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What is Granger Causality

Chapter 1
Handbook of Research on Global Enterprise Operations and Opportunities
Granger causality is a statistical concept of causality that is based on prediction. According to Granger causality, if a signal X 1 “Granger-causes” (or “G-causes”) a signal X 2 , then past values of X 1 should contain information that helps predict X 2 above and beyond the information contained in past values of X 2 alone. Its mathematical formulation is based on linear regression modeling of stochastic processes.
Published in Chapter:
Re-Examining the Impact of Financial System on Economic Growth: New Evidence From Heterogeneous Regional Panels
Bülent Altay (Afyon Kocatepe University, Turkey) and Mert Topcu (Nevşehir Hacı Bektaş Veli University, Turkey)
Copyright: © 2017 |Pages: 16
DOI: 10.4018/978-1-5225-2245-4.ch001
Abstract
Recent developments in panel data econometrics allow researchers to estimate heterogeneous parameters. Given this novelty, the goal of this paper is to revisit the financial development-economic growth nexus for a panel of 76 developing counties using recent heterogeneous panel time series estimation methods. Findings indicate that results are very volatile across different empirical specifications. Overall, results provide a strong support of a negative impact that banking development on growth. At regional level, however, there is relatively little evidence of such relationship. On the side of the stock market, there is no much indication in favor of stock market-led growth hypothesis either at pooled panel or at regional level.
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Chapter 22
Granger Causality: Its Foundation and Applications in Systems Biology
A technique for determining whether one time series is the cause of another one.
Published in Chapter: Granger Causality: Its Foundation and Applications in Systems Biology; From: Handbook of Research on Computational and Systems Biology: Interdisciplinary Applications
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Chapter 1
Oil Prices and Economic Growth in Major Emerging Economies: Evidence From Asymmetric Frequency Domain Causality Tests
A way to investigate causality between two variables in a time series. The method is a probabilistic account of causality; it uses empirical data to find patterns of correlation.
Published in Chapter: Oil Prices and Economic Growth in Major Emerging Economies: Evidence From Asymmetric Frequency Domain Causality Tests; From: Applied Econometric Analysis: Emerging Research and Opportunities
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Chapter 15
The COVID-19 Pandemic and Agricultural Futures in the USA: Evidence From a Dynamic Fourier Quantile Causality Test
It is a statistical hypothesis test that is developed for determining whether one series is useful in forecasting another or not.
Published in Chapter: The COVID-19 Pandemic and Agricultural Futures in the USA: Evidence From a Dynamic Fourier Quantile Causality Test; From: Technological Development and Impact on Economic and Environmental Sustainability
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Chapter 9
Interplays Among Railway Investment, Revenue, and GDP in India: An Empirical Study
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Chapter 17
Major Macroeconomic Dynamics for Labor Market in Turkey: A Causality Analysis
The Granger causality test is a statistical hypothesis test for determining whether one time series is useful in forecasting another, first proposed in 1969. The intuition behind the Granger causality test is the quite straightforward. Ordinarily, regressions reflect “mere” correlations, but C. Granger argued that causality in economics could be tested for by measuring the ability to predict the future values of a time series using prior values of another time series.
Published in Chapter: Major Macroeconomic Dynamics for Labor Market in Turkey: A Causality Analysis; From: Handbook of Research on Unemployment and Labor Market Sustainability in the Era of Globalization
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Chapter 4
Does Contagion Effect of Bubbles and Causality Exist Among Bitcoin, Gold, and Oil Markets?
Briefly, it shows the relationship of cause and effect between underlying variables. Broadly speaking, however, it is a statistical hypothesis test for determining whether using one variable's current information increases the prediction probability of the future value of another variable.
Published in Chapter: Does Contagion Effect of Bubbles and Causality Exist Among Bitcoin, Gold, and Oil Markets?; From: Global Risk and Contingency Management Research in Times of Crisis
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