SHAZAM Examples
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Examples to accompany the SHAZAM User's Reference Manual
Version 10 |
- A note on using SHAZAM procedures should be reviewed.
- The SHAZAM examples can be run over the internet.
| 3. Data Input and Output | |
| rdata.sha | Reading character data with the
FORMAT command
(p. 36). |
| readchar.sha | Reading character data with the
CHARVARS= option. |
| 4. Descriptive Statistics | |
| anova.sha | A two-way ANOVA table (p. 51). |
| teststat.sha | t-test statistic for differences in population mean and an
F-test statistic for different population variances
(p. 52).
Data file : urate.txt Data file description: urate.html |
| stemleaf.sha | Stem-and-Leaf Display |
| 5. Plots and Graphs | |
| graph.sha | Graph of monthly time series data with
dates on the x-axis. (p. 56).
Data file : urate.txt Data file description: urate.html |
| 6. Generating Variables | |
| log10.sha | Working with logarithms to the base 10 (pp. 65-66). |
| wreplace.sha | Sampling Without Replacement (p. 77). |
| 7. Ordinary Least Squares | |
| homeown.sha | Weighted Least Squares - Analysis of Proportions Data |
| 8. Hypothesis Testing and Confidence Intervals | |
| hyptest.sha | Linear and non-linear hypothesis tests (pp. 104-110). |
| confid.sha | Interval estimation for a population mean (pp. 112-113). |
| confid2.sha | Confidence ellipse for 2 regression coefficients
from 2SLS estimation. (pp. 115-116).
Also see system.sha.
Data file : klein.txt |
| 9. Inequality Restrictions | |
| bayes.sha | Linear regression with inequality restrictions (pp. 119-121). |
| sureq.sha | SURE with inequality restrictions (pp. 121-122). |
| 10. ARIMA Models | |
| pacf.sha | Calculation of the partial autocorrelation function (pp. 127-128). |
| arima.sha | ARIMA estimation - an example from Enders. |
| arseas.sha | Seasonal ARIMA models - examples with the Box and Jenkins airline passenger data set and the Enders Spanish tourism data set. |
| 11. Autocorrelation Models | |
| ar1.sha | Estimation and forecasting for a model with
AR(1) errors. The commands show how to replicate the estimation
results of the AUTO command by using OLS on transformed observations. |
| 13. Cointegration and Unit Root Tests | |
| unitroot.sha | Tests for unit roots using the Perron test
applied to the Nelson-Plosser data set.
Data file : nelplos.txt Data file description: nelplos.html |
| johansen.prc | Johansen trace test procedure for cointegration
(pp. 174-177).
Command file : johan.sha Data file : macro.txt Data file description: macro.html |
| 14. Diagnostic Tests | |
| diagnos.sha | Examples of programming test statistics in SHAZAM
by illustrating some of the computations implemented by the
DIAGNOS command. Calculations for tests for
autocorrelation and tests for heteroskedasticity are shown
(pp. 182-185). |
| recur.sha | More examples of programming test statistics. Calculations for recursive coefficient estimates and the Hansen test of model stability are shown (pp. 185-188). |
| reset.sha | More examples of programming test statistics. Calculations for RESET tests are shown (pp. 190-191). |
| 15. Distributed-Lag Models | |
| dlag.sha | Estimation of distributed lag models including Almon lags (pp. 194-199). |
| gcause.sha | Testing for Granger causality
(pp. 199-200).
Data file : judge18.txt |
| 16. Forecasting | |
| poolfc.sha | Forecasting with time-series cross-section data. |
| 17. Fuzzy Set Models | |
| fuzzy.sha | Measuring the underground economy using the methodology of Giles and Draeseke (pp. 215-216). |
| 18. Generalized Entropy | |
| gme.sha | Example of generalized entropy estimation (pp. 219-222). |
| 19. Generalized Least Squares | |
| glsar1.sha | Example of generalized least squares estimation for the model with AR(1) errors (pp. 226-228). |
| 20. Heteroskedastic Models | |
| hetreg.sha | Multiplicative Heteroskedasticity
Data file : credit.txt |
| 21. Maximum Likelihood Estimation of Non-Normal Models | |
| poisson.sha | Poisson regression. |
| mlebeta.sha | Models with Beta-Distributed Dependent Variables
Data file : soss.txt |
| 22. Nonlinear Regression | |
| nlces.sha | Estimation of a CES production function and testing for autocorrelated errors (p. 257). |
| maxfunc.sha | Maximizing a function of a single variable (p. 257). |
| nlsure.sha | Nonlinear seemingly unrelated regression applied to the estimation of a linear expenditure system (p. 258). |
| sysnl.sha | N2SLS, N3SLS and GMM estimation applied to Klein's
Model I (pp. 260-268).
Also see system.sha.
Data file : klein.txt |
| Examples of the LOGDEN option | |
| mhet.sha | Estimation of the multiplicative heteroskedastic error model. |
| boxhet.sha | Maximum likelihood estimation of Box-Cox models with heteroskedasticity. |
| poisnl.sha | Poisson regression. Note that Poisson regression is
implemented with the MLE command as shown
in the command file poisson.sha.
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| tobithet.sha | Tobit model with heteroskedasticity.
Data file : mroz.txt |
| homeown.sha | Analysis of Proportions Data |
| 23. Nonparametric Methods | |
| nonpar.sha | Nonparametric regression of a nonlinear function (pp. 279-280). |
| semipar.sha | Robinson's semiparametric regression. |
| 24. Pooled Cross-Section Time-Series | |
| pool.sha | Estimation methods available with the
POOL command
(pp. 289-292). |
| poolfc.sha | Forecasting with time-series cross-section data. |
| poolec.sha | Pooling with error components - an example of programming in SHAZAM. |
| 25. Probit and Logit Regression | |
| logit.sha | Logit model estimation - comparisons with the
probit model are also shown (pp. 300-301).
Data file : school.txt |
| probit.sha | Probit model estimation and Heckit procedure
(pp. 302-304).
Data file : mroz.txt |
| logitw.sha | Weighted Logit estimation |
| 26. Robust Estimation | |
| lad.sha | Least Absolute Error estimation.
Calculation of bootstrap standard errors is also shown.
Data file : industry.txt |
| 27. Time-Varying Linear Regression | |
| fls.sha | Flexible least squares simulation experiment from Kalaba and Tesfatsion (pp. 313-314). |
| 28. Tobit Regression | |
| tobit.sha | Tobit regression
(pp. 321-322).
Data file : judge19.txt |
| tobitm.sha | Calculating marginal effects for Tobit models including the
McDonald and Moffitt (1980) decomposition.
Data file : judge19.txt |
| 29. Two-Stage Least Squares and Systems of Equations | |
| system.sha | Estimation of Klein's Model I by 2SLS and 3SLS
(pp. 325-326 and pp. 335-337).
Data file : klein.txt |
| hetcov.sha | Computation of heteroskedasticity-consistent standard errors for
2SLS estimation.
Data file : klein.txt |
| 30. Data Smoothing, Moving Averages and Seasonal Adjustment | |
| smooth.sha | Seasonal adjustment (p. 342). |
| expsmth.sha | Moving averages and exponential smoothing. |
| 31. Financial Time Series | |
| stock.sha | Chart of stock market prices
(pp. 349-350).
Data file : spy.txt |
| portfol.sha | Portfolio selection problem
(pp. 353-355).
Data file : p.txt |
| eurocall.sha | Pricing European call options (pp. 358-359). |
| bsprice.sha | Black-Scholes formula for a call option price, put option price and implied volatility. |
| 32. Linear Programming | |
| lp.sha | Linear Programming (pp. 362-364). |
| 33. Matrix Manipulation | |
| matrix.sha | Matrix operations (p. 366). |
| matols.sha | OLS estimation with the MATRIX command
(p. 370). |
| 34. Price Indexes | |
| prindex.sha | Computing price indexes (p. 376). |
| 35. Principal Components and Factor Analysis | |
| pcomp.sha | Example of multicollinearity diagnostics and principal components regression (pp. 381-382). |
| 36. Probability Distributions | |
| pvalue.sha | Calculating p-values for test statistics (pp. 394-395). |
| distchi.sha | Calculating probabilities for chi-square (p. 395). |
| distf.sha | Calculating probabilities for non-central F (pp. 395-396). |
| 37. Sorting Data | |
| wreplace.sha | Sampling Without Replacement (p. 77). |
| 40. Programming in SHAZAM | |
| splice.sha | Splicing price index series (p. 417). |
| power.sha | Computing the power of a test (pp. 418-420). |
| ridge.sha | Ridge Regression. (pp. 420-422). |
| nlsroc.sha | Nonlinear least squares by the rank one correction method (pp. 426-427). |
| mcarlo.sha | Monte Carlo experiments (pp. 428-430). |
| boot.sha | Bootstrapping regression coefficients (pp. 430-432). |
| olscov.sha | Estimating the variance of the OLS estimator in the presence of heteroskedastic errors or autocorrelated errors (pp. 432-434). |
| hausman.sha | Hausman specification test for errors in variables (pp. 434-435). |
| nonnest.sha | Non-Nested model testing (pp. 435-438). |
| solve.sha | Solving nonlinear sets of equations (pp. 438-439). |
| mnlogit.sha | Multinomial logit estimation (pp. 440-442). |
| More Examples | |
| cor.sha | Computing p-values for correlation coefficients. |
| archprog.sha | ARCH estimation using Engle's algorithm. |
| vif.sha | Computation of Variance Inflation Factors as an indicator of the severity of multicollinearity. |
| probelas.sha | Computing elasticities from probit estimation
when variables have been log-transformed.
Also see logit.sha.
Data file : school.txt |
| bvprob.sha | Bivariate Probit models - Testing for zero error
correlation by computing a Lagrange multiplier test statistic.
Data file : school.txt |
| fiml.sha | Full information maximum likelihood - Klein Model I.
Data file : klein.txt |
| 41. SHAZAM Procedures | |
| sqrta.prc
sqrtm.prc |
Square root of a matrix
(pp. 448-449) using: - an eigenvalue-vector decomposition - the Golub-Van Loan procedure Command file : sqrtm.sha |
| bs.prc
impvol.prc |
Black-Scholes option pricing and implied
volatility (pp. 451-454).
Command file : bsvol.sha Note that Black-Scholes option pricing is implemented with the CALL and PUT commands as shown
in the command file bsprice.sha. |
| liml.prc | Limited information maximum likelihood
(pp. 454-457).
Command file : liml.sha Data file : klein.txt |
| multi.prc | Generating multivariate random numbers
(pp. 457-459).
Command file : multi.sha |
| More Procedures | |
| dwpvalue.prc | Calculation of a p-value for the Durbin-Watson
statistic
Command file : dwpvalue.sha |
| gauss.prc | Nonlinear equation estimation by the Gauss-Newton method
Command file : gauss.sha |
| granger.prc | Testing for Granger causality
Command file : granger.sha Data file : judge18.txt Granger causality tests are also available using the commands shown in gcause.sha. |
| huf.prc | Robinson's heteroskedasticity of unknown form estimator
Command file : huf.sha |
| qr.prc
hh.prc |
Solving OLS with the Householder transformation
Command file : qr.sha |
| randcoef.prc | Random coefficients models - pooled time-series cross-section data.
Command file : rand.sha |
| seasroot.prc | Tests for seasonal unit roots
Command file : seas.sha Data file : gdpcan.txt |
| stest.prc | Stationarity tests proposed by Leybourne and McCabe
Command file : stest.sha Data file : citibase.txt Data file description: citibase.html |
| ols.prc | Replication of the SHAZAM OLS command.
Command file : ols.sha |
A Note on using SHAZAM Procedures
SHAZAM command files that use SHAZAM procedures may need a revision to
the FILE PROC
Run SHAZAM over the Internet
The SHAZAM examples can be run over the internet from:
Data files can be loaded with the READ
command:
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where filename is the name of
the data file and variable_list
is the list of variable names.
SHAZAM procedures can be located by using:
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where proc_name is the name of
the procedure file.
Upper and lower case are not interchangeable for filenames.
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