Prof. Angela D. Nalica
School of Statistics Faculty
University of the Philippines, Diliman
In Partial Fulfillment of the
Statistics 136: Regression Analysis
Mary Ann A. Boter
Michael Daniel C. Lucagbo
Krystalyn Candy C. Mago
April 9, 2009
The level of a country’s imports measures its participation and competitiveness in the international market. As such, it is important to identify economic indicators that affect the level of imports. Economic theory rarely presents imports as a response variable. It appears very frequently, however, as a predictor in formulas that model a multitude of variables, supporting the fact that it is highly related with other economic variables. The paper aims to construct a model with imports as the response variable and choose those independent variables that affect it significantly.
The results of the study confirm the significance of GDP and labor force size in predicting imports. These were the two main variables that had been potentially significant even as theory describes them to be. Another economic measure, budget revenue, turned out to be a good predictor for imports. The final model expresses imports as a function of GDP, labor force size and budget revenue.
All countries are linked to the rest of the world through trade. Presence of trade means that some of a country’s domestically-produced goods are exported to other countries. It also means that countries purchase needed goods not available locally. The amount of goods a country purchases from other countries is, by definition, the level of its imports. Imports, being indicative of a country’s participation and competitiveness in international trade, is an important economic variable. However, imports is not commonly expressed as an endogenous variable (that is, a dependent variable in an economic model). It appears in formulas as a value that determines the value of other variables. In this paper the researchers wish to make imports the dependent variable and pick variables that affect it much and build a model based on these variables.
It is well-accepted in economic literature that the level of a country’s imports is affected by its income. Richer countries tend to import more as they have the capacity to do so. In purchasing those goods that are not produced locally (foreign shoes, foreign foods, computers etc.), they spend on greater volumes. America, still the richest country in terms of GDP, has exceedingly high import levels. On the other hand, countries that have low incomes are a bit low on imports. Their financial resources limit the purchasing of goods and services to within geographic bounds. This study aims to determine the extent to which income is linearly related to imports, where, this time, imports is the variable to be predicted.
One common and well-understood measure of a country’s income is the Gross Domestic Product (GDP), which measures the amount of goods and services produced in a country for a given year. The researchers intend on verifying the relationship between GDP and imports by building a regression model relating these two. At the outset, a linear relationship between the two is hypothesized.
Another variable that is closely related to the level of imports is the size of the labor force. A larger labor force means greater national employment and, hence, greater capacity of the country to buy foreign goods and services and even foreign labor. China and the USA are obvious examples. Both have a large labor force and both are giant importers in the world market. Another objective of this study is to relate the level of employment with the level of imports. This relationship is not well-discussed in open-economy macroeconomics, hence the importance of a model that links the two.