Recent empirical studies reveal that the convergence speed of nominal and real variables are fairly different. In this paper, we study the temporal evolution of the mutual influence between the convergences of a nominal and a real variable. We first refer to sigma-convergence analysis. In order...

This study presents an approach to apply the maximum likelihood estimation (MLE) method to estimate the parameters in quantitative spatial economic models. The proposed method can be applied to any model in which the unique values of the error terms can be recovered from the observed data on the...

In many microeconometric models we use distances. For instance, in modelling the individual behavior in labor economics or in health studies, the distance from a relevant point of interest (such as a hospital or a workplace) is often used as a predictor in a regression framework. However, in...

This paper investigates the impact of the Covid-19 pandemic on trade flows in the case of the European countries. First, an ARDL dynamic panel model is estimated using the PMG method to analyse monthly data covering the most recent period (2019M1-2021M12); then, the GMM and PCSE approaches are...

This paper introduces a new framework for quantile estimation. Quantile regression techniques have proven to be extremely valuable in understanding the relationship between explanatory variables and the conditional distribution of the outcome variable. Quantile regression allows the effect of...

An innovative and simple experiment with cross-section data ordering is carried out to exploit a basic feature between many economic variables – nonlinear scale dependence. The experiment is tried on hedonic price models using two data sets: automobiles and computers. Our key findings are: (a)...

This paper estimates individual treatment effects in a triangular model with binary — valued endogenous treatments. Following the identification strategy established in Vuong and Xu (2015), we propose a two — stage estimation approach. First, we estimate the counterfactual outcome and hence...

This paper proposes a quantile regression estimator for a heterogeneous panel model with lagged dependent variables and interactive effects. The paper adopts the Common Correlated Effects (CCE) approach proposed by Pesaran (2006) and Chudik and Pesaran (2015) and demonstrates that the extension...

In this paper, we propose an approach to estimate models with network interactions in the presence of individual unobserved heterogeneity. The latter may impact the formation of ties and/or exogenous effects, thereby undermining identi cation of the associated parameters. In a panel setting, we...

I propose a computational algorithm for estimating heterogeneous agent macro models with micro data. The main challenge is that the state vector is infinite-dimensional and the likelihood of the stationary distribution is intractable. The key feature of the framework is that it minimizes the...