Price Announcements Research Articles

Constraints Faced by the Farmers in the Production and Marketing of Onions in the Western Undulating Zone of Odisha, India

This paper aimed to investigate the limitations associated with onion farming in the western undulating agroclimatic zone of Odisha, specifically regarding production, marketing, and storage. The study employed a multi-stage purposive sampling technique. The state was divided into 10 zones based on agro-climatic characteristics, and the district from the western undulating zone, Kalahandi districts, was purposively chosen since many farmers in these regions, like others in Odisha, cultivate onions throughout the winter season. A total of 90 farmers (45 from Bhawanipatna block and 45 from Golamunda block) were selected at random and interviewed directly for the purpose of study. Furthermore, the location, climatic conditions, and soil are ideal for onion cultivation. Kalahandi was chosen in 2021–2022. According to the survey, labour shortages for weeding, ignorance of improved varieties, high labour costs, ineffective and expensive weedicides, high seed costs, etc. were the top five problems faced by onion growers. The main difficulties faced by onion growers during marketing included low prices during harvest, which were followed by sharp price fluctuations, high transportation costs, payment delays, a lack of market news and information, a lack of storage facilities, etc. in the research area. To ensure an effective produce marketing system, the government, developmental agencies, marketing boards, and NAFED should intervene by enhancing the market infrastructure at the taluk and district levels and supplying timely market information. Farmers may be able to overcome the issue of price fluctuations if government authorities intervene promptly and announce an extension or announcement of the government support price for onion crops.

Can long-term institutional owners improve market efficiency in parsing complex legal disputes?

Long-horizon institutional investors can help mitigate information asymmetries around securities class action (SCA) lawsuits. We find that the machine readability of SCA complaint filings can predict the outcome and duration of class actions. Long-term institutional investor ownership leads to a more positive post-SCA announcement price reaction and increases the volatility ratio of prices as a measure of price informativeness. Furthermore, there is a significant interaction effect between long-term institutional ownership and SCA complexity on price informativeness consistent with a superior information processing ability about complex corporate events affecting portfolio firms.

부동산 공시가격 현실화 정책에 따른 재산세부담의 변화 분석

This study focused on the impact of the policy of realizing published prices of real estate on real estate property taxes and estimated the property tax burden using real estate price announcement data for land, single-family house, and apartment from 2017 to 2020. In addition, the changes in tax burden by year were analyzed and compared by real estate type, price level, and region to discuss the impact of the published price realization policy and suggest policy implications. According to the analysis of changes in the estimated property tax burden, the property tax burden increased significantly after the realization policy, and the gap in the property tax burden by region and price level widened. And the tax burden increased intensively on specific real estate types and high-priced real estate. This suggests that the policy of applying the realization of the published price differently by price range can rather hinder vertical and horizontal equity of taxation among taxpayers.

Price commitment and the strategic launch of a fighter brand

AbstractWe consider a vertically differentiated market where an incumbent strategically wants to launch a fighter brand to thwart a new entrant. Without a credibly commitment this launch is ineffective because the incumbent always has an incentive to price the fighter brand ex-post out of the market. Endogenous price leadership with fixed or list price announcement, and dual channeling with an intermediary retailer to distribute the fighter brand are analyzed as commitment devices. The optimal mode then depends on customers’ sensitivities to a deviation from the price announcement as well as on the attractiveness of the underlying market.

“This could only have been done by a person of the capitalist breed”: Retail price increases in the late Soviet Union (1977-1983)

The article studies an attempt at late Soviet economic reform consisting in mitigating consumer goods shortages and the growth of the black market, namely a series of retail price increases for “non-essential goods” between 1977 and 1983. A major principle of Soviet economics was that in contrast to capitalist countries, prices in the Soviet Union were supposed not to be defined by the market, but were to be based on the cost of labor invested in production. Low stable prices, together with rising wages, became the cornerstone of a state policy designed to bring about widespread economic prosperity. By the end of the 1970s, however, the government had to compromise its principles and significantly increased prices for “non-essential goods” such as rugs, crystalware, cars, and furs, among others. The goal of this measure was primarily to retaliate against underground dealers who grew rich thanks to their illegal economic activity and regularly purchased these luxury items at artificially low prices. However, this policy provoked resentment among the broader population. While many citizens were not planning to buy the goods on which prices rose, the very announcement of price increases for luxuries spotlighted for them the growth of economic inequality and the state’s betrayal of socialist principles.

Decision-Dependent Risk Minimization in Geometrically Decaying Dynamic Environments

This paper studies the problem of expected loss minimization given a data distribution that is dependent on the decision-maker's action and evolves dynamically in time according to a geometric decay process. Novel algorithms for both the information setting in which the decision-maker has a first order gradient oracle and the setting in which they have simply a loss function oracle are introduced. The algorithms operate on the same underlying principle: the decision-maker deploys a fixed decision repeatedly over the length of an epoch, thereby allowing the dynamically changing environment to sufficiently mix before updating the decision. The iteration complexity in each of the settings is shown to match existing rates for first and zero order stochastic gradient methods up to logarithmic factors. The algorithms are evaluated on a ``semi-synthetic" example using real world data from the SFpark dynamic pricing pilot study; it is shown that the announced prices result in an improvement for the institution's objective (target occupancy), while achieving an overall reduction in parking rates.

Profit maximization for an electricity retailer using a novel customers’ behavior leaning in a smart grid environment

With the establishment of the smart grids platform, demand response (DR) programs have improved the operation and reliability of the power grid by increasing the participation of customers. This article investigates the issue of bidding strategy for an electricity retailer, which interacts with a set of residential customers. In this environment, the price-responsive customers react to the announced prices optionally. Thus, the retailer requires to learn the behavior of its customers. The proposed model enlisting the analytic hierarchy process (AHP) and a strength deep learning (DL) algorithm represents a pioneer study of applying a data-driven method into the bidding strategy problem. Herein, the energy usage patterns of customers in response to the dynamic pricing are firstly extracted, and a profit maximization problem of the retailer for the DR management is then developed with the consideration of the market constraints. The numerical results show the good performance of the proposed approach for improving the profitability of the retailer.

Discount Rates, Subscription Prices, and Subscription Rates in Equity Rights Offerings

This study analyzes the wealth effect of discount rates, subscription price announcement effects, and subscription rates with 407 equity rights offerings (with unsubscribed shares to the public) announced between 2004 and 2016. The major results of this study are as follows. First, the market not only responds negatively to the right offering announcements (3-day CAR of -13.83%) but also to announcements of final subscription prices (3-day CAR of -4.85%). The announcement effects of final subscription prices are not related to changes in subscription prices, but become more negative as announcements are delayed. Second, the discount rate significantly affects the wealth effects. This means that discount rates provide the information on firms’ future prospects. Firms with low information asymmetry and high ownership by the largest shareholders choose lower discount rates. Third, the non-subscription rate is about 14% and wealth transfer due to non-subscription is 7.08% of the amount raised by the right offerings. As the offering process is delayed, the subscription rates decrease. In addition, the listing of subscription rights have a significant positive impact on subscription rates. However, as market value decrease due to a right offering is similar to the amount raised, firms should consider alternative financing methods.

Optimal timing of acquisition price announcement for used products in a dual-recycling channel reverse supply chain

The rapid development of information technologies enables recycling companies to purchase and collect used products from consumers through both traditional and Internet-based online channels. Because an online channel transmits price information instantly to consumers, choosing the best time to announce the recycling price (i.e., acquisition price) of used products to consumers has become a critical problem for recycling companies. This paper seeks to solve this problem by developing a game-theoretic model describing a dual-channel reverse supply chain consisting of a recycling company and a third-party collector in which the recycling company purchases products not only through a third-party collector, but also directly from consumers online. We derive two major results by solving the model. The first is that first-mover advantage arises, which indicates that each firm constituting a dual-channel reverse supply chain should announce its own recycling price before the other. This first result is notable because it is exactly opposite to conventional wisdom that the second-mover advantage of pricing usually emerges when price competition occurs among firms in a horizontal relationship, which is well known in noncooperative game theory. The second result is that the recycling company can maximize its own profit and consumers' surplus by announcing its recycling price in the online channel before or upon, but not after, determining the transfer price paid to the collector for products collected in the offline channel. Both results can be used as practical decision-making guidelines in dual-recycling channel reverse supply chain management.

공동주택 공시가격 현실화율 결정요인 분석 - 아파트 공시가격을 중심으로 -

본 연구는 헤도닉모형을 활용하여 현재 문제가 되고 있는 공동주택 공시가격 중 아파 트 공시가격의 현실화율 결정요인을 분석하여 정부의 공동주택 공시가격의 현실화 계획 의 원활한 이행을 돕기 위해 시작된 것이다. 연구는 선행연구를 조사․분석하여 연구 모형 을 작성하여 3가지 가설을 설정하고, 가설에 대한 입증을 위해 국토교통부에서 공시한 2019년도 전국 실거래가격 정보와 공동주택 공시가격 정보, 관련 통계 등을 활용하여 헤 도닉모형을 작성하였다. 작성된 모형을 근거로 가설을 검증하였으며, 마지막에 검증 결과 에 따른 시사점을 정리하였다. 검증 결과 실거래 아파트 거래요인에 따라 아파트 공시지가 현실화율은 차이가 있을 것이라는 제1가설은 채택되었으며, 실거래 아파트 개별요인에 따라 아파트 공시지가 현실 화율은 차이가 있을 것이라는 제2가설도 채택되었다. 다만, 실거래 아파트 지역요인에 따 라 아파트 공시지가 현실화율은 차이가 있을 것이라는 제3가설은 부분 채택되었다. 또한, 채택된 가설과 가설 검증과정에서의 분석 내용을 근거로 APT공시가현실화율에 영향을 미치는 외부요인 중 다음과 같은 14개 변수를 아파트 공시지가 현실화율에 대한 결정요인로 제시하였다. 거래요인은 거래단가, 저가더미, 계약시점이다. 개별요인은 건물 요인으로 전용면적, 층수, 저층더미, 1층더미, 고층더미, 신축건물더미, 30년초과더미이며, 단지요인은 단지최고층, 저층단지더미, 소규모단지더미이다. 그리고 지역요인은 가격변동율이다.

Profitability of Mulberry cocoon production in West Bengal

Objectives: To examine the profitability of mulberry cocoon production and to identify the reasons for marginalization of mulberry sericulture in West Bengal, India. Methods/Statistical analysis: The primary data pertaining to socio-economic status of farmers and costs & returns of mulberry cocoon production was collected from 240 respondents (Malda, Murshidabad & Birbhum) using pre-tested structured interview schedule following multi-stage purposive random sampling. The economics of mulberry cocoon production was worked out using budgeting technique. Findings: Mulberry cultivation in West Bengal was pronounced on marginal/small farms with average mulberry holding of 0.66 acre. Cost of production per kg of mulberry cocoon on marginal farms worked out to |283 and the profitability expressed in terms of the returns per rupee of expenditure was |1.47. Inadequate land holding and labour-intensive nature of mulberry cultivation are identified as major causes for marginalization of mulberry sericulture in West Bengal. Application/Improvements: The cost estimates will serve as the basis for policy-makers to intervene for the announcement of minimum support price in the event of price crash. Labour cost formed major chunk in the total cost of production of mulberry cocoon on marginal/small farms reelecting the scope for development of suitable implements & equipments for economizing mulberry sericulture. JEL classification: Q1 Keywords: Profitability; marginal farm; small farm; Mulberry sericulture; cocoon; budgeting technique

Announcing High Prices to Deter Innovation

Price announcements—similar to the ones made by tech firms at media events—are effective in deterring innovation. By announcing (and setting) a high price, a firm increases its rivals’ short-run profits, reducing the rival firms’ incentives to innovate by magnifying their Arrow’s replacement effect. We show that the equilibrium prices are greater and research and development (R&D) investments lower relative to when price announcements cannot be used strategically. We call this the R&D deterrence effect of price and show that it induces equilibrium prices that may exceed the multiproduct monopoly prices and even dissipate the consumer benefits of innovation. This paper was accepted by Joshua Gans, business strategy.

Covid 19 dan Harga Saham Perbankan di Indonesia

This study examines whether there are differences in the prices of Top Ten shares of the Banking Company with the largest assets in Indonesia in three periods, namely the share price before Indonesia contracted Covid 19, the share price at the time of the announcement of the first case of Covid 19 in Indonesia and the Post-3 Month Share Price announcement of the Covid 19 case in Indonesia. Processed by means of the Paired Sample T test analysis results show that during the study period there were significant differences between the stock prices in the three periods.

한국부동산원의 법적 기능과 향후 입법과제

With the enactment of the Korea Appraisal Board Act in 2016, the Korea Appraisal Board stopped appraisal work, which had been in competition with the appraisal industry, and focused on public affairs such as real estate price announcement, statistics, and surveys. However, as the industry continued to raise an issue with the Board’s name, claiming that the term “appraisal” still caused confusion in the appraisal market, the need for revision increased. In response, the National Assembly passed the Korea Real Estate Board Act, which replaced the Korea Appraisal Board Act, in a plenary session on May 20, 2020. Accordingly, the launch of the Korea Real Estate Board (tentative name) is expected to mark a turning point for the policy of the real estate market and industry. Therefore, this paper examines the legislative history of the Korea Real Estate Board Act and the major legal functions of the Korea Real Estate Board, and suggests the legislative policy tasks to be reviewed ahead of the launch of the Korea Real Estate Board in 2021.

Sustainable Electric Vehicle Charging using Adaptive Pricing

A transition to electric vehicles (EVs) is widely assumed to be an important step along the road to environmental sustainability. However, large‐scale adoption of EVs may put electricity grids under critical strain, since peaks in electricity demand are likely to increase radically. Efforts to manage demand peaks through pricing schemes may create new peaks at low‐price periods, if large numbers of EV owners use smart charging to benefit from low prices. This effect is expected to be amplified when EV owners adopt smart decision support to assist them with optimal charging decisions. Therefore, energy policymakers are interested in advanced pricing schemes that can smooth demand or induce demand that comes as close as possible to a desired profile. We show, through simulations calibrated with real‐world data, that current approaches to electricity pricing are limited in their ability to induce desired demand profiles. To address this challenge, we present adaptive pricing, a method to learn from EV owner reactions to prices and adjust announced prices accordingly. Our method draws on the Green Information Systems principles and can assist grid operators in ensuring the reliable operation of the grid. We evaluate our results in simulations, where we find that adaptive pricing outperforms current electricity pricing schemes, yielding results close to the theoretically optimal ones. We test our method in inducing both flat and extremely volatile demand profiles, and we see that in both cases it manages to induce EV charging close to the ideal scenario under perfect information.

An Analysis of Service Effort Strategies in Dual-Channel Supply Chains with Showrooming Effect

Nowadays, the rapid growth of the online market poses great challenges for the brick-and-mortar (BM) retailers. In response to this threat, BM retailers exert various service efforts to promote sales in the offline market. This service effort, maybe unintentionally, also increases sales in the online market as customers might benefit from the offline service even if they shop online; this is called the showrooming effect. In this paper, our objective is to analyze multichannel retailing under different service effort strategies with the showrooming effect. We develop a series of game theoretical models that each involve a manufacturer, a retailer and an e-tailer. We investigate the showrooming effect on the pricing and service effort and determine optimal pricing strategies for each player. We first consider two scenarios where the service is provided by only one firm: a retailer exerting effort case and a manufacturer exerting effort case. In the retailer exerting effort case, we discuss three subcases that differ in when the level of service effort is chosen: an ex-ante case, an ex-post case, and a simultaneous case. Thus we explore incentives to provide service for the different firms and how the optimal pricing strategy for each player and the total profits of the whole supply chain depend on the timing. The results indicate that in most cases, the service provider increases the service effort as the showrooming effect gets stronger. In addition, the analysis on the timing of exerting the service effort reveals that the retailer’s profit is highest when he exerts the effort after the announcement of the wholesale price using the ex-post strategy obtains the highest profits in the ex-post case than in the ex-ante case and the simultaneous case. In the end, we discuss a scenario in which all the supply chain members jointly determine the service and compare it to other cases. We find that the total supply chain’s profit under the joint decision-making case is always superior.

Can Long-Term Institutional Owners Improve Market Efficiency in Parsing Complex Legal Disputes?

Long-horizon institutional investors can help mitigate information asymmetries around securities class action (SCA) lawsuits. We find that the machine readability of SCA complaint filings can predict the outcome and duration of class actions. Long-term institutional investor ownership leads to a more positive post-SCA announcement price reaction and increases the volatility ratio of prices as a measure of price informativeness. Furthermore, there is a significant interaction effect between long-term institutional ownership and SCA complexity on price informativeness consistent with a superior information processing ability about complex corporate events affecting portfolio firms.

Contract-Theoretic Demand Response Management in Smart Grid Systems

The sheer growth of electricity demand and the rising number of electricity-hungry devices have highlighted and elevated the need of addressing the demand response management problem in residential smart grid systems. In this article, a novel contract-theoretic demand response management (DRM) framework in residential smart grid systems is introduced based on the principles of labor economics. The residential households produce and consume electricity, acting as dynamic prosumers. Initially, the prosumers' personal electricity generation and consumption characteristics are captured by introducing the concept of prosumers' types. Then, the prosumers' and the electricity market's profit is depicted in representative utility functions. Based on the labor economics principles, Contract Theory is adopted to design the interactions among the electricity market, which offers personalized rewards to the prosumers in order to buy electricity at an announced price, and the prosumers, who offer their “effort” by paying for the purchased electricity. The contract-theoretic DRM problem is formulated as a maximization problem of the electricity market's utility, while jointly guaranteeing the optimal satisfaction of the prosumers, under the scenarios of complete and incomplete information from the electricity market's perspective regarding knowing or not the prosumers' types, respectively. The corresponding optimization problems are solved following a convex optimization approach and the optimal contracts, i.e., rewards and efforts, are determined. Detailed numerical results obtained via modeling and simulation, highlight the key operation features and superiority of the proposed framework.

A Generic Way of Determining Cost of Production of a Crop Using Dynamics Weights: A Case Study in Pakistan

To determine cost of production (CoP) of a crop is a persistent distress for the Government of Punjab (Pakistan) in the given conditions of rural and political dynamics. For the purpose, Crop Reporting Service (CRS), Agriculture Department Punjab has been evolving, using and analyzing sample data based on Area Frame Sampling (AFS) technique for conducting surveys to gather information regarding crop acreage, CoP, grain yield / production and other agricultural items. Timely decision on CoP of a crop by the government before the arrival of a crop is, obviously, very important for the announcement of support price for the crop and also for the evaluation of cost and benefit analysis of agriculture sector. Using AFS technique, based on two-stage sampling design, 5500 segments of 150 acre each have been selected covering almost 2600 Union Councils (UCs) of the Punjab for the study. From each randomly selected segment, two farmers were randomly selected. Through a detailed questionnaire, covering almost 75 variables on CoP of a crop, data are collected from the farmers of a specific crop. For this purpose wheat crop (Wheat is one of the core agricultural crops in Pakistan) has been selected as a case study for the comparison of Average (using Arithmetic Mean) CoP and Weighted Average CoP (WACoP) of wheat. In this paper, a detailed data flow and method for the determination of CoP of a crop is discussed. Average (using Arithmetic Mean) CoP technique was available to determine the production cost of any crop using the root level data from the farmers. But while compiling the report of COP on Punjab level, it has to be mentioned that the average cost of each head then ultimately total of all heads’ averages computed to find out the average COP of the specific crop. To overcome this problem, it has been proposed a new method to determine the CoP of any crop by using WACoP and taking proportion of usage of a specific head as a weight of the head. Data are compiled on provincial level and proportion of each cost factor of a crop was calculated as usage of each cost factor varies from crop to crop and area to area. The proportion of each cost factor has been used as its weight for the final evaluation of CoP of the crop. As cost factors vary, so for, all crops during a season, each year these weights of cost factors were freshly calculated to get latest CoP of a crop. Government of Pakistan has declared Rs. 1400/40kg as support price of wheat during Rabi season 2019-20 based on this study.

Dividend announcement and share price behaviour: A study of selected Indian companies

Dividend announcement and share price behaviour: A study of selected Indian companies