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Branching Instructions 1
Conditional Statements
• There are two forms of the IF instruction
%if(x,y,z)– if condition x is true, then y, else z– Example:
• SET flag = %if(resids > 0, 1, 0)
• SET dummy = %if(t.GE.1992:1,1,0)
Branching Instructions 2
If-Else• IF condition 1
next statement or block executed if condition is trueExamples1. If x = = 0
display ‘Zero encountered’2. If x = = 0 {
program statements}
end if (needed when IF is not within a compiled section)• ELSE IF condition n• ELSE• RATS performs the first IF or ELSE IF condition that is true. If all are
false, RATS will perform ELSE (if present).
Branching Instructions 3
Relational Operators
• RATS uses the standard relational operators– A == B A.EQ.B
– A <> B A.NE.B
– A > B A.GE.B
– A < B A.LT.B
– A >= B A.GE.B
– A <= B A.LE.B
– A.AND.B
– A.OR.B
Branching Instructions 4
If-Else Examples
Example 1IF COUNT>=5 DISPLAY 'COUNT IS GREATER THAN OR EQUAL TO 5'ELSE DISPLAY 'COUNT IS LESS THAN 5'END IF
Example 2Examples of both types of IF are in PHI_NO.PRG
Example 3: Bootknown.prg
Branching Instructions 5
Notes
Series vs. Constants• There is an important distinction between a series and a constant. A
constant is a single number (i.e., a scalar). A series is a ‘vector’ of numbers. – compute a = 5 – compute a = 5.0– set a = 5– set a = 5.0
• The first crates an integer a, the second creates the floating point number 5.0, the third creates a series with each element equal to the integer 5, the last creates a series with each element equal to the floating point number 5.0.
• You cannot switch a ‘character’ between a series and a constant.• You can use multiple assignments on a COM statement
– e.g., com a = 5, b = 3.2, c = d = f = 4.
• COM can perform all standard numerical operations
Branching Instructions 6
Dates as Integers
• If CAL is used, each date can be expressed as an integer or in RATS date form.
• It is not necessary to use CAL. You can begin a program with:– ALLOCATE 100
RATE ALT DATE1959:01 2.84 11959:02 2.71 21959:03 2.85 31959:04 2.96 41959:05 2.85 51959:06 3.25 61959:07 3.24 71959:08 3.36 81959:09 4.00 91959:10 4.12 101959:11 4.21 111959:12 4.57 12
Branching Instructions 7
DATES as Integers: Example
cal 1947 1 4all 2003:2open data c:\\gdp.xlsdata(format=xls,org=obs) /
There are 226 observations between 1947:1 and 2003:2. The following statements are equivalent to those above:
all 226open data c:\\gdp.xlsdata(format=xls,org=obs) /
To estimate a regression over the first 100 observations use:
LIN rcons 1 100# constant trend t2
Branching Instructions 8
Series as Integers
• Each series has its own sequence number. The number can be determined from the position of the series obtained from TABLE /
• Example from gdp.xls
table• Series Obs Mean Std Error Minimum Maximum• RGDP 214 4350.07009346 2128.96321099 1481.70000000
9311.50000000• RCONS 214 2856.75700935 1461.19505124 963.40000000
6258.20000000• RINV 214 616.25560748 383.72298968 153.90000000
1862.40000000
Here rcons is series 2
Branching Instructions 9
Series as Integers II
• Anywhere RATS expects a series name, you can use the sequence number.– The series number is an integer
– EXAMPLES using gdp.xls
• print / 1 3 [prints rgdp and rinv]
• print / 1 to 3 [prints rgdp, rcons and rinv]
• lin 2
# constant 2{1}
– To check the series number, you can also use:• com snum = rgdp ; dis snum
Branching Instructions 10
Series as Integers III
• Care must be taken if a series is on the right hand-side of a FRML, SET or COM instruction since RATS will interpret the integer as a scalar. On the right hand side use: [series]number– Example: You want to SET y equal to the log
of series 2– NOT: set y = log(2)– USE: set y = log([series]2)
Branching Instructions 11
Rats Programming Language
Loops1. Do i = 1,100,increment
program statementsend do i
Notes: The increment is optional BUT i must always take on integer values.
The increment can be negative Loops can be nested BUT each must have its own end
do. end do can be used instead of end do i
Example:DO REGEND=1994:1,1994:12 LINREG Y 1980:1 REGEND # CONSTANT X1 X2END DO
Branching Instructions 12
Loops
Loops1. Do i = 1,100,increment
program statementsend do i
Notes: The increment is optional BUT i must always take on integer values.
The increment can be negative Loops can be nested
Example:DO LAST = 1994:1,1994:12 LINREG Y 1980:1 LAST # CONSTANT X1 X2END DO
Branching Instructions 13
Loops II
Example 2do ar = 1,3
do ma = 1,3box(constant,ar=ar,ma=ma) yend do ma
end do ar
2. DOFOR index = list of values end dofor
The index can be almost any type of variableExampledofor j = rgdp rcons
lin j ; # constant j{1}end dofor
Branching Instructions 14
Loops III
3. WHILE condition {program statements}
end while
4. UNTIL condition {program statements}
end while
5. Branch label:labelThis is an unconditional
jump
6. LOOPbreak
end loopThis will cycle forever until break
is encountered
Branching Instructions 15
Loops and Date Manipulation
1. DO REGEND=1994:1,1994:12LINREG Y 1980:1 REGEND# CONSTANT X1 X2END DO
Is Equivalent to:
2. DO I =169,180LINREG Y 1980:1 I# CONSTANT X1 X2END DO I
Branching Instructions 16
Loops and Series Manipulation
Example 1:
do i = 1,5lin i# constant i{1} x
end do i
Example 2:Loops.prg: The program illustrates date and series manipulations using real exchange rate data.
Branching Instructions 17
Introduction to Monte Carlo Analysis
• The goal is to recreate a random outcome many times is order to assess the probability distribution of the outcome. – In RATS you can create random numbers using:
• %ran(x)
• %uniform(x1,x2)
• Example:
– SET x = %ran(1)
– You can obtain the fractiles using: STATISTICS(FRACTILES) or FRACT.SRC
• NOTE: The DENSITY Instruction will estimate an entire density function
– EXAMPLE: MONTE.PRG
Branching Instructions 18
Introduction to Bootstrapping
• In bootstrapping, we typically perform a type of Monte Carlo analysis but we use a particular data set to generate the random variables.– Examples:
• bootgdp.prg
Branching Instructions 19
Simulating a Single Equation
• SIMULATE 1 steps start # equation forecasts forstart
Supplementary Informationequation: the equation name or numberforecasts: series for simulated valuesnewstart: starting entry for storing values (default: start)
Example: lin(define=eq1) y ; # constant y{1}SIMULATE 1 100 70:1# eq1 foresSimulates a model with random Normally distributed shocks.
An error in RATS 5.0 See Simulations.prg (USE RATSW)
Branching Instructions 20
Simulating Multiple Equations
• You can create a model using SYSTEM or GROUP. and them use SIMULATE. One way to use SIM is:
SIMULATE(model=model,results=output) * steps start VCM
model = model to simulate
results = vector[series] for result seriesThis provides a VECTOR of SERIES which will be filled with the results. For instance, RESULTS=SIMULS will make SIMULS(i) the series of simulations for the ith equation in the model.