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平稳遍历性的一致检验AI 解读

A formal statistical test of stationary-ergodicity is developed for known Markovian processes on ℝ d This makes it applicable to testing models and algorithms, as well as estimated time series processes ignoring the estimation error. The analysis is conducted by examining the asymptotic properties of the Markov operator on density space generated by the transition in the state space. The test is developed under the null of stationary-ergodicity, and it is shown to be…

误差修正模型的解释：部分调整、前瞻行为与国际动态货币需求AI 解读

Abstract An error correction model is derived from a stochastic dynamic programming problem incorporating rational expectations. A parametric restriction is derived that allows a test for the theoretical proposition that the optimal strategy behind the error correction from entails the failure to asymptotically close the gap between the choice variable and the growing target. This is accomplished by nesting a partial adjustment model with forward‐looking expectations within…

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相依观测下的非线性回归AI 解读

This paper provides general conditions which ensure consistency and asymptotic normality for the nonlinear least squares estimator. These conditions apply to time-series, cross-section, panel, or experimental data for single equations as well as systems of equations. The regression errors may be serially correlated and/or heteroscedastic. For an important special case, we propose a new covariance matrix estimator which is consistent regardless of the presence of…

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