The authors study the prediction of latent variables in a finite mixture of linear structural equation models. The latent variables can be viewed as well-defined variables measured with error or as theoretical constructs that cannot be measured objectively, but for which proxies are observed....

Using the multiple indicator-multiple cause (MIMIC) approach, this paper generates a novel global database by estimating the size of the shadow economy for 157 countries over 1991 to 2017. The results suggest that the OECD countries are by far the lowest with values below 20% of off official GDP...

The key proposition of the paper lies in the treatment of financial statements as a matrix of endogenous information codetermined by double entry. To account for the highly structured information set in econometric estimation, we develop a generalised structural system for use with accounting...

All parameters in structural vector autoregressive (SVAR) models are locally identified when the structural shocks are independent and follow non-Gaussian distributions. Unfortunately, standard inference methods that exploit such features of the data for identification fail to yield correct...

We investigate into the simulated (Monte Carlo) performance of some LAD-based estimators vis-a-vis that of the LS-based estimators for multi-equation linear econometric models of various error specifications - such as Normal, Cauchy, Gamma, Beta1 and Beta2 - in presence of outliers different in...

Arnold Zellner and Nagesh Revankar in their well-known paper "Generalized Production Functions" [The Review of Economic Studies, 36(2), pp. 241-250, 1969] introduced a new generalized production function, which was illustrated by an example of fitting the generalized Cobb-Douglas function to the...

We present a new Stata command, BMTE (bias-minimizing treatment e ects), which implements two new estimators proposed in Millimet and Tchernis (2012) designed to estimate the effect of treatment when there exists selection on unobserved variables and appropriate exclusion restrictions are...

In the framework of structural VAR models with ARCH effect, we show that a sufficient condition for the local identification of a structural model is that at most one structural shock is homoskedastic. Our approach is based on a result of Rothenberg (1971)

The problem of multicollinearity in the assessments of coefficients is well established. However, it is rarely researched in the estimations of macroeconomic variables and economic performance of developing countries. Predicatively, it has impacts on the estimations of coefficients that should...

All parameters in structural vector autoregressive (SVAR) models are locally identified when the structural shocks are independent and follow non-Gaussian distributions. Unfortunately, standard inference methods that exploit such features of the data for identification fail to yield correct...