Background
In econometrics and statistical analysis, understanding the components of regression equations is essential. One integral element of these equations is the right-hand-side variable, often abbreviated as RHS variable. This term is frequently used in academic writings, research papers, and practical data analysis.
Historical Context
The concept of regression analysis can be traced back to the 19th century with the work of Sir Francis Galton. Over time, as statistical techniques evolved, terminology also developed. The term “right-hand-side variable” emerged to clearly delineate the components of regression equations, especially with the rise in computational and algorithmic analysis used in economics and related fields.
Definitions and Concepts
A right-hand-side variable (RHS variable) refers to an explanatory variable in a regression equation. In such an equation, variables placed on the right-hand side (RHS) serve to explain the variance in the left-hand-side variable (dependent variable). These are also known as independent variables or predictors.
Example:
In the simple regression equation:
Y = β0 + β1X1 + ε
Y is the dependent variable, while X1 is the right-hand-side variable.
Major Analytical Frameworks
When discussing right-hand-side variables within different economic schools of thought, they may be addressed with some variations in interpretation and usage.
Classical Economics
Classical economists might use RHS variables to study relationships between aggregate outputs and factors of production.
Neoclassical Economics
Neoclassical economists might employ RHS variables to explore supply and demand, price setting, and individual rationality within markets.
Keynesian Economics
Keynesian economists use these variables to analyze broader economic phenomena such as consumption, investment, and government spending’s impact on aggregate demand.
Marxian Economics
Marxian analyses might apply RHS variables to explore distributions of wealth and the relationships between different classes within the economy.
Institutional Economics
Institutional economists consider RHS variables crucial in understanding how institutions affect economic behavior and outcomes.
Behavioral Economics
Behavioral economists would look at RHS variables to study human biases, heuristics, and decision-making processes.
Post-Keynesian Economics
These variables in Post-Keynesian models aid in exploring the dynamics of economies over time, focusing on elements like price and wage stickiness.
Austrian Economics
Austrian scholars often use RHS variables to understand individual actions and market processes free from government interventions.
Development Economics
Development economists utilize RHS variables to study factors that influence economic development, such as education, infrastructure, and policy impacts.
Monetarism
For monetarists, RHS variables relate to factors influencing money supply, inflation, and monetary policy interventions.
Comparative Analysis
Right-hand-side variables are crucial regardless of the economic framework due to their role in explaining the behavior of the dependent variable. However, the choice of RHS variables, their theoretical underpinnings, and their economic interpretations can differ significantly across different schools of thought.
Case Studies
Refer to practical examples like analyzing the impact of education on wage levels, where education level is the RHS variable and wage level is the dependent variable.
Suggested Books for Further Studies
- “Econometric Analysis” by William H. Greene
- “Applied Econometrics” by Dimitrios Asteriou and Stephen G. Hall
- “Basic Econometrics” by Damodar N. Gujarati and Dawn C. Porter
Related Terms with Definitions
- Dependent Variable: The outcome you are trying to explain or predict.
- Independent Variable: Another term for right-hand-side variables; factors that explain changes in the dependent variable.
- Regression Equation: A mathematical way of describing the relationship between the dependent and independent variables.
- Explanatory Variable: Synonymous with RHS variable; denotes factors included on the right side of a regression equation to explain the dependent variable.
