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A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances
Spatial autoregressive model two-stage least squares generalized moments estimation
2015/9/24
Cross-sectional spatial models frequently contain a spatial lag of the dependent variable as a regressor or a disturbance term that is spatially autoregressive. In this article we describe a computati...
Dating business cycles entails ascertaining economy-wide turning points. Broadly speaking, there are two approachesin the literature. The first approach, which dates to Burns and Mitchell (1946), is t...
Estimating discriminatory power and PD curves when the number of defaults is small
Estimating discriminatory power PD curves defaults
2010/11/1
The intention with this paper is to provide all the estimation concepts and techniques that
are needed to implement a two-phases approach to the parametric estimation of probability
of default (PD) ...
Money Demand in General Equilibrium Endogenous Growth: Estimating the Role of a Variable Interest Elasticity
Money demand interest elasticity exchange credit cash-in-advance
2010/9/7
The paper presents and tests a theory of the demand for money that is derived from a general equilibrium,endogenous growth economy, which in effect combines a special case of the shopping time exchang...
Estimating Continuous-Time Models Using Discretely Sampled Data
Continuous-Time Models Discretely Sampled Data
2014/3/13
Estimating Continuous-Time Models Using Discretely Sampled Data.
The Effects of Random and Discrete Sampling When Estimating Continuous-Time Diffusions
The Effects of Random Discrete Sampling Estimating Continuous-Time Diffusions
2014/3/13
The Effects of Random and Discrete Sampling When Estimating Continuous-Time Diffusions.
ESTIMATING DETERMINISTIC TRENDS IN THE PRESENCE OF SERIALLY CORRELATED ERRORS
DETERMINISTIC TRENDS PRESENCE OF SERIALLY CORRELATED ERRORS
2014/3/18
This paper studies the problems of estimation and inference in the linear trend model yt = a + P3t + ut, where ut follows an autoregressive process with largest root p and , is...