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1
Onour, Ibrahim. "Dynamics of Crude Oil Price Change and Global Food Commodity Prices." Finance & Economics Review 3, no. 1 (April 28, 2021): 38–50. http://dx.doi.org/10.38157/finance-economics-review.v3i1.248.
Повний текст джерелаАнотація:
Purpose: This study investigates the effect of crude oil price fluctuations (price change as well as volatility) on wheat, sugar, corn, and fertilizers price changes.
Methods: The study employs Markov switching dynamic regression, Dynamic Conditional Correlation (DCC), and Generalized Autoregressive Conditional Hetrosekadicity (GARCH) on monthly data covering the period from January 1988 to April 2018.
Results: The findings of the research support evidence of two states. State 1, pertains to the low volatility of crude oil price, and state 2 belong to the case of the high volatility of crude oil prices. Our results indicated that at state 1, an increase in crude oil prices leads to a decline in food commodity prices, while in state 2, an increase in crude oil price levels causes 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.
Implications: The findings of the research imply that volatility in global food commodity prices is not due to oil price volatility but due to the oil price levels attained at extreme points.
Originality: The paper investigates the impact of different volatility levels of crude oil prices on global food commodity prices.
2
Nikonenko, Uliana, Tetiana Shtets, Andrii Kalinin, Iryna Dorosh, and Larysa Sokolik. "Assessing the Policy of Attracting Investments in the Main Sectors of the Economy in the Context of Introducing Aspects of Industry 4.0." International Journal of Sustainable Development and Planning 17, no. 2 (April 26, 2022): 497–505. http://dx.doi.org/10.18280/ijsdp.170214.
Повний текст джерелаАнотація:
The purpose of this work is to study and evaluate the impact of world commodity prices on the dynamics of investment in exporting countries of natural resources using the developed methodology under the influence of industry 4.0 aspects. Modern economic activity is accompanied not only by the impact of COVID-19, but also by the impact of the first manifestations of industry 4.0. This applies not only to export-import operations but also to the very need for them due to the cost of new technologies. Using mathematical methods, we investigate the impact of world commodity price indices, in particular, the general commodity price index, the agricultural commodity price index, the food price index, the metal price index, and the crude oil price index, on the dynamics of investment in commodity-type economies in both dimensions – level and volatility. The innovativeness of the study lies in determining the significance of the impact of world commodity prices on the dynamics of foreign direct investment (FDI) of raw material exporting countries (on the example of three groups of countries with different levels of economic development). The proposed methodology makes it possible to empirically evaluate the mechanisms of the macroeconomic impact of commodity prices on investment dynamics.
3
Nikonenko, Uliana, Tetiana Shtets, Andrii Kalinin, Iryna Dorosh, and Larysa Sokolik. "Assessing the Policy of Attracting Investments in the Main Sectors of the Economy in the Context of Introducing Aspects of Industry 4.0." International Journal of Sustainable Development and Planning 17, no. 2 (April 26, 2022): 497–505. http://dx.doi.org/10.18280/ijsdp.170214.
Повний текст джерелаАнотація:
The purpose of this work is to study and evaluate the impact of world commodity prices on the dynamics of investment in exporting countries of natural resources using the developed methodology under the influence of industry 4.0 aspects. Modern economic activity is accompanied not only by the impact of COVID-19, but also by the impact of the first manifestations of industry 4.0. This applies not only to export-import operations but also to the very need for them due to the cost of new technologies. Using mathematical methods, we investigate the impact of world commodity price indices, in particular, the general commodity price index, the agricultural commodity price index, the food price index, the metal price index, and the crude oil price index, on the dynamics of investment in commodity-type economies in both dimensions – level and volatility. The innovativeness of the study lies in determining the significance of the impact of world commodity prices on the dynamics of foreign direct investment (FDI) of raw material exporting countries (on the example of three groups of countries with different levels of economic development). The proposed methodology makes it possible to empirically evaluate the mechanisms of the macroeconomic impact of commodity prices on investment dynamics.
4
Rizvi, Syed Aun R., and Sahminan Sahminan. "COMMODITY PRICE AND INFLATION DYNAMICS: EVIDENCE FROM BRIICS." Buletin Ekonomi Moneter dan Perbankan 23, no. 4 (January 22, 2021): 485–500. http://dx.doi.org/10.21098/bemp.v23i4.1418.
Повний текст джерелаАнотація:
In this study, we use a commodity augmented Phillips curve to investigate the impact of global commodity prices on domestic inflation in Brazil, Russia, India, Indonesia, China, and South Africa. Oil and energy prices cause inflationary pressures in all countries, except Russia, where they cause deflationary pressures. In Indiaand Indonesia, global food prices are highly significant and positively related to inflation, while in South Africa precious metal prices impact inflation negatively. For policymakers, this study provides insights on the domestic adjustments required for inflation targeting in response to global commodity price volatility.
5
Pindyck, Robert S. "Volatility and commodity price dynamics." Journal of Futures Markets 24, no. 11 (2004): 1029–47. http://dx.doi.org/10.1002/fut.20120.
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6
Gnidchenko, A., and V. Salnikov. "Russian foreign trade price competitiveness." Voprosy Ekonomiki, no. 1 (January 20, 2014): 108–29. http://dx.doi.org/10.32609/0042-8736-2014-1-108-129.
Повний текст джерелаАнотація:
We examine export and import prices for Russian commodities relative to world prices during 2002—2011 across aggregated and disaggregated commodity groups. We also propose an aggregated export price competitiveness index as a tool of monitoring quality dynamics and a composite price competitiveness rating by commodity groups.
7
He, Xue-Zhong, and Frank H. Westerhoff. "Commodity markets, price limiters and speculative price dynamics." Journal of Economic Dynamics and Control 29, no. 9 (September 2005): 1577–96. http://dx.doi.org/10.1016/j.jedc.2004.09.003.
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8
Eickmeier, Sandra, and Markus Kühnlenz. "CHINA'S ROLE IN GLOBAL INFLATION DYNAMICS." Macroeconomic Dynamics 22, no. 2 (September 28, 2016): 225–54. http://dx.doi.org/10.1017/s1365100516000158.
Повний текст джерелаАнотація:
We apply a structural dynamic factor model to a large quarterly data set covering 38 countries between 2002 and 2011 to analyze China's role in global inflation dynamics. We identify Chinese supply and demand shocks and examine their contributions to global price dynamics and the transmission mechanism. Our main findings are as follows: (i) Chinese supply and demand shocks affect prices in other countries significantly. Demand shocks matter slightly more than supply shocks. Producer prices tend to be more strongly affected than consumer prices by Chinese shocks. The overall share of international inflation explained by Chinese shocks is notable (about 6 percent on the average over all countries but not more than 13 percent in each region). (ii) Direct channels (via import and export prices) and indirect channels (via greater exposure to foreign competition and commodity prices) both matter. (iii) Differences in trade and in commodity exposure help explain cross-country differences in price responses.
9
Lai, Ching‐chong, Shih‐wen Hu, and Vey Wang. "Commodity Price Dynamics and Anticipated Shocks." American Journal of Agricultural Economics 78, no. 4 (November 1996): 982–90. http://dx.doi.org/10.2307/1243854.
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10
Deaton, Angus, and Guy Laroque. "Competitive Storage and Commodity Price Dynamics." Journal of Political Economy 104, no. 5 (October 1996): 896–923. http://dx.doi.org/10.1086/262046.
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11
Cevik, Serhan, and Tahsin Saadi Sedik. "A Barrel of Oil or a Bottle of Wine: How Do Global Growth Dynamics Affect Commodity Prices?" Journal of Wine Economics 9, no. 1 (March 27, 2014): 34–50. http://dx.doi.org/10.1017/jwe.2014.2.
Повний текст джерелаАнотація:
AbstractThis paper explores empirically the causes of extreme fluctuations in commodity prices from January 1990 to June 2010 and seeks to identify the relative contribution of advanced and emerging market economies to the changes in commodity prices. Our assumption is that analyzing two very distinct goods—crude oil and fine wine—helps to identify common determinants of commodity prices. We find that the growth rate of global aggregate demand is the key macroeconomic determinant of the fluctuations in both crude oil and fine wine prices over the sample period. While advanced economies account for more than half of global consumption, emerging market and developing economies make up the bulk of the incremental change in demand, thereby having a greater weight in commodity price formation. The coefficient of emerging market industrial output growth is about three times as high as that of advanced economies in oil price regressions and almost five times as powerful in fine wine price regressions. The results also show that the shift in the composition of aggregate commodity demand is a recent phenomenon. (JEL Classifications: Q11, Q39, Q41, Q43)
12
Irz, Xavier, Jyrki Niemi, and Liu Xing. "Determinants of food price inflation in Finland." Suomen Maataloustieteellisen Seuran Tiedote, no. 28 (January 31, 2012): 1–7. http://dx.doi.org/10.33354/smst.75469.
Повний текст джерелаАнотація:
The agricultural commodity crisis of 2006-8 and the recent evolution of commodity markets have reignited anxieties in Finland over fast-rising food prices and food security. Although the impact of farm commodity price shocks on the final consumer is mitigated by a large degree of processing as well as the complex structure of the food chain, little is known about the strength of the linkages between food markets and input markets. Using monthly series of price indices from 1995 to 2010, we estimate a vector error-correction (VEC) model in a co-integration framework in order to investigate the short-term and long-term dynamics of food price formation. The results indicate that a statistically significant long-run equilibrium relationship exists between the prices of food and those of the main variable inputs consumed by the food chain, namely agricultural commodities, labour, and energy. When judged by the magnitude of long-run pass-through rates, farm prices represent the main determinant of food prices, followed by wages in food retail and the price of energy. However, highly volatile energy prices are also important in explaining food price variability. The parsimonious VEC model suggests that the dynamics of food price formation is dominated by a relatively quick process of adjustment to the long-run equilibrium, the half life of the transitional dynamics being six to eight months following a shock.
13
PODSOKHA, Anna. "ORGANIZATIONAL AND ECONOMIC MECHANISM OF PRICING IN THE COMMODITY EXCHANGE MARKET." Ukrainian Journal of Applied Economics 5, no. 1 (March 1, 2020): 40–48. http://dx.doi.org/10.36887/2415-8453-2020-1-5.
Повний текст джерелаАнотація:
Introduction. The low development level of commodity exchange trade in Ukraine remains a rather acute issue in the domestic economy for a long time. This indicates the need to find new ways to improve the activities of exchanges. The purpose of scientific research is the development of theoretical and methodological aspects of the formation of the organizational and economic pricing mechanism in the commodity exchange market. Results. The essence and the main functions of the price are defined. The economic indicators of efficiency are characterized, which are defined on the basis of the price. Features of market pricing are given. The pricing methodology is outlined. It is established that the pricing mechanism is based on the interaction of supply and demand. The role of legislative and executive bodies in setting and regulating prices through pricing policy is outlined. The methodical aspect of pricing is described. The price model and price methods are determined. The influence of tactical and strategic factors on price dynamics is substantiated. It is proved that companies must use both factors to succeed in the market. The foreign practice of regulation on the basis of price mechanisms is described. This approach helps the company choose the most favorable strategy in the market. The characteristics, features and differences of the cash and futures markets are given. It is determined that commodity exchanges act as a price barometer. It is established that pricing is the main task of commodity exchanges. Determined prices for goods are made public, this information is open to buyers and sellers. The role of international exchange trade is described in the formation of world prices at specific world trade centers. The tools for quantitative assessment of changes in the dynamics and level of world prices are identified. The essence and purpose of exchange quotation are determined. Conclusions. Exchange trade determines the level of commodity prices. Published information on price dynamics allows to make decisions in the process of trade relations between seller and buyer. The exchange helps to concentrate supply and demand within world trade centers. Exchange trade significantly affects the prices of agricultural products. Keywords: commodity exchange, economic mechanism, exchange market, world trade centers, price regulation, agricultural products.
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Cahyaningrum, Anisha Wirasti. "FORMATION OF COMPOSITE GLOBAL COMMODITY PRICES AS AN INFLATION INDICATOR FOR EAST JAVA." East Java Economic Journal 2, no. 2 (August 5, 2021): 210–17. http://dx.doi.org/10.53572/ejavec.v2i2.20.
Повний текст джерелаАнотація:
With the average contribution of imports to Gross Regional Domestic Product (GRDP) in the last five years reaching 19.1%, the dynamics of global commodity prices also influence the economic performance of East Java, including the movement of inflation. A composite indicator of global commodity prices is needed to find out the impact of changes in various global commodity prices on inflation in East Java. By adopting the Bank Indonesia methodology in forming a composite global price known as the Imported Inflation Price Index (IHIM) which has considered the method of forming a global composite price created by the IMF (IMF Commodity Price Index), the compilation of East Java global price composites also examines the accuracy of commodity selection and aspects of data availability. The selected global price composite for East Java is a composite of seven global commodities which include food (wheat, soybeans, corn and CPO) and non-food (iron, gold and oil). These are two aspects determining the relative weight, namely (I) the import portion of the total input based on the Input-Output table and (ii) the commodity weight of derivatives in the East Java Consumer Price Index (IHK) basket. Furthermore, with OLS regression, the composite of East Java global commodity prices affects the core-traded inflation movement in East Java. Thus, the composite of global commodity prices in East Java can be used as an indicator of East Java inflation projections, especially core-traded inflation. This study, in general, will also examine the effect of the exchange rate impact on the movement of core inflation, especially traded groups in East Java. Based on the regression results it is known that the impact of the exchange rate movement on core traded inflation in East Java is more significant than the effect of world commodity price movements.
15
Nikonenko, Uliana, Solomiia Hanushchyn, Galyna Boikivska, Yuliia Andriichuk, and Vasyl Kokhan. "INFLUENCE OF WORLD COMMODITY PRICES ON THE DYNAMICS OF INCOME OF EXPORTING COUNTRIES OF NATURAL RESOURCES UNDER GLOBALIZATION." Business: Theory and Practice 21, no. 1 (June 22, 2020): 440–51. http://dx.doi.org/10.3846/btp.2020.12202.
Повний текст джерелаАнотація:
A feature of modern globalization processes is their vulnerability to the volatility of short-term capital flows, which, combined with the growing volatility of commodity prices, have created serious difficulties for the economic policies of commodity-oriented countries. Therefore, the study of the impact of world commodity prices on the dynamics of economic growth of countries with commodity exports and the development of an appropriate methodology based on modern economic and mathematical tools is an urgent task. The purpose of the study is the impact of volatility and the level of world commodity prices on income dynamics (GDP and industrial production) using three groups of countries with different levels of economic development as an example. Functional dependencies were studied for three groups of countries: industrial countries exporting raw materials, countries – commodity exporters of low income and commodity countries of the former Soviet Union. The analysis is based on quarterly data for the period 1980–2018 using the Two-Step Least Squares (2SLS) method. We developed a methodology for the economic and statistical analysis of the functional dependencies of the commodity economy, which provides for the simultaneous accounting of the level of world commodity prices and their volatility, allows us to empirically evaluate the mechanisms of the macroeconomic influence of commodity prices on the dynamics of economic growth, primarily income (GDP and industrial production). It has been established that rising world prices for raw materials improves the dynamics of GDP and industrial production of countries exporting primary resources, while the consequences of high volatility of price indices are predominantly negative. If the impact on the economic growth of the exporting countries of raw materials of individual price indices coincides, then the corresponding estimates for volatility can differ significantly.
16
BACK, JANIS, and MARCEL PROKOPCZUK. "COMMODITY PRICE DYNAMICS AND DERIVATIVE VALUATION: A REVIEW." International Journal of Theoretical and Applied Finance 16, no. 06 (September 2013): 1350032. http://dx.doi.org/10.1142/s0219024913500325.
Повний текст джерелаАнотація:
This paper reviews extant research on commodity price dynamics and commodity derivative pricing models. In the first half, we provide an overview of key characteristics of commodity price behavior that have been explored and documented in the theoretical and empirical literature. In the second half, we review existing derivative pricing models and discuss how the peculiarities of commodity markets have been integrated in these models. We conclude the paper with a brief outlook on various important research questions that need to be addressed in the future.
17
Naifar, Nader. "Exploring the Dynamic Links between GCC Sukuk and Commodity Market Volatility." International Journal of Financial Studies 6, no. 3 (August 13, 2018): 72. http://dx.doi.org/10.3390/ijfs6030072.
Повний текст джерелаАнотація:
This study investigates the impact of commodity price volatility (including soft commodities, precious metals, industrial metals, and energy) on the dynamics of corporate sukuk returns. Using a sample of sukuk indices from Gulf Cooperation Council (GCC) countries, we study the dynamic conditional correlation using a multivariate generalized autoregressive conditional heteroskedasticity dynamic conditional correlation (GARCH-DCC) process. Empirical results show a time-varying negative correlation between GCC sukuk returns and commodity prices. In fact, a negative conditional correlation among assets of a given portfolio implies higher gain-to-risk ratios. An understanding of volatility and dynamic co-movements in financial and commodity markets is important for portfolio allocation and risk management practices.
18
Belke,, Ansgar, and Oliver von Ledebur. "Determinants and Impact of Commodity Price Dynamics." Credit and Capital Markets – Kredit und Kapital 48, no. 2 (June 2015): 343–45. http://dx.doi.org/10.3790/ccm.48.2.343.
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19
Zou, Liping, Boliang Zheng, and Xiaoming Li. "The Commodity Price and Exchange Rate Dynamics." Theoretical Economics Letters 07, no. 06 (2017): 1770–93. http://dx.doi.org/10.4236/tel.2017.76120.
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20
Huang, Shian-Chang, and Cheng-Feng Wu. "Energy Commodity Price Forecasting with Deep Multiple Kernel Learning." Energies 11, no. 11 (November 5, 2018): 3029. http://dx.doi.org/10.3390/en11113029.
Повний текст джерелаАнотація:
Oil is an important energy commodity. The difficulties of forecasting oil prices stem from the nonlinearity and non-stationarity of their dynamics. However, the oil prices are closely correlated with global financial markets and economic conditions, which provides us with sufficient information to predict them. Traditional models are linear and parametric, and are not very effective in predicting oil prices. To address these problems, this study developed a new strategy. Deep (or hierarchical) multiple kernel learning (DMKL) was used to predict the oil price time series. Traditional methods from statistics and machine learning usually involve shallow models; however, they are unable to fully represent complex, compositional, and hierarchical data features. This explains why traditional methods fail to track oil price dynamics. This study aimed to solve this problem by combining deep learning and multiple kernel machines using information from oil, gold, and currency markets. DMKL is good at exploiting multiple information sources. It can effectively identify the relevant information and simultaneously select an apposite data representation. The kernels of DMKL were embedded in a directed acyclic graph (DAG), which is a deep model and efficient at representing complex and compositional data features. This provided a solid foundation for extracting the key features of oil price dynamics. By using real data for empirical testing, our new system robustly outperformed traditional models and significantly reduced the forecasting errors.
21
Poncela, Pilar, Eva Senra, and Lya Paola Sierra. "Global vs Sectoral Factors and the Impact of the Financialization in Commodity Price Changes." Open Economies Review 31, no. 4 (March 20, 2020): 859–79. http://dx.doi.org/10.1007/s11079-019-09564-4.
Повний текст джерелаАнотація:
Abstract Commodity prices influence price levels of a broad range of goods and, in the case of some developing economies, production and export activity. Therefore, information about future commodity inflation is useful for central banks, forward-looking policy-makers, and economic agents whose decisions depend on their expectations about it. After 2004, we have witnessed the so-called financialization of the commodity markets, which might induce greater communalities among commodity prices. This paper reports evidence on the relevance of the forecasting content of co-movement after 2004. With the use of large and small scale factor models we find that for the short run, in addition to dynamics, sectoral communality has relevant predictive content. For 12 months ahead, dynamics lose relevance while communality remains relevant.
22
Panella, Massimo, Francesco Barcellona, and Rita L. D'Ecclesia. "Forecasting Energy Commodity Prices Using Neural Networks." Advances in Decision Sciences 2012 (December 31, 2012): 1–26. http://dx.doi.org/10.1155/2012/289810.
Повний текст джерелаАнотація:
A new machine learning approach for price modeling is proposed. The use of neural networks as an advanced signal processing tool may be successfully used to model and forecast energy commodity prices, such as crude oil, coal, natural gas, and electricity prices. Energy commodities have shown explosive growth in the last decade. They have become a new asset class used also for investment purposes. This creates a huge demand for better modeling as what occurred in the stock markets in the 1970s. Their price behavior presents unique features causing complex dynamics whose prediction is regarded as a challenging task. The use of a Mixture of Gaussian neural network may provide significant improvements with respect to other well-known models. We propose a computationally efficient learning of this neural network using the maximum likelihood estimation approach to calibrate the parameters. The optimal model is identified using a hierarchical constructive procedure that progressively increases the model complexity. Extensive computer simulations validate the proposed approach and provide an accurate description of commodities prices dynamics.
23
Cortazar, Gonzalo, Cristobal Millard, Hector Ortega, and Eduardo S. Schwartz. "Commodity Price Forecasts, Futures Prices, and Pricing Models." Management Science 65, no. 9 (September 2019): 4141–55. http://dx.doi.org/10.1287/mnsc.2018.3035.
Повний текст джерелаАнотація:
Even though commodity-pricing models have been successful in fitting the term structure of futures prices and its dynamics, they do not generate accurate true distributions of spot prices. This paper develops a new approach to calibrate these models using not only observations of oil futures prices, but also analysts’ forecasts of oil spot prices. We conclude that to obtain reasonable expected spot curves, analysts’ forecasts should be used, either alone or jointly with futures data. The use of both futures and forecasts, instead of using only forecasts, generates expected spot curves that do not differ considerably in the short/medium term, but long term estimations are significantly different. The inclusion of analysts’ forecasts in addition to futures, instead of only futures prices, does not alter significantly the short/medium part of the futures curve but does have a significant effect on long-term futures estimations. This paper was accepted by Gustavo Manso, finance.
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Guo, Jingyi, Junwu Wang, Denghui Liu, Shi Qiao, and Han Wu. "Study of a System Dynamics Model of Wuhan Commodity Housing Price." Advances in Civil Engineering 2021 (July 10, 2021): 1–21. http://dx.doi.org/10.1155/2021/6672038.
Повний текст джерелаАнотація:
Commodity housing is the most important product in the development of modern civil engineering, and it is also the frontier problem of modern engineering project management research. The progress of civil engineering in China can be seen to a great extent through the development of commercial housing. In order to solve the severe problem of rapid growth of commodity housing price in China, considering the advantages of system dynamics theory, a system dynamics model of commodity housing price is constructed. Eight subsystems, namely, housing demand, housing supply, housing price, urban population, urban economy, housing land, housing tenancy, and macro-control, are studied. Taking the relevant data of Wuhan as an example, the Vensim DSS is used for simulations. In addition, a validity test and sensitivity test are used to verify the validity and feasibility of the model, respectively. Based on the model, it is successfully predicted that the price of commercial housing in Wuhan will reach 18,207.9 yuan/m2 in 2030, which provides a more systematic method of prediction for synthesis simulation of commercial housing markets. From the perspective of the developer loan interest rate, real estate tax rate, purchase restriction, and other policies, we show that the developer loan interest rate regulation policy has the strongest effect on guiding the change in commercial housing prices in Wuhan. Generally, this study provides insight into the responses that the national government could use to control housing prices.
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Steinmetz, Alexander. "Price and Inventory Dynamics in an Oligopoly Industry: A Framework for Commodity Markets." B.E. Journal of Theoretical Economics 16, no. 1 (January 1, 2016): 159–80. http://dx.doi.org/10.1515/bejte-2014-0064.
Повний текст джерелаАнотація:
AbstractThis paper analyzes the interaction between price and inventory decisions in an oligopoly industry and its implications for the dynamics of prices. The work extends existing literature and especially the work of Hall and Rust (2007) to endogenous prices and strategic oligopoly competition. We show that the optimal decision rule is an $$(S, s)$$ order policy and prices and inventory are strategic substitutes. Fixed ordering costs generate infrequent orders. Additionally, with strategic competition in prices, $$(S, s)$$ inventory behavior together with demand uncertainty generates endogenous cyclical patterns in prices without any exogenous shocks. Hence, the developed model provides a promising framework for explaining dynamics of commodity markets and especially observed autocorrelation in price fluctuations.
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Syrovátka, Pavel. "Analysis of price interactions between Czech and world wheat markets." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 58, no. 6 (2010): 533–42. http://dx.doi.org/10.11118/actaun201058060533.
Повний текст джерелаАнотація:
The paper is focused on the analysis of the price interactions between the Czech and world markets for the wheat. The long-term interactions of the wheat market prices were tested by means of the co-integration analysis (Engle-Granger test). The dynamic autoregressive model developed by the author was used for evaluation of the short-term price interactions. Monthly time series of the market prices from January 1995 till April 2010 were obtained from the Czech Statistical Office and the International Monetary Fund. The results of the co-integration analysis showed, that the price dynamics in the world wheat market does not have a long-term impact on the level of prices in the Czech market for the given commodity. According to the constructed and statistically verified model, the short-term price interactions between the studied markets are not strong too. The value of the determination index (0.5063) implies other factors forming the price dynamics of the Czech wheat market.
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Belke, Ansgar H., Ingo G. Bordon, and Torben W. Hendricks. "Monetary policy, global liquidity and commodity price dynamics." North American Journal of Economics and Finance 28 (April 2014): 1–16. http://dx.doi.org/10.1016/j.najef.2013.12.003.
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Frankel, Jeffrey A. "Expectations and Commodity Price Dynamics: The Overshooting Model." American Journal of Agricultural Economics 68, no. 2 (May 1986): 344–48. http://dx.doi.org/10.2307/1241436.
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XIARCHOS, IRENE M., and J. WESLEY BURNETT. "DYNAMIC VOLATILITY SPILLOVERS BETWEEN AGRICULTURAL AND ENERGY COMMODITIES." Journal of Agricultural and Applied Economics 50, no. 3 (April 2, 2018): 291–318. http://dx.doi.org/10.1017/aae.2017.34.
Повний текст джерелаАнотація:
AbstractThis study contributes to the literature by using a spillover index method to examine the changing interrelations in volatility among corn and energy future prices. This methodology allows us to account for endogenously determined economic fundamentals and market speculation. After controlling for market trends and seasonality, we find relative large increases in volatility spillovers between corn, crude oil, and ethanol futures prices. Our results suggest that the cross-commodity spillovers provide useful incremental information in determining future price volatility; however, a commodity's own dynamics explain the largest portion of volatility spillovers.
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Salisu, Afees Adebare, and Idris A. Adediran. "The U.S. Shale Oil Revolution and the Behavior of Commodity Prices." Econometric Research in Finance 3, no. 1 (September 3, 2018): 27–53. http://dx.doi.org/10.33119/erfin.2018.3.1.2.
Повний текст джерелаАнотація:
The United States is committed to technological improvements in horizontal drilling and hydraulic fracturing in its drive of toppling the world's leading oil producers by the mid-2020s and evolving into a net oil exporter by 2030. Consequently, these technological innovations revolutionized the U.S. oil sector and the international oil market with increasing relevance of the shale oil and attendant shock spillovers to financial and commodity markets. Upon these attractions and consistent with evidence in the literature, we trace the oil price and commodity price dynamics to the shale oil revolution using a recursive structural VAR model of the shale supply shocks. In line with the standard practice of ensuring sensitivity of results, we conduct analyses such as impulse responses, forecast-error variance decomposition, and historical decompositions to accommodate energy and nonenergy commodity components. We show, in addition to the popular view in the extant literature, that the shale oil revolution is not only associated with the recent oil price plunge, but also responsible for the tumble in the total energy-based commodity prices with crude oil price being just a component.
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Gao, Debao. "Analysis of 3D Cobweb Economic Differential Dynamic System Based on Supply-Demand and Price Relationships." Discrete Dynamics in Nature and Society 2022 (March 7, 2022): 1–10. http://dx.doi.org/10.1155/2022/2742485.
Повний текст джерелаАнотація:
When the supply and demand of commodities are out of equilibrium, the dynamic changes in supply and demand are mainly manifested in the dynamic fluctuation of commodity prices and the change of price will drive the change of supply and demand. This paper proposes a method for constructing a three-dimensional cobweb economic model using the “predator-prey” theory. Firstly, based on the intrinsic driving relationships among supply, price, and demand, a differential dynamic model of the commodity and a pulse differential model when productivity increases are established. Secondly, the differential dynamics theory is used to analyze the existence of the model’s positive equilibrium and to prove its global asymptotic stability, uniform boundedness, persistence, and existence of the periodic solution. Finally, the correctness of the conclusions of the model is verified by numerical simulation. The relevant conclusions of model (1) reveal the evolution laws of supply, price, and demand that fluctuate around the positive equilibrium and tend to balance. Model (32) reveals that with the continuous improvement of production technology, supply quantity, price, and demand will fluctuate, but all three will change periodically. These conclusions can provide valuable help for people in the production, sale, and purchase of goods.
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Svetlov, Nikolai. "Influence of strategic consumers on the network goods market." Economics and the Mathematical Methods 57, no. 4 (2021): 5. http://dx.doi.org/10.31857/s042473880017514-4.
Повний текст джерелаАнотація:
One of the important trends in modern economic development is the expanding variety ofso-called network commodities. Network commodity is such a good the usefulness of which for each consumer depends on the total number of using it consumers. The purpose of the paper is to study dynamic pricing in the network commodity market with a positive network effect in the presence of two types of consumers: myopic, taking into account only the current utility of the commodity, and strategic, focused on utility for the entire period of use of the commodity. Market dynamics, including price trajectories maximizing the monopolist supplier's revenues, are established by running numerical experiments on the corresponding theoretical model. The features of this dynamics are revealed for the cases of a large share of myopic consumers and under the conditions of dominance of strategic consumers. It is demonstrated that, in contrast to the situation in the market of ordinary commodities, a monopoly supplier of the network commodity may be interested in the presence of strategic consumers in the market. The more such consumers are present, the shorter the period of warming up the market by the supplier by means of low prices and the higher the rate of the consequent price growth. Strategic consumers find themselves hostage of their own focus on the integral effect in consumption. The directions of further research of the market of network commodities with the heterogeneous consumers are presented.
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Plummer, P. "Competitive Dynamics in Hierarchically Organized Markets: Spatial Duopoly and Demand Asymmetries." Environment and Planning A: Economy and Space 28, no. 11 (November 1996): 2021–40. http://dx.doi.org/10.1068/a282021.
Повний текст джерелаАнотація:
In recent years, there has been considerable interest in the impact of corporate organizational structure on the configuration of prices, outputs, and profits in spatially extensive markets. In previous research I examined the general and analytical conditions defining both the existence and stability of an equilibrium in hierarchically organized spatial markets dominated by oligopolistic corporations that distribute a commodity directly to consumers through their retail franchises. Here I examine the disequilibrium dynamics resulting from this model. A bilevel decisionmaking process is hypothesized in which corporations vary their delivered prices in response to changes in urban market demand and in which franchises vary their retail prices in response both to changes in the cost of the commodity from their parent corporation and to the pricing strategies pursued by their competitors. The complexity of interactions operating between the two levels of the model and the presence of asymmetrical demand conditions facing duopolistic corporations suggests that it is unlikely that an overall spatial price equilibrium can actually be reached by such disequilibrium price-adjustment strategies.
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Pani, Upananda, Ştefan Cristian Gherghina, Mário Nuno Mata, Joaquim António Ferrão, and Pedro Neves Mata. "Does Indian Commodity Futures Markets Exhibit Price Discovery? An Empirical Analysis." Discrete Dynamics in Nature and Society 2022 (March 8, 2022): 1–14. http://dx.doi.org/10.1155/2022/6431403.
Повний текст джерелаАнотація:
Price discovery function analyses the dynamics of futures and spot price behavior in an asset’s intertemporal dimensions. The present study examines the price discovery function of the bullion, metal, and energy commodity futures and spot prices through the Granger causality and Johansen–Juselius cointegration tests. The Granger causality test results show bidirectional causality between the spot and futures returns for gold, silver, aluminum, lead, nickel, and zinc. The Johansen cointegration test shows that spot and futures prices are in the long-run equilibrium path for silver, aluminum, lead, nickel, zinc, crude oil, and natural gas. The vector error correction model results suggest that both the spot and futures markets are equally efficient in price discovery for the nickel. The spot market leads the futures market in price discovery for copper and zinc. However, the futures market leads the spot market in price discovery for silver, aluminum, and lead. The findings of the study suggest the market participants for implementing hedging and arbitrage strategies. It also helps the market regulators to examine the stability of these rapidly growing commodity futures markets in India.
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Bodhanwala, Shernaz, Harsh Purohit, and Nidhi Choudhary. "The Causal Dynamics in Indian Agriculture Commodity Prices and Macro-Economic Variables in the Presence of a Structural Break." Global Business Review 21, no. 1 (October 25, 2018): 241–61. http://dx.doi.org/10.1177/0972150918800561.
Повний текст джерелаАнотація:
Agriculture commodity prices have been quite volatile in India. The proposed study explores the effect of structural change on the flow of information between the spot and futures market of agriculture commodities and select macro-economic factors. The volatility in agriculture commodity prices is studied with respect to three dominant macro-economic factors—movement in crude price which serves as an input to agriculture sector, movement in INR/USD exchange rate and movement in Sensex which is considered as a barometer of investment in India. The study uses non-linear cointegration and causality test to understand the direction of causality in volatility of commodities and impact of macro-economic factors. The study observed the agriculture commodities spot and futures prices to be co-integrated with crude, forex and Sensex for majority of the break periods. We find robust evidence that futures market played a leading role in the price discovery function and information processing. Breaks in agriculture commodity prices are attributed to fundamentals of demand and supply in the market and global financial turmoil of 2007. We observed mixed results of influence of the exchange rate, Sensex and crude on agriculture prices in different sub-periods.
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Lagi, Marco, Yavni Bar-Yam, Karla Z. Bertrand, and Yaneer Bar-Yam. "Accurate market price formation model with both supply-demand and trend-following for global food prices providing policy recommendations." Proceedings of the National Academy of Sciences 112, no. 45 (October 26, 2015): E6119—E6128. http://dx.doi.org/10.1073/pnas.1413108112.
Повний текст джерелаАнотація:
Recent increases in basic food prices are severely affecting vulnerable populations worldwide. Proposed causes such as shortages of grain due to adverse weather, increasing meat consumption in China and India, conversion of corn to ethanol in the United States, and investor speculation on commodity markets lead to widely differing implications for policy. A lack of clarity about which factors are responsible reinforces policy inaction. Here, for the first time to our knowledge, we construct a dynamic model that quantitatively agrees with food prices. The results show that the dominant causes of price increases are investor speculation and ethanol conversion. Models that just treat supply and demand are not consistent with the actual price dynamics. The two sharp peaks in 2007/2008 and 2010/2011 are specifically due to investor speculation, whereas an underlying upward trend is due to increasing demand from ethanol conversion. The model includes investor trend following as well as shifting between commodities, equities, and bonds to take advantage of increased expected returns. Claims that speculators cannot influence grain prices are shown to be invalid by direct analysis of price-setting practices of granaries. Both causes of price increase, speculative investment and ethanol conversion, are promoted by recent regulatory changes—deregulation of the commodity markets, and policies promoting the conversion of corn to ethanol. Rapid action is needed to reduce the impacts of the price increases on global hunger.
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Choi, Michael, and Guillaume Rocheteau. "Money Mining and Price Dynamics." American Economic Journal: Macroeconomics 13, no. 4 (October 1, 2021): 246–94. http://dx.doi.org/10.1257/mac.20200034.
Повний текст джерелаАнотація:
We develop a random-matching model to study the price dynamics of monies produced privately according to a time-consuming mining technology. For our leading example, there exists a unique equilibrium where the value of money increases over time and reaches a steady state. There is also a continuum of perfect-foresight equilibria where the price of money inflates and bursts gradually over time. Initially, money is held for a speculative motive, but it acquires a transactional role as it becomes sufficiently abundant. We study fiat, commodity, and crypto monies, endogenous acceptability, and adopt implementation and equilibrium approaches. (JEL E31, E42, E51, N13, N14, N23, N24)
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Gordon, J. Douglas. "Expectations and Commodity Price Dynamics: The Overshooting Model: Comment." American Journal of Agricultural Economics 69, no. 4 (November 1987): 852–55. http://dx.doi.org/10.2307/1242198.
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Frankel, Jeffrey A. "Expectations and Commodity Price Dynamics: The Overshooting Model: Reply." American Journal of Agricultural Economics 69, no. 4 (November 1987): 856. http://dx.doi.org/10.2307/1242199.
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Xue, Huidan, Chenguang Li, Liming Wang, and Wen-Hao Su. "Spatial Price Transmission and Price Dynamics of Global Butter Export Market under Economic Shocks." Sustainability 13, no. 16 (August 19, 2021): 9297. http://dx.doi.org/10.3390/su13169297.
Повний текст джерелаАнотація:
Recently, the world has experienced striking economic and policy changes, and subsequent uncertainties have impacts on dairy trade price fluctuations. The Global Vector Autoregressive (GVAR) methodology was established in this paper to better understand international butter export prices transmission, the feedback between the economic context changes and price fluctuations, and the link between the global butter market, energy market, and other commodity markets. We assessed which key factors are typically associated with butter export price movements with regards to shocks to crude oil price, palm oil price, farm-gate raw milk price, exchange rates, and consumer price index (CPI) for food of the EU, New Zealand, the U.S., and the rest of world (RoW), respectively. Using generalized impulse response functions, this study found that decreases in farm-gate raw milk price could be swiftly transmitted to butter export prices of not only a home country but other foreign countries. However, palm oil price and crude oil price merely affects global butter export prices. We also found that U.S. dollar depreciations against the Euro will cause a decline in U.S. butter export price. It is concluded that butter export markets are not well-integrated, yet butter export prices of New Zealand and the U.S. are highly linked.
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Dincerler, Cantekin, Zeigham Khokher, and Timothy Simin. "An Empirical Analysis of Commodity Convenience Yields." Quarterly Journal of Finance 10, no. 02 (June 2020): 2050009. http://dx.doi.org/10.1142/s2010139220500093.
Повний текст джерелаАнотація:
We study convenience yield dynamics using a dataset of inventories to proxy for relative scarcity. We confirm that convenience yields are negatively related to inventories although they plateau during periods of scarcity for crude oil. Inventory withdrawals are non-monotonically related to the convenience yield and they forecast significant futures returns. Testing for the effect of demand shocks, we document both temporary and permanent price components. Importantly, we show that mean reversion in expected equilibrium prices varies with relative scarcity. This result suggests an important bias in contingent claims models in extant practice.
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Janda, Karel, Eva Michalikova, Luiz Célio Souza Rocha, Paulo Rotella Junior, Barbora Schererova, and David Zilberman. "Review of the Impact of Biofuels on U.S. Retail Gasoline Prices." Energies 16, no. 1 (December 30, 2022): 428. http://dx.doi.org/10.3390/en16010428.
Повний текст джерелаАнотація:
This study aims to provide a review of the state-of-the-art literature regarding the impacts and contributions of corn ethanol on retail gasoline prices in the US. For this, a systematic literature review following PRISMA statement was carried out, seeking to answer four research questions: (1) What are the main characteristics of the literature regarding the impact and contributions of ethanol on US retail gasoline prices? (2) What are the main article clusters identified in the evaluated literature? (3) What was the numerical impact of the Volumetric Ethanol Excise Tax Credit/Renewable Fuel Standard (VEETC/RFS) mandate on the price of gasoline and what are the main methods used for calculation in the literature? (4) What are the main trends and possibly new research directions for this literature? As a result of the characterization of the sample, driving themes, such as energy policy, costs, price dynamics, trade and energy market, were identified. Furthermore, three main clusters were identified in the sample: (i) impacts of biofuels on commodity prices and general price dynamics; (ii) impacts of public policies on the implementation of ethanol and flexibility in formulating fuel blends; and (iii) impact of biofuels on environmental aspects. As a practical implication, the prevailing result in the analyzed literature is that the addition of ethanol reduces the price of gasoline at the pump, and estimates range from no effect to nearly 10% off the price of gasoline. Finally, the topic on the impacts of biofuels on commodity prices and on the general dynamics of prices is the most relevant research line and the trend suggested by the proposed research agenda.
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Sipiczki, Zoltán, and József Varga. "Inflation Dynamics and Food Prices in Hungarian Agricultural Economy." Acta Carolus Robertus 12, Különszám (2022): 130–41. http://dx.doi.org/10.33032/acr.3436.
Повний текст джерелаАнотація:
During 2021-2022, many commodity prices rose to record levels. As a result, Hungary in 2022 experiencing high inflation, large trade deficits, and an unstable macroeconomic environment. High commodity prices, particularly for food, also have adverse effects on poverty. Hungary has not experienced for a long time such increase in inflation, which is among the highest in Europe. Inflation growth has recently associated with large energy price shocks, food price increases are traditionally believed to have rather small effects. At the same time, there has been an absence of rigorous work to identify empirically the relative importance of each factor contributing to inflation. It is thus of vital importance to improve the understanding of the causes of inflation in Hungary to allow adequate policies to be put in place. The purpose of this paper is to fill this gap and thoroughly analyze the determinants of inflation in Hungary using data for the current decade, with a focus on food prices. The authors identify the relative importance of several factors contributing to overall inflation and its major components. The main finding is that, in a longer perspective, one of the main factors that determine domestic inflation are the food prices. In the short run, agricultural supply shocks strongly affect domestic inflation, causing large deviations from long-run price trends. The results suggest the need for a multi-pronged approach to fight inflation. This analysis suggest monetary and exchange rate policies need to take into account agricultural production, which is among the key determinants of inflation. Moreover it has a greater influence on inflation than is widely known.
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Rishabh, Kumar, and Somnath Sharma. "Global Liquidity, Financialization and Commodity Price Inflation." Journal of International Commerce, Economics and Policy 06, no. 02 (June 2015): 1550012. http://dx.doi.org/10.1142/s179399331550012x.
Повний текст джерелаАнотація:
This paper examines the effect of global liquidity and financialization on commodity price inflation. The novelty of the paper lies in exploiting recent advances in our understanding of global liquidity by separating private liquidity from official liquidity and digging into disaggregated level non-commercial commodity traders data. Private liquidity is found to be inflationary, while official liquidity is not. Among the non-commercial traders, both, active money managers and passive swap dealers seem to have played an important role in commodity inflation dynamics during the period 2006–2012. The paper also discusses emerging policy issues in a rapidly changing global commodities market.
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Woods, Bethany. "Links between food price behaviour and nutrition in the developing world." SURG Journal 5, no. 2 (April 22, 2012): 51–62. http://dx.doi.org/10.21083/surg.v5i2.1785.
Повний текст джерелаАнотація:
With the recent financial crisis and its enduring fallout, questions surrounding the state of global food security have become more pressing. A key element influencing the nutritional status of the world’s poor is price behavior within global food commodity markets. In recent decades, food commodity markets have experienced both significant price increases, and an increase in volatility. These price trends have had significant impacts on the diversity of diets in impoverished households worldwide, which in turn has impacted nutrition and health. This paper will discuss the causes behind recent trends in food commodity prices, and the extent of their impact on food security and nutrition. Specifically, it will address the impact of food price increases and the uncertainty induced by food price volatility on household food consumption and nutrition. Micronutrient intake is the focus of the nutritional discussion of this work, and variations of consumption behavior in various regions and within different household dynamics are all taken into account. Existing policy actions are discussed in terms of the frequency of their implementation, the factors encouraging or deterring their implementation, and their intended and unintended consequences. Finally, the paper concludes with suggestions for future actions and areas for future research.
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Cabrales, Carolina Arteaga, Joan Camilo Granados Castro, and Jair Ojeda Joya. "The Effect of Monetary Policy on Commodity Prices: Disentangling the Evidence for Individual Prices." Economics Research International 2014 (December 24, 2014): 1–13. http://dx.doi.org/10.1155/2014/649734.
Повний текст джерелаАнотація:
We study the effect of monetary policy shocks on commodity prices. While most of the literature has found that expansionary shocks have a positive effect on aggregate price indices, we study the effect on individual prices of a sample of four commodities. This set of commodity prices is essential to understand the dynamics of the balance of payments in Colombia. The analysis is based on structural VAR models; we identify monetary policy shocks following Kim (1999, 2003) upon quarterly data for commodity prices and their fundamentals for the period from 1980q1 to 2010q3. Our results show that commodity prices overshoot their long run equilibrium in response to a contractionary shock in the US monetary policy and, in contrast with literature, the response of the individual prices considered is stronger than what has been found in aggregate indices. Additionally, it is found that the monetary policy explains a substantial share of the fluctuations in prices.
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Ramadhan, Gaffari. "ANALISIS KETERKAITAN HARGA ANTAR KELOMPOK KOMODITAS PEMBENTUK INFLASI DI SUMATERA BARAT." Buletin Ekonomi Moneter dan Perbankan 11, no. 3 (May 25, 2009): 233–74. http://dx.doi.org/10.21098/bemp.v11i3.338.
Повний текст джерелаАнотація:
This study analyzes the correlation and the interaction among commodity groups which determine the inflation rate in West Sumatera. Using the monthly data from January 2002 to December 2008, the estimation applies the Vector Error Correction Model (VECM) in order to analyze the dynamics of commodity prices in the model.The results show some groups have significant contributions in determining other group prices. We found that the volatility of Prepared Food, Drink, Cigarette, and Tobacco is affected by Food group, Transportation, Communication and Financial Services. All commodity group is mostly affected by its own movement, especially for the high regulated prices group; Water, Electricity, and Fuel group including Housing.This paper underlines that in controlling regional inflation, the partial effort by focusing only on the basket goods which gives the highest contribution to the regional inflation (i.e. foodstuff and prepared food) is not effective when the region faces high volatility in other basket goods (i.e. transportation). The price determining of basket goods is a simultaneous process, and controlling the regional inflation needs greater concern to all goods. The government intervention on the price setting is also one of the important parts in causing the volatility of the basket goods.JEL Classification: C32, E31, R10.Keywords: Consumer Price Index, regional inflation, vector error corection model, impulse response, variance decomposition.
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Manera, Matteo, and Apostolos Serletis. "INTRODUCTION TO MACROECONOMIC DYNAMICS SPECIAL ISSUE ON DYNAMICS OF OIL AND COMMODITIES PRICES." Macroeconomic Dynamics 22, no. 3 (December 29, 2016): 541–45. http://dx.doi.org/10.1017/s1365100516000341.
Повний текст джерелаАнотація:
This special issue of Macroeconomic Dynamics presents a timely and fresh body of high-quality research on the complexity and evolution of the international oil markets, the dynamics of the price of oil, and the financialization and the interconnections of oil, energy, and nonenergy commodity markets.
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Sun, Mao, and Yong Zhou. "Based on the Coordinated Development of CGE Model of Affordable Housing and Commercial Housing Research." Advanced Materials Research 1079-1080 (December 2014): 1089–92. http://dx.doi.org/10.4028/www.scientific.net/amr.1079-1080.1089.
Повний текст джерелаАнотація:
Construction of affordable housing is not possible, their development and the development of commodity housing market should adapt to achieve coordinated development. Based on previous studies, drawing on ideas put forward specific judgment of affordable housing and the coordinated development of commodity housing, that is, under the premise to meet the total demand, through reasonable adjustments to the proportion of affordable housing and the supply of commodity housing, thereby affecting the price of commodity housing, strikes a reasonable price earnings ratio. In this coordination criteria, the paper uses system dynamics theory constructed residential market system dynamics model, and in Xi'an City, for 2003 and 2020 in Xi'an residential market simulation, testing the validity of the model; Furthermore performed by adjusting the supply of affordable housing a large number of simulation experiments, and ultimately determining the affordable housing and the coordinated development of commodity housing supply ratio between the two is 21.88%: 78.12%, and accordingly proposed to promote the coordinated development of both policy recommendations.
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Gutierrez, Luciano, Guillaume Pierre, and Maria Sabbagh. "Agricultural Grain Markets in the COVID-19 Crisis, Insights from a GVAR Model." Sustainability 14, no. 16 (August 10, 2022): 9855. http://dx.doi.org/10.3390/su14169855.
Повний текст джерелаАнотація:
The objective of this paper is to combine cross-commodity and spatial price transmission analysis to study the dynamics of the global cereal feed market during the COVID-19 pandemic. After reviewing the nascent literature on the impact of COVID-19 on agricultural markets, we discuss the different impact channels on prices. Then, we provide stylized market reactions of three relevant feed markets, wheat, barley, and maize, to a set of simulated possible future shocks on oil prices, stock-to-use ratios, and export restrictions. These three shocks are useful to assess what could be the consequences of policy responses to COVID-19 (export restrictions) or the disruptions due to the virus (stock-to-use reductions), in a context of lower oil prices. To generate these market reactions, we use a Global Vector Auto Regression (GVAR) model where each market is modelled independently, and connected through trade-based composite variables. We expand the work on the global wheat market by introducing maize and barley. The results of the empirical analysis indicate that the fall in the oil price may have contributed to the stability of the world grain market in early 2020, despite fears of supply chain disruption. We also note that export restrictions could significantly increase global prices, and that such restrictions could affect more than the targeted commodity, through significant cross-commodity price linkages.