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Accurately measuring real economic output in the space economy is made difficult by the rapid increase in capabilities and decrease in prices of launch and satellite technologies achieved over the past two decades. Nominal measures of output in space will tend to underestimate real growth if customers are paying lower prices for better services over time. In this paper, we use price indexes that apply techniques to the space economy that have been used for decades to adjust nominal measures of output in sectors such as information technology, including matched-model and explicit hedonic quality adjustment. We find that adjusting for price and quality changes in the space economy has substantial effects on estimated growth in economic output, especially across its sectors. Price increases over time in the space information sector, which is dominated by direct-to-home (DTH) satellite television, mean that real growth has been slower than nominal growth since at least 2012, the typical pattern in industries not undergoing rapid technological change. In sharp contrast, rapid price decreases and quality increases in other areas—especially launch and manufacturing of satellite, earth observation, and positioning, navigation, and timing (PNT) equipment—have meant that nominal growth rates substantially understate real growth rates in those industries. Given the central importance of space to our modern economy, having accurate information on growth in the space economy is vital for efficiently allocating the substantial private and public investment being devoted to its development. • Adjusting space output for price and quality changes impacts economic growth rates. • Growth in the US space sector masks underlying heterogeneity across its subsectors. • US space manufacturing products exhibit rapid price decreases and quality increases. • US space information product prices are rising even as overall output is falling. [ABSTRACT FROM AUTHOR]

Purpose: The research documented in this paper aims to examine multiple factors related to borrowers' default in peer-to-peer (P2P) lending in the USA. This study is motivated by the hypothesis that both P2P loan characteristics and macroeconomic variables have influence on loan performance. The authors define a set of loan characteristics, borrower characteristics and macroeconomic variables that are significant in determining the probability of default and should be taken into consideration when assessing credit risk. Design/methodology/approach: The research question in this study is to find the significant explanatory variables that are essential in determining the probability of default for LendingClub loans. The empirical study is based on a total number of 1,863,491 loan records issued through LendingClub from 2007 to 2020Q3 and a logistic regression model is developed to predict loan defaults. Findings: The results, in line with prior research, show that a number of borrower and contractual loan characteristics predict loan defaults. The innovation of this study is the introduction of specific macroeconomic indicators. The study indicates that macroeconomic variables assessed alongside loan data can significantly improve the forecasting performance of default model. The general finding demonstrates that higher percentage change in House Price Index, Consumer Sentiment Index and S&P500 Index is associated with a lower probability of delinquency. The empirical results also exhibit significant positive effect of unemployment rate and GDP growth rate on P2P loan default rates. Practical implications: The results have important implications for investors for whom it is of great importance to know the determinants of borrowers' creditworthiness and loan performance when estimating the investment in a certain P2P loan. In addition, the forecasting performance of the model could be applied by authorities in order to deal with the credit risk in P2P lending and to prevent the effects of increasing defaults on the economy. Originality/value: This paper fulfills an identified need to shed light on the association between specific macroeconomic indicators and the default risk from P2P lending within an economy, while the majority of the existing literature investigate loan and borrower information to evaluate credit risk of P2P loans and predict the likelihood of default. [ABSTRACT FROM AUTHOR]

Access control has always been one of the effective methods to protect data security. However, in new computing environments such as big data, data resources have the characteristics of distributed cross-domain sharing, massive and dynamic. Traditional access control mechanisms are difficult to meet the security needs. This paper proposes CACM-MMSR to solve distributed cross-domain access control problem for massive resources. The method uses blockchain and smart contracts as a link between different security domains. A permission decision model migration method based on access control logs is designed. It can realize the migration of historical policy to solve the problems of access control heterogeneity among different security domains and the updating of the old and new policies in the same security domain. Meanwhile, a semantic reasoning-based permission decision method for unstructured text data is designed. It can achieve a flexible permission decision by similarity thresholding. Experimental results show that the proposed method can reduce the decision time cost of distributed access control to less than 28.7% of a single node. The permission decision model migration method has a high decision accuracy of 97.4%. The semantic reasoning-based permission decision method is optimal to other reference methods in vectorization and index time cost. [ABSTRACT FROM AUTHOR]

In input-output analysis, the Leontief and Ghosh models can be used to determine the price indexes of goods, which is convenient for analyzing inter-industry inflation. Their respective merits are debated, but both provide the same solution. We demonstrate that, contrary to common belief, it is superfluous to use the Leontief or Ghosh model to calculate price indexes: the price index vector alone satisfies the accounting identities without assuming constant coefficients. So, in contrast to the Leontief and Ghosh models, price indexes can be derived 'instantly', without a round-by-round process. Conducting research on price indexes deduce from the Leontief or Ghosh model becomes pointless: it suffices to study price indexes deduced from the data. We illustrate these findings with an application for France 2018. The same is demonstrated for prices with the data given in physical quantities. [ABSTRACT FROM AUTHOR]

There is a broad consensus in international statistical organizations such as Eurostat and the International Monetary Fund that house price indices (HPIs) should be constructed using transaction data. We show here how transaction data for new‐built properties can undermine the timeliness of hedonic HPIs when new‐built properties are pre‐sold during the planning or building stage, but entered into deed books only once the projects are completed. As a consequence, HPIs for new‐builds will include stale transaction prices. We investigate this issue for two Polish cities (Warsaw and Poznan) and find that HPIs for existing properties lead indices for new‐builds by up to 2 years. This lag can dramatically distort National HPIs. The lag also has implications for the flagship measure of inflation in Europe—the Harmonized Index of Consumer Prices (HICP)—since it is planned to include owner‐occupied housing in the HICP using a transactions HPI specifically for new‐builds. We show that the timeliness issue disappears when preliminary agreements on new‐builds are used instead of transactions in the compilation of an HPI. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to examine income inequality in the process of economic growth and structural transformation with emphasis on the role of economic openness using a new measure of trade openness (the price convergence index [PCI]), which is an alternative measure to the widely used trade‐to‐GDP ratio. The analysis is based on a multi‐country panel data covering 48 countries for the period from 1960 to 2010. The results suggest that an increase in the share of employment in manufacturing is associated with a reduction in income inequality. This inequality‐reducing effect is significantly greater for countries with more open trade regimes. In addition, the Kuznets‐type relationship exists between services employment share and income inequality, with inequality first increasing with the movement of workers from agriculture to services and then decreasing. This inequality‐increasing effect of services employment share is also larger for countries with more open trade regimes. The findings withstand the inclusion of relevant explanatory variables, an alternative measure of income inequality, and alternative estimator to address possible endogeneity. [ABSTRACT FROM AUTHOR]

While asymmetric mixture models improve option pricing over generic pricing models, mispricing remains due to their inability to capture the effect of economic factors on price levels. This paper uses the hidden truncation normal (HTN) distribution introduced by Arnold et al. (1993) and the NGARCH model of Engle and Ng (J Finance, 48:1749–1778, 1993) to price options. Compared to the Black–Scholes model, the HTN -NGARCH option pricing model has extra parameters linked to economic dynamics and with economic interpretations. The model integrates some stylized facts underlying option prices such as a time-varying price of risk, non-normal innovations, asymmetry, and kurtosis. The model can be estimated by maximum likelihood. With an application to market data, we show that the HTN -NGARCH model accurately prices index options and captures adequately the smirk of implied volatility. [ABSTRACT FROM AUTHOR]

Objective To evaluate the impact of DRG medical insurance payment reform on the quality development of a tertiary comprehensive hospital in Guangxi. Methods This study selected data on all inpatient settlement cases in the hospital from 2020 to 2021, and calculated the DRG grouping of all cases according to the national CHS-DRG version 1.0 grouping plan. The interruption time series analysis method was further used to analyze the level and trend changes of indicators after the DRG policy reform in hospitals in December 2020.These indicators included total weight, case group index, cost consumption index, time consumption index, average length of stay, average hospitalization cost per visit, etc. They were used to evaluate the hospital' s medical service capacity, medical service efficiency, and medical safety, in order to understand the quality of the hospital. Results A total of 72 089 cases were included in this study. Indicators such as cost consumption index (β = -0.242, P = 0.001), time consumption index (β = -0.119, P = 0.002), average length of stay (β = -1.543, P = 0.011), proportion of high incidence cases (β = -0.028, P = 0.026), and average cost of hospitalization (β = -3 669.366, P = 0.026) showed an immediate decrease during the implementation of DRG policy. Conclusion After implementing the DRG policy reform, the hospital has significantly improved the efficiency of medical services, but still faces the challenge of adjusting structure and increasing quality. [ABSTRACT FROM AUTHOR]

This paper compiles a market-based price index by accounting for the impact of price regulation. We then use the parallel market exchange rate and market-based price index to test Purchasing Power Parity (PPP) over a more extended period (1952–2019) in China. We find weak evidence support PPP when official data are used. However, we fail to find evidence against PPP when the parallel market exchange rate and the market-based price index are used. Moreover, the half-life of the RMB real exchange rate is approximately one year, substantially lower than the consensus estimates of 3–5 years. [ABSTRACT FROM AUTHOR]

Despite the high recurrence rate of sigmoid volvulus, there is reluctance to perform a prophylactic colectomy in frail patients due to the operation's perceived risks. We used a nationally representative database to compare risk of recurrence in patients undergoing a prophylactic colectomy versus endoscopic detorsion alone. We performed a retrospective cohort study using the National Readmission Database (2016-2019) including patients aged ≥18 y who had an emergent admission for sigmoid volvulus and underwent endoscopic detorsion on the day of admission. We performed a 1:1 propensity matching adjusting for patient demographics, frailty score comprising of 109 components, and hospital characteristics. Our primary outcome was readmission due to colonic volvulus and secondary outcomes included mortality, complications, length of stay (LOS), and costs during index admission and readmission. We performed a subgroup analysis in patients with Hospital Frailty Score >5. We included 2113 patients of which 1046 patients (49.5%) underwent a colectomy during the initial admission. In the matched population of 830 pairs, readmission due to colonic volvulus was significantly lower in patients undergoing endoscopy followed by colectomy than endoscopy alone. Patients undergoing a colectomy had higher gastric and renal complications, longer LOS, and higher costs but no difference in mortality. In the subgroup analysis of frail patients, readmission was significantly lower in patients with prophylactic colectomy with no significant difference in mortality in 439 matched patients. Prophylactic colectomy was associated with lower readmission, a higher rate of complications, increased LOS, and higher costs compared to sigmoid decompression alone. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to discuss the simultaneous longitudinal and lateral flight control of the octorotor, a rotary wing unmanned aerial vehicle (UAV), for the first time under the effect of morphing and to improve autonomous flight performance. Design/methodology/approach: This study aims to design and control the octorotor flight control system with stochastic optimal tuning under morphnig effect. For this purpose, models of different arm lengths of the octorotor were drawn in the Solidworks program. The morphing was carried out by simultaneously lengthening or shortening the arm lengths of the octorotor. The morphing rate was estimated by using simultaneous perturbation stochastic approximation (SPSA). The stochastic gradient descent algorithm, which is frequently used in machine learning, was used to estimate the changing moments of inertia with the change of arm lengths. The proportional integral derivative (PID) controller has been preferred as an octorotor control algorithm because of its simplicity of structure. The PID gains required to control both longitudinal and lateral flight were also estimated with SPSA. Findings: With SPSA, three longitudinal flight PID gains, three lateral flight PID gains and one morphing ratio were estimated. PID gains remained within the limits set for SPSA, giving satisfactory results. In addition, the cost index created was 93% successful. The gradient descent algorithm used for the moment of inertia estimation achieved the optimum result in 1,570 iterations. However, in the simulations made with the obtained data, longitudinal and lateral flight was successfully carried out. Originality/value: Octorotor longitudinal and lateral flight control was performed quickly and effectively with the proposed method. In addition, the desired parameters were obtained with the optimization methods used, and the longitudinal and lateral flight of the octorotor was successfully carried out in the desired trajectory. [ABSTRACT FROM AUTHOR]

Construction prices rose rapidly during 2020 and 2021, making it almost impossible for contractors to adhere to agreed contract prices. For this reason, there was a request from contractors to adjust the contract price after signing a contract for work. During the implementation of the construction contracts, they were unable to comply with the fixed contract price. Forecasting the development of price indices could solve this problem by creating a reserve that would limit the adjustment of the contract price and the contractors' withdrawal from the contracts. The forecast could be enshrined in the contractual conditions before the start of construction, which would eliminate the risk of changing the agreed contract price for the investor and the possible occurrence of additional work. Data from statistical offices were used to create the price index forecast. In this article, four methods were used in the search for a more accurate forecast: regression analysis, exponential smoothing, the naïve method, and the Autoregressive Integrated Moving Average (ARIMA) model. From these methods, the most appropriate method was selected by multi-criteria decision-making, which was subsequently verified with actual published price index data. The main goals of this study are to determine the most suitable prognostic method for forecasting the development of the prices of construction materials and work and then comparing the forecasted data with the actual published data of statistical offices in the countries of Central Europe. [ABSTRACT FROM AUTHOR]

Over-budgeting due to inflation is a common phenomenon in the construction industry of both developed and developing countries. Inflation, with time changes, leaves an adverse effect on the project budget. Hence, this study aims to focus on the construction price index (CPI) behavior and inspect its correlation with inflation in Thailand's construction industry as there has not been much work performed. The prediction of CPI was made from 2024 to 2028, relying on the data set from 2000 to 2023. The relationship between inflation and CPI categories helps in prediction by considering inflation as the independent variable and CPI (All Commodities, Lumber and Wood Products, Cement, and Iron Products) as the dependent variable that was incorporated in EViews to perform automated ARIMA forecasting. The correlation results show that out of four CPI, only Iron Products showed a significant relationship with inflation. For All Commodities, Lumber, and Wood Products, the predicted values were fluctuating, while for Cement and Iron Products, a clear seasonal pattern was observed. This prediction gives a direction to construction industry practitioners to make necessary adjustments to their budget estimation before signing the contract to overcome cost overrun obstruction. [ABSTRACT FROM AUTHOR]

Most sovereign defaults are partial, with heterogeneous post-default outcomes, and commodity prices are an important determinant of sovereign default and the subsequent restructurings. In the case of emerging countries, as a result of direct dependence of government on revenues from commodity exports, declines in commodity prices reduce government's resources to service the external debt thereby increase the chances of default. In this paper, we construct a country-specific commodity price index with time-varying weights based on commodity exports to quantify the impact of commodity prices on the partial default rate measured by debt arrears. We show that declines in commodity prices have a significant, positive effect on the default rate. The overall predicted effects for a one-standard deviation decrease in a composite of the level and change of the price index at its 1st, 2nd, and 3rd quartile, on average, are 14.2, 12.5, and 9.3 percentage points respectively. We also show that for a country-specific one-standard deviation decrease in the composite price index, the predicted effect varies from insignificant to an increase of 33.8 percentage points. The country-specific effect on the default rate generally increases in magnitude with a country's dependence on commodity exports, while it depends heterogeneously on external indebtedness—increasing in magnitude for low levels (below a threshold of about 30 percent) of debt and decreasing thereafter. [ABSTRACT FROM AUTHOR]

Purpose: The Chinese housing market has gone through rapid growth during the past decade, and house price forecasting has evolved to be a significant issue that draws enormous attention from investors, policy makers and researchers. This study investigates neural networks for composite property price index forecasting from ten major Chinese cities for the period of July 2005–April 2021. Design/methodology/approach: The goal is to build simple and accurate neural network models that contribute to pure technical forecasts of composite property prices. To facilitate the analysis, the authors consider different model settings across algorithms, delays, hidden neurons and data spitting ratios. Findings: The authors arrive at a pretty simple neural network with six delays and three hidden neurons, which generates rather stable performance of average relative root mean square errors across the ten cities below 1% for the training, validation and testing phases. Originality/value: Results here could be utilized on a standalone basis or combined with fundamental forecasts to help form perspectives of composite property price trends and conduct policy analysis. [ABSTRACT FROM AUTHOR]

Under local protectionism, environmental regulation may harm market integration and create expensive domestic trade cost. After matching data of trade flows from Chinese Customs to A-listed enterprise, the Head–Ries trade cost index is used to measure domestic and international trade costs during 2003–2013. Then, the environmental information disclosure (EID) released in 2008 is introduced as a policy cutoff, and this article adopts the regression discontinuity in time model to explore its effects on trade costs. After a set of robustness tests, the results show that EID leads to significant discontinuities in trade costs, suggesting a 0.077 increase in domestic trade cost but a 0.222 decrease in international trade cost. Domestic market segmentation goes against internal circulation of commodities, and regulated enterprises alternatively enter international markets to seek scale economies. The further mechanism test applies the two-stage least squares model to investigate corporate strategy, and it proves that EID generates an overall decline in corporate productivity. After the exit of low-productivity enterprises, the market structure becomes more concentrated and remaining enterprises gain export competitiveness. However, corporate productivity fails to significantly reduce international trade cost, while the export scale of leading enterprises in high-concentrated market has an absolute advantage. [ABSTRACT FROM AUTHOR]

The growing demand and market penetration of electric vehicles (EVs) have led to an expansion in the size of the market for used EVs, accompanied by a continuous increase in the return rate of aging battery systems. Consequently, a second-hand market for aged battery systems, known as second-life batteries, is slowly emerging. Understanding this market is crucial for enabling a functioning circular economy for batteries. This paper analyzes the market mechanisms influencing price formation for used goods, drawing parallels to the largest second-hand market, the used car market, and applies them to the second-life battery market. By examining these mechanisms, insights are provided into the dynamics of the second-life battery market, facilitating the development of strategies to optimize resource utilization and sustainability in the EV industry. Finally, the second-life battery price index is introduced, increasing the transparency of prices for lithium-ion batteries and the circular economy. [ABSTRACT FROM AUTHOR]

This article presents a model agnostic methodology for producing property price indices. The motivation to develop this methodology is to include non-linear and non-parametric models, such as Machine Learning (ML), in the pool of algorithms to produce price indices. The key innovation is the use of individual out-of-time prediction errors to measure price changes. The data used in this study consist of 29,998 commercial real estate transactions in New York, in the period 2000–2019. The results indicate that the prediction accuracy is higher for the ML models compared to linear models. On the other hand, ML algorithms depend more on the data used for calibration; they produce less stable results when applied to small samples and may exhibit estimation bias. Hence, measures to reduce or eliminate bias need to be implemented, taking into consideration the bias and variance trade-off. [ABSTRACT FROM AUTHOR]

Traditional cost models ignore the internal structure of decision-making units (DMUs), so, may produce ambiguous outcomes and provide a biased assessment. In this paper, we evaluate the performance of the units by considering their internal structures. We proposed a new cost Malmquist index for measuring the cost productivity change of the units with bi-level structures. The bi-level structure is a special case of hierarchical structures with two levels, where the leader unit is positioned at the upper level and followers are located at the lower level. The overall system of bi-level units tries to use inputs and produce outputs in a costefficient way. However, each subunit performs according to its goals and limited resources. This research tries to develop a bi-level cost model that is suitable for measuring the cost efficiency of bi-level units. Based on this model, a new cost Malmquist index (CMI) is suggested to evaluate the productivity changes of bi-level units. This index presents a new aspect of CMI and provides the productivity changes of units by considering the impact of the leader's and the subunits' performance. In addition, similar to the traditional CMI, it decomposes into various components, such as cost efficiency changes and cost technological changes. The developed CMI is applied to a real-world case study to evaluate eight management regions which all together manage 198 branches. The results show that the proposed CMI provides a more meaningful evaluation of DMUs compared to the conventional CMI. [ABSTRACT FROM AUTHOR]

Trends in the transport and storage industry's labor markets in Europe have significantly impacted changes in labor costs. Technological advancements, increased privatization and deregulation, and changes in global capital flows are among the key reasons that have resulted in significant changes in labor costs in the logistics sector during the last few decades, especially in Europe. The amount of remuneration for logistics personnel and its pace of change over time are essential aspects influencing not just capital investment choices but also country competitiveness. The clusters of countries with similar wage increases over time are also impacted by their economic, social, and ecological problems to a similar extent. The existence of probable trends in labor costs in transport and storage on a country level, as well as cluster analysis over the countries where the trend is found, will aid in revealing significant similarities and contrasts concerning the sector and the countries involved in the research. The Labor Cost Index (LCI), according to NACE Rev. 2 Activity-nominal value, quarterly data released by Eurostat was utilized for this research. Sixty-four quarterly periods have been covered between the first quarter of 2007 and the fourth quarter of 2022. The research was based on data collected from 23 different European countries. The Mann-Kendall trend test and Sen's slope test were used for trend analysis, and the K-means clustering algorithm was used for cluster analysis. [ABSTRACT FROM AUTHOR]

Fiber reinforced polymer (FRP) reinforced ultra‐high‐performance concrete (UHPC) structural elements have become increasing popular in research and industry communities. In this paper, uniaxial tension tests were conducted to study the effects of fiber type, fiber length, and fiber content on tensile behavior of FRP grid reinforced UHPC plates (FGRUPs). Additionally, the microstructure analysis of specimens was conducted using scanning electron microscopy. Test results reveal that carbon FRP (CFRP) grid can substantially enhance the tensile performance of UHPC under tension: (1) the FGRUPs exhibit a post‐crack strain‐hardening behavior while the UHPC plates exhibit a post‐crack strain‐softening behavior; (2) the FRP grid enhances the cracking stress of UHPC specimens (except for plates with 1% basalt fibers) and the stiffness of the second segment of the stress–strain curve, and substantially enhances the ultimate tensile stress UHPC specimens. Also, the cost‐effectiveness analysis indicates that plates containing 1% of 12 mm length PE fibers have a highest cost efficiency index. Finally, a modified tensile stress–strain model for FGRUPs is proposed and verified. [ABSTRACT FROM AUTHOR]

Persimmons contribute positively to human health. Although off‐season utilization typically presents a challenge due to permissions' perishable nature, it may become feasible through the implementation of appropriate drying methods. In this study, round sliced samples were dried to assess drying kinetics, modeling potential, color attributes, rehydration capacity, energy consumption (EC), cost index, and thermal properties. The fruits were subjected to distinct drying methodologies including freeze‐drying, continuous infrared drying (300, 400, and 500 W), and intermittent infrared drying (PR = 1 [continuous], PR = 2 [30 s on–30 s off], and PR = 3 [20 s on–40 s off]). The duration of the drying process ranged from 40 to 390 min. It was determined that the most suitable models for depicting continuous and infrared drying kinetics of persimmon fruit were the Midilli et al. and Page models, whereas the Logarithmic model was identified as the optimal choice for characterization of freeze‐drying kinetics. Assessment of EC revealed that both intermittent and continuous infrared drying methods incurred lower energy expenditure in comparison to the freeze‐drying technique. Remarkably, throughout the course of the infrared drying processes, product surface temperatures varied between 106.33 and 22.65°C across different treatments. Despite its high EC, it has been found that high‐quality products are produced by freeze‐drying. However, infrared and intermittent infrared applications can be a low energy cost and feasible method for drying persimmon with a shorter duration. Practical Application: Persimmon is an important fruit with high nutritional value. However, as with many fresh products, they have a short shelf life. Within the scope of this research, three different drying methodologies were employed in the desiccation of persimmon specimens, and the impact of these methodologies on the overall qualitative attributes of the persimmon product was investigated. Despite its elevated energy consumption, the freeze‐drying approach was found to yield high‐quality products. Moreover, it was discerned that infrared drying represented a viable and expeditious alternative for drying the fruit, particularly when executed intermittently. [ABSTRACT FROM AUTHOR]

With inflation on the rise in recent years, there has been an important debate on price increases and their impact on different areas of the economy, politics, and society. This article analyzes different methods of statistical measurement of price increases at different stages of production and consumption, as well as inflation. It exemplifies, in particular, with cases from the United States and the Netherlands. It also points out some shortcomings in the methods applied, especially in neoclassical macroeconomic models. [ABSTRACT FROM AUTHOR]

The article provides information on the 2023 U.S. College Book Price Index which was compiled from reviews of books published in the journal during 2023. Topics discussed include the overall average price for books in the Humanities, Sciences, and Social & Behavioral Sciences, number of titles, dollar amounts, percentages, and average price for books in each subject category for 2023, and average price and indexing information for the years 2021 through 2023.

In this paper we extend the denominator rule for ratios given in different units of measurement and we explain how to derive the relevant aggregation shares, which are given in terms of the denominator variable and the constants converting the relevant variables into the same unit of measurement. [ABSTRACT FROM AUTHOR]

The HWWI Commodity Price Index, which aims at reflecting price developments of raw materials imported by highly industrialized countries, dates back to the 1950s. This paper explains the calculation of the index at the example of its latest revision, which became effective on 1st September 2023. While the index and its subindices are still calculated for OECD and European Momentary Union countries at four different frequencies (annual, monthly, quarterly and daily) for two different currencies (USD, EUR), it now additionally includes index values for several weighting periods (long-term: 2012–2021, pre-crisis: 2017–2019 and crisis years: 2020–2021), for individual countries and for different perspectives (daily revised, real-time and historical time series). The paper also provides detailed information on the employed methodology and the input data (commodities, import data, prices) used to calculate the weights and the index values. Although the revision is not without effect on the resulting index values, especially throughout the crises periods, the correlation between the initial and the revised index remains very high. [ABSTRACT FROM AUTHOR]

This research created an estimator for a near-real-time US truckload spot market price index. This work applied an ARX-GARCH model to assess freight volatility by incorporating explanatory variables in the mean-equation to address the sector-specific behavioural patterns. The results suggest that daily rate volatility can be better specified with such an extended version of standard GARCH. It was also observed the reduction of immediate shock effects in freight rate variation, especially when controlling for fuel surcharge and truck capacity. [ABSTRACT FROM AUTHOR]

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We explore the impact of geographic disaggregation of house price stress paths on single-family credit risk measurement. Specifically, we focus on the value added of moving from national, to state-level, to core-based statistical area (CBSA)–level house price paths on estimates of mortgage credit–related stress losses. To ensure the robustness of our results, we estimate losses across two different loan portfolios and three credit models. We find that CBSA-level paths provide additional insight on localized credit risk and can be reliably constructed using quarterly house price indices. Further, the variation in results across credit models suggests an implicit confidence interval around any one stress loss estimate. Accounting for this uncertainty through a model risk add-on could potentially offer a more conservative view of portfolio credit risk. [ABSTRACT FROM AUTHOR]

This paper focuses on the examination of the long-run relationship between money supply and selected national and global stock indices. Detailed knowledge of this relationship can be used by analysts, investors and monetary policy makers. Analysis of the relationship was performed using a 2-stage Engle-Granger cointegration. First, the stationarity of the time series was tested, then both the long-term OLS model and the short-term EC model were estimated. Time series were always tested on the longest period for which data were available. The long-term dependence of stock indices on the respective M2 was confirmed for the BOVESPA, FTSE100, S&P/BMV IPC, S&P BSE500, TSX and The 5000 Wilshire Small Cap Price Return indices. In contrast, the dependence between world money supply indicator GlobalM2, the stock index FTSEALL World, and the S&P500 index was not demonstrated. Additionally, no dependence was identified between the respective M2 and the DAX, PX, Nikkei225, KOSPI, SMI, SPCITIC300, Eurostoxx50, Willshire5000PR and ATX indices. Backward dependence of M2 on the stock index was found only for the Chinese SPCITIC300 index. [ABSTRACT FROM AUTHOR]

There is no consensus in the economics theory about the determinants of household saving. The article composes vector error correction (VEC) models to identify the determinants of household saving in the East Central European countries from 2005–2020. Its novelty is that it identifies push and pull factors in accordance with the Keynesian and neoclassical theories whose mixed approach has not been included in the methodology of relevant papers in relation with East Central European countries. The examined countries are indicated to be homogenous from macroeconomic perspective. Results confirm that household saving increases because of decreases in consumer confidence, unemployment, and inflation rates. Increases in the deposit rate and real house price index are related to these pull factors, while decreases in the official share index correlates withincreases in household saving. Results can serve as guidelines for policy makers about incentives which stimulate household saving most effectively in the region. [ABSTRACT FROM AUTHOR]