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Production Techniques with Conditionally Fixed Coefficients

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Part of the book series: Lecture Notes in Economics and Mathematical Systems ((LNE,volume 684))

Abstract

Such technologies describe the case of completely rigid industrial plants. Examples have already been encountered here in the context of electricity (Sect. 5.1): both thermal generation and pumped storage, though not hydro, are such techniques.

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Notes

  1. 1.

    At 0, the normal cone to Y 0 equals the polar cone Y 0 . When Y 0 is a vector subspace of Y, as in (5.1.7), the normal cone is the same at every y: it is the annihilator space (a.k.a. orthogonal complement) Y 0  ⊥ .

  2. 2.

    For example, the function \(\check{k}\left (y\right ):=\mathop{ \mathrm{EssSup}}\nolimits \left (y\right ):=\mathop{ \mathrm{ess}}\nolimits \sup _{t}y\left (t\right )\), for \(y \in Y:= L^{\infty }\left [0,T\right ]\), has no subgradient in \(P:= L^{1}\left [0,T\right ]\) at any y with \(\mathop{\mathrm{meas}}\nolimits \left \{t: y\left (t\right ) =\mathop{ \mathrm{EssSup}}\nolimits \left (y\right )\right \} = 0\). This is because \(\gamma \in L^{1} \cap \partial ^{\mathrm{a}}\mathop{ \mathrm{EssSup}}\nolimits \left (y\right )\) if and only if γ ≥ 0, \(\int _{0}^{T}\gamma \left (t\right )\mathrm{d}t = 1\) and γ = 0 on \(\left \{t: y\left (t\right ) <\mathop{ \mathrm{EssSup}}\nolimits \left (y\right )\right \}\): see, e.g., [32, 4.5.1: Example 3].

  3. 3.

    To see that (7.1.18)–(7.1.21) are indeed the FFE Conditions, recall from (3.1.5) that primal and dual feasibilities mean that \(\left (y,-k,-v\right ) \in \mathbb{Y}\) and \(\left (\,p,r,w\right ) \in \mathbb{Y}^{\circ }\). In the c.f.c. case, the two feasibility conditions expand into (7.1.18) and (7.1.19)–(7.1.20).

  4. 4.

    The term corresponding to any inactive capacity constraint ϕ must be deleted from the sum in (7.1.24) as expanded in (7.1.8).

  5. 5.

    This term is an outward normal vector to the intersection of the sublevel sets of \(\check{k}_{\phi }\)’s in (7.1.23): see, e.g., [42, 23.7.1 and 23.8.1] or [32, 4.3: Propositions 1 and 2].

  6. 6.

    This is the borderline case between Hicks-Allen complements and substitutes: see, e.g., [47, 1.F.d].

  7. 7.

    Formally, the multi-valued rate of substitution equals \(\mathbb{R}_{+} = \left [0, +\infty \right )\).

  8. 8.

    Shown in [21] and in [27, Section 9], the result is summarized and used in Sects. 5.2 and 5.3 here.

  9. 9.

    When y is a decision variable, as in the SRP programme, this is Slater’s Condition on the constraints (inequalities and equations) that define Y0.

  10. 10.

    For a linear functional aj, its \(\mathrm{m}\left (Y,P\right )\)-continuity is equivalent to its \(\mathrm{w}\left (Y,P\right )\)-continuity (and it simply means that aj ∈ P). But a concave function (bl) or a convex function (\(\check{k}_{\phi }\) or \(\check{v}_{\xi }\)) can be \(\mathrm{m}\left (Y,P\right )\)-continuous (and hence \(\mathrm{w}\left (Y,P\right )\)-u.s.c. or l.s.c., respectively) without being \(\mathrm{w}\left (Y,P\right )\)-continuous. The weak and Mackey topologies are briefly discussed in Sect. 6.2

  11. 11.

    [42, 22.3.1] and [48, 4.19] give only Farkas’s Lemma, but this contains the Factorization Lemma.

  12. 12.

    For ϱ = 0, this fails if and only if D ≠ ∅ but PD = ∅ (in which case \(P \cap 0D = \left \{0\right \}\) but \(0\left (P \cap D\right ) =\emptyset\)).

  13. 13.

    This is a case of the ordinary Lagrangian (with Y 0 as an “abstract” constraint, unpriced by \(\mathcal{L}\)): see, e.g., [44, (4.4)], where it is derived from the generalized Lagrangian defined in [44, (4.2)].

  14. 14.

    \(\Pi _{\mathrm{Exc}}\left (y\right )\) is the excess a.k.a. pure profit from an output y (i.e., revenue at prices p less minimum input cost at prices r and w).

  15. 15.

    The partial derivatives \(\partial \Pi _{\mathrm{SR}}/\partial \zeta _{j}^{{\prime}}\) and \(\partial \Pi _{\mathrm{SR}}/\partial \zeta _{l}^{{\prime\prime}}\) exist if the α j and β l associated by (7.2.1) with the optimal y are unique. If not, the derivative property still holds for the superdifferential, i.e., \(\hat{\partial }_{\zeta ^{{\prime}},\zeta ^{{\prime\prime}}}\Pi \) contains each \(\left (\alpha,\beta \right )\) that satisfies (7.2.1) for some optimal y (and hence for every optimal y).

  16. 16.

    In other words, each \(\check{k}_{\phi }\) or \(\check{v}_{\xi }\) is a p.l.h. convex finite function.

  17. 17.

    When each \(\check{k}_{\phi }\) is weakly* l.s.c. and Y 0 is weakly* closed as in Part  2 , this is equivalent to weak* compactness of \(\left \{y \in Y _{0}:\check{ k}\left (y\right ) \leq k\right \}\).

  18. 18.

    This assumption holds vacuously when \(\Xi =\emptyset\) (i.e., when there are no variable inputs, as with the storage and the hydro techniques (5.1.3) and  (5.1.4) ).

  19. 19.

    Formally,  (7.4.1) holds also when \(k\ngeq0\) : in this case, \(\hat{Y } = Y = \partial _{p}\Pi _{\mathrm{SR}}\) (the programme  (7.1.11)–(7.1.13) is then infeasible, so every y is an improper solution, and \(\Pi _{\mathrm{SR}}\left (\cdot,k,w\right ) = -\infty \)).

  20. 20.

    When \(\check{k}\) and \(\check{v}\) are norm-continuous, the l.s. continuity of C SR (on Y × K) can be deduced also by using Lemma 7.3.1 to verify the assumptions of Lemma 6.2.5.

  21. 21.

    Being also weakly* closed, the set \(\left \{y \in Y _{0}:\check{ k}\left (y\right ) \leq k\right \}\) is actually weakly* compact by the Banach-Alaoglu Theorem.

  22. 22.

    Similarly, if a unit output requires a unit of a costlessly storable variable input, whose total amount available, v ξ , can be spread as an input flow \(\tilde{v}_{\xi }\left (\cdot \right )\) over the period, then the output rate is constrained to a nonnegative \(y\left (t\right ) \leq \tilde{v}_{\xi }\left (t\right )\) for some \(\tilde{v}_{\xi }\left (t\right ) \geq 0\) with \(\int _{0}^{T}\tilde{v}_{\xi }\left (t\right )\mathrm{d}t = v_{\xi }\). This can be summarized in the single constraint \(v_{\xi } \geq \check{ v}_{\xi }\left (y\right ):=\int _{ 0}^{T}y\left (t\right )\mathrm{d}t\).

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Horsley, A., Wrobel, A.J. (2016). Production Techniques with Conditionally Fixed Coefficients. In: The Short-Run Approach to Long-Run Equilibrium in Competitive Markets. Lecture Notes in Economics and Mathematical Systems, vol 684. Springer, Cham. https://doi.org/10.1007/978-3-319-33398-4_7

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