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We exploit a city-level panel comprised of individual house price estimates to estimate the impact of COVID-19 on both small and big real-estate markets in California USA. Descriptive analysis of spot house price estimates, including contemporaneous price uncertainty and 30-day price change for individual properties listed on the online real-estate platform Zillow.com, together facilitate quantifying both the excess valuation and valuation confidence attributable to this global socio-economic shock. Our quasi-experimental pre-/post-COVID-19 design spans several years around 2020 and leverages contemporaneous price estimates of rental properties – i.e., off-market real estate entering the habitation market, just not for purchase and hence free of speculation – as an appropriate counterfactual to properties listed for sale, which are subject to on-market speculation. Combining unit-level matching and multivariate difference-in-difference regression approaches, we obtain consistent estimates regarding the sign and magnitude of excess price growth observed after the pandemic onset. Specifically, our results indicate that properties listed for sale appreciated an additional 1% per month above what would be expected in the absence of the pandemic. This corresponds to an excess annual price growth of roughly 12.7 percentage points, which accounts for more than half of the actual annual price growth in 2021 observed across the studied regions. Simultaneously, uncertainty in price estimates decreased, signaling the irrational confidence characteristic of prior asset bubbles. We explore how these two trends are related to market size, local market supply and borrowing costs, which altogether lend support for the counterintuitive roles of uncertainty and interruptions in decision-making. [ABSTRACT FROM AUTHOR]

In anticipation of price hikes and shortages caused by supplier disruptions and manufacturer production stops, customers might stockpile extra products. In the case of a supplier disruption, a manufacturer may decide to continue producing using a contingent source. Capturing the price dynamics in four disruption-related periods (i.e., responding, rising, recovering, and recovered), we derive optimal hoarding policies for customers. The results indicate that customer hoarding decisions fall into multiple patterns depending on the interactions between disruption events, market responses (quick and slow), and market recovery (instant, quick, slow, and never). We next present contingent sourcing tactics for manufacturers to mitigate disruptions with and without customer hoarding. We find that future price increases could induce contingent sourcing even if it is unprofitable to resume production during the price-responding phase. Our results offer recommendations regarding when and how to use hoarding and contingent sourcing accounting for uncertain disruption duration and asymmetric information along with disruption- and recovery-driven price dynamics. These recommendations can be of particular value for supply chain decision-making at times of growing inflation. We also demonstrate the impacts of customer hoarding and disruption information on the value of contingent sourcing. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the impact of short-stay accommodation (SSA) on housing dynamics, community welfare, and economic development in the Margaret River regional area. Grounded in an exploratory research paradigm, qualitative methods were used to gather insights from key stakeholders such as property owners, realtors, and council officials. Purposive sampling was utilized to select participants with diverse experiences and perspectives on SSA. Semi-structured interviews were conducted, totaling 21 interview sessions spanning almost 600 min, to capture in-depth and nuanced perspectives on SSA's impact and regulatory landscape. Thematic analysis of the interview data, which was divided into two segments, revealed significant concerns regarding housing affordability, community well-being, and regulatory effectiveness. Additionally, the study uncovered a complex relationship between SSA and population dynamics, highlighting implications for the local housing infrastructure and market stability. The findings underscore the urgency of collaborative policy interventions to address the housing crisis and mitigate the adverse effects of SSA on local communities. Policymakers and stakeholders can utilize these insights to develop holistic strategies that prioritize equity, inclusivity, and shared prosperity in shaping the future of housing in regional areas such as Margaret River. This study contributes original insights by providing a nuanced understanding of the multifaceted implications of SSA on housing dynamics and community welfare in a regional context. By using qualitative methods and engaging key stakeholders, the research offers unique perspectives on the challenges and opportunities associated with the proliferation of SSA, thereby advancing scholarly discourse, and informing evidence-based policymaking in the field of housing studies. [ABSTRACT FROM AUTHOR]

Abstract We exploit a city-level panel comprised of individual house price estimates to estimate the impact of COVID-19 on both small and big real-estate markets in California USA. Descriptive analysis of spot house price estimates, including contemporaneous price uncertainty and 30-day price change for individual properties listed on the online real-estate platform Zillow.com, together facilitate quantifying both the excess valuation and valuation confidence attributable to this global socio-economic shock. Our quasi-experimental pre-/post-COVID-19 design spans several years around 2020 and leverages contemporaneous price estimates of rental properties – i.e., off-market real estate entering the habitation market, just not for purchase and hence free of speculation – as an appropriate counterfactual to properties listed for sale, which are subject to on-market speculation. Combining unit-level matching and multivariate difference-in-difference regression approaches, we obtain consistent estimates regarding the sign and magnitude of excess price growth observed after the pandemic onset. Specifically, our results indicate that properties listed for sale appreciated an additional 1% per month above what would be expected in the absence of the pandemic. This corresponds to an excess annual price growth of roughly 12.7 percentage points, which accounts for more than half of the actual annual price growth in 2021 observed across the studied regions. Simultaneously, uncertainty in price estimates decreased, signaling the irrational confidence characteristic of prior asset bubbles. We explore how these two trends are related to market size, local market supply and borrowing costs, which altogether lend support for the counterintuitive roles of uncertainty and interruptions in decision-making.

The information base of the study is the time series of the daily exchange rate of the currency pair USD/JPY, the US 10-year Treasury bond (TB 10), the Japanese government bond 10-year (JGB 10), the volatility index (VIX) of the Chicago Board Options Exchange (CBOE), which calculated by Bloomberg. Study period: December 1, 2015 (the date the Federal Reserve raised interest rates, which initiated a new regime - began easing its ZIRP zero interest rate policy) to December 29, 2023. The relationship between monetary policy and the currency pair USD/JPY is evaluated using 3 approaches: 1) a rally dynamic system based on the standard theory of nonlinear differential equations aimed at eliminating psychological noise (1/f noise, pink noise, trend noise with spectrum capacity); 2) regression of instrumental variables with heteroskedasticity aimed at managing unobservable sources of variability; 3) an event tracking method to measure anomalous asset price response, analyzing the daily price action of USD/JPY to detect market-related fluctuations in the exchange rate and separate the impact of general market trends from related differences in interest rates. The study found that the US Federal Reserve's (Fed’s) monetary policy only occasionally affects the USD/JPY exchange rate, and it changes mainly when monetary policy deviates from expected future trajectories. Within the studied period, this happened only 3 times: growth on December 16, 2015; emergency rate reduction due to COVID-19 on March 15, 2020; and the first increase of 75 basis points on June 15, 2022 (the article estimates the impact of each of these episodes on the exchange rate). Statements by the Fed on monetary policy affect the price dynamics of the USD/JPY pair in the short term (since short-term psychological expectations play a decisive role in shaping the dynamics of the currency market), but not often (if the statement on monetary policy is consistent with market forecasts, it is practically will not affect exchange rates). The Fed’s adoption of tools such as "forward guidance" and official statements to inform the future course of monetary policy indirectly affects the price dynamics of USD/JPY. The price action of USD/JPY was driven by the fundamentals of the difference in interest rates between the US and Japanese bonds, which are influenced by the monetary policy of the US Federal Reserve and the Bank of Japan (BoJ). In 2023, it could be hard to attempt to challenge FX intervention except to curb “excess volatility and disorderly movements in exchange rates” like the Minister of Finance’s (MoF) 2022 intervention.

We combine nonparametric price response modeling and dynamic pricing. In particular, we model sales response for fast-moving consumer goods sold by a physical retailer using a Bayesian semiparametric approach and incorporate the price of the previous period as well as further time-dependent covariates. All nonlinear effects including the one-period lagged price dynamics are modeled via P-splines, and embedding the semiparametric model into a Hierarchical Bayesian framework enables the estimation of nonlinear heterogeneous (i.e., store-specific) immediate and lagged price effects. The nonlinear heterogeneous model specification is used for price optimization and allows the derivation of optimal price paths of brands for individual stores of retailers. In an empirical study, we demonstrate that our proposed model can provide higher expected profits compared to competing benchmark models, while at the same time not seriously suffering from boundary problems for optimized prices and sales quantities. Optimal price policies for brands are determined by a discrete dynamic programming algorithm. [ABSTRACT FROM AUTHOR]

The study investigates the effect of price support policies on market price distribution and its dynamics in the Indian wheat market. The analysis uses a quantile autoregression model that provides a flexible representation of price dynamics and the 2001–2020 monthly wholesale market price data. The analysis is conducted conditional on the net stock level held in the previous period. The results reveal that the net purchase by the government prevented very low market prices for wheat but resulted in price spikes. It has a price‐enhancing effect as well. The associated moments of price distribution show that public stockholding reduced variation in market price distribution. However, the government's release of stock did not prevent price rises. Findings show that dynamic adjustments tend to be qualitatively different across regimes. Government intervention in the grain market reduced stability through dynamic adjustments in wheat market prices. The results have policy implications for India and other countries in Southeast Asia in the context of the WTO's negotiations on public stockholdings and using public stockholdings as an instrument in addressing price volatility and food shortages. [ABSTRACT FROM AUTHOR]

The European fruit and vegetable (F&V) trade regime is regulated by the Entry Price System (EPS), a nontariff measure on imported goods. We investigate the trade effects of the EPS by estimating a structural gravity model for the major European suppliers of apples, lemons, oranges, peaches, pears, table grapes, and tomatoes. We assess how imports react to EPS overshoots, and price dynamics. The EPS limits imports, but marked differences exist across products. The efficacy of the EPS is valid for all products; its effectiveness is found only for less perishable F&Vs. [ABSTRACT FROM AUTHOR]

This research explores changes in staple food price trends and their impact on the Farmers' Term of Trade (FTT) as a primary indicator of farmer prosperity. Utilizing secondary data analysis, the study processes monthly staple food price data from January 2018 to July 2023 and FTT data from January 2019 to July 2023. This analysis employs a coefficient of variation method to track food price changes and calculates the FTT value based on the comparison of the price index received by farmers to their expenses, serving as a marker of farmer welfare. The study's findings reveal a significant influence of food price alterations on FTT and farmer welfare. There is a marked difference in the dynamics of staple food prices and FTT across various regions in Indonesia. These price variations are influenced by changes in agricultural input costs, such as fertilizers and labor wages, impacting the FTT value. Sectoral analysis indicates that during the Covid-19 era, food crop farmers have a lower level of prosperity (>100) during the pandemic. This study highlights the importance of farmers' understanding and adaptation to the dynamics of food prices and FTT. Adaptation strategies may include changes in production strategies, government support, crop diversification, and the adoption of new technologies, even amidst external challenges such as climate change. The interaction between food price dynamics, FTT, and its relation to farmer welfare provides essential insights for formulating more effective policies to support farmer welfare and food security in Indonesia.

This study aimed to investigate the impact of short-stay accommodation (SSA) on housing dynamics, community welfare, and economic development in the Margaret River regional area. Grounded in an exploratory research paradigm, qualitative methods were used to gather insights from key stakeholders such as property owners, realtors, and council officials. Purposive sampling was utilized to select participants with diverse experiences and perspectives on SSA. Semi-structured interviews were conducted, totaling 21 interview sessions spanning almost 600 min, to capture in-depth and nuanced perspectives on SSA’s impact and regulatory landscape. Thematic analysis of the interview data, which was divided into two segments, revealed significant concerns regarding housing affordability, community well-being, and regulatory effectiveness. Additionally, the study uncovered a complex relationship between SSA and population dynamics, highlighting implications for the local housing infrastructure and market stability. The findings underscore the urgency of collaborative policy interventions to address the housing crisis and mitigate the adverse effects of SSA on local communities. Policymakers and stakeholders can utilize these insights to develop holistic strategies that prioritize equity, inclusivity, and shared prosperity in shaping the future of housing in regional areas such as Margaret River. This study contributes original insights by providing a nuanced understanding of the multifaceted implications of SSA on housing dynamics and community welfare in a regional context. By using qualitative methods and engaging key stakeholders, the research offers unique perspectives on the challenges and opportunities associated with the proliferation of SSA, thereby advancing scholarly discourse, and informing evidence-based policymaking in the field of housing studies.

A core research area of computational behavioral finance investigates emergent price dynamics when heterogeneous traders follow a mix of rule-based strategies and interact indirectly through a limit order book. This paper offers a detailed specification of such a model in order to raise questions about some previous findings. The questions force a comprehensive reconsideration of the price dynamics of a well-known model. This leads to a surprising clarification of the contributions of various trading strategies to market outcomes: a popular characterization of chartism proves largely irrelevant for price dynamics. We also shed new light on the volume-volatility relationship, and provide improved visualizations to expose market behavior. [ABSTRACT FROM AUTHOR]

Causal flow analyses combined with time series analyses are used to examine price relationships among fresh broiler retail markets (Northeast, South, Midwest, and West). Results indicate structural changes have occurred in this industry. Reasons for changes in price relationships include the perishable nature of fresh broilers, along with vertical integration and increases in production and concentration in the industry. The four markets are integrated, but the level of integration has decreased over time. With the markets becoming more exogenous, there may be a decrease in society's welfare. The South market is the most important market for price discovery. [ABSTRACT FROM AUTHOR]

We explore the synergic interplay between entropy (disorder), predictability, and informational efficiency of the daily closing price time series of 13 sectoral economics components of the Shanghai index letter considering three non-overlapping periods (before and during COVID-19 and Russia–Ukraine war). Our findings reveal that the telecom services, financials, and consumer discretionary sectors are marked by higher informational efficiency. Otherwise, the industrials, utilities, and transportation sectors exhibit lower informational efficiency. These insights are relevant for financial agents to make informed decisions, manage risk, and seek opportunities in an ever-changing market environment. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Economia e Sociologia Rural is the property of Sociedade Brasileira de Economia e Sociologia Rural and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The price of red chilies in surplus and deficit areas in Indonesia is interrelated because an excess supply of red chilies in surplus areas can affect prices in deficit areas and vice versa. The study wants to provide information on the shape of price dynamics and price relationships between surplus and deficit markets. Using red chili price data for the weekly period from January 2019 to December 2021. The price of red chilies in the East Lombok market, West Nusa Tenggara Province (WNT) is a surplus area, and Kupang City, East Nusa Tenggara Province (ENT) is a deficit area. Data source from the National Strategic Food Price Information Center released by Bank Indonesia. Data were analyzed using the coefficient of variation (CV) and the Vector Error Correction Model (VECM) method. The study found that there are significant differences in price dynamics and there are price linkages in both the short and long term between markets in surplus and deficit areas. The differences in geography, distance, marketing infrastructure, and market information systems also contribute to price linkages between markets in surplus and deficit areas. Collaboration between market players, the government, and accurate and easily accessible market information is required to create effective price linkages throughout Indonesia.

Purpose: During the ongoing COVID-19 pandemic, many branches of the world's economies were negatively affected by the pandemic. The purpose of this study is to see if the coronavirus had a negative impact on the price dynamics of undeveloped land property using Polish suburban areas as an example. Method: 945 transactions from 3 localities in the West Pomeranian Voivodeship over the period 2015 - 2021 were used for the study. The data was divided into quarters and the median was calculated, then a linear model was estimated. At the end, in order to check whether there is seasonality in the real estate market, the non-parametric Kendall's consistency test was used. Results: The results indicate that the SARS-CoV-2 virus did not have a negative impact on the price dynamics of undeveloped real estate for single-family housing. [ABSTRACT FROM AUTHOR]

This paper presents empirical evidence of the potential impact of the COVID-19 pandemic on the price structure and dynamics within two food value chains. Different proxies are applied to high-frequency panel data of beef and poultry prices in Iran. Results show that during the COVID-19 pandemic increased markups are associated with reduced cost pass-through along the value chains of beef and poultry in Iran. The results indicate that the COVID-19 pandemic induces market frictions on the supply and demand side, which decreases market performance. [ABSTRACT FROM AUTHOR]

Using data collected from an experimental double auction market, we study the dynamics of interaction among traders. Our focus is on the effect the trading network has on price dynamics and price-fundamental convergence. At the aggregate level, the network of empirical exchanges reveals properties that are dissimilar from random graphs and, in particular, high centrality and high clustering. Precisely, these properties are identifiable as the cause of price volatility and divergence from the fundamental value. At the microscopic level, we find out how the topological properties of the network derive from the behavior of traders. In fact, our findings show that it is the unbridled trading action of very centralized players who implement a minority game, to give rise to volatility clustering and arbitrage opportunities. [ABSTRACT FROM AUTHOR]

The European carbon emission trading market is the largest and most mature market, while China's carbon market has a short history. Institutionally, cross-market transaction is infeasible between the two markets. This paper investigates the long-run trend between the two markets as well as the price dynamics. Results show that a long-run trend exists between the Chinese and European carbon markets. Both markets possess self-correction capability in reducing price deviations, signaling a certain level of market efficiency. However, both markets also exhibit pricing inefficiency as historical price movements are able to impact prices. The European market informationally leads the Chinese market. Policy implications are that China should further upgrade its information disclosure system, such as unifying information disclosure standards across industries, and further develop its carbon derivatives markets to improve market transparency and market competition. [ABSTRACT FROM AUTHOR]

By observing the actual movement of asset prices, we find that there is a persistent shock impact of jumps on prices rather than a transient effect. To address this phenomenon, we propose a new jump-diffusion model that restores the process of price by assuming that its continuous changes are determined by the diffusion process, while individual jumps are inscribed by a filtered Poisson process. We also come up with estimation methods for the parameters involved in the jump process, as well as methods for identifying jumps and determining the duration of the transit impact of jumps based on the actual price series. In terms of simulations, the consistency of the estimation results is verified in detail. Finally, we select two representative indexes in the China's stock market as empirical objects. We build the price models, perform jump tests and parameter estimation for them, and compare the results with that of the traditional multi-sample BN-s to demonstrate the validity and robustness of the proposed models and estimation methods. [ABSTRACT FROM AUTHOR]

As a major share expenditure for the poor, rice is attributed as a strategic food commodity in the Indonesian economy. For many decades, the Indonesian rice market has been intervened by the price regulation. The Indonesian government had set two types of rice price policies of 2016 and 2017 with the argument of price stabilization during the last five years. This study aimed to investigate the effect of price policies of 2016 and 2017 on the domestic price dynamics in the Indonesian rice market. This study used daily price series taken from the Cipinang Wholesale Rice Market in Jakarta within the period of October 1st, 2014, until February 12th, 2018 covering 10 rice varieties. The role of price policy on the price dynamics was evaluated by using a multivariate error correction model (MVECM). The empirical findings confirmed that generally, these price policies had different effects on the price dynamics which proposed different reactions from the different rice varieties both in magnitude and signs. The variations were also found regarding the short-run and long-run behavior. Generally, the findings suggested a relatively small elasticity of the policy on the prices.

Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Recent research in cryptocurrencies has considered the effects of the behavior of individuals on the price of cryptocurrencies through actions such as social media usage. However, some celebrities have gone as far as affixing their celebrity to a specific cryptocurrency, becoming a crypto-tastemaker. One such example occurred in April 2021 when Elon Musk claimed via Twitter that “SpaceX is going to put a literal Dogecoin on the literal moon”. He later called himself the “Dogefather” as he announced that he would be hosting Saturday Night Live (SNL) on 8 May 2021. By performing sentiment analysis on relevant tweets during the time he was hosting SNL, evidence is found that negative perceptions of Musk’s performance led to a decline in the price of Dogecoin, which dropped 23.4% during the time Musk was on air. This shows that cryptocurrencies are affected in real time by the behaviors of crypto-tastemakers.

This paper finds strong support for a Phillips curve that becomes nonlinear when inflation is “low”—which our baseline model defines as less than 3 percent. The nonlinear curve is steep when output is above potential (slack is negative) but flat when output is below potential (slack is positive) so that further increases in economic slack have little effect on inflation. This finding is consistent with evidence of downward nominal wage and price rigidity. When inflation is high, the Phillips curve is linear and relatively steep. These results are robust to placing the threshold between the high and low inflation regimes at 2, 3, or 4 percent inflation or for a threshold based on country-specific medians of inflation. In this nonlinear model, international factors play a large role in explaining headline inflation (albeit less so for core inflation), a role that has been increasing since the global financial crisis. These results provide evidence of channels which could boost inflation in the future, even if they were dormant before the Covid pandemic.

Virtual cross-border medical tourism allows many residents in the United States to purchase brand name medicines from companies in Mexico without travelling there. Monthly economic reports indicate that the online brand name pharmaceutical product prices in Mexico are noticeably lower than the corresponding internet prices in the United States. There have been very few econometric studies on how these prices are linked and the dynamic nature of those relationships. Results in this study indicate that online medicine prices in Mexico respond very rapidly to online prices changes in the high-price market. [ABSTRACT FROM AUTHOR]

The main issue of the article is the impact of the recent inflation rate and price dynamics at the subsistence level in Georgia. It clarifies how the situation changed by the COVID-19 pandemic and the processes that developed as a result, how it affects the living standards of each citizen, employment and income. The paper comprehensively analyzes the main causes of inflation for Georgia as an import-dependent country, supply-side delays and sharply increased price dynamics in the international commodity market. Based on results received in the scope of research there are given conclusions and recommendations. The COVID-19 pandemic has become the biggest challenge of the 21st century not only for the healthcare system but also for the economies of each country and the world in general. Challenges in different sectors of the economy are also compounded by the significant increase in consumer price inflation globally, which has the greatest impact on the living standards of each citizen. Over the past several millennia unprecedented global inflationary pressures have been recorded in the world, which is having a very severe impact on the economies of developing countries in particular. It should be mmentioned that Georgia is an import-dependent country, both for food raw materials and fuel, respectively, the main drivers of inflation, disruption of supply chains and sharply increased prices in the international commodity market, which have a major impact on local consumer prices. It should also be noted that the process of economic recovery has begun, which, through strong fiscal stimulus, credit assets and accumulated excess savings, is putting upward pressure on prices, which greatly complicates the economic picture in the country. In April 2022, compared to the previous month, the inflation rate in Georgia was 1.8%, and the annual inflation rate, much higher than the target of 3%, was 12.8%. As for core inflation, this figure was 5.0% in April 2022 compared to the same period last year, while the annual core inflation rate was set at 5.7%. Compared to the same period last year, prices increased significantly in the subgroups of food and non-alcoholic beverages (21.3%) and transport (22.4%), which are essential products / services for every citizen and are directly reflected in their standard of living. It is also noteworthy that in the consumer basket of Georgia, the weight of food and non-alcoholic beverages occupies the largest place and is equal to 33.09%, of which 30.23% comes from food. In the food and non-alcoholic beverages group, we see a 21.3% increase in prices compared to the same month last year, which was reflected in 6.77% points of annual inflation. Prices are significantly higher for each product in this group. Alongside the alarming numbers of inflation, the picture is very grim for the subsistence level. According to the data published by the National Statistics Office, in April, the subsistence level for men of working age was 241.0 GEL, which is 2.8 GEL more than the previous month, and the average subsistence level was 213.5 GEL, which is 2.5 GEL more than the previous month. It should also be noted that according to 2020 data, the share of the population below the absolute poverty line is 21.3%, and if we take into account the high level of inflation after 2020, unfortunately, the probability of an increase in the percentage is very high. What about the average nominal salary of hired employees, it increased by 11.3% and amounted to 1463.8 GEL, which is 149.1 GEL more than the previous year, and as for the employment rate, in the IV quarter of 2021, the unemployment rate in Georgia decreased by 1.4 percentage points compared to the same period last year and amounted to 19.0%. However, it is also necessary to take into account that these salaries are calculated by means of arithmetic mean, which does not mean that one employee receives 1463.8 GEL per month, moreover, the current socio-economic environment, based on in-depth observations, allows us to assume that for most employees, monthly the nominal wage reaches a much lower mark. At the same time, it is necessary to take into account the purchasing power of money, without which taking into account the increase in pay is absurd, nor does it allow us to say whether the pay for employees has really increased or not. For this it is necessary to take into account two specific indicators, namely:  How has the employee's nominal income changed?  How has the level of consumer prices (inflation) changed in the country? It should be noted that this figure also includes income tax, except for which the average monthly nominal salary is equal to 1171 GEL. Everyone agrees that the main drivers of inflation are supply disruptions and sharply increased prices in the commodity market, which have a major impact on local consumer prices. At the same time, there is a growing fiscal stimulus in the process of economic recovery through the channel of credit assets and accumulated excess savings, which is an additional contributing factor to price growth. It is well known that since 2009, the National Bank of Georgia has been conducting monetary policy in the mode of inflation targeting. This means that it determines the target, annual rate of inflation. As it is known for 2019-2022, the inflation target was set at 3%. It should also be noted that monetary policy transmission mechanisms do not work in all countries, therefore the inflation targeting regime is not used everywhere. Moreover, for developing countries, it is the cause of challenges such as fiscal deficit, fiscal dominance, high dollarization, and most importantly, high inflation, with corresponding high fluctuations that take a very long time to balance. According to the latest data for April 2022, the annual inflation rate was set at 12.8%. According to an economics expert, Vladimer Papava, all this indicates that the targeting regime in Georgia is not working, that the central bank has no mechanism to regulate inflation due to rising costs, which is the source of additional economic problems. The President of the National Bank of Georgia has a completely different position, arguing that the general rise in prices is caused by the global economic crisis and has nothing to do with the effectiveness of monetary policy within the country. The fact is that the general increase in prices in Georgia began in the summer of 2019 and according to today's data has almost exceeded the target four times, which for me personally, as a researcher, further supports the opinion of Mr. Vladimer Papava. Consequently, several causes of inflation can be distinguished. First, it is the ineffective monetary policy in the country, more specifically the existence of a targeting regime, which further aggravates the economic situation in the country. On the other hand, supply disruptions and sharply increased prices in the international commodity market, which have the greatest impact on the growth of local consumer prices. The high level of public expectations of inflation, the Ukraine war has raised long-term inflation expectations. For the global economy, Russia and Ukraine are important suppliers of raw materials such as energy, metals, and agricultural products. The war has called into question the supply of these resources and accelerated their price development. The problem is complex, no one disputes the fact that the main goal of the state should be to pursue an economic, fiscal and monetary policy that ensures a stable rate of inflation. Against the background of the alarming figures presented above, it is necessary to work in several areas, including: strengthening the mechanisms of the basic system, promoting the development of the real sector of the country's economy (industry, agriculture, etc.), lowering inflation expectations, reducing budget deficits, long-term monetary policy and more. [ABSTRACT FROM AUTHOR]

We aim to evaluate two different econometric screens for identifying anti-competitive behavior in the fuel retail market: (i) The Markov-Switching GARCH (MS-GARCH) Models; (ii) The Local Gaussian Correlation (LGC) approach. Using the gasoline cartel judged and condemned in Brasília as a benchmark, our results indicate that the LGC model, based on the correlation of the resale price margin and price variability, may provide a biased likelihood as well as an incorrect identification of cartel behavior over time. The MSGARCH model, based only on the log deviation of the average gasoline sales price, showed better accuracy in cartel detection.

During the last years, cryptocurrencies have been increasingly becoming a relevant subject of academic researchers and investors. This paper adopts a novel framework that combines a multivariate Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) and Copula modeling in a two-stage approach to analyze the cryptocurrency volatility dynamics. By combining the aforementioned techniques, on top of showing that price movements in one cryptocurrency can significantly influence others, the use of copulas highlight how these effects can vary across different parts of distributions and thus for different types of events with respect to their extreme nature. The interconnectedness complexity should be taken into consideration when managing risk in portfolio and constructing relevant models. • Cryptocurrencies are characteristic by high levels of volatility. • This paper adopts a novel framework to analyze the cryptocurrency volatility. • The results show that large cryptoassets are highly interconnected. • Diversification in such setting is highly challenging. • Investor needs to explore more risky and less liquid avenues to manage their portfolio. [ABSTRACT FROM AUTHOR]

This paper analyses the explanatory power of the frequency of abnormal returns in the FOREX over the period 1994–2019. The following hypotheses are tested: frequency of abnormal returns is asignificant driver of price movements (H1); it does not exhibit seasonal patterns (H2); it is stable over time (H3). For our purposes avariety of statistical methods are applied including ADF, PP and KPSS tests, Granger causality tests, correlation analysis, regression analysis, Probit and Logit regression models. No evidence is found of either seasonal patterns or instability. However, there appears to be astrong positive (negative) relationship between returns in the FOREX and the frequency of positive (negative) abnormal returns. On the whole, the results suggest that the latter is an important driver of price dynamics in the FOREX, is informative about crises and can be the basis of profitable trading strategies, which is inconsistent with market efficiency.

The European carbon emission trading market is the largest and most mature market, while China’s carbon market has a short history. Institutionally, cross-market transaction is infeasible between the two markets. This paper investigates the long-run trend between the two markets as well as the price dynamics. Results show that a long-run trend exists between the Chinese and European carbon markets. Both markets possess self-correction capability in reducing price deviations, signaling a certain level of market efficiency. However, both markets also exhibit pricing inefficiency as historical price movements are able to impact prices. The European market informationally leads the Chinese market. Policy implications are that China should further upgrade its information disclosure system, such as unifying information disclosure standards across industries, and further develop its carbon derivatives markets to improve market transparency and market competition.

This study delves into the supply chain intricacies of chili in Yogyakarta, a major determinant in recent inflation trends. Utilizing a quantitative approach, data were garnered from 53 key stakeholders encompassing farmers, traders, and auction market managers. The chili supply chain was delineated into four principal stages: farmers, assembly points, auction markets, and traders, underpinning three core flows - product, monetary transactions, and information dissemination. Noteworthy findings highlight an exemplary performance of the chili supply chain, marked by high responsiveness, agility, and commendable asset management efficiency. Interestingly, an intertwined price dynamic was observed: the Yogyakarta auction market's chili prices mirror those of the Jakarta market, and vice versa. The implications of these insights can be pivotal for devising strategies to ensure price stability and bolstering food security, emphasizing the potential role of auction markets as integral mechanisms in stabilizing commodity prices.

This paper finds strong support for a Phillips curve that becomes nonlinear when inflation is "low"-which our baseline model defines as less than 3 percent. The nonlinear curve is steep when output is above potential (slack is negative) but flat when output is below potential (slack is positive) so that further increases in economic slack have little effect on inflation. This finding is consistent with evidence of downward nominal wage and price rigidity. When inflation is high, the Phillips curve is linear and relatively steep. These results are robust to placing the threshold between the high and low inflation regimes at 2, 3, or 4 percent inflation or for a threshold based on country-specific medians of inflation. In this nonlinear model, international factors play a large role in explaining headline inflation (albeit less so for core inflation), a role that has been increasing since the global financial crisis. These results provide evidence of channels which could boost inflation in the future, even if they were dormant before the Covid pandemic. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic that hit the world economy at the end of 2019 had a strong impact on the significant economic issues at global and national level. This paper presents how this phenomenon has influenced price dynamics. This article proposes a comparative study between 2019 and 2020 regarding the change in the inflation rate in Romania, as well as the causes that led to it. [ABSTRACT FROM AUTHOR]

Recent research in cryptocurrencies has considered the effects of the behavior of individuals on the price of cryptocurrencies through actions such as social media usage. However, some celebrities have gone as far as affixing their celebrity to a specific cryptocurrency, becoming a crypto-tastemaker. One such example occurred in April 2021 when Elon Musk claimed via Twitter that "SpaceX is going to put a literal Dogecoin on the literal moon". He later called himself the "Dogefather" as he announced that he would be hosting Saturday Night Live (SNL) on 8 May 2021. By performing sentiment analysis on relevant tweets during the time he was hosting SNL, evidence is found that negative perceptions of Musk's performance led to a decline in the price of Dogecoin, which dropped 23.4% during the time Musk was on air. This shows that cryptocurrencies are affected in real time by the behaviors of crypto-tastemakers. [ABSTRACT FROM AUTHOR]

Wheat is an integral part of food as well as nutrition security holding a significant share in the consumption basket. Hence, any extreme deviations in the staple food price will affect the prospects of the economy. In the context, we analysed the price dynamics and price volatility in Indian wholesale wheat markets using compound annual growth rate, instability indices, and Generalised Autoregressive Conditional Heteroscedasticity (GARCH) model. The study sourced monthly data (July 2002 to June 2019) from the AGMARKNET portal for 15 states. Research findings indicated that the wholesale price, as well as divergence between maximum and minimum price, was highest in the case of Kerala implying the non-production region. Monthly price indices (highest as well as lowest in Haryana respectively during December: 109.90 and July: 91.48) exhibited a clear-cut seasonality attributed to the wheat arrivals post-crop harvest. Barring Maharashtra, the growth and variation in seasonal price indices were positive and relatively low respectively across markets. Corroborating the price trend, Kerala exhibited the highest volatility as evident by the GARCH model estimates, followed by Gujarat, Haryana and Chhattisgarh. Inter alia, volatility in wheat prices is directly linked to regional production. The study advocates for effective dissemination of market information such as price forecast, demand and supply to counter the price volatility as well as decision making for profitable agri-business.

Since nominal interest rate and nominal exchange rate are common for the Euro-zone (EZ) members, inflation differentials initiate real interest rate and real exchange rate divergences with further spill-over effects. The aim of the research is to investigate in which extent national price level, real interest rate and real exchange rate, co-move or diverge from supranational EZ variables. The research results, based on heterogeneous dynamic macro-panel data of 12 initial EZ members in the period 1999Q1-2019Q4, confirm heterogeneous adjustment, as well as the lack of balancing towards equilibrium, as a sign of EZ vulnerability.

This paper presents an econometric investigation of price dynamics and volatility in multiple markets. The econometric approach relies on a quantile autoregressive (QAR) model and a copula to provide a flexible representation of price dynamics and volatility in related markets. The analysis allows for an arbitrary distribution of prices across markets, nonlinear dynamics and the presence of price cycles. We propose a two-step estimation method to support a consistent estimation of the multivariate price distribution and its evolution over time. The analysis is illustrated in an econometric application to price dynamics in the US pork vertical sector. The application provides new and useful information on the nature of the pork cycle, the linkages between farm price and retail price and the evolving price volatility in this market. [ABSTRACT FROM AUTHOR]

Several drivers may generate market instability, but the partial contribution of different factors is still debated. We investigate how market-based drivers influence the global price volatility of three major grains: wheat, corn, barley. We adopt a Seemingly Unrelated Regression Equations model, in order to investigate potential common patterns. We compare inter-annual, intra-annual, and global volatility, to conclude on short-run and long-run dynamics of markets instability. We quantify the negative relationship linking (temporal) arbitrage and grain price volatility and conclude on the effects of supply movements on price volatility.

Virtual cross-border medical tourism allows many residents in the United States to purchase brand name medicines from companies in Mexico without travelling there. Monthly economic reports indicate that the online brand name pharmaceutical product prices in Mexico are noticeably lower than the corresponding internet prices in the United States. There have been very few econometric studies on how these prices are linked and the dynamic nature of those relationships. Results in this study indicate that online medicine prices in Mexico respond very rapidly to online prices changes in the high-price market.

China's housing sector offers an interesting case study of relationship between government interventions and price dynamics. Frequent and intensive government interventions create a highly fluctuant housing market in China. This paper applies a structural break model to investigate the dynamics in the evolution of China's housing price between 1998 and 2016. Results show that the development of China's real estate market exhibits much richer characteristics of structural changes rather than simple switching between boom and burst. Further studies indicate that government interventions is the most important source of structural changes in the dynamics of China's housing market because of the inherent conflict between policy aims of market stability and rapid economic development mainly backed up by the housing sector. [ABSTRACT FROM AUTHOR]

The agricultural product market is changing from a producer-orientated to a more consumer-orientated market. Consumer rely on the classification system within the red meat types. Different red meat types and carcass classifications influence the prices of red meat. This study was conducted to determine the price dynamics of different red meat carcasses and carcass classes. It was theorised that the different red meat classification classes and number of carcasses sold influence the price and demand of red meats. It was also theorised that specific meat classes have a greater influence on meat prices and demand than others. The results of this study supports the hypothesis that red meat carcass type and specific meat classes within carcass type influence red meat carcass prices. There is a differentiation among classes in terms of the degree to which class influences price, since classes were identified that had no influence on price dynamics of other meat types.

This article discusses an option of the mathematical model of economic situations with public goods consumed by several market participants simultaneously. Computer analysis of this model was performed by using the MATHCAD package which allows toillustrate some techniques of determining of market balance. It was assumed that the participants, considering the choice of the other is equal to their previous decision, comes to the agreed result in finish.

Market models are considered in which a liquidity factor associated with price dynamics and the agents' trading strategies is incorporated. The case is studied in which the liquidity factor is a deterministic function of the price and another in which this factor is stochastic described by a Cox-Ingersoll-Ross process. Different types of trading strategies are considered and the stochastic differential equations for price dynamics as well as the corresponding nonlinear partial differential equations for the valuation of contingent assets are explicitly established. [ABSTRACT FROM AUTHOR]

The U.S. catfish aquaculture industry has undergone a continuous and alarming contraction over the last 15 years or so. The rapid increase in cheaper imports, which has coincided with the decline in the domestic catfish farming industry, is being blamed by industry commentators as a major cause of the decline. The impact of increased market share of imports on prices is of particular significance as prices are fundamental to the market process. We use an innovative approach to understand the impact of import shares on the linkage among prices in the U.S. catfish market. We divide the time-series data on market prices into high-import and low-import regimes using empirical techniques and analyze the difference in responsiveness of prices to shocks in the two regimes. Our main finding is that the domestic prices at the farm and processor level have become more responsive to shocks in each other and in themselves in the high-import regime. [ABSTRACT FROM AUTHOR]