Econometric Analysis of Radiata Pine Log Trade between New Zealand and East Asian Countries

There is an increasing interest in the sustainable supply of wood from New Zealand’s plantation forests.This is due to the importance of New Zealand in global trade and uncertainty about the sustainabilityof supply from other countries, such as Russia. The aim of this paper is to identify importantfactors that influence log supply and demand for New Zealand and its key Asian markets (South Korea,Japan and China). To this end we used annual time series data from 1990 to 2008 to estimate exportsupply and import demand functions by two stage least squares with stepwise regression estimation.We found that New Zealand’s log exports to Japan and South Korea are not sensitive to price,but exports to China are sensitive to price, while New Zealand’s total harvest has a stronger influenceon log export supply to China and South Korea. New Zealand’s domestic log consumption competeswith exports to Japan, but does not compete with supply to South Korea or China. Import demand inSouth Korea, Japan, and China for New Zealand logs is negatively affected by import price, with Japan’simport demand the most price-sensitive. The three markets differ in the impact of gross domesticproduct on import demand. Gross domestic product has a strong positive impact on log demand inJapan and China, but a modest impact in South Korea

Approximating Forest Resource Dynamics in Peninsular Malaysia Using Parametric and Nonparametric Models, and Its Implications for Establishing Forest Reference (Emission) Levels under REDD+

Forest reference (emission) levels (FREL/FRLs) are baselines for REDD+, and 34 countries have submitted their FREL/FRLs to UNFCCC by January 2018. Most of them used simple historical average without considering the stages of forest transition. This research suggested that the period of calculating FREL/FRLs of simple historical average should be properly chosen if these countries are occupying multiple stages or sub-stages of forest transition. Moreover, as a case study, this research applied both parametric and nonparametric models to approximate forest area dynamics with regard to per capita GDP in Peninsular Malaysia from 1971 to 2016. This research found that, in the case of Peninsular Malaysia, among the parametric models, the biexponential model outperformed the other growth models, while two of the nonparametric models i.e. Friedman local averaging and Nadaraya–Watson kernel smoothing models are the best among all the models on the basis of their RSS, RMSE, and MAE indices. Based on the results of our leave-last-five-out CV, however, the research found that the biexponential and Nadaraya–Watson kernel smoothing models performed best, although the performance of the other two nonparametric models remains unknown. Nonparametric model results indicated that Peninsular Malaysia experienced four sub-stages since 1971 and each sub-stage had different linear trends, yet it still did not reach the turning point of forest transition. This research also found that a linear projection using historical deforestation data when the per capita GDP level reached US$8000 was appropriate for setting FREL/FRLs

Forecasting Forest Areas in Myanmar Based on Socioeconomic Factors

National circumstances should be considered in establishing and adjusting forest reference emission levels (FRELs/FRLs) under the United Nations Programme on Reducing Emissions from Deforestation and Forest Degradation (UN-REDD+ Programme). Myanmar, one of the world’s least developed countries may face accelerating deforestation under an open and democratic political system that desires rapid economic development. This research analyzes the impacts of population growth and economic development on forest areas in Myanmar by using panel data analysis, an econometrics approach based on panel data of forest areas, population, and gross domestic product (GDP) by states and regions in 2005, 2010, and 2015. This research revealed that per capita GDP and population density gave statistically significant negative impacts on forest areas. Using the regression model obtained above, medium population growth projections, and three GDP development scenarios, annual forest areas from 2016 to 2020 were forecast. The forecasting results showed possible higher deforestation under higher economic development. Finally, this research showed the necessity of adjusting the current average deforestation for RELs in the REDD+ scheme in Myanmar and the direction in which the adjustment should go

Forecasting Monthly Prices of Japanese Logs

Forecasts of prices can help industries in their risk management. This is especially true for Japanese logs, which experience sharp fluctuations in price. In this research, the authors used an exponential smoothing method (ETS) and autoregressive integrated moving average (ARIMA) models to forecast the monthly prices of domestic logs of three of the most important species in Japan: sugi (Japanese cedar, Cryptomeria japonica D. Don), hinoki (Japanese cypress, Chamaecyparis obtusa (Sieb. et Zucc.) Endl.), and karamatsu (Japanese larch, Larix kaempferi (Lamb.) Carr.). For the 12-month forecasting periods, forecasting intervals of 80% and 95% were given. By measuring the accuracy of forecasts of 12- and 6-month forecasting periods, it was found that ARIMA gave better results than did the ETS in the majority of cases. However, the combined method of averaging ETS and ARIMA forecasts gave the best results for hinoki in several cases