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NLS in Mincer's model with gender

R Software Module: esteq.wasp (opens new window with default values)

Title produced by software: Estimate Equation

Date of computation: Sat, 15 Mar 2008 22:48:24 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Mar/16/t12056451663ps8e55lq3fvn1e.htm/, Retrieved Sun, 16 Mar 2008 06:26:06 +0100

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Text written by user:

Output produced by software:

This free online calculator computes equations with the following options: constant, linear deterministic trend, first differences, hyperbolic, exponential, geometric, quadratic, cubic, quartic, seasonal dummies, predetermination (lagged endogenous variables), Ordinary Least Squares, Bootstrap, Jackknife.

Econometric Regression Equation

Multiple Linear Regression - Estimated Regression Equation

ln(incwage[t]) = +0.10229152838667 school[t] +0.086791778577986 workexp[t] -0.001083642311728 work2[t] +0.75362724182658 gender[t] +6.9074313103488 + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.E.	T-STAT H0: parameter = 0	2-tail p-value	1-tail p-value
school[t]	0.102292	0.028522	3.586394	0.000466	0.000233
workexp[t]	0.086792	0.016346	5.309586	0	0
work2[t]	-0.001084	0.000331	-3.271698	0.001355	0.000677
gender[t]	0.753627	0.155944	4.832674	4.0E-6	2.0E-6
Constant	6.907431	0.428337	16.126172	0	0

Variable	Elasticity	S.E.^*	T-STAT H0: \|elast\| = 1	2-tail p-value	1-tail p-value
%school[t]	0.140111	0.039067	-22.010491	0	0
%workexp[t]	0.18619	0.035067	-23.207481	0	0
%work2[t]	-0.068676	0.020991	-44.368241	0	0
%gender[t]	0.044294	0.009165	-104.272806	0	0
%Constant	0.698082	0.043289	-6.974525	0	0
Variable	Stand. Coeff.	S.E.^*	T-STAT H0: coeff = 0	2-tail p-value	1-tail p-value
S-school[t]	0.243343	0.067852	3.586394	0.000466	0.000233
S-workexp[t]	1.026499	0.193329	5.309586	0	0
S-work2[t]	-0.632408	0.193296	-3.271698	0.001355	0.000677
S-gender[t]	0.33096	0.068484	4.832674	4.0E-6	2.0E-6
S-Constant	0	0	0	1	0.5
^*Note	computed against deterministic endogenous series
Variable	Partial Correlation
school[t]	0.293945
workexp[t]	0.414367
work2[t]	-0.270117
gender[t]	0.382829
Constant	0.810316
Critical Values (alpha = 5%)
1-tail CV at 5%	1.65
2-tail CV at 5%	1.96

Multiple Linear Regression - Regression Statistics
Multiple R	0.629172
R-squared	0.395857
Adjusted R-squared	0.378088
F-TEST	22.278071
Observations	141
Degrees of Freedom	136
Multiple Linear Regression - Residual Statistics
Standard Error	0.889005
Sum Squared Errors	107.484912
Log Likelihood	-180.93597
Durbin-Watson	2.126934
Von Neumann Ratio	2.142127
# e[t] > 0	76
# e[t] < 0	65
# Runs	79
Stand. Normal Runs Statistic	1.34856

Multiple Linear Regression - Ad Hoc Selection Test Statistics
Akaike (1969) Final Prediction Error	0.818356
Akaike (1973) Log Information Criterion	-0.200487
Akaike (1974) Information Criterion	0.818332
Schwarz (1978) Log Criterion	-0.095921
Schwarz (1978) Criterion	0.908535
Craven-Wahba (1979) Generalized Cross Validation	0.819386
Hannan-Quinn (1979) Criterion	0.853854
Rice (1984) Criterion	0.820496
Shibata (1981) Criterion	0.816368

Multiple Linear Regression - Analysis of Variance
ANOVA	DF	Sum of Squares	Mean Square
Regression	4	70.428133	17.607033
Residual	136	107.484912	0.79033
Total	140	177.913045	1.27080746112
F-TEST	22.278071
p-value	0

Ramsey RESET test for Misspecification

Multiple Linear Regression - Help Regression
Variable	Parameter	S.E.	T-STAT H0: parameter = 0	2-tail p-value	1-tail p-value
school[t]	0.108423	0.051799	2.093138	0.038236	0.019118
workexp[t]	0.079536	0.035196	2.25979	0.02546	0.01273
work2[t]	-0.000953	0.000507	-1.877742	0.062606	0.031303
gender [t]	0.742832	0.3497	2.124199	0.035504	0.017752
@F[t]^2	0	0	0.350704	0.726365	0.363183
@F[t]^3	-0	0	-0.385391	0.700563	0.350282
@F[t]^4	0	0	0.359421	0.71985	0.359925
Constant	6.811869	0.881303	7.72932	0	0

Multiple Linear Regression - Help Regression Statistics
Multiple R	0.632458
R-squared	0.400003
F-TEST	12.66684
p-value	0
Standard Error	0.895886
Observations	141
Degrees of Freedom	133

Ramsey RESET Test for Misspecification - Reduction F-test
SSR Ramsey Model	106.747244
SSR Reduced Model	107.484912
# Reduced Parameters	3
Degrees of Freedom	133
Reduction F-test	0.3133
p-value	0.815761

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Parameters (R input):

R code (references can be found in the software module):

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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