ACREM researchers have enormous experience and expertise in the usage of econometric and qualitative analysis techniques. We have the technical know-how of modeling, presenting and explaining complex Analysis scenarios in an understandable way to any kind of stakeholders. We have the ability to adapt the level of technical detail as required by our clients to each target audience’s requirements.
Our technical expertise in analyzing data using econometric and qualitative analysis are not limited to;
- Bivariate and multivariate analysis of cross-section data, including: logistic regression; probit; tobit; loglinear modelling; structural equation modelling; factor analysis; reliability analysis; analysis of variance; cluster analysis; discriminant analysis.
- Weighting and grossing of survey data, for sampling and response bias, inter-wave attrition in longitudinal studies etc.
- The use of regression models (including panel data, dynamic GMM); selection models (including extensions e.g. control function estimators); and non- and semi-parametric matching (propensity score matching, kernel matching).
- Longitudinal and panel data analysis, including multivariate modelling; survivor/event history analysis (non-parametric and parametric modelling, Cox regressions etc.)
- As well as conducting empirical analysis in particular cases, we can provide advice about the strengths and weaknesses of particular quantitative techniques and their relevance (or lack thereof) to specific real-world questions, and staff training in the use of quantitative techniques.