论文标题
使用纵向目标最大似然估计，估算中央银行独立性对通货膨胀的影响
Estimating the Effect of Central Bank Independence on Inflation Using Longitudinal Targeted Maximum Likelihood Estimation
论文作者
论文摘要
独立中央银行减少一个国家通货膨胀的观念是一个有争议的假设。迄今为止，还没有可能令人满意地回答这个问题，因为产生数据的复杂宏观经济结构尚未充分地纳入统计分析中。我们开发了一个因果模型，总结了通货膨胀的经济过程。基于此因果模型和最新数据，我们讨论并确定了可以识别和估计中央银行独立性对通货膨胀影响的假设。鉴于这些和替代性假设，我们使用现代双重稳健效应估计器（即纵向目标最大似然估计器）估算了这种效果。估计过程包含机器学习算法，并量身定制以应对与复杂的纵向宏观经济数据相关的挑战。我们没有对这样的假设有强烈的支持，即长期以来拥有独立的中央银行必然会降低通货膨胀。仿真研究评估了当某些假设违反某些假设时所提出的方法在复杂环境中的敏感性，并强调了使用适当的学习算法进行估计的重要性。
The notion that an independent central bank reduces a country's inflation is a controversial hypothesis. To date, it has not been possible to satisfactorily answer this question because the complex macroeconomic structure that gives rise to the data has not been adequately incorporated into statistical analyses. We develop a causal model that summarizes the economic process of inflation. Based on this causal model and recent data, we discuss and identify the assumptions under which the effect of central bank independence on inflation can be identified and estimated. Given these and alternative assumptions, we estimate this effect using modern doubly robust effect estimators, i.e., longitudinal targeted maximum likelihood estimators. The estimation procedure incorporates machine learning algorithms and is tailored to address the challenges associated with complex longitudinal macroeconomic data. We do not find strong support for the hypothesis that having an independent central bank for a long period of time necessarily lowers inflation. Simulation studies evaluate the sensitivity of the proposed methods in complex settings when certain assumptions are violated and highlight the importance of working with appropriate learning algorithms for estimation.
