Modeling a country's political environment using dynamic factor analysis (DFA): A new methodology for IB research

Tatiana Lukoianove, James Agarwal and Oleksiy Osiyevskyy

Journal of World Business, 2022, vol. 57, issue 5

Abstract: Political uncertainty generates non-trivial costs for business, resulting in suboptimal decision-making and suppression of economic activity. Managing political uncertainty and attaining greater accuracy in risk analysis of a country's political environment remain a challenge. Our research attempts to fill this gap by re-directing scholarly attention from the questions of what and why to how political uncertainty and political risks can be identified and assessed by (1) offering a process-based theoretical framework of a country's political environment that explicitly incorporates its dynamic structure; and (2) proposing a new methodological framework based on DFA to empirically estimate it. We demonstrate how DFA enables evaluating the country's political environment, in terms of: (1) complexity of the political environment, (2) potency (or importance) of the dimensions of the political environment; (3) stability of the political environment, and (4) nomological validity of the model. To demonstrate the application of this methodology, we analyze Brazil's political environment for the period 1984–2018 using monthly political risk time-series data. The paper then maps Brazil's political environment using political science scholarship with our empirical results triangulating the insights. The final section discusses contributions to research on political risk in IB as well as the methodological challenges and opportunities of using DFA.

Date: 2022
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DOI: 10.1016/j.jwb.2022.101313

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