Marginal Revenue Research Articles

Integrated Management of Corn Marigold (Glebionis segetum) in Tef Field at Western and Southwestern Shewa Zones in Ethiopia

Background: Corn marigold (Glebionis segetum (L.) Frourr.) is a serious weed species of agricultural crops in many parts of Ethiopia. However, there is a lack of information on its management in tef fields in the country. Therefore, the current work was designed with the objectives of evaluating integrated management of the weed and determining the most economical integrated weed management options in tef fields. Methods: The field experiments were conducted in naturally corn marigold infested fields of Cheliya and Woliso districts of West and Southwest Shewa Zones in Ethiopia, respectively, during 2020 to 2021 cropping seasons. Results: Different corn marigold management practices exhibited different responses to different parameters of the target weed and the test crop differently. Application of Pyroxsulam 45g L-1 at a rate of 0.40 l ha -1 supplemented with once-hand weeding and Halauxifen-methyl 100g kg-1 + Florasulam 100g kg-1 sprayed at a rate of 50 g ha -1 supplemented with once-hand weeding increased grain yield by about 70 and 50%, respectively, over the weedy check. The marginal revenue and benefit-cost ratio obtained from the marketing of goods for the application of Pyroxsulam 45g L-1 with one supplementary hand weeding of corn marigold increased by110 89%, respectively, as compared to the weedy check. Conclusions: The present study revealed the role of integrated management of corn marigold in improving tef production and productivity by combating the weed. Future research should be directed towards scaling up and popularizing these technologies among the growers.

Impact of Policy Signals on Business Performance: An Empirical Analysis of Financial Subsidy Effects on High-tech Enterprises Using Panel Data from 2095 Listed Companies

Based on the samples of A-share listed companies with high-tech certification from 2017 to 2021, this study empirically analyzes the influence of financial subsidy as a "policy signal" on the business performance of high-tech enterprises by analogy with Shannon-Weaver communication model. Using the regulatory effect model and intermediary effect model, and with the help of soft budget constraint and diminishing marginal revenue theory, this study analyzes the reasons why financial subsidy affects the enterprise business performance differently. This study indicates that financial subsidy, as a kind of policy signal source, is regulated by the nature and scale of enterprises, and ultimately improves the financial performance and innovation performance of enterprises through the intermediary effect of R&D investment intensity and external market valuation.

The economic effects of unmanned aerial vehicles in pesticide application: evidence from Chinese grain farmers

Unmanned aerial vehicles (UAVs) are a recent innovation in precision agriculture technology. They are being used in a wide range of agricultural practices, whereby pesticide application is one of the most common uses of UAVs in China’s agriculture. However, the economic effects of UAVs in pesticide application have not been sufficiently investigated. To address the gap, this paper used propensity score matching to evaluate the economic effects of UAV adoption on outcome variables including revenue, pesticide costs, time spent on pesticide application, and pesticide application frequency based on a dataset covering over 2000 grain farmers across 11 provinces of China. Furthermore, generalized propensity score matching was used to evaluate the heterogeneity of outcome variables arising from differing UAV adoption intensities. The empirical results show that adoption of UAV increased revenue by approximately 434–488 dollars per hectare and reduced the time spent on pesticide application in the range of 14.4–15.8 h per hectare. Depending on the area with use of UAVs for pesticide spraying, UAV adoption has heterogeneous impacts on grain farmers’ revenue and the time spent on pesticide application. In terms of marginal revenue and marginal time spent on pesticide application, the optimal area with use of UAVs for pesticide spraying is estimated to be 20 hectares of arable land.

How does the digitization of government environmental governance affect environmental pollution？ spatial and threshold effects

Digitalization has become the core engine of a scientific and technological revolution and a new phase of industrial transformation, while the integrated digitalization development and environmental governance has become a strategic choice for high-quality development in the modern era. Focusing on the relationship between the digitalization of government environmental governance (DGEG) and environmental pollution, this study empirically tested the impact of DGEG on environmental pollution and its spatial spillover effect using the spatial Durbin model based on provincial panel data for China from 2015 to 2019. The threshold effect of this impact was examined using the threshold regression model from the perspective of digital infrastructure as well as digitalization developments in economic and social spheres. We found that DGEG can not only reduce environmental pollution in the local area but also improve the environmental quality of surrounding areas through the spatial spillover effect, showing an obvious “digital pollution reduction dividend”. However, this spillover effect has a spatial spillover boundary, only playing a role in pollution reduction within a certain geographical range. The impact of DGEG on environmental pollution has a single threshold effect based on digital infrastructure. As the digital infrastructure has improved over time, the “digital pollution reduction dividend” of DGEG has continued to strengthen, showing a characteristic of “increasing marginal revenue”. Under the constraints of digitalization development in the economic and social spheres, the impact of DGEG on environmental pollution has developed the characteristics of a single threshold, i.e., the pollution reduction effect of DGEG is not significant or even positive in the initial stage, but its impact gradually becomes prominent once it exceeds a certain threshold value.

Opinion Dynamics of Social Networks With Intermittent-Influence Leaders

This article constructs a leader-follower architecture by introducing intermittent-influence opinion leaders to the DeGroot model and analyzes the influence of this type of leaders on the evolution of opinions. Different from the existing studies where the leaders can convey their opinions to the followers uninterruptedly, the leaders in this article can only convey its opinion by broadcasting at some intermittent moments. First, we analyze the relationship between the leaders' broadcast moments and the consensus opinion of followers and explain that the marginal revenue of the broadcasts is diminishing. Second, we describe the connotation of assimilation and calculate the minimum number of broadcasts required for the leaders to assimilate the followers' opinions. Finally, aiming to make the consensus opinion of the followers and the leaders' as close as possible, we give an optimal strategy on how to select followers to broadcast. The correctness of theoretical results is verified by numerical simulations.

Utilization of water conserved by interprovincial renewable energy substitution for thermal power: Incremental benefits and advanced reservoir operation rules

Renewable energy has been rapidly developed and transmitted across provinces to accelerate carbon neutrality in China. Water has been saved in power-receiving regions due to interprovincial renewable energy substitution for water-intensive thermal power (RST). The re-utilization of the water saved by RST through various ways is an urgent issue to be addressed. To establish the correlation between the saved water and related source reservoir and further utilize the saved water to maximize its incremental benefits, a general model framework is proposed to quantify the saved water and reallocate it to cope with emergency events and promote hydropower-based reservoir operation. The model is applied to an energy-water system centered around Henan Province. The incremental benefits and optimal reallocation mode of the saved water have been revealed. The results indicate that RST produces an annual water savings of 175.160 million m3 in Henan Province, which contributes to the increase in hydropower generation and emergency water supply ranging from 14.584 GWh to 32.267 GWh and 0 to 1.724 × 108 m3, respectively, under different hydrological scenarios. To boost the incremental benefits of water reallocation under RST, the source reservoir should concentrate on the emergency water supply in dry years and enhance hydropower generation in wet years. Conserving the saved water for future use would produce additional 12.771 GWh to 22.324 GWh of hydropower generation in the following year. As RST capacity increases from 40 to 320 TWh, the marginal revenues of hydropower generation and emergency water supply decrease by 75.4% and 40.7%, respectively, in wet years. This indicates that water supply from different sources should be rearranged to maximize total benefits according to the volume of water saved by RST and the marginal revenue characteristics. The general framework can be extended to other energy-water systems to assess incremental benefits and propose adaptive reservoir operation rules, which provides new insights into water management from the perspective of renewable energy substitution.

Can land misallocation be a greater barrier to development than capital? Evidence from manufacturing firms in Sri Lanka

We quantify cross-firm misallocation in land and compare it with that in capital. Misallocation arises when a production factor produces greater marginal revenue product (MRP) in some firms than in others because the former firms have to pay a higher shadow production factor price which is usually distorted by persistent institutional factors. Consequently, the aggregate total factor productivity (TFP) could be increased through cross-firm factor reallocation within an industry. Existing literature mainly emphasizes the misallocation in capital and labour, or in agricultural land. Little is done to quantify the misallocation of industrial land. By using annual-firm-level survey data from Sri Lanka's manufacturing sector over 1994–2015, we find that the aggregate TFP gain from reallocating land is about five times of that from capital. Further, we find that firms can hardly grow bigger due to size-dependent land distortion. The results suggest that land distortion can be a crucial barrier to development.

What is Measured in National Accounts?

Most statistical agencies construct sectoral real GDP using double deflation and base period prices. When the base period price used for intermediate inputs is not equal to their marginal revenue product, such as when firms apply a markup, real GDP fluctuations become mechanically linked to variations in intermediate inputs. This is because these inputs generate profits that are incorporated into real value added. Taking this channel into account, we demonstrate that real GDP reported in national accounts substantially diverges from a theory-consistent "physical" value added. This, in turn, has implications for the measurement of productivity. Between 1999 and 2021, "physical" productivity cumulative growth in the Finance sector was 15pp lower compared to the Solow Residual, while it was 15pp higher in the Manufacturing sector.

Access to finance, bureaucracy, and capital allocation efficiency

We study the degree and determinants of capital allocation efficiency across firms, using comprehensive firm-level survey data covering a broad spectrum of developing countries. As measured by the dispersion in firms’ marginal revenue product of capital, we document that capital misallocation is pervasive. Limited access to finance, bureaucracy, information asymmetry, and gender inequality play essential roles in impeding the most efficient capital allocation. Quantile regression estimates indicate more significant effects of these factors on already highly distorted firms. The results have direct policy implications; governments could achieve a more efficient capital allocation by eliminating these distortions to enhance economic performance.

Optimizing rice in-season nitrogen topdressing by coupling experimental and modeling data with machine learning algorithms

The modern in-season crop N recommendation approaches should have high reliability in promoting agricultural sustainability. These approaches are relevant to soil properties, meteorological conditions, management practices, and crop in-season growing status. This study aims to use machine learning (ML) algorithms to incorporate the above variables as well as the field reactive nitrogen (N) losses (i.e., N damage cost) simulated by a DeNitrification–DeComposition (DNDC) model to develop a new strategy for optimizing rice in-season topdressing N (TN) usage. Rice field experiments with multiple N treatments and rice varieties were carried out during 2015–2021 at four study sites in eastern China. Four ML algorithms, namely random forest regression (RFR), support vector regression (SVR), lasso regression (LSR), and partial least square regression (PLSR) were used to develop in-season prediction models of yield and reactive N losses by combining soil, meteorological, and management data with crop remote sensing data. The observed in-season agronomic optimum N rates (AONR) that can maximize rice yield at different sites were in the range of 116.5 to 177.4 kg N ha−1, while the in-season economic optimum N rates (EONR) that can maximize marginal revenue (i.e., yield income minus N fertilizer costs and N damage costs) were in the range of 97.4 to 163.6 kg N ha−1. The developed ML models were further used to simulate yield and marginal revenue responses to a series of assumed TN rates (0–300 kg N ha−1, gradient = 20 kg N ha−1). Comparably, RFR model and SVR model were more suitable for determining optimum TN rates, because their simulated response curves of yield and marginal revenue fit the normal regulation (linear plus plateau or single-peak shapes). Independent validation results showed that the in-season AONR and EONR predicted by RFR and SVR well accorded with the observed values (R2 ≥ 0.64, RRMSE ≤ 18.3 %), and the accuracy of ML models containing both historical and in-season meteorological information is superior to ML models that contain in-season meteorological information only. The proposed ML-based strategy is expected to help the regional rice production systems precisely manage N use, improve net profits, and reduce environmental footprints.

The effect of changes in the terms of trade on GDP and welfare: A Divisia approach to the System of National Accounts

AbstractWhat effect, if any, do changes in the terms of trade have on the level of output (GDP) or welfare? I examine this issue through two versions of a textbook, Heckscher‐Ohlin‐Samuelson (HOS), two‐good model of a small, open economy. In the first version both goods are for final consumption. In the second, one good is an imported intermediate input into the other. In both versions, economic theory suggests that an improvement in the terms of trade raises welfare (consumption) but leaves aggregate output (GDP) unchanged. I then show that a national income accountant applying the principles of the 2008 System of National Accounts (SNA) would reach the same conclusions. This follows from a continuous‐time analysis using Divisia index numbers. However in the case where imports are intermediate inputs and competition is imperfect, an improvement in the terms of trade does raise GDP: the size of the effect depends on the size of the markup of price over marginal revenue. I argue that the continuous time Divisia approach is the right framework for national income accounting, even though it can only be implemented approximately in practice. If the aim is to find the best approximation to the Divisia index, then the chained Fisher index (as used in the US and Canadian national accounts) or the chained Törnqvist are better approximations than is the chained Laspeyres (as used in Europe).

Integrated management of Corn Marigold (Glebionis segetum) in Tef Field at Western and Southwestern Shewa zones in Ethiopia

Background: Corn marigold is a serious weed species of agricultural crops in many parts of Ethiopia. However, there is a lack of information on its management in tef fields in the country. Therefore, the current work was designed with the objectives of evaluating integrated management of the weed and determining the most economical integrated weed management options in tef fields. Methods: The field experiment was conducted at naturally Corn marigold infested fields of Chaliya and Waliso districts of Western and Southwestern Ethiopia, respectively during 2020 to 2021 cropping seasons. Results: Different Corn marigold management practices exhibited different responses to different parameters of the target weed and the test crop differently. Application of Pallas 45 OD at a rate of 0.40 l ha-1 supplemented with once-hand weeding and QuelexTM 200 WG sprayed at a rate of 50 g ha-1 supplemented with once-hand weeding increased grain yield by about 70 and 50%, respectively, over weedy check. The marginal revenue and benefit-cost ratio inflicted from the marketing of goods for every one of integrated management of Corn marigold increased by about 42–110 and 32–89%, respectively as compared to a weedy check. Conclusions: The present study revealed the role of integrated management of Corn marigold in improving tef production and productivity by combating the weed. Future research should be directed towards scaling up and popularizing these technologies among end users.

The Role of Ambiguity Aversion in Contract-farming Supply Chains: A Distributionally Robust Approach

Contract farming is an important tool to promote the agricultural development in the developing countries. In this paper, we study three types of contracts commonly used in a contract-farming agricultural supply chain with a farmer and an agribusiness firm, including fixed procurement price contract, market spot price contract and protection procurement price contract. To accurately capture the correlation between uncertainties and avoid the misspecification of true distribution, a moment-based distributionally robust optimization framework is introduced to analyze the three contracts. We then derive equilibrium solutions of both the farmer and the agribusiness firm under each price contract. Leveraging these results, we can prove that the protection procurement price contract is equivalent to either the fixed procurement price contract or the market spot price contract, which depends on under which contract the farmer can obtain a larger marginal revenue. We further investigate the intrinsic mechanism of the protection procurement price contract, including its impact on the performance of both contract parties and the entire supply chain. Finally, we provide numerical comparisons of our ambiguity-averse solution with the ambiguity-neutral one and also discuss the impact of demand and yield unertainties on the equilibrium profits of both contract parties.

An optimal freshness-keeping effort model for fresh produce with constraints of special funds

<p style='text-indent:20px;'>The quality deterioration in the post-production process of fresh products is very serious, and the life-cycle freshness-keeping technology investment is an effective way to reduce the deterioration. Because the investment cost is high in practice, enterprises need to allocate special funds for each stage to maximize their marginal revenue. In this paper, we use freshness to characterize the quality level of fresh products and investigate a maximize marginal revenue problem where a firm assigns special funds for the freshness-keeping effort with each post-production process. An optimal freshness-keeping model with the constraints of special funds is discussed. The investigation shows that both the optimal freshness-keeping effort and the closed-form optimal solutions of enterprises exist uniquely. A reasonable freshness-keeping investment in different post-production processes can improve the performance of enterprises with limited fund constraints. We then simulate the effect rules of funds constraint on these solutions based on numerical analysis and give some management insights.</p>

An Optimized Method for Accounting Information in Logistic Systems

In the era of rapid information development, with the popularity of computers, the advancement of science and technology, and the ongoing expansion of IT technology and business, the enterprise resource planning (ERP) system has evolved into a platform and a guarantee for the fulfilment of company management procedures after long-term operations. Because of developments in information technology, most manual accounting procedures are being replaced by computerized Accounting Information Systems (AIS), which are quicker and more accurate. The primary factors influencing the decisions of logistics firm trading parties are investigated in order to enhance the design of decision-supporting modules and to improve the performance of logistics enterprises through AIS. This paper proposed a novel approach to calculate the weights of each information element in order to establish their important degree. The main purpose of this research is to present a quantitative analytic approach for determining the important information of logistics business collaboration response. Furthermore, the idea of total orders and the significant degrees stated above are used to identify the optimal order of all information elements. Using the three ways of marginal revenue, marginal cost, and business matching degree, the information with cumulative weights is which is deployed to form the data from the intersection of the best order. It has the ability to drastically reduce the time and effort required to create a logistics business control/decision-making system.

The Minimum Wage Law: A Snare and a Delusion

In the view of many people, understandably, and all too many economists, disgracefully, the minimum wage law actually boosts compensation for people who would otherwise earn less than the amount established by this legislation. This is a snare and a delusion. In actual point of fact, this law increases the wages of no one at all, at least not in equilibrium; rather it leads to unemployment for those workers unfortunate to have a marginal revenue product below the level mandated by this enactment. It is the burden of the present paper to make good on this claim.

Racism Pays: How Racial Exploitation Gets Innovation Off the Ground

Recent work on the history of capitalism documents the key role that racial exploitation played in the launch of the global cotton economy and the construction of the transcontinental railroad. But racial exploitation is not a thing of the past. Drawing on three case studies, this Paper argues that some of our most celebrated innovations in the digital economy have gotten off the ground by racially exploiting workers of color, paying them less than the marginal revenue product of their labor for their essential contributions. Innovators like Apple and Uber have been able to racially exploit workers of color because they have monopsony power to do so. Workers of color have far fewer outside options than white workers, owing to intentional and structural discrimination against workers on the basis of their race. In the emerging digital economy, racial exploitation has paid off by giving innovators a workforce that is cheap, easy to scale, flexible, and productive—the kind of workforce that is especially useful in digital markets, where a first-mover advantage often translates to winner-take-all. This Paper argues that these workers should be paid the marginal revenue product of their labor, and it proposes a number of potential ways to do so: by increasing worker compensation or worker power. More generally, I argue that we should value the essential contributions of workers of color and immigrant workers who make innovation possible.

Misallocation and Capital Market Integration: Evidence From India

We show that foreign capital liberalization reduces capital misallocation and increases aggregate productivity for affected industries in India. The staggered liberalization of access to foreign capital across disaggregated industries allows us to identify changes in firms' input wedges, overcoming major challenges in the measurement of the effects of changing misallocation. Liberalization increases capital overall. For domestic firms with initially high marginal revenue products of capital (MRPK), liberalization increases revenues by 23%, physical capital by 53%, wage bills by 28%, and reduces MRPK by 33% relative to low MRPK firms. The effects of liberalization are largest in areas with less developed local banking sectors, indicating that inefficiencies in that sector may cause misallocation. Finally, we propose an assumption under which a novel method exploiting natural experiments can be used to bound the effect of changes in misallocation on treated industries' aggregate productivity. These industries' Solow residual increases by 3–16%.

Fiscal Exchange and Tax Compliance: Evidence From a Field Experiment

AbstractBehavioral interventions appealing to taxpayers’ reciprocity often leave tax compliance unaffected. We provide evidence that a “fiscal exchange nudge” increased tax compliance in a setting where one might not expect it: crisis‐ridden Argentina. In a randomized controlled trial with over 20,000 taxpayers, a tax bill visually celebrating realized public works benefiting children increased payment rates of tax delinquents by about 20 percent, or almost 40 percent when the bills were delivered in person. Without the appeal, the new bill design generated significantly fewer payments. Changes in the design of the tax bill also increased arrears cancellation. We estimate the ratio of marginal revenues to costs for the fiscal exchange bill to be 18. The factors we associate with the unexpectedly positive impacts are consistent with strengthening an affective response. We find persistent effects of the experiment two years later. The results suggest that communities have more scope to increase tax revenues through non‐threatening interventions.

Quantitative indexes of monopoly and problems of their implementation in antitrust regulation

We considered the quantitative indexes to control different monopoly’s types and identified the main disadvantages, which obstacle the usage of these indicators in practice of the antitrust regulation. Economic methods of antitrust control can be divided into two groups: (1) direct and (2) indirect. The direct ones are based on the market and competitive prices analysis, marginal revenue (MR) and marginal costs (MC) and theoretically, they permit to evaluate directly the negative monopoly’s impact on the market. Indirect methods are based on the non-price indexes (for instance, concentration or share of the firm on market) and identify only the potential hazard from monopoly. However they do not permit to determine whether monopoly indeed negatively impacts on market and in addition the level of such impact. By analyzing of some disadvantages of the monopoly control indexes, we determined several main features, which should have belonged to the new more perfect monopoly index, which would be the subject of our further investigation: (1) to be a dynamic (not a static one) quantitative index of the monopoly power, which evaluates both the fact of the monopoly power existence and the level of the power’s manifestation on the different hierarchical levels (economy, industry, firm) in the mode of real time; (2) to have a capability to separate in the new indicator the innovational component of the monopolist’s costs on the different hierarchical stages; (3) to display the correlation between the monopoly’s power index and the business cycle phases, since the level of the negative monopoly’s impact may be intensified in the recession phase and may be weakened in the recovery phase; (4) to perform the direct control of monopoly through the control of the difference between the market and “natural” (competitive) prices. This control could be realized permanently, actually in “on-line” mode. As compared to indirect methods (which are discrete ones), the price control does not require the confidential information of a firm’s activity, which is often unavailable for the regulator.
 JEL classіfіcatіon: D40, D41, D42, D43