The purpose of this paper is, through a system of software, to analyze some theoretical aggregate models. We suggest to build a disaggregated model to compare its results with these of the aggregated one. The disaggregated model uses an analogical mechanism of the individual behaviors so that a...

SINGUL is a imperfect competition market (without any auctioneer process) price and quantity calculation model. Its algorithm is analogical because it is built from the most realistic (as possible) behavior of the agents of a market. Our model simulates the meeting between the agents. Each agent...

In all areas of human knowledge, datasets are increasing in both size and complexity, creating the need for richer statistical models. This trend is also true for economic data, where high-dimensional and nonlinear/noparametric inference is the norm in several fields of applied econometric work....

This paper attempts to highlight the role of new short-term forecasting methods. It leads to the fact that artificial neural networks (LSTM) are more efficient than classical methods (ARIMA and HOLT-WINTERS) in forecasting the HICP of Côte d'Ivoire. The data are from the “Direction des...

In many statistical problems there is the need to analyze the structure of an unknown n-dimensional array given its marginal distributions. The usual method utilized to solve the problem is linear programming, which involves a large amount of computational time when the original array is large....

In the microsimulation literature, it is still uncommon to test the statistical significance of results. In this paper we argue that this situation is both undesirable and unnecessary. Provided the parameters used in the microsimulation are exogenous, as is often the case in static...

Linear fractional stable motion is a type of a stochastic integral driven by symmetric alpha-stable L´evy motion. The integral could be considered as a non-Gaussian analogue of the fractional Brownian motion. The present paper discusses R package rlfsm created for numerical procedures with the...

As the amount of economic and other data generated worldwide increases vastly, a challenge for future generations of econometricians will be to master efficient algorithms for inference in empirical models with large information sets. This Chapter provides a review of popular estimation...

This note describes ParallelKnoppix, a bootable CD that allows econometricians with average knowledge of computers to create and begin using a high performance computing cluster for parallel computing in very little time. The computers used may be heterogeneous machines, and clusters of up to...

In many statistical problems there is the need to analyze the structure of an unknown n-dimensional array given its marginal distributions. The usual method utilized to solve the problem is linear programming, which involves a large amount of computational time when the original array is large....