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  Issue 14 | Archive Feb 2013

Is Policy Instability Priced in International Equity Markets?

A paper by Lam Swee Sum (National University of Singapore) and Weina Zhang (National University of Singapore)

RMI affiliated researcher Dr. Weina Zhang, in collaboration with her co-author A/P Lam Swee Sum, both from the Department of Finance at the National University of Singapore, test whether policy instability is priced in international equity markets. Policy instability refers to a non-zero probability that existing policies may be changed. Using a recent empirical measure of policy instability from Baker, Bloom and Davis (2011) that counts the total number of policy changes in the U.S, they find that this is only significantly priced in U.S returns. It has little explanatory power for international data. The insignificance of the policy instability measure has two explanations. First, policy instability does not matter with the exception of the U.S. Secondly, the empirical construct is inadequate in an international setting. They evaluate the latter explanation and find support for the view.

They propose two new risk factors based on the ratings from international country risk guide to capture two sources of policy instability, one due to frequent government changes and the other due to the inability of a country’s bureaucracy to absorb shocks in policy changes. The first risk factor related to policy instability is named as GOVLMH, which compensates for the countries with more frequent political power shifts in equity returns. The second policy instability risk factor is named as BURLMH, which compensates for the countries with poor bureaucracy to reduce policy changes as a result of political power shifts. The two proxies of policy instability risk factors have been found to significantly affect both the time series and cross section of equity returns in the sample of 49 countries from 1995 to 2006. On average, a one-standard deviation increase in the GOVLMH factor leads to an additional return of 8% per year and the same increase in the BURLMH factor results in an additional annual return of 27%. The bureaucracy factor is also significantly priced in the cross section of returns with an annual risk premium of 8%.

Across different countries, they find significant variations in the return exposures to the two factors. In a politically stable country such as China (with negative exposure to the GOVLMH factor), the exposure to the BURLMH factor is significantly positive. In a country with high bureaucracy quality such as Belgium, France, Portugal and Switzerland (with negative exposure to the BURLMH factor), the exposure to the GOVLMH is significantly positive. It is interesting to note that none of the 49 countries in the sample has negative exposures to both factors whereas many countries have significantly positive exposures to both factors (e.g., Chile, Czech Republic, Hungary, Korea, Pakistan, Poland, and Sri Lanka). This result implies that none of the countries can be used as a perfect hedging instrument for both types of policy instability.

They also find that the importance of the two factors depends on the country’s economic and institutional conditions. In developed countries, the equity returns are more exposed to the GOVLMH factor rather than the BURLMH factor and in developing countries, the results are the opposite. Similar contrasting results are also found in the countries with high democratic accountability scores in contrast to those with low scores. High democratic accountability signifies a political system in which the government is highly accountable to the public and vice versa. These results are consistent with the understanding that in a developed and highly democratic accountable country, the investors may perceive that the major source of policy instability is due to the instability of the government because the bureaucracy would have matured with sophistication and quality. On the other hand, in a developing country or a low democratic accountable country, since the government is expected to be unstable, investors will demand additional compensation if the bureaucracy is incapable in reducing the instability related to policymaking.

Using a more straight-forward technique such as principal component analysis, they show that the bureaucracy factor rewards the countries with better socio-economic development and more economic freedom whereas the government stability factor rewards the countries with better stock market performance among all well-known country factors. This result again confirms that the two types of policy instability are very different from each other. Specifically, they examine more than 20 other country-level variables such as GDP growth, inflation rate, legal origins, economic risk, financial risk, the usage of bank financing, stock market development, bond market development, tax factors, and national cultures. The horse-race between the two policy instability risk factors and other country-level factors continues to support the economical and statistical significance of the policy instability risk.

Further explorations reveal that the equity market has not fully priced in the policy instability risk. In predictive tests, they find that the bureaucracy factor can predict future equity returns after controlling for all the existing risk factors. The underpricing of the policy instability risk can be potentially explored by some institutional investors with low transaction costs.

Overall, their findings provide two implications. First, the findings are consistent with theories such as Pastor and Veronesi (2012) that policy uncertainty is systematically priced. International investors should take such risk into consideration. Second, given that the strength of bureaucracy machinery is sometimes more important than the stability of government, it is useful for a government to commit to building a strong and autonomous bureaucracy machinery. In doing so, the country can still be an attractive investment destination even if the government were to become unstable.

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Published quarterly by Risk Management Institute, NUS
Editor: Ivy Wang (rmiwy@nus.edu.sg)