This study empirically re-examines the relationship between transport infrastructure and economic growth in India for period 1990–2017. Multivariate dynamic models are applied to estimate different modes of namely road, rail air transports vector error correction model framework. The results reveal that road have significant positive contribution long-run while is insignificant. further examine...

The breakdown of the Bretton Woods system and the adoption of generalized ‡oating exchange rates ushered in a new era of exchange rate volatility and uncertainty. This increased volatility lead economists to search for economic models able to describe observed exchange rate behavior. The present is a technical Appendix to Cerrato et al. (2009) and presents detailed simulations of the proposed m...

Employing a probit, logit and gompit model this paper demonstrates that small firm development, represented by a group of structural, behavioral and performance variables determines regional location in Poland. The paper uses original data that samples the small firm stratum in two contrasting regions, Pomorskie and Lubelskie. The following variables were shown to be significantly correlated wi...

In this paper, we re-examine the empirical relevance of the cost channel of monetary policy. We employ recently developed moment-conditions inference procedures, which provide a more e¢ cient and reliable econometric framework than in previous literature. Using US data, our results suggest that there is no substantial evidence for the existence of a cost channel. Keywords: Cost channel; Phillip...

Google Econometrics and Unemployment Forecasting The current economic crisis requires fast information to predict economic behavior early, which is difficult at times of structural changes. This paper suggests an innovative new method of using data on internet activity for that purpose. It demonstrates strong correlations between keyword searches and unemployment rates using monthly German data...

A least squares estimation approach for the estimation of a GARCH (1,1) model is developed. The asymptotic properties of the estimator are studied given mild regularity conditions, which require only that the error term has a conditional moment of some order. We establish the consistency, asymptotic normality and the law of iterated logarithm for our estimate. The finite sample properties are a...

This paper develops a Bayesian quantile regression model with time-varying parameters (TVPs) for forecasting inflation risks. The proposed parametric methodology bridges the empirically established benefits of TVP regressions ability to flexibly whole distribution inflation. In order make our approach accessible and relevant forecasting, we derive an efficient Gibbs sampler by transforming stat...

This paper proposes a Gaussian estimator for nonlinear continuous time models of the short term interest rate. The approach is based on a stopping time argument that produces a normalizing transformation facilitating the use of a Gaussian likelihood. A Monte Carlo study shows that the finite sample performance of the proposed procedure offers an improvement over the discrete approximation metho...

In this paper we apply the wavelets methodology to the analysis of the comovements of for some MENA countries from June 1997 until March 2005. We decompose weekly stock market returns into di¤erent time scale components using the non-decimated discrete wavelet transform and then analyze the relationships among these variables at the di¤erent time scales. Keywords : Stock market returns, Wavelet...

The use of GARCH models with stable Paretian innovations in financial modeling has been recently suggested in the literature. This class of processes is attractive because it allows for conditional skewness and leptokurtosis of financial returns without ruling out normality. This contribution illustrates their usefulness in predicting the downside risk of financial assets in the context of mode...