Central bank independence, elections and fiscal policy in Africa

Abstract

Purpose The purpose of this paper is to primarily investigate the ability of independent central banks (central bank independence (CBI)) to improve fiscal performances in Africa, accounting for election years, and also to examine whether the effectiveness of CBI in improving fiscal performance is enhanced by higher political institutional quality. Design/methodology/approach Using recent CBI data from Garriga (2016) on 48 African countries, 90 other developing countries and 40 developed countries over the period 1970–2012, the authors apply a two stage system GMM with Windmeijer (2005) small sample robust correction estimator to examine the impact of CBI and elections on fiscal policy in Africa, other developing countries and developed countries. Findings The authors provide evidence that unlike in other developing countries and developed countries, CBI does not significantly improve fiscal performance in Africa. However, the effectiveness of CBI in improving fiscal performance in Africa is enhanced by higher levels of institutional quality. Although elections directly worsen fiscal performance in Africa, institutional quality enhances CBI’s effect on improving fiscal performance in election years across Africa, other developing countries and developed countries. Practical implications The findings of the study are significant as they provide insight into the benefits of having strong institutions to complement independent central banks in order to control fiscal indiscipline in election years. Originality/value The study is the first among the studies of CBI-fiscal policy nexus, to measure fiscal policy using net central bank claims on government as a percentage of GDP. In addition to the use of fiscal balance, this study also uses cyclically adjusted fiscal balance as a measure of fiscal policy. This is a critical channel through which independent central banks can constrain government spending. It also compares findings in Africa to other developing countries, noting some differences.

Financial sector development, anti-money laundering regulations and economic growth

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“…The AML index for a country is calculated using the weighted scores from each domain. We rescale the AML regulations index using the formula −1*(AMLR-10) proposed by Agoba et al. (2019) and Ofoeda et al.…”

“…The AML index for a country is calculated using the weighted scores from each domain. We rescale the AML regulations index using the formula À1*(AMLR-10) proposed by Agoba et al (2019) and Ofoeda et al (2020), where higher values denote a robust AML framework while lower values denote weak AML frameworks. Furthermore, ðFD * AMLRÞ it denotes the interaction term between financial sector growth and AML regulations.…”

Central bank's communication and markets' reactions: Polish evidence

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