Lunyu Xie Forest Stock And Harvest In China After The

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  • 1. Forest Stock and Harvest in China after the Reform By Peter Berck, Lunyu Xie and Jintao Xu We thank the S.J.Hall Fund
  • 2. Outline
    • Background
    • Research Question
    • Theory
    • Data
    • Empirical Tests
    • Results
    • Conclusion
  • 3. Background
    • 1950-1960 Consolidation of forest and agricultural land into state and collective management
    • 1981 Three Fixes Policy; Agricultural and forest land tenure reform
    • 1980s Fujian Province explores alternative path of shareholding system
    • 2002 Rural Contract Law introduced
    • 2003 Resolution on Development of Forestry adopted; Fujian Province decentralizes collective forests
    • 2004-2007 Ten additional provinces announce new round of forest land tenure reforms
    • 2006 New Countryside Development Initiative announced
    • 2008 National guideline on forest tenure reform to be issued by State Council
  • 4. Question of Interest
    • Do private forest owners behave as present value maximizers ?
    • If so, what changes in rotation age, harvest and volume do we expect to see?
  • 5. Theory
    • The main economic facts that count for differences in treatment between government and private ownership
      • Interest rate
      • External values
      • costs
    • We expect a shorter rotation period, and a higher harvest associated with a higher volume when private
  • 6. Data * * * * * Households * * Cell phone * * Phone * * * * * Income * * * Permit * * Labor Force * * Land * * * * * Population * * * * * * * * * Forest Land * * * * * * * * * Volume * * * Harvest 2005 2004 2003 2002 2001 2000 1995 1990 1985
  • 7. Empirical Tests
    • We estimated growth and harvest as a function of volume and other covariates
    • We expect that most villages will have average volumes that exhibit strong and positive net growth.
    • We expect that harvest will be increasing with volume, but household characteristics will not matter.
  • 8.
    • Two regressions:
      • Growth function, to compare the marginal growth with an interest rate and predict the growth classes that will be harvested
      • Harvest function, to see what the relation is between harvest and volume and household characteristics.
  • 9.
    • Growth function
      • Regress annual growth G on the beginning of the period volume in m 3 /mu
      • G is calculated for the 2002-03 and 2004-2005 intervals as the change in volume plus harvest
      • Number of observations is 66 and R square is 0.32
    -4.4994*** (0.5706) 0.8829*** (0.2362) -.0538 *** (0.01940) constant vol vol 2 log(G)
  • 10.
    • Growth and the slope of growth
  • 11.
    • Harvest regression
      • Tobit with instrumental variables
      • Percentage of phone use as an instrument
    • Many plausible regressions
    • Consistent positive value of the coefficients on volume, ranging from 0.013-0.028
    • Household characteristics are not significant
      • Number of observations is 69.
    0.0293884 (0.2538027) 5.75e-06 (0.0000924) -0.1958474 (0.1865536) 0.0124005* (0.0066224) 0.026532 (0.2322212) 4.14e-07 (0.0000648) -0.1845147 (0.1474787) 0.0665504 (0.1715402) -0.0348751 (0.0641979) 0.012671** (0.0051543) constant income ppd laborp workoutp vol yh
  • 12.
    • Alternative identification: lagged variables.
    • Results are broadly consistent with previous.
      • Number of observations is 32
    -0.0984967 ( 0.0797639 ) 0.0401263 *** (0.0154786) -0.0779717 0.1470662 0.0000275 (0.0000437) 0.0229257 * (0.0136693 ) 0.0029956 (0.195711) 0.0000292 (0.0000606) -0.0613472 (0.1771524) -0.0740891 (0.151716) -0.2308471 (0.5443996) 0.0205537 (0.0160033) constant income00 laborp00 workoutp00 ppd05 vol04 sharvest05
  • 13.
    • Household characteristics are not significant in any formula
    • Likelihood Ratio test does not reject zero for all of them
    • No evidence that the households act differently than firms
  • 14.
    • Prediction of harvest
      • A censored value of harvest prediction given the observations of all independent variables
      • Use the sample mean value for all but the volume
      • When volume increase 1 cubic meter, harvest increases 0.2 cubic meters.
  • 15.
    • Test the different harvest behavior of village and private ownership
      • Regress harvest on the private volume and non-private volume
      • Test for whether the coefficients are equal.
    • Get the different coefficients, but not significantly different.
    • One explanation could be that most fruit trees are in private hands, and we don’t distinguish them from timber trees in our data for private percentage
      • Number of observations is 156
    -.1131343*** .0395075 0.0271118** 0.0111501 0.03214*** 0.0066054 constant (1-%private) * volume %private * volume harvest
  • 16. Future research
    • Puzzle : growth, even for high volume villages, is above the predicted harvest.
      • It does not appear likely that volume will increase without bound
      • We are examining these functions further, hope to find that harvest function has greater upwards slope.
    • In terms of optimal management, we want to know the value of trees as a function of volume. Are villages with higher volumes producing for sawtimber where the lower volume villages are mainly producing for polewood, firewood, etc.?
  • 17. Conclusion
    • The growth rate peak is 0.9 m 3 /mu at a volume of 8 m 3 /mu,so we expect to find most villages with volumes below that number and our data does support it.
    • The data do not contradict the idea that the plots are managed in the way a competitive firm would manage them.
    • The data on harvest does support that harvest increase with volume. However, the predicted increase is not enough to counter growth.
    • Harvest increases differently with private volume and with non-private volume, but not significantly.