Efficient minimum distance estimator stata software

For a proof of the inverse of the covariance matrices being optimal weights, see 53, p. We say that the estimator is a finitesample efficient estimator in the class of unbiased. Dear statalist, does anyone have a code to estimate a minimum distance estimator using mata optimize or lm. It attempts to estimate the parameters such that the squared distance between the cdf and edf estimates is minimized. An efficient minimum distance estimator for dsge models.

Best, carlos dear statalist, does anyone have a code to estimate a minimum distance estimator using mata optimize or lm. Efficient minimum distance estimation with multiple rates. How to write an efficient code in stata in terms of time. In fact, when i estimate te for my cost function using command predict ce, te after estimating with the command xtfrontier lcost ly1 ly2 lw1 lw2, tvd cost, i obtain cost efficiency scores. Thus estimators with small variances are more concentrated, they estimate the parameters more precisely. Minimum distance estimation mde is a statistical method for fitting a mathematical model to data, usually the empirical distribution. However, under mild conditions, a minimal sufficient statistic does always exist. Thus, the answer to the posed question is that the estimator defined in 3 is most efficient estimator among all the estimators that are linear combinations of the regression. I posted on the stata forum but havent got a response yet and this really urges me. The approach, which is structural in nature, uses a set of reducedform parameters to recover the structural parameters of interest using an optimal minimum distance estimator. Does anyone know how to implement a minimum distance estimator in stata.

Users of any of the software, ideas, data, or other materials published in the. This estimator belongs to the class of minimum distance estimators. Stochastic frontier analysis vs data envelopment analysis. This term effectively captures the rate of convergence of the difference between the feasible and. Introduction gmm for ols gmm for iv poisson extras references optimize is exciting stu. In this setup, there are several a lternative interpretations of z. I have the parameters and the varcov matrix from an unrestricted model and would like to estimate the following function.

Some improvement in the storage efficiency of the j mean deviated firm dummies can be. An efficient estimator is also the minimum variance unbiased estimator mvue. Cross validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization. The stata command felsdvreg to fit a linear model with two high. Murod, yes you can test common factor restrictions with testnl. Implementing minimum distance estimation cross validated. Minimum distance estimation of search costs using price. Simulated minimum distance estimation of a model of.

This tool uses meanvariance optimization to calculate and plot the efficient frontier for the specified asset classes, mutual funds, etfs or stocks for the specified time period. I find it gives results that are almost indistinguishable from the. Estimate efficient portfolios and frontiers matlab. How can i calculate technical efficiency of each household in the stata. Monte carlo simulation evidences based on a mediumscale dsge model reveal very encouraging results for the proposed estimator when it is compared against modern bayesian maximum likelihood and less modern maximum likelihood and non efficient ir matching dsge estimators. Minimum distance estimation of covariance structures. Watson research center, usa 2department of statistics, university of oxford, uk july 11, 20 abstract we propose a minimum distance. Given that the naive estimator is unbiased, how can we verify that it is less efficient than the ols estimator. I have a set of estimators b and a mapping of these estimators into another set of parameters such that ahb. Covariance structure analysis of panel data has the aim of decomposing the total variation of individual timeseries processes into a persistent component representing variation between individual processes and volatility i. Estimating semiparametric output distance functions with. But you need to use minimum distance estimation to recover the structural coefficients. In this note we analyze efficiency improvements over the gaussian maximum likelihood ml estimator for frequency domain minimum distance md estimation for causal and invertible autoregressive moving average arma models. Minimum hellingertype distance estimation for censored data ying, zhiliang, the annals of statistics, 1992.

Stata module providing robust regression estimators. Pdf stochastic frontier analysis and efficiency estimation. The naive estimator is an estimate of the slope obtained by joining the first and last observations and dividing the increase in the height by the horizontal distance between them. Simulated minimum distance estimation of a model of optimal commodity price speculation with endogenously sampled prices george hall, yale university john rust, university of maryland july 2003.

Determine the range of returns from minimum to maximum to refine a search for a portfolio with a specific target return. The randomeffects estimator, it turns out, is a matrixweighted average of those two results. Practical considerations including a software tutorial in stata and spss article in research synthesis methods 5. Mata optimization or stata gmm can be used to obtain minimum distance estimates. In this note we analyze efficiency improvements over the gaussian maximum likelihood ml estimator for frequency domain minimum distance md estimation for causal and invertible autoregressive. I have implemented this in another software, and it yields different results to the gmm method that is, after fixing the weight matrix to identity to make them comparable. Citeseerx document details isaac councill, lee giles, pradeep teregowda. How can i calculate technical efficiency of each household. Estimating parameters by maximum likelihood and method of moments using mlexp and gmm. Some improvement in the storage efficiency of the j meandeviated firm dummies.

Stata module to calculate distance based variables and export distance matrix to text file, statistical software components s457110, boston college department of economics, revised 07 feb. A case in which there is no minimal sufficient statistic was shown by bahadur, 1954. Minimum distance estimation for robust highdimensional. Thus, the answer to the posed question is that the estimator defined in 3 is most efficient estimator among all the estimators that are linear combinations of the regression quantiles. Practical estimation methods for linked employeremployee data iab. Under assumption 1, assumption 2, assumption 3, assumption 4, assumption 5, assumption 6 or 6.

Minimum distance estimation for robust highdimensional regression aur elie c. Estimating distance functions in empirical applications is not straightforward. Statistical properties of minimum distance estimates the minimum distance estimate is an implicit function as given in equation 2. I tried using gmm in stata, but it gave me an error message. Efficiency improvements for minimum distance estimation of. I the new as of stata 10 optimize function in mata is exciting. Some improvement in the storage efficiency of the j meandeviated firm dummies can be. A good estimator should not only be unbiased, but also remain unaffected as much as possible by sampling fluctuation efficiency, that is, the extent to which the estimator takes on different values with different samples. The only work i have seen so far about metafrontier analysis has been in shazam software. Under the assumption that b1 really does have the same effect in the crosssection as in the timeseriesand that b2, b3. In the sense of efficient code, its important to distinguish between computational efficiency use the least memory to accomplish a task or just writing code briefly.

Obtaining efficient portfolios for target returns to obtain efficient portfolios. Does anyone know how to estimate a metafrontier production function in stata. Robust variance estimation with dependent effect sizes. Unbiased estimation of standard deviation wikipedia. Among them are the high breakdownpoint and high efficiency mm estimator, the huber and bisquare m estimator, and the s estimator. Covariance structure analysis of panel data has the aim of decomposing the total variation of individual timeseries processes into a persistent. Having the expressions above involving the variance of the population, and of an estimate of the mean of that population, it would seem logical to simply.

In fact, a number of competing specifications have been proposed in the literature kumbhakar and lovell, 2000. Estimating the standard deviation of the population. There is also a cols option for the stochastic fron tier case in which the ols estimator of. Is there an algorithm in stata to apply this method. This paper extends the asymptotic theory of gmm inference to allow sample counterparts of the estimating equations to. However, as we will learn later on, it might not be possible to. Estimating the endpoint of a probability distribution using minimum distance methods hall, peter and wang, julian z.