Real Oil Price Research Articles

Domestic Investment, Foreign Direct Investment and Macroeconomic Stability in Nigeria

This study examines the relationship between the two major investment components (domestic investment and foreign direct investment) and macroeconomic stability in Nigeria. In order to capture the macroeconomic stability, some selected macroeconomic variables are presented, namely: real GDP growth rate (RGDPgr), trade openness (TOP), exchange rate (EXR), inflation rate (INFR), interest rate (INTR), private sector credit (PSC) which represent domestic variables and world oil price (WOP) which represent foreign variable. The study employs Johansen cointegration and Vector Autoregressive model as the estimation techniques. Findings from the study reveals that there is no long-run relationship between the selected macroeconomic variables and the two investment variables. The study also reveals that shocks and fluctuations from real GDP growth rate (RGDPgr), private sector credit (PSC), inflation rate (INFR), interest rate (INTR), exchange rate (EXR) and world oil price (WOP) strongly and significantly affect domestic investment in Nigeria; while the shocks and instabilities arising from real GDP growth rate (RGDPgr), inflation rate (INFR), interest rate (INTR), exchange rate (EXR), trade openness (TOP) and world oil price (WOP) majorly and significantly affect foreign direct investment in Nigeria during the period under review. The study therefore recommends that Nigerian government should provide stability measures in all the aforementioned macroeconomic indicators, as this will attract a higher level of FDI and this will create an enabling business environment for domestic investment to operate.

Oil price shocks and credit spread: Structural effect and dynamic spillover

This study analyzes the heterogeneous response of U.S. credit spread to global oil price shocks by building an extended structural vector autoregressive model (SVAR), which can distinguish among the U.S. and non-US oil supply shocks, aggregated demand shocks and oil market-specific demand shocks behind the real oil prices. Meanwhile, a spillover index model developed by Diebold and Yilmaz (2012) (hereafter D.Y. (2012)) is used to estimate the link between oil price shocks and the U.S. credit spread over time. The results show that (i) the credit spread does not respond to global oil supply shocks and non-US oil supply shocks, but has a negative reaction to the U.S. oil supply shocks, aggregate demand shocks, and oil-market-specific demand shocks. (ii) There exists a close connectedness between oil price shocks and the U.S. credit spread, and the link fluctuates cyclically and relates to the economic cycle and the U.S. shale oil revolution. (iii) The spillover from different oil price shocks to the U.S. credit spread shows significant heterogeneity over time. Our findings suggest that policymakers and investors can better track the U.S. credit spread changes using oil price information.

Bayesian TVP-VARX models with time invariant long-run multipliers

The time-varying parameters vector autoregression models with exogenous variables (TVP-VARX) have become an indispensable tool for modeling time-varying relationships between macroeconomic indicators. At the same time, TVP-VARX models are often outperformed in forecasting by simpler benchmarks due to large parameter space. In order to reduce the number of parameters, we assume long-run monetary policy neutrality for the influence of exogenous shocks on endogenous variables. We propose a novel modification of TVP-VARX incorporating the time-invariant long-run multipliers. We present a Gibbs sampling scheme for Bayesian model estimation. The empirical analysis of quarterly data of real GDP, exchange rate, and real oil prices from Norway and Russia demonstrates significantly better forecasting performance of the proposed model compared to VAR, VARX, and TVP-VARX without multipliers, thus giving indirect support to the long-term neutrality assumption.

THE IMPACT OF OIL PRICES ON THE FOOD INFLATION IN KAZAKHSTAN

This paper assesses empirically the effects of real oil price shocks on the food inflation in Kazakhstan for the monthly period 2004-2019 by using a VAR model. Standard unit root tests do not yield reliable results in the presence of breaks. In this regard, Zivot-Andrews (1992) has been tested with the help of unit root test. Food prices have been proven to be I(1) according to the Zivot-Andrews (1992) test, while I(0) is according to the ADF test. In subsequent steps, the causality test of the variables was performed. According to the test, there is a double-chance causality between oil prices and food prices. The short-term effect of the variables is investigated with the help of the VAR model. As a result, crude oil prices have an indirect impact on food prices.

External imbalances from a GVAR perspective

AbstractWe study the drivers governing external disequilibria through a Global VAR (GVAR) analysis applied to a group of 24 countries during the period 1972–2017. The GVAR methodology is particularly well suited for our research question. First, it permits to measure the effects of both domestic and foreign country‐specific shocks. Second, it allows us to analyse the long‐run relationships and dynamics through generalised impulse response functions. Third, it enables us to test many hypotheses from a macroeconomic perspective and the existence of spillovers. Our results show evidence of international financial integration in terms of fulfilling the real interest rate parity. Concerning the twin deficits hypothesis, we find no conclusive results. In addition, we show how German fiscal policy has relevant spillover effects on other European countries (such as France, Spain and the Netherlands) and the United States and India. Finally, global shocks have long‐lasting effects in most countries analysed, primarily through real oil prices. These results provide clues about how to implement a more symmetrical external adjustment, especially inside the euro area.

Counterfactual shock in energy commodities affects stock market dynamics: Evidence from the United States

Volatilities in the stock market are due to fluctuations in essential energy commodities. This in effect underpins the impact of short- and long-run prices on producers, consumers, portfolio managers, and policymakers. To understand the past, present, and future dynamics of energy commodities and stock market uncertainty — this paper investigated the nexus between real stock index in the US. We investigated energy commodities namely oil price, coal price, and natural gas price employing over decadal monthly data from 1991:01 to 2019:12. The study applied autoregressive distributed lag (ARDL) and dynamic simulations of ARDL (DYNARDL) techniques to investigate long-term shocks in oil price, coal price, natural gas price, short-term interest rate, and industrial production index. The study found negative long-run relationship between real oil price, real coal price, real natural gas price, short-term interest rate, and real stock index, with only industrial production index reporting a positive relationship with real stock index in both ARDL and dynamic simulated ARDL models. While we found positive relationship between energy commodities and real stock index in the short run, negative relationship was reported between short-term interest rate, industrial production index, and real stock index. Incorporating real Western Texas Intermediate oil in S&P500 stock price index function corrects historical fluctuations by 64% compared to 54% speed of adjustment with real brent oil. The dynamic ARDL simulation further provides key insight into how energy commodity prices and economic activity shocks are transmitted to stock market prices in the U.S.

MULTI-SOURCE MODEL OF HETEROGENEOUS DATA ANALYSIS FOR OIL PRICE FORECASTING

This article sheds light on the question of whether it is possible to create fairly accurate forecasts of real oil prices. For this purpose, a multi-level machine learning model has been created to analyze several sources of heterogeneous data to predict future prices. The article uses different types of data: market condition data, titles, and transaction data. Then, they have been processed to be able to load them into the model. The validation of the regression neural network results showed that the model is more accurate than in previous studies. In fact, this paper presents an artificial neural network model that solves the problem of determining the most informative relationship between different types of oil price data. Keywords: artificial neural network, oil forecasting, machine learning, price prediction, energy resources.JEL Classifications: C45, C51, Q43, Q47DOI: https://doi.org/10.32479/ijeep.10853

On the China factor in the world oil market: A regime switching approach

Abstract We investigate the relationship between China's macroeconomic performance and the world oil market over the past two decades. Unlike existing studies, we allow for possible regime changes by utilizing a class of Markov-switching vector autoregression (MS-VAR) models. The model identifies key regime changes in the structural shocks when the oil market experiences low and high volatility. We find that demand shocks from China and the rest of the world have a larger impact on the real price of crude oil during periods of high volatility. Supply shocks, in contrast, have a large effect on the price in the low volatility regime. A similar state-dependent phenomenon is observed for the impact of oil price shocks on China economic activity, however the size of these responses is relatively small. Thus, despite China being a major player in international oil markets, we conclude that oil market shocks tend to have little impact on China's real GDP growth.

The differential effects of oil price shocks on exchange rate, inflation, and monetary policy rate in Ghana

This paper investigates the differential effects of oil price shocks on exchange rate, inflation, and monetary policy rate in Ghana. The paper also introduces the trade weighted U.S. dollar-major currencies index as another measure for identifying the speculative component of the real price of oil. To execute its objective, the paper employed a two-step estimation technique and monthly data from 1973 to 2018. The two-step method involves structural VAR in the first step and OLS regressions in the second step. Full sample estimation results indicate that oil price shocks are inconsequential to exchange rate, inflation, and monetary policy rate in Ghana. Furthermore, when the sample is split into two sub-periods, the study did not find the fact that Ghana switching from a net oil-importer to a net oil-exporter have any deferential effect. Taken together, the findings suggest that even in emerging and developing countries, a fading relationship between oil price shocks and macroeconomic indicators could exist.

Quantifying time-varying forecast uncertainty and risk for the real price of oil

We propose a novel and numerically efficient quantification approach to forecast uncertainty of the real price of oil using a combination of probabilistic individual model forecasts. Our combination method extends earlier approaches that have been applied to oil price forecasting, by allowing for sequentially updating of time-varying combination weights, estimation of time-varying forecast biases and facets of miscalibration of individual forecast densities and time-varying inter-dependencies among models. To illustrate the usefulness of the method, we present an extensive set of empirical results about time-varying forecast uncertainty and risk for the real price of oil over the period 1974-2018. We show that the combination approach systematically outperforms commonly used benchmark models and combination approaches, both in terms of point and density forecasts. The dynamic patterns of the estimated individual model weights are highly time-varying, reflecting a large time variation in the relative performance of the various individual models. The combination approach has built-in diagnostic information measures about forecast inaccuracy and/or model set incompleteness, which provide clear signals of model incompleteness during three crisis periods. To highlight that our approach also can be useful for policy analysis, we present a basic analysis of profit-loss and hedging against price risk.

The real equilibrium exchange rate in a commodity­exporting economy: the experience of Azerbaijan

The case of Azerbaijan serves to study the adequacy of exchange-rate policy in a resource-rich economy. This paper analyses the behavior of Azerbaijan’s external accounts over the past twenty years. Declining oil prices made an existing exchange-rate peg unsustainable and led to a large devaluation in 2015. Since then, the current account balance has improved, but by less than expected. We use the EBA-Lite method to derive regression-based estimates of the equilibrium real exchange rate, and relate misalignments to measures of “policy gaps”. Our findings suggest that only a few years after the devaluation, Azerbaijan’s currency has once more become overvalued. Moreover, the equilibrium real exchange rate is volatile and hardly compatible with a long-run exchange rate peg. Exchange rate policy should try to accommodate shifts in the fundamental determinants such as relative productivity and real oil prices.

Влияние шоков мировой деловой активности, предложения нефти и спекулятивных нефтяных шоков на экономику РФ

In this work we build a Bayesian vector autoregression model to estimate the impact of global economic activity shocks, supply shocks in the global oil market, as well as speculative oil shocks on key macroeconomic variables of the Russian economy: GDP, household consumption, fixed capital investment, import, export, real effective exchange rate, real wages and income, MIACR interest rate and GDP deflator. The model uses real oil prices, the index of global economic activity, oil production and oil inventories as exogenous variables. The model parameters are estimated for the period from Q1 1999 to Q4 2019. The dynamics of four exogenous variables is described using a separate external vector autoregression model, which is estimated over an extended time period from Q1 1974 to Q4 2019 in order to more accurately estimateits parameters and identify shocks. Shocks are identified based on the approach proposed in [Kilian, Murphy, 2014], which uses sign restrictions and restrictions on the price elasticities of oil demand and oil supply. According to estimates of impulse responses, such variables as real household consumption, imports, and the exchange rate respond positively and statistically significantly to all three shocks leading to an increase in oil prices. However, a shock to global economic activity has a stronger impact. With an increase in oil prices for real GDP, investment and exports a stable and statistically significant positive impact is observed only when this price increase is due to a shock to global economic activity. The work also estimates a forecast error variance decomposition and a historical decomposition of the domestic variables by shocks, which indicate the prevailing role of shocks in global economics activity in the dynamics of Russian macroeconomic variables.

Financial instability as a sustained export growth limiting factor of the Russian far east regions

The paper analyses the export dynamics of the Russian Far East regions in the context of cyclical business activity. A multi-regression model with lag variables is formed during correlation-regression analysis, since a tendency for a lagging export reaction in response to fluctuations in financial instability indicators was revealed. The analysis showed that exports are influenced by factors of economic activity, fluctuations in real exchange rates, oil prices and levels of external debt relative to GDP. During the crisis, there was a short-term pattern of growth, but in the subsequent period, the decline in the output of exporters, the shortage of financial resources, the increase in the cost of materials and other costs led to a reduction in the sales of products for export. Financial instability is becoming the main source of financial risk for exporters, requiring regional government intervention and business support mechanisms.

Quantifying Time-Varying Forecast Uncertainty and Risk for the Real Price of Oil

Quantifying Time-Varying Forecast Uncertainty and Risk for the Real Price of Oil

Real Oil Price Forecasting: Gains and Pitfalls of Text Data

Real Oil Price Forecasting: Gains and Pitfalls of Text Data

The relation between petroleum product prices and crude oil prices

We present an empirical examination of the relation between real spot Brent oil prices and real spot petroleum product prices, specifically gasoline and heating oil prices. Based upon weekly price data spanning a 30-year period ending in April 2019, we provide consistent evidence of Granger causality running from oil prices to product prices accounting for both non-stationarity of the series, and separately conditional heteroskedasticity. No evidence of Granger causality from product prices to oil prices is found for the full sample period nor the period up to the end of 2005, but evidence that gasoline prices Granger-caused oil prices is found for post-2005. Similar results are found for an extended model that also includes potentially endogenous real market variables related to supply and demand in the oil, heating oil and gasoline markets. Given the reduced form model results that oil prices Granger-cause gasoline and heating oil prices, we specify and estimate recursively identified structural vector autoregressive models that specifically account for structural supply and demand shocks in the oil market as well as the petroleum product markets. The oil market block follows Kilian (2009). We find that real spot gasoline prices and real heating oil prices do not respond to structural oil supply shocks, respond transiently to global commodity demand shocks, but do respond to oil-specific demand shocks. We conclude the result that spot oil prices Granger-cause spot gasoline and heating oil prices largely occurs through the channel of oil-specific demand shocks.

Macroeconomic Determinants of Stock Market Performance in Nigeria

This study investigated the macroeconomic determinants of stock market performance in Nigeria between 1985 and 2018. The source of the data for the study were from World Bank Development Indicator, 2020 edition and Central Bank of Nigeria statistical bulletin. The study employed ARDL co-integration approach as estimation technique. Findings from the study showed that inflation rate, real interest rate, real effective exchange rate and world oil price were the major determinants of Nigeria stock market performance during the study period. Based on these findings, the study therefore concludes that both endogeneous and exogeneous macroeconomic variables determine Nigeria stock market performance. Hence, the activities in the global oil market should be monitored in formulating policies to enhance stock market performance in Nigeria.

A FORECASTING APPROACH TO REAL EFFECTIVE EXCHANGE RATE-OIL PRICE NEXUS IN CHINA

Motivated by the theoretical link between real exchange rates and oil prices, we utilize a univariate moving average (MA) and an augmented MA (A-MA) model to generate multi-period forecasts of China’s real effective exchange rate for 2008–2018. The MA model utilizes past information in real exchange rates, and the A-MA model utilizes past information in both real exchange rates and oil prices. We show that the A-MA forecasts are unbiased and embody useful predictive information beyond that contained in the MA forecasts. In addition, the A-MA forecasts are directionally accurate under asymmetric loss. Such accurate forecasts are useful as inputs for policymakers to design an optimal real exchange rate policy to promote trade and attract foreign investment, and for foreign entities that regard China as an attractive environment for investing in various sectors.

Internet Usage and Economic Growth: The Case of Mexico

This paper finds that more internet users as a percentage of total population promote economic growth in Mexico and that the impact exhibited a nonlinear relation and was greater in the initial stage of Internet adoption. In addition, less government budget deficit as a percent of GDP, a higher real stock price, real peso appreciation, a higher real crude oil price or a lower expected inflation rate would enhance economic growth.

Are the responses of output and investment to oil price shocks asymmetric?: The case of an oil-importing small open economy

In this paper, we investigate whether there are asymmetric effects of oil price changes on GDP, industrial production and investment in Turkey for the period between 1998:q1 and 2019:q2 applying the methodology advanced by Kilian and Vigfusson (Quant Econ 2(3):419–453, 2011a). Based on the results of the slope-based tests, we cannot find significant evidence against the null of symmetry in the effects of oil price shocks on real GDP growth, industrial production growth and investment. Next, we concentrate on the impulse response-based tests which allow us to examine the issue of asymmetry of the impulse response functions directly. Overall, both the results of the impulse response-based symmetry tests and the impulse response analysis present significant evidence confirming the asymmetry in the responses to real oil price shocks. That is, our findings show that the responses of all macroeconomic aggregates to positive oil price shocks are considerably greater than those of to negative oil price shocks, especially at short horizons. Moreover, the asymmetry seems to be more apparent in the responses of investment and industrial production growth. Our study also emphasizes the importance of using an appropriate model to analyze the underlying relations.