Measuring the impacts of credit restrictions on the trade performance of debtor nations

Premakumar, Velupillai
Journal Title
Journal ISSN
Volume Title
Research Projects
Organizational Units
Organizational Unit
Journal Issue

The interdependence of the developed world economy and that of the third world has been increasingly evident since the debt crisis of the eighties. International trade declined with the consequence of global economic stagnation. One major contributor to the cumulative and self reinforcing nature of the crisis is the trade impacts of the restrictive capital flows. Trade models applied to extract the debt-to-trade linkages have generally over looked the micro economic behavior that lead to the observed macroeconomic performance. Micro economic models abound that examine the theoretical concerns of this issue. This study re-examines the theoretical considerations, especially as they apply to limited capital availability and the consequences in consumption and investment behavior. Such decisions, made under limited borrowing ability, are linked to the conventional trade model via the national income and balance of payments account identities. The observed consumption and investments are modelled as deviating from the optimal, with no limits on borrowing, and a model is developed to measure this adjustment in total absorption. Import decisions arise from the consumption and investment demands so determined. Export production is dependent on the capacity to import. Thus the trade performance is linked to the consumption and investment decisions and is affected by the capital constraints. The adjustment factor thus obtained, in combination with the traditional elasticity measures enables constructing export and import elasticities with respect to constraining capital. The model estimates were made on a pooled data of eighteen countries that face debt problems. The model estimates confirm the linkages. However, the sensitivity of trade to credit limits appear too low, possibly due to the degree of heterogeneity in the pooled data.