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From |
Joshua Mitts <joshua.mitts@yale.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Regression discontinuity with interrupted time series |

Date |
Thu, 7 Mar 2013 19:08:52 -0500 |

Austin, This is very useful, thank you again. Very much appreciate it. Josh On Thu, Mar 7, 2013 at 5:09 PM, Austin Nichols <austinnichols@gmail.com> wrote: > Joshua Mitts <joshua.mitts@yale.edu>: > I suggest you design a simulation that matches your data and your > hypothesized effects, then see what seems to work well. Below is a > quick foray along lines that I gather match your setting > approximately, where OLS seems to win on MSE grounds but over-rejects > a true null badly, and the higher MSE of my proposed long differences > seems outweighed by a good pattern of mean estimated coefs and > rejection rates. But YMMV. > > clear all > ssc inst rd, replace > prog rdits, rclass > syntax [, n(int 1000) c(real .5) f(real .5)] > matrix C = (1, .5 \ .5, 1) > drawnorm x u, corr(C) n(`n') clear > drawnorm e z > g int i=_n > expand 20 > * serial correlation in e and x governed by `c' > bys i:replace e=e[_n-1]*`c'+rnormal()*(1-`c') if _n>1 > by i:replace x=x[_n-1]*`c'+1+rnormal()*(1-`c') if _n>1 > replace x=exp(x) > by i:g byte t=_n > g A=(z>0) > * A increases p(T) but T and x linked > g T=(t>6)*(uniform()<(A*(`f'))+normal(ln(x))/2) > * y increases linearly in t, x > g y=t/2+x/10+z/10-z^2/10+T/2+T*(t-6)/4+e > * but we don't observe x, u > g Tt=T*t > g At=A*t > reg y T t Tt, cl(i) > return scalar tols=_b[t] > return scalar setols=_se[t] > return scalar tTols=_b[Tt] > return scalar setTols=_se[Tt] > ivreg y t (T Tt=A At), cl(i) > return scalar tiv=_b[t] > return scalar setiv=_se[t] > return scalar tTiv=_b[Tt] > return scalar setTiv=_se[Tt] > g k=max(0,1.5-abs(z)) > ivreg y t (T Tt=A At) [aw=k], cl(i) > return scalar trd=_b[t] > return scalar setrd=_se[t] > return scalar tTrd=_b[Tt] > return scalar setTrd=_se[Tt] > tsset i t > forv i=1/12 { > g dy`i'=y-L`i'.y if t==6+`i' > rd dy`i' T z, mbw(100) > return scalar t`i'=_b[lwald] > return scalar set`i'=_se[lwald] > } > eret clear > end > > simul, r(1000):rdits > tw kdensity tols||kdensity tiv||kdensity trd, name(main) > tw kdensity tTols||kdensity tTiv||kdensity tTrd, name(interact) > foreach v in ols iv rd { > g mse_t`v'=(t`v'-.5)^2 > g mse_tT`v'=(tT`v'-.25)^2 > } > forv v=1/12 { > g mse_t`v'=(t`v'-.5-.25*`v')^2 > } > foreach v in ols iv rd { > g rej_t`v'=abs((t`v'-.5)/set`v')>abs(invnormal(.05)) > g rej_tT`v'=abs((tT`v'-.25)/setT`v')>abs(invnormal(.05)) > } > forv v=1/12 { > g rej_t`v'=abs((t`v'-.5-.25*`v')/set`v')>abs(invnormal(.05)) > } > su rej*, sep(6) > su mse*, sep(6) > g i=_n > reshape long t, i(i) j(time) > egen mt=mean(t), by(time) > sc t mt time, msize(tiny)||function .5+x/4, ra(0 10) > > > On Thu, Mar 7, 2013 at 4:00 PM, Joshua Mitts <joshua.mitts@yale.edu> wrote: >> Hi all, >> >> Thank you all so much for the responses. Austin, your comments were >> very helpful and I greatly appreciate it. > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/statalist-faq/ > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**re: Re: st: Regression discontinuity with interrupted time series***From:*"Ariel Linden. DrPH" <ariel.linden@gmail.com>

**Re: st: Regression discontinuity with interrupted time series***From:*Joshua Mitts <joshua.mitts@yale.edu>

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