We consider an abstract setting of the differential r&d game, where participating firms are allowed for strategic behavior. We assume the information asymmetry across those firms and the government, which seeks to support newer technologies in a socially optimal manner. We develop a general...

Uncertainty about the choice of identifying assumptions is common in causal studies, but is often ignored in empirical practice. This paper considers uncertainty over models that impose different identifying assumptions, which, in general, leads to a mix of point- and set-identified models. We...

Researchers frequently test identifying assumptions in regression based research designs (which include instrumental variables or difference-in-differences models) by adding additional control variables on the right hand side of the regression. If such additions do not affect the coefficient of...

In the causal inference literature a class of semi-parametric estimators is called robust if the estimator has desirable properties under the assumption that at least one of the working models is correctly specified. A standard example is a doubly robust estimator that specifies parametric...

In this paper we apply robust linear programming technique for multidimensional analysis of preference (LINMAP) method for a decision making problem. During the last two decades, many methods have been extensively used for decision making problems. However, there is no investigation among many...