Search results

The causal relationship between money and income (output) has been an important topic and has been extensively studied. However, those empirical studies are almost entirely on Granger-causality in the conditional mean. Compared to conditional mean, conditional quantiles give a broader picture of an economy in various scenarios. In this paper, we explore whether forecasting conditional quantiles of output growth can be improved using money growth information. We compare the check loss values of quantile forecasts of output growth with and without using past information on money growth, and assess the statistical significance of the loss-differentials. Using U.S. monthly series of real personal income or industrial production for income and output, and M1 or M2 for money, we find that out-of-sample quantile forecasting for output growth is significantly improved by accounting for past money growth information, particularly in tails of the output growth conditional distribution. On the other hand, money–income Granger-causality in the conditional mean is quite weak and unstable. These empirical findings in this paper have not been observed in the money–income literature. The new results of this paper have an important implication on monetary policy, because they imply that the effectiveness of monetary policy has been under-estimated by merely testing Granger-causality in conditional mean. Money does Granger-cause income more strongly than it has been known and therefore information on money growth can (and should) be more utilized in implementing monetary policy.

Contrary to the restrictive bivariate results of Saunders (1995), our findings from open‐economy multivariate models accord with the conventional IS/LM apparatus and decisively support the use of fiscal policy as a key macrostablization tool in the U.S. economy. We provide theoretical explanations for our results and produce empirical evidence for their robustness.

A number of recent papers have raised serious questions about the validity of the German dominance hypothesis, using Granger (temporal) causality tests. If Germany dominates within the European Monetary System, then German monetary policy, measured by either money stocks or interest rates should Granger (temporally) cause other EMS countries’ monetary policies, but not vice versa. Empirical evidence leads analysts to conclude that the German dominance hypothesis is invalid, or at a minimum, in need of significant reformulation. Explores similar Granger causality tests, using the recent cointegration and error‐correction modelling strategy, for the US and a group of developing countries during the Bretton Woods period, where conventional wisdom suggests that US policy dominated. Finds significant evidence of two‐way causality between the US money stock and the money stocks of a large number of developing countries. These findings raise a serious questions about the interpretation and/or appropriateness of the Granger causality test for investigating policy dominance hypotheses.

The purpose of this paper is twofold. First, the paper examines the risk transmission between crude oil and petroleum product prices of Japan’s oil futures market. Second, it compares the performance of two tests for Granger causality using realized variance (RV) and the exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model.

The author measures the daily RV of crude oil, kerosene and gasoline futures listed on the Tokyo Commodity Exchange using high-frequency data, and he examines the Granger causality in variance between these variables using the vector autoregression model. Further, the author estimates the EGARCH model based on daily data and test for Granger causality in variance between commodity futures using Hong’s (2001) approach.

The results of the RV approach reveal that the hypothesis on the existence of a mutual volatility spillover between crude oil and petroleum product markets is accepted. However, the results of the conventional approach indicate that all the hypotheses on Granger causalities in variance are rejected. The methodology based on intraday high-frequency data exhibits higher power than the conventional approach based on daily data.

This is the first paper to investigate Japan’s oil market using RV. The authors conclude that the approach based on RV is universally adoptable when testing for Granger causality in variance.

The purpose of this paper is to examine the causal relationship between inward foreign direct investment (FDI) and economic growth in Southern African Development Community (SADC) countries over the period 1980-2012. It also investigates whether the causal relationship between FDI inflows and economic growth is dependent on the level of income.

In order to assess whether the causal relationship between FDI inflows and economic growth is dependent on the level of income, the study divided the SADC countries into two groups, namely, the middle-income countries and the low-income countries. The study used the recent panel-data analysis methods to examine this linkage. The Granger causality test for the middle-income countries was conducted within a vector-error correction mechanism framework; while that of the low-income countries was conducted within a vector autoregressions framework.

The results for the middle-income countries’ panel show that there is a uni-directional causal flow from GDP to FDI, and not vice versa. However, for the low-income countries’ panel, there was no evidence of causality in either direction. The study concludes that the FDI-led growth hypothesis does not apply to SADC countries.

Methodology applied in this study is a bivariate framework which is likely to suffer from the omission of variable bias (Odhiambo, 2008, 2011). Second, the Granger causality analysis employed in this only investigates the direction of causality and whether each variable can be used to explain another, but does not directly test for the mechanisms through which FDI leads to economic growth and economic growth leads to FDI.

Future studies may include a third variable such as domestic savings, exports, or financial development in a trivariate or multivariate panel causality model. A more complete analysis which seeks to explain the channels through which FDI impacts growth is suggested for future studies. Lastly, sector level analysis will help policy makers draft effective industrial policies, which can guide allocation of incentives.

The results of this study support the Growth-led FDI hypothesis, but not the FDI-led growth hypothesis. In other words, it is economic growth that drives FDI inflows into the SADC region and into Southern Africa, and not vice versa. This implies that the recent high economic growth rates that have been recorded in some of the SADC countries, especially the middle-income countries, have led to a massive inflow of FDI into this region.

At the regional level, SADC as a regional bloc has been actively pursuing policies and strategies aimed at attracting FDI into the region. Despite the important role of FDI in economic development, and the increase in FDI inflows into SADC countries in particular, there is a significant dearth of literature on the causal relationship between FDI and economic growth. The study used the recent panel-data analysis methods to examine the causal relationship between FDI and economic growth in SADC countries.

The purpose of this paper is to gain a deeper insight on how education boosts economic progress in key emerging economies. This project is aimed at exploring the interactive dynamics between the tertiary education sector and economic development in BRICS countries. The author also aims to examine how the structure of higher education contributes to economic expansion.

The author uses the time series data of BRICS countries across approximately two decades to determine the statistical causality between the size of tertiary enrollment and economic development. The linear regression model is then used to figure out the different impact levels of academic and vocational training programs at the tertiary level to economic development.

Data from all BRICS countries exhibited a unidirectional statistical causality relationship, except the Brazilian data. The national economic expansion Granger Caused increased tertiary enrollment in Russia and India, while in China and South Africa, higher education enrollment Granger Caused economic progress. The impact from tertiary academic training is found to be positive for all BRICS nations, while tertiary vocation training is shown to have impaired the Russian and South African economy.

This project is based on a rather small sample size, and the stationary feature of the time series could be different should a larger pool of data spanning a longer period of time is used. In addition, the author also neglects other control variables in the regression model. Therefore, the impact level could be distorted due to possible omitted variable bias.

Tertiary academic study is found to have a larger impact level to all countries’ economic advancement, except for China, during the time frame studied. There is a statistical correlation between the education and economic progress. This is particularly true for BRICS countries, especially China. But the exception is Brazil.

The government should provide education up to the certain level, as there is a direct correlation to the job creation and economic progress. Furthermore, the government should also work closely with industry to ensure growth of industry and creation of new jobs.

The comparative analysis and evaluation of the dynamic interaction of tertiary enrollment and economic output across all five BRICS nations is unique, and it deepens the understanding of the socioeconomic development in these countries from a holistic management perspective.

This study aims to revisit the empirical debate about the asymmetric relationship between oil prices, energy consumption, CO₂ emissions and economic growth in a panel of 184 countries from 1981 to 2020.

A relatively new research method, the PVAR system GMM, is applied.

The outcome of the PVAR system GMM model at the group level in the study suggests that oil prices exert a positive but statistically insignificant effect on economic growth. Energy consumption is inversely related to economic growth but statistically significant, and the correlation between CO₂ emissions and economic growth is negative but statistically insignificant. The Granger causality test indicates that oil prices, CO₂ emissions, oil rents, energy consumption and savings jointly Granger-cause economic growth. A unidirectional causality runs from energy consumption, savings and economic growth to oil prices. At countries’ income grouping levels, oil prices, oil rent, CO₂ emissions, energy consumption and savings jointly Granger-cause economic growth for the high-income and upper-middle-income countries groups only, while those variables did not jointly Granger-cause economic growth for the low-income and lower-middle-income countries groups. The modulus emanating from the eigenvalue stability condition with the roots of the companion matrix indicates that the model is stable. The results support the asymmetric impacts of oil prices on economic growth and aid policy formulation, particularly the cross-country disparities regarding the nexus between oil prices and growth.

From a methodological perspective, to the best of the author’s knowledge, the study is the first attempt to use the PVAR system GMM and such a large sample group of 184 economies in the post-COVID-19 era to examine the impacts of oil prices on countries’ growth while controlling for other crucial variables, which is noteworthy. Two, using the World Bank categorisation of countries according to income groups, the study adds another layer of contribution to the literature by decomposing the 184 sample economies into four income groups: high-income, low-income, upper-middle-income and lower-middle-income groups to investigate the potential for asymmetric effects of oil prices on growth, the first of its kind in the post-COVID-19 period.

The purpose of this paper is to investigate both linear and/or nonlinear effects of inflation on income inequality and to test the Kuznets hypothesis using panel data of 24 developed countries (DCs) and 66 developing countries (LDCs) observed over the period of 1990–2014.

This paper explores the short- and long-run Granger causality relationship between inflation and income inequality using the Toda and Yamamoto (1995) procedure and a Vector Error Correction Model (VECM) approach. The existence of a nonlinear relationship between inflation and income inequality is confirmed implying as inflation rises income inequality decreases. Income inequality then reaches a minimum and then starts rising again. The findings of this paper show the existence of Kuznets “U-shaped” hypothesis between income inequality and real GDP per capita in DCs group, and the existence of Kuznets’ inverted “U-shaped” hypothesis for LDCs group.

The results indicate that there is no bi-directional Granger causality between inflation and income inequality in the short-run, but, there is bi-directional Granger causality in the long-run for both the DCs and LDCs group. The results help us to assess the effectiveness of monetary policy in reducing income inequality in both the DCs and LDCs group. As a policy implication, monetary policy is often aimed at controlling the annual rate of inflation in the long-run with a short-run focus on reducing output gaps and creating employment. However, managing inflation may have implications for income inequality.

This is original research paper which analyzes the “U-shaped” and inverted “U-shaped” paths of income inequality and real GDP per capita for large sample of two group countries including developed and developing countries, respectively. Also, this paper analyzes the nonlinear relationship between inflation and income inequality in two groups. Furthermore, this paper investigates the short- and long-run relationship between variables. The results are important for policy makers.

This paper tests for longrun relationships among the national equity markets of the G'7 countries using the Engle‐Granger two‐step procedure. Results indicate that cointegration is the norm among these seven equity markets in the post‐Bretton Woods period. Further, market adjustments to system equilibria are accelerating as one moves toward the present implying that markets are becoming more integrated.

Proposes to re‐examine empirically the causal relationship between defence spending and economic growth in mainland China. First, using a VAR modelling technique with suitable diagnostics, e.g. Akaike’s FPE statistics and a likelihood ratio test for over‐ and under‐fitting the causal model, the results indicate a positive unidirectional causality flowing from defence spending to economic growth. Second, by evaluating a dynamic vector error‐correction model, variance decomposition and impulse response functions, then analyses the direction, duration and strength of Granger‐causality between defence spending and economic growth. The results broadly indicate that defence spending and economic growth did share a common trend over the sample period under analysis, but it was the former which stimulated the latter. Moreover, it is defence spending that has a much more perceptible and prolonged effect on economic growth, giving rise to implications that although expenditure on defence may have been politically motivated, over the long‐run this spending did play a significant indirect role in enhancing the growth potential of this, for many years, closed‐door economy.