Pedro Cadahia | Searcharxiv

arXiv2026

ACT, WAIT, or EXPERIMENT: A Causal Governance Framework for Retail Price Optimization Under Abstentions

This paper presents a causal decision-making framework for estimating price elasticity in retail channels, a process typically confounded by promotions, competitor movements, and market frictions. Rather than forcing a calculation when data is ambiguous, the system introduces decision abstention (\textsc{wait}) as an active diagnostic tool rather than an estimation failure. Combining Double Machine Learning and conformal prediction, the tool evaluates whether reliable conditions exist to adjust prices or if pausing the decision is preferable. When the system abstains, it exhaustively classifies the reason for the pause, identifying which products require designed pricing experiments or whether aggregating data to the brand level restores usable estimates. Tested on controlled synthetic data, the model shows that this operational discipline drastically reduces estimation error (lowering RMSE from 0.571 to 0.159) and offers a practical, secure alternative to blind estimation in thin-data retail environments.

econ.EM↗

arXiv2022

Measuring anomalies in cigarette sales by using official data from Spanish provinces: Are there only the anomalies detected by the Empty Pack Surveys (EPS) used by Transnational Tobacco Companies (TTCs)?

There is literature that questions the veracity of the studies commissioned by the transnational tobacco companies (TTC) to measure the illicit tobacco trade. Furthermore, there are studies that indicate that the Empty Pack Surveys (EPS) ordered by the TTCs are oversized. The novelty of this study is that, in addition to detecting the anomalies analyzed in the EPSs, there are provinces in which cigarette sales are higher than reasonable values, something that the TTCs ignore. This study analyzed simultaneously, firstly, if the EPSs established in each of the 47 Spanish provinces were fulfilled. Second, anomalies observed in provinces where sales exceed expected values are measured. To achieve the objective of the paper, provincial data on cigarette sales, price and GDP per capita are used. These data are modeled with machine learning techniques widely used to detect anomalies in other areas. The results reveal that the provinces in which sales below reasonable values are observed (as detected by the EPSs) present a clear geographical pattern. Furthermore, the values provided by the EPSs in Spain, as indicated in the previous literature, are slightly oversized. Finally, there are regions bordering other countries or with a high tourist influence in which the observed sales are higher than the expected values.

stat.AP↗