• Title/Summary/Keyword: Inflation Volatility

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Dynamic Linkages between Food Inflation and Its Volatility: Evidence from Sri Lankan Economy

  • MOHAMED MUSTAFA, Abdul Majeed;SIVARAJASINGHAM, Selliah
    • The Journal of Asian Finance, Economics and Business
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    • v.6 no.4
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    • pp.139-145
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    • 2019
  • This study examines the dynamic linkages between food price inflation and its volatility in the context of Sri Lanka. The empirical evidence derived from the monthly data for the period from 2003M1 to 2017M12 for Sri Lanka. The relationship between inflation rate and inflation volatility has attracted more attention by theoretical and empirical macroeconomists. Empirical studies on the relationship between food inflation and food inflation variability is scarce in the literature. Food price inflation is defined as log difference of food price series. The volatility of a food price inflation is measured by conditional variance generated by the FIGARCH model. Preliminary analysis showed that food inflation is stationary series. Granger causality test reveals that food inflation seems to exert positive impact on inflation variability. We find no evidence for inflation uncertainty affecting food inflation rates. Hence, the findings of the study supports the Friedman-Ball hypothesis in both cases of consumer food price inflation and wholesale food price inflation. This implies that past information on food inflation can help improve the one-step-ahead prediction of food inflation variability but not vice versa. Our results have some important policy implications for the design of monetary policy, food policy thereby promoting macroeconomic stability.

An Empirical Study on the Effect of Inflation Targeting on PPP: Evidence From 19 OECD countries (물가안정목표제가 구매력평가에 미친 영향: 19개의 OECD 국가들을 대상으로)

  • Eun-Son Lim
    • Korea Trade Review
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    • v.47 no.5
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    • pp.75-93
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    • 2022
  • Purchasing Power Parity (hereafter, PPP) means the purchasing power of two currencies is the same when one is converted into the other one. According to previous studies on PPP, as the volatility of the real exchange rate is smaller, PPP may be more likely to hold. Since New Zealand adopted the inflation targeting policy in December 1989, many countries started to adopt it as their monetary policy frame. Previous studies on inflation targeting found that inflation targeting policy has positive effects on not only achieving price stability but also reducing the volatility of nominal/ real exchange rates. Therefore, in this study, I explored whether inflation targeting policy has positive effects on purchasing power parity subject to 19 OECD countries, applying an Exponential Smooth Transition Autoregressive (ESTAR) model during the sample periods, from 1974:Q1 to 2019:Q4. Based on the ESTAR estimate results, I found limited favorable evidence of PPP for only two countries- England and Switzerland- among 9 inflation targeters, compared to non-inflation targeters, and also I found that favorable evidence of PPP only for these two countries among 9 inflation targeters during post-inflation targeting, but not during pre-inflation targeting. These findings imply that the positive effects of inflation targeting on PPP may be questionable unlike Ding and Kim (2012) and Kim (2014)'s study.

The Study of the Effect of Terms of Trade and its Volatility Using the Panel Model (패널모형을 이용한 교역조건과 변동성의 영향 분석)

  • Choi, Yong-Jae
    • International Area Studies Review
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    • v.21 no.4
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    • pp.19-39
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    • 2017
  • The purpose of this paper is to investigate the impact of terms of trade and its volatility on real GDP and inflation. I estimate the linear and dynamic panel model including variables such as real GDP, inflation, terms of trade, capital stock, employment and education. The sample countries consist of OECD 26 countries and panel data ranges from 1990 to 2015. The empirical results show that terms of trade and its volatility do not affect the real GDP significantly. Even if the terms of trade has a negative relationship with real GDP, the magnitude of the estimated coefficients was very small. This result seems to be related with the industry structure and domestic demand structure of the member countries. On the other hand, terms of trade and its volatility have the significant impact on inflation. When the terms of trade and its volatility increase, the inflation increases.

Evolution of China's Economy and Monetary Policy: An Empirical Evaluation Using a TVP-VAR Model

  • Kim, Seewon
    • East Asian Economic Review
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    • v.25 no.1
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    • pp.73-97
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    • 2021
  • China has experienced many structural changes in the process of economic development over the past three decades. Using a time-varying parameter VAR model with stochastic volatility and mixture innovations, this study investigates whether such structural changes in, especially tools and operational aims of monetary policy, affect the monetary transmission mechanism. We find that impulse responses of output growth and inflation to monetary shocks have substantially increased and then reversed to decrease around 2005-2006. This time variation is mainly caused by changes in the monetary transmission mechanism, i.e., the manner in which main macroeconomic variables respond to policy shocks, rather than by changes in volatilities of exogenous shocks. The result implies that aggressive monetary policy to facilitate economic growth in the developing economies may be legitimized, unless it causes inflation seriously.

Dynamic Interaction between Conditional Stock Market Volatility and Macroeconomic Uncertainty of Bangladesh

  • ALI, Mostafa;CHOWDHURY, Md. Ali Arshad
    • Asian Journal of Business Environment
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    • v.11 no.4
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    • pp.17-29
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    • 2021
  • Purpose: The aim of this study is to explore the dynamic linkage between conditional stock market volatility and macroeconomic uncertainty of Bangladesh. Research design, data, and methodology: This study uses monthly data covering the time period from January 2005 to December 2018. A comprehensive set of macroeconomic variables, namely industrial production index (IP), consumer price index (CPI), broad money supply (M2), 91-day treasury bill rate (TB), treasury bond yield (GB), exchange rate (EX), inflow of foreign remittance (RT) and stock market index of DSEX are used for analysis. Symmetric and asymmetric univariate GARCH family of models and multivariate VAR model, along with block exogeneity and impulse response functions, are implemented on conditional volatility series to discover the possible interactions and causal relations between macroeconomic forces and stock return. Results: The analysis of the study exhibits time-varying volatility and volatility persistence in all the variables of interest. Moreover, the asymmetric effect is found significant in the stock return and most of the growth series of macroeconomic fundamentals. Results from the multivariate VAR model indicate that only short-term interest rate significantly influence the stock market volatility, while conditional stock return volatility is significant in explaining the volatility of industrial production, inflation, and treasury bill rate. Conclusion: The findings suggest an increasing interdependence between the money market and equity market as well as the macroeconomic fundamentals of Bangladesh.

A Study on the Impact of Oil Price Volatility on Korean Macro Economic Activities : An EGARCH and VECM Approach (국제유가의 변동성이 한국 거시경제에 미치는 영향 분석 : EGARCH 및 VECM 모형의 응용)

  • Kim, Sang-Su
    • Journal of Distribution Science
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    • v.11 no.10
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    • pp.73-79
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    • 2013
  • Purpose - This study examines the impact of oil price volatility on economic activities in Korea. The new millennium has seen a deregulation in the crude oil market, which invited immense capital inflow into Korea. It has also raised oil price levels and volatility. Drawing on the recent theoretical literature that emphasizes the role of volatility, this paper attends to the asymmetric changes in economic growth in response to the oil price movement. This study further examines several key macroeconomic variables, such as interest rate, production, and inflation. We come to the conclusion that oil price volatility can, in some part, explain the structural changes. Research design, data, and methodology - We use two methodological frameworks in this study. First, in regards to the oil price uncertainty, we use an Exponential-GARCH (Exponential Generalized Autoregressive Conditional Heteroskedasticity: EGARCH) model estimate to elucidate the asymmetric effect of oil price shock on the conditional oil price volatility. Second, along with the estimation of the conditional volatility by the EGARCH model, we use the estimates in a VECM (Vector Error Correction Model). The study thus examines the dynamic impacts of oil price volatility on industrial production, price levels, and monetary policy responses. We also approximate the monetary policy function by the yield of monetary stabilization bond. The data collected for the study ranges from 1990: M1 to 2013: M7. In the VECM analysis section, the time span is split into two sub-periods; one from 1990 to 1999, and another from 2000 to 2013, due to the U.S. CFTC (Commodity Futures Trading Commission) deregulation on the crude oil futures that became effective in 2000. This paper intends to probe the relationship between oil price uncertainty and macroeconomic variables since the structural change in the oil market became effective. Results and Conclusions - The dynamic impulse response functions obtained from the VECM show a prolonged dampening effect of oil price volatility shock on the industrial production across all sub-periods. We also find that inflation measured by CPI rises by one standard deviation shock in response to oil price uncertainty, and lasts for the ensuing period. In addition, the impulse response functions allude that South Korea practices an expansionary monetary policy in response to oil price shocks, which stems from oil price uncertainty. Moreover, a comparison of the results of the dynamic impulse response functions from the two sub-periods suggests that the dynamic relationships have strengthened since 2000. Specifically, the results are most drastic in terms of industrial production; the impact of oil price volatility shocks has more than doubled from the year 2000 onwards. These results again indicate that the relationships between crude oil price uncertainty and Korean macroeconomic activities have been strengthened since the year2000, which resulted in a structural change in the crude oil market due to the deregulation of the crude oil futures.

Threshold-asymmetric volatility models for integer-valued time series

  • Kim, Deok Ryun;Yoon, Jae Eun;Hwang, Sun Young
    • Communications for Statistical Applications and Methods
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    • v.26 no.3
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    • pp.295-304
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    • 2019
  • This article deals with threshold-asymmetric volatility models for over-dispersed and zero-inflated time series of count data. We introduce various threshold integer-valued autoregressive conditional heteroscedasticity (ARCH) models as incorporating over-dispersion and zero-inflation via conditional Poisson and negative binomial distributions. EM-algorithm is used to estimate parameters. The cholera data from Kolkata in India from 2006 to 2011 is analyzed as a real application. In order to construct the threshold-variable, both local constant mean which is time-varying and grand mean are adopted. It is noted via a data application that threshold model as an asymmetric version is useful in modelling count time series volatility.

Zero-Inflated INGARCH Using Conditional Poisson and Negative Binomial: Data Application (조건부 포아송 및 음이항 분포를 이용한 영-과잉 INGARCH 자료 분석)

  • Yoon, J.E.;Hwang, S.Y.
    • The Korean Journal of Applied Statistics
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    • v.28 no.3
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    • pp.583-592
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    • 2015
  • Zero-inflation has recently attracted much attention in integer-valued time series. This article deals with conditional variance (volatility) modeling for the zero-inflated count time series. We incorporate zero-inflation property into integer-valued GARCH (INGARCH) via conditional Poisson and negative binomial marginals. The Cholera frequency time series is analyzed as a data application. Estimation is carried out using EM-algorithm as suggested by Zhu (2012).

Modeling Effect of Exchange Rate Volatility on Growth of Trade Volume in Pakistan

  • Siddiqui, Muhammad Ayub;Erum, Naila
    • The Journal of Asian Finance, Economics and Business
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    • v.3 no.2
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    • pp.33-39
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    • 2016
  • This study empirically evaluates the impact of exchange rate volatility, foreign direct investment, terms of trade, inflation, and industrial production and foreign exchange reserves on Pakistani trade volume over the period of 1975-2010 using quarterly data set. The study employs financial econometrics methods such as Augmented Dickey Fuller (ADF) test GARCH (1, 1) technique and Almon Polynomial Distributed Lag (APDL) models to estimate the relationship of variables. Findings of the study are in accordance with theoretical relationships presented by Clark, Tamirisa, Wei, Sadikov, & Zeng (2004), McKenzie (1999), Dellas & Zilberfarb (1993) and Côté (1994). These findings are also in accordance with the empirical studies which support positive relationship of exchange rate volatility and exports presented by Hsu & Chiang (2011), Chit (2008), Feenstra & Kendall (1991), Esquivel & Larraín (2002) and Onafowora & Owoye (2008). Findings of the study in terms of imports are supported by the studies such as Lee (1999), Alam & Ahmad (2011) and Arize (1998). The study also recommends some very important policy prescriptions.

Integer-Valued GARCH Models for Count Time Series: Case Study (계수 시계열을 위한 정수값 GARCH 모델링: 사례분석)

  • Yoon, J.E.;Hwang, S.Y.
    • The Korean Journal of Applied Statistics
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    • v.28 no.1
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    • pp.115-122
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    • 2015
  • This article is concerned with count time series taking values in non-negative integers. Along with the first order mean of the count time series, conditional variance (volatility) has recently been paid attention to and therefore various integer-valued GARCH(generalized autoregressive conditional heteroscedasticity) models have been suggested in the last decade. We introduce diverse integer-valued GARCH(INGARCH, for short) processes to count time series and a real data application is illustrated as a case study. In addition, zero inflated INGARCH models are discussed to accommodate zero-inflated count time series.