What Information is Most Relevant for Estimating Output Gaps in Emerging Economies?
利用贝叶斯向量自回归模型估计东南亚四个新兴经济体的产出缺口，发现金融变量和外部因素比传统劳动力指标更能解释经济周期波动。
Despite the importance of the output gap for guiding macroeconomic policy, little is known about how financial and global factors influence its dynamics in emerging economies. To address this, I estimate output gaps for the Southeast Asian emerging economies of Indonesia, Malaysia, Thailand, and the Philippines using a multivariate Beveridge-Nelson decomposition within a Bayesian vector autoregression framework. The model incorporates a range of macroeconomic indicators using an open-economy assumption by including block-exogenous foreign sector variables, imposes an alternative Minnesota prior to avoid an “upward bias” in the signal-to-noise ratio, and accounts for outlier observations that affect emerging economies, including during the pandemic. There are three key findings. First, traditional slack measures are largely uninformative for these economies, likely due to structural issues, limited coverage, and, more importantly, the prevalence of informal employment which weakens the link between labor market indicators and the business cycle. Second, financial variables are highly informative and were particularly influential during the Asian and the Global Financial Crisis. Third, external variables explain a substantial share of cyclical fluctuations, often exceeding the contribution of domestic output, suggesting the susceptibility of these emerging market economies to global forces.