scholarly journals Quantile composite-based path modeling: algorithms, properties and applications

2021 ◽  
Author(s):  
Pasquale Dolce ◽  
Cristina Davino ◽  
Domenico Vistocco
Keyword(s):  
Least Squares ◽  
Heavy Tails ◽  
Traditional Approach ◽  
Asymptotic Properties ◽  
Ordinary Least Squares ◽  
Diabetic Patients ◽  
Path Modeling ◽  
Theoretical Concepts ◽  
Tail Part ◽  
Conditional Means

AbstractComposite-based path modeling aims to study the relationships among a set of constructs, that is a representation of theoretical concepts. Such constructs are operationalized as composites (i.e. linear combinations of observed or manifest variables). The traditional partial least squares approach to composite-based path modeling focuses on the conditional means of the response distributions, being based on ordinary least squares regressions. Several are the cases where limiting to the mean could not reveal interesting effects at other locations of the outcome variables. Among these: when response variables are highly skewed, distributions have heavy tails and the analysis is concerned also about the tail part, heteroscedastic variances of the errors is present, distributions are characterized by outliers and other extreme data. In such cases, the quantile approach to path modeling is a valuable tool to complement the traditional approach, analyzing the entire distribution of outcome variables. Previous research has already shown the benefits of Quantile Composite-based Path Modeling but the methodological properties of the method have never been investigated. This paper offers a complete description of Quantile Composite-based Path Modeling, illustrating in details the method, the algorithms, the partial optimization criteria along with the machinery for validating and assessing the models. The asymptotic properties of the method are investigated through a simulation study. Moreover, an application on chronic kidney disease in diabetic patients is used to provide guidelines for the interpretation of results and to show the potentialities of the method to detect heterogeneity in the variable relationships.

scholarly journals A Unified Approach to Robust, Regression-Based Specification Tests

1990 ◽  
Vol 6 (1) ◽  
pp. 17-43 ◽  
Author(s):  
Jeffrey M. Wooldridge
Keyword(s):  
Least Squares ◽  
Robust Regression ◽  
Nonlinear Least Squares ◽  
Ordinary Least Squares ◽  
Conditional Variance ◽  
Least Squares Regression ◽  
Specification Tests ◽  
Conditional Mean ◽  
Quasi Maximum Likelihood ◽  
Conditional Means

This paper develops a general approach to robust, regression-based specification tests for (possibly) dynamic econometric models. A useful feature of the proposed tests is that, in addition to estimation under the null hypothesis, computation requires only a matrix linear least-squares regression and then an ordinary least-squares regression similar to those employed in popular nonrobust tests. For the leading cases of conditional mean and/or conditional variance tests, the proposed statistics are robust to departures from distributional assumptions that are not being tested, while maintaining asymptotic efficiency under ideal conditions. Moreover, the statistics can be computed using any √T-consistent estimator, resulting in significant simplifications in some otherwise difficult contexts. Among the examples covered are conditional mean tests for models estimated by weighted nonlinear least squares under misspecification of the conditional variance, tests of jointly parameterized conditional means and variances estimated by quasi-maximum likelihood under nonnormality, and some robust specification tests for a dynamic linear model estimated by two-stage least squares.

scholarly journals Relationship of Trace Metal Covariates and pH Distribution in Groundwater within Gold mining and Non-Gold mining Areas in Ghana

2020 ◽  
Author(s):  
Frederick Armah ◽  
Arnold Paintsil ◽  
Michael Adu ◽  
David Oscar Yawson ◽  
Justice Odoi
Keyword(s):  
Quantile Regression ◽  
Least Squares ◽  
Gold Mining ◽  
Ordinary Least Squares ◽  
Sub Saharan Africa ◽  
Ph Distribution ◽  
Ph Values ◽  
Sampling Locations ◽  
Spatio Temporal ◽  
Conditional Means

One of the most important defining characteristics of groundwater quality is pH as it fundamentally controls the amount and chemical form of many organic and inorganic solutes in groundwater. Groundwater data are frequently characterized by a wide degree of variability of the factors which possibly influence pH distribution. For this reason, it is challenging to link the spatio-temporal dynamics of pH to a single environmental factor by the ordinary least squares regression technique of the conditional mean. In this study, quantile regression was used to estimate the response of pH to nine environmental factors (As, Cd, Fe, Mn, Pb, turbidity, electrical conductivity, total dissolved solids and nitrates). Results of 25%, 50%, 75% quantile regression and ordinary least squares (OLS) regression were compared. The standard regression of the conditional means (OLS) underestimated the rates of change of pH due to the selected factors in comparison with the regression quantiles. The effect of arsenic increased for sampling locations with higher pH values (higher quantiles) likewise the influence of Pb and Mn. However, the effects of Cd and Fe decreased for sampling locations in higher quantiles. It can be concluded that these detected heterogeneities would be missed if this study had focused exclusively on the conditional means of the pH values. Consequently, quantile regression provides a more comprehensive account of possible spatio-temporal relationships between environmental covariates in groundwater. This study is one of the first to apply this technique on groundwater systems in sub-Saharan Africa. The approach is useful and interesting and has broad application for other mining environments especially tropical low-income countries where climatic conditions can drive rapid cycling or transformations of pollutants. It is also pertinent to geopolitical contexts where regulatory; monitoring and management capacities are weak and where mining pollution of groundwater largely occur.

PENGARUH STRUKTUR KEPEMILIKAN BANK TERHADAP KINERJA UNIT USAHA SYARIAH PADA BANK DI INDONESIA

2018 ◽  
Vol 1 (2) ◽  
pp. 25-32
Author(s):  
Hafidzah Nurjannah ◽  
Yul Efnita ◽  
Eva Sundari
Keyword(s):  
Least Squares ◽  
Firm Size ◽  
Ordinary Least Squares

Penelitian ini bertujuan untuk menganalisa pengaruh secara signifikan baik partial maupun simultan pada variabel kepemilikan bank, simpanan (DPK), rasio pinjaman terhadap simpanan (LDR) dan rasio kecukupan modal (CAR), Non Performing Loan (NPL) dan ukuran perusahaan terhadap profitabilitas (ROA) pada bank yang memiliki Unit Usaha Syariah (UUS) baik itu pada Bank Pembangunan Daerah (BPD) maupun Bank Swasta. Populasi dan sampel terdiri dari 24 UUS milik Bank Pembangunan Daerah (BPD) dan Bank Swasta. Dari ke 24 bank tersebut, hanya 18 bank yang dipilih menjadi sampel. Bank-bank tersebut adalah 7 Bank Swasta dan 11 Bank Pembangunan Daerah. Periode penelitian ini adalah 2010-2014. Data diambil dari laporan tahunan bank. Penelitian ini menggunakan data panel dan pooled Ordinary Least Squares (OLS). Hasil penelitian menunjukkan UUS milik Bank Pembangunan Daerah lebih baik daripada Bank Swasta. Hal ini disebabkan beberapa faktor. Pertama, pinjaman hanya untuk pejabat pemerintah daerah di mana pembayaran pinjaman melalui pengurangan gaji, sehingga kemungkinan tidak dapat membayar pinjaman sangat rendah meskipun situasi ekonomi tidak stabil. Kedua, karena Bank Pembangunan Daerah menyediakan layanan hanya untuk lokal saja, sehingga memiliki pengetahuan khusus tentang daerah tersebut. Sehingga akan memungkinkan nasabah menilai penerapan pinjaman dan mengidentifikasi pinjaman yang memenuhi syarat. Ketiga, kinerja Bank Pembangunan Daerah yang diawasi oleh pemerintah daerah lebih intensif. Kata Kunci : Hedging, Laverage, Cash Ratio, Firm Size, Bank Syariah.

The antecedents of corporate social and environmental responsibility discourse in Pakistan: Multiple theoretical perspectives

2019 ◽  
Author(s):  
Muhammad Farhan Basheer ◽  
Saqib Muneer ◽  
Muhammad Atif ◽  
Zubair Ahmad
Keyword(s):  
Institutional Theory ◽  
Least Squares ◽  
Agency Theory ◽  
Stakeholder Theory ◽  
Fixed Effects ◽  
Ordinary Least Squares ◽  
Environmental Responsibility ◽  
Legitimacy Theory ◽  
Discourse Practices ◽  
Corporate Social

The primary purpose of the study is to explore the antecedents of corporate social and environmental responsibilities discourse practices in Pakistan. The industry sensitivity, government shareholding, block holder ownership, print media coverage, environmental monitoring programs, and strategic posture are examined as antecedents of corporate social and environmental responsibility practices. A multidimensional theoretical perspective namely stakeholder theory (ST), institutional theory (IT), agency theory (PAT), and legitimacy theory (LT) is used to conceptualize the phenomena. All the four of perspective theories (positive accounting theory, legitimacy theory, stakeholder theory, and institutional theory) claim that there are ‘pressures’ that impact the organization. How much ‘pressures’ are recognized, managed or satisfied differs from one perspective of theory to the other. To estimate the data, this study uses three sets of panel data models, i.e., the pooled ordinary least squares model (POLS) or constant coefficients model, fixed effects (FEM or least squares dummy variable/LSDV model) and random-effects models. The final sample is comprising of 173 firms over eight years from 2011 to 2017. The firms listed in PSX are included in the sample. Overall the findings of the study have shown agreement with the proposed results. However, the study has provided more support to the institutional theory and stakeholder theory. Keywords: Corporate Social Responsibility, Stakeholders Theory, Agency Theory, Pakistan

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