Inflation and Endogenous Growth in Underground Economies

The paper examines the effect of inflation on the growth rate in economies with underground, or ”non-market”, sectors. The model incorporates a non-market good into an endogenous growth cash-inadvance economy with human capital. Taxes on labor and capital induce substitution into the non-market sector which avoids such taxes. However the non-market sector uses only cash for exchange and cannot avoid the inflation tax, while the market sector allows costly credit use. We estimate a MIMIC model for latent underground economy using monthly data for Bulgaria, Croatia and Romania. Furthermore, we estimate a dynamic structural equation model and investigate short-run effects of the underground economy on output growth and test for Granger causality and long-run cointegrating relationships using bivariate Granger-causality tests and Johansen’s maximum likelihood technique. The result indicate different shares of underground economies across the three countries and a positive long-run effect of underground economy on output growth.Shadow economy, endogenous growth, dynamic structural equation modelling, latent variables

Regional development assessment: A structural equation approach

Abstract We propose a multivariate statistical framework for regional development assessment based on structural equation modelling with latent variables and show how such methods can be combined with non-parametric classification methods such as cluster analysis to obtain development grouping of territorial units. This approach is advantageous over the current approaches in the literature in that it takes account of distributional issues such as departures from normality in turn enabling application of more powerful inferential techniques; it enables modelling of structural relationships among latent development dimensions and subsequently formal statistical testing of model specification and testing of various hypothesis on the estimated parameters; it allows for complex structure of the factor loadings in the measurement models for the latent variables which can also be formally tested in the confirmatory framework; and enables computation of latent variable scores that take into account structural or causal relationships among latent variables and complex structure of the factor loadings in the measurement models. We apply these methods to regional development classification of Slovenia and Croatia

Determinants of the Low SME Loan Approval Rate in Croatia

commercial banks, credit rationing, latent variable models, loan assessment, small and medium enterprises., C31, C51, C52, G21, H81,