If the researchers go by the traditional definition provided for explaining regression analysis, then it can be easily understood that the association that can exist between dependent and independent variable(s) is unidirectional in nature, may it be linear or non-linear. The direction of this association runs from independent to dependent variable. That is the reason behind the naming conventions of dependent and independent variables, as it had been believed that no other direction can exist between these two variables, and that was the foundation of regression analysis.
However, situations have changed in last couple of years. Advent of several domains in the field of applied economics has made the researchers to think beyond the boundaries of unidirectional associations, as incidences of several negative economic consequences have made them mull over it. For example, for achieving the desired rate of growth and to boost up industrialization, a nation needs energy the most and this is the primary driver of growth considering most of the developing nations across the world. Now, this energy is generally produced from fossil fuels, like coal, oil, petroleum etc. Continuous combustion of these fossil fuels in turn results in rise in the level of emission in the atmosphere. The emissions are in the forms of carbon dioxide, sulphur dioxide, nitrogen dioxide, suspended particulate matters, fecal coliform etc. These negative environmental consequences of accelerated economic growth can possibly cause harm to the growth itself, by causing harm towards the other drivers of growth, li
ke hygienic state of labor force. If this example can be framed by denoting dependent and independent variables, then for the first half of the example, economic growth is the dependent variable and fossil fuel consumption is the independent variable. However, in the second half of the example, the variables swap their positions. Hence, unidirectional association does not exist in this case. For more information about various directions of economic analysis, kindly browse through the pages of www.elkstatistics.com.