Assigning responsibility
According to the literature, there are basically two ways of assigning responsibility: internal (in-house) responsibility, to individuals or groups within the firm; or external, using other institutions to assess political risk. The literature points to the various deficiencies of relying on external bodies: (a) the differences in how various exte rnal assessors define political risk, leading to different assessment results (Alon and Martin, 1998); (b) the reliance of risk assessment models used by external assessors on historical data when there are good reasons to think such data will not predict future risk (De La Torre and Neckar, 1988); (c) the particular, specialised focus of external institutions; for example, a concentration on creditworthiness, while ignoring other risks (Alon and Martin, 1998); and lastly (d), the external assessors provide general assessment that does not necessarily take account of the specific characteristics of the investor and the situations they encounter (Pahud de Mortanges and Allers, 1996).
As a result of these deficiencies, coupled with increased investment abroad (Alon and Martin, 1998), many firms are said to be carrying out in-house assessment of political risk. According to Blank et al. (1980), in order for the international firms to be classified as institutionalised, they should at least have dedicated employees for this work. Similarly, Kobrin (1982, p.89) suggested that institutionalised firms should have an internal “function, role and position differentiated” for the responsibility of assessing political risk. However, Kobrin (1982) admitted that firms may implicitly
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conduct political risk assessment without assigning such responsibilities, and Al Khattab et al. (2008) found the majority of Jordanian international firms were conducting the assessment through various individuals without assigning formal responsibility.
Regularity of performing the assessment
The regularity of political risk assessment is typically taken as the frequency with which political risks are assessed (Blank et al., 1980). An increased regularity of political risk assessments indicates a higher degree of institutionalisation (Blank et al., 1980; Al Khattab et al., 2008a) as the regularity allows organisations to cope with environmental changes and detect unfavourable events that negatively affect their activities (Brink, 2004). Political risk assessment has often been found to be “crisis- oriented” and “on demand”, that is triggered by external events or internal activities rather than being in some way planned or pro-active (Rice and Mahmoud,, 1990; Pahud de Mortanges and Allers, 1996; Oetzel, 2005; Al Khattab et al., 2008b). Such external events might include war, taxation restriction and social unrest, whereas internal stimuli include the existence of a new investment opportunity or a firm’s expansions into different host countries (Al Khattab et al., 2008b).
Risk assessment procedures
According to Brink (2004), there are essentially two different procedures for assessing political risk: heuristic (or qualitative) and scientific (or quantitative). The heuristic procedure is regarded as involving subjective judgments, whereas the scientific procedure is seen as typically using mathematical modelling (Waring and Glendon, 2001). Heuristic procedures include the opinion of experts (Walker et al., 2003; Rice and Mahmoud 1990), the Delphi technique of elicitation specifically (Tsai and Su,
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2005; Al Khattab et al., 2011), the intuition and judgment of managers (Rice and Mahmoud, 1990), and scenario-based methods (Brink, 2004; Al Khattab et al., 2011).
With reference to expert opinion, firms typically rely on international organisations, local government officials, banks, journalists and former politicians (Pahud de Mortanges and Allers, 1996). The main disadvantage of this technique is its vulnerability to any bias among such experts (Kobrin, 1981a).
According to Merna and Al-Thani (2005), Delphi is a way of collecting expert opinion in which a panel of experts are requested to make their judgments about the risk, independently at first and afterwards by consensus in order to discard any extreme opinions. Burmester (2000) argued that the outcome of Delphi method relies on the quality and the ability of the experts selected and their enthusiasm to participate. The main criticism of this technique is the delay in achieving final results so that the assessment might quickly become invalid (Simon, 1985). It has been found that this technique was not commonly used for political risk (Pahud de Mortanges and Allers, 1996; Rice and Mahmoud, 1990; Al Khattab et al., 2011).
With regard to the intuition and judgment of managers, firms may send managers to the host country for investigation (Pahud de Mortanges and Allers 1996) and meeting with government authorities (Kobrin, 1980). Even then their understanding can be limited and selective. It is thus typically recommended to combine this method with other less subjective methods (Pahud de Mortanges and Allers 1996). But various studies have found that this method was the most common for risk assessment: see, for example, Al Khattab et al. (2011) within Jordanian firms, Pahud de Mortanges and Allers (1996) within Dutch firms, and Rice and Mahmoud (1990) within Canadian firms.
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A scenario-based method is a commonly accepted technique used to identify the important risks and opportunities of political risk (Brink, 2004). This method depends on visualizing the future rather than inferring from the past (Levinsohn, 2002).
In order to decrease the subjectivity and the bias of the qualitative procedures, quantitative assessment of political risk is also used (Pahud de Mortanges and Allers, 1996). The quantitative procedures include techniques that depend on mathematical or statistical processes (Ting, 1988) such as the use of regression procedure to predict the political risk (Rice and Mahmoud, 1990). The quantitative techniques could provide a sensible and systematic structure in the assessment of political risk (Tsai and Su, 2005).
A number of quantitative risk assessment techniques exist that have been applied specifically to country risks including political risks. Some of the commonly applied ones include Discriminant Analysis (DA), Logit and Probit models, and Artificial Neural Networks (ANN) (Bouchet et al., 2003). Discriminant Analysis, for instance, has used data such as that on price inflation as independent variables to predict categorical dependent variances such as expropriation (Yim and Mitchell, 2005, Lindeberg and Mörndal, 2002). Discriminant Analysis is used when dependent variables (also known as grouping variables) are known a priori (Bouchet et al., 2003). Accordingly, this technique allows prediction of the extent to which a country is likely to take an action that is unfavourable for foreign investment (Bouchet et al., 2003). Logit and Probit models look into dichotomous or binary variables, thus making them suitable for political risks that normally have either/or results, e.g. either a country goes into war or not. All such approaches have limitations – for example Bouchet et al. (2003) describe the problem that independent variables vary across countries and
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times, citing the way in which debt service ratio can have a negative sign in some models but a positive sign in others. In these cases, where data do not fulfil the assumptions, techniques such as Artificial Neural Networks are used (Yim and Mitchell, 2005). Artificial Neural Networks do not follow traditional statistical techniques as they do not assume dependence of the predictors, i.e. the relationship between outputs and inputs is non-linear (Yim and Mitchell, 2005). Several studies (e.g. Cosset and Roy, 1990) have established Artificial Neural Networks as superior to statistical models in terms of providing more accurate predictions of risk in the case of political risks. Yim and Mitchell (2005), studying country risk of Belize, Uruguay, Croatia, Kazakhstan and Panama, combined several of the above mentioned techniques and found that hybrid neural networks produced the best results in predicting country risk.
According to Hood and Nawaz (2004, p.10), the measurement and management of political risk “tend to be more subjective than objective” in practice. Al Khattab et al. (2011) found that managers justified their substantial use of qualitative rather than quantitative procedures with three reasons: firstly, qualitative procedures are quicker to use, especially in rapidly changing environments; secondly, qualitative procedures are less expensive as there is no need to gather historical information; thirdly, quantitative procedures need data that are vulnerable to statistical manipulation and so are unreliable.
In addition to effective risk assessment techniques, firms also employ risk mitigation strategies to reduce the consequences of political risks. Ling and Hoi (2006) summarised several mitigation strategies, including the avoidance of “political hotspots” in countries or regions. Hood and Nawaz (2004) made similar arguments,
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but also added that avoidance should be balanced against available opportunities. Ling and Hoi (2006) also supported selecting short-duration projects, and avoiding the participation in government projects whilst working towards keeping good relationships with host governments. Diversification of international activities across different regions can equally be an effective strategy to mitigate political risks (Hood and Nawaz, 2004). In addition to these strategies, insurance is mentioned as a strategy to mitigate political risks (Jensen, 2008) and political risk insurance facilities are provided by a number of firms; e.g. Overseas Private Investment Corporation (OPIC), AON Hewitt, and the Arab Investment and Export Credit Guarantee.