Applications of Quantile Regression of Experimental and Cross Section Data using EViews: Applications on Experimental and Cross Section Data using EViews

Cover
Title Page
Copyright
Contents
Preface
About the Author
Chapter 1 Test for the Equality of Medians by Series/Group of Variables
	1.1 Introduction
	1.2 Test for Equality of Medians of Y1 by Categorical Variables
	1.3 Test for Equality of Medians of Y1 by Categorical Variables
	1.4 Testing the Medians of Y1 Categorized by X1
	1.5 Testing the Medians of Y1 Categorized by RX1 = @Ranks(X1,a)
	1.6 Unexpected Statistical Results
	1.7 Testing the Medians of Y1 by X1 and Categorical Factors
	1.8 Testing the Medians of Y by Numerical Variables
		1.8.1 Findings Based on Data&uscore;Faad.wf1
		1.8.2 Findings Based on Mlogit.wf1
	1.9 Application of the Function @Mediansby(Y,IV)
Chapter 2 One‐ and Two‐way ANOVA Quantile Regressions
	2.1 Introduction
	2.2 One‐way ANOVA Quantile Regression
	2.3 Alternative Two‐way ANOVA Quantile Regressions
		2.3.1 Applications of the Simplest Equation Specification
		2.3.2 Application of the Quantile Process
		2.3.3 Applications of the Models with Intercepts
	2.4 Forecasting
	2.5 Additive Two‐way ANOVA Quantile Regressions
	2.6 Testing the Quantiles of Y1 Categorized by X1
	2.7 Applications of QR on Population Data
		2.7.1 One‐way‐ANOVA‐QRs
		2.7.2 Application of the Forecasting
		2.7.3 Two‐way ANOVA‐QRs
	2.8 Special Notes and Comments on Alternative Options
Chapter 3 N‐Way ANOVA Quantile Regressions
	3.1 Introduction
	3.2 The Models Without an Intercept
	3.3 Models with Intercepts
	3.4 I × J × K Factorial QRs Based on susenas.wf1
		3.4.1 Alternative ESs of CWWH on F1, F2, and F3
			3.4.1.1 Applications of the Simplest ES in (3.5a)
			3.4.1.2 Applications of the ES in (3.5b)
			3.4.1.3 Applications of the ES in (3.5c)
	3.5 Applications of the N‐Way ANOVA‐QRs
		3.5.1 Four‐Way ANOVA‐QRs
Chapter 4 Quantile Regressions Based on (X1,Y1)
	4.1 Introduction
	4.2 The Simplest Quantile Regression
	4.3 Polynomial Quantile Regressions
		4.3.1 Quadratic Quantile Regression
		4.3.2 Third Degree Polynomial Quantile Regression
		4.3.3 Forth Degree Polynomial Quantile Regression
		4.3.4 Fifth Degree Polynomial Quantile Regression
	4.4 Logarithmic Quantile Regressions
		4.4.1 The Simplest Semi‐Logarithmic QR
		4.4.2 The Semi‐Logarithmic Polynomial QR
			4.4.2.1 The Basic Semi‐Logarithmic Third Degree Polynomial QR
			4.4.2.2 The Bounded Semi‐Logarithmic Third Degree Polynomial QR
	4.5 QRs Based on MCYCLE.WF1
		4.5.1 Scatter Graphs of (MILL,ACCEL) with Fitted Curves
		4.5.2 Applications of Piecewise Linear QRs
		4.5.3 Applications of the Quantile Process
		4.5.4 Alterative Piecewise Linear QRs
		4.5.5 Applications of Piecewise Quadratic QRs
		4.5.6 Alternative Piecewise Polynomial QRs
		4.5.7 Applications of Continuous Polynomial QRs
		4.5.8 Special Notes and Comments
	4.6 Quantile Regressions Based on SUSENAS‐2013.wf1
		4.6.1 Application of CWWH on AGE
			4.6.1.1 Quantile Regressions of CWWH on AGE
			4.6.1.2 Application of Logarithmic QRs
		4.6.2 An Application of Life‐Birth on AGE for Ever Married Women
			4.6.2.1 QR(Median) of LBIRTH on AGE as a Numerical Predictor
Chapter 5 Quantile Regressions with Two Numerical Predictors
	5.1 Introduction
	5.2 Alternative QRs Based on Data&uscore;Faad.wf1
		5.2.1 Alternative QRs Based on (X1,X2,Y1)
			5.2.1.1 Additive QR
			5.2.1.2 Semi‐Logarithmic QR of log(Y1) on X1 and X2
			5.2.1.3 Translog QR of log(Y1) on log(X1) and log(X2)
		5.2.2 Two‐Way Interaction QRs
			5.2.2.1 Interaction QR of Y1 on X1 and X2
			5.2.2.2 Semi‐Logarithmic Interaction QR Based on (X1,X2,Y1)
			5.2.2.3 Translogarithmic Interaction QR Based on (X1,X2,Y1)
	5.3 An Analysis Based on Mlogit.wf1
		5.3.1 Alternative QRs of LW
		5.3.2 Alternative QRs of INC
			5.3.2.1 Using Z‐Scores Variables as Predictors
			5.3.2.2 Alternative QRs of INC on Other Sets of Numerical Predictors
			5.3.2.3 Alternative QRs Based on Other Sets of Numerical Variables
	5.4 Polynomial Two‐Way Interaction QRs
	5.5 Double Polynomial QRs
		5.5.1 Additive Double Polynomial QRs
		5.5.2 Interaction Double Polynomial QRs
Chapter 6 Quantile Regressions with Multiple Numerical Predictors
	6.1 Introduction
	6.2 Alternative Path Diagrams Based on (X1,X2,X3,Y1)
		6.2.1 A QR Based on the Path Diagram in Figure a
		6.2.2 A QR Based on the Path Diagram in Figure b
		6.2.3 QR Based on the Path Diagram in Figure c
			6.2.3.1 A Full Two‐Way Interaction QR
			6.2.3.2 A Full Three‐Way Interaction QR
		6.2.4 QR Based on the Path Diagram in Figure d
	6.3 Applications of QRs Based on Data&uscore;Faad.wf1
	6.4 Applications of QRs Based on Data in Mlogit.wf1
	6.5 QRs of PR1 on (DIST1,X1,X2)
	6.6 Advanced Statistical Analysis
		6.6.1 Applications of the Quantiles Process
			6.6.1.1 An Application of the Process Coefficients
			6.6.1.2 An Application of the Quantile Slope Equality Test
			6.6.1.3 An Application of the Symmetric Quantiles Test
		6.6.2 An Application of the Ramsey RESET Test
		6.6.3 Residual Diagnostics
	6.7 Forecasting
		6.7.1 Basic Forecasting
		6.7.2 Advanced Forecasting
	6.8 Developing a Complete Data&uscore;LW.wf1
	6.9 QRs with Four Numerical Predictors
		6.9.1 An Additive QR
		6.9.2 Alternative Two‐Way Interaction QRs
			6.9.2.1 A Two‐Way Interaction QR Based on Figure a
			6.9.2.2 A Two‐Way Interaction QR Based on Figure b
			6.9.2.3 A Two‐Way Interaction QR Based on Figure c
			6.9.2.4 A Two‐Way Interaction QR Based on Figure d
		6.9.3 Alternative Three‐Way Interaction QRs
			6.9.3.1 Alternative Models Based on Figure a
			6.9.3.2 Alternative Models Based on Figure b
			6.9.3.3 Alternative Models Based on Figure c
			6.9.3.4 Alternative Models Based on Figure d
	6.10 QRs with Multiple Numerical Predictors
		6.10.1 Developing an Additive QR
		6.10.2 Developing a Simple Two‐Way Interaction QR
		6.10.3 Developing a Simple Three‐Way Interaction QR
Chapter 7 Quantile Regressions with the Ranks of Numerical Predictors
	7.1 Introduction
	7.2 NPQRs Based on a Single Rank Predictor
		7.2.1 Alternative Piecewise NPQRs of ACCEL on R&uscore;Milli
		7.2.2 Polynomial NPQRs of ACCEL on R&uscore;Milli
		7.2.3 Special Notes and Comments
	7.3 NPQRs on Group of R&uscore;Milli
		7.3.1 An Application of the G&uscore;Milli as a Categorical Variable
		7.3.2 The kth‐Degree Polynomial NPQRs of ACCEL on G&uscore;Milli
	7.4 Multiple NPQRs Based on Data‐Faad.wf1
		7.4.1 An NPQR Based on a Triple Numerical Variable (X1,X2,Y)
		7.4.2 NPQRs with Multi‐Rank Predictors
	7.5 Multiple NPQRs Based on MLogit.wf1
Chapter 8 Heterogeneous Quantile Regressions Based on Experimental Data
	8.1 Introduction
	8.2 HQRs of Y1 on X1 by a Cell‐Factor
		8.2.1 The Simplest HQR
		8.2.2 A Piecewise Quadratic QR
		8.2.3 A Piecewise Polynomial Quantile Regression
	8.3 HLQR of Y1 on (X1,X2) by the Cell‐Factor
		8.3.1 Additive HLQR of Y1 on (X1,X2) by CF
		8.3.2 A Two‐Way Interaction Heterogeneous‐QR of Y1 on (X1,X2) by CF
		8.3.3 An Application of Translog‐Linear QR of Y1 on (X1,X2) by CF
	8.4 The HLQR of Y1 on (X1,X2,X3) by a Cell‐Factor
		8.4.1 An Additive HLQR of Y1 on (X1,X2,X3) by CF
		8.4.2 A Full Two‐Way Interaction HQR of Y1 on (X1,X2,X3) by CF
		8.4.3 A Full Three‐Way Interaction HQR of Y1 on (X1,X2,X3) by CF
Chapter 9 Quantile Regressions Based on CPS88.wf1
	9.1 Introduction
	9.2 Applications of an ANOVA Quantile Regression
		9.2.1 One‐Way ANOVA‐QR
		9.2.2 Two‐Way ANOVA Quantile Regression
			9.2.2.1 The Simplest Equation of Two‐Way ANOVA‐QR
			9.2.2.2 A Special Equation of the Two‐Way ANOVA‐QR
			9.2.2.3 An Additive Two‐Way ANOVA‐QR
		9.2.3 Three‐Way ANOVA‐QRs
	9.3 Quantile Regressions with Numerical Predictors
		9.3.1 QR of LWAGE on GRADE
			9.3.1.1 A Polynomial QR of LWAGE on GRADE
			9.3.1.2 The Simplest Linear QR of Y1 on a Numerical X1
		9.3.2 Quantile Regressions of Y1 on (X1,X2)
			9.3.2.1 Hierarchical and Nonhierarchical Two‐Way Interaction QRs
			9.3.2.2 A Special Polynomial Interaction QR
			9.3.2.3 A Double Polynomial Interaction QR of Y1 on (X1,X2)
		9.3.3 QRs of Y1 on Numerical Variables (X1,X2,X3)
			9.3.3.1 A Full Two‐Way Interaction QR
			9.3.3.2 A Full‐Three‐Way‐Interaction QR
	9.4 Heterogeneous Quantile‐Regressions
		9.4.1 Heterogeneous Quantile Regressions by a Factor
			9.4.1.1 A Heterogeneous Linear QR of LWAGE on POTEXP by IND1
			9.4.1.2 A Heterogeneous Third‐Degree Polynomial QR of LWAGE on GRADE
			9.4.1.3 An Application of QR for a Large Number of Groups
			9.4.1.4 Comparison Between Selected Heterogeneous QR(Median)
Chapter 10 Quantile Regressions of a Latent Variable
	10.1 Introduction
	10.2 Spearman‐rank Correlation
	10.3 Applications of
ANOVA‐QR(τ)
		10.3.1 One‐way ANOVA‐QR of
BLV
		10.3.2 A Two‐Way ANOVA‐QR of
BLV
			10.3.2.1 The Simplest Equation of a Two‐Way ANOVA‐QR of
BLV
			10.3.2.2 A Two‐way ANOVA‐QR of
BLV with an Intercept
			10.3.2.3 A Special Equation of Two‐Way ANOVA‐QR of
BLV
	10.4 Three‐way ANOVA‐QR of
BLV
	10.5 QRs of
BLV on Numerical Predictors
		10.5.1 QRs of
BLV on
MW
			10.5.1.1 The Simplest Linear Regression of
BLV on
MW
			10.5.1.2 Polynomial Regression of
BLV on
MW
		10.5.2 QRs of
BLV on Two Numerical Predictors
			10.5.2.1 An Additive QR of
BLV
			10.5.2.2 A Two‐Way Interaction QR of
BLV on
MW and
AGE
			10.5.2.3 A Two‐way Interaction Polynomial QR of
BLV on
MW and
AGE
		10.5.3 QRs of
BLV on Three Numerical Variables
			10.5.3.1 Additive QR of
BLV on
MW, AGE, and
HB
			10.5.3.2 A Full Two‐Way Interaction QR of
BLV on
MW, GE, and
HB
			10.5.3.3 A Full Three‐Way Interaction QR of
BLV on
AGE, HB, and
MW
	10.6 Complete Latent Variables QRs
		10.6.1 Additive Latent Variable QRs of
BLV
		10.6.2 Advanced Latent Variables QRs
			10.6.2.1 The Two‐Way‐Interaction QR of
PBLV on
(PLV1,PLV2)
			10.6.2.2 Two‐Way‐Interaction QRs of
PBLV on (PLV1,PLV2,PLV3)
			10.6.2.3 A Special Full‐Two‐Way‐Interaction QR of
PBLV
			10.6.2.4 An Application of a Nonlinear QR of
PBLV
			10.6.2.5 An Application of Semi‐Log Polynomial QR of
log(PBLV)
	10.7 An Application of Heterogeneous Quantile‐regressions
		10.7.1 A Heterogeneous QR of
BLV by a Categorical Factor
			10.7.1.1 A Two‐level Heterogeneous QR of
BLV
			10.7.1.2 A Three‐Level Heterogeneous QR of
PBLV
		10.7.2 Heterogeneous QR of
BLV by Two Categorical Factors
	10.8 Piecewise QRs
		10.8.1 The Simplest PW‐QR of
BLV on
MLV
		10.8.2 An Extension of the SPW‐QR of
BLV on
MLV in
		10.8.3 Reduced Models of the Previous PW‐QRs of
BLV
			10.8.3.1 A Reduced Model of the SPW‐QR of
BLV in
			10.8.3.2 A Reduced Model of the PW‐2WI‐QR of
BLV in
Appendix A Mean and Quantile Regressions
	A.1 The Single Parameter Mean and Quantile Regressions
		A.1.1 The Single‐Parameter Mean Regression
		A.1.2 The Single‐Parameter Quantile Regression
	A.2 The Simplest Conditional Mean and Quantile Regressions
		A.2.1 The Simplest Conditional Mean Regression
		A.2.2 The Simplest Conditional Quantile Regressions
	A.3 The Estimation Process of the Quantile Regression
		A.3.1 Applications of the Quantile Process
			A.3.1.1 An Application of Quantile Process/Process Coefficients
			A.3.1.2 An Application of Quantile Process/Slope Equality Test
			A.3.1.3 An Application of the Quantile Process/Symmetric Quantile Test
			A.3.1.4 The Impacts of the Combinations of Options
	A.4 An Application of the Forecast Button
Appendix B Applications of the t‐Test Statistic for Testing Alternative Hypotheses
	B.1 Testing a Two‐Sided Hypothesis
	B.2 Testing a Right‐Sided Hypothesis
	B.3 Testing a Left‐Sided Hypothesis
Appendix C Applications of Factor Analysis
	C.1 Generating the BLV
	C.2 Generating the MLV
References
Index
EULA