A Model is a representation of the actual observable phenomenon. In the absence of an observable phenomenon, a framework is developed to represent it in order to proceed with the desirable inferences. In aeronautics, for example, costs are substantially reduced when one uses a model to design and test an aircraft or its spare parts before the actual mass manufacturing process is initiated. Thus, we can classify three basic approaches of generating statistical data. They are: design based approach where sampling techniques are dully employed to collect reliable data for decision making or even to monitor MDGs. The second approach is the Model-assisted approach where data gaps are filled using tested and approved statistical methodologies for missing data so as to confidently derive population estimates. The third approach is model-based where all the data for a given indicator are solely generated using a given model that has been tested using historic data over time. This is normally done through aspects commonly referred to as data simulation and modeling for extremely hard to get obtain data. The major aim of application of this kind of approach is to maintain sustainability in planning, decision making, monitoring and inferences about a particular development indicator.

During the presentation at the workshop on the development and management of MDGs databases at the country level held in Nairobi, Kenya for 15^th to 19^th February, a presenter in his analysis gave model-based estimates as one of the causes of discrepancies between national and international data. Whereas it might hold some drops of water, there is no sufficient evidence to believe that the national estimates are better given the fact that they suffer from very high sampling errors of the magnitude higher than 11 percent with low study coverage, bias error and poor indicator specifications. Many developing countries are faced with scarcity of sufficient and consistent data to monitor MDGs. Besides, between the year of MDG declaration, 2000 and 2005, no data, hence no report was published showing the status of MDGs in any African country. For example, in Uganda, the first ever substantive MDG report was released in the year 2007 and as I write, the second MDG country status report is yet to be released. Therefore, under such circumstances, shouldn’t model based data be used to facilitate monitoring of MDGs at country level? What about situations whereby resources both financial and human resource are insufficient for carrying out reliable surveys and yet the country or the international community need to know its MDG status? On the positive note, what if the country has good statisticians that can develop data based models whose sensitivity analysis show very high correlations between expected data and model-based data?

In conclusion, model based data are increasingly becoming an integral part in the monitoring of MDGs in the both developed and developing countries, but more so in the developing countries majorly because of their unsustainable ability to regularly collect quality data over time.

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