The aim of this article is to analyse empirically whether the level of institutional quality influences how financial development affects poverty for a sample of developing countries covering the period from 1984 to 2012. Using an interaction term constructed as a product between financial development and institutional quality we find that the pro-poor impact of financial development decreases as the quality of institutions rises. Such a differential effect can be ascribed to the capacity of banks to provide functions that mimic those performed by an institutional framework that works well. The results of this article can be used for policy management.

This paper empirically assesses the potential nonlinear relationship between competition and bank risk for a sample of commercial banks in the Baltic countries over the period 2000–2014. Competition is measured by two alternative indexes, the Lerner index and the market share, while we consider the Z-score and loan loss reserves as proxies for bank risk. In line with the theoretical predictions, we find an inverse U-shaped relationship between competition and financial stability. This then means that above a certain threshold, the lack of competition is likely to exacerbate the individual risk-taking behaviour of banks, and could be detrimental to the stability of the banking sector in the Baltic countries. The threshold is around 0.60 for the Lerner index, and close to 50% for market share in terms of assets. The policy implications are that the existence of such a threshold suggests that the future evolution of the structure of the banking industry in these countries is of critical importance. Specifically, this implies that policy-makers should place greater emphasis on mergers and acquisitions to avoid any significant increase of banking sector concentration.

This paper examines the interaction between non-linear deterministic trends and long run dependence by means of employing Chebyshev time polynomials and assuming that the detrended series displays long memory with the pole or singularity in the spectrum occurring at one or more possibly non-zero frequencies. The combination of the non-linear structure with the long memory framework produces a model which is linear in parameters and therefore it permits the estimation of the deterministic terms by standard OLS-GLS methods. Moreover, the orthogonality property of Chebyshev’s polynomials makes them especially attractive to approximate non-linear structures of data. We present a procedure which allows us to test (possibly fractional) orders of integration at various frequencies in the presence of the Chebyshev trends with no effect on the standard limit distribution of the method. Several Monte Carlo experiments are conducted and the results indicate that the method performs well. An empirical application, using data of real exchange rates is also carried out at the end of the article.