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The crude birth rate (cbr) is defined as the ratio of the number of births in a year over the population in the mid-year,

     

The crude birth rate (cbr) is defined as the ratio of the number of births in a year over the population in the mid-year, expressed per 1000 population. The infant mortality rate (mort) is defined as the ratio of the number of deaths of infants under the age of one in a year over the number of live births in that year, expressed per 1000 live births. Data on these variables for 125 countries in the year 1985 can be used to run these two simple regressions: cbr=B,+Bmort+ & or cbra,+a, log(mort) +u where & and u are the errors in the respective equations. (1) (2) (a) Mukherjee et al. (Econometrics and Data Analysis for Developing Countries, 1998, where these data can be found) state, "Under conditions of poverty and ill-health, where infant mortality is high, it is the expected number of surviving children - that is, children who survive into adulthood - which guides fertility decisions". According to this reasoning, what is the expected sign of , or a,? (2 marks) (b) Given the scatter plots of cbr on mort and log(mort) below, which of the linear regressions above is likely to offer a better fit to the data? Why? (2 marks) MD 50- 40- 50- 10- MORT 120 100 200 40- 30- 20 10- 20 24 28 32 38 40 44 48 82 LOG(MORT) (c) Using data for all countries, least squares estimation of the two regressions above generated the results below. Can we compare the R measures in these two regressions? Explain. (2 marks) Regression 1: Dependent Variable cbr Estimate Std. Error t-statistic p-value Intercept 16.04092 0.98127 16.35

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