Analysis of GDP using the n-variable Regression Model
Keywords:GDP negative, Dependency, n-variable Regression Model, initial conditions, forex
Purpose: Gross Domestic Product(GDP) depends on Agriculture, Service, and industry performance. The main aim of the study is to assess the relationship between dependent variable GDP and Independent variables agriculture, industry, and service sector by using the n-variable Regression Model at initial condition.
Design/Methodology/Approach: The study is an application of the n-variable Regression Model at the initial condition to analyze the situation of GDP along with reasons not becoming zero GDP even after using the initial condition. The secondary data of the GDP of Nepal from the Central Bureau of Statistics of 10 years till 2019/20 has been analyzed. By finding cofactors of correlation coefficient matrix, Mean and standard deviation of the individual data to establish the linear relationship between dependent and independent variable.
Findings/Result: Under initial conditions, if all the independent variables zero, the GDP is −751028.431 billion, negative sign shows that GDP decreases highly if the entire major factor has no role in GDP. It is non-zero GDP. It means in the 11th year the stated amount will be expended from the previous year saving for forex to import which will not be possible in a sustainable economy. It will not be possible in real conditions however it may be hypothetical possible either because of the impact of informal economy or disinvestment or negative net exports. It is significant for forecasting the future GDP of a country effectively assuming different conditions for policy formulation.
Originality/Value: It is the first empirical research using the n-variable Regression Model for GDP Analysis.
Paper Type: Analytical Policy Research