We consider integrated modified least squares estimation for systems of cointegrating multivariate polynomial regressions, i. e., systems of regressions that include deterministic variables, integrated processes and products of these variables as regressors. The errors are allowed to be...

This article analyzes the impact of capital structure and bank liquidity on the performance of commercial banks in Vietnam, a transition market in Asia. This research is unique because it is the first study to employ the Bayesian Estimation methods in banking studies. The data includes 463...

We consider fully modified least squares estimation for systems of cointegrating polynomial regressions, i. e., systems of regressions that include deterministic variables, integrated processes and their powers as regressors. The errors are allowed to be correlated across equations, over time...

The study aims to examine the determinants that affect the firm's performance in the service industries. Moreover, the study examines step-by-step how to choose the best model among the various panel data models.After employing the secondary data of the service industry firms from the CRIBIS...

This study examines how tourism development in Tunisia responds to environmental degradation, renewable energy consumption, technological innovation, and foreign direct investment. Using annual data for 1990-2023, we apply the Autoregressive Distributed Lag (ARDL) bounds approach to identify...

Food waste (FW) has become a major concern in the global era, which is affecting the societal environment and economy consistently. Rising population and urbanization have increased food production and consumption, especially in developing countries like Bangladesh. Due to limited recycling and...

This paper uses firm level data from the World Bank Enterprise surveys conducted in 2019 and from the COVID-19 follow-up surveys conducted in 2020 in eight European countries to investigate the link between firm characteristics before the pandemic and firm survival until 2020. For the first time...

This paper studies linear time‐series regressions with many regressors. Weak exogeneity is the most used identifying assumption in time series. Weak exogeneity requires the structural error to have zero conditional expectation given present and past regressor values, allowing errors to...

The most widely used textbooks on Introductory Econometrics conflate three distinct population parameters: the population regression function (PRF), the conditional expectation function (CEF), and the causal effect. They also incorrectly suggest, and sometimes state, that the Conditional Mean...

This study examines the impact of inward foreign direct investment (FDI) on economic growth in South and Southeast Asia from 2006 to 2022, using a comprehensive panel dataset and multiple econometric techniques. The baseline estimation employs Feasible Generalized Least Squares (FGLS), with...

The total assets of the banking sector in Romania increased significantly over the past decade, from RON 364.1 billion at the end of 2014 to RON 881.7 billion at the end of 2024, according to the statistics of the National Bank of Romania (NBR). This evolution was supported by several factors,...

Firm characteristics in empirical models for margins of international trade usually enter these models in linear form. If non-linearities do matter and are ignored this leads to biased results. Researchers, however, can never be sure that all possible non-linear relationships are taken care of....

Regressors often have heterogeneous effects in the social sciences, implying unit-specific slopes. OLS is frequently applied to these correlated coefficient models. I first show that without restrictions on the relation between slopes and regressors, OLS estimates can take any value including...

In this paper we study a class of weighted estimands, which we define as parameters that can be expressed as weighted averages of the underlying heterogeneous treatment effects. The popular ordinary least squares (OLS), two-stage least squares (2SLS), and two-way fixed effects (TWFE) estimands...

In this paper we study a class of weighted estimands, which we define as parameters that can be expressed as weighted averages of the underlying heterogeneous treatment effects. The popular ordinary least squares (OLS), two-stage least squares (2SLS), and two-way fixed effects (TWFE) estimands...

Poverty is a complex global issue, closely linked to economic and social inequalities. It encompasses not only a lack of financial resources but also disparities in access to education, healthcare, employment, and social participation. In alignment with the United Nations' Sustainable...

This article derives an equation characterizing the difference between OLS and IV coefficients under potentially heterogenous treatment effects. This leads to what I call the Coefficient Difference Check, which consists of checking that the difference between the estimated OLS and IV...

This paper considers transformations of nonlinear semiparametric mean functions that yield moment conditions for estimation. Such transformations are said to be information equivalent if they yield the same asymptotic efficiency bound. I derive a unified theory of algebraic equivalence for...

We study a set of fully modified (FM) estimators in multivariate cointegrating polynomial regressions. Such regressions allow for deterministic trends, stochastic trends, and integer powers of stochastic trends to enter the cointegrating relations. A new feasible generalized least squares...

A multivariate, non-Bayesian, regression-based, or feasible generalized least squares (GLS)-based approach is proposed to estimate time-varying VAR parameter models. Although it has been known that the Kalman-smoothed estimate can be alternatively estimated using GLS for univariate models, we...

We consider integrated modified least squares estimation for systems of cointegrating multivariate polynomial regressions, i. e., systems of regressions that include deterministic variables, integrated processes and products of these variables as regressors. The errors are allowed to be...

The paper introduces two estimators for the linear random effects panel data model with known heteroskedasticity. Examples where heteroskedasticity can be treated as given include panel regressions with averaged data, meta regressions and the linear probability model. While one estimator builds...

The paper considers two estimators for the linear random effects panel data model with known heteroskedasticity. Examples where heteroskedasticity can be treated as given include panel regression with averaged data, meta regression and the linear probability model. While one estimator builds on...

The widespread use of information and communication technologies (ICT) is evidenced by various devices, systems, and applications that enable organizations and individuals to interact with one another and the digital world. In this study, a comparative analysis framework was employed to evaluate...