Decisions, Counterfactual Explanations and Strategic Behavior

As data-driven predictive models are increasingly used to inform decisions, it has been argued that decision makers should provide explanations that help individuals understand what would have to change for these decisions to be beneficial ones. However, there has been little discussion on the possibility that individuals may use the above counterfactual explanations to invest effort strategically and maximize their chances of receiving a beneficial decision. In this paper, our goal is to find policies and counterfactual explanations that are optimal in terms of utility in such a strategic setting. We first show that, given a pre-defined policy, the problem of finding the optimal set of counterfactual explanations is NP-hard. Then, we show that the corresponding objective is nondecreasing and satisfies submodularity and this allows a standard greedy algorithm to enjoy approximation guarantees. In addition, we further show that the problem of jointly finding both the optimal policy and set of counterfactual explanations reduces to maximizing a non-monotone submodular function. As a result, we can use a recent randomized algorithm to solve the problem, which also offers approximation guarantees. Finally, we demonstrate that, by incorporating a matroid constraint into the problem formulation, we can increase the diversity of the optimal set of counterfactual explanations and incentivize individuals across the whole spectrum of the population to self improve. Experiments on synthetic and real lending and credit card data illustrate our theoretical findings and show that the counterfactual explanations and decision policies found by our algorithms achieve higher utility than several competitive baselines.Comment: New data preprocessing method, experiments on credit card data and experiments under a matroid constrain

Do Citizens Vote Strategically (if they vote at all)? Evidence from U.S. National Elections

Two prominent facts emerge from data on U.S. presidential and congressional elections. First, often people vote a split-ticket, that is, they vote for different parties' candidates for President and for Congress. Second, many citizens do not go to vote and, after going to vote, some decide to vote in one election but not in the other (typically more people vote for President than for Congress). This paper addresses two main questions: (1) To what extent is split-ticket voting the natural result of individuals who vote in each election according to their immediate policy preferences? In particular, what is the proportion of citizens who vote ''sincerely'' versus ''strategically''? (2) Can we simultaneously account for the patterns of abstention and voting observed in the data? To answer these questions, we propose and estimate, using individual-level data on voting choices in presidential and congressional elections from 1972 to 2000, a unified model of turnout and voting with asymmetric information. Our main findings are as follows. While a majority of citizens behave ''sincerely'', a significant proportion of citizens behave ''strategically''. Split-ticket voting is not only generated by strategic behavior but also by sincere behavior. In contrast to the implications of the ''balancing theories'', we find that a big portion of split-ticket behavior comes from extreme voters and that those middle-of-the-road voters that split their ticket do so as a result of voting according to their policy preferences in each election separately without any need for balancing purposes. We use the estimated model to conduct counterfactual experiments to assess the effect of sincere behavior, information, and abstention on electoral outcomes and the insurgency of divided governments.split-ticket, abstention, strategic voters

A Structural Approach to Identifying the Sources of Local-Currency Price Stability

The inertia of the local-currency prices of traded goods in the face of exchange-rate changes is a well-documented phenomenon in International Economics. This paper develops a structural model to identify the sources of this local-currency price stability and applies it to micro data from the beer market. The empirical procedure exploits manufacturers’ and retailers’ first-order conditions in conjunction with detailed information on the frequency of price adjustments following exchange-rate changes to quantify the relative importance of local non-traded cost components, markup adjustment by manufacturers and retailers, and nominal price rigidities in the incomplete transmission of such changes to prices. We find that, on average, approximately 60% of the incomplete exchange rate pass-through is due to local non-traded costs; 8% to markup adjustment; 30% to the existence of own-brand price adjustment costs, and 1% to the indirect/strategic effect of such costs, though these results vary considerably across individual brands according to their market shares.