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In this study, we aim at investigating dynamic relations among steel price indices of all seven regional markets in China, spanning the period of 2010M1–2021M4. With daily data, we apply techniques of vector error correction modeling and the directed acyclic graph to analyze the issue of contemporaneous causality among the seven indices, the latter of which is facilitated through the LiNGAM algorithm. We find via vector error correction modeling that each of the seven indices is part of cointegration relations and responses to long-run equilibrium disturbances. We arrive at causal paths via the LiNGAM algorithm for enabling innovation accounting analysis. With this analysis, we find sophisticated dynamics in price adjustment processes following shocks, for which east and northeast regions have the most significant impacts on other regions, followed by south and north regions, followed by the southwest region. Central south and northwest regions are not found to have significant impacts on others. These results suggest that policies on regional steel prices in the long run might be designed with most attention paid to five of the seven regions, particularly east and northeast regions. [ABSTRACT FROM AUTHOR]

This study investigates the factors influencing food inflation in Turkey, employing both endogenous and exogenous models and integrating major literature findings. Utilizing monthly data from February 2007 to November 2023, standardized for analysis, it explores the relationship between food inflation and various determinants through classical and Bayesian methods. The analysis reveals that increases in the real effective exchange rate, money supply (M1), Turkish and Federal Reserve interest rates, and the food and beverage price index contribute to rising food inflation. Conversely, higher oil prices have a statistically significant negative effect on food inflation. The most influential variables, determined by their inclusion probabilities in the model, are the money supply, Federal Reserve interest rate, real effective exchange rate, and Turkish interest rate. These findings underscore their importance in understanding and analyzing changes in Turkey's food inflation. [ABSTRACT FROM AUTHOR]

This study aims to predict financial distress in an emerging country using data on ST listed companies in China from 2001 to 2021. A new Aalen hazard model with mixed data sampling (MIDAS) is adopted to investigate the impact of monthly macroeconomic variables and quarterly financial variables on financial distress. The empirical results show that the current ratio, operating profit ratio, current capital ratio, retention ratio, profit ratio and income ratio of listed companies have a significant impact on the time-varying intensity of financial distress. The consumer price index has a negative relation with the intensity of financial distress, while the production price index and credit spreads have a positive influence. Finally, the results of the robustness tests are consistent with those with different lag orders. [ABSTRACT FROM AUTHOR]

The Supplemental Nutrition Assistance Program (SNAP) aims to improve food security among low‐income households and is one of the largest safety net programs in the United States. SNAP benefits are legislated at the federal level and fixed across the contiguous United States. Hence, due to regional food price differences, the real value of SNAP benefits is unequal and could have consequential impacts on program participation. This paper estimates the extent to which SNAP purchasing power differs across states by constructing the first spatially and temporally consistent Thrifty Food Plan (TFP) price index using retail scanner data for the period 2006–2016. We find that the difference in the real value of SNAP benefits between the highest and the lowest cost states ranges from 5% to 9% for a household of four during the sample period. Subsequently, we estimate the effect of real SNAP benefits on program participation. Our results show that a 10% increase in SNAP purchasing power leads to a 0.9 percentage point increase in the SNAP caseload per capita and an 8.1 percentage point increase in the SNAP caseload per eligible individual. We show that these effects would be overlooked if the TFP price index is not corrected for expenditure and outlet biases. [ABSTRACT FROM AUTHOR]

Legislation designed for one purpose may have unrelated side effects. In this article we examine the impact of recent changes in the application of the sole purpose test for artworks to be used as assets in retirement funds on the Australian Aboriginal art market. This is important since art sales represent a significant source of non‐government income for remote Australian Aboriginal communities. In this article we estimate the impact of this change and others on the price index based on the hammer prices paid for 13,555 works by 187 artists at art auctions from 1994 to 2019. [ABSTRACT FROM AUTHOR]

Edge computing has low transmission delay and unites more agile interconnected devices spread across geographies, which enables cloud-edge storage more suitable for distributed data sharing. This paper proposes a trustworthy and reliable multi-keyword search (TRMS) in blockchain-assisted cloud-edge storage, where data users can choose a faster search based on edge servers or a wider search based on cloud servers. To acquire trustworthy search results and find reliable servers, the blockchain-based smart contract is introduced in our scheme, which will execute the search algorithm and update the score-based trust management model. In this way, search results and trust scores will be published and recorded on the blockchain. By checking search results, data users can judge whether the returned documents are top-k documents. Based on the trust management model, we can punish the malicious behavior of search servers, while data users can choose more reliable servers based on trust scores. To improve efficiency, we design a threshold-based depth-first search algorithm. Extensive experiments are simulated on Hyperledger Fabric v2.4.1, which demonstrate our scheme (with 16 threads) can reduce the time cost of index construction by 92% and the time cost of search by 82%, approximately. Security analysis and extensive experiments can prove the security and efficiency of the proposed scheme. [ABSTRACT FROM AUTHOR]

Despite the rapid growth in digital payments (DP) adoption and its positive socio-economic impacts in low-income countries, a large portion of the population remains disconnected from DP. At the same time, usage of DP conditional on adoption is low, highlighting the unexplored potential for financial inclusion and economic advancement. This paper reviews the burgeoning academic literature on DP and categorizes both macro-level adoption barriers (extensive margin) and micro-level usage challenges (intensive margin). We draw on the Transaction Cost Index, a new comprehensive database encompassing 16 low-income countries, to shed light on major themes in markets for DP. We conclude by outlining potential avenues for future research in this area. [ABSTRACT FROM AUTHOR]

In terms of well‐being, how costly is inflation? To answer this question, empirical evaluations have typically studied average inflation rates at the national level, thus disregarding the role of inflation inequalities within a country. In this article, we relax the assumptions that heterogeneous consumers face homogeneous inflation rates, and study the correlation between price changes and self‐reported satisfaction with living standards. We use newly available data from France and adopt two approaches. First, we focus on individually perceived inflation and use the internationally harmonized Opinion Price Index as a proxy for experienced inflation. Variations in perceived inflation help predict well‐being differences among consumers, even when controlling for relevant sociodemographic factors, personality traits, and common method variance. We estimate their marginal impact to be higher than equivalent variations in nominal income. Second, we compare groups of consumers over time and find that changes in the price of a good disproportionately affect the relative well‐being of those who consume it. The study shows that the well‐being cost of the inflation crisis would be underestimated if looking at aggregate figures only. [ABSTRACT FROM AUTHOR]

Due to outdated weighting information, a Laspeyres‐based consumer price index (CPI) is prone to accumulating upward bias. Therefore, the present study introduces and examines simple and transparent revision approaches that retrospectively address the source of the bias. They provide a consistent long‐run time series of the CPI and require no additional information. Furthermore, a coherent decomposition of the bias into the contributions of individual product groups is developed. In a case study, the approaches are applied to a Laspeyres‐based CPI. The empirical results confirm the theoretical predictions. The proposed revision approaches are adoptable not only to most national CPIs but also to other price‐level measures such as the producer price index or the import and export price indices. [ABSTRACT FROM AUTHOR]

I show that conventional price index formulas and time‐dummy hedonic regression techniques all consistently estimate growth parameters in the same generalized model of product pricing. I then use that result to make two points. First, the "stochastic approach" is not a helpful tool for choosing price index formulas, because in its complete form it can justify any of them. Second, the literature uses flawed arguments for replacing time‐dummy hedonic regression with hedonic imputation. The time‐dummy method is an excellent, underrated option. [ABSTRACT FROM AUTHOR]

Motivation: The Macroeconomic Imbalance Procedure (MIP) is a key step in the European Semester, aimed at the coordination of the economic policies of the EU Member States to prevent excessive macroeconomic imbalances in the EU and support structural reforms. The MIP was originally envisaged as a legal tool for crisis prevention, allowing macroeconomic imbalances to be detected and then remedied, but is also used as an Early Warning System. However, the real strength of MIP indicators to predict crises has not been proved in practice and is widely contested in the literature. Aim: Fourteen scoreboard ("main") and 28 auxiliary MIP indicators are currently in use. This paper is aimed at the assessment of the power of all MIP indicators in predicting crises. Results: The added value of our research is to test the MIP's ability to predict changes in GDP, which may be considered as a proxy for the deterioration or improvement of the economic situation. Very little investigation has been done in this area so far. In addition, to our knowledge, no research papers have investigated the relevance of auxiliary MIP indicators. Our results show that only four main indicators (house price index, nominal unit labour cost index, general government sector debt, and export market shares) and another four auxiliary indicators (residential construction as percentage of GDP, activity rate, people living in households with very low work intensity, and export performance against advanced economies) seem to be able to predict the upcoming crises. [ABSTRACT FROM AUTHOR]

This paper econometrically models the dynamics of Indian rupee (INR) swap yields based on key macroeconomic factors using the autoregressive distributive lag (ARDL) approach. It examines whether the short-term interest rate has a decisive influence on long-term INR swap yields after controlling for other factors, such as core inflation, the growth of industrial production, the logarithm of the equity price index, and the logarithm of the INR exchange rate. The estimated models show that the short-term interest rate has an important influence on swap yields. This implies that the Reserve Bank of India (RBI) can sway borrowing and lending rates not just on Indian government bonds but also INR-denominated private-market financial instruments, such as swaps and swaptions. [ABSTRACT FROM AUTHOR]

This study focuses on the real estate bubble burst in the US housing market during 2007–2008. We analyze the dynamics of the housing market crash and the after-crash sequence during the Great Recession. When a complex system deviates away from its typical path by the occurrence of an extreme event, its behavior is strongly characterized as nonstationary with higher volatility. With the utilization of a robust method, we present the characteristics of the aftershock period and provide useful information about the spatial distribution and the decay process of the aftershock sequence in terms of time. The returns of the housing price indices are well approximated by the empirics of a power law. Although we deal with low-frequency data, a time power-law relaxation pattern is identified. Our findings align with those in geophysics, indicating that the value of the relaxation parameter typically hovers around one and varies across different thresholds. [ABSTRACT FROM AUTHOR]

Featured Application: This work designed a motion planning algorithm for autonomous vehicles in unanticipated obstacle scenarios. In standard driving scenarios, the proposed motion planning algorithm plans a trajectory that complies with intersection regulations, including lane-marking, recommended turning lane, traffic light, right-of-way, and no-parking rules. In unanticipated obstacle scenarios, after the necessity of obstacle avoidance is identified, the ego vehicle would break the rules temporarily to ensure the safety and mobility of autonomous vehicles. In unanticipated obstacle scenarios at intersections, the safety and mobility of autonomous vehicles (AVs) are negatively impacted due to the conflict between traffic law compliance and obstacle avoidance. To solve this problem, an obstacle avoidance motion planning algorithm based on artificial potential field (APF) is proposed. An APF-switching logic is utilized to design the motion planning framework. Collision risk and travel delay are quantified as the switching triggers. The intersection traffic laws are digitalized and classified to construct compliance-oriented potential fields. A potential violation cost index (PVCI) is designed according to theories of autonomous driving ethics. The compliance-oriented potential fields are reconfigured according to the PVCI, forming violation cost potential fields. A cost function is designed based on compliance-oriented and violation cost potential fields, integrated with model predictive control (MPC) for trajectory optimization and tracking. The effectiveness of the proposed algorithm is verified through simulation experiments comparing diverse traffic law constraint strategies. The results indicate that the algorithm can help AVs avoid obstacles safely in unanticipated obstacle scenarios at intersections. [ABSTRACT FROM AUTHOR]

To evaluate and compare the financial burden of various surgical interventions for the management of benign prostatic hyperplasia (BPH). We identified commercially insured men with a diagnosis of BPH who underwent a procedure of interest (simple prostatectomy (SP), transurethral resection of the prostate (TURP), holmium laser enucleation of the prostate (HoLEP), photovaporization of the prostate (PVP), prostatic urethral lift (PUL), or water vapor thermal therapy (WVTT)) between 2015 and 2021 with the OptumLabs Data Warehouse. Primary outcome was total health care costs (THC) which included both patient out-of-pocket (OOP) and health plan paid costs for the index procedure and combined follow-up years 1-5. A generalized linear model was used to estimate adjusted costs controlling for demographic and clinical characteristics. Patients undergoing WVTT were excluded from extended follow-up analyses due to limited data. Among 25,407 patients with BPH, 10,117 (40%) underwent TURP, 6353 (25%) underwent PUL, 5411 (21%) underwent PVP, 1319 (5%) underwent SP, 1243 (5%) underwent WVTT, and 964 (4%) underwent HoLEP. Index procedure costs varied significantly with WVTT being the least costly [THC: $2637 (95% confidence interval (CI): $2513-$2761)], and SP being the costliest [THC: $14,423 (95% CI: $12,772-$16,075)]. For aggregate index and 5-year follow-up costs, HoLEP ($31,926 [95% CI: $29,704-$34,148]) was the least costly and PUL ($36,596 [95% CI: $35,369-37,823]) was the costliest. BPH surgical treatment is associated with significant system-level health care costs. The level of impact varies between procedures. Minimally invasive options, such as WVTT, may offer initial cost reductions; however, HoLEP and SP are associated with lower follow-up costs. [ABSTRACT FROM AUTHOR]

Interdisciplinary fields have become the driving force of modern science and a significant source of scientific innovation. However, there is still a paucity of analysis about the essential characteristics of disciplines' cross-disciplinary impact. In this study, we define cross-disciplinary impact on one discipline as its impact to other disciplines, and refer to a three-dimensional framework of variety-balance-disparity to characterize the structure of cross-disciplinary impact. The variety of cross-disciplinary impact of the discipline was defined as the proportion of the high cross-disciplinary impact publications, and the balance and disparity of cross-disciplinary impact were measured as well. To demonstrate the cross-disciplinary impact of the disciplines in science, we chose Microsoft Academic Graph (MAG) as the data source, and investigated the relationship between disciplines' cross-disciplinary impact and their positions in the Hierarchy of Science (HOS). Analytical results show that there is a significant correlation between the ranking of cross-disciplinary impact and the HOS structure, and that the discipline exerts a greater cross-disciplinary impact on its neighboring disciplines. Several bibliometric features that measure the hardness of a discipline, including the number of references, the number of cited disciplines, the citation distribution, and the Price index have a significant positive effect on the variety of cross-disciplinary impact. The number of references, the number of cited disciplines, and the citation distribution have significant positive and negative effects on balance and disparity, respectively. It is concluded that the less hard the discipline, the greater the cross-disciplinary impact, the higher balance and the lower disparity of cross-disciplinary impact. In the empirical analysis of HOS, we only included five broad disciplines. This study also has some biases caused by the data source and applied regression models. This study contributes to the formulation of discipline-specific policies and promotes the growth of interdisciplinary research, as well as offering fresh insights for predicting the cross-disciplinary impact of disciplines. This study provides a new perspective to properly understand the mechanisms of cross-disciplinary impact and disciplinary integration. [ABSTRACT FROM AUTHOR]

Pork price fluctuations are closely related to the national economy and people's livelihoods in China. Based on the monthly pork price fluctuations in China from January 2011 to August 2022, this study uses ARCH family models to assess the characteristics and laws of these fluctuations in China. The pork price fluctuations show obvious clustering, with external shock information from the previous month affecting the pork price in the following period; the pork market price is characterized by risk compensation, with the high risk of pork supply driving the pork price up. In addition, the pork price fluctuations are characterized by asymmetry, with a greater impact of good than of bad news on the pork price. Due to the pork industry' low entry threshold and the existence of sunk costs, positive information on the pork market has a stronger impact on price fluctuations than negative information. To guide pork supply, we recommend improving monitoring and earlywarning mechanisms in the pork market to identify the pork price volatility threshold and measure the price volatility. In addition, price index insurance products should be constantly strengthened, with different types of insurance products being offered to meeting the insurance demand of various sectors in the pig meat supply chain. [ABSTRACT FROM AUTHOR]

Purpose: The main purpose of this paper is to examine the convergence hypothesis of House Price Index (HPI) in the case of 18 major Indian cities for the period 2014–2019. Design/methodology/approach: To attain the authors main goal, this study applies a clustering algorithm advanced by Phillips and Sul. This test creates a club of convergence based on the growth of the cities in terms of HPI. Findings: The study findings show the existence of two convergence clubs and one non-convergent group. Club 1 includes the cities with high HPI growth, whereas club 2 comprises of cities with least HPI growth. Cities belonging to the non-convergent group are neither converging nor diverging. Practical implications: This study findings will benefit home buyers, sellers, investors, regulators and policymakers interested in the dynamic interlinkages of house price (HP) among Indian cities. Originality/value: The majority of the studies are conducted in the case of China at the province or city levels. Furthermore, in the case of India, none of the studies has investigated the HP club convergence across Indian cities. Therefore, the present study fills this research gap by examining the HP club convergence across Indian cities. [ABSTRACT FROM AUTHOR]

Healthcare facilities (HCFs) are complex building structures that are becoming more challenging with ever-changing codes and regulations. Previously completed projects become a basis for future guidance regarding costs and scope. A robust normalization framework to assess previously completed projects with today's costs and location will benefit various stakeholders. The current study provides a complete picture for normalizing the overall project cost and phase cost by life cycle and HCF cost elements. This study aims to develop a cost normalization approach tailored to HCF-specific cost elements to extend the normalization framework for the overall project cost. Further, the researchers developed a distinct framework for normalizing the effect of shell space on the normalization of Total Installed Cost (TIC) to establish fixed cost adjustment rates for cold and warm shell spaces in HCFs, which can increase the accuracy of cost normalization of the overall project cost. This study identified an appropriate set of cost indices for normalizing HCF cost elements using publicly available indices. The cost elements identified for normalization included HCF-specific and Construction Specifications Institute Master Format (CSIMF) cost elements for assigning individual normalization procedures. This study provides individual and unique approaches for normalizing all identified cost elements, such as mechanical, concrete, etc. The initial framework was evaluated through a case study analysis that developed into the proposed approach built upon the collaborative efforts of academic researchers and industry experts. This study introduced shell space cost adjustment rates for warm and cold shell spaces to further develop a space normalization framework. This paper addresses the challenges of normalizing HCF project costs using the breakdown of HCF cost elements. Moreover, the paper provides the HCF's overall cost normalization approach, emphasizing cost elements that allow accurate comparisons between various HCFs for early scope and cost guidance. [ABSTRACT FROM AUTHOR]

How should we measure changes in consumer welfare given observed data on prices and expenditures? This article proposes a nonparametric approach that holds under arbitrary preferences that may depend on observable consumer characteristics, for example, when expenditure shares vary with income. Using total expenditures under a constant set of prices as our money metric for real consumption (welfare), we derive a principled measure of real consumption growth featuring a correction term relative to conventional measures. We show that the correction can be nonparametrically estimated with an algorithm leveraging the observed, cross-sectional relationship between household-level price indices and household characteristics such as income. We demonstrate the accuracy of our algorithm in simulations. Applying our approach to data from the United States, we find that the magnitude of the correction can be large because of the combination of fast growth and lower inflation for income-elastic products. Setting reference prices in 2019, we find that (i) the uncorrected measure underestimates average real consumption per household in 1955 by 11.5%, and (ii) the correction reduces the annual growth rate from 1955 to 2019 by 18 basis points, which is larger than the well-known "expenditure-switching bias" over the same time horizon. [ABSTRACT FROM AUTHOR]

Since the 1980s inflationary pressures seem to materialise over‐proportionately outside sectors of consumer goods and services. We combine the Harmonised Index of Consumer Prices with indices for asset prices, such as stocks and real estate, as well as a proxy for the costs of public goods to develop alternative inflation measures in Germany since the introduction of the Euro. Real economic growth as well as median wage developments are reexamined in light of the alternative inflation estimates. Both turn out to be negative over the past decade in the most pessimistic scenarios. [ABSTRACT FROM AUTHOR]

The article focuses on analyzing the impact of seasonal adjustment on quarterly estimates of the Employment Cost Index (ECI), which tracks changes in employee compensation over three-month periods. It discusses how seasonal adjustment affects various industry groups within the ECI and demonstrates that while the effect is generally small for most aggregate series, there are industry groups where it has a more significant impact.

This study addresses the large bias in chained price indices that persists even at lower frequencies. The bias arises from intertemporal substitution caused by consumer hoarding, and is problematic for purchase‐based data. In order to resolve this issue, we propose a method for calculating changes in inventories and consumption using retailer scanner data. We construct a partial equilibrium model to estimate inventories and consumption and show that the model accurately predicts the sign and size of the bias. We also demonstrate that the bias is smaller for consumption‐based data and propose a particular type of price index that eliminates intertemporal substitution bias. [ABSTRACT FROM AUTHOR]

We use house prices (HP) and house price indices (HPI) as a proxy to income distribution. Specifically, we analyze distribution of sale prices in the 1970–2010 window of over 116,000 single-family homes in Hamilton County, Ohio, including Cincinnati metro area of about 2.2 million people. We also analyze distributions of HPI, published by Federal Housing Finance Agency (FHFA), for nearly 18,000 US ZIP codes that cover a period of over 40 years starting in 1980's. If HP can be viewed as a first derivative of income, HPI can be viewed as its second derivative. We use generalized beta (GB) family of functions to fit distributions of HP and HPI since GB naturally arises from the models of economic exchange described by stochastic differential equations. Our main finding is that HP and multi-year HPI exhibit a negative Dragon King (nDK) behavior, wherein power-law distribution tail gives way to an abrupt decay to a finite upper limit value, which is similar to our recent findings for realized volatility of S&P500 index in the US stock market. This type of tail behavior is best fitted by a modified GB (mGB) distribution. Tails of single-year HPI appear to show more consistency with power-law behavior, which is better described by a GB Prime (GB2) distribution. We supplement full distribution fits by mGB and GB2 with direct linear fits (LF) of the tails. Our numerical procedure relies on evaluation of confidence intervals (CI) of the fits, as well as of p-values that give the likelihood that data come from the fitted distributions. [ABSTRACT FROM AUTHOR]

Using 1.7 million consumers' purchasing records in Japan, this study constructs two types of price indexes at the consumer level. The first measures the relative price level of each consumer in a given time period (i.e., cross-sectional price-level comparison), while the other captures the change in prices between two different time periods for a given consumer (i.e., individual inflation rate). This study shows that these price indexes do not comove over the life cycle. In particular, older consumers who have retired pay higher prices for identical goods than working-age consumers, while facing the lower inflation rate. This difference in inflation rates stems from the fact that retired consumers tend to adjust their shopping baskets. Life-cycle variation in individual inflation rates is consistent with the argument that older consumers tend to increase the shopping frequency and search for low-priced goods. [ABSTRACT FROM AUTHOR]

This paper examines the time-varying spillover effects and connectedness of the Bitcoin price with clean and renewable energy stocks using the quantile VAR framework. We use daily price indices spanning from 1 January 2014, to 18 October 2022. Before probing the quantile spillover effects between the markets examined, we first examine the mean-based averaged connectedness. These results indicate that Bitcoin receives more shocks from markets in the system than it transmits. Additionally, Bitcoin emerges as a net receiver of return shocks with index evolution among the markets examined, driven mainly by own shocks. Shifting to the results obtained using the QVAR approach, evidence reveals that Bitcoin acts as a net recipient of shocks under different quantiles in the system. In addition, Bitcoin returns strongly correlate with renewable energy stock returns under extreme events. We also confirm the dominance of renewable energy markets over Bitcoin and that the magnitude of their connectedness is time and event dependent. These findings confirm the diversification potential and safe-haven properties of Bitcoin for portfolio investors. [ABSTRACT FROM AUTHOR]

This research paper addresses the impact of the positive or negative polarity of the presidential messages contained in the stenographic version of the daily conferences issued by the president of Mexico, obtained by means of semantic and machine learning text mining techniques, on the performance of the Mexican Stock Exchange's Price and Quotations Index (Índice de Precios y Cotizaciones-IPC). Our results provide evidence of the existence of a negative and significant relationship of the polarity of presidential messages with IPC performance, i.e., as the positive polarity of messages increases, IPC performance decreases. [ABSTRACT FROM AUTHOR]

This paper examines how closely aggregate macroeconomic indices such as the Gross Domestic Product (GDP) and market price volatility indices are associated with social welfare when heterogeneous beliefs are present. While it is widely recognised that the GDP fails to capture distributional effects, volatility measures are often argued to supplement the GDP with this regard. Although heterogeneous beliefs are known to be capable of generating large economic and/or price fluctuations, it is not straightforward whether volatility is closely associated with welfare when heterogeneous beliefs are present. By constructing a simulation model of a financial economy with production and credit constraints that allows for heterogeneous beliefs, we show that major discrepancies between aggregate measures, including volatility measures, and ex post welfare are not the exception, but the rule. Also, the paper analyses the mechanism that causes the discrepancies. Our results strongly suggest welfare be measured by observing the distribution of realised consumption across agents and over time — in particular, its lower tail. In short, macroeconomic indices may well easily become a fool's gold. [ABSTRACT FROM AUTHOR]

The recently launched California water price index (NASDAQ: NQH2O) and corresponding futures market provide an opportunity for water users to hedge against seasonal drought risk. While the volume of futures trading remains low, the index can be analyzed as a spatially aggregated price of physical water trades that responds to hydrology and management. This study investigates the extent to which the NQH2O index can be predicted from a combination of reservoir storage anomalies and inflow forecasts throughout the state. Over the available record (November 2013–June 2023), the daily hydrologic time-series are reduced to a set of principal components, which are shown to be nonlinearly correlated with the current and season-ahead price index. The PCs are then used as features in an exponential regression to predict the forward six-month average price. The most accurate model in cross-validation performs with R2=0.81 using four PCs that contain 85% of the total variance in the features. Predictions generally fall within $100/AF of the observed value, with larger errors associated with hydrologic forecast uncertainty during the winter. A threshold-based hedging strategy is developed to analyze the potential cost savings of buying during the winter (November–March) when the forecasted six-month average price is greater than the current index. This strategy shows an average cost reduction of 17% compared with the six-month average price, with reductions above 35% at the onset of dry water years. This study contributes a statistical modeling approach to support the development of more advanced hedging strategies in water portfolios. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this research paper is to recover the autonomous flight performance of a mini unmanned aerial vehicle (UAV) via stochastically optimizing the wing over certain parameters (i.e. wing taper ratio and wing aspect ratio) while there are lower and upper constraints on these redesign parameters. Design/methodology/approach: A mini UAV is produced in the Iskenderun Technical University (ISTE) Unmanned Aerial Vehicle Laboratory. Its complete wing can vary passively before the flight with respect to the result of the stochastic redesign of the wing while maximizing autonomous flight performance. Flight control system (FCS) parameters (i.e. gains of longitudinal and lateral proportional-integral-derivative controllers) and wing redesign parameters mentioned before are simultaneously designed to maximize autonomous flight performance index using a certain stochastic optimization strategy named as simultaneous perturbation stochastic approximation (SPSA). Found results are used while composing UAV flight simulations. Findings: Using stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV over previously mentioned wing parameters and FCS, it obtained a maximum UAV autonomous flight performance. Research limitations/implications: Permission of the directorate general of civil aviation in the Republic of Türkiye is essential for real-time UAV autonomous flights. Practical implications: Stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV wing parameters and FCS approach is very useful for improving any mini UAV autonomous flight performance cost index. Social implications: Stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV wing parameters and FCS approach succeeds confidence, highly improved autonomous flight performance cost index and easy service demands of mini UAV operators. Originality/value: Creating a new approach to recover autonomous flight performance cost index (e.g. satisfying less settling time and less rise time, less overshoot during flight trajectory tracking) of a mini UAV and composing a novel procedure performing simultaneous mini UAV having passively morphing wing over certain parameters while there are upper and lower constraints and FCS design idea. [ABSTRACT FROM AUTHOR]

Background Little is known about the short- and long-term healthcare costs of invasive Scedosporium/Lomentospora prolificans infections, particularly in patient groups without haematological malignancy. This study investigated excess index hospitalization costs and cumulative costs of these infections. The predictors of excess cost and length of stay (LOS) of index hospitalization were determined. These estimates serve as valuable inputs for cost-effectiveness models of novel antifungal agents. Methods A retrospective case-control study was conducted at six Australian hospitals. Cases of proven/probable invasive Scedosporium/L. prolificans infections between 2011 and 2021 (n = 34) were matched with controls (n = 66) by predefined criteria. Cost data were retrieved from activity-based costing systems and analysis was performed from the Australian public hospital perspective. All costs were presented in 2022 Australian dollars (AUD). Median regression analysis was used to adjust excess costs of index hospitalization whereas cumulative costs up to 1.5 years follow-up were estimated using interval-partitioned survival probabilities. Results Invasive Scedosporium/L. prolificans infections were independently associated with an adjusted median excess cost of AUD36 422 (P = 0.003) and LOS of 16.27 days (P < 0.001) during index hospitalization. Inpatient stay was the major cost driver (42.7%), followed by pharmacy cost, of which antifungal agents comprised 23.8% of the total cost. Allogeneic haematopoietic stem cell transplant increased the excess cost (P = 0.013) and prolonged LOS (P < 0.001) whereas inpatient death within ≤28 days reduced both cost (P = 0.001) and LOS (P < 0.001). The median cumulative cost increased substantially to AUD203 292 over 1.5 years in cases with Scedosporium/L. prolificans infections. Conclusions The economic burden associated with invasive Scedosporium/L. prolificans infections is substantial. [ABSTRACT FROM AUTHOR]

This study applies the date-stamping methodologies for explosive behaviors proposed in the seminal work of Phillips, P. C. B., and J. Yu. (2011. "Dating the Timeline of Financial Bubbles during the Subprime Crisis." Quantitative Economics 2 (3): 455–91), Phillips, P. C. B., S. Shi, and J. Yu. (2015a. "Testing for Multiple Bubbles: Historical Episodes of Exuberance and Collapse in the S&P 500." International Economic Review 56 (4): 1043–78), and Phillips, P. C. B., S. Shi, and J. Yu. (2015b. "Testing for Multiple Bubbles: Limit Theory of Real Time Detectors." International Economic Review 56 (4): 1079–134) to a large dimensional factor model. To this end, we compare two methods of identifying common and idiosyncratic components: the Panel Analysis of Nonstationarity in Idiosyncratic and Common Components (PANIC) method by Bai, J., and S. Ng. (2004. "A Panic Attack on Unit Roots and Cointegration." Econometrica 72 (4): 1127–77) and the Cross-Sectional regression (CS) method by Yamamoto, Y., and T. Horie. (2022. "A Cross-Sectional Method for Right-Tailed PANIC Tests under a Moderately Local to Unity Framework." Econometric Theory (forthcoming)). We show that, when the explosive behavior lies only in the common component, the origination and termination dates are precisely estimated by either method. However, when the explosive behaviors exist in idiosyncratic components, only the CS method can detect them. We apply our method to the U.S. state-level real house price indices. We find that the 2000s boom was driven by not only the national bubble factors but also local components, while the 2010s onward expansion is dominated by the effect of national components. [ABSTRACT FROM AUTHOR]

Efficient budget management is crucial for the successful execution of construction projects. To achieve this, the design of a Construction Project Audit Budget Management System based on combinatorial optimization offers significant advantages. Combinatorial optimization techniques focus on finding optimal solutions from a vast number of possible combinations, making them well -suited for complex budget management scenarios. This system employs advanced algorithms to analyze and optimize various factors such as resource allocation, cost estimation, risk assessment, and scheduling. This paper focused on the construction of the Project Fuzzy Audit System in China. The developed model computes total investment decision, preliminary design, design, contracting, construction, completion acceptance and other stages of the investment/cost, namely investment estimation, budget estimate, control price, contract price and settlement price. According to the project total investment/cost control needs in China Project. The constructed model uses the combinatorial Optimization model for the estimation of the investment estimation of the Construction Project for the cost index. Through the Fuzzy Audit System new method abolishes the "maximum price" in the bidding document with the limit as the unit, and gradually terminates the preparation of the budget quota, highlighting the market price, so there is an urgent need for a set of cost index in line with the actual needs. The results demonstrated that with the fuzzy Audit system new method abolishes the "maximum price" in the bidding document with the limit as the unit, and gradually terminates the preparation of the budget quota, highlighting the market price, Through analysis it is concluded that with fuzzy based optimization model effectively accumulate fast and accurate calculation of the Project cost. [ABSTRACT FROM AUTHOR]

Purpose: 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. Design/methodology/approach: The dynamic conditional correlation generalized autoregressive conditional heteroscedasticity model is used to study the dynamic relationship between variables over a while. Findings: 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. Originality/value: 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. [ABSTRACT FROM AUTHOR]

Given the widespread use of technical analysis and the tight relationship between derivatives and the underlying assets, we employ the copula approach to investigate whether the technical indicators based on underlying assets convey extra information about the future movements of implied volatility (IV) indexes. The empirical results, based on long samples of five well‐known IV indexes, suggest that although the technical indicators are not informative for forecasting the future prices of IV indexes, they can provide extra information about the size of forecasting errors of the IV indexes. The findings are also robust to the impact of COVID‐19. The technical indicators are then used to extend Threshold ARCH and Exponencial GARCH models for improving the estimation of Value at Risks (VaRs). The out‐of‐sample forecast results show that the proposed model outperforms the benchmark in estimating the VaRs. These findings have implications for pricing options of IV indexes and managing the risks of IV‐related portfolios. [ABSTRACT FROM AUTHOR]

Public departments of transportation (DOTs) are increasingly adopting alternative contracting methods (ACMs), such as Indefinite Delivery/Indefinite Quantity (IDIQ) agreements, to shorten project delivery and increase scheduling flexibility. However, the challenge remains to decide when an IDIQ contract would offer better value for money in a project compared to the conventional Design-Bid-Build (DBB) method. This paper proposes an IDIQ project selection framework that incorporates expected construction costs to identify suitable candidate projects. Historical bid data, an alternate cost indexing system, nonlinear regression analysis, and the Monte Carlo simulation technique are used to create and compare IDIQ and DBB probabilistic construction cost estimates. The study demonstrates the effectiveness of the framework using a single-award IDIQ granted through the Minnesota Department of Transportation (MnDOT) and past bidding information for projects awarded between January 2008 and April 2015. Additionally, the paper acknowledges the limitations of the study, including its reliance on MnDOT data, the exclusion of non-cost factors, and the assumption of project homogeneity. The study also provides valuable recommendations for future research to address these limitations and enhance the understanding and practical implementation of IDIQ contracting in the construction industry. [ABSTRACT FROM AUTHOR]

We analyze the time variation in the average dependence within a set of regional monthly house price index returns in a regime-switching multivariate copula model with a high and a low dependence regime. Using equidependent Gaussian copulas, we show that the dependence of house price returns varies across time with changes in credit market conditions, which reduces the gains from the geographic diversification of real estate and mortgage portfolios. More specifically, we show that a decrease in leverage, measured by the loan-to-value ratio, and to a lesser extent an increase in mortgage rates, are associated with a higher probability of moving to and staying in the high dependence regime. [ABSTRACT FROM AUTHOR]

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This paper empirically investigates the Gibson Paradox and the Fisher Effect for the UK during different metallic and non‐metallic regimes. The paper applies long‐span monthly data on the long‐term interest rate and the price index from 1790 to 1931. The ARDL cointegration is employed to study the long‐term relationship. Significant evidence is provided for the paradox during the uninterrupted gold standard era of the UK (1821–1914). We also find evidence of the paradox during the short‐term gold exchange standard era (1925–1931). Further results also confirm the Fisher Effect during the 1821–1914 period, providing some backing to its ability to explain the paradox. This is further asserted by the short‐run mutual influence between the rate of interest and the inflation rate. [ABSTRACT FROM AUTHOR]

The paper deals with the efficiency of the monetary policy on growth and inflation for the Euro zone within a low interest rate environment (LIRE) even if since 2022 the interest rate have increased. It is worthy to note that the low interest rate period was a very extraordinary situation and the theoretical scope was not able to explain this situation. Since the financial crisis, several conventional and unconventional measures were undertaken to avoid the systemic risk. The interest rate has been reduced to reach its effective lower bound (ELB). The ELB case has largely been discussed by the economic and empirical literature particularly by Keynesian and post-Keynesian theories. They have assumed that when the interest rate is too low, the monetary policy becomes inefficient because of the famous liquidity trap. To validate the liquidity trap theory and to contribute empirically to understand the role of (un)conventional policy, we run a MIDAS-VAR model for the Euro-zone. We have distinguished three periods: the full period (1999Q1-2019Q4), the non-negative interest rate period (1999Q1-2013Q4) and the post-crisis period (2008Q1-2019Q4). The results have suggested that the monetary policy, even in a low interest rate environment, sill simulates output (measured by the GDP) and inflation (HCPI, Harmonized Consumption Price Index). [ABSTRACT FROM AUTHOR]

Purpose: This study aims to identify the ability of gold and cryptocurrency (Cryptocurrency Uncertainty Index (UCRY) Price) as safe haven assets (SHA) for stocks and bonds in both conventional (i.e. stock indices and government bonds) and Islamic markets (i.e. Islamic stock indices and Islamic bonds (IB)). Design/methodology/approach: The authors employed the nonadditive panel quantile regression model by Powell (2016). It measured the safe haven characteristics of gold and UCRY Price for stock indices, government bonds, Islamic stocks, and IB under gold circumstances and level of cryptocurrency uncertainty, respectively. The period spanned from 11 March 2020 to 31 December 2021. Findings: This study discovered three findings, including: (1) gold is a strong safe haven for stocks and bonds in conventional and Islamic markets under bearish conditions; (2) UCRY Price is a strong safe haven for conventional stocks and bonds but only a weak safe haven for Islamic stocks under high crypto uncertainty; and (3) gold offers a safe haven in both emerging and developed countries, while UCRY Price provides a better safe haven in developed than in emerging countries. Practical implications: Gold always wins big for safe haven properties during unstable economy. It can also win over investors who consider shariah compliant products. Therefore, it should be included in an investor's portfolio. Meanwhile, cryptocurrencies are more common for developed countries. Thus, the governments and regulators of emerging countries need to provide more guidance around cryptocurrency so that the societies have better literacy. On top of that, the investors can consider crypto to mitigate risks but with limited safe haven functions. Originality/value: The originality aspects of this study include: (1) four chosen assets from conventional and Islamic markets altogether (i.e. stock indices, government bonds, Islamic stock indices and IB); (2) indicator countries selected based on the most used and owned cryptocurrencies for the SHA study; and (3) the utilization of UCRY Price as a crypto indicator and a further examination of the SHA study toward four financial assets. [ABSTRACT FROM AUTHOR]

This study investigates the regional differences in how consolidation has affected the efficiency of Shinkin banks, a representative cooperative financial institution in Japan, using the stochastic meta‐frontier approach based on cost and profit functions. The findings support the quiet life hypothesis that a significant negative relationship exists between efficiency‐adjusted Lerner indices and cost efficiency. By contrast, the relation between market power and profit efficiency is consistently positive. Moreover, independent Shinkin banks not involved in mergers exhibit higher costs and profit efficiency than other banks, suggesting that mergers can deteriorate efficiency. [ABSTRACT FROM AUTHOR]

Integrated capital markets provide better risk sharing and market efficiency, but presence of different barriers such as information asymmetry across borders hinders these benefits. This study investigates whether the adoption of International Financial Reporting Standards (IFRS) (uniform accounting standards) impacts the integration of worldwide capital markets by decreasing financial information frictions. Staggered adoption dates with price‐based measures (Beta and Sigma Convergence) of integration are used to measure the incremental impact of IFRS adoption on integration. The sample includes all the countries with capital markets that have benchmark indices and price data available. Overall statistical results suggest no significant impact of IFRS adoption on capital market integration. [ABSTRACT FROM AUTHOR]

Share Market/ Equity Market are the most important current research topic. Machine learning is increasingly used in stock/index price prediction due to its ability to analyze large amounts of data and identify complex patterns that may not be immediately obvious to human analysts. There are several deep learning algorithms commonly used for stock price prediction, including RNN, CNN, LSTM, and DNN. In stock price prediction, hybrid models can be used to combine the predictions of multiple models to produce more accurate predictions. The paper proposed hybrid deep learning DNN-CNN based method to improve the prediction of NSE Bank i.e. Bank Nifty. The ensemble DNN-CNN technique consists of two main components a DNN for feature extraction and a CNN for regression or classification tasks. In DNN-CNN model DNN layer is used to extract features from input data related to an estimated future value and CNN layer is used to combine features learned from the DNN layers. The results represent that proposed method recall is 91.02, precision is 98.2 and accuracy is 97.4. [ABSTRACT FROM AUTHOR]

Over the last two decades, the regulators of the financial services sector in Saudi Arabia have aimed to develop a level of fair competition in the provision of banking services across the country. This paper utilizes non-structural approaches, the H-statistic developed by, and the Granger causality test. The second approach involves determining the Granger-based causal relationship between banks' cost efficiency and competition via data envelope analysis (DEA) using the generalized method of moments (GMM) panel. The study's data were drawn from 11 traditional banks in Saudi Arabia, covering the period from 2015 to 2021 (yearly data). The results of the non-structural approach, i.e., the H-statistic, demonstrate that the average fund rate had a positive effect on competition; however, the physical capital price index, the index of leverage, and the credit risk negatively affect the total revenue. Furthermore, a positive H-statistic value reflects the positive causality between competition and cost efficiency (higher efficiency results in a higher level of competition). The DEA results indicate that competition in the year 2021 was influenced by the competition level of the previous year (2020); moreover, the relationship between the previous year's cost efficiency Granger value, the greater availability, and the lower prices of banking products had a significant influence on the competition in the years under consideration (since a positive significant result from the test is available), which reflects the higher level of market structure and the greater availability and lower prices of banking products. Cost efficiency in the year 2021 was also positively influenced by the cost efficiency level of the previous year (2020), with competition forcing efficiency via the cutting of costs. [ABSTRACT FROM AUTHOR]