Global Prices Research Articles

A Bayesian approach to assessing uncertainty in the effect of fertilization strategies on paddy rice yield via multiple on-farm experiments

ABSTRACT The surge in global agricultural input prices, particularly for nitrogen (N) fertilizers, has presented challenges for farmers facing stagnant crop prices and rising production costs. This study explored a system designed to sustain or enhance farmers’ income while reducing production costs, with a specific focus on implementing practices that involve cultivating crops with lower rates of fertilizer than conventional rates, particularly in smaller land settings, through on-farm experimentation (OFE). OFE was conducted over three years across 11 fields in Gifu, Japan, utilizing a strip trial design to investigate the effect of fertilizer input rates on rice yield. To collect yield data, unmanned aerial vehicle (UAV)-mounted multispectral cameras were deployed. A Gaussian process model was used to address the impact of fertilizer input rates on yield while accounting for spatial yield variation. The study further assessed the number of field trials achieving positive profits at certain probability levels by integrating outcomes from multiple OFEs. The results highlighted little rice yield response to fertilizer input in most of the fields, while several fields showed significant positive yield responses. Notably, the use of lower fertilizer input rates in certain fields proved to be more profitable whereas higher fertilizer input rates were less profitable in most fields. The results further emphasized the economic viability of lower rates, especially when fertilizer prices are high, thus contributing valuable insights for sustainable and profitable rice production in Japanese cultivation.

Pricing Strategies for Distribution Network Electric Vehicle Operators Considering the Uncertainty of Renewable Energy

In the future, the active load of the distribution network side will be dominated by electric vehicles (EVs), showing that the charging power demand of electric vehicles will change with the change in charging electricity price. With the popularity of electric vehicles in the distribution network, their aggregation operators will play a more prominent role in pricing management and charging behavior, and setting an appropriate charging price can achieve a win–win situation for operators and electric vehicle users. At the same time, the proportion of scenery in the distribution network is relatively high, and the uncertainty of self-output has a certain impact on the pricing strategy of operators and the charging behavior of electric vehicle users, which has become an important research topic. Based on the above background, an EV operator pricing strategy considering the landscape uncertainty is proposed, a Stackelberg game model is established to maximize the respective benefits of operators and EV users, and the two-layer model is further transformed into a single-layer model through the Karush–Kuhn–Tucker (KKT) condition and duality theorem. Finally, the IEEE 33 system is simulated with the CPLEX solver, and the global optimal pricing strategy is obtained. Simulation results prove that electric vehicle operators experience a maximum profit increase of 2.6% due to the impact of maximum capacity of energy storage equipment and the uncertainty of renewable energy output can result in electric vehicle operators losing approximately 20% of their profits at most.

New Developmentalism Under Neoliberalism: The Case of Brazil

This study provides a comprehensive analysis of Brazil's socioeconomic policies and growth models under the Brazilian Workers Party from 2003 to 2016. It examines two key growth models implemented in this process: namely, primary-export led and domestic consumption-oriented growth models. By utilizing official statistics and secondary sources, it shows that primary exports were the driving force behind economic growth in Brazil until 2006. It also indicates that after 2006, despite not being the main facilitator of economic growth, the exporting sectors continued to support the current account balance in Brazil, thanks to increasing global demand and prices for Brazilian primary commodities. Nevertheless, the post-2006 period in Brazil witnessed an increasing weight of domestic consumption in growth dynamics. This mainly results from expanding social transfers and income distribution programs, growing employment, and increasing minimum wages. The study demonstrates that Brazil's inclusive growth model was not sustainable due to the strong dependence of domestic accumulation on foreign capital inflows and external demand.

How do households cope during aggregate shocks? Evidence from the 2009–2015 oil crisis in Nigeria

The effect of global oil price fluctuations on households' costs of living in Nigeria is examined. We extend the Aggregate Demand/Supply (AD/AS) model by incorporating aggregate shock and idiosyncratic risk with cross-sectional heterogeneity in households' distributions and consumption substitution dynamics. Results from our model show that while positive oil prices reflect higher output, whether growth results from inflation or income-level growth remains unclear ―demand-side inflation will raise price levels, amplify budget constraints and ultimately lower welfare. For the empirical analysis, we use oil prices between 2009 and 2015 and micro-level data from the Nigerian General Household Survey (GHS) collected between 2010 and 2016 in Nigeria. In support, we show that increasing oil prices leads to greater consumption. However, the effect varies heterogeneously ―reflecting households' location and consumption substitution dynamics, adjustments in household size, and labor supply are some coping responses to oil price changes.

Estimating the cost and affordability of healthy diets: How much do methods matter?

Recently developed cost and affordability of healthy diet (CoAHD) metrics have quickly become mainstream food security indicators. However, published research on the sensitivity of estimation methods is limited. This paper focuses on two important innovations in CoAHD measurement at the global level. First, we develop a demographic scaling factor to adjust healthy diet costs for cross-country differences in age structures, since younger populations generally require fewer calories than older populations. Second, we improve the way in which household expenditure available for purchasing food (“food budgets”) are derived. In addition, we explore sensitivity of global CoAHD estimates to potential problems with the representativeness and food product coverage of global food price data and vary assumptions for activity levels that shape energy expenditure requirements. We apply these explorations to the EAT-Lancet reference diet in 137 countries using price data from 2017. Relative to the conventional methods, we find that demographic scaling and improved food budget derivation substantially reduces the estimated population who cannot afford a healthy diet, from 3.02 to 2.13 billion. Adjustments for low product coverage can lead to modest reductions for specific regions and food groups, while higher physical activity assumptions increase the share of people who cannot afford a healthy diet, though perhaps implausibly so. Methods clearly matter in CoAHD estimation, and more accurate and timelier CoAHD estimates have substantial scope to improve policy analysis, design and targeting.

Innovation Policy Beyond Patents: A Case Study on the Development of Climate-Friendly Fertilizers

Abstract Nitrogen fertilizers have revolutionized agriculture since the early 20th century and made a decisive contribution to combating world hunger. Nevertheless, the technology is controversial today because production is energy-intensive and contributes significantly to climate change. In addition, conventional fertilizers pollute groundwater, rivers and coastal waters. Synthetic nitrogen fertilizer is made from ammonia (NH3) produced by the Haber-Bosch process, for which a patent was filed with the German Imperial Patent Office in 1908 (DE235421). For the urgently needed development of modern climate-friendly fertilizers, patent law seems to have played a minor role so far. The large and patent-active agrochemical corporations in the industrialized countries are focusing on other technologies, leaving fertilizer production to companies with direct access to energy below the global market price. Another reason is the very generous regulation of nitrogen fertilizers. For farmers, the use of less climate-damaging fertilizers is not worthwhile. However, the disruption of supply chains in the wake of Russia’s aggression in Ukraine and the aggravation of climate change could lead to a rethink. In the US, the first support programs for the development of climate-friendly, innovative ‘next-generation’ fertilizers have been launched. This paper examines the interplay of patent law in concert with regulatory law and government funding tools in the area of innovative fertilizers. It starts from the hypothesis that other legal frameworks have a stronger influence on innovation activity than patent law at the moment. But this could change if the regulatory framework were to impose stricter requirements for the use of fertilizers.

Estimation of global natural gas spot prices using big data and symbolic regression

This article provides an estimation of future natural gas spot prices on the global international market based on symbolic regression where the sensitivity analysis is performed to identify the most important input parameters. Numerical data sets, comprising various parameters, some of which demonstrate stronger correlations with the global spot price of natural gas, are utilised in this context. PySR (Python Symbolic Regression), a free and open-source software for symbolic regression written in Python, and Julia is used for the presented analysis. Based on the accuracy of the prediction and after sensitivity analysis performed in SALib software, some of the parameters are discovered to be more influencing on natural gas prices compared with others, making this approach suitable for further deeper energy analysis. The analysis shows that in general, global prices of natural gas are influenced mostly by the price of crude oil. The article also presents an overview of methods for predicting natural gas prices with a complementary contribution (interpretable models provided by symbolic regression and sensitivity analysis) tested on the real gas price time-series dataset.

Economic Diversification In Iraq: A Comprehensive Review

Economic diversification is crucial for Iraq to overcome the limitations imposed by its heavy reliance on oil. This study explores Iraq's economic history, current structure, and the urgent challenges it faces, emphasizing the need for structural transformation. It examines the vulnerabilities caused by fluctuating global oil prices, geopolitical instability, and internal demographic pressures for the period of 2004 to 2022. By analyzing government policies, sectoral developments, and international collaborations, this research highlights the efforts and obstacles in achieving economic diversification. The findings indicate that while Iraq has made strides toward diversifying its economy, it still faces significant challenges such as bureaucratic inefficiencies, political instability, and security concerns. International collaborations and foreign direct investment (FDI) emerge as crucial components, providing the financial support and technological expertise needed for economic transformation. Lastly, economic diversification is more than just an economic strategy for Iraq; it is a comprehensive approach to achieving long-term stability and growth. A diversified economy can help Iraq build resilience against external shocks, promote inclusive growth, and secure a sustainable and prosperous future. The imperative for economic diversification is clear: to create a stable, balanced, and resilient economy that can withstand global market fluctuations and geopolitical dynamics, ultimately improving the well-being of its population

Assessing the impact of global oil prices on domestic price levels in Thailand: A nonlinear ARDL investigation

Oil prices play a pivotal role in Thailand's economic development due to its heavy reliance on oil imports to meet its energy needs. Fluctuations in global oil prices directly and significantly impact domestic price levels, affecting production costs, inflation, and overall economic growth. To ensure stability and foster economic development, it is crucial to comprehend and effectively manage these dynamics. Therefore, this study aims to assess the impact of global oil prices on domestic price levels in Thailand, including key indexes such as the producer price index, consumer price index, and export price index, as well as prices of essential commodities like oil palm, sugarcane, cassava, diesel, and gasohol. The study employs both linear and nonlinear ARDL specifications, analyzing monthly time series data from January 2005 to June 2023 to unveil the nature of the relationship between global oil prices and product price levels. The empirical results indicate that most product prices respond to changes in global oil prices in an asymmetrical manner. However, oil palm prices exhibit a symmetrical response, and sugarcane prices do not display a clear pattern during testing. Based on these findings, the study offers recommendations for short-term and long-term policies aimed at mitigating the impact of domestic oil price fluctuations, ensuring energy stability, and promoting sustainability in the future.

Return volatility of Asian stock exchanges; a GARCH DCC analysis with reference of Bitcoin and global crude oil price movement

PurposeThis study aims to investigate the conditional volatility of the Asian stock market concerning Bitcoin and global crude oil price movement.Design/methodology/approachThis study uses the newest Dynamic Conditional Correlation (DCC)-Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model to examine the conditional volatility of the stock market for Bitcoin and crude oil prices in the Asian perspective. The sample stock market includes Chinese, Indian, Japanese, Malaysian, Pakistani, Singaporean, South Korean and Turkish stock exchanges, with daily time series data ranging from 4 April 2015−31 July 2023.FindingsThe outcome reveals the presence of volatility clustering on the return series of crude oil, Bitcoin and all selected stock exchanges of the current study. Secondly, the outcome of DCC, manifests that there is no short-run volatility spillover from crude oil to the Malaysian, Pakistani and South Korean and Turkish stock markets, whereas Chinese, Indian, Japanese, Singapore stock exchanges show the short-run volatility spillover from crude oil in the short run. On the other hand, in the long run, there is a volatility spillover effect from crude oil to all the stock exchanges. Thirdly, the findings suggest that there is no immediate spillover of volatility from Bitcoin to the stock markets return volatility of China, India, Malaysia, Pakistan, South Korea and Singapore. In contrast, both the Japanese and Turkish stock exchanges exhibit a short-term volatility spillover from Bitcoin. In the long term, a volatility spillover effect from Bitcoin is observed in all stock exchanges except for Malaysia. Lastly, based on the outcome of conditional variance, it can be concluded that there was increase in the return volatility of stock exchanges during the period of the COVID-19 pandemic.Research limitations/implicationsThe analysis below does not account for the bias induced due to certain small sample properties of DCC-GARCH model. There exists a huge literature that suggests other methodologies for small sample corrections such as the DCC connectedness approach. On the other hand, decisive corollaries of the conclusions drawn above have been made purely based on a comprehensive investigation of eight Asian stock exchange economies. However, there is scope for inclusive examination by considering other Nordic and Western financial markets with panel data approach to get more robust inferences about the reality.Originality/valueMost of the empirical analysis in this perspective skewed towards the Nordic and Western countries. In addition to that many empirical investigations examine either the impact of crude oil price movement or Bitcoin performance on the stock market return volatility. However, none of the examinations quests the crude oil and Bitcoin together to unearth their implication on the stock market return volatility in a single study, especially in the Asian context. Hence, current investigation endeavours to examine the ramifications of Bitcoin and crude oil price movement on the stock market return volatility from an Asian perspective, which has significant implications for the investors of the Asian financial market.

Re-validating the Phillips Curve hypothesis in Africa and the role of oil prices: A mixed-frequency approach

This paper investigates the relationship between unemployment and inflation in 29 African economies by re-examining the Phillips Curve hypothesis and evaluating the role of global oil prices in predicting inflation. Existing studies often use uniform-frequency variables, which can lead to biased results by omitting information from high-frequency series. We employ a mixed data sampling regression model to analyze inflation in selected African countries by regressing monthly inflation rates on annual unemployment rates and daily oil price returns. Our findings show that the Phillips Curve hypothesis holds in a few countries across Central Africa (Cameroon, the Central African Republic, Chad, and Republic of the Congo), East Africa (Rwanda), North Africa (Algeria), Southern Africa (Botswana and Malawi), and West Africa (Burkina Faso and Mauritania). In the other countries, the hypothesis does not hold, potentially indicating a predominance of cost-push inflation. Our analysis demonstrates that global oil prices impact inflation differently across these countries. Additionally, daily oil price data significantly enhance inflation forecasting compared to monthly data. Incorporating additional economic variables, such as exchange rates and interest rates, further improves forecast accuracy. We recommend targeted monetary policies to mitigate the impacts of oil price fluctuations and unemployment on inflation.

The effect of exchange rate pass-through to inflation in Nigeria

The study examines the effect of exchange rate pass-through (ERPT) to inflation in Nigeria. The study period spans from 1990 to 2022 and data were sourced from Central Bank of Nigeria Statistical Bulletin and World Bank’s Development indicators (WDI). The study employed preliminary test of Augmented Dickey Fuller unit root test. Analytical technique of Autoregressive Distributed Lag (ARDL) model was used for the analysis. The dependent variable is Consumer price index proxied by inflation while the explanatory variables include monetary policy rate (MPR), nominal effective exchange rate (NEER), import price index (IMPI) and Global oil price (GOP). The result of unit root suggests mixed order of integration while the ARDL bound test demonstrate long run relationship among the variables under consideration. Findings indicate that exchange rate exhibit a positive and significant impact on consumer price while import price exerts a negative and significant influence on consumer price. Based on this outcome, the study suggests that monetary authority should exercise caution in using devaluation of the domestic currency to promote economic growth, as that would not only aggravate domestic inflation but also likely increase the ERPT. Given that exchange rate devaluation is unlikely to improve the country’s chances in the international market vis-à-vis its exports.

Transition from fossil fuels to renewable energy: Identifying the necessary dynamic capabilities for a transition among Norwegian oil and gas companies

AbstractThe increasing awareness of the role of fossil fuels in global warming, fluctuating oil and gas prices, and governments' commitments to phase out fossil fuels are driving the Norwegian oil and gas industry to increasingly aim for a transition to more sustainable renewable energy. There are few studies investigating how highly emission‐intensive oil and gas firms can transition into greener industries. In this multiple‐case study, we investigate how these firms can develop green innovations and enter renewable industries by developing dynamic capabilities. We find several microfoundations of dynamic capabilities that are important for green innovation development. Expanding the search window and proactive behavior are key for identifying new opportunities, while developing market insight, cross‐sector collaboration, and structural ambidexterity are crucial to seize and reconfigure opportunities. The findings also illuminate how firm strategy in the sensing stage impacts what opportunities firms seize. The study is one of few studies that explore the microfoundations of dynamic capabilities necessary for entering new and unfamiliar markets, and it contributes to the understanding of the dynamics of the underlying microfoundations and the impact of green innovation type on these dynamics.

Does export underreporting contribute to the resource curse?

Since the 1970s, resource-exporting countries have tended to develop more slowly, a phenomenon known as the resource curse. The literature suggests that governance problems and extractible resources exacerbate the curse by diverting talent, effort, and funds into conflict, corruption, and patronage. In this paper, I argue that another mechanism may be export underreporting and capital flight, which can reduce savings, fiscal revenues, and foreign exchange. I present an economic model of underreporting and show that primary export revenues, fiscal revenues, and GDP are 30–50 % less responsive to global commodity prices in autocratic countries. The effects are concentrated in extractive industries and not restricted to oil exporters. The facts that developing countries tend to tax the primary sector and the incentive to underreport should be larger in autocracies − where firms are less accountable to citizens − suggest that primary exports may be underreported, which might contribute to the resource curse.

The non-linear impact of monetary policy on shifts in economic policy uncertainty: evidence from the United States of America

A stochastic volatility estimation of VIX index’s latent volatility is used for the United States of America, as a proxy for the adjustments in the levels of investors’ uncertainty related to current and future economic policies. The impact of monetary policy stance on such measure is examined in the framework of the distributed lag non-linear models (DLNM). We place this analysis in the literature stream emphasizing the various sources of heterogeneity concerning investors’ expectations. The main finding is that the monetary policy does impact non-linearly the adjustments in investors’ predictions. While a tighter monetary policy does generally contribute to an increase in VIX’s latent volatility, the shape of such effect varies across different GLM and GAM specifications of DLNM. This outcome remains robust, even if: (1) we control for the global price of Brent crude and consumers’ confidence; (2) we use, instead of the stochastic framework, a Markov-switching GARCH-based estimator; or (3) we replace the monetary policy instrument with monetary policy uncertainty. We argue that accounting for its nonlinear effects on financial markets is of critical importance for the design of a monetary policy pursuing global financial stability.

Could the EU carbon border adjustment mechanism promote climate mitigation? An economy-wide analysis

Due to concerns about carbon leakage and sectoral competitiveness, the European Union (EU) proposed implementing the carbon border adjustment mechanism (CBAM). The effectiveness and potential negative consequences of CBAM have aroused extensive discussion. From the perspective of the economy-wide analysis, this study uses a global computable general equilibrium model to explore the rationality of CBAM from the aspects of socioeconomic impact and the effects of promoting climate mitigation. Furthermore, the potential alternative mechanism of CBAM is proposed. The results show that CBAM can reduce the EU's gross domestic product (GDP) loss; however, the GDP loss in all other regions increases. Moreover, CBAM raises household welfare losses in most regions, including the EU. Second, although CBAM can reduce the marginal abatement cost in eight regions, it comes at the cost of greater economic losses. Furthermore, the economic and household welfare cost of raising emissions reduction targets in regions like the USA and Japan is substantially higher than the impact of passively accepting the CBAM; therefore, CBAM's ability to drive ambitious emission reduction initiatives may be limited. Finally, for the potential alternative mechanism, from the perspective of reducing economic cost and household welfare losses, the EU could implement domestic tax cuts in the short-term and promote global unified carbon pricing in the long-term.

Geopolitical risk, supply chains, and global inflation

AbstractThis paper investigates the effects of global geopolitical risks and global supply chain pressures on global inflation for the monthly period of 1999M1–2022M12. The investigation is based on a structural vector autoregression model, where the effects of global oil prices and global monetary policy are controlled for. Four alternative measures of inflation are used, including headline, core, food, and energy inflation. The empirical results show that disruptions in global supply chains are the main drivers of global inflation in the long run as the corresponding shocks explain the lion's share of volatilities in headline inflation (by 32%), core inflation (by 30%), and food inflation (by 22%), followed by oil price shocks and policy rate shocks. In comparison, energy inflation is explained the most by oil price shocks (by 55%) followed by supply chain shocks and policy rate shocks. Positive supply chain pressure and oil price shocks have positive and statistically significant effects on headline inflation even after five years, whereas positive policy rate shocks have negative and statistically significant effects on headline inflation in the long run. In contrast, positive shocks to geopolitical risk result in higher headline inflation only up to one year, with insignificant effects in the long run. Several policy implications follow.

Oil Prices and Economic Growth in China: A Time-Frequency Analysis

This study analyses the inherent evolution dynamics of economic activity and global oil prices in China using the tools of wavelet and wavelet-based VAR-GARCH-BEKK model. Besides, the Wavelet-Granger causality test of Olayeni (2016) provides us further insights into the magnitude and direction of causal connectedness between oil prices and economic activity in China over time and across different frequencies simultaneously. We find that the spillover effects between China’s economic activity and global oil prices are time-varying in different time and frequencies in terms of direction and strength. More accurately, the prices and volatility spillovers between them are significant in the short and medium run but eventually neutral toward the long run. The Wavelet-Granger causality provides us further insights into the lead-lag relationships between oil prices and China’s economic activity from an economic perspective. The dynamic time-frequency association findings suggest crucial implications that might assist policymakers and other market participants in mitigating risk.

Exploring local–global stock price interconnections & patterns via augmented deep neural links for stock predictions

Exploring local–global stock price interconnections & patterns via augmented deep neural links for stock predictions

Influence of Purchase Decision for An Advanced Production Digital Platform Adoption Process in The Coal Industry: The Investigation Using Pls-Sem Analysis

In 2022, the coal-producing sector faced unusual difficulties, which were paralleled by a significant rise in global pricing. The business is too complex for the the most advanced technologies, especially when it comes to figuring out the best blend scenarios. This calls for a comprehensive approach that combines modern technology with careful consideration to support companies in surviving in a competitive and unpredictable commercial environment. Over the past few years, industries have been seeking technological advancement in an effort to improve operating procedures and efficiency, but these innovations still face challenges in being broadly accepted and adopted. In order to determine the primary characteristics that most significantly promote technology adoption, this study combines the Unified Theory of Acceptance and Use of Technology (UTAUT) with purchasing decision theory. The main tool used to collect data is structured questionnaires, which are given to respondents who fulfill predetermined requirements. The replies are gathered, and the SmartPLS 4.0.9.9 software is used to handle them. According to the study, behavioral intention and behavior manner use are not significantly mediated by unanticipated situational events or other people’s attitudes that align with purchase decision theory. Additionally, users’ use of behavior to adopt digital production platforms in the coal mine business is positively impacted by behavioral intention. Policymakers could consider encouraging all staff members on a regular basis to help them develop a positive mindset, which will enhance their usage behavior.