Estimating the effect of central bank independence on inflation using longitudinal targeted maximum likelihood estimation

Author:

Baumann Philipp F. M.1,Schomaker Michael23,Rossi Enzo4

Affiliation:

1. KOF Swiss Economic Institute, Department of Management, Technology, and Economics (D-MTEC), ETH Zurich , 8092 Zurich , Zurich , Switzerland

2. Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology , Hall in Tirol , Austria

3. Centre for Infectious Disease Epidemiology & Research, School of Public Health and Family Medicine, University of Cape Town , Cape Town , South Africa

4. Swiss National Bank, Department I , 8022 Zurich , Zurich , Switzerland

Abstract

Abstract 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.

Publisher

Walter de Gruyter GmbH

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. What drives inflation and how? Evidence from additive mixed models selected by cAIC;Frontiers in Applied Mathematics and Statistics;2023-11-22

2. Political monetary cycles: An empirical study;European Journal of Political Economy;2023-09

3. Central Bank Governor Turnover And Inflation In Zambia:Using Complex Wavelets for a Clearer Picture;Cogent Business & Management;2022-10-11

4. Central Bank Policies and Market Power Over the Business Cycle in Africa;Journal of Emerging Market Finance;2022-04-04

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