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From |
Danielle H Ferry <[email protected]> |

To |
[email protected] |

Subject |
st: xtabond machinations |

Date |
Wed, 08 Dec 2004 15:26:07 -0500 |

Hi all,

I've got a bunch of questions about <xtabond>. I apologize for the long email, but if you are v. familiar with <xtabond> and have a few extra minutes, I'd really appreciate any input.

Consider a simple model where x(t) is endog:

y(t) - y(t-1) = a[y(t-1) - y(t-2)] + b[x(t-1) - x(t-2)] + u(t) - u(t-1)

(Notice that unlike the example in the manual, I use lagged diff's of the x's.)

I start out with 4 obs per person. So I am left w/ 2 obs for each person once I've taken lagged differences.

1) I thought that <xtabond> would run the following 4 regressions in the first stage:

y2-y1 = a * y1 + b * x1 --> predict y2-y1

x2-x1 = a * y1 + b * x1 --> predict x2-x1

y3 - y2 = a * y1 + b * y2 + c * x1 + d * x2 --> predict y3 - y2

x3 - x2 = a * y1 + b * y2 + c * x1 + d * x2 --> predict x3 - x2

Then I thought it would use those predictions in the second stage to estimate the first eqn above. When carry out these steps manually, however, I don't get the same results as when I just use <xtabond>. The code for using <xtabond> would look like this:

ge x_lag = L.x

xtabond y, pre(x_lag, endog)

Which part of what <xtabond> am I misunderstanding?

2) If x(t) is predetermined instead of endog in my model, there is no need to instrument for x(t-1) - x(t-2). Will Stata know this?

3) It seems reasonable to me that if I have only 1 obs per person, then <xtabond> is equivalent to using <ivreg>. I tested this by dropping my y4 observations. The only equation I have to estimate then is:

y3-y2 = a(y2-y1) + b(x2-x1) + (u3-u2)

I was able to run <ivreg> just fine, but <xtabond> dropped my x variable from the estimation. I think this has to do with the fact that the Sargan DF = -1, but I don't know why this matters.

e(df_m) = 3

e(zcols) = 2

e(sar_df) = -1

As I understand it, e(zcols) is the total # of vars used to instrument for y2-y1 & x2-x1 and e(df_m) is the total # of parameters (y2-y1, x2-x1, & _cons).

If you've read this far and have any input, thanks v. much for taking the time.

Danielle Ferry

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