Causal Models for Improving Trade, Market Potential and Development

Abstract

Substantial attention continues to be focused upon the relationship between trade performance and the economic development of nations, and the implications of this relationship for marketers and government policy-makers. This author uses causal analysis for testing models which relate variables such as level of development, per capita growth of Gross Domestic Product per Capita (GDPC), population growth, individualism, and import and export performance. While the usefulness of per capita growth and the usual means of categorizing level of development is questioned, other important discoveries are made. Improved literacy levels, GDPC, trade performance (including both exports and imports), and reduced population growth are essential for the long-term well-being of a nation. The casual and noncasual likns between these variables lead to significant perscriptions for marketers and government policy-makers. Path analysis was found to produce righer results that typical correlation analysis. The latter methods lead to unreliable and dangerous conclusions.