Variable-lag Granger Causality for Time Series Analysis

Granger causality is a fundamental technique for causal inference in time series data, commonly used in the social and biological sciences. Typical operationalizations of Granger causality make a strong assumption that every time point of the effect time series is influenced by a combination of other time series with a fixed time delay. However, the assumption of the fixed time delay does not hold in many applications, such as collective behavior, financial markets, and many natural phenomena. To address this issue, we develop variable-lag Granger causality, a generalization of Granger causality that relaxes the assumption of the fixed time delay and allows causes to influence effects with arbitrary time delays. In addition, we propose a method for inferring variable-lag Granger causality relations. We demonstrate our approach on an application for studying coordinated collective behavior and show that it performs better than several existing methods in both simulated and real-world datasets. Our approach can be applied in any domain of time series analysis.Comment: This paper will be appeared in the proceeding of 2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA). The R package is available at https://github.com/DarkEyes/VLTimeSeriesCausalit

Pengujian Kausalitas antara Variabel Makroekonomi dengan Return Pasar di Bursa Efek Indonesia : sebuah Pendekatan Vector Auto

Indicators of macroeconomic have major impact on capital markets in general and stocks in particular. Influence of these indicators can be positive or negative. Vector Auto Regression (VAR) is a method of analysis used to predict the time series variable and analyze the dynamic impact factor interference in a system variable. VAR analysis is very useful to assess the linkages between economic variables. This research aims to see the influence of iIndicators of macroeconomic such as the exchange rate (EXCHANGE), interest rate Bank Central of Indonesia Certificates (SBI) and rate of inflation (INFLATION) to market return (REIHSG) in Indonesian Stock Exchange in the period 2004:1-2011:10. Data obtained from the Monthly Stock Price Index Statistics JSX. This research appllying several stages of testing as follows: unit root test, the optimal lag test, Granger causality test and Vector Auto Regression model (VAR). The results of unit root test in this study suggests that the data used for processing in the first degree and VAR Granger test because only the stationary stock index return variable in zero degree (level). On the test results suggested the optimal lag is the lag 3. On the Granger causality test is known that the Granger test variable rate (EXCHANGE) has a one-way impact or the exchange rate (EXCHANGE) affect market return (REIHSG) interest rate of Bank Central of Indonesia Certificates (SBI) and the rate of inflation (INFLATION) has a two direction or impact mutual Causality. These results indicate that there is a weak Granger causality between interest rates Bank Central of Indonesia Certificates (SBI) and rate of inflation (INFLATION) to market return (REIHSG)

PENGUJIAN KAUSALITAS ANTARA VARIABEL MAKROEKONOMI DENGAN RETURN PASAR DI BURSA EFEK INDONESIA : SEBUAH PENDEKATAN VECTOR AUTO

Indicators of macroeconomic have major impact on capital markets in general and stocks in particular. Influence of these indicators can be positive or negative. Vector Auto Regression (VAR) is a method of analysis used to predict the time series variable and analyze the dynamic impact factor interference in a system variable. VAR analysis is very useful to assess the linkages between economic variables. This research aims to see the influence of iIndicators of macroeconomic such as the exchange rate (EXCHANGE), interest rate Bank Central of Indonesia Certificates (SBI) and rate of inflation (INFLATION) to market return (REIHSG) in Indonesian Stock Exchange in the period 2004:1-2011:10. Data obtained from the Monthly Stock Price Index Statistics JSX. This research appllying several stages of testing as follows: unit root test, the optimal lag test, Granger causality test and Vector Auto Regression model (VAR). The results of unit root test in this study suggests that the data used for processing in the first degree and VAR Granger test because only the stationary stock index return variable in zero degree (level). On the test results suggested the optimal lag is the lag 3. On the Granger causality test is known that the Granger test variable rate (EXCHANGE) has a one-way impact or the exchange rate (EXCHANGE) affect market return (REIHSG) interest rate of Bank Central of Indonesia Certificates (SBI) and the rate of inflation (INFLATION) has a two direction or impact mutual Causality. These results indicate that there is a weak Granger causality between interest rates Bank Central of Indonesia Certificates (SBI) and rate of inflation (INFLATION) to market return (REIHSG).Keywords: Vector Auto Regressive (VAR), Macroeconomic, Granger Causality, IHSG stock retur

A multivariate analysis of savings, investment and growth in Nepal

This paper examines the relationship between the gross domestic savings, investment and growth for Nepal using annual time series data for the period of 1974/75 to 2009/10. The study employs the Autoregressive Distributed Lag (ARDL) approach to test for cointegration and Error correction based Granger causality analysis for exploring the causality between the variables. Empirical results show that there exist cointegration between gross domestic savings, investment and gross domestic product when each of these is taken as dependent variable. Granger causality analysis shows that there exists short-run bidirectional causality between investment and gross domestic product as well as between gross domestic savings and investment. Nevertheless, no short-run causality is found between gross domestic savings and gross domestic product. Thus, the policy of accelerating growth by promoting investment works to some extant only since the long-run investment multiplier is below one

A multivariate analysis of savings, investment and growth in Nepal

This paper examines the relationship between the gross domestic savings, investment and growth for Nepal using annual time series data for the period of 1974/75 to 2009/10. The study employs the Autoregressive Distributed Lag (ARDL) approach to test for cointegration and Error correction based Granger causality analysis for exploring the causality between the variables. Empirical results show that there exist cointegration between gross domestic savings, investment and gross domestic product when each of these is taken as dependent variable. Granger causality analysis shows that there exists short-run bidirectional causality between investment and gross domestic product as well as between gross domestic savings and investment. Nevertheless, no short-run causality is found between gross domestic savings and gross domestic product. Thus, the policy of accelerating growth by promoting investment works to some extant only since the long-run investment multiplier is below one

The Impact of Income Inequality, Environmental Degradation and Globalization on Life Expectancy in Pakistan: An Empirical Analysis

This study has investigated the impact of income inequality, globalization and environmental degradation on life expectancy in Pakistan. The study uses time series data for the period 1980-2015 for empirical analysis. Augmented Dickey-Fuller (ADF) and Phillip and Perron (PP) unit root tests are employed for examining the order of integration of the variables. Auto-Regressive Distributed Lag (ARDL) approach is used for investigating the cointegration among the variables of the model. For examining the causal relationship Granger Causality test is used. The results of the study reveal that income inequality and environmental degradation have negative and significant impact on life expectancy in Pakistan. On the other hand globalization have positive and significant impact on life expectancy in Pakistan. The results of Granger causality show that there is unidirectional causality running from all independent variables to dependent variable

Analisis Strategi Pemanfaatan Limbah Tanaman Pangan Sebagai Pakan Ruminansia Di Sulawesi Selatan

Vector Auto Regression (VAR) is an analysis or statistic method which can be used to predict time series variable and to analyst dynamic impact of disturbance factor in the variable system. In addition, VAR analysis is very useful to assess the interrelationship between economic variables. This research through the following test phases: unit root test, test of hypothesis, Granger causality test, and form a vector autoregresion model (VAR). The data used in this research is the GDP data and budget data of South Sulawesi in the period 1985-2004. The research aims to analyze the interrelationship between public expenditure and economic growth in South Sulawesi. The result showed statistically significant in economic growth (PDRB) influence public expenditure (APBD), however, not vice versa. Otherwise, for the need of APBD prediction, the used of lag 4 was the optimum model based on the causal relationship to PDRB

Does Government Expenditure on Education Promote Economic Growth? An Econometric Analysis

Education being an important component of human capital has always attracted the interests of economists, researchers and policy makers. Governments across the globe in general and in India in particular are trying to improve the human capital by pumping more investments in education. But the issue that whether improved level of education resulting from more education spending can promote economic growth is still controversial. Some economists and researchers have supported the bi-directional relation between these two variables, while it has also been suggested that it is the economic growth that stimulates governments spend more on education, not the other way. Considering this research issue, the present paper uses linear and non-linear Granger Causality methods to determine the causal relationship between education spending and economic growth in India for the period 1951-2009. The findings of this paper indicate that economic growth affects the level of government spending on education irrespective of any lag effects, but investments in education also tend to influence economic growth after some time-lag. The results are particularly useful in theoretical and empirical research by economists, regulators and policy makers