Harold Ngalawa

This study examines global shocks and the volatility of the Russian rubble/United States dollar exchange rate using the symmetric Generalized Autoregressive Conditional Heteroscedasticity (GARCH), and Asymmetric Power Autoregressive Conditional Heteroscedasticity (APARCH) models. The GARCH and APARCH are employed under normal (Normal Gaussian) and non-normal (Student’s t and Generalized Error) distributions. Using monthly exchange rate data covering January 1994 – December 2013, the study finds that the symmetric (GARCH) model has the best fit under the non-normal distribution, which improves the overall estimation for measuring conditional variance. Conversely, the APARCH model does not show asymmetric response in exchange rate volatility and global shocks, resulting in no presence of leverage effect. The GARCH model under the Student’s t distribution produces better fit for estimating exchange rate volatility and global shocks in Russia, compared to the APARCH model.

Keywords: exchange rate volatility, global Shocks, GARCH and APARCH models.
JEL Classification: F30, F31, P33

The principal objective of this study is to investigate the relationship between monetary policy and growth of the manufacturing sector in Algeria. Using a structural vector autoregressive model and quarterly frequency data for the period 1980Q1 to 2010Q4, the study finds no evidence that money supply responds to fluctuations in manufacturing sector growth or Gross Domestic Product (GDP) growth. Interest rates, however, are seen to explain nearly a third of the variations in manufacturing output growth, suggesting that the manufacturing sector is sensitive to interest rates. The study also reveals that money supply variations are largely explained by changes in interest rates. A peek at the monetary transmission process reveals that Algeria employs monetary aggregates as the primary operating tool of monetary policy. The monetary authorities adjust total money supply in response to any movements in the rate of interest, probably to keep the rate of interest within a certain target given other developments in the fundamentals. The interest rates, in turn, play an important role in determining variations in manufacturing sector growth. In addition, the interest rates significantly affect exchange rates, which are observed to respond to changes in overall GDP growth. It is the overall GDP growth that has the largest influence on manufacturing sector growth, probably due to strong forward and backward linkages between the manufacturing sector and other sectors of the economy.

Keywords: Monetary policy, transmission mechanism, manufacturing output, oil price shocks.
JEL Classifications: E23, E31, E52

The paper conducts a short-run analysis of the implications of oil price movements and exchange rate relationship for the Nigerian manufacturing sector growth between January 2008 and September 2017. Monthly data are extracted on variables such as oil price, exchange rate, inflation rate, interest (lending) rate, money supply and the manufacturing sector growth rate. Oil price movements are viewed in terms of both volatility and change. While EGARCH is used to estimate oil price volatility, oil price change is measured using Hamilton index for both oil price sharp drop and jump. The SVAR results indicate that exchange rate and inflation rate are more responsive to sharp drop in oil price. The two variables also have the highest impact on the manufacturing sector growth. Findings further indicate that Nigerian manufacturing sector is more affected at the cost side than the output side. This underscores the importance of tackling the inflation pressure in Nigeria from the structural perspective as against the monetary perspective.