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GDP growth, money growth and inflation are essential to an economy's macroeconomic stability and have a direct impact on the policymaking process. Sri Lanka is currently concerned about high inflation. Inflation is a monetary phenomenon. Inflation has been caused by monetary policy in several nations. According to the economic theories of Karl Marx, Irving Fisher and Milton Friedman, a continuous increase in the money supply causes inflation. This paper aims to investigate the relationship between Sri Lanka's GDP growth, money growth and inflation.

An econometric model and the economic theories of Fisher and Friedman are used to figure out how money supply, inflation and economic growth are linked. Between 1990 and 2021, data were gathered from secondary sources.

The increase in the money supply is found to cause inflation. Inflation has negative effects on both short- and long-term economic growth. Long-term, the increase in money supply has a negative effect on economic growth.

According to research, the money supply and inflation are inextricably linked, and the money supply has a direct impact on economic growth. As a result, the government should have an appropriate monetary policy and proposals to control inflation levels and stimulate economic growth.

The paper adds to the existing literature in two ways. First, it fills in the lack of studies in Sri Lanka, where there are no papers on this important relationship, especially with a modern econometric study. Second, it tries to shed light on the asymmetric shocks (both positive and negative shocks and changes) between the three variables, which was not done in previous studies.

This paper aims to deepen the understanding of the relationship between global economic uncertainty and price volatility, specifically focusing on commodity, industrial materials and energy price indices as proxies for global inflation, analyzing data from 1997 to 2020.

The dynamic conditional correlation generalized autoregressive conditional heteroscedasticity model is used to study the dynamic relationship between variables over a while.

The results demonstrated a positive relationship between commodity prices and the global economic policy uncertainty (GEPU). Except for 1999–2000 and 2006–2008, the results of the energy price index model were very similar to those of the commodity price index. A predominant positive relationship is observed focusing on the connection between GEPU and the industrial material price index. The results of the pairwise Granger causality reveal a unidirectional relationship between the GEPU – the Global Commodity Price Index – and the GEPU – the Global Industrial Material Price Index. However, there is bidirectional causality between the GEPU – the Global Energy Price Index. In sum, changes in price indices can be driven by GEPU as a political factor indicating unfavorable economic conditions.

This paper provides a deeper understanding of the role of global uncertainty in the global inflation process. It fills the gap in the literature by empirically investigating the dynamic movements of global uncertainty and the three most important groups of prices.

The purpose of this study paper is to focus on developing novel ways to monitor an economy in real time during the COVID-19 pandemic. A fully automated framework is proposed for collecting and analyzing online food prices in Poland. This is important, as the COVID-19 outbreak in Europe in 2020 has led many governments to impose lockdowns that have prevented manual price data collection from food outlets. The study primarily addresses whether food price inflation can be accurately measured during the pandemic using only a laptop and Internet connection, without needing to rely on official statistics.

The big data approach was adopted to track food price inflation in Poland. Using the web-scraping technique, daily price information about individual food and non-alcoholic beverage products sold in online stores was gathered.

Based on raw online data, reliable estimates of monthly and annual food inflation were provided about 30 days before final official indexes were published.

This is the first paper to focus on measuring inflation in real time during the COVID-19 pandemic. Monthly and annual food price inflation are estimated in real time and updated daily, thereby improving previous forecasting solutions with weekly or monthly indicators. Using daily frequency price data deepens understanding of price developments and enables more timely detection of inflation trends, both of which are useful for policymakers and market participants. This study also provides a review of crucial issues regarding inflation that emerged during the COVID-19 pandemic.

Growth enterprise market (GEM) in Hong Kong is acknowledged as one of the world’s most successful examples of small and medium enterprise (SME) stock market. The purpose of this paper is to examine the evolving efficiency and dual long memory in the GEM. This paper also explores the joint impacts of thin trading, structural breaks and inflation on the dual long memory.

State-space GARCH-M model, Kalman filter estimation, factor-adjustment techniques and fractionally integrated models: ARFIMA–FIGARCH, ARFIMA–FIAPARCH and ARFIMA–HYGARCH are adopted for the empirical analysis.

The results indicate that the GEM is still weak-form inefficient but shows a tendency towards efficiency over time except during the global financial crisis. There also exists a stationary long-memory property in the market return and volatility; however, these long-memory properties weaken in magnitude and/or statistical significance when the joint impacts of the three aforementioned factors were taken into account.

A forecasts of the hedging model that capture dual long memory could provide investors further insights into risk management of investments in the GEM.

The findings of this study are relevant to market authorities in improving the GEM market efficiency and investors in modelling hedging strategies for the GEM.

This study is the first to investigate the evolving efficiency and dual long memory in an SME stock market, and the joint impacts of thin trading, structural breaks and inflation on the dual long memory.

The purpose is to market a reinterpretation of Brazilian economic history highlighting the importance of non-tradable goods to understand major historical developments such as the lack of industrialization in the mining boom; the rise and contribution of industries to development in the early 20th century; indexation as hyperinflation in the late 20th century; growth and cycles in the early 21st century.

Section 2 introduces analytical perspectives on the relationship between non-tradables, transport costs and external shocks. Section 3 presents a historical overview of the gold and coffee cycles in the Brazilian economy, which highlights the crucial role played by transport costs in the genesis of industrialization. Thus, in a more precise way, industrialization was not an import substitution process but the substitution of non-tradables by the domestic tradable manufactures.

Section 4 shows that Brazilian statistical records and historiography disregard this characterization and, to that extent, underestimate economic growth in the primary export phase (1872–1920) and overestimate growth rates in the industrialization period (1920–1940). Section 5 shifts to the end of the 20th century to analyze the relationship between non-tradables, indexation and hyperinflation. Section 6 concludes with a brief discussion of the role played by the terms of trade and non-tradables in the unfolding of the 2014 economic crisis.

Distance from international markets and a continental geographic size made transport costs in Brazil historically prohibitive: the relevance of non-tradables in the Brazilian economic history. While the theme is not new, it seldom received proper attention in the historiography.

Using cross-sectional household survey data, this paper aims to determine the impact of food price increases on poverty in Indonesia.

This paper uses the quadratic almost ideal demand system applied to the 2013 Indonesian household survey data. The impact of food price increase on household welfare is calculated using a welfare measure, compensating variation.

Three food groups with the most outstanding price impact on poverty, rice, vegetables and fish, were studied. The 20% increase in the price of each food group causes an increase in the headcount ratio by 1.360 points (rice), 0.737 points (vegetables) and 0.636 points (fish). Maintaining food price stability for these food groups is very important because the more the price increases, the more the impact on poverty. Food price policies in rural areas are also more critical than in urban areas because the impact of food price increases in rural areas is higher.

This paper does not consider the positive impact of rising food prices on food-producing households.

Implementing appropriate poverty alleviation policies through food policies for main food groups and social protection.

Promoting rural development policies and agricultural growth.

This paper contributes to the existing literature by providing empirical results regarding the impact of domestic food prices increase on poverty in Indonesia.

The purpose of this study is to describe the design and validation of a three-dimensional (3D)-printed phantom of a uterus to support the development of uterine balloon tamponade devices conceived to stop post-partum haemorrhages (PPHs).

The phantom 3D model is generated by analysing the main requirements for validating uterine balloon tamponade devices. A modular approach is implemented to guarantee that the phantom allows testing these devices under multiple working conditions. Once finalised the design, the phantom effectiveness is validated experimentally.

The modular phantom allows performing the required measurements for testing the performance of devices designed to stop PPH.

PPH is the leading obstetric cause of maternal death worldwide, mainly in low- and middle-income countries. The proposed phantom could speed up and optimise the design and validation of devices for PPH treatment, reducing the maternal mortality ratio.

To the best of the authors’ knowledge, the 3D-printed phantom represents the first example of a modular, flexible and transparent uterus model. It can be used to validate and perform usability tests of medical devices.

The purpose of this study is to investigate the pivotal role of environmental innovations in driving sustainability practices within medium and large manufacturing firms operating in Uganda.

Using a cross-sectional and quantitative methodology, data were collected through a questionnaire survey involving 208 manufacturing companies. The smart partial least squares path modelling technique was used for the analysis.

The analysis unveils significant and positive associations. Specifically, product innovation exhibits a robust and affirmative relationship with sustainability practices. Similarly, the correlation between process innovation and sustainability practices emerges as statistically significant. Moreover, the findings underscore the noteworthy and constructive predictive influence of environmental innovation on sustainability practices.

These empirical results present substantial implications for theoretical frameworks and practical applications. From a policy perspective, the findings emphasise the importance of incentivising eco product and eco process innovations as potential drivers of eco-friendly practices. On the managerial front, strategic resource allocation and the adoption of integrated environmental innovation strategies are advocated, with the ultimate goal of enhancing sustainable business approaches within Uganda’s manufacturing subsector.

To the best of the authors' knowledge, this study represents the inaugural attempt to investigate the role of environmental innovations in elucidating sustainability practices within a least developed country. Notably, while all dimensions demonstrate significance, it is noteworthy that product innovation emerges as the more substantial contributor to the promotion of sustainability practices.

This study aims to investigate, for the first time in the literature, the stochastic properties of the US aggregate health-care price inflation rate series, using the data on health-care inflation rates for a panel of 17 major US urban areas for the period 1966-2006.

This goal is undertaken by applying the first- and second-generation panel unit root tests and the panel stationary test developed recently by Carrion-i-Silvestre et al. (2005) that allows for endogenously determined multiple structural breaks and is flexible enough to control for the presence of cross-sectional dependence.

The empirical findings indicate that after controlling for the presence of cross-sectional dependence, finite sample bias, and asymptotic normality, the US aggregate health-care price inflation rate series can be characterized as a non-stationary process and not as a regime-wise stationary innovation process.

The research findings apply to understanding of health-care sector price escalation in US urban areas. These findings have timely implications for the understanding of the data structure and, therefore, constructs of economic models of urban health-care price inflation rates. The results confirming the presence of a unit root indicating a high degree of inflationary persistence in the health sector suggests need for further studies on health-care inflation rate persistence using the alternative measures of persistence. This study’s conclusions do not apply to non-urban areas.

The mean and variance of US urban health-care inflation rate are not constant. Therefore, insurers and policy rate setters need good understanding of the interplay of the various factors driving the explosive health-care insurance rates over the large US metropolitan landscape. The study findings have implications for health-care insurance premium rate setting, health-care inflation econometric modeling and forecasting.

Payers (private and public employers) of health-care insurance rates in US urban areas should evaluate the value of benefits received in relation to the skyrocketing rise of health-care insurance premiums.

This is the first empirical research focusing on the shape of urban health-care inflation rates in the USA.

This study seeks to examine the extent to which strands of inflationary related conditions (inflation expectations, inflation uncertainty and realized inflation); macroeconomic uncertainty and the likelihood of recessionary conditions influence performance indicators in the US banking sector over a specified time period.

The study adopts seemingly unrelated regression model (SUR) advanced by Zellner (1962) in its examination of how specific strands of inflationary conditions, and other adverse macroeconomic conditions influence performance dynamics in the US banking sector.

Empirical evidence suggest that among various adverse macroeconomic conditions examined, inflation expectations and macroeconomic uncertainty tend to have significant constraining impact on key performance indicators in the US banking sector than other conditions examined. Comparatively, this study finds that inflation expectations and macroeconomic uncertainty tend to have much more constraining impact on return on equity, than on return on assets in the US banking sector. Results further suggest that among the three bank performance indicators examined, net interest margin is the least vulnerable bank performance indicator to various adverse macroeconomic conditions examined in the study.

Apart from the various empirical results noted above, this study's findings are projected to help inform strategic planning decisions among institutions in the banking sector. The various findings could, for instance, inform policies and operational strategies geared toward reducing vulnerability associated with specific performance indicators such as return on equity. This reduction could be achieved by critically examining how the various performance indicators react to individual adverse macroeconomic conditions examined in this study. The process could ultimately help in developing tailored measures/procedures aimed at reducing how susceptible key performance indicators are to the various adverse macroeconomic conditions. This study's findings could also provide the platform for more adaptive policies aimed at minimizing the effects of noted macroeconomic conditions on operational efficiency in the banking sector.

The uniqueness of this study, compared to related ones found in the literature, stems from its treatment of three variant of related strands of macroeconomic condition (different variant of inflationary conditions) in the same framework in its empirical analysis.

本研究旨在探討與通貨膨脹有關的狀況的組成部分(通脹預期 、通脹不確定性及體現了的通脹), 宏觀經濟不確定性及經濟衰退狀況的可能性、在一段特定時間內對美國銀行業的表現指數有何種程度的影響。

研究採用塞爾納 (Zellner) (1962) 提出的看似無關迴歸模型 (SUR)，去探討通脹狀況的特定組成部分及其它不利的宏觀經濟狀況如何影響美國銀行業內的績效動態。

實證證據暗示在被研究的各個不利宏觀經濟狀況中，通脹預期及宏觀經濟不確定性，對美國銀行業內的主要業績指標的約束影響, 與其它被探討的狀況相比，往往會較重大。相對地、本研究結果顯示通脹預期及宏觀經濟不確定性，對美國銀行業資本回報率的約束影響、往往遠多於資產收益率。研究結果進一步顯示，在被探討的三個銀行業績指標中，就本研究所探討的各個不利的宏觀經濟狀況而言，淨息差是脆弱性最小的銀行業績指標。

除了上述各實證結果外，本研究結果預期會給銀行業內機構間作戰略規劃的決定時提供資料，譬如，各項研究結果或可在制定旨在減少與特定業績指標如資本回報率相聯繫的脆弱性的政策和經營策略時提供資料。這脆弱性的減少，是透過嚴謹地研究各個業績指標，如何對在本研究中被探討的個別不利宏觀經濟狀況作出反應而達致的。這程序或許最終會幫助建立一個以減少各個不利宏觀經濟狀況對主要業績指標的影響為目的的量身定制措施／程序。本研究的結果，或許亦可為更多旨在減弱眾所周知的宏觀經濟狀況對銀行業運營效率的影響的適應性政策提供平台。

與文獻中可見的相關研究比較，本研究的獨特性源於其實證分析，是涉及在同一個構架內處理宏觀經濟狀況相互有關的組成部分的三個變體 (通脹狀況的不同變體) 。