Estimation of Money Demand Function of South Korea Considering Regime Switching

The stability of money demand function is an important issue in macroeconomic policy implementation. Money demand of Korean economy was estimated. Cointegration test with time dummy variables results show that there is not only long-run equilibrium relationship between money demand and macroeconomic variables, but also structural breaks in this equilibrium relationships. Least squares, state-space, and Marcov switching methods show that there also has been instability （or regime shifts） of parameters in money demand, especially over 1997 crisis and the early 2000s. This fact implies that monetary policy for stabilization might encounter big problems due to change （instability） of money demand.

Inventory Management and Demand Forecasting Improvement of a Forecasting Model Based on Artificial Neural Networks

Forecasting is predicting or estimating a future event or trend.Supply chains have been constantly growing in most countries ever since the industrial revolution of the 18th century.As the competitiveness between supply chains intensifies day by day,companies are shifting their focus to predictive analytics techniques to minimize costs and boost productivity and profits.Excessive inventory(overstock)and stock outs are very significant issues for suppliers.Excessive inventory levels can lead to loss of revenue because the company's capital is tied up in excess inventory.Excess inventory can also lead to increased storage,insurance costs and labor as well as lower and degraded quality based on the nature of the product.Shortages or out of stock can lead to lost sales and a decline in customer contentment and loyalty to the store.If clients are unable to find the right products on the shelves,they may switch to another vendor or purchase alternative items.Demand forecasting is valuable for planning,scheduling and improving the coordination of all supply chain activities.This paper discusses the use of neural networks for seasonal time series forecasting.Our objective is to evaluate the contribution of the correct choice of the transfer function by proposing a new form of the transfer function to improve the quality of the forecast.

Toward a sustainable future:Examining the interconnectedness among Foreign Direct Investment(FDI),urbanization,trade openness,economic growth,and energy usage in Australia

The energy demand in Australia is increasing with the industrialization and rapid economic growth.This study analyzed the relationships among the economic growth,Foreign Direct Investment(FDI),trade openness,urbanization,and energy usage in Australia based on the data from World Development Indicators(WDI)from 1972 to 2021.The results indicates that there is a cointegration among economic growth,FDI,trade openness,urbanization,and energy usage,which was traced through the autoregressivedistributed lag(ARDL).The Zivot-Andrews unit root test reveals that energy usage,economic growth,FDI,urbanization,and trade openness show significant structural breaks in 1993,1996,1982,2008,and 1994,respectively.The ARDL model shows that economic growth has a positive and significant effect on energy usage in the long-run(0.814)and short-run(0.809).Moreover,the results also show that FDI(0.028)and trade openness(0.043)have positive impacts on energy usage in the long-run.However,urbanization shows a negative and significant influence on energy usage in the long-run(–0.965).Then,the research demonstrates a unidirectional causation between energy usage and trade openness,with energy usage significantly causing trade openness.The current study endorses energy consumption policies and investment strategies for a paradigm shifting from a reliance on fossil fuels as the primary energy source to renewable energy sources.These findings have profound implications for sustainable energy usage.

Segmentation of electricity market for households in Slovenia

This paper investigates the electricity market for households in Slovenia. The focus is on the investigation of some empirical facts in the Slovenian electricity market for households focusing on market segmentation, market concentration measures, real electricity price developments, and their implications for electrical energy consumption and consumer welfare. The authors apply descriptive statistics, Lorenz curve and Gini coefficient of concentration, and demand function using regression framework on time-series data. The authors found that the market liberalization and entry of new competitors have slightly caused variations in the patterns in real electricity price developments. Households＇ real income and real electricity prices for households are found as the crucial determinants for the electrical energy demands by households.

Droop Control for Micro-grid Operations Including Generation Cost and Demand Side Management

A new cost-based droop control method based upon generation cost and demand side cost management of the microgrid is proposed in this paper.At present,many droop control methods have been developed based on either the power rating or the generation cost of the distributed generation(DG)unit,without consideration of the demand side participation in the operation and control.This exclusion might not be appropriate,if different types of consumers are connected in the micro-grid systems.This study proposes a droop control method considering both DG and load operating cost characteristics in order to minimize the generation cost of the micro-grid.

Pricing and Inventory Control Strategy for a Periodic-Review Energy Buy-Back System

Along with the rapid development of economics and enhancement of industrialization, the power demand keeps rising and frequently creates mismatch between demand and supply in electricity.This provides miscellaneous energy buy-back programs with great opportunities. Such programs, when activated, offer certain amount of financial compensations to participants for reducing their energy consumption during peak time. They aim at encouraging participants to shift their electricity usage from peak to non-peak time, and thereby release the demand pressure during peak time. This paper considers a periodic-review joint pricing and inventory decision model under an energy buy-back program over finite planning horizons, in which the compensation levels, setup cost and additive random demand function are incorporated. The objective is to maximize a manufacturer's expected total profit.By using Veinott's conditions, it is shown that the manufacturer's optimal decision is a state dependent(s, S, P) policy under a peak market condition, or partly an(s, S, A, P) policy under the normal market condition.