What is the probability of high inflation; how high, when? These questions are important to all investors since even the 2% level to which we are accustomed will cut an investor's portfolio by over 17% during a decade. This 2% level is the target of the Federal Reserve, along with near 0%...

Konchitchki and Patatoukas (2014) (hereafter KP 2014) show that aggregate accounting earnings growth predicts future nominal Gross Domestic Product (GDP) growth and that professional macro forecasters do not fully incorporate the information contained in aggregate accounting earnings. Based on...

Tourism is one of the most important factors in the productivity of the Greek economy with significant multiplier effects on the country's economic activity. This study tests for the existence and direction of causality between output growth and tourism expenditure using a trivariate model with...

В данной работе представлен краткий обзор теоретических и эмпирических работ по учету научно-технического прогресса в моделях экономического роста, выявлены...

You're probably familiar, at least in passing, with the 'convexity' of long-term bonds - i.e. that yields dropping 1% produce a bigger price move than yields rising 1%. A significant amount of brainpower has gone into understanding all the ramifications of this convexity in the fixed income...

This research utilises a non-linear Smooth Transition Regression (STR) approach to modelling and forecasting the exchange rate, based on the Taylor rule model of exchange rate determination. The separate literatures on exchange rate models and the Taylor rule have already shown that the...

We propose a general simulation-based procedure for estimating quality of approximate policies in heterogeneous-agent equilibrium models, which allows to verify that such approximate solutions describe a near-rational equilibrium. Our procedure endows agents with superior knowledge of the future...

We examine how conditionality inherent to the real-life observable data influences our forecasting and decision-making based on this data. We show the importance of conditioning the observable data sets for correct forecasts and subsequent decision-making by analyzing examples ranging from logic...

ARFIMA models, as advocated by Jiang and Tian for use in long-term volatility forecasting, are found in a follow-up empirical study to be dominated by a certain simple historical predictor of stock price volatility at a five-year horizon. (This particular historical predictor is not recommended...

This paper investigates whether predictions of future economic growth can be improved by using standard measures of broadband infrastructure. The investigation is carried out by comparing the predictive accuracy of dynamic panel models of economic growth estimated with and without measures of...