Modeling and forecasting pine sawtimber stumpage prices in the US South by various time series models

Mei, Bin; Clutter, Michael ClutterM.; Harris, Thomas HarrisT.

doi:10.1139/x10-087

Cited by 39 publications

(10 citation statements)

References 35 publications

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“…In Zhou and Buongiorno (2006) the authors propose an econometric model in which space-time correlations between prices in neighboring regions are used as price predictors. In Mei et al (2010) the authors show, by applying various time-series techniques, that the vector autoregressive model provides the best forecasting for a 1-year period under the mean absolute percentage error criterion. The recent paper of Latta et al (2013) reviews the most important partial equilibrium models used nowadays in Forestry, in which commodity prices are determined endogenously.…”

Section: Price Processmentioning

confidence: 99%

The stochastic Mitra–Wan forestry model: risk neutral and risk averse cases

Piazza

Pagnoncelli

2014

J. Econ.

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We extend the classic Mitra and Wan forestry model by assuming that prices follow a geometric Brownian motion. We move one step further in the model with stochastic prices and include risk aversion in the objective function. We prove that, as in the deterministic case, the optimal program is periodic both in the risk neutral and risk averse frameworks, when the benefit function is linear. We find the optimal rotation ages in both stochastic cases and show that they may differ significantly from the deterministic rotation age. In addition, we show how the drift of the price process affects the optimal rotation age and how the degree of risk aversion shortens it. We illustrate our findings for an example of a biomass function and for different values of the model's parameters.

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Section: Price Processmentioning

confidence: 99%

The stochastic Mitra–Wan forestry model: risk neutral and risk averse cases

Piazza

Pagnoncelli

2014

J. Econ.

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“…The globalization of the forest industry has given rise to interconnections between markets and the need to quickly react to macroeconomic changes [28,29]. Therefore, increasing attention has been devoted to analysis of current market conditions and short-term forecasting, which play an essential role in managing forest resources, with prices being crucial predictors [24,[30][31][32][33]. Relatively little is known about the stochastic properties of roundwood prices, relationships between different timber markets, and in particular the ways in which they affect market policies and economic changes.…”

Section: Introductionmentioning

confidence: 99%

The Dynamics of Beech Roundwood Prices in Selected Central European Markets

Kożuch

Banaś

2020

Forests

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The European beech (Fagus sylvatica L.) is the most prevalent deciduous tree species in Central Europe. The implementation of sustainable, close-to-nature silvicultural practices increased the percentage share of beech in forest species composition, raising the economic significance of beech roundwood, especially in terms of revenues from timber sales. The elucidation of roundwood price mechanisms as well as long-term equilibrium relations between international markets may be helpful in calculating the profitability of beech roundwood production. The study material consists of quarterly time series of beech roundwood prices from Austria, Czechia, Germany, Poland, Slovakia, and Slovenia in the years 2005–2018. The price time series were described with a multiplicative model incorporating seasonal, cyclical, and irregular, as well as long-term trend components. The time series were decomposed using the Census X11 method. Stationarity was tested by means of the augmented Dickey–Fuller test (ADF) and the Kwiatkowski–Phillips–Schmidt–Shin test (KPSS). Cointegration was assessed using the Johansen and Engle–Granger methods. From 2005–2018, the highest mean beech roundwood prices were found for Austria (77.5 € m−3) and Germany, and the lowest for Poland and Slovakia. Roundwood prices were badly affected by the 2008/2009 financial crisis, which caused an approx. 27% decline. The prices of large-diameter beech logs exhibited seasonal fluctuations, typically reaching a maximum in Q1 and a minimum in Q3. The amplitude of those fluctuations was the highest in Slovenia in 2005 (10.1%), while in Czechia and Germany, seasonal effects increased over the period of study. The lowest seasonality was found in Slovakia and Austria (in the latter country it was not statistically significant). On an annual scale, cyclical changes generally accounted for the largest proportion of price variation, and were particularly pronounced in Poland (78.9%), Slovakia (78.6%), and Austria (69.2%). On the other hand, seasonal effects were predominant in the Slovenian (40.6%), German (34.1%), and Czech (33.3%) markets. In countries with price series of type I(0), simple correlation between stationary beech roundwood prices is positive and the strongest between Czechia–Poland and Czechia–Austria; on the other hand they are the weakest in the German market. In Slovakia and Slovenia with nonstationary price series, both Johansen’s and Engle-Granger’s cointegration tests indicated the absence of a long-term equilibrium between the analyzed beech timber markets. Results revealed integration between the prices of large-diameter beech logs in Czechia, Austria, and Poland. It should be mentioned that in this study, the time series of price used are rather short for long time cointegration analysis, which might prevent the proper detection of cointegration between all analyzed countries.

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“…Therefore, it is pertinent to model and forecast stumpage prices. Previous studies that examined actual stumpage prices paid in individual sales have mainly focused on two aspects: the time series of stumpage prices [2][3][4][5][6][7][8][9] and the factors influencing stumpage prices [10][11][12][13][14][15][16][17][18]. The former set of studies were aimed at examining the dynamics of stumpage markets, whereas the latter group sought to investigate the relationship between stumpage prices and factors such as harvestable volume density, the total area involved in the sale, and the diameter of the trees.…”

Section: Introductionmentioning

confidence: 99%

An Assessment of Stumpage Price and the Price Index of Chinese Fir Timber Forests in Southern China Using a Hedonic Price Model

Chen

Hong

et al. 2020

Forests

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Research Highlights: Stumpage price is the most important factor affecting the value of forests. Therefore, an understanding of the factors affecting stumpage prices and trends is critical for effective forest management. Background and Objectives: Chinese fir is the most important fast-growing timber species in China, it is also the tree species with the largest trading volume in the stumpage markets of Southern China. The aim of this study was to analyze the determinants and trends of stumpage prices for Chinese fir timber forests. Materials and Methods: Data on 928 sales of Chinese fir timber forests transacted between 2007 and 2016 were gathered from the stumpage markets in Southern China. We analyzed the relationship between stumpage prices and sales characteristics using the hedonic price method (HPM) and measured the stumpage price index with a dummy time hedonic index. Results: (1) The double logarithmic form of the HPM yielded a more accurate estimate than the semi logarithmic form. The R2ad values in the nine annual prediction models were all above 80%. Stock volume made the greatest contribution to stumpage price, followed by stand age. Stand area had no significant impact on the stumpage price. (2) Stumpage prices of Chinese fir timber forests fluctuated greatly, especially in 2010 and 2015 when the sequential price indexes were 180.01% and 74.95%, respectively. Taking 2007 as the baseline, we calculated the base price index in 2016 to be 197%, with an average annual growth rate of 7.82%. (3) The stumpage market was associated with a higher degree of risk than the timber market. Conclusions: Our findings provide valuable inputs that can guide and facilitate the Chinese government’s efforts to optimize resource allocation and standardize the stumpage market.

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Modeling and forecasting pine sawtimber stumpage prices in the US South by various time series models

Cited by 39 publications

References 35 publications

The stochastic Mitra–Wan forestry model: risk neutral and risk averse cases

The stochastic Mitra–Wan forestry model: risk neutral and risk averse cases

The Dynamics of Beech Roundwood Prices in Selected Central European Markets

An Assessment of Stumpage Price and the Price Index of Chinese Fir Timber Forests in Southern China Using a Hedonic Price Model

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