Alecos Papadopoulos

Alecos Papadopoulos
Athens University of Economics and Business | AUEB · Department of Economics

PhD in Economics

About

23
Publications
3,086
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74
Citations
Citations since 2017
22 Research Items
72 Citations
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Introduction
Alecos Papadopoulos does research in Econometrics, Microeconomics and Macroeconomics. His PhD thesis "The Two-tier Stochastic Frontier (2TSF) framework: Theory and Applications, Models and Tools", was finished during August 2018, and he was awarded the Philosophical Diploma in Economic Sciences in November 2018. He has been active in research ever since. Visit the blog https://alecospapadopoulos.wordpress.com for more.

Publications

Publications (23)
Article
Full-text available
Data for 30-day readmission rates in American hospitals often show that patients that receive Home Health Care (HHC) have a higher probability of being readmitted to hospital than those that did not receive such services, but it is expected that when control variables are included in a regression we will obtain a “sign reversal” of the treatment ef...
Article
Full-text available
With a little help from a handful of scholars, the noise component of the composed error in a production model created the stochastic frontier analysis field. But after that glorious moment, it was confined to obscurity. We review what little research has been done on it. We present two cases where it torments us from the shadows, by sabotaging ide...
Article
Full-text available
This article was originally written in Greek and it has been published as part of a three-volume symposium on the concept of freedom in various scientific disciplines, in THEOLOGIA 93, 3 (2022), pp. 261-308, the scholarly journal of the Holy Synod of the Church of Greece. The present translation of the full text in English was done by the author. I...
Article
Full-text available
Quantile regression has become one of the standard tools of econometrics. We examine its compatibility with the special goals of stochastic frontier analysis. We document several conflicts between quantile regression and stochastic frontier analysis. From there we review what has been done up to now, we propose ways to overcome the conflicts that e...
Article
Full-text available
The two-tier stochastic frontier model has seen widespread application across a range of social science domains. It is particularly useful in examining bilateral exchanges where unobserved side-specific information exists on both sides of the transaction. These buyer and seller specific informational aspects offer opportunities to extract surplus f...
Article
Full-text available
We examine whether Hoyos’ (Empir Econ, 2021) critical replication of Estevadeordal and Taylor (Rev Econ Stat 95(5):1669–1690, 2013) that dealt with trade liberalization and growth, does provide, as the author claims, clear evidence that the estimation results and the conclusions of the original should be discarded, the first as “non-robust,” the se...
Article
Full-text available
In this paper, we consider various methods for evaluating the cdf of the Skew Normal distribution. This distribution arises in the stochastic frontier model because it is the distribution of the composed error, which is the sum (or difference) of a Normal and a Half-Normal random variable. The cdf must be evaluated in models in which the composed e...
Article
Full-text available
We revisit the production frontier of a firm and we examine the effects that the firm's management has on output. In order to estimate these effects using a cross-sectional sample while avoiding the costly requirement of obtaining data on management as a production factor, we develop a two-tier stochastic frontier (2TSF) model where management is t...
Article
Full-text available
We provide a detailed presentation and guide for the use of Copulas in order to account for endogeneity in linear regression models without the need for instrumental variables. We start by developing the model from first principles of likelihood inference, and then focus on the Gaussian Copula. We discuss its merits and propose diagnostics to asses...
Article
Full-text available
We present a new, single-parameter distributional specification for the one-sided error components in single-tier and two-tier stochastic frontier models. The distribution has its mode away from zero, and can represent cases where the most likely outcome is non-zero inefficiency. We present the necessary formulas for estimating production, cost and...
Article
Full-text available
The distributional specifications for the composite regression error term most often used in stochastic frontier analysis are inherently bounded as regards their skewness and excess kurtosis coefficients. We derive general expressions for the skewness and excess kurtosis of the composed error term in the stochastic frontier model based on the ratio...
Chapter
Stochastic frontier analysis (SFA) focuses mostly on measuring and analyzing matters of efficiency in production and in cost decisions, based on the conceptual and modeling device of a frontier, a boundary beyond which a firm can find itself only by chance, literally. But the existence of frontiers in human activity is a consequence of physical and...
Preprint
Full-text available
The distributional specifications for the composite regression error term most often used in stochastic frontier analysis are inherently bounded as regards their skewness and excess kurtosis coefficients. We derive general expressions for the skewness and excess kurtosis of the composed error term in the stochastic frontier model based on the ratio...
Article
In pursuit of efficiency, we propose a new way to construct least squares estimators, as the minimizers of an augmented objective function that takes explicitly into account the variability of the error term and the resulting uncertainty, as well as the possible existence of heteroskedasticity. We initially derive an infeasible estimator which we t...
Preprint
Full-text available
In pursuit of efficiency, we propose a new way to construct least squares estimators, as the minimizers of an augmented objective function that takes explicitly into account the variability of the error term and the resulting uncertainty, as well as the possible existence of heteroskedasticity. We initially derive an infeasible estimator which we t...
Preprint
We review econometric studies that attempt to estimate the effects of management on production, being on output, productivity, or efficiency. We group the studies mainly by a methodological criterion: whether they treat management as a latent variable, whether they proxy it by some other variable(s), or whether they attempt to construct a direct me...
Article
Full-text available
Data for 30-day readmission rates in American hospitals often show that patients that receive Home Health Care (HHC) have a higher probability of being readmitted to hospital than those that did not receive such services, but it is expected that when control variables are included in a regression we will obtain a "sign reversal" of the treatment ef...
Article
The distributional specifications for the composite regression error term most often used in Stochastic Frontier Analysis (SFA) are inherently bounded as regards their skewness and excess kurtosis coefficients. These bounds provide simple diagnostic tools and model selection/rejection criteria for empirical studies which appear to have been overloo...
Article
Full-text available
In the context of the two-tier stochastic frontier model, we present a new closed-form stochastic specification, the half-normal one. Expressions to calculate average and conditional measures of inefficiency are provided, for regression specifications in levels and in logs. Some results related to model validation and maximum likelihood estimation...

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Projects

Projects (5)
Project
To detail all practical steps in order to use copulas to account for possible regressor endogeneity in a linear regression setup, without the need of using instrumental variables. The project grows out from work included in my PhD thesis.
Project
The aim here is to extend the reach of Stochastic Frontier Analysis beyond matters of efficiency. In the short-term, firms set prices rather than quantities, face uncertainty and downward slopping demand, and have goals that take precedence over profit maximization. This creates a stochastic frontier model to determine the actual price, with the profit-maximizing price being the frontier. The work will be presented in EWEPA Conference London 2019, June.
Project
Together with Chris Parmeter, we leave no skewed stone unturned in Stochastic Frontier models. Namely, we offer simple model diagnostics based on the skewness (and the excess kurtosis) of the OLS residuals.