1. 1 CM Optimal Resource Control Model & General continuous time optimal control model of a forest resource, comparative dynamics and CO2 storage consideration effects Peter Lohmander Presented in the seminar series of Dept. of Forest Economics, Swedish University of Agricultural Sciences, Umea, Sweden, Thursday 2008-09-18, 1400 – 1500 HRS Marginally updated 111215

2. 2 First some General optimal control theory

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7. 7 Taylor expansion:

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16. 16 is not a function of Hence, we may exclude from the optimization.

17. 17 is optimized via We assume an unconstrained local maximum.

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19. 19 The adjoint equation:

20. 20 Terminal boundary condition:

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22. 22 The maximum principle: Necessary conditions for to be an optimal control:

23. 23 Now, a more specific Optimal control model

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27. 27 Determination of the time derivative of via the adjoint equation:

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29. 29 Determination of the time derivative of via

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31. 31 The time derivative ofas determined via must equal the time derivative of as determined via the adjoint equation:

32. 32 Definition: Observation: This differential equation can be used to determine the optimal control function.

33. 33 Solution of the homogenous differential equation: Let

34. 34 Determination of the particular solution: Let

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37. 37 Conclusion: The optimal control function is:

38. 38 Determination of the optimal stock path equation:

39. 39 The optimal control function is introduced in the differential equation of the stock path equation:

40. 40 As a result, the differential equation of the optimal stock path equation is:

41. 41 Solution of the homogenous differential equation: Let

42. 42 Determination of the particular solution: Let:

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46. 46 Conclusion: The optimal stock path equation is:

47. 47 Determination ofvia the initial and terminal conditions

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58. 58 Determination ofviaand

59. 59 Conclusion: The optimal adjoint variable path equation is:

60. 60 Determination of the optimal objective function value:

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69. 69 Now, we determine, the antiderivative of K.. Below, we exclude the constant of integration.

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71. 71 Code section for calculation of J (in JavaScript): var r2 = r-g1; var z1 = 1/(2*k3)*(f1/r2 + f2/r2/r2 - k1); var z2 = 1/(2*k3)*(f2/r2 - k2); var c0 = 1/g1*(z1+(z2-g2)/g1 - g0); var c1 = (z2-g2)/g1;

72. 72 var sysdet = Math.exp(r2*t1)/(g1-r2) *Math.exp(g1*t2) - Math.exp(r2*t2) /(g1-r2)*Math.exp(g1*t1); var A = ( (x1-c0-c1*t1)*Math.exp(g1*t2) -(x2-c0-c1*t2)*Math.exp(g1*t1) ) -/sysdet; var B = ( Math.exp(r2*t1)/(g1-r2)*(x2-c0-c1*t2) – Math.exp(r2*t2)/(g1-r2)*(x1-c0-c1*t1)) /sysdet;

73. 73 var D = A/(g1-r2); var w0 = f1*c0 + k1*z1 + k3*z1*z1; var w1 = f1*c1 + f2*c0 + k1*z2 + k2*z1 + 2*k3*z1*z2; var w2 = f2*c1 + k2*z2 + k3*z2*z2; var w3 = f1*B; var w4 = f1*D + k1*A + 2*k3*z1*A; var w5 = k3*A*A; var w6 = f2*B; var w7 = f2*D + k2*A + 2*k3*z2*A;

74. 74 var s0 = - r; var s1 = g1 - r; var s2 = r2 - r; var s3 = 2*r2 - r;

75. 75 var AntidK2 = w0*(1/s0*Math.exp(s0*t2)) + w1*(Math.exp(s0*t2)*(t2/s0 - 1/(s0*s0))) + w2*(Math.exp(s0*t2)*((s0*s0*t2*t2-2*s0*t2+2) /(s0*s0*s0))) + w3*(1/s1*Math.exp(s1*t2)) + w4*(1/s2*Math.exp(s2*t2)) + w5*(1/s3*Math.exp(s3*t2)) + w6*(Math.exp(s1*t2)*(t2/s1 - 1/(s1*s1))) + w7*(Math.exp(s2*t2)*(t2/s2 - 1/(s2*s2))) ;

76. 76 var AntidK1 = w0*(1/s0*Math.exp(s0*t1)) + w1*(Math.exp(s0*t1)*(t1/s0 - 1/(s0*s0))) + w2*(Math.exp(s0*t1)*((s0*s0*t1*t1-2*s0*t1 + 2) /(s0*s0*s0))) + w3*(1/s1*Math.exp(s1*t1)) + w4*(1/s2*Math.exp(s2*t1)) + w5*(1/s3*Math.exp(s3*t1)) + w6*(Math.exp(s1*t1)*(t1/s1 - 1/(s1*s1))) + w7*(Math.exp(s2*t1)*(t1/s2 - 1/(s2*s2))) ; var Integral = AntidK2 - AntidK1; var J = Integral;

77. 77 General observations of optimal solutions: First we consider the following objective function. Note that the stock level does not influence the objective function directly in this first version of the problem.

78. 78 The Hamiltonian function is:

79. 79 When we have an interior optimum, the first order derivative of the objective function with respect to the control variable is 0. As a result, we find that the present value of the marginal profit, is equal to the marginal resource value at the same point in time,.

80. 80 The adjoint equation says that Since, we know that

81. 81 Now, we make the following definition:, consists of many different parts. The resource, with total stock Different parts of the resource have different relative growth. A particular part of the resource,, has relative growth.

82. 82 We may define the relative growth of that particular unit as (is the stock level of that particular unit and is the growth.)

83. 83 When we integrate, we arrange the different particular resource units in such a way that

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85. 85 Observation: The relative decrease of the marginal resource value over time is equal to the relative growth of the marginal resource unit.

86. 86 Example with explanation from forestry: If the marginal cubic metre grows by 5% per year (and will give 0.05 new cubic metres next year) then the value of the marginal cubic metre this year is 5% higher than the value of the marginal cubic metre next year.

87. 87 The value of an already existing cubic metre must be higher than the value of a cubic metre in the future year since the cubic metre that we already have may give us more than one cubic metre in the future year, thanks to the growth.

88. 88 The relative marginal resource value decrease is higher in case the relative marginal growth is higher.

89. 89 The relationship between the speed of change of the relative marginal resource value and direct valuation of the stock level

90. 90 Here, we add to the objective function.

91. 91 As a result, we get:

92. 92 The Hamiltonian function becomes:

93. 93 These derivatives are obtained:

94. 94 The adjoint equation gives a modified result:

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96. 96 Observation: >0 implies that becomes more negative ifincreases.

97. 97 Explanation and connection to forestry: means that the stock gives an “instant contribution” to the objective function. One such case is if the forest owner continuously gets paid for the amount of stored CO2 in the forest. In such a case, one cubic metre that exists now (and that will not be instantly harvested), will give contributions in this period and in the following period.

98. 98 One cubic metre that will exist in the next period, but not already in this period, will not “be able” to give the contribution during this period. As a result, the fact that we get “instant contributions”, directly from the stock, means that the relative marginal value of the stock falls faster over time.

99. 99 Software for the optimal control model http://www.lohmander.com/CM/CM.htm

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103. 103 J1216344 t x u Lambda 03100143139 52920138132 102761132126 152628124120 202533115114 252485104108 30250090103

104. 104 Optimal strategy and dynamic effects of the rate of interest

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109. 109 Comparisions with alternatives that are not optimal:

110. 110 Optimal strategy and dynamic effects of the slope of the demand function

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116. 116 Comparisions with two alternatives:

117. 117 Optimal strategy and dynamic effects of the terminal condition

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123. 123 Optimal strategy and dynamic effects of continuous stock level valuation

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129. 129 Optimal strategy and dynamic effects of continuous stock level valuation in combination with variations of the the slope of the demand function

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135. 135 Optimal strategy and dynamic effects of the growth function

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