Kuan-Pin Lin

Qualitative reasoning in economics

Abstract We present a scheme for qualitative reasoning about economic systems. The fundamental element of our scheme is the market, a homeostatic entity that adjusts to restore equilibrium after perturbation. Complex theories are represented in terms of multiple markets, with their interaction realized by variables of one market being parameters to others. We define a simulation process, making it possible to reason about multiple-market models. Comparing final with initial values of market variables implements comparative statics. We define a process of backward reasoning from changes in variables as desired effects to parameter perturbations as possible causes. Our notions are illustrated by consideration of Keynesian IS-LM and general macroeconomic models.

Causal reasoning in econometric models

Abstract Propagation of change based on causal ordering is a central element of causal reasoning in economic models. While causal reasoning has most often been applied in qualitative models, we demonstrate a technique for causal reasoning that offers explanations of structure and behaviour in quantitative, econometric contexts. Given a matching of equations with endogenous variables, causal reasoning can be applied to both static and dynamic system models. By propagating the disturbance of one or more exogenous variables, impact or static multipliers of the model can be derived along with a causal explanation. Dynamic analysis is achieved by propagation of lagged endogenous variables carried from the previous time periods. Two versions of Keynesian macro-econometric models, Kleins Model I, and the Klein-Goldberger Model are used as examples.

Simulated maximum likelihood estimation of spatial stochastic frontier model and its application

This paper considers a spatial stochastic frontier model that accounts for possible unknown geographical variation of the outputs. The stochastic frontier model is augmented with a spatial autoregressive structure for the two-sided part of the disturbance, and the time-varying technical inefficiency is not imposed a rigorous function structure. Because of the spatial effect and the asymmetry composed error structure, it is intractable to employ maximum likelihood method directly to estimate the proposed model. Simulated maximum likelihood estimation is used instead. We derive the simulated likelihood function of the model, and present an application of the estimation method on China province-level panel data from 2000 to 2007. The results show that the spatial effect is highly significant, and the ignorance of the spatial effect produces significantly different rankings of technical efficiencies across production units.

A logic programming approach to revealed preference theory

This paper shows the direct translation of revealed preference theory into a logic program. Tests of exact and approximate rationality based on the economic theory of revealed preference are presented in PROLOG. A special case of homothetic preference of the consumer behavior is also considered.