Measuring the effects of inflation and inflation uncertainty on output growth in the central and eastern European countries

Živkov, Dejan; Kovačević, Jelena; Papić-Blagojević, Nataša

doi:10.1080/1406099x.2020.1846877

Cited by 8 publications

(3 citation statements)

References 37 publications

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“…Table 5 presents the results of the estimated Bayesian quantile parameters for quarterly and monthly data. Following Živkov et al (2020), we estimate all BQR parameters under 70% confidence level, and Figures 5 and 6 graphically illustrate these results. It can be seen that QR parameters are heterogeneous in magnitude across the quantiles and the selected countries, and they bear both positive and negative signs.…”

Section: Research Resultsmentioning

confidence: 99%

How does oil price uncertainty affect output in the Central and Eastern European economies? – the Bayesian-based approaches

Živkov

Đurašković²

2022

AEA

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Purpose This paper aims to investigate how oil price uncertainty affects real gross domestic product (GDP) and industrial production in eight Central and Eastern European countries (CEEC). Design/methodology/approach In the research process, the authors use the Bayesian method of inference for the two applied methodologies – Markov switching generalized autoregressive conditional heteroscedasticity (GARCH) model and quantile regression. Findings The results clearly indicate that oil price uncertainty has a low effect on output in moderate market conditions in the selected countries. On the other hand, in the phases of contraction and expansion, which are portrayed by the tail quantiles, the authors find negative and positive Bayesian quantile parameters, which are relatively high in magnitude. This implies that in periods of deep economic crises, an increase in the oil price uncertainty reduces output, amplifying in this way recession pressures in the economy. Contrary, when the economy is in expansion, oil price uncertainty has no influence on the output. The probable reason lies in the fact that the negative effect of oil volatility is not strong enough in the expansion phase to overpower all other positive developments which characterize a growing economy. Also, evidence suggests that increased oil uncertainty has a more negative effect on industrial production than on real GDP, whereas industrial share in GDP plays an important role in how strong some CEECs are impacted by oil uncertainty. Originality/value This paper is the first one that investigates the spillover effect from oil uncertainty to output in CEEC.

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Section: Research Resultsmentioning

confidence: 99%

How does oil price uncertainty affect output in the Central and Eastern European economies? – the Bayesian-based approaches

Živkov

Đurašković²

2022

AEA

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“…Their results are consistent for the whole 1966-2000 period of the analysis and different subperiods. (Zivkov, et al, 2020) find that inflation volatility has, indeed, larger negative effects on output growth than the level of inflation. This confirms (Friedman, 1977) hypothesis, who conjectured that an increased variability of actual or anticipated inflation may raise the natural rate of unemployment.…”

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confidence: 76%

The determinants of inﬂation volatility: a panel data analysis for US-product categories

Arespa

Alegre

2022

Applied Economics

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Some macroeconomic dimensions like the economic business cycle, the exchange rate movements when the degree of country openness is significant, or the level of inflation are often considered to explain measured-inflation dynamics. However, inflation volatility may also be affected by statistical agencies methodological changes. This paper explores both potential explanations in a panel data for 100 United States CPI-U subcategories. We find that crucial changes in how agencies consider quality adjustment in products, together with the aforementioned macroeconomic variables help t o understand CPI volatility over time, both in the short-run and in the long-run.JEL codes: E30, E31.

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“…Research on inflation and inflation modeling has been carried out (Yolanda, 2017;Živkov et al, 2020). However, there has been no research on the characteristics of inflation for the cities used in calculating the national inflation rate.…”

Section: Introductionmentioning

confidence: 99%

Identification and comparison of characteristics of inflation rate in cities in Indonesia in the period of 2009–2014 with the period of 2014–2019

Setiawan

Wijayanto

Wattimanela

2021

JoSSE

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This study aims to identify the characteristics of the MoM inflation rate in cities in Indonesia. In addition, it also compares the distribution of the monthly inflation rate for the 2009–2014 period with the 2014-2019 period in cities in Indonesia. The method used to identify the characteristics of the MoM inflation rate is by using summary of statistics, while to compare the distribution of the monthly inflation rate for the 2009–2014 period and the 2014–2019 period, the two-sample Kolmogorov-Smirnov test is used. Characteristics of the month to month (MoM) inflation rate in cities in Indonesia for the period October 2009 to March 2019 was presented. Furthermore, the comparison of the characteristics of the MoM inflation rate from October 2009 to September 2014 (period 1) and the period from October 2014 to March 2019 (period 2) was also shown. The cities of Banda Aceh, Kendari, Yogyakarta, Jakarta and Sorong had an average characteristic of inflation each month which tended to be low in February, March, April and September.Six cities had significantly different characteristics during period 2 inflation rate compared to period 1.

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Measuring the effects of inflation and inflation uncertainty on output growth in the central and eastern European countries

Cited by 8 publications

References 37 publications

How does oil price uncertainty affect output in the Central and Eastern European economies? – the Bayesian-based approaches

How does oil price uncertainty affect output in the Central and Eastern European economies? – the Bayesian-based approaches

The determinants of inﬂation volatility: a panel data analysis for US-product categories

Identification and comparison of characteristics of inflation rate in cities in Indonesia in the period of 2009–2014 with the period of 2014–2019

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