Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This article develops a threshold panel data nonlinearity test for poverty traps. The new testing strategy extends the work on nonlinearity tests for panel data by considering threshold nonlinearities in the fixed-effects components. Monte Carlo simulations are conducted to evaluate the finite-sample performance of these tests. The tests are applied to the relationship between Gross Domestic Product (GDP) per capita and capital stock per capita. Our application to a panel of countries for the period 1973 to 2007 uncovers the presence of two regimes determined by the level of capital stock per capita. The conclusions from our test also support the existence of a poverty trap determined by a capital stock per capita level at the 11% quantile of its pooled worldwide distribution.