Explore the vast range of titles available.

Purpose: This study aimed to analyze the effect of Inflation on food prices in Palopo City, where the inflation rate is calculated based on index numbers collected from several commodities traded at each price level in the market, namely the Consumer Price Index (CPI).   Theoretical framework: The Vector Autoregressive (VAR) method is simultaneous equation modeling that has several endogenous variables simultaneously, but each endogenous variable is explained by lags of its own value and other endogenous variables in the model. Forecasting using the VAR method is in some cases better than complex simultaneous equations.   Design/methodology/approach:  The stationarity test in this study uses the Augmented Dickey-Fuller (ADF) method, followed by determining lag optimal Akaike Information Criteria (AIC) and Schwarz information Criterion (SC) analysis. The stability test of the VAR model was carried out through the Johansen Cointegration Test at a 5% significance level which produced six equations with a trace statistically more significant than the critical value. Then an analysis of Impulse Response Functions (IRF) was carried out to see the dynamic response of the CPI variable to food commodity prices. The data used are time series for January 2018 to December 2020.   Findings: The inflation response to food price fluctuations in Palopo City resulted in three conditions. The Palopo City CPI responded positively to the price fluctuations of garlic and red chili. In contrast, shallots and chicken meat price fluctuations responded negatively to the Palopo City CPI. The Palopo City CPI did not permanently affect the price fluctuations of cayenne pepper and chicken eggs.   Research, Practical & Social implications: The practical implication of this research is that food commodity prices still have an influence on inflation movements. Local governments should cooperate with city governments in the production of food commodities by implementing cropping patterns on these commodities to overcome excess production, and it is necessary to carry out off-season production to achieve harvest deficits so that prices remain stable. Improvements to the trade system also need to be improved in addition to the production system. This is intended so that the distribution of food commodity products can be more efficient by implementing supply chain management.   Originality/value: Collecting time series data of the Consumer Price Index (CPI) for 6 commodities, namely shallots, garlic, chili peppers, cayenne pepper, broiler meat, and broiler eggs, in a modern model, namely a multivariate time series model with a high level of predictive accuracy of the model among these variables to predict and analyze the effects among these series and estimate the interactions among these series with the latest data is the value of this research, and then provide recommendations for the government in making economic strategies, especially for those related to inflation and food prices.

Policies and programs often aim to improve the affordability of nutritious diets, but existing food price indexes are based on observed quantities that may not meet nutritional goals. To measure changes in the cost of reaching international standards of diet quality, we introduce a new cost of diet diversity index based on the lowest-cost way to include at least five different food groups as defined by the widely used minimum dietary diversity for women (MDD-W) indicator and compare that to a Cost of Nutrient Adequacy indicator for the lowest-cost way to meet estimated average requirements of essential nutrients and dietary energy. We demonstrate application of both indexes using national average monthly prices from two very different sources: an agricultural market information system in Ghana (2009–14) and the data used for national consumer price indexes in Tanzania (2011–15). We find that the cost of diet diversity index for Ghana fluctuated seasonally and since mid-2010 rose about 10% per year faster than national inflation, due to rising relative prices for fruit, which also drove up the cost of nutrient adequacy. In Tanzania there were much smaller changes in total daily costs, but more adjustment in the mix of food groups used for the least-cost diet. These methods can show where and when nutritious diets are increasingly (un)affordable, and which nutritional criteria account for the change. These results are based on monthly national average prices, but the method is generalizable to other contexts for monitoring, evaluation, and assessment of changing food environments.

This article examines how product innovations led to inflation inequality in the United States from 2004 to 2015. Using scanner data from the retail sector, I find that annual inflation for retail products was 0.661 (std. err. 0.0535) percentage points higher for the bottom income quintile relative to the top income quintile. When including changes in product variety over time, this difference increases to 0.8846 (std. err. 0.0739) percentage points a year. In CEX-CPI data covering the full consumption basket, the annual inflation difference is 0.368 (std. err. 0.0502) percentage points. I investigate the following hypothesis: (i) the relative demand for products consumed by high-income households increased because of growth and rising inequality; (ii) in response, firms introduced more new products catering to such households; (iii) as a result, the prices of continuing products in these market segments fell due to increased competitive pressure. Using a shift-share research design, I find causal evidence that increasing relative demand leads to increasing product variety and lower inflation for continuing products. A calibration indicates that the hypothesized channel accounts for a large fraction (over 50%) of observed inflation inequality.

Purpose: The construction sector is essential for the economic development of a country. This industry is likewise a key player and has a significant influence on the stock market. Hence, it is necessary to analyze the variables that influence the stock prices in the construction sector, as this will enable investors to maximize profits and mitigate risks.   Theoretical framework: This study evaluates the impact of macro factors and internal factors on the stock prices of the construction industry.   Design/Methodology/Approach: This study utilizes quarterly financial reports from 56 construction industry enterprises in the Vietnamese stock market during the period from 2016 to 2022 to examine the factors affecting the stock prices of this sector.   Findings: The results of the analysis indicate that the Random Effects Model (REM) is the most appropriate model, with factors such as the Consumer Price Index (CPI), Earnings Per Share (EPS), firm size (SIZE), and Price-Earnings ratio (PE) all having a positive impact on the stock prices of the construction industry.   Research,  Practical  &  Social  implications: Based on these findings, the article provides recommendations for investors and relevant industry stakeholders.   Originality/value: This article has conducted extensive analyses of factors influencing the stock prices of construction industry enterprises. The authors also provide suggestions for investors and relevant industry stakeholders to make investment decisions.

The pandemic caused expenditure shares to vary more than usual, leading to serious ramifications when combined with the fact that the expenditure shares used to calculate CPI inflation are 1-2 years old. This caused a potential bias in the measurement of inflation. We also look at the cost-of-living crisis and found that the lags in updating the expenditure shares for energy and food led to an underestimate of inflation in 2022. Inflation also has a large effect on the measurement of the public sector deficit. With a high debt-GDP ratio and high inflation, there was a substantial inflation tax.

Any researcher on corruption has faced at some point the dataset dilemma. How can one assess the incidence of a phenomenon on corruption levels if we cannot determine how much corruption is there in the first place? The problem compounds when the research has a transnational or comparative element. How can one assess how different corruption levels are in different jurisdictions if we cannot be sure if the measurements are comparable? It becomes critical when the research has a diachronic component, and tries to incorporate changes over time, as the stability and consistency of datasets become essential. This article reviews the literature on the topic from the last fifteen years and evaluates all the main options available today for researchers and policy designers in terms of validity and reliability, explaining first the particularities of these two concepts in the context of measurements of the prevalence of corruption. It pays particular attention to the limitations of the different datasets and determines the validity and reliability of the oft-used Corruption Perceptions Index post-2012 (CPI) and the Control of Corruption (CoC) indicator for the whole data series. This conclusion partially vindicates those researchers and policy designers who have used these datasets in the past, especially when compared to all the other options, while firmly warning users about the kind of conclusions that can be extracted from them.

This paper compares the amendments introduced by the Regulation of Lobbying and Oireachtas (Allowances to Members) (Amendment) Act 2023 with the original regulations of the Regulation of Lobbying Act 2015. The study was conducted using the Hired Guns Method for assessing the robustness of lobbying legislation, developed by the Centre for Public Integrity (CPI), allowing findings to be compared with lobbying regulations internationally. The 2015 legislation was introduced after years of tribunals, scandals, unfulfilled political promises, and economic crisis, in an effort to increase the public’s trust in politicians, representative institutions, democracy and the wider bureaucracy. The 2023 Amendment came in the wake of a 2020 lobbying scandal. The paper finds that, despite the CPI score remaining unchanged, in-depth examination of the legislation showed that the amendment introduced more rules and sanctions, particularly in relation to designated public officials, and closed off outstanding legislative loopholes.

As a nontraditional T-cell subgroup, γδT cells have gained popularity in the field of immunotherapy in recent years. They have extraordinary antitumor potential and prospects for clinical application. Immune checkpoint inhibitors (ICIs), which are efficacious in tumor patients, have become pioneer drugs in the field of tumor immunotherapy since they were incorporated into clinical practice. In addition, γδT cells that have infiltrated into tumor tissues are found to be in a state of exhaustion or anergy, and there is upregulation of many immune checkpoints (ICs) on their surface, suggesting that γδT cells have a similar ability to respond to ICIs as traditional effector T cells. Studies have shown that targeting ICs can reverse the dysfunctional state of γδT cells in the tumor microenvironment (TME) and exert antitumor effects by improving γδT-cell proliferation and activation and enhancing cytotoxicity. Clarification of the functional state of γδT cells in the TME and the mechanisms underlying their interaction with ICs will solidify ICIs combined with γδT cells as a good treatment option.

Osimertinib is the only third‐generation EGFR tyrosine kinase inhibitor clinically approved for first‐line treatment of advanced NSCLC patients harboring EGFR mutations. However, drug resistance severely hinders its clinical efficacy. Acquired MET amplification is an important mechanism causing osimertinib resistance. This study is the first to identify fexofenadine, originally indicated for allergic rhinitis and chronic urticaria, as a putative Met‐inhibitor by in silico chemical‐protein interactome analysis of known Met inhibitors. Fexofenadine was verified to inhibit recombinant Met kinase in cell‐free assay and phosphorylation of Met and other downstream signaling molecules in osimertinib‐resistant NSCLC cell lines. KINOME profiling revealed a similar kinase inhibition profile between fexofenadine and a known Met‐inhibiting drug cabozantinib using Spearman rank‐order correlation analysis. Among the tested osimertinib‐resistant NSCLC cell lines, fexofenadine was the most efficacious in potentiating osimertinib in NCI‐H820 (having MET amplification and EGFR‐T790M mutation). Transcriptome profiling in NCI‐H820 revealed that the differentially expressed genes following fexofenadine treatment were enriched in epithelial‐mesenchymal transition‐related biological pathways. Importantly, fexofenadine was also shown to significantly potentiate the antitumor effect of osimertinib in a drug‐refractory NSCLC patient‐derived tumor xenograft model in NSG mice, without inducing notable adverse effects. These findings advocate the clinical evaluation of repurposing fexofenadine to overcome osimertinib resistance. Fexofenadine was identified as a new Met inhibitory drug by a computational drug repurposing tool called “DRAR‐CPI” via chemical‐protein interactome analysis of known Met inhibitors. It was shown to overcome osimertinib resistance in non‐small cell lung cancer by inhibiting Met in vitro and in vivo.

Despite the advances in screening protocols and treatment options, hepatocellular carcinoma (HCC) is still considered to be the most lethal malignancy in patients with liver cirrhosis. Moreover, the survival outcomes after failure of first-line therapy for unresectable HCC is still poor with limited therapeutic options. One of these options is immune checkpoint inhibitors. The aim of this study is to comprehensively review the efficacy and safety of immune checkpoint inhibitors for patients with HCC.