Empirical Regularities of Inflation Volatility: Evidence from Advanced and Developing Countries

Abstract

How does volatility of inflation differ across the economies? Addressing this research question, the article undertakes an empirical exercise on monthly consumer price inflation over the sample period of M01, 1958 to M02, 2016 for 41 countries using the generalized autoregressive conditional heteroscedasticity (GARCH) (1, 1) model. The country-level analysis shows a modest difference of conditional volatility of inflation between the advanced and developing economies. However, this difference increases after controlling the country-specific traits by fixed effect panel estimation using generalized methods of moments on the estimated GARCH series. It is observed that, in the long run, the conditional variability of inflation is nearly three and half times greater in developing countries compared to advanced countries. JEL Classification: E10, E30, E31

Effect of Inflation On Growth of Manufacturing Sector in Kenya (2008-2017)

“…It relates manufacturing to inflation, which are the variables of the same study. The study is different from the previous studies by Banerjee [10] and Nyoni [13] since the previous studies portrayed the variable of inflation without relating it to manufacturing.…”

“…In turn, the impact of inflation on the developed nations' overall economic progress is lesser compared to the impact on the developing nations. However, the findings by Banerjee [10] differed from those of Mukoka [11]. Mukoka [11] carried out a study to establish the impact of inflation on Zimbabwe's economic growth for the period 1990 to 2017.…”

“…The manufacturing industry has similarly suffered the perils of this radical shift. Banerjee [10] studied inflation volatility from the developing countries' perspective compared to the developed economies to establish a clear distinction between developing and developed nations. The approach adopted by Banerjee in his study was country-level analysis.…”

“…The researcher determined the difference between the two economic set-ups by controlling the country-specific traits. A fixed-effect panel estimation was used through generalized methods of moments on the estimated Generalized Autoregressive Conditional Heteroscedastic (GARCH) series [10]. Based on the study's findings, the long-term variability of inflation is almost three and a half greater among the developing countries as contrasted to the developed economies.…”

Modeling Inflation in Bangladesh

“…Vector autoregressive (VAR) models have been employed for forecasting inflation by Lack et al [11] in Switzerland; Callen and Chang [12] in India; Kelikume and Salami [13], Inam [14] in Nigeria; and Younus and Roy [15] in Bangladesh. The generalized autoregressive conditional heteroscedasticity (GARCH) models were investigated for inflation forecasting by Nyoni and Nathaniel [6] in Zambia; Fwaga et al [16] in Kenya; Ngailo et al [17] in Tanzania; and Banerjee [18] for 41 developed and developing countries for the time period 1958-2016.…”