<abstract xmlns="http://www.w3.org/1999/xhtml"><p>In the article “Professor Tinbergen’s Method” (Keynes J. M. Professor Tinbergen’s Method. − The Economic Journal. 1939. Vol. 49. No. 195) John Maynard Keynes expressed critical notes concerning insufficient scientific level of the Jan Tinbergen’s results obtained with the help of econometric methods. The conclusion of present research is that the critical appraisal of econometric applying given by John Maynard Keynes in 1939 can be completely assigned to many published in Latvia research in economics and business done by inductive statistics because scientists carelessly apply the linear regression model in absence of the knowledge <italic>a priori</italic> required by proper theorems and algorithms. Moreover, many times there is no sense even to speak about stochastic experiment because the most important condition − <italic>ceteris paribus</italic> does not fulfil, namely, economic environment is not homogeneous enough. As the result, the causal inferences derived from Regression Report are not scientifically justified. The second conclusion is that the objective criticism in econometrics applications area in order to keep the satisfactory level of scientific correctness and scientific ethics in Latvia has to be established. We also assert that the applications of inductive econometrics in agriculture are much more justified due to possibility to repeat the stochastic experiments many times in constant circumstances like in physics and mechanics. The meta-target of present article is to remind the protests of John Maynard Keynes to the careless utilization of econometric theorems and to raise a wide discussion about the problems of correctness in applying inductive statistics in economics and agriculture in Latvia.</p></abstract>

In the article “Professor Tinbergen’s Method” (Keynes J. M. Professor Tinbergen’s Method. − The Economic Journal. 1939. Vol. 49. No. 195) John Maynard Keynes expressed critical notes concerning insufficient scientific level of the Jan Tinbergen’s results obtained with the help of econometric methods. The conclusion of present research is that the critical appraisal of econometric applying given by John Maynard Keynes in 1939 can be completely assigned to many published in Latvia research in economics and business done by inductive statistics because scientists carelessly apply the linear regression model in absence of the knowledge a priori required by proper theorems and algorithms. Moreover, many times there is no sense even to speak about stochastic experiment because the most important condition − ceteris paribus does not fulfil, namely, economic environment is not homogeneous enough. As the result, the causal inferences derived from Regression Report are not scientifically justified. The second conclusion is that the objective criticism in econometrics applications area in order to keep the satisfactory level of scientific correctness and scientific ethics in Latvia has to be established. We also assert that the applications of inductive econometrics in agriculture are much more justified due to possibility to repeat the stochastic experiments many times in constant circumstances like in physics and mechanics. The meta-target of present article is to remind the protests of John Maynard Keynes to the careless utilization of econometric theorems and to raise a wide discussion about the problems of correctness in applying inductive statistics in economics and agriculture in Latvia.

The Correctness Problems in Applying Inductive Statistics in Economics and Agriculture

Rural Sustainability Research

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

In the article “Professor Tinbergen’s Method” (Keynes J. M. Professor Tinbergen’s Method. − The Economic Journal. 1939. Vol. 49. No. 195) John Maynard Keynes...

The Correctness Problems in Applying Inductive Statistics in Economics and Agriculture

Published Online: Aug 05, 2017

Page range: 20 - 28

DOI: https://doi.org/10.1515/plua-2017-0003

Keywords
randomness, probability, descriptive statistics, inductive statistics, linear regression

© 2017 Andrejs Jaunzems et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The Correctness Problems in Applying Inductive Statistics in Economics and Agriculture

Published Online: Aug 05, 2017

Page range: 20 - 28

DOI: https://doi.org/10.1515/plua-2017-0003

Keywordsrandomness, probability, descriptive statistics, inductive statistics, linear regression

© 2017 Andrejs Jaunzems et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
randomness, probability, descriptive statistics, inductive statistics, linear regression