1 (absolute inequality). The Gini coefficient of South Africa was estimated at 0.77 in 2014; among the highest Gini coefficients in the world. (Statistics South Africa, 2014c).
Abstract: Environmental issues have been ranked among the most intense debates over the past decades by governments around the world. Sustainable development goals have been top priorities in the working agenda of national cabinets and administrations which questions the chronic trade-off between environment and economic performance. This paper aims at contributing further insights into the above-mentioned linkage to the contemporary literature by testing the validity of the environmental Kuznets curve (EKC) hypothesis. By conducting a panel data analysis on ASEAN-10 countries’ statistics of carbon dioxide emissions percapita (COEpc), real grossdomesticproductpercapita (rGDPpc), foreign direct investment inflow (FDIif), trade openness index (TOI), and urbanisation (URB), the findings have empirically confirmed the valid causality running from economic growth, international trade and demographic changes to environmental degradation. Additionally, the existence of an earlier inverted U-shaped and a later N-shaped EKC has been investigated and significantly confirmed the cyclical changes of the eco-enviro trade-off. Also, this paper provides implications for policymakers to consider the cost-benefit issue in the establishment and implementation of economic and environmental protection policies.
In a study, Farzanegan (2009) examined the time series of illegal trade in Iran during the period 1970-2002. The variables penalties for trafficking, differences between exchange rates in formal and informal market, tariff barriers, GROSSDOMESTICPRODUCTpercapita and GROSSDOMESTICPRODUCTpercapita growth rate, unemployment rate, degree of openness in economy, the literacy rate and the quality of institutions measures are considered as causes of illegal trade and the variables real income of the state, the index of import prices and consumption growth rates of petrochemical products are considered as the effects of the illegal trade in the economy. The results show that the average trafficking during the above-mentioned period is almost 13% of the total trade in Iran.
The aim of this paper is to study the economic (grossdomesticproductpercapita, inflation rate, unemployment rate and current account balance) and non-economic (democracy, corruption and the coup) determinants of number of power alternation in Africa over the period 1990-2015. As the number of power alternation is a count variable, a poisson model is used. The hypothesis of equidispersion underlying the poisson model and the goodness of fit of the model have been approved. The estimation results indicate that a low GDP percapita growth, a high level of democracy and coups explain the power alternations in Africa over the period 1990-2015.
Aims of the study were to critically examine the extent to which electricity consumption influences economic growth in Ghana and also determine, if it is electricity consumption that causes economic growth in Ghana or otherwise. The study employed Augmented Dickey-Fuller test, Cointegration test, Vector Error Correction Model and Granger Causality test. The study revealed that, in the long term, a hundred percent increase in electricity power consumption will cause real grossdomesticproductpercapita to increase by approximately fifty-two percent. However, in the short run, electricity consumption negatively affects real grossdomesticproductpercapita. The study again revealed that unidirectional causality run from electricity consumption to economic growth meaning that any policy actions taken to affect the smooth consumption of electricity in Ghana will definitely affect her grossdomesticproductpercapita. Therefore, the current load shedding policy due to low supply of electricity will definitely affect the Ghanaian economy negatively, that is lower production levels, high inflation, and high rates of unemployment and lower standard of living. Therefore, the government of Ghana should invest massively into electricity infrastructure and conservation measures to meet the needs of the various sectors of the Ghanaian economy.
and characteristics. For the CEE countries, the macro- regional level is related, as an example, to the analyses completed by Carstensen & Troubal (2004), Turnock (2005), Ginevicius & Simelyte (2011) which addressed the impact of foreign direct investment on the transformation of national economies or selected sectors in selected countries. With regards to foreign direct investment on lower territorial levels, studies prevail, which deal with the penetration of foreign direct investment in the individual CEE countries. For the Baltic countries (Yucel, 2014) , analyses of the impact of DFI on the economies of Lithuania or Estonia (Tvaronaviciene & Grybaite, 2007; Ginevicius & Tvaronaviciene, 2005) or Latvia (Revina & Brekis, 2009), and of the impact of globalisation processes on Lithuania, Latvia and Estonia contained in the paper by Ginevicius & Tvaronaviciene (2003) deserve to be mentioned here. Further studies which dealt with the inflow of foreign investment to other Central and Eastern European countries, namely Hungary (Boudier-Bensebaa, 2005), Poland (Gorynia, Nowak & Wolniak, 2007), the Czech Republic (Tousek & Tonev, 2003; Hlavacek & Koutsky, 2013; Hlavacek, 2009), Slovakia (Wokoun, Tvrdon & Damborsky, 2010) and Slovenia (Bucar, Rojec & Stare, 2009) were also published. The purpose of the article is to identify the impact of foreign direct investment on economic growth in selected Central and Eastern European countries, with an emphasis on post-2000 development. This is followed by compiling a model based on the Endogenous Growth Model (Mankiw, Romer & Weil, 1992) processed according to Solow's neo- classical growth model. The model employs such indicators as grossdomesticproductpercapita, inward foreign direct investment stock percapita, gross fixed capital formation percapita, increase in labour force, human resources in science and technology as the percentage of active population, which are followed for each country between 2000 and 2012. The construction of the model seeks to assess the impact and relevance of selected economic factors, including foreign direct investment, with regard to the economic growth of transitional economies in Central and Eastern European countries. Intensively, how foreign direct investment in transitional economies contributes to the development process in the individual countries.
C: Real percapita household final consumption, Y: Real percapita GDP, G: Real percapita government final consumption. (1) Jarque-Bera normality test, (2) Breusch-Pagan-Godfrey heteroscedasticity test, (3) Breusch-Godfrey Serial Correlation LM Test. Lag structure of the ARDL model is selected using the AIC criterion with maximum lag set to 5. Models are estimated under restricted constant. Figures in [.] are p values. (*) indicates the rejection of the null hypothesis of no cointegration at 5% level of significance. GDP: Grossdomesticproduct, ARDL: Autoregressive distributed lag
The above tables reveals descriptive statistics such as mean, standard deviation, minimum and maximum of gross domestics savings (GDS), Foreign Direct investment, age dependency ration , money supply growth rate, grossdomesticproduct, inflation and percapita income during the period from 1995 to 2016 of six different countries i.e Pakistan, China, Japan, Singapore, Turkey and Russia . According to the above table gross domestics saving has mean value of 31.98 % in grossdomestic saving of the selected countries other variables such as foreign direct investment, age dependency ratio, money supply growth rate, grossdomesticproduct, inflation and per capital income have mean values of 4.27,50.66,19.61,4.56,11.71 and 3.81 respectively while the minimum values of gross domestics saving, foreign direct investment, age dependency ratio, money supply growth rate, grossdomesticproduct, inflation and per capital income is 16.88,-.05,35.59,-17.23,- 7.82,-1.40 and 2.66 respectively. The maximum of grossdomestic savings (GDS), gross domestics saving, foreign direct investment, age dependency ratio, money supply growth rate, grossdomesticproduct, inflation and per capital is 53.46, 26.52,87.55,116.53,15.24,197.47 and 4.75 respectively.
The multivariate time series inspected in this work covers repeated measures of the grossdomesticproduct (GDP) of 190 countries published in Heston, Summers and Aten (2012) but not every time series could be used for cluster analysis. ‘GDP measures the monetary value of final goods and services’ (Callen, 2008). Final goods are all commodities currently produced, exchanged and consumed although this definition is controversial (England, 1998). Thus, GDP is an indicator of the economic performance of a country (Mazumdar, 2000). Each country's data has to be converted into a common currency to make interna- tional comparisons. An exchange rate is defined through the purchasing power parity (PPP) at which the currency of a country is converted into that of another country to pur- chase the same volume of goods and services in both countries (Rogoff, 1996).
ADF: augmented Dickey–Fuller test; AIC: Akaike information criteria; GDP: grossdomesticproduct; GDPp: percapitagrossdomesticproduct; GHEp: percapita government healthcare expenditure; HC: health care; HCE: healthcare expenditure; HSDP: health sector development planning; LAD: least absolute deviation; LMS: least median of squares; M: Huber’s M-estimation; MDGs: mil- lennium development goals; NHA: National Health Accounts; OECD: Organiza- tion for Economic Co-operation and Development; OLS: ordinary least square; SSA: sub-Saharan Africa; THEp: percapita total healthcare expenditure; USD: United States Dollar; WHO: World Health Organization.
The lowest absolute value of regression coefficients among other global factors in our regression model belonged to health expenditure. In other words, one SD increase in global health expenditure was associated with 0.11 SD decrease in global maternal mortality. Assess- ment of the indicators composing this factor and their bivariate correlations with MMR suggested greater share of governmental health expenditure to be negatively re- lated with maternal mortality. In contrast, private sector share and out-of-pocket health expenditure showed a positive correlation. Since appropriate government fi- nancing can ensure better access to some essential ma- ternal health services, greater absolute levels of health expenditure will be required for developing countries in order to achieve MDG on maternal mortality . Total health expenditure varies between around 2%-3% of grossdomesticproduct (GDP) in low-income countries (< $1000 percapita) to 8%-9% of GDP in high-income countries (> $7000 percapita). Contrary to our expect- ation, poor countries and communities, i.e. groups with the greatest need for protection from financial catastro- phe, receive the least level of support in the form of pre- payment and risk-sharing. While the mean out-of-pocket expenditure in low-income countries is as high as 20%- 80% of the total expenditure, the rates drops sharply and the variation narrows in high-income countries. In other words, increased income is associated with greater public financing and higher share of GDP and health from total public expenditure . As the existing degrees of public- health expenditure in many developing countries are far different from the targeted values , revising national health policies to address the current inequalities, promote a long-term perspective plan, and concentrate on a para- digm shift from the current ‘biomedical model’ to a ‘socio- cultural model’ is essential to tackle the numerous health problems in these countries .