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diff --git a/ps1/main.tex b/ps1/main.tex index f888998..943d0f5 100644 --- a/ps1/main.tex +++ b/ps1/main.tex @@ -169,4 +169,19 @@ utility in this case will be $u' = w_1(v-b)$ which is less than $u$. We have now established the uniqueness of a symmetric Bayes-Nash equilibrium. We can now conclude by applying Theorem 2.10 which states that there are no asymmetric strategy profiles. + +\section{Exercise 3.1} + +We recall that the virtual value function for agent $i$ is defined as $$\phi_i(v_i) = v_i - \frac{1 - F_i(v_i)}{f_i(v_i)}$$ for a cumulative density function $F_i(v_i)$ and density function $f_i(v_i)$, with $F_i'(v_i) \stackrel{\text{def}}{=} f_i(v_i)$. The virtual function satisfies the following relationship: $$\E[p_i(v_i)] = \E[\phi_i(v_i)x_i(v_i)].$$ If the residual surplus is $$\sum_i \left(v_ix_i - p_i\right) - c({\mathbf x}),$$ where $x_i$ is the probability that agent $i$ will be allocated the item and $c({\mathbf x})$ is the service cost, and so if we want to maximize this, we are maximizing + +\begin{align*} \E\left[\sum_i \left(v_ix_i - p_i\right)\right] = \end{align*} + +\section{Exercise 3.4} + +\begin{enumerate}[(a)] + +\item By the definition of virtual functions, we will maximize revenue when we maximize the virtual surplus (this follows from the definition $\E[p_i(v_i)] = \E[\phi_i(v_i)x_i(v_i)]$. Following Definition 3.5, we can do this via the VSM (VCG) mechanism. + +\end{enumerate} + \end{document} |
