gecm.to.adl

Translate the coefficients from the General Error Correction Model (GECM) to the autoregressive distributed lag (ADL) model

utilities

Autoregressive distributed lag (A[R]DL) models (and their reparameterized equivalent, the Generalized Error-Correction Model [GECM]) are the workhorse models in uncovering dynamic inferences. ADL models are simple to estimate; this is what makes them attractive. Once these models are estimated, what is less clear is how to uncover a rich set of dynamic inferences from these models. We provide tools for recovering those inferences. These tools apply to traditional time-series quantities of interest: especially instantaneous effects for any period and cumulative effects for any period (including the long-run effect). They also allow for a variety of shock histories to be applied to the independent variable (beyond just a one-time, one-unit increase) as well as the recovery of inferences in levels for shocks applies to (in)dependent variables in differences (what we call the Generalized Dynamic Response Function). These effects are also available for the general conditional dynamic model advocated by Warner, Vande Kamp, and Jordan (2026 <doi:10.1017/psrm.2026.10087>). We also provide the actual formulae for these effects.

Soren Jordan

tseffects

Dynamic Inferences from Time Series (with Interactions)

Garrett N. Vande Kamp 

Reshi Rajan 

gecm.to.adl function

<dl><dt>x.vrbl</dt>
<dd>a named vector of the x variables (of the lower level of differencing, usually in levels d = 0) and corresponding lag orders in the GECM model</dd>
<dt>y.vrbl</dt>
<dd>a named vector of the (lagged) y variables (of the lower level of differencing, usually in levels d = 0) and corresponding lag orders in the GECM model</dd>
<dt>x.d.vrbl</dt>
<dd>a named vector of the x variables (of the higher level of differencing, usually first differences d = 1) and corresponding lag orders in the GECM model</dd>
<dt>y.d.vrbl</dt>
<dd>a named vector of the y variables (of the higher level of differencing, usually first differences d = 1) and corresponding lag orders in the GECM model</dd></dl>

Arguments

Soren Jordan, Garrett N. Vande Kamp, and Reshi Rajan

Author

Translate the coefficients from the General Error Correction Model (GECM) to the autoregressive distributed lag (ADL) model — gecm.to.adl

<dl>

<dt>x.vrbl</dt>
<dd>a named vector of the x variables (of the lower level of differencing, usually in levels d = 0) and corresponding lag orders in the GECM model</dd>


<dt>y.vrbl</dt>
<dd>a named vector of the (lagged) y variables (of the lower level of differencing, usually in levels d = 0) and corresponding lag orders in the GECM model</dd>


<dt>x.d.vrbl</dt>
<dd>a named vector of the x variables (of the higher level of differencing, usually first differences d = 1) and corresponding lag orders in the GECM model</dd>


<dt>y.d.vrbl</dt>
<dd>a named vector of the y variables (of the higher level of differencing, usually first differences d = 1) and corresponding lag orders in the GECM model</dd>

</dl>

gecm.to.adl: Translate the coefficients from the General Error Correction Model (GECM) to the autoregressive distributed lag (ADL) model

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