On the Link between Volatility and Growth: A Spatial Econometrics Approach

Abstract

This paper examines the link between macro volatility and economic growth in the lens of spatial econometrics. We present an unconstrained spatial Durbin Ramey-Ramey model. We test the extended model in a panel of 78 countries to investigate all the possible dimensions along which spatial interactions can affect the link between macro volatility and growth. In contrast to previous literature, we split the effects of volatility on growth into direct and indirect effects using partial derivative impacts approach. We found that both the direct and indirect effects of volatility on growth are negative; the latter effect suggesting the transmission of volatility shocks to neighbouring countries. Growth rates observed in neighbouring countries has a positive effect on growth rate of a particular country.

Du lien entre volatilité et croissance: une méthode d’économétrie spatiale

Résuméla présente communication examine le lien entre la macro-volatilité et la croissance économique dans l’optique de l’économétrie spatiale. Nous présentons un modèle spatial sans contrainte de Durbin Ramey-Ramey. Nous soumettons le modèle élargi à un groupe de 78 pays pour examiner toutes les dimensions possibles conjointement avec des interactions spatiales pouvant affecter le lien entre la macro-volatilité et la croissance. Contrairement à des recherches précédentes, nous subdivisons les effets de la volatilité sur la croissance entre effets directs et indirects, en adoptant une méthode d’impacts à dérivée partielle. Nous relevons que les effets tant directs qu’indirects de la volatilité sur la croissance sont négatifs, dans le deuxième cas, l’effet pouvant indiquer une transmission de chocs de volatilité à des pays avoisinants. Les taux de croissance observés dans des pays voisins a un effet positif sur le taux de croissance d’un certain pays.

Sobre la interrelación entre la volatilidad y el crecimiento: un enfoque econométrico espacial

Resumeneste estudio analiza la interrelación entre la macrovolatilidad y el crecimiento económico bajo una perspectiva econométrica espacial. Presentamos un modelo espacial no limitado de Durbin Ramey-Ramey. Probamos el modelo ampliado en un panel de 78 países para investigar todas las dimensiones posibles junto con las interacciones espaciales que pueden afectar la interrelación entre la macrovolatilidad y el crecimiento. En contraste con los estudios anteriores, dividimos los efectos de la volatilidad sobre el crecimiento en efectos directos e indirectos utilizando el enfoque de los efectos derivados parciales. Hemos encontrado que los efectos directos e indirectos de la volatilidad sobre el crecimiento son negativos y en el caso de los indirectos, se sugiere que la transmisión de la volatilidad afecta a los países vecinos. Las tasas de crecimiento observadas en los países vecinos tienen un efecto sobre la tasa de crecimiento de un país en particular.

波动性与增长的关联：一个空间计量经济学方法

摘要 ：本文从计量 经济学的视角审视了宏观波动性与经济增长之间的关联。我们提出了一个无约束空间 Durbin Ramey-Ramey 模型。我们在 78 个国家进行了这项扩展模型试验，以调查所有可能对宏观波动性与增长之间的关联产生影响的空间交互作用维度。与以往的文献不同，我们用偏导 数影响分析法将波动性对增长产生的效应分成直接效应和间接效应两类。我们发现，波动性对增长产生的直接效应和间接效应都是负面的；间接效应表明波动性震荡 会向周边国家传播。在周边国家观察到的增长率则对某一特定国家的增长率有着积极的影响。

Keywords:

• Spatial effects
• volatility
• growth
• spatial Durbin model

JEL classification:

• C31
• F41
• O40

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. See, for example, Asgharian et al. (2012) and Dewachter et al. (2012) for motivation and an application of bilateral spatial trade weight matrix.

2. Note that we allow v ² to vary both across countries and over time later in Section 4 when we introduce country-specific and time period fixed effects.

3. See also LeSage & Fischer (2008) and Elhorst et al. (2010) for a recent SDM specification of the Solow-Swan growth model.

4. Neighbour here refers economic neighbourhood not necessarily the mere geographical closeness.

5. Note that volatility is measured as the standard deviation of growth in the simple cross-sectional specification. In the panel data framework as in equations (1) and (2), volatility is measured as the standard deviation of the residuals of the growth equation. See Dejuan & Gurr (2006), Dawson & Stephenson (1997) and Ramey & Ramey (1995) for details. Whereas the measure of volatility as the standard deviation of growth is sometimes called the unconditional volatility of growth, the measure of volatility as the standard deviation of the residuals of the growth equation is called conditional volatility of growth. Unless otherwise stated, volatility in this paper refers the latter definition.

6. See Appendix C for general procedures and Greene (2011) for proofs and details on the two-step maximum likelihood estimation.

7. For technical details on LM tests, see Anselin et al. (1996).

8. Note that Ramey & Ramey (1995) use similar procedure (at least partially) in their model, see their footnotes associated with Table A3 in Appendix A. As indicated in footnote 6, Greene (2011) presents detailed proofs and motivations for adopting the two-step estimation procedure.

9. The great-circle distance, the shortest distance between any two points is computed as:

10. There could be different sources of volatility, taxes, for example, see Posch & Wälde (2011).