Price Cycles Research Articles

Convergence in House Price Cycles across the US: Recent Developments and the Impact of Covid

Convergence in House Price Cycles across the US: Recent Developments and the Impact of Covid

Performance of different models in iron ore price prediction during the time of commodity price spike

Future prediction of commodity price based on available data is very important for mining investors and operators. Commodity prices cointegrate and show Granger causality to and from one another. This research reviewed five different estimation techniques which are Bivariate Non-Linear Regression (BNLR), Multiple Linear Regression (MLR), Multiple Non-Linear Regression (MNLR) as well as logsig and tansig model of Levenberg-Marquardt Artificial Neural Network modelling to simulate the future iron ore price based on 12 other monthly commodity prices and indices including LNG, aluminium, nickel, silver, Australian coal, zinc, gold, oil, tin, copper, lead, and Commodity Price Index (Metals).Six different models were tested in the paper to forecast the iron ore prices from 1 to 6 months over 10 months period. Linear model (purelin) using Levenberg-Marquardt technique was able to exhibit the best forecast result with average accuracy of 5.92% for 1 month ahead, 9.48% for 2 months, 11.21% for 3 months, etc. It is important to highlight that high accuracy is achieved (accuracy under 5% between forecasts and actuals in 40–50% cases) by purelin model for up to 2 months forecast for the period between July 2020 and April 2021. This indicates that prediction of iron ore price for the coming month is possible for up to 2 months period using the purelin model. It can be noted that the period tested was unstable for iron ore prices where rapid surge in iron ore price was observed. Same principle can be applied in the time of next commodity price cycle.

The Quality-Adjusted Cyclical Price of Labor

The Quality-Adjusted Cyclical Price of Labor

Price Analysis of Coffee in India

The present study is proposed with the objective to analyze the trend, seasonal and cyclical price variations of coffee in India. Secondary data collected from Coffee Board over a period of 13 years (2007-2020). Compound Annual Growth Rate Analysis, Seasonal Index, Bry - Boschan algorithm used to identify the price trend, seasonal and cyclical price variations of coffee in India. The farm gate price of coffee in the selected markets Chikmagalur and Tamil Nadu was positive and significant. In Chikmagalur market, prices prevailed lean during March, April, August, September, October and November and higher in the months of December, January and February for Arabica. Robusta parchment and cherry prices prevailed lean during January, November and December and higher in March, June and July. In Tamil Nadu market, price was higher in the months of January, February and March and lean during September, October and November.

DISCRETE-CONTINUOUS MODEL OF SALES MANAGEMENT IN REAL TIME

The subject of the research is the development of a strategy for dynamic price management when selling products over a fixed time interval. We consider the case when the demand for the seller's products can be represented as a combination of two random processes: 1) Poisson flow of potential consumers; 2) the purchase of goods by an individual consumer, the probability of which is inversely related to the price of the product. Consumers need at most one unit of the good and have independent equally distributed estimates of its consumer value. Such demand structure allows to formalize the choice of the optimal pricing strategy as an optimal control problem. Employing dynamic programming methods to solving this problem yields a system of Riccati differential equations. The optimal solution is obtained in the closedloop form as a function of the time to expiration of the product value and unsold inventory levels. Examples of a practical solution to the optimal pricing problem are given for special cases when it is possible to find an analytical solution. For the general case, it is shown how to find the optimal prices using numerical methods. Calculations show that optimal prices are decreasing functions of time and inventory levels. The combination of these factors, together with the random nature of the product sales, leads to rather complex observed price trajectories, examples of which were obtained using computer simulations. In particular, in many cases, the implementation of the proposed strategy results in cyclical price behavior, the prevalence of which in retail is well documented. The problem of optimizing the expected income of the seller when using constant prices was also solved. Comparison of the expected income of the seller under static and dynamic prices indicates a significant advantage of the latter. The economic effect of using dynamic pricing is most significant near the expiration of the product value.

Farmer field school participation and exit decisions in hog production: A case study from Beijing

AbstractThe worsening volatility in the domestic and global hog and pork markets is a cause of concern for China's producers and government, as well as the global market. Cyclical price fluctuations have been caused by domestic small‐ and medium‐scale farmers' frequent exits and re‐entries into the hog market, which may have been partly driven by information asymmetry and risk resistance. This study examines the impact of a farmer field school (FFS) program aiming to deliver information and services that may facilitate hog farmers' decision‐making. Using survey data collected from 226 hog farms in Beijing, we employ probit models to examine the exit decisions of hog farmers based on their FFS participation and its effect on hog farm size. We find evidence that FFS participation significantly reduces hog farmers' exit rates, and that this effect increases as farm scale decreases. The findings suggest that such a program may be an effective policy tool to support and improve the resilience of small‐ and medium‐scale hog farms, thereby alleviating the volatility in China's hog industry and those of other developing countries where small‐ and medium‐scale hog farms play an important role. [EconLit Citations: C21, D13, Q16, Q18].

Financial cycles across G7 economies: A view from wavelet analysis

We analyse the cross-country dimension of financial cycles by examining cyclical co-movements in credit, house prices, equity prices and interest rates across the G7 economies. We use wavelet-based statistics to assess at which frequencies cyclical fluctuations and their cross-country co-movements are important and how these change over time. We show that cycles in interest rates and equity prices are at least as synchronised as cycles in real GDP, while cycles in credit and house prices are less synchronised. Furthermore, we propose a measure of the importance of common cycles for developments in individual countries. It shows that common cycles across countries in equity prices and long-term interest rates account for a larger share of the volatility of these variables at the country level than is the case for common cycles in credit aggregates. The importance of common cycles for fluctuations at the country level is roughly similar for house price growth and long-term interest rates.

Production and Price Cycles in Beef Cattle in Rondônia State, Brazilian Amazon

The study evaluates the behavior of production and prices in the beef cattle market in Rondônia, Brazilian Amazon. Covering the period from 1995 to 2020, we used statistical analysis based on the classical multiplicative method of time series. Resultingly, we found that the occurrence of annual seasonality in prices, with a reduction in the first half of the year and an increase in the second half of the year, corresponding to the bovine and off-season harvests, respectively. It was possible to observe the existence of three complete livestock cycles, with an average duration of five years. Trend, seasonality, and cycles of livestock in Rondônia, over the last 25 years, expose a series of relevant information for decision-making by agents in the livestock production chain, in addition to contributing to the understanding of the dynamics of this important agricultural market for Rondônia and Brazilian economy.

Research on trading strategy based on improved LSTM network model

The economic foundation determines the superstructure of society. Sustainable development of society is inseparable from economic prosperity, and investment has an irreplaceable role as one of the "troika" to promote social economy. Based on this, the modeling in this paper aims to study the trading strategy problem. In this paper, firstly, outliers and missing values are processed by Laiida's rule for the attached data, and then a multi-layer LSTM weighted model is proposed to learn the influencing factors of input time span on output time span by using multi-layer LSTM network, and the model is trained to achieve higher accuracy relative to the LSTM model through the embedded method: superposition of the influence generation cycle sequence. Attention mechanisms are introduced and short and long term forecasts are continuously made. The fluctuations of MACD, RSI indicators, Apriori and other parameters are quantified; then, a risk measurement index is constructed, where the greater the cyclical price fluctuations, the greater the risk. The results show that timely buying and selling maximizes returns, and that a $1,000 investment ends up with a $900,000 return. The model is run again by increasing or decreasing the percentage of transaction costs, setting 0.5%, 1%, 1.5% and 2% points, to test the magnitude of sensitivity (trading decision results) at different transaction costs. The results show that the model is more robust, i.e., the model constructed in this paper has better results under different transaction costs.

Behaviors of Flippers, Rental Housing Investors and Owner-Occupiers in the Singapore Private Housing Market

We classify housing investors into flippers, rental housing investors and owner occupiers. We adopt the Singapore private housing transaction database between 2006 and 2010 to analyze their trading behaviors. The investigation period witnessed a full housing price cycle and had limited policy interventions. By comparing the trading behaviors of the three types of housing investors, we find that flippers can always buy at the highest price discounts and sell at the highest price premiums in housing transactions. Flippers show the highest propensity for trend chasing and act as momentum traders. When the housing market moves from its upward trend to a downward trend, flippers’ price discounts at buying increases, but their likelihood of buying decreases, while flippers’ price premiums at selling decrease, and their likelihood of selling increases. Rental housing investors show slightly higher price discounts at buying or price premiums at selling when trading with owner occupiers. However, they show a lower propensity for trend chasing than owner-occupiers. The findings have policy implications for anti-speculation policy designs.

Heterogeneous effects and spillovers of macroprudential policy in an agent-based model of the UK housing market

AbstractWe develop an agent-based model of the UK housing market to study the impact of macroprudential policy experiments on key housing market indicators. The heterogeneous nature of this model enables us to assess the effects of such experiments on the housing, rental, and mortgage markets not only in the aggregate, but also at the level of individual households and sub-segments, such as first-time buyers, homeowners, buy-to-let (BTL) investors, and renters. This approach can, therefore, offer a broad picture of the disaggregated effects of financial stability policies. The model is calibrated using a large selection of micro-data, including data from a leading UK real-estate online search engine as well as loan-level regulatory data. With a series of comparative static exercises, we investigate the impact of (i) a hard loan-to-value limit and (ii) a soft loan-to-income limit, allowing for a limited share of unconstrained new mortgages. We find that, first, these experiments tend to mitigate the house price cycle by reducing credit availability and therefore leverage. Second, an experiment targeting a specific risk measure may also affect other risk metrics, thus necessitating a careful calibration of the policy to achieve a given reduction in risk. Third, experiments targeting the owner-occupier housing market can spill over to the rental sector, as a compositional shift in home ownership from owner-occupiers to BTL investors affects both the supply of and the demand for rental properties.

The Effect of Market Isolation on Competitive Behavior in Retail Petrol Markets

Regarding the importance of energy for societies, this study examines the characteristics of the petrol price cycle in Perth, Australia. Given the micro-and macro-economic changes, the study’s purpose was to determine whether the Edgeworth features of the cycle are robust and resilient to market changes. The contribution is to extend previous studies, evaluate Edgeworth’s consistency, and capture several episodes of economic activity that have been unexplored. The findings showed a frequent and asymmetric weekly cycle that is characterized by decreasing prices over six consecutive days, followed by a large price jump in one day. The average price rise in the relenting phase for major stations was 14.10 cents per liter (CPL) and 13.14 CPL for independents. For the major and independents, the daily average price drops in the undercutting phase were 2.25 and 1.92 CPL, respectively. Despite the market changes, Edgeworth’s cycle characteristics, cycle duration, and the stations’ role have remained stable during the last 15 years, but peak and trough days have changed. The study is crucial as it provides insights into the robustness of price cycles and competition during significant downturns and prolonged periods of growth. This analysis is critical from a regulatory, policy, and consumer welfare perspective. Furthermore, this paper investigates future petrol consumption in light of renewable energy developments.

Gold price dynamics in India: A pre-post-liberalisation comparison

There are considerable differences in gold price movements in India in the periods of pre-and-post globalised regimes. This is because of a change in the controlled regime in the pre-liberalised to a meticulous dilution in the post-liberalised era. Hence, the liberalised period witnessed an upward trend in price dynamics with only occasional dampening in the price cycles. The jewellery sector in India is not driven by local forces as most of the inputs are imported for production and value-added export. It is revealed that the positive impact is the result of liberalisation and related mechanisation. Gold price shows a kind of co-integration of domestic prices with the global cues. In the pre-post-dichotomy, the post-liberalisation period is more integrated with the global prices than the pre-liberalised.

Drivers of tuition fee setting practices for higher education institutions involved in international student recruitment

ABSTRACT Tuition fee (or price) setting drivers are still an under-researched area. We attempt to fill this gap using universities as the basis of analysis. Grounded in pricing contingency theory, specifically, pricing capability literature, a conceptual model is developed using qualitative data from eight annual pricing cycles (2009–2017). We test the model using quantitative data collected over 18 months between 2017 and 2019. The findings add to the research on higher education marketing and provide managerial insights into how tuition fee setting can serve as an international marketing tool.

Impact of Climate Change on Egg Production in India and Price Behaviour of Eggs in Selected Markets of India

The present study entitled “Impact of Climate Change on Egg Production in India and Price Behaviour of Eggs in Selected Markets of India” aims to study the impact of climatic variables such as temperature, rainfall and relative humidity on egg production in India and various components of prices of eggs in selected markets of India. Multiple regression analysis revealed that temperature has a negative effect and rainfall and relative humidity have a positive effect on egg production in India. Decomposition of prices of eggs to trend, seasonal, cyclical and irregular components was done using Minitab. The data on egg prices from June 2009 to May 2022 was obtained from National Egg Coordination Committee (NECC) website. Bengaluru, Chennai, Delhi and Mumbai are the four markets considered for the study. The average price per 100 eggs is highest in Mumbai (Rs.366.06) followed by Chennai (Rs.360.25), Bengaluru (Rs.348.52) and Delhi (Rs.341.17). the prices of eggs showed wide fluctuations and there is uniformity in prices of eggs across all the selected markets due to organized egg marketing. The prices of eggs in all the selected markets showed a highly significant increasing trend. The annual increase in egg prices was highest in the Mumbai market (Rs.1.57/100 eggs) and lowest in the Delhi market (Rs.1.35/100 eggs). The highest seasonal index was observed during the month of June in Bengaluru and Chennai markets and during the month of July in Delhi and Mumbai markets. In the month of April, the prices of eggs decreased due to their short shelf life because of summer whereas in the month of November the prices of eggs decreased due to an increase in arrivals of eggs. The highest price of eggs during the June and July months is due to an increase in the consumption of eggs. Egg prices do not have any price cycles and irregular variations are observed for all the markets considered under study. Government should take initiative to educate poultry farmers regarding the impact of climate change on egg production as well as prevailing egg prices in the market.

Analysis of the Relationship between Fiscal Policy Shocks and Monetary Stability in Iraq's Economy for the Period 1990-2018

The research aims to measure the impact of positive and negative fiscal policy shocks on monetary stability in Iraq, which represents monetary stability as an indicator of real and price stability. Fiscal policy shocks are quantitative changes in public spending and public revenue affecting the output and price cycle, and fiscal policy despite the accompanying time gaps, but it remains a policy Influential and has a significant degree of impact on economic growth and development in developing countries. The fiscal policy represents a numerical translation of the economic and social objectives planned in the state's general budget tool consistent with the GDP cycle. The economic and social goals stem from the core of the functions and the main objectives of the fiscal policy, namely the allocation of resources, stability and restoration Distribution and these functions, as we know, free market techniques may fail to achieve them, which interferes with the financial policy to address the failure of the market to reach the set goals, and that coordination between fiscal and monetary policies does not mean a loss of independence as much as it means correcting fiscal and monetary policies without causing undesirable adverse effects upon the necessary correction. For local courses Opposing this coordination, and we have touched on the monetary stability index adopted by the International Monetary Fund (IMF) to discuss the impact of financial shocks on the monetary stability index in Iraq, where the Iraqi economy witnessed positive fiscal and revenue policy shocks with limited negative financial shocks in spending. Public and public revenue and the impact was studied through the existence of long-term relationships that link fiscal policy shocks, i.e. quantitative changes in public spending and public revenue on monetary stability. The boundary test within the Autoregression techniques of distributed Lag demonstrated the existence of a long-term relationship between fiscal policy shocks and monetary stability in Iraq.

Revolution in Development: Mexico and the Governance of the Global Economy

Revolution in Development: Mexico and the Governance of the Global Economy

(A)Synchronous Housing Markets of Global Cities

In this paper we examine house price synchronization in 15 global cities using real house price data from 1995:Q1-2020:Q2. We find that although there is evidence for bilateral positive phase synchronization, there is no evidence for an integrated global housing market for our sample of cities. Using a hierarchical clustering approach, we identify three clusters of cities with similar housing price cycles that are not solely determined by geographic proximity. We interpret this finding as suggestive of a rather segmented housing market for the global cities in our sample. Using a dynamic factor model with time-varying stochastic volatility, we decompose a city’s real housing price growth into a global component, a cluster-based component, and an idiosyncratic component. For most cities in our sample, the global component plays a minor role, whereas the cluster-based factor explains a large fraction of the observed variation in real house price growth, with its contribution peaking during the Great Recession of 2007-09.

What the Past Tells About the Future: Historical Prices in the Durable Goods Market

We investigate how historical price information (e.g., accessed through price trackers) influences consumers’ purchase decisions and thus affects a firm’s dynamic pricing strategy. We first show that when consumers with heterogeneous tastes are not informed about historical prices, the monopolist charges a high regular price for most of the time and periodically holds low-price sales. Then we consider the case in which a small fraction of consumers (such as price tracker users) become informed of historical prices. At the new equilibrium, the monopolist lowers the regular price and advances sales, implying shorter price cycles, more frequent sales, and a positive spillover effect of price tracker users’ informational advantage on the rest of uninformed consumers. We conclude with a discussion of the impact of price trackers on firms and other relevant managerial implications of the model. This paper was accepted by Dmitri Kuksov, marketing. Funding: Y. Chen thanks the National Science Foundation of China [Grant 71972043] for the support. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.4309 .

Breaks, trends and correlations in commodity prices in the very long-run

We present evidence on breaks, stationarity, trends, dynamic correlations, and cycles in prices for eight agricultural and industrial commodities over seven centuries. We utilise a sequential testing procedure that endogenously determines structural changes in the trend and level of each series. We find that breaks in the slope and the trend function can be attributed to major historical events such as the linking of the ‘Old’ and ‘New’ Worlds during the sixteenth century, the early free trade agreements in the nineteenth century and World War I, World War II and the Depression in the twentieth century. Give the importance of crude oil and its impact on agricultural and industrial commodities, we find a time-varying correlation structure which has intensified in the post-World War II period. We also find that three quarters of the commodity prices contain a unit root and that mean periodicity of cycles range between 30 and 35 years, depending on the commodity. These results suggest that during periods of rising or falling commodity prices, prices may not return to the long-run trend for extended periods. Consequently, there is a need for long-term planning initiatives that smooth commodity prices around the trend, with particular attention given during oil price shock.