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\(\mathbf{x}_1,..., \mathbf{x}_k \in V\), linear combination is \[c_1 \mathbf{x}_1 + ... + c_k \mathbf{x}_k \] where \(c_1, ..., c_k \in \mathbb{R}\)
span of \(W \subseteq V\) is set of all linear combinations of elements of \(W\)
Lemma: If \(A\) and \(B\) are bases for \(V\), then \(|A| = |B|\)
Lemma: Let \(V\) be a vector space, then \(\exists\) a basis
Differentiation: \(C^k([0,1]) =\) \(\{f:[0,1] \to \mathbb{R} \;,\; f \text{ k times cont differentiable}\}\)
\(D:C^1([0,1]) \to C^0([0,1])\), \[ (Df)(x) = \frac{df}{dx}(x) \]
\[ \begin{aligned} A(B g_k) = & A (\sum_{j=1}^n b_{jk} f_j) = \sum_{j=1}^n b_{jk} A f_j \\ = & \sum_{j=1}^n b_{jk} \left(\sum_{i=1}^m a_{ij} e_i\right) = \sum_{i=1}^m \left(\sum_{j=1}^n a_{ij} b_{jk} \right) e_i \\ = & \begin{pmatrix} \sum_{j=1}^n a_{1j} b_{j1} & \cdots & \sum_{j=1}^n a_{1j} b_{jp} \\ \vdots & \ddots & \vdots \\ \sum_{j=1}^n a_{mj} b_{j1} & \cdots & \sum_{j=1}^n a_{mj} b_{jp} \end{pmatrix} g_k \\ = & (AB)g_k . \end{aligned} \]
Hyperplane \(H_{\xi,c} = \{x \in V: \xi x = c\}\) where \(c \in \mathbb{R}\) and \(\xi \in V^\ast\)
Let \(A\) be an \(m\) by \(n\) matrix and \(b \in \mathbb{R}^m\) either:
but not both.
Allocation \((x^e,y^e)\) and price, \(p \in S^*\) such that
If \((x^e,y^e)\) and \(p\) is a competitive equilibrium and preferences a locally non-satiated, then \((x^e,y^e)\) is Paretor efficient.
If preferences are locally non-satiated, convex, and continuous, and \((x^e, y^e)\) is Pareto efficient, then \(\exists p \in S^*\) such that \((x^e,y^e)\) and \(p\) is a competitive equilibrium.