A generalized maximum entropy estimator is developed for the linear simultaneous equations model. Monte Carlo sampling experiments are used to evaluate the estimator’s performance in small and medium sized samples, suggesting contexts in which the current generalized maximum entropy estimator is superior in mean square error to two and three stage least squares. Analytical results are provided ...

This study uses Monte Carlo simulation to compare three relatively popular techniques, with findings that run counter to extant suggestions in MIS literature. We compare multiple regression, Partial Least Squares and LISREL under varying sample sizes (N = 40, 90, 150, and 200) and varying effect sizes (large, medium, small and no effect). The focus of the analysis was on determining how frequen...

Solar power for clean energy is an important asset that will drive the future of sustainable generation. As interest in increases with Korea’s renewable expansion plan, a strategy photovoltaic investment (PV) from investor’s point view. Previous research primarily focused on assessing and analyzing impact volatility but paid little attention to modeling decision-making project obtain optimal ti...

When no discharge record is available for a site, a regional regression relationship can be used to estimate low-flow quantiles. Problems arise in the derivation of such models when some at-site quantile estimates are reported as zero. One concern is that quantile estimates reported as zero may be in the range from zero to the measurement threshold. A second concern is that a logarithmic transf...

Motivated by recent critique toward partial least squares path modeling (PLS), we present a research question if the PLS method, as used currently, is at all an appropriate tool for theory testing. We briefly summarize some of the recent critique of the use of PLS in IS as a theory testing tool. Then we analyze the results of 12 PLS analyzes published in leading IS journals testing if these mod...

The unit root tests based on the robust estimator for the first-order autoregressive process are proposed and compared with the unit root tests based on the ordinary least squares (OLS) estimator. The percentiles of the null distributions of the unit root test are also reported. The empirical probabilities of Type I error and powers of the unit root tests are estimated via Monte Carlo simulatio...

This paper develops a consistent OLS estimate of a fractionally integrated processes' di erencing parameter, using continuous wavelet theory as constructed from smoothing kernels. We show that a log-log linear relationship exists between the variance of the wavelet coe cient and the level at which the fractionally integrated processes is smoothed. This linear relationship occurs because the sel...

We consider two example systems, a logistic-growth population model and a damped spring-mass model. These models are each parameterized in two different ways. In one case (the logistic) the parameters are independent in one formulation and dependent in the other. In the other example (the spring-mass), the parameterizations are each independent. We carry out a series of inverse problems for the...

Pricing of American options can be achieved by solving optimal stopping problems. This in turn can be done by computing so-called continuation values, which we represent as regression functions defined by the aid of a cash flow for the next few time periods. We use Monte Carlo to generate data and apply nonparametric least squares regression estimates to estimate the continuation values from th...