We propose a generic algorithm for numerically accurate likelihood evaluation of a broad class of spatial models characterized by a high-dimensional latent Gaussian process and non-Gaussian response variables. The class of models under consideration includes specifications for discrete choices,...

The paper focuses on the issue of the modifiable areal unit problem (MAUP), which is frequently discussed within spatial econometrics. This issue concerns the changeability of the characteristics of the analysed phenomena under the impact of the change in the composition of territorial units...

The paper focuses on the issue of the aggregation problem which is frequently discussed within spatial econometrics. Aggregation problem is one of two aspects of the modifiable areal unit problem (MAUP). The aggregation problem is connected with the volatility of the obtained results occurred...

The traditional approach to estimate spatial models bases on a preconceived spatial weights matrix to measure spatial interaction among locations. The a priori assumptions used to define this matrix are supposed to be in line with the "true" spatial relationships among the locations of the...

Studying the poverty and income distribution effects of macroeconomic policies or shocks requires a methodology that accounts on the one hand for the nature of the policy or shock being studied and their aggregate impact on the economy and, on the other hand, the heterogeneity of their overall...

This paper measures the potential impacts of the devaluation of domestic currency of the small, developing, landlocked and transition South Asian economy of Nepal, which is lagging behind in policy studies. The impacts on growth, distribution, price changes in factor and product markets, and on...

In this study we assess the impact of the Working Income Tax Benefit (WITB) on labour supply, GDP and income distribution in Canada, using a general equilibrium microsimulation model. We also estimate labour supply and demand elasticities using survey data to ensure that households’ behaviour...

A family of scaling corrections aimed to improve the chi-square approximation of goodness-of-fit test statistics in small samples, large models, and nonnormal data was proposed in Satorra and Bentler (1994). For structural equations models, Satorra-Bentler's (SB) scaling corrections are...

The three-step generalized methods of moments (GMM) approach of Kapoor, Kelejian and Prucha (2007), which corrects for spatially correlated errors in static panel data models, is extended by introducing fixed effects, a spatial lag, and a one-period lag of the dependent variable as additional...

Microeconometrics researchers have increasingly realized the essential need to account for any within-group dependence in estimating standard errors of regression parameter estimates. The typical preferred solution is to calculate cluster-robust or sandwich standard errors that permit quite...