Print basic information about a BIMETS model
This function prints basic information about a BIMETS model, e.g. behaviorals and identities count, coefficients count, the presence of estimated coefficients or simulated time series.
## S3 method for class 'BIMETS_MODEL' summary(object,...) ## S3 method for class 'BIMETS_MODEL' print(x,...)
object |
A BIMET model. |
x |
A BIMET model. |
... |
Arguments list for the generic method. |
This function prints basic information about a BIMETS model, i.e.:
- the name of the model;
- the behaviorals count;
- the identities count;
- the coefficients count;
- the check for the compliance of the model data;
- the check for the coefficients definition in all the behaviorals;
- the check for the definition of a simulated time series for each related endogenous variable of the model;
#define model myModelDefinition= "MODEL COMMENT> Modified Klein Model 1 of the U.S. Economy with PDL, COMMENT> autocorrelation on errors, restrictions and conditional evaluations COMMENT> Consumption BEHAVIORAL> cn TSRANGE 1925 1 1941 1 EQ> cn = a1 + a2*p + a3*TSLAG(p,1) + a4*(w1+w2) COEFF> a1 a2 a3 a4 ERROR> AUTO(2) COMMENT> Investment BEHAVIORAL> i TSRANGE 1923 1 1941 1 EQ> i = b1 + b2*p + b3*TSLAG(p,1) + b4*TSLAG(k,1) COEFF> b1 b2 b3 b4 RESTRICT> b2 + b3 = 1 COMMENT> Demand for Labor BEHAVIORAL> w1 TSRANGE 1925 1 1941 1 EQ> w1 = c1 + c2*(y+t-w2) + c3*TSLAG(y+t-w2,1) + c4*time COEFF> c1 c2 c3 c4 PDL> c3 1 3 COMMENT> Gross National Product IDENTITY> y EQ> y = cn + i + g - t COMMENT> Profits IDENTITY> p EQ> p = y - (w1+w2) COMMENT> Capital Stock with switches IDENTITY> k EQ> k = TSLAG(k,1) + i IF> i > 0 IDENTITY> k EQ> k = TSLAG(k,1) IF> i <= 0 END" #define model data myModelData=list( cn =TIMESERIES(39.8,41.9,45,49.2,50.6,52.6,55.1,56.2,57.3,57.8,55,50.9, 45.6,46.5,48.7,51.3,57.7,58.7,57.5,61.6,65,69.7, START=c(1920,1),FREQ=1), g =TIMESERIES(4.6,6.6,6.1,5.7,6.6,6.5,6.6,7.6,7.9,8.1,9.4,10.7,10.2,9.3,10, 10.5,10.3,11,13,14.4,15.4,22.3, START=c(1920,1),FREQ=1), i =TIMESERIES(2.7,-.2,1.9,5.2,3,5.1,5.6,4.2,3,5.1,1,-3.4,-6.2,-5.1,-3,-1.3, 2.1,2,-1.9,1.3,3.3,4.9, START=c(1920,1),FREQ=1), k =TIMESERIES(182.8,182.6,184.5,189.7,192.7,197.8,203.4,207.6,210.6,215.7, 216.7,213.3,207.1,202,199,197.7,199.8,201.8,199.9, 201.2,204.5,209.4, START=c(1920,1),FREQ=1), p =TIMESERIES(12.7,12.4,16.9,18.4,19.4,20.1,19.6,19.8,21.1,21.7,15.6,11.4, 7,11.2,12.3,14,17.6,17.3,15.3,19,21.1,23.5, START=c(1920,1),FREQ=1), w1 =TIMESERIES(28.8,25.5,29.3,34.1,33.9,35.4,37.4,37.9,39.2,41.3,37.9,34.5, 29,28.5,30.6,33.2,36.8,41,38.2,41.6,45,53.3, START=c(1920,1),FREQ=1), y =TIMESERIES(43.7,40.6,49.1,55.4,56.4,58.7,60.3,61.3,64,67,57.7,50.7,41.3, 45.3,48.9,53.3,61.8,65,61.2,68.4,74.1,85.3, START=c(1920,1),FREQ=1), t =TIMESERIES(3.4,7.7,3.9,4.7,3.8,5.5,7,6.7,4.2,4,7.7,7.5,8.3,5.4,6.8,7.2, 8.3,6.7,7.4,8.9,9.6,11.6, START=c(1920,1),FREQ=1), time =TIMESERIES(NA,-10,-9,-8,-7,-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6,7,8,9,10, START=c(1920,1),FREQ=1), w2 =TIMESERIES(2.2,2.7,2.9,2.9,3.1,3.2,3.3,3.6,3.7,4,4.2,4.8,5.3,5.6,6,6.1, 7.4,6.7,7.7,7.8,8,8.5, START=c(1920,1),FREQ=1) ) #load model myModel=LOAD_MODEL(modelText=myModelDefinition) #model summary summary(myModel) #BIMETS MODEL #----------------------------------- #name: myModelDefinition #behaviorals: 3 #identities: 3 #coefficients: 12 #model data: not OK #.CHECK_MODEL_DATA(): model has no data. Please use LOAD_MODEL_DATA(). #fully estimated: FALSE #simulated: FALSE #load data into the model myModel=LOAD_MODEL_DATA(myModel,myModelData,showWarnings = TRUE) #estimate the model myModel=ESTIMATE(myModel) #model summary print(myModel) #BIMETS MODEL #----------------------------------- #name: myModelDefinition #behaviorals: 3 #identities: 3 #coefficients: 12 #model data: OK #fully estimated: TRUE #simulated: FALSE
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