Abstract
Business cycles in emerging markets are characterized by several features that seem difficult to reconcile with consumption smoothing, such as volatile consumption and strongly countercyclical current accounts. Although there are several alternative approaches trying to explain business cycles in emerging markets by modeling different shocks and transmission mechanisms, there is little direct evidence about exogenous shocks and their transmission in emerging markets. Using a newly constructed dataset on disaster events, I test how emerging markets respond to actual exogenous shocks in a dynamic panel distributed lag model. This approach allows me to identify the dynamic effects of shocks on macroeconomic variables while controlling for unobserved global shocks, unobserved time invariant characteristics of different countries and the possible serial correlations in macroeconomic aggregates. My results show that political shocks and terrorist attacks can drive business cycles in emerging markets, having a significant and long-lasting negative effect on output and the domestic components of aggregate absorption. I also test whether savings, investments and the current account respond to these shocks as suggested by forward-looking models.
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Notes
This dataset also collects information on natural disasters, however I chose not to include them in the main analysis. One reason is that natural disasters, contrary to political shocks and terrorist attacks, do not typically have significant consequences on the macroeconomy, on macroeconomic policy or on expectations about the future. Numerous other studies have examined the effects of natural disasters, see for example Cavallo et al. (2013).
In this respect, the shocks I study in this paper are similar to news shocks, such as anticipated productivity shocks that affect only future expectations. When a shock affects not only future expectations but also current macroeconomic quantities, the predictions of intertemporal models for savings and the current account are more subtle.
Fuchs-Schuendeln and Hassan (2015) survey a growing literature that use natural experiments to establish causal effects in macroeconomics.
Here pol refers to both revolution and coup. Note that although the study of natural disaster is not the focus of this paper, however, given the data availability, they are still used as control variables.
Previous research (Judson and Owen 1996) has shown that with a time dimension around 30, a “restricted GMM estimator” that uses a subset of the lagged dependent variables as instruments increases computational efficiency without significantly losing its effectiveness. Therefore I also use an alternative specification that employs the Anderson - Hsiao first-difference IV estimator and find results are qualitatively similar. The alternative IV estimates are available upon request.
In the literature of lag selection in distributed lag models, there are in general three different criteria one can follow: joint hypothesis testing, AIC and BIC. Both AIC and BIC results suggest the longer lag the better fits. However, because longer lags suffer from a loss of degrees of freedom, I consider the maximum lag to be q = 10. In Section 5.5, I show that the results are quantitatively similar to the baseline results using a larger q.
Cross-sectional dependence is likely to occur because of spillovers among countries in the presence of common global (unobserved) factors.
Political shocks and terrorist attacks are found to have significant effects on the macroeconomy, in terms of their output loss, consumption loss, and current account adjustments, etc. However, due to the different nature of natural disasters, they seem to have only insignificant macroeconomic effects in our sample and therefore I do not include them in the main discussion. Instead I will discuss the results separately in Section 5.6.
As mentioned above, in this respect terrorist attacks and political shocks seem similar to news shocks, such as anticipated productivity shocks that affect only future expectations. When a shock affects not only future expectations but also current macroeconomic quantities, the predictions of intertemporal models for savings and the current account are ambiguous and depend on the nature of the shocks.
KAOPEN is based on the binary dummy variables that codify the tabulation of restrictions on cross-border financial transactions reported in the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions. As noted by Chinn and Ito (2008), their index, by the nature of its construction, is a de jure measure of financial openness, as it attempts to measure regulatory restrictions on capital account transactions. Hence, it differs from price-based (interest rate parity approach) de facto measures of financial openness.
For example, one may expect that political movement that overthrows a corrupt and dictatorial regime and that replaces it by a democracy may have a positive effect on the macroeconomy. Other political shocks, by contrast can be detrimental to economic activity (e.g. a communist revolution). I thank the referee for this suggestion.
The exact definition of each type of political events is defined in Section 2 along with a statistical summary of the incidence and scale.
Investment drops significantly on impact and returns to its pre-shock level only after more than two decades. Similarly consumption falls by 8% on impact and remains significantly below its pre-shock level for 20 years.
This dataset also collects information on natural disasters, however I chose not to include them in the main analysis. One reason is that natural disasters, contrary to political shocks and terrorist attacks, do not typically have significant consequences on the macroeconomy, on macroeconomic policy or on expectations about the future. Numerous other studies have examined the effects of natural disasters, see for example Cavallo et al. (2013).
In this respect, the shocks I study in this paper are similar to news shocks, such as anticipated productivity shocks that affect only future expectations. When a shock affects not only future expectations but also current macroeconomic quantities, the predictions of intertemporal models for savings and the current account are more subtle.
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The author thanks the Associate Editor at Open Economies Review for his/her insightful comments and suggestions. The author also thanks seminar participants at Williams College.
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Appendix: Additional Figures and Tables
Appendix: Additional Figures and Tables
The effect of natural disasters
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Wang, Y. How Do Emerging Markets Respond to Macroeconomic Shocks? - Dynamic Panel Evidence on the Effects of Disasters. Open Econ Rev 28, 731–760 (2017). https://doi.org/10.1007/s11079-017-9440-5
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DOI: https://doi.org/10.1007/s11079-017-9440-5