scholarly journals Relationship between Foreign Direct Investments and Capital Flight in Kenya: 1998-2018

2019 ◽  
Vol 3 (3) ◽  
pp. 251
Author(s):  
Mercy Wairimu Mwangi ◽  
Amos Njuguna ◽  
George Achoki
Keyword(s):  
Growth Rate ◽  
Gross Domestic Product ◽  
Capital Flight ◽  
Domestic Product ◽  
Foreign Direct Investments ◽  
Gross Domestic Product Growth ◽  
P Values ◽  
Long Run ◽  
Short Run ◽  
Product Growth Rate

The study established the relationship between Foreign Direct investments and Capital Flight in Kenya over the period 1998 to 2018. Quarterly time series data for calculation of capital flight and Gross Domestic Product growth rate, inflation and Foreign Direct investments were collected from the Central Bank of Kenya and Kenya National Bureau of Statistics. Two Autoregressive Distributed-lagged model models were fitted. Regression coefficients for FDI were 0.44 and -0.040 in the short run and -0.501 in the long run. The p values were 0.008 and 0.015 and 0.654 respectively. The results indicated that a 1 % increase in current quarters FDI would lead to a 0.44% increase in capital flight and a 1% increase in previous quarters FDI would lead to a decrease of 0.040% in capital flight. Regression results showed a coefficient of 0.006 and - 0.004 for Gross Domestic Product growth rate in the short run, and 0.038 in the long run. The p values were 0.422, and 0.638 and 0.749 respectively meaning that Gross Domestic Product growth rate and the capital flight had no significant relationship. Regression results showed a coefficient of -0.001 and -0.005 for inflation in the short run and -0.088 for inflation for the long run. The p values were 0.844 and 0.363 and 0.253 respectively. This indicated that inflation and the capital flight had an insignificant relationship. The study recommends that government adopts strategic management on FDI inflow transactions to avoid possible leakages of the same money going out as capital flight.

scholarly journals Relationship between corruption and capital flight in Kenya: 1998-2018

2019 ◽  
Vol 8 (5) ◽  
pp. 237-250
Author(s):  
Mercy Mwangi ◽  
Amos Njuguna ◽  
George Achoki
Keyword(s):  
Growth Rate ◽  
Exchange Rate ◽  
Significant Relationship ◽  
Capital Flight ◽  
Series Data ◽  
National Bureau ◽  
P Values ◽  
Long Run ◽  
Short Run ◽  
The Exchange Rate

The study established the relationship between corruption and capital flight in Kenya over the period 1998 to 2018. Quarterly time series data for calculation of capital flight and for GDP growth rate and exchange rates were collected from the Central Bank of Kenya and Kenya National Bureau of Statistics. Corruption perception index data was collected from the Transparency International website. Two Autoregressive Distributed-lagged models were fitted. Regression coefficients for corruption were -0.114 and 0.066 in the short run and -0.501 in the long run and the p values were 0.523 and 0.691 and 0.558 respectively, indicating no significant relationship. Regression results showed a coefficient of 0.01 and 0.003 for the Gross Domestic Product growth rate in the short run, and 0.049 in the long run. The p values were 0.670, 0.855 and 0.578 respectively denoting no significant relationship. Regression results showed a coefficient of 0.002 and 0.003 for the exchange rate in the short run, 0.43 for the exchange rate in the long run. The p values were 0.891 and 0.584 and 0.095 respectively indicating that a one % increase in the exchange rate would lead to a 0.043 % increase in capital flight in the long run. Regression results of lagged capital flight on capital flight showed a coefficient of 0.904. The p-value was 0.000 meaning that a one % increase in lagged capital flight would lead to a 0.904 % increase in capital flight. The study recommended that the government devises policies that would prevent further capital flight and generate capital flight reversal.

Infrastructure Investment and Economic Growth: Evidence from India

2016 ◽  
Vol 17 (1) ◽  
pp. 90-111
Author(s):  
Naliniprava Tripathy ◽  
Maram Srikanth ◽  
Lagesh Aravalath
Keyword(s):  
Economic Growth ◽  
Gross Domestic Product ◽  
Error Correction ◽  
Capital Formation ◽  
Domestic Product ◽  
Government Revenue ◽  
Indian Economy ◽  
Long Run ◽  
Domestic Capital ◽  
Short Run

This study examines the long-run and short-run relationship between investment in infrastructure and economic growth in the Indian economy by using Auto Regressive Distributed Lag Model, Error Correction Model, and Granger Causality Test. The study reports that there is no short-run relationship among gross domestic product, gross domestic capital formation, revenue of the governmentand exports. However, the study finds that unidirectional causality exists between employment and gross domestic product; gross domestic productandinflation. It implies that employmentlevel in organised sector and inflationinfluence the economic growth in India for a short period. The study finds that there is a long-run relation exists between economic growth, domestic investment, inflation and government revenue. Therefore, emphasis should be placed on capital formation, government income and inflation to accelerate growth and development in the Indian economy. The error correction term is indicating that long term relationship is stable and any disequilibrium created in short termwill be temporary and will correct over a period. However, it is suggested to maintain balance among inflation,gross domestic product, employment, exports, savings, investment and government revenue to keep an economy growing. These findings have important policy implications since an economy built on investment in infrastructural development.

13th Five-Year Plan Reorientates China’s Housing Policy

2016 ◽  
Vol 08 (03) ◽  
pp. 33-41
Author(s):  
Zhihua ZHOU
Keyword(s):  
Economic Growth ◽  
Growth Rate ◽  
Gross Domestic Product ◽  
Housing Policy ◽  
Harmonious Society ◽  
Housing Development ◽  
Gross Domestic Product Growth ◽  
Stable Housing ◽  
Product Growth Rate

The 13th Guideline has created a friendly policy atmosphere for a moderately prosperous and stable housing development to attain a 6.5% gross domestic product growth rate and ensure a harmonious society. However, the overall impact remains unclear as details have yet to be rolled out. As the role of housing development in overall development changes, the contribution of housing development to future economic growth is expected to be lower.

scholarly journals Empirical Analysis of House Price Bubble: A Case Study on Malaysia

2016 ◽  
Vol 11 (12) ◽  
pp. 127
Author(s):  
Fong Kean Yan ◽  
Yap Lya Keng ◽  
Kwek Kien Teng
Keyword(s):  
Gross Domestic Product ◽  
House Prices ◽  
House Price ◽  
Domestic Product ◽  
Price Bubble ◽  
Long Run ◽  
Residential Properties ◽  
Short Run ◽  
Per Capita ◽  
House Price Bubble

The main objective of this research is to investigate the relationship between house price with macroeconomics variables - Gross Domestic Product per capita, inflation rate, Base Lending Rate and amount of household loan disbursed for purchase of residential properties. We try to use these variables to examine if they could trigger a housing bubble to burst in Malaysia. Granger Causality results show that there is univariate relationship from house price to Gross Domestic Product per capita. Though house price and other macroeconomics variables do not Granger–cause each other in short run, but these variables are cointegrated in the long run, i.e. there is no evidence of house price bubble in Malaysia. We suggest that soaring house prices in Malaysia is being supported by the large inflow of foreign funds into the housing sector and the unresponsive supply of houses.

scholarly journals Analysis of Macroeconomic Factors Effect to Gross Domestic Product of Bosnia and Herzegovina Using the Multiple Linear Regression Model

ECONOMICS ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 91-97
Author(s):  
Stanko Stanić ◽  
Željko V. Račić
Keyword(s):  
Growth Rate ◽  
Gross Domestic Product ◽  
Regression Model ◽  
Bosnia And Herzegovina ◽  
Export Growth ◽  
Domestic Product ◽  
Foreign Direct Investments ◽  
Macroeconomic Factors ◽  
Important Indicator ◽  
Independent Variables

Abstract This paper presents the application of the multiple regression analysis model in macroeconomic research using the model of Bosnia and Herzegovina in the period from 2005 to 2018. The objective of the research is to evaluate the effects of macroeconomic factors (independent variables) to gross domestic product (dependent variable), and based on theoretical and methodological research. Applying the Enter method, out of six independent variables, they are all included in the regression model, whereas the sequence of inclusion in the model is the following: foreign direct investments, Import, Export, Growth rate, unemployment and inflation. Numerous research indicate positive connection between gross domestic product as the dependent variable and foreign direct investments, Import, Export, Growth rate, unemployment and inflation, as independent variables. Other factors negligibly explain the most important indicator of economic activities of a country. Our assignment is to either confirm or reject the abovementioned statement.

scholarly journals Do gross domestic product changes have asymmetric effects on India’s energy use?

2017 ◽  
Vol 1 (1) ◽  
pp. 1-10
Author(s):  
Manzoor Ahmad ◽  
Zia Ullah Khan ◽  
Shehzad Khan
Keyword(s):  
Gross Domestic Product ◽  
Energy Use ◽  
Time Series Data ◽  
Developing Economies ◽  
Domestic Product ◽  
Series Data ◽  
Distributed Lag ◽  
Long Run ◽  
Short Run ◽  
Symmetric Effect

The existing literature on the linkage between Gross Domestic Product (GDP) and energy use in both industrialized and developing economies usually assumes that the impacts of gross domestic product changes are symmetric. In this study, we utilized nonlinear autoregressive distributed lag (NARDL) model and test whether or not the effect of variations in the gross domestic product on energy use is symmetric or asymmetric from the context of India. Using time series data over 1971-2014, the findings depict that the change in the gross domestic product has a symmetric effect on energy use both in short-run and the long-run. Our conclusions infer that there is no asymmetrical association between GDP and energy use, leading to support the symmetric impact of GDP on energy use.

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