This research investigates the impact of inflation on income inequality in Indonesia. This study is part of a comprehensive examination investigating which monetary policy can be utilized to lessen inequality. As a central bank objective, inflation can influence the distribution of income, wealth, and endogenous consumption, hence defining inequality. This study employed dynamic panel data analysis for linear autoregressive data using the generalized method of moments (GMM) for both first differences GMM (FD-GMM or AB-GMM) and system GMM (Sys-GMM or BB-GMM) with regional data from 58 cities in 2010-2020. The Arellano-Bond estimator reveals a positive and statistically significant association between inflation and inequality. When inflation rises, the purchasing power of the poor will decline, while the wealthiest will benefit as their non-cash assets proliferate. This study finds, indirectly, that Indonesia’s monetary policy can play a crucial role in lowering income distribution gaps. As one of the nations with an inflation-targeting framework, the Indonesian Central Bank can target the inflation rate by considering inequality. The ITF becomes the most effective monetary policy for stabilizing prices and promoting economic stability. The ITF reduces income inequality by reducing inflation rates. The study also finds that, similar to other emerging nations, economic growth in Indonesia exacerbates inequality. Poverty can be reduced by increased economic growth, but the positive impact of development on the wealthy is significantly more significant than on the poor. Therefore, economic expansion increases inequality.

This study examined the causal relationships between inflation, Gross Domestic Product (GDP), domestic savings, and investment in Zimbabwe using Toda-Yamamoto causality tests and the Autoregressive Distributed Lag (ARDL) approach with secondary data spanning from 1990-2022. The Granger causality analysis revealed a bidirectional causal effect between inflation and GDP, indicating that inflation significantly impacts the country's economic growth. Additionally, the analysis showed a unidirectional causal relationship from inflation to domestic savings, suggesting that high and persistent inflation can erode the value of existing savings and discourage individuals from saving. Furthermore, the study found a distinct causal flow from savings to investment, without feedback in the opposite direction, highlighting the crucial role of a robust savings culture in providing the necessary foundation for sustained investment and economic growth. The ARDL approach provided further insights into the dynamic relationships between these variables. In the short run, lagged GDP and current and lagged savings positively influenced GDP, while the second lag of savings had a negative impact, supporting the Carroll-Weil hypothesis that savings typically follow, rather than precede, economic growth in the short run. The analysis also found a positive short-run and long-run relationship between investment and GDP, supporting the view that investment is an important factor of economic growth. The study recommends that the policy makers can leverage the synergies between savings, investment, and inflation management to foster sustained economic growth and development in line with the government development policies. Developing policies to attract savings and reduce the cost of savings, as well as promoting long-term savings over transactional savings, can increase the country's overall savings base.

In this article, the research team uses the VAR self-regression vector model to evaluate the impact of exchange rates on inflation and economic growth in Vietnam over the period 2005-2018. With six endogenous variables included in the VAR model: bilateral real exchange rate (Er), money supply (M2), exports (X), imports (IM), GDP at 2010 comparative prices (GDPR), the consumer price index (CPI) and the two exogenous variables, international price (Pw) and US Federal Reserve interest rate (Ifed), the research team examines the impact of exchange rates on endogenous variables in the model and considers the reaction of inflation and economic growth on various shocks. Based on the quantitative results, the research team will recommend some discus-sions to contribute for the improvement of Vietnam's macro environment, trade balance, inflation control, and economic growth support; implementing the goal of macroeconomic stability to suit the period of international economic integration and improving national competitiveness.

This paper analyses the causal relationship between Foreign Portfolio Investment (FPI), Equities Market Volatility, Exchange Rate and Inflation in Zimbabwe using a monthly time series data between October 2018 and November 2021. The granger causality model was used to present the link between the variables, and EGARCH was used to account for volatility and asymmetric effects on the variables. To incorporate innovations and responses into the Granger model, impulse response functions were used. Links between exchange rate and foreign portfolio investments were found. This only suggests that exchange rate volatility will vary when overseas investors purchase and sell financial securities on the Zimbabwe Stock Exchange (ZSE). In contrast, foreign investors sell local financial securities when local stock market returns are negative, leading to a significant outflow of foreign portfolio investment thereby reducing demand for currency. A significant causal relationship was found between the volatility of the exchange rate and stock market returns. It is assumed that stock market returns, and foreign portfolio investments are caused by fluctuating currency rates. The relationship between exchange rate and ZSE returns, and inflation was found based on Granger causality. This implies that stocks are not suitable for long-term investments that compensate investors for their diminished purchasing power. Policy makers should advise the Zimbabwe Stock Exchange to recommend a reduction in capital gains tax and withholding tax and this encourages investors to hold local equities for a long time.

Deteriorating inventory models are used as decision support tools for managers primarily, although not exclusively, in the retail trade. The mathematical modeling of deteriorating items allows managers to analyze their inventory management systems to identify areas that can be improved and to measure the corresponding potential benefits. This study develops an enhanced deteriorating inventory model for optimizing the inventory control strategy of companies operating in sectors with deteriorating products. In contrast with previous studies, our model holistically accounts for the overall financial effect of a company’s policies on product price discounting and on inventory shortages while considering the time value of money (TVM). We aim to find the optimal replenishment strategy and the optimal price reductions that maximize the discounted profit function of this analytical model over a fixed planning horizon. To this end, we use an economic order quantity model to study the effects of the TVM and inflation. The model accounts for pre- and post-deterioration discounts on the selling price for non-instantaneous deteriorating products with the demand rate being a function of time, price-discounts and stock-keeping units. Shortages are allowed and partially backordered, depending on the waiting time until the next replenishment. Additionally, we consider the effect of discounts on the selling price when items have either an instant deterioration or a fixed lifetime. We propose five implementable solutions for obtaining the optimal values, and examine their performance. We present some numerical examples to illustrate the applicability of the models, and carry out a sensitivity analysis. The study reveals that accounting for TVM and inventory shortages is complex and time-consuming; nevertheless, we find that accounting for TVM and shortages can be valuable in terms of increasing the yields of companies. Finally, we provide some important managerial implications to support decision-making processes.

The stock prices of mining companies are affected by several factors, such as world oil price, inflation, exchange rate, and Price to Earnings Ratio (PER), political affairs, basic metal prices, etc. The objective of this study is to analyze the effects of some factors influencing the stock prices of the mining companies including Price to Earnings Ratio (PER), world oil price, inflation, and exchange rate. Secondary data from Annual Reports of Indonesia Stock Exchange (IDX), Energy Information Administration (EIA), and Bank Indonesia are used as the sources of data analysis. 35 mining companies are selected as samples from four mining sub-sectors; namely coal, oil & gas, other metal & mineral, and rock. The results are analyzed by using panel data regression analysis model through applying EVIEWS 10. The results indicate that Price to Earnings Ratio (PER) and world oil price had positive and significant effects on stock price. Moreover, inflation has negative and significant effect on the stock price while exchange rate has no significant effect on stock price.

The study examines the relationship between money supply and inflation in Vietnam in the period of 2005-2021. The relationship between money supply and inflation is addressed in economic theories and models and has been studied by many experts in different economies in different periods. To examine the relationship between money supply and inflation in Vietnam in the period of 2005-2021, the research team collected data on money supply and inflation rate, then analyzed this relationship during three periods of 2005-2011, 2012-2019 and 2019-2021. Next, the research team collected data on money supply (MS - total means of payment) and consumer price index (CPI), quarterly data from the first quarter of 2005 to the fourth quarter of 2021 and uses Eviews 8 software for analyzing. The research team uses a linear regression model to evaluate the impact of money supply growth (GMS) on consumer price index (CPI), a variable representing the inflation rate, of Vietnam during the research period. The model results support the view that money supply growth and past inflation are among the factors affecting inflation in Vietnam. From the research results and the actual money supply, the money supply growth rate as well as the inflation rate in Vietnam during the research period, the research team makes some policy recommendations to achieve the targets of supporting economic recovery, controlling inflation, stabilizing the macro-economy in Vietnam after the Covid-19 pandemic.

The purpose of this study is to describe the Foreign Direct Investment (FDI) determinants of 6 countries, each of which is 3 countries from Southeast Asia and South Asia. Foreign Direct Investment (FDI) shows capital flows in 6 countries (Indonesia, Philippines, Malaysia, India, Pakistan and Bangladesh) that are affected by inflation, wage, Exchange Rate, Market Size and Trade Openness. The research method used is the regression of panel data for the period 2004-2019 from 6 countries in Southeast Asia obtained from the World Bank database. The results showed simultaneously and partially variable wage, exchange rate, market size and trade openness had a significant relationship with FDI inflows, except for variable inflation at α = 10%. Of the several variables studied, the dominant variable affecting the inflow of FDI in a country is the size of the market and followed by the wage level. In addition, of the 6 countries studied by countries that have great potential as recipients of FDI is Philippines.

This study aims to investigate the multi-item inventory model in a production/rework system with multiple production setups. Rework can be depicted as the transformation of production rejects, failed, or non-conforming items into re-usable products of the same or lower quality during or after inspection. Rework is very valuable and profitable, especially if materials are limited in availability and also pricey. Moreover, rework can be a good contribution to a ‘green image environment’. In this paper, we establish a multi-item inventory model to determine the optimal inventory replenishment policy for the economic production quantity (EPQ) model for imperfect, deteriorating items with multiple productions and rework under inflation and learning environment. In inventory modelling, Inflation plays a very important role. In one cycle, production system produces items in n production setups and one rework setup, i.e. system follows (n, 1) policy. To reduce the deterioration of products preservation technology investment is also considered in this model. Holding cost is taken as time dependent. We develop expressions for the average profit per time unit, including procurement of input materials, costs for production, rework, deterioration cost and storage of serviceable and reworkable lots. Using those expressions, the proposed model is demonstrated numerically and the sensitivity analysis is also performed to study the behaviour of the model.

The present study investigates an inventory model for non-instantaneous deteriorating items under inflationary conditions with partially backlogged shortages. In today’s market structure consumers are looking for goods for which there is a delay in deterioration. At the same time, the consumers’ willingness to wait has been decreased over time, which leads to lost sales. Moreover in financial decision-making, the effects of inflation and time value of money cannot be oblivious to an inventory system. In this scenario, managing inventory of goods remains a challenging task for the decision makers, who may also have to rent warehouse under different prevailing factors such as, bulk discount, limited space in the retail outlet, or increasing inflation rates. With a focus on reduction of costs and increasing customer service, warehouse decision models are crucial for an organization’s profitability. Hence a mathematical model has been developed in the view of above scenario, in order to determine the optimal policy for the decision maker, by minimizing the present worth of total cost. The optimization procedure has been illustrated by a numerical example and detailed sensitivity analysis of the optimal solution has been performed to showcase the effect of various parameters. Managerial implications has also been presented to aid the decision making process.