Tag Archives: Granger Causality

Examining the Integration between Vietnamese Stock Market and Markets from US, UK, China, Japan and ASEAN (Published)

Portfolio diversification has long been in spotlight, however, the growing integration among stock markets lowers the diversification opportunities. This paper examines the integration of Vietnamese stock market with markets of ASEAN countries as well with the leading global markets such as US, UK, Japan and China. The investigation has taken place over two periods: long-term period 2007-2017 (normal period); and short-term period 2007-2008 (crisis period). The study employs unit root test, Engel and Granger co-integration, and Granger causality in order to test whether Vietnamese stock market has co-integration with stock markets of US, UK, China, Japan and other ASEAN countries. The results reveal that there is no relationship between Vietnam stock market and other stock markets in short-term period. However, in the long-term period, Vietnamese stock market is found to have positive relationship with the Chinese stock market. The result is not unexpected keeping in view the fact that Vietnam and China have close relationships in multiple fields including but not limited to geography, trading, history, and politics. Moreover, Granger causality test results reveal that Vietnam has mono-directional causal relationships with stock markets of US, Japan and Indonesia in short as well as long term.

Keywords: Diversification, Granger Causality, Long-Run Relationship, Stock Market Integration

The Analysis of Factors Affecting CPO Export Price of Indonesia (Published)

This study aims to determine and analyze the influences of world crude oil price shocks, world soybean oil prices, world CPO prices, palm oil TBS prices and the exchange rate of rupiah/US dollar towards the transmission on CPO export prices of Indonesia. This study uses quantitative analysis model with the approach of vector autogression model (VAR) which includes three main analysis tools namely Granger causality test, impulse response function (IRF) and forecast error decomposition of variance (FEDV). The variables which are used in this research are world petroleum price, world soybean oil price, CPO price of Rotterdam, CPO export price of Indonesia, fresh fruit bunch price and real exchange rate (real exchange rate). From Granger Causality test result, The price transmission process takes place the plot as follows: world crude oil prices significantly influence the CPO price of world (Rotterdam) which will significantly influence the world soybean oil prices and so on have a significant influence on the value of the real exchange rate which will influence the price of fresh fruit bunches and ultimately have a significant influence on CPO price export of Indonesia. From the estimation result of VAR model, there are significant influences of world crude oil price shocks, world soybean oil prices, world CPO prices, palm oil TBS prices and rupiah/US dollar exchange rates simultaneously to the transmission on CPO export prices of Indonesia. Based on analysis of Impulse response and variance decomposition, in the first period, one hundred percent average variability of CPO export price growth is significantly explained by the average growth of CPO export prices itself. In the subsequent period, the average variability of CPO export price growth is significantly explained by the average growth of CPO export price itself as well as other variables.

Keywords: : Petroleum Price, CPO export price, Granger Causality, Price Transmission, Real Exchange Rate, Soybean Oil Price, TBS, VAR, Variance Decomposition, impulse response function

Interfaces between Road Infrastructure and Poverty in Africa: The Case of Malawi, 1994-2013 (Published)

Critical assessment on the correlation between public investment on road infrastructure and poverty was carried out, and therefore this research paper provides an in depth analyses of the linkage between road infrastructure and poverty, as well as, other relevant macro economic variables used in the Malawi Growth and Development Strategy (MGDS) as target indicators. Using primary and secondary data from 1994-2013, dynamic time series models were applied in elaborating the various factors with thrust on road infrastructure that may influence poverty in Malawi. Noting poverty reduction as priority of Malawi Government’s development agenda since the early 1990s, MGDS provides the country’s socioeconomic growth and development platforms. According to the latest 2010 Integrated Household Survey (IHS3), the majority of Malawians (50.7 percent) are languishing in abysmal poverty; this level is remotely far from the MDGS target of 27 percent by end 2015.  The country has a high inequality index (Gini 0.38) reflecting profound inequalities in access to assets, services and opportunities across the population. The distribution of the benefits of economic growth is also important for the alleviation of poverty. However, the distribution of income and wealth are highly skewed, with a majority of the population living in a state of absolute poverty. Based on NSO surveys (1998-2010), the poorest 20 percent of the population control only around 10 percent of national consumption implying inequality is not decreasing at all for long time. Hosts of factors explaining why poverty level continues to be rampant are: share of agricultural as a percent of GDP (proxy to agricultural production) and export as percent of GDP (proxy to exports). However, this paper findings show that there is significant (p=0.000<0.05) relationship between road network and poverty levels. Estimates from Granger Causality analysis indicate that for one percent increase in road network, a reduction of 7.2 percent in poverty level is perhaps achievable. Average inflation rate over the last 20 years stands at 22.41 percent, and this has an immense impact on poverty level since it dramatically reduces the purchasing power of the majority of the population. For a one percent increase in the inflation rate, there is a consequence of about 3.7 percent increase in the average poverty level. Average Gross Domestic Product (GDP) growth rate is 4.7 percent annually with a minimum of -4.9 percent and a maximum of 10.2 percent in the last 20 years. Poverty level appears to significantly respond to (GDP). There is a 4.27 percent reduction in poverty level if a one percent GDP increment takes place as shown in the dynamic time series analysis. In fact, the declining of agricultural production for export and the growing gap in balance of payment (average Malawi Kwacha -498.92 billions or approximately US$1.1 billion) would immensely influence GDP negatively and therefore poverty becomes abysmal as GDP growth plummets. In a nutshell, the findings confirm that in the long run economic growth is the key to alleviation of extreme poverty since it creates the resources to raise incomes. Given the importance of agriculture in contributing towards GDP in Malawi, the positive impact that this sector has on poverty is evident. For agriculture to meaningfully impact economic growth, road infrastructure plays a great role. Other pro-poor variables such as development roads and other investment on infrastructure are vital for economic growth and hence poverty alleviation. 

Keywords: Granger Causality, Infrastructure, Malawi, Poverty, Public Investment, Vector Autoregression

Disaggregated Imports and Economic Growth in Nigeria (Published)

This study examines how much of the variance in economic growth can be explained by various categories of imports in Nigeria. The study is set to investigate whether it is the import-led or export-led growth hypothesis that holds for Nigeria. The Johansen testing approach to cointegration and the standard desk top pairwise Granger-causality test technique were implimented to achieve this objective. The cointegration test results demonstrate that the relationship between economic growth and decomposed import variables in Nigeria are stable and coalescing in the long run. Particular categories of interest in this study are Food & Life Animal, Manufactured Goods, and Machinery & Transport Equipment as the trio constitute over 75 percent of aggregate import bills during the period under review. Evidence from the pairwise granger casualty tests, contrary to expectation, suggests that import-led growth hypothesis does not hold for Nigeria. These results cannot be divorced from certain factors such as lack of capacity to take advantage of the advanced technologies embodied in the imported capital goods, inability to sustain installed manufacturing capacity and corrupt practices in procurement processes, associated with contracts for the importation of manufactured and capital goods for most failed capital projects.

Keywords: Cointrgration, Disaggregated Imports, Exports, GDP growth, Granger Causality

Direct Versus Indirect Taxation and Income Inequality (Published)

In this paper, we employed multivariate econometric analysis approach to study the relationship between taxation and income inequality in Nigeria. The study was a country-specific approach using tax and macroeconomic data from 1980 to 2011. We collected data from the Central Bank of Nigeria Publications, Federal Inland Revenue Service, World Bank and Index Mundi. We estimated the data using a combination of co-integration and error correction model. Preliminary diagnostic analysis using Ramsey RESET test, Breuch-Pagan-Godfrey, Granger causality test and Breuch-Godfrey test of serial correlation were affected to check the accuracy of our model. The preliminary analysis where favourable with no cases of serial correlation, non-normality, bi-directional causality and model misspecification. We found a negative and robust relationship between total tax revenue, total tax revenue to GDP ratio and income inequality in Nigeria with t-values of (-2.748706) and (-2.287270) and negative coefficients of (-0.007869) and (-0.512235) respectively. We found a negative but insignificant relationship between GDPPC, PCREDIT/GDP, TDT/TIT*TTR while LFP and TDT/TIT had positive but insignificant relationship with income inequality with coefficients of (0.421) and (1.243794) and t-values of (1.732565) and (1.717362) respectively.

Keywords: Direct Taxation, Error Correction Model, Granger Causality, Income Inequality, Indirect Taxation, Total Tax Revenue