Demand Components Research Articles

Public-Private Investment and Economic Growth in Pakistan: An Empirical Analysis

Investment is an important component of aggregate demand and a leading source of economic growth. Change in investment not only affect aggregate demand but also enhance the productive capacity of an economy. A third important role highlighted in the literature refers to the innovation and modernisation of the capital equipment via technological progress. The investment plays an essential and vital role in expanding the productive. Maryam capacity of the economy and promoting long term economic growth [Jongwanich and Kohpaiboon (2008)]. Levine and Renelt (1992) argued that investment in capital goods is the most robust and vital determinant of economic growth. Gross domestic investment boosts economic growth by increasing physical capital directly and indirectly through technological spillovers [De Long and Summers (1995)].

WITHDRAWN: Does stock return affect decomposed energy shocks differently? Evidence from a time frequency quantile-based framework

We study the interconnections and consequences of fluctuations in energy prices on the returns of stocks within both highly optimistic and pessimistic market conditions, considering both short and extended timeframes. The research follows a two-part methodology: initially breaking down energy price shocks into components of demand, supply, and risk using the Ready method, and subsequently applying a quantile frequency connectedness technique. The outcomes demonstrate that the correlation between energy price shocks and stock returns in the enlarged BRICS markets is substantial during extremely bullish and bearish periods, but comparatively lower during normal circumstances. Among the various types of energy price shocks, those driven by shifts in demand exhibit a more pronounced influence on stock returns compared to supply and risk-induced shocks. The transmission of effects from energy price shocks to stock returns becomes evident over extended periods, i.e., beyond five days, particularly in the context of extreme bullish and bearish market conditions. Notably affected by these shocks, mainly in the long term, are the oil-exporting countries such as Russia, Brazil and the upcoming joiner Saudi Arabia (KSA), as well as China – an oil-importing nation. Given the economic and political significance of the inclusion of the heavyweight oil-exporting nations in BRICS is likely to make in minimising the gap between the global North and the South, these findings hold significant implications for both investors and policymakers, guiding them in making well-informed investment choices and crafting effective strategies for managing risks.

N − 1 Security Criteria Based Integrated Deterministic and Probabilistic Framework for Composite Power System Reliability

Unpredictable variations in load demand and unanticipated component failures are progressively impacting the operation of modern power systems, making system evaluation more stochastic in nature. Although deterministic approaches were formerly the norm for determining system status, probabilistic approaches have greatly improved the capacity to capture the stochastic behavior characteristic of power system operations. The presented work in the paper recommends the use of probabilistic modelling approaches with deterministic approaches, highlighting their crucial function in augmenting the reliability and security of contemporary power systems to unanticipated failures. In this paper, N − 1 security criteria based reliability of the composite power system (CPS) is proposed using an integrated deterministic and probabilistic framework (D-P) considering outage of the transmission line. For the deterministic approach (DA), line overloading on available lines is determined using the static security index (SSI). For the probabilistic approach (PA), reliability indices such as expected loss of power (ELOP), expected frequency of contingency (EFOC), expected loss of load (ELOL), probability of load curtailment (PLC), and expected duration of load curtailments (EDLC) are calculated. Further, for each contingency, a performance index is determined using both approaches to assess the severity of the contingency that occurred on the power system. Based on the N − 1 security criteria based reliability analysis using an integrated D-P framework, a credible critical set of transmission lines is obtained, which can serve as important information to system operators. The proposed techniques have been tested on IEEE 24 bus reliability test system (RTS).

Aggregate demand and inflation response to monetary policy shocks in Tunisia

We investigate the response of aggregate demand (AD) components and inflation to monetary policy (MP) shocks in the Tunisian context where studies on this issue are rare. By estimating SVAR models on historical data ending in 2021, we found that: i) The Tunisian Central Bank’s (TCB) efforts to control inflation through interest rate tightening end up significantly slowing down private investment and consumption, while inflation response is not enough to mitigate the recently exacerbated inflationary trend; ii) Such efforts are hampered, if not outweighed, by the “pass-through” effect associated with exchange-rate continued depreciation; iii) The interest rate is Granger-caused by the exchange rate rather than the inflation rate, suggesting that de jure and de facto objectives of the TCB are divergent; and iv) The continued exchange rate depreciation alone is not enough to address the structural trade deficit. In light of these findings, we suggest that i) The transition from a discretionary MP to a rule-based inflation-targeting MP and with a well-defined role for the exchange rate, would help TCB gain credibility and improve efficiency of its MP; and ii) Tunisian policymakers should also consider consolidating MP in achieving its price stabilization objective particularly through implementing “supply-side policy” actions aiming at promoting economic growth and addressing unsustainable fiscal and external imbalances.

Using Principal Component Analysis to Explore Optimization Strategies for Field Engineer Course Design in Higher Vocational Education

Abstract In the process of cultivating field engineers and vocational education in colleges and universities, there are such realistic dilemmas as the imperfect collaborative education platform and the urgent need to reconstruct the whole process of integrated education in the curriculum system. This paper explores the talent cultivation path of field engineers from the realistic dilemma of field engineer cultivation and designs the field engineer curriculum system based on the integration of industry and education and school-enterprise cooperation. Then, construct the index system of influencing factors for field engineer curriculum design and explore the further optimization strategy of curriculum design using principal component analysis. The KMO value is 0.962>0.9, and the Sig. of Bartlett’s spherical test is 0.000<0.05. There is a correlation between the variables of the influencing factors, and it is suitable for principal component analysis. The study extracted six principal components of social demand, practical ability, innovation, and entrepreneurship ability, teaching feedback, comprehensive literacy, and theoretical knowledge using principal component analysis, whose cumulative contribution rate reached 95.428%, and the results of the principal component analysis can better explain the influencing factors of the design of the field engineer course. The purpose of this paper is to provide a strategic direction for further optimizing the design of field engineering courses in higher vocational education.

Optimization of Neutrosophic EOQ Model for Effective Demand Management in Uncertain Environment Using Genetic Optimization

Inventory management is characterized by a continuous struggle to lower goods levels and related costs while also providing customers with the goods they need. However, reducing costs while simultaneously striving for ideal inventory levels is difficult, notably in the current situation of high unpredictability of goods demand and lead time. Traditional inventory models are not strong enough to endure changes like goods demand and lead-time demand. As a result, it must be adjusted to achieve results. The oeuvre below presents a new kind of inventory model that deals with uncertainty in the demand for goods and lead time. In this regard, the presented work, the novel Neutrosophic Economic Order Quantity approach is a mechanism to account for the likely imprecision in the model. Specifically, the Neutrosophic set theory is integrated into the EOQ model so that it can handle variations in the demand and lead-time pattern successfully. An objective function is established for obtaining economical order quantities that include demand, lead-time, and other necessary components’ irregularities. The process variables in the model are given the final values using genetic algorithms and simulated annealing. To highlight the impact of the proposed Neutrosophic approach, it is then applied to several realistic examples. This will provide the audience a sense of how effective inventory management may be in high-uncertainty situations. The rapid evolution of organizations necessitates innovative inventory control tactics to meet growing demands

An analysis of economic growth using input–output tables

Two perspectives on the analysis of economic growth have developed within the input–output framework. On the one hand, Leontief proposed a dynamic model, where investment supplies the necessary capital stock needed to produce future output. On the other hand, Structural Decomposition Analysis assumes that changes in the output level are dependent on the behaviour of the technological and final demand components. This paper examines the differences between input–output tables of different periods to explain growth, as well as the contribution of the final demand components in the phenomenon. Further, the article provides examples based on the coefficient tables of five OECD economies, between 1995 and 2011, to illustrate the relevance of the method proposed here.

How diversification of products impact emissions in China: a provincial perspective.

Currently, global warming and air pollution are the world's most urgent issues partly caused by carbon dioxide (CO2) and sulfur dioxide (SO2) emissions, and prompt actions are needed to address these global concerns. Sustainable development cannot be attained until we reverse the negative impact of economic factors on the quality of the environment. It is noteworthy to offer a new indication on whether and how the empirical liaison between product diversification and environmental degradation evolved in China from 2008 to 2019. Product diversification (PD) is a remedy for reducing environmental degradation (ED). It is a crucial component of energy demand, which a significant impact on reducing energy consumption and ED. The purpose of this study is to investigate the impact of PD on ED in China using the provincial panel dataset. Employing the fixed effects-Driscoll-Kraay standard errors (FE-DKSE) and feasible generalized least squares (FGLS) methods, we discover an inverted U-shaped link between PD and ED. The control variable urbanization (URB) and technological innovation (TI) reduce ED significantly. However, industry value added (IVA) and energy consumption (EC) promote ED. Our results are robust with the addition of various controls in all models. The policy implication from our findings is that, to achieve a target of carbon neutrality, countries should adopt the product diversification strategy.

Components of Autonomous Demand Growth and Financial Feedbacks: Implications for Growth Drivers and Growth Regime Analysis

ABSTRACT This paper presents a simple closed-economy model that is driven by the growth of two autonomous components of demand, namely government spending and rentiers’ consumption out of interest income. Using this model, it seeks to make two contributions. First, by focusing on the financial dynamics that arise from debt-financed government spending, we show that an underlying stock-flow interaction provides an endogenous mechanism which, under certain conditions, aligns the two autonomous growth rates in the long run. Hence, an economy can be driven by two autonomous components of demand, without one dominating the other in the long-run nor without policy changes being required to align the two growth drivers. Second, we prove that if two autonomous demand components are dynamically interdependent, then the relative size of their growth contributions may be misleading as a guide to classify growth regimes, both in the long-run equilibrium as well as during the traverse towards this equilibrium. Furthermore, we show that the relative growth contributions are economic policy contingent. We thus argue that interdependencies between autonomous growth components arising from financial stock-flow interactions should not be ignored in Sraffian supermultiplier growth decomposition exercises that aim to identify underlying growth drivers.

قياس وتحليل مكوّنات دالّة الطلب الكينزية وأثرها على النموّ الاقتصادي ( العراق حالة دراسية ) للمدّة 2000- 2020

As known that, Iraqi economy rely significantly on oil export, therefore this economy consider to be addiction to oil. Oil sector finance the most government expenditure. Aggregate demand in Iraq depends on government expenditure in turn government expenditure depends on foreign trade. The research highlight on components of aggregate demand in Iraqi economy and in what extent those components effect on the growth of GDP. Modern econometrics methods was used to analysis and test the relationship between dependents variables which represented by aggregate demand components and independent variable which represented by GDP growth and their conformity to the Keynesian model. The research concluded that there is distortion in aggregate demand components in effect to the GDP growth.

Learning, externalities, and export dynamics: Evidence from Chilean exporters

This paper presents a model of exporting with demand uncertainty where incumbents reveal signals about a shared component of demand that potential entrants use to update beliefs. Using Chilean export data, signals are estimated and used to examine the effects of information on entry into new markets, quantity of output sold, and duration of exporting. A one-standard-deviation-increase in signals by incumbents is associated with 6.3% higher entry rates, 11.7% larger first-year export volumes, and 0.6% longer duration. Information spillovers are larger in distant countries, in countries where Spanish is not an official language, for homogeneous products, and for larger firms.

An Activity Theoretical Perspective on Writing and Supervising a Master’s Thesis

For students as novice researchers, a master’s thesis is the most demanding component because it requires them to display and learn research skills and work independently. Unfortunately, master thesis supervision has remained far from the limelight of university pedagogy. Drawing on mixed-methods research, this paper characterizes the writing and supervising of a master’s thesis from the perspective of cultural-historical activity theory. It presents various components of the activity system and how the interaction between these systems creates conflicts and contradictions. The implications of such an understanding to effective master’s thesis writing and supervision have been provided.

The COVID-19 recession on both sides of the Atlantic: A model-based comparison

This paper compares the COVID-19 recession in the euro area (EA) and the US using an estimated multi-region New Keynesian macroeconomic model. To capture quarterly dynamics from 2020 onwards, we introduce relevant extensions such as ‘forced’ savings, extensive versus intensive employment margins, and trade in commodities as inputs to production and final demand. Transitory (‘forced’) savings are central to account for the behaviour of economic activity in both regions during the pandemic, which was strongly driven by private consumption, alongside other shocks to domestic demand and shocks to foreign activity. The model highlights the importance of demand recovery and rising commodity prices for the inflation acceleration during 2021–22. EA inflation has a stronger supply component (including commodity prices) compared to a stronger demand component in the US.

La evolución reciente de las exportaciones españolas de servicios no turísticos

RationaleThe strong growth in exports of non-travel services following the pandemic has contributed significantly to Spain’s economic recovery. It is therefore useful to analyse recent developments in these exports.Takeaways•The cumulative growth of real exports of non-travel services between 2020 and 2022 amounted to practically 50%. In 2022, they thus stood almost 20% above their 2019 level, a significantly larger gap than for other final demand components.•The recovery in non-travel services exports following the pandemic has boosted this item’s sustained growth of recent decades and has been mainly underpinned by exports of business, transport and IT services, especially to the euro area and North America.•The competitiveness of large Spanish exporting firms, which generally form part of corporate groups, might explain, at least in part, the robust growth in non-travel services exports after the pandemic.

Extension and update of multiscale monthly household carbon footprint in Japan from 2011 to 2022

Household consumption significantly contributes to greenhouse gas emissions as it is the largest component of final demand in the national accounting system. Nevertheless, there is an apparent lack of comprehensive and consistent datasets detailing emissions from household consumption. Here, we expand and update Japan’s multiscale monthly household carbon footprint from January 2011 to September 2022, combining data from government statistics and surveys. We constructed a dataset comprising 37,692 direct and 4,852,845 indirect emission records, covering households at the national, regional, and prefectural city levels. The dataset provides critical spatiotemporal information that allows for revealing carbon emission patterns, pinpointing primary sources of emissions, and discerning regional variances. Moreover, the inclusion of micro-scale carbon footprint data enables the identification of specific consumption habits, thereby regulating individual consumption behavior to achieve a low-carbon society.

Application of graphene based supercapacitor in DC-Microgrids

Developments in renewable resource technology, advancement in power electronics and upgradation in storage element technology is leading to formation of DC-Microgrids. Graphene is a single layer of carbon allotrope graphite which is packed in honeycomb structure. Graphene offers high surface area and high energy density. Graphene is extensively used in supercapacitor development as an electrode material. In a DC-microgrid a combination of supercapacitor and battery is used as a storage element to take care of transient and steady-state disturbances in DC-link power. While meeting the dc link power demand, the supercapacitor supplies the transient power component of the dc-link power demand whereas the battery will supply the average power component of the dc-link demand. In this work a closed loop controller is proposed for controlling the power flow through a graphene-based supercapacitor and battery energy storage system for meeting the dc-link power demand in a DC-microgrid. The above proposed system is studied in MATLAB/SimPowerSystems softwares alongwith the hardware results obtained from the setup comprising of battery and supercapacitor.

O quarteto impossível em um modelo supermultiplicador de crescimento liderado pela demanda para uma pequena economia aberta

ABSTRACT The aim of this paper is to investigate the long run sustainability of a growth path led by multiple non-creating capacity autonomous expenditures in a demand led-supermultiplier model for a small open economy. Using two different models the results show that it is impossible to have in the same model long-term economic growth driven by the non-capacity creating component of domestic demand, exogenous income distribution, long-run balance between productive capacity and aggregate demand and balance of payments equilibrium. Economic viability of the balanced-growth path demands growth to be led by exports, at least for small open economies.

Regimes de crescimento nos países centrais e periféricos: uma análise econométrica, 1980-2018

ABSTRACT We explore structural differences in growth patterns and income distribution between central and peripheral countries. We provide dimensions that account for the structural limitations that dependent positions have in the peripheries and semi-peripheries. We conducted an analysis through different estimates of panel data models for 35 central and peripheral countries for the period 1980-2018. In particular, in addition to making the usual estimates of the components of aggregate demand, we include three variables that we consider representative of the dynamics that capital accumulation takes in the periphery: participation in global value chains, levels of foreignization of economies and labor productivity differentials.

La evolución reciente de la inversión en España desde una perspectiva macroeconómica

RationaleCyclical fluctuations in investment are usually sharper than fluctuations in other components of aggregate demand. This article aims to analyse, based on an econometric model, the role played by interest rates, demand and agents’ confidence (the drivers traditionally studied in the literature) in the behaviour of investment under such atypical cyclical circumstances as those derived from the pandemic and the energy crisis.Takeaways•The results show that investment responds negatively to interest rate rises, while enhanced agents’ confidence and greater demand have the opposite effect.•In the absence of new shocks, the bulk of the impact of interest rates on investment occurs with a lag of several quarters, whereas agents’ confidence and demand operate with shorter lags. Given these lags, the interest rate increases and the decline in confidence which took place in 2022 appear to have had a negative effect on investment in 2023, partially offset by the positive impact of the buoyancy of demand recorded last year.•In order to analyse the changes in investment, the effects deriving from any shocks that may arise this year, including those deriving from the variables analysed in this article and other shocks not addressed in this model, should be added to the above-mentioned effects.

Effect of climate change on reservoir water balance and irrigation water demand: a case of Gidabo irrigation project, Rift Valley Basin, Ethiopia.

The consequences of climate change on agriculture water demand are among the current and prospective challenges. The amount of water needed by crops is significantly affected by the regional climate. The influence of climate change on irrigation water demand and reservoir water balance components were examined. The results of seven regional climate models were compared, and the top-performing model was chosen for the study area. After model calibration and validation, the HEC-HMS model was used to forecast future water availability in the reservoir. The results show that under the RCP 4.5 and RCP 8.5 emission scenarios, the reservoir's water availability in the 2050s will decline by approximately 7% and 9%, respectively. The CROPWAT results showed that the required irrigation water might rise by 26 to 39% in the future. However, the water supply for irrigation may be drastically reduced due to the drop in reservoir water storage. As a result, the irrigation command area could drop up to 21% (2878.4ha) to 33% (4502ha) in future climatic conditions. Therefore, we recommend alternative watershed management techniques and climate change adaptation measures to endure upcoming water shortages in the area.