%% Assess Trend Stationarity of a Series
% Reproduce the first row of the second half of Table 5 in Kwiatkowski et al., 1992.
% Load the Nelson-Plosser Macroeconomic series data set.

load Data_NelsonPlosser

%
% Linearize the real gross national product series (RGNP).

logGNPR = log(DataTable.GNPR);

%
% Assess the null hypothesis that the series is trend stationary over a range of lags.

lags = (0:8)';
[~,pValue,stats] = kpsstest(logGNPR,'Lags',lags,'Trend',true);
results = [lags pValue stats]

% The tests corresponding to 0 \le lags \le 2 produce p-values that are less than 0.01. For lags < 7, the tests indicate sufficient evidence to suggest that log rGNP is unit root nonstationary (i.e., not trend stationary) at the default 5% level.
% Copyright 2015 The MathWorks, Inc.