Sanghamitra Das

The Environmental Impact of Poverty: Evidence from Firewood Collection in Rural Nepal

We investigate determinants of household firewood collection in rural Nepal, using 1995–96 and 2002–3 World Bank Living Standards Measurement Survey (LSMS) data. We incorporate village fixed effects, endogenous censoring, measurement error in living standards and heterogeneous effects of different household assets. We find no evidence in favor of the poverty‐environment hypothesis. The evidence for the environmental Kuznets curve depends on the precise measure of living standards and time period studied. Firewood collections fall with a transition to modern occupations and rise with increasing population and household division. The local interhousehold collection externality is negligible, indicating that policy interventions are justified only by ecological considerations or nonlocal spillovers.

Duration of firms in an infant industry: the case of Indian computer hardware

Abstract This study analyses survival of firms in an infant industry in a developing economy. It is found that (a) entry size and the probability of exit are positively related, which is the opposite of the result in most previous studies; (b) similar to previous studies, post-entry size is negatively related to the hazard; (c) firms with longer duration have a more volatile time path of size; (d) the hazard declines with age at an increasing rate suggesting increasing returns to learning and (e) diversification of firms and public ownership have little effect on duration.

Dynamics of entry and exit of firms in the presence of entry adjustment costs

Abstract This paper presents a simple model of industry dynamics with entry adjustment costs. These costs imply a non-instantaneous adjustment path to the steady state, so that the model permits the short-run and long-run characterization of industry dynamics in a single framework. The type of the steady state (zero entry and exit or positive entry and exit with the co-existence of high-efficiency and low-efficiency firms) depends on the fixed cost of entry as well as entry adjustment costs. The short-run dynamics exhibits non-monotonicity if persistence in efficiency over time is not too high. The model is consistent with the empirical observations that the total number of firms and net entry follow non-monotonic paths and entry and exit are positively correlated over time.

Economic cost analysis in cancer management and its relevance today.

The global cancer burden has shown a distinct shift in the last two decades and its financial impact can be large, even among patients living in high resource countries, with comprehensive health insurance policies. It is hard to imagine its impact on patients of developing countries where insurance policies exist infrequently and often cost becomes the greatest barrier in availing cancer treatment. It is recognized that these costs include the direct cost of disease treatment and care, indirect costs accrued by the patient and the family, and economic losses to the society as a whole. Economic cost analysis or cost-effectiveness analysis has emerged as a basic tool in the evaluation of health-care practices. To date, these cost data have been collected only sporadically, even in the most developed countries, and there is a great need for incorporating economic cost assessment practices in developing countries, so that patients and their families can access the care adequately. The current review has been done using PubMed and MEDLINE search with keywords like cancer, cost-analysis, cost-effectiveness, economic burden, medical cost, etc.

Negative Reality of the HIV Positives: Integrating Mental Health in Welfare Evaluation

Using primary household data we estimate family utility function parameters that measure the relative importance of consumption, schooling of children and health (both physical and mental) and find that mental health is far more important than consumption or childrens schooling in determining household utility. We then estimate the monetary equivalent of the welfare loss to an HIV family to be Rs. 65,690 per month. Aggregating to the all India level we find that the annual welfare loss due to the only 0.9% prevalence of HIV/AIDS is a staggering 3,800 billion rupees per year, which is about two and a half times the annual health expenditure of the country in 2004 and 13.4% of its GDP! This huge magnitude is not surprising as it includes private valuation of ones own life as well as the cost of stigma for being HIV positive. In addition, the annual loss from external transfers (through debt, dissavings and social insurance) account for 5% of annual health expenditure and 0.23% of GDP. The significance of mental health can be gauged from the fact that had we not included it in the family welfare analysis, the welfare loss would have been just about 0.067% of GDP.

Negative Reality of the HIV Positives: Evaluating Welfare Loss in a Low Prevalence Country

Using primary household data from India we estimate family utility function parameters that measure the relative importance of consumption, schooling of children and health (both physical and mental) and find that mental health is far more important than consumption or children’s schooling in determining household utility. We then estimate that the monetary equivalent of the welfare loss to an HIV family is Rs. 66,039 per month, whereas the losses to an HIV male and female are Rs. 67,601 and Rs. 65,120 per month respectively. These figures are huge given that the average per capita consumption expenditure of the families in our sample is just Rs. 1,019 per month. This huge magnitude is not surprising as it includes private valuation of one’s own life as well as the cost of stigma for being HIV positive. In addition, the annual loss from external transfers (through debt, sale of assets and social insurance) accounts for 2.6% of annual health expenditure and 0.12% of GDP in 2004. The significance of mental health in welfare evaluation can be gauged from the fact that, for an average HIV family, a whopping 74% of the welfare loss comes from aspects of mental health.