Reporting on Research Based on Regression Analysis


In this economic research paper, the author investigates the stability of given macroeconomic policies. To achieve this objective, it is crucial to establish an existence relationship between variables under the study. Many empirical and theoretical studies have explored on this topic and reached varied conclusions. Specifically, effects of medium or high inflation hinder the economic growth. This arises from the change of relative prices, which in turn affect the efficiency in resource distribution.  This paper designed to analyze the non-linearity in inflation and the growth relationship for several countries in a period of eight years.

In this work, several questions are studied; the first is the estimation of the threshold inflation level for a set of transitional countries comparing their economic performance. These countries are Moldova, Kazakhstan, Russia, Georgia, Belarus and Ukraine. The first consideration is the time, commonly known as the period for economic development, although other studies analyzed earlier transitional period between 1991- 1998. The concept of structural breaks in the data, which is econometrically confined, is vital to help people make a choice for this time-frame. The 1990’s period saw a lot of transition processes linked to the fall of the Soviet Union. Our second consideration is the use of different sets of descriptive variables in the data model.  The paper clarifies the growth dynamics that employs such regressors like transitional index, war dummy, fiscal deficits and structural reforms. They are, thus, the set of regressors that explain growth in such a period, but not at other times of economic development (Doane, David & Seward, 2012).

The other motive of this research is the usefulness of results to the policymakers from countries in question. The question one ought to ask is if inflation is truly harmful to economic growth after reaching a particular level, then the awareness of this level is vital to policymakers to formulate macroeconomic policies.  One, therefore, analyzes nonlinear interactions between the inflation rate and economic growth by the use of nonlinear least square approach. This allows for a threshold estimation of inflation level and a formal way of testing its significance. The other part of the study discusses the existing empirical and theoretical evidence about the nature of relationship between two variables.

The first theoretical study has inflation among other dependent variables. For example, the Clarida and Gali models (1999) are given by a system of three blocks of equations. These equations describe the aggregate demand, aggregate supply and the monetary policy in models that base on the real business cycle theory. In these models, an extended nominal price rigidity and monopolistic competition makes them different from traditional Keynesian model. Therefore, all dynamic systems coefficients explicitly derived from the original theory. A common problem with most theoretical models is that resultant equations are non-linear and highly dimensional. This makes them hard to solve in a closed system without transformation or additional assumptions. For example, the basic equation for aggregating supply and demand form a three-dimensional function that can be solved in a general form for a number of non-linear specifications.


To begin with, the analyzing quantitatively the relationship between inflation and growth by the use of a growth regression appears to be the main works of Barro (1991).

d logY=Xβ +ε

In this case, Y is the real output, X is the matrix for descriptive variables, β is the coefficient matrix while ε is the error term. Endogenous and neo-Keynesian growth has a common problem of empirical and numerical studies that never produces a precise list of explanatory variables. Endogeneity is the fact that an independent variable in the model is potentially a choice variable correlated to unobserved relegated error terms. The observation of independent variable performed to all variables in the data.  For example, if few able bodied workers are likely to join the given union, and, receive lower salaries, a failure to control such correlation will yield the estimated effect of down biased wages. In case of the equation above, all theories approve that the level of technology is a determinant in economic growth, but none shows a way in which to measure it. The same applies to the level of human capital and the degrees of monopoly in a country.

This requires a different approach for selecting the explanatory variable. Neo-classical growth model insists on using investment and population growth as variables in the regression. Therefore, this method predicts that a rise in the investment level and reduction in population growth has a positive effect on the population growth. 

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