Identifying terms of trade shocks in a developing country using a sign restrictions approach

ABSTRACT

Using annual data for Botswana from 1960 to 2012, we examine the responses of macroeconomic variables to four generalized positive terms of trade shocks – global demand, globalizing, sector-specific and global supply. A sign-restricted structural vector autoregression model with a penalty function is estimated to identify the four possible shocks. While positive global demand and globalization shocks are both expansionary, they have opposite effects on inflation. A positive commodity market specific shock dampens real GDP growth and is inflationary, suggesting a possible Dutch disease response. A negative global supply shock suppresses both output growth and inflation. All but the last shock leads to a significant declining interest rate. Monetary policy contraction is recommended for the first shock and expansion for the others.

KEYWORDS:

• Terms of trade shocks
• SVAR models
• sign restrictions
• penalty function
• developing country

JEL CLASSIFICATION:

• C32
• E52
• F41

Acknowledgement

We would like to thank the Editor and an anonymous referee for very helpful comments and suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ Interestingly, while clearly bothersome, terms of trade shocks tend to be relatively short-lived for some developing countries (Cashin, McDermott, and Pattillo 2004), and longer lived for others.

² This implies that ${\epsilon }_t=B_0{e}_t$. If $P=B_0^{-1}$ so that, $e_t=P{\epsilon }_t$, then $V=PE(\epsilon {\epsilon }^{\prime })P^{\prime }=P\mathrm{\Sigma }{P}^{\prime }$. This is the identification problem for the SVAR methodology.