We forecast income growth over the period 2000-2050 in the US, Canada, and France. To ground the forecasts on relationships that are as robust as possible to changes in the environment, we use a quantitative theoretical approach which consists in calibrating and simulating a general equilibrium...

Artificial neural networks have become increasingly popular for statistical model fitting over the last years, mainly due to increasing computational power. In this paper, an introduction to the use of artificial neural network (ANN) regression models is given. The problem of predicting the GDP...

In the article the authors attempted to develop the neoclassical model of economic growth, repealing two assumptions regarding the Solow growth model. First of all, the authors assume that the growth path of the number of employees is increasing asymptotically to a fixed value, not to infinity...

This paper considers panel growth regressions in the presence of model uncertainty and reverse causality concerns. For this purpose, my econometric framework combines Bayesian Model Averaging with a suitable likelihood function for dynamic panel models with weakly exogenous regressors and fixed...

A new causal simulation model of economic development was created, which comprehensively in detail and fully reflects various types of legal and shadow economic activities and their interrelations. The model is used to forecast the whole (legal and shadow) country' s economy up to 2022. The...

Oil discoveries can constitute a major positive and exogenous shock to economic activity, but the resource curse hypothesis would suggest they might also be detrimental to growth over the long run. This paper utilizes a new methodology for estimating growth underperformance to examine the extent...

Oil discoveries can constitute a major positive and exogenous shock to economic activity, but the resource curse hypothesis would suggest they might also be detrimental to growth over the long run. This paper utilizes a new methodology for estimating growth underperformance to examine the extent...

This paper attempts to estimate long-run forecasting of Indian GDP for the post-COVID period using the factor error correction model (FECM). The model builds on a dynamic factor model that directly and indirectly captures many dimensions affecting the cycles of a macro variable. The availability...