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This paper examines the impact of inflation and other macroeconomic variables such as physical capital, government expenditure, and money supply on GDP growth in Ghana. The study obtained data from the World Development Indicators for the period 1986-2018 and employed vector autoregressive (VAR) models for the analysis. The results showed that general inflation, low inflation rates, physical capital, and money supply have positive, statistically, significant, effect on GDP growth, while, government expenditure and high inflation have negative, statistically significant, effect on GDP growth for the period studied. The study concludes that GDP grows positively at a general level of inflation and low rates of inflation but grows negatively at a high rate of inflation in Ghana. The study, therefore, recommends that government should implement monetary and fiscal policies that will help keep inflation rates low and redirect her spending to the productive sectors in the country to enhance GDP growth.

The purpose of this study is to use time-series econometric methods, specifically Vector Autoregression (VAR) models, to predict the growth of Tanzania's Gross Domestic Product (GDP), Inflation, and Foreign Direct Investment (FDI) using annual data from 1991 to 2020. The research finds that there is a Granger causality between GDP and FDI, largely due to increased private investment and consumption. However, there is no Granger causality between inflation and GDP or FDI. The study predicts that inflation will remain stable but may experience occasional spikes due to supply-side shocks. Additionally, the study anticipates that FDI will continue to increase due to ongoing reforms aimed at improving the business climate and attracting more overseas investments. The model diagnostic test shows no autocorrelation and a stable model. Finally, the study forecasts that both GDP and FDI will continue to rise due to major sectoral projects taking place in Tanzania. This information is useful for policymakers and investors who can use it to make informed decisions and manage the risks associated with economic growth and development in Tanzania.

The file associated with this record is under embargo until 12 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above. ; This paper considers an often forgotten relationship, the time delay between a cause and its effect in economies and finance. We treat the case of Foreign Direct Investment (FDI) and economic growth, - measured through a country Gross Domestic Product (GDP). The pertinent data refers to 43 countries, over 1970-2015, - for a total of 4278 observations. When countries are grouped according to the Inequality-Adjusted Human Development Index (IHDI), it is found that a time lag dependence effect exists in FDI-GDP correlations. This is established through a time-dependent Pearson 's product-moment correlation coefficient matrix. Moreover, such a Pearson correlation coefficient is observed to evolve from positive to negative values depending on the IHDI, from low to high. It is "politically and policy "relevant" that the correlation is statistically significant providing the time lag is less than 3 years. A "rank-size" law is demonstrated. It is recommended to reconsider such a time lag effect when discussing previous analyses whence conclusions on international business, and thereafter on forecasting. ; Peer-reviewed ; Post-print

This paper considers an often forgotten relationship, the time delay between a cause and its effect in economies and finance. We treat the case of Foreign Direct Investment (FDI) and economic growth, - measured through a country Gross Domestic Product (GDP). The pertinent data refers to 43 countries, over 1970-2015, - for a total of 4278 observations. When countries are grouped according to the Inequality-Adjusted Human Development Index (IHDI), it is found that a time lag dependence effect exists in FDI-GDP correlations. This is established through a time-dependent Pearson 's product-moment correlation coefficient matrix. Moreover, such a Pearson correlation coefficient is observed to evolve 1 from positive to negative values depending on the IHDI, from low to high. It is "politically and policy "relevant" that the correlation is statistically significant providing the time lag is less than 3 years. A "rank-size" law is demonstrated. It is recommended to reconsider such a time lag effect when discussing previous analyses whence conclusions on international business, and thereafter on forecasting

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.