We provide a new framework to identify demand elasticities in markets where managers rely on algorithmic recommendations for price setting, and apply it to a dataset containing bookings for a sample of mid-sized hotels in Europe. Using non-binding algorithmic price recommendations and observed...

In recent years, extreme shocks (such as natural disasters) have increased in both frequency and intensity. Consequently, many cities have experienced significant economic losses. Quantifying the economic cost to local businesses after extreme shocks is important for postdisaster assessment and...

This paper examines the effect of board characteristics, especially board independence, on firm performance from a dynamic perspective through copula-based quantile regression approaches, which allow us to focus on changes at different points in the distribution of board characteristics. We find...

We investigate how protectionist policies influence short-run economic growth. Our empirical strategy exploits an extraordinary tax scandal that gave rise to an unexpected change of government in Sweden. A free-trade majority in parliament was overturned by a protectionist majority in 1887. We...

Purpose The purpose of this paper is to explore the role of qualitative research in causality, with particular emphasis on process causality. In one paper, it is not possible to discuss all the issues of causality, but the aim is to provide useful ways of thinking about causality and qualitative...

Purpose Nonexperimental research, defined as any kind of quantitative or qualitative research that is not an experiment, is the predominate kind of research design used in the social sciences. How to unambiguously and correctly present the results of nonexperimental research, however, remains...

This paper focus on the determinants of poverty dynamics in Tunisia by performing a two-stage endogenous model using a Bayesian algorithm to avoid missing data. Based on this approach author show that panel data analysis can be performed through potential variables such presented by the work of...

Abstract The paper considers the properties of and relations between confounding and effect modification from the perspective of causal inference and with a distinction drawn as to how each of these two epidemiologic concepts can be defined both with respect to a distribution of potential...

Abstract Mediation analysis is widely adopted to infer causal mechanism by disentangling indirect or mediated effects of an exposure on an outcome through given intermediaries, from the remaining direct effect. Traditional approaches build on standard regression models for the outcome and...

Abstract The between-within (BW) model is a popular regression model for twin data. Despite its popularity, the properties of the BW model have not yet been thoroughly investigated, and most reviews are largely heuristic. The aim of this paper is to provide a formal guide to the causal...