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Distributions of error correction tests for cointegration

This paper provides densities and finite sample critical values for the single-equation error correction statistic for testing cointegration. Graphs and response surfaces summarize extensive Monte Carlo simulations and highlight simple dependencies of the statistic's quantiles on the number of variables in the error correction model, the choice of deterministic components, and the sample size. The response surfaces provide a convenient way for calculating finite sample…

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Output and inflation in the long run

长期中的产出与通货膨胀

Abstract Cross‐country regressions explaining output growth often obtain a negative effect from inflation. However, that result is not robust, due to the selection of countries in sample, temporal aggregation, and omission of consequential variables in levels. This paper demonstrates some implications of these mis‐specifications, both analytically and empirically. In particular, for most G‐7 countries, annual time series of inflation and the log‐ level of output are…

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Modeling Inflation in Australia

澳大利亚通胀建模

This article develops an empirically constant, data-coherent, error-correction model for inflation in Australia. The level of consumer prices is a markup over domestic and import costs, with adjustments for dynamics and relative aggregate demand. The authors address issues of cointegration, general to specific modeling, dynamic specification, model evaluation and testing, parameter constancy, forecasting, and exogeneity. They also test this model against existing models of…

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Exogeneity, Cointegration, and Economic Policy Analysis

外生性、协整与经济政策分析

This overview examines conditions for reliable economic policy analysis based on econometric models, focusing on the econometric concepts of exogeneity, cointegration, causality, and invariance. Weak, strong, and super exogeneity are discussed in general and these concepts are then applied to the use of econometric models in policy analysis when the variables are cointegrated. Implications follow for model constancy, the Lucas critique, equation inversion, and impulse…

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Modeling Inflation in Australia

澳大利亚通胀建模

This article develops an empirically constant, data-coherent, error-correction model for inflation in Australia. The level of consumer prices is a markup over domestic and import costs, with adjustments for dynamics and relative aggregate demand. The authors address issues of cointegration, general to specific modeling, dynamic specification, model evaluation and testing, parameter constancy, forecasting, and exogeneity. They also test this model against existing models of…

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A framework for economic forecasting

This paper proposes a tripartite framework of design, evaluation, and post-evaluation analysis for generating and interpreting economic forecasts. This framework?s value is illustrated by re-examining mean square forecast errors from dynamic models and nonlinearity biases from empirical forecasts of US external trade. Previous studies have examined properties such as nonlinearity bias and the possible nonmonotonicity and nonexistence of mean square forecast errors in…

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Monte Carlo Methodology and the Finite Sample Properties of Instrumental Variables Statistics for Testing Nested and Non-Nested Hypotheses

工具变量统计量检验嵌套与非嵌套假设的蒙特卡洛研究及有限样本性质

Using Monte Carlo methodology, this paper investigates the effect of dynamics and simultaneity on the finite sample properties of instrumental variables statistics for testing nested and nonnested hypotheses. Simple numerical-analytical formulae (response surfaces) are obtained which closely approximate the statistics' unknown size and power functions for a dynamic simultaneous-equations model. The analysis illustrates the value and limitations of asymptotic theory in…

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Post-simulation Analysis of Monte Carlo Experiments: Interpreting Pesaran's (1974) Study of Non-nested Hypothesis Test Statistics

"Monte Carlo experimentation in econometrics helps ‘solve’ deterministic problems by simulating stochastic analogues in which the analytical unknowns are reformulated as parameters to be estimated." (Hendry (1980)) With that in mind, Monte Carlo studies may be divided operationally into three phases: design, simulation, and post-simulation analysis. This paper provides a guide to the last of those three, post-simulation analysis, given the design and simulation of a Monte…

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Asymptotic Properties of Instrumental Variables Statistics for Testing Non-Nested Hypotheses

This paper develops Instrumental Variables statistics for testing non-nested hypotheses when the hypotheses considered are single equations from a system of linear dynamic simultaneous equations. Asymptotic distributions of those statistics and of comparable Maximum Likelihood statistics are derived under the null hypothesis, a local non-nested alternative hypothesis, and a local "comprehensive" alternative hypothesis. The asymptotic powers of the non-nested hypothesis tests…

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