Sovereign debt risk in emerging market economies: Does inflation targeting adoption make any difference?

Balima, Hippolyte; Combes, Jean-Louis; Minea, Alexandru

doi:10.1016/j.jimonfin.2016.10.005

Cited by 42 publications

(32 citation statements)

References 42 publications

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“…indicate that high inflation volatility decreases the likelihood to adopt inflation targeting. 19 This result is in line with studies by Lucotte (2012), Minea and Tapsoba (2014), Ebeke and Fouejieu (2015) and Balima, Combes, and Minea (2017) among others, who show that high or volatile inflation is negatively associated with the probability of adopting IT. GDP share and trade openness is also found to negatively affect IT adoption.…”

Section: The Propensity Score For Inflation Targetingsupporting

confidence: 77%

“…We consider a sample of 48 advanced and emerging economies that have and have not adopted explicit IT between 1982 and 2016: Argentina, Australia*, Austria, Belgium, Brazil*,Canada*, Chile*, Colombia*, Costa Rica, Denmark, Finland*, France, Germany, Greece, Hong Kong, China, Hungary*, India, Indonesia*, Ireland, Israel*, Italy, Japan, Korea*, Latvia, Malaysia, Mexico*, Netherlands, New Zealand*, Norway*, Peru*, Philippines*, Poland*, Portugal, Romania*, Russia, Singapore, Slovak Republic*, Slovenia, South Africa*, Spain*, Sweden*, Switzerland*, Thailand*, Turkey*, The United Kingdom* and The United States. 10 Following Rose (2007), Minea and Tapsoba (2014) and Balima, Combes, and Minea (2017) we classify an observation as IT distinguishing between Full-fledge (FF henceforth) and Soft starting dates of IT. The difference between the two dates captures the fact that some central banks first adopted "soft or informal" IT (see Vega and Winkelried (2005)), in which the central bank's reaction, following a deviation of inflation from its targeted level, is slower compared to its reaction under an explicit "full-fledged or formal" IT.…”

Section: Data and Descriptive Statisticsmentioning

confidence: 99%

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Does inflation targeting always matter for the ERPT? A robust approach

López-Villavicencio

Pourroy

2019

Journal of Macroeconomics

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This paper estimates the effects of different forms of inflation targeting (IT) in the exchange rate pass-through (ERPT). To this end, we first estimate the ERPT for a large sample of countries using state-space models. We then consider the adoption of an inflation targeting framework by a country as a treatment to find suitable counterfactuals to the actual targeters. By controlling for self-selection bias and endogeneity of the monetary policy regime, we confirm that the ERPT tends to be lower for countries adopting explicit IT. However, we uncover that older regimes, adopting a range or point with tolerance band and keeping inflation close to the target, outperform other IT regimes. We also show that IT is effective even with a relatively high inflation target or low central bank independence. JEL Classification: E31; E42; E52; C30.

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Section: The Propensity Score For Inflation Targetingsupporting

confidence: 77%

Section: Data and Descriptive Statisticsmentioning

confidence: 99%

Does inflation targeting always matter for the ERPT? A robust approach

López-Villavicencio

Pourroy

2019

Journal of Macroeconomics

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“…According to Mishkin (2004) or Hammond (2012), a central bank has an IT framework if it fullfills the five following criteria : 1) Price stability is explicitly recognized as the main goal of monetary policy; 2) There is a public announcement of a quantitative target for inflation; 3) Monetary policy is based on a wide set of information, including an inflation forecast; 4) Transparency; and 5) Accountability mechanisms. For the sake of robustness, we follow Rose (2007), Minea and Tapsoba (2014) and Balima, Combes, and Minea (2017) and distinguished between Full-fledge (FF from now on) and Soft starting dates of IT. The difference between the two dates captures the fact that some central banks first adopted "soft or informal" IT (see Vega and Winkelried (2005)), in which the central bank's reaction, following a deviation of inflation from its targeted level, is slower compared to its reaction under an explicit "full-fledged or formal" IT.…”

Section: Data and Descriptive Statisticsmentioning

confidence: 99%

“…For a given country i we have a i = β + i − β − i . It can easily be shown that the average treatment effect of IT on the pass-through asymmetry is equal to the difference between the ATT when oil price increases and the ATT when 11 For the sake of robustness, we estimate the average treatment effect for the "Soft IT" classification adoption date and we add variables related to the structure of the economy, the financial sector or the fiscal position of the country while computing the PS index (see Balima, Combes, and Minea (2017)). The estimated ATT in both cases are similar to the baseline estimation.…”

Section: Average Treatment Effect Of Inflation Targeting On the Pass-mentioning

confidence: 99%

Inflation target and (a)symmetries in the oil price pass-through to inflation

López-Villavicencio

Pourroy

2019

Energy Economics

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In this paper we employ state-space models to estimate the pass-through of oil price changes to consumer prices for a large sample of countries from 1970 to 2017. By controlling for self-selection bias and endogeneity and allowing for different responses to positive and negative price changes, we asses the differences between explicit inflation targeting (IT) countries and a control group. Surprisingly perhaps, our results suggest that the pass-through is higher for IT countries. Our main contribution is to show that these is mainly due to IT countries having a significant higher pass-through than non-IT countries when the oil price decreases: a 10% drop in oil price leads about a 0.11% drop in inflation in ITers (of which 4pp are explained by the monetary regime). Importantly, we show that adopting IT reduces the asymmetry of the pass-through. We run several robustness checks and conclude that falling oil prices are more welcomed by the central banks with an IT framework, in particular during deflationary episodes or when inflation is above the target. JEL Classification: E31; E42; Q43.

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“…Following Minea and Tapsoba (2014), and Balima et al (2017), we consider the nearest (N = 1), the two-nearest (N = 2), and the three-nearest (N = 3). The second method is the radius or caliper matching (Dehejia and Wahba, 2002), which matches each treated i with untreated j that falls within radius r. We use the PS to define a medium (r = 0.1), a small (r = 0.05) and a wide (r = 0.2) radius.…”

Section: Propensity Score Matching Resultsmentioning

confidence: 99%

Informal Sector and Mobile Financial Services in Developing Countries: Does Financial Innovation Matter?

2019

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This paper investigates the impact of mobile financial services -MFS (mobile money, and mobile credit and savings) on the informal sector. Using both parametric and non-parametric methods on panel data from 101 emerging and developing countries over the period 2000-15, we find that MFS negatively affect the size of the informal sector. According to estimates derived from propensity score matching, MFS adoption decreases the informal sector size in a range of 2.4 -4.3 percentage points of GDP. These formalization effects may stem from different possible transmission channels: improvement in credit access, increase in the productivity/profitability of informal firms attenuating subsistence constraints typical of entrepreneurship in the informal sector, as well as possible induced growth of firms already in the formal sector. The robustness of these results is supported by the use of an alternative estimation approach (instrumental variables). These findings lay the groundwork for the scarce literature on the macroeconomic impact of mobile financial services, a major dimension of the growing drive towards economic digitalization.

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Sovereign debt risk in emerging market economies: Does inflation targeting adoption make any difference?

Cited by 42 publications

References 42 publications

Does inflation targeting always matter for the ERPT? A robust approach

Does inflation targeting always matter for the ERPT? A robust approach

Inflation target and (a)symmetries in the oil price pass-through to inflation

Informal Sector and Mobile Financial Services in Developing Countries: Does Financial Innovation Matter?

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