Simplicity, scientific inference and econometric modelling

Article Abstract:

Simplicity or parsimony is an ideal in econometric modeling. Simplicity in terms of the specification of econometric models is defined as well as the conditions for the optimal degree of simplicity. Statistical reductionism, which refers to inference beginning from a general model to a more specific one, is evaluated and found wanting. Instead, an inductive-deductive process is proposed based on iterations that bridge that gap between approximation and reduction. Such iterations involve the use of additional variables or lags in simplifying models.

Evaluation, Mathematical models

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Trends, cycles and autoregressions

Article Abstract:

An econometrician argues the use of autoregression in econometrics. The use of autoregression is deceptive because it could put emphasis on less important issues and could divert attention from more effective methods. Although autoregressive models have contributed to theoretical study, univariate and multivariate autoregressions are limited in range. Autoregressions are usually used to integrate regression with time series in the structural time series method.

Methods, Economics, Economic methods

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Measuring the hidden economy: implications for econometric modelling

Article Abstract:

A two-part modelling methodology has been used to measure the size of the hidden economy. The proposed econometric technique involves the use of a comprehensive 'Multiple Indicators, Multiple Causes' (MIMIC) model and a 'cash-demand' model to respectively get the time-series index of hidden/measure output of the underground economy and to develop a benchmark for transforming this index into percentage units.

Usage, Measurement, Underground economy

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