An assessment of the growth and inequality causality relationship

Assane, Djeto; Grammy, Abbas P.

doi:10.1080/13504850310001635249

Cited by 14 publications

(14 citation statements)

References 7 publications

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“…The non-stationarity in levels of the inequality measure is also found in Assane & Grammy (2003) and Nath & Mamun (2004). 12 We then adjust the inequality variables by taking the first differences.…”

Section: Panel Unit Root Testsmentioning

confidence: 65%

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Military Spending and Inequality: Panel Granger Causality Test

Lin

Ali

2009

Journal of Peace Research

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The relationship between military spending and economic inequality is not well documented within the empirical literature, while numerous studies have uncovered the linkages between military spending and other macroeconomic variables, such as economic growth, unemployment, purchasing power parity, black market premium, poverty and investment. The purpose of this article is to examine the causal relationship between military spending and inequality using BVC and SIPRI data across 58 countries from 1987 to 1999. Panel unit root tests indicate that two inequality measures (Theil and EHII) under consideration are likely to be non-stationary. The authors' work addresses the adverse implications of modeling with non-stationary variables, since this omission casts serious doubt on the reliability of the relationship between military spending and inequality. The recent developed panel Granger non-causality tests provide no evidence to support the causal relationship in either direction between the military spending and the change in economic inequality. The results are consistently robust to alternative data sources for military spending, to alternative definitions of the inequality measures, to the log transformation of the military spending, to the deletion of some data points, and to the division of OECD and non-OECD countries. Finally, the impulse responses and variance decompositions based on the panel vector autoregressive regression model are consistent with the findings relied on Granger non-causality tests.

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Section: Panel Unit Root Testsmentioning

confidence: 65%

“…12 Assane & Grammy (2003) use U.S. annual data (1960 to determine the causal relationship between the growth and inequality. Nath & Mamun (2004) show that the EHII in levels are non-stationary in Bangladesh for the period from 1967 to 1992.…”

Section: Panel Unit Root Testsmentioning

confidence: 99%

Military Spending and Inequality: Panel Granger Causality Test

Lin

Ali

2009

Journal of Peace Research

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“…As is appreciated, causality runs from pcGDP to income inequality but not in the opposite direction. Applying multivariate cointegration analysis to US data, Assane and Grammy (2003) find that growth unidirectionally and significantly Granger causes inequality. According to Table 1, the best adjustment specification only includes one autoregressive term, because it has the smallest probability and also the greatest estimated coefficient, according to the Bayesian information criterion.…”

Section: Data Set Causality and Unit Root Testsmentioning

confidence: 98%

Cointegration with structural changes between per capita product and income inequality in Mexico

Germán–Soto

Cantú

2015

Applied Economics

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The long-run relationship between per capita product and income inequality in Mexico is assessed for the period 1963-2010. The methodology consists of stochastic unit root techniques with structural changes. The integration and cointegration tests suggest that it is not possible to understand this link if the possibility of structural changes is not taken into account. Causality, running from per capita product to income inequality, and a negative and significant overall effect are estimated. However, after the regime shifts -mainly estimated to occur in the 1980s -the connection is no longer meaningful. This result seems to be linked to the slow growth of the Mexican economy after these structural breaks, affecting, in turn, the reductions in income inequality.

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“…11 By using a different methodological approach, Assane and Grammy (2003) analyse the causal relationship between growth and inequality. 12 The Gini index is more sensitive to the changes in the centre of the distribution (Sen, 1997), while the Theil index, with the parameter c set to zero, is more sensitive to changes in the extremes (Shorrocks, 1980).…”

Section: Transfers Redistribution and Inequality Minimizationmentioning

confidence: 99%

Linear SAM models for inequality changes analysis: an application to the Extremadurian economy

Vélez

Mayo

2006

Applied Economics

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Social accounting matrices are adequate databases for the economic modelling. These matrices emphasize the role of households in the economy, and so, they usually disaggregate the household sector into several groups. This disaggregation allows social accounting matrices to be used for diverse income distribution analysis. The objective of this work is to use the linear SAM models to study how inequality is modified by several exogenous injections of income. The set of multipliers and indicators presented is applied to the economy of Extremadura - a region situated in the southwest of Spain. In particular, together with the accounting multipliers, two redistributed income matrices are presented to show how changes in final demand and in income transfers cause opposite effects in inequality. For contrasting these results, Gini and Theil indices are also used. Finally, a major reduction in both would result from an appropriate re-allocation of transfers.

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An assessment of the growth and inequality causality relationship

Abstract: Applying multivariate cointegration analysis to US data, we find growth unidirectionally and significantly Granger causes inequality.

Cited by 14 publications

References 7 publications

Military Spending and Inequality: Panel Granger Causality Test

Military Spending and Inequality: Panel Granger Causality Test

Cointegration with structural changes between per capita product and income inequality in Mexico

Linear SAM models for inequality changes analysis: an application to the Extremadurian economy

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