Econometric Modeling of Deforestation

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4.3 Econometric Modeling of Deforestation

The term deforestation in this study refers to the potential deforestation, not to the real deforestation condition due to the data availability on deforestation. There are two proxies to represent the potential deforestation. First, it refers to the distortion rate which is calculated from the deviation between annual allowable cut and the real production. The negative distortion implies the presence of over- harvesting activities in wood industry. This study assumes that with the present of negative distortion, the potential deforestation will likely be higher. Second, it refers to the illegally logwood export. Since the logwood export has been banned since 1987, it is assumed that the present of logwood export is considered as illegal activities. Both proxies are converted to the amount of hectares which is calculated under the following formula: dist = AAC i – Q i where dist denotes the rate of distortion, AAC stands for annual allowable cut, Q is the logwood production quantity, and i denotes one particular period. To address the implication of wood price changes on deforestation, it simply regress the proxy variable of deforestation the dependent variable with the variable of domestic prices of wood products, particularly as described in the following equation. This study employs two regression models according to the proxy of deforestation: 1 semi logarithmic regression, and 2 logarithmic regression. dist = + 1 lnpdl + 2 lnpdl + 3 lnpdl + 4 lnpdl + 5 lnpdl + 6 lnpdl + 1θ where : dist : distortion rate pdl : domestic logwood price IDRm 3 pds : domestic sawnwood price IDRm 3 pdp : domestic plywood price IDRm 3 pwl : world logwood price m 3 28 pws : world sawnwood price m 3 pwp : world plywood price m 3 n , n : estimated parameters 0, 0 : constanta , ν : residuals To check the significance of each independent variable refers to the values of t-statistic. Meanwhile, the significance of the overall model is evaluated by observing the value of F-statistics. If the p-value of the statistics is less than the desired level of significance 1 percent, 5 percent, and 10 ten percent, it can be concluded that the variable is statistically significant. Furthermore, whether the variance of the model can represent the variance of the dependent variable is checked by referring to the value of R-square and adjusted R-square. The R- square denotes how many percent the model the independent variables which are involved in the model can explain the variance of the dependent variable. 29 5 PRICE TRANSMISSION ANALYSIS BETWEEN DOMESTIC AND WORLD PRICE OF INDONESIAN WOOD PRODUCTS This chapter explains the result of price transmission analysis as mentioned in the first objective of this study. First, it begins with the analysis of stationarity of data using Augmented Dickey Fuller test which is necessary for the next step of analysis. Second, it continues with co-integration analysis between world and domestic level of wood prices using two-step engel-granger and Johansen techniques. Then it also provides results from granger causality test. The price transmission between world and domestic wood products prices is estimated by using the standard linear error correction model. Stability analysis is also conducted in the ECM by using Chow test. The last part is discussion which gives the summary of the whole analysis in this chapter emphasizing whether the prices in world and domestic market are co-integrated and its implications. Some recommendations for further research are mentioned as well mainly with regard to price transmission model. Initially, monthly price data, which are available for this study, are from 1997 until 2011, but only data from 1998 are included in the analysis due to the presence of economic crisis during 1997. As shown in the three figures: figures 6, 7, and 8, it is indicated the extreme contradictory trend between the domestic price and the world price which could generate the strange result from statistical perspective. Meanwhile, the data which are used for the econometric modeling of deforestation are annual data from 1978 until 2007. 30 Figure 5 Plot Series of Logwood Figure 6 Plot Series of Plywood Figure 7 Plot Series of Sawn wood

5.1 Unit Root Test