Fuzzy Differences in Differences
نویسندگان
چکیده
Difference in differences (DID) require that the treatment rate is equal to 0% in the control group and during period 0 (no “always takers”) and to 100% in the treatment group in period 1 (no “never takers”). Sometimes, treatment rate increases more in the treatment than in the control group but there are never or always takers. This paper derives identification results applying to such settings. They only require one common trend assumption on the outcome of interest (Y) whereas the standard instrumental variable result usually invoked also requires common trend on treatment rate. When there are never takers but no or few always takers, common trend on Y is sufficient to identify exactly an ATT or at least its sign.
منابع مشابه
Gas Flow Metering Using the PSO Optimized Interval Type- 2 Fuzzy Neural Network
Orifice flow meter is one of the most common devices in industry which is used for measuring the gas flow. This system includes an orifice plate, temperature and pressure transmitters, and a flow computer. The flow computer is used for collecting information related to temperature, pressure, and their differences under various conditions. Also the flow computer can calculate the flow rate of ga...
متن کاملFeatures of Mathematical Theories in Formal Fuzzy Logic
A genuine fuzzy approach to fuzzy mathematics consists in constructing axiomatic theories over suitable systems of formal fuzzy logic. The features of formal fuzzy logics (esp. the invalidity of the law of contraction) entail certain differences in form between theories axiomatized in fuzzy logic and usual theories known from classical mathematics. This paper summarizes the most important diffe...
متن کاملEntropy Differences of Arithmetic Operations with Shannon Function on Triangular Fuzzy Numbers
The main purposes of this paper are to probe for the entropy differences between arithmetically manipulated Triangular Fuzzy Numbers (TFNs) using Shannon’s Function; and to study the relationships between any two TFNs. Simultaneously, we expand on the articles of Wang et al. [6] and Wang et al. [5]. The entropy differences between two TFNs subjected to different arithmetic operations are classi...
متن کاملInterpolation of fuzzy data by using flat end fuzzy splines
In this paper, a new set of spline functions called ``Flat End Fuzzy Spline" is defined to interpolate given fuzzy data. Some important theorems on these splines together with their existence and uniqueness properties are discussed. Then numerical examples are presented to illustrate the differences between of using our spline and other interpolations that have been studied before.
متن کامل(Economic and Social Duality in Iran (Using Fuzzy Topsis Decision-making
One of the planners and policy-makers’ aims on the one hand is optimum allocating and distributing of credits and facilities among regions and on the other hand is providing and compiling a suitable model aiming at achieving economic and social equity as well as creating reasonable and real economic growth. Paying attention to the balanced regional development, decreasing regional and district ...
متن کاملOperation Planning of Wind Farms with Pumped Storage Plants Based on Interval Type-2 Fuzzy Modeling of Uncertainties
The operation planning problem encounters several uncertainties in terms of the power system’s parameters such as load, operating reserve and wind power generation. The modeling of those uncertainties is an important issue in power system operation. The system operators can implement different approaches to manage these uncertainties such as stochastic and fuzzy methods. In this paper, new ...
متن کامل