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{* *! version 1.1.1}{...}
{title:Title}
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{bf:npeivreg} {hline 2} Executes estimation of nonparametric errors-in-variables (EIV) regression and construction of its uniform confidence band.
{marker syntax}{...}
{title:Syntax}
{p 4 17 2}
{cmd:npeivreg}
{it:y}
{it:x1}
{it:x2}
{ifin}
[{cmd:,} {bf:numx}({it:real}) {bf:domain}({it:real}) {bf:cover}({it:real}) {bf:tp}({it:real})]
{marker description}{...}
{title:Description}
{phang}
{cmd:npeivreg} executes estimation of nonparametric errors-in-variables (EIV) regression and construction of its uniform confidence band based on
{browse "https://www.sciencedirect.com/science/article/abs/pii/S0304407619301605":Kato and Sasaki (2019)}.
In addition to the dependent variable {bf:y}, the command requires as input two measurements, {bf:x1} and {bf:x2}, of the unobserved independent variable {bf:x} with classical measurement errors,
{bf:e1} = {bf:x1} - {bf:x}
and
{bf:e2} = {bf:x2} - {bf:x},
respectively. The output consists of a deconvolution estimate of the nonparametric EIV regression {it:g}({bf:x}) of {bf:y} on {bf:x}, and its uniform confidence band over a domain of {bf:x}.
{marker options}{...}
{title:Options}
{phang}
{phang}
{bf:numx({it:real})} sets the number of grid points of {bf:x} for estimation of the nonparametric EIV regression {it:g}({bf:x}) and its uniform confidence band. The default value is {bf: numx(20)}.
{phang}
{bf:domain({it:real})} sets the domain of estimation of the nonparametric EIV regression {it:g}({bf:x}) and its uniform confidence band. The default value {bf:domain(2)} defines the domain as +/- 2 standard deviations of {bf:x}.
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{bf:cover({it:real})} sets the nominal uniform coverage probability for the uniform confidence band of the nonparametric EIV regression {it:g}({bf:x}). The default value {bf: cover(0.95)} constructs a 95% uniform confidence band.
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{bf:tp({it:real})} sets the scale-normalized tuning parameter. The default value is {bf: tp(0.2)}.
{marker examples}{...}
{title:Examples}
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({bf:y} dependent variable, {bf:x1} 1st measurement of unobserved independent variable {bf:x}, {bf:x2} 2nd measurement of unobserved independent variable {bf:x}){p_end}
{phang}Construction of a 95% uniform confidence band:
{phang}{cmd:. npeivreg y x1 x2}{p_end}
{phang}Construction of a 90% uniform confidence band:
{phang}{cmd:. npeivreg y x1 x2, cover(0.90)}{p_end}
{phang}Constructing a uniform confidence band on a grid points of 100 points in the domain corresponding to +/- 3 standard deviations of {bf:x}:
{phang}{cmd:. npeivreg y x1 x2, numx(100) domain(3)}{p_end}
{phang}
({bf:huq050} number of doctor visits, {bf:bmi_exam} clinically measured BMI, {bf:bmi_self} self reported BMI){p_end}
{phang}Nonparametric EIV regression of the number of doctor visits on BMI, accounting for measurement errors in clinically measured BMI and/or self reported BMI:
{phang}{cmd:. use "doctor_visit_male50.dta"}{p_end}
{phang}{cmd:. npeivreg huq050 bmi_exam bmi_self, domain(1.5)}{p_end}
{marker stored}{...}
{title:Stored results}
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{bf:npeivreg} stores the following in {bf:e()}:
{p_end}
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Scalars
{p_end}
{phang2}
{bf:r(N)} {space 10}observations
{p_end}
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Macros
{p_end}
{phang2}
{bf:r(cmd)} {space 8}{bf:npeivreg}
{p_end}
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Matrices
{p_end}
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{bf:r(x)} {space 10}vector of x
{p_end}
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{bf:r(g)} {space 10}vector of g(x)
{p_end}
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{bf:r(lower)} {space 6}confidence band (lower boundary)
{p_end}
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{bf:r(upper)} {space 6}confidence band (upper boundary)
{p_end}
{title:Reference}
{p 4 8}Kato, K. and Y. Sasaki. 2019. Uniform Confidence Bands for Nonparametric Errors-in-Variables Regression. {it:Journal of Econometrics}, 213 (2), pp. 516-555.
{browse "https://www.sciencedirect.com/science/article/abs/pii/S0304407619301605":Link to Paper}.
{p_end}
{title:Authors}
{p 4 8}Kengo Kato, Cornell University, Ithaca, NY.{p_end}
{p 4 8}Yuya Sasaki, Vanderbilt University, Nashville, TN.{p_end}