scholarly journals Market Structure and Spatial Price Dynamics

1991 ◽  
Vol 23 (2) ◽  
pp. 65-74 ◽  
Author(s):  
B. Wade Brorsen ◽  
Jean-Paul Chavas ◽  
Warren R. Grant

AbstractA method was developed with time series models to test hypotheses about the relationship between market structure and spatial price dynamics. Long-run dynamic multipliers measuring the magnitude of lagged adjustment for spatial milled rice prices were calculated from the time series model and used as the dependent variable in a regression model that included a number of factors expected to influence price determination. Results show that price adjustments were slower as regional submarket concentration increased and were faster in the regions with a higher market share. Arkansas, the state with the largest market share, was consistently a price leader.

2009 ◽  
Vol 13 (5) ◽  
pp. 625-655 ◽  
Author(s):  
Christophre Georges ◽  
John C. Wallace

In this paper, we explore the consequence of learning to forecast in a very simple environment. Agents have bounded memory and incorrectly believe that there is nonlinear structure underlying the aggregate time series dynamics. Under social learning with finite memory, agents may be unable to learn the true structure of the economy and rather may chase spurious trends, destabilizing the actual aggregate dynamics. We explore the degree to which agents' forecasts are drawn toward a minimal state variable learning equilibrium as well as a weaker long-run consistency condition.


2010 ◽  
Vol 14 (3) ◽  
pp. 499-519 ◽  
Author(s):  
Baomin Dong ◽  
Xuefeng Li ◽  
Boqiang Lin

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sviatlana Engerstam

PurposeThis study examines the long term effects of macroeconomic fundamentals on apartment price dynamics in major metropolitan areas in Sweden and Germany.Design/methodology/approachThe main approach is panel cointegration analysis that allows to overcome certain data restrictions such as spatial heterogeneity, cross-sectional dependence, and non-stationary, but cointegrated data. The Swedish dataset includes three cities over a period of 23 years, while the German dataset includes seven cities for 29 years. Analysis of apartment price dynamics include population, disposable income, mortgage interest rate, and apartment stock as underlying macroeconomic variables in the model.FindingsThe empirical results indicate that apartment prices react more strongly on changes in fundamental factors in major Swedish cities than in German ones despite quite similar development of these macroeconomic variables in the long run in both countries. On one hand, overreactions in apartment price dynamics might be considered as the evidence of the price bubble building in Sweden. On the other hand, these two countries differ in institutional arrangements of the housing markets, and these differences might contribute to the size of apartment price elasticities from changes in fundamentals. These arrangements include various banking sector policies, such as mortgage financing and valuation approaches, as well as different government regulations of the housing market as, for example, rent control.Originality/valueIn distinction to the previous studies carried out on Swedish and German data for single-family houses, this study focuses on the apartment segment of the market and examines apartment price elasticities from a long term perspective. In addition, the results from this study highlight the differences between the two countries at the city level in an integrated long run equilibrium framework.


Author(s):  
Kai-Ting Huang ◽  

The Prebisch-Singer Hypothesis states that in structural time series analysis, the terms of trade between primary products and manufacturers have a negative deterministic trend. Many researchers argued that the deterioration in trade is the type of country in which the products are exported, regardless of whether the types of products exported by such countries are primary or manufactured products. This paper employs a development-differentiated model to analyze the correlation between various terms of trade and the export proportion of manufactured products on different economies of development status. In the long run, stable co-integration relations exist between terms of trade and the export proportion of manufactured products for development status. Furthermore, the increased proportion of manufactured products exports is the Granger casualty for the worse terms of trade for several economies of development status. The results demonstrated that changing the terms of trade is significantly influenced by structured changes in the export proportion of manufactured products for the development status of economies.


2015 ◽  
Vol 11 (27) ◽  
pp. 120
Author(s):  
Osama Eldeeb ◽  
Petr Prochazka ◽  
Mansoor Maitah

<p>Indonesian biodiversity is threatened by massive deforestation. In this research paper, claims that deforestation in Indonesia is caused by corruption and supported by crude palm oil production is verified using time series analysis. Using Engel Granger cointegration test, three time series of data, specifically corruption perception index, rate of deforestation and price of crude palm oil are inspected for a long-run relationship. Test statistics suggests that there is no long-run relationship among these variables. Authors provide several explanations for this result. For example, corruption in Indonesia, as measured by CPI is still very high. This may mean that forest cover loss is possible even though there is a positive change in corruption level. According to the results, crude palm oil price has also no effect upon forest cover loss. This is likely due to very low shut-down price of crude palm oil for which production is still economical.</p>


2020 ◽  
Vol 6 (1) ◽  
pp. 273-282
Author(s):  
Majid Hussain Phul ◽  
Muhammad Saleem Rahpoto ◽  
Ghulam Muhammad Mangnejo

This research paper empirically investigates the outcome of Political stability on economic growth (EG) of Pakistan for the period of 1988 to 2018. Political stability (PS), gross fixed capital formation (GFCF), total labor force (TLF) and Inflation (INF) are important explanatory variables. Whereas for model selection GDPr is used as the dependent variable. To check the stationary of time series data Augmented Dickey Fuller (ADF) unit root (UR) test has been used,  and whereas to find out the long run relationship among variables, OLS method has been used. The analysis the impact of PS on EG (EG) in the short run, VAR model has been used. The outcomes show that all the variables (PS, GFCF, TLF and INF) have a significantly positive effect on the EG of Pakistan in the long run period. But the effect of PS on GDP is smaller. Further, in this research we are trying to see the short run relationship between GDP and other explanatory variables. The outcomes show that PS does not have such effect on GDP in the short run analysis. While GFCF, TLF and INF have significantly positive effect on GDP of Pakistan in the short run period.


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