Category: Learning modules
Time series data requires some diagnostic tests in order to check the properties of the independent variables. This is called ‘normality’. This article explains how to perform normality test in STATA.
assumption tests in STATA, empirical analysis with econometrics, STATA for data analysis, time series analysisThe underlying assumption in pooled regression is that space and time dimensions do not create any distinction within the observations and there are no set of fixed effects in the data.
empirical analysis with econometrics, exploratory model analysis, panel data regression in STATA, STATA for data analysisThis article of the module explains how to perform panel data analysis using STATA. In the case of panel data, the observations are present in time and space dimensions. For instance, a survey of the same cross-sectional unit such as firm, country or state over time.
empirical analysis with econometrics, panel data analysis, panel data regression in STATAGM (1,1) modeling is a popular grey forecasting method because of its computational efficiency. There are many challenges in GM (1,1) modeling, but they are solvable using MS Excel. This article is a detailed guide on how to overcome these challenges.
dea cost efficiency, DEA moduleA systematic literature review attempts ‘to identify, appraise and summarise all the empirical evidence. Evidence must meet pre-specified eligibility criteria to answer a given research question. A systematic review of literature helps to develop the study that allows identification, quality, limitations and potential.
Bibliometrics, literature review techniques, research paper writing, systematic reviewThis article explains the application of PINDIS separately in Hamlet II. It also presents an example using PINDIS analysis to understand the application in depth. Accessing PINDIS separately is possible only after creating the input file using ‘Select’ function.
analysis and scaling, hamletPINDIS method applies a series of variations by increasing flexibility in each iteration. The aim is to maximize the optimization. It provides better specifics when compared to the INDSCAL results.
analysis and scaling, hamletThis article explains how to perform metric multidimensional scaling method MRSCAL in Hamlet II. MRSCAL stands for metric scaling.
analysis and scaling, hamlet