Government Expenditure and Economic Growth: Evidence from Trivariate Causality Testing

By J. Loizides, G. Vamvoukas. 2005

373 citations recorded by the source corpus.

This paper seeks to examine if the relative size of government (measured as the share of total expenditure in GNP can be determined to Granger cause the rate of economic growth, or if the rate of economic growth can be determined to Granger cause the relative size of government. For this purpose, we first use a bivariate error correction model within a Granger causality framework, as well as adding unemployment and inflation (separately) as explanatory variables, creating a simple ‘trivariate’ analysis for each of these two variables. The combined analysis of bivariate and trivariate tests offers a rich menu of possible causal patterns. Using data on Greece, UK and Ireland, the analysis shows: i) government size Granger causes economic growth in all countries of the sample in the short run and in the long run for Ireland and the UK; ii) economic growth Granger causes increases in the relative size of government in Greece, and, when inflation is included, in the UK.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/74eb9a4377c998cd4d5e4779b6ad8b9d26d21a04

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Citations in the corpus

Government Expenditure And Economic Growth In Nigeria, 1970-2008: A Disaggregated Analysis (2010, methodology): “[21] employed the trivariate causality test to examine the relationship between government expenditure and economic growth, using data set on Greece, United Kingdom and Ireland.”
Public Expenditure and Economic Growth: Evidence from the Developing Countries (2020, methodology): “Several research works have explored the effect of government expenditure on economic growth using various econometric tools and diverse measures of government spending (Chandran et al., 2011; Dogan & Tang, 2006; Ebaidalla, 2013; Loizides & Vamvoukas, 2005).”
Energy consumption, pollutant emissions and economic growth in South Africa (2010, methodology): “However, since a five-variable case incorporates more information than a bivariate case, the causal inference drawn may be relatively more reliable (Loizides and Vamvoukas, 2005). In this paper, tests for establishing the long-run relationship between the variables are carried out by using the coint”
Energy consumption and economic growth: The experience of African countries revisited (2009, background): “It is possible that the introduction of capital and labor in the causality framework may not only alter the direction of causality but also the magnitude of the estimates (Loizides and Vamvoukas, 2005; Odhiambo, 2008).”
Natural Gas Consumption and Economic Growth in Pakistan (2013, methodology): “This shortcoming can be overcomed by including capital and labour in the estimation to make the result more reliable (Loizides and Vamvoukas, [10]; Odhiambo, [27]).”
Nuclear energy consumption and economic growth in nine developed countries (2010, background): “Moreover, unlike Yoo and Ku (2009) we incorporated more information, and our causal inference may be relatively more reliable than their bivariate case (Loizides and Vamvoukas, 2005).”
Re-examining the financial development and economic growth nexus in Kenya (2009, background): “It is possible that the introduction of a third or a fourth variable in the causality framework may not only alter the direction of causality but also the magnitude of the estimates (Loizides and Vamvoukas, 2005; Odhiambo, 2008a).”
Nuclear energy consumption, oil prices, and economic growth: Evidence from highly industrialized countries (2011, background): “Loizides and Vamvoukas (2005) argue that the introduction of a third or a fourth variable in the causality test may change the direction of causality.”
The impact of tourism on income inequality in developing economies: Does Kuznets curve hypothesis exist? (2016, neutral): “It is possible that the introduction of a third or more variables in the regression framework may not only alter the direction of relationship but also the magnitude of the estimates (Loizides and Vamvoukas, 2005).”