However, because the HPL was uniformly enforced nationwide to a certain point (May 2003), this dummy variable can be expressed in a linear combination of survey year dummy variables.
The vital query that remains is whether is it appropriate to use a pooled sample of adopters and non-adopters (where a dummy variable can be used in the regression model to evaluate the impact of adoption of modern technology on productivity)?
In Table 4, we exclude occupation dummies from the estimating equation, as these variables can be regarded as potentially endogenous.
Such data can be analyzed with models analyzing dummy variables; all time-varying and nontime-varying variables can be easily placed in that model (Singer and Willett [2003]).
For example, when using method absence as reference category, one dummy variable can represent method application consistent with conditions (correct application) and one dummy variable can represent method application that is not or only partially consistent with theoretical conditions (partial application).
Again dummies and lags of the dependent variable can be introduced.
Alternatively, "fixed unit effects," in which each observed unit is identified with a dummy variable, can also be used.
Second, while a dummy variable approach3 can be applied to a single cross-sectional survey data, the fundamental difference between children between the age of 0 4 years (treatment group) and 5 10 years (control group) could result in biased estimate of the treatment effect.
The explanatory variables are defined, and summary statistics are provided in Table 1. a S.D. values for dummy variables are omitted since they can be calculated from √ m-m), where m is the fraction in the sample.
As can be seen in model (II.4), in which we introduced dummy variables for series ranks, no major changes can be observed with regard to the explanatory variable CONCORDANCE.
