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econometric analysis of china\'s plywood market.

by:Qin Ge Ceramic & Building     2020-03-12
Primary wood in China
Wood processing industry
In recent years, the consumer industry has experienced rapid growth.
Plywood is the most important primary wood product in China in terms of consumption, production and export.
One of China\'s most important export destinations is the United States, which exports not only plywood to the United States, but also wood in the form of furniture to the United States.
In this paper, we analyze the development of China plywood industry since 1990;
Overview of the demand, supply and export of plywood in China;
And give the results of the measurement economy model. The Engle-Granger error-
Revised model applied to annual time analysis
Series data from 1993 to 2007.
The results show that the growth of Plywood Demand in China is mainly driven by the growth of consumer income, while the increase in product prices has only had a small negative impact.
In contrast, the rise in raw material prices has had a significant negative impact, but in the end
The use of sector activities had no significant impact on the supply of plywood in China.
Over the same period, China\'s Plywood Export growth benefited from the growth of consumer income in the US market.
The flexibility and knowledge found here can serve as a useful reference for foreign and domestic wood products companies that plan to invest, as well as government agencies and public authorities that plan economic and forest policies.
China\'s unprecedented economic growth in the past 30 years has led to strong demand for various commodities.
At the same time, the growth in global demand for forest industrial products is shifting from Europe and North America to China.
China\'s booming economy, its large population, growing construction activities and housing reform have driven a sharp increase in infrastructure development, construction, wood and wood products consumption for interior decoration, furniture manufacturing.
Market growth is also a major driver of foreign direct investment (FDIs)
To China in the forest (
EY company 2009).
With China\'s incentive policies for forestry development and low
In developed countries, many companies have invested in timber in China-
Processing industry in recent years.
China has become the world\'s largest timber processing country, export price
Competitive value-
The addition of wood products, mainly furniture, followed by plywood (Wan 2009).
China is the largest furniture exporter in the world, and the largest export destination is the United States.
China exports 43 in 2007.
5% of the furniture is sold to the United States, 22.
1% of the EU.
China is also the world\'s largest exporter of plywood, and the United States is China\'s second largest destination.
Followed by Saudi Arabia, the United States imports 9.
6% of plywood in China in 2007 (
Alberta China officeACO]2008).
However, due to the increase in labor and production costs, reliance on log imports, the appreciation of the RMB and the reduction of export tax rebates in China, as well as the recent anti-dumping and stricter environmental regulations in the United States, as well as the downturn in the US real estate market, the competitive advantage of Chinese manufacturers has been weakened.
This forced the United States to seek a lower
Cost location such as Vietnam or Cambodia (
Pullman and Schuler 2009)
And encourage some large Chinese exports.
Wood products-oriented companies shift focus to domestic markets and expand market share in other regions such as the Middle East, Africa and Japan (ACO 2008).
At the same time, consumers\' increasing sensitivity to greener products will provide an advantage for domestic furniture manufacturers in the United States who intend to produce on a large scale.
Custom and green furniture (
Pullman and Schuler 2009).
Despite the negative impact of the recent global recession on China\'s wood products trade, at the end of 2008, the Chinese government acted quickly, stimulate domestic demand by implementing a policy of reducing taxes on home purchases and local interest rates by 30% (
Timber Market Report 2010.
However, there is little research on China\'s forest product market.
For example, Li and others. (2006)
The demand model for paper and cardboard products in China was investigated. Wang and Wu (2000)
Factors related to Plywood Demand and supply affecting the Taiwan market were investigated.
However, due to limited reliable time,
So far, there has been little academic research on the Chinese wood products market.
Since plywood is an important export product of China\'s wood products industry in the international market and an important raw material of China\'s huge furniture industry, we are here to focus on China\'s Plywood Market.
We analyze the market situation by estimating the metrological economic model of factors affecting the demand, supply and export of plywood in China.
Since China\'s plywood industry has experienced rapid growth since the beginning of 1990, we have been analyzing since 1993.
In the following sections, we review the development of the plywood industry in China.
We then outline the econometric models used in statistical analysis, describe the methods and data used, and give empirical results.
Finally, we briefly discuss these findings and compare the results with previous studies to identify the main areas of future research.
The development of China\'s plywood industry the rapid growth of China\'s economy has led to a surge in housing, luxury hotels and office space construction.
The rise in living standards and the emergence of affluent consumers have translated into higher consumer demand.
Quality wood for home and office decoration and furniture (Sun et al. 2005).
China\'s housing reforms aimed at privatizing public housing have stimulated demand for affordable energy.
High efficiency
The quality of the home, better facilities, thus driving the demand for decorative wood products.
Due to the large population and the continuous progress of urbanization, the Chinese government has been taking measures to increase housing supply.
In response to strong domestic demand for these strong residential buildings,
China\'s plywood industry, especially hardwood flooring, has made great progress in related activities and real estate development.
Hardwood floors are used as the preferred material for interior, floor molding, wall panels, doors, windows and kitchen cabinets, while Cork plywood is widely used in house buildings.
Market growth is also the main driver of China\'s forestry FDIs (
EY company 2009).
With the arrival of a large number of foreign enterprises and the establishment of joint ventures, especially China\'s accession to the World Trade Organization, the inflow of foreign direct investment has increased dramatically.
The high cost of local labor, land and raw materials and the limited domestic market have encouraged plywood enterprises in Taiwan, Hong Kong, Singapore, and other countries to invest and transfer their facilities to China.
The introduction of modern equipment, strict quality control and continuous improvement of technology have enabled China plywood to meet the quality standards of the international market (
Adams and MA 2002).
Statistics from the State Forestry Administration show that the production of plywood in China has increased from 2. 13 million [m. sup. 3]in 1993 to 35. 62 million [m. sup. 3]in 2007.
In the total production of plywood in China, hard plywood accounts for about 85%.
About 80% of hardwood floors are used in the furniture, non-structural building materials and interior decoration industries (
International Trade Commission of the United StatesUSITC]2008).
In 2003, China overtook the United States as the world\'s largest producer of plywood.
With the rapid growth of plywood production in China, the import of logs will increase in the future.
For example, Ashley, one of the largest furniture companies in the United States, has set up a factory in Kunshan city, Jiangsu province, China.
The furniture made in China has not only opened up the retail market in China, but also opened up the United States and the global market (ACO 2008).
The plywood industry in China is highly dispersed by a large number of small-
Scale is big of the company and quantity is less of inand large-sized entities.
It is estimated that there are more than 5,000 plywood factories: small-
Small and medium-sized factories play a vital role in China\'s plywood industry, while medium-sized factories
Large factories and large factories account for 30% of China\'s total plywood production capacity and less than 10%.
Four pieces of plywood.
China manufacturing base: Jiangsu pzhou, Zhejiang Jiashan, Linyi, Shandong, Hebei Zhengding.
As the world\'s largest exporter of plywood, state p played a key role in China\'s growth as more than 35% of plywood manufacturers in the region exported their products.
In Jiashan, the plywood industry has become a pillar industry in the county.
However, due to the remote location of the plantation, it is difficult for the factory there to export (
Ryden and Tan 2004).
China imports plywood from 1980.
From 1993 to 2007, China\'s plywood trade developed rapidly.
Figure 1 shows that 1998 is a watershed in the import of logs and plywood from China.
Before 1998, China\'s tropical timber imports were mainly low.
Plywood prices are high in Indonesia and Malaysia.
This has seriously damaged the competitive position of Chinese manufacturers, so the Chinese authorities have to cancel tariffs on the import of logs and crack down on the smuggling of plywood.
In the case of a ban on logging in China and a reduction in tariffs on log imports to zero, the slow decline in log imports suddenly escalated rapidly after 1998. [
Figure 1 slightly]
Figure 2 shows the opposite trend of China\'s plywood trade: the import of plywood from 2. 23 million [m. sup. 3]
Only 306,600 by 1993 [m. sup. 3]in 2007.
In 2007, plywood was imported mainly from Indonesia and Malaysia, accounting for 45. 8 and 32.
7% respectively (Wan 2009).
Due to the competitive price of plywood production as a labor force --
China\'s plywood exports have experienced strong growth in the international market, from 94,000m. sup. 3]in 1993 to 8. 78 million [m. sup. 3]in 2007.
By contrast, imports have been negligible and have declined in recent years.
In 2001, China\'s plywood exports exceeded imports for the first time. Since then, China has become a net exporter of plywood, mainly for the United States, Japan and the United Kingdom (Wan 2009).
China has become the world\'s largest exporter of plywood since 2003. Ma 2008).
From 2002 to 2006, China\'s hardwood flooring exports to the United States increased by 8 times, mainly driven by the growth of the US housing market (USITC 2008).
According to the calculation of production plus import minus export, the apparent consumption of plywood in China is from 4. 26 million [m. sup. 3]in 1993 to 27. 14 million [m. sup. 3]in 2007 (Wan 2009).
As shown in Figure 2, two-
The third purpose of production is to meet domestic demand.
It is reported that hard plywood sold to the domestic market in China is often used to make furniture, which is usually exported to developed countries including the United States (USITC 2008).
The theoretical background analysis of China plywood market is based on the model structure proposed in the previous research on forest product market modeling.
In a pioneering study, Buongiorno (1979)
Modeling the demand of forest industrial products as consumer demand, after which the demand modeling is usually based on the derived demand method (
Good morning, 1996, good morning, etc.
2003, heemaki and others.
2004, Hanninen and others. 2007).
In order to simulate the import and export of forest products, Amington (1969)
Theory is often applied (
Hanninen 1998a, 1998b;
Hanning en and Tobin Ning 1999).
A simple form of product supply can be expressed as a function of its price (
Koutsoyiannis 1977)and end-
Using departmental activities (
Buongiorno and others. 2003). [
Figure 2:
The apparent consumption of plywood in China is a classic double
Logarithmic formula (Good morning 1979)
The consumption is explained by consumer income and the actual domestic price of Chinese plywood.
Because there is no exact annual data during the study period, China\'s actual gross domestic product (GDP)
The actual export unit price of Chinese plywood is used as an agent.
Therefore, the estimated equation after the logarithmic transformation of the variable can be expressed as follows :[
Mathematical expressions that cannot be reproduced in ASCII](1)
LACP is the apparent consumption of plywood in China, LGDPR is the actual GDP of China, LEPR is the actual export price of plywood in China, a is constant, B and c are respectively, the income elasticity and price elasticity of demand, u is the error term, t represents the time.
The symbol under the coefficient represents the expected symbol of the estimated coefficient: indicates the positive number and--
Negative sign.
Plywood Supply Mode China\'s Plywood Supply is a function of price (
Including product price and raw material price)and end-
Use Department activities.
Supply of plywood and ends
The activities of the use department are described by the production volume of plywood and wooden furniture respectively, while the product price and raw material price of plywood production are indicated by the actual plywood price and the actual log price respectively.
Since there was no exact data during the study, the existing data on the actual unit export price of Chinese plywood and the actual unit import price of Chinese logs were used as agents for the actual domestic price of Chinese plywood and logs, respectively.
Therefore, the estimated equation for the supply of plywood can be given in the following logarithmic form :[
Mathematical expressions that cannot be reproduced in ASCII](2)
Among them, LQP is the production volume of Chinese plywood, LWFQ is the production volume of Chinese wooden furniture, LEPR is the real export price of Chinese plywood, LIPR is the real import price of Chinese logs, and a is a constant, B is the supply elasticity of furniture production in China, C and d are the price elasticity of plywood and the logarithmic price elasticity of supply respectively, u is the error term and t represents the time.
As shown in equation 1, symbols under coefficients represent the type of desired symbol (
Positive and negative)
The estimated coefficient.
China\'s Plywood Export is Armington (1969)
Export demand theory
As the largest export destination of Chinese plywood products, the United States represents the entire export market of China.
According to Amington\'s theory, the export of Chinese plywood is explained by the consumer income of the export market and the actual export price of Chinese plywood.
In this model, it is also necessary to describe the agent of the empirical variable: the income variable of the export market is described by the actual GDP of the United States, the actual unit export price of Chinese plywood to the United States is by the United States market flat reduction index (Wan 2009).
The logarithmic form of the specification is [
Mathematical expressions that cannot be reproduced in ASCII](3)
Among them, LEP is the total export volume of Chinese plywood, LUS is the actual GDP of the United States, LEPR is the actual export price of Chinese plywood, a is constant, and B and c are respectively, the income elasticity and price elasticity of export demand, u is the error term, t is the time.
As shown in equations 1 and 2, symbols under coefficients represent the desired symbol (
Positive and negative)
The estimated coefficient.
The methods and data we applyGranger (
Engel and Grainger 1987error-
Correction method (ECM)
Measure economic estimates in two steps, which willrun from short-
Operating effect of plywood market model.
In general, sound time-
Series modeling should be described at the same time
Run balance and short term
Running dynamics at the same time (
Asterio and Hall 2007).
For this, from long-
Balance regression was used after the first run
Estimate step estimates for ECM.
This, in turn, is used to analyze the length. run and short-
The running effect of the variable and the viewing adjustment coefficient.
This coefficient is called lag error-
Amendment (ECT)
This is the long term lag remaining item
Running relationship (
Asterio and Hall 2007).
ECM will be from long-
Short-term operational relationships found in co-integration analysis
Dynamic factors of operation (
Engel and Grainger 1987.
However, before modeling, we need to take advantage of the enhanced Dickey-Fuller (ADF)
Unit root test method (
Dicky and Fuller 1979, Abildtrup, etc.
1999, Helles and others. 1999)
Test the stability of the time series.
Then, according to Engle-Granger (1987)
Program, we use the ordinary least squares (OLS)
A regression method for estimating equations 1, 2 and 3 and obtaining their residual values.
With the help of the ADF test, we are also able to test the stability of the residual value.
If the residual value is stable, the variable is cointeger and has a long time
Running balance relationship (
Asterio and Hall 2007).
For the remaining diagnostic tests of the two stages, Breusch-Godfrey (BG)
, The multiplier (LM), and Jarque-Bera (JB)
The self-correlation, variance and normality of residual values were tested respectively.
Empirical analysis using EViews statistical software (
Quantitative Micro Software, Irvine, California Limited).
The demand, supply and export elasticity of plywood in China is estimated by using annual data for the period 1993 to 2007.
We suggest this 15-
The annual sample represents the most meaningful data span in Chinese Plywood Market Modeling.
Despite a small number of observations, we note that data span or data frequency increases to monthly or quarterly levels will not be able to extract basic information about these market adjustments.
However, a small amount of observation data does not allow us to use system estimates, so the results of Equations 1 to 3 must be estimated separately.
Detailed data sources are explained in the Wan (2009)
The most important sources are the China Statistical Yearbook, China Customs statistics, the China State Forestry Administration, the National Bureau of Statistics of China, the World Bank Development Indicators database, and the US Bureau of Labor Statistics.
China\'s GDP, the export price of Chinese plywood and the import price of Chinese logs were originally calculated in nominal US dollars, but were converted into actual US dollars by China\'s GDP deflator index, the benchmark year is 2004.
The real GDP of the United States is converted into US dollars with a purchasing power parity of 2005 (Wan 2009).
Results analyze the time before the model is formed and estimated-
The series of attributes of the data, for example, normality and stability.
The JB test shows that all series appear to be distributed normally.
The ADF unit root test results shown in Table 1 show that there are first-order stationary and non-stationary variables in the dataset.
LEP, LQP, and LWFQ are static at the horizontal level, while LACP, LEPR, and LIPR are static at the horizontal level, but become static at the first difference.
LUS is non-stationary in both levels and in the first difference, but becomes stationary in the second difference.
In contrast, the test results of LGDPR are not clear because it is not only horizontal, but also non-stationary after the second difference.
Next, the model is estimated in two stages.
In the first phase, we used OLS to estimate the demand, supply and export functions of Chinese plywood, where logarithmic variables were used.
In the second phase, we estimatedrun ECM models.
These results are shown in Tables 2 and 3, respectively.
Plywood Demand model first-
The stage estimation results of the Chinese Plywood Demand model shown in Table 2 are expressed in equation 4, with T values in parentheses :[
Mathematical expressions that cannot be reproduced in ASCII](4)
Among them, all the estimated coefficients showed the expected signs, and the demand for plywood in China (LACP)
It seems that income is resilient, but prices are not, and the impact of prices on LACP is not statistically significant.
As shown in Table 2, [Adjusted [R. sup. 2]
The variance of 85% in the LACP series is explained, and the F statistics show that the coefficients are generally significant.
Nevertheless, it should be borne in mind that in the presence of non-stationary variables, t statistics do not follow the standard t distribution;
So these long
The operating coefficient cannot be explained as usual.
BG, JB, and LM tests show that there is no problem with self-correlation, normality, and variance in the remaining sequences.
Based on ADF statistics, the residual value is stable, so we assume that the variable for a long time
Collaborative running demand model.
So we started the second one.
Phase estimation.
In the second phase, the ECM is estimated using the first difference of the variable and from the first-stage model. [ECT. sub. (t-1)]
Error correction term of lag.
The results given in Table 3 are represented by Equation 5, with T values in parentheses :[
Mathematical expressions that cannot be reproduced in ASCII](5)
In the short term, revenue and price factors also show signs of expectation.
Coefficient of lag ECT measures the adjustment speed of the response variable to its long-term responserun value.
This shows that LACP is almost completely adjusted (over 99%)in 1 year.
By contrast, the adjusted [R. sup. 2](0. 53)in first-
The differential form is lower than the horizontal form, except for the remaining items according to the diagnostic test.
Plywood Supply model estimate-
The phase coefficients of the plywood supply model shown in Table 2 are expressed in Equation 6.
Since the estimated coefficient shows the wrong negative number, the plywood price LEPR drops from equation 4.
Therefore, the regression equation with t value in parentheses is [
Mathematical expressions that cannot be reproduced in ASCII](6)
Coefficient of wooden furniture production in China (LWFQ)
And the real price of logs (LIPR)
If there are expected signs, this means that the increase in LWFQ increases the domestic supply of plywood, while the increase in LIPR reduces the domestic supply of plywood.
Plywood Supply in China (LQP)
It seems to depend on LWFQ and LIPR.
Obviously, the unit export price of plywood is not a suitable proxy variable for the domestic plywood price.
Therefore, it is not possible to estimate the impact of Plywood prices on their supply. The long-
Operating supply mode (Eq. 6)
Because after adjustment [R. sup. ]
Explains 79% of the differences in the LQP series.
The coefficient is significant, according to F statistics.
Nevertheless, due to the presence of non-stationary time series, the t statistics again failed to follow the standard t distribution.
The residual value test shows that the model also has no self-correlation, normality or variance, and the residual value is stable according to ADF statistics.
So, variables in long-
It is also assumed that the running supply model is co-integrated.
Enterprise content management is based on this first
Stage regression equation.
The results in Table 3 are represented by Equation 7 with t values in parentheses :[
Mathematical expressions that cannot be reproduced in ASCII](7)The short-
The results of the operation show that the coefficient of the first difference of the lwq represented by alwq shows the expected symbol, but the coefficient of the first difference of LIPR expressed in ALIPR is that this is contrary to our expectations of economic theory.
However, the effect in the short term may be different from that in the long term
Because economic theory focuses on long-term operational relationshipsRun balance.
The lagging ECT coefficient shows that LQP is adjusted by more than 92% in 1 year.
And long-
Operation mode, adjusted 【R. sup. ]in the ECM (0. 63)
Quite low, the test shows that there is no serious problem with the self-correlation, normality, or variance in the remaining sequence.
Plywood Export model first-
The stage estimation results of the Chinese Plywood Export model shown in Table 2 are expressed in equation 8.
In this model, the estimated coefficient of the export price of Chinese plywood LEPR also showed the wrong sign, so it dropped from Equation 3.
Therefore, the regression equation with t value in parentheses is [
Mathematical expressions that cannot be reproduced in ASCII](8)
The coefficient of actual GDP in the United States (LUS)
Showing the expected signs and the export of plywood in China (LEP)
S. Consumer income is highly dependent.
According to economic theory, the dependence of export demand on the export price of products is negative, but the coefficient is positive in the estimation.
This may be because the unit price of the total export volume of Chinese plywood is inaccurate, representing the export price of Chinese plywood to the United States, or the multiple colinearity between GDP and price in the model. With 0.
91 after adjustment [R. sup. ], the long-
The running model shows good fit again.
The residual test shows that there is no problem with self-correlation, normality or variance, and the surplus is stable based on ADF statistics.
Again, let\'s assume long-
Run export model is integrated.
In the second phase, the ECM estimates for the plywood outlet shown in Table 3 are expressed in equation 9 with t values in parentheses :[
Mathematical expressions that cannot be reproduced in ASCII](9)The short-
The operational revenue elasticity showed positive signs of expectation but was not statistically significant.
The coefficient of the lagging ECT indicates that the LEP adjusted more than 50% in 1 year, which means that the whole market adjustment takes about 2 years.
However, F statistics show that not all regression coefficients are significant, so we conclude that the results of the export model are not satisfactory, which may be due to the first problem --
Phase estimation.
Using statistical analysis of China Plywood Market and discussion and conclusion of measurement error
Revised modeling method, this paper estimates the long-termrun and short-
Elasticity of demand, supply and export of plywood in China.
As expected by economic theory, our empirical results show that both income and product prices are important demand determinants, but the income effect is the main driver.
The elasticity of demand income is roughly single (1. 11)
China\'s demand for plywood is growing at almost the same rate as China\'s economy and consumer income.
Similar size in length-
Li et al found the effect of running income in a previous study. (2006)
The paper market in China, while in buyono (1979)
Long estimated time-
According to international data, the operating income elasticity of Plywood Demand is 0. 95.
And long-
Short-term operational impact
The operating income effect of China\'s plywood demand is much lower.
Regarding the price of Chinese plywood, it affects the demand of Chinese plywood in the long run, but has no effect in the short term.
The order of the Dragon-
Low price elasticity for running Chinese Plywood Demand (-0. 33)
This also reflects the fact that if a commodity is used in a small amount in the consumer economy, its price may not play such an important role in its market.
This is the case with the use of plywood in Chinese buildings, wooden furniture or other related end-use.
Although China\'s domestic demand for plywood is growing, due to its large land area and large population, the use of plywood in the construction and furniture industry is relatively small.
The low price elasticity may also be due to the use of agency prices (export price)
Rather than the exact price variable (domestic price)
And Engel and Grainger (1987)
Method cannot be used for two-
Phase least squares estimation of price endogenous.
Our estimate shows the domestic supply elasticity of the price of plywood and raw materials in China (
Import price of logs in China)and end-
Using departmental activities (
Production of domestic wooden furniture)were -1. 67 and 0.
72 respectively.
This shows that China\'s plywood supply has a strong elasticity in terms of changes in log prices, but lacks flexibility in the production of wooden furniture, which means changes in the log market, however, the production of furniture has had a significant negative impact on the supply of plywood in China.
Our results can be compared with the results of Wang and Wu (2000)
He estimated the domestic supply elasticity of Taiwan plywood in terms of raw material prices (
Import price of logs)and end-
Using departmental activities (
Residential building area)as -1. 02 and 0.
31, which means that the supply of Taiwanese plywood has fallen at almost the same rate as the price of logs has risen, but is more resilient in terms of the final price
Use Department activities.
Due to limited forest resources in China and rising prices of imported logs from Russia, the domestic supply of logs has been unable to meet the growing demand for logs.
In fact, the supply of raw materials is currently the biggest challenge facing the plywood industry in China.
In order to remain competitive in the global wood products market, it is clear that China will have to find new sources for logs, and Russia will be the most likely source if export tariffs do not increase too high (Solberg et al. 2010).
From the perspective of foreign investors, there may be some alternative solutions;
For example, they can work with local Chinese partners to develop plantations in China or import logs at reasonable delivery prices.
Most notably, during the period from 2002 to 328%, U. S. Exports of hard wood to China increased by 2007 (
Schuler and Pullman 2008).
Corresponding to the above results, the impact of furniture production on the supply of plywood in China is negligible, which again means that the use of plywood in the furniture industry in China is still very small.
According to the measurement results, China\'s plywood exports are highly dependent on the income of consumers in the United States.
In addition, there are other factors that may affect the future export of Chinese plywood to the United States, but because the data is not available, it is difficult to be included in our metrological economic analysis.
These factors include recent revisions to the Lacey Act, the green building movement and the US formaldehyde standard.
To combat illegal logging, the revised Lacey Act of the United States not only prohibits logs and timber, but also applies to all forest products.
In fact, many Chinese wood products are made of wood harvested from countries where illegal logging and other legal acts that violate the Lacey Act.
For example, in the huge and rapidly expanding hardwood flooring market, from 2002 to 2007, Sino-US trade grew at a rate of 37% per year, as most of the wood was supplied from high places
Risk countries such as Russia, Papua New Guinea, Malaysia, Gabon and Solomon Islands (
International Network of environmental compliance and law enforcement 2008).
Therefore, this legislation will affect manufacturers and exporters that ship various products made of wood to the United States, including furniture, plywood and flooring made of illegally harvested wood (
Gregg and Bogg 2008).
Similar to the Lacey Act, Forest Law Enforcement, Governance and Trade (FLEGT)
Aimed at cracking down on illegal logging and related trade outside the United States, and will take effect on 2012, which may affect China\'s export of plywood and furniture to Europe.
China\'s growing reliance on timber imports and expectations of future economic growth mean that China\'s demand may continue to have a huge social, environmental and economic impact on forest and forestry personnel.
These trends will continue to challenge the efforts of non-governmental organizations and some governments to address the problem of illegal logging and trade, as well as the establishment of a sound supplier forest management body (Sun et al. 2004).
Driven by the increasing public impact on global climate change, the cost and availability of non-renewable energy sources, and the impact of the building environment on human health and the natural environment, the transition to green buildings.
Green buildings emphasize the use of renewable resources, such as fast and renewable plant materials such as solar energy, bamboo and straw, as well as certified, sustainably managed forest wood.
The green building movement in the United States may affect the demand for wood products in the United States in housing construction, interior decoration and furniture, thus affecting China\'s hardwood flooring and furniture exports to the United States.
In addition, some Chinese plywood and low-
The formaldehyde content of furniture is very high.
In order to reduce the formaldehyde emission of wood products, it is healthier and more environment-friendly.
The United States recently signed a new law (O\'Donnel 2010)
Limit the content of formaldehyde in composite wood products such as hardwood floors, plywood and cardboard.
Similarly, most European countries have passed laws on formaldehyde.
All of this will lead to higher prices for furniture and cabinets, thus limiting China\'s export of plywood and furniture to the United States and Europe.
Like China\'s exports, in addition to the economic factors we include in the model, there are other factors that may affect the demand and supply of plywood in China, such as population growth, urbanization, construction demand, expansion of wood processing capacity and relaxation of trade and foreign investment.
Nevertheless, not all possible factors and explanatory variables can be included in the model.
We must reduce the selection of variables based on economic theory, limited degrees of freedom in the model, statistical features, and data availability.
Due to data constraints, a relatively simple time can only be estimated-
China plywood series
However, due to the rapid growth of volatile markets, it makes no sense to merge longer data spans or higher data
Frequency data in the estimation process.
Many other researchers, such as Hondroyiannis and Papapetrou (1995)
And, though it\'s simple, Engel-
The Grainger method used in empirical analysis also revealed some shortcomings.
First of all, when there are more than two variables, there may be multiple co-integration relationships and Engle-
Using the residual value of a single relationship, this possibility cannot be dealt with by the Granger program;
Therefore, the most important problem is that it does not give us the number of total integral vectors.
Second, since Engel-
There are two ways to rely on Granger Law
Step estimator, any errors introduced in the first step will be brought into the second step (
Asterio and Hall 2007).
Nevertheless, we believe that the method we have chosen is the best choice for the study at hand, with more statistically elegant methods such as Johansson (1995)
When the statistical base is allowed to be used, a vector self-regression model can be used (
Toppinen 1998, Abildtrup et al. 1999).
Nevertheless, we still hope that the existing results of the statistical model can be used as a useful reference for Wood
In particular, plywood companies, government agencies and processing companies that act as public authorities for decision makers.
Strong economic growth and large population in China
Based on the market potential, we have reason to expect the plywood market in China to continue to grow globally.
This will encourage more local and foreign investment in the Chinese Plywood Market, thus increasing the use of plywood in China.
To this end, increasing the price of plywood may not be an obstacle to the consumption of plywood.
In order to obtain more satisfactory statistical results, future research should focus on collecting more accurate data from China.
Although our findings can be applied to a range of topics, there is still a significant need for further analysis, modeling and synthesis for the world\'s fastest growing Plywood Market.
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The authors are researchers and professors, respectively. of Forest Sci. , Univ.
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Topinen @ Helsinki. fi);
Senior researcher, Finnish Forest Research Institute
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The document was published in April 2010. Article no. 10747.
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