Cotton Prices Research Articles

Price Transmission in Cotton Futures Market: Evidence from Three Countries

This study examines the price transmission between cotton prices in U.S., Indian, and Chinese futures markets. We focus on studying the long-run price movements using cointegration and alternate causality tests. The empirical results indicate the following: (a) the U.S. cotton futures market continues to be the most dominant market, and it leads price changes in India and China; (b) the cotton prices in India also impacts the cotton prices in China as we report a unidirectional relationship flowing from India to China; (c) there is duality of direction of price transmission for U.S. and Chinese commodity markets as we document bi-directional causality between U.S. to Chinese cotton futures for the entire period and uni-directional causality from U.S. to Chinese markets for the two sub-periods; (d) the long-term relationship between the three markets has seen a significant shift as documented by the absence of cointegration which may be due to changes in government policy, especially in India and China specifically after 2014. Overall, results provide support for further reforms especially for Indian and Chinese commodity exchanges so that they can play a vital role in the price discovery process especially for commodities that are largely produced or consumed in these economies.

The effect of China's domestic public storage on world market prices: the case of cotton

PurposeDuring world price spike periods, the government is more likely to apply trade distortions to stabilize domestic prices, but the trade distortions would amplify fluctuations of international market prices. Which type of policy may stabilize the domestic market price, but not disturb the international market? This paper answers the question by taking public storage policy as a case study in the context of trade policy. Specially, this paper tries to identify the effect of domestic public storage on the world market price.Design/methodology/approachThis article extends a standard theoretical model of trade policy through incorporating domestic public storage policy and makes the model more applicable in the context of China. The extended model is then applied to analysis how domestic public storage policy affects the international market price in the context of trade policy. Finally, a properly identified structural vector auto-regression technique is applied to test the effect of domestic public storage on the world market price by using cotton data from China.FindingsThe theoretical model indicates that China's public storage policy could stabilize the international market price. In order to test the working mechanisms, China's soaring public storage between 2010 and 2014 is employed to identify the effects of China's cotton storage on the volatility of the world price. The empirical findings show that China was able to stabilize the international price of cotton to a non-trivial extent through alteration of its public stockpile.Originality/valueThe first contribution is that this paper extends a standard theoretical model of trade policy to incorporate domestic public storage policy, which enables us to explore the effects of domestic public storage policy on the world price in the context of China. The second major contribution is that this paper provides evidence that, as a large player in the world market, China's public storage policy could stabilize the international agricultural price to a substantial degree.

Profitability of farm-scale management strategies against the boll weevil in the tropics: case study from the Colombian Caribbean

Decision making in pest management is a challenging task. While pest dynamics are often quite uncertain, such decisions are often based on tenuous assumptions of certainty (economic injury levels and marginal utility approximations). To overcome such assumptions and adequately consider uncertainty, we apply decision analysis to evaluate management strategies used by farmers in the Colombian Caribbean against the boll weevil (BW). We represent the decision to protect the crop using partial budget analysis. This allows us to capture key properties of BW control strategies, while accounting for uncertainty about pest infestation pressure, control effectiveness and cotton yield and price. Our results indicate that proactive pest management is more efficient than reactive control given the current BW infestation pressure. However, farmers may prefer the reactive strategy, since they have experienced seasons with low infestation pressure where no insecticide applications were required. The proactive strategy, in contrast, requires scheduled pesticide applications in all years. Results show that in seasons with high infestation pressure the expected revenues of the reactive strategy tend to decrease, mainly because more spray applications are required when fields are heavily infested by the weevil. Value of information analysis revealed that uncertainties related to the start of the infestation, loss damage rate and attainable yield have the greatest influence on the decision recommendation for crop protection. Narrowing these key knowledge gaps may offer additional clarity on the performance of the current management strategies and provide guidance for the development of strategies to reduce insecticide use. This is particularly important for the promotion of the proactive strategy, which, under the current infestation pressure, has potential to reduce insecticide use. While economic injury levels can only be applied to responsive measures, our approach of partial budget analysis under uncertainty allows us to assess and compare both responsive and preventive measures in the same methodological framework. This framework can be extended to non-pesticide control measures.

Machine learning regression model for material synthesis prices prediction in agriculture

Agriculture is the back bone of India, one of the major sources for some notable population from past decade, slowly the agriculture is facing downward growth. Due to less rain fall, they are not getting proper yield, and also expected price for their crops. The farmers are getting loss or less profit. If they know the price of particular commodity, accordingly they can grow selected crop depending upon their geographical area. We can use some of the machine leaning regression algorithms to predict the price of the agricultural commodities that helps the formers to do the decision making. This research work focus on detailed study of predicting the price of the cotton using five different ML regression algorithms namely Linear Regression, Bayesian Linear Regression, Boosted Decision Tree Regression, Decision forest Regression, Poisson Regression. Metrics for evaluating the performance of ML model. The Data set contains the cotton prices of different states of India. The cotton price 2019 data set is used for this work and the prediction values are compared with 2020 data set and the predicted prices are nearing to the actual values. Compare to all other algorithms Boosted decision tree giving the good accuracy, after that Bayesian and Linear regression also performing well.

RETRACTED: Computer prediction of cotton and sporting goods prices in e-commerce environment based on ARIMA model

In the current society, e-commerce is enjoying extremely rapid development, with a goal of helping enterprises smooth their production process, management process and trade process. China has always been the center of world's garment industry, especially in the production sector of sportswear, in which it has become the world's sportswear production outsourcing center and an important market. In this paper, time series analysis method is used to analyze the weekly data of settlement price of common cotton price (unit: yuan/ton) from March 3rd, 2003 to May 7th, 2012 in China. ARIMA (2,1,3) model is established to fit and predict the future price of Chinese sportswear. The fitting results show that the prediction effect of the model is quite impressive, that in a short run, the settlement price of ordinary blended Cotton price will continue to rise. This result can provide certain reference for enterprises closely related to sportswear production enterprises, to seek profits and avoid disadvantages, and grasp the initiative of economic decision-making to win profits for enterprises.

Climate Change, Cotton Prices and Production in Cameroon

This study aims to examine the impact of (i) climate change and international market price volatility on cotton production in Cameroon, (ii) climate change and international market price volatility on the prices of cotton farmers, (iii) the purchase price of cotton farmers on cotton production, (iv) cotton production on the purchase price of cotton farmers. The statistics used mainly come from the SODECOTON database, the World Bank Group Climate Change Knowledge Portal and Trading Economics. Econometric estimates made using a VAR model reveal that (i) the purchase price of seed cotton tends to significantly boost production, (ii) production does not significantly influence the purchase price of seed cotton, and (iii) the increase in the world price of cotton and significant variations in temperature are conducive to a revaluation of the purchase price of seed cotton. To improve cotton production, it would be advisable, in particular, to (i) make the purchase price of seed cotton more attractive to cotton growers and (ii) adopt effective adaptation or mitigation techniques against variations in rainfall.

Impact of cropping pattern shift on livelihood assets of the farmers in Punjab, Pakistan

Cotton area is shrinking in Pakistan as the farmers have started adopting sugarcane for many reasons such as increasing number of sugar mills in core cotton areas. This study aimed at exploring the impacts of this cropping pattern shift on livelihood of the farmers. This study was conducted in district Rahim Yar Khan, one of the cotton core area of Punjab province. Total 400 farmers participated in the study. A well-structured interview schedule was administered in the field to conduct face to face interviews of the respondents. Descriptive statistics were applied to analyze the collected data through the Statistical Package for Social Sciences (SPSS) to form conclusions and to make recommendations. The results indicated that knowledge and skills about production of other crops, linkage with research and development institutions, livestock possession and cash income of the respondents increased in result of cropping pattern shift. Conversely, land fertility and water conservation were compromised after shifting from cotton to sugarcane crop in the study area. This study urges further exploration of merits and demerits of cropping pattern shifts followed by the impacts on agricultural system in the country. It is further recommended that the government should revamp the cotton policy for the coming year. For instance, announcing and sustaining a minimum support price of cotton for cotton growers could reinstate the growers to cotton cultivation.

Profitability of irrigating for corn, cotton, and soybeans under projected drought scenarios in the Southeastern United States

This study estimates breakeven price distributions for irrigated and non-irrigated corn, cotton, and soybean production in Tennessee under conventional tillage and no-till for three field sizes and two sources of energy for irrigation. The distributions were compared using forecasted prices of corn, cotton, and soybean realized under different climate scenarios. The price simulation focuses on the short-, medium-, and long-term impacts of drought-induced yield reduction on commodity market prices. Electric pump irrigation systems in the southeastern United States have lower energy costs and, thus, a lower breakeven price than diesel-fueled irrigation pumps. A corn producer could obtain a lower breakeven price per kg by irrigating fields of 51–81 hectares. Cotton and soybean producers managing fields of 81 hectares or less could realize lower breakeven prices by not irrigating. Under extended drought conditions during which the market price for corn, soybeans, and cotton are higher, irrigated corn is more likely to be profitable compared to irrigated cotton or soybeans. These results could inform the development of irrigation management plans for row crop producers in the southeastern United States.

Farmers’ Knowledge of Integrated Pest Management of Cotton Crop in Some Villages of Ismailia Governorate

The aim of this research was to determine knowledge level of the farmers concerned the integrated pest management recommendations (IPM) of cotton at Ismailia Governorate. In addition to determine the correlation relationship between knowledge degree of the farmers and the studied variables. Furthmore, determine the information sources of the (IPM) . Consequently, identification of the most important problems facing cotton growers in the research area . This research was conducted in Ismailia on a sample of 302 respondents with a percentage of 22% of the whole farmers of country Data were collected through which a personal interview guided by a questionnaire during the months of March of 2020, and the data were quantitatively processed and statistically analyzed using the tabular presentation with frequency, percentages, and arithmetic mean , And the simple correlation coefficient. The most important results were: - The general level of knowledge of the surveyed farmer was low regarding with their knowledge about the integrated management methods, it reaches 48.4% of the respondents. - Farmers of knowledge degree was average regarding both of application of Agricultural duration and agricultural Practices that reaches to 51.8% besides the use of mechanical control which found to be 59%, On the contrary, farmers knowledge level regarding was use of legislative control was low as it reached 40% likewise the chemical control that found to be 42.8% of the respondents. - It was found that there was a correlation a significant between the Farmers’ Technical Knowledge of (IPM) on Cotton Crop and the age variable of the surveyed farmer (-.147*) however,this relationship goes direct at a significant level (0.01) for the surveyed farmer according to : The degree of regular education, years of experiences of (IPM) and the rate of visit of the IPM experts which found to be 0.232 ** , 0.287 ** and 0.211 **, respectively . - The most reliable information sources of IPM were : family, neighbors and friends, director of the agricultural administration, director of the extension center, and local leaders with a percentage of 96%, 83%, 70%, 58%, respectively . - The most important problems facing farmers in the field of using (IPM) of Cotton were: the low price of the cotton quintal, high labor costs, high costs of weeds control, high prices of insecticides and chemical fertilizers beside the equal prices of cotton among farmers regardless of their rank with percentage of 88.7%, 82.8%, 77.2% and 73.5%, respectively.

Microeconomics and raw material price on capital structure adjustment through dynamic target in Indonesian textile industries

This study aims to examine the effects of company-specific macroeconomic fluctuation in raw materials prices on the speed of adjustment through dynamic targeting capital structure on textile companies listed on the Indonesia Stock Exchange during 2012 and the second quarter of 2020. Using panel data regression of the fixed-effect method, we discovered that the speed of adjustment varies in each industry and period. Textile companies listed on the Indonesia Stock Exchange adjust their capital structure through a dynamic target of 53.3% per year. It takes 1 year and 10 months to close the target capital structure. The factors that determine the target capital structure include company size, tangibility, liquidity and growth opportunity, asset utilization, as well as retained earnings. On the other side, factors that contribute to the speed of adjustment include company size, growth opportunity, earnings volatility, asset utilization, retained earnings, distance to the target, and economic growth. Other factors that also affect the speed of adjustment include fluctuations in the prices of cotton and crude oil. The result of this study is expected to provide an optimal capital structure formulation to the textile industries in Indonesia to finance companies’ operational activities and growth opportunities effectively. This study also provides an overview of how textile companies make capital structure adjustment, as there are changes in company-specific factors, macroeconomic conditions, and fluctuation in raw material prices.

Developed Countries Agricultural Subsidies and Cotton Production in Burkina Faso: An Analysis Using the Vector Autoregressive Model (VAR)

For several years, cotton prices have been experiencing a sustained decline on the world market. For cotton-producing developing countries, this low price is the result of subsidies granted by developed countries, particularly the United States and the European Union to their producers. As a result, these developing countries expect substantial gains in trade and economic development once the subsidies are ended. This article aims to analyze the effect of U.S. and European subsidies on the production of Burkina Faso, one of Africa’s leading cotton exporters whose cotton sector is currently experiencing serious difficulties. The data used in this thesis are secondary data, drawn from existing databases or specialized journals and using an econometric model, the Vector Auto Regressive (VAR) model, the analysis shows that a negative and significant impact of subsidies on cotton production in Burkina Faso is highlighted. The consequences of the end of subsidies on the Burkinabe economy should be positive. Analysis by the VAR model through impulse response functions shows that U.S. and European subsidies negatively affect Burkina Faso’s cotton production and that these impacts do not occur directly but through the world price of cotton. Therefore, the State, cotton companies and producers, the three main actors in the sector, should see their situation improve simultaneously in the event of subsidy removal.

Spatial equilibrium analysis of Chinese tariff on world cotton markets

AbstractWe develop a theoretical and an empirical spatial equilibrium model (SEM) to analyse the effects of the 25% Chinese cotton tariff on United States, Chinese and world markets. The tariff causes US cotton price, production and exports to decrease, while simultaneously increasing China's price and production. The SEM determines the trade reallocations caused by the Chinese tariff. The United States diverts some of its exports to other importing countries, which allows the United States to mitigate some of its losses. Other cotton exporters increase their exports to China at the expense of the United States.

Yield estimation and profitability of cotton production in Northern Nigeria

The study estimated the yield and profitability of cotton production in northern Nigeria. Primary data were used for the study using a well-structured questionnaire and experimental plots. Data were collected on the cost of inputs, price and quantity of output as well as constraints facing the enterprise. Crop cut experiment was used to estimate the yield per hectare during a given cultivation cycle. The budgetary technique was used to estimate cost and returns to cotton production and Likert scale was used to identify and rank the constraints facing the enterprise. Random Sampling was employed to select eleven cotton farmers from Anka, Maru and Talata-mafara Local Government Areas to have a sum of thirty-three respondents from which one respondent from each of the three local governments volunteered to host the experimental plot for the crop cut. These selections were done based on their prominence in cotton production. The average estimated quantity of the three plots located in the three local government gives an estimated value of 1183 kg/ha. The study showed that cotton production is profitable with a gross margin of ₦40 while the profit index and benefit-cost ratio were 0.12 and 1.13 respectively. Major constraints facing the production of cotton were insufficient funding, poor/unstable pricing, high cost of inputs, policy summersault, poor linkage with off-takers and pest and diseases. This study recommends that governments at all levels should provide loans with no or very low interest for the farmers to solve the problem of funds and put in place policy measures aimed at regulating the price of cotton to establish a good marketing system. There is a need for research institutes to develop more high yielding cotton seeds for cotton farmers to increase yield for more profit. Cotton farmers need to be introduced to new techniques and innovations for maximum output, hence a need for more extension services. Keywords: Cotton production, crop cut experiment, profitability.

Development of portable user-interactive holographic information collector for agricultural product markets

The efficient and accurate collection of agricultural product market information serves as the basis for the effective regulation of agricultural product markets. To achieve a comprehensive, accurate, and timely collection of agricultural product market information, this study puts forth a technique for collecting holographic information of agricultural product markets. A portable human-machine interaction device with an Advanced RISC (reduced instruction set computer) Machines (ARM)-based processor as the core is developed. Holographic information such as agricultural product market trading time, trading place, product name, price, and trading volume can be collected. Via embedded technology and component technology, innovative agricultural product market positioning, and matching, standardized collection, and data processing, and in combination with intelligent algorithms for analysis and early warning, a mobile application terminal for information collection is developed, namely, a holographic information collector for agricultural product markets (named Nongxincai). By using a layered structure, the hardware integrates microprocessor, storage, power, application and communication interface, and human-machine interaction modules. The device has the advantages of miniaturization, the whole-machine power consumption of less than 0.5 W, and continuous operating time of at least 10 h. A supporting software system for Nongxincai has also been developed, in which Microsoft Windows Mobile 6.5 is employed as the operating system, and the CPU frequency is up to 600 MHz. This configuration fully meets the computing requirements of map processing and large-volume data processing and has high compatibility. Nongxincai has been popularized and applied in 12 provinces/municipalities in China. It has played an important role in the monitoring and early warning of different varieties of agricultural products and target prices of soybean and cotton. Keywords: agricultural product market, holographic information, portable, user-interactive, information collector, monitoring and early warning DOI: 10.25165/j.ijabe.20201303.5845 Citation: Xu S W, Li D H, Zhang Y E, Chen W, Zhuang J Y, Liu J J, et al. Development of portable user-interactive holographic information collector for agricultural product markets. Int J Agric & Biol Eng, 2020; 13(3): 143–153.

Analysis of Cotton Price Fluctuation Characteristics and Trends in Kashi Area of Xinjiang

This paper studies the characteristics of cotton price fluctuation in Kashi Area from 2002 to 2015, the SAS software was used to conduct regression analysis of cotton price index and cotton price, through the goodness of fit test, the optimal regression model was selected and the variation amount, variation rate, volatility index and forecast value of cotton price were calculated, to study the characteristics and trends of cotton prices, discovery: cotton of Kashi Area future price shows rising trend. From the government, cotton farmers and consumers, the countermeasures and Suggestions to deal with the fluctuation of cotton price are put forward.

To Assess the Association between Exchange Rate, Commodity Prices and Cryptocurrency in Indonesia

The paper aimed to assess the association among exchange rate, commodity prices and crypto currency in Indonesia. This study is quantitative in which the data has been gathered from the Investing.com from 2016 to 2020. The variables which were considered in the study include exchange rate, gold prices, cotton prices, oil prices, Bitcoin and Ethereum. In terms of the analysis, the vector autoregression and granger causality test has been adopted.The results of this study identified that there is no effect of exchange rate, oil price, cotton price and gold price on Bitcoin. On the other hand, there is only significant effect of gold prices on Ethereum. The results of this study are restricted to Indonesian context and the data has been considered from 2016 to 2019 due to the lack of data on crypto currency.

Factors Affecting Sesame Seed Exports in Burkina Faso: The Vector Error Correction Approach

The research is financed by Academia Sinica, Taiwan. Grant No. AS-SS-107-02. Abstract Burkina Faso's (BFA) dependence on a single export crop, namely cotton, has so far threatened its economy since the fluctuating and uncontrollable drops in world cotton prices. The diversification of cash crops has become a national priority that is appropriated day by day by actors of rural development, and more particularly by farmers seeking to improve and secure their income. Thus, export crops, such as sesame, appear obvious and essential, not only for farmers’ income security but also for the country by its ability to attract currencies. In the last decade, BFA’s the sesame sector has recorded a tremendous growth both in quantity and value of exports to being the eighth world largest exporter of sesame seed. Considering its unequaled performance in the export of sesame seed, we deemed relevant to identify the key factors affecting that performance and to study their effects on sesame seed export earnings in order to draft appropriated policies aimed to enhance the country’s earnings. This study uses the cointegration approach, and has purposely designed exports value as the independent variable to analyze the country exports performance using time series data for the period of 47 years (1970-2016). One cointegration vector is found between the variables employed; thereby the Vector Error Correction Model has been performed. The empirical results reveal that nominal exchange rate, producer price, world export volume of sesame seed as a proxy of world demand, and world price are key factors affecting significantly the country’s exports performance in the short-run. Moreover, in the long-run nominal exchange rate, production, producer price, and world export price are factors determining significantly export earnings of sesame seed in Burkina Faso. For Burkina Faso to increase its market shares and export earnings, especially in the long-run, it is principally recommended to boost the production by increasing significantly yields and ensure an appropriate transmission of international prices increments to farmers. Keywords: Agricultural Export, Determinants of Agricultural Exports, Sesame Seed, Cointegration, Burkina Faso. DOI: 10.7176/DCS/10-4-03 Publication date: April 30 th 2020

Export price shocks and rural labor markets: The role of labor market distortions

To what extent can workers in developing countries seize gains from trade? To answer this question we resort to a unique exogenous labor demand shock triggered by a surge in the world market price of cotton in 2010/11. By capitalizing on Tajikistan's geographic variation in the suitability for cotton production, we identify the effect of the export price hike on wages of rural workers. The shock induces agricultural firms to shift towards labor intensive cotton production. The subsequent greater labor demand doubles wages for female cotton pickers on small entrepreneurial private farms, but does not affect their wages on large parastatal farms. We present evidence that parastatal farms recruit workers for low wages based on monopsony power and expand employment based on labor coercion of children and public sector workers. Our results highlight the importance of accounting for competitive structures in local labor markets when assessing the wage pass-through of world market prices to workers in developing countries.

Slavery and Anglo‐American capitalism revisited

AbstractBritish and American debates on the relationship between slavery and economic growth have had little interaction with each other. This article attempts intellectual arbitrage by joining these two literatures. The linkage turns on the neglected part two of the ‘Williams thesis’: that slavery and the slave trade, once vital for the expansion of British industry and commerce, were no longer needed by the nineteenth century. In contrast to recent assertions of the centrality of slavery for US economic development, the article argues that part two of the Williams thesis applies with equal force to nineteenth‐century America. Unlike sugar, cotton required no large investments of fixed capital and could be cultivated efficiently at any scale, in locations that would have been settled by free farmers in the absence of slavery. Cheap cotton was undoubtedly important for the growth of textiles, but cheap cotton did not require slavery. The best evidence for this claim is that after two decades of war, abolition, and Reconstruction, cotton prices returned to their prewar levels. In both countries, the rise of anti‐slavery sentiment was not driven by the prospect of direct economic benefits, but major economic interest groups acquiesced in abolition because they no longer saw slavery as indispensable.

The impact of unifying agricultural wholesale markets on prices and farmers’ profitability

As a leading effort to improve the welfare of smallholder farmers, several governments have led major reforms in improving market access for these farmers through online agricultural platforms. Leveraging collaboration with the state government of Karnataka, India, this paper provides an empirical assessment on the impact of such a reform-implementation of the Unified Market Platform (UMP)-on market prices and farmers' profitability. UMP was created in 2014 to unify all trades in the agricultural wholesale markets of the state to be carried out within a single platform. By November 2019, 62.8 million metric tons of commodities valued at $21.7 billion (USD) have been traded on UMP. Employing a difference-in-differences method, we demonstrate that the impact of UMP on modal prices varies substantially across commodities. In particular, the implementation of UMP has yielded an average 5.1%, 3.6%, and 3.5% increase in the modal prices of paddy, groundnut, and maize. Furthermore, UMP has generated a greater benefit for farmers who produce higher-quality commodities. Given low profit margins of smallholder farmers (2 to 9%), the range of profit improvement is significant (36 to 159%). In contrast, UMP has no statistically significant impact on the modal prices of cotton, green gram, or tur. Using detailed market data from UMP, we analyze how features related to logistical challenges, bidding efficiency, in-market concentration, and the price discovery process differ between commodities with and without a significant price increase due to UMP. These analyses lead to several policy insights regarding the design of similar agri-platforms in developing countries.