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.

政治不确定性会给企业带来不小的成本，导致决策不理想和经济活动受到抑制。管理政治不确定性和提高国家政治环境风险分析的准确性仍然是一项挑战。我们的研究试图通过将学术注意力从“什么”和“为什么”的问题重新引导到“如何”来填补这一空白可以通过以下方式识别和评估政治不确定性和政治风险：（1）提供一个基于过程的国家政治环境理论框架，明确纳入其动态结构；(2) 提出一种新的基于 DFA 的方法论框架来对其进行经验估计。我们展示了 DFA 如何从以下方面评估国家的政治环境：（1）政治环境的复杂性，（2）政治环境维度的效力（或重要性）；(3) 政治环境的稳定性，以及 (4) 模型的法理有效性。为了证明该方法的应用，我们使用每月政治风险时间序列数据分析了 1984-2018 年期间巴西的政治环境。该论文随后绘制了巴西的地图 使用政治学学术研究的政治环境和我们的经验结果对这些见解进行了三角剖分。最后一部分讨论了对 IB 政治风险研究的贡献以及使用 DFA 的方法挑战和机遇。