Capital Inputs Research Articles

Inequality in agricultural greenhouse gas emissions intensity has risen in rural China from 1993 to 2020.

Reducing greenhouse gas (GHG) emissions in crop production while ensuring emission equity is crucial for sustainable agriculture in China, yet long-term large-scale data on GHG emissions intensity (GEI) are limited. Using an extensive dataset based on surveyed farm households (n > 430,000 households) from 1993 to 2020, we reveal that 2015 was a turning point for GEI levels, which dropped 16% in 2020, while inequality-measured as average GHG emissions per unit planted area-increased 13%. The key driving forces behind such trends included farmland input, all other inputs, agricultural labour input and total factor productivity but not capital input. Notably, farmland input and all other inputs contributed to 80% of the inequality, while contribution of total factor productivity gradually declined and was replaced by migration-induced agricultural labour input differences. Reducing GEI levels and guarding against widening inequality require optimizing production factor inputs.

Non-optimality of intellectual capital inputs: a new avenue for research

PurposeThis paper aims to initiate new avenues of research by examining optimal intellectual capital (IC) inputs, introducing three theories into the discussion: diminishing returns to scale, transaction costs economics and efficiency wage theory. In the second part, it advocates for demonstrating the existence of such non-optimality through empirical tests.Design/methodology/approachThis paper is divided into two parts. The first part provides a theoretical justification for the necessity of observing nonlinear relationships between IC inputs and firm performance. In the empirical section, the research design follows a four-step process, each progressively building on insights gained from the preceding phase: (1) establishing a baseline linear regression model; (2) introducing the logarithm of the IC inputs; (3) incorporating the square terms of the IC inputs and (4) investigating the phenomena of over- and under-input in IC.FindingsThe background theories and the obtained results highlight the necessity for firms to adopt a strategic approach to IC, acknowledging the diverse effects of IC components on different outcomes. They emphasize the nonlinear nature of IC returns, underscoring the importance of investing up to an optimal level to maximize benefits.Practical implicationsThe study’s discovery of optimal levels for the components of IC highlights the importance for practitioners to identify and invest up to these optimal levels. This ensures that IC initiatives are strategically aligned to maximize their positive impact on firm performance.Originality/valueThe integration of theories such as diminishing returns to scale, transaction costs economics and efficiency wage theory, alongside traditional frameworks like the resource-based view, the theory of dynamic capabilities and the knowledge-based theory of the firm, opens up new avenues for research on IC. The proposed methodology and measures – from financial reports – provide opportunities for replicating this type of study.

Spatial connection strength and endogenous and exogenous interactive driving factors of carbon efficiency in China's metropolitan areas with higher energy consumption

Investigating the spatial effects and driving factors of carbon efficiency is meaningful for the sustainable development of metropolitan areas. However, research on the spatial connection strength and endogenous and exogenous interactive driving factors for metropolitan areas' carbon efficiency are limited. This research studies the carbon efficiency in China's metropolitan areas within year 2003–2019. The spatial connection strength using the gravity model with the “dual” driving factors and the geographical detector are analyzed. The results show that: 1) Shanghai metropolitan area performs well and promotes the development of neighboring cities, but Shenyang and Taiyuan metropolitan areas have negative effects on the neighboring cities; 2) The interaction between land resource consumption and pollution index, energy consumption and economic development level is the main endogenous driving factor with the determinant force values of 0.712, 0.674 and 0.634. Energy consumption is a secondary endogenous factor. Capital input, labor input and pollution play weaker roles. 3) Openness degree and education development level and their interaction are the main exogenous driving factors of carbon efficiency in China's metropolitan areas with the determinant force value of 0.673. Based on the results of interactive driving factors of China's metropolitan areas, this paper gives policy suggestions accordingly.

Determinan Keputusan Petani Mengelola Usahatani Padi Di Lahan Suboptimal

The conversion of paddy fields seriously impacts rice availability for national food reserves, so the government is implementing a sub-optimal land extension program. Indonesia has suboptimal land that has the potential to become a national rice barn if appropriately managed. The types of suboptimal land most widely used in rice cultivation are lowland and tidal swamps, where the community can work. This research analyzes the determinants of rice farmers' decisions in managing suboptimal land. This research was conducted in West Tanjung Jabung Regency, Jambi Province, with a sample of 90 rice farmers. Data were analyzed using the multinomial logistic regression method. The determining factors are seen from the demographic and economic aspects. The research results show that factors that significantly influence farmers' decisions to choose tidal land from the demographic aspect are age and farming experience; from the economic element are the number of family dependents, land ownership status, and non-farming income. The significant determining factors in farmers' decisions to manage lowland swamp land from the demographic aspect are age and farming experience, and from the economic element are the number of family dependents and non-farming income. From the research, recommendations that can maximize the use of suboptimal land are increasing promotion and education to the community about rice cultivation on suboptimal land, providing easy access for farmers to rent land, and it is hoped that farmers will continue to have non-farming income to balance household needs and procurement of capital and farming input.

Capital misallocation and economic development in a dynamic open economy

Some countries, such as Canada, Italy, and Mexico, have experienced a higher growth rate of capital per worker but a lower growth rate for GDP per worker compared to the United States. This paper explains these two facts through the lens of a dynamic multisector open economy model where capital flows across countries. In the model, firms face sector-specific distortions on capital and intermediate inputs that influence the actual rate of return on capital and the aggregate total factor productivity (TFP). We calibrate the model to Mexico for the period 2000-2014 and show that changes in sectoral distortions and productivities reduced the actual rate of return on capital, triggering capital accumulation and a reduction in TFP. The results show that aggregate output decreased by 7.3% and aggregate capital increased by 10.6%. From 33 sectors (out of 48) that suffered productivity losses, approximately 50% accumulated more capital. Furthermore, the capital-intensive sectors explain 82% of the capital-output ratio increase.

Transmission of flood damage to the real economy and financial intermediation: Simulation analysis using a DSGE model

We assess physical risk associated with floods in Japan, using a dynamic stochastic general equilibrium (DSGE) model. We construct a model that incorporates transmission mechanism of floods and estimate the model using the data of flood-induced damage to capital stock and public infrastructure collected by the government in the last 40 years. The result of the analysis is threefold. First, a flood that reduces the private capital stock by about 0.1% as a direct effect causes GDP to fall by about 0.1% in the first period, with a gradual recovery to pre-flood level. Second, floods dampen GDP through multiple channels. From the supply side, a decline in capital stock inputs and total factor productivity (TFP) reduce GDP. From the demand side, the balance sheets of firms and financial intermediaries are impaired, resulting in disruptions to financial intermediation and depressing GDP. Based on our estimates, all these channels are quantitatively comparable in magnitude. Third, the quantitative impacts of flood shocks on GDP up to now have been minor compared to the standard structural shocks that are considered important in existing macroeconomic studies. However, according to the estimates that use the relationship between the key variables in our model together with climate change scenarios published by the Network for Greening the Financial System (NGFS), the impacts of these shocks could become somewhat larger in the future.

Auroral ecosystem services: A cascade model and investigation of co-production processes

This paper serves as an initial exploration of the stages involved in the formation of auroral ecosystem services (ES) and interactions between the geosphere, biosphere and anthroposphere. This is performed through the development of an auroral ES cascade model with the integration of four main co-production stages: (i) value attribution, (ii) mobilization of ES potential, (iii) value appropriation, and (iv) commercialization. The cascade model is expanded upon in detail by using examples from published academic and grey literature, highlighting the demand for capital inputs and strengthening the conceptual understanding of human-nature relationships in the context of auroral ES. The co-production stages illustrate the importance of action on the demand-side in order for the supply of benefits from auroral ES to be delivered. The potential for feedback from the anthroposphere into geophysical properties, processes and functions through anthropogenic space weather and artificial particle precipitation from the Van Allen Radiation Belts via ionospheric heating and low frequency radio wave generation is emphasized. Additionally, feedback via policy and decision making from the anthroposphere into the biosphere and geosphere is highlighted, especially in the context of managing light pollution and artificial space weather. The discussion considers the potential implications of the expanded model, in addition to the valuation of auroral ES across three value domains (monetary, socio-cultural and biophysical) and the potential use of such information in decision-making, followed by reflecting on the potential limitations of the expanded model.

Imported inputs and productivity: Unraveling the dynamics in India's manufacturing sector

AbstractThis study investigates effects of imported intermediate inputs on firms' productivity in the Indian manufacturing. We use a panel data of manufacturing firms from 2001 to 2021 and adopt the production function approach for analysis. Our results confirm the crucial role of all three imported input types at aggregated and disaggregated levels. However, the productivity effect of imported raw materials is the largest, followed by finished goods and capital inputs. Results show the role of imports is marginally higher for high innovation, specialist‐suppliers and science‐based industries. We also show that spillover effects of foreign technology embodied in imported capital goods.

Old wisdom and the New Economic Geography: Managing uncertainty in 21st century regional and urban development

The New Economic Geography (NEG) has over the past decades become a leading paradigm in regional science and geography. This paper seeks to provide a retrospective and prospective look into its achievements and current challenges. Clearly, regions are not oases of tranquility. Uncertainty and shocks in regional and urban development are omnipresent and call for adaptive and resilient strategies on spatial dynamics. The spatial arena is governed by many factors; this is mapped out in the present paper by means of a ‘Pentagon’ model of critical territorial capital inputs which form interdependent anchor points for policy and action based on the principle of confluence. The space-economy is multi-faceted and three prominent challenges in particular, are highlighted in this study: (i) the influence of digital technology on the standard NEG framework; (ii) the livability and proximity conditions in urban agglomerations, critically assessed through the lenses of the currently popular 15-minute city framework; (iii) the implications of social wellbeing and happiness motives for regional and urban planning in an NEG context. The conclusion of the study is that the NEG legacy and principles continue to be prominent signposts for regional and urban analysis and policy, conditional upon a flexible adaptivity of this legacy to new framework conditions in the ever-changing space-economy.

Trends in Greenhouse Production Technology with Special Reference to Protected Cultivation of Horticultural Crops

Greenhouse is an important application scenario of modern agriculture. With the improvement of people's life quality, the demand for vegetables, fruits, flowers and has also increased, and the amount of greenhouses has developed rapidly. Greenhouse adopts artificial technical means to change natural light and temperature conditions, and to create environmental factors to optimize the growth of animals and plants, so that greenhouse crops can grow throughout the year and the weather. Compared with traditional planting methods, the greenhouse is more automated, intelligent, and mechanized. Greenhouse farming (Protected cultivation) refers to the practice of growing crops in an enclosed or partially enclosed environment, such as greenhouses, shade houses, or high tunnels. The primary purpose of protected cultivation is to create a controlled microclimate that shields the crops from adverse weather conditions, pests, and diseases, while optimizing environmental factors. It involves the use of structures, materials, and technologies that provide a protective barrier and allow for manipulation of temperature, humidity, light, and other environmental variables. The benefits of greenhouses are high production per unit area because the genetic potential of the crop can be completely exploited, vegetables and nurseries can be grown off-season that obtain high market prices, good quality products and it is easy to protect the crops from pests, diseases and extreme climatic conditions. Greenhouse farming is a highly intensive industry that needs considerable labour and capital inputs. Because of this, all factors important for a successful enterprisers should be carefully considered by potential growers.

Trade and energy efficiency: theory and evidence

PurposeSome existing studies have begun to discuss how trade will change the environment from a country or province perspective. However, so far, only a limited number of studies have provided evidence at the product level. This study aims to investigate the environmental impacts of trade at the product level.Design/methodology/approachThe effects of importing intermediates and capital inputs on energy performance are examined using theoretical analysis. Empirical analyses are conducted using data on product trade, and the effects of importing intermediate inputs and capital inputs on energy efficiency are identified using a Propensity Score Matching-Difference in Difference (PSM-DID) estimation.FindingsThe results demonstrate that importing intermediates and capital inputs effectively enhance energy efficiency. Importing these inputs from foreign markets leads to increased productivity and ultimately improves energy performance.Originality/valueThis research provides new evidence on the relationship between importing and energy use at the product trade level. It offers insights into enterprise behaviors regarding importing intermediates and capital inputs, contributing to a deeper understanding of the environmental effects of trade. Additionally, a micro-theoretical model is developed to examine the impacts of imports on energy efficiency, complementing existing literature with theoretical insights.

Recent CO2 emission and projections in Chinese provinces: New drivers and ensemble forecasting

Although extensive studies focused on the driver of changing CO2 emission, the roles of labor and capital were largely ignored in shaping spatiotemporal change in CO2 emission and forecasting differences on CO2 emission was few considered, hindering relevant policymaking towards sustainable development in both climate change mitigation and economic growth for developing countries in particular. To fill the gap above, the study explored the roles of capital and labor in contributing to recent CO2 emission in a case of China over 2010–2019 and projecting provincial CO2 emissions to 2030, by proposing two new spatiotemporal logarithmic mean Divisia index models with Cobb-Douglas production function and developing an ensemble forecasting model including machine learning. We found, first, the effects of capital and labor inputs and carbon factor were the positive drivers affecting aggregate CO2 emissions, while the effects of the total-factor productivity and energy intensity were negative drivers. Second, the effects of capital and labor inputs were the negative drivers for narrowing the emission gap. Third, the ensemble forecasting model can improve the generalization ability of CO2 emission predictions. Therefore, we recommend that policymakers focus on optimizing the carbon reduction effects of capital and labor inputs while promoting the development of a circular economy to achieve sustainable economic growth.

The high price U.S green economy: A specific factor modeling

The high price of energy due to the green energy policy will cause adjustments across the U.S. economy is predicted in the present computable general equilibrium with specific factors model. This includes energy input, especially electricity with capital and labor to produce manufacturing and service goods. 2022 labor, energy, and sector-specific capital input data on U.S. manufacturing, service, and agricultural sectors is applied to specific factors of the computable general equilibrium model. The model, which assumes constant returns, full employment, competitive pricing, and perfect labor mobility across industries hypothesizes a range of price changes due to project potential adjustments in factor prices and outputs. The U.S manufacturing sector is revealed to have a higher degree of noncompetitive pricing for energy factor inputs, but not on labor and capital as advocates for green energy tout by the new technology. The policy has virtually no significant impact on the service and agricultural sectors. The high price of green energy will cause an elastic decrease in all energy inputs. The output from energy-intensive manufacturing only rises in the long run by 4 % while service and agriculture fall. Clear winners are the owners of energy resources through their price-searching behavior. This includes the government, which owns a large share of hydrocarbon reserves.

How does the development of digital economy in central cities promote the coordinated development of regions? Evidence from 19 urban agglomerations in China

Externality is the power source of the spillover effect of digital economy development in China's central cities. Based on panel data of 200 prefecture-level cities in 19 urban agglomerations in China from 2011 to 2020, this research constructs a theoretical model with income output, labor, and capital input and adopts the panel fixed effect model to empirically test the impact of central cities' digital economy development on peripheral cities' urban agglomerations. The results are as follows. First, digital economy development in central cities significantly improves the level of such development in peripheral cities. Second, the spillover effect of this development in central cities is affected by their own geographical location, economic development level, and city size. Third, the spillover effect of digital economy development in central cities mainly arises through the learning mechanism.

Analysis of labor force, capital and production outputs of border territories of Kazakhstan and Uzbekistan on economic growth

Border areas can play a crucial role in market integration and infrastructure development between Central Asian countries, thus creating favorable economic growth and regional cooperation conditions. This study aims to assess the economic impact of border areas between Kazakhstan and Uzbekistan, focusing on their role in enhancing market integration and infrastructure development to foster regional growth and cooperation. Focusing on labor and capital as essential production drivers, this study employs a sophisticated panel data regression model to explore the Cobb-Douglas production function’s application in these border territories. The research findings indicate that regions’ elasticity towards capital and labor inputs vary, necessitating differentiated economic strategies. For capital-intensive areas, we recommend prioritizing investments in infrastructure and technology to boost production outputs. Conversely, in regions where labor significantly influences production, the emphasis should be on human capital development through education, training, and improved labor market conditions. The study’s insights into the evolving trade relations between the two countries underscore the need for flexible economic policies to enhance regional integration and cooperation. This research not only fills a crucial knowledge gap but also offers a blueprint for leveraging the diverse economic landscapes of Central Asia’s border areas in future policy-making and regional economic strategy.

City-level green growth accounting: Evidence from China's thirteen urban agglomerations

Cities play a pivotal role in achieving 'Carbon Peak' and 'Carbon Neutrality' objectives through the implementation of strategies aimed at mitigating environmental risks. While the environmental impacts of industrial production activities have been widely examined, the nuances of their internal structures remain obscure. This study delves into the industrial sector across the 'thirteen urban agglomerations (TUAs)' in mainland China, covering the years 2006–2016, by developing a comprehensive (source-specific and variable-specific) decomposition framework for Malmquist productivity index. The framework is utilized to discern whether efficiency changes or technological advancements drive productivity growth, considering input/output variables such as capital and labor. Findings show that the average annual environmental productivity gain during the examined period was 2.6 %, suggesting a general enhancement in productivity within TUAs' industrial sectors. A detailed breakdown of productivity changes indicates that a combined contribution of 1.8 % to environmental productivity growth stemmed from energy use and pollutant variables, with emissions of industrial sulfur dioxide being the most significant at 0.9 %. Conversely, the 'catch-up effect,' or environmental efficiency change, was negative (−0.2 %), indicating the TUAs' inability to emulate the productivity levels of more advanced areas. Industrial energy use and capital inputs were the primary contributors to this negative trend, each accounting for a −0.2 % impact. The results underscore the importance of facilitating technology transfers from more developed to less advanced regions, especially regarding renewable energy and capital investment, to bolster environmental performance and productivity in the TUAs' industrial sectors.

Sectoral impacts of climate change in Iran: A dynamic analysis with emphasis on agriculture

Iranian agriculture, the largest consumer of water, is highly vulnerable to sever climate change-induced droughts. This study aimed to analyze the impact of climate change on various sectors, with a focus on agricultural output and gross domestic product (GDP). To achieve this, a dynamic Computable General Equilibrium (CGE) model incorporating a climate damage function was utilized to project the consequences of climate change on various sectors of Iran's economy. The damage function is based on the temperature anomaly. This study simulated the impact of shocks caused by climate scenarios by 2060. The modified Social Accounting Matrix served as the primary dataset for CGE modeling. By simulating climate scenarios up to 2060, the findings indicated that certain agricultural products, such as cereals and livestock, have the potential for an annual output expansion of 2–3.5 % under the most severe climatic scenarios. This expansion is attributed to their lower reliance on capital inputs and their increased final demand for agricultural commodities. Conversely, the growth rates of output expansion and final demand for services products are lower than those for agricultural products. With climate change options, there may be a shift in output composition, favoring crops, agricultural industries, and energy products, while the growth of services output remains comparatively lower. The GDP growth path also deviates from the current path of 1.8 %, reaching rates of 1.5–1.7 %. In the most restrictive scenario, the GDP is projected to decline in the mid-2050s. Similarly, the range for consumption growth is estimated to be 1.8–2.1 %. Climate change does not significantly alter the income distribution within rural and urban income groups. However, it exacerbates rural-urban inequality by favoring urban households with higher consumption levels. The current state of the Iranian economy, especially the agricultural sector, faces increased vulnerability due to climate change. Nevertheless, certain agricultural activities may experience a relatively greater increase in output because of the growing demand for these products.

Collaborative strategies in the product-sharing market considering manufacturer's capital entry

Digital technology and online platforms have enabled large-scale business-to-consumer (B2C) sharing of normalized products. Recently, B2C sharing platforms have also become very popular. The impact of B2C sharing on traditional manufacturers can be very significant. With increased competition on the business end, many manufacturers (e.g., BYD and Didi; FAW and T3) have accessed the sharing market to provide customized products and technology services in addition to outright sales to platforms. This paper studies a capital-constrained sharing platform and manufacturer's optimal collaborative strategy in the sharing market and the economic implications of their collaboration. We propose a decomposition framework to establish three capital collaborative strategies based on a non-collaborative strategy (N-with-C), which is associated with different levels of the platform's capital and the manufacturer's capital entry. The three collaborative strategies are physical capital collaboration without service capital constraints (P-without-SC), physical capital collaboration with physical and service capital constraints (P-with-SC) and physical and service capital collaboration with physical and service capital constraints (PS-with-SC). We employ a game-theoretic analytical model for our analysis. Our results show that (i) the choice of a certain collaboration strategy depends on the platform's and manufacturer's decisions and how such interaction is affected by decision parameters such as initial capital level, claim proportion, spillover of product launch quantity, utilization efficiency and service efficiency; (ii) with a decrease in the platform's capital level, the N-with-C strategy gradually ceases to be the sharing platform's strategy choice; and (iii) with the manufacturer's service entry, the manufacturer suffers a complete reversal of the optimal strategy choices when choosing between the non-collaborative strategy and collaborative strategies, but P-with-SC is better than non-collaboration under a higher claim proportion and the sharing platform always prefers to collaborate. These results suggest that an increasing asymmetry of capital input and control rights influences the level of collaboration between the sharing platform and manufacturer.

Human Capital Structure and Innovation Efficiency Under Technological Progress: Evidence from China

This paper innovatively defines the structure of human capital based on existing theories and use the heterogeneous stochastic frontier model to test the relationship between various types of human capital and innovation. It is found that with the progress of technology, the structure of human capital and the mechanism of promoting innovation have undergone profound changes. Together with commercial leasing human capital, financial human capital, and entrepreneurs, information human capital and transportation human capital participate in innovation activities and create a new collaborative space, which in turn helps to spread the value of innovation and influence the effectiveness of the entire innovation system. This study enriches the theoretical research on the mechanism of human capital promoting innovation in the information age and provides new insight to explain the imbalance between human capital input and innovation output. Based on the theory of innovation chain value and flow space, this study redefines the connotation of innovative human capital structure by distinguishing the nature of innovation activities. This study also reveals the difference in the influence of human capital structure on different types of innovation activities. This study partly explains the problem of increasing human capital input but decreasing innovation efficiency in developing countries. Therefore, from a macro perspective, our research provides guidance for understanding the transformation of innovation under the background of technological progress and formulating effective urban innovation strategies for managers.

Export Instability, Investment, Export Growth and Economic Growth in India

The “Export-led Growth Hypothesis,” as it is known in the literature, is still a popular issue in both theoretical and empirical research. According to the export-led growth hypothesis (ELGH), a key factor in determining growth is the expansion of exports. It asserts that growing capital and labour inputs into the economy as well as exports can contribute to a country’s overall growth. The association between economic development, export growth, export fluctuation, and real effective exchange rate (REER) in India from 2001 to 2021 is examined in this paper using a multiple linear regression analysis model. Additionally, the impacts of foreign exchange, export fluctuation on investment, and import of capital goods have also been studied. The autocorrelation is also tested using the Durbin-Watson (D-W) test. Investigation of the association between income growth and exports in the context of India reveals that the country’s exports haven’t increased significantly enough to prove the theory of export-led growth. For instance, ceteris paribus, one per cent change in exports over time is expected to result in a 0.007 per cent increase in GDP. Weaker global demand, inflation, dropping exports, and growing global trade conflict all contribute to a weaker-than-expected positive link between GDP and exports. However, the findings have also shown that one per cent rise in instability increases GDP by 5.04 per cent. Furthermore, research has indicated that export instability does contribute to import for capital goods and demonstrates the relationship between investment and export instability is positive but not statistically significant. The result for policy is that, in order to decrease the negative impacts of export fluctuations, India should concentrate on those goods in which it has a competitive edge. The primary factors of the excessive volatility and restricted growth must be fully investigated in order to mitigate instability, and inherent flaws must be addressed.