IRIS Toolbox Reference Manual

## chowlin

Chow-Lin distribution of low-frequency observations over higher-frequency periods

#### Syntax

    [Y2,B,RHO,U1,U2] = chowlin(Y1,X2)
    [Y2,B,RHO,U1,U2] = chowlin(Y1,X2,range,...)

#### Input arguments

- `Y1` [ tseries ] - Low-frequency input tseries object that will be distributed over higher-frequency observations.

- `X2` [ tseries ] - Tseries object with regressors used to distribute the input data.

- `range` [ numeric ] - Low-frequency date range on which the distribution will be computed.

#### Output arguments

- `Y2` [ tseries ] - Output data distributed with higher frequency.

- `B` [ numeric ] - Vector of regression coefficients.

- `RHO` [ numeric ] - Actually used autocorrelation coefficient in the residuals.

- `U1` [ tseries ] - Low-frequency regression residuals.

- `U2` [ tseries ] - Higher-frequency regression residuals.

#### Options

- `'constant='` [ `true` | `false` ] - Include a constant term in the regression.

- `'log='` [ `true` | `false` ] - Logarithmise the data before distribution, de-logarithmise afterwards.

- `'ngrid='` [ numeric | `200` ] - Number of grid search points for finding autocorrelation coefficient for higher-frequency residuals.

- `'rho='` [ `'estimate'` | `'positive'` | `'negative'` | numeric ] - How to determine the autocorrelation coefficient for higher-frequency residuals.

- `'timeTrend='` [ `true` | `false` ] - Include a time trend in the regression.

#### Description

Chow,G.C., and A.Lin (1971). Best Linear Unbiased Interpolation, Distribution and Extrapolation of Time Series by Related Times Series. Review of Economics and Statistics, 53, pp. 372-75.

See also Appendix 2 in Robertson, J.C., and E.W.Tallman (1999). Vector Autoregressions: Forecasting and Reality. FRB Atlanta Economic Review, 1st Quarter 1999, pp.4-17.

#### Example

IRIS Toolbox. Copyright © 2007—2013 Jaromir Benes.