Effects of crude oil prices on copper and maize prices

This study explains the effects of crude oil prices on copper and maize prices. Vector autoregressive and vector error correction models are used to study the relationship between oil prices and prices of copper and maize. The commodity price data used consist of average monthly prices of each of the commodities: crude oil, copper and maize for the months January 1982 to June 2021. For robustness, the analysis was also run on a sample of the same data for the period January 2000 to June 2021. A long-run relationship was found between crude oil and copper prices on the one hand and maize prices on the other for the 1982 to 2021 period at the 5% significance level. The same was not true for the shorter sample (2000 to 2021). Granger causality flowing from crude oil prices alone to copper and maize prices was not found. Recommendations that are useful for energy, mining, agriculture and general development policy and practice are made. The findings are also useful for bilateral and multilateral aid discussions. The limitations of the study and recommendations for future scholarship are also made.

Investigating the impact of Covid-19 on stock markets

This paper aims to examine the impact of Covid-19 pandemic on stock markets. This paper also analyses the stock market cointegration of selected global equity indices that performed better and have a quick speed of recovery during the pandemic. This paper also questions how increasing uncertainty and volatility deters investors’ perception of the diversification of equity investments. The dataset for the selected 12 global equity indices has been used from Thompson Reuters’s EIKON database in a given period of time between 2010 and 2021. This paper employs Vector Error Correction Models to assess the relationship among the selected global equity indices. Findings demonstrate that (i) there is an adverse impact of Covid-19 on the Global Equity markets, (ii) there is a clear sign of cointegration in global equity indices, (ii) investors can benefit from investing in particular equity indices that have exhibited quick speed of recovery from the pandemic records lows. The findings finally provide a strong foundation for constructing a resilient equity portfolio in a highly uncertain market environment.

Market Integration and Price Leadership among Major Mulberry Cocoon Markets in South India

Market integration is a good proxy for measuring market efficiency and the emerging price signals from the markets can be utilized to benefit both farmers and reelers alike. The present study empirically examines the dynamic interrelationships among the prices of major cocoons markets viz. Ramanagaram (Karnataka), Sidlaghatta (Karnataka), Hindupur (Andra Pradesh) and Dharmapuri (Tamil Nadu) in terms of market integration. The monthly average prices of cross breed mulberry cocoons for a period between April 2002 and March 2021 were considered for the present study. The Augmented Dickey-Fuller (ADF) (tau) testindicated that all the price series were non-stationary at level, but were stationary after first difference. The Johansen's multivariate cointegration procedure revealed existence of cointegration among the prices of cocoon markets. The Vector Error Correction Models (VECM) revealed a long run price causality running from Ramanagaram and Sidlaghatta markets to all other markets considered under study. The Granger causality test indicated a unidirectional causality running from Ramanagaram and Sidlaghatta markets to all markets and not vice versa. The prices prevailed in Ramanagaram and Sidlaghatta markets controlled and decided the current prices of cross breed cocoons both in long run and short run in all other markets considered for the study.

Vertical price transmission in Swiss dairy and cheese value chains

In Switzerland, there are separated value chains for dairy and cheese products, which differ in terms of industry concentration, value chain governance, and product characteristics. We analyze how milk prices are passed on along these different value chains. Using detailed price data on farm gate, wholesale, export, and retail levels, we apply asymmetric vector autoregressive and vector error correction models to study vertical price transmission in Swiss dairy and cheese chains. Contrary to most existing literature, we find almost no long-run price relationships and no significant asymmetries between the different stages and products and discuss the potential reasons.

Contemporary Literature Review of the Russian Rouble Determinants

This short literature review’s goal is to examine available papers regarding the study of Russian Rouble determinants. For purpose of analysis, 35 articles were studied among which 22 were selected, for a total of 414 pages shelled. This work analyzes most recent empirical articles, in order to identify factors responsible for the Russian currency fluctuations. Different models will be compared to learn if some are more effective than others, from basic Linear regression to Structural vector autoregressive, through Ordinary least squares or Vector error correction models. Moreover, a very special and particular attention will be paid to variables used. Which combinations of variables are used to study factors influencing the Russian currency? While it seems vital to include oil prices, interest rate, and consumer price index, is it important to have them all together in the same model? Are results among papers similar? In addition, would it be necessary to add variables such as GDP, gold price, gas price, M2 aggregate or sanctions? However, this paper will compare data from each model and try to find out if there is one best way to study the Russian currency determinants.

Intermediary performance of Islamic banks in the disruption era: Does it contribute to economic growth?

The study aims to measure the intermediary performance of Islamic banks in relation to economic growth in Indonesia in the short and long term. There are four main variables used, namely financing, fund placement in BI (Central Bank of Indonesia), investment in securities, and third-party funds in all Islamic banks from 2007 to 2019. The data were tested using vector error correction models (VECM), Granger Causality, Impulse Response Function (IRF), and Variant Decomposition (VDC) to examine causality relationships, the short- and long-term effects, shocks, and variances in Islamic bank intermediary performance to economic growth. The results show that there is a two-way causality relationship between financing and third-party funds to economic growth. While in the short term, fund placement in BI, investment in securities, and financing have a significant influence on economic growth, but in the long run, only the placement of funds in BI will affect economic growth. Also, only fund placement in BI can shock and significantly contribute to economic growth in the long term. The overall intermediary performance of Islamic banks has not contributed to Indonesia’s economic growth in the long term.

Forecasting Financial System Stability Using Vector Error Correction Model Approach

Indonesia is one of the developing countries whose economic system is still very dependent on other developed countries. This reliance often becomes one of the causes of the occurrence of economic turmoil sectors that interfere with financial system stability in Indonesia. Therefore, to forecast financial system stability indicators, primarily macroeconomic variables, become essential to do to provide an accurate index value. Then, Forecasting signs of stability of the financial system in Indonesia using Vector Error Correction models (VECM) approach with financial system stability indicators used are Banking Stability Inde