Corrupt clubs and the convergence hypothesis1
Empirical work in a cross-section framework demonstrates little or no support for absolute convergence in per capita GDP. I argue in this paper that “divergence in corruption”, defined as the tendency of corrupt countries to become more corrupt faster than less corrupt nations, is a neglected factor that also determines the speed of convergence. Using Transparency International (TI) corruption perceptions index, I estimate C-σ and C-γ coefficients for corrupt and less corrupt economies to explore the C-divergence in corruption rankings. The study concludes that corrupt countries are C-converging, forming a “corrupt club”.
AbstractLetX1,…,Xn be iid observations of a random variableX with probability density functionf(x) on the q-dimensional unit sphere Ωq in Rq+1,q ⩾ 1. Let ::: $$f_n (x) = n^{ - 1} c(h)\sum\nolimits_{i = 1}^n {K[(1 - x'X_i )/h^2 ]} $$ ::: be a kernel estimator off(x). In this paper we establish a central limit theorem for integrated square error offn under some mild conditions.