Changes In Commodity Prices Research Articles

Commodity Shocks and Incumbency Effects

AbstractWhy do incumbents enjoy an electoral advantage in some political settings but suffer from a disadvantage in others? We propose a novel explanation linking variation in incumbency effects with exogenous commodity shocks. While voters attempt to sanction incumbents for economic performance, changes in commodity prices affect their evaluations and condition the electoral fortunes of incumbents vis-à-vis challengers. We test our argument in Brazilian municipalities, combining a plausibly exogenous measure of variation in commodity prices with a close election regression discontinuity design. Our results show that increases in the price of agricultural commodities greatly enhance the prospects of incumbents, while negative shocks exacerbate their incumbency disadvantage, especially in rural municipalities. Further investigation suggests that commodity shocks do not operate via voter learning about candidate quality, changes in the pool of candidates, shifts in voter preferences, or strategic elite investments. Instead, we find suggestive evidence that commodity shocks affect voters' evaluations through their effect on local economic growth.

Long-term impacts of carbon allowance allocation in China: An IC-DCGE model optimized by the hypothesis of imperfectly competitive market

This study presents the construction of a 14-sector, recursive dynamic CGE model and introduces the hypothesis of imperfect competition as the model's improvement. The novel CGE model (IC-DCGE), which is calibrated with the 2017 social accounting matrix, is used to examine the impact mechanism of free-quota ratios on the economy–energy–environment system. Five simulation scenarios are designed with different free-quota ratios and one BAU scenario as a benchmark. The conclusions drawn from this study are as follows: (i) GDP loss due to the ETS policy is typically underestimated in previous studies using the traditional CGE model with a hypothesis of the perfectly competitive market, and the loss could be alleviated with a high free-quota ratio. (ii) Changes in outputs and commodity prices of the ETS-covered industries are more apparent than those of the remaining industries, and the most conspicuous change occurs in the power industry. (iii) Less free-quota ratios would yield better performance in CO2 mitigation and the optimization of energy structure. Overall, this study suggests that China set a high initial free-quota ratio and gradually decrease it to attain the emission reduction target while decreasing economic losses.

Price sensitivity of the consumer-investor: Evidence from energy prices and mutual fund fees

This study documents a significant relation between changes in commodity prices and investors' price sensitivity in the market for mutual funds. Specifically, price sensitivity⸺defined as the negative relation between fund-level flows and a fund's cost of ownership⸺is more pronounced in periods when energy commodity prices increase sharply. Aggregate flows into actively managed funds relative to the cheaper passively managed funds decrease (increase) when energy prices rise (fall). The results furnish novel evidence supporting an integrated view of the representative “consumer-investor,” whose price sensitivity in choosing financial products is related to price shocks in household consumption goods.

Forecasting Commodity Prices Using the Term Structure

The aim of this study is to test the ability of the yield curve on US government bonds to forecast the future evolution in the prices of commodities often used in as raw materials. We consider the monthly prices of nine commodities for more than 30 years. Our findings, confirmed by several parametric and non-parametric tests, are robust and indicate that the ability to forecast future performance changes over time. Specifically, between 1986 and the early 2000s the yield curve was quite successful in forecasting monthly changes in commodity prices, but that success diminished in the period following. One possible explanation for this outcome is the increased flow of capital into the commodity market resulting in stronger correlations with the equity markets and a breakdown of the obvious relationship between commodities and business cycle. Our findings are important for asset pricing, commodity traders and policy makers.

Potential Output in a Commodity‐Exporting Economy*

The surge in global demand for natural resources has driven the terms of trade in commodity‐exporting economies to historically high levels. A critical question is how the upswing in commodity prices influences these economies' potential output. I estimate the potential output and output gap that are consistent with a small open economy model featuring a commodities sector and study the implications of permanent commodity price changes on potential output and output gap. Following a 70 per cent permanent commodity price increase, the output gap improves on impact but deteriorates afterwards, falling to −0.75 per cent in the transition.

The asymmetric relationship between Baltic Dry Index and commodity spot prices: evidence from nonparametric causality-in-quantiles test

The Baltic Dry Index (BDI) is a unique gauge for measuring the marine transportation of major dry bulk shipments. Increased sea freight is a precursor to the increase in economic activities. The volumes of sea trade and freight rates are influenced by import–export dynamics and changes in commodity prices. So, levels of commodity prices are monitored to gain insight into the anticipated demand for bulk shipments. In this study, the causality-in-quantiles (CiQ) model is used to model the causal relationship between BDI spot values and spot price of major dry bulk commodities like iron ore, aluminum, copper, agricultural products by considering 12 years of daily data. CiQ model is superior compared to other linear causality models as it helps in capturing the asymmetry and nonlinearity in causality based on different quantiles or market conditions i.e., bearish, normal, and bullish market conditions. Also, it captures the causality-in-mean as well as variance and helps in exploring the causal relationship in returns as well as volatility transmission between BDI and commodity prices. The finding of the paper throws interesting light on the asymmetric relationship between BDI and commodity prices- commodity prices are causing BDI in all market conditions, but the influence is stronger in normal periods than bearish and bullish periods. The causality from commodity to BDI follows a common pattern across most of the commodities. However, the effect of BDI on commodities considerably varies across the range of commodities and across market conditions. So, this model provides a plethora of information that will help commodity market participants to hedge the risk of variations in commodity price and freight rates effectively.

Do Crude Oil Price Levels Or Its Volatility Matter In Global Food Commodity Price Change?

This study investigates the effect of crude oil price fluctuations on wheat, sugar, corn, and fertilizers. Results of Markov switching dynamic regression support evidence of two states. State 1, pertains to the low volatility of crude oil prices, and state 2, refers to higher volatility of crude oil prices. At state 1 higher levels of oil prices lead to a decline in food commodity prices, whereas in state 2, higher oil prices cause an increase in food commodity prices. Results of Dynamic Conditional Correlation (DCC) GARCH estimates indicate the coefficients of oil price levels are significant and positively associated with the conditional volatility of the four commodity prices, implying that fluctuations in global food commodity prices are not due to oil price volatility but due to the oil price levels attained at the extreme points.

The distributional dimension of the resource curse: Commodity price shocks and income inequality

How does high dependence on natural resources affect income inequality? Surprisingly little is known about the impact of dependence on primary goods on income distribution. Building on insights from the resource curse literature, this paper studies the relationship between income shocks through changes in commodity prices and income inequality in a panel of 80 countries from 1990 to 2016. We analyze differentiated effects of commodity price shocks depending on the type of commodity (labor vs. capital-intensive). We also study differences across world regions and explore potential mechanisms by looking at different types of inequality (pay-driven vs. capital-rents-driven). Results show that commodity price shocks have an impact on income inequality. However, this impact depends on the type of commodity and inequality.

The new Ricardian specific factor model

This paper explores the implications on trade and wage inequality of introducing financial capital or credit in the standard Ricardian model of production, where a given amount of start-up credit is used to employ sector specific skilled and unskilled workers following the Wage Fund approach of classical economists. Thus, we have the Specific Factor (SF) structure of Jones (1971) in a new Ricardian model (NRM) with credit and two types of labour. With an entirely different mechanism from the conventional Neo-Classical structure, distributional consequences of changes in endowments, commodity prices, and financial capital are established. Comparisons with Jones (1971) show that unlike SF model, credit expansion affects wages and nominal costs without affecting trade patterns, while rise in the relative price of the skill-intensive good causes skilled wage to hike less than proportionately, and may cause return to capital to inflate more than the wages. We extend the basic model to analyse immigration, unemployment and imperfect credit market.

Revisiting the relationship between spot and futures markets: evidence from commodity markets and NARDL framework.

This study aims to investigate the relationship between the spot and futures commodity markets. Considering the complexity of the relationship, we use a nonlinear autoregressive distributed lag (NARDL) framework that considers the asymmetry and nonlinearity in both the long and short run. Based on the daily returns of six commodity indices reaggregated on three commodity types, our study reaches some interesting findings. Our analysis highlights a bidirectional relationship between both markets over the short and long run, with a greater lead for the futures market. This result confirms the future market’s dominant contribution to price discovery in commodities. Changes in commodity prices appear first in the futures market, as informed investors and speculators prefer trading on this market that is characterized by low costs and a high-leverage effect. Then, the information is transmitted from the futures to the spot market through arbitrageurs’ activity, which explains the nonlinearity of the relationship. These results are helpful to scholars, investors and policymakers.

Commodity price fluctuations and development: perspective from emerging economies

PurposeThis paper aims to examine the impact of commodity price changes (crude oil, cocoa, coffee, cotton and gold) on the international market on development (development proxied by the human development index) (HDI) among emerging economies in Sub-Saharan Africa (SSA).Design/methodology/approachEmpirical estimates verifying theorized relationships in question were performed using the two-step system generalized method of moments framework.FindingsResults from the empirical estimates suggest that a percentage increase in the prices of crude oil, cocoa and gold in the world market have a significant positive influence on development among economies in the sub-region all things being equal; however, similar price changes in cotton and coffee showed a negative effect on development. Further empirical estimates suggest that the extent to which prices of key commodities such as crude oil, influence development in the sub-region benefit less from institutional variables such as government effectiveness, corruption control and political stability. The same institutional variables, however, were found to augment how changes in cocoa prices influence development among economies in the sub-region.Originality/valueThis study specifically examines the extent to which commodity price fluctuations impact a holistic measure of development, (HDI which inherently captures economic growth) among emerging economies such as those in the SSA region, and how such relationship may be moderated by conditions such as corruption control and government effectiveness. The review suggests that such a study is rare, did not find any specific empirical inquiry focusing on what this study is designed to accomplish. A major gap or deficit identified among most reviewed studies is the failure to verify how the surmised relationship between movements in prices of commodities traded on the international market and development is moderated by institutional factors such as corruption control, government effectiveness and political stability. This study specifically examines such interaction effects in its empirical analysis.

Do the RMB exchange rate and global commodity prices have asymmetric or symmetric effects on China\u2019s stock prices?

With the rapid expansion of the RMB exchange rate’s floating range, the effects of the RMB exchange rate and global commodity price changes on China’s stock prices are likely to increase. This study uses both auto regressive distributed lag (ARDL) and nonlinear ARDL (NARDL) approaches to explore the symmetric and asymmetric effects of the RMB exchange rate and global commodity prices on China’s stock prices. Our findings show that without considering the critical variable of global commodity prices, there is no cointegration relationship between the RMB exchange rate and China’s stock prices, and the coefficient of the RMB exchange rate is not statistically significant. However, when we introduce global commodity prices into the NARDL model, the result shows that the RMB exchange rate has a negative effect on China’s stock prices, that there indeed exists a long-run cointegration relationship among the RMB exchange rate, global commodity prices, and stock prices in the NARDL model, and that global commodity price changes have an asymmetric effect on China’s stock prices in the long run. Specifically, China’s stock prices are more sensitive to increases than decreases in global commodity prices. Thus, increases in global commodity prices cause China’s stock prices to decline sharply. In contrast, the same magnitude of decline in global commodity prices induces a smaller increase in China’s stock prices.

ANALYSIS OF FACTORS AFFECTING THE PRICE FLUCTUATION OF CAYENNE PEPPER IN MALANG REGENCY

This study aims to 1) Analyze the pattern of changes in commodity prices for spanish pepper in Malang District. 2) Analyzing the factors that influence fluctuations in the price of spanish pepper in Malang District. The research method used is quantitative method that uses secondary data in the form of time series obtained from several related agencies, namely the Central Statistics Agency of Malang District, Department of Industry and Trade, and Department of food crops, horticulture, and plantation in Malang District. Analysis of the data used is multiple linear regression with the dependent variable is the price at the consumer level from 2009-2018, while the independent variables use the data of the price of spanish pepper at the producer level, the amount of production, and the amount of consumption from 2009-2018. The study found that: 1) The development of the price of spanish pepper had a trend that tended to increase during the last 10 years. 2) From the results of data processing using multiple linear regression method with Eviews 9.0 application, it is found that the factor that significantly influences changes in the price of spanish pepper is the price at the producer level, while the amount of production of spanish pepper and the number of requests does not significantly affect the change in spanish pepper prices in Malang District.

Welfare impacts of introducing water pollution tax in the Olifants river basin in South Africa: A revisited analysis using a top-down micro-accounting approach

ABSTRACT Addressing the high levels of poverty and inequality in South Africa remains a central policy concern. In this regard, this paper uses a Computable General Equilibrium (CGE) microsimulation approach to revisit the effects of taxing water pollution on poverty and inequality at the level of a river basin. We combined the commodity and factor price changes from a regional environmental CGE model, after introducing the water pollution tax, with household survey data from the 2012 National Income Dynamics Survey (NIDS) to explain the welfare impacts. The result shows that the tax policy will in general have adverse impacts in terms of welfare, poverty, and inequality. However, the tax policy coupled with a supply-side compensatory measure such as subsidising water pollution abatement has the potential to reduce regional poverty and inequality as well as improve the ecological status of the river. Our finding has policy implications for national and regional water resource managers.

Connectedness between oil and agricultural commodity prices during tranquil and volatile period. Is crude oil a victim indeed?

Increasing financialization of energy and commodity markets offer a variety of tradeoff for the investors and consumers. On the one hand, this increased financialization of the two markets helps investors design a well-diversified investment portfolio with assets from different asset categories. However, at the same time, this increases the connectedness between the two markets significantly, which may have strong implications for investors and consumers. In this paper, we examine the long-term connectedness and causality between Crude oil and agricultural commodity prices. The advantage of long-term time series is that we may be able to uncover the demand and supply shocks that originated in both markets during the tranquil period and the shocks during the volatile period such as the Global Financial Crisis of 2008 and COVID-19 pandemic. For this purpose, we employ the full bootstrap sample and rolling window causality tests primarily. Our results are surprisingly different from most of the studies that have held oil prices responsible for causing changes in agricultural commodity prices (ACP). In contrast, our results confirm the presence of bidirectional causality and show that Oil prices are as much affected by the ACP as vice versa. This significant reverse causality running from ACP to Oil prices can open up a completely new interpretation domain. Finally, it is surprisingly interesting that both ACP and Oil prices remain immune to the shocks that originated in both markets during the entire time period of the COVID-19 pandemic.

Commodity prices and exchange rates: evidence from commodity-dependent developed and emerging economies

PurposeIn this paper the authors examine evidence on exchange rate predictability through commodity prices for a set of countries categorized as commodity import- and export-dependent developed and emerging countries.Design/methodology/approachThe authors perform in-sample and out-of-sample forecasting analysis. The commodity prices are modeled to predict the exchange rate and to analyze whether this commodity price model can perform better than the random walk model (RWM) or not. These two models are compared and evaluated in terms of exchange rate forecasting abilities based on mean squared forecast error and Theil inequality coefficient.FindingsThe authors find that primary commodity prices better predict exchange rates in almost two-thirds of export-dependent developed countries. In contrast, the RWM shows superior performance in the majority of export-dependent emerging, import-dependent emerging and developed countries.Originality/valuePrevious studies examined the exchange rate of commodity export-dependent developed countries mainly. This study examines both developed and emerging countries and finds for which one the changes in prices of export commodities (in case of commodity export-dependent country) or prices of major importing commodities (in case of import-dependent countries) can significantly predict the exchange rate.

Anterior Cingulate Cortex Lesions Abolish Budget Effects on Effort-Based Decision-Making in Rat Consumers.

Demand theory can be applied to analyze how animal consumers change their selection of commodities in response to changes in commodity prices, given budget constraints. Previous work has shown that demand elasticities in rats differed between uncompensated budget conditions in which the budget available to be spent on the commodities (e.g., the finite number of discrete operants to "purchase" rewards in two-alternative fixed-ratio schedules) was kept constant, and compensated budget conditions in which the budget was adjusted so that consumers could potentially continue to obtain the original reward bundles. Here, we hypothesized that rat anterior cingulate cortex (ACC) was necessary to produce this budget effect on demand elasticities. We applied excitotoxic or sham lesions to ACC in rats performing an effort task in which the prices of liquid vanilla or chocolate rewards (the effort required to obtain rewards) and the budget (the total number of operants) was manipulated. When reward prices changed, and the budget was compensated, all rats adjusted their demand for chocolate and vanilla accordingly. In sham-lesioned rats, changes in demand were even more pronounced when the budget was not compensated for the price changes. By contrast, ACC-lesioned animals did not show this additional budget effect. An in-depth comparison of the rats' choice patterns showed that, unlike sham rats, ACC-lesioned animals failed to maximize session-bundle utility after price/budget changes, revealing deficits in higher-order choice-strategy adaptations. Our results suggest a novel role of ACC in considering purchasing power during complex cost-benefit value computations.SIGNIFICANCE STATEMENT Anterior cingulate cortex (ACC) is important for allocating effort in cost-benefit calculations in animals and humans. Economic theory prescribes that the value of the costs in cost-benefit analyses not only depends on the net nominal costs required to purchase a reward, but also on the available budget resources, i.e., on the budget's "purchasing value." We asked whether ACC, a region implicated in effort-based decision-making and reward comparisons, is required for computing the value of effort relative to a budget constraint. Applying demand theory to describe rat choices in a rodent effort allocation task with varying effort prices and budgets, we show that ACC integrity was necessary for computing purchasing power, a core variable in economic choice theory.

Fiscal Rules for Natural Disaster- and Climate Change-Prone Small States

How should small states formulate a countercyclical fiscal policy to achieve economic stability and fiscal sustainability when they are prone to natural disasters, climate change, commodity price changes, and uncertain donor grants? We study how natural disasters and climate change affect long-term debt dynamics, and we propose cutting-edge fiscal policy rules. We find the primacy of a recurrent expenditure rule based on non-resource and non-grant revenue, interdependently determined by government debt and budget balance targets with expected disaster shocks. This innovative fiscal rule is classified as a natural disaster-resilient fiscal rule, which comprises a plethora of new advantages compared to existing fiscal rules. This new type of fiscal rule can be called as the third-generation fiscal rule. It encompasses natural disasters and climate change, uses budget data only, avoids the need for escape clauses, and operates on a timely basis. Our rule-based fiscal policy framework is practically applicable for many developing countries facing an increasing frequency and impact of devastating natural hazards, and climatic change.

Effects of a carbon tax in the United States on agricultural markets and carbon emissions from land-use change

There is increased interest in a carbon tax in the United States (U.S.) and policy makers, farmers, and other stakeholders need to understand the various economic and environmental aspects of such a policy on agriculture. A global agricultural simulation model assesses changes in production, commodity prices, and trade resulting from a U.S. carbon tax. In addition, greenhouse gas (GHG) emissions from land-use change are quantified to evaluate the possible unintended consequence of increasing emissions in the rest of the world. Three U.S. carbon tax scenarios are evaluated ranging from $15–$144 per metric ton of carbon dioxide equivalent (t−1 CO2-e) and covering a 10-year projection period. The results show that the production cost for corn and soybeans increase by a maximum of 32.6% and 22.4%, respectively at a carbon tax of $144 t−1 CO2-e. The production cost increase is compensated in part by an increase in commodity prices. Hence, the decrease in net returns for corn, soybeans, and wheat is 11.4%, 8.7%, and 11.0%, respectively, in the scenario with the highest carbon price. U.S. exports decrease for major commodities such as corn (24.9%), sorghum (20.5%), and wheat (8.7%). Barley, soybeans, and sunflower see an increase in exports of 1.2–8.8%. These changes in trade patterns also result in a re-allocation of land-use in the rest of the world leading to a slight increase in global GHG emissions from land-use change representing 1.8% of total U.S. emissions in 2017. The increase in emissions is small compared to the overall projected reduction from the carbon tax. Policy makers need to be cognizant of leakage in terms of land-use change and that measures must be taken to avoid expansion into carbon rich native vegetation.

Do Commodity Price Shocks Cause Armed Conflict? A Meta-Analysis of Natural Experiments

Scholars of the resource curse argue that reliance on primary commodities destabilizes governments: price fluctuations generate windfalls or periods of austerity that provoke or intensify civil conflict. Over 350 quantitative studies test this claim, but prominent results point in different directions, making it difficult to discern which results reliably hold across contexts. We conduct a meta-analysis of 46 natural experiments that use difference-in-difference designs to estimate the causal effect of commodity price changes on armed civil conflict. We show that commodity price changes, on average, do not change the likelihood of conflict. However, there are cross-cutting effects by commodity type. In line with theory, we find price increases for labor-intensive agricultural commodities reduce conflict, while increases in the price of oil, a capital-intensive commodity, provoke conflict. We also find that price increases for lootable artisanal minerals provoke conflict. Our meta-analysis consolidates existing evidence, but also highlights opportunities for future research.