Search results for: Engle%20and%20Granger%20casualty%20test

Authors: Himayatullah Khan, Alena Fedorova

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The present paper analyses the income-consumption relationships in Pakistan using annual time series data from 1980-81 to 2010-1. The paper uses the Augmented Dickey-Fuller test to check the unit root and stationarity in these two time series. The paper finds that the two time series are nonstationary but stationary at their first difference levels. The Augmented Engle-Granger test and the Cointegrating Regression Durbin-Watson test imply that the two time series of consumption and income are cointegrated and that long-run marginal propensity to consume is 0.88 which is given by the estimated (static) equilibrium relation. The paper also used the error correction mechanism to find out to model dynamic relationship. The purpose of the ECM is to indicate the speed of adjustment from the short-run equilibrium to the long-run equilibrium state. The results show that MPC is equal to 0.93 and is highly significant. The coefficient of Engle-Granger residuals is negative but insignificant. Statistically, the equilibrium error term is zero, which suggests that consumption adjusts to changes in GDP in the same period. The short-run changes in GDP have a positive impact on short-run changes in consumption. The paper concludes that we may interpret 0.93 as the short-run MPC. The pair-wise Granger Causality test shows that both GDP and consumption Granger cause each other.

Keywords: cointegrating regression, Augmented Dickey Fuller test, Augmented Engle-Granger test, Granger causality, error correction mechanism

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Authors: Surayyo Shaamirova, Anwar Hasan Abdullah Othman

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This study investigates the co-integration association between the top 10 cryptocurrencies, namely Bitcoin, Ethereum, Ripple, Bitcoin Cash, EOS, Cardano, Litecoin, Stellar, IOTA, and NEO. The study applies Johansen Juselius co-integration test to examine the long-run co-integration and utilize the Engle and Granger casualty test to examine the short-run relationship. The findings of the study show that there is a strong co-integration relationship among the cryptocurrencies; however, in the short run, there is no causal relationship among the crypto currencies. These results, therefore, suggest that there are portfolio diversification opportunities in the cryptocurrencies industry when it comes to long run investment decisions, on the other hand, the cryptocurrencies industry shows the characteristics of efficiency in the short-run. This is an indication of a non-speculation investment in the cryptocurrencies industry in the short term investment.

Keywords: cryptocurrencies, Johansen-Juselius co-integration test, Engle and Granger casualty test, portfolio diversification

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Authors: Mesut BALIBEY, Serpil TÜRKYILMAZ

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A popular topic in the econometrics and time series area is the cointegrating relationships among the components of a nonstationary time series. Engle and Granger’s least squares method and Johansen’s conditional maximum likelihood method are the most widely-used methods to determine the relationships among variables. Furthermore, a method proposed to test a unit root based on the periodogram ordinates has certain advantages over conventional tests. Periodograms can be calculated without any model specification and the exact distribution under the assumption of a unit root is obtained. For higher order processes the distribution remains the same asymptotically. In this study, in order to indicate advantages over conventional test of periodograms, we are going to examine a possible relationship between tourism and economic growth during the period 1999:01-2010:12 for Turkey by using periodogram method, Johansen’s conditional maximum likelihood method, Engle and Granger’s ordinary least square method.

Keywords: cointegration, economic growth, periodogram ordinate, tourism

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Authors: Himayatullah Khan

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This study estimates supply response function of sugarcane in Pakistan from 1980-81 to 2012-13. The study uses co-integration approach and error correction mechanism. Sugarcane production, area and price series were tested for unit root using Augmented Dickey Fuller (ADF). The study found that these series were stationary at their first differenced level. Using the Augmented Engle-Granger test and Cointegrating Regression Durbin-Watson (CRDW) test, the study found that “production and price” and “area and price” were co-integrated suggesting that the two sets of time series had long-run or equilibrium relationship. The results of the error correction models for the two sets of series showed that there was disequilibrium in the short run there may be disequilibrium. The Engle-Granger residual may be thought of as the equilibrium error which can be used to tie the short-run behavior of the dependent variable to its long-run value. The Granger-Causality test results showed that log of price granger caused both the long of production and log of area whereas, the log of production and log of area Granger caused each other.

Keywords: co-integration, error correction mechanism, Granger-causality, sugarcane, supply response

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Authors: Pouneh Soleimaninejadian, Chengyu Yang

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In this paper, we use data on Household Income and Expenditure survey of Statistics Centre of Iran, conducted from 2005-2014, to calculate several inequality measures and to estimate the effects of Iran’s targeted subsidy reform act on consumption and income inequality. We first calculate Gini coefficients for income and consumption in order to study the relation between the two and also the effects of subsidy reform. Results show that consumption inequality has not been always mirroring changes in income inequality. However, both Gini coefficients indicate that subsidy reform caused improvement in inequality. Then we calculate Generalized Entropy Index based on consumption and income for years before and after the Subsidy Reform Act of 2010 in order to have a closer look into the changes in internal structure of inequality after subsidy reforms. We find that the improvement in income inequality is mostly caused by the decrease in inequality of lower income individuals. At the same time consumption inequality has been decreased as a result of more equal consumption in both lower and higher income groups. Moreover, the increase in Engle coefficient after the subsidy reform shows that a bigger portion of income is allocated to consumption on food which is a sign of lower living standard in general. This increase in Engle coefficient is due to rise in inflation rate and relative increase in price of food which partially is another consequence of subsidy reform. We have conducted some experiments on effect of subsidy payments and possible effects of change on distribution pattern and amount of cash subsidy payments on income inequality. Result of the effect of cash payments on income inequality shows that it leads to a definite decrease in income inequality and had a bigger share in improvement of rural areas compared to those of urban households. We also examine the possible effect of constant payments on the increasing income inequality for years after 2011. We conclude that reduction in value of payments as a result of inflation plays an important role regardless of the fact that there may be other reasons. We finally experiment with alternative allocations of transfers while keeping the total amount of cash transfers constant or make it smaller through eliminating three higher deciles from the cash payment program, the result shows that income equality would be improved significantly.

Keywords: consumption inequality, generalized entropy index, income inequality, Irans subsidy reform

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Authors: Calvin Rong, Regina Agassian, Joel Hernandez, Mindy Engle-Friedman

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This study assessed strategies to stimulate engagement with future environmental needs. 32 participants were randomly assigned to one of three conditions which involved imagining and drawing: 1) a generic person in current life, 2) one’s self in current life or 3) one’s self in the future. Participants before and after the intervention indicated connectedness to their selves 50 years in the future on an adapted Future Self-Continuity Scale. A significant interaction (p = .03) showed no difference in connectedness into one’s future self in the control group, a decrease in connectedness in those who imagined themselves in the present and an increase in connectedness in those who imagined themselves in the future. Results suggest attention to one’s present life circumstances may interfere with one’s connection with future environmental issues but imagining one’s future life may stimulate actions that result in future environmental protection.

Keywords: environmental psychology, future priming, climate change, global warming

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Authors: Abigail Mosetsanagape Mooketsi, Itumeleng Pleasure Mongale, Joel Hinaunye Eita

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The aim of this study is to analyse the impact of transport infrastructure on economic growth in South Africa through Engle Granger two step approach using the data from 1970 to 2013. GDP is used as a proxy for economic growth whilst rail transport (rail lines, rail goods transported) and air transport(air passengers carried, air freight) are used as proxies for transport infrastructure. The results showed that there is a positive long-run relationship between transport infrastructure and economic growth. The results show that South Africa’s economic growth can be boosted by providing transport infrastructure. The estimated models were simulated and the results that the model is a good fit. The findings of this research will be beneficial to policy makers, academics and it will also enhance the ability of the investors to make informed decisions about investing in South Africa.

Keywords: transport, infrastructure, economic growth, South Africa

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Authors: Piotr Fiszeder, Marcin Fałdziński, Peter Molnár

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The dynamic conditional correlation model of Engle (2002) is one of the most popular multivariate volatility models. However, this model is based solely on closing prices. It has been documented in the literature that the high and low price of the day can be used in an efficient volatility estimation. We, therefore, suggest a model which incorporates high and low prices into the dynamic conditional correlation framework. Empirical evaluation of this model is conducted on three datasets: currencies, stocks, and commodity exchange-traded funds. The utilisation of realized variances and covariances as proxies for true variances and covariances allows us to reach a strong conclusion that our model outperforms not only the standard dynamic conditional correlation model but also a competing range-based dynamic conditional correlation model.

Keywords: volatility, DCC model, high and low prices, range-based models, covariance forecasting

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Authors: El Andari Chifaa, Bouaziz Rached

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The central focus of this paper was to check whether the Okun’s law in Tunisia is valid or not. For this purpose, we have used quarterly time series data during the period 1990Q1-2014Q1. Firstly, we applied the error correction model instead of the difference version of Okun's Law, the Engle-Granger and Johansen test are employed to find out long run association between unemployment, production, and how error correction mechanism (ECM) is used for short run dynamic. Secondly, we used the gap version of Okun’s law where the estimation is done from three band pass filters which are mathematical tools used in macro-economic and especially in business cycles theory. The finding of the study indicates that the inverse relationship between unemployment and output is verified in the short and long term, and the Okun's law holds for the Tunisian economy, but with an Okun’s coefficient lower than required. Therefore, our empirical results have important implications for structural and cyclical policymakers in Tunisia to promote economic growth in a context of lower unemployment growth.

Keywords: Okun’s law, validity, unit root, cointegration, error correction model, bandpass filters

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Authors: Tanimola Kazeem Abiodun

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In the paper, attempt was made to investigate the impact of international trade on economic growth at the disaggregate level both from the theoretical and economic angle. The study in its contribution examines this impact at the disaggregated level. To this end, a hypothesis was formulated to investigate the short ?run and long run impact of international trade on growth in the country. In the econometrics investigation that follow, international trade was disaggregated to export and imports and their short run and long run effect on growth was examined. Also, the aggregate international trade was also investigated to see the long run effects of its own growth. The results of the findings indicate that; both export and import impact significantly to growth in the short run. The long-run impact of export on growth was found to be positive, significant and stable both. Engle-Granger co integration test and error correlation mechanism were applied to these long run relationships. For the import, while the short run was found to be positive and significant on its impact on growth, the long run relationship was found to be negative but not significant. Therefore, it is thus recommended among others that the country should engage more on export promotion drives.

Keywords: international trade, disaggregated, import, export, econometrics, trade, economic growth, foreign trade, import, export

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Authors: Abderrazek Ben Maatoug, Ibrahim Fatnassi, Wassim Ben Ayed

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In this paper we investigate the issue of market risk quantification for Middle East and North Africa (MENA) Islamic market equity. We use Value-at-Risk (VaR) as a measure of potential risk in Islamic stock market, for long and short position, based on Riskmetrics model and the conditional parametric ARCH class model volatility with normal, student and skewed student distribution. The sample consist of daily data for the 2006-2014 of 11 Islamic stock markets indices. We conduct Kupiec and Engle and Manganelli tests to evaluate the performance for each model. The main finding of our empirical results show that (i) the superior performance of VaR models based on the Student and skewed Student distribution, for the significance level of α=1% , for all Islamic stock market indices, and for both long and short trading positions (ii) Risk Metrics model, and VaR model based on conditional volatility with normal distribution provides the best accurate VaR estimations for both long and short trading positions for a significance level of α=5%.

Keywords: value-at-risk, risk management, islamic finance, GARCH models

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Authors: Abdelmounaim Lahrech, Hajar Bousfiha

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This paper examines equity market integration between Morocco and France and its consequent implications on international portfolio diversification. In the absence of stock market linkages, Morocco can act as a diversification destination to European investors, allowing higher returns at a comparable level of risk in developed markets. In contrast, this attractiveness is limited if both financial markets show significant linkage. The research empirically measures financial market’s integration in by capturing the conditional correlation between the two markets using the Generalized Autoregressive Conditionally Heteroscedastic (GARCH) model. Then, the research uses the Dynamic Conditional Correlation (DCC) model of Engle (2002) to track the correlations. The research findings show that there is no important increase over the years in the correlation between the Moroccan and the French equity markets, even though France is considered Morocco’s first trading partner. Failing to prove evidence of the stock index linkage between the two countries, the volatility series of each market were assumed to change over time separately. Yet, the study reveals that despite the important historical and economic linkages between Morocco and France, there is no evidence that equity markets follow. The small correlations and their stationarity over time show that over the 10 years studied, correlations were fluctuating around a stable mean with no significant change at their level. Different explanations can be attributed to the absence of market linkage between the two equity markets.

Keywords: equity market linkage, DCC GARCH, international portfolio diversification, Morocco, France

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Authors: Patricia M. B. Saint-Vincent, Anna Furches, Stephanie Galanie, Erica Teixeira Prates, Piet Jones, Nancy Engle, David Kainer, Wellington Muchero, Daniel Jacobson, Timothy J. Tschaplinski

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Uridine diphosphate-glycosyltransferases (UGTs) are enzymes that catalyze sugar transfer to a variety of plant metabolites. UGT substrates, which include plant secondary metabolites involved in lignification, demonstrate new activities and incorporation when glycosylated. Knowledge of UGT function, substrate specificity, and enzyme products is important for plant engineering efforts, especially related to increasing plant biomass through lignification. UGTs in Populus trichocarpa, a biofuel feedstock, and model woody plant, were selected from a pool of gene candidates using rapid prioritization strategies. A functional genomics workflow, consisting of a metabolite genome-wide association study (mGWAS), expression of synthetic codon-optimized genes, and high-throughput biochemical assays with mass spectrometry-based analysis, was developed for determining the substrates and products of previously-uncharacterized enzymes. A total of 40 UGTs from P. trichocarpa were profiled, and the biochemical assay results were compared to predicted mGWAS connections. Assay results confirmed seven of 11 leaf mGWAS associations and demonstrated varying levels of substrate specificity among candidate UGTs. P. trichocarpa UGT substrate processing confirms the role of these newly-characterized enzymes in lignan, flavonoid, and phytohormone metabolism, with potential implications for cell wall biosynthesis, nitrogen uptake, and biotic and abiotic stress responses.

Keywords: Populus, metabolite-gene associations, GWAS, bio feedstocks, glycosyltransferase

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Authors: Calvin Rong, Regina Agassian, Mindy Engle-Friedman

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Climate changes, including rising sea levels and increases in global temperature, can have major effects on resource availability, leading to increased competition for resources and rising food prices. The abstract nature and often delayed consequences of many ecological problems cause people focus on immediate, specific, and personal events and circumstances that compel immediate and emotional involvement. This finding may be explained by the challenges humans have in imagining themselves in the future, a shortcoming that interferes with decision-making involving far-off rewards, and leads people to indicate a lower concern toward the future than to present circumstances. The present study sought to assess whether priming people to think of themselves in the future might strengthen the connection to their future selves and stimulate environmentally-protective behavior. We hypothesize that priming participants to think about themselves in the future would increase concern for the future environment. 45 control participants were primed to think about themselves in the present, and 42 participants were primed to think about themselves in the futures. After priming, the participants rated their concern over access to clean water, food, and energy on a scale of 1 to 10. They also rated their predicted care levels for the environment at age points 40, 50, 60, 70, 80, and 90 on a scale of 1(not at all) to 10 (very much). Predicted care levels at age 90 for the experimental group was significantly higher than for the control group. Overall the experimental group rated their concern for resources higher than the control. In comparison to the control group (M=7.60, SD=2.104) participants in the experimental group had greater concern for clean water (M=8.56, SD=1.534). In comparison to the control group (M=7.49, SD=2.041) participants in the experimental group were more concerned about food resources (M=8.41, SD=1.830). In comparison to the control group (M=7.22, SD=1.999) participants in the experimental group were more concerned about energy resources (M=8.07, SD=1.967). This study assessed whether a priming strategy could be used to encourage pro-environmental practices that protect limited resources. Future-self priming helped participants see past short term issues and focus on concern for the future environment.

Keywords: climate change, future, priming, global warming

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Authors: Shay Kee Tan, Kok Haur Ng, Jennifer So-Kuen Chan

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This paper extends the conditional autoregressive range (CARR) model to multivariate CARR (MCARR) model and further to the two-stage MCARR-return model to model and forecast volatilities, correlations and returns of multiple financial assets. The first stage model fits the scaled realised Parkinson volatility measures using individual series and their pairwise sums of indices to the MCARR model to obtain in-sample estimates and forecasts of volatilities for these individual and pairwise sum series. Then covariances are calculated to construct the fitted variance-covariance matrix of returns which are imputed into the stage-two return model to capture the heteroskedasticity of assets’ returns. We investigate different choices of mean functions to describe the volatility dynamics. Empirical applications are based on the Standard and Poor 500, Dow Jones Industrial Average and Dow Jones United States Financial Service Indices. Results show that the stage-one MCARR models using asymmetric mean functions give better in-sample model fits than those based on symmetric mean functions. They also provide better out-of-sample volatility forecasts than those using CARR models based on two robust loss functions with the scaled realised open-to-close volatility measure as the proxy for the unobserved true volatility. We also find that the stage-two return models with constant means and multivariate Student-t errors give better in-sample fits than the Baba, Engle, Kraft, and Kroner type of generalized autoregressive conditional heteroskedasticity (BEKK-GARCH) models. The estimates and forecasts of value-at-risk (VaR) and conditional VaR based on the best MCARR-return models for each asset are provided and tested using Kupiec test to confirm the accuracy of the VaR forecasts.

Keywords: range-based volatility, correlation, multivariate CARR-return model, value-at-risk, conditional value-at-risk

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Authors: Huseyin Guler, Cigdem Kosar

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The aim of this study is to propose Bridge estimator for seasonal unit root tests. Seasonality is an important factor for many economic time series. Some variables may contain seasonal patterns and forecasts that ignore important seasonal patterns have a high variance. Therefore, it is very important to eliminate seasonality for seasonal macroeconomic data. There are some methods to eliminate the impacts of seasonality in time series. One of them is filtering the data. However, this method leads to undesired consequences in unit root tests, especially if the data is generated by a stochastic seasonal process. Another method to eliminate seasonality is using seasonal dummy variables. Some seasonal patterns may result from stationary seasonal processes, which are modelled using seasonal dummies but if there is a varying and changing seasonal pattern over time, so the seasonal process is non-stationary, deterministic seasonal dummies are inadequate to capture the seasonal process. It is not suitable to use seasonal dummies for modeling such seasonally nonstationary series. Instead of that, it is necessary to take seasonal difference if there are seasonal unit roots in the series. Different alternative methods are proposed in the literature to test seasonal unit roots, such as Dickey, Hazsa, Fuller (DHF) and Hylleberg, Engle, Granger, Yoo (HEGY) tests. HEGY test can be also used to test the seasonal unit root in different frequencies (monthly, quarterly, and semiannual). Another issue in unit root tests is the lag selection. Lagged dependent variables are added to the model in seasonal unit root tests as in the unit root tests to overcome the autocorrelation problem. In this case, it is necessary to choose the lag length and determine any deterministic components (i.e., a constant and trend) first, and then use the proper model to test for seasonal unit roots. However, this two-step procedure might lead size distortions and lack of power in seasonal unit root tests. Recent studies show that Bridge estimators are good in selecting optimal lag length while differentiating nonstationary versus stationary models for nonseasonal data. The advantage of this estimator is the elimination of the two-step nature of conventional unit root tests and this leads a gain in size and power. In this paper, the Bridge estimator is proposed to test seasonal unit roots in a HEGY model. A Monte-Carlo experiment is done to determine the efficiency of this approach and compare the size and power of this method with HEGY test. Since Bridge estimator performs well in model selection, our approach may lead to some gain in terms of size and power over HEGY test.

Keywords: bridge estimators, HEGY test, model selection, seasonal unit root

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Authors: O. E. Akinyemi, P. O. Alege, O. O. Ajayi, L. A. Amaghionyediwe, A. A. Ogundipe

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Nigeria as an oil-producing developing country in Africa is one of the many countries that had been subsidizing consumption of fossil fuel. Despite the numerous advantage of this policy ranging from increased energy access, fostering economic and industrial development, protecting the poor households from oil price shocks, political considerations, among others; they have been found to impose economic cost, wasteful, inefficient, create price distortions discourage investment in the energy sector and contribute to environmental pollution. These negative consequences coupled with the fact that the policy had not been very successful at achieving some of its stated objectives, led to a number of organisations and countries such as the Group of 7 (G7), World Bank, International Monetary Fund (IMF), International Energy Agency (IEA), Organisation for Economic Co-operation and Development (OECD), among others call for global effort towards reforming fossil fuel subsidies. This call became necessary in view of seeking ways to harmonise certain existing policies which may by design hamper current effort at tackling environmental concerns such as climate change. This is in addition to driving a green growth strategy and low carbon development in achieving sustainable development. The energy sector is identified to play a vital role. This study thus investigates the prospects of using fuel subsidy reform as a viable tool in driving an economy that de-emphasizes carbon growth in Nigeria. The method used is the Johansen and Engle-Granger two-step Co-integration procedure in order to investigate the existence or otherwise of a long-run equilibrium relationship for the period 1971 to 2011. Its theoretical framework is rooted in the Environmental Kuznet Curve (EKC) hypothesis. In developing three case scenarios (case of subsidy payment, no subsidy payment and effective subsidy), findings from the study supported evidence of a long run sustainable equilibrium model. Also, estimation results reflected that the first and the second scenario do not significantly influence the indicator of environmental quality. The implication of this is that in reforming fuel subsidy to drive environmental quality for an economy like Nigeria, strong and effective regulatory framework (measure that was interacted with fuel subsidy to yield effective subsidy) is essential.

Keywords: environmental quality, fuel subsidy, green growth, low carbon growth strategy

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Authors: Adeola Adenikinju, Olusanya E. Olubusoye, Lateef O. Akinpelu, Dilinna L. Nwobi

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Since the enactment of the Fiscal Responsibility Act (2007), the Federal Government of Nigeria (FGN) has made public its fiscal budget and the subsequent implementation report. A critical review of these documents shows significant variations in the five macroeconomic variables which are inputs in each Presidential budget; oil Production target (mbpd), oil price ($), Foreign exchange rate(N/$), and Gross Domestic Product growth rate (%) and inflation rate (%). This results in underperformance of the Federal budget expected output in terms of non-oil and oil revenue aggregates. This paper evaluates first the existing variance between budgeted and actuals, then the relationship and causality between the determinants of Federal fiscal budget assumptions, and finally the determinants of FGN’s Gross Oil Revenue. The paper employed the use of descriptive statistics, the Autoregressive distributed lag (ARDL) model, and a Profit oil probabilistic model to achieve these objectives. This model permits for both the static and dynamic effect(s) of the independent variable(s) on the dependent variable, unlike a static model that accounts for static or fixed effect(s) only. It offers a technique for checking the existence of a long-run relationship between variables, unlike other tests of cointegration, such as the Engle-Granger and Johansen tests, which consider only non-stationary series that are integrated of the same order. Finally, even with small sample size, the ARDL model is known to generate a valid result, for it is the dependent variable and is the explanatory variable. The results showed that there is a long-run relationship between oil revenue as a proxy for budget performance and its determinants; oil price, produced oil quantity, and foreign exchange rate. There is a short-run relationship between oil revenue and its determinants; oil price, produced oil quantity, and foreign exchange rate. There is a long-run relationship between non-oil revenue and its determinants; inflation rate, GDP growth rate, and foreign exchange rate. The grangers’ causality test results show that there is a mono-directional causality between oil revenue and its determinants. The Federal budget assumptions only explain 68% of oil revenue and 62% of non-oil revenue. There is a mono-directional causality between non-oil revenue and its determinants. The Profit oil Model describes production sharing contracts, joint ventures, and modified carrying arrangements as the greatest contributors to FGN’s gross oil revenue. This provides empirical justification for the selected macroeconomic variables used in the Federal budget design and performance evaluation. The research recommends other variables, debt and money supply, be included in the Federal budget design to explain the Federal budget revenue performance further.

Keywords: ARDL, budget performance, oil price, oil quantity, oil revenue

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