# Econometrics Project

**Topics:**Regression analysis, Macroeconomics, Autocorrelation

**Pages:**20 (4289 words)

**Published:**February 19, 2012

LITERATURE REVIEW

The current economic crisis has become a major concern of all nations today. It has led policymakers and economists to rethink about the instrument for economics stability. One of the most damaging consequences of this crisis is the consumption instability, which negatively affects risk adverse agents’ welfare. As mentioned by Athahasoulis and van Wincoop (2000) as well as Pallage and Robes (2003), consumption instability could have detrimental consequences for the accumulation of human capital and physical capital. Therefore, the study of the relationship between the economic indicators such as household consumption, GDP growth, GNI per capita and inflation rate is necessary and important in order to contribute to the economic stability as well as the economic growth. This paper examines the impact of GDP growth, GNI per capita and inflation rate as independent variables on the total private domestic consumption, which is considered as the dependent variable. It takes in account data from set countries in year 2007, the year that indicates the entrance period of 2008 world economic crisis. The objective is to evaluate the impact of these independent variables on the total private domestic consumption through the econometrics tools for these set countries, which have been randomly chosen in function of the world geography repartition. In addition, we want to describe the economic relationship between those variables. For example according to Keynesian model, aggregate consumption is volatile rather than smooth because any change in current income is reflected by a change in consumption. Moreover, according to the economics theory, GDP growth is a measure of the social welfare. So it implies the notion of consumption as well as inflation rate. METHODOLOGY

All data used in our econometrics model were secondary date whereby they were obtained from World Bank website taken from a specific year, which is 2007. Therefore, this is a cross-sectional analysis because our research involves the observation of the entire population of 50 countries across the world which was taken at a specific time (2007).

THE ECONOMETRICS MODEL

The econometric model that we would like to propose in our research paper is as follows: Ci = β0 + β1Gi + β2Yi + β3Ii + εi

Based on this model, the dependent variable and three independent variables are as follows:

Dependent Variable

Ci: Total private domestic consumption as a percentage of GDP (measured in %). Total private domestic consumption can be defined as the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. In this model, we would like to see the effect of annual GDP growth, gross fixed investment as a percentage of GDP and gross national income per capita on private domestic consumption as a percentage of GDP. The data for this variable were obtained from this site - http://data.worldbank.org/indicator/NE.CON.PETC.ZS

Independent Variables

There are 3 independent variables in this model. They are:

1. Gi: Percentage of annual GDP growth (measured in %). It can be defined as the annual percentage growth rate of GDP at market prices based on constant local currency. In this model, we want to observe if percentage of annual GDP growth has a significant effect on total private domestic consumption as a percentage of GDP. Annual GDP growth is expected to be positively related to total private domestic consumption as a percentage of GDP, whereby the higher the annual GDP growth, the higher the total private domestic consumption as a percentage of GDP would be because total private domestic consumption is typically the largest component of GDP. Therefore, when there is a positive growth (an increase) in annual GDP, the total private domestic consumption as a percentage of GDP would definitely increase as well. Thus, β1 is expected to be positive. The data for...

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