Reference no: EM132948379

Malaria is a disease that is highly prevalent through much of the developing world. It takes the form of a parasite that is carried by mosquitoes, and hence it is particularly severe in warm and wet climates where the insects thrive. Given that malaria has a high mortality rate and can incapacitate a large proportion of the working age population, the disease is thought to contribute greatly to poverty throughout Africa and Asia.

There is a large research effort dedicated to assessing the effectiveness of preventative measures in order to control the disease, including the use of mosquito nets. Your task is to examine the effectiveness of a mosquito net program using data collected from villages in Senegal. In some villages the researchers distributed mosquito nets (the treatment group) while in others they did not (the control group). The data was obtained by recording details of each village twice, before and after the nets were handed out.

The data can be found in the file malaria.wf1 where the variables are defined as follows: malaria gives the percent infection rate in the village, income gives the average income level (in USD), rain gives the annual rainfall, water is a dummy variable which is equal to one if there is a stagnant water source, and temperature is the average temperature in degrees Celsius. In addition there are two dummy variables. Period denotes the time period where 0 indicates the period before the nets were distributed, and 1 denotes the period after. MN denotes the villages that received the nets with a value of 1.

1. Why can't we estimate the effectiveness of the program by simply averaging the malarial rates (in the latter period) for villages that did and did not receive the nets? Briefly explain

2. Calculate the difference-in-differences estimate of the effectiveness of the program (in terms of reduction in percent infections) based only upon average rates before and after the nets were distributed.

3. Give the regression equation that would be used to calculate the full difference-in-difference estimate employing the full set of control variables. Also estimate this equation and interpret the results. Why is this estimate preferable to the estimate given in part 3?

4. Briefly perform some diagnostics on your model. Do the coefficients make sense? Are there any signs of misspecification? Are the residuals in line with your assumptions?