Unconditional government social cash transfer in Africa does not increase fertility

Among policymakers, a common perception surrounding the effects of cash transfer programmes, particularly unconditional programmes targeted to families with children, is that they induce increased fertility. We evaluate the Zambian Child Grant Programme, a government unconditional cash transfer targeted to families with a child under the age of 5 and examine impacts on fertility and household composition. The evaluation was a cluster randomized control trial, with data collected over 4 years from 2010 to 2014. Our results indicate that there are no programme impacts on overall fertility. Our results contribute to a small evidence base demonstrating that there are no unintended incentives related to fertility due to cash transfers.     

Migration and fuel use in rural Zambia

Population and Environment - What is the effect of migration on fuel use in rural Zambia? Opportunities to increase income can be scarce in this setting; in response, households may pursue a...     

Parenting skills and early childhood development: production function estimates from longitudinal data

Review of Economics of the Household - We provide evidence on the importance of specific inputs for child cognitive skills by estimating alternative specifications of the early childhood production...     

Exponentiated Teissier distribution with increasing,decreasing and bathtub hazard functions

This article introduces a two-parameter exponentiated Teissier distribution. It is the main advantage of the distribution to have increasing, decreasing and bathtub shapes for its hazard rate function. The expressions of the ordinary moments, identifiability, quantiles, moments of order statistics, mean residual life function and entropy measure are derived. The skewness and kurtosis of the distribution are explored using the quantiles. In order to study two independent random variables, stress–strength reliability and stochastic orderings are discussed. Estimators based on likelihood, least squares, weighted least squares and product spacings are constructed for estimating the unknown parameters of the distribution. An algorithm is presented for random sample generation from the distribution. Simulation experiments are conducted to compare the performances of the considered estimators of the parameters and percentiles. Three sets of real data are fitted by using the proposed distribution over the competing distributions.