Price Expectations Research Articles

Spatial analysis of speculation in the US housing market

This study examines the spatial impact of speculation on the US housing market from 1990 to 2021, highlighting regional variations and economic implications. Employing advanced analytical techniques, including nonlinear least squares and time-varying parameter ordinary least squares, we delve into the spatial patterns of speculation within the housing market. This study aims to illuminate the role of speculation in influencing housing market dynamics, which has significant implications for economic stability and housing policy. Our investigation reveals that speculation is primarily driven by price expectations and historical price trend analysis, exerting a significant influence on housing market dynamics. Given the inherent constraints in housing supply, effectively managing these fluctuations necessitates a multifaceted strategy. This approach involves measures such as accelerating production, streamlining supply chains, and facilitating affordable land access and tax incentives for low-income households, all designed to stimulate investment in construction and housing. Our empirical findings indicate variations in speculation prevalence across different regions of the USA, with a higher incidence in the western and midwestern regions compared to the eastern counterparts. In light of these insights, policymakers are urged to consider tailored regulatory interventions to mitigate excessive speculation in the US housing market. These measures could encompass stricter lending standards and enhanced transparency requirements in real estate transactions. This study contributes to a deeper understanding of the dynamics of speculation within the US housing market, offering valuable insights for policymakers and researchers seeking to address its implications for economic stability. Moreover, Our findings not only highlight regional variations but also validate theories of speculative behavior, particularly the role of price expectations and feedback loops, as established by Shiller (2005) and Glaeser (2013). These insights contribute to a deeper understanding of the dynamics driving speculation in the housing market.

Betting on the House: Subjective Expectations and Market Choices

Home price expectations play a central role in macroeconomics and finance. However, there is little direct evidence on their effect on market choices. We provide causal evidence using a large-scale, high-stakes field experiment in the United States. We sent letters about home price trends to 57,910 homeowners who listed their homes. These letters contained randomized information creating nondeceptive, exogenous variation in home price expectations. Consistent with economic theory, higher expectations reduced selling probability. Behavior was highly elastic: a 1 percentage point increase in expectations caused a 2.63 percentage point reduction in the probability of selling the property within 12 weeks. (JEL C93, D83, D84, R31)

Adaptation of rice to climate change in high-latitude regions of China: Will price expectation make differences?

Adaptation of rice to climate change in high-latitude regions of China: Will price expectation make differences?

Pricing strategies and economic uncertainty

In August 2019 an unexpected presidential election result caused achange in expected exchange and inflation rates. The objective of this study is toanalyze the relation between market share and the decision of increasing prices inthe pharmaceutical industry in Argentina.Methods: Online weekly data on variations of some medicine’s prices were obtainedusing web scraping, and then classification algorithms (Random Forests, GradientBoosting Machine and logistic regression) were applied.Results: The results were mixed: market share was found to have high importancein tree-based methods. (Random Forests and Gradient Boosting Machine).However, in logistic regression, this variable wasn’t significant.Conclusions: Exchange rate volatility after the election result caused severalchanges on price expectations, and pharmaceutical market structure influencedthe resulting price reactions. Laboratories which owned a higher market share rosetheir prices first.

Breaking up with your bank: the role of competitors’ effective advertising in customer switching intention

The discrepancy between customer expectations and experiences can result in significant adverse consequences. This study, exploratory in nature, utilised the structural equation modelling technique to reveal how competitors’ effective advertising influences customers’ expectations of in-using banks, triggering their switching intentions in line with the expectation-confirmation theory, with a dataset of 471 responses from retail bank customers in China via an online semi-structured survey with a convenient and non-probability method. This study revealed that competitors’ effective advertising not only directly influences customers’ bank switching intentions but also indirectly impacts customers’ switching intentions by influencing customers’ expectations of price and service quality. The study also found that the price was positively correlated with customers’ perceptions of service failure and customers’ switching intentions, while service failure is associated with customers’ switching intentions. This study is the first attempt in the literature to examine customers’ decisions to switch banks that focus mainly on competitors’ effective advertising and provide in-depth insights.

Navigating the Energy Crisis：Automakers’ Coopetition Strategies under Dual Credit Policy

To tackle the energy and climate crises and achieve sustainable development, China has designated the development of new energy vehicles (NEVs) as a national strategy.This paper delves into the coopetition strategy of dual-model automakers under the dual credit policy (DCP) using a subsidy-R&D-production three-stage game model, considering government subsidies and consumer preferences. The model explores various strategies, including full competition and different R&D cooperation scenarios for fuel vehicles (FVs) and NEVs. Key findings include: (1) R&D subsidies boost NEVs R&D investments but may not always optimize social welfare. (2) When NEVs technology spillovers are low, firms should fully cooperate; otherwise, the FVs R&D cooperation is optimal, especially with high FVs spillovers. (3) Investments and outputs in both vehicle types positively correlate with technology spillovers, and consumer preferences. Conversely, FVs equilibrium decreases with NEVs credit proportion and fuel consumption disparities. (4) The credit price positively influences R&D investments and outputs of NEVs, but its effects on FVs' R&D investments, outputs, corporate profits, and social welfare vary based on market dynamics. Recommendations include optimizing subsidy policies, supporting low-carbon FVs, enhancing infrastructure, and strengthening DCP regulations to stabilize credit price expectations.

The Art of Balancing Price and Plug: Developing a Theoretical Model for Dynamic Pricing in the Electric Vehicle Market

This study presents a novel approach to understanding the complex dynamics of the electric vehicle (EV) market through the lens of differential game theory. We developed a comprehensive model that captures the strategic interactions between EV manufacturers and charging network operators, while incorporating the effects of consumer behavior, market uncertainties, and reference price effects. Using differential game theory, we examined the impact of reference price effects and the charging network’s influence on pricing strategies, focusing on three distinct approaches: basic pricing, static pricing considering reference price effects, and dynamic pricing strategies. Our model offers new insights into consumer behavior and price expectations in the rapidly evolving EV market. The key findings reveal that under static or dynamic pricing strategies, the optimal pricing for EV manufacturers is positively correlated with the initial reference price. When the initial reference price is high (low), the optimal pricing strategy resembles skimming pricing (penetration pricing). As the effort level of charging network operators increases and their influence on consumers’ purchase decisions grows stronger, EV manufacturers tend to set higher prices. Notably, while dynamic pricing strategies can optimize EV manufacturers’ profits, the profits of charging network operators may decrease compared with static pricing strategies. This integrated approach significantly contributes to the field by bridging gaps among market dynamics, pricing strategies, and the infrastructure’s development in the context of electric mobility, providing a comprehensive framework for understanding and optimizing the EV ecosystem. Ultimately, this study advances sustainable business models that balance profitability, consumer behavior, and the infrastructure’s growth in the rapidly evolving EV market.

Risk premium, price of risk and expected volatility in the oil market: Evidence from survey data

Risk premium, price of risk and expected volatility in the oil market: Evidence from survey data

Carbon market design and market sentiment

Carbon market design and market sentiment

Functional Oil Price Expectations Shocks and Inflation

ABSTRACTThis paper investigates the inflation effects of oil price expectations shocks constructed as functional shocks, that is, as shifts in the entire oil futures term structure (both standard and risk‐adjusted). The latter are then included in a vector autoregressive model with exogenous variables (VARX) to examine the US case. Counterfactual analysis is also carried out to investigate second‐round effects on inflation through the inflation expectations channel. These are found to be significant, in contrast to earlier studies based on standard oil price shocks. Additional nonlinear local projections including a shock decomposition exercise show that inflation and inflation expectations are primarily driven by changes in the curvature (level and slope) factor when the latter are anchored (unanchored). These findings provide useful information to policymakers concerning the impact of oil price expectations on inflation and inflation expectations.

General equilibrium and dynamic inconsistency

General equilibrium and dynamic inconsistency

Are milk quota prices a rational investment? Modeling quotas as financial assets

AbstractOur objective in this paper is to examine the growth of the price of farm milk quotas in Canada, to shed light on their patterns of growth within the last 15 years. Our quota price model is based on the Gordon growth model, supplemented by some important characteristics of the milk quota market. Our explanatory variables include the quota rental price, interest rate, and expectations of both price and quantity growth, all for the province of Alberta over the 2009–2023 time period. Our economic model of quota prices performs well by giving results with the predicted signs for all variables in our model and high levels of statistical significance except for expectations of quantity allocations when entered separately. The model has two variants, one with the expectation of growth in quota rents and the other with the expectation of growth in the quota asset price. Econometric issues related to time series problems are dealt with. The model allows calculation of policy risk, which shows an interesting pattern over this time period.

A study on wood waste potential in Turkey

A study on wood waste potential in Turkey

Selection of Modelling for Forecasting Crude Palm Oil Prices Using Deep Learning (GRU & LSTM)

The unstable crude palm oil (CPO) prices have an impact on assessments of economic growth and environmental sustainability, as well as market strategies, international trade discussions, and consumer pricing expectations for products made from CPO. Therefore, it is crucial to identify the best prediction method to accurately forecast this cost. This research aims to develop an accurate time series data prediction model for crude palm oil prices using GRU and LSTM methods. The study also aims to identify the best-performing model by comparing their performance. This study uses LSTM and GRU methods as well as Bi-LSTM as a comparison, using crude palm oil price data from the Indonesian Ministry of Trade (August 1, 2018–August 31, 2023) from Medan (1064 data points) and Rotterdam SPOT (617 data), Rotterdam Forward 1 Month (1,022 data), and Rotterdam Forward 2 Month (950 data). Each dataset is then split into training and testing data with a 70:30 ratio. The hyperparameters used are (a) learning rate: (0.001); (b) batch size: 100; (c) node: (512); (d) optimizer: Adam; (e) and epoch: 50. The results of the forecast are highly accurate with a MAPE of less than 10%. Overall, both LSTM and GRU techniques demonstrate excellent performance in forecasting crude palm oil prices, but they may need to be modified based on data features. The ARIMA method can also be considered for forecasting. Future studies may consider optimizing parameters and model structures. Doi: 10.28991/ESJ-2024-08-03-05 Full Text: PDF

Carbon pricing and inflation expectations: Evidence from France

Carbon pricing and inflation expectations: Evidence from France

The Role of Speculative Demand in Housing Price Changes in Turkey

Housing accounts for the largest portion of households' total assets in Turkey. It is an economic sector that requires careful analysis, especially considering the government's housing sector support policies and the significant price increases in recent years. This study utilizes the theoretical model developed within the Efficient Markets Hypothesis framework and the SVAR methodology to estimate house price changes. These changes are then decomposed into structural shocks, including supply, residential demand, and speculative demand shocks. The empirical results highlight the significant role of speculative demand in driving house price changes, with house price expectations being the main factor influencing speculative demand shocks. The behavior of the banking sector and interest rates also play a significant role in this process. Consequently, policies to stabilize house prices should consider these factors and not solely focus on credit regulations when consumer expectations are the driving force behind house price changes.

Hierarchical online energy management for residential microgrids with Hybrid hydrogen–electricity Storage System

Hierarchical online energy management for residential microgrids with Hybrid hydrogen–electricity Storage System

Inferring Expectations from Observables: Evidence from the Housing Market

Abstract We propose a method to detect shifts in housing price expectations by observing excess capacity. Anticipated future price hikes lead to increased current supply, resulting in temporary vacancies. Using a structural vector autoregression with sign restrictions, we analyze the impact of these expectations on the U.S. housing market. Our findings indicate that price expectation shocks primarily drove the 1996–2006 boom, especially in the Sand States. At the boom's peak, these shocks stemmed from unrealistic growth expectations, which reversed during the bust.

Behavioural Aspects of Price Expectations and the Anchoring Effect on the Housing Market – Polish Case Study

ABSTRACT Housing is a heterogeneous good, which makes choosing a house a complex process. An unexplained variability of the housing prices led to growing interest in studying prices and price expectations from a behavioural perspective. We conduct an experiment to study house price anchoring. In this research we use empirical data, examining the strength of the anchoring effect in terms of the external paradigm. We check whether and how respondents revise their valuations and expectations after receiving additional external information. It turns out that anchors impact households’ decisions regarding the housing price valuation and dynamics forecasts, which could suggest households’ autoregressive way of thinking.

Analysts’ extrapolative expectations in the cross-section

Analysts’ extrapolative expectations in the cross-section