Cobb-Douglas Research Articles

Farmer’s Income and Allocative Efficiency Analysis in Rice Production in Koto Tangah Subdistrict Padang City

The low productivity of lowland rice (Oryza sativa L.) in Koto Tangah District is affecting farmers’ income. The objectives of this research were to analyze : (i) income from lowland rice cultivation, (ii) factors that influence rice production, and (iii) the efficiency of utilization of lowland rice production factors in Koto Tangah District. The method used in this research was quantitative, using probability sampling techniques with proportional random sampling method and 44 respondents were involved. The data analysis techniques used were income analysis, Cobb-Douglas production function, T-test (partial), F-test (simultaneous), coefficient of determination, and efficiency analysis. Based on the survey results, it was known that the total income from lowland rice cultivation in Koto Tangah District was IDR2,607,860.36/average land area/ MT, and lowland rice cultivation was possible with an R/C value of 1.21. The factors that influenced lowland rice production in Koto Tangah District were land area, seeds, and chemical fertilizers, which significantly affected production levels. In contrast, pesticides, labor within the family, and labor outside the family do not significantly affected lowland rice production in Koto Tangah District. Although production factors such as land area, seeds, fertilizers, pesticides, and family labor (TKDK) were still inefficient, non-family labor (TKLK) had almost reached an efficient level.

Algorithm for identifying parameters of production function models using a neural network

The purpose of the work is to ensure the monitoring and reliability of statistical data used for the analysis and forecasting of the production development on the basis of generalized indicators that take into account the volume of resources used and the ways of their use. An algorithm for parametric identification of production functions models from time series of statistical data using generalized regression, which provides the best estimation of the parametric optimization error by the method of least squares, is proposed. In contrast to existing assessment methods, neural networks are used to build models, which significantly expand the technical capabilities of modeling and contribute to improving the accuracy of calculations through the use of neural network technologies. It is shown that in order to solve the problems of this class, it is advisable to use generalized regression neural networks with simple training modes and high modeling accuracy. As a result, it is possible to propose an algorithm for quantitative assessment of the production functions parameters, which consists in the construction of a neural model with its subsequent use to fit the trajectory of the production model of a given structure to the obtained data by means of recurrent estimates of the vector of the desired coefficients at a given initial approximation. The proposed algorithm is demonstrated by estimating the parameters of the Cobb-Douglas production function and the discrete-dynamic model of the consumption function according to the corresponding statistical series. The calculations are performed using the functions of the Neural Networks package of the MATLAB software environment. The algorithm is applicable for quantitative estimation of the production models parameters with complex logical-probabilistic relationships, as well as for obtaining numerical values of target indicators and indicators for assessing the inland water transport development by statistical series and monitoring.

The Impact of Using Renewable Energy Resources on Sustainable Development in the Kingdom of Saudi Arabia

This study examines the impact of renewable energy on sustainable development in the Kingdom of Saudi Arabia from 2000 to 2019 and analyzes the kingdom’s most essential practices in this field to achieve sustainable development. The Cobb–Douglas production function is used in this study to investigate the impact of renewable energy on sustainable development using ordinary least squares (OLS) estimation. According to the findings, renewable energy consumption has a negative but insignificant effect on GDP. Additionally, traditional energy consumption has a major negative influence on GDP. The findings also demonstrate that fixed capital formulation and technical progress have a significant positive impact on Saudi Arabia’s sustainable development. Furthermore, while the labor force has a positive impact on GDP, this effect is not statistically significant. This report provides some recommendations for Saudi government policymakers to reform the country’s energy efficiency and consumption technologies in order to reduce energy waste and satisfy the goals of sustainable development. While the labor force is recognized as having a positive influence on GDP, it is notable that this result lacks statistical significance. The suggestions of these findings are mainly applicable to Saudi policymakers, and we present recommendations to improve energy competence and utilization technologies. Specially, our suggestions are intended to reduce energy dissipation and to support the objectives of sustainable development.

Possibilities and limits of modelling of long-range economic consequences of air pollution – A case study

Air pollution is the biggest environmental problem in modern societies, causing considerable health damage and requiring substantial financial resources for health care. The goal of the study is to demonstrate the adverse economic consequences of air pollution on example of a small, open Central European country, Hungary, and to provide quantified financial arguments for macroeconomic decision-making for the development of a long-term energy strategy. On the basis of the Cobb-Douglas production function and Solow-Swann model of dynamic economic systems a simple and robust model was constructed to estimate and predict economic losses, caused by the pollution. On base of results it is obvious, that on base of macroeconomic theory and combination of various, publicly available, quality-controlled statistical resources quantifiable models can be constructed to characterise the economic consequences of air pollution, but it should be taken into consideration, that the reliability of economic models considerably depends on their initial parameters and practical validity of assumptions, based on which the underlying economic theories were built. The most important economic burden of air pollution is caused by the loss of working–age population, resulting in a decrease of 4.1–9.4 % a year in Gross Domestic Product (GDP) in the next fifty years. The additional burden of health care costs amounts to 0.1 % of GDP. Reducing air pollution is not only a quality of life improvement but also an investment into the economic development. Notwithstanding of statistical biases it could be proven the importance of combination health economic and econometric methods in preparation of more efficient environmental-related socio-economic decisions.

Analisis Faktor-faktor Produksi Usahatani Tebu di Desa Banyuputih Kecamatan Banyuputih Kabupaten Situbondo

The aim of this research is to identify factors that influence production in the sugar cane farming sector and evaluate the scale of production in sugar cane farming in Banyuputih Village, Banyuputih District, Situbondo Regency. The data used involves primary information obtained directly from farmers, including variables such as name, age, education level, land area, amount of seed used, amount of fertilizer used, and number and type of workforce. Secondary data was also obtained from various agencies and institutions, including the Central Statistics Agency (BPS). The research was carried out on all sugar cane farmers in Banyuputih Village, Banyuputih District, by selecting 30 respondents as samples using non-probability sampling with a purposive sampling technique. The data analysis method applied is the Cobb-Douglas production function model using SPSS software. The research results show that, based on the Cobb-Douglas production function analysis, it can be concluded that sugar cane farming in Banyuputih Village, Banyuputih District, Situbondo Regency, is significantly influenced by the use of seeds, urea fertilizer, phonska fertilizer, and labor. Simultaneously, all observed variables have a significant influence on sugarcane production. Furthermore, the scale of production businesses in sugar cane farming in Banyuputih Village, Banyuputih District, Situbondo Regency, was found to be in a condition of Increasing Return to Scale.

Comparative Economics of Main Season and Spring Rice Production in Kanchanpur District, Nepal

Rice is the major staple food crop in Nepal which has been growing in two different seasons mainly June/July – October/November as main season rice (MSR) whereas during February/March – June/July as spring rice (SR). A comparative economic analysis of MSR and SR production in Kanchanpur district Nepal was conducted during March to July 2023. A total of 120 rice-growing farmers including 60 MSR and 60 SR growers were randomly selected from the available grower list to collect primary information by using pre-tested interview schedules. Descriptive statistics, independent sample t-tests, and the Cobb-Douglas production function were employed for the data analysis. The study finding revealed that the average landholding of MSR growers was 0.65 ha/hh, whereas the same for SR growers, was 0.55 ha/hh. The average area for MSR and SR were at 0.53 ha and 0.29 ha, respectively. The average productivity of the SR (3.69 t/ha) in the study area was found to be significantly higher than the MSR (4.61 t/ha). Despite the higher cost of production for SR (Rs. 80309.95/ha) than MSR (Rs. 75048.45/ha), the Benefit-Cost ratio for SR was found to be higher (1.61) than that of MSR (1.38). The analysis of coefficients indicated a decreasing for main season rice and increasing return to scale for spring rice, with sums of coefficients measuring 0.74 and 1.24 respectively. This implies that a 100% increase in expenditure on the variables outlined in the model for MSR and SR led to a 74% and 95% increase in the gross return of rice production. These results underscore the potential advantages of promoting improved seed varieties and adopting commercial farming practices in the spring rice cultivation area. The findings indicated the need to replace manual labor with machinery to reduce costs and increase rice cultivation profits.

Overcoming barriers to technology transfer: empirical evidence from the German Democratic Republic

This paper provides empirical evidence on a special case of restricted technology transfer: the German Democratic Republic (GDR) characterized by a socialist innovation system with a supply-side-oriented technology-push model encompassing intellectual property rights protection partially distinct from the one employed in most market economies. We exploit the natural experiment setting of the formerly separated regions in Germany and compare the productivity effects of knowledge generation, accumulation, and diffusion in the GDR with those of the Federal Republic of Germany (FRG) between 1970 and 1989. By applying a Cobb–Douglas production function to original primary and harmonized productivity data and manually cleaned patent data, we show that knowledge generation, accumulation and diffusion contributed to sectoral productivity in the GDR similarly compared to the FRG, despite the institutional misalignments in the socialist innovation system. We explain these findings and provide implications for present organizations with regard to incentive schemes for patenting, the support of personal creativity and education, and alternative technology transfer mechanisms in case of institutional barriers to innovation.

Analysis of Efficiency, Productivity, and Performance of Small and Medium Industries in the Sarbagita Region, Bali Province

This study aims to: 1) analyze the level of efficiency, elasticity, and the impact of inputs on the productivity of Small and Medium Industries (SMIs) in the Sarbagita region of Bali Province; 2) examine the influence of inputs and productivity on the performance of SMIs in the Sarbagita region of Bali Province; and 3) investigate the indirect effect of inputs on performance through the productivity of SMIs in the Sarbagita region of Bali Province. Non-probability sampling was employed, with a quota of 200 samples, and each district/city represented by 50 SMI actors. Data collection methods included observation, collection of relevant documents, and structured interviews using questionnaires. The analysis technique utilizes the Cobb-Douglas production function and SEM PLS. The analysis concludes that: 1) the use of capital and labor inputs has not yet reached optimum efficiency, and the elasticity of output to input is inelastic; 2) capital and labor inputs have a positive and significant effect on productivity, social capital has a positive and significant effect on performance, and productivity has an insignificant impact on the performance of SMIs in the Sarbagita region of Bali Province; and 3) there is no indirect influence of capital and labor inputs on performance through productivity in SMIs in the Sarbagita region of Bali Province. If the use of inputs, especially labor, is not well regulated, it results in inefficient operations and does not impact the improvement of business performance.

Evaluating the carbon total factor productivity of China: based on Cobb-Douglas production function.

This paper introduces a novel methodology for estimating carbon total factor productivity based on the Cobb-Douglas production function. The research method introduced in this article expands upon the framework for assessing total factor productivity through the Solow residual method. It unifies the conceptual and methodological aspects of carbon total factor productivity with those of single factor productivity. Utilizing panel data from various provinces between 2010 and 2021, we computed carbon total factor productivity to understand its implications for China in combating global climate change. We demonstrate that (i) we have introduced a method to handle negative coefficients in the Cobb-Douglas production function by incorporating productivity in lieu of input factors during calculations. (ii) Carbon total factor productivity, encapsulating the geometric weighted mean of labor, capital, and carbon productivity, holds notable economic relevance. Further, it serves as an integrative metric comprising carbon productivity intertwined with the mean labor and capital carbon factors. And (iii) the influence of carbon total factor productivity growth on economic progression remains relatively subdued, with escalating labor force growth posing detrimental effects on several provincial economies. Enhancing carbon total factor productivity emerges as an imperative to harmonize robust economic growth with strategic carbon curtailment. Our analytical framework provides nuanced perspectives on productivity determinants, accentuating the thrust towards sustainable evolution amidst climatic challenges. This investigation bears profound significance for policymakers endeavoring to sculpt a carbon-conscious economic paradigm in consonance with global climatic ambitions.

The Impact Of The Digital Economy And New Infrastructure On China’s Economic Development

With the rapid growth of digital technology and the advent of the epidemic and post-epidemic era, digital economy has become a vital force driving China’s monetary growth and transformation and modernizing. The digital economy and new infrastructure are two important directions in current China’s economic development. Using the newly implemented infrastructure policies released by municipality governments in China from 2018 to 2022 as a data source, the concept of new progress, driven by novel technologies, and built on digitized networks of information, is used to provide a source of power for further economic development. This paper investigates the positive and negative effects of the mathematical economy on economic growth using the Cobb-Douglas production function, Keynes-Hicks social welfare function, and Differential pricing model. One way that the digital economy might advance is by lowering transaction costs, increasing economic growth rates and total factor productivity, creating new employment opportunities, raising individual income levels, improving social services and public administration, raising social welfare levels, and further promoting economic development. On the other hand, new infrastructure includes digital infrastructure, smart manufacturing, new energy, and transportation infrastructure. The construction of these infrastructures can promote industrial upgrading and the adjustment and optimization of industrial structures. The transformation of traditional service and manufacturing industries into digitized online industries will ultimately lead to a more transparent and efficient overall economy. Even if the new infrastructure and digital economy can cause problems such as unfair competition and privacy breaches, the combination of them can lead to a win-win situation for economic development in China.

Functional Analysis of Thyme Production in Denizli Province

This study aimed to conduct an econometric analysis of thyme production in Denizli province agricultural enterprises. The data used in the research were obtained through face-to-face questionnaires in 82 agricultural enterprises determined according to the Simple Random Sampling Method. Research findings revealed that to obtain an average yield of 95.10 kg per decare, 10.296 seedlings, 8,93 cc pesticides, 52.34 kg of chemical fertilizers, 16.57 liters of diesel, 4.49 hours of machinery, and 17.84 hours of labor were needed. In this study, the relationships between the amount of thyme production and the number of seedlings, chemical fertilizers, pesticides, and the machinery used in the whole production, the amount of diesel, the amount of labor used, and the production area were analyzed with the help of the Cobb-Douglas production function. The coefficient of determination for the estimation equation was 0.89 and was found to be significant at the 1% level. Among the variables included in the estimation equation, the production elasticity coefficients of pesticide use and diesel use were negative, while the production elasticity coefficients of the seedling number, chemical fertilizer amount, labor, and production area variables were found to be positive. The fact that the sum of the production elasticity coefficients of the factors in the estimation equation for the amount of thyme production (∑βi) was 1.12 indicates there is increasing returns to scale. Among the variables in the production function, the variables with marginal efficiency coefficient above 1 were determined as the production area (3.20) and the fertilizer factor (1.33). The research findings revealed that production factors, except fertilizer amount and production area inputs, were not used effectively in thyme production.

Factors Affecting the Rice Yield During the Rainy Season Among Farmers in Southeastern Cambodia

A research study utilized the Cobb-Douglas production function to examine the elements influencing paddy production during the wet season in three rural provinces of Cambodia. This analysis was based on data gathered from a survey of farmers’ households conducted in 2022. The study discovered that the use of fertilizers and herbicides, the size of the family, and income from off-farm sources significantly impacted the output of wet-season paddy. A one percent increase in the use of fertilizer, herbicide, and family size resulted in an increase in rice output by 0.06 percent, 0.04 percent, and 0.05 percent respectively. Furthermore, a one percent increase in the age of the household head, hired labor, and off-farm income led to an increase in rice yield by 0.08 percent, 0.11 percent, and 0.05 percent respectively. The use of seeds, pesticides, household labor, and the education level of the household heads were found to enhance rice yields in southeastern Cambodia. However, these production relationships varied significantly across different regions. The study concluded that higher yields during the rainy season improved the effectiveness of paddy production, primarily due to the increased responsiveness to fertilizer application.

ВИКОРИСТАННЯ ФУНКЦІЇ КОББА-ДУГЛАСА ДЛЯ АНАЛІЗУ ЕКОНОМІЧНОЇ ДИНАМІКИ

The purpose of the study is to enhance the capabilities of analyzing the dynamics and efficiency of the national economy, as well as forecasting its development, based on the use of the Cobb-Douglas production function apparatus. To this end, the article demonstrates that production functions, including the Cobb-Douglas function, are powerful tool for analyzing economic dynamics. The advantages of the Cobb-Douglas function and its application peculiarities are analyzed. Production functions enable the evaluation of production efficiency and the productivity of factors such as labor, capital, etc. They can be used to forecast trends in the national economy's development. However, using the Cobb-Douglas production function can cause some problems and limitations. The article presents four calculation options based on actual statistical data of the Ukrainian economy. The analysis of the calculations revealed that it is advisable to use the following indicators to obtain accurate results. The dependent output variable is gross domestic product at actual prices. The independent variables are the cost of capital investment at actual prices and the effective volume of labor. Based on the calculations, the parameters of the Cobb-Douglas production function for the Ukrainian economy were found. The adequacy of the constructed econometric model and the feasibility of its application for analyzing the dynamics of the national economy of Ukraine have been demonstrated. 93.6% of the variation in the gross domestic product depends on the variation in the effective volume of labor and the variation in capital investment. The economic interpretation of the parameters of the constructed Cobb-Douglas production function is provided. It was concluded that labor-intensive economic growth is occurring in the economy of Ukraine, along with a certain tendency towards intensive economic growth. The constructed Cobb-Douglas model was applied to find a point forecast of the gross domestic product. The values of capital return and labor productivity for the economy of Ukraine were determined. The results of the work can be used to analyze the economic dynamics of indicators of the national economy.

The Fusion of Digital Technologies in Small Business for Ensuring the Socio-Economic Development: Panel Data Analysis

This paper analyzes the development of the activities of small business entities through the fusion of digital technologies in ensuring the social and economic development of Uzbekistan, its significant aspects in the development of the country’s economy. In Uzbekistan the economic, social and legal levels of small business entities in organizing their activities through digital technologies were determined. 5 directions of its economic and social support were analyzed based on today's policy, and the advantage of using the digital economy in the activities of small business entities compared to large enterprises was determined. The research employs a confluence of descriptive statistics, panel data regression models, and time-series analysis to unravel the intricate correlation matrix that binds various dimensions of investment outcomes within the country's distinct economic climate. A conclusion was made based on the results of the study of the main economic development indicators of the development of small business entities through digital technologies. In assessing the effectiveness of the development of the activities of small business entities through digital technologies, the effectiveness of digitalization on the activities of small business entities was determined using the Cobb-Douglas production function. Proposals and recommendations were developed according to the forecasting results.

An economic study and resource use efficiency of brinjal production in Bangladesh

This study assessed brinjal producers' socioeconomic characteristics, profitability, and resource use efficiency. The study was carried out in Boalmari and Faridpur sadar upazila in Faridpur district, Mithapukur, and Gangachara upazila in Rangpur district,Kaligonj upazila in Shatkhira district, and Jashore sadar upazila in Jashore district. Data were gathered via the use of an interview schedule from a sample of 60 respondents chosen at random between the dates of January 1stand March 31st, 2021. A Cobb-Douglas production function (CDPF) analysis was performed with descriptive statistics to explore the factors influencing brinjal production. In this study,majority of respondents (46.67%) were found middle-aged (31–45 years old). A major percentage of brinjal farmers (45%) were illiterate, while 23.33% had secondary education. About 41.67% of brinjal farmers had a medium family (5-6 persons), while over 30% had a big family of more than 6. Fertilizers, seed, and insecticides were the major variable costs during the brinjal production. The findings also revealed that the total production cost, gross returns, gross margin, and net return per hectare were Tk. 169877, Tk.534594, Tk. 388767, and Tk.364717, respectively. The brinjal cultivation was found profitable as the benefit-cost ratio (BCR) was found 3.14. The CDPF analysis revealed that the machinery utilized was negatively significant for brinjal production, whereas the coefficients of hired labor and urea were favorably significant. Except forthe overuse of insecticides, resource usage efficiency showed that all the resources were underutilized for brinjal farming.

Harnessing Technology for Sustainable Agriculture: A Case Study from Bihar, India

The "End of Hunger" initiative, a key Sustainable Development Goal endorsed by the United Nations in 2015, aims to promote sustainable agriculture by doubling the productivity and income of small-scale food producers by 2030. Despite significant technological advancements over the past seven decades, their indiscriminate use has led to ecological consequences, raising sustainability concerns. This study addresses the need for technological developments that enhance agricultural stability and productivity through environmental modeling and risk management algorithms. Focusing on Bihar, a predominantly agricultural Indian state with low industrialization, the study aims to improve rural livelihoods by maximizing agricultural income through effective risk management strategies. It examines the impact of various agricultural technologies, including mechanization, chemical technology, management practices, and policy measures, on agricultural GDP. Using the CobbDouglas production function, the study analyzes a 29-year dataset with one endogenous variable (agricultural value-added) and nine exogenous variables, ensuring data stationarity with the Augmented Dickey-Fuller Test and processing the data using R programming. Findings indicate that technological advancements, such as multi-cropping, agroforestry, new seed varieties, and improved resource management, have significantly enhanced agricultural productivity in Bihar. Capital investment and mechanization substantially contribute to agricultural value-added, though they require periodic reinforcement. Sustainable practices are essential, as extensive use of chemical fertilizers and irrigation may have adverse effects. The study concludes that sustained investment in agricultural technologies, timely capital stock reinforcement, and promotion of sustainable practices are crucial for driving agricultural growth in Bihar. Additionally, effective credit management and recognizing forests' environmental benefits can further support sustainable development.

Analysis of the Influencing Factors of Economic Growth in Beijing Based on the Cobb-Douglas Function

Analysis of the Influencing Factors of Economic Growth in Beijing Based on the Cobb-Douglas Function

Modeling the rational use of natural resources and innovative quantum technologies in agribusiness

The influence of quantum computing techniques on the optimization of resource allocation in the agricultural sector is analyzed. The use of variational quantum eigensolver (VQE) algorithm to achieve optimal resource allocation is explored. It has been found that production functions, such as the Cobb-Douglas function, effectively describe the transformation of input parameters into output. Parameterization of a quantum circuit and minimization of the expected value of the Hamiltonian to optimize resource allocation are studied. It is determined that the quantum optimization approach demonstrates improved computational efficiency compared to classical methods. It has been found that the integration of quantum technologies can significantly improve resource allocation in agriculture. An assumption has been made about increasing productivity and sustainability in the agricultural sector thanks to quantum methods. Further research on quantum algorithms is proposed to improve the efficiency of natural resource management. New software has been developed for modeling and optimizing production functions in agriculture. The use of quantum computing to solve complex problems in the agricultural sector is justified. A detailed description of the quantum algorithm and its benefits in the context of agriculture is presented.

Comparative Profitability and Productivity Analysis of Rice Production in Coastal and Arable Land Areas of Bangladesh

This study aims to compare the productivity and profitability of rice production in coastal and arable land areas in Bangladesh while analyzing the factors influencing productivity and profitability. It seeks to provide insights into the differences in agricultural outcomes between these two types of land, essential for policy formulation and agricultural development. The research employs a stratified random sampling method to gather primary data from six villages in Gopalganj and Khulna districts, targeting 30 farmers from each village. Cobb-Douglas profit and production function analysis is utilized to estimate the impact of various factors such as seed cost, labor cost, fertilizer cost, insecticide cost, ploughing cost, and irrigation cost on profitability. The study reveals significant differences in productivity and profitability between coastal and arable land areas for rice cultivation. It identifies key factors affecting productivity and profitability, emphasizing the importance of policy support for enhancing the quality of inputs to bridge yield gaps and improve rice crop outcomes. One limitation of this research is the focus on specific regions within Bangladesh, potentially limiting the generalizability of findings to other areas. Additionally, the study may not capture all variables influencing productivity and profitability due to data constraints. The findings provide valuable insights for policymakers, suggesting the need for targeted interventions to support farmers in improving productivity and profitability. This research contributes to the existing literature by offering empirical evidence on the productivity and profitability dynamics of rice production in coastal and arable land areas in Bangladesh.

THE IMPACT OF FOREIGN AND NATIVE HUMAN CAPITAL ON TURKEY'S ECONOMIC GROWTH

In this study, the impact of human capital on Turkey's economic growth during 2003-2021 was investigated. For this purpose, the effects of native and foreign labor are examined separately within the framework of the Cobb-Douglas production function. The Johansen cointegration method was used for the analysis. The results of the estimation of the long-run model show that both foreign and native labors have a positive effect on economic growth, with the effect of native labors being larger than the effect of foreign labor. Both native and foreign labor play an essential role in creating the right background for Turkey's economic growth, so native and foreign labor should be used to increase productivity and production.