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Regional Analytical Model (RAM):

Regional Spatial-intertemporal Data Modeling and Representation using ArcGIS Geostatistical Analytics. ArcGIS Geostatistical Analytics generate optimal surfaces from sample data and evaluate predictions for better decision making.

ArcGIS Geostatistical Analytics offers a suite of interactive tools to visually investigate data prior to analysis. These tools allow modelers to:

  • Investigate the distribution of your data and look for outliers (Histogram, QQ Plots)
  • Look for systematic trends in your data (Trend Analysis)
  • Explore local variability and clusters (Voronoi Map)
  • Visualize spatial correlation within and between datasets (Semivariogram/Cross-Covariance Clouds)

When data are incomplete or subject to error, ArcGIS Geostatistical Analyst provides a probabilistic framework for quantifying uncertainties. Create surfaces from sample data using these interpolation methods:

  • Inverse distance weighted
  • Radial-based functions
  • Global and local polynomials
  • Kriging for exact data and for error-contaminated data
  • Cokriging (multivariate version of the above-mentioned kriging models)
  • Isotropical or anisotropical models

Evaluate how special models perform using the following diagnostics.

  • Cross-validation for checking the model’s quality
  • Validation for checking prediction quality
  • Compare cross-validation results of several models
  • Show predicted value at cursor (MapTips)
  • Create multiple versions of a surface to perform risk analyses. Geostatistical simulation produces multiple surfaces that mimic the real phenomenon and provide possible values. This provides a basis for risk analyses, economic decision making, and other estimations involving uncertainty, allowing analysts to make more informed decisions.
  • Improve decision making by enhancing and sharing visualized data surfaces. Use renderers such as contours, regular grids and hillshading for enhanced surfaces visualization. You can then export your prediction results as contour lines, polygons, raster or as a layer that stores the model parameters for the renderers that were used.
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Built Models within
Advanced Analytics

SDCGE MODEL

SDCGE has been developed to be used in studying the economic impact of economic policies, projecting key macroeconomic variables and monitoring the Saudi Arabia's developing plans and Economic Reforms

Main Use

Policy Impact Analysis (Med-Long Term, 3-10 Years)
Med.-Long term Forecasting of Key Economic Indicators

SVAR MODEL

The Saudi S-VAR is Vector Auto-Regressive Model of Major Macroeconomic Indicators, Augmented with a Structural Macro-econometric Model of 8 blocks and 14 Sectors (86 Activities as per ISIC4) of the economy. The Model contains three main blocks

Main Use

Policy Impact Analysis (Short Term, Upto 2 Years)
Short term Forecasting of Key Economic Indicators

MIMIC MODEL

The MIMIC Model is a Structural Equation Model which takes into account the determination of Shadow Economy's causes and indicators.

Main Use

Estimating and Forecasting the Size Shadow Economy of Saudi (within the formal and informal economy ) and any shadow/ uncaptured economic activity based on the data availability.

Gini - HDI Model

The Gini - HDI Model aims to estimate the factors determining the Gini and HDI Indices and their dimensions and linking them to other economic models to estimate the impact of any future policy if the Gini Coefficient and the Human Developement Index.

Main Use

Capturing Impact Of Economic and Social Policy on the Gini Coefficient and the Human Development Index by Linking the Model to any Economic / Social Model

SNMEM Model

Nested Modelling: If Model A is nested in Model B, then the parameters of Model A are a subset of the parameters of Model B. In the case of a Nested Macro Econometric Model, any previous policy, investment plan, social regulation.

Main Use

Assessment Historical Impact of previously applied policies.

Dynamic Stochastic Labour Transition Model

The Model measures: Inertia, Reliability, Activity Rate, Entrant Rate, Exit Rate, Unemployment Rate, Guve-up Rate, Net Outflow.

Main Use

Provide Analytics of the Saudi Labour Market and could be used to forecast and assess impact of future policies on the measures which the model produces

GAMEbit Toolkit Model

The Gambit Toolkit is a generic game theoretic model for solving extensive and normal form game theoretic models.

Main Use

Gambit is for finite games only. Because of the mathematical structure of finite games, it is possible to write many general- purpose routines for analyzing these games. Thus, Gambit can be used in a wide variety of applications of game theory.

Early Warning System (EWS) Modeling

Recurrent Neural Networks (RNN) and a Deep Learning (DL) approach based on Long-Short Term Memory (LSTM)

Main Use

The intensification of key socioeconomic cycles’ indicators raises concerns about future trends and turning points of such indicators and their impact on economic and social growth and developments plans.

Regional Analytical Model (RAM)

Regional Spatial-intertemporal Data Modeling and Representation using ArcGIS Geostatistical Analytics.

Main Use

ArcGIS Geostatistical Analytics generate optimal surfaces from sample data and evaluate predictions for better decision making. (I)ArcGIS Geostatistical Analytics offers a suite of interactive tools to visually investigate data prior to analysis

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المركز السعودي للأعمال

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Riyadh 13323, Saudi Arabia

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