NDK_JOHANSENTEST

Returns the Johansen (cointegration) test statistics for two or more time series.

Returns

status code of the operation

Return values

NDK_SUCCESS	Operation successful
NDK_FAILED	Operation unsuccessful. See Macros for full list.

Parameters

[in]	XX	is the multivariate time series matrix data (two dimensional).
[in]	N	is the number of observations in XX.
[in]	M	is the number of variables in XX.
[in]	K	is the number of lagged difference terms used when computing the estimator.
[in]	nPolyOrder	is the order of the polynomial: (-1=no constant, 0=contant-only (default), 1=constant and trend).
[in]	tracetest	is a flag to select test: TRUE=trace, FALSE=maximal eignvalue test.
[in]	R	is the assumed number of cointegrating relationships between the variables (if missing, r=1).
[in]	alpha	is the statistical significance level. If missing, a default of 5% is assumed.
[out]	retStat	is the calculated test statistics score.
[out]	retCV	is the calculated test critical value.

Remarks

1. Each column in the input matrix corresponds to a separate time series variable.

2. The input matrix can have no more than twelve (12) columns (or variables).

3. Each row in the input matrix corresponds to an observation.

4. The number of cointegrating relationships should be no greater than the number of input variables.

5. The time series data are homogeneous or equally spaced.

6. The time series may include missing values (e.g. NaN) at either end.

7. There are two types of Johansen tests - with trace or with eigenvalue - and the inferences might be a bit different for each.

• The null hypothesis for the trace test is the number of cointegration vectors \(r = 0\)
• The null hypothesis for the eigenvalue test is \(r = m\)

Requirements

Header	SFSDK.H
Library	SFSDK.LIB
DLL	SFSDK.DLL

Examples

const double NAN = std::numeric_limits<double>::quiet_NaN();


// We have 173 observations for 8 different factors
double US_MINING_EMPLOYMENT[173][8];

WORD wMaxOrder= 9;        // nlag = 9;
short nPolyOrder = 0;     // Only constant
BOOL  traceTest = TRUE;   // if traceTest = FALSE, then eignvalue based test 
WORD nNoRelations = 0;    // nNoRelations can be between 1 and 7
double alpha=0.05f;
double retStat=NAN;
double retCV=NAN;


// (1) Trace test
nRet = NDK_JOHANSENTEST(
  US_MINING_EMPLOYMENT,     // is the multivariate time series matrix data (two dimensional)
  173,                      // is the number of observations (rows) US_MINING_EMPLOYMENT.
  8 ,                       // is the number of variables (columns) in US_MINING_EMPLOYMENT.
  wMaxOrder,                // is the number of lagged difference terms used when computing the estimator
  nPolyOrder,               // is the order of the polynomial: 
                            // (-1=no constant, 0=contant-only (default), 1=constant and trend)
  traceTest,                // is a flag to select test: TRUE=trace, FALSE=maximal eignvalue test.
  nNoRelations,             // is the assumed number of cointegrating relationships between the variables.
  alpha,                    // is the statistical significance level (e.g. 5%). 
  &retStat,                 // is the calculated test statistics score.
  &retCV                    // is the calculated test critical value.
  );

// (8) Eignvalue test
nNoRelations = 0; 
traceTest = FALSE;
retStat=NAN;
retCV=NAN;
  
nRet = NDK_JOHANSENTEST(
  US_MINING_EMPLOYMENT,     // is the multivariate time series matrix data (two dimensional)
  173,                      // is the number of observations (rows) US_MINING_EMPLOYMENT.
  8 ,                       // is the number of variables (columns) in US_MINING_EMPLOYMENT.
  wMaxOrder,                // is the number of lagged difference terms used when computing the estimator
  nPolyOrder,               // is the order of the polynomial: 
                            // (-1=no constant, 0=contant-only (default), 1=constant and trend)
  traceTest,                // is a flag to select test: TRUE=trace, FALSE=maximal eignvalue test.
  nNoRelations,             // is the assumed number of cointegrating relationships between the variables.
  alpha,                    // is the statistical significance level (e.g. 5%). 
  &retStat,                 // is the calculated test statistics score.
  &retCV                    // is the calculated test critical value.
  );