Limited Dependent Variables in Management Research

2020 ◽  
Author(s):  
Harry Bowen
Keyword(s):  
Linear Regression ◽  
Statistical Characteristics ◽  
Categorical Variable ◽  
Management Research ◽  
Response Variable ◽  
Limited Dependent Variable ◽  
Limited Dependent Variables ◽  
Dependent Variables ◽  
Discrete Values ◽  
Range Of Values

A limited dependent variable (LDV) is an outcome or response variable whose value is either restricted to a small number of (usually discrete) values or limited in its range of values. The first type of LDV is commonly called a categorical variable; its value indicates the group or category to which an observation belongs (e.g., male or female). Such categories often represent different choice outcomes, where interest centers on modeling the probability each outcome is selected. An LDV of the second type arises when observations are drawn about a variable whose distribution is truncated, or when some values of a variable are censored, implying that some values are wholly or partially unobserved. Methods such as linear regression are inadequate for obtaining statistically valid inferences in models that involve an LDV. Instead, different methods are needed that can account for the unique statistical characteristics of a given LDV.

scholarly journals An Analysis of the Effectiveness of Supplemental Instruction: The Problem of Selection Bias and Limited Dependent Variables

2003 ◽  
Vol 5 (2) ◽  
pp. 235-243 ◽  
Author(s):  
Tyler J. Bowles ◽  
Jason Jones
Keyword(s):  
Regression Models ◽  
Supplemental Instruction ◽  
Single Equation ◽  
Simultaneous Equation ◽  
Academic Ability ◽  
Variable Model ◽  
Limited Dependent Variable ◽  
Limited Dependent Variables ◽  
Dependent Variables ◽  
Endogenous Variables

Single equation regression models have been used rather extensively to test the effectiveness of Supplemental Instruction (SI). This approach, however, fails to account for the possibility that SI attendance and the outcome of SI attendance are jointly determined endogenous variables. Moreover, the standard approach fails to account for the fact that these two endogenous variables are categorical. This article presents and applies a simultaneous equation, limited dependent variable model of SI effectiveness. Our analysis suggests that results from applying this type of model may differ markedly from the traditional statistical models applied in SI research. Specifically, our results suggest that students with below average academic ability are more likely to attend SI and that common measures of student ability included in single equation models fail to adequately control for this characteristic. Therefore, single equation OLS models may underestimate SI effectiveness.

scholarly journals Risk Assessment of Large-Scale Infrastructure Projects—Assumptions and Context

2020 ◽  
Vol 11 (1) ◽  
pp. 109
Author(s):  
Jana Korytárová ◽  
Vít Hromádka
Keyword(s):  
Risk Assessment ◽  
Economic Efficiency ◽  
Large Scale ◽  
Cash Flows ◽  
Statistical Characteristics ◽  
Individual Risk ◽  
Dependent Variables ◽  
Research Findings ◽  
Input Variables ◽  
Individual Risk Factors

This article deals with the partial outputs of large-scale infrastructure project risk assessment, specifically in the field of road and motorway construction. The Department of Transport spends a large amount of funds on project preparation and implementation, which however, must be allocated effectively, and with knowledge of the risks that may accompany them. Therefore, documentation for decision-making on project financing also includes their analysis. This article monitors the frequency of occurrence of individual risk factors within the qualitative risk analysis, with the support of the national risk register, and identifies dependent variables that represent part of the economic cash flows for determining project economic efficiency. At the same time, it compares these dependent variables identified by sensitivity analysis with critical variables, followed by testing the interaction of the critical variables’ effect on the project efficiency using the Monte Carlo method. A partial section of the research was focused on the analysis of the probability distribution of input variables, especially “the investment costs” and “time savings of infrastructure users” variables. The research findings conclude that it is necessary to pay attention to the setting of statistical characteristics of variables entering the economic efficiency indicator calculations, as the decision of whether or not to accept projects for funding is based on them.

scholarly journals PENGARUH KOMITE AUDIT, RETURN ON ASSETS (ROA), DAN LEVERAGE TERHADAP PENGHINDARAN PAJAK

2019 ◽  
Vol 3 (01) ◽  
pp. 9-20
Author(s):  
Fabia Tiala ◽  
Ratnawati Ratnawati ◽  
M.Taufiq Noor Rokhman
Keyword(s):  
Data Analysis ◽  
Linear Regression ◽  
Audit Committee ◽  
Stock Exchange ◽  
Tax Avoidance ◽  
Financial Statements ◽  
Manufacturing Companies ◽  
Return On Assets ◽  
Regression Methods ◽  
Dependent Variables

This study aims to test and describe Tax Avoidance which is influenced by the Audit Committee, Return On Assets (ROA), and Leverage. This study uses two variables, namely the independent and dependent variables, and the source of data in this study in the form of financial statements of mining sector manufacturing companies listed on the Indonesia Stock Exchange (BEI) in 2015-2017. Data analysis was performed by classical assumption test and hypothesis testing in this study using multiple linear regression methods. The results of this study indicate that partially the Audit Committee and Leverage variables have a significant effect on tax avoidance, while the Return on Assets (ROA) does not affect tax avoidance.

scholarly journals PENGARUH REVIU RKA-K/L OLEH APIP TERHADAP EFISIENSI ALOKASI ANGGARAN KEMENTERIAN AGAMA

2019 ◽  
Vol 1 (1) ◽  
pp. 12
Author(s):  
Edy Effendi ◽  
Muhammad Imron
Keyword(s):  
Linear Regression ◽  
Simple Linear Regression ◽  
Independent Variables ◽  
Dependent Variables ◽  
Before And After ◽  
The Impact ◽  
The Relationship ◽  
Positive Effect

Research on the role of the APIP review of the Ministry/agency Work Plan and Budget document to determine the impact on the efficiency of ministry/agency spending (case study at the Ministry of Religion). The method used in this study uses simple linear regression with dummy. The use of linear regression is used to examine the relationship between independent variables (certain types of expenditure) and dependent variables (total expenditure). Whereas, dummy is used to find out before and after the APIP review is done. Throughout the author's search, this research has never been done. Based on the results of linear regression obtained, the APIP review significantly had a positive effect on official travel expenditure and honorarium but did not significantly affect building spending and equipment. Abstrak   Penelitian atas peran reviu APIP atas dokumen Rencana Kerja dan Anggaran Kementerian Negara/Lembaga untuk mengetahui dampaknya terhadap efisiensi belanja kementerian/lembaga (studi kasus pada Kementerian Agama). Metode yang digunakan dalam penelitian ini menggunakan regresi linier sederhana dengan dummy. Penggunaan regresi liner digunakan untuk meneliti hubungan antara variable independen (jenis belanja tertentu) dan variable dependen (total belanja). Sedangkan, dummy digunakan untuk mengetahui sebelum dan setelah reviu APIP dilakukan. Sepanjang penelusuran penulis, penelitian ini belum pernah dilakukan. Berdasarkan hasil regresi linier diperoleh, reviu APIP signifikan berpengaruh positif terhadap  belanja perjalanan dinas dan honorarium tetapi tidak signifikan berbengaruh terhadap belanja gedung dan alat.

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