This article analyzes demographic responses to the 1984-1985 Ethiopian famine and compares them with Bongaarts and Cain's (1982) hypothesized responses. After briefly describing the data collection, I estimate the age distribution and the age-specific mortality and fertility rates of Ethiopian famine victims in a resettlement area and compare these with mortality estimates for the 1972-1973 Bangladesh famine and with fertility estimates from the 1981 Ethiopian demographic survey. The results show that the mortality rate among Ethiopian famine victims was about seven times higher than the rate among the Bangladesh victims and that the Ethiopian famine-related mortality was general and not a function of household socioeconomic variables. The data also show a 26 percent lower total fertility rate among famine victims.

The study attempts to estimate the demand for cigarettes in Tanzania and presents simulation results on the effect of the cigarette excise tax on smoking participation, government revenue, and related topics. After briefly summarizing the magnitude and spread of cigarette consumption in the country, the paper reviews some empirical estimates from African and other countries. The 2008 Tanzanian household budget survey was used to estimate the demand for cigarettes in Tanzania. The descriptive statistics suggest that the smoking prevalence for Tanzania is 15.35 percent with low variability across expenditure (income) groups. Smoking intensity and per capita consumption were estimated at 7.08 cigarettes and 1.33 cigarettes, respectively, a relatively low value. A two-part demand equation model was used to estimate various elasticities. For the overall equation, the price elasticities of smoking participation, smoking intensity, and total elasticity were estimated at −0.879, −0.853, and −1.732, respectively. Compared to similar results in other developing countries, the estimates appear quite high. When estimated by expenditure (income) groups, the magnitude of the elasticity appears higher among high expenditure groups than among low expenditure groups. Two simulation exercises were undertaken. First, the effect of different excise rates on smoking participation rate, cigarette consumption, tax revenue, and related responses was estimated and highlighted. Second, the same exercise was undertaken to determine the effect of a given increase in the cigarette excise tax on various expenditure groups. The overall results suggest that an increase in the excise tax on cigarettes in Tanzania would reduce cigarette consumption and increase government tax revenue.

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A brief summary of famine and drought from a historical perspective is given. In an attempt to estimate the magnitude of deaths due to the 1984-85 famine in Ethiopia, a survey was conducted among the resettled famine victims. The results show that the expected life at birth among the male and female famine victims was 6.2 and 5.7 years, respectively. When compared with the highest mortality rates ever recorded (that is Coale-Demeny, West Model Life Table level 1), the Ethiopian famine induced rate seems to be considerably higher. Regional variations between the two famine affected regions show that mortality in Tigrai was slightly higher than that of Wello. Also prefamine socio-economic differentials between households did not seem to have an effect on mortality. The results suggest that as much as 700,000 excess deaths might have occurred during the 1984-85 famine period in Ethiopia.

In this paper we examine the welfare implications of the Tanzanian fisheries boom following from the increase in quantities and prices of the Lake Victoria Nile perch export during [1993][1994][1995][1996][1997][1998][1999][2000][2001][2002][2003][2004][2005][2006][2007][2008]. We use the theoretical model by Brander and Taylor (1997) that we try to test empirically.We have a micro level perspective using data from a 1993 World Bank household survey and our own study from 2008, both containing data from about 520 households in the two regions Mwanza and Mara by the lake. Our results indicate that average income has increased in both rural and urban areas. For the poorest part of the population, rural areas experienced only modestly and non-significantly reductions in the fraction below basic needs, while urban areas had a substantial reduction. However, growth was modest and inequality seems to have increased during the period. Concerning human capital measured as education for the household head we found substantial improvements in educational level and a simple regression model confirmed the significant impact of education on household income. We also found that households on average are better off when situated close to the lake. Acknowledgement