2014 ◽  
Vol 1 (3) ◽  
pp. 156-162
Author(s):  
Tendai Makoni

The time series yearly data for Gross Domestic Product (GDP), inflation and unemployment from 1980 to 2012 was used in the study. First difference of the logged data became stationary as suggested by the time series plots. Johansen Maximum Likelihood Cointegration test indicated a long-run relationship among the variables. Granger Causality tests suggested unidirectional causality between inflation and GDP, implying that GDP is Granger caused by inflation in Zimbabwe. Another unidirectional causality was noted between unemployment and inflation. The causality between unemployment and inflation imply that unemployment do affect GDP indirectly since unemployment influences inflation which in turn positively affect GDP.


2017 ◽  
Vol 9 (10) ◽  
pp. 145 ◽  
Author(s):  
Bibi Rouksar-Dussoyea ◽  
Ho Ming-Kang ◽  
Raja Rajeswari ◽  
Benjamin Chan Yin-Fah

This panel analysis study is conducted to examine the relationship between inflation rates (CPI) and unemployment rates (HUR) with the Gross Domestic Product growth rates (GDP), before and after the 2008 European crisis. Quarterly data for 18 consecutive years and six sample countries from Europe (Austria, France, Germany, Greece, Hungary and United Kingdom) have been considered in the panel. In order to get a more profound understanding of the impacts of the European crisis on the relationship between the variables, the panel data set has been classified into 3 separate panels, such that Panel 1 (1999Q1-2007Q4) represents before-crisis panel, Panel 2 (2008Q1-2016Q4) represents the during/after crisis panel and lastly, Panel 3 (1999Q1-2016Q4) represents the long-run panel. Panel 1 is subject to the Fixed Effects with LSDV model, whereby four out of the six countries are significant, and CPI and HUR are insignificant predictors of the GDP. Both Panel 2 and Panel 3 are subject to the Two-way Random Effects model, whereby both CPI and HUR have negative significant effect on GDP. Granger Causality test has also been carried out to determine whether causality is present among variables, based on each panel.


10.12737/437 ◽  
2013 ◽  
Vol 1 (1) ◽  
pp. 44-50
Author(s):  
Шишкин ◽  
Andrey Shishkin

Analysis of terms associated with economic growth. In particular conducted a more detailed analysis of the gross domestic product. Describing the relationship of the gross domestic product, and social indicators connected with the movement of the labour force. The analysis of statistical indicators characterizing the innovation potential of the state. Touched upon the issues related to the preparation of personnel in the field of development of innovative processes. According to the survey of statistical data formed findings on the interaction of indicators characterizing the economic growth and indicators characterizing the innovative development of the state. Touched upon the issues of interaction of state corporations and the growth of the innovation development of the state, as well as the historical aspects of formation of state corporations. Analyzed the dependence between the development of innovation processes and the formation of human capital as a major factor of development of innovations. The conclusions which allow to compare the trends in the development of economic growth with the trends in the development of innovative processes.


1992 ◽  
Vol 71 (3) ◽  
pp. 723-726
Author(s):  
Y. G. Pillay

The data set from the Organization for Economic Cooperation and Development (OECD) was explored to investigate the relationship of gross domestic product (which provides an indication of the wealth of a country) and the provision of psychiatric services (specifically inpatient psychiatric services) in selected OECD countries. Gross domestic product per capita correlated .84 with expenditure per capita on psychiatric hospitals but r was zero between number of beds per 1000 population and length of stay.


Author(s):  
Jana Hvozdenska

The steepness of the bond yield curve is an excellent indicator of a possible future economic activity. A rise in the short rate tends to flatten the yield curve and slows down real growth in the near-term. This paper analyses the dependence between slope of the yield curve and an economic activity of selected countries between 2000 and 2016. The slope of the yield curve can be measured as the yield spread between sovereign 10-year and 3-month bonds. The results showed that the best predictive lags are the lag of four and five quarters. The results also confirm that 10-year and 3-month yield spread has a significant predictive power for real GDP growth after a financial crisis. These findings can benefit investors and provide evidence of the potential usefulness of the yield curve spreads as indicators of the future economic activity. Keywords: GDP prediction, yield curve, slope, spread.


2021 ◽  
Vol 1 (10) ◽  
pp. 91-106
Author(s):  
Evgeny V. Sokolov ◽  
◽  
Evgeny V. Kostyrin ◽  
Svetlana V. Lasunova ◽  
◽  
...  

The proposed technology of financing enterprises and the Russian economy, harmoniously combining the interests of working citizens, owners and the state, makes it possible, at quite achievable rates of gross domestic product growth (enterprise revenue) by 3.5% per year, to ensure a 46.6% increase in wages of working citizens over 5 years, which will practically end poverty. To increase contributions to the development fund for 5 years by 25%, which the owners of enterprises and the entire workforce are interested in, since this ensures the growth of their incomes and the possibility of constant modernization and updating of technological equipment and the release of new competitive products. Increase in 5 years (despite a gradual decrease to 14.51% of contributions to the Pension Fund RF) the amount of funds received by budgets of all levels by 22%, which will allow the state to solve many social problems.


Circulation ◽  
2014 ◽  
Vol 129 (suppl_1) ◽  
Author(s):  
Rajesh Vedanthan ◽  
Mondira Ray ◽  
Valentin Fuster ◽  
Ellen Magenheim

Introduction: Hypertension is the leading global risk for mortality and its prevalence is increasing in many low- and middle-income countries. Hypertension treatment rates are low worldwide, potentially in part due to insufficient human resources. However, the relationship between health worker density and hypertension treatment rates is unknown. Objective: To conduct an econometric analysis of the relationship between health worker density and hypertension treatment rates worldwide. Methods: Hypertension treatment rates were collected from published reports between 1980 and 2010. Data on health worker (physician and nurse) density were obtained from the World Health Organization (WHO). Data for potential confounding variables--per capita gross domestic product, hospital bed density, burden of infectious diseases, land area and urban population--were obtained from WHO and World Bank databases. Potential interaction by per capita gross domestic product was evaluated. Multivariable logistic-logarithmic regression analysis was performed using Stata. Results: Full data were available from 146 countries spanning all World Bank income classification categories. Health worker density was significantly associated with hypertension treatment rate in the unadjusted model (beta = 0.23; p < 0.005). In the fully adjusted model, the association remained positive but was not statistically significant (beta = 0.30; p = 0.078) (Figure). Hypertension treatment rates were more strongly related to physician than nurse density (beta = 0.21 vs 0.08; p = 0.10 vs 0.49). Conclusion: Hypertension treatment rates across the world appear to be related to health worker density, although the relationship does not achieve strict statistical significance. Our results suggest that a 10% increase in health worker density is associated with a 2-3% increase in hypertension treatment rate. Given the global burden of hypertension and other chronic diseases, WHO guidelines for health workforce staffing may need to be reconsidered.


2019 ◽  
pp. 171-182
Author(s):  
Erum Khushnood Zahid Shaikh ◽  
Zahid H. Channa ◽  
Mehwish Bhutto

In the modern world, the exchange rate plays an important role in measuring the strength of country’s economy in global economic conditions. An exchange rate is an important tool for controlling various macro-economic variables, and it is itself affected by different macro-economic variables. Pakistan is a developing country of the world and its unstable economy faces high variability in the exchange rate or devaluation of the domestic currency. Therefore, this study investigates the relationship of an exchange rate with selected macro-economic variables (i.e. import, GDP, Inflation & export), with a special focus on Pakistan’s economy. It also aims at finding out the degree of strength at which selected independent variables to leave a significant impact on the exchange rate in the economy of Pakistan (i.e. during the period of 1992 to 2017). For this secondary database study, data extracted from official website of World Bank, State Bank of Pakistan and Economic Surveys of Pakistan. Multiple regression models were used to measure the empirical impact of selected independent variables on exchange rate. Findings show that the Import and Gross Domestic Product (GDP) have a significant negative impact on exchange rate whereas, export and inflation have a significant positive impact on the exchange rate in the economy of Pakistan. The study recommends that the Government of Pakistan should adapt to make its exchange rate policy more effective through high production, more export with a reduction of import and price stability.


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