Price Inflation Research Articles

Analysis of grain and rice prices in the rice milling supply chain in pengadang village central lombok regency

The threat of rice price inflation is increasingly having an impact on Indonesian society, especially the poor, both rural and especially urban. Several expert reviews state that the problem of rice prices continuing to rise is due to increasing rice consumption due to population growth which is not in line with the increase in rice production capacity which continues to decline, one of which is due to the conversion of agricultural land. Rice production in Central Lombok in 2020 reached 314 327.90 GKG or the equivalent of 21.6% of NTB province's rice production. Consumption: Rice consumption for the population of Central Lombok district with a population of 947,488 people multiplied by the rice requirement of 140 kg/person/year is 132,548 tons of rice per year from rice production of 178 103 tons or a surplus of 45,555 tons. However, the rice surplus condition was unable to withstand rice price inflation in early 2024, until it reached IDR 18,000 per kg. Pengadang Village, Central Praya District, Central Lombok Regency is one of the villages with the largest number of rice mills on the island of Lombok, with 10 units and has been a supplier of Bulog rice and some of it is traded to the islands of Bali and Java. This research aims to determine the difference in prices of grain and rice in the rice milling supply chain in Pengadang Village, Praya Tengah District, Central Lombok Regency. The research method uses percentage analysis of price differences and the factors that influence it. The research results show that the lowest supply chain profit is at the price of GKP grain in Merchant at 0.26% or Rp. 20/Kg GKP, and the highest profit in the GKG grain supply chain at the mill is IDR 495/Kg or the equivalent of 6.27%. The rice price profit in the rice milling supply chain is IDR. 30/Kg or equivalent to 0.30%, but there are other benefits from by-products in the form of fine bran and coarse bran amounting to Rp. 1,219/Kg GKG or the equivalent of 12.19%. The yield of GKP grain into GKG is at an average of 84.0% and the yield of GKG to rice is at an average of 64.02%, so that a rice price of IDR can be achieved. 16,000/Kg in the milling unit.

Auditing the prescription drug consumer price index in a changing marketplace.

Changes in the dynamics of prescription drug markets have raised issues regarding whether the United States Bureau of Labor Statistics' (BLS') Prescription Drug Consumer Price Index (CPI-Rx) has adequately kept up with the evolving marketplace. The CPI-Rx limits its sampling frame to retail outpatient outlets and excludes prescription pharmaceuticals dispensed in non-retail settings such as hospitals, physician/clinic outpatient facilities, and nursing homes. Thus, the CPI-Rx overlooks the increasingly important specialty pharmaceuticals dispensed in non-retail settings, whose transactions are instead captured in the overall hospital and professional services component of the medical care CPI. Specialty drugs now account for about 55% of all U.S. drug spending, double the share of a decade earlier. To the extent specialty drug price growth differs from that of traditional pharmaceuticals, the CPI-Rx could provide an inaccurate measure of overall drug price inflation. We calculate a chained Laspeyres CPI using data from the Merative™ MarketScan® Databases for the years 2010-2019 and IQVIA-designated specialty drugs and offer evidence showing that by not sampling specialty drugs in non-retail settings, the CPI-Rx has understated overall U.S. prescription drug inflation by just under 75 basis points annually. We discuss implications for health care policy and suggest the BLS examine the feasibility of publishing an overall pharmaceutical price index incorporating both traditional and specialty pharmaceuticals dispensed in retail and non-retail settings.

External financial and monetary policy shocks: Do they matter for Korean macroeconomy?

Given Korea's status as a small, open economy, it exhibits a pronounced sensitivity to external shocks. Consequently, this article seeks to elucidate the impact of external financial and monetary policy shocks on the fluctuation of critical macroeconomic variables within Korea. Employing Bayesian estimation alongside the impulse response function for empirical analysis, the findings reveal that external financial and monetary policy shocks precipitate declines in exports, output, employment, real wages, consumption, investment, and imports. Conversely, these shocks are associated with increases in both the price level and inflation, highlighting the multifaceted effects of external pressures on the domestic economic landscape. Further, through forecast error variance decomposition, this study demonstrates that, relative to shocks stemming from productivity, terms of trade, and real exchange rate variations, external financial and monetary policy shocks exert a considerably milder impact on the fluctuations of Korea's key macroeconomic variables. This insight suggests a potential area for enhancement in the existing Korean literature on this topic, advocating for the integration of these findings to enrich understanding and analysis. In summary, by delving into the nuanced effects of external shocks on Korea's economy, this article contributes valuable perspectives to the discourse, suggesting avenues for further research and policy formulation. The integration of these results into the broader body of Korean economic literature could significantly augment current understandings and interpretations of Korea's economic dynamics in the face of global financial and monetary turbulence.

Food habits and food inflation in the US and India; An experience in Covid-19 pandemic

The US and India are different in various socioeconomic aspects. Still the inflation are rates between them showed moderately correlated in respected in respect of food prices 2022. Both countries adopted necessary measures to supply food and beverages in the lockdown and related bottlenecks in order to check the rapidly rising commodity prices. But still the food prices increased continuously almost in the whole year,2022. Food and fuel have been said the drivers of inflation during the Covid-19 pandemic period (Philip Barrett Sep,12,2022). The world itself was partially a closed economy as foreign trade dwindled to a large extent. So countries had to depend mostly on indigenous production and market supply network. But as the food and beverage demand, it is dependent on economic factors like testes, habits and preference of the households. These factors played important role in the head line inflation in different countries during Covit-19 pandemic. The present study is an attempt to highlight the complex factors such as food habits ,tastes and preferences in the US and India. This shows how the said factors impacted upon the food inflation in them.

Exploring food system resilience to the global polycrisis in six Asian countries.

The world is currently in the midst of a global food crisis brought about and exacerbated by a series of mutually reinforcing shocks to food systems This study investigated the resilience of food systems in six Asian countries (Bangladesh, Kyrgyz Republic, Lao PDR, Pakistan, Philippines, and Sri Lanka) amidst the global 'polycrisis' caused by COVID-19, geopolitical conflicts, and climate change. Trend analyses were performed for 19 indicators sourced from global databases and World Food Programme national data, representing the four domains of food system resilience: exposure to shocks; resilience capacities and agro- and food diversity, resilience responses and strategies; and long-term resilience outcomes. The analysis revealed that all six countries experienced the effects of the 'polycrisis', leading to diverse impacts on exchange rates, with Sri Lanka, Pakistan, and Lao PDR facing significant currency depreciation. While most countries increased crop production and decreased food imports during the crisis, government economic support during the pandemic varied widely. Resilience outcomes, including national food price inflation and the proportion of populations facing food insecurity, witnessed upward variations. Overall, countries with higher resilience capacities at the start of the 'polycrisis' showed less severe long-term resilience outcomes. Our findings highlight the varied challenges and resilience capacities across each country, influenced by a complex interplay of economic, political, agricultural, and food affordability factors crucial for determining long-term resilience in their food systems. Recommendations for future research include focusing on resilience assessment in food systems, integrating climate change adaptation measures, and developing early intervention strategies.

Predict the Inflation of Food Prices based on the Linear Regression Models

Using the large "Global Food Price Inflation" dataset from Kaggle, this paper provides a thorough analysis of food price inflation in Cameroon. In the framework of Cameroon's dynamic economy, the research focuses on comprehending the complex financial indicators and their relationship to trends in food prices between 2015 and 2017. The study addresses the crucial role that agriculture plays in Cameroon's economy by using both polynomial and linear regression models to analyze and forecast food inflation rates. Because of its simple methodology, the linear regression model works better for making short-term predictions because it can capture the main inflation rate trend without getting bogged down in the details of capturing small variations in the data. Conversely, polynomial regression tends to overfit in this situation even though it is skilled at simulating non-linear relationships. The study's conclusions emphasize how crucial it is to select the right model for economic forecasting and stress the value of clarity and simplicity in identifying key economic trends, particularly in short-term scenarios. This research adds significant knowledge to the field of economic analysis and forecasting methodology; it is especially pertinent to policymakers, economists, and researchers who specialize in developing economies.

Unraveling the Nexus: Oil Price Dynamics and Inflation in Madagascar

Unraveling the Nexus: Oil Price Dynamics and Inflation in Madagascar

Evolution of food price inflation in the European Union 27 member states

ABSTRACT The objective of the research is to investigate the evolution of food price inflation in the 27 Member States between January 2001 and May 2022. Our paper focuses on the role of global oil prices, exchange rate volatility, and the impact of the Russian-Ukrainian war, which started in February 2022 and their effects on food prices. We compiled a panel data set that includes monthly values. Based on the a priori test results, Granger causality test, panel ADRL model, along with Random Effects (RE), linear regression with panel-corrected standard errors (PCSE), cointegration regression using panel fully modified ordinary least squares (FMOLS) regression methods and panel event study estimation were applied. Our result shows that both the increasing Brent oil prices and the fluctuating exchange rates significantly stimulated food price inflation in the EU-27. Data demonstrates that Russia’s war against Ukraine also contributed to increasing food prices in the EU-27. In this regard, we also provide a country-level analysis. Our results contribute to theoretical analyses, as well as the implication for policymakers, and food service companies.

Research Leadership and High Standards in Economic Forecasting: Neural Network Models Compared with Etalon ARIMA Models

Maintaining high standards in socio-economic research and achieving leadership positions in scientific circles requires a scientist to have a perfect command of mathematical tools developing accurate forecasts. Traditional forecasting methods typically involve fitting data to a pre-established relationship between dependent and independent variables, often making specific assumptions about a stochastic process. In contrast, machine learning presents an alternative approach to statistical analysis and forecasting, emphasising a data-driven methodology that does not assume any predefined statistical relationships in the data. The ARIMA method is recognised as the most effective forecasting method in the social sciences and is widely used for analyzing time series data. At the same time, deep learning methods (neural network models) are now forming a serious alternative to traditional econometric models, including ARIMA, as they can exploit nonlinear patterns in the data, which are often hidden from standard linear models. The aim of this study is to evaluate the performance of different neural network (NN) models compared to ARIMA models for economic forecasting. Five different network architectures are studied: Multilayer Perceptron (MLP), Simple Recurrent Neural Network (Simple RNN), Long Short-Term Memory Network (LSTM), Bidirectional LSTM (BILSTM), Convolutional Neural Networks (CNN). The performance of these models is compared with two benchmark ARIMA models: ARIMA based on AIC criteria (ARIMA-AIC) and ARIMA based on BIC criteria (ARIMA-BIC). The performance of these models is compared with two benchmark ARIMA models: ARIMA based on AIC criteria (ARIMA-AIC) and ARIMA based on BIC criteria (ARIMA-BIC). Prior training the NN models, hyperparameters were fine-tuned to obtain optimal performance for each model. The models’ performance on out-of-sample forecasting (test dataset) was evaluated using two metrics: RMSE (root mean square error) and MAE (mean absolute error). The data used to test the effectiveness of these models were monthly year-on-year consumer price inflation data in Algeria. The results show that the MLP model outperformed other models, including the benchmark, in the short and medium term (6-12 months). At the outperformed same time, the LSTM model outperformed all other models, including the benchmarks, in the long term (18-24 month forecasting horizon). Although Simple RNN models performed well in short-term forecasting, their performance deteriorated with the increase in the forecasting horizon. For the benchmark models, the forecasting results were the worst among all models, even in the short term. As a result, MLP and LSTM models were found to be the most appropriate for forecasting Algerian inflation, and deep learning is a promising alternative to traditional time series forecasting methods.

Climate change impacts on agricultural trade and food security in emerging economies: case of Southern Africa

Climate change has been a significant threat to sustainable agriculture impacting trade and food security. This research investigates the impacts of climate change on agricultural trade and food security in emerging economies focusing on Southern Africa. The research employed the dynamic panel Generalised Method of Moments (GMM) using panel data for the period 2012 to 2021 obtained from a sample of 12 Southern African countries selected based on data availability. The main independent variables to the research were climate change variables (temperature and precipitation). Other control variables included were population growth, food inflation and agricultural growth. The study found significant negative effects of climate change on agriculture trade. Whilst temperature changes were found to have insignificant effects, precipitation changes were found to have significant positive effects. The research recommends concerted efforts towards climate change adaptation and mitigation for sustainable agriculture. Based on the Findings, sustainable food security and agricultural trade Southern African emerging economies may be attained through effective climate change mitigation and adaptation approaches particularly promoting climate-smart agriculture (CSA).

Fuel Subsidy Payments and Food Inflation in Nigeria

Fuel Subsidy Payments and Food Inflation in Nigeria

Managing Food Inflation in India

Managing Food Inflation in India

FOOD IMPORT, FOOD PRICE INFLATION, WAGES AND AGRICULTURAL EMPLOYMENT IN SOUTH AFRICA

Agricultural industry plays a significant role in the South African economy, specifically in creating jobs. However, this sector is facing significant challenges owing to economic and social unrest. Within the application of both Autoregressive Distributed Lag (ARDL) and Error Correction Model (ECM) on time series data from 2010q1 to 2021q4; this paper assessed the effects of food imports, inflation, and real wage on agricultural employment in South Africa. The results from bounds testing indicated that food imports, inflation and real wage stimulate longterm disruptions in agricultural employment. However, short-run results indicated that agricultural employment is only affected by the real wage. Based on these findings, this study suggests a policy that incorporation of both inflation rate and real wages policy to improve employment in the agricultural industry. Additionally, easing the import of food products that are complements to domestic agricultural products should be another strategy to increase the number of people employed in the agricultural industry.

Food supply in the context of destabilization of the global economy

The goal is to analyze the state of food supply for the country's population in the context of destabilization of the world economy, inflation of prices for goods, primarily food, which in recent years have had a steady growth pattern. Methods – comparative analysis, economicstatistical, cause-and-effect. Results - the main signs of instability in economic situation in the world, their characteristics, main causes and consequences are revealed. The average annual growth rate of agricultural production for 2000-2020, 2020-2022 is shown and their impact on per capita supply of basic products and consumption rates. Comparison of these indicators allows to identify actual level of food support in Kazakhstan for specific years. The authors note that in the last two decades, physiological dietary and calorie standards for certain food products have not yet been achieved. Food security is also determined by the share of imports in consumer demand. Conclusions - it is recommended in the near and medium term to take effective measures to increase main types of products to volumes that will allow to move to import substitution and per capita consumption to the standards of physiological needs. Measures of state support to create favorable economic and organizational conditions for doing business in agricultural sector of the republic are proposed. Resolving food issue is recognized as the highest priority of government policy. The results of the study have practical significance for the organization and management of food supply system. It is important to promote the use of innovative technologies for production, processing, storage and rational use of food; formation of effective system for distribution of raw materials and agricultural products from producers to the final consumer; development of transport and warehouse infrastructure for wholesale trade.

The Effect of Global Monetary Policy Changes on the Financial Strategy of International Companies

In the interconnected global economy, the financial strategies of international corporations play a crucial role in navigating the dynamic landscape shaped by various factors, including monetary policies set by central banks worldwide. This narrative explores the intricate interplay between global monetary policy changes and the financial strategies of multinational corporations, investigating how shifts in these policies reverberate across borders, impacting corporate decision-making, risk management, and performance. Over recent decades, significant transformations in monetary policy frameworks have occurred, driven by evolving economic paradigms, financial crises, and geopolitical dynamics. Central banks have deployed a range of tools, from conventional inflation targeting to unconventional measures like quantitative easing, to stabilize economies and stimulate growth. However, the effectiveness and unintended consequences of these policies transcend domestic boundaries, permeating the international financial system and shaping the strategic imperatives of multinational corporations. The impact of global monetary policy changes on international companies' financial strategies is substantial. U.S. monetary policy shocks notably affect foreign firms, especially those with extensive global production linkages and financial constraints. Financial globalization has made domestic financial conditions more vulnerable to external shocks, reinforcing the case for price stability as an optimal monetary rule. The volatility of foreign currency exchange rates significantly affects international budgeting, while multinationals with foreign involvement exhibit lower leverage ratios and rely more on short-term borrowing. One primary channel through which global monetary policy changes influence international companies is by altering financing costs and access to capital. Changes in interest rates and liquidity conditions affect borrowing costs for firms operating across borders, impacting investment decisions, capital allocation, and capital structure optimization. Additionally, these changes induce currency fluctuations and volatility, necessitating robust currency risk management strategies to safeguard revenues and mitigate exchange rate exposure. Furthermore, global monetary policy changes affect asset prices, financial markets, and investor sentiment, shaping the risk-return dynamics faced by international companies. Expansive monetary policies often fuel asset price inflation and influence investment strategies, while abrupt policy shifts can trigger market dislocations and liquidity constraints. Beyond financial markets, monetary policy changes influence macroeconomic variables, such as economic growth, inflation, and trade patterns, shaping international companies' operating environments and strategic decisions. In conclusion, the interconnectedness of global financial markets accentuates the importance of agility, flexibility, and strategic foresight for multinational corporations in navigating the impact of monetary policy changes on their financial strategies and overall performance.

Impact of Penang South Reclamation Project on Fisherman Socio-economic Case Study: Southwest Penang

The Penang South Reclamation, proposed in 2015, aims to fund the Penang Transport Master Plan, which aims to improve public transport and access roads; however, it remains in the approval stage. Penang 2030 aims to improve traffic and public transport through the Penang Transport Master Plan but faces challenges like noise and air pollution. Aquaculture Industrial Zones and artificial reefs support housing. The study aims to evaluate the Penang South Reclamation project's impact on fishermen, particularly those in Southwest Penang, by assessing income, quality of living, and family education and well-being, focusing on house ownership. The survey reveals that most fishermen in the study area are sole income earners, with household incomes under RM2,500, making them vulnerable to economic changes and food inflation. Fishermen heavily depend on fishing for family survival, with 90% staying within a 5-kilometer radius from their source of income. Despite good infrastructure, they live in densely populated areas. The Social Impact Assessment report reveals that fishermen are the least educated, highlighting the need for improved education opportunities for future generations. They agree on adequate education but struggle with extra tuition fees and tertiary education.

Global warming and heat extremes to enhance inflationary pressures

Climate impacts on economic productivity indicate that climate change may threaten price stability. Here we apply fixed-effects regressions to over 27,000 observations of monthly consumer price indices worldwide to quantify the impacts of climate conditions on inflation. Higher temperatures increase food and headline inflation persistently over 12 months in both higher- and lower-income countries. Effects vary across seasons and regions depending on climatic norms, with further impacts from daily temperature variability and extreme precipitation. Evaluating these results under temperature increases projected for 2035 implies upwards pressures on food and headline inflation of 0.92-3.23 and 0.32-1.18 percentage-points per-year respectively on average globally (uncertainty range across emission scenarios, climate models and empirical specifications). Pressures are largest at low latitudes and show strong seasonality at high latitudes, peaking in summer. Finally, the 2022 extreme summer heat increased food inflation in Europe by 0.43-0.93 percentage-points which warming projected for 2035 would amplify by 30-50%.

Do ESG fund managers pump and dump the stocks in their portfolios? European evidence

We investigate portfolio pumping around quarter-ends by ESG equity mutual funds domiciled in the largest European markets in sustainable investments, i.e., the UK, France and Germany, for the period from January 2010 to December 2022. We find strong evidence that the UK funds inflate quarter-end returns, with price spikes being stronger at year-ends; nevertheless, the magnitude of price inflation is less than that of their conventional counterparts. On the contrary, results indicate that German and French funds do not engage in portfolio pumping. The COVID-19 pandemic strengthened the propensity of fund managers to cause a profound artificial enhancement to the performance of the investment portfolio. Further analysis shows that portfolio pumping is more prominent among the worst-performing funds, funds that charge investors with lower fees and achieve a poor ESG rating. However, managers that pump fund returns do not attract significantly more flows. Our results have produced valuable insights for regulators and investors participating in ESG markets, highlighting the necessity for a rigorous surveillance of the UK ESG equity market.

Energy Price Inflation, Geopolitical Risk, and Bitcoin Dependence Structure: Evidence from BRICS

ABSTRACT This study examines the co-movement between geopolitical risk (GPR), energy price, and bitcoin (BTC) in BRICS countries, namely Brazil, Russia, India, China, and South Africa. Previous studies have focused on the impact of GPR on the volatility and risk premium of BTC investment. However, very limited studies have focused on integrating BTC as an extension of the mix of GPR on the co-movement with energy price. The analysis is based on monthly data of GPR index for BRICS countries, brent oil futures, natural gas futures and BTCs covering the period between March 2012 and Jun 2021. We employ the Bayesian graphical structural vector autoregressive model and time-varying parameter vector autoregressions-based dynamic connectedness to investigate the network-dependence structure. This research project provides useful empirical evidence for assessing the impact of both BTC and GPR on energy prices. Nonetheless, it will also be informative about the likelihood of co-movements occurring at different stages.

Contradictory Results: Reassessing the Impact of Loan‐to‐Value Restrictions on House Price Inflation

AbstractUsing Bayesian Structural Time Series analysis, this study examines the causal impact of loan‐to‐value (LTV) restrictions imposed by the Reserve Bank of New Zealand in October 2013. By incorporating state‐space components, such as local linear trend, seasonality and regression, counterfactual values of house price indices are predicted. Surprisingly, the study reveals that the implementation of LTV restrictions had no significant effect on national house price indices, contradicting prior Central Bank studies that reported a nearly 3 percentage‐point decrease in housing cost inflation. This contradictory evidence challenges existing perceptions of the effectiveness of LTV restrictions in curbing house price inflation.