OlaOluwa S. Yaya

Do sunspot numbers cause global temperatures? Evidence from a frequency domain causality test

This article applies the causality test in the frequency domain, developed by Breitung and Candelon (2006), to analyse whether sunspot numbers (used as a partial approximation to solar irradiance) cause global temperatures, using monthly data covering the time period 1880:1–2013:9. While standard time domain Granger causality test fails to reject the null hypothesis that sunspot numbers do not cause global temperatures for both full and sub-samples (identified based on tests of structural breaks), the frequency domain causality test detects predictability for both the full-sample and the last sub-sample at short (2–2.6 months) and long (10.3 months and above) cycle lengths, respectively. Our results highlight the importance of analysing causality using the frequency domain test, which, unlike the time domain Granger causality test, allows us to decompose causality by different time horizons, and hence, could detect predictability at certain cycle lengths even when the time domain causality test might fail to pick up any causality. Further, given the widespread discussion in the literature, those results for the full-sample causality, irrespective of whether it is in time or frequency domains, cannot be relied upon when there are structural breaks present, and one needs to draw inference regarding causality from the sub-samples, we can conclude that there has been an emergence of causality running from sunspot numbers to global temperatures only recently at cycle length of 10.3 months and above.

Seasonal fractional integrated time series models for rainfall data in Nigeria

Rainfall variability, seasonality and extremity have a lot of consequences in planning and decision making of every sphere of human endeavour especially in Nigeria where majority of agricultural practices and planning is dependent on rainfed agriculture. For this reason, an extensive understanding of rainfall regime is an important prerequisite in such planning. We approach this work using time series approach. Seasonality and possibility of long-term dependence in rainfall data are considered, and these have significant effects in explaining the distribution of rainfall in each state of the six geopolitical zones of Nigeria. The estimated seasonal autoregressive fractionally integrated moving average (SARFIMA) model for each of the six rainfall zones was found to perform better in predicting rainfall distribution than the corresponding seasonal autoregressive moving average (SARMA) model in terms of minimum Akaike information criterion (AIC) and other model diagnostic measures.

Time series analysis of volatility in the petroleum pricing markets: the persistence, asymmetry and jumps in the returns series

The petroleum energy market is becoming more volatile owing to recent fluctuations in oil price, which in the long run affects the pricing and volatility persistence levels of other petroleum products. Apart from the symmetry and asymmetry that are known with volatility series, jumps have recently been identified, while the symmetric and asymmetric models failed in predicting the jump components in the financial series. The historical prices of crude oil and its distilled constituents possess occasional jumps as a result of global political or economic constraints. We applied both fractional persistence and volatility modelling frameworks in studying the volatility persistence in crude oil and petroleum products prices. We chose among symmetric, asymmetric and jumps volatility models. Results indicated that prices of crude oil and gasoline were less persistent when compared with volatility series of other petroleum products. The newly proposed jump volatility model variants outperformed other existing volatility models in predicting the volatility in the prices of crude oil, heating oil and diesel. The exception was the Asymmetric Power ARCH (APARCH) model, which emerged best in predicting the prices of gasoline, kerosene and propane prices; but GAS variants were still ranked second and third competing models in predicting the volatility in gasoline and kerosene prices. Using wrongly specified model for predicting the volatility in petroleum pricing can misinform oil markets, thereby generating intense conditional oil market volatility that is capable of distorting the price of oil and macroeconomic stability of the entire globe.

Long memory, strcutural breaks and mean shifts in the inflation rates in Nigeria

This paper deals with the analysis of the inflation rate in Nigeria. We use long range dependence techniques based on fractional integration or I(d) models, incorporating structural breaks in the model. The results indicate that inflation in Nigeria displays long memory behaviour, with an order of integration of about 0.3 in spite of the existence of breaks at different periods. Including the growth rate of money (M1) as an exogenous term, the results indicate that this variable significantly affects inflation two and three periods (quarters) after the initial shock.

Long Memory and Estimation of Memory Parameters: Nigerian and US Inflation Rates

Most economic series have been analyzed on the assumption that they are integrated of order d that is I(d), where d is an integer. Such series exhibit a short memory process characterized with exponential decay in the autocorrelation function (ACF) sometimes with alternating signs after dth order of difference. However, evidence of long memory and persistent autocorrelations characterized by (fractional integration) has been documented in literature for many economic series. Thus results of analysis based on wrong assumptions of the order of integration will produce biased estimates and unreliable forecast values. This paper therefore focuses on investigating the existence or otherwise of long memory in the Nigerian and US inflation series using some standard tests. It also seeks to estimate the memory parameters if it exists using the parametric and non-parametric methods. Even though the US inflation is fractionally integrated and Nigerian inflation series has unit root, the linear model specified for them are not adequate. The residual analyses shows evidence of nonlinearity and ARCH effect implying suggesting that nonlinear models or generalized autoregressive conditional heteroscedastic models may be appropriate for the series.

Long-range dependence, nonlinear trend, and breaks in historical sea surface and land air surface global and regional temperature anomalies

The global temperature series is a major indicator of climate change, whereas this indicator has undergone shift in trend over the twentieth century, changing from linear trend to nonlinear trend as a result of structural breaks. This paper investigates global and regional sea surface (SS) and land air surface (LS) temperature series from 1880 to 2016 by means of fractional integration technique. The results show that temperature series are described by trend stationary process, mostly in long memory range in the case of LS temperature while in the case of SS temperature, temperature series are in nonstationary mean reverting range for global and hemispheric temperature as well as for three other regional locations. By applying the multiple structural break test, the trend line is found breaking in many dates, locking up into many regimes which can be described using nonlinear trend structure. Nonlinear trend, based on Chebyshev inequality in the fractional integration framework, shows that global and regional temperature series can be represented using nonlinear trend up to the third order since this further lowers the integration order to long memory range in both SS and LS temperature series.

Time series analysis of quarterly rainfall and temperature (1900–2012) in sub-Saharan African countries

In this paper, we examine the statistical properties of rainfall data and temperature in six sub-Saharan African countries in the western, eastern, and southern regions (Botswana, Ethiopia, Ghana, Nigeria, Uganda, and South Africa) using time series data spanning between 1900 and 2012. By using linear trends, seasonality, and long-range dependence models, in fractional or I(d) frameworks, the results first indicate that time trends are required in most cases to explain the time series properties of the climatic series. Evidence of anti-persistence (d < 0) or I(0) behavior is found for the rainfall data, while long memory (d > 0) is found for the temperature data. Evidence of structural breaks are only found in the cases of Ethiopia, Ghana, and Uganda for the temperature data. With both series displaying significant evidence of seasonality and by working with the seasonally differenced data, the results show evidence of I(0) behavior or anti-persistence (d < 0) for the rainfall data but long memory (d > 0) for the temperature data. Testing the causality between the two variables, the results indicate evidence of causality in the two directions in all cases except for the case of the temperature on the rainfall in South Africa. The implication of the results obtained here is that erratic or constant rainfall is expected in Africa in the future while temperature is likely to continue to increase, and these subsequently lead to future warming experiences.

Socio-demographic correlates of volunteerism among undergraduate students at North-West University, South Africa

ABSTRACT This article reports on a study that used a sample of undergraduate students at the North-West University, Mafikeng Campus, South Africa, to examine the effect of selected sociodemographic factors on the participation of voluntary activities amongst youth who have been exposed to the country’s higher education system. Specifically, the binary logit regression model was employed to analyse the effects of sociodemographic factors, such as age, gender, race, ethnicity, religion, family structure, maternal education, family socioeconomic status, academic performance and respondents’ perception of the importance of volunteering on five voluntary activities. The study found that male, older, black African, and Afrikaans-speaking youth are more likely to be involved in voluntary activities. Moreover, higher parental education, regular church attendance and being a Protestant as opposed to being a Catholic are all positively associated with youth volunteering. The single most important factor with regard to youth volunteerism is their perception of the importance of volunteering, a finding which underscores the role of socialisation in youth volunteerism.

The global financial crisis: Testing For Fractional Cointegration Between The Us And Nigerian Stock Markets

ABSTRACT:As a result of the dependency of United States (US) on Nigerian oil exports, coupled with her greatest share in Nigerian foreign direct investment, the recent global financial crisis of 2008/09 which emanated from the country spilled over to the Nigerian capital market, affecting majorly the financial sectors. Since the period of the crisis, the interests of the researchers have been gingered towards studying the interdependencies in financial market series of nations that are trading partners, particularly in relation to technological advanced economies like the US and the United Kingdom. This paper examines the effects of the global financial crisis on the Nigerian stock market. We use daily US stocks (S&P500, Nasdaq and Dow Jones industrial stock indices) and All Share Index (ASI) of Nigerian Stock Exchange, testing for long run equilibrium relationships between the Nigerian ASI and each of the US indices. Apart from the initial nonstationarities displayed by the stock time series, plots of a US stock index and ASI also display the possibility of possible co-movement over time, particularly during the crisis period. That called for possible test for cointegration. However, instead of restricting ourselves to integer degrees of differentiation we allow for the possibility of fractional values. Thus, we test for fractional integration, and the results first indicate that the ASI and the three US stock indices display similar orders of integration, which are all very close to 1. Testing for fractional cointegration, we do not find any significant evidence of a long run equilibrium relationship between the two markets. The lack of fractional cointegration can be due to the presence of breaks in the data that have not been taken into account. This is something very plausible in the context of the global financial crisis. Also, the fact that long-run relationships do not exist between each of the US stocks and the Nigerian stock markets does not imply no contagion effect. Contagion effect may be as forms of returns, shocks or volatility between the US and Nigeria market. This finding therefore calls for alternative testing procedure, other than cointegration, in other to establish the influence of United States economy on the Nigerian capital market.